Computing multiple zeros using a class of quartically convergent methods
F. Soleymani
2013-09-01
For functions with finitely many real roots in an interval, relatively little literature is known, while in applications, the users wish to find all the real zeros at the same time. Hence, the second aim of this paper will be presented by designing a fourth-order algorithm, based on the developed methods, to find all the real solutions of a nonlinear equation in an interval using the programming package Mathematica 8.
Fazlollahtabar, Hamed; Saidi-Mehrabad, Mohammad; Balakrishnan, Jaydeep
2015-01-01
This paper proposes an integrated Markovian and back propagation neural network approaches to compute reliability of a system. While states of failure occurrences are significant elements for accurate reliability computation, Markovian based reliability assessment method is designed. Due to drawbacks shown by Markovian model for steady state reliability computations and neural network for initial training pattern, integration being called Markov-neural is developed and evaluated. To show efficiency of the proposed approach comparative analyses are performed. Also, for managerial implication purpose an application case for multiple automated guided vehicles (AGVs) in manufacturing networks is conducted. - Highlights: • Integrated Markovian and back propagation neural network approach to compute reliability. • Markovian based reliability assessment method. • Managerial implication is shown in an application case for multiple automated guided vehicles (AGVs) in manufacturing networks
Grolet, Aurelien; Thouverez, Fabrice
2015-02-01
This paper is devoted to the study of vibration of mechanical systems with geometric nonlinearities. The harmonic balance method is used to derive systems of polynomial equations whose solutions give the frequency component of the possible steady states. Groebner basis methods are used for computing all solutions of polynomial systems. This approach allows to reduce the complete system to an unique polynomial equation in one variable driving all solutions of the problem. In addition, in order to decrease the number of variables, we propose to first work on the undamped system, and recover solution of the damped system using a continuation on the damping parameter. The search for multiple solutions is illustrated on a simple system, where the influence of the retained number of harmonic is studied. Finally, the procedure is applied on a simple cyclic system and we give a representation of the multiple states versus frequency.
Itagaki, Masafumi; Sahashi, Naoki.
1996-01-01
The multiple reciprocity method (MRM) in conjunction with the boundary element method has been employed to solve one-group eigenvalue problems described by the three-dimensional (3-D) neutron diffusion equation. The domain integral related to the fission source is transformed into a series of boundary-only integrals, with the aid of the higher order fundamental solutions based on the spherical and the modified spherical Bessel functions. Since each degree of the higher order fundamental solutions in the 3-D cases has a singularity of order (1/r), the above series of boundary integrals requires additional terms which do not appear in the 2-D MRM formulation. The critical eigenvalue itself can be also described using only boundary integrals. Test calculations show that Wielandt's spectral shift technique guarantees rapid and stable convergence of 3-D MRM computations. (author)
Hyung-Jun Kim
2018-01-01
Full Text Available Extreme rainfall causes surface runoff to flow towards lowlands and subterranean facilities, such as subway stations and buildings with underground spaces in densely packed urban areas. These facilities and areas are therefore vulnerable to catastrophic submergence. However, flood modeling of underground space has not yet been adequately studied because there are difficulties in reproducing the associated multiple horizontal layers connected with staircases or elevators. This study proposes a convenient approach to simulate underground inundation when two layers are connected. The main facet of this approach is to compute the flow flux passing through staircases in an upper layer and to transfer the equivalent quantity to a lower layer. This is defined as the ‘adaptive transfer method’. This method overcomes the limitations of 2D modeling by introducing layers connecting concepts to prevent large variations in mesh sizes caused by complicated underlying obstacles or local details. Consequently, this study aims to contribute to the numerical analysis of flow in inundated underground spaces with multiple floors.
Computer-generated holograms by multiple wavefront recording plane method with occlusion culling.
Symeonidou, Athanasia; Blinder, David; Munteanu, Adrian; Schelkens, Peter
2015-08-24
We propose a novel fast method for full parallax computer-generated holograms with occlusion processing, suitable for volumetric data such as point clouds. A novel light wave propagation strategy relying on the sequential use of the wavefront recording plane method is proposed, which employs look-up tables in order to reduce the computational complexity in the calculation of the fields. Also, a novel technique for occlusion culling with little additional computation cost is introduced. Additionally, the method adheres a Gaussian distribution to the individual points in order to improve visual quality. Performance tests show that for a full-parallax high-definition CGH a speedup factor of more than 2,500 compared to the ray-tracing method can be achieved without hardware acceleration.
A multiple-scaling method of the computation of threaded structures
Andrieux, S.; Leger, A.
1989-01-01
The numerical computation of threaded structures usually leads to very large finite elements problems. It was therefore very difficult to carry out some parametric studies, especially in non-linear cases involving plasticity or unilateral contact conditions. Nevertheless, these parametric studies are essential in many industrial problems, for instance for the evaluation of various repairing processes of the closure studs of PWR. It is well known that such repairing generally involves several modifications of the thread geometry, of the number of active threads, of the flange clamping conditions, and so on. This paper is devoted to the description of a two-scale method, which easily allows parametric studies. The main idea of this method consists of dividing the problem into a global part, and a local part. The local problem is solved by F.E.M. on the precise geometry of the thread of some elementary loadings. The global one is formulated on the gudgeon scale and is reduced to a monodimensional one. The resolution of this global problem leads to the unsignificant computational cost. Then, a post-processing gives the stress field at the thread scale anywhere in the assembly. After recalling some principles of the two-scales approach, the method is described. The validation by comparison with a direct F.E. computation and some further applications are presented
Fischer, E A J; De Vlas, S J; Richardus, J H; Habbema, J D F
2008-09-01
Microsimulation of infectious diseases requires simulation of many life histories of interacting individuals. In particular, relatively rare infections such as leprosy need to be studied in very large populations. Computation time increases disproportionally with the size of the simulated population. We present a novel method, MUSIDH, an acronym for multiple use of simulated demographic histories, to reduce computation time. Demographic history refers to the processes of birth, death and all other demographic events that should be unrelated to the natural course of an infection, thus non-fatal infections. MUSIDH attaches a fixed number of infection histories to each demographic history, and these infection histories interact as if being the infection history of separate individuals. With two examples, mumps and leprosy, we show that the method can give a factor 50 reduction in computation time at the cost of a small loss in precision. The largest reductions are obtained for rare infections with complex demographic histories.
Stoykov, S.; Atanassov, E.; Margenov, S.
2016-10-01
Many of the scientific applications involve sparse or dense matrix operations, such as solving linear systems, matrix-matrix products, eigensolvers, etc. In what concerns structural nonlinear dynamics, the computations of periodic responses and the determination of stability of the solution are of primary interest. Shooting method iswidely used for obtaining periodic responses of nonlinear systems. The method involves simultaneously operations with sparse and dense matrices. One of the computationally expensive operations in the method is multiplication of sparse by dense matrices. In the current work, a new algorithm for sparse matrix by dense matrix products is presented. The algorithm takes into account the structure of the sparse matrix, which is obtained by space discretization of the nonlinear Mindlin's plate equation of motion by the finite element method. The algorithm is developed to use the vector engine of Intel Xeon Phi coprocessors. It is compared with the standard sparse matrix by dense matrix algorithm and the one developed by Intel MKL and it is shown that by considering the properties of the sparse matrix better algorithms can be developed.
König, Gerhard; Mei, Ye; Pickard, Frank C; Simmonett, Andrew C; Miller, Benjamin T; Herbert, John M; Woodcock, H Lee; Brooks, Bernard R; Shao, Yihan
2016-01-12
A recently developed MESS-E-QM/MM method (multiple-environment single-system quantum mechanical molecular/mechanical calculations with a Roothaan-step extrapolation) is applied to the computation of hydration free energies for the blind SAMPL4 test set and for 12 small molecules. First, free energy simulations are performed with a classical molecular mechanics force field using fixed-geometry solute molecules and explicit TIP3P solvent, and then the non-Boltzmann-Bennett method is employed to compute the QM/MM correction (QM/MM-NBB) to the molecular mechanical hydration free energies. For the SAMPL4 set, MESS-E-QM/MM-NBB corrections to the hydration free energy can be obtained 2 or 3 orders of magnitude faster than fully converged QM/MM-NBB corrections, and, on average, the hydration free energies predicted with MESS-E-QM/MM-NBB fall within 0.10-0.20 kcal/mol of full-converged QM/MM-NBB results. Out of five density functionals (BLYP, B3LYP, PBE0, M06-2X, and ωB97X-D), the BLYP functional is found to be most compatible with the TIP3P solvent model and yields the most accurate hydration free energies against experimental values for solute molecules included in this study.
Neutron source multiplication method
Clayton, E.D.
1985-01-01
Extensive use has been made of neutron source multiplication in thousands of measurements of critical masses and configurations and in subcritical neutron-multiplication measurements in situ that provide data for criticality prevention and control in nuclear materials operations. There is continuing interest in developing reliable methods for monitoring the reactivity, or k/sub eff/, of plant operations, but the required measurements are difficult to carry out and interpret on the far subcritical configurations usually encountered. The relationship between neutron multiplication and reactivity is briefly discussed and data presented to illustrate problems associated with the absolute measurement of neutron multiplication and reactivity in subcritical systems. A number of curves of inverse multiplication have been selected from a variety of experiments showing variations observed in multiplication during the course of critical and subcritical experiments where different methods of reactivity addition were used, with different neutron source detector position locations. Concern is raised regarding the meaning and interpretation of k/sub eff/ as might be measured in a far subcritical system because of the modal effects and spectrum differences that exist between the subcritical and critical systems. Because of this, the calculation of k/sub eff/ identical with unity for the critical assembly, although necessary, may not be sufficient to assure safety margins in calculations pertaining to far subcritical systems. Further study is needed on the interpretation and meaning of k/sub eff/ in the far subcritical system
Essential numerical computer methods
Johnson, Michael L
2010-01-01
The use of computers and computational methods has become ubiquitous in biological and biomedical research. During the last 2 decades most basic algorithms have not changed, but what has is the huge increase in computer speed and ease of use, along with the corresponding orders of magnitude decrease in cost. A general perception exists that the only applications of computers and computer methods in biological and biomedical research are either basic statistical analysis or the searching of DNA sequence data bases. While these are important applications they only scratch the surface of the current and potential applications of computers and computer methods in biomedical research. The various chapters within this volume include a wide variety of applications that extend far beyond this limited perception. As part of the Reliable Lab Solutions series, Essential Numerical Computer Methods brings together chapters from volumes 210, 240, 321, 383, 384, 454, and 467 of Methods in Enzymology. These chapters provide ...
Possibilities of computer tomography in multiple sclerosis
Vymazal, J.; Bauer, J.
1983-01-01
Computer tomography was performed in 41 patients with multiple sclerosis, the average age of patients being 40.8 years. Native examinations were made of 17 patients, examinations with contrast medium of 19, both methods were used in the examination of 5 patients. In 26 patients, i.e. in almost two-thirds, cerebral atrophy was found, in 11 of a severe type. In 9 patients atrophy affected only the hemispheres, in 16 also the stem and cerebellum. The stem and cerebellum only were affected in 1 patient. Hypodense foci were found in 21 patients, i.e. more than half of those examined. In 9 there were multiple foci. In most of the 19 examined patients the hypodense changes were in the hemispheres and only in 2 in the cerebellum and brain stem. No hyperdense changes were detected. The value and possibilities are discussed of examinations by computer tomography multiple sclerosis. (author)
Multiple network alignment on quantum computers
Daskin, Anmer; Grama, Ananth; Kais, Sabre
2014-12-01
Comparative analyses of graph-structured datasets underly diverse problems. Examples of these problems include identification of conserved functional components (biochemical interactions) across species, structural similarity of large biomolecules, and recurring patterns of interactions in social networks. A large class of such analyses methods quantify the topological similarity of nodes across networks. The resulting correspondence of nodes across networks, also called node alignment, can be used to identify invariant subgraphs across the input graphs. Given graphs as input, alignment algorithms use topological information to assign a similarity score to each -tuple of nodes, with elements (nodes) drawn from each of the input graphs. Nodes are considered similar if their neighbors are also similar. An alternate, equivalent view of these network alignment algorithms is to consider the Kronecker product of the input graphs and to identify high-ranked nodes in the Kronecker product graph. Conventional methods such as PageRank and HITS (Hypertext-Induced Topic Selection) can be used for this purpose. These methods typically require computation of the principal eigenvector of a suitably modified Kronecker product matrix of the input graphs. We adopt this alternate view of the problem to address the problem of multiple network alignment. Using the phase estimation algorithm, we show that the multiple network alignment problem can be efficiently solved on quantum computers. We characterize the accuracy and performance of our method and show that it can deliver exponential speedups over conventional (non-quantum) methods.
Shen, L.; Levine, S.H.; Catchen, G.L.
1987-01-01
This paper describes an optimization method for determining the beta dose distribution in tissue, and it describes the associated testing and verification. The method uses electron transport theory and optimization techniques to analyze the responses of a three-element thermoluminescent dosimeter (TLD) system. Specifically, the method determines the effective beta energy distribution incident on the dosimeter system, and thus the system performs as a beta spectrometer. Electron transport theory provides the mathematical model for performing the optimization calculation. In this calculation, parameters are determined that produce calculated doses for each of the chip/absorber components in the three-element TLD system. The resulting optimized parameters describe an effective incident beta distribution. This method can be used to determine the beta dose specifically at 7 mg X cm-2 or at any depth of interest. The doses at 7 mg X cm-2 in tissue determined by this method are compared to those experimentally determined using an extrapolation chamber. For a great variety of pure beta sources having different incident beta energy distributions, good agreement is found. The results are also compared to those produced by a commonly used empirical algorithm. Although the optimization method produces somewhat better results, the advantage of the optimization method is that its performance is not sensitive to the specific method of calibration
Secure Multiparty Quantum Computation for Summation and Multiplication.
Shi, Run-hua; Mu, Yi; Zhong, Hong; Cui, Jie; Zhang, Shun
2016-01-21
As a fundamental primitive, Secure Multiparty Summation and Multiplication can be used to build complex secure protocols for other multiparty computations, specially, numerical computations. However, there is still lack of systematical and efficient quantum methods to compute Secure Multiparty Summation and Multiplication. In this paper, we present a novel and efficient quantum approach to securely compute the summation and multiplication of multiparty private inputs, respectively. Compared to classical solutions, our proposed approach can ensure the unconditional security and the perfect privacy protection based on the physical principle of quantum mechanics.
Multiple Shooting and Time Domain Decomposition Methods
Geiger, Michael; Körkel, Stefan; Rannacher, Rolf
2015-01-01
This book offers a comprehensive collection of the most advanced numerical techniques for the efficient and effective solution of simulation and optimization problems governed by systems of time-dependent differential equations. The contributions present various approaches to time domain decomposition, focusing on multiple shooting and parareal algorithms. The range of topics covers theoretical analysis of the methods, as well as their algorithmic formulation and guidelines for practical implementation. Selected examples show that the discussed approaches are mandatory for the solution of challenging practical problems. The practicability and efficiency of the presented methods is illustrated by several case studies from fluid dynamics, data compression, image processing and computational biology, giving rise to possible new research topics. This volume, resulting from the workshop Multiple Shooting and Time Domain Decomposition Methods, held in Heidelberg in May 2013, will be of great interest to applied...
Computing Nash equilibria through computational intelligence methods
Pavlidis, N. G.; Parsopoulos, K. E.; Vrahatis, M. N.
2005-03-01
Nash equilibrium constitutes a central solution concept in game theory. The task of detecting the Nash equilibria of a finite strategic game remains a challenging problem up-to-date. This paper investigates the effectiveness of three computational intelligence techniques, namely, covariance matrix adaptation evolution strategies, particle swarm optimization, as well as, differential evolution, to compute Nash equilibria of finite strategic games, as global minima of a real-valued, nonnegative function. An issue of particular interest is to detect more than one Nash equilibria of a game. The performance of the considered computational intelligence methods on this problem is investigated using multistart and deflection.
Method for computed tomography
Wagner, W.
1980-01-01
In transversal computer tomography apparatus, in which the positioning zone in which the patient can be positioned is larger than the scanning zone in which a body slice can be scanned, reconstruction errors are liable to occur. These errors are caused by incomplete irradiation of the body during examination. They become manifest not only as an incorrect image of the area not irradiated, but also have an adverse effect on the image of the other, completely irradiated areas. The invention enables reduction of these errors
Computation of subsonic flow around airfoil systems with multiple separation
Jacob, K.
1982-01-01
A numerical method for computing the subsonic flow around multi-element airfoil systems was developed, allowing for flow separation at one or more elements. Besides multiple rear separation also sort bubbles on the upper surface and cove bubbles can approximately be taken into account. Also, compressibility effects for pure subsonic flow are approximately accounted for. After presentation the method is applied to several examples and improved in some details. Finally, the present limitations and desirable extensions are discussed.
Computational methods working group
Gabriel, T.A.
1997-09-01
During the Cold Moderator Workshop several working groups were established including one to discuss calculational methods. The charge for this working group was to identify problems in theory, data, program execution, etc., and to suggest solutions considering both deterministic and stochastic methods including acceleration procedures.
Zhang, Xuping; Sørensen, Rasmus; RahbekIversen, Mathias
2018-01-01
This paper presents a novel and computationally efficient modeling method for the dynamics of flexible-link robot manipulators. In this method, a robot manipulator is decomposed into components/elements. The component/element dynamics is established using Newton–Euler equations, and then is linea......This paper presents a novel and computationally efficient modeling method for the dynamics of flexible-link robot manipulators. In this method, a robot manipulator is decomposed into components/elements. The component/element dynamics is established using Newton–Euler equations......, and then is linearized based on the acceleration-based state vector. The transfer matrices for each type of components/elements are developed, and used to establish the system equations of a flexible robot manipulator by concatenating the state vector from the base to the end-effector. With this strategy, the size...... manipulators, and only involves calculating and transferring component/element dynamic equations that have small size. The numerical simulations and experimental testing of flexible-link manipulators are conducted to validate the proposed methodologies....
Evaluation of myocardial ischemia by multiple detector computed tomography
Fernandes, Fabio Vieira, E-mail: rccury@me.com [Hospital do Coracao (HCor), Sao Paulo, SP (Brazil); Cury, Roberto Caldeira [Hospital Samaritano, Sao Paulo, SP (Brazil)
2015-01-15
For years, cardiovascular diseases have been the leading cause of death worldwide, bringing on important social and economic consequences. Given this scenario, the search for a method capable of diagnosing coronary artery diseases in an early and accurate way is increasingly higher. The coronary computed tomography angiogram is already widely established for the stratification of coronary artery diseases, and, more recently, the computed tomography myocardial perfusion imaging has been providing relevant information by correlating ischemia and the coronary anatomy. The objective of this review is to describe the evaluation of myocardial ischemia by multiple detector computed tomography. This study will resort to controlled clinical trials that show the possibility of a single method to identify the atherosclerotic load, presence of coronary artery luminal narrowing and possible myocardial ischemia, by means of a fast, practical and reliable method validated by a multicenter study. (author)
Computational Methods in Medicine
Angel Garrido
2010-01-01
Full Text Available Artificial Intelligence requires Logic. But its Classical version shows too many insufficiencies. So, it is absolutely necessary to introduce more sophisticated tools, such as Fuzzy Logic, Modal Logic, Non-Monotonic Logic, and so on [2]. Among the things that AI needs to represent are Categories, Objects, Properties, Relations between objects, Situations, States, Time, Events, Causes and effects, Knowledge about knowledge, and so on. The problems in AI can be classified in two general types
[3, 4], Search Problems and Representation Problem. There exist different ways to reach this objective. So, we have [3] Logics, Rules, Frames, Associative Nets, Scripts and so on, that are often interconnected. Also, it will be very useful, in dealing with problems of uncertainty and causality, to introduce Bayesian Networks and particularly, a principal tool as the Essential Graph. We attempt here to show the scope of application of such versatile methods, currently fundamental in Medicine.
Computational and mathematical methods in brain atlasing.
Nowinski, Wieslaw L
2017-12-01
Brain atlases have a wide range of use from education to research to clinical applications. Mathematical methods as well as computational methods and tools play a major role in the process of brain atlas building and developing atlas-based applications. Computational methods and tools cover three areas: dedicated editors for brain model creation, brain navigators supporting multiple platforms, and atlas-assisted specific applications. Mathematical methods in atlas building and developing atlas-aided applications deal with problems in image segmentation, geometric body modelling, physical modelling, atlas-to-scan registration, visualisation, interaction and virtual reality. Here I overview computational and mathematical methods in atlas building and developing atlas-assisted applications, and share my contribution to and experience in this field.
Numerical methods in matrix computations
Björck, Åke
2015-01-01
Matrix algorithms are at the core of scientific computing and are indispensable tools in most applications in engineering. This book offers a comprehensive and up-to-date treatment of modern methods in matrix computation. It uses a unified approach to direct and iterative methods for linear systems, least squares and eigenvalue problems. A thorough analysis of the stability, accuracy, and complexity of the treated methods is given. Numerical Methods in Matrix Computations is suitable for use in courses on scientific computing and applied technical areas at advanced undergraduate and graduate level. A large bibliography is provided, which includes both historical and review papers as well as recent research papers. This makes the book useful also as a reference and guide to further study and research work. Åke Björck is a professor emeritus at the Department of Mathematics, Linköping University. He is a Fellow of the Society of Industrial and Applied Mathematics.
Numerical computer methods part D
Johnson, Michael L
2004-01-01
The aim of this volume is to brief researchers of the importance of data analysis in enzymology, and of the modern methods that have developed concomitantly with computer hardware. It is also to validate researchers' computer programs with real and synthetic data to ascertain that the results produced are what they expected. Selected Contents: Prediction of protein structure; modeling and studying proteins with molecular dynamics; statistical error in isothermal titration calorimetry; analysis of circular dichroism data; model comparison methods.
Computational Methods in Plasma Physics
Jardin, Stephen
2010-01-01
Assuming no prior knowledge of plasma physics or numerical methods, Computational Methods in Plasma Physics covers the computational mathematics and techniques needed to simulate magnetically confined plasmas in modern magnetic fusion experiments and future magnetic fusion reactors. Largely self-contained, the text presents the basic concepts necessary for the numerical solution of partial differential equations. Along with discussing numerical stability and accuracy, the author explores many of the algorithms used today in enough depth so that readers can analyze their stability, efficiency,
Multiple histogram method and static Monte Carlo sampling
Inda, M.A.; Frenkel, D.
2004-01-01
We describe an approach to use multiple-histogram methods in combination with static, biased Monte Carlo simulations. To illustrate this, we computed the force-extension curve of an athermal polymer from multiple histograms constructed in a series of static Rosenbluth Monte Carlo simulations. From
An algebraic substructuring using multiple shifts for eigenvalue computations
Ko, Jin Hwan; Jung, Sung Nam; Byun, Do Young; Bai, Zhaojun
2008-01-01
Algebraic substructuring (AS) is a state-of-the-art method in eigenvalue computations, especially for large-sized problems, but originally it was designed to calculate only the smallest eigenvalues. Recently, an updated version of AS has been introduced to calculate the interior eigenvalues over a specified range by using a shift concept that is referred to as the shifted AS. In this work, we propose a combined method of both AS and the shifted AS by using multiple shifts for solving a considerable number of eigensolutions in a large-sized problem, which is an emerging computational issue of noise or vibration analysis in vehicle design. In addition, we investigated the accuracy of the shifted AS by presenting an error criterion. The proposed method has been applied to the FE model of an automobile body. The combined method yielded a higher efficiency without loss of accuracy in comparison to the original AS
Computational methods in earthquake engineering
Plevris, Vagelis; Lagaros, Nikos
2017-01-01
This is the third book in a series on Computational Methods in Earthquake Engineering. The purpose of this volume is to bring together the scientific communities of Computational Mechanics and Structural Dynamics, offering a wide coverage of timely issues on contemporary Earthquake Engineering. This volume will facilitate the exchange of ideas in topics of mutual interest and can serve as a platform for establishing links between research groups with complementary activities. The computational aspects are emphasized in order to address difficult engineering problems of great social and economic importance. .
Methods for computing color anaglyphs
McAllister, David F.; Zhou, Ya; Sullivan, Sophia
2010-02-01
A new computation technique is presented for calculating pixel colors in anaglyph images. The method depends upon knowing the RGB spectral distributions of the display device and the transmission functions of the filters in the viewing glasses. It requires the solution of a nonlinear least-squares program for each pixel in a stereo pair and is based on minimizing color distances in the CIEL*a*b* uniform color space. The method is compared with several techniques for computing anaglyphs including approximation in CIE space using the Euclidean and Uniform metrics, the Photoshop method and its variants, and a method proposed by Peter Wimmer. We also discuss the methods of desaturation and gamma correction for reducing retinal rivalry.
Efficiently outsourcing multiparty computation under multiple keys
Peter, Andreas; Tews, Erik; Tews, Erik; Katzenbeisser, Stefan
2013-01-01
Secure multiparty computation enables a set of users to evaluate certain functionalities on their respective inputs while keeping these inputs encrypted throughout the computation. In many applications, however, outsourcing these computations to an untrusted server is desirable, so that the server
Computational methods in drug discovery
Sumudu P. Leelananda
2016-12-01
Full Text Available The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein–ligand docking, pharmacophore modeling and QSAR techniques are reviewed.
Combinatorial methods with computer applications
Gross, Jonathan L
2007-01-01
Combinatorial Methods with Computer Applications provides in-depth coverage of recurrences, generating functions, partitions, and permutations, along with some of the most interesting graph and network topics, design constructions, and finite geometries. Requiring only a foundation in discrete mathematics, it can serve as the textbook in a combinatorial methods course or in a combined graph theory and combinatorics course.After an introduction to combinatorics, the book explores six systematic approaches within a comprehensive framework: sequences, solving recurrences, evaluating summation exp
Fuzzy multiple linear regression: A computational approach
Juang, C. H.; Huang, X. H.; Fleming, J. W.
1992-01-01
This paper presents a new computational approach for performing fuzzy regression. In contrast to Bardossy's approach, the new approach, while dealing with fuzzy variables, closely follows the conventional regression technique. In this approach, treatment of fuzzy input is more 'computational' than 'symbolic.' The following sections first outline the formulation of the new approach, then deal with the implementation and computational scheme, and this is followed by examples to illustrate the new procedure.
Computational methods for fluid dynamics
Ferziger, Joel H
2002-01-01
In its 3rd revised and extended edition the book offers an overview of the techniques used to solve problems in fluid mechanics on computers and describes in detail those most often used in practice. Included are advanced methods in computational fluid dynamics, like direct and large-eddy simulation of turbulence, multigrid methods, parallel computing, moving grids, structured, block-structured and unstructured boundary-fitted grids, free surface flows. The 3rd edition contains a new section dealing with grid quality and an extended description of discretization methods. The book shows common roots and basic principles for many different methods. The book also contains a great deal of practical advice for code developers and users, it is designed to be equally useful to beginners and experts. The issues of numerical accuracy, estimation and reduction of numerical errors are dealt with in detail, with many examples. A full-feature user-friendly demo-version of a commercial CFD software has been added, which ca...
Numerical computer methods part E
Johnson, Michael L
2004-01-01
The contributions in this volume emphasize analysis of experimental data and analytical biochemistry, with examples taken from biochemistry. They serve to inform biomedical researchers of the modern data analysis methods that have developed concomitantly with computer hardware. Selected Contents: A practical approach to interpretation of SVD results; modeling of oscillations in endocrine networks with feedback; quantifying asynchronous breathing; sample entropy; wavelet modeling and processing of nasal airflow traces.
A computer program for multiple decrement life table analyses.
Poole, W K; Cooley, P C
1977-06-01
Life table analysis has traditionally been the tool of choice in analyzing distribution of "survival" times when a parametric form for the survival curve could not be reasonably assumed. Chiang, in two papers [1,2] formalized the theory of life table analyses in a Markov chain framework and derived maximum likelihood estimates of the relevant parameters for the analyses. He also discussed how the techniques could be generalized to consider competing risks and follow-up studies. Although various computer programs exist for doing different types of life table analysis [3] to date, there has not been a generally available, well documented computer program to carry out multiple decrement analyses, either by Chiang's or any other method. This paper describes such a program developed by Research Triangle Institute. A user's manual is available at printing costs which supplements the contents of this paper with a discussion of the formula used in the program listing.
Computational methods for stellerator configurations
Betancourt, O.
1992-01-01
This project had two main objectives. The first one was to continue to develop computational methods for the study of three dimensional magnetic confinement configurations. The second one was to collaborate and interact with researchers in the field who can use these techniques to study and design fusion experiments. The first objective has been achieved with the development of the spectral code BETAS and the formulation of a new variational approach for the study of magnetic island formation in a self consistent fashion. The code can compute the correct island width corresponding to the saturated island, a result shown by comparing the computed island with the results of unstable tearing modes in Tokamaks and with experimental results in the IMS Stellarator. In addition to studying three dimensional nonlinear effects in Tokamaks configurations, these self consistent computed island equilibria will be used to study transport effects due to magnetic island formation and to nonlinearly bifurcated equilibria. The second objective was achieved through direct collaboration with Steve Hirshman at Oak Ridge, D. Anderson and R. Talmage at Wisconsin as well as through participation in the Sherwood and APS meetings
Sharp, John T; Angwin, Jane; Boers, Maarten; Duryea, Jeff; Finckh, Axel; Hall, James R; Kauffman, Joost A; Landewé, Robert; Langs, Georg; Lukas, Cédric; Moens, H J Bernelot; Peloschek, Philipp; Strand, C Vibeke; van der Heijde, Désirée
2009-08-01
Previously reported data on 5 computer-based programs for measurement of joint space width focusing on discriminating ability and reproducibility are updated, showing new data. Four of 5 different programs for measuring joint space width were more discriminating than observer scoring for change in narrowing in the 12 months interval. Three of 4 programs were more discriminating than observer scoring for the 0-18 month interval. The program that failed to discriminate in the 0-12 month interval was not the same program that failed in the 0-18 month interval. The committee agreed at an interim meeting in November 2007 that an important goal for computer-based measurement programs is a 90% success rate in making measurements of joint pairs in followup studies. This means that the same joint must be measured in images of both timepoints in order to assess change over time in serial radiographs. None of the programs met this 90% threshold, but 3 programs achieved 85%-90% success rate. Intraclass correlation coefficients for assessing change in joint space width in individual joints were 0.98 or 0.99 for 4 programs. The smallest detectable change was < 0.2 mm for 4 of the 5 programs, representing 29%-36% of the change within the 99th percentile of measurements.
Computer simulation of multiple dynamic photorefractive gratings
Buchhave, Preben
1998-01-01
The benefits of a direct visualization of space-charge grating buildup are described. The visualization is carried out by a simple repetitive computer program, which simulates the basic processes in the band-transport model and displays the result graphically or in the form of numerical data. The...
Computational methods for molecular imaging
Shi, Kuangyu; Li, Shuo
2015-01-01
This volume contains original submissions on the development and application of molecular imaging computing. The editors invited authors to submit high-quality contributions on a wide range of topics including, but not limited to: • Image Synthesis & Reconstruction of Emission Tomography (PET, SPECT) and other Molecular Imaging Modalities • Molecular Imaging Enhancement • Data Analysis of Clinical & Pre-clinical Molecular Imaging • Multi-Modal Image Processing (PET/CT, PET/MR, SPECT/CT, etc.) • Machine Learning and Data Mining in Molecular Imaging. Molecular imaging is an evolving clinical and research discipline enabling the visualization, characterization and quantification of biological processes taking place at the cellular and subcellular levels within intact living subjects. Computational methods play an important role in the development of molecular imaging, from image synthesis to data analysis and from clinical diagnosis to therapy individualization. This work will bring readers fro...
Computing multiple-output regression quantile regions
Paindaveine, D.; Šiman, Miroslav
2012-01-01
Roč. 56, č. 4 (2012), s. 840-853 ISSN 0167-9473 R&D Projects: GA MŠk(CZ) 1M06047 Institutional research plan: CEZ:AV0Z10750506 Keywords : halfspace depth * multiple-output regression * parametric linear programming * quantile regression Subject RIV: BA - General Mathematics Impact factor: 1.304, year: 2012 http://library.utia.cas.cz/separaty/2012/SI/siman-0376413.pdf
Continuous analog of multiplicative algebraic reconstruction technique for computed tomography
Tateishi, Kiyoko; Yamaguchi, Yusaku; Abou Al-Ola, Omar M.; Kojima, Takeshi; Yoshinaga, Tetsuya
2016-03-01
We propose a hybrid dynamical system as a continuous analog to the block-iterative multiplicative algebraic reconstruction technique (BI-MART), which is a well-known iterative image reconstruction algorithm for computed tomography. The hybrid system is described by a switched nonlinear system with a piecewise smooth vector field or differential equation and, for consistent inverse problems, the convergence of non-negatively constrained solutions to a globally stable equilibrium is guaranteed by the Lyapunov theorem. Namely, we can prove theoretically that a weighted Kullback-Leibler divergence measure can be a common Lyapunov function for the switched system. We show that discretizing the differential equation by using the first-order approximation (Euler's method) based on the geometric multiplicative calculus leads to the same iterative formula of the BI-MART with the scaling parameter as a time-step of numerical discretization. The present paper is the first to reveal that a kind of iterative image reconstruction algorithm is constructed by the discretization of a continuous-time dynamical system for solving tomographic inverse problems. Iterative algorithms with not only the Euler method but also the Runge-Kutta methods of lower-orders applied for discretizing the continuous-time system can be used for image reconstruction. A numerical example showing the characteristics of the discretized iterative methods is presented.
Computer methods in general relativity: algebraic computing
Araujo, M E; Skea, J E F; Koutras, A; Krasinski, A; Hobill, D; McLenaghan, R G; Christensen, S M
1993-01-01
Karlhede & MacCallum [1] gave a procedure for determining the Lie algebra of the isometry group of an arbitrary pseudo-Riemannian manifold, which they intended to im- plement using the symbolic manipulation package SHEEP but never did. We have recently ﬁnished making this procedure explicit by giving an algorithm suitable for implemen- tation on a computer [2]. Specifically, we have written an algorithm for determining the isometry group of a spacetime (in four dimensions), and partially implemented this algorithm using the symbolic manipulation package CLASSI, which is an extension of SHEEP.
Introduction to programming multiple-processor computers
Hicks, H.R.; Lynch, V.E.
1985-04-01
FORTRAN applications programs can be executed on multiprocessor computers in either a unitasking (traditional) or multitasking form. The latter allows a single job to use more than one processor simultaneously, with a consequent reduction in wall-clock time and, perhaps, the cost of the calculation. An introduction to programming in this environment is presented. The concepts of synchronization and data sharing using EVENTS and LOCKS are illustrated with examples. The strategy of strong synchronization and the use of synchronization templates are proposed. We emphasize that incorrect multitasking programs can produce irreproducible results, which makes debugging more difficult
Optimization of breeding methods when introducing multiple ...
Optimization of breeding methods when introducing multiple resistance genes from American to Chinese wheat. JN Qi, X Zhang, C Yin, H Li, F Lin. Abstract. Stripe rust is one of the most destructive diseases of wheat worldwide. Growing resistant cultivars with resistance genes is the most effective method to control this ...
Fast computation of the characteristics method on vector computers
Kugo, Teruhiko
2001-11-01
Fast computation of the characteristics method to solve the neutron transport equation in a heterogeneous geometry has been studied. Two vector computation algorithms; an odd-even sweep (OES) method and an independent sequential sweep (ISS) method have been developed and their efficiency to a typical fuel assembly calculation has been investigated. For both methods, a vector computation is 15 times faster than a scalar computation. From a viewpoint of comparison between the OES and ISS methods, the followings are found: 1) there is a small difference in a computation speed, 2) the ISS method shows a faster convergence and 3) the ISS method saves about 80% of computer memory size compared with the OES method. It is, therefore, concluded that the ISS method is superior to the OES method as a vectorization method. In the vector computation, a table-look-up method to reduce computation time of an exponential function saves only 20% of a whole computation time. Both the coarse mesh rebalance method and the Aitken acceleration method are effective as acceleration methods for the characteristics method, a combination of them saves 70-80% of outer iterations compared with a free iteration. (author)
Hybrid multiple criteria decision-making methods
Zavadskas, Edmundas Kazimieras; Govindan, K.; Antucheviciene, Jurgita
2016-01-01
Formal decision-making methods can be used to help improve the overall sustainability of industries and organisations. Recently, there has been a great proliferation of works aggregating sustainability criteria by using diverse multiple criteria decision-making (MCDM) techniques. A number of revi...
Computational Methods and Function Theory
Saff, Edward; Salinas, Luis; Varga, Richard
1990-01-01
The volume is devoted to the interaction of modern scientific computation and classical function theory. Many problems in pure and more applied function theory can be tackled using modern computing facilities: numerically as well as in the sense of computer algebra. On the other hand, computer algorithms are often based on complex function theory, and dedicated research on their theoretical foundations can lead to great enhancements in performance. The contributions - original research articles, a survey and a collection of problems - cover a broad range of such problems.
SWIMS: a small-angle multiple scattering computer code
Sayer, R.O.
1976-07-01
SWIMS (Sigmund and WInterbon Multiple Scattering) is a computer code for calculation of the angular dispersion of ion beams that undergo small-angle, incoherent multiple scattering by gaseous or solid media. The code uses the tabulated angular distributions of Sigmund and Winterbon for a Thomas-Fermi screened Coulomb potential. The fraction of the incident beam scattered into a cone defined by the polar angle α is computed as a function of α for reduced thicknesses over the range 0.01 less than or equal to tau less than or equal to 10.0. 1 figure, 2 tables
Building an organic computing device with multiple interconnected brains
Pais-Vieira, Miguel; Chiuffa, Gabriela; Lebedev, Mikhail; Yadav, Amol; Nicolelis, Miguel A. L.
2015-01-01
Recently, we proposed that Brainets, i.e. networks formed by multiple animal brains, cooperating and exchanging information in real time through direct brain-to-brain interfaces, could provide the core of a new type of computing device: an organic computer. Here, we describe the first experimental demonstration of such a Brainet, built by interconnecting four adult rat brains. Brainets worked by concurrently recording the extracellular electrical activity generated by populations of cortical ...
Multiple-User, Multitasking, Virtual-Memory Computer System
Generazio, Edward R.; Roth, Don J.; Stang, David B.
1993-01-01
Computer system designed and programmed to serve multiple users in research laboratory. Provides for computer control and monitoring of laboratory instruments, acquisition and anlaysis of data from those instruments, and interaction with users via remote terminals. System provides fast access to shared central processing units and associated large (from megabytes to gigabytes) memories. Underlying concept of system also applicable to monitoring and control of industrial processes.
Computed Tomography diagnosis of skeletal involvement in multiple myeloma
Scutellari, Pier Nuccio; Galeotti, Roberto; Leprotti, Stefano; Piva, Nadia; Spanedda, Romedio
1997-01-01
The authors assess the role of Computed Topography in the diagnosis and management of multiple myeloma (MM) and investigate if Computed Tomography findings can influence the clinical approach, prognosis and treatment. 273 multiple myeloma patients submitted to Computed Tomography June 1994, to December, 1996. The patients were 143 men and 130 women (mean age: 65 years): 143 were stage I, 38 stage II and 92 stage III according to Durie and Salomon's clinical classification. All patients were submitted to blood tests, spinal radiography and Computed Tomography, the latter with serial 5-mm scans on several vertebral bodies. Computed Tomography despicted vertebral arch and process involvement in 3 cases with the vertebral pedicle sign. Moreover, Computed Tomography proved superior to radiography in showing the spread of myelomatous masses into the soft tissues in a case with solitary permeative lesion in the left public bone, which facilitated subsequent biopsy. As for extraosseous localizations, Computed Tomography demonstrated thoracic soft tissue (1 woman) and pelvic (1 man) involvement by myelomtous masses penetrating into surrounding tissues. In our series, only a case of osteosclerotic bone myeloma was observed in the pelvis, associated with lytic abnormalities. Computed Tomography findings do not seem to improve the clinical approach and therapeutic management of the disease. Nevertheless, the authors reccommend Computed Tomography for some myelomatous conditions, namely: a) in the patients with focal bone pain but normal skeletal radiographs; b) in the patients with M protein, bone marrow plasmocytosis and back pain, but with an incoclusive multiple myeloma diagnosis; c) to asses bone spread in the regions which are anatomically complex or difficult to study with radiography and to depict soft tissue involvement; d) for bone biopsy
Computational methods for reversed-field equilibrium
Boyd, J.K.; Auerbach, S.P.; Willmann, P.A.; Berk, H.L.; McNamara, B.
1980-01-01
Investigating the temporal evolution of reversed-field equilibrium caused by transport processes requires the solution of the Grad-Shafranov equation and computation of field-line-averaged quantities. The technique for field-line averaging and the computation of the Grad-Shafranov equation are presented. Application of Green's function to specify the Grad-Shafranov equation boundary condition is discussed. Hill's vortex formulas used to verify certain computations are detailed. Use of computer software to implement computational methods is described
Methods for monitoring multiple gene expression
Berka, Randy [Davis, CA; Bachkirova, Elena [Davis, CA; Rey, Michael [Davis, CA
2012-05-01
The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.
Methods for monitoring multiple gene expression
Berka, Randy; Bachkirova, Elena; Rey, Michael
2013-10-01
The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.
MULGRES: a computer program for stepwise multiple regression analysis
A. Jeff Martin
1971-01-01
MULGRES is a computer program source deck that is designed for multiple regression analysis employing the technique of stepwise deletion in the search for most significant variables. The features of the program, along with inputs and outputs, are briefly described, with a note on machine compatibility.
Performance of Cloud Computing Centers with Multiple Priority Classes
Ellens, W.; Zivkovic, Miroslav; Akkerboom, J.; Litjens, R.; van den Berg, Hans Leo
In this paper we consider the general problem of resource provisioning within cloud computing. We analyze the problem of how to allocate resources to different clients such that the service level agreements (SLAs) for all of these clients are met. A model with multiple service request classes
Computer optimization of cutting yield from multiple ripped boards
A.R. Stern; K.A. McDonald
1978-01-01
RIPYLD is a computer program that optimizes the cutting yield from multiple-ripped boards. Decisions are based on automatically collected defect information, cutting bill requirements, and sawing variables. The yield of clear cuttings from a board is calculated for every possible permutation of specified rip widths and both the maximum and minimum percent yield...
Teacher regulation of multiple computer-supported collaborating groups
Van Leeuwen, Anouschka; Janssen, Jeroen; Erkens, Gijsbert; Brekelmans, Mieke
2015-01-01
Teachers regulating groups of students during computer-supported collaborative learning (CSCL) face the challenge of orchestrating their guidance at student, group, and class level. During CSCL, teachers can monitor all student activity and interact with multiple groups at the same time. Not much is
Multiple Embedded Processors for Fault-Tolerant Computing
Bolotin, Gary; Watson, Robert; Katanyoutanant, Sunant; Burke, Gary; Wang, Mandy
2005-01-01
A fault-tolerant computer architecture has been conceived in an effort to reduce vulnerability to single-event upsets (spurious bit flips caused by impingement of energetic ionizing particles or photons). As in some prior fault-tolerant architectures, the redundancy needed for fault tolerance is obtained by use of multiple processors in one computer. Unlike prior architectures, the multiple processors are embedded in a single field-programmable gate array (FPGA). What makes this new approach practical is the recent commercial availability of FPGAs that are capable of having multiple embedded processors. A working prototype (see figure) consists of two embedded IBM PowerPC 405 processor cores and a comparator built on a Xilinx Virtex-II Pro FPGA. This relatively simple instantiation of the architecture implements an error-detection scheme. A planned future version, incorporating four processors and two comparators, would correct some errors in addition to detecting them.
New weighting methods for phylogenetic tree reconstruction using multiple loci.
Misawa, Kazuharu; Tajima, Fumio
2012-08-01
Efficient determination of evolutionary distances is important for the correct reconstruction of phylogenetic trees. The performance of the pooled distance required for reconstructing a phylogenetic tree can be improved by applying large weights to appropriate distances for reconstructing phylogenetic trees and small weights to inappropriate distances. We developed two weighting methods, the modified Tajima-Takezaki method and the modified least-squares method, for reconstructing phylogenetic trees from multiple loci. By computer simulations, we found that both of the new methods were more efficient in reconstructing correct topologies than the no-weight method. Hence, we reconstructed hominoid phylogenetic trees from mitochondrial DNA using our new methods, and found that the levels of bootstrap support were significantly increased by the modified Tajima-Takezaki and by the modified least-squares method.
Novel methods in computational finance
Günther, Michael; Maten, E
2017-01-01
This book discusses the state-of-the-art and open problems in computational finance. It presents a collection of research outcomes and reviews of the work from the STRIKE project, an FP7 Marie Curie Initial Training Network (ITN) project in which academic partners trained early-stage researchers in close cooperation with a broader range of associated partners, including from the private sector. The aim of the project was to arrive at a deeper understanding of complex (mostly nonlinear) financial models and to develop effective and robust numerical schemes for solving linear and nonlinear problems arising from the mathematical theory of pricing financial derivatives and related financial products. This was accomplished by means of financial modelling, mathematical analysis and numerical simulations, optimal control techniques and validation of models. In recent years the computational complexity of mathematical models employed in financial mathematics has witnessed tremendous growth. Advanced numerical techni...
COMPUTER METHODS OF GENETIC ANALYSIS.
A. L. Osipov
2017-02-01
Full Text Available The basic statistical methods used in conducting the genetic analysis of human traits. We studied by segregation analysis, linkage analysis and allelic associations. Developed software for the implementation of these methods support.
Vertical Load Distribution for Cloud Computing via Multiple Implementation Options
Phan, Thomas; Li, Wen-Syan
Cloud computing looks to deliver software as a provisioned service to end users, but the underlying infrastructure must be sufficiently scalable and robust. In our work, we focus on large-scale enterprise cloud systems and examine how enterprises may use a service-oriented architecture (SOA) to provide a streamlined interface to their business processes. To scale up the business processes, each SOA tier usually deploys multiple servers for load distribution and fault tolerance, a scenario which we term horizontal load distribution. One limitation of this approach is that load cannot be distributed further when all servers in the same tier are loaded. In complex multi-tiered SOA systems, a single business process may actually be implemented by multiple different computation pathways among the tiers, each with different components, in order to provide resilience and scalability. Such multiple implementation options gives opportunities for vertical load distribution across tiers. In this chapter, we look at a novel request routing framework for SOA-based enterprise computing with multiple implementation options that takes into account the options of both horizontal and vertical load distribution.
Computational methods in drug discovery
Sumudu P. Leelananda; Steffen Lindert
2016-01-01
The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery project...
Multiple predictor smoothing methods for sensitivity analysis
Helton, Jon Craig; Storlie, Curtis B.
2006-01-01
The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (1) locally weighted regression (LOESS), (2) additive models, (3) projection pursuit regression, and (4) recursive partitioning regression. The indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present
Multiple predictor smoothing methods for sensitivity analysis.
Helton, Jon Craig; Storlie, Curtis B.
2006-08-01
The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (1) locally weighted regression (LOESS), (2) additive models, (3) projection pursuit regression, and (4) recursive partitioning regression. The indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present.
Computer studies of multiple-quantum spin dynamics
Murdoch, J.B.
1982-11-01
The excitation and detection of multiple-quantum (MQ) transitions in Fourier transform NMR spectroscopy is an interesting problem in the quantum mechanical dynamics of spin systems as well as an important new technique for investigation of molecular structure. In particular, multiple-quantum spectroscopy can be used to simplify overly complex spectra or to separate the various interactions between a nucleus and its environment. The emphasis of this work is on computer simulation of spin-system evolution to better relate theory and experiment.
A computer program for determining multiplicities of powder reflexions
Rouse, K.D.; Cooper, M.J.
1977-01-01
A computer program has been written which determines the multiplicity factors for a given set of X-ray or neutron powder diffraction reflexions for crystals of any space group. The value of the multiplicity for each reflexion is determined from a look-up table which is indexed by the symmetry type, determined directly from the space-group number, and the reflexion type, determined from the Miller indices. There are no restrictions on the choice of indices which are used to specify the reflexions. (Auth.)
Computer studies of multiple-quantum spin dynamics
Murdoch, J.B.
1982-11-01
The excitation and detection of multiple-quantum (MQ) transitions in Fourier transform NMR spectroscopy is an interesting problem in the quantum mechanical dynamics of spin systems as well as an important new technique for investigation of molecular structure. In particular, multiple-quantum spectroscopy can be used to simplify overly complex spectra or to separate the various interactions between a nucleus and its environment. The emphasis of this work is on computer simulation of spin-system evolution to better relate theory and experiment
Computing all hybridization networks for multiple binary phylogenetic input trees.
Albrecht, Benjamin
2015-07-30
The computation of phylogenetic trees on the same set of species that are based on different orthologous genes can lead to incongruent trees. One possible explanation for this behavior are interspecific hybridization events recombining genes of different species. An important approach to analyze such events is the computation of hybridization networks. This work presents the first algorithm computing the hybridization number as well as a set of representative hybridization networks for multiple binary phylogenetic input trees on the same set of taxa. To improve its practical runtime, we show how this algorithm can be parallelized. Moreover, we demonstrate the efficiency of the software Hybroscale, containing an implementation of our algorithm, by comparing it to PIRNv2.0, which is so far the best available software computing the exact hybridization number for multiple binary phylogenetic trees on the same set of taxa. The algorithm is part of the software Hybroscale, which was developed specifically for the investigation of hybridization networks including their computation and visualization. Hybroscale is freely available(1) and runs on all three major operating systems. Our simulation study indicates that our approach is on average 100 times faster than PIRNv2.0. Moreover, we show how Hybroscale improves the interpretation of the reported hybridization networks by adding certain features to its graphical representation.
Computational predictive methods for fracture and fatigue
Cordes, J.; Chang, A. T.; Nelson, N.; Kim, Y.
1994-09-01
The damage-tolerant design philosophy as used by aircraft industries enables aircraft components and aircraft structures to operate safely with minor damage, small cracks, and flaws. Maintenance and inspection procedures insure that damages developed during service remain below design values. When damage is found, repairs or design modifications are implemented and flight is resumed. Design and redesign guidelines, such as military specifications MIL-A-83444, have successfully reduced the incidence of damage and cracks. However, fatigue cracks continue to appear in aircraft well before the design life has expired. The F16 airplane, for instance, developed small cracks in the engine mount, wing support, bulk heads, the fuselage upper skin, the fuel shelf joints, and along the upper wings. Some cracks were found after 600 hours of the 8000 hour design service life and design modifications were required. Tests on the F16 plane showed that the design loading conditions were close to the predicted loading conditions. Improvements to analytic methods for predicting fatigue crack growth adjacent to holes, when multiple damage sites are present, and in corrosive environments would result in more cost-effective designs, fewer repairs, and fewer redesigns. The overall objective of the research described in this paper is to develop, verify, and extend the computational efficiency of analysis procedures necessary for damage tolerant design. This paper describes an elastic/plastic fracture method and an associated fatigue analysis method for damage tolerant design. Both methods are unique in that material parameters such as fracture toughness, R-curve data, and fatigue constants are not required. The methods are implemented with a general-purpose finite element package. Several proof-of-concept examples are given. With further development, the methods could be extended for analysis of multi-site damage, creep-fatigue, and corrosion fatigue problems.
Hybrid Monte Carlo methods in computational finance
Leitao Rodriguez, A.
2017-01-01
Monte Carlo methods are highly appreciated and intensively employed in computational finance in the context of financial derivatives valuation or risk management. The method offers valuable advantages like flexibility, easy interpretation and straightforward implementation. Furthermore, the
Advanced computational electromagnetic methods and applications
Li, Wenxing; Elsherbeni, Atef; Rahmat-Samii, Yahya
2015-01-01
This new resource covers the latest developments in computational electromagnetic methods, with emphasis on cutting-edge applications. This book is designed to extend existing literature to the latest development in computational electromagnetic methods, which are of interest to readers in both academic and industrial areas. The topics include advanced techniques in MoM, FEM and FDTD, spectral domain method, GPU and Phi hardware acceleration, metamaterials, frequency and time domain integral equations, and statistics methods in bio-electromagnetics.
Computational Methods for Biomolecular Electrostatics
Dong, Feng; Olsen, Brett; Baker, Nathan A.
2008-01-01
An understanding of intermolecular interactions is essential for insight into how cells develop, operate, communicate and control their activities. Such interactions include several components: contributions from linear, angular, and torsional forces in covalent bonds, van der Waals forces, as well as electrostatics. Among the various components of molecular interactions, electrostatics are of special importance because of their long range and their influence on polar or charged molecules, including water, aqueous ions, and amino or nucleic acids, which are some of the primary components of living systems. Electrostatics, therefore, play important roles in determining the structure, motion and function of a wide range of biological molecules. This chapter presents a brief overview of electrostatic interactions in cellular systems with a particular focus on how computational tools can be used to investigate these types of interactions. PMID:17964951
A level set method for multiple sclerosis lesion segmentation.
Zhao, Yue; Guo, Shuxu; Luo, Min; Shi, Xue; Bilello, Michel; Zhang, Shaoxiang; Li, Chunming
2018-06-01
In this paper, we present a level set method for multiple sclerosis (MS) lesion segmentation from FLAIR images in the presence of intensity inhomogeneities. We use a three-phase level set formulation of segmentation and bias field estimation to segment MS lesions and normal tissue region (including GM and WM) and CSF and the background from FLAIR images. To save computational load, we derive a two-phase formulation from the original multi-phase level set formulation to segment the MS lesions and normal tissue regions. The derived method inherits the desirable ability to precisely locate object boundaries of the original level set method, which simultaneously performs segmentation and estimation of the bias field to deal with intensity inhomogeneity. Experimental results demonstrate the advantages of our method over other state-of-the-art methods in terms of segmentation accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.
Integrating computational methods to retrofit enzymes to synthetic pathways.
Brunk, Elizabeth; Neri, Marilisa; Tavernelli, Ivano; Hatzimanikatis, Vassily; Rothlisberger, Ursula
2012-02-01
Microbial production of desired compounds provides an efficient framework for the development of renewable energy resources. To be competitive to traditional chemistry, one requirement is to utilize the full capacity of the microorganism to produce target compounds with high yields and turnover rates. We use integrated computational methods to generate and quantify the performance of novel biosynthetic routes that contain highly optimized catalysts. Engineering a novel reaction pathway entails addressing feasibility on multiple levels, which involves handling the complexity of large-scale biochemical networks while respecting the critical chemical phenomena at the atomistic scale. To pursue this multi-layer challenge, our strategy merges knowledge-based metabolic engineering methods with computational chemistry methods. By bridging multiple disciplines, we provide an integral computational framework that could accelerate the discovery and implementation of novel biosynthetic production routes. Using this approach, we have identified and optimized a novel biosynthetic route for the production of 3HP from pyruvate. Copyright © 2011 Wiley Periodicals, Inc.
Case studies: Soil mapping using multiple methods
Petersen, Hauke; Wunderlich, Tina; Hagrey, Said A. Al; Rabbel, Wolfgang; Stümpel, Harald
2010-05-01
Soil is a non-renewable resource with fundamental functions like filtering (e.g. water), storing (e.g. carbon), transforming (e.g. nutrients) and buffering (e.g. contamination). Degradation of soils is meanwhile not only to scientists a well known fact, also decision makers in politics have accepted this as a serious problem for several environmental aspects. National and international authorities have already worked out preservation and restoration strategies for soil degradation, though it is still work of active research how to put these strategies into real practice. But common to all strategies the description of soil state and dynamics is required as a base step. This includes collecting information from soils with methods ranging from direct soil sampling to remote applications. In an intermediate scale mobile geophysical methods are applied with the advantage of fast working progress but disadvantage of site specific calibration and interpretation issues. In the framework of the iSOIL project we present here some case studies for soil mapping performed using multiple geophysical methods. We will present examples of combined field measurements with EMI-, GPR-, magnetic and gammaspectrometric techniques carried out with the mobile multi-sensor-system of Kiel University (GER). Depending on soil type and actual environmental conditions, different methods show a different quality of information. With application of diverse methods we want to figure out, which methods or combination of methods will give the most reliable information concerning soil state and properties. To investigate the influence of varying material we performed mapping campaigns on field sites with sandy, loamy and loessy soils. Classification of measured or derived attributes show not only the lateral variability but also gives hints to a variation in the vertical distribution of soil material. For all soils of course soil water content can be a critical factor concerning a succesful
Computational methods in power system analysis
Idema, Reijer
2014-01-01
This book treats state-of-the-art computational methods for power flow studies and contingency analysis. In the first part the authors present the relevant computational methods and mathematical concepts. In the second part, power flow and contingency analysis are treated. Furthermore, traditional methods to solve such problems are compared to modern solvers, developed using the knowledge of the first part of the book. Finally, these solvers are analyzed both theoretically and experimentally, clearly showing the benefits of the modern approach.
Computational methods for data evaluation and assimilation
Cacuci, Dan Gabriel
2013-01-01
Data evaluation and data combination require the use of a wide range of probability theory concepts and tools, from deductive statistics mainly concerning frequencies and sample tallies to inductive inference for assimilating non-frequency data and a priori knowledge. Computational Methods for Data Evaluation and Assimilation presents interdisciplinary methods for integrating experimental and computational information. This self-contained book shows how the methods can be applied in many scientific and engineering areas. After presenting the fundamentals underlying the evaluation of experiment
Fibonacci’s Computation Methods vs Modern Algorithms
Ernesto Burattini
2013-12-01
Full Text Available In this paper we discuss some computational procedures given by Leonardo Pisano Fibonacci in his famous Liber Abaci book, and we propose their translation into a modern language for computers (C ++. Among the other we describe the method of “cross” multiplication, we evaluate its computational complexity in algorithmic terms and we show the output of a C ++ code that describes the development of the method applied to the product of two integers. In a similar way we show the operations performed on fractions introduced by Fibonacci. Thanks to the possibility to reproduce on a computer, the Fibonacci’s different computational procedures, it was possible to identify some calculation errors present in the different versions of the original text.
Computer code MLCOSP for multiple-correlation and spectrum analysis with a hybrid computer
Oguma, Ritsuo; Fujii, Yoshio; Usui, Hozumi; Watanabe, Koichi
1975-10-01
Usage of the computer code MLCOSP(Multiple Correlation and Spectrum) developed is described for a hybrid computer installed in JAERI Functions of the hybrid computer and its terminal devices are utilized ingeniously in the code to reduce complexity of the data handling which occurrs in analysis of the multivariable experimental data and to perform the analysis in perspective. Features of the code are as follows; Experimental data can be fed to the digital computer through the analog part of the hybrid computer by connecting with a data recorder. The computed results are displayed in figures, and hardcopies are taken when necessary. Series-messages to the code are shown on the terminal, so man-machine communication is possible. And further the data can be put in through a keyboard, so case study according to the results of analysis is possible. (auth.)
Evaluation of Network Reliability for Computer Networks with Multiple Sources
Yi-Kuei Lin
2012-01-01
Full Text Available Evaluating the reliability of a network with multiple sources to multiple sinks is a critical issue from the perspective of quality management. Due to the unrealistic definition of paths of network models in previous literature, existing models are not appropriate for real-world computer networks such as the Taiwan Advanced Research and Education Network (TWAREN. This paper proposes a modified stochastic-flow network model to evaluate the network reliability of a practical computer network with multiple sources where data is transmitted through several light paths (LPs. Network reliability is defined as being the probability of delivering a specified amount of data from the sources to the sink. It is taken as a performance index to measure the service level of TWAREN. This paper studies the network reliability of the international portion of TWAREN from two sources (Taipei and Hsinchu to one sink (New York that goes through a submarine and land surface cable between Taiwan and the United States.
Galerkin projection methods for solving multiple related linear systems
Chan, T.F.; Ng, M.; Wan, W.L.
1996-12-31
We consider using Galerkin projection methods for solving multiple related linear systems A{sup (i)}x{sup (i)} = b{sup (i)} for 1 {le} i {le} s, where A{sup (i)} and b{sup (i)} are different in general. We start with the special case where A{sup (i)} = A and A is symmetric positive definite. The method generates a Krylov subspace from a set of direction vectors obtained by solving one of the systems, called the seed system, by the CG method and then projects the residuals of other systems orthogonally onto the generated Krylov subspace to get the approximate solutions. The whole process is repeated with another unsolved system as a seed until all the systems are solved. We observe in practice a super-convergence behaviour of the CG process of the seed system when compared with the usual CG process. We also observe that only a small number of restarts is required to solve all the systems if the right-hand sides are close to each other. These two features together make the method particularly effective. In this talk, we give theoretical proof to justify these observations. Furthermore, we combine the advantages of this method and the block CG method and propose a block extension of this single seed method. The above procedure can actually be modified for solving multiple linear systems A{sup (i)}x{sup (i)} = b{sup (i)}, where A{sup (i)} are now different. We can also extend the previous analytical results to this more general case. Applications of this method to multiple related linear systems arising from image restoration and recursive least squares computations are considered as examples.
Electromagnetic field computation by network methods
Felsen, Leopold B; Russer, Peter
2009-01-01
This monograph proposes a systematic and rigorous treatment of electromagnetic field representations in complex structures. The book presents new strong models by combining important computational methods. This is the last book of the late Leopold Felsen.
Decreasing Multicollinearity: A Method for Models with Multiplicative Functions.
Smith, Kent W.; Sasaki, M. S.
1979-01-01
A method is proposed for overcoming the problem of multicollinearity in multiple regression equations where multiplicative independent terms are entered. The method is not a ridge regression solution. (JKS)
Strategies for Sharing Seismic Data Among Multiple Computer Platforms
Baker, L. M.; Fletcher, J. B.
2001-12-01
the user. Commercial software packages, such as MatLab, also have the ability to share data in their own formats across multiple computer platforms. Our Fortran applications can create plot files in Adobe PostScript, Illustrator, and Portable Document Format (PDF) formats. Vendor support for reading these files is readily available on multiple computer platforms. We will illustrate by example our strategies for sharing seismic data among our multiple computer platforms, and we will discuss our positive and negative experiences. We will include our solutions for handling the different byte ordering, floating-point formats, and text file ``end-of-line'' conventions on the various computer platforms we use (6 different operating systems on 5 processor architectures).
Methods in computed angiotomography of the brain
Yamamoto, Yuji; Asari, Shoji; Sadamoto, Kazuhiko.
1985-01-01
Authors introduce the methods in computed angiotomography of the brain. Setting of the scan planes and levels and the minimum dose bolus (MinDB) injection of contrast medium are described in detail. These methods are easily and safely employed with the use of already propagated CT scanners. Computed angiotomography is expected for clinical applications in many institutions because of its diagnostic value in screening of cerebrovascular lesions and in demonstrating the relationship between pathological lesions and cerebral vessels. (author)
Methods and experimental techniques in computer engineering
Schiaffonati, Viola
2014-01-01
Computing and science reveal a synergic relationship. On the one hand, it is widely evident that computing plays an important role in the scientific endeavor. On the other hand, the role of scientific method in computing is getting increasingly important, especially in providing ways to experimentally evaluate the properties of complex computing systems. This book critically presents these issues from a unitary conceptual and methodological perspective by addressing specific case studies at the intersection between computing and science. The book originates from, and collects the experience of, a course for PhD students in Information Engineering held at the Politecnico di Milano. Following the structure of the course, the book features contributions from some researchers who are working at the intersection between computing and science.
Monitoring system of multiple fire fighting based on computer vision
Li, Jinlong; Wang, Li; Gao, Xiaorong; Wang, Zeyong; Zhao, Quanke
2010-10-01
With the high demand of fire control in spacious buildings, computer vision is playing a more and more important role. This paper presents a new monitoring system of multiple fire fighting based on computer vision and color detection. This system can adjust to the fire position and then extinguish the fire by itself. In this paper, the system structure, working principle, fire orientation, hydrant's angle adjusting and system calibration are described in detail; also the design of relevant hardware and software is introduced. At the same time, the principle and process of color detection and image processing are given as well. The system runs well in the test, and it has high reliability, low cost, and easy nodeexpanding, which has a bright prospect of application and popularization.
The Multiple Intelligences Teaching Method and Mathematics ...
The Multiple Intelligences teaching approach has evolved and been embraced widely especially in the United States. The approach has been found to be very effective in changing situations for the better, in the teaching and learning of any subject especially mathematics. Multiple Intelligences teaching approach proposes ...
Neural Computations in a Dynamical System with Multiple Time Scales.
Mi, Yuanyuan; Lin, Xiaohan; Wu, Si
2016-01-01
Neural systems display rich short-term dynamics at various levels, e.g., spike-frequency adaptation (SFA) at the single-neuron level, and short-term facilitation (STF) and depression (STD) at the synapse level. These dynamical features typically cover a broad range of time scales and exhibit large diversity in different brain regions. It remains unclear what is the computational benefit for the brain to have such variability in short-term dynamics. In this study, we propose that the brain can exploit such dynamical features to implement multiple seemingly contradictory computations in a single neural circuit. To demonstrate this idea, we use continuous attractor neural network (CANN) as a working model and include STF, SFA and STD with increasing time constants in its dynamics. Three computational tasks are considered, which are persistent activity, adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, and hence cannot be implemented by a single dynamical feature or any combination with similar time constants. However, with properly coordinated STF, SFA and STD, we show that the network is able to implement the three computational tasks concurrently. We hope this study will shed light on the understanding of how the brain orchestrates its rich dynamics at various levels to realize diverse cognitive functions.
Computational techniques of the simplex method
Maros, István
2003-01-01
Computational Techniques of the Simplex Method is a systematic treatment focused on the computational issues of the simplex method. It provides a comprehensive coverage of the most important and successful algorithmic and implementation techniques of the simplex method. It is a unique source of essential, never discussed details of algorithmic elements and their implementation. On the basis of the book the reader will be able to create a highly advanced implementation of the simplex method which, in turn, can be used directly or as a building block in other solution algorithms.
Materials and nanosystems : interdisciplinary computational modeling at multiple scales
Huber, S.E.
2014-01-01
Over the last five decades, computer simulation and numerical modeling have become valuable tools complementing the traditional pillars of science, experiment and theory. In this thesis, several applications of computer-based simulation and modeling shall be explored in order to address problems and open issues in chemical and molecular physics. Attention shall be paid especially to the different degrees of interrelatedness and multiscale-flavor, which may - at least to some extent - be regarded as inherent properties of computational chemistry. In order to do so, a variety of computational methods are used to study features of molecular systems which are of relevance in various branches of science and which correspond to different spatial and/or temporal scales. Proceeding from small to large measures, first, an application in astrochemistry, the investigation of spectroscopic and energetic aspects of carbonic acid isomers shall be discussed. In this respect, very accurate and hence at the same time computationally very demanding electronic structure methods like the coupled-cluster approach are employed. These studies are followed by the discussion of an application in the scope of plasma-wall interaction which is related to nuclear fusion research. There, the interactions of atoms and molecules with graphite surfaces are explored using density functional theory methods. The latter are computationally cheaper than coupled-cluster methods and thus allow the treatment of larger molecular systems, but yield less accuracy and especially reduced error control at the same time. The subsequently presented exploration of surface defects at low-index polar zinc oxide surfaces, which are of interest in materials science and surface science, is another surface science application. The necessity to treat even larger systems of several hundreds of atoms requires the use of approximate density functional theory methods. Thin gold nanowires consisting of several thousands of
Numerical Methods for Stochastic Computations A Spectral Method Approach
Xiu, Dongbin
2010-01-01
The first graduate-level textbook to focus on fundamental aspects of numerical methods for stochastic computations, this book describes the class of numerical methods based on generalized polynomial chaos (gPC). These fast, efficient, and accurate methods are an extension of the classical spectral methods of high-dimensional random spaces. Designed to simulate complex systems subject to random inputs, these methods are widely used in many areas of computer science and engineering. The book introduces polynomial approximation theory and probability theory; describes the basic theory of gPC meth
Empirical evaluation methods in computer vision
Christensen, Henrik I
2002-01-01
This book provides comprehensive coverage of methods for the empirical evaluation of computer vision techniques. The practical use of computer vision requires empirical evaluation to ensure that the overall system has a guaranteed performance. The book contains articles that cover the design of experiments for evaluation, range image segmentation, the evaluation of face recognition and diffusion methods, image matching using correlation methods, and the performance of medical image processing algorithms. Sample Chapter(s). Foreword (228 KB). Chapter 1: Introduction (505 KB). Contents: Automate
A computational method for sharp interface advection
Roenby, Johan; Bredmose, Henrik; Jasak, Hrvoje
2016-01-01
We devise a numerical method for passive advection of a surface, such as the interface between two incompressible fluids, across a computational mesh. The method is called isoAdvector, and is developed for general meshes consisting of arbitrary polyhedral cells. The algorithm is based on the volu...
A new fault detection method for computer networks
Lu, Lu; Xu, Zhengguo; Wang, Wenhai; Sun, Youxian
2013-01-01
Over the past few years, fault detection for computer networks has attracted extensive attentions for its importance in network management. Most existing fault detection methods are based on active probing techniques which can detect the occurrence of faults fast and precisely. But these methods suffer from the limitation of traffic overhead, especially in large scale networks. To relieve traffic overhead induced by active probing based methods, a new fault detection method, whose key is to divide the detection process into multiple stages, is proposed in this paper. During each stage, only a small region of the network is detected by using a small set of probes. Meanwhile, it also ensures that the entire network can be covered after multiple detection stages. This method can guarantee that the traffic used by probes during each detection stage is small sufficiently so that the network can operate without severe disturbance from probes. Several simulation results verify the effectiveness of the proposed method
Computing discharge using the index velocity method
Levesque, Victor A.; Oberg, Kevin A.
2012-01-01
Application of the index velocity method for computing continuous records of discharge has become increasingly common, especially since the introduction of low-cost acoustic Doppler velocity meters (ADVMs) in 1997. Presently (2011), the index velocity method is being used to compute discharge records for approximately 470 gaging stations operated and maintained by the U.S. Geological Survey. The purpose of this report is to document and describe techniques for computing discharge records using the index velocity method. Computing discharge using the index velocity method differs from the traditional stage-discharge method by separating velocity and area into two ratings—the index velocity rating and the stage-area rating. The outputs from each of these ratings, mean channel velocity (V) and cross-sectional area (A), are then multiplied together to compute a discharge. For the index velocity method, V is a function of such parameters as streamwise velocity, stage, cross-stream velocity, and velocity head, and A is a function of stage and cross-section shape. The index velocity method can be used at locations where stage-discharge methods are used, but it is especially appropriate when more than one specific discharge can be measured for a specific stage. After the ADVM is selected, installed, and configured, the stage-area rating and the index velocity rating must be developed. A standard cross section is identified and surveyed in order to develop the stage-area rating. The standard cross section should be surveyed every year for the first 3 years of operation and thereafter at a lesser frequency, depending on the susceptibility of the cross section to change. Periodic measurements of discharge are used to calibrate and validate the index rating for the range of conditions experienced at the gaging station. Data from discharge measurements, ADVMs, and stage sensors are compiled for index-rating analysis. Index ratings are developed by means of regression
Computing and physical methods to calculate Pu
Mohamed, Ashraf Elsayed Mohamed
2013-01-01
Main limitations due to the enhancement of the plutonium content are related to the coolant void effect as the spectrum becomes faster, the neutron flux in the thermal region tends towards zero and is concentrated in the region from 10 Ke to 1 MeV. Thus, all captures by 240 Pu and 242 Pu in the thermal and epithermal resonance disappear and the 240 Pu and 242 Pu contributions to the void effect became positive. The higher the Pu content and the poorer the Pu quality, the larger the void effect. The core control in nominal or transient conditions Pu enrichment leads to a decrease in (B eff.), the efficiency of soluble boron and control rods. Also, the Doppler effect tends to decrease when Pu replaces U, so, that in case of transients the core could diverge again if the control is not effective enough. As for the voiding effect, the plutonium degradation and the 240 Pu and 242 Pu accumulation after multiple recycling lead to spectrum hardening and to a decrease in control. One solution would be to use enriched boron in soluble boron and shutdown rods. In this paper, I discuss and show the advanced computing and physical methods to calculate Pu inside the nuclear reactors and glovebox and the different solutions to be used to overcome the difficulties that effect, on safety parameters and on reactor performance, and analysis the consequences of plutonium management on the whole fuel cycle like Raw materials savings, fraction of nuclear electric power involved in the Pu management. All through two types of scenario, one involving a low fraction of the nuclear park dedicated to plutonium management, the other involving a dilution of the plutonium in all the nuclear park. (author)
Computational efficiency for the surface renewal method
Kelley, Jason; Higgins, Chad
2018-04-01
Measuring surface fluxes using the surface renewal (SR) method requires programmatic algorithms for tabulation, algebraic calculation, and data quality control. A number of different methods have been published describing automated calibration of SR parameters. Because the SR method utilizes high-frequency (10 Hz+) measurements, some steps in the flux calculation are computationally expensive, especially when automating SR to perform many iterations of these calculations. Several new algorithms were written that perform the required calculations more efficiently and rapidly, and that tested for sensitivity to length of flux averaging period, ability to measure over a large range of lag timescales, and overall computational efficiency. These algorithms utilize signal processing techniques and algebraic simplifications that demonstrate simple modifications that dramatically improve computational efficiency. The results here complement efforts by other authors to standardize a robust and accurate computational SR method. Increased speed of computation time grants flexibility to implementing the SR method, opening new avenues for SR to be used in research, for applied monitoring, and in novel field deployments.
Computational methods in molecular imaging technologies
Gunjan, Vinit Kumar; Venkatesh, C; Amarnath, M
2017-01-01
This book highlights the experimental investigations that have been carried out on magnetic resonance imaging and computed tomography (MRI & CT) images using state-of-the-art Computational Image processing techniques, and tabulates the statistical values wherever necessary. In a very simple and straightforward way, it explains how image processing methods are used to improve the quality of medical images and facilitate analysis. It offers a valuable resource for researchers, engineers, medical doctors and bioinformatics experts alike.
Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing
Fan Zhang
2016-04-01
Full Text Available With the development of synthetic aperture radar (SAR technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO. However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.
Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing.
Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin
2016-04-07
With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.
Digital image processing mathematical and computational methods
Blackledge, J M
2005-01-01
This authoritative text (the second part of a complete MSc course) provides mathematical methods required to describe images, image formation and different imaging systems, coupled with the principle techniques used for processing digital images. It is based on a course for postgraduates reading physics, electronic engineering, telecommunications engineering, information technology and computer science. This book relates the methods of processing and interpreting digital images to the 'physics' of imaging systems. Case studies reinforce the methods discussed, with examples of current research
Zonal methods and computational fluid dynamics
Atta, E.H.
1985-01-01
Recent advances in developing numerical algorithms for solving fluid flow problems, and the continuing improvement in the speed and storage of large scale computers have made it feasible to compute the flow field about complex and realistic configurations. Current solution methods involve the use of a hierarchy of mathematical models ranging from the linearized potential equation to the Navier Stokes equations. Because of the increasing complexity of both the geometries and flowfields encountered in practical fluid flow simulation, there is a growing emphasis in computational fluid dynamics on the use of zonal methods. A zonal method is one that subdivides the total flow region into interconnected smaller regions or zones. The flow solutions in these zones are then patched together to establish the global flow field solution. Zonal methods are primarily used either to limit the complexity of the governing flow equations to a localized region or to alleviate the grid generation problems about geometrically complex and multicomponent configurations. This paper surveys the application of zonal methods for solving the flow field about two and three-dimensional configurations. Various factors affecting their accuracy and ease of implementation are also discussed. From the presented review it is concluded that zonal methods promise to be very effective for computing complex flowfields and configurations. Currently there are increasing efforts to improve their efficiency, versatility, and accuracy
COMPUTER-IMPLEMENTED METHOD OF PERFORMING A SEARCH USING SIGNATURES
2017-01-01
A computer-implemented method of processing a query vector and a data vector), comprising: generating a set of masks and a first set of multiple signatures and a second set of multiple signatures by applying the set of masks to the query vector and the data vector, respectively, and generating...... candidate pairs, of a first signature and a second signature, by identifying matches of a first signature and a second signature. The set of masks comprises a configuration of the elements that is a Hadamard code; a permutation of a Hadamard code; or a code that deviates from a Hadamard code...
Basic thinking patterns and working methods for multiple DFX
Andreasen, Mogens Myrup; Mortensen, Niels Henrik
1997-01-01
This paper attempts to describe the theory and methodologies behind DFX and linking multiple DFX's together. The contribution is an articulation of basic thinking patterns and description of some working methods for handling multiple DFX.......This paper attempts to describe the theory and methodologies behind DFX and linking multiple DFX's together. The contribution is an articulation of basic thinking patterns and description of some working methods for handling multiple DFX....
Electron beam treatment planning: A review of dose computation methods
Mohan, R.; Riley, R.; Laughlin, J.S.
1983-01-01
Various methods of dose computations are reviewed. The equivalent path length methods used to account for body curvature and internal structure are not adequate because they ignore the lateral diffusion of electrons. The Monte Carlo method for the broad field three-dimensional situation in treatment planning is impractical because of the enormous computer time required. The pencil beam technique may represent a suitable compromise. The behavior of a pencil beam may be described by the multiple scattering theory or, alternatively, generated using the Monte Carlo method. Although nearly two orders of magnitude slower than the equivalent path length technique, the pencil beam method improves accuracy sufficiently to justify its use. It applies very well when accounting for the effect of surface irregularities; the formulation for handling inhomogeneous internal structure is yet to be developed
Domain decomposition methods and parallel computing
Meurant, G.
1991-01-01
In this paper, we show how to efficiently solve large linear systems on parallel computers. These linear systems arise from discretization of scientific computing problems described by systems of partial differential equations. We show how to get a discrete finite dimensional system from the continuous problem and the chosen conjugate gradient iterative algorithm is briefly described. Then, the different kinds of parallel architectures are reviewed and their advantages and deficiencies are emphasized. We sketch the problems found in programming the conjugate gradient method on parallel computers. For this algorithm to be efficient on parallel machines, domain decomposition techniques are introduced. We give results of numerical experiments showing that these techniques allow a good rate of convergence for the conjugate gradient algorithm as well as computational speeds in excess of a billion of floating point operations per second. (author). 5 refs., 11 figs., 2 tabs., 1 inset
Multiple single-element transducer photoacoustic computed tomography system
Kalva, Sandeep Kumar; Hui, Zhe Zhi; Pramanik, Manojit
2018-02-01
Light absorption by the chromophores (hemoglobin, melanin, water etc.) present in any biological tissue results in local temperature rise. This rise in temperature results in generation of pressure waves due to the thermoelastic expansion of the tissue. In a circular scanning photoacoustic computed tomography (PACT) system, these pressure waves can be detected using a single-element ultrasound transducer (SUST) (while rotating in full 360° around the sample) or using a circular array transducer. SUST takes several minutes to acquire the PA data around the sample whereas the circular array transducer takes only a fraction of seconds. Hence, for real time imaging circular array transducers are preferred. However, these circular array transducers are custom made, expensive and not easily available in the market whereas SUSTs are cheap and readily available in the market. Using SUST for PACT systems is still cost effective. In order to reduce the scanning time to few seconds instead of using single SUST (rotating 360° ), multiple SUSTs can be used at the same time to acquire the PA data. This will reduce the scanning time by two-fold in case of two SUSTs (rotating 180° ) or by four-fold and eight-fold in case of four SUSTs (rotating 90° ) and eight SUSTs (rotating 45° ) respectively. Here we show that with multiple SUSTs, similar PA images (numerical and experimental phantom data) can be obtained as that of PA images obtained using single SUST.
Neural Computations in a Dynamical System with Multiple Time Scales
Yuanyuan Mi
2016-09-01
Full Text Available Neural systems display rich short-term dynamics at various levels, e.g., spike-frequencyadaptation (SFA at single neurons, and short-term facilitation (STF and depression (STDat neuronal synapses. These dynamical features typically covers a broad range of time scalesand exhibit large diversity in different brain regions. It remains unclear what the computationalbenefit for the brain to have such variability in short-term dynamics is. In this study, we proposethat the brain can exploit such dynamical features to implement multiple seemingly contradictorycomputations in a single neural circuit. To demonstrate this idea, we use continuous attractorneural network (CANN as a working model and include STF, SFA and STD with increasing timeconstants in their dynamics. Three computational tasks are considered, which are persistent activity,adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, andhence cannot be implemented by a single dynamical feature or any combination with similar timeconstants. However, with properly coordinated STF, SFA and STD, we show that the network isable to implement the three computational tasks concurrently. We hope this study will shed lighton the understanding of how the brain orchestrates its rich dynamics at various levels to realizediverse cognitive functions.
Computational and instrumental methods in EPR
Bender, Christopher J
2006-01-01
Computational and Instrumental Methods in EPR Prof. Bender, Fordham University Prof. Lawrence J. Berliner, University of Denver Electron magnetic resonance has been greatly facilitated by the introduction of advances in instrumentation and better computational tools, such as the increasingly widespread use of the density matrix formalism. This volume is devoted to both instrumentation and computation aspects of EPR, while addressing applications such as spin relaxation time measurements, the measurement of hyperfine interaction parameters, and the recovery of Mn(II) spin Hamiltonian parameters via spectral simulation. Key features: Microwave Amplitude Modulation Technique to Measure Spin-Lattice (T1) and Spin-Spin (T2) Relaxation Times Improvement in the Measurement of Spin-Lattice Relaxation Time in Electron Paramagnetic Resonance Quantitative Measurement of Magnetic Hyperfine Parameters and the Physical Organic Chemistry of Supramolecular Systems New Methods of Simulation of Mn(II) EPR Spectra: Single Cryst...
Proceedings of computational methods in materials science
Mark, J.E. Glicksman, M.E.; Marsh, S.P.
1992-01-01
The Symposium on which this volume is based was conceived as a timely expression of some of the fast-paced developments occurring throughout materials science and engineering. It focuses particularly on those involving modern computational methods applied to model and predict the response of materials under a diverse range of physico-chemical conditions. The current easy access of many materials scientists in industry, government laboratories, and academe to high-performance computers has opened many new vistas for predicting the behavior of complex materials under realistic conditions. Some have even argued that modern computational methods in materials science and engineering are literally redefining the bounds of our knowledge from which we predict structure-property relationships, perhaps forever changing the historically descriptive character of the science and much of the engineering
Computational botany methods for automated species identification
Remagnino, Paolo; Wilkin, Paul; Cope, James; Kirkup, Don
2017-01-01
This book discusses innovative methods for mining information from images of plants, especially leaves, and highlights the diagnostic features that can be implemented in fully automatic systems for identifying plant species. Adopting a multidisciplinary approach, it explores the problem of plant species identification, covering both the concepts of taxonomy and morphology. It then provides an overview of morphometrics, including the historical background and the main steps in the morphometric analysis of leaves together with a number of applications. The core of the book focuses on novel diagnostic methods for plant species identification developed from a computer scientist’s perspective. It then concludes with a chapter on the characterization of botanists' visions, which highlights important cognitive aspects that can be implemented in a computer system to more accurately replicate the human expert’s fixation process. The book not only represents an authoritative guide to advanced computational tools fo...
Computer-Aided Modelling Methods and Tools
Cameron, Ian; Gani, Rafiqul
2011-01-01
The development of models for a range of applications requires methods and tools. In many cases a reference model is required that allows the generation of application specific models that are fit for purpose. There are a range of computer aided modelling tools available that help to define the m...
Applying Human Computation Methods to Information Science
Harris, Christopher Glenn
2013-01-01
Human Computation methods such as crowdsourcing and games with a purpose (GWAP) have each recently drawn considerable attention for their ability to synergize the strengths of people and technology to accomplish tasks that are challenging for either to do well alone. Despite this increased attention, much of this transformation has been focused on…
The asymptotic expansion method via symbolic computation
Navarro, Juan F.
2012-01-01
This paper describes an algorithm for implementing a perturbation method based on an asymptotic expansion of the solution to a second-order differential equation. We also introduce a new symbolic computation system which works with the so-called modified quasipolynomials, as well as an implementation of the algorithm on it.
The Asymptotic Expansion Method via Symbolic Computation
Juan F. Navarro
2012-01-01
Full Text Available This paper describes an algorithm for implementing a perturbation method based on an asymptotic expansion of the solution to a second-order differential equation. We also introduce a new symbolic computation system which works with the so-called modified quasipolynomials, as well as an implementation of the algorithm on it.
Computationally efficient methods for digital control
Guerreiro Tome Antunes, D.J.; Hespanha, J.P.; Silvestre, C.J.; Kataria, N.; Brewer, F.
2008-01-01
The problem of designing a digital controller is considered with the novelty of explicitly taking into account the computation cost of the controller implementation. A class of controller emulation methods inspired by numerical analysis is proposed. Through various examples it is shown that these
Erlangga, Mokhammad Puput [Geophysical Engineering, Institut Teknologi Bandung, Ganesha Street no.10 Basic Science B Buliding fl.2-3 Bandung, 40132, West Java Indonesia puput.erlangga@gmail.com (Indonesia)
2015-04-16
Separation between signal and noise, incoherent or coherent, is important in seismic data processing. Although we have processed the seismic data, the coherent noise is still mixing with the primary signal. Multiple reflections are a kind of coherent noise. In this research, we processed seismic data to attenuate multiple reflections in the both synthetic and real seismic data of Mentawai. There are several methods to attenuate multiple reflection, one of them is Radon filter method that discriminates between primary reflection and multiple reflection in the τ-p domain based on move out difference between primary reflection and multiple reflection. However, in case where the move out difference is too small, the Radon filter method is not enough to attenuate the multiple reflections. The Radon filter also produces the artifacts on the gathers data. Except the Radon filter method, we also use the Wave Equation Multiple Elimination (WEMR) method to attenuate the long period multiple reflection. The WEMR method can attenuate the long period multiple reflection based on wave equation inversion. Refer to the inversion of wave equation and the magnitude of the seismic wave amplitude that observed on the free surface, we get the water bottom reflectivity which is used to eliminate the multiple reflections. The WEMR method does not depend on the move out difference to attenuate the long period multiple reflection. Therefore, the WEMR method can be applied to the seismic data which has small move out difference as the Mentawai seismic data. The small move out difference on the Mentawai seismic data is caused by the restrictiveness of far offset, which is only 705 meter. We compared the real free multiple stacking data after processing with Radon filter and WEMR process. The conclusion is the WEMR method can more attenuate the long period multiple reflection than the Radon filter method on the real (Mentawai) seismic data.
On multiple level-set regularization methods for inverse problems
DeCezaro, A; Leitão, A; Tai, X-C
2009-01-01
We analyze a multiple level-set method for solving inverse problems with piecewise constant solutions. This method corresponds to an iterated Tikhonov method for a particular Tikhonov functional G α based on TV–H 1 penalization. We define generalized minimizers for our Tikhonov functional and establish an existence result. Moreover, we prove convergence and stability results of the proposed Tikhonov method. A multiple level-set algorithm is derived from the first-order optimality conditions for the Tikhonov functional G α , similarly as the iterated Tikhonov method. The proposed multiple level-set method is tested on an inverse potential problem. Numerical experiments show that the method is able to recover multiple objects as well as multiple contrast levels
Advances of evolutionary computation methods and operators
Cuevas, Erik; Oliva Navarro, Diego Alberto
2016-01-01
The goal of this book is to present advances that discuss alternative Evolutionary Computation (EC) developments and non-conventional operators which have proved to be eﬀective in the solution of several complex problems. The book has been structured so that each chapter can be read independently from the others. The book contains nine chapters with the following themes: 1) Introduction, 2) the Social Spider Optimization (SSO), 3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB) algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search (LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE) method, 8) the multimodal CAB, 9) the constrained SSO method.
Computational Methods in Stochastic Dynamics Volume 2
Stefanou, George; Papadopoulos, Vissarion
2013-01-01
The considerable influence of inherent uncertainties on structural behavior has led the engineering community to recognize the importance of a stochastic approach to structural problems. Issues related to uncertainty quantification and its influence on the reliability of the computational models are continuously gaining in significance. In particular, the problems of dynamic response analysis and reliability assessment of structures with uncertain system and excitation parameters have been the subject of continuous research over the last two decades as a result of the increasing availability of powerful computing resources and technology. This book is a follow up of a previous book with the same subject (ISBN 978-90-481-9986-0) and focuses on advanced computational methods and software tools which can highly assist in tackling complex problems in stochastic dynamic/seismic analysis and design of structures. The selected chapters are authored by some of the most active scholars in their respective areas and...
Multiple network interface core apparatus and method
Underwood, Keith D [Albuquerque, NM; Hemmert, Karl Scott [Albuquerque, NM
2011-04-26
A network interface controller and network interface control method comprising providing a single integrated circuit as a network interface controller and employing a plurality of network interface cores on the single integrated circuit.
Multiple tag labeling method for DNA sequencing
Mathies, R.A.; Huang, X.C.; Quesada, M.A.
1995-07-25
A DNA sequencing method is described which uses single lane or channel electrophoresis. Sequencing fragments are separated in the lane and detected using a laser-excited, confocal fluorescence scanner. Each set of DNA sequencing fragments is separated in the same lane and then distinguished using a binary coding scheme employing only two different fluorescent labels. Also described is a method of using radioisotope labels. 5 figs.
Multiple time scale methods in tokamak magnetohydrodynamics
Jardin, S.C.
1984-01-01
Several methods are discussed for integrating the magnetohydrodynamic (MHD) equations in tokamak systems on other than the fastest time scale. The dynamical grid method for simulating ideal MHD instabilities utilizes a natural nonorthogonal time-dependent coordinate transformation based on the magnetic field lines. The coordinate transformation is chosen to be free of the fast time scale motion itself, and to yield a relatively simple scalar equation for the total pressure, P = p + B 2 /2μ 0 , which can be integrated implicitly to average over the fast time scale oscillations. Two methods are described for the resistive time scale. The zero-mass method uses a reduced set of two-fluid transport equations obtained by expanding in the inverse magnetic Reynolds number, and in the small ratio of perpendicular to parallel mobilities and thermal conductivities. The momentum equation becomes a constraint equation that forces the pressure and magnetic fields and currents to remain in force balance equilibrium as they evolve. The large mass method artificially scales up the ion mass and viscosity, thereby reducing the severe time scale disparity between wavelike and diffusionlike phenomena, but not changing the resistive time scale behavior. Other methods addressing the intermediate time scales are discussed
Distributed Factorization Computation on Multiple Volunteered Mobile Resource to Break RSA Key
Jaya, I.; Hardi, S. M.; Tarigan, J. T.; Zamzami, E. M.; Sihombing, P.
2017-01-01
Similar to common asymmeric encryption, RSA can be cracked by usmg a series mathematical calculation. The private key used to decrypt the massage can be computed using the public key. However, finding the private key may require a massive amount of calculation. In this paper, we propose a method to perform a distributed computing to calculate RSA’s private key. The proposed method uses multiple volunteered mobile devices to contribute during the calculation process. Our objective is to demonstrate how the use of volunteered computing on mobile devices may be a feasible option to reduce the time required to break a weak RSA encryption and observe the behavior and running time of the application on mobile devices.
Computational methods for industrial radiation measurement applications
Gardner, R.P.; Guo, P.; Ao, Q.
1996-01-01
Computational methods have been used with considerable success to complement radiation measurements in solving a wide range of industrial problems. The almost exponential growth of computer capability and applications in the last few years leads to a open-quotes black boxclose quotes mentality for radiation measurement applications. If a black box is defined as any radiation measurement device that is capable of measuring the parameters of interest when a wide range of operating and sample conditions may occur, then the development of computational methods for industrial radiation measurement applications should now be focused on the black box approach and the deduction of properties of interest from the response with acceptable accuracy and reasonable efficiency. Nowadays, increasingly better understanding of radiation physical processes, more accurate and complete fundamental physical data, and more advanced modeling and software/hardware techniques have made it possible to make giant strides in that direction with new ideas implemented with computer software. The Center for Engineering Applications of Radioisotopes (CEAR) at North Carolina State University has been working on a variety of projects in the area of radiation analyzers and gauges for accomplishing this for quite some time, and they are discussed here with emphasis on current accomplishments
Solution of Constrained Optimal Control Problems Using Multiple Shooting and ESDIRK Methods
Capolei, Andrea; Jørgensen, John Bagterp
2012-01-01
of this paper is the use of ESDIRK integration methods for solution of the initial value problems and the corresponding sensitivity equations arising in the multiple shooting algorithm. Compared to BDF-methods, ESDIRK-methods are advantageous in multiple shooting algorithms in which restarts and frequent...... algorithm. As we consider stiff systems, implicit solvers with sensitivity computation capabilities for initial value problems must be used in the multiple shooting algorithm. Traditionally, multi-step methods based on the BDF algorithm have been used for such problems. The main novel contribution...... discontinuities on each shooting interval are present. The ESDIRK methods are implemented using an inexact Newton method that reuses the factorization of the iteration matrix for the integration as well as the sensitivity computation. Numerical experiments are provided to demonstrate the algorithm....
BLUES function method in computational physics
Indekeu, Joseph O.; Müller-Nedebock, Kristian K.
2018-04-01
We introduce a computational method in physics that goes ‘beyond linear use of equation superposition’ (BLUES). A BLUES function is defined as a solution of a nonlinear differential equation (DE) with a delta source that is at the same time a Green’s function for a related linear DE. For an arbitrary source, the BLUES function can be used to construct an exact solution to the nonlinear DE with a different, but related source. Alternatively, the BLUES function can be used to construct an approximate piecewise analytical solution to the nonlinear DE with an arbitrary source. For this alternative use the related linear DE need not be known. The method is illustrated in a few examples using analytical calculations and numerical computations. Areas for further applications are suggested.
Spatial analysis statistics, visualization, and computational methods
Oyana, Tonny J
2015-01-01
An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present practical applications of geospatial data tools, techniques, and strategies in geographic studies. They offer a problem-based learning (PBL) approach to spatial analysis-containing hands-on problem-sets that can be worked out in MS Excel or ArcGIS-as well as detailed illustrations and numerous case studies. The book enables readers to: Identify types and characterize non-spatial and spatial data Demonstrate their competence to explore, visualize, summarize, analyze, optimize, and clearly present statistical data and results Construct testable hypotheses that require inferential statistical analysis Process spatial data, extract explanatory variables, conduct statisti...
Computer Animation Based on Particle Methods
Rafal Wcislo
1999-01-01
Full Text Available The paper presents the main issues of a computer animation of a set of elastic macroscopic objects based on the particle method. The main assumption of the generated animations is to achieve very realistic movements in a scene observed on the computer display. The objects (solid bodies interact mechanically with each other, The movements and deformations of solids are calculated using the particle method. Phenomena connected with the behaviour of solids in the gravitational field, their defomtations caused by collisions and interactions with the optional liquid medium are simulated. The simulation ofthe liquid is performed using the cellular automata method. The paper presents both simulation schemes (particle method and cellular automata rules an the method of combining them in the single animation program. ln order to speed up the execution of the program the parallel version based on the network of workstation was developed. The paper describes the methods of the parallelization and it considers problems of load-balancing, collision detection, process synchronization and distributed control of the animation.
Computational methods of electron/photon transport
Mack, J.M.
1983-01-01
A review of computational methods simulating the non-plasma transport of electrons and their attendant cascades is presented. Remarks are mainly restricted to linearized formalisms at electron energies above 1 keV. The effectiveness of various metods is discussed including moments, point-kernel, invariant imbedding, discrete-ordinates, and Monte Carlo. Future research directions and the potential impact on various aspects of science and engineering are indicated
Hossein Karimi
2011-04-01
Full Text Available The permutation method of multiple attribute decision making has two significant deficiencies: high computational time and wrong priority output in some problem instances. In this paper, a novel permutation method called adjusted permutation method (APM is proposed to compensate deficiencies of conventional permutation method. We propose Tabu search (TS and particle swarm optimization (PSO to find suitable solutions at a reasonable computational time for large problem instances. The proposed method is examined using some numerical examples to evaluate the performance of the proposed method. The preliminary results show that both approaches provide competent solutions in relatively reasonable amounts of time while TS performs better to solve APM.
Calculation of U, Ra, Th and K contents in uranium ore by multiple linear regression method
Lin Chao; Chen Yingqiang; Zhang Qingwen; Tan Fuwen; Peng Guanghui
1991-01-01
A multiple linear regression method was used to compute γ spectra of uranium ore samples and to calculate contents of U, Ra, Th, and K. In comparison with the inverse matrix method, its advantage is that no standard samples of pure U, Ra, Th and K are needed for obtaining response coefficients
A method for the generation of random multiple Coulomb scattering angles
Campbell, J.R.
1995-06-01
A method for the random generation of spatial angles drawn from non-Gaussian multiple Coulomb scattering distributions is presented. The method employs direct numerical inversion of cumulative probability distributions computed from the universal non-Gaussian angular distributions of Marion and Zimmerman. (author). 12 refs., 3 figs
Mathematical optics classical, quantum, and computational methods
Lakshminarayanan, Vasudevan
2012-01-01
Going beyond standard introductory texts, Mathematical Optics: Classical, Quantum, and Computational Methods brings together many new mathematical techniques from optical science and engineering research. Profusely illustrated, the book makes the material accessible to students and newcomers to the field. Divided into six parts, the text presents state-of-the-art mathematical methods and applications in classical optics, quantum optics, and image processing. Part I describes the use of phase space concepts to characterize optical beams and the application of dynamic programming in optical wave
Efficient computation of the joint sample frequency spectra for multiple populations.
Kamm, John A; Terhorst, Jonathan; Song, Yun S
2017-01-01
A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity.
Delamination detection using methods of computational intelligence
Ihesiulor, Obinna K.; Shankar, Krishna; Zhang, Zhifang; Ray, Tapabrata
2012-11-01
Abstract Reliable delamination prediction scheme is indispensable in order to prevent potential risks of catastrophic failures in composite structures. The existence of delaminations changes the vibration characteristics of composite laminates and hence such indicators can be used to quantify the health characteristics of laminates. An approach for online health monitoring of in-service composite laminates is presented in this paper that relies on methods based on computational intelligence. Typical changes in the observed vibration characteristics (i.e. change in natural frequencies) are considered as inputs to identify the existence, location and magnitude of delaminations. The performance of the proposed approach is demonstrated using numerical models of composite laminates. Since this identification problem essentially involves the solution of an optimization problem, the use of finite element (FE) methods as the underlying tool for analysis turns out to be computationally expensive. A surrogate assisted optimization approach is hence introduced to contain the computational time within affordable limits. An artificial neural network (ANN) model with Bayesian regularization is used as the underlying approximation scheme while an improved rate of convergence is achieved using a memetic algorithm. However, building of ANN surrogate models usually requires large training datasets. K-means clustering is effectively employed to reduce the size of datasets. ANN is also used via inverse modeling to determine the position, size and location of delaminations using changes in measured natural frequencies. The results clearly highlight the efficiency and the robustness of the approach.
Method of generating a computer readable model
2008-01-01
A method of generating a computer readable model of a geometrical object constructed from a plurality of interconnectable construction elements, wherein each construction element has a number of connection elements for connecting the construction element with another construction element. The met......A method of generating a computer readable model of a geometrical object constructed from a plurality of interconnectable construction elements, wherein each construction element has a number of connection elements for connecting the construction element with another construction element....... The method comprises encoding a first and a second one of the construction elements as corresponding data structures, each representing the connection elements of the corresponding construction element, and each of the connection elements having associated with it a predetermined connection type. The method...... further comprises determining a first connection element of the first construction element and a second connection element of the second construction element located in a predetermined proximity of each other; and retrieving connectivity information of the corresponding connection types of the first...
Fuzzy multiple attribute decision making methods and applications
Chen, Shu-Jen
1992-01-01
This monograph is intended for an advanced undergraduate or graduate course as well as for researchers, who want a compilation of developments in this rapidly growing field of operations research. This is a sequel to our previous works: "Multiple Objective Decision Making--Methods and Applications: A state-of-the-Art Survey" (No.164 of the Lecture Notes); "Multiple Attribute Decision Making--Methods and Applications: A State-of-the-Art Survey" (No.186 of the Lecture Notes); and "Group Decision Making under Multiple Criteria--Methods and Applications" (No.281 of the Lecture Notes). In this monograph, the literature on methods of fuzzy Multiple Attribute Decision Making (MADM) has been reviewed thoroughly and critically, and classified systematically. This study provides readers with a capsule look into the existing methods, their characteristics, and applicability to the analysis of fuzzy MADM problems. The basic concepts and algorithms from the classical MADM methods have been used in the development of the f...
Efficient computation method of Jacobian matrix
Sasaki, Shinobu
1995-05-01
As well known, the elements of the Jacobian matrix are complex trigonometric functions of the joint angles, resulting in a matrix of staggering complexity when we write it all out in one place. This article addresses that difficulties to this subject are overcome by using velocity representation. The main point is that its recursive algorithm and computer algebra technologies allow us to derive analytical formulation with no human intervention. Particularly, it is to be noted that as compared to previous results the elements are extremely simplified throughout the effective use of frame transformations. Furthermore, in case of a spherical wrist, it is shown that the present approach is computationally most efficient. Due to such advantages, the proposed method is useful in studying kinematically peculiar properties such as singularity problems. (author)
Computational method for free surface hydrodynamics
Hirt, C.W.; Nichols, B.D.
1980-01-01
There are numerous flow phenomena in pressure vessel and piping systems that involve the dynamics of free fluid surfaces. For example, fluid interfaces must be considered during the draining or filling of tanks, in the formation and collapse of vapor bubbles, and in seismically shaken vessels that are partially filled. To aid in the analysis of these types of flow phenomena, a new technique has been developed for the computation of complicated free-surface motions. This technique is based on the concept of a local average volume of fluid (VOF) and is embodied in a computer program for two-dimensional, transient fluid flow called SOLA-VOF. The basic approach used in the VOF technique is briefly described, and compared to other free-surface methods. Specific capabilities of the SOLA-VOF program are illustrated by generic examples of bubble growth and collapse, flows of immiscible fluid mixtures, and the confinement of spilled liquids
Soft Computing Methods for Disulfide Connectivity Prediction.
Márquez-Chamorro, Alfonso E; Aguilar-Ruiz, Jesús S
2015-01-01
The problem of protein structure prediction (PSP) is one of the main challenges in structural bioinformatics. To tackle this problem, PSP can be divided into several subproblems. One of these subproblems is the prediction of disulfide bonds. The disulfide connectivity prediction problem consists in identifying which nonadjacent cysteines would be cross-linked from all possible candidates. Determining the disulfide bond connectivity between the cysteines of a protein is desirable as a previous step of the 3D PSP, as the protein conformational search space is highly reduced. The most representative soft computing approaches for the disulfide bonds connectivity prediction problem of the last decade are summarized in this paper. Certain aspects, such as the different methodologies based on soft computing approaches (artificial neural network or support vector machine) or features of the algorithms, are used for the classification of these methods.
Interval sampling methods and measurement error: a computer simulation.
Wirth, Oliver; Slaven, James; Taylor, Matthew A
2014-01-01
A simulation study was conducted to provide a more thorough account of measurement error associated with interval sampling methods. A computer program simulated the application of momentary time sampling, partial-interval recording, and whole-interval recording methods on target events randomly distributed across an observation period. The simulation yielded measures of error for multiple combinations of observation period, interval duration, event duration, and cumulative event duration. The simulations were conducted up to 100 times to yield measures of error variability. Although the present simulation confirmed some previously reported characteristics of interval sampling methods, it also revealed many new findings that pertain to each method's inherent strengths and weaknesses. The analysis and resulting error tables can help guide the selection of the most appropriate sampling method for observation-based behavioral assessments. © Society for the Experimental Analysis of Behavior.
A computational procedure for finding multiple solutions of convective heat transfer equations
Mishra, S; DebRoy, T
2005-01-01
In recent years numerical solutions of the convective heat transfer equations have provided significant insight into the complex materials processing operations. However, these computational methods suffer from two major shortcomings. First, these procedures are designed to calculate temperature fields and cooling rates as output and the unidirectional structure of these solutions preclude specification of these variables as input even when their desired values are known. Second, and more important, these procedures cannot determine multiple pathways or multiple sets of input variables to achieve a particular output from the convective heat transfer equations. Here we propose a new method that overcomes the aforementioned shortcomings of the commonly used solutions of the convective heat transfer equations. The procedure combines the conventional numerical solution methods with a real number based genetic algorithm (GA) to achieve bi-directionality, i.e. the ability to calculate the required input variables to achieve a specific output such as temperature field or cooling rate. More important, the ability of the GA to find a population of solutions enables this procedure to search for and find multiple sets of input variables, all of which can lead to the desired specific output. The proposed computational procedure has been applied to convective heat transfer in a liquid layer locally heated on its free surface by an electric arc, where various sets of input variables are computed to achieve a specific fusion zone geometry defined by an equilibrium temperature. Good agreement is achieved between the model predictions and the independent experimental results, indicating significant promise for the application of this procedure in finding multiple solutions of convective heat transfer equations
Optimization of Inventories for Multiple Companies by Fuzzy Control Method
Kawase, Koichi; Konishi, Masami; Imai, Jun
2008-01-01
In this research, Fuzzy control theory is applied to the inventory control of the supply chain between multiple companies. The proposed control method deals with the amountof inventories expressing supply chain between multiple companies. Referring past demand and tardiness, inventory amounts of raw materials are determined by Fuzzy inference. The method that an appropriate inventory control becomes possible optimizing fuzzy control gain by using SA method for Fuzzy control. The variation of ...
Computational methods for nuclear criticality safety analysis
Maragni, M.G.
1992-01-01
Nuclear criticality safety analyses require the utilization of methods which have been tested and verified against benchmarks results. In this work, criticality calculations based on the KENO-IV and MCNP codes are studied aiming the qualification of these methods at the IPEN-CNEN/SP and COPESP. The utilization of variance reduction techniques is important to reduce the computer execution time, and several of them are analysed. As practical example of the above methods, a criticality safety analysis for the storage tubes for irradiated fuel elements from the IEA-R1 research has been carried out. This analysis showed that the MCNP code is more adequate for problems with complex geometries, and the KENO-IV code shows conservative results when it is not used the generalized geometry option. (author)
Evolutionary Computing Methods for Spectral Retrieval
Terrile, Richard; Fink, Wolfgang; Huntsberger, Terrance; Lee, Seugwon; Tisdale, Edwin; VonAllmen, Paul; Tinetti, Geivanna
2009-01-01
A methodology for processing spectral images to retrieve information on underlying physical, chemical, and/or biological phenomena is based on evolutionary and related computational methods implemented in software. In a typical case, the solution (the information that one seeks to retrieve) consists of parameters of a mathematical model that represents one or more of the phenomena of interest. The methodology was developed for the initial purpose of retrieving the desired information from spectral image data acquired by remote-sensing instruments aimed at planets (including the Earth). Examples of information desired in such applications include trace gas concentrations, temperature profiles, surface types, day/night fractions, cloud/aerosol fractions, seasons, and viewing angles. The methodology is also potentially useful for retrieving information on chemical and/or biological hazards in terrestrial settings. In this methodology, one utilizes an iterative process that minimizes a fitness function indicative of the degree of dissimilarity between observed and synthetic spectral and angular data. The evolutionary computing methods that lie at the heart of this process yield a population of solutions (sets of the desired parameters) within an accuracy represented by a fitness-function value specified by the user. The evolutionary computing methods (ECM) used in this methodology are Genetic Algorithms and Simulated Annealing, both of which are well-established optimization techniques and have also been described in previous NASA Tech Briefs articles. These are embedded in a conceptual framework, represented in the architecture of the implementing software, that enables automatic retrieval of spectral and angular data and analysis of the retrieved solutions for uniqueness.
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.
Study of the multiple scattering effect in TEBENE using the Monte Carlo method
Singkarat, Somsorn.
1990-01-01
The neutron time-of-flight and energy spectra, from the TEBENE set-up, have been calculated by a computer program using the Monte Carlo method. The neutron multiple scattering within the polyethylene scatterer ring is closely investigated. The results show that multiple scattering has a significant effect on the detected neutron yield. They also indicate that the thickness of the scatterer ring has to be carefully chosen. (author)
Ratschek, H
2003-01-01
This undergraduate and postgraduate text will familiarise readers with interval arithmetic and related tools to gain reliable and validated results and logically correct decisions for a variety of geometric computations plus the means for alleviating the effects of the errors. It also considers computations on geometric point-sets, which are neither robust nor reliable in processing with standard methods. The authors provide two effective tools for obtaining correct results: (a) interval arithmetic, and (b) ESSA the new powerful algorithm which improves many geometric computations and makes th
A multiple regression method for genomewide association studies ...
Bujun Mei
2018-06-07
Jun 7, 2018 ... Similar to the typical genomewide association tests using LD ... new approach performed validly when the multiple regression based on linkage method was employed. .... the model, two groups of scenarios were simulated.
The multiple imputation method: a case study involving secondary data analysis.
Walani, Salimah R; Cleland, Charles M
2015-05-01
To illustrate with the example of a secondary data analysis study the use of the multiple imputation method to replace missing data. Most large public datasets have missing data, which need to be handled by researchers conducting secondary data analysis studies. Multiple imputation is a technique widely used to replace missing values while preserving the sample size and sampling variability of the data. The 2004 National Sample Survey of Registered Nurses. The authors created a model to impute missing values using the chained equation method. They used imputation diagnostics procedures and conducted regression analysis of imputed data to determine the differences between the log hourly wages of internationally educated and US-educated registered nurses. The authors used multiple imputation procedures to replace missing values in a large dataset with 29,059 observations. Five multiple imputed datasets were created. Imputation diagnostics using time series and density plots showed that imputation was successful. The authors also present an example of the use of multiple imputed datasets to conduct regression analysis to answer a substantive research question. Multiple imputation is a powerful technique for imputing missing values in large datasets while preserving the sample size and variance of the data. Even though the chained equation method involves complex statistical computations, recent innovations in software and computation have made it possible for researchers to conduct this technique on large datasets. The authors recommend nurse researchers use multiple imputation methods for handling missing data to improve the statistical power and external validity of their studies.
Wang, Shijun; McKenna, Matthew T; Nguyen, Tan B; Burns, Joseph E; Petrick, Nicholas; Sahiner, Berkman; Summers, Ronald M
2012-05-01
In this paper, we present development and testing results for a novel colonic polyp classification method for use as part of a computed tomographic colonography (CTC) computer-aided detection (CAD) system. Inspired by the interpretative methodology of radiologists using 3-D fly-through mode in CTC reading, we have developed an algorithm which utilizes sequences of images (referred to here as videos) for classification of CAD marks. For each CAD mark, we created a video composed of a series of intraluminal, volume-rendered images visualizing the detection from multiple viewpoints. We then framed the video classification question as a multiple-instance learning (MIL) problem. Since a positive (negative) bag may contain negative (positive) instances, which in our case depends on the viewing angles and camera distance to the target, we developed a novel MIL paradigm to accommodate this class of problems. We solved the new MIL problem by maximizing a L2-norm soft margin using semidefinite programming, which can optimize relevant parameters automatically. We tested our method by analyzing a CTC data set obtained from 50 patients from three medical centers. Our proposed method showed significantly better performance compared with several traditional MIL methods.
Multiple independent identification decisions: a method of calibrating eyewitness identifications.
Pryke, Sean; Lindsay, R C L; Dysart, Jennifer E; Dupuis, Paul
2004-02-01
Two experiments (N = 147 and N = 90) explored the use of multiple independent lineups to identify a target seen live. In Experiment 1, simultaneous face, body, and sequential voice lineups were used. In Experiment 2, sequential face, body, voice, and clothing lineups were used. Both studies demonstrated that multiple identifications (by the same witness) from independent lineups of different features are highly diagnostic of suspect guilt (G. L. Wells & R. C. L. Lindsay, 1980). The number of suspect and foil selections from multiple independent lineups provides a powerful method of calibrating the accuracy of eyewitness identification. Implications for use of current methods are discussed. ((c) 2004 APA, all rights reserved)
Design and Delivery of Multiple Server-Side Computer Languages Course
Wang, Shouhong; Wang, Hai
2011-01-01
Given the emergence of service-oriented architecture, IS students need to be knowledgeable of multiple server-side computer programming languages to be able to meet the needs of the job market. This paper outlines the pedagogy of an innovative course of multiple server-side computer languages for the undergraduate IS majors. The paper discusses…
A computational method for sharp interface advection
Bredmose, Henrik; Jasak, Hrvoje
2016-01-01
We devise a numerical method for passive advection of a surface, such as the interface between two incompressible fluids, across a computational mesh. The method is called isoAdvector, and is developed for general meshes consisting of arbitrary polyhedral cells. The algorithm is based on the volume of fluid (VOF) idea of calculating the volume of one of the fluids transported across the mesh faces during a time step. The novelty of the isoAdvector concept consists of two parts. First, we exploit an isosurface concept for modelling the interface inside cells in a geometric surface reconstruction step. Second, from the reconstructed surface, we model the motion of the face–interface intersection line for a general polygonal face to obtain the time evolution within a time step of the submerged face area. Integrating this submerged area over the time step leads to an accurate estimate for the total volume of fluid transported across the face. The method was tested on simple two-dimensional and three-dimensional interface advection problems on both structured and unstructured meshes. The results are very satisfactory in terms of volume conservation, boundedness, surface sharpness and efficiency. The isoAdvector method was implemented as an OpenFOAM® extension and is published as open source. PMID:28018619
A computational method for sharp interface advection.
Roenby, Johan; Bredmose, Henrik; Jasak, Hrvoje
2016-11-01
We devise a numerical method for passive advection of a surface, such as the interface between two incompressible fluids, across a computational mesh. The method is called isoAdvector, and is developed for general meshes consisting of arbitrary polyhedral cells. The algorithm is based on the volume of fluid (VOF) idea of calculating the volume of one of the fluids transported across the mesh faces during a time step. The novelty of the isoAdvector concept consists of two parts. First, we exploit an isosurface concept for modelling the interface inside cells in a geometric surface reconstruction step. Second, from the reconstructed surface, we model the motion of the face-interface intersection line for a general polygonal face to obtain the time evolution within a time step of the submerged face area. Integrating this submerged area over the time step leads to an accurate estimate for the total volume of fluid transported across the face. The method was tested on simple two-dimensional and three-dimensional interface advection problems on both structured and unstructured meshes. The results are very satisfactory in terms of volume conservation, boundedness, surface sharpness and efficiency. The isoAdvector method was implemented as an OpenFOAM ® extension and is published as open source.
Curvelet-domain multiple matching method combined with cubic B-spline function
Wang, Tong; Wang, Deli; Tian, Mi; Hu, Bin; Liu, Chengming
2018-05-01
Since the large amount of surface-related multiple existed in the marine data would influence the results of data processing and interpretation seriously, many researchers had attempted to develop effective methods to remove them. The most successful surface-related multiple elimination method was proposed based on data-driven theory. However, the elimination effect was unsatisfactory due to the existence of amplitude and phase errors. Although the subsequent curvelet-domain multiple-primary separation method achieved better results, poor computational efficiency prevented its application. In this paper, we adopt the cubic B-spline function to improve the traditional curvelet multiple matching method. First, select a little number of unknowns as the basis points of the matching coefficient; second, apply the cubic B-spline function on these basis points to reconstruct the matching array; third, build constraint solving equation based on the relationships of predicted multiple, matching coefficients, and actual data; finally, use the BFGS algorithm to iterate and realize the fast-solving sparse constraint of multiple matching algorithm. Moreover, the soft-threshold method is used to make the method perform better. With the cubic B-spline function, the differences between predicted multiple and original data diminish, which results in less processing time to obtain optimal solutions and fewer iterative loops in the solving procedure based on the L1 norm constraint. The applications to synthetic and field-derived data both validate the practicability and validity of the method.
Muhammad, Akram; Musavarah, Sarwar
2016-01-01
In this research study, we introduce the concept of bipolar neutrosophic graphs. We present the dominating and independent sets of bipolar neutrosophic graphs. We describe novel multiple criteria decision making methods based on bipolar neutrosophic sets and bipolar neutrosophic graphs. We also develop an algorithm for computing domination in bipolar neutrosophic graphs.
Non-Abelian Kubo formula and the multiple time-scale method
Zhang, X.; Li, J.
1996-01-01
The non-Abelian Kubo formula is derived from the kinetic theory. That expression is compared with the one obtained using the eikonal for a Chern endash Simons theory. The multiple time-scale method is used to study the non-Abelian Kubo formula, and the damping rate for longitudinal color waves is computed. copyright 1996 Academic Press, Inc
Computational electromagnetic methods for transcranial magnetic stimulation
Gomez, Luis J.
Transcranial magnetic stimulation (TMS) is a noninvasive technique used both as a research tool for cognitive neuroscience and as a FDA approved treatment for depression. During TMS, coils positioned near the scalp generate electric fields and activate targeted brain regions. In this thesis, several computational electromagnetics methods that improve the analysis, design, and uncertainty quantification of TMS systems were developed. Analysis: A new fast direct technique for solving the large and sparse linear system of equations (LSEs) arising from the finite difference (FD) discretization of Maxwell's quasi-static equations was developed. Following a factorization step, the solver permits computation of TMS fields inside realistic brain models in seconds, allowing for patient-specific real-time usage during TMS. The solver is an alternative to iterative methods for solving FD LSEs, often requiring run-times of minutes. A new integral equation (IE) method for analyzing TMS fields was developed. The human head is highly-heterogeneous and characterized by high-relative permittivities (107). IE techniques for analyzing electromagnetic interactions with such media suffer from high-contrast and low-frequency breakdowns. The novel high-permittivity and low-frequency stable internally combined volume-surface IE method developed. The method not only applies to the analysis of high-permittivity objects, but it is also the first IE tool that is stable when analyzing highly-inhomogeneous negative permittivity plasmas. Design: TMS applications call for electric fields to be sharply focused on regions that lie deep inside the brain. Unfortunately, fields generated by present-day Figure-8 coils stimulate relatively large regions near the brain surface. An optimization method for designing single feed TMS coil-arrays capable of producing more localized and deeper stimulation was developed. Results show that the coil-arrays stimulate 2.4 cm into the head while stimulating 3
The display of multiple images derived from emission computed assisted tomography (ECAT)
Jackson, P.C.; Davies, E.R.; Goddard, P.R.; Wilde, R.P.H.
1983-01-01
In emission computed assisted tomography, a technique has been developed to display the multiple sections of an organ within a single image, such that three dimensional appreciation of the organ can be obtained, whilst also preserving functional information. The technique when tested on phantoms showed no obvious deterioration in resolution and when used clinically gave satisfactory visual results. Such a method should allow easier appreciation of the extent of a lesion through an organ and thus allow dimensions to be obtained by direct measurement. (U.K.)
Modules and methods for all photonic computing
Schultz, David R.; Ma, Chao Hung
2001-01-01
A method for all photonic computing, comprising the steps of: encoding a first optical/electro-optical element with a two dimensional mathematical function representing input data; illuminating the first optical/electro-optical element with a collimated beam of light; illuminating a second optical/electro-optical element with light from the first optical/electro-optical element, the second optical/electro-optical element having a characteristic response corresponding to an iterative algorithm useful for solving a partial differential equation; iteratively recirculating the signal through the second optical/electro-optical element with light from the second optical/electro-optical element for a predetermined number of iterations; and, after the predetermined number of iterations, optically and/or electro-optically collecting output data representing an iterative optical solution from the second optical/electro-optical element.
Optical design teaching by computing graphic methods
Vazquez-Molini, D.; Muñoz-Luna, J.; Fernandez-Balbuena, A. A.; Garcia-Botella, A.; Belloni, P.; Alda, J.
2012-10-01
One of the key challenges in the teaching of Optics is that students need to know not only the math of the optical design, but also, and more important, to grasp and understand the optics in a three-dimensional space. Having a clear image of the problem to solve is the first step in order to begin to solve that problem. Therefore to achieve that the students not only must know the equation of refraction law but they have also to understand how the main parameters of this law are interacting among them. This should be a major goal in the teaching course. Optical graphic methods are a valuable tool in this way since they have the advantage of visual information and the accuracy of a computer calculation.
FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants.
Bednar, David; Beerens, Koen; Sebestova, Eva; Bendl, Jaroslav; Khare, Sagar; Chaloupkova, Radka; Prokop, Zbynek; Brezovsky, Jan; Baker, David; Damborsky, Jiri
2015-11-01
There is great interest in increasing proteins' stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt's reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.
FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants.
David Bednar
2015-11-01
Full Text Available There is great interest in increasing proteins' stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt's reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.
HARMONIC ANALYSIS OF SVPWM INVERTER USING MULTIPLE-PULSES METHOD
Mehmet YUMURTACI
2009-01-01
Full Text Available Space Vector Modulation (SVM technique is a popular and an important PWM technique for three phases voltage source inverter in the control of Induction Motor. In this study harmonic analysis of Space Vector PWM (SVPWM is investigated using multiple-pulses method. Multiple-Pulses method calculates the Fourier coefficients of individual positive and negative pulses of the output PWM waveform and adds them together using the principle of superposition to calculate the Fourier coefficients of the all PWM output signal. Harmonic magnitudes can be calculated directly by this method without linearization, using look-up tables or Bessel functions. In this study, the results obtained in the application of SVPWM for values of variable parameters are compared with the results obtained with the multiple-pulses method.
Research on neutron source multiplication method in nuclear critical safety
Zhu Qingfu; Shi Yongqian; Hu Dingsheng
2005-01-01
The paper concerns in the neutron source multiplication method research in nuclear critical safety. Based on the neutron diffusion equation with external neutron source the effective sub-critical multiplication factor k s is deduced, and k s is different to the effective neutron multiplication factor k eff in the case of sub-critical system with external neutron source. The verification experiment on the sub-critical system indicates that the parameter measured with neutron source multiplication method is k s , and k s is related to the external neutron source position in sub-critical system and external neutron source spectrum. The relation between k s and k eff and the effect of them on nuclear critical safety is discussed. (author)
Computed tomography shielding methods: a literature review.
Curtis, Jessica Ryann
2010-01-01
To investigate available shielding methods in an effort to further awareness and understanding of existing preventive measures related to patient exposure in computed tomography (CT) scanning. Searches were conducted to locate literature discussing the effectiveness of commercially available shields. Literature containing information regarding breast, gonad, eye and thyroid shielding was identified. Because of rapidly advancing technology, the selection of articles was limited to those published within the past 5 years. The selected studies were examined using the following topics as guidelines: the effectiveness of the shield (percentage of dose reduction), the shield's effect on image quality, arguments for or against its use (including practicality) and overall recommendation for its use in clinical practice. Only a limited number of studies have been performed on the use of shields for the eyes, thyroid and gonads, but the evidence shows an overall benefit to their use. Breast shielding has been the most studied shielding method, with consistent agreement throughout the literature on its effectiveness at reducing radiation dose. The effect of shielding on image quality was not remarkable in a majority of studies. Although it is noted that more studies need to be conducted regarding the impact on image quality, the currently published literature stresses the importance of shielding in reducing dose. Commercially available shields for the breast, thyroid, eyes and gonads should be implemented in clinical practice. Further research is needed to ascertain the prevalence of shielding in the clinical setting.
Feng, Bo; Gao, Feng; Zhao, Huijuan; Zhang, Limin; Li, Jiao; Zhou, Zhongxing
2018-02-01
The purpose of this work is to introduce and study a novel x-ray beam irradiation pattern for X-ray Luminescence Computed Tomography (XLCT), termed multiple intensity-weighted narrow-beam irradiation. The proposed XLCT imaging method is studied through simulations of x-ray and diffuse lights propagation. The emitted optical photons from X-ray excitable nanophosphors were collected by optical fiber bundles from the right-side surface of the phantom. The implementation of image reconstruction is based on the simulated measurements from 6 or 12 angular projections in terms of 3 or 5 x-ray beams scanning mode. The proposed XLCT imaging method is compared against the constant intensity weighted narrow-beam XLCT. From the reconstructed XLCT images, we found that the Dice similarity and quantitative ratio of targets have a certain degree of improvement. The results demonstrated that the proposed method can offer simultaneously high image quality and fast image acquisition.
An Intuitionistic Multiplicative ORESTE Method for Patients’ Prioritization of Hospitalization
Cheng Zhang
2018-04-01
Full Text Available The tension brought about by sickbeds is a common and intractable issue in public hospitals in China due to the large population. Assigning the order of hospitalization of patients is difficult because of complex patient information such as disease type, emergency degree, and severity. It is critical to rank the patients taking full account of various factors. However, most of the evaluation criteria for hospitalization are qualitative, and the classical ranking method cannot derive the detailed relations between patients based on these criteria. Motivated by this, a comprehensive multiple criteria decision making method named the intuitionistic multiplicative ORESTE (organísation, rangement et Synthèse dedonnées relarionnelles, in French was proposed to handle the problem. The subjective and objective weights of criteria were considered in the proposed method. To do so, first, considering the vagueness of human perceptions towards the alternatives, an intuitionistic multiplicative preference relation model is applied to represent the experts’ preferences over the pairwise alternatives with respect to the predetermined criteria. Then, a correlation coefficient-based weight determining method is developed to derive the objective weights of criteria. This method can overcome the biased results caused by highly-related criteria. Afterwards, we improved the general ranking method, ORESTE, by introducing a new score function which considers both the subjective and objective weights of criteria. An intuitionistic multiplicative ORESTE method was then developed and further highlighted by a case study concerning the patients’ prioritization.
Multiscale Methods, Parallel Computation, and Neural Networks for Real-Time Computer Vision.
Battiti, Roberto
1990-01-01
This thesis presents new algorithms for low and intermediate level computer vision. The guiding ideas in the presented approach are those of hierarchical and adaptive processing, concurrent computation, and supervised learning. Processing of the visual data at different resolutions is used not only to reduce the amount of computation necessary to reach the fixed point, but also to produce a more accurate estimation of the desired parameters. The presented adaptive multiple scale technique is applied to the problem of motion field estimation. Different parts of the image are analyzed at a resolution that is chosen in order to minimize the error in the coefficients of the differential equations to be solved. Tests with video-acquired images show that velocity estimation is more accurate over a wide range of motion with respect to the homogeneous scheme. In some cases introduction of explicit discontinuities coupled to the continuous variables can be used to avoid propagation of visual information from areas corresponding to objects with different physical and/or kinematic properties. The human visual system uses concurrent computation in order to process the vast amount of visual data in "real -time." Although with different technological constraints, parallel computation can be used efficiently for computer vision. All the presented algorithms have been implemented on medium grain distributed memory multicomputers with a speed-up approximately proportional to the number of processors used. A simple two-dimensional domain decomposition assigns regions of the multiresolution pyramid to the different processors. The inter-processor communication needed during the solution process is proportional to the linear dimension of the assigned domain, so that efficiency is close to 100% if a large region is assigned to each processor. Finally, learning algorithms are shown to be a viable technique to engineer computer vision systems for different applications starting from
Computational methods in calculating superconducting current problems
Brown, David John, II
Various computational problems in treating superconducting currents are examined. First, field inversion in spatial Fourier transform space is reviewed to obtain both one-dimensional transport currents flowing down a long thin tape, and a localized two-dimensional current. The problems associated with spatial high-frequency noise, created by finite resolution and experimental equipment, are presented, and resolved with a smooth Gaussian cutoff in spatial frequency space. Convergence of the Green's functions for the one-dimensional transport current densities is discussed, and particular attention is devoted to the negative effects of performing discrete Fourier transforms alone on fields asymptotically dropping like 1/r. Results of imaging simulated current densities are favorably compared to the original distributions after the resulting magnetic fields undergo the imaging procedure. The behavior of high-frequency spatial noise, and the behavior of the fields with a 1/r asymptote in the imaging procedure in our simulations is analyzed, and compared to the treatment of these phenomena in the published literature. Next, we examine calculation of Mathieu and spheroidal wave functions, solutions to the wave equation in elliptical cylindrical and oblate and prolate spheroidal coordinates, respectively. These functions are also solutions to Schrodinger's equations with certain potential wells, and are useful in solving time-varying superconducting problems. The Mathieu functions are Fourier expanded, and the spheroidal functions expanded in associated Legendre polynomials to convert the defining differential equations to recursion relations. The infinite number of linear recursion equations is converted to an infinite matrix, multiplied by a vector of expansion coefficients, thus becoming an eigenvalue problem. The eigenvalue problem is solved with root solvers, and the eigenvector problem is solved using a Jacobi-type iteration method, after preconditioning the
Symbolic interactionism as a theoretical perspective for multiple method research.
Benzies, K M; Allen, M N
2001-02-01
Qualitative and quantitative research rely on different epistemological assumptions about the nature of knowledge. However, the majority of nurse researchers who use multiple method designs do not address the problem of differing theoretical perspectives. Traditionally, symbolic interactionism has been viewed as one perspective underpinning qualitative research, but it is also the basis for quantitative studies. Rooted in social psychology, symbolic interactionism has a rich intellectual heritage that spans more than a century. Underlying symbolic interactionism is the major assumption that individuals act on the basis of the meaning that things have for them. The purpose of this paper is to present symbolic interactionism as a theoretical perspective for multiple method designs with the aim of expanding the dialogue about new methodologies. Symbolic interactionism can serve as a theoretical perspective for conceptually clear and soundly implemented multiple method research that will expand the understanding of human health behaviour.
Analysis of Computer Experiments with Multiple Noise Sources
Dehlendorff, Christian; Kulahci, Murat; Andersen, Klaus Kaae
2010-01-01
In this paper we present a modeling framework for analyzing computer models with two types of variations. The paper is based on a case study of an orthopedic surgical unit, which has both controllable and uncontrollable factors. Our results show that this structure of variation can be modeled...
Computational Studies of Protein Hydration Methods
Morozenko, Aleksandr
It is widely appreciated that water plays a vital role in proteins' functions. The long-range proton transfer inside proteins is usually carried out by the Grotthuss mechanism and requires a chain of hydrogen bonds that is composed of internal water molecules and amino acid residues of the protein. In other cases, water molecules can facilitate the enzymes catalytic reactions by becoming a temporary proton donor/acceptor. Yet a reliable way of predicting water protein interior is still not available to the biophysics community. This thesis presents computational studies that have been performed to gain insights into the problems of fast and accurate prediction of potential water sites inside internal cavities of protein. Specifically, we focus on the task of attainment of correspondence between results obtained from computational experiments and experimental data available from X-ray structures. An overview of existing methods of predicting water molecules in the interior of a protein along with a discussion of the trustworthiness of these predictions is a second major subject of this thesis. A description of differences of water molecules in various media, particularly, gas, liquid and protein interior, and theoretical aspects of designing an adequate model of water for the protein environment are widely discussed in chapters 3 and 4. In chapter 5, we discuss recently developed methods of placement of water molecules into internal cavities of a protein. We propose a new methodology based on the principle of docking water molecules to a protein body which allows to achieve a higher degree of matching experimental data reported in protein crystal structures than other techniques available in the world of biophysical software. The new methodology is tested on a set of high-resolution crystal structures of oligopeptide-binding protein (OppA) containing a large number of resolved internal water molecules and applied to bovine heart cytochrome c oxidase in the fully
A General Method for QTL Mapping in Multiple Related Populations Derived from Multiple Parents
Yan AO
2009-03-01
Full Text Available It's well known that incorporating some existing populations derived from multiple parents may improve QTL mapping and QTL-based breeding programs. However, no general maximum likelihood method has been available for this strategy. Based on the QTL mapping in multiple related populations derived from two parents, a maximum likelihood estimation method was proposed, which can incorporate several populations derived from three or more parents and also can be used to handle different mating designs. Taking a circle design as an example, we conducted simulation studies to study the effect of QTL heritability and sample size upon the proposed method. The results showed that under the same heritability, enhanced power of QTL detection and more precise and accurate estimation of parameters could be obtained when three F2 populations were jointly analyzed, compared with the joint analysis of any two F2 populations. Higher heritability, especially with larger sample sizes, would increase the ability of QTL detection and improve the estimation of parameters. Potential advantages of the method are as follows: firstly, the existing results of QTL mapping in single population can be compared and integrated with each other with the proposed method, therefore the ability of QTL detection and precision of QTL mapping can be improved. Secondly, owing to multiple alleles in multiple parents, the method can exploit gene resource more adequately, which will lay an important genetic groundwork for plant improvement.
Method for measuring multiple scattering corrections between liquid scintillators
Verbeke, J.M., E-mail: verbeke2@llnl.gov; Glenn, A.M., E-mail: glenn22@llnl.gov; Keefer, G.J., E-mail: keefer1@llnl.gov; Wurtz, R.E., E-mail: wurtz1@llnl.gov
2016-07-21
A time-of-flight method is proposed to experimentally quantify the fractions of neutrons scattering between scintillators. An array of scintillators is characterized in terms of crosstalk with this method by measuring a californium source, for different neutron energy thresholds. The spectral information recorded by the scintillators can be used to estimate the fractions of neutrons multiple scattering. With the help of a correction to Feynman's point model theory to account for multiple scattering, these fractions can in turn improve the mass reconstruction of fissile materials under investigation.
Computer simulation of FT-NMR multiple pulse experiment
Allouche, A.; Pouzard, G.
1989-04-01
Using the product operator formalism in its real form, SIMULDENS expands the density matrix of a scalar coupled nuclear spin system and simulates analytically a large variety of FT-NMR multiple pulse experiments. The observable transverse magnetizations are stored and can be combined to represent signal accumulation. The programming language is VAX PASCAL, but a MacIntosh Turbo Pascal Version is also available.
Computer simulation of FT-NMR multiple pulse experiment
Allouche, A.; Pouzard, G.
1989-01-01
Using the product operator formalism in its real form, SIMULDENS expands the density matrix of a scalar coupled nuclear spin system and simulates analytically a large variety of FT-NMR multiple pulse experiments. The observable transverse magnetizations are stored and can be combined to represent signal accumulation. The programming language is VAX PASCAL, but a MacIntosh Turbo Pascal Version is also available. (orig.)
INTEGRATED FUSION METHOD FOR MULTIPLE TEMPORAL-SPATIAL-SPECTRAL IMAGES
H. Shen
2012-08-01
Full Text Available Data fusion techniques have been widely researched and applied in remote sensing field. In this paper, an integrated fusion method for remotely sensed images is presented. Differently from the existed methods, the proposed method has the performance to integrate the complementary information in multiple temporal-spatial-spectral images. In order to represent and process the images in one unified framework, two general image observation models are firstly presented, and then the maximum a posteriori (MAP framework is used to set up the fusion model. The gradient descent method is employed to solve the fused image. The efficacy of the proposed method is validated using simulated images.
Integrating multiple scientific computing needs via a Private Cloud infrastructure
Bagnasco, S; Berzano, D; Brunetti, R; Lusso, S; Vallero, S
2014-01-01
In a typical scientific computing centre, diverse applications coexist and share a single physical infrastructure. An underlying Private Cloud facility eases the management and maintenance of heterogeneous use cases such as multipurpose or application-specific batch farms, Grid sites catering to different communities, parallel interactive data analysis facilities and others. It allows to dynamically and efficiently allocate resources to any application and to tailor the virtual machines according to the applications' requirements. Furthermore, the maintenance of large deployments of complex and rapidly evolving middleware and application software is eased by the use of virtual images and contextualization techniques; for example, rolling updates can be performed easily and minimizing the downtime. In this contribution we describe the Private Cloud infrastructure at the INFN-Torino Computer Centre, that hosts a full-fledged WLCG Tier-2 site and a dynamically expandable PROOF-based Interactive Analysis Facility for the ALICE experiment at the CERN LHC and several smaller scientific computing applications. The Private Cloud building blocks include the OpenNebula software stack, the GlusterFS filesystem (used in two different configurations for worker- and service-class hypervisors) and the OpenWRT Linux distribution (used for network virtualization). A future integration into a federated higher-level infrastructure is made possible by exposing commonly used APIs like EC2 and by using mainstream contextualization tools like CloudInit.
Security prospects through cloud computing by adopting multiple clouds
Jensen, Meiko; Schwenk, Jörg; Bohli, Jens Matthias
2011-01-01
Clouds impose new security challenges, which are amongst the biggest obstacles when considering the usage of cloud services. This triggered a lot of research activities in this direction, resulting in a quantity of proposals targeting the various security threats. Besides the security issues coming...... with the cloud paradigm, it can also provide a new set of unique features which open the path towards novel security approaches, techniques and architectures. This paper initiates this discussion by contributing a concept which achieves security merits by making use of multiple distinct clouds at the same time....
MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method.
Tuta, Jure; Juric, Matjaz B
2018-03-24
This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method), a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah) and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.). Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.
MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method
Jure Tuta
2018-03-01
Full Text Available This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method, a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.. Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.
Urdan, Tim; Munoz, Chantico
2012-01-01
Multiple methods were used to examine the academic motivation and cultural identity of a sample of college undergraduates. The children of immigrant parents (CIPs, n = 52) and the children of non-immigrant parents (non-CIPs, n = 42) completed surveys assessing core cultural identity, valuing of cultural accomplishments, academic self-concept,…
Correction of measured multiplicity distributions by the simulated annealing method
Hafidouni, M.
1993-01-01
Simulated annealing is a method used to solve combinatorial optimization problems. It is used here for the correction of the observed multiplicity distribution from S-Pb collisions at 200 GeV/c per nucleon. (author) 11 refs., 2 figs
Fedorenko, Sergei V.
2011-01-01
A novel method for computation of the discrete Fourier transform over a finite field with reduced multiplicative complexity is described. If the number of multiplications is to be minimized, then the novel method for the finite field of even extension degree is the best known method of the discrete Fourier transform computation. A constructive method of constructing for a cyclic convolution over a finite field is introduced.
An introduction to programming multiple-processor computers
Hicks, H.R.; Lynch, V.E.
1986-01-01
Fortran applications programs can be executed on multiprocessor computers in either a unitasking (traditional) or multitasking form. The later allows a single job to use more than one processor simultaneously, with a consequent reduction in elapsed time and, perhaps, the cost of the calculation. An introduction to programming in this environment is presented. The concept of synchronization and data sharing using EVENTS and LOCKS are illustrated with examples. The strategy of strong synchronization and the use of synchronization templates are proposed. We emphasize that incorrect multitasking programs can produce irreducible results, which makes debugging more difficult
Application of multiple timestep integration method in SSC
Guppy, J.G.
1979-01-01
The thermohydraulic transient simulation of an entire LMFBR system is, by its very nature, complex. Physically, the entire plant consists of many subsystems which are coupled by various processes and/or components. The characteristic integration timesteps for these processes/components can vary over a wide range. To improve computing efficiency, a multiple timestep scheme (MTS) approach has been used in the development of the Super System Code (SSC). In this paper: (1) the partitioning of the system and the timestep control are described, and (2) results are presented showing a savings in computer running time using the MTS of as much as five times the time required using a single timestep scheme
System and method for image registration of multiple video streams
Dillavou, Marcus W.; Shum, Phillip Corey; Guthrie, Baron L.; Shenai, Mahesh B.; Deaton, Drew Steven; May, Matthew Benton
2018-02-06
Provided herein are methods and systems for image registration from multiple sources. A method for image registration includes rendering a common field of interest that reflects a presence of a plurality of elements, wherein at least one of the elements is a remote element located remotely from another of the elements and updating the common field of interest such that the presence of the at least one of the elements is registered relative to another of the elements.
Multiple time-scale methods in particle simulations of plasmas
Cohen, B.I.
1985-01-01
This paper surveys recent advances in the application of multiple time-scale methods to particle simulation of collective phenomena in plasmas. These methods dramatically improve the efficiency of simulating low-frequency kinetic behavior by allowing the use of a large timestep, while retaining accuracy. The numerical schemes surveyed provide selective damping of unwanted high-frequency waves and preserve numerical stability in a variety of physics models: electrostatic, magneto-inductive, Darwin and fully electromagnetic. The paper reviews hybrid simulation models, the implicitmoment-equation method, the direct implicit method, orbit averaging, and subcycling
Sun, Xiaoli; Shen, Wenbin; Chen, Xiaobai; Wen, Tingguo; Duan, Yongli; Wang, Rengui
2017-10-01
To analyse the findings of multiple detector computed tomography (MDCT) after direct lymphangiography in primary intestinal lymphangiectasia (PIL). Fifty-five patients with PIL were retrospectively reviewed. All patients underwent MDCT after direct lymphangiography. The pathologies of 16 patients were confirmed by surgery and the remaining 39 patients were confirmed by gastroendoscopy and/or capsule endoscopy. After direct lymphangiography, MDCT found intra- and extraintestinal as well as lymphatic vessel abnormalities. Among the intra- and extraintestinal disorders, 49 patients had varying degrees of intestinal dilatation, 46 had small bowel wall thickening, 9 had pleural and pericardial effusions, 21 had ascites, 41 had mesenteric oedema, 20 had mesenteric nodules and 9 had abdominal lymphatic cysts. Features of lymphatic vessel abnormalities included intestinal trunk reflux (43.6%, n = 24), lumbar trunk reflux (89.1%, n = 49), pleural and pulmonary lymph reflux (14.5%, n = 8), pericardial and mediastinal lymph reflux (16.4%, n = 9), mediastinal and pulmonary lymph reflux (18.2%, n = 10), and thoracic duct outlet obstruction (90.9%, n = 50). Multiple detector computed tomography after direct lymphangiography provides a safe and accurate examination method and is an excellent tool for the diagnosis of PIL. © 2017 The Royal Australian and New Zealand College of Radiologists.
Computed tomography in multiple trauma patients. Technical aspects, work flow, and dose reduction
Fellner, F.A.; Krieger, J.; Floery, D.; Lechner, N.
2014-01-01
Patients with severe, life-threatening trauma require a fast and accurate clinical and imaging diagnostic workup during the first phase of trauma management. Early whole-body computed tomography has clearly been proven to be the current standard of care of these patients. A similar imaging quality can be achieved in the multiple trauma setting compared with routine imaging especially using rapid, latest generation computed tomography (CT) scanners. This article encompasses a detailed view on the use of CT in patients with life-threatening trauma. A special focus is placed on radiological procedures in trauma units and on the methods for CT workup in routine cases and in challenging situations. Another focus discusses the potential of dose reduction of CT scans in multiple trauma as well as the examination of children with severe trauma. Various studies have demonstrated that early whole-body CT positively correlates with low morbidity and mortality and is clearly superior to the use of other imaging modalities. Optimal trauma unit management means a close cooperation between trauma surgeons, anesthesiologists and radiologists, whereby the radiologist is responsible for a rapid and accurate radiological workup and the rapid communication of imaging findings. However, even in the trauma setting, aspects of patient radiation doses should be kept in mind. (orig.) [de
Computational methods in sequence and structure prediction
Lang, Caiyi
This dissertation is organized into two parts. In the first part, we will discuss three computational methods for cis-regulatory element recognition in three different gene regulatory networks as the following: (a) Using a comprehensive "Phylogenetic Footprinting Comparison" method, we will investigate the promoter sequence structures of three enzymes (PAL, CHS and DFR) that catalyze sequential steps in the pathway from phenylalanine to anthocyanins in plants. Our result shows there exists a putative cis-regulatory element "AC(C/G)TAC(C)" in the upstream of these enzyme genes. We propose this cis-regulatory element to be responsible for the genetic regulation of these three enzymes and this element, might also be the binding site for MYB class transcription factor PAP1. (b) We will investigate the role of the Arabidopsis gene glutamate receptor 1.1 (AtGLR1.1) in C and N metabolism by utilizing the microarray data we obtained from AtGLR1.1 deficient lines (antiAtGLR1.1). We focus our investigation on the putatively co-regulated transcript profile of 876 genes we have collected in antiAtGLR1.1 lines. By (a) scanning the occurrence of several groups of known abscisic acid (ABA) related cisregulatory elements in the upstream regions of 876 Arabidopsis genes; and (b) exhaustive scanning of all possible 6-10 bps motif occurrence in the upstream regions of the same set of genes, we are able to make a quantative estimation on the enrichment level of each of the cis-regulatory element candidates. We finally conclude that one specific cis-regulatory element group, called "ABRE" elements, are statistically highly enriched within the 876-gene group as compared to their occurrence within the genome. (c) We will introduce a new general purpose algorithm, called "fuzzy REDUCE1", which we have developed recently for automated cis-regulatory element identification. In the second part, we will discuss our newly devised protein design framework. With this framework we have developed
Computational methods for corpus annotation and analysis
Lu, Xiaofei
2014-01-01
This book reviews computational tools for lexical, syntactic, semantic, pragmatic and discourse analysis, with instructions on how to obtain, install and use each tool. Covers studies using Natural Language Processing, and offers ideas for better integration.
Cloud computing methods and practical approaches
Mahmood, Zaigham
2013-01-01
This book presents both state-of-the-art research developments and practical guidance on approaches, technologies and frameworks for the emerging cloud paradigm. Topics and features: presents the state of the art in cloud technologies, infrastructures, and service delivery and deployment models; discusses relevant theoretical frameworks, practical approaches and suggested methodologies; offers guidance and best practices for the development of cloud-based services and infrastructures, and examines management aspects of cloud computing; reviews consumer perspectives on mobile cloud computing an
Statistics of electron multiplication in multiplier phototube: iterative method
Grau Malonda, A.; Ortiz Sanchez, J.F.
1985-01-01
An iterative method is applied to study the variation of dynode response in the multiplier phototube. Three different situations are considered that correspond to the following ways of electronic incidence on the first dynode: incidence of exactly one electron, incidence of exactly r electrons and incidence of an average anti-r electrons. The responses are given for a number of steps between 1 and 5, and for values of the multiplication factor of 2.1, 2.5, 3 and 5. We study also the variance, the skewness and the excess of jurtosis for different multiplication factors. (author)
Statistics of electron multiplication in a multiplier phototube; Iterative method
Ortiz, J. F.; Grau, A.
1985-01-01
In the present paper an iterative method is applied to study the variation of dynode response in the multiplier phototube. Three different situation are considered that correspond to the following ways of electronic incidence on the first dynode: incidence of exactly one electron, incidence of exactly r electrons and incidence of an average r electrons. The responses are given for a number of steps between 1 and 5, and for values of the multiplication factor of 2.1, 2.5, 3 and 5. We study also the variance, the skewness and the excess of jurtosis for different multiplication factors. (Author) 11 refs
Advanced Computational Methods in Bio-Mechanics.
Al Qahtani, Waleed M S; El-Anwar, Mohamed I
2018-04-15
A novel partnership between surgeons and machines, made possible by advances in computing and engineering technology, could overcome many of the limitations of traditional surgery. By extending surgeons' ability to plan and carry out surgical interventions more accurately and with fewer traumas, computer-integrated surgery (CIS) systems could help to improve clinical outcomes and the efficiency of healthcare delivery. CIS systems could have a similar impact on surgery to that long since realised in computer-integrated manufacturing. Mathematical modelling and computer simulation have proved tremendously successful in engineering. Computational mechanics has enabled technological developments in virtually every area of our lives. One of the greatest challenges for mechanists is to extend the success of computational mechanics to fields outside traditional engineering, in particular to biology, the biomedical sciences, and medicine. Biomechanics has significant potential for applications in orthopaedic industry, and the performance arts since skills needed for these activities are visibly related to the human musculoskeletal and nervous systems. Although biomechanics is widely used nowadays in the orthopaedic industry to design orthopaedic implants for human joints, dental parts, external fixations and other medical purposes, numerous researches funded by billions of dollars are still running to build a new future for sports and human healthcare in what is called biomechanics era.
Sauer, J.; Schramme, S.; Rüttinger, B.
2000-01-01
This article presents a study that examines multiple effects of using different means of computer-mediated communication and knowledge elicitation methods during a product design process. The experimental task involved a typical scenario in product design, in which a knowledge engineer consults two experts to generate knowledge about a design issue. Employing a 3x2 between-subjects design, three conference types (face-to-face, computer, multivedia) and two knowledge elicitation methods (struc...
Walking path-planning method for multiple radiation areas
Liu, Yong-kuo; Li, Meng-kun; Peng, Min-jun; Xie, Chun-li; Yuan, Cheng-qian; Wang, Shuang-yu; Chao, Nan
2016-01-01
Highlights: • Radiation environment modeling method is designed. • Path-evaluating method and segmented path-planning method are proposed. • Path-planning simulation platform for radiation environment is built. • The method avoids to be misled by minimum dose path in single area. - Abstract: Based on minimum dose path-searching method, walking path-planning method for multiple radiation areas was designed to solve minimum dose path problem in single area and find minimum dose path in the whole space in this paper. Path-planning simulation platform was built using C# programming language and DirectX engine. The simulation platform was used in simulations dealing with virtual nuclear facilities. Simulation results indicated that the walking-path planning method is effective in providing safety for people walking in nuclear facilities.
Multiple centroid method to evaluate the adaptability of alfalfa genotypes
Moysés Nascimento
2015-02-01
Full Text Available This study aimed to evaluate the efficiency of multiple centroids to study the adaptability of alfalfa genotypes (Medicago sativa L.. In this method, the genotypes are compared with ideotypes defined by the bissegmented regression model, according to the researcher's interest. Thus, genotype classification is carried out as determined by the objective of the researcher and the proposed recommendation strategy. Despite the great potential of the method, it needs to be evaluated under the biological context (with real data. In this context, we used data on the evaluation of dry matter production of 92 alfalfa cultivars, with 20 cuttings, from an experiment in randomized blocks with two repetitions carried out from November 2004 to June 2006. The multiple centroid method proved efficient for classifying alfalfa genotypes. Moreover, it showed no unambiguous indications and provided that ideotypes were defined according to the researcher's interest, facilitating data interpretation.
Unplanned Complex Suicide-A Consideration of Multiple Methods.
Ateriya, Navneet; Kanchan, Tanuj; Shekhawat, Raghvendra Singh; Setia, Puneet; Saraf, Ashish
2018-05-01
Detailed death investigations are mandatory to find out the exact cause and manner in non-natural deaths. In this reference, use of multiple methods in suicide poses a challenge for the investigators especially when the choice of methods to cause death is unplanned. There is an increased likelihood that doubts of homicide are raised in cases of unplanned complex suicides. A case of complex suicide is reported where the victim resorted to multiple methods to end his life, and what appeared to be an unplanned variant based on the death scene investigations. A meticulous crime scene examination, interviews of the victim's relatives and other witnesses, and a thorough autopsy are warranted to conclude on the cause and manner of death in all such cases. © 2017 American Academy of Forensic Sciences.
Characterizing lentic freshwater fish assemblages using multiple sampling methods
Fischer, Jesse R.; Quist, Michael C.
2014-01-01
Characterizing fish assemblages in lentic ecosystems is difficult, and multiple sampling methods are almost always necessary to gain reliable estimates of indices such as species richness. However, most research focused on lentic fish sampling methodology has targeted recreationally important species, and little to no information is available regarding the influence of multiple methods and timing (i.e., temporal variation) on characterizing entire fish assemblages. Therefore, six lakes and impoundments (48–1,557 ha surface area) were sampled seasonally with seven gear types to evaluate the combined influence of sampling methods and timing on the number of species and individuals sampled. Probabilities of detection for species indicated strong selectivities and seasonal trends that provide guidance on optimal seasons to use gears when targeting multiple species. The evaluation of species richness and number of individuals sampled using multiple gear combinations demonstrated that appreciable benefits over relatively few gears (e.g., to four) used in optimal seasons were not present. Specifically, over 90 % of the species encountered with all gear types and season combinations (N = 19) from six lakes and reservoirs were sampled with nighttime boat electrofishing in the fall and benthic trawling, modified-fyke, and mini-fyke netting during the summer. Our results indicated that the characterization of lentic fish assemblages was highly influenced by the selection of sampling gears and seasons, but did not appear to be influenced by waterbody type (i.e., natural lake, impoundment). The standardization of data collected with multiple methods and seasons to account for bias is imperative to monitoring of lentic ecosystems and will provide researchers with increased reliability in their interpretations and decisions made using information on lentic fish assemblages.
Ibrahim, Khaled Z. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Epifanovsky, Evgeny [Q-Chem, Inc., Pleasanton, CA (United States); Williams, Samuel W. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Krylov, Anna I. [Univ. of Southern California, Los Angeles, CA (United States). Dept. of Chemistry
2016-07-26
Coupled-cluster methods provide highly accurate models of molecular structure by explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix-matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts to extend the Libtensor framework to work in the distributed memory environment in a scalable and energy efficient manner. We achieve up to 240 speedup compared with the best optimized shared memory implementation. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures, (Cray XC30&XC40, BlueGene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance. Nevertheless, we preserve a uni ed interface to both programming models to maintain the productivity of computational quantum chemists.
Application of Soft Computing Techniques and Multiple Regression Models for CBR prediction of Soils
Fatimah Khaleel Ibrahim
2017-08-01
Full Text Available The techniques of soft computing technique such as Artificial Neutral Network (ANN have improved the predicting capability and have actually discovered application in Geotechnical engineering. The aim of this research is to utilize the soft computing technique and Multiple Regression Models (MLR for forecasting the California bearing ratio CBR( of soil from its index properties. The indicator of CBR for soil could be predicted from various soils characterizing parameters with the assist of MLR and ANN methods. The data base that collected from the laboratory by conducting tests on 86 soil samples that gathered from different projects in Basrah districts. Data gained from the experimental result were used in the regression models and soft computing techniques by using artificial neural network. The liquid limit, plastic index , modified compaction test and the CBR test have been determined. In this work, different ANN and MLR models were formulated with the different collection of inputs to be able to recognize their significance in the prediction of CBR. The strengths of the models that were developed been examined in terms of regression coefficient (R2, relative error (RE% and mean square error (MSE values. From the results of this paper, it absolutely was noticed that all the proposed ANN models perform better than that of MLR model. In a specific ANN model with all input parameters reveals better outcomes than other ANN models.
Geometric calibration method for multiple head cone beam SPECT systems
Rizo, Ph.; Grangeat, P.; Guillemaud, R.; Sauze, R.
1993-01-01
A method is presented for performing geometric calibration on Single Photon Emission Tomography (SPECT) cone beam systems with multiple cone beam collimators, each having its own orientation parameters. This calibration method relies on the fact that, in tomography, for each head, the relative position of the rotation axis and of the collimator does not change during the acquisition. In order to ensure the method stability, the parameters to be estimated in intrinsic parameters and extrinsic parameters are separated. The intrinsic parameters describe the acquisition geometry and the extrinsic parameters position of the detection system with respect to the rotation axis. (authors) 3 refs
A crack growth evaluation method for interacting multiple cracks
Kamaya, Masayuki
2003-01-01
When stress corrosion cracking or corrosion fatigue occurs, multiple cracks are frequently initiated in the same area. According to section XI of the ASME Boiler and Pressure Vessel Code, multiple cracks are considered as a single combined crack in crack growth analysis, if the specified conditions are satisfied. In crack growth processes, however, no prescription for the interference between multiple cracks is given in this code. The JSME Post-Construction Code, issued in May 2000, prescribes the conditions of crack coalescence in the crack growth process. This study aimed to extend this prescription to more general cases. A simulation model was applied, to simulate the crack growth process, taking into account the interference between two cracks. This model made it possible to analyze multiple crack growth behaviors for many cases (e.g. different relative position and length) that could not be studied by experiment only. Based on these analyses, a new crack growth analysis method was suggested for taking into account the interference between multiple cracks. (author)
Inferring Human Activity in Mobile Devices by Computing Multiple Contexts.
Chen, Ruizhi; Chu, Tianxing; Liu, Keqiang; Liu, Jingbin; Chen, Yuwei
2015-08-28
This paper introduces a framework for inferring human activities in mobile devices by computing spatial contexts, temporal contexts, spatiotemporal contexts, and user contexts. A spatial context is a significant location that is defined as a geofence, which can be a node associated with a circle, or a polygon; a temporal context contains time-related information that can be e.g., a local time tag, a time difference between geographical locations, or a timespan; a spatiotemporal context is defined as a dwelling length at a particular spatial context; and a user context includes user-related information that can be the user's mobility contexts, environmental contexts, psychological contexts or social contexts. Using the measurements of the built-in sensors and radio signals in mobile devices, we can snapshot a contextual tuple for every second including aforementioned contexts. Giving a contextual tuple, the framework evaluates the posteriori probability of each candidate activity in real-time using a Naïve Bayes classifier. A large dataset containing 710,436 contextual tuples has been recorded for one week from an experiment carried out at Texas A&M University Corpus Christi with three participants. The test results demonstrate that the multi-context solution significantly outperforms the spatial-context-only solution. A classification accuracy of 61.7% is achieved for the spatial-context-only solution, while 88.8% is achieved for the multi-context solution.
Jalali, T.
2015-07-01
In this paper, we present dielectric elliptical shapes modelling with respect to a highly confined power distribution in the resulting nanojet, which has been parameterized according to the beam waist and its beam divergence. The method is based on spherical bessel function as a basis function, which is adapted to standard multiple multipole method. This method can handle elliptically shaped particles due to the change of size and refractive indices, which have been studied under plane wave illumination in two and three dimensional multiple multipole method. Because of its fast and good convergence, the results obtained from simulation are highly accurate and reliable. The simulation time is less than minute for two and three dimension. Therefore, the proposed method is found to be computationally efficient, fast and accurate.
Modular multiple sensors information management for computer-integrated surgery.
Vaccarella, Alberto; Enquobahrie, Andinet; Ferrigno, Giancarlo; Momi, Elena De
2012-09-01
In the past 20 years, technological advancements have modified the concept of modern operating rooms (ORs) with the introduction of computer-integrated surgery (CIS) systems, which promise to enhance the outcomes, safety and standardization of surgical procedures. With CIS, different types of sensor (mainly position-sensing devices, force sensors and intra-operative imaging devices) are widely used. Recently, the need for a combined use of different sensors raised issues related to synchronization and spatial consistency of data from different sources of information. In this study, we propose a centralized, multi-sensor management software architecture for a distributed CIS system, which addresses sensor information consistency in both space and time. The software was developed as a data server module in a client-server architecture, using two open-source software libraries: Image-Guided Surgery Toolkit (IGSTK) and OpenCV. The ROBOCAST project (FP7 ICT 215190), which aims at integrating robotic and navigation devices and technologies in order to improve the outcome of the surgical intervention, was used as the benchmark. An experimental protocol was designed in order to prove the feasibility of a centralized module for data acquisition and to test the application latency when dealing with optical and electromagnetic tracking systems and ultrasound (US) imaging devices. Our results show that a centralized approach is suitable for minimizing synchronization errors; latency in the client-server communication was estimated to be 2 ms (median value) for tracking systems and 40 ms (median value) for US images. The proposed centralized approach proved to be adequate for neurosurgery requirements. Latency introduced by the proposed architecture does not affect tracking system performance in terms of frame rate and limits US images frame rate at 25 fps, which is acceptable for providing visual feedback to the surgeon in the OR. Copyright © 2012 John Wiley & Sons, Ltd.
New or improved computational methods and advanced reactor design
Nakagawa, Masayuki; Takeda, Toshikazu; Ushio, Tadashi
1997-01-01
Nuclear computational method has been studied continuously up to date, as a fundamental technology supporting the nuclear development. At present, research on computational method according to new theory and the calculating method thought to be difficult to practise are also continued actively to find new development due to splendid improvement of features of computer. In Japan, many light water type reactors are now in operations, new computational methods are induced for nuclear design, and a lot of efforts are concentrated for intending to more improvement of economics and safety. In this paper, some new research results on the nuclear computational methods and their application to nuclear design of the reactor were described for introducing recent trend of the nuclear design of the reactor. 1) Advancement of the computational method, 2) Reactor core design and management of the light water reactor, and 3) Nuclear design of the fast reactor. (G.K.)
A computer method for spectral classification
Appenzeller, I.; Zekl, H.
1978-01-01
The authors describe the start of an attempt to improve the accuracy of spectroscopic parallaxes by evaluating spectroscopic temperature and luminosity criteria such as those of the MK classification spectrograms which were analyzed automatically by means of a suitable computer program. (Auth.)
Computational structural biology: methods and applications
Schwede, Torsten; Peitsch, Manuel Claude
2008-01-01
... sequencing reinforced the observation that structural information is needed to understand the detailed function and mechanism of biological molecules such as enzyme reactions and molecular recognition events. Furthermore, structures are obviously key to the design of molecules with new or improved functions. In this context, computational structural biology...
A novel method for producing multiple ionization of noble gas
Wang Li; Li Haiyang; Dai Dongxu; Bai Jiling; Lu Richang
1997-01-01
We introduce a novel method for producing multiple ionization of He, Ne, Ar, Kr and Xe. A nanosecond pulsed electron beam with large number density, which could be energy-controlled, was produced by incidence a focused 308 nm laser beam onto a stainless steel grid. On Time-of-Flight Mass Spectrometer, using this electron beam, we obtained multiple ionization of noble gas He, Ne, Ar and Xe. Time of fight mass spectra of these ions were given out. These ions were supposed to be produced by step by step ionization of the gas atoms by electron beam impact. This method may be used as a ideal soft ionizing point ion source in Time of Flight Mass Spectrometer
Measuring multiple residual-stress components using the contour method and multiple cuts
Prime, Michael B [Los Alamos National Laboratory; Swenson, Hunter [Los Alamos National Laboratory; Pagliaro, Pierluigi [U. PALERMO; Zuccarello, Bernardo [U. PALERMO
2009-01-01
The conventional contour method determines one component of stress over the cross section of a part. The part is cut into two, the contour of the exposed surface is measured, and Bueckner's superposition principle is analytically applied to calculate stresses. In this paper, the contour method is extended to the measurement of multiple stress components by making multiple cuts with subsequent applications of superposition. The theory and limitations are described. The theory is experimentally tested on a 316L stainless steel disk with residual stresses induced by plastically indenting the central portion of the disk. The stress results are validated against independent measurements using neutron diffraction. The theory has implications beyond just multiple cuts. The contour method measurements and calculations for the first cut reveal how the residual stresses have changed throughout the part. Subsequent measurements of partially relaxed stresses by other techniques, such as laboratory x-rays, hole drilling, or neutron or synchrotron diffraction, can be superimposed back to the original state of the body.
Recent advances in computational structural reliability analysis methods
Thacker, Ben H.; Wu, Y.-T.; Millwater, Harry R.; Torng, Tony Y.; Riha, David S.
1993-10-01
The goal of structural reliability analysis is to determine the probability that the structure will adequately perform its intended function when operating under the given environmental conditions. Thus, the notion of reliability admits the possibility of failure. Given the fact that many different modes of failure are usually possible, achievement of this goal is a formidable task, especially for large, complex structural systems. The traditional (deterministic) design methodology attempts to assure reliability by the application of safety factors and conservative assumptions. However, the safety factor approach lacks a quantitative basis in that the level of reliability is never known and usually results in overly conservative designs because of compounding conservatisms. Furthermore, problem parameters that control the reliability are not identified, nor their importance evaluated. A summary of recent advances in computational structural reliability assessment is presented. A significant level of activity in the research and development community was seen recently, much of which was directed towards the prediction of failure probabilities for single mode failures. The focus is to present some early results and demonstrations of advanced reliability methods applied to structural system problems. This includes structures that can fail as a result of multiple component failures (e.g., a redundant truss), or structural components that may fail due to multiple interacting failure modes (e.g., excessive deflection, resonate vibration, or creep rupture). From these results, some observations and recommendations are made with regard to future research needs.
Soft computing methods for geoidal height transformation
Akyilmaz, O.; Özlüdemir, M. T.; Ayan, T.; Çelik, R. N.
2009-07-01
Soft computing techniques, such as fuzzy logic and artificial neural network (ANN) approaches, have enabled researchers to create precise models for use in many scientific and engineering applications. Applications that can be employed in geodetic studies include the estimation of earth rotation parameters and the determination of mean sea level changes. Another important field of geodesy in which these computing techniques can be applied is geoidal height transformation. We report here our use of a conventional polynomial model, the Adaptive Network-based Fuzzy (or in some publications, Adaptive Neuro-Fuzzy) Inference System (ANFIS), an ANN and a modified ANN approach to approximate geoid heights. These approximation models have been tested on a number of test points. The results obtained through the transformation processes from ellipsoidal heights into local levelling heights have also been compared.
Measurement of subcritical multiplication by the interval distribution method
Nelson, G.W.
1985-01-01
The prompt decay constant or the subcritical neutron multiplication may be determined by measuring the distribution of the time intervals between successive neutron counts. The distribution data is analyzed by least-squares fitting to a theoretical distribution function derived from a point reactor probability model. Published results of measurements with one- and two-detector systems are discussed. Data collection times are shorter, and statistical errors are smaller the nearer the system is to delayed critical. Several of the measurements indicate that a shorter data collection time and higher accuracy are possible with the interval distribution method than with the Feynman variance method
Soft Computing Methods in Design of Superalloys
Cios, K. J.; Berke, L.; Vary, A.; Sharma, S.
1996-01-01
Soft computing techniques of neural networks and genetic algorithms are used in the design of superalloys. The cyclic oxidation attack parameter K(sub a), generated from tests at NASA Lewis Research Center, is modelled as a function of the superalloy chemistry and test temperature using a neural network. This model is then used in conjunction with a genetic algorithm to obtain an optimized superalloy composition resulting in low K(sub a) values.
Statistical methods and computing for big data
Wang, Chun; Chen, Ming-Hui; Schifano, Elizabeth; Wu, Jing
2016-01-01
Big data are data on a massive scale in terms of volume, intensity, and complexity that exceed the capacity of standard analytic tools. They present opportunities as well as challenges to statisticians. The role of computational statisticians in scientific discovery from big data analyses has been under-recognized even by peer statisticians. This article summarizes recent methodological and software developments in statistics that address the big data challenges. Methodologies are grouped into three classes: subsampling-based, divide and conquer, and online updating for stream data. As a new contribution, the online updating approach is extended to variable selection with commonly used criteria, and their performances are assessed in a simulation study with stream data. Software packages are summarized with focuses on the open source R and R packages, covering recent tools that help break the barriers of computer memory and computing power. Some of the tools are illustrated in a case study with a logistic regression for the chance of airline delay. PMID:27695593
Statistical methods and computing for big data.
Wang, Chun; Chen, Ming-Hui; Schifano, Elizabeth; Wu, Jing; Yan, Jun
2016-01-01
Big data are data on a massive scale in terms of volume, intensity, and complexity that exceed the capacity of standard analytic tools. They present opportunities as well as challenges to statisticians. The role of computational statisticians in scientific discovery from big data analyses has been under-recognized even by peer statisticians. This article summarizes recent methodological and software developments in statistics that address the big data challenges. Methodologies are grouped into three classes: subsampling-based, divide and conquer, and online updating for stream data. As a new contribution, the online updating approach is extended to variable selection with commonly used criteria, and their performances are assessed in a simulation study with stream data. Software packages are summarized with focuses on the open source R and R packages, covering recent tools that help break the barriers of computer memory and computing power. Some of the tools are illustrated in a case study with a logistic regression for the chance of airline delay.
A permutation-based multiple testing method for time-course microarray experiments
George Stephen L
2009-10-01
Full Text Available Abstract Background Time-course microarray experiments are widely used to study the temporal profiles of gene expression. Storey et al. (2005 developed a method for analyzing time-course microarray studies that can be applied to discovering genes whose expression trajectories change over time within a single biological group, or those that follow different time trajectories among multiple groups. They estimated the expression trajectories of each gene using natural cubic splines under the null (no time-course and alternative (time-course hypotheses, and used a goodness of fit test statistic to quantify the discrepancy. The null distribution of the statistic was approximated through a bootstrap method. Gene expression levels in microarray data are often complicatedly correlated. An accurate type I error control adjusting for multiple testing requires the joint null distribution of test statistics for a large number of genes. For this purpose, permutation methods have been widely used because of computational ease and their intuitive interpretation. Results In this paper, we propose a permutation-based multiple testing procedure based on the test statistic used by Storey et al. (2005. We also propose an efficient computation algorithm. Extensive simulations are conducted to investigate the performance of the permutation-based multiple testing procedure. The application of the proposed method is illustrated using the Caenorhabditis elegans dauer developmental data. Conclusion Our method is computationally efficient and applicable for identifying genes whose expression levels are time-dependent in a single biological group and for identifying the genes for which the time-profile depends on the group in a multi-group setting.
Yanjushkin, V.A.
1991-01-01
At developing new methods of non-destructive determination of plutonium full mass in nuclear materials and products being involved in uranium -plutonium fuel cycle by its intrinsic neutron radiation, it may be useful to know not only separate moments but the multiplicity distribution law itself of neutron leaving this material surface using the following as parameters - firstly, unconditional multiplicity distribution laws of neutrons formed in spontaneous and induced fission acts of the given fissionable material corresponding nuclei and unconditional multiplicity distribution law of neutrons caused by (α,n) reactions at light nuclei of some elements which compose this material chemical structure; -secondly, probability of induced fission of this material nuclei by an incident neutron of any nature formed during the previous fissions or(α,n) reactions. An attempt to develop similar theory has been undertaken. Here the author proposes his approach to this problem. The main advantage of this approach, to our mind, consists in its mathematical simplicity and easy realization at the computer. In principle, the given model guarantees any good accuracy at any real value of induced fission probability without limitations dealing with physico-chemical composition of nuclear material
Xu, Qun; Wang, Xianchao; Xu, Chao
2017-06-01
Multiplication with traditional electronic computers is faced with a low calculating accuracy and a long computation time delay. To overcome these problems, the modified signed digit (MSD) multiplication routine is established based on the MSD system and the carry-free adder. Also, its parallel algorithm and optimization techniques are studied in detail. With the help of a ternary optical computer's characteristics, the structured data processor is designed especially for the multiplication routine. Several ternary optical operators are constructed to perform M transformations and summations in parallel, which has accelerated the iterative process of multiplication. In particular, the routine allocates data bits of the ternary optical processor based on digits of multiplication input, so the accuracy of the calculation results can always satisfy the users. Finally, the routine is verified by simulation experiments, and the results are in full compliance with the expectations. Compared with an electronic computer, the MSD multiplication routine is not only good at dealing with large-value data and high-precision arithmetic, but also maintains lower power consumption and fewer calculating delays.
Dong, Yumin; Xiao, Shufen; Ma, Hongyang; Chen, Libo
2016-12-01
Cloud computing and big data have become the developing engine of current information technology (IT) as a result of the rapid development of IT. However, security protection has become increasingly important for cloud computing and big data, and has become a problem that must be solved to develop cloud computing. The theft of identity authentication information remains a serious threat to the security of cloud computing. In this process, attackers intrude into cloud computing services through identity authentication information, thereby threatening the security of data from multiple perspectives. Therefore, this study proposes a model for cloud computing protection and management based on quantum authentication, introduces the principle of quantum authentication, and deduces the quantum authentication process. In theory, quantum authentication technology can be applied in cloud computing for security protection. This technology cannot be cloned; thus, it is more secure and reliable than classical methods.
A global calibration method for multiple vision sensors based on multiple targets
Liu, Zhen; Zhang, Guangjun; Wei, Zhenzhong; Sun, Junhua
2011-01-01
The global calibration of multiple vision sensors (MVS) has been widely studied in the last two decades. In this paper, we present a global calibration method for MVS with non-overlapping fields of view (FOVs) using multiple targets (MT). MT is constructed by fixing several targets, called sub-targets, together. The mutual coordinate transformations between sub-targets need not be known. The main procedures of the proposed method are as follows: one vision sensor is selected from MVS to establish the global coordinate frame (GCF). MT is placed in front of the vision sensors for several (at least four) times. Using the constraint that the relative positions of all sub-targets are invariant, the transformation matrix from the coordinate frame of each vision sensor to GCF can be solved. Both synthetic and real experiments are carried out and good result is obtained. The proposed method has been applied to several real measurement systems and shown to be both flexible and accurate. It can serve as an attractive alternative to existing global calibration methods
Field evaluation of personal sampling methods for multiple bioaerosols.
Wang, Chi-Hsun; Chen, Bean T; Han, Bor-Cheng; Liu, Andrew Chi-Yeu; Hung, Po-Chen; Chen, Chih-Yong; Chao, Hsing Jasmine
2015-01-01
Ambient bioaerosols are ubiquitous in the daily environment and can affect health in various ways. However, few studies have been conducted to comprehensively evaluate personal bioaerosol exposure in occupational and indoor environments because of the complex composition of bioaerosols and the lack of standardized sampling/analysis methods. We conducted a study to determine the most efficient collection/analysis method for the personal exposure assessment of multiple bioaerosols. The sampling efficiencies of three filters and four samplers were compared. According to our results, polycarbonate (PC) filters had the highest relative efficiency, particularly for bacteria. Side-by-side sampling was conducted to evaluate the three filter samplers (with PC filters) and the NIOSH Personal Bioaerosol Cyclone Sampler. According to the results, the Button Aerosol Sampler and the IOM Inhalable Dust Sampler had the highest relative efficiencies for fungi and bacteria, followed by the NIOSH sampler. Personal sampling was performed in a pig farm to assess occupational bioaerosol exposure and to evaluate the sampling/analysis methods. The Button and IOM samplers yielded a similar performance for personal bioaerosol sampling at the pig farm. However, the Button sampler is more likely to be clogged at high airborne dust concentrations because of its higher flow rate (4 L/min). Therefore, the IOM sampler is a more appropriate choice for performing personal sampling in environments with high dust levels. In summary, the Button and IOM samplers with PC filters are efficient sampling/analysis methods for the personal exposure assessment of multiple bioaerosols.
Field evaluation of personal sampling methods for multiple bioaerosols.
Chi-Hsun Wang
Full Text Available Ambient bioaerosols are ubiquitous in the daily environment and can affect health in various ways. However, few studies have been conducted to comprehensively evaluate personal bioaerosol exposure in occupational and indoor environments because of the complex composition of bioaerosols and the lack of standardized sampling/analysis methods. We conducted a study to determine the most efficient collection/analysis method for the personal exposure assessment of multiple bioaerosols. The sampling efficiencies of three filters and four samplers were compared. According to our results, polycarbonate (PC filters had the highest relative efficiency, particularly for bacteria. Side-by-side sampling was conducted to evaluate the three filter samplers (with PC filters and the NIOSH Personal Bioaerosol Cyclone Sampler. According to the results, the Button Aerosol Sampler and the IOM Inhalable Dust Sampler had the highest relative efficiencies for fungi and bacteria, followed by the NIOSH sampler. Personal sampling was performed in a pig farm to assess occupational bioaerosol exposure and to evaluate the sampling/analysis methods. The Button and IOM samplers yielded a similar performance for personal bioaerosol sampling at the pig farm. However, the Button sampler is more likely to be clogged at high airborne dust concentrations because of its higher flow rate (4 L/min. Therefore, the IOM sampler is a more appropriate choice for performing personal sampling in environments with high dust levels. In summary, the Button and IOM samplers with PC filters are efficient sampling/analysis methods for the personal exposure assessment of multiple bioaerosols.
Tensor network method for reversible classical computation
Yang, Zhi-Cheng; Kourtis, Stefanos; Chamon, Claudio; Mucciolo, Eduardo R.; Ruckenstein, Andrei E.
2018-03-01
We develop a tensor network technique that can solve universal reversible classical computational problems, formulated as vertex models on a square lattice [Nat. Commun. 8, 15303 (2017), 10.1038/ncomms15303]. By encoding the truth table of each vertex constraint in a tensor, the total number of solutions compatible with partial inputs and outputs at the boundary can be represented as the full contraction of a tensor network. We introduce an iterative compression-decimation (ICD) scheme that performs this contraction efficiently. The ICD algorithm first propagates local constraints to longer ranges via repeated contraction-decomposition sweeps over all lattice bonds, thus achieving compression on a given length scale. It then decimates the lattice via coarse-graining tensor contractions. Repeated iterations of these two steps gradually collapse the tensor network and ultimately yield the exact tensor trace for large systems, without the need for manual control of tensor dimensions. Our protocol allows us to obtain the exact number of solutions for computations where a naive enumeration would take astronomically long times.
Advanced Computational Methods for Monte Carlo Calculations
Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2018-01-12
This course is intended for graduate students who already have a basic understanding of Monte Carlo methods. It focuses on advanced topics that may be needed for thesis research, for developing new state-of-the-art methods, or for working with modern production Monte Carlo codes.
Computational methods for two-phase flow and particle transport
Lee, Wen Ho
2013-01-01
This book describes mathematical formulations and computational methods for solving two-phase flow problems with a computer code that calculates thermal hydraulic problems related to light water and fast breeder reactors. The physical model also handles the particle and gas flow problems that arise from coal gasification and fluidized beds. The second part of this book deals with the computational methods for particle transport.
Reference depth for geostrophic computation - A new method
Varkey, M.J.; Sastry, J.S.
Various methods are available for the determination of reference depth for geostrophic computation. A new method based on the vertical profiles of mean and variance of the differences of mean specific volume anomaly (delta x 10) for different layers...
Lattice Boltzmann method fundamentals and engineering applications with computer codes
Mohamad, A A
2014-01-01
Introducing the Lattice Boltzmann Method in a readable manner, this book provides detailed examples with complete computer codes. It avoids the most complicated mathematics and physics without scarifying the basic fundamentals of the method.
An Augmented Fast Marching Method for Computing Skeletons and Centerlines
Telea, Alexandru; Wijk, Jarke J. van
2002-01-01
We present a simple and robust method for computing skeletons for arbitrary planar objects and centerlines for 3D objects. We augment the Fast Marching Method (FMM) widely used in level set applications by computing the paramterized boundary location every pixel came from during the boundary
Classical versus Computer Algebra Methods in Elementary Geometry
Pech, Pavel
2005-01-01
Computer algebra methods based on results of commutative algebra like Groebner bases of ideals and elimination of variables make it possible to solve complex, elementary and non elementary problems of geometry, which are difficult to solve using a classical approach. Computer algebra methods permit the proof of geometric theorems, automatic…
Methods for teaching geometric modelling and computer graphics
Rotkov, S.I.; Faitel`son, Yu. Ts.
1992-05-01
This paper considers methods for teaching the methods and algorithms of geometric modelling and computer graphics to programmers, designers and users of CAD and computer-aided research systems. There is a bibliography that can be used to prepare lectures and practical classes. 37 refs., 1 tab.
Borst, de R.
2008-01-01
Novel experimental possibilities together with improvements in computer hardware as well as new concepts in computational mathematics and mechanics in particular multiscale methods are now, in principle, making it possible to derive and compute phenomena and material parameters at a macroscopic
Le, Anh H.; Park, Young W.; Ma, Kevin; Jacobs, Colin; Liu, Brent J.
2010-03-01
Multiple Sclerosis (MS) is a progressive neurological disease affecting myelin pathways in the brain. Multiple lesions in the white matter can cause paralysis and severe motor disabilities of the affected patient. To solve the issue of inconsistency and user-dependency in manual lesion measurement of MRI, we have proposed a 3-D automated lesion quantification algorithm to enable objective and efficient lesion volume tracking. The computer-aided detection (CAD) of MS, written in MATLAB, utilizes K-Nearest Neighbors (KNN) method to compute the probability of lesions on a per-voxel basis. Despite the highly optimized algorithm of imaging processing that is used in CAD development, MS CAD integration and evaluation in clinical workflow is technically challenging due to the requirement of high computation rates and memory bandwidth in the recursive nature of the algorithm. In this paper, we present the development and evaluation of using a computing engine in the graphical processing unit (GPU) with MATLAB for segmentation of MS lesions. The paper investigates the utilization of a high-end GPU for parallel computing of KNN in the MATLAB environment to improve algorithm performance. The integration is accomplished using NVIDIA's CUDA developmental toolkit for MATLAB. The results of this study will validate the practicality and effectiveness of the prototype MS CAD in a clinical setting. The GPU method may allow MS CAD to rapidly integrate in an electronic patient record or any disease-centric health care system.
Xi Yang
2015-04-01
Full Text Available OBJECTIVES: To investigate the prevalence, extent, severity, and features of coronary artery lesions in stable patients with multiple cardiovascular risk factors. METHODS: Seventy-seven patients with more than 3 cardiovascular risk factors were suspected of having coronary artery disease. Patients with high-risk factors and 39 controls with no risk factors were enrolled in the study. The related risk factors included hypertension, impaired glucose tolerance, dyslipidemia, smoking history, and overweight. The characteristics of coronary lesions were identified and evaluated by 64-slice coronary computed tomography angiography. RESULTS: The incidence of coronary atherosclerosis was higher in the high-risk group than in the no-risk group. The involved branches of the coronary artery, the diffusivity of the lesion, the degree of stenosis, and the nature of the plaques were significantly more severe in the high-risk group compared with the no-risk group (all p < 0.05. CONCLUSION: Among stable individuals with high-risk factors, early coronary artery lesions are common and severe. Computed tomography has promising value for the early screening of coronary lesions.
Murni, Bustamam, A.; Ernastuti, Handhika, T.; Kerami, D.
2017-07-01
Calculation of the matrix-vector multiplication in the real-world problems often involves large matrix with arbitrary size. Therefore, parallelization is needed to speed up the calculation process that usually takes a long time. Graph partitioning techniques that have been discussed in the previous studies cannot be used to complete the parallelized calculation of matrix-vector multiplication with arbitrary size. This is due to the assumption of graph partitioning techniques that can only solve the square and symmetric matrix. Hypergraph partitioning techniques will overcome the shortcomings of the graph partitioning technique. This paper addresses the efficient parallelization of matrix-vector multiplication through hypergraph partitioning techniques using CUDA GPU-based parallel computing. CUDA (compute unified device architecture) is a parallel computing platform and programming model that was created by NVIDIA and implemented by the GPU (graphics processing unit).
Hesitant fuzzy methods for multiple criteria decision analysis
Zhang, Xiaolu
2017-01-01
The book offers a comprehensive introduction to methods for solving multiple criteria decision making and group decision making problems with hesitant fuzzy information. It reports on the authors’ latest research, as well as on others’ research, providing readers with a complete set of decision making tools, such as hesitant fuzzy TOPSIS, hesitant fuzzy TODIM, hesitant fuzzy LINMAP, hesitant fuzzy QUALIFEX, and the deviation modeling approach with heterogeneous fuzzy information. The main focus is on decision making problems in which the criteria values and/or the weights of criteria are not expressed in crisp numbers but are more suitable to be denoted as hesitant fuzzy elements. The largest part of the book is devoted to new methods recently developed by the authors to solve decision making problems in situations where the available information is vague or hesitant. These methods are presented in detail, together with their application to different type of decision-making problems. All in all, the book ...
Correlation expansion: a powerful alternative multiple scattering calculation method
Zhao Haifeng; Wu Ziyu; Sebilleau, Didier
2008-01-01
We introduce a powerful alternative expansion method to perform multiple scattering calculations. In contrast to standard MS series expansion, where the scattering contributions are grouped in terms of scattering order and may diverge in the low energy region, this expansion, called correlation expansion, partitions the scattering process into contributions from different small atom groups and converges at all energies. It converges faster than MS series expansion when the latter is convergent. Furthermore, it takes less memory than the full MS method so it can be used in the near edge region without any divergence problem, even for large clusters. The correlation expansion framework we derive here is very general and can serve to calculate all the elements of the scattering path operator matrix. Photoelectron diffraction calculations in a cluster containing 23 atoms are presented to test the method and compare it to full MS and standard MS series expansion
Computational Methods for Conformational Sampling of Biomolecules
Bottaro, Sandro
mathematical approach to a classic geometrical problem in protein simulations, and demonstrated its superiority compared to existing approaches. Secondly, we have constructed a more accurate implicit model of the aqueous environment, which is of fundamental importance in protein chemistry. This model......Proteins play a fundamental role in virtually every process within living organisms. For example, some proteins act as enzymes, catalyzing a wide range of reactions necessary for life, others mediate the cell interaction with the surrounding environment and still others have regulatory functions...... is computationally much faster than models where water molecules are represented explicitly. Finally, in collaboration with the group of structural bioinformatics at the Department of Biology (KU), we have applied these techniques in the context of modeling of protein structure and flexibility from low...
Computational Method for Atomistic-Continuum Homogenization
Chung, Peter
2002-01-01
The homogenization method is used as a framework for developing a multiscale system of equations involving atoms at zero temperature at the small scale and continuum mechanics at the very large scale...
Semi-coarsening multigrid methods for parallel computing
Jones, J.E.
1996-12-31
Standard multigrid methods are not well suited for problems with anisotropic coefficients which can occur, for example, on grids that are stretched to resolve a boundary layer. There are several different modifications of the standard multigrid algorithm that yield efficient methods for anisotropic problems. In the paper, we investigate the parallel performance of these multigrid algorithms. Multigrid algorithms which work well for anisotropic problems are based on line relaxation and/or semi-coarsening. In semi-coarsening multigrid algorithms a grid is coarsened in only one of the coordinate directions unlike standard or full-coarsening multigrid algorithms where a grid is coarsened in each of the coordinate directions. When both semi-coarsening and line relaxation are used, the resulting multigrid algorithm is robust and automatic in that it requires no knowledge of the nature of the anisotropy. This is the basic multigrid algorithm whose parallel performance we investigate in the paper. The algorithm is currently being implemented on an IBM SP2 and its performance is being analyzed. In addition to looking at the parallel performance of the basic semi-coarsening algorithm, we present algorithmic modifications with potentially better parallel efficiency. One modification reduces the amount of computational work done in relaxation at the expense of using multiple coarse grids. This modification is also being implemented with the aim of comparing its performance to that of the basic semi-coarsening algorithm.
Gong, Jian; Lou, Shuntian; Guo, Yiduo
2016-04-01
An estimation of signal parameters via a rotational invariance techniques-like (ESPRIT-like) algorithm is proposed to estimate the direction of arrival and direction of departure for bistatic multiple-input multiple-output (MIMO) radar. The properties of a noncircular signal and Euler's formula are first exploited to establish a real-valued bistatic MIMO radar array data, which is composed of sine and cosine data. Then the receiving/transmitting selective matrices are constructed to obtain the receiving/transmitting rotational invariance factors. Since the rotational invariance factor is a cosine function, symmetrical mirror angle ambiguity may occur. Finally, a maximum likelihood function is used to avoid the estimation ambiguities. Compared with the existing ESPRIT, the proposed algorithm can save about 75% of computational load owing to the real-valued ESPRIT algorithm. Simulation results confirm the effectiveness of the ESPRIT-like algorithm.
Study on validation method for femur finite element model under multiple loading conditions
Guan, Fengjiao; Zhang, Guanjun; Liu, Jie; Wang, Shujing; Luo, Xu
2018-03-01
Acquisition of accurate and reliable constitutive parameters related to bio-tissue materials was beneficial to improve biological fidelity of a Finite Element (FE) model and predict impact damages more effectively. In this paper, a femur FE model was established under multiple loading conditions with diverse impact positions. Then, based on sequential response surface method and genetic algorithms, the material parameters identification was transformed to a multi-response optimization problem. Finally, the simulation results successfully coincided with force-displacement curves obtained by numerous experiments. Thus, computational accuracy and efficiency of the entire inverse calculation process were enhanced. This method was able to effectively reduce the computation time in the inverse process of material parameters. Meanwhile, the material parameters obtained by the proposed method achieved higher accuracy.
Instrument design optimization with computational methods
Moore, Michael H. [Old Dominion Univ., Norfolk, VA (United States)
2017-08-01
Using Finite Element Analysis to approximate the solution of differential equations, two different instruments in experimental Hall C at the Thomas Jefferson National Accelerator Facility are analyzed. The time dependence of density uctuations from the liquid hydrogen (LH2) target used in the Q_{wea}k experiment (2011-2012) are studied with Computational Fluid Dynamics (CFD) and the simulation results compared to data from the experiment. The 2.5 kW liquid hydrogen target was the highest power LH2 target in the world and the first to be designed with CFD at Jefferson Lab. The first complete magnetic field simulation of the Super High Momentum Spectrometer (SHMS) is presented with a focus on primary electron beam deflection downstream of the target. The SHMS consists of a superconducting horizontal bending magnet (HB) and three superconducting quadrupole magnets. The HB allows particles scattered at an angle of 5:5 deg to the beam line to be steered into the quadrupole magnets which make up the optics of the spectrometer. Without mitigation, remnant fields from the SHMS may steer the unscattered beam outside of the acceptable envelope on the beam dump and limit beam operations at small scattering angles. A solution is proposed using optimal placement of a minimal amount of shielding iron around the beam line.
Computer methods in physics 250 problems with guided solutions
Landau, Rubin H
2018-01-01
Our future scientists and professionals must be conversant in computational techniques. In order to facilitate integration of computer methods into existing physics courses, this textbook offers a large number of worked examples and problems with fully guided solutions in Python as well as other languages (Mathematica, Java, C, Fortran, and Maple). Its also intended as a self-study guide for learning how to use computer methods in physics. The authors include an introductory chapter on numerical tools and indication of computational and physics difficulty level for each problem.
Multiple-time-stepping generalized hybrid Monte Carlo methods
Escribano, Bruno, E-mail: bescribano@bcamath.org [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); Akhmatskaya, Elena [BCAM—Basque Center for Applied Mathematics, E-48009 Bilbao (Spain); IKERBASQUE, Basque Foundation for Science, E-48013 Bilbao (Spain); Reich, Sebastian [Universität Potsdam, Institut für Mathematik, D-14469 Potsdam (Germany); Azpiroz, Jon M. [Kimika Fakultatea, Euskal Herriko Unibertsitatea (UPV/EHU) and Donostia International Physics Center (DIPC), P.K. 1072, Donostia (Spain)
2015-01-01
Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2–4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC). The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.
Electromagnetic computation methods for lightning surge protection studies
Baba, Yoshihiro
2016-01-01
This book is the first to consolidate current research and to examine the theories of electromagnetic computation methods in relation to lightning surge protection. The authors introduce and compare existing electromagnetic computation methods such as the method of moments (MOM), the partial element equivalent circuit (PEEC), the finite element method (FEM), the transmission-line modeling (TLM) method, and the finite-difference time-domain (FDTD) method. The application of FDTD method to lightning protection studies is a topic that has matured through many practical applications in the past decade, and the authors explain the derivation of Maxwell's equations required by the FDTD, and modeling of various electrical components needed in computing lightning electromagnetic fields and surges with the FDTD method. The book describes the application of FDTD method to current and emerging problems of lightning surge protection of continuously more complex installations, particularly in critical infrastructures of e...
Three-dimensional protein structure prediction: Methods and computational strategies.
Dorn, Márcio; E Silva, Mariel Barbachan; Buriol, Luciana S; Lamb, Luis C
2014-10-12
A long standing problem in structural bioinformatics is to determine the three-dimensional (3-D) structure of a protein when only a sequence of amino acid residues is given. Many computational methodologies and algorithms have been proposed as a solution to the 3-D Protein Structure Prediction (3-D-PSP) problem. These methods can be divided in four main classes: (a) first principle methods without database information; (b) first principle methods with database information; (c) fold recognition and threading methods; and (d) comparative modeling methods and sequence alignment strategies. Deterministic computational techniques, optimization techniques, data mining and machine learning approaches are typically used in the construction of computational solutions for the PSP problem. Our main goal with this work is to review the methods and computational strategies that are currently used in 3-D protein prediction. Copyright © 2014 Elsevier Ltd. All rights reserved.
Novitsky, Andrey; de Lasson, Jakob Rosenkrantz; Frandsen, Lars Hagedorn
2017-01-01
Five state-of-the-art computational methods are benchmarked by computing quality factors and resonance wavelengths in photonic crystal membrane L5 and L9 line defect cavities. The convergence of the methods with respect to resolution, degrees of freedom and number of modes is investigated. Specia...
Ho, Pang-Yen; Chuang, Guo-Syong; Chao, An-Chong; Li, Hsing-Ya
2005-05-01
The capacity of complex biochemical reaction networks (consisting of 11 coupled non-linear ordinary differential equations) to show multiple steady states, was investigated. The system involved esterification of ethanol and oleic acid by lipase in an isothermal continuous stirred tank reactor (CSTR). The Deficiency One Algorithm and the Subnetwork Analysis were applied to determine the steady state multiplicity. A set of rate constants and two corresponding steady states are computed. The phenomena of bistability, hysteresis and bifurcation are discussed. Moreover, the capacity of steady state multiplicity is extended to the family of the studied reaction networks.
Wainwright, Carroll L.
2012-09-01
I present a numerical package (CosmoTransitions) for analyzing finite-temperature cosmological phase transitions driven by single or multiple scalar fields. The package analyzes the different vacua of a theory to determine their critical temperatures (where the vacuum energy levels are degenerate), their supercooling temperatures, and the bubble wall profiles which separate the phases and describe their tunneling dynamics. I introduce a new method of path deformation to find the profiles of both thin- and thick-walled bubbles. CosmoTransitions is freely available for public use.Program summaryProgram Title: CosmoTransitionsCatalogue identifier: AEML_v1_0Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEML_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 8775No. of bytes in distributed program, including test data, etc.: 621096Distribution format: tar.gzProgramming language: Python.Computer: Developed on a 2009 MacBook Pro. No computer-specific optimization was performed.Operating system: Designed and tested on Mac OS X 10.6.8. Compatible with any OS with Python installed.RAM: Approximately 50 MB, mostly for loading plotting packages.Classification: 1.9, 11.1.External routines: SciPy, NumPy, matplotLibNature of problem: I describe a program to analyze early-Universe finite-temperature phase transitions with multiple scalar fields. The goal is to analyze the phase structure of an input theory, determine the amount of supercooling at each phase transition, and find the bubble-wall profiles of the nucleated bubbles that drive the transitions.Solution method: To find the bubble-wall profile, the program assumes that tunneling happens along a fixed path in field space. This reduces the equations of motion to one dimension, which can then be solved using the overshoot
Computational Methods for Physicists Compendium for Students
Sirca, Simon
2012-01-01
This book helps advanced undergraduate, graduate and postdoctoral students in their daily work by offering them a compendium of numerical methods. The choice of methods pays significant attention to error estimates, stability and convergence issues as well as to the ways to optimize program execution speeds. Many examples are given throughout the chapters, and each chapter is followed by at least a handful of more comprehensive problems which may be dealt with, for example, on a weekly basis in a one- or two-semester course. In these end-of-chapter problems the physics background is pronounced, and the main text preceding them is intended as an introduction or as a later reference. Less stress is given to the explanation of individual algorithms. It is tried to induce in the reader an own independent thinking and a certain amount of scepticism and scrutiny instead of blindly following readily available commercial tools.
Multiple predictor smoothing methods for sensitivity analysis: Description of techniques
Storlie, Curtis B.; Helton, Jon C.
2008-01-01
The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (i) locally weighted regression (LOESS), (ii) additive models, (iii) projection pursuit regression, and (iv) recursive partitioning regression. Then, in the second and concluding part of this presentation, the indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present
Multiple predictor smoothing methods for sensitivity analysis: Example results
Storlie, Curtis B.; Helton, Jon C.
2008-01-01
The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described in the first part of this presentation: (i) locally weighted regression (LOESS), (ii) additive models, (iii) projection pursuit regression, and (iv) recursive partitioning regression. In this, the second and concluding part of the presentation, the indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present
Integrating Multiple Teaching Methods into a General Chemistry Classroom
Francisco, Joseph S.; Nicoll, Gayle; Trautmann, Marcella
1998-02-01
In addition to the traditional lecture format, three other teaching strategies (class discussions, concept maps, and cooperative learning) were incorporated into a freshman level general chemistry course. Student perceptions of their involvement in each of the teaching methods, as well as their perceptions of the utility of each method were used to assess the effectiveness of the integration of the teaching strategies as received by the students. Results suggest that each strategy serves a unique purpose for the students and increased student involvement in the course. These results indicate that the multiple teaching strategies were well received by the students and that all teaching strategies are necessary for students to get the most out of the course.
Fuzzy multiple objective decision making methods and applications
Lai, Young-Jou
1994-01-01
In the last 25 years, the fuzzy set theory has been applied in many disciplines such as operations research, management science, control theory, artificial intelligence/expert system, etc. In this volume, methods and applications of crisp, fuzzy and possibilistic multiple objective decision making are first systematically and thoroughly reviewed and classified. This state-of-the-art survey provides readers with a capsule look into the existing methods, and their characteristics and applicability to analysis of fuzzy and possibilistic programming problems. To realize practical fuzzy modelling, it presents solutions for real-world problems including production/manufacturing, location, logistics, environment management, banking/finance, personnel, marketing, accounting, agriculture economics and data analysis. This book is a guided tour through the literature in the rapidly growing fields of operations research and decision making and includes the most up-to-date bibliographical listing of literature on the topi...
Measurement method of cardiac computed tomography (CT)
Watanabe, Shigeru; Yamamoto, Hironori; Yumura, Yasuo; Yoshida, Hideo; Morooka, Nobuhiro
1980-01-01
The CT was carried out in 126 cases consisting of 31 normals, 17 cases of mitral stenosis (MS), 8 cases of mitral regurgitation (MR), 11 cases of aortic stenosis (AS), 9 cases of aortic regurgitation (AR), 20 cases of myocardial infarction (MI), 8 cases of atrial septal defect (ASD) and 22 hypertensives. The 20-second scans were performed every 1.5 cm from the 2nd intercostal space to the 5th or 6th intercostal space. The computed tomograms obtained were classified into 8 levels by cross-sectional anatomy; levels of (1) the aortic arch, (2) just beneath the aortic arch, (3) the pulmonary artery bifurcation, (4) the right atrial appendage or the upper right atrium, (5) the aortic root, (6) the upper left ventricle, (7) the mid left ventricle, and (8) the lower left ventricle. The diameter (anteroposterior and transverse) and cross-sectional area were measured about ascending aorta (Ao), descending aorta (AoD), superior vena cava (SVC), inferoir vena cava (IVC), pulmonary artery branch (PA), main pulmonary artery (mPA), left atrium (LA), right atrium (RA), and right ventricular outflow tract (RVOT) on each level where they were clearly distinguished. However, it was difficult to separate cardiac wall from cardiac cavity because there was little difference of X-ray attenuation coefficient between the myocardium and blood. Therefore, on mid ventricular level, diameter and area about total cardiac shadow were measured, and then cardiac ratios to the thorax were respectively calculated. The normal range of their values was shown in table, and abnormal characteristics in cardiac disease were exhibited in comparison with normal values. In MS, diameter and area in LA were significantly larger than normal. In MS and ASD, all the right cardiac system were larger than normal, especially, RA and SVC in MS, PA and RVOT in ASD. The diameter and area of the aortic root was larger in the order of AR, AS and HT than normal. (author)
Three numerical methods for the computation of the electrostatic energy
Poenaru, D.N.; Galeriu, D.
1975-01-01
The FORTRAN programs for computation of the electrostatic energy of a body with axial symmetry by Lawrence, Hill-Wheeler and Beringer methods are presented in detail. The accuracy, time of computation and the required memory of these methods are tested at various deformations for two simple parametrisations: two overlapping identical spheres and a spheroid. On this basis the field of application of each method is recomended
Eichenberger, Alexandre E; Gschwind, Michael K; Gunnels, John A
2013-11-05
Mechanisms for performing matrix multiplication operations with data pre-conditioning in a high performance computing architecture are provided. A vector load operation is performed to load a first vector operand of the matrix multiplication operation to a first target vector register. A load and splat operation is performed to load an element of a second vector operand and replicating the element to each of a plurality of elements of a second target vector register. A multiply add operation is performed on elements of the first target vector register and elements of the second target vector register to generate a partial product of the matrix multiplication operation. The partial product of the matrix multiplication operation is accumulated with other partial products of the matrix multiplication operation.
Reduced order methods for modeling and computational reduction
Rozza, Gianluigi
2014-01-01
This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics. Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects. This...
Testing and Validation of Computational Methods for Mass Spectrometry.
Gatto, Laurent; Hansen, Kasper D; Hoopmann, Michael R; Hermjakob, Henning; Kohlbacher, Oliver; Beyer, Andreas
2016-03-04
High-throughput methods based on mass spectrometry (proteomics, metabolomics, lipidomics, etc.) produce a wealth of data that cannot be analyzed without computational methods. The impact of the choice of method on the overall result of a biological study is often underappreciated, but different methods can result in very different biological findings. It is thus essential to evaluate and compare the correctness and relative performance of computational methods. The volume of the data as well as the complexity of the algorithms render unbiased comparisons challenging. This paper discusses some problems and challenges in testing and validation of computational methods. We discuss the different types of data (simulated and experimental validation data) as well as different metrics to compare methods. We also introduce a new public repository for mass spectrometric reference data sets ( http://compms.org/RefData ) that contains a collection of publicly available data sets for performance evaluation for a wide range of different methods.
Kim, Yoonsang; Choi, Young-Ku; Emery, Sherry
2013-08-01
Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods' performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages-SAS GLIMMIX Laplace and SuperMix Gaussian quadrature-perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes.
A General Cross-Layer Cloud Scheduling Framework for Multiple IoT Computer Tasks.
Wu, Guanlin; Bao, Weidong; Zhu, Xiaomin; Zhang, Xiongtao
2018-05-23
The diversity of IoT services and applications brings enormous challenges to improving the performance of multiple computer tasks' scheduling in cross-layer cloud computing systems. Unfortunately, the commonly-employed frameworks fail to adapt to the new patterns on the cross-layer cloud. To solve this issue, we design a new computer task scheduling framework for multiple IoT services in cross-layer cloud computing systems. Specifically, we first analyze the features of the cross-layer cloud and computer tasks. Then, we design the scheduling framework based on the analysis and present detailed models to illustrate the procedures of using the framework. With the proposed framework, the IoT services deployed in cross-layer cloud computing systems can dynamically select suitable algorithms and use resources more effectively to finish computer tasks with different objectives. Finally, the algorithms are given based on the framework, and extensive experiments are also given to validate its effectiveness, as well as its superiority.
Developing a multimodal biometric authentication system using soft computing methods.
Malcangi, Mario
2015-01-01
Robust personal authentication is becoming ever more important in computer-based applications. Among a variety of methods, biometric offers several advantages, mainly in embedded system applications. Hard and soft multi-biometric, combined with hard and soft computing methods, can be applied to improve the personal authentication process and to generalize the applicability. This chapter describes the embedded implementation of a multi-biometric (voiceprint and fingerprint) multimodal identification system based on hard computing methods (DSP) for feature extraction and matching, an artificial neural network (ANN) for soft feature pattern matching, and a fuzzy logic engine (FLE) for data fusion and decision.
Computational Simulations and the Scientific Method
Kleb, Bil; Wood, Bill
2005-01-01
As scientific simulation software becomes more complicated, the scientific-software implementor's need for component tests from new model developers becomes more crucial. The community's ability to follow the basic premise of the Scientific Method requires independently repeatable experiments, and model innovators are in the best position to create these test fixtures. Scientific software developers also need to quickly judge the value of the new model, i.e., its cost-to-benefit ratio in terms of gains provided by the new model and implementation risks such as cost, time, and quality. This paper asks two questions. The first is whether other scientific software developers would find published component tests useful, and the second is whether model innovators think publishing test fixtures is a feasible approach.
Computer systems and methods for visualizing data
Stolte, Chris; Hanrahan, Patrick
2013-01-29
A method for forming a visual plot using a hierarchical structure of a dataset. The dataset comprises a measure and a dimension. The dimension consists of a plurality of levels. The plurality of levels form a dimension hierarchy. The visual plot is constructed based on a specification. A first level from the plurality of levels is represented by a first component of the visual plot. A second level from the plurality of levels is represented by a second component of the visual plot. The dataset is queried to retrieve data in accordance with the specification. The data includes all or a portion of the dimension and all or a portion of the measure. The visual plot is populated with the retrieved data in accordance with the specification.
Gadalla, Tahany M.
The equivalence of multiple-choice (MC) and constructed response (discrete) (CR-D) response formats as applied to mathematics computation at grade levels two to six was tested. The difference between total scores from the two response formats was tested for statistical significance, and the factor structure of items in both response formats was…
An algorithm to compute a rule for division problems with multiple references
Sánchez Sánchez, Francisca J.
2012-01-01
Full Text Available In this paper we consider an extension of the classic division problem with claims: Thedivision problem with multiple references. Hinojosa et al. (2012 provide a solution for this type of pro-blems. The aim of this work is to extend their results by proposing an algorithm that calculates allocationsbased on these results. All computational details are provided in the paper.
The MORPG-Based Learning System for Multiple Courses: A Case Study on Computer Science Curriculum
Liu, Kuo-Yu
2015-01-01
This study aimed at developing a Multiplayer Online Role Playing Game-based (MORPG) Learning system which enabled instructors to construct a game scenario and manage sharable and reusable learning content for multiple courses. It used the curriculum of "Introduction to Computer Science" as a study case to assess students' learning…
The computer-aided design of a servo system as a multiple-criteria decision problem
Udink ten Cate, A.J.
1986-01-01
This paper treats the selection of controller gains of a servo system as a multiple-criteria decision problem. In contrast to the usual optimization-based approaches to computer-aided design, inequality constraints are included in the problem as unconstrained objectives. This considerably simplifies
Melendez Rodriguez, J.C.; Ginneken, B. van; Maduskar, P.; Philipsen, R.H.H.M.; Ayles, H.; Sanchez, C.I.
2016-01-01
The major advantage of multiple-instance learning (MIL) applied to a computer-aided detection (CAD) system is that it allows optimizing the latter with case-level labels instead of accurate lesion outlines as traditionally required for a supervised approach. As shown in previous work, a MIL-based
The importance of neurophysiological-Bobath method in multiple sclerosis
Adrian Miler
2018-02-01
Full Text Available Rehabilitation treatment in multiple sclerosis should be carried out continuously, can take place in the hospital, ambulatory as well as environmental conditions. In the traditional approach, it focuses on reducing the symptoms of the disease, such as paresis, spasticity, ataxia, pain, sensory disturbances, speech disorders, blurred vision, fatigue, neurogenic bladder dysfunction, and cognitive impairment. In kinesiotherapy in people with paresis, the most common methods are the (Bobathian method.Improvement can be achieved by developing the ability to maintain a correct posture in various positions (so-called postural alignment, patterns based on corrective and equivalent responses. During the therapy, various techniques are used to inhibit pathological motor patterns and stimulate the reaction. The creators of the method believe that each movement pattern has its own postural system, from which it can be initiated, carried out and effectively controlled. Correct movement can not take place in the wrong position of the body. The physiotherapist discusses with the patient how to perform individual movement patterns, which protects him against spontaneous pathological compensation.The aim of the work is to determine the meaning and application of the Bobath method in the therapy of people with MS
Method for Statically Checking an Object-oriented Computer Program Module
Bierhoff, Kevin M. (Inventor); Aldrich, Jonathan (Inventor)
2012-01-01
A method for statically checking an object-oriented computer program module includes the step of identifying objects within a computer program module, at least one of the objects having a plurality of references thereto, possibly from multiple clients. A discipline of permissions is imposed on the objects identified within the computer program module. The permissions enable tracking, from among a discrete set of changeable states, a subset of states each object might be in. A determination is made regarding whether the imposed permissions are violated by a potential reference to any of the identified objects. The results of the determination are output to a user.
Control rod computer code IAMCOS: general theory and numerical methods
West, G.
1982-11-01
IAMCOS is a computer code for the description of mechanical and thermal behavior of cylindrical control rods for fast breeders. This code version was applied, tested and modified from 1979 to 1981. In this report are described the basic model (02 version), theoretical definitions and computation methods [fr
Musick, Charles R [Castro Valley, CA; Critchlow, Terence [Livermore, CA; Ganesh, Madhaven [San Jose, CA; Slezak, Tom [Livermore, CA; Fidelis, Krzysztof [Brentwood, CA
2006-12-19
A system and method is disclosed for integrating and accessing multiple data sources within a data warehouse architecture. The metadata formed by the present method provide a way to declaratively present domain specific knowledge, obtained by analyzing data sources, in a consistent and useable way. Four types of information are represented by the metadata: abstract concepts, databases, transformations and mappings. A mediator generator automatically generates data management computer code based on the metadata. The resulting code defines a translation library and a mediator class. The translation library provides a data representation for domain specific knowledge represented in a data warehouse, including "get" and "set" methods for attributes that call transformation methods and derive a value of an attribute if it is missing. The mediator class defines methods that take "distinguished" high-level objects as input and traverse their data structures and enter information into the data warehouse.
Computation of saddle-type slow manifolds using iterative methods
Kristiansen, Kristian Uldall
2015-01-01
with respect to , appropriate estimates are directly attainable using the method of this paper. The method is applied to several examples, including a model for a pair of neurons coupled by reciprocal inhibition with two slow and two fast variables, and the computation of homoclinic connections in the Fitz......This paper presents an alternative approach for the computation of trajectory segments on slow manifolds of saddle type. This approach is based on iterative methods rather than collocation-type methods. Compared to collocation methods, which require mesh refinements to ensure uniform convergence...
The System of Inventory Forecasting in PT. XYZ by using the Method of Holt Winter Multiplicative
Shaleh, W.; Rasim; Wahyudin
2018-01-01
Problems at PT. XYZ currently only rely on manual bookkeeping, then the cost of production will swell and all investments invested to be less to predict sales and inventory of goods. If the inventory prediction of goods is to large, then the cost of production will swell and all investments invested to be less efficient. Vice versa, if the inventory prediction is too small it will impact on consumers, so that consumers are forced to wait for the desired product. Therefore, in this era of globalization, the development of computer technology has become a very important part in every business plan. Almost of all companies, both large and small, use computer technology. By utilizing computer technology, people can make time in solving complex business problems. Computer technology for companies has become an indispensable activity to provide enhancements to the business services they manage but systems and technologies are not limited to the distribution model and data processing but the existing system must be able to analyze the possibilities of future company capabilities. Therefore, the company must be able to forecast conditions and circumstances, either from inventory of goods, force, or profits to be obtained. To forecast it, the data of total sales from December 2014 to December 2016 will be calculated by using the method of Holt Winters, which is the method of time series prediction (Multiplicative Seasonal Method) it is seasonal data that has increased and decreased, also has 4 equations i.e. Single Smoothing, Trending Smoothing, Seasonal Smoothing and Forecasting. From the results of research conducted, error value in the form of MAPE is below 1%, so it can be concluded that forecasting with the method of Holt Winter Multiplicative.
Discrete linear canonical transform computation by adaptive method.
Zhang, Feng; Tao, Ran; Wang, Yue
2013-07-29
The linear canonical transform (LCT) describes the effect of quadratic phase systems on a wavefield and generalizes many optical transforms. In this paper, the computation method for the discrete LCT using the adaptive least-mean-square (LMS) algorithm is presented. The computation approaches of the block-based discrete LCT and the stream-based discrete LCT using the LMS algorithm are derived, and the implementation structures of these approaches by the adaptive filter system are considered. The proposed computation approaches have the inherent parallel structures which make them suitable for efficient VLSI implementations, and are robust to the propagation of possible errors in the computation process.
Platform-independent method for computer aided schematic drawings
Vell, Jeffrey L [Slingerlands, NY; Siganporia, Darius M [Clifton Park, NY; Levy, Arthur J [Fort Lauderdale, FL
2012-02-14
A CAD/CAM method is disclosed for a computer system to capture and interchange schematic drawing and associated design information. The schematic drawing and design information are stored in an extensible, platform-independent format.
Computerized nipple identification for multiple image analysis in computer-aided diagnosis
Zhou Chuan; Chan Heangping; Paramagul, Chintana; Roubidoux, Marilyn A.; Sahiner, Berkman; Hadjiiski, Labomir M.; Petrick, Nicholas
2004-01-01
Correlation of information from multiple-view mammograms (e.g., MLO and CC views, bilateral views, or current and prior mammograms) can improve the performance of breast cancer diagnosis by radiologists or by computer. The nipple is a reliable and stable landmark on mammograms for the registration of multiple mammograms. However, accurate identification of nipple location on mammograms is challenging because of the variations in image quality and in the nipple projections, resulting in some nipples being nearly invisible on the mammograms. In this study, we developed a computerized method to automatically identify the nipple location on digitized mammograms. First, the breast boundary was obtained using a gradient-based boundary tracking algorithm, and then the gray level profiles along the inside and outside of the boundary were identified. A geometric convergence analysis was used to limit the nipple search to a region of the breast boundary. A two-stage nipple detection method was developed to identify the nipple location using the gray level information around the nipple, the geometric characteristics of nipple shapes, and the texture features of glandular tissue or ducts which converge toward the nipple. At the first stage, a rule-based method was designed to identify the nipple location by detecting significant changes of intensity along the gray level profiles inside and outside the breast boundary and the changes in the boundary direction. At the second stage, a texture orientation-field analysis was developed to estimate the nipple location based on the convergence of the texture pattern of glandular tissue or ducts towards the nipple. The nipple location was finally determined from the detected nipple candidates by a rule-based confidence analysis. In this study, 377 and 367 randomly selected digitized mammograms were used for training and testing the nipple detection algorithm, respectively. Two experienced radiologists identified the nipple locations
Kim, Yoonsang; Emery, Sherry
2013-01-01
Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods’ performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages—SAS GLIMMIX Laplace and SuperMix Gaussian quadrature—perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes. PMID:24288415
Simulating elastic light scattering using high performance computing methods
Hoekstra, A.G.; Sloot, P.M.A.; Verbraeck, A.; Kerckhoffs, E.J.H.
1993-01-01
The Coupled Dipole method, as originally formulated byPurcell and Pennypacker, is a very powerful method tosimulate the Elastic Light Scattering from arbitraryparticles. This method, which is a particle simulationmodel for Computational Electromagnetics, has one majordrawback: if the size of the
Acoustic scattering by multiple elliptical cylinders using collocation multipole method
Lee, Wei-Ming
2012-01-01
This paper presents the collocation multipole method for the acoustic scattering induced by multiple elliptical cylinders subjected to an incident plane sound wave. To satisfy the Helmholtz equation in the elliptical coordinate system, the scattered acoustic field is formulated in terms of angular and radial Mathieu functions which also satisfy the radiation condition at infinity. The sound-soft or sound-hard boundary condition is satisfied by uniformly collocating points on the boundaries. For the sound-hard or Neumann conditions, the normal derivative of the acoustic pressure is determined by using the appropriate directional derivative without requiring the addition theorem of Mathieu functions. By truncating the multipole expansion, a finite linear algebraic system is derived and the scattered field can then be determined according to the given incident acoustic wave. Once the total field is calculated as the sum of the incident field and the scattered field, the near field acoustic pressure along the scatterers and the far field scattering pattern can be determined. For the acoustic scattering of one elliptical cylinder, the proposed results match well with the analytical solutions. The proposed scattered fields induced by two and three elliptical–cylindrical scatterers are critically compared with those provided by the boundary element method to validate the present method. Finally, the effects of the convexity of an elliptical scatterer, the separation between scatterers and the incident wave number and angle on the acoustic scattering are investigated.
Computational and experimental methods for enclosed natural convection
Larson, D.W.; Gartling, D.K.; Schimmel, W.P. Jr.
1977-10-01
Two computational procedures and one optical experimental procedure for studying enclosed natural convection are described. The finite-difference and finite-element numerical methods are developed and several sample problems are solved. Results obtained from the two computational approaches are compared. A temperature-visualization scheme using laser holographic interferometry is described, and results from this experimental procedure are compared with results from both numerical methods
Method and computer program product for maintenance and modernization backlogging
Mattimore, Bernard G; Reynolds, Paul E; Farrell, Jill M
2013-02-19
According to one embodiment, a computer program product for determining future facility conditions includes a computer readable medium having computer readable program code stored therein. The computer readable program code includes computer readable program code for calculating a time period specific maintenance cost, for calculating a time period specific modernization factor, and for calculating a time period specific backlog factor. Future facility conditions equal the time period specific maintenance cost plus the time period specific modernization factor plus the time period specific backlog factor. In another embodiment, a computer-implemented method for calculating future facility conditions includes calculating a time period specific maintenance cost, calculating a time period specific modernization factor, and calculating a time period specific backlog factor. Future facility conditions equal the time period specific maintenance cost plus the time period specific modernization factor plus the time period specific backlog factor. Other embodiments are also presented.
Computer Anti-forensics Methods and their Impact on Computer Forensic Investigation
Pajek, Przemyslaw; Pimenidis, Elias
2009-01-01
Electronic crime is very difficult to investigate and prosecute, mainly\\ud due to the fact that investigators have to build their cases based on artefacts left\\ud on computer systems. Nowadays, computer criminals are aware of computer forensics\\ud methods and techniques and try to use countermeasure techniques to efficiently\\ud impede the investigation processes. In many cases investigation with\\ud such countermeasure techniques in place appears to be too expensive, or too\\ud time consuming t...
SmartShadow models and methods for pervasive computing
Wu, Zhaohui
2013-01-01
SmartShadow: Models and Methods for Pervasive Computing offers a new perspective on pervasive computing with SmartShadow, which is designed to model a user as a personality ""shadow"" and to model pervasive computing environments as user-centric dynamic virtual personal spaces. Just like human beings' shadows in the physical world, it follows people wherever they go, providing them with pervasive services. The model, methods, and software infrastructure for SmartShadow are presented and an application for smart cars is also introduced. The book can serve as a valuable reference work for resea
Liu, Xiaodong
2017-08-01
A sampling method by using scattering amplitude is proposed for shape and location reconstruction in inverse acoustic scattering problems. Only matrix multiplication is involved in the computation, thus the novel sampling method is very easy and simple to implement. With the help of the factorization of the far field operator, we establish an inf-criterion for characterization of underlying scatterers. This result is then used to give a lower bound of the proposed indicator functional for sampling points inside the scatterers. While for the sampling points outside the scatterers, we show that the indicator functional decays like the bessel functions as the sampling point goes away from the boundary of the scatterers. We also show that the proposed indicator functional continuously depends on the scattering amplitude, this further implies that the novel sampling method is extremely stable with respect to errors in the data. Different to the classical sampling method such as the linear sampling method or the factorization method, from the numerical point of view, the novel indicator takes its maximum near the boundary of the underlying target and decays like the bessel functions as the sampling points go away from the boundary. The numerical simulations also show that the proposed sampling method can deal with multiple multiscale case, even the different components are close to each other.
320-row detector computed tomography angiography findings of a case with multiple
Akay, S.; Bozlar, U.; Demirkol, S.; Tasar, M.
2012-01-01
Full text: Introduction: Computed tomography angiography (CTA) with three-dimensional imaging capability is a very reliable imaging modality for the evaluation of the coronary arteries. Objectives and tasks: To discuss the 320-row detector CTA findings of a case with multiple coronary artery course anomaly. Materials and methods: A 46-year-old man with palpitation, admitted to Cardiology department of our hospital. On electrocardiography, polymorphic ventricular early beats were observed. The patient was referred to Radiology department for CTA examination in terms of probable coronary artery anomaly. Results: On CTA, left main coronary artery was short. The bridging causes nearly 75% luminal stenosis was observed in the middle part of left descending artery. Circumflex artery was continuing as the first obtuse margin and this branch was separating to four branches in the middle part. They were coursing subepicardially in the middle and distal part. Right main coronary artery has also subepicardial course in its middle and distal part. Conclusion: Myocardial bridging is not a rare situation in routine clinical practice. But bridging in all of the three coronary arteries is very uncommon. Multidetector CTA is an effective and non-invasive imaging modality for understanding the normal anatomy and detecting the congenital anomalies of the coronary arteries
Multiple-instance learning for computer-aided detection of tuberculosis
Melendez, J.; Sánchez, C. I.; Philipsen, R. H. H. M.; Maduskar, P.; van Ginneken, B.
2014-03-01
Detection of tuberculosis (TB) on chest radiographs (CXRs) is a hard problem. Therefore, to help radiologists or even take their place when they are not available, computer-aided detection (CAD) systems are being developed. In order to reach a performance comparable to that of human experts, the pattern recognition algorithms of these systems are typically trained on large CXR databases that have been manually annotated to indicate the abnormal lung regions. However, manually outlining those regions constitutes a time-consuming process that, besides, is prone to inconsistencies and errors introduced by interobserver variability and the absence of an external reference standard. In this paper, we investigate an alternative pattern classi cation method, namely multiple-instance learning (MIL), that does not require such detailed information for a CAD system to be trained. We have applied this alternative approach to a CAD system aimed at detecting textural lesions associated with TB. Only the case (or image) condition (normal or abnormal) was provided in the training stage. We compared the resulting performance with those achieved by several variations of a conventional system trained with detailed annotations. A database of 917 CXRs was constructed for experimentation. It was divided into two roughly equal parts that were used as training and test sets. The area under the receiver operating characteristic curve was utilized as a performance measure. Our experiments show that, by applying the investigated MIL approach, comparable results as with the aforementioned conventional systems are obtained in most cases, without requiring condition information at the lesion level.
Page, B.; Hilty, L.M.
1994-01-01
Environmental computer science is a new partial discipline of applied computer science, which makes use of methods and techniques of information processing in environmental protection. Thanks to the inter-disciplinary nature of environmental problems, computer science acts as a mediator between numerous disciplines and institutions in this sector. The handbook reflects the broad spectrum of state-of-the art environmental computer science. The following important subjects are dealt with: Environmental databases and information systems, environmental monitoring, modelling and simulation, visualization of environmental data and knowledge-based systems in the environmental sector. (orig.) [de
Multiple instance learning tracking method with local sparse representation
Xie, Chengjun
2013-10-01
When objects undergo large pose change, illumination variation or partial occlusion, most existed visual tracking algorithms tend to drift away from targets and even fail in tracking them. To address this issue, in this study, the authors propose an online algorithm by combining multiple instance learning (MIL) and local sparse representation for tracking an object in a video system. The key idea in our method is to model the appearance of an object by local sparse codes that can be formed as training data for the MIL framework. First, local image patches of a target object are represented as sparse codes with an overcomplete dictionary, where the adaptive representation can be helpful in overcoming partial occlusion in object tracking. Then MIL learns the sparse codes by a classifier to discriminate the target from the background. Finally, results from the trained classifier are input into a particle filter framework to sequentially estimate the target state over time in visual tracking. In addition, to decrease the visual drift because of the accumulative errors when updating the dictionary and classifier, a two-step object tracking method combining a static MIL classifier with a dynamical MIL classifier is proposed. Experiments on some publicly available benchmarks of video sequences show that our proposed tracker is more robust and effective than others. © The Institution of Engineering and Technology 2013.
Massanes, Francesc; Cadennes, Marie; Brankov, Jovan G
2011-07-01
In this paper we describe and evaluate a fast implementation of a classical block matching motion estimation algorithm for multiple Graphical Processing Units (GPUs) using the Compute Unified Device Architecture (CUDA) computing engine. The implemented block matching algorithm (BMA) uses summed absolute difference (SAD) error criterion and full grid search (FS) for finding optimal block displacement. In this evaluation we compared the execution time of a GPU and CPU implementation for images of various sizes, using integer and non-integer search grids.The results show that use of a GPU card can shorten computation time by a factor of 200 times for integer and 1000 times for a non-integer search grid. The additional speedup for non-integer search grid comes from the fact that GPU has built-in hardware for image interpolation. Further, when using multiple GPU cards, the presented evaluation shows the importance of the data splitting method across multiple cards, but an almost linear speedup with a number of cards is achievable.In addition we compared execution time of the proposed FS GPU implementation with two existing, highly optimized non-full grid search CPU based motion estimations methods, namely implementation of the Pyramidal Lucas Kanade Optical flow algorithm in OpenCV and Simplified Unsymmetrical multi-Hexagon search in H.264/AVC standard. In these comparisons, FS GPU implementation still showed modest improvement even though the computational complexity of FS GPU implementation is substantially higher than non-FS CPU implementation.We also demonstrated that for an image sequence of 720×480 pixels in resolution, commonly used in video surveillance, the proposed GPU implementation is sufficiently fast for real-time motion estimation at 30 frames-per-second using two NVIDIA C1060 Tesla GPU cards.
Seismic PSA method for multiple nuclear power plants in a site
Hakata, Tadakuni [Nuclear Safety Commission, Tokyo (Japan)
2007-07-15
The maximum number of nuclear power plants in a site is eight and about 50% of power plants are built in sites with three or more plants in the world. Such nuclear sites have potential risks of simultaneous multiple plant damages especially at external events. Seismic probabilistic safety assessment method (Level-1 PSA) for multi-unit sites with up to 9 units has been developed. The models include Fault-tree linked Monte Carlo computation, taking into consideration multivariate correlations of components and systems from partial to complete, inside and across units. The models were programmed as a computer program CORAL reef. Sample analysis and sensitivity studies were performed to verify the models and algorithms and to understand some of risk insights and risk metrics, such as site core damage frequency (CDF per site-year) for multiple reactor plants. This study will contribute to realistic state of art seismic PSA, taking consideration of multiple reactor power plants, and to enhancement of seismic safety. (author)
A Decentralized Eigenvalue Computation Method for Spectrum Sensing Based on Average Consensus
Mohammadi, Jafar; Limmer, Steffen; Stańczak, Sławomir
2016-07-01
This paper considers eigenvalue estimation for the decentralized inference problem for spectrum sensing. We propose a decentralized eigenvalue computation algorithm based on the power method, which is referred to as generalized power method GPM; it is capable of estimating the eigenvalues of a given covariance matrix under certain conditions. Furthermore, we have developed a decentralized implementation of GPM by splitting the iterative operations into local and global computation tasks. The global tasks require data exchange to be performed among the nodes. For this task, we apply an average consensus algorithm to efficiently perform the global computations. As a special case, we consider a structured graph that is a tree with clusters of nodes at its leaves. For an accelerated distributed implementation, we propose to use computation over multiple access channel (CoMAC) as a building block of the algorithm. Numerical simulations are provided to illustrate the performance of the two algorithms.
A fast computation method for MUSIC spectrum function based on circular arrays
Du, Zhengdong; Wei, Ping
2015-02-01
The large computation amount of multiple signal classification (MUSIC) spectrum function seriously affects the timeliness of direction finding system using MUSIC algorithm, especially in the two-dimensional directions of arrival (DOA) estimation of azimuth and elevation with a large antenna array. This paper proposes a fast computation method for MUSIC spectrum. It is suitable for any circular array. First, the circular array is transformed into a virtual uniform circular array, in the process of calculating MUSIC spectrum, for the cyclic characteristics of steering vector, the inner product in the calculation of spatial spectrum is realised by cyclic convolution. The computational amount of MUSIC spectrum is obviously less than that of the conventional method. It is a very practical way for MUSIC spectrum computation in circular arrays.
Yidong Xu
2017-10-01
Full Text Available A novel localization method based on multiple signal classification (MUSIC algorithm is proposed for positioning an electric dipole source in a confined underwater environment by using electric dipole-receiving antenna array. In this method, the boundary element method (BEM is introduced to analyze the boundary of the confined region by use of a matrix equation. The voltage of each dipole pair is used as spatial-temporal localization data, and it does not need to obtain the field component in each direction compared with the conventional fields based localization method, which can be easily implemented in practical engineering applications. Then, a global-multiple region-conjugate gradient (CG hybrid search method is used to reduce the computation burden and to improve the operation speed. Two localization simulation models and a physical experiment are conducted. Both the simulation results and physical experiment result provide accurate positioning performance, with the help to verify the effectiveness of the proposed localization method in underwater environments.
Computational methods for protein identification from mass spectrometry data.
Leo McHugh
2008-02-01
Full Text Available Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology.
Agopian, A J; Evans, Jane A; Lupo, Philip J
2018-01-15
It is estimated that 20 to 30% of infants with birth defects have two or more birth defects. Among these infants with multiple congenital anomalies (MCA), co-occurring anomalies may represent either chance (i.e., unrelated etiologies) or pathogenically associated patterns of anomalies. While some MCA patterns have been recognized and described (e.g., known syndromes), others have not been identified or characterized. Elucidating these patterns may result in a better understanding of the etiologies of these MCAs. This article reviews the literature with regard to analytic methods that have been used to evaluate patterns of MCAs, in particular those using birth defect registry data. A popular method for MCA assessment involves a comparison of the observed to expected ratio for a given combination of MCAs, or one of several modified versions of this comparison. Other methods include use of numerical taxonomy or other clustering techniques, multiple regression analysis, and log-linear analysis. Advantages and disadvantages of these approaches, as well as specific applications, were outlined. Despite the availability of multiple analytic approaches, relatively few MCA combinations have been assessed. The availability of large birth defects registries and computing resources that allow for automated, big data strategies for prioritizing MCA patterns may provide for new avenues for better understanding co-occurrence of birth defects. Thus, the selection of an analytic approach may depend on several considerations. Birth Defects Research 110:5-11, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Big data mining analysis method based on cloud computing
Cai, Qing Qiu; Cui, Hong Gang; Tang, Hao
2017-08-01
Information explosion era, large data super-large, discrete and non-(semi) structured features have gone far beyond the traditional data management can carry the scope of the way. With the arrival of the cloud computing era, cloud computing provides a new technical way to analyze the massive data mining, which can effectively solve the problem that the traditional data mining method cannot adapt to massive data mining. This paper introduces the meaning and characteristics of cloud computing, analyzes the advantages of using cloud computing technology to realize data mining, designs the mining algorithm of association rules based on MapReduce parallel processing architecture, and carries out the experimental verification. The algorithm of parallel association rule mining based on cloud computing platform can greatly improve the execution speed of data mining.
A Krylov Subspace Method for Unstructured Mesh SN Transport Computation
Yoo, Han Jong; Cho, Nam Zin; Kim, Jong Woon; Hong, Ser Gi; Lee, Young Ouk
2010-01-01
Hong, et al., have developed a computer code MUST (Multi-group Unstructured geometry S N Transport) for the neutral particle transport calculations in three-dimensional unstructured geometry. In this code, the discrete ordinates transport equation is solved by using the discontinuous finite element method (DFEM) or the subcell balance methods with linear discontinuous expansion. In this paper, the conventional source iteration in the MUST code is replaced by the Krylov subspace method to reduce computing time and the numerical test results are given
Computational methods for high-energy source shielding
Armstrong, T.W.; Cloth, P.; Filges, D.
1983-01-01
The computational methods for high-energy radiation transport related to shielding of the SNQ-spallation source are outlined. The basic approach is to couple radiation-transport computer codes which use Monte Carlo methods and discrete ordinates methods. A code system is suggested that incorporates state-of-the-art radiation-transport techniques. The stepwise verification of that system is briefly summarized. The complexity of the resulting code system suggests a more straightforward code specially tailored for thick shield calculations. A short guide line to future development of such a Monte Carlo code is given
Monte Carlo methods of PageRank computation
Litvak, Nelli
2004-01-01
We describe and analyze an on-line Monte Carlo method of PageRank computation. The PageRank is being estimated basing on results of a large number of short independent simulation runs initiated from each page that contains outgoing hyperlinks. The method does not require any storage of the hyperlink
Geometric optical transfer function and tis computation method
Wang Qi
1992-01-01
Geometric Optical Transfer Function formula is derived after expound some content to be easily ignored, and the computation method is given with Bessel function of order zero and numerical integration and Spline interpolation. The method is of advantage to ensure accuracy and to save calculation
Efficient Numerical Methods for Stochastic Differential Equations in Computational Finance
Happola, Juho
2017-09-19
Stochastic Differential Equations (SDE) offer a rich framework to model the probabilistic evolution of the state of a system. Numerical approximation methods are typically needed in evaluating relevant Quantities of Interest arising from such models. In this dissertation, we present novel effective methods for evaluating Quantities of Interest relevant to computational finance when the state of the system is described by an SDE.
Fully consistent CFD methods for incompressible flow computations
Kolmogorov, Dmitry; Shen, Wen Zhong; Sørensen, Niels N.
2014-01-01
Nowadays collocated grid based CFD methods are one of the most e_cient tools for computations of the ows past wind turbines. To ensure the robustness of the methods they require special attention to the well-known problem of pressure-velocity coupling. Many commercial codes to ensure the pressure...
Efficient Numerical Methods for Stochastic Differential Equations in Computational Finance
Happola, Juho
2017-01-01
Stochastic Differential Equations (SDE) offer a rich framework to model the probabilistic evolution of the state of a system. Numerical approximation methods are typically needed in evaluating relevant Quantities of Interest arising from such models. In this dissertation, we present novel effective methods for evaluating Quantities of Interest relevant to computational finance when the state of the system is described by an SDE.
Matrix-vector multiplication using digital partitioning for more accurate optical computing
Gary, C. K.
1992-01-01
Digital partitioning offers a flexible means of increasing the accuracy of an optical matrix-vector processor. This algorithm can be implemented with the same architecture required for a purely analog processor, which gives optical matrix-vector processors the ability to perform high-accuracy calculations at speeds comparable with or greater than electronic computers as well as the ability to perform analog operations at a much greater speed. Digital partitioning is compared with digital multiplication by analog convolution, residue number systems, and redundant number representation in terms of the size and the speed required for an equivalent throughput as well as in terms of the hardware requirements. Digital partitioning and digital multiplication by analog convolution are found to be the most efficient alogrithms if coding time and hardware are considered, and the architecture for digital partitioning permits the use of analog computations to provide the greatest throughput for a single processor.
Multiple exciton generation in chiral carbon nanotubes: Density functional theory based computation
Kryjevski, Andrei; Mihaylov, Deyan; Kilina, Svetlana; Kilin, Dmitri
2017-10-01
We use a Boltzmann transport equation (BE) to study time evolution of a photo-excited state in a nanoparticle including phonon-mediated exciton relaxation and the multiple exciton generation (MEG) processes, such as exciton-to-biexciton multiplication and biexciton-to-exciton recombination. BE collision integrals are computed using Kadanoff-Baym-Keldysh many-body perturbation theory based on density functional theory simulations, including exciton effects. We compute internal quantum efficiency (QE), which is the number of excitons generated from an absorbed photon in the course of the relaxation. We apply this approach to chiral single-wall carbon nanotubes (SWCNTs), such as (6,2) and (6,5). We predict efficient MEG in the (6,2) and (6,5) SWCNTs within the solar spectrum range starting at the 2Eg energy threshold and with QE reaching ˜1.6 at about 3Eg, where Eg is the electronic gap.
Computational methods for structural load and resistance modeling
Thacker, B. H.; Millwater, H. R.; Harren, S. V.
1991-01-01
An automated capability for computing structural reliability considering uncertainties in both load and resistance variables is presented. The computations are carried out using an automated Advanced Mean Value iteration algorithm (AMV +) with performance functions involving load and resistance variables obtained by both explicit and implicit methods. A complete description of the procedures used is given as well as several illustrative examples, verified by Monte Carlo Analysis. In particular, the computational methods described in the paper are shown to be quite accurate and efficient for a material nonlinear structure considering material damage as a function of several primitive random variables. The results show clearly the effectiveness of the algorithms for computing the reliability of large-scale structural systems with a maximum number of resolutions.
Computational mathematics models, methods, and analysis with Matlab and MPI
White, Robert E
2004-01-01
Computational Mathematics: Models, Methods, and Analysis with MATLAB and MPI explores and illustrates this process. Each section of the first six chapters is motivated by a specific application. The author applies a model, selects a numerical method, implements computer simulations, and assesses the ensuing results. These chapters include an abundance of MATLAB code. By studying the code instead of using it as a "black box, " you take the first step toward more sophisticated numerical modeling. The last four chapters focus on multiprocessing algorithms implemented using message passing interface (MPI). These chapters include Fortran 9x codes that illustrate the basic MPI subroutines and revisit the applications of the previous chapters from a parallel implementation perspective. All of the codes are available for download from www4.ncsu.edu./~white.This book is not just about math, not just about computing, and not just about applications, but about all three--in other words, computational science. Whether us...
Multi-chain Markov chain Monte Carlo methods for computationally expensive models
Huang, M.; Ray, J.; Ren, H.; Hou, Z.; Bao, J.
2017-12-01
Markov chain Monte Carlo (MCMC) methods are used to infer model parameters from observational data. The parameters are inferred as probability densities, thus capturing estimation error due to sparsity of the data, and the shortcomings of the model. Multiple communicating chains executing the MCMC method have the potential to explore the parameter space better, and conceivably accelerate the convergence to the final distribution. We present results from tests conducted with the multi-chain method to show how the acceleration occurs i.e., for loose convergence tolerances, the multiple chains do not make much of a difference. The ensemble of chains also seems to have the ability to accelerate the convergence of a few chains that might start from suboptimal starting points. Finally, we show the performance of the chains in the estimation of O(10) parameters using computationally expensive forward models such as the Community Land Model, where the sampling burden is distributed over multiple chains.
Sekimura, Naoto; Okita, Taira
2006-01-01
Scientific computational methods have advanced remarkably with the progress of nuclear development. They have played the role of weft connecting each realm of nuclear engineering and then an introductory course of advanced scientific computational methods and their applications to nuclear technologies were prepared in serial form. This is the fourth issue showing the overview of scientific computational methods with the introduction of continuum simulation methods and their applications. Simulation methods on physical radiation effects on materials are reviewed based on the process such as binary collision approximation, molecular dynamics, kinematic Monte Carlo method, reaction rate method and dislocation dynamics. (T. Tanaka)
The methods for detecting multiple small nodules from 3D chest X-ray CT images
Hayase, Yosuke; Mekada, Yoshito; Mori, Kensaku; Toriwaki, Jun-ichiro; Natori, Hiroshi
2004-01-01
This paper describes a method for detecting small nodules, whose CT values and diameters are more than -600 Hounsfield unit (H.U.) and 2 mm, from three-dimensional chest X-ray CT images. The proposed method roughly consists of two submodules: initial detection of nodule candidates by discriminating between nodule regions and other regions such as blood vessels or bronchi using a shape feature computed from distance values inside the regions and reduction of false positive (FP) regions by using a minimum directional difference filter called minimum directional difference filter (Min-DD) changing its radius suit to the size of the initial candidates. The performance of the proposed method was evaluated by using seven cases of chest X-ray CT images including six abnormal cases where multiple lung cancers are observed. The experimental results for nodules (361 regions in total) showed that sensitivity and FP regions are 71% and 7.4 regions in average per case. (author)
Class of reconstructed discontinuous Galerkin methods in computational fluid dynamics
Luo, Hong; Xia, Yidong; Nourgaliev, Robert
2011-01-01
A class of reconstructed discontinuous Galerkin (DG) methods is presented to solve compressible flow problems on arbitrary grids. The idea is to combine the efficiency of the reconstruction methods in finite volume methods and the accuracy of the DG methods to obtain a better numerical algorithm in computational fluid dynamics. The beauty of the resulting reconstructed discontinuous Galerkin (RDG) methods is that they provide a unified formulation for both finite volume and DG methods, and contain both classical finite volume and standard DG methods as two special cases of the RDG methods, and thus allow for a direct efficiency comparison. Both Green-Gauss and least-squares reconstruction methods and a least-squares recovery method are presented to obtain a quadratic polynomial representation of the underlying linear discontinuous Galerkin solution on each cell via a so-called in-cell reconstruction process. The devised in-cell reconstruction is aimed to augment the accuracy of the discontinuous Galerkin method by increasing the order of the underlying polynomial solution. These three reconstructed discontinuous Galerkin methods are used to compute a variety of compressible flow problems on arbitrary meshes to assess their accuracy. The numerical experiments demonstrate that all three reconstructed discontinuous Galerkin methods can significantly improve the accuracy of the underlying second-order DG method, although the least-squares reconstructed DG method provides the best performance in terms of both accuracy, efficiency, and robustness. (author)
Data analysis through interactive computer animation method (DATICAM)
Curtis, J.N.; Schwieder, D.H.
1983-01-01
DATICAM is an interactive computer animation method designed to aid in the analysis of nuclear research data. DATICAM was developed at the Idaho National Engineering Laboratory (INEL) by EG and G Idaho, Inc. INEL analysts use DATICAM to produce computer codes that are better able to predict the behavior of nuclear power reactors. In addition to increased code accuracy, DATICAM has saved manpower and computer costs. DATICAM has been generalized to assist in the data analysis of virtually any data-producing dynamic process
Multigrid methods for the computation of propagators in gauge fields
Kalkreuter, T.
1992-11-01
In the present work generalizations of multigrid methods for propagators in gauge fields are investigated. We discuss proper averaging operations for bosons and for staggered fermions. An efficient algorithm for computing C numerically is presented. The averaging kernels C can be used not only in deterministic multigrid computations, but also in multigrid Monte Carlo simulations, and for the definition of block spins and blocked gauge fields in Monte Carlo renormalization group studies of gauge theories. Actual numerical computations of kernels and propagators are performed in compact four-dimensional SU(2) gauge fields. (orig./HSI)
Multiple travelling wave solutions of nonlinear evolution equations using a unified algebraic method
Fan Engui
2002-01-01
A new direct and unified algebraic method for constructing multiple travelling wave solutions of general nonlinear evolution equations is presented and implemented in a computer algebraic system. Compared with most of the existing tanh methods, the Jacobi elliptic function method or other sophisticated methods, the proposed method not only gives new and more general solutions, but also provides a guideline to classify the various types of the travelling wave solutions according to the values of some parameters. The solutions obtained in this paper include (a) kink-shaped and bell-shaped soliton solutions, (b) rational solutions, (c) triangular periodic solutions and (d) Jacobi and Weierstrass doubly periodic wave solutions. Among them, the Jacobi elliptic periodic wave solutions exactly degenerate to the soliton solutions at a certain limit condition. The efficiency of the method can be demonstrated on a large variety of nonlinear evolution equations such as those considered in this paper, KdV-MKdV, Ito's fifth MKdV, Hirota, Nizhnik-Novikov-Veselov, Broer-Kaup, generalized coupled Hirota-Satsuma, coupled Schroedinger-KdV, (2+1)-dimensional dispersive long wave, (2+1)-dimensional Davey-Stewartson equations. In addition, as an illustrative sample, the properties of the soliton solutions and Jacobi doubly periodic solutions for the Hirota equation are shown by some figures. The links among our proposed method, the tanh method, extended tanh method and the Jacobi elliptic function method are clarified generally. (author)
Water demand forecasting: review of soft computing methods.
Ghalehkhondabi, Iman; Ardjmand, Ehsan; Young, William A; Weckman, Gary R
2017-07-01
Demand forecasting plays a vital role in resource management for governments and private companies. Considering the scarcity of water and its inherent constraints, demand management and forecasting in this domain are critically important. Several soft computing techniques have been developed over the last few decades for water demand forecasting. This study focuses on soft computing methods of water consumption forecasting published between 2005 and 2015. These methods include artificial neural networks (ANNs), fuzzy and neuro-fuzzy models, support vector machines, metaheuristics, and system dynamics. Furthermore, it was discussed that while in short-term forecasting, ANNs have been superior in many cases, but it is still very difficult to pick a single method as the overall best. According to the literature, various methods and their hybrids are applied to water demand forecasting. However, it seems soft computing has a lot more to contribute to water demand forecasting. These contribution areas include, but are not limited, to various ANN architectures, unsupervised methods, deep learning, various metaheuristics, and ensemble methods. Moreover, it is found that soft computing methods are mainly used for short-term demand forecasting.
Short-term electric load forecasting using computational intelligence methods
Jurado, Sergio; Peralta, J.; Nebot, Àngela; Mugica, Francisco; Cortez, Paulo
2013-01-01
Accurate time series forecasting is a key issue to support individual and organizational decision making. In this paper, we introduce several methods for short-term electric load forecasting. All the presented methods stem from computational intelligence techniques: Random Forest, Nonlinear Autoregressive Neural Networks, Evolutionary Support Vector Machines and Fuzzy Inductive Reasoning. The performance of the suggested methods is experimentally justified with several experiments carried out...
A stochastic method for computing hadronic matrix elements
Alexandrou, Constantia [Cyprus Univ., Nicosia (Cyprus). Dept. of Physics; The Cyprus Institute, Nicosia (Cyprus). Computational-based Science and Technology Research Center; Dinter, Simon; Drach, Vincent [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Jansen, Karl [Cyprus Univ., Nicosia (Cyprus). Dept. of Physics; Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Hadjiyiannakou, Kyriakos [Cyprus Univ., Nicosia (Cyprus). Dept. of Physics; Renner, Dru B. [Thomas Jefferson National Accelerator Facility, Newport News, VA (United States); Collaboration: European Twisted Mass Collaboration
2013-02-15
We present a stochastic method for the calculation of baryon three-point functions that is more versatile compared to the typically used sequential method. We analyze the scaling of the error of the stochastically evaluated three-point function with the lattice volume and find a favorable signal-to-noise ratio suggesting that our stochastic method can be used efficiently at large volumes to compute hadronic matrix elements.
The Direct Lighting Computation in Global Illumination Methods
Wang, Changyaw Allen
1994-01-01
Creating realistic images is a computationally expensive process, but it is very important for applications such as interior design, product design, education, virtual reality, and movie special effects. To generate realistic images, state-of-art rendering techniques are employed to simulate global illumination, which accounts for the interreflection of light among objects. In this document, we formalize the global illumination problem into a eight -dimensional integral and discuss various methods that can accelerate the process of approximating this integral. We focus on the direct lighting computation, which accounts for the light reaching the viewer from the emitting sources after exactly one reflection, Monte Carlo sampling methods, and light source simplification. Results include a new sample generation method, a framework for the prediction of the total number of samples used in a solution, and a generalized Monte Carlo approach for computing the direct lighting from an environment which for the first time makes ray tracing feasible for highly complex environments.
Numerical methods design, analysis, and computer implementation of algorithms
Greenbaum, Anne
2012-01-01
Numerical Methods provides a clear and concise exploration of standard numerical analysis topics, as well as nontraditional ones, including mathematical modeling, Monte Carlo methods, Markov chains, and fractals. Filled with appealing examples that will motivate students, the textbook considers modern application areas, such as information retrieval and animation, and classical topics from physics and engineering. Exercises use MATLAB and promote understanding of computational results. The book gives instructors the flexibility to emphasize different aspects--design, analysis, or computer implementation--of numerical algorithms, depending on the background and interests of students. Designed for upper-division undergraduates in mathematics or computer science classes, the textbook assumes that students have prior knowledge of linear algebra and calculus, although these topics are reviewed in the text. Short discussions of the history of numerical methods are interspersed throughout the chapters. The book a...
The Experiment Method for Manufacturing Grid Development on Single Computer
XIAO Youan; ZHOU Zude
2006-01-01
In this paper, an experiment method for the Manufacturing Grid application system development in the single personal computer environment is proposed. The characteristic of the proposed method is constructing a full prototype Manufacturing Grid application system which is hosted on a single personal computer with the virtual machine technology. Firstly, it builds all the Manufacturing Grid physical resource nodes on an abstraction layer of a single personal computer with the virtual machine technology. Secondly, all the virtual Manufacturing Grid resource nodes will be connected with virtual network and the application software will be deployed on each Manufacturing Grid nodes. Then, we can obtain a prototype Manufacturing Grid application system which is working in the single personal computer, and can carry on the experiment on this foundation. Compared with the known experiment methods for the Manufacturing Grid application system development, the proposed method has the advantages of the known methods, such as cost inexpensively, operation simple, and can get the confidence experiment result easily. The Manufacturing Grid application system constructed with the proposed method has the high scalability, stability and reliability. It is can be migrated to the real application environment rapidly.
Zhou, Chuan, E-mail: chuan@umich.edu; Chan, Heang-Ping; Hadjiyski, Lubomir M.; Chughtai, Aamer; Wei, Jun; Kazerooni, Ella A. [Department of Radiology, The University of Michigan, Ann Arbor, Michigan 48109-0904 (United States)
2016-10-15
Purpose: The authors are developing an automated method to identify the best-quality coronary arterial segment from multiple-phase coronary CT angiography (cCTA) acquisitions, which may be used by either interpreting physicians or computer-aided detection systems to optimally and efficiently utilize the diagnostic information available in multiple-phase cCTA for the detection of coronary artery disease. Methods: After initialization with a manually identified seed point, each coronary artery tree is automatically extracted from multiple cCTA phases using our multiscale coronary artery response enhancement and 3D rolling balloon region growing vessel segmentation and tracking method. The coronary artery trees from multiple phases are then aligned by a global registration using an affine transformation with quadratic terms and nonlinear simplex optimization, followed by a local registration using a cubic B-spline method with fast localized optimization. The corresponding coronary arteries among the available phases are identified using a recursive coronary segment matching method. Each of the identified vessel segments is transformed by the curved planar reformation (CPR) method. Four features are extracted from each corresponding segment as quality indicators in the original computed tomography volume and the straightened CPR volume, and each quality indicator is used as a voting classifier for the arterial segment. A weighted voting ensemble (WVE) classifier is designed to combine the votes of the four voting classifiers for each corresponding segment. The segment with the highest WVE vote is then selected as the best-quality segment. In this study, the training and test sets consisted of 6 and 20 cCTA cases, respectively, each with 6 phases, containing a total of 156 cCTA volumes and 312 coronary artery trees. An observer preference study was also conducted with one expert cardiothoracic radiologist and four nonradiologist readers to visually rank vessel segment
Zhou, Chuan; Chan, Heang-Ping; Hadjiyski, Lubomir M.; Chughtai, Aamer; Wei, Jun; Kazerooni, Ella A.
2016-01-01
Purpose: The authors are developing an automated method to identify the best-quality coronary arterial segment from multiple-phase coronary CT angiography (cCTA) acquisitions, which may be used by either interpreting physicians or computer-aided detection systems to optimally and efficiently utilize the diagnostic information available in multiple-phase cCTA for the detection of coronary artery disease. Methods: After initialization with a manually identified seed point, each coronary artery tree is automatically extracted from multiple cCTA phases using our multiscale coronary artery response enhancement and 3D rolling balloon region growing vessel segmentation and tracking method. The coronary artery trees from multiple phases are then aligned by a global registration using an affine transformation with quadratic terms and nonlinear simplex optimization, followed by a local registration using a cubic B-spline method with fast localized optimization. The corresponding coronary arteries among the available phases are identified using a recursive coronary segment matching method. Each of the identified vessel segments is transformed by the curved planar reformation (CPR) method. Four features are extracted from each corresponding segment as quality indicators in the original computed tomography volume and the straightened CPR volume, and each quality indicator is used as a voting classifier for the arterial segment. A weighted voting ensemble (WVE) classifier is designed to combine the votes of the four voting classifiers for each corresponding segment. The segment with the highest WVE vote is then selected as the best-quality segment. In this study, the training and test sets consisted of 6 and 20 cCTA cases, respectively, each with 6 phases, containing a total of 156 cCTA volumes and 312 coronary artery trees. An observer preference study was also conducted with one expert cardiothoracic radiologist and four nonradiologist readers to visually rank vessel segment
Simplified computational methods for elastic and elastic-plastic fracture problems
Atluri, Satya N.
1992-01-01
An overview is given of some of the recent (1984-1991) developments in computational/analytical methods in the mechanics of fractures. Topics covered include analytical solutions for elliptical or circular cracks embedded in isotropic or transversely isotropic solids, with crack faces being subjected to arbitrary tractions; finite element or boundary element alternating methods for two or three dimensional crack problems; a 'direct stiffness' method for stiffened panels with flexible fasteners and with multiple cracks; multiple site damage near a row of fastener holes; an analysis of cracks with bonded repair patches; methods for the generation of weight functions for two and three dimensional crack problems; and domain-integral methods for elastic-plastic or inelastic crack mechanics.
Sakamoto, Shinichi; Otsuru, Toru
2014-01-01
This book reviews a variety of methods for wave-based acoustic simulation and recent applications to architectural and environmental acoustic problems. Following an introduction providing an overview of computational simulation of sound environment, the book is in two parts: four chapters on methods and four chapters on applications. The first part explains the fundamentals and advanced techniques for three popular methods, namely, the finite-difference time-domain method, the finite element method, and the boundary element method, as well as alternative time-domain methods. The second part demonstrates various applications to room acoustics simulation, noise propagation simulation, acoustic property simulation for building components, and auralization. This book is a valuable reference that covers the state of the art in computational simulation for architectural and environmental acoustics.
Hamiltonian lattice field theory: Computer calculations using variational methods
Zako, R.L.
1991-01-01
I develop a variational method for systematic numerical computation of physical quantities -- bound state energies and scattering amplitudes -- in quantum field theory. An infinite-volume, continuum theory is approximated by a theory on a finite spatial lattice, which is amenable to numerical computation. I present an algorithm for computing approximate energy eigenvalues and eigenstates in the lattice theory and for bounding the resulting errors. I also show how to select basis states and choose variational parameters in order to minimize errors. The algorithm is based on the Rayleigh-Ritz principle and Kato's generalizations of Temple's formula. The algorithm could be adapted to systems such as atoms and molecules. I show how to compute Green's functions from energy eigenvalues and eigenstates in the lattice theory, and relate these to physical (renormalized) coupling constants, bound state energies and Green's functions. Thus one can compute approximate physical quantities in a lattice theory that approximates a quantum field theory with specified physical coupling constants. I discuss the errors in both approximations. In principle, the errors can be made arbitrarily small by increasing the size of the lattice, decreasing the lattice spacing and computing sufficiently long. Unfortunately, I do not understand the infinite-volume and continuum limits well enough to quantify errors due to the lattice approximation. Thus the method is currently incomplete. I apply the method to real scalar field theories using a Fock basis of free particle states. All needed quantities can be calculated efficiently with this basis. The generalization to more complicated theories is straightforward. I describe a computer implementation of the method and present numerical results for simple quantum mechanical systems
Hamiltonian lattice field theory: Computer calculations using variational methods
Zako, R.L.
1991-01-01
A variational method is developed for systematic numerical computation of physical quantities-bound state energies and scattering amplitudes-in quantum field theory. An infinite-volume, continuum theory is approximated by a theory on a finite spatial lattice, which is amenable to numerical computation. An algorithm is presented for computing approximate energy eigenvalues and eigenstates in the lattice theory and for bounding the resulting errors. It is shown how to select basis states and choose variational parameters in order to minimize errors. The algorithm is based on the Rayleigh-Ritz principle and Kato's generalizations of Temple's formula. The algorithm could be adapted to systems such as atoms and molecules. It is shown how to compute Green's functions from energy eigenvalues and eigenstates in the lattice theory, and relate these to physical (renormalized) coupling constants, bound state energies and Green's functions. Thus one can compute approximate physical quantities in a lattice theory that approximates a quantum field theory with specified physical coupling constants. The author discusses the errors in both approximations. In principle, the errors can be made arbitrarily small by increasing the size of the lattice, decreasing the lattice spacing and computing sufficiently long. Unfortunately, the author does not understand the infinite-volume and continuum limits well enough to quantify errors due to the lattice approximation. Thus the method is currently incomplete. The method is applied to real scalar field theories using a Fock basis of free particle states. All needed quantities can be calculated efficiently with this basis. The generalization to more complicated theories is straightforward. The author describes a computer implementation of the method and present numerical results for simple quantum mechanical systems
Application of statistical method for FBR plant transient computation
Kikuchi, Norihiro; Mochizuki, Hiroyasu
2014-01-01
Highlights: • A statistical method with a large trial number up to 10,000 is applied to the plant system analysis. • A turbine trip test conducted at the “Monju” reactor is selected as a plant transient. • A reduction method of trial numbers is discussed. • The result with reduced trial number can express the base regions of the computed distribution. -- Abstract: It is obvious that design tolerances, errors included in operation, and statistical errors in empirical correlations effect on the transient behavior. The purpose of the present study is to apply above mentioned statistical errors to a plant system computation in order to evaluate the statistical distribution contained in the transient evolution. A selected computation case is the turbine trip test conducted at 40% electric power of the prototype fast reactor “Monju”. All of the heat transport systems of “Monju” are modeled with the NETFLOW++ system code which has been validated using the plant transient tests of the experimental fast reactor Joyo, and “Monju”. The effects of parameters on upper plenum temperature are confirmed by sensitivity analyses, and dominant parameters are chosen. The statistical errors are applied to each computation deck by using a pseudorandom number and the Monte-Carlo method. The dSFMT (Double precision SIMD-oriented Fast Mersenne Twister) that is developed version of Mersenne Twister (MT), is adopted as the pseudorandom number generator. In the present study, uniform random numbers are generated by dSFMT, and these random numbers are transformed to the normal distribution by the Box–Muller method. Ten thousands of different computations are performed at once. In every computation case, the steady calculation is performed for 12,000 s, and transient calculation is performed for 4000 s. In the purpose of the present statistical computation, it is important that the base regions of distribution functions should be calculated precisely. A large number of
Alves, Pedro; Liu, Shuang; Wang, Daifeng; Gerstein, Mark
2018-01-01
Machine learning is an integral part of computational biology, and has already shown its use in various applications, such as prognostic tests. In the last few years in the non-biological machine learning community, ensembling techniques have shown their power in data mining competitions such as the Netflix challenge; however, such methods have not found wide use in computational biology. In this work, we endeavor to show how ensembling techniques can be applied to practical problems, including problems in the field of bioinformatics, and how they often outperform other machine learning techniques in both predictive power and robustness. Furthermore, we develop a methodology of ensembling, Multi-Swarm Ensemble (MSWE) by using multiple particle swarm optimizations and demonstrate its ability to further enhance the performance of ensembles.
Koch, K.R.
1985-01-01
A new analysis method specially suited for the inherent difficulties of fusion neutronics was developed to provide detailed studies of the fusion neutron transport physics. These studies should provide a better understanding of the limitations and accuracies of typical fusion neutronics calculations. The new analysis method is based on the direct integration of the integral form of the neutron transport equation and employs a continuous energy formulation with the exact treatment of the energy angle kinematics of the scattering process. In addition, the overall solution is analyzed in terms of uncollided, once-collided, and multi-collided solution components based on a multiple collision treatment. Furthermore, the numerical evaluations of integrals use quadrature schemes that are based on the actual dependencies exhibited in the integrands. The new DITRAN computer code was developed on the Cyber 205 vector supercomputer to implement this direct integration multiple-collision fusion neutronics analysis. Three representative fusion reactor models were devised and the solutions to these problems were studied to provide suitable choices for the numerical quadrature orders as well as the discretized solution grid and to understand the limitations of the new analysis method. As further verification and as a first step in assessing the accuracy of existing fusion-neutronics calculations, solutions obtained using the new analysis method were compared to typical multigroup discrete ordinates calculations
The computation of multiple MHD equilibria in axisymmetric and straight geometry
Thomas, C.Ll.
1979-01-01
The details of the numerical methods used in codes for computing MHD equilibria in discrete conductor configurations are described with both code users and code writers in mind. Results produced by the codes have been successfully verified against analytic results and independent computations. The axisymmetric code has proved to be a valuable diagnostic aid for the TOSCA experiment. The user images of the codes are described in the appendices. (author)
Shahriari, Mohammadali; Biglarbegian, Mohammad
2018-01-01
This paper presents a new conflict resolution methodology for multiple mobile robots while ensuring their motion-liveness, especially for cluttered and dynamic environments. Our method constructs a mathematical formulation in a form of an optimization problem by minimizing the overall travel times of the robots subject to resolving all the conflicts in their motion. This optimization problem can be easily solved through coordinating only the robots' speeds. To overcome the computational cost in executing the algorithm for very cluttered environments, we develop an innovative method through clustering the environment into independent subproblems that can be solved using parallel programming techniques. We demonstrate the scalability of our approach through performing extensive simulations. Simulation results showed that our proposed method is capable of resolving the conflicts of 100 robots in less than 1.23 s in a cluttered environment that has 4357 intersections in the paths of the robots. We also developed an experimental testbed and demonstrated that our approach can be implemented in real time. We finally compared our approach with other existing methods in the literature both quantitatively and qualitatively. This comparison shows while our approach is mathematically sound, it is more computationally efficient, scalable for very large number of robots, and guarantees the live and smooth motion of robots.
Computational methods for three-dimensional microscopy reconstruction
Frank, Joachim
2014-01-01
Approaches to the recovery of three-dimensional information on a biological object, which are often formulated or implemented initially in an intuitive way, are concisely described here based on physical models of the object and the image-formation process. Both three-dimensional electron microscopy and X-ray tomography can be captured in the same mathematical framework, leading to closely-related computational approaches, but the methodologies differ in detail and hence pose different challenges. The editors of this volume, Gabor T. Herman and Joachim Frank, are experts in the respective methodologies and present research at the forefront of biological imaging and structural biology. Computational Methods for Three-Dimensional Microscopy Reconstruction will serve as a useful resource for scholars interested in the development of computational methods for structural biology and cell biology, particularly in the area of 3D imaging and modeling.
Cai Congbo; Chen Zhong; Cai Shuhui; Zhong Jianhui
2005-01-01
In this paper, behaviors of single-quantum coherences and inter-molecular multiple-quantum coherences under restricted diffusion in nuclear magnetic resonance experiments were investigated. The propagator formalism based on the loss of spin phase memory during random motion was applied to describe the diffusion-induced signal attenuation. The exact expression of the signal attenuation under the short gradient pulse approximation for restricted diffusion between two parallel plates was obtained using this propagator method. For long gradient pulses, a modified formalism was proposed. The simulated signal attenuation under the effects of gradient pulses of different width based on the Monte Carlo method agrees with the theoretical predictions. The propagator formalism and computer simulation can provide convenient, intuitive and precise methods for the study of the diffusion behaviors
Computations of finite temperature QCD with the pseudofermion method
Fucito, F.; Solomon, S.
1985-01-01
The authors discuss the phase diagram of finite temperature QCD as it is obtained including the effects of dynamical quarks by the pseudofermion method. They compare their results with the results obtained by other groups and comment on the actual state of the art for these kind of computations
Multiscale methods in computational fluid and solid mechanics
Borst, de R.; Hulshoff, S.J.; Lenz, S.; Munts, E.A.; Brummelen, van E.H.; Wall, W.; Wesseling, P.; Onate, E.; Periaux, J.
2006-01-01
First, an attempt is made towards gaining a more systematic understanding of recent progress in multiscale modelling in computational solid and fluid mechanics. Sub- sequently, the discussion is focused on variational multiscale methods for the compressible and incompressible Navier-Stokes
Oka, Yoshiaki; Okuda, Hiroshi
2006-01-01
Scientific computational methods have advanced remarkably with the progress of nuclear development. They have played the role of weft connecting each realm of nuclear engineering and then an introductory course of advanced scientific computational methods and their applications to nuclear technologies were prepared in serial form. This is the first issue showing their overview and introduction of continuum simulation methods. Finite element method as their applications is also reviewed. (T. Tanaka)
Chen, Chao; Sheng, Yuping; Jun, Wang
2018-01-01
A high performed multiple band metamaterial absorber is designed and computed through the software Ansofts HFSS 10.0, which is constituted with two kinds of separated metal particles sub-structures. The multiple band absorption property of the metamaterial absorber is based on the resonance of localized surface plasmon (LSP) modes excited near edges of metal particles. The damping constant of gold layer is optimized to obtain a near-perfect absorption rate. Four kinds of dielectric layers is computed to achieve the perfect absorption perform. The perfect absorption perform of the metamaterial absorber is enhanced through optimizing the structural parameters (R = 75 nm, w = 80 nm). Moreover, a perfect absorption band is achieved because of the plasmonic hybridization phenomenon between LSP modes. The designed metamaterial absorber shows high sensitive in the changed of the refractive index of the liquid. A liquid refractive index sensor strategy is proposed based on the computed figure of merit (FOM) value of the metamaterial absorber. High FOM values (116, 111, and 108) are achieved with three liquid (Methanol, Carbon tetrachloride, and Carbon disulfide).
Regression modeling methods, theory, and computation with SAS
Panik, Michael
2009-01-01
Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs.The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression,
Recent Development in Rigorous Computational Methods in Dynamical Systems
Arai, Zin; Kokubu, Hiroshi; Pilarczyk, Paweł
2009-01-01
We highlight selected results of recent development in the area of rigorous computations which use interval arithmetic to analyse dynamical systems. We describe general ideas and selected details of different ways of approach and we provide specific sample applications to illustrate the effectiveness of these methods. The emphasis is put on a topological approach, which combined with rigorous calculations provides a broad range of new methods that yield mathematically rel...
Method and system for environmentally adaptive fault tolerant computing
Copenhaver, Jason L. (Inventor); Jeremy, Ramos (Inventor); Wolfe, Jeffrey M. (Inventor); Brenner, Dean (Inventor)
2010-01-01
A method and system for adapting fault tolerant computing. The method includes the steps of measuring an environmental condition representative of an environment. An on-board processing system's sensitivity to the measured environmental condition is measured. It is determined whether to reconfigure a fault tolerance of the on-board processing system based in part on the measured environmental condition. The fault tolerance of the on-board processing system may be reconfigured based in part on the measured environmental condition.
Hayashi Takeshi
2013-01-01
Full Text Available Abstract Background Genomic selection is an effective tool for animal and plant breeding, allowing effective individual selection without phenotypic records through the prediction of genomic breeding value (GBV. To date, genomic selection has focused on a single trait. However, actual breeding often targets multiple correlated traits, and, therefore, joint analysis taking into consideration the correlation between traits, which might result in more accurate GBV prediction than analyzing each trait separately, is suitable for multi-trait genomic selection. This would require an extension of the prediction model for single-trait GBV to multi-trait case. As the computational burden of multi-trait analysis is even higher than that of single-trait analysis, an effective computational method for constructing a multi-trait prediction model is also needed. Results We described a Bayesian regression model incorporating variable selection for jointly predicting GBVs of multiple traits and devised both an MCMC iteration and variational approximation for Bayesian estimation of parameters in this multi-trait model. The proposed Bayesian procedures with MCMC iteration and variational approximation were referred to as MCBayes and varBayes, respectively. Using simulated datasets of SNP genotypes and phenotypes for three traits with high and low heritabilities, we compared the accuracy in predicting GBVs between multi-trait and single-trait analyses as well as between MCBayes and varBayes. The results showed that, compared to single-trait analysis, multi-trait analysis enabled much more accurate GBV prediction for low-heritability traits correlated with high-heritability traits, by utilizing the correlation structure between traits, while the prediction accuracy for uncorrelated low-heritability traits was comparable or less with multi-trait analysis in comparison with single-trait analysis depending on the setting for prior probability that a SNP has zero
Numerical evaluation of methods for computing tomographic projections
Zhuang, W.; Gopal, S.S.; Hebert, T.J.
1994-01-01
Methods for computing forward/back projections of 2-D images can be viewed as numerical integration techniques. The accuracy of any ray-driven projection method can be improved by increasing the number of ray-paths that are traced per projection bin. The accuracy of pixel-driven projection methods can be increased by dividing each pixel into a number of smaller sub-pixels and projecting each sub-pixel. The authors compared four competing methods of computing forward/back projections: bilinear interpolation, ray-tracing, pixel-driven projection based upon sub-pixels, and pixel-driven projection based upon circular, rather than square, pixels. This latter method is equivalent to a fast, bi-nonlinear interpolation. These methods and the choice of the number of ray-paths per projection bin or the number of sub-pixels per pixel present a trade-off between computational speed and accuracy. To solve the problem of assessing backprojection accuracy, the analytical inverse Fourier transform of the ramp filtered forward projection of the Shepp and Logan head phantom is derived
High-integrity software, computation and the scientific method
Hatton, L.
2012-01-01
Computation rightly occupies a central role in modern science. Datasets are enormous and the processing implications of some algorithms are equally staggering. With the continuing difficulties in quantifying the results of complex computations, it is of increasing importance to understand its role in the essentially Popperian scientific method. In this paper, some of the problems with computation, for example the long-term unquantifiable presence of undiscovered defect, problems with programming languages and process issues will be explored with numerous examples. One of the aims of the paper is to understand the implications of trying to produce high-integrity software and the limitations which still exist. Unfortunately Computer Science itself suffers from an inability to be suitably critical of its practices and has operated in a largely measurement-free vacuum since its earliest days. Within computer science itself, this has not been so damaging in that it simply leads to unconstrained creativity and a rapid turnover of new technologies. In the applied sciences however which have to depend on computational results, such unquantifiability significantly undermines trust. It is time this particular demon was put to rest. (author)
Zhao, Yingfeng; Liu, Sanyang
2016-01-01
We present a practical branch and bound algorithm for globally solving generalized linear multiplicative programming problem with multiplicative constraints. To solve the problem, a relaxation programming problem which is equivalent to a linear programming is proposed by utilizing a new two-phase relaxation technique. In the algorithm, lower and upper bounds are simultaneously obtained by solving some linear relaxation programming problems. Global convergence has been proved and results of some sample examples and a small random experiment show that the proposed algorithm is feasible and efficient.
Computational biology in the cloud: methods and new insights from computing at scale.
Kasson, Peter M
2013-01-01
The past few years have seen both explosions in the size of biological data sets and the proliferation of new, highly flexible on-demand computing capabilities. The sheer amount of information available from genomic and metagenomic sequencing, high-throughput proteomics, experimental and simulation datasets on molecular structure and dynamics affords an opportunity for greatly expanded insight, but it creates new challenges of scale for computation, storage, and interpretation of petascale data. Cloud computing resources have the potential to help solve these problems by offering a utility model of computing and storage: near-unlimited capacity, the ability to burst usage, and cheap and flexible payment models. Effective use of cloud computing on large biological datasets requires dealing with non-trivial problems of scale and robustness, since performance-limiting factors can change substantially when a dataset grows by a factor of 10,000 or more. New computing paradigms are thus often needed. The use of cloud platforms also creates new opportunities to share data, reduce duplication, and to provide easy reproducibility by making the datasets and computational methods easily available.
Review of Monte Carlo methods for particle multiplicity evaluation
Armesto-Pérez, Nestor
2005-01-01
I present a brief review of the existing models for particle multiplicity evaluation in heavy ion collisions which are at our disposal in the form of Monte Carlo simulators. Models are classified according to the physical mechanisms with which they try to describe the different stages of a high-energy collision between heavy nuclei. A comparison of predictions, as available at the beginning of year 2000, for multiplicities in central AuAu collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and PbPb collisions at the CERN Large Hadron Collider (LHC) is provided.
Review of Monte Carlo methods for particle multiplicity evaluation
Armesto, Nestor
2005-01-01
I present a brief review of the existing models for particle multiplicity evaluation in heavy ion collisions which are at our disposal in the form of Monte Carlo simulators. Models are classified according to the physical mechanisms with which they try to describe the different stages of a high-energy collision between heavy nuclei. A comparison of predictions, as available at the beginning of year 2000, for multiplicities in central AuAu collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and PbPb collisions at the CERN Large Hadron Collider (LHC) is provided
Stuive, Ilse
2007-01-01
Confirmatieve Factor Analyse (CFA) is een vaak gebruikte methode wanneer onderzoekers een bepaalde veronderstelling hebben over de indeling van items in één of meerdere subtests en willen onderzoeken of deze indeling ook wordt ondersteund door verzamelde onderzoeksgegevens. De meest gebruikte
BIOFEEDBACK: A NEW METHOD FOR CORRECTION OF MOTOR DISORDERS IN PATIENTS WITH MULTIPLE SCLEROSIS
Ya. S. Pekker
2014-01-01
Full Text Available Major disabling factors in multiple sclerosis is motor disorders. Rehabilitation of such violations is one of the most important medical and social problems. Currently, most of the role given to the development of methods for correction of motor disorders based on accessing natural resources of the human body. One of these methods is the adaptive control with biofeedback (BFB. The aim of our study was the correction of motor disorders in multiple sclerosis patients using biofeedback training. In the study, we have developed scenarios for training rehabilitation program computer EMG biofeedback aimed at correction of motor disorders in patients with multiple sclerosis (MS. The method was tested in the neurological clinic of SSMU. The study included 9 patients with definite diagnosis of MS with the presence of the clinical picture of combined pyramidal and cerebellar symptoms. Assessed the effectiveness of rehabilitation procedures biofeedback training using specialized scales (rating scale functional systems Kurtzke; questionnaire research quality of life – SF-36, evaluation of disease impact Profile – SIP and score on a scale fatigue – FSS. In the studied group of patients decreased score on a scale of fatigue (FSS, increased motor control (SIP2, the physical and mental components of health (SF-36. The tendency to reduce the amount of neurological deficit by reducing the points on the pyramidal Kurtske violations. Analysis of the exchange rate dynamics of biofeedback training on EMG for trained muscles indicates an increase in the recorded signal OEMG from session to session. Proved a tendency to increase strength and coordination trained muscles of patients studied.Positive results of biofeedback therapy in patients with MS can be recommended to use this method in the complex rehabilitation measures to correct motor and psycho-emotional disorders.
Mildenhall, Paula; Sherriff, Barbara
2017-06-01
Recent research indicates that using multimodal learning experiences can be effective in teaching mathematics. Using a social semiotic lens within a participationist framework, this paper reports on a professional learning collaboration with a primary school teacher designed to explore the use of metaphors and modalities in mathematics instruction. This video case study was conducted in a year 2 classroom over two terms, with the focus on building children's understanding of computational strategies. The findings revealed that the teacher was able to successfully plan both multimodal and multiple metaphor learning experiences that acted as semiotic resources to support the children's understanding of abstract mathematics. The study also led to implications for teaching when using multiple metaphors and multimodalities.
Multiple single-board-computer system for the KEK positron generator control
Nakahara, Kazuo; Abe, Isamu; Enomoto, Atsushi; Otake, Yuji; Urano, Takao
1986-01-01
The KEK positron generator is controlled by means of a distributed microprocessor network. The control system is composed of three kinds of equipment: device controllers for the linac equipment, operation management stations and a communication network. Individual linac equipment has its own microprocessor-based controller. A multiple single board computer (SBC) system is used for communication control and for equipment surveillance; it has a database containing communication and linac equipment status information. The linac operation management that should be the most soft part in the control system, is separated from the multiple SBC system and is carried out by work-stations. The principle that every processor executes only one task is maintained throughout the control system. This made the software architecture very simple. (orig.)
Computational Methods for Modeling Aptamers and Designing Riboswitches
Sha Gong
2017-11-01
Full Text Available Riboswitches, which are located within certain noncoding RNA region perform functions as genetic “switches”, regulating when and where genes are expressed in response to certain ligands. Understanding the numerous functions of riboswitches requires computation models to predict structures and structural changes of the aptamer domains. Although aptamers often form a complex structure, computational approaches, such as RNAComposer and Rosetta, have already been applied to model the tertiary (three-dimensional (3D structure for several aptamers. As structural changes in aptamers must be achieved within the certain time window for effective regulation, kinetics is another key point for understanding aptamer function in riboswitch-mediated gene regulation. The coarse-grained self-organized polymer (SOP model using Langevin dynamics simulation has been successfully developed to investigate folding kinetics of aptamers, while their co-transcriptional folding kinetics can be modeled by the helix-based computational method and BarMap approach. Based on the known aptamers, the web server Riboswitch Calculator and other theoretical methods provide a new tool to design synthetic riboswitches. This review will represent an overview of these computational methods for modeling structure and kinetics of riboswitch aptamers and for designing riboswitches.
An Exact Method for the Double TSP with Multiple Stacks
Lusby, Richard Martin; Larsen, Jesper; Ehrgott, Matthias
2010-01-01
The double travelling salesman problem with multiple stacks (DTSPMS) is a pickup and delivery problem in which all pickups must be completed before any deliveries can be made. The problem originates from a real-life application where a 40 foot container (configured as 3 columns of 11 rows) is used...
An Exact Method for the Double TSP with Multiple Stacks
Larsen, Jesper; Lusby, Richard Martin; Ehrgott, Matthias
The double travelling salesman problem with multiple stacks (DTSPMS) is a pickup and delivery problem in which all pickups must be completed before any deliveries can be made. The problem originates from a real-life application where a 40 foot container (configured as 3 columns of 11 rows) is used...
A Lévy HJM Multiple-Curve Model with Application to CVA Computation
Crépey, Stéphane; Grbac, Zorana; Ngor, Nathalie
2015-01-01
, the calibration to OTM swaptions guaranteeing that the model correctly captures volatility smile effects and the calibration to co-terminal ATM swaptions ensuring an appropriate term structure of the volatility in the model. To account for counterparty risk and funding issues, we use the calibrated multiple......-curve model as an underlying model for CVA computation. We follow a reduced-form methodology through which the problem of pricing the counterparty risk and funding costs can be reduced to a pre-default Markovian BSDE, or an equivalent semi-linear PDE. As an illustration, we study the case of a basis swap...... and a related swaption, for which we compute the counterparty risk and funding adjustments...
Computational electrodynamics the finite-difference time-domain method
Taflove, Allen
2005-01-01
This extensively revised and expanded third edition of the Artech House bestseller, Computational Electrodynamics: The Finite-Difference Time-Domain Method, offers engineers the most up-to-date and definitive resource on this critical method for solving Maxwell's equations. The method helps practitioners design antennas, wireless communications devices, high-speed digital and microwave circuits, and integrated optical devices with unsurpassed efficiency. There has been considerable advancement in FDTD computational technology over the past few years, and the third edition brings professionals the very latest details with entirely new chapters on important techniques, major updates on key topics, and new discussions on emerging areas such as nanophotonics. What's more, to supplement the third edition, the authors have created a Web site with solutions to problems, downloadable graphics and videos, and updates, making this new edition the ideal textbook on the subject as well.
A Computationally Efficient Method for Polyphonic Pitch Estimation
Ruohua Zhou
2009-01-01
Full Text Available This paper presents a computationally efficient method for polyphonic pitch estimation. The method employs the Fast Resonator Time-Frequency Image (RTFI as the basic time-frequency analysis tool. The approach is composed of two main stages. First, a preliminary pitch estimation is obtained by means of a simple peak-picking procedure in the pitch energy spectrum. Such spectrum is calculated from the original RTFI energy spectrum according to harmonic grouping principles. Then the incorrect estimations are removed according to spectral irregularity and knowledge of the harmonic structures of the music notes played on commonly used music instruments. The new approach is compared with a variety of other frame-based polyphonic pitch estimation methods, and results demonstrate the high performance and computational efficiency of the approach.
Evolutionary Computation Methods and their applications in Statistics
Francesco Battaglia
2013-05-01
Full Text Available A brief discussion of the genesis of evolutionary computation methods, their relationship to artificial intelligence, and the contribution of genetics and Darwin’s theory of natural evolution is provided. Then, the main evolutionary computation methods are illustrated: evolution strategies, genetic algorithms, estimation of distribution algorithms, differential evolution, and a brief description of some evolutionary behavior methods such as ant colony and particle swarm optimization. We also discuss the role of the genetic algorithm for multivariate probability distribution random generation, rather than as a function optimizer. Finally, some relevant applications of genetic algorithm to statistical problems are reviewed: selection of variables in regression, time series model building, outlier identification, cluster analysis, design of experiments.
Variational-moment method for computing magnetohydrodynamic equilibria
Lao, L.L.
1983-08-01
A fast yet accurate method to compute magnetohydrodynamic equilibria is provided by the variational-moment method, which is similar to the classical Rayleigh-Ritz-Galerkin approximation. The equilibrium solution sought is decomposed into a spectral representation. The partial differential equations describing the equilibrium are then recast into their equivalent variational form and systematically reduced to an optimum finite set of coupled ordinary differential equations. An appropriate spectral decomposition can make the series representing the solution coverge rapidly and hence substantially reduces the amount of computational time involved. The moment method was developed first to compute fixed-boundary inverse equilibria in axisymmetric toroidal geometry, and was demonstrated to be both efficient and accurate. The method since has been generalized to calculate free-boundary axisymmetric equilibria, to include toroidal plasma rotation and pressure anisotropy, and to treat three-dimensional toroidal geometry. In all these formulations, the flux surfaces are assumed to be smooth and nested so that the solutions can be decomposed in Fourier series in inverse coordinates. These recent developments and the advantages and limitations of the moment method are reviewed. The use of alternate coordinates for decomposition is discussed
Computer-aided methods of determining thyristor thermal transients
Lu, E.; Bronner, G.
1988-08-01
An accurate tracing of the thyristor thermal response is investigated. This paper offers several alternatives for thermal modeling and analysis by using an electrical circuit analog: topological method, convolution integral method, etc. These methods are adaptable to numerical solutions and well suited to the use of the digital computer. The thermal analysis of thyristors was performed for the 1000 MVA converter system at the Princeton Plasma Physics Laboratory. Transient thermal impedance curves for individual thyristors in a given cooling arrangement were known from measurements and from manufacturer's data. The analysis pertains to almost any loading case, and the results are obtained in a numerical or a graphical format. 6 refs., 9 figs
HOLM,ELIZABETH A.; BATTAILE,CORBETT C.; BUCHHEIT,THOMAS E.; FANG,HUEI ELIOT; RINTOUL,MARK DANIEL; VEDULA,VENKATA R.; GLASS,S. JILL; KNOROVSKY,GERALD A.; NEILSEN,MICHAEL K.; WELLMAN,GERALD W.; SULSKY,DEBORAH; SHEN,YU-LIN; SCHREYER,H. BUCK
2000-04-01
Computational materials simulations have traditionally focused on individual phenomena: grain growth, crack propagation, plastic flow, etc. However, real materials behavior results from a complex interplay between phenomena. In this project, the authors explored methods for coupling mesoscale simulations of microstructural evolution and micromechanical response. In one case, massively parallel (MP) simulations for grain evolution and microcracking in alumina stronglink materials were dynamically coupled. In the other, codes for domain coarsening and plastic deformation in CuSi braze alloys were iteratively linked. this program provided the first comparison of two promising ways to integrate mesoscale computer codes. Coupled microstructural/micromechanical codes were applied to experimentally observed microstructures for the first time. In addition to the coupled codes, this project developed a suite of new computational capabilities (PARGRAIN, GLAD, OOF, MPM, polycrystal plasticity, front tracking). The problem of plasticity length scale in continuum calculations was recognized and a solution strategy was developed. The simulations were experimentally validated on stockpile materials.
Fast calculation method for computer-generated cylindrical holograms.
Yamaguchi, Takeshi; Fujii, Tomohiko; Yoshikawa, Hiroshi
2008-07-01
Since a general flat hologram has a limited viewable area, we usually cannot see the other side of a reconstructed object. There are some holograms that can solve this problem. A cylindrical hologram is well known to be viewable in 360 deg. Most cylindrical holograms are optical holograms, but there are few reports of computer-generated cylindrical holograms. The lack of computer-generated cylindrical holograms is because the spatial resolution of output devices is not great enough; therefore, we have to make a large hologram or use a small object to fulfill the sampling theorem. In addition, in calculating the large fringe, the calculation amount increases in proportion to the hologram size. Therefore, we propose what we believe to be a new calculation method for fast calculation. Then, we print these fringes with our prototype fringe printer. As a result, we obtain a good reconstructed image from a computer-generated cylindrical hologram.
Computational methods in metabolic engineering for strain design.
Long, Matthew R; Ong, Wai Kit; Reed, Jennifer L
2015-08-01
Metabolic engineering uses genetic approaches to control microbial metabolism to produce desired compounds. Computational tools can identify new biological routes to chemicals and the changes needed in host metabolism to improve chemical production. Recent computational efforts have focused on exploring what compounds can be made biologically using native, heterologous, and/or enzymes with broad specificity. Additionally, computational methods have been developed to suggest different types of genetic modifications (e.g. gene deletion/addition or up/down regulation), as well as suggest strategies meeting different criteria (e.g. high yield, high productivity, or substrate co-utilization). Strategies to improve the runtime performances have also been developed, which allow for more complex metabolic engineering strategies to be identified. Future incorporation of kinetic considerations will further improve strain design algorithms. Copyright © 2015 Elsevier Ltd. All rights reserved.
Method of Computer-aided Instruction in Situation Control Systems
Anatoliy O. Kargin
2013-01-01
Full Text Available The article considers the problem of computer-aided instruction in context-chain motivated situation control system of the complex technical system behavior. The conceptual and formal models of situation control with practical instruction are considered. Acquisition of new behavior knowledge is presented as structural changes in system memory in the form of situational agent set. Model and method of computer-aided instruction represent formalization, based on the nondistinct theories by physiologists and cognitive psychologists.The formal instruction model describes situation and reaction formation and dependence on different parameters, effecting education, such as the reinforcement value, time between the stimulus, action and the reinforcement. The change of the contextual link between situational elements when using is formalized.The examples and results of computer instruction experiments of the robot device “LEGO MINDSTORMS NXT”, equipped with ultrasonic distance, touch, light sensors.
Turner, L.R.; Shindler, J.
1984-09-01
For upcoming fusion experiments and future fusion reactors, superconducting magnetic have been chosen or considered which employ cooling by pool-boiling HeI, by HeII, and by internally flowing HeI. The choice of conductor and cooling method should be determined in part by the response of the magnet to sudden localized heat pulses of various magnitudes. The paper describes the successful computer simulation of multiple stability in internally cooled conductors, as observed experimentally, using the computer code SSICC. It also describes the modeling of helium replenishment in the cooling channels of a bath-cooled conductor, using the computer code TASS
Practical methods to improve the development of computational software
Osborne, A. G.; Harding, D. W.; Deinert, M. R.
2013-01-01
The use of computation has become ubiquitous in science and engineering. As the complexity of computer codes has increased, so has the need for robust methods to minimize errors. Past work has show that the number of functional errors is related the number of commands that a code executes. Since the late 1960's, major participants in the field of computation have encouraged the development of best practices for programming to help reduce coder induced error, and this has lead to the emergence of 'software engineering' as a field of study. Best practices for coding and software production have now evolved and become common in the development of commercial software. These same techniques, however, are largely absent from the development of computational codes by research groups. Many of the best practice techniques from the professional software community would be easy for research groups in nuclear science and engineering to adopt. This paper outlines the history of software engineering, as well as issues in modern scientific computation, and recommends practices that should be adopted by individual scientific programmers and university research groups. (authors)
Endo, Tomohiro
2011-01-01
In this paper, an alternative definition of a neutron multiplication factor, detected-neutron multiplication factor kdet, is produced for the neutron source multiplication method..(NSM). By using kdet, a search strategy of appropriate detector position for NSM is also proposed. The NSM is one of the practical subcritical measurement techniques, i.e., the NSM does not require any special equipment other than a stationary external neutron source and an ordinary neutron detector. Additionally, the NSM method is based on steady-state analysis, so that this technique is very suitable for quasi real-time measurement. It is noted that the correction factors play important roles in order to accurately estimate subcriticality from the measured neutron count rates. The present paper aims to clarify how to correct the subcriticality measured by the NSM method, the physical meaning of the correction factors, and how to reduce the impact of correction factors by setting a neutron detector at an appropriate detector position
Computing homography with RANSAC algorithm: a novel method of registration
Li, Xiaowei; Liu, Yue; Wang, Yongtian; Yan, Dayuan
2005-02-01
An AR (Augmented Reality) system can integrate computer-generated objects with the image sequences of real world scenes in either an off-line or a real-time way. Registration, or camera pose estimation, is one of the key techniques to determine its performance. The registration methods can be classified as model-based and move-matching. The former approach can accomplish relatively accurate registration results, but it requires the precise model of the scene, which is hard to be obtained. The latter approach carries out registration by computing the ego-motion of the camera. Because it does not require the prior-knowledge of the scene, its registration results sometimes turn out to be less accurate. When the model defined is as simple as a plane, a mixed method is introduced to take advantages of the virtues of the two methods mentioned above. Although unexpected objects often occlude this plane in an AR system, one can still try to detect corresponding points with a contract-expand method, while this will import erroneous correspondences. Computing homography with RANSAC algorithm is used to overcome such shortcomings. Using the robustly estimated homography resulted from RANSAC, the camera projective matrix can be recovered and thus registration is accomplished even when the markers are lost in the scene.
Pair Programming as a Modern Method of Teaching Computer Science
Irena Nančovska Šerbec
2008-10-01
Full Text Available At the Faculty of Education, University of Ljubljana we educate future computer science teachers. Beside didactical, pedagogical, mathematical and other interdisciplinary knowledge, students gain knowledge and skills of programming that are crucial for computer science teachers. For all courses, the main emphasis is the absorption of professional competences, related to the teaching profession and the programming profile. The latter are selected according to the well-known document, the ACM Computing Curricula. The professional knowledge is therefore associated and combined with the teaching knowledge and skills. In the paper we present how to achieve competences related to programming by using different didactical models (semiotic ladder, cognitive objectives taxonomy, problem solving and modern teaching method “pair programming”. Pair programming differs from standard methods (individual work, seminars, projects etc.. It belongs to the extreme programming as a discipline of software development and is known to have positive effects on teaching first programming language. We have experimentally observed pair programming in the introductory programming course. The paper presents and analyzes the results of using this method: the aspects of satisfaction during programming and the level of gained knowledge. The results are in general positive and demonstrate the promising usage of this teaching method.
Applications of meshless methods for damage computations with finite strains
Pan Xiaofei; Yuan Huang
2009-01-01
Material defects such as cavities have great effects on the damage process in ductile materials. Computations based on finite element methods (FEMs) often suffer from instability due to material failure as well as large distortions. To improve computational efficiency and robustness the element-free Galerkin (EFG) method is applied in the micro-mechanical constitute damage model proposed by Gurson and modified by Tvergaard and Needleman (the GTN damage model). The EFG algorithm is implemented in the general purpose finite element code ABAQUS via the user interface UEL. With the help of the EFG method, damage processes in uniaxial tension specimens and notched specimens are analyzed and verified with experimental data. Computational results reveal that the damage which takes place in the interior of specimens will extend to the exterior and cause fracture of specimens; the damage is a fast procedure relative to the whole tensing process. The EFG method provides more stable and robust numerical solution in comparing with the FEM analysis
Improved computation method in residual life estimation of structural components
Maksimović Stevan M.
2013-01-01
Full Text Available This work considers the numerical computation methods and procedures for the fatigue crack growth predicting of cracked notched structural components. Computation method is based on fatigue life prediction using the strain energy density approach. Based on the strain energy density (SED theory, a fatigue crack growth model is developed to predict the lifetime of fatigue crack growth for single or mixed mode cracks. The model is based on an equation expressed in terms of low cycle fatigue parameters. Attention is focused on crack growth analysis of structural components under variable amplitude loads. Crack growth is largely influenced by the effect of the plastic zone at the front of the crack. To obtain efficient computation model plasticity-induced crack closure phenomenon is considered during fatigue crack growth. The use of the strain energy density method is efficient for fatigue crack growth prediction under cyclic loading in damaged structural components. Strain energy density method is easy for engineering applications since it does not require any additional determination of fatigue parameters (those would need to be separately determined for fatigue crack propagation phase, and low cyclic fatigue parameters are used instead. Accurate determination of fatigue crack closure has been a complex task for years. The influence of this phenomenon can be considered by means of experimental and numerical methods. Both of these models are considered. Finite element analysis (FEA has been shown to be a powerful and useful tool1,6 to analyze crack growth and crack closure effects. Computation results are compared with available experimental results. [Projekat Ministarstva nauke Republike Srbije, br. OI 174001
An introduction to computer simulation methods applications to physical systems
Gould, Harvey; Christian, Wolfgang
2007-01-01
Now in its third edition, this book teaches physical concepts using computer simulations. The text incorporates object-oriented programming techniques and encourages readers to develop good programming habits in the context of doing physics. Designed for readers at all levels , An Introduction to Computer Simulation Methods uses Java, currently the most popular programming language. Introduction, Tools for Doing Simulations, Simulating Particle Motion, Oscillatory Systems, Few-Body Problems: The Motion of the Planets, The Chaotic Motion of Dynamical Systems, Random Processes, The Dynamics of Many Particle Systems, Normal Modes and Waves, Electrodynamics, Numerical and Monte Carlo Methods, Percolation, Fractals and Kinetic Growth Models, Complex Systems, Monte Carlo Simulations of Thermal Systems, Quantum Systems, Visualization and Rigid Body Dynamics, Seeing in Special and General Relativity, Epilogue: The Unity of Physics For all readers interested in developing programming habits in the context of doing phy...
NATO Advanced Study Institute on Methods in Computational Molecular Physics
Diercksen, Geerd
1992-01-01
This volume records the lectures given at a NATO Advanced Study Institute on Methods in Computational Molecular Physics held in Bad Windsheim, Germany, from 22nd July until 2nd. August, 1991. This NATO Advanced Study Institute sought to bridge the quite considerable gap which exist between the presentation of molecular electronic structure theory found in contemporary monographs such as, for example, McWeeny's Methods 0/ Molecular Quantum Mechanics (Academic Press, London, 1989) or Wilson's Electron correlation in moleeules (Clarendon Press, Oxford, 1984) and the realization of the sophisticated computational algorithms required for their practical application. It sought to underline the relation between the electronic structure problem and the study of nuc1ear motion. Software for performing molecular electronic structure calculations is now being applied in an increasingly wide range of fields in both the academic and the commercial sectors. Numerous applications are reported in areas as diverse as catalysi...
Comparing the index-flood and multiple-regression methods using L-moments
Malekinezhad, H.; Nachtnebel, H. P.; Klik, A.
In arid and semi-arid regions, the length of records is usually too short to ensure reliable quantile estimates. Comparing index-flood and multiple-regression analyses based on L-moments was the main objective of this study. Factor analysis was applied to determine main influencing variables on flood magnitude. Ward’s cluster and L-moments approaches were applied to several sites in the Namak-Lake basin in central Iran to delineate homogeneous regions based on site characteristics. Homogeneity test was done using L-moments-based measures. Several distributions were fitted to the regional flood data and index-flood and multiple-regression methods as two regional flood frequency methods were compared. The results of factor analysis showed that length of main waterway, compactness coefficient, mean annual precipitation, and mean annual temperature were the main variables affecting flood magnitude. The study area was divided into three regions based on the Ward’s method of clustering approach. The homogeneity test based on L-moments showed that all three regions were acceptably homogeneous. Five distributions were fitted to the annual peak flood data of three homogeneous regions. Using the L-moment ratios and the Z-statistic criteria, GEV distribution was identified as the most robust distribution among five candidate distributions for all the proposed sub-regions of the study area, and in general, it was concluded that the generalised extreme value distribution was the best-fit distribution for every three regions. The relative root mean square error (RRMSE) measure was applied for evaluating the performance of the index-flood and multiple-regression methods in comparison with the curve fitting (plotting position) method. In general, index-flood method gives more reliable estimations for various flood magnitudes of different recurrence intervals. Therefore, this method should be adopted as regional flood frequency method for the study area and the Namak-Lake basin
An Adaptive Reordered Method for Computing PageRank
Yi-Ming Bu
2013-01-01
Full Text Available We propose an adaptive reordered method to deal with the PageRank problem. It has been shown that one can reorder the hyperlink matrix of PageRank problem to calculate a reduced system and get the full PageRank vector through forward substitutions. This method can provide a speedup for calculating the PageRank vector. We observe that in the existing reordered method, the cost of the recursively reordering procedure could offset the computational reduction brought by minimizing the dimension of linear system. With this observation, we introduce an adaptive reordered method to accelerate the total calculation, in which we terminate the reordering procedure appropriately instead of reordering to the end. Numerical experiments show the effectiveness of this adaptive reordered method.
Experiences using DAKOTA stochastic expansion methods in computational simulations.
Templeton, Jeremy Alan; Ruthruff, Joseph R.
2012-01-01
Uncertainty quantification (UQ) methods bring rigorous statistical connections to the analysis of computational and experiment data, and provide a basis for probabilistically assessing margins associated with safety and reliability. The DAKOTA toolkit developed at Sandia National Laboratories implements a number of UQ methods, which are being increasingly adopted by modeling and simulation teams to facilitate these analyses. This report disseminates results as to the performance of DAKOTA's stochastic expansion methods for UQ on a representative application. Our results provide a number of insights that may be of interest to future users of these methods, including the behavior of the methods in estimating responses at varying probability levels, and the expansion levels for the methodologies that may be needed to achieve convergence.
Advanced soft computing diagnosis method for tumour grading.
Papageorgiou, E I; Spyridonos, P P; Stylios, C D; Ravazoula, P; Groumpos, P P; Nikiforidis, G N
2006-01-01
To develop an advanced diagnostic method for urinary bladder tumour grading. A novel soft computing modelling methodology based on the augmentation of fuzzy cognitive maps (FCMs) with the unsupervised active Hebbian learning (AHL) algorithm is applied. One hundred and twenty-eight cases of urinary bladder cancer were retrieved from the archives of the Department of Histopathology, University Hospital of Patras, Greece. All tumours had been characterized according to the classical World Health Organization (WHO) grading system. To design the FCM model for tumour grading, three experts histopathologists defined the main histopathological features (concepts) and their impact on grade characterization. The resulted FCM model consisted of nine concepts. Eight concepts represented the main histopathological features for tumour grading. The ninth concept represented the tumour grade. To increase the classification ability of the FCM model, the AHL algorithm was applied to adjust the weights of the FCM. The proposed FCM grading model achieved a classification accuracy of 72.5%, 74.42% and 95.55% for tumours of grades I, II and III, respectively. An advanced computerized method to support tumour grade diagnosis decision was proposed and developed. The novelty of the method is based on employing the soft computing method of FCMs to represent specialized knowledge on histopathology and on augmenting FCMs ability using an unsupervised learning algorithm, the AHL. The proposed method performs with reasonably high accuracy compared to other existing methods and at the same time meets the physicians' requirements for transparency and explicability.
Geometric calibration method for multiple-head cone-beam SPECT system
Rizo, P.; Grangeat, P.; Guillemaud, R.
1994-01-01
A method is presented for estimating the geometrical parameters of cone beam systems with multiple heads, each head having its own orientation. In tomography, for each head, the relative position of the rotation axis and f the collimator do not change during the data acquisition. The authors thus can separate the parameters into intrinsic parameters and extrinsic parameters. The intrinsic parameters describe the detection system geometry and the extrinsic parameters the position of the detection system with respect to the rotation axis. Intrinsic parameters must be estimated each time the acquisition geometry is modified. Extrinsic parameters are estimated by minimizing the distances between the measured position of a point source projection and the computed position obtained using the estimated extrinsic parameters. The main advantage of this method is that the extrinsic parameters are only weakly correlated when the intrinsic parameters are known. Thus the authors can use any simple least square error minimization method to perform the estimation of the extrinsic parameters. Giving a fixed value to the distance between the point source and the rotation axis in the estimation process, ensures the coherence of the extrinsic parameters between each head. They show that with this calibration method, the full width at half maximum measured with point sources is very close to the theoretical one, and remains almost unchanged when more than one head is used. Simulation results and reconstructions on a Jaszczak phantom are presented that show the capabilities of this method
Kim, Sue Min; Cook, Kyung Hoon; Lee, Il Jae; Park, Dong Ha; Park, Myong Chul
2017-04-01
In our hospital, an adverse event reporting system was initiated that alerts the plastic surgery department immediately after suspecting contrast media extravasation injury. This system is particularly important for a large volume of extravasation during power injector use. Between March 2011 and May 2015, a retrospective chart review was performed on all patients experiencing contrast media extravasation while being treated at our hospital. Immediate treatment by squeezing with multiple slit incisions was conducted for a portion of these patients. Eighty cases of extravasation were reported from approximately 218 000 computed tomography scans. The expected extravasation volume was larger than 50 ml, or severe pressure was felt on the affected limb in 23 patients. They were treated with multiple slit incisions followed by squeezing. Oedema of the affected limb disappeared after 1-2 hours after treatment, and the skin incisions healed within a week. We propose a set of guidelines for the initial management of contrast media extravasation injuries for a timely intervention. For large-volume extravasation cases, immediate management with multiple slit incisions is safe and effective in reducing the swelling quickly, preventing patient discomfort and decreasing skin and soft tissue problems. © 2016 Medicalhelplines.com Inc and John Wiley & Sons Ltd.
Splitting method for computing coupled hydrodynamic and structural response
Ash, J.E.
1977-01-01
A numerical method is developed for application to unsteady fluid dynamics problems, in particular to the mechanics following a sudden release of high energy. Solution of the initial compressible flow phase provides input to a power-series method for the incompressible fluid motions. The system is split into spatial and time domains leading to the convergent computation of a sequence of elliptic equations. Two sample problems are solved, the first involving an underwater explosion and the second the response of a nuclear reactor containment shell structure to a hypothetical core accident. The solutions are correlated with experimental data
Complex Data Modeling and Computationally Intensive Statistical Methods
Mantovan, Pietro
2010-01-01
The last years have seen the advent and development of many devices able to record and store an always increasing amount of complex and high dimensional data; 3D images generated by medical scanners or satellite remote sensing, DNA microarrays, real time financial data, system control datasets. The analysis of this data poses new challenging problems and requires the development of novel statistical models and computational methods, fueling many fascinating and fast growing research areas of modern statistics. The book offers a wide variety of statistical methods and is addressed to statistici
Computational methods for planning and evaluating geothermal energy projects
Goumas, M.G.; Lygerou, V.A.; Papayannakis, L.E.
1999-01-01
In planning, designing and evaluating a geothermal energy project, a number of technical, economic, social and environmental parameters should be considered. The use of computational methods provides a rigorous analysis improving the decision-making process. This article demonstrates the application of decision-making methods developed in operational research for the optimum exploitation of geothermal resources. Two characteristic problems are considered: (1) the economic evaluation of a geothermal energy project under uncertain conditions using a stochastic analysis approach and (2) the evaluation of alternative exploitation schemes for optimum development of a low enthalpy geothermal field using a multicriteria decision-making procedure. (Author)
Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments
Lane, Peter C. R.; Gobet, Fernand
2013-03-01
Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the `speciated non-dominated sorting genetic algorithm' for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.
Yanni Li
2012-01-01
Full Text Available Searching for the multiple longest common subsequences (MLCS has significant applications in the areas of bioinformatics, information processing, and data mining, and so forth, Although a few parallel MLCS algorithms have been proposed, the efficiency and effectiveness of the algorithms are not satisfactory with the increasing complexity and size of biologic data. To overcome the shortcomings of the existing MLCS algorithms, and considering that MapReduce parallel framework of cloud computing being a promising technology for cost-effective high performance parallel computing, a novel finite automaton (FA based on cloud computing called FACC is proposed under MapReduce parallel framework, so as to exploit a more efficient and effective general parallel MLCS algorithm. FACC adopts the ideas of matched pairs and finite automaton by preprocessing sequences, constructing successor tables, and common subsequences finite automaton to search for MLCS. Simulation experiments on a set of benchmarks from both real DNA and amino acid sequences have been conducted and the results show that the proposed FACC algorithm outperforms the current leading parallel MLCS algorithm FAST-MLCS.
Estimation of subcriticality by neutron source multiplication method
Sakurai, Kiyoshi; Suzaki, Takenori; Arakawa, Takuya; Naito, Yoshitaka
1995-03-01
Subcritical cores were constructed in a core tank of the TCA by arraying 2.6% enriched UO 2 fuel rods into nxn square lattices of 1.956 cm pitch. Vertical distributions of the neutron count rates for the fifteen subcritical cores (n=17, 16, 14, 11, 8) with different water levels were measured at 5 cm interval with 235 U micro-fission counters at the in-core and out-core positions arranging a 252 C f neutron source at near core center. The continuous energy Monte Carlo code MCNP-4A was used for the calculation of neutron multiplication factors and neutron count rates. In this study, important conclusions are as follows: (1) Differences of neutron multiplication factors resulted from exponential experiment and MCNP-4A are below 1% in most cases. (2) Standard deviations of neutron count rates calculated from MCNP-4A with 500000 histories are 5-8%. The calculated neutron count rates are consistent with the measured one. (author)
Automated uncertainty analysis methods in the FRAP computer codes
Peck, S.O.
1980-01-01
A user oriented, automated uncertainty analysis capability has been incorporated in the Fuel Rod Analysis Program (FRAP) computer codes. The FRAP codes have been developed for the analysis of Light Water Reactor fuel rod behavior during steady state (FRAPCON) and transient (FRAP-T) conditions as part of the United States Nuclear Regulatory Commission's Water Reactor Safety Research Program. The objective of uncertainty analysis of these codes is to obtain estimates of the uncertainty in computed outputs of the codes is to obtain estimates of the uncertainty in computed outputs of the codes as a function of known uncertainties in input variables. This paper presents the methods used to generate an uncertainty analysis of a large computer code, discusses the assumptions that are made, and shows techniques for testing them. An uncertainty analysis of FRAP-T calculated fuel rod behavior during a hypothetical loss-of-coolant transient is presented as an example and carried through the discussion to illustrate the various concepts
Comparison of different methods for shielding design in computed tomography
Ciraj-Bjelac, O.; Arandjic, D.; Kosutic, D.
2011-01-01
The purpose of this work is to compare different methods for shielding calculation in computed tomography (CT). The BIR-IPEM (British Inst. of Radiology and Inst. of Physics in Engineering in Medicine) and NCRP (National Council on Radiation Protection) method were used for shielding thickness calculation. Scattered dose levels and calculated barrier thickness were also compared with those obtained by scatter dose measurements in the vicinity of a dedicated CT unit. Minimal requirement for protective barriers based on BIR-IPEM method ranged between 1.1 and 1.4 mm of lead demonstrating underestimation of up to 20 % and overestimation of up to 30 % when compared with thicknesses based on measured dose levels. For NCRP method, calculated thicknesses were 33 % higher (27-42 %). BIR-IPEM methodology-based results were comparable with values based on scattered dose measurements, while results obtained using NCRP methodology demonstrated an overestimation of the minimal required barrier thickness. (authors)
A feature point identification method for positron emission particle tracking with multiple tracers
Wiggins, Cody, E-mail: cwiggin2@vols.utk.edu [University of Tennessee-Knoxville, Department of Physics and Astronomy, 1408 Circle Drive, Knoxville, TN 37996 (United States); Santos, Roque [University of Tennessee-Knoxville, Department of Nuclear Engineering (United States); Escuela Politécnica Nacional, Departamento de Ciencias Nucleares (Ecuador); Ruggles, Arthur [University of Tennessee-Knoxville, Department of Nuclear Engineering (United States)
2017-01-21
A novel detection algorithm for Positron Emission Particle Tracking (PEPT) with multiple tracers based on optical feature point identification (FPI) methods is presented. This new method, the FPI method, is compared to a previous multiple PEPT method via analyses of experimental and simulated data. The FPI method outperforms the older method in cases of large particle numbers and fine time resolution. Simulated data show the FPI method to be capable of identifying 100 particles at 0.5 mm average spatial error. Detection error is seen to vary with the inverse square root of the number of lines of response (LORs) used for detection and increases as particle separation decreases. - Highlights: • A new approach to positron emission particle tracking is presented. • Using optical feature point identification analogs, multiple particle tracking is achieved. • Method is compared to previous multiple particle method. • Accuracy and applicability of method is explored.
Razek, Ahmed Abdel Khalek Abdel; Ezzat, Amany; Azmy, Emad; Tharwat, Nehal
2013-08-01
The authors evaluated the role of whole-body 64-slice multidetector computed tomography (WB-MDCT) in treatment planning for multiple myeloma. This was a prospective study of 28 consecutive patients with multiple myeloma (19 men, nine women; age range, 51-73 years; mean age, 60 years) who underwent WB-MDCT and conventional radiography (CR) of the skeleton. The images were interpreted for the presence of bony lesions, medullary lesions, fractures and extraosseous lesions. We evaluated any changes in treatment planning as a result of WB-MDCT findings. WB-MDCT was superior to CR for detecting bony lesions (p=0.001), especially of the spine (p=0.001) and thoracic cage (p=0.006). WB-MDCT upstaged 14 patients, with a significant difference in staging (p=0.002) between WB-MDCT and CR. Medullary involvement either focal (n=6) or diffuse (n=3) had a positive correlation with the overall score (r=0.790) and stage (r=0.618) of disease. Spine fractures were better detected at WB-MDCT (n=4) than at CR (n=2). Extraosseous soft tissue lesions (n=7) were detected only at WB-MDCT. Findings detected at the WB-MDCT led to changes in the patient's treatment plan in 39% of cases. Upstaging of seven patients (25%) altered the medical treatment plan, and four of 28 (14%) patients required additional radiotherapy (7%) and vertebroplasty (7%). We conclude that WB-MDCT has an impact on treatment planning and prognosis in patients with multiple myeloma, as it has high rate of detecting cortical and medullary bone lesions, spinal fracture and extraosseous lesions. This information may alter treatment planning in multiple myeloma due to disease upstaging and detection of spine fracture and extraosseous spinal lesions.
Multiple Beta Spectrum Analysis Method Based on Spectrum Fitting
Lee, Uk Jae; Jung, Yun Song; Kim, Hee Reyoung [UNIST, Ulsan (Korea, Republic of)
2016-05-15
When the sample of several mixed radioactive nuclides is measured, it is difficult to divide each nuclide due to the overlapping of spectrums. For this reason, simple mathematical analysis method for spectrum analysis of the mixed beta ray source has been studied. However, existing research was in need of more accurate spectral analysis method as it has a problem of accuracy. The study will describe the contents of the separation methods of the mixed beta ray source through the analysis of the beta spectrum slope based on the curve fitting to resolve the existing problem. The fitting methods including It was understood that sum of sine fitting method was the best one of such proposed methods as Fourier, polynomial, Gaussian and sum of sine to obtain equation for distribution of mixed beta spectrum. It was shown to be the most appropriate for the analysis of the spectrum with various ratios of mixed nuclides. It was thought that this method could be applied to rapid spectrum analysis of the mixed beta ray source.
AN EFFICIENT METHOD FOR AUTOMATIC ROAD EXTRACTION BASED ON MULTIPLE FEATURES FROM LiDAR DATA
Y. Li
2016-06-01
Full Text Available The road extraction in urban areas is difficult task due to the complicated patterns and many contextual objects. LiDAR data directly provides three dimensional (3D points with less occlusions and smaller shadows. The elevation information and surface roughness are distinguishing features to separate roads. However, LiDAR data has some disadvantages are not beneficial to object extraction, such as the irregular distribution of point clouds and lack of clear edges of roads. For these problems, this paper proposes an automatic road centerlines extraction method which has three major steps: (1 road center point detection based on multiple feature spatial clustering for separating road points from ground points, (2 local principal component analysis with least squares fitting for extracting the primitives of road centerlines, and (3 hierarchical grouping for connecting primitives into complete roads network. Compared with MTH (consist of Mean shift algorithm, Tensor voting, and Hough transform proposed in our previous article, this method greatly reduced the computational cost. To evaluate the proposed method, the Vaihingen data set, a benchmark testing data provided by ISPRS for “Urban Classification and 3D Building Reconstruction” project, was selected. The experimental results show that our method achieve the same performance by less time in road extraction using LiDAR data.
An Efficient Method for Automatic Road Extraction Based on Multiple Features from LiDAR Data
Li, Y.; Hu, X.; Guan, H.; Liu, P.
2016-06-01
The road extraction in urban areas is difficult task due to the complicated patterns and many contextual objects. LiDAR data directly provides three dimensional (3D) points with less occlusions and smaller shadows. The elevation information and surface roughness are distinguishing features to separate roads. However, LiDAR data has some disadvantages are not beneficial to object extraction, such as the irregular distribution of point clouds and lack of clear edges of roads. For these problems, this paper proposes an automatic road centerlines extraction method which has three major steps: (1) road center point detection based on multiple feature spatial clustering for separating road points from ground points, (2) local principal component analysis with least squares fitting for extracting the primitives of road centerlines, and (3) hierarchical grouping for connecting primitives into complete roads network. Compared with MTH (consist of Mean shift algorithm, Tensor voting, and Hough transform) proposed in our previous article, this method greatly reduced the computational cost. To evaluate the proposed method, the Vaihingen data set, a benchmark testing data provided by ISPRS for "Urban Classification and 3D Building Reconstruction" project, was selected. The experimental results show that our method achieve the same performance by less time in road extraction using LiDAR data.
Multiscale methods in turbulent combustion: strategies and computational challenges
Echekki, Tarek
2009-01-01
A principal challenge in modeling turbulent combustion flows is associated with their complex, multiscale nature. Traditional paradigms in the modeling of these flows have attempted to address this nature through different strategies, including exploiting the separation of turbulence and combustion scales and a reduced description of the composition space. The resulting moment-based methods often yield reasonable predictions of flow and reactive scalars' statistics under certain conditions. However, these methods must constantly evolve to address combustion at different regimes, modes or with dominant chemistries. In recent years, alternative multiscale strategies have emerged, which although in part inspired by the traditional approaches, also draw upon basic tools from computational science, applied mathematics and the increasing availability of powerful computational resources. This review presents a general overview of different strategies adopted for multiscale solutions of turbulent combustion flows. Within these strategies, some specific models are discussed or outlined to illustrate their capabilities and underlying assumptions. These strategies may be classified under four different classes, including (i) closure models for atomistic processes, (ii) multigrid and multiresolution strategies, (iii) flame-embedding strategies and (iv) hybrid large-eddy simulation-low-dimensional strategies. A combination of these strategies and models can potentially represent a robust alternative strategy to moment-based models; but a significant challenge remains in the development of computational frameworks for these approaches as well as their underlying theories. (topical review)
Mathematical modellings and computational methods for structural analysis of LMFBR's
Liu, W.K.; Lam, D.
1983-01-01
In this paper, two aspects of nuclear reactor problems are discussed, modelling techniques and computational methods for large scale linear and nonlinear analyses of LMFBRs. For nonlinear fluid-structure interaction problem with large deformation, arbitrary Lagrangian-Eulerian description is applicable. For certain linear fluid-structure interaction problem, the structural response spectrum can be found via 'added mass' approach. In a sense, the fluid inertia is accounted by a mass matrix added to the structural mass. The fluid/structural modes of certain fluid-structure problem can be uncoupled to get the reduced added mass. The advantage of this approach is that it can account for the many repeated structures of nuclear reactor. In regard to nonlinear dynamic problem, the coupled nonlinear fluid-structure equations usually have to be solved by direct time integration. The computation can be very expensive and time consuming for nonlinear problems. Thus, it is desirable to optimize the accuracy and computation effort by using implicit-explicit mixed time integration method. (orig.)
Teo, Timothy
2010-01-01
Purpose: The purpose of this paper is to examine the effect of gender on pre-service teachers' computer attitudes. Design/methodology/approach: A total of 157 pre-service teachers completed a survey questionnaire measuring their responses to four constructs which explain computer attitude. These were administered during the teaching term where…
Statistical Genetics Methods for Localizing Multiple Breast Cancer Genes
Ott, Jurg
1998-01-01
.... For a number of variables measured on a trait, a method, principal components of heritability, was developed that combines these variables in such a way that the resulting linear combination has highest heritability...
A numerical method to compute interior transmission eigenvalues
Kleefeld, Andreas
2013-01-01
In this paper the numerical calculation of eigenvalues of the interior transmission problem arising in acoustic scattering for constant contrast in three dimensions is considered. From the computational point of view existing methods are very expensive, and are only able to show the existence of such transmission eigenvalues. Furthermore, they have trouble finding them if two or more eigenvalues are situated closely together. We present a new method based on complex-valued contour integrals and the boundary integral equation method which is able to calculate highly accurate transmission eigenvalues. So far, this is the first paper providing such accurate values for various surfaces different from a sphere in three dimensions. Additionally, the computational cost is even lower than those of existing methods. Furthermore, the algorithm is capable of finding complex-valued eigenvalues for which no numerical results have been reported yet. Until now, the proof of existence of such eigenvalues is still open. Finally, highly accurate eigenvalues of the interior Dirichlet problem are provided and might serve as test cases to check newly derived Faber–Krahn type inequalities for larger transmission eigenvalues that are not yet available. (paper)
Laboratory Sequence in Computational Methods for Introductory Chemistry
Cody, Jason A.; Wiser, Dawn C.
2003-07-01
A four-exercise laboratory sequence for introductory chemistry integrating hands-on, student-centered experience with computer modeling has been designed and implemented. The progression builds from exploration of molecular shapes to intermolecular forces and the impact of those forces on chemical separations made with gas chromatography and distillation. The sequence ends with an exploration of molecular orbitals. The students use the computers as a tool; they build the molecules, submit the calculations, and interpret the results. Because of the construction of the sequence and its placement spanning the semester break, good laboratory notebook practices are reinforced and the continuity of course content and methods between semesters is emphasized. The inclusion of these techniques in the first year of chemistry has had a positive impact on student perceptions and student learning.
An analytical method for computing atomic contact areas in biomolecules.
Mach, Paul; Koehl, Patrice
2013-01-15
We propose a new analytical method for detecting and computing contacts between atoms in biomolecules. It is based on the alpha shape theory and proceeds in three steps. First, we compute the weighted Delaunay triangulation of the union of spheres representing the molecule. In the second step, the Delaunay complex is filtered to derive the dual complex. Finally, contacts between spheres are collected. In this approach, two atoms i and j are defined to be in contact if their centers are connected by an edge in the dual complex. The contact areas between atom i and its neighbors are computed based on the caps formed by these neighbors on the surface of i; the total area of all these caps is partitioned according to their spherical Laguerre Voronoi diagram on the surface of i. This method is analytical and its implementation in a new program BallContact is fast and robust. We have used BallContact to study contacts in a database of 1551 high resolution protein structures. We show that with this new definition of atomic contacts, we generate realistic representations of the environments of atoms and residues within a protein. In particular, we establish the importance of nonpolar contact areas that complement the information represented by the accessible surface areas. This new method bears similarity to the tessellation methods used to quantify atomic volumes and contacts, with the advantage that it does not require the presence of explicit solvent molecules if the surface of the protein is to be considered. © 2012 Wiley Periodicals, Inc. Copyright © 2012 Wiley Periodicals, Inc.
An Accurate liver segmentation method using parallel computing algorithm
Elbasher, Eiman Mohammed Khalied
2014-12-01
Computed Tomography (CT or CAT scan) is a noninvasive diagnostic imaging procedure that uses a combination of X-rays and computer technology to produce horizontal, or axial, images (often called slices) of the body. A CT scan shows detailed images of any part of the body, including the bones muscles, fat and organs CT scans are more detailed than standard x-rays. CT scans may be done with or without "contrast Contrast refers to a substance taken by mouth and/ or injected into an intravenous (IV) line that causes the particular organ or tissue under study to be seen more clearly. CT scan of the liver and biliary tract are used in the diagnosis of many diseases in the abdomen structures, particularly when another type of examination, such as X-rays, physical examination, and ultra sound is not conclusive. Unfortunately, the presence of noise and artifact in the edges and fine details in the CT images limit the contrast resolution and make diagnostic procedure more difficult. This experimental study was conducted at the College of Medical Radiological Science, Sudan University of Science and Technology and Fidel Specialist Hospital. The sample of study was included 50 patients. The main objective of this research was to study an accurate liver segmentation method using a parallel computing algorithm, and to segment liver and adjacent organs using image processing technique. The main technique of segmentation used in this study was watershed transform. The scope of image processing and analysis applied to medical application is to improve the quality of the acquired image and extract quantitative information from medical image data in an efficient and accurate way. The results of this technique agreed wit the results of Jarritt et al, (2010), Kratchwil et al, (2010), Jover et al, (2011), Yomamoto et al, (1996), Cai et al (1999), Saudha and Jayashree (2010) who used different segmentation filtering based on the methods of enhancing the computed tomography images. Anther
Computer experiments of the time-sequence of individual steps in multiple Coulomb-excitation
Boer, J. de; Dannhaueser, G.
1982-01-01
The way in which the multiple E2 steps in the Coulomb-excitation of a rotational band of a nucleus follow one another is elucidated for selected examples using semiclassical computer experiments. The role a given transition plays for the excitation of a given final state is measured by a quantity named ''importance function''. It is found that these functions, calculated for the highest rotational state, peak at times forming a sequence for the successive E2 transitions starting from the ground state. This sequential behaviour is used to approximately account for the effects on the projectile orbit of the sequential transfer of excitation energy and angular momentum from projectile to target. These orbits lead to similar deflection functions and cross sections as those obtained from a symmetrization procedure approximately accounting for the transfer of angular momentum and energy. (Auth.)
Iodide and xenon enhancement of computed tomography (CT) in multiple sclerosis (MS)
Radue, E.W.; Kendall, B.E.
1978-01-01
The characteristic findings on computed tomography (CT) in multiple sclerosis (MS) are discussed. In a series of 49 cases plain CT was normal in 21 (43%), cerebral atrophy alone was present in 17 (35%) and plaques were visible in 11 (23%). These were most often adjacent to the lateral ventricles (14 plaques) and in the parietal white matter (10 plaques). CT was performed after the intravenous administration of iodide in 16 of these cases. Two patients with low attenuation plaques were scanned with xenon enhancement; the plaques absorbed less xenon than the corresponding contralateral brain substance and additional, previously isodense plaques were revealed. In one case the white matter absorbed much less xenon than normal and its uptake relative to grey matter was reduced. (orig.) [de
Mining Emerging Patterns for Recognizing Activities of Multiple Users in Pervasive Computing
Gu, Tao; Wu, Zhanqing; Wang, Liang
2009-01-01
Understanding and recognizing human activities from sensor readings is an important task in pervasive computing. Existing work on activity recognition mainly focuses on recognizing activities for a single user in a smart home environment. However, in real life, there are often multiple inhabitants...... activity models, and propose an Emerging Pattern based Multi-user Activity Recognizer (epMAR) to recognize both single-user and multiuser activities. We conduct our empirical studies by collecting real-world activity traces done by two volunteers over a period of two weeks in a smart home environment...... sensor readings in a home environment, and propose a novel pattern mining approach to recognize both single-user and multi-user activities in a unified solution. We exploit Emerging Pattern – a type of knowledge pattern that describes significant changes between classes of data – for constructing our...
A discrete ordinate response matrix method for massively parallel computers
Hanebutte, U.R.; Lewis, E.E.
1991-01-01
A discrete ordinate response matrix method is formulated for the solution of neutron transport problems on massively parallel computers. The response matrix formulation eliminates iteration on the scattering source. The nodal matrices which result from the diamond-differenced equations are utilized in a factored form which minimizes memory requirements and significantly reduces the required number of algorithm utilizes massive parallelism by assigning each spatial node to a processor. The algorithm is accelerated effectively by a synthetic method in which the low-order diffusion equations are also solved by massively parallel red/black iterations. The method has been implemented on a 16k Connection Machine-2, and S 8 and S 16 solutions have been obtained for fixed-source benchmark problems in X--Y geometry
THE METHOD OF MULTIPLE SPATIAL PLANNING BASIC MAP
C. Zhang
2018-04-01
Full Text Available The “Provincial Space Plan Pilot Program” issued in December 2016 pointed out that the existing space management and control information management platforms of various departments were integrated, and a spatial planning information management platform was established to integrate basic data, target indicators, space coordinates, and technical specifications. The planning and preparation will provide supportive decision support, digital monitoring and evaluation of the implementation of the plan, implementation of various types of investment projects and space management and control departments involved in military construction projects in parallel to approve and approve, and improve the efficiency of administrative approval. The space planning system should be set up to delimit the control limits for the development of production, life and ecological space, and the control of use is implemented. On the one hand, it is necessary to clarify the functional orientation between various kinds of planning space. On the other hand, it is necessary to achieve “multi-compliance” of various space planning. Multiple spatial planning intergration need unified and standard basic map(geographic database and technical specificaton to division of urban, agricultural, ecological three types of space and provide technical support for the refinement of the space control zoning for the relevant planning. The article analysis the main space datum, the land use classification standards, base map planning, planning basic platform main technical problems. Based on the geographic conditions, the results of the census preparation of spatial planning map, and Heilongjiang, Hainan many rules combined with a pilot application.
The Method of Multiple Spatial Planning Basic Map
Zhang, C.; Fang, C.
2018-04-01
The "Provincial Space Plan Pilot Program" issued in December 2016 pointed out that the existing space management and control information management platforms of various departments were integrated, and a spatial planning information management platform was established to integrate basic data, target indicators, space coordinates, and technical specifications. The planning and preparation will provide supportive decision support, digital monitoring and evaluation of the implementation of the plan, implementation of various types of investment projects and space management and control departments involved in military construction projects in parallel to approve and approve, and improve the efficiency of administrative approval. The space planning system should be set up to delimit the control limits for the development of production, life and ecological space, and the control of use is implemented. On the one hand, it is necessary to clarify the functional orientation between various kinds of planning space. On the other hand, it is necessary to achieve "multi-compliance" of various space planning. Multiple spatial planning intergration need unified and standard basic map(geographic database and technical specificaton) to division of urban, agricultural, ecological three types of space and provide technical support for the refinement of the space control zoning for the relevant planning. The article analysis the main space datum, the land use classification standards, base map planning, planning basic platform main technical problems. Based on the geographic conditions, the results of the census preparation of spatial planning map, and Heilongjiang, Hainan many rules combined with a pilot application.
Review methods for image segmentation from computed tomography images
Mamat, Nurwahidah; Rahman, Wan Eny Zarina Wan Abdul; Soh, Shaharuddin Cik; Mahmud, Rozi
2014-01-01
Image segmentation is a challenging process in order to get the accuracy of segmentation, automation and robustness especially in medical images. There exist many segmentation methods that can be implemented to medical images but not all methods are suitable. For the medical purposes, the aims of image segmentation are to study the anatomical structure, identify the region of interest, measure tissue volume to measure growth of tumor and help in treatment planning prior to radiation therapy. In this paper, we present a review method for segmentation purposes using Computed Tomography (CT) images. CT images has their own characteristics that affect the ability to visualize anatomic structures and pathologic features such as blurring of the image and visual noise. The details about the methods, the goodness and the problem incurred in the methods will be defined and explained. It is necessary to know the suitable segmentation method in order to get accurate segmentation. This paper can be a guide to researcher to choose the suitable segmentation method especially in segmenting the images from CT scan
A computer method for simulating the decay of radon daughters
Hartley, B.M.
1988-01-01
The analytical equations representing the decay of a series of radioactive atoms through a number of daughter products are well known. These equations are for an idealized case in which the expectation value of the number of atoms which decay in a certain time can be represented by a smooth curve. The real curve of the total number of disintegrations from a radioactive species consists of a series of Heaviside step functions, with the steps occurring at the time of the disintegration. The disintegration of radioactive atoms is said to be random but this random behaviour is such that a single species forms an ensemble of which the times of disintegration give a geometric distribution. Numbers which have a geometric distribution can be generated by computer and can be used to simulate the decay of one or more radioactive species. A computer method is described for simulating such decay of radioactive atoms and this method is applied specifically to the decay of the short half life daughters of radon 222 and the emission of alpha particles from polonium 218 and polonium 214. Repeating the simulation of the decay a number of times provides a method for investigating the statistical uncertainty inherent in methods for measurement of exposure to radon daughters. This statistical uncertainty is difficult to investigate analytically since the time of decay of an atom of polonium 218 is not independent of the time of decay of subsequent polonium 214. The method is currently being used to investigate the statistical uncertainties of a number of commonly used methods for the counting of alpha particles from radon daughters and the calculations of exposure
Comparison of multiple gene assembly methods for metabolic engineering
Chenfeng Lu; Karen Mansoorabadi; Thomas Jeffries
2007-01-01
A universal, rapid DNA assembly method for efficient multigene plasmid construction is important for biological research and for optimizing gene expression in industrial microbes. Three different approaches to achieve this goal were evaluated. These included creating long complementary extensions using a uracil-DNA glycosylase technique, overlap extension polymerase...
Simulation of Cavity Flow by the Lattice Boltzmann Method using Multiple-Relaxation-Time scheme
Ryu, Seung Yeob; Kang, Ha Nok; Seo, Jae Kwang; Yun, Ju Hyeon; Zee, Sung Quun
2006-01-01
Recently, the lattice Boltzmann method(LBM) has gained much attention for its ability to simulate fluid flows, and for its potential advantages over conventional CFD method. The key advantages of LBM are, (1) suitability for parallel computations, (2) absence of the need to solve the time-consuming Poisson equation for pressure, and (3) ease with multiphase flows, complex geometries and interfacial dynamics may be treated. The LBM using relaxation technique was introduced by Higuerea and Jimenez to overcome some drawbacks of lattice gas automata(LGA) such as large statistical noise, limited range of physical parameters, non- Galilean invariance, and implementation difficulty in three-dimensional problem. The simplest LBM is the lattice Bhatnager-Gross-Krook(LBGK) equation, which based on a single-relaxation-time(SRT) approximation. Due to its extreme simplicity, the lattice BGK(LBGK) equation has become the most popular lattice Boltzmann model in spite of its well-known deficiencies, for example, in simulating high-Reynolds numbers flow. The Multiple-Relaxation-Time(MRT) LBM was originally developed by D'Humieres. Lallemand and Luo suggests that the use of a Multiple-Relaxation-Time(MRT) models are much more stable than LBGK, because the different relaxation times can be individually tuned to achieve 'optimal' stability. A lid-driven cavity flow is selected as the test problem because it has geometrically singular points in the flow, but geometrically simple. Results are compared with those using SRT, MRT model in the LBGK method and previous simulation data using Navier-Stokes equations for the same flow conditions. In summary, LBM using MRT model introduces much less spatial oscillations near geometrical singular points, which is important for the successful simulation of higher Reynolds number flows
Comparison of two methods of surface profile extraction from multiple ultrasonic range measurements
Barshan, B; Baskent, D
Two novel methods for surface profile extraction based on multiple ultrasonic range measurements are described and compared. One of the methods employs morphological processing techniques, whereas the other employs a spatial voting scheme followed by simple thresholding. Morphological processing
A new computational method for reactive power market clearing
Zhang, T.; Elkasrawy, A.; Venkatesh, B.
2009-01-01
After deregulation of electricity markets, ancillary services such as reactive power supply are priced separately. However, unlike real power supply, procedures for costing and pricing reactive power supply are still evolving and spot markets for reactive power do not exist as of now. Further, traditional formulations proposed for clearing reactive power markets use a non-linear mixed integer programming formulation that are difficult to solve. This paper proposes a new reactive power supply market clearing scheme. Novelty of this formulation lies in the pricing scheme that rewards transformers for tap shifting while participating in this market. The proposed model is a non-linear mixed integer challenge. A significant portion of the manuscript is devoted towards the development of a new successive mixed integer linear programming (MILP) technique to solve this formulation. The successive MILP method is computationally robust and fast. The IEEE 6-bus and 300-bus systems are used to test the proposed method. These tests serve to demonstrate computational speed and rigor of the proposed method. (author)
Empirical method for simulation of water tables by digital computers
Carnahan, C.L.; Fenske, P.R.
1975-09-01
An empirical method is described for computing a matrix of water-table elevations from a matrix of topographic elevations and a set of observed water-elevation control points which may be distributed randomly over the area of interest. The method is applicable to regions, such as the Great Basin, where the water table can be assumed to conform to a subdued image of overlying topography. A first approximation to the water table is computed by smoothing a matrix of topographic elevations and adjusting each node of the smoothed matrix according to a linear regression between observed water elevations and smoothed topographic elevations. Each observed control point is assumed to exert a radially decreasing influence on the first approximation surface. The first approximation is then adjusted further to conform to observed water-table elevations near control points. Outside the domain of control, the first approximation is assumed to represent the most probable configuration of the water table. The method has been applied to the Nevada Test Site and the Hot Creek Valley areas in Nevada
A Novel Automated Method for Analyzing Cylindrical Computed Tomography Data
Roth, D. J.; Burke, E. R.; Rauser, R. W.; Martin, R. E.
2011-01-01
A novel software method is presented that is applicable for analyzing cylindrical and partially cylindrical objects inspected using computed tomography. This method involves unwrapping and re-slicing data so that the CT data from the cylindrical object can be viewed as a series of 2-D sheets in the vertical direction in addition to volume rendering and normal plane views provided by traditional CT software. The method is based on interior and exterior surface edge detection and under proper conditions, is FULLY AUTOMATED and requires no input from the user except the correct voxel dimension from the CT scan. The software is available from NASA in 32- and 64-bit versions that can be applied to gigabyte-sized data sets, processing data either in random access memory or primarily on the computer hard drive. Please inquire with the presenting author if further interested. This software differentiates itself in total from other possible re-slicing software solutions due to complete automation and advanced processing and analysis capabilities.
Computer codes and methods for simulating accelerator driven systems
Sartori, E.; Byung Chan Na
2003-01-01
A large set of computer codes and associated data libraries have been developed by nuclear research and industry over the past half century. A large number of them are in the public domain and can be obtained under agreed conditions from different Information Centres. The areas covered comprise: basic nuclear data and models, reactor spectra and cell calculations, static and dynamic reactor analysis, criticality, radiation shielding, dosimetry and material damage, fuel behaviour, safety and hazard analysis, heat conduction and fluid flow in reactor systems, spent fuel and waste management (handling, transportation, and storage), economics of fuel cycles, impact on the environment of nuclear activities etc. These codes and models have been developed mostly for critical systems used for research or power generation and other technological applications. Many of them have not been designed for accelerator driven systems (ADS), but with competent use, they can be used for studying such systems or can form the basis for adapting existing methods to the specific needs of ADS's. The present paper describes the types of methods, codes and associated data available and their role in the applications. It provides Web addresses for facilitating searches for such tools. Some indications are given on the effect of non appropriate or 'blind' use of existing tools to ADS. Reference is made to available experimental data that can be used for validating the methods use. Finally, some international activities linked to the different computational aspects are described briefly. (author)
Methodics of computing the results of monitoring the exploratory gallery
Krúpa Víazoslav
2000-09-01
Full Text Available At building site of motorway tunnel Viòové-Dubná skala , the priority is given to driving of exploration galley that secures in detail: geologic, engineering geology, hydrogeology and geotechnics research. This research is based on gathering information for a supposed use of the full profile driving machine that would drive the motorway tunnel. From a part of the exploration gallery which is driven by the TBM method, a fulfilling information is gathered about the parameters of the driving process , those are gathered by a computer monitoring system. The system is mounted on a driving machine. This monitoring system is based on the industrial computer PC 104. It records 4 basic values of the driving process: the electromotor performance of the driving machine Voest-Alpine ATB 35HA, the speed of driving advance, the rotation speed of the disintegrating head TBM and the total head pressure. The pressure force is evaluated from the pressure in the hydraulic cylinders of the machine. Out of these values, the strength of rock mass, the angle of inner friction, etc. are mathematically calculated. These values characterize rock mass properties as their changes. To define the effectivity of the driving process, the value of specific energy and the working ability of driving head is used. The article defines the methodics of computing the gathered monitoring information, that is prepared for the driving machine Voest Alpine ATB 35H at the Institute of Geotechnics SAS. It describes the input forms (protocols of the developed method created by an EXCEL program and shows selected samples of the graphical elaboration of the first monitoring results obtained from exploratory gallery driving process in the Viòové Dubná skala motorway tunnel.
Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods
Werner, Arelia T.; Cannon, Alex J.
2016-04-01
Gridded statistical downscaling methods are the main means of preparing climate model data to drive distributed hydrological models. Past work on the validation of climate downscaling methods has focused on temperature and precipitation, with less attention paid to the ultimate outputs from hydrological models. Also, as attention shifts towards projections of extreme events, downscaling comparisons now commonly assess methods in terms of climate extremes, but hydrologic extremes are less well explored. Here, we test the ability of gridded downscaling models to replicate historical properties of climate and hydrologic extremes, as measured in terms of temporal sequencing (i.e. correlation tests) and distributional properties (i.e. tests for equality of probability distributions). Outputs from seven downscaling methods - bias correction constructed analogues (BCCA), double BCCA (DBCCA), BCCA with quantile mapping reordering (BCCAQ), bias correction spatial disaggregation (BCSD), BCSD using minimum/maximum temperature (BCSDX), the climate imprint delta method (CI), and bias corrected CI (BCCI) - are used to drive the Variable Infiltration Capacity (VIC) model over the snow-dominated Peace River basin, British Columbia. Outputs are tested using split-sample validation on 26 climate extremes indices (ClimDEX) and two hydrologic extremes indices (3-day peak flow and 7-day peak flow). To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational data sets are used as downscaling target data. The skill of the downscaling methods generally depended on reanalysis and gridded observational data set. However, CI failed to reproduce the distribution and BCSD and BCSDX the timing of winter 7-day low-flow events, regardless of reanalysis or observational data set. Overall, DBCCA passed the greatest number of tests for the ClimDEX indices, while BCCAQ, which is designed to more accurately resolve event
A Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.
Marceau, Rachel; Lu, Wenbin; Holloway, Shannon; Sale, Michèle M; Worrall, Bradford B; Williams, Stephen R; Hsu, Fang-Chi; Tzeng, Jung-Ying
2015-09-01
Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level. © 2015 WILEY PERIODICALS, INC.
Description of a method for computing fluid-structure interaction
Gantenbein, F.
1982-02-01
A general formulation allowing computation of structure vibrations in a dense fluid is described. It is based on fluid modelisation by fluid finite elements. For each fluid node are associated two variables: the pressure p and a variable π defined as p=d 2 π/dt 2 . Coupling between structure and fluid is introduced by surface elements. This method is easy to introduce in a general finite element code. Validation was obtained by analytical calculus and tests. It is widely used for vibrational and seismic studies of pipes and internals of nuclear reactors some applications are presented [fr
Computer Aided Flowsheet Design using Group Contribution Methods
Bommareddy, Susilpa; Eden, Mario R.; Gani, Rafiqul
2011-01-01
In this paper, a systematic group contribution based framework is presented for synthesis of process flowsheets from a given set of input and output specifications. Analogous to the group contribution methods developed for molecular design, the framework employs process groups to represent...... information of each flowsheet to minimize the computational load and information storage. The design variables for the selected flowsheet(s) are identified through a reverse simulation approach and are used as initial estimates for rigorous simulation to verify the feasibility and performance of the design....
Method and apparatus for managing transactions with connected computers
Goldsmith, Steven Y.; Phillips, Laurence R.; Spires, Shannon V.
2003-01-01
The present invention provides a method and apparatus that make use of existing computer and communication resources and that reduce the errors and delays common to complex transactions such as international shipping. The present invention comprises an agent-based collaborative work environment that assists geographically distributed commercial and government users in the management of complex transactions such as the transshipment of goods across the U.S.-Mexico border. Software agents can mediate the creation, validation and secure sharing of shipment information and regulatory documentation over the Internet, using the World-Wide Web to interface with human users.
Numerical methods and computers used in elastohydrodynamic lubrication
Hamrock, B. J.; Tripp, J. H.
1982-01-01
Some of the methods of obtaining approximate numerical solutions to boundary value problems that arise in elastohydrodynamic lubrication are reviewed. The highlights of four general approaches (direct, inverse, quasi-inverse, and Newton-Raphson) are sketched. Advantages and disadvantages of these approaches are presented along with a flow chart showing some of the details of each. The basic question of numerical stability of the elastohydrodynamic lubrication solutions, especially in the pressure spike region, is considered. Computers used to solve this important class of lubrication problems are briefly described, with emphasis on supercomputers.
Support Operators Method for the Diffusion Equation in Multiple Materials
Winters, Andrew R. [Los Alamos National Laboratory; Shashkov, Mikhail J. [Los Alamos National Laboratory
2012-08-14
A second-order finite difference scheme for the solution of the diffusion equation on non-uniform meshes is implemented. The method allows the heat conductivity to be discontinuous. The algorithm is formulated on a one dimensional mesh and is derived using the support operators method. A key component of the derivation is that the discrete analog of the flux operator is constructed to be the negative adjoint of the discrete divergence, in an inner product that is a discrete analog of the continuum inner product. The resultant discrete operators in the fully discretized diffusion equation are symmetric and positive definite. The algorithm is generalized to operate on meshes with cells which have mixed material properties. A mechanism to recover intermediate temperature values in mixed cells using a limited linear reconstruction is introduced. The implementation of the algorithm is verified and the linear reconstruction mechanism is compared to previous results for obtaining new material temperatures.
The computational form of craving is a selective multiplication of economic value.
Konova, Anna B; Louie, Kenway; Glimcher, Paul W
2018-04-17
Craving is thought to be a specific desire state that biases choice toward the desired object, be it chocolate or drugs. A vast majority of people report having experienced craving of some kind. In its pathological form craving contributes to health outcomes in addiction and obesity. Yet despite its ubiquity and clinical relevance we still lack a basic neurocomputational understanding of craving. Here, using an instantaneous measure of subjective valuation and selective cue exposure, we identify a behavioral signature of a food craving-like state and advance a computational framework for understanding how this state might transform valuation to bias choice. We find desire induced by exposure to a specific high-calorie, high-fat/sugar snack good is expressed in subjects' momentary willingness to pay for this good. This effect is selective but not exclusive to the exposed good; rather, we find it generalizes to nonexposed goods in proportion to their subjective attribute similarity to the exposed ones. A second manipulation of reward size (number of snack units available for purchase) further suggested that a multiplicative gain mechanism supports the transformation of valuation during laboratory craving. These findings help explain how real-world food craving can result in behaviors inconsistent with preferences expressed in the absence of craving and open a path for the computational modeling of craving-like phenomena using a simple and repeatable experimental tool for assessing subjective states in economic terms. Copyright © 2018 the Author(s). Published by PNAS.
A hybrid method for the parallel computation of Green's functions
Petersen, Dan Erik; Li Song; Stokbro, Kurt; Sorensen, Hans Henrik B.; Hansen, Per Christian; Skelboe, Stig; Darve, Eric
2009-01-01
Quantum transport models for nanodevices using the non-equilibrium Green's function method require the repeated calculation of the block tridiagonal part of the Green's and lesser Green's function matrices. This problem is related to the calculation of the inverse of a sparse matrix. Because of the large number of times this calculation needs to be performed, this is computationally very expensive even on supercomputers. The classical approach is based on recurrence formulas which cannot be efficiently parallelized. This practically prevents the solution of large problems with hundreds of thousands of atoms. We propose new recurrences for a general class of sparse matrices to calculate Green's and lesser Green's function matrices which extend formulas derived by Takahashi and others. We show that these recurrences may lead to a dramatically reduced computational cost because they only require computing a small number of entries of the inverse matrix. Then, we propose a parallelization strategy for block tridiagonal matrices which involves a combination of Schur complement calculations and cyclic reduction. It achieves good scalability even on problems of modest size.
Shi Yongqian; Zhu Qingfu; Hu Dingsheng; He Tao; Yao Shigui; Lin Shenghuo
2004-01-01
The paper gives experiment theory and experiment method of neutron source multiplication method for site measurement technology in the nuclear critical safety. The measured parameter by source multiplication method actually is a sub-critical with source neutron effective multiplication factor k s , but not the neutron effective multiplication factor k eff . The experiment research has been done on the uranium solution nuclear critical safety experiment assembly. The k s of different sub-criticality is measured by neutron source multiplication experiment method, and k eff of different sub-criticality, the reactivity coefficient of unit solution level, is first measured by period method, and then multiplied by difference of critical solution level and sub-critical solution level and obtained the reactivity of sub-critical solution level. The k eff finally can be extracted from reactivity formula. The effect on the nuclear critical safety and different between k eff and k s are discussed
A high-resolution computational localization method for transcranial magnetic stimulation mapping.
Aonuma, Shinta; Gomez-Tames, Jose; Laakso, Ilkka; Hirata, Akimasa; Takakura, Tomokazu; Tamura, Manabu; Muragaki, Yoshihiro
2018-05-15
Transcranial magnetic stimulation (TMS) is used for the mapping of brain motor functions. The complexity of the brain deters determining the exact localization of the stimulation site using simplified methods (e.g., the region below the center of the TMS coil) or conventional computational approaches. This study aimed to present a high-precision localization method for a specific motor area by synthesizing computed non-uniform current distributions in the brain for multiple sessions of TMS. Peritumoral mapping by TMS was conducted on patients who had intra-axial brain neoplasms located within or close to the motor speech area. The electric field induced by TMS was computed using realistic head models constructed from magnetic resonance images of patients. A post-processing method was implemented to determine a TMS hotspot by combining the computed electric fields for the coil orientations and positions that delivered high motor-evoked potentials during peritumoral mapping. The method was compared to the stimulation site localized via intraoperative direct brain stimulation and navigated TMS. Four main results were obtained: 1) the dependence of the computed hotspot area on the number of peritumoral measurements was evaluated; 2) the estimated localization of the hand motor area in eight non-affected hemispheres was in good agreement with the position of a so-called "hand-knob"; 3) the estimated hotspot areas were not sensitive to variations in tissue conductivity; and 4) the hand motor areas estimated by this proposal and direct electric stimulation (DES) were in good agreement in the ipsilateral hemisphere of four glioma patients. The TMS localization method was validated by well-known positions of the "hand-knob" in brains for the non-affected hemisphere, and by a hotspot localized via DES during awake craniotomy for the tumor-containing hemisphere. Copyright © 2018 Elsevier Inc. All rights reserved.
Multigrid Methods for the Computation of Propagators in Gauge Fields
Kalkreuter, Thomas
Multigrid methods were invented for the solution of discretized partial differential equations in order to overcome the slowness of traditional algorithms by updates on various length scales. In the present work generalizations of multigrid methods for propagators in gauge fields are investigated. Gauge fields are incorporated in algorithms in a covariant way. The kernel C of the restriction operator which averages from one grid to the next coarser grid is defined by projection on the ground-state of a local Hamiltonian. The idea behind this definition is that the appropriate notion of smoothness depends on the dynamics. The ground-state projection choice of C can be used in arbitrary dimension and for arbitrary gauge group. We discuss proper averaging operations for bosons and for staggered fermions. The kernels C can also be used in multigrid Monte Carlo simulations, and for the definition of block spins and blocked gauge fields in Monte Carlo renormalization group studies. Actual numerical computations are performed in four-dimensional SU(2) gauge fields. We prove that our proposals for block spins are “good”, using renormalization group arguments. A central result is that the multigrid method works in arbitrarily disordered gauge fields, in principle. It is proved that computations of propagators in gauge fields without critical slowing down are possible when one uses an ideal interpolation kernel. Unfortunately, the idealized algorithm is not practical, but it was important to answer questions of principle. Practical methods are able to outperform the conjugate gradient algorithm in case of bosons. The case of staggered fermions is harder. Multigrid methods give considerable speed-ups compared to conventional relaxation algorithms, but on lattices up to 184 conjugate gradient is superior.
Improved exact method for the double TSP with multiple stacks
Lusby, Richard Martin; Larsen, Jesper
2011-01-01
and delivery problems. The results suggest an impressive improvement, and we report, for the first time, optimal solutions to several unsolved instances from the literature containing 18 customers. Instances with 28 customers are also shown to be solvable within a few percent of optimality. © 2011 Wiley...... the first delivery, and the container cannot be repacked once packed. In this paper we improve the previously proposed exact method of Lusby et al. (Int Trans Oper Res 17 (2010), 637–652) through an additional preprocessing technique that uses the longest common subsequence between the respective pickup...
Fluid history computation methods for reactor safeguards problems using MNODE computer program
Huang, Y.S.; Savery, C.W.
1976-10-01
A method for predicting the pressure-temperature histories of air, water liquid, and vapor flowing in a zoned containment as a result of high energy pipe rupture is described. The computer code, MNODE, has been developed for 12 connected control volumes and 24 inertia flow paths. Predictions by the code are compared with the results of an analytical gas dynamic problem, semiscale blowdown experiments, full scale MARVIKEN test results, Battelle-Frankfurt model PWR containment test data. The MNODE solutions to NRC/AEC subcompartment benchmark problems are also compared with results predicted by other computer codes such as RELAP-3, FLASH-2, CONTEMPT-PS. The analytical consideration is consistent with Section 6.2.1.2 of the Standard Format (Rev. 2) issued by U.S. Nuclear Regulatory Commission in September 1975
Rondon Silmara
2013-02-01
Full Text Available Abstract Background Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Methods Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students’ prior knowledge (i.e. before undergoing the learning method, short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method were assessed with a multiple choice questionnaire. Students’ performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Results Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. Conclusions The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students’ short and long-term knowledge retention.
A code to compute borehole fluid conductivity profiles with multiple feed points
Hale, F.V.; Tsang, C.F.
1988-03-01
It is of much current interest to determine the flow characteristics of fractures intersecting a wellbore in order to understand the hydrologic behavior of fractured rocks. Often inflow from these fractures into the wellbore is at very low rates. A new procedure has been proposed and a corresponding method of analysis developed to obtain fracture inflow parameters from a time sequence of electric conductivity logs of the borehole fluid. The present report is a companion document to NTB--88-13 giving the details of equations and computer code used to compute borehole fluid conductivity distributions. Verification of the code used and a listing of the code are also given. (author) 9 refs., 5 figs., 7 tabs
Effective multiplication factor measurement by feynman-α method. 3
Mouri, Tomoaki; Ohtani, Nobuo
1998-06-01
The sub-criticality monitoring system has been developed for criticality safety control in nuclear fuel handling plants. In the past experiments performed with the Deuterium Critical Assembly (DCA), it was confirmed that the detection of sub-criticality was possible to k eff = 0.3. To investigate the applicability of the method to more generalized system, experiments were performed in the light-water-moderated system of the modified DCA core. From these experiments, it was confirmed that the prompt decay constant (α), which was a index of the sub-criticality, was detected between k eff = 0.623 and k eff = 0.870 and the difference of 0.05 - 0.1Δk could be distinguished. The α values were numerically calculated with 2D transport code TWODANT and monte carlo code KENO V.a, and the results were compared with the measured values. The differences between calculated and measured values were proved to be less than 13%, which was sufficient accuracy in the sub-criticality monitoring system. It was confirmed that Feynman-α method was applicable to sub-critical measurement of the light-water-moderated system. (author)
Oligomerization of G protein-coupled receptors: computational methods.
Selent, J; Kaczor, A A
2011-01-01
Recent research has unveiled the complexity of mechanisms involved in G protein-coupled receptor (GPCR) functioning in which receptor dimerization/oligomerization may play an important role. Although the first high-resolution X-ray structure for a likely functional chemokine receptor dimer has been deposited in the Protein Data Bank, the interactions and mechanisms of dimer formation are not yet fully understood. In this respect, computational methods play a key role for predicting accurate GPCR complexes. This review outlines computational approaches focusing on sequence- and structure-based methodologies as well as discusses their advantages and limitations. Sequence-based approaches that search for possible protein-protein interfaces in GPCR complexes have been applied with success in several studies, but did not yield always consistent results. Structure-based methodologies are a potent complement to sequence-based approaches. For instance, protein-protein docking is a valuable method especially when guided by experimental constraints. Some disadvantages like limited receptor flexibility and non-consideration of the membrane environment have to be taken into account. Molecular dynamics simulation can overcome these drawbacks giving a detailed description of conformational changes in a native-like membrane. Successful prediction of GPCR complexes using computational approaches combined with experimental efforts may help to understand the role of dimeric/oligomeric GPCR complexes for fine-tuning receptor signaling. Moreover, since such GPCR complexes have attracted interest as potential drug target for diverse diseases, unveiling molecular determinants of dimerization/oligomerization can provide important implications for drug discovery.
Computing thermal Wigner densities with the phase integration method
Beutier, J.; Borgis, D.; Vuilleumier, R.; Bonella, S.
2014-01-01
We discuss how the Phase Integration Method (PIM), recently developed to compute symmetrized time correlation functions [M. Monteferrante, S. Bonella, and G. Ciccotti, Mol. Phys. 109, 3015 (2011)], can be adapted to sampling/generating the thermal Wigner density, a key ingredient, for example, in many approximate schemes for simulating quantum time dependent properties. PIM combines a path integral representation of the density with a cumulant expansion to represent the Wigner function in a form calculable via existing Monte Carlo algorithms for sampling noisy probability densities. The method is able to capture highly non-classical effects such as correlation among the momenta and coordinates parts of the density, or correlations among the momenta themselves. By using alternatives to cumulants, it can also indicate the presence of negative parts of the Wigner density. Both properties are demonstrated by comparing PIM results to those of reference quantum calculations on a set of model problems
Computing thermal Wigner densities with the phase integration method.
Beutier, J; Borgis, D; Vuilleumier, R; Bonella, S
2014-08-28
We discuss how the Phase Integration Method (PIM), recently developed to compute symmetrized time correlation functions [M. Monteferrante, S. Bonella, and G. Ciccotti, Mol. Phys. 109, 3015 (2011)], can be adapted to sampling/generating the thermal Wigner density, a key ingredient, for example, in many approximate schemes for simulating quantum time dependent properties. PIM combines a path integral representation of the density with a cumulant expansion to represent the Wigner function in a form calculable via existing Monte Carlo algorithms for sampling noisy probability densities. The method is able to capture highly non-classical effects such as correlation among the momenta and coordinates parts of the density, or correlations among the momenta themselves. By using alternatives to cumulants, it can also indicate the presence of negative parts of the Wigner density. Both properties are demonstrated by comparing PIM results to those of reference quantum calculations on a set of model problems.
Computational methods for ab initio detection of microRNAs
Malik eYousef
2012-10-01
Full Text Available MicroRNAs are small RNA sequences of 18-24 nucleotides in length, which serve as templates to drive post transcriptional gene silencing. The canonical microRNA pathway starts with transcription from DNA and is followed by processing via the Microprocessor complex, yielding a hairpin structure. Which is then exported into the cytosol where it is processed by Dicer and then incorporated into the RNA induced silencing complex. All of these biogenesis steps add to the overall specificity of miRNA production and effect. Unfortunately, their modes of action are just beginning to be elucidated and therefore computational prediction algorithms cannot model the process but are usually forced to employ machine learning approaches. This work focuses on ab initio prediction methods throughout; and therefore homology-based miRNA detection methods are not discussed. Current ab initio prediction algorithms, their ties to data mining, and their prediction accuracy are detailed.
Data graphing methods, articles of manufacture, and computing devices
Wong, Pak Chung; Mackey, Patrick S.; Cook, Kristin A.; Foote, Harlan P.; Whiting, Mark A.
2016-12-13
Data graphing methods, articles of manufacture, and computing devices are described. In one aspect, a method includes accessing a data set, displaying a graphical representation including data of the data set which is arranged according to a first of different hierarchical levels, wherein the first hierarchical level represents the data at a first of a plurality of different resolutions which respectively correspond to respective ones of the hierarchical levels, selecting a portion of the graphical representation wherein the data of the portion is arranged according to the first hierarchical level at the first resolution, modifying the graphical representation by arranging the data of the portion according to a second of the hierarchal levels at a second of the resolutions, and after the modifying, displaying the graphical representation wherein the data of the portion is arranged according to the second hierarchal level at the second resolution.
A finite element solution method for quadrics parallel computer
Zucchini, A.
1996-08-01
A distributed preconditioned conjugate gradient method for finite element analysis has been developed and implemented on a parallel SIMD Quadrics computer. The main characteristic of the method is that it does not require any actual assembling of all element equations in a global system. The physical domain of the problem is partitioned in cells of n p finite elements and each cell element is assigned to a different node of an n p -processors machine. Element stiffness matrices are stored in the data memory of the assigned processing node and the solution process is completely executed in parallel at element level. Inter-element and therefore inter-processor communications are required once per iteration to perform local sums of vector quantities between neighbouring elements. A prototype implementation has been tested on an 8-nodes Quadrics machine in a simple 2D benchmark problem
A novel dual energy method for enhanced quantitative computed tomography
Emami, A.; Ghadiri, H.; Rahmim, A.; Ay, M. R.
2018-01-01
Accurate assessment of bone mineral density (BMD) is critically important in clinical practice, and conveniently enabled via quantitative computed tomography (QCT). Meanwhile, dual-energy QCT (DEQCT) enables enhanced detection of small changes in BMD relative to single-energy QCT (SEQCT). In the present study, we aimed to investigate the accuracy of QCT methods, with particular emphasis on a new dual-energy approach, in comparison to single-energy and conventional dual-energy techniques. We used a sinogram-based analytical CT simulator to model the complete chain of CT data acquisitions, and assessed performance of SEQCT and different DEQCT techniques in quantification of BMD. We demonstrate a 120% reduction in error when using a proposed dual-energy Simultaneous Equation by Constrained Least-squares method, enabling more accurate bone mineral measurements.
Thomas, Bex George; Elasser, Ahmed; Bollapragada, Srinivas; Galbraith, Anthony William; Agamy, Mohammed; Garifullin, Maxim Valeryevich
2016-03-29
A system and method of using one or more DC-DC/DC-AC converters and/or alternative devices allows strings of multiple module technologies to coexist within the same PV power plant. A computing (optimization) framework estimates the percentage allocation of PV power plant capacity to selected PV module technologies. The framework and its supporting components considers irradiation, temperature, spectral profiles, cost and other practical constraints to achieve the lowest levelized cost of electricity, maximum output and minimum system cost. The system and method can function using any device enabling distributed maximum power point tracking at the module, string or combiner level.
A projection gradient method for computing ground state of spin-2 Bose–Einstein condensates
Wang, Hanquan, E-mail: hanquan.wang@gmail.com [School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, Yunnan Province, 650221 (China); Yunnan Tongchang Scientific Computing and Data Mining Research Center, Kunming, Yunnan Province, 650221 (China)
2014-10-01
In this paper, a projection gradient method is presented for computing ground state of spin-2 Bose–Einstein condensates (BEC). We first propose the general projection gradient method for solving energy functional minimization problem under multiple constraints, in which the energy functional takes real functions as independent variables. We next extend the method to solve a similar problem, where the energy functional now takes complex functions as independent variables. We finally employ the method into finding the ground state of spin-2 BEC. The key of our method is: by constructing continuous gradient flows (CGFs), the ground state of spin-2 BEC can be computed as the steady state solution of such CGFs. We discretized the CGFs by a conservative finite difference method along with a proper way to deal with the nonlinear terms. We show that the numerical discretization is normalization and magnetization conservative and energy diminishing. Numerical results of the ground state and their energy of spin-2 BEC are reported to demonstrate the effectiveness of the numerical method.
A projection gradient method for computing ground state of spin-2 Bose–Einstein condensates
Wang, Hanquan
2014-01-01
In this paper, a projection gradient method is presented for computing ground state of spin-2 Bose–Einstein condensates (BEC). We first propose the general projection gradient method for solving energy functional minimization problem under multiple constraints, in which the energy functional takes real functions as independent variables. We next extend the method to solve a similar problem, where the energy functional now takes complex functions as independent variables. We finally employ the method into finding the ground state of spin-2 BEC. The key of our method is: by constructing continuous gradient flows (CGFs), the ground state of spin-2 BEC can be computed as the steady state solution of such CGFs. We discretized the CGFs by a conservative finite difference method along with a proper way to deal with the nonlinear terms. We show that the numerical discretization is normalization and magnetization conservative and energy diminishing. Numerical results of the ground state and their energy of spin-2 BEC are reported to demonstrate the effectiveness of the numerical method
de Lasson, Jakob Rosenkrantz; Frandsen, Lars Hagedorn; Burger, Sven
2016-01-01
We benchmark four state-of-the-art computational methods by computing quality factors and resonance wavelengths in photonic crystal membrane L5 and L9 line defect cavities.The convergence of the methods with respect to resolution, degrees of freedom and number ofmodes is investigated. Special att...... attention is paid to the influence of the size of the computational domain. Convergence is not obtained for some of the methods, indicating that some are moresuitable than others for analyzing line defect cavities....
Computer prediction of subsurface radionuclide transport: an adaptive numerical method
Neuman, S.P.
1983-01-01
Radionuclide transport in the subsurface is often modeled with the aid of the advection-dispersion equation. A review of existing computer methods for the solution of this equation shows that there is need for improvement. To answer this need, a new adaptive numerical method is proposed based on an Eulerian-Lagrangian formulation. The method is based on a decomposition of the concentration field into two parts, one advective and one dispersive, in a rigorous manner that does not leave room for ambiguity. The advective component of steep concentration fronts is tracked forward with the aid of moving particles clustered around each front. Away from such fronts the advection problem is handled by an efficient modified method of characteristics called single-step reverse particle tracking. When a front dissipates with time, its forward tracking stops automatically and the corresponding cloud of particles is eliminated. The dispersion problem is solved by an unconventional Lagrangian finite element formulation on a fixed grid which involves only symmetric and diagonal matrices. Preliminary tests against analytical solutions of ne- and two-dimensional dispersion in a uniform steady state velocity field suggest that the proposed adaptive method can handle the entire range of Peclet numbers from 0 to infinity, with Courant numbers well in excess of 1
Parallel computation of multigroup reactivity coefficient using iterative method
Susmikanti, Mike; Dewayatna, Winter
2013-09-01
One of the research activities to support the commercial radioisotope production program is a safety research target irradiation FPM (Fission Product Molybdenum). FPM targets form a tube made of stainless steel in which the nuclear degrees of superimposed high-enriched uranium. FPM irradiation tube is intended to obtain fission. The fission material widely used in the form of kits in the world of nuclear medicine. Irradiation FPM tube reactor core would interfere with performance. One of the disorders comes from changes in flux or reactivity. It is necessary to study a method for calculating safety terrace ongoing configuration changes during the life of the reactor, making the code faster became an absolute necessity. Neutron safety margin for the research reactor can be reused without modification to the calculation of the reactivity of the reactor, so that is an advantage of using perturbation method. The criticality and flux in multigroup diffusion model was calculate at various irradiation positions in some uranium content. This model has a complex computation. Several parallel algorithms with iterative method have been developed for the sparse and big matrix solution. The Black-Red Gauss Seidel Iteration and the power iteration parallel method can be used to solve multigroup diffusion equation system and calculated the criticality and reactivity coeficient. This research was developed code for reactivity calculation which used one of safety analysis with parallel processing. It can be done more quickly and efficiently by utilizing the parallel processing in the multicore computer. This code was applied for the safety limits calculation of irradiated targets FPM with increment Uranium.
Multiple-Parameter Estimation Method Based on Spatio-Temporal 2-D Processing for Bistatic MIMO Radar
Shouguo Yang
2015-12-01
Full Text Available A novel spatio-temporal 2-dimensional (2-D processing method that can jointly estimate the transmitting-receiving azimuth and Doppler frequency for bistatic multiple-input multiple-output (MIMO radar in the presence of spatial colored noise and an unknown number of targets is proposed. In the temporal domain, the cross-correlation of the matched filters’ outputs for different time-delay sampling is used to eliminate the spatial colored noise. In the spatial domain, the proposed method uses a diagonal loading method and subspace theory to estimate the direction of departure (DOD and direction of arrival (DOA, and the Doppler frequency can then be accurately estimated through the estimation of the DOD and DOA. By skipping target number estimation and the eigenvalue decomposition (EVD of the data covariance matrix estimation and only requiring a one-dimensional search, the proposed method achieves low computational complexity. Furthermore, the proposed method is suitable for bistatic MIMO radar with an arbitrary transmitted and received geometrical configuration. The correction and efficiency of the proposed method are verified by computer simulation results.
Rondon, Silmara; Sassi, Fernanda Chiarion; Furquim de Andrade, Claudia Regina
2013-02-25
Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students' prior knowledge (i.e. before undergoing the learning method), short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method) were assessed with a multiple choice questionnaire. Students' performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students' short and long-term knowledge retention.
Bakker, M.; Heuvel-Panhuizen, M.H.A.M. van den; Robitzsch, A.
2016-01-01
This study examined the effects of a teacher-delivered intervention with online mathematics mini-games on special education students' multiplicative reasoning ability (multiplication and division). The games involved declarative, procedural, as well as conceptual knowledge of multiplicative
Methods for meta-analysis of multiple traits using GWAS summary statistics.
Ray, Debashree; Boehnke, Michael
2018-03-01
Genome-wide association studies (GWAS) for complex diseases have focused primarily on single-trait analyses for disease status and disease-related quantitative traits. For example, GWAS on risk factors for coronary artery disease analyze genetic associations of plasma lipids such as total cholesterol, LDL-cholesterol, HDL-cholesterol, and triglycerides (TGs) separately. However, traits are often correlated and a joint analysis may yield increased statistical power for association over multiple univariate analyses. Recently several multivariate methods have been proposed that require individual-level data. Here, we develop metaUSAT (where USAT is unified score-based association test), a novel unified association test of a single genetic variant with multiple traits that uses only summary statistics from existing GWAS. Although the existing methods either perform well when most correlated traits are affected by the genetic variant in the same direction or are powerful when only a few of the correlated traits are associated, metaUSAT is designed to be robust to the association structure of correlated traits. metaUSAT does not require individual-level data and can test genetic associations of categorical and/or continuous traits. One can also use metaUSAT to analyze a single trait over multiple studies, appropriately accounting for overlapping samples, if any. metaUSAT provides an approximate asymptotic P-value for association and is computationally efficient for implementation at a genome-wide level. Simulation experiments show that metaUSAT maintains proper type-I error at low error levels. It has similar and sometimes greater power to detect association across a wide array of scenarios compared to existing methods, which are usually powerful for some specific association scenarios only. When applied to plasma lipids summary data from the METSIM and the T2D-GENES studies, metaUSAT detected genome-wide significant loci beyond the ones identified by univariate analyses
Adler, Georg; Lembach, Yvonne
2015-08-01
Cognitive impairments may have a severe impact on everyday functioning and quality of life of patients with multiple sclerosis (MS). However, there are some methodological problems in the assessment and only a few studies allow a representative estimate of the prevalence and severity of cognitive impairments in MS patients. We applied a computer-based method, the memory and attention test (MAT), in 531 outpatients with MS, who were assessed at nine neurological practices or specialized outpatient clinics. The findings were compared with those obtained in an age-, sex- and education-matched control group of 84 healthy subjects. Episodic short-term memory was substantially decreased in the MS patients. About 20% of them reached a score of only less than two standard deviations below the mean of the control group. The episodic short-term memory score was negatively correlated with the EDSS score. Minor but also significant impairments in the MS patients were found for verbal short-term memory, episodic working memory and selective attention. The computer-based MAT was found to be useful for a routine assessment of cognition in MS outpatients.
LSHSIM: A Locality Sensitive Hashing based method for multiple-point geostatistics
Moura, Pedro; Laber, Eduardo; Lopes, Hélio; Mesejo, Daniel; Pavanelli, Lucas; Jardim, João; Thiesen, Francisco; Pujol, Gabriel
2017-10-01
Reservoir modeling is a very important task that permits the representation of a geological region of interest, so as to generate a considerable number of possible scenarios. Since its inception, many methodologies have been proposed and, in the last two decades, multiple-point geostatistics (MPS) has been the dominant one. This methodology is strongly based on the concept of training image (TI) and the use of its characteristics, which are called patterns. In this paper, we propose a new MPS method that combines the application of a technique called Locality Sensitive Hashing (LSH), which permits to accelerate the search for patterns similar to a target one, with a Run-Length Encoding (RLE) compression technique that speeds up the calculation of the Hamming similarity. Experiments with both categorical and continuous images show that LSHSIM is computationally efficient and produce good quality realizations. In particular, for categorical data, the results suggest that LSHSIM is faster than MS-CCSIM, one of the state-of-the-art methods.
Method of experimental and theoretical modeling for multiple pressure tube rupture for RBMK reactor
Medvedeva, N.Y.; Goldstein, R.V.; Burrows, J.A.
2001-01-01
The rupture of single RBMK reactor channels has occurred at a number of stations with a variety of initiating events. It is assumed in RBMK Safety Cases that the force of the escaping fluid will not cause neighbouring channels to break. This assumption has not been justified. A chain reaction of tube breaks could over-pressurise the reactor cavity leading to catastrophic failure of the containment. To validate the claims of the RBMK Safety Cases the Electrogorsk Research and Engineering Centre, in participation with experts from the Institute of Mechanics of RAS, has developed the method of interacting multiscale physical and mathematical modelling for coupled thermophysical, hydrogasodynamic processes and deformation and break processes causing and (or) accompanying potential failures, design and beyond the design RBMK reactor accidents. To realise the method the set of rigs, physical and mathematical models and specialized computer codes are under creation. This article sets out an experimental philosophy and programme for achieving this objective to solve the problem of credibility or non-credibility for multiple fuel channel rupture in RBMK.(author)
Computationally efficient method for optical simulation of solar cells and their applications
Semenikhin, I.; Zanuccoli, M.; Fiegna, C.; Vyurkov, V.; Sangiorgi, E.
2013-01-01
This paper presents two novel implementations of the Differential method to solve the Maxwell equations in nanostructured optoelectronic solid state devices. The first proposed implementation is based on an improved and computationally efficient T-matrix formulation that adopts multiple-precision arithmetic to tackle the numerical instability problem which arises due to evanescent modes. The second implementation adopts the iterative approach that allows to achieve low computational complexity O(N logN) or better. The proposed algorithms may work with structures with arbitrary spatial variation of the permittivity. The developed two-dimensional numerical simulator is applied to analyze the dependence of the absorption characteristics of a thin silicon slab on the morphology of the front interface and on the angle of incidence of the radiation with respect to the device surface.
Fernandez-Lozano, Carlos; Gestal, Marcos; Munteanu, Cristian R; Dorado, Julian; Pazos, Alejandro
2016-01-01
The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the field of Computational Intelligence and especially on a correct comparison between the different results provided for different methods, as those techniques are complex systems that require further study to be fully understood. A methodology commonly accepted in Computational intelligence is implemented in an R package called RRegrs. This package includes ten simple and complex regression models to carry out predictive modeling using Machine Learning and well-known regression algorithms. The framework for experimental design presented herein is evaluated and validated against RRegrs. Our results are different for three out of five state-of-the-art simple datasets and it can be stated that the selection of the best model according to our proposal is statistically significant and relevant. It is of relevance to use a statistical approach to indicate whether the differences are statistically significant using this kind of algorithms. Furthermore, our results with three real complex datasets report different best models than with the previously published methodology. Our final goal is to provide a complete methodology for the use of different steps in order to compare the results obtained in Computational Intelligence problems, as well as from other fields, such as for bioinformatics, cheminformatics, etc., given that our proposal is open and modifiable.
Carlos Fernandez-Lozano
2016-12-01
Full Text Available The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the field of Computational Intelligence and especially on a correct comparison between the different results provided for different methods, as those techniques are complex systems that require further study to be fully understood. A methodology commonly accepted in Computational intelligence is implemented in an R package called RRegrs. This package includes ten simple and complex regression models to carry out predictive modeling using Machine Learning and well-known regression algorithms. The framework for experimental design presented herein is evaluated and validated against RRegrs. Our results are different for three out of five state-of-the-art simple datasets and it can be stated that the selection of the best model according to our proposal is statistically significant and relevant. It is of relevance to use a statistical approach to indicate whether the differences are statistically significant using this kind of algorithms. Furthermore, our results with three real complex datasets report different best models than with the previously published methodology. Our final goal is to provide a complete methodology for the use of different steps in order to compare the results obtained in Computational Intelligence problems, as well as from other fields, such as for bioinformatics, cheminformatics, etc., given that our proposal is open and modifiable.
Integration of multiple determinants in the neuronal computation of economic values.
Raghuraman, Anantha P; Padoa-Schioppa, Camillo
2014-08-27
Economic goods may vary on multiple dimensions (determinants). A central conjecture in decision neuroscience is that choices between goods are made by comparing subjective values computed through the integration of all relevant determinants. Previous work identified three groups of neurons in the orbitofrontal cortex (OFC) of monkeys engaged in economic choices: (1) offer value cells, which encode the value of individual offers; (2) chosen value cells, which encode the value of the chosen good; and (3) chosen juice cells, which encode the identity of the chosen good. In principle, these populations could be sufficient to generate a decision. Critically, previous work did not assess whether offer value cells (the putative input to the decision) indeed encode subjective values as opposed to physical properties of the goods, and/or whether offer value cells integrate multiple determinants. To address these issues, we recorded from the OFC while monkeys chose between risky outcomes. Confirming previous observations, three populations of neurons encoded the value of individual offers, the value of the chosen option, and the value-independent choice outcome. The activity of both offer value cells and chosen value cells encoded values defined by the integration of juice quantity and probability. Furthermore, both populations reflected the subjective risk attitude of the animals. We also found additional groups of neurons encoding the risk associated with a particular option, the risky nature of the chosen option, and whether the trial outcome was positive or negative. These results provide substantial support for the conjecture described above and for the involvement of OFC in good-based decisions. Copyright © 2014 the authors 0270-6474/14/3311583-21$15.00/0.
Malcolm, Andrew A.; Liu, Tong; Ng, Ivan Kee Beng; Teng, Wei Yuen; Yap, Tsi Tung; Wan, Siew Ping; Kong, Chun Jeng
2013-01-01
X-ray Computed Tomography (CT) allows visualisation of the physical structures in the interior of an object without physically opening or cutting it. This technology supports a wide range of applications in the non-destructive testing, failure analysis or performance evaluation of industrial products and components. Of the numerous factors that influence the performance characteristics of an X-ray CT system the energy level in the X-ray spectrum to be used is one of the most significant. The ability of the X-ray beam to penetrate a given thickness of a specific material is directly related to the maximum available energy level in the beam. Higher energy levels allow penetration of thicker components made of more dense materials. In response to local industry demand and in support of on-going research activity in the area of 3D X-ray imaging for industrial inspection the Singapore Institute of Manufacturing Technology (SIMTech) engaged in the design, development and integration of large scale multiple source X-ray computed tomography system based on X-ray sources operating at higher energies than previously available in the Institute. The system consists of a large area direct digital X-ray detector (410 x 410 mm), a multiple-axis manipulator system, a 225 kV open tube microfocus X-ray source and a 450 kV closed tube millifocus X-ray source. The 225 kV X-ray source can be operated in either transmission or reflection mode. The body of the 6-axis manipulator system is fabricated from heavy-duty steel onto which high precision linear and rotary motors have been mounted in order to achieve high accuracy, stability and repeatability. A source-detector distance of up to 2.5 m can be achieved. The system is controlled by a proprietary X-ray CT operating system developed by SIMTech. The system currently can accommodate samples up to 0.5 x 0.5 x 0.5 m in size with weight up to 50 kg. These specifications will be increased to 1.0 x 1.0 x 1.0 m and 100 kg in future
Kim, Youe Ree; Lee, Young Hwan; Lee, Jong-Ho; Yoon, Kwon-Ha
Granulomatosis with polyangiitis (GPA) is a systemic disorder that affects small- and medium- sized vessels in many organs. Although the kidneys are the second most commonly involved organ in patients with GPA, its manifestation as multiple intrarenal aneurysms is rare. We report an unusual manifestation of GPA with multiple intrarenal microaneurysms, as demonstrated by contrast-enhanced ultrasound and computed tomography. Copyright © 2017 Elsevier Inc. All rights reserved.
Application of Computational Methods in Planaria Research: A Current Update
Ghosh Shyamasree
2017-07-01
Full Text Available Planaria is a member of the Phylum Platyhelminthes including flatworms. Planarians possess the unique ability of regeneration from adult stem cells or neoblasts and finds importance as a model organism for regeneration and developmental studies. Although research is being actively carried out globally through conventional methods to understand the process of regeneration from neoblasts, biology of development, neurobiology and immunology of Planaria, there are many thought provoking questions related to stem cell plasticity, and uniqueness of regenerative potential in Planarians amongst other members of Phylum Platyhelminthes. The complexity of receptors and signalling mechanisms, immune system network, biology of repair, responses to injury are yet to be understood in Planaria. Genomic and transcriptomic studies have generated a vast repository of data, but their availability and analysis is a challenging task. Data mining, computational approaches of gene curation, bioinformatics tools for analysis of transcriptomic data, designing of databases, application of algorithms in deciphering changes of morphology by RNA interference (RNAi approaches, understanding regeneration experiments is a new venture in Planaria research that is helping researchers across the globe in understanding the biology. We highlight the applications of Hidden Markov models (HMMs in designing of computational tools and their applications in Planaria decoding their complex biology.
Nguyen, D. T.; Rogers, J. L., Jr.
1986-01-01
A finite element based programming system for minimum weight design of a truss-type structure subjected to displacement, stress, and lower and upper bounds on design variables is presented. The programming system consists of a number of independent processors, each performing a specific task. These processors, however, are interfaced through a well-organized data base, thus making the tasks of modifying, updating, or expanding the programming system much easier in a friendly environment provided by many inexpensive personal computers. The proposed software can be viewed as an important step in achieving a 'dummy' finite element for optimization. The programming system has been implemented on both large and small computers (such as VAX, CYBER, IBM-PC, and APPLE) although the focus is on the latter. Examples are presented to demonstrate the capabilities of the code. The present programming system can be used stand-alone or as part of the multilevel decomposition procedure to obtain optimum design for very large scale structural systems. Furthermore, other related research areas such as developing optimization algorithms (or in the larger level: a structural synthesis program) for future trends in using parallel computers may also benefit from this study.
Software Defects, Scientific Computation and the Scientific Method
CERN. Geneva
2011-01-01
Computation has rapidly grown in the last 50 years so that in many scientific areas it is the dominant partner in the practice of science. Unfortunately, unlike the experimental sciences, it does not adhere well to the principles of the scientific method as espoused by, for example, the philosopher Karl Popper. Such principles are built around the notions of deniability and reproducibility. Although much research effort has been spent on measuring the density of software defects, much less has been spent on the more difficult problem of measuring their effect on the output of a program. This talk explores these issues with numerous examples suggesting how this situation might be improved to match the demands of modern science. Finally it develops a theoretical model based on an amalgam of statistical mechanics and Hartley/Shannon information theory which suggests that software systems have strong implementation independent behaviour and supports the widely observed phenomenon that defects clust...
Computation of Hemagglutinin Free Energy Difference by the Confinement Method
2017-01-01
Hemagglutinin (HA) mediates membrane fusion, a crucial step during influenza virus cell entry. How many HAs are needed for this process is still subject to debate. To aid in this discussion, the confinement free energy method was used to calculate the conformational free energy difference between the extended intermediate and postfusion state of HA. Special care was taken to comply with the general guidelines for free energy calculations, thereby obtaining convergence and demonstrating reliability of the results. The energy that one HA trimer contributes to fusion was found to be 34.2 ± 3.4kBT, similar to the known contributions from other fusion proteins. Although computationally expensive, the technique used is a promising tool for the further energetic characterization of fusion protein mechanisms. Knowledge of the energetic contributions per protein, and of conserved residues that are crucial for fusion, aids in the development of fusion inhibitors for antiviral drugs. PMID:29151344
Conference on Boundary and Interior Layers : Computational and Asymptotic Methods
Stynes, Martin; Zhang, Zhimin
2017-01-01
This volume collects papers associated with lectures that were presented at the BAIL 2016 conference, which was held from 14 to 19 August 2016 at Beijing Computational Science Research Center and Tsinghua University in Beijing, China. It showcases the variety and quality of current research into numerical and asymptotic methods for theoretical and practical problems whose solutions involve layer phenomena. The BAIL (Boundary And Interior Layers) conferences, held usually in even-numbered years, bring together mathematicians and engineers/physicists whose research involves layer phenomena, with the aim of promoting interaction between these often-separate disciplines. These layers appear as solutions of singularly perturbed differential equations of various types, and are common in physical problems, most notably in fluid dynamics. This book is of interest for current researchers from mathematics, engineering and physics whose work involves the accurate app roximation of solutions of singularly perturbed diffe...
Computational Methods for Sensitivity and Uncertainty Analysis in Criticality Safety
Broadhead, B.L.; Childs, R.L.; Rearden, B.T.
1999-01-01
Interest in the sensitivity methods that were developed and widely used in the 1970s (the FORSS methodology at ORNL among others) has increased recently as a result of potential use in the area of criticality safety data validation procedures to define computational bias, uncertainties and area(s) of applicability. Functional forms of the resulting sensitivity coefficients can be used as formal parameters in the determination of applicability of benchmark experiments to their corresponding industrial application areas. In order for these techniques to be generally useful to the criticality safety practitioner, the procedures governing their use had to be updated and simplified. This paper will describe the resulting sensitivity analysis tools that have been generated for potential use by the criticality safety community
Statistical physics and computational methods for evolutionary game theory
Javarone, Marco Alberto
2018-01-01
This book presents an introduction to Evolutionary Game Theory (EGT) which is an emerging field in the area of complex systems attracting the attention of researchers from disparate scientific communities. EGT allows one to represent and study several complex phenomena, such as the emergence of cooperation in social systems, the role of conformity in shaping the equilibrium of a population, and the dynamics in biological and ecological systems. Since EGT models belong to the area of complex systems, statistical physics constitutes a fundamental ingredient for investigating their behavior. At the same time, the complexity of some EGT models, such as those realized by means of agent-based methods, often require the implementation of numerical simulations. Therefore, beyond providing an introduction to EGT, this book gives a brief overview of the main statistical physics tools (such as phase transitions and the Ising model) and computational strategies for simulating evolutionary games (such as Monte Carlo algor...
Activation method for measuring the neutron spectra parameters. Computer software
Efimov, B.V.; Ionov, V.S.; Konyaev, S.I.; Marin, S.V.
2005-01-01
The description of mathematical statement of a task for definition the spectral characteristics of neutron fields with use developed in RRC KI unified activation detectors (UKD) is resulted. The method of processing of results offered by authors activation measurements and calculation of the parameters used for an estimation of the neutron spectra characteristics is discussed. Features of processing of the experimental data received at measurements of activation with using UKD are considered. Activation detectors UKD contain a little bit specially the picked up isotopes giving at irradiation peaks scale of activity in the common spectrum scale of activity. Computing processing of results of the measurements is applied on definition of spectrum parameters for nuclear reactor installations with thermal and close to such power spectrum of neutrons. The example of the data processing, the measurements received at carrying out at RRC KI research reactor F-1 is resulted [ru
A computed microtomography method for understanding epiphyseal growth plate fusion
Staines, Katherine A.; Madi, Kamel; Javaheri, Behzad; Lee, Peter D.; Pitsillides, Andrew A.
2017-12-01
The epiphyseal growth plate is a developmental region responsible for linear bone growth, in which chondrocytes undertake a tightly regulated series of biological processes. Concomitant with the cessation of growth and sexual maturation, the human growth plate undergoes progressive narrowing, and ultimately disappears. Despite the crucial role of this growth plate fusion ‘bridging’ event, the precise mechanisms by which it is governed are complex and yet to be established. Progress is likely hindered by the current methods for growth plate visualisation; these are invasive and largely rely on histological procedures. Here we describe our non-invasive method utilising synchrotron x-ray computed microtomography for the examination of growth plate bridging, which ultimately leads to its closure coincident with termination of further longitudinal bone growth. We then apply this method to a dataset obtained from a benchtop microcomputed tomography scanner to highlight its potential for wide usage. Furthermore, we conduct finite element modelling at the micron-scale to reveal the effects of growth plate bridging on local tissue mechanics. Employment of these 3D analyses of growth plate bone bridging is likely to advance our understanding of the physiological mechanisms that control growth plate fusion.
Methods and computer codes for probabilistic sensitivity and uncertainty analysis
Vaurio, J.K.
1985-01-01
This paper describes the methods and applications experience with two computer codes that are now available from the National Energy Software Center at Argonne National Laboratory. The purpose of the SCREEN code is to identify a group of most important input variables of a code that has many (tens, hundreds) input variables with uncertainties, and do this without relying on judgment or exhaustive sensitivity studies. Purpose of the PROSA-2 code is to propagate uncertainties and calculate the distributions of interesting output variable(s) of a safety analysis code using response surface techniques, based on the same runs used for screening. Several applications are discussed, but the codes are generic, not tailored to any specific safety application code. They are compatible in terms of input/output requirements but also independent of each other, e.g., PROSA-2 can be used without first using SCREEN if a set of important input variables has first been selected by other methods. Also, although SCREEN can select cases to be run (by random sampling), a user can select cases by other methods if he so prefers, and still use the rest of SCREEN for identifying important input variables
Emerging Computational Methods for the Rational Discovery of Allosteric Drugs.
Wagner, Jeffrey R; Lee, Christopher T; Durrant, Jacob D; Malmstrom, Robert D; Feher, Victoria A; Amaro, Rommie E
2016-06-08
Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages.
Computation of rectangular source integral by rational parameter polynomial method
Prabha, Hem
2001-01-01
Hubbell et al. (J. Res. Nat Bureau Standards 64C, (1960) 121) have obtained a series expansion for the calculation of the radiation field generated by a plane isotropic rectangular source (plaque), in which leading term is the integral H(a,b). In this paper another integral I(a,b), which is related with the integral H(a,b) has been solved by the rational parameter polynomial method. From I(a,b), we compute H(a,b). Using this method the integral I(a,b) is expressed in the form of a polynomial of a rational parameter. Generally, a function f (x) is expressed in terms of x. In this method this is expressed in terms of x/(1+x). In this way, the accuracy of the expression is good over a wide range of x as compared to the earlier approach. The results for I(a,b) and H(a,b) are given for a sixth degree polynomial and are found to be in good agreement with the results obtained by numerically integrating the integral. Accuracy could be increased either by increasing the degree of the polynomial or by dividing the range of integration. The results of H(a,b) and I(a,b) are given for values of b and a up to 2.0 and 20.0, respectively
Brewe, Eric; Bruun, Jesper; Bearden, Ian G.
2016-01-01
We describe "Module Analysis for Multiple Choice Responses" (MAMCR), a new methodology for carrying out network analysis on responses to multiple choice assessments. This method is used to identify modules of non-normative responses which can then be interpreted as an alternative to factor analysis. MAMCR allows us to identify conceptual…
29 CFR 4010.12 - Alternative method of compliance for certain sponsors of multiple employer plans.
2010-07-01
... BENEFIT GUARANTY CORPORATION CERTAIN REPORTING AND DISCLOSURE REQUIREMENTS ANNUAL FINANCIAL AND ACTUARIAL INFORMATION REPORTING § 4010.12 Alternative method of compliance for certain sponsors of multiple employer... part for an information year if any contributing sponsor of the multiple employer plan provides a...
Multiple scattering of low energy rare gas ions: a comparison of experiment and computer simulation
Heiland, W.; Taglauer, E.; Robinson, M.T.
1976-01-01
Some aspects of ion scattering below a few keV have been interpreted by multiple scattering. This can partly be simulated by chain or string models, where the single crystal surface is replaced by a chain of atoms. The computer program MARLOWE allows a simulation of solid-ion interaction, which is much closer to reality, e.g. the crystal is three-dimensional, includes lattice vibrations, electronic stopping power, different scattering potentials, etc. It is shown that the energy of the reflected ions as a function of the primary energy, lattice constant, impact angle and scattering angle can be understood within the string model. These results of the string model are confirmed by the MARLOWE calculations. For an interpretation of the measured intensities the simple string model is insufficient, whereas with MARLOWE reasonable agreement with experimental data may be achieved, if the thermal vibrations of the lattice atoms are taken into account. The experimental data include Ne + →Ni, Ne + →Ag and preliminary data on Ne + →W. The screening parameters of the scattering potentials are estimated for these ion-atom combinations. The results allow some conclusions about surface Debye temperatures. (Auth.)
Kenyon Colin
2009-05-01
Full Text Available Abstract Background Despite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the Plasmodium parasite, some are promising targets to carry out rational drug discovery. Motivation Recent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR, and on a new promising one, glutathione-S-transferase. Methods In silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate in silico docking and in information technology to design and operate large scale grid infrastructures. Results On the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, In vitro results are underway for all the targets against which screening is performed. Conclusion The current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software
On the solution of a few problems of multiple scattering by Monte Carlo method
Bluet, J.C.
1966-02-01
Three problems of multiple scattering arising from neutron cross sections experiments, are reported here. The common hypothesis are: - Elastic scattering is the only possible process - Angular distributions are isotropic - Losses of particle energy are negligible in successive collisions. In the three cases practical results, corresponding to actual experiments are given. Moreover the results are shown in more general way, using dimensionless variable such as the ratio of geometrical dimensions to neutron mean free path. The FORTRAN codes are given together with to the corresponding flow charts, and lexicons of symbols. First problem: Measurement of sodium capture cross-section. A sodium sample of given geometry is submitted to a neutron flux. Induced activity is then measured by means of a sodium iodide cristal. The distribution of active nuclei in the sample, and the counter efficiency are calculated by Monte-Carlo method taking multiple scattering into account. Second problem: absolute measurement of a neutron flux using a glass scintillator. The scintillator is a use of lithium 6 loaded glass, submitted to neutron flux perpendicular to its plane faces. If the glass thickness is not negligible compared with scattering mean free path λ, the mean path e' of neutrons in the glass is different from the thickness. Monte-Carlo calculation are made to compute this path and a relative correction to efficiency equal to (e' - e)/e. Third problem: study of a neutron collimator. A neutron detector is placed at the bottom of a cylinder surrounded with water. A neutron source is placed on the cylinder axis, in front of the water shield. The number of neutron tracks going directly and indirectly through the water from the source to the detector are counted. (author) [fr
Trace element analysis of environmental samples by multiple prompt gamma-ray analysis method
Oshima, Masumi; Matsuo, Motoyuki; Shozugawa, Katsumi
2011-01-01
The multiple γ-ray detection method has been proved to be a high-resolution and high-sensitivity method in application to nuclide quantification. The neutron prompt γ-ray analysis method is successfully extended by combining it with the γ-ray detection method, which is called Multiple prompt γ-ray analysis, MPGA. In this review we show the principle of this method and its characteristics. Several examples of its application to environmental samples, especially river sediments in the urban area and sea sediment samples are also described. (author)
Sabourin, David; Snakenborg, Detlef; Dufva, Hans Martin
2009-01-01
In this paper a method is presented for creating 'interconnection blocks' that are re-usable and provide multiple, aligned and planar microfluidic interconnections. Interconnection blocks made from polydimethylsiloxane allow rapid testing of microfluidic chips and unobstructed microfluidic observ...
Ma, J.; Liu, Q.
2018-02-01
This paper presents an improved short circuit calculation method, based on pre-computed surface to determine the short circuit current of a distribution system with multiple doubly fed induction generators (DFIGs). The short circuit current, injected into power grid by DFIG, is determined by low voltage ride through (LVRT) control and protection under grid fault. However, the existing methods are difficult to calculate the short circuit current of DFIG in engineering practice due to its complexity. A short circuit calculation method, based on pre-computed surface, was proposed by developing the surface of short circuit current changing with the calculating impedance and the open circuit voltage. And the short circuit currents were derived by taking into account the rotor excitation and crowbar activation time. Finally, the pre-computed surfaces of short circuit current at different time were established, and the procedure of DFIG short circuit calculation considering its LVRT was designed. The correctness of proposed method was verified by simulation.
A method for describing the doses delivered by transmission x-ray computed tomography
Shope, T.B.; Gagne, R.M.; Johnson, G.C.
1981-01-01
A method for describing the absorbed dose delivered by x-ray transmission computed tomography (CT) is proposed which provides a means to characterize the dose resulting from CT procedures consisting of a series of adjacent scans. The dose descriptor chosen is the average dose at several locations in the imaged volume of the central scan of the series. It is shown that this average dose, as defined, for locations in the central scan of the series can be obtained from the integral of the dose profile perpendicular to the scan plane at these same locations for a single scan. This method for estimating the average dose from a CT procedure has been evaluated as a function of the number of scans in the multiple scan procedure and location in the dosimetry phantom using single scan dose profiles obtained from five different types of CT systems. For the higher dose regions in the phantoms, the multiple scan dose descriptor derived from the single scan dose profiles overestimates the multiple scan average dose by no more than 10%, provided the procedure consists of at least eight scans
Analysis and performance estimation of the Conjugate Gradient method on multiple GPUs
Verschoor, M.; Jalba, A.C.
2012-01-01
The Conjugate Gradient (CG) method is a widely-used iterative method for solving linear systems described by a (sparse) matrix. The method requires a large amount of Sparse-Matrix Vector (SpMV) multiplications, vector reductions and other vector operations to be performed. We present a number of
Fish, Laurel J.; Halcoussis, Dennis; Phillips, G. Michael
2017-01-01
The Monte Carlo method and related multiple imputation methods are traditionally used in math, physics and science to estimate and analyze data and are now becoming standard tools in analyzing business and financial problems. However, few sources explain the application of the Monte Carlo method for individuals and business professionals who are…
Massimiliano Ferraioli
2016-01-01
Full Text Available Although the most commonly used isolation systems exhibit nonlinear inelastic behaviour, the equivalent linear elastic analysis is commonly used in the design and assessment of seismic-isolated structures. The paper investigates if the linear elastic model is suitable for the analysis of a seismically isolated multiple building structure. To this aim, its computed responses were compared with those calculated by nonlinear dynamic analysis. A common base isolation plane connects the isolation bearings supporting the adjacent structures. In this situation, the conventional equivalent linear elastic analysis may have some problems of accuracy because this method is calibrated on single base-isolated structures. Moreover, the torsional characteristics of the combined system are significantly different from those of separate isolated buildings. A number of numerical simulations and parametric studies under earthquake excitations were performed. The accuracy of the dynamic response obtained by the equivalent linear elastic model was calculated by the magnitude of the error with respect to the corresponding response considering the nonlinear behaviour of the isolation system. The maximum displacements at the isolation level, the maximum interstorey drifts, and the peak absolute acceleration were selected as the most important response measures. The influence of mass eccentricity, torsion, and high-modes effects was finally investigated.
Salisbury, Margaret L; Lynch, David A; van Beek, Edwin J R; Kazerooni, Ella A; Guo, Junfeng; Xia, Meng; Murray, Susan; Anstrom, Kevin J; Yow, Eric; Martinez, Fernando J; Hoffman, Eric A; Flaherty, Kevin R
2017-04-01
Adaptive multiple features method (AMFM) lung texture analysis software recognizes high-resolution computed tomography (HRCT) patterns. To evaluate AMFM and visual quantification of HRCT patterns and their relationship with disease progression in idiopathic pulmonary fibrosis. Patients with idiopathic pulmonary fibrosis in a clinical trial of prednisone, azathioprine, and N-acetylcysteine underwent HRCT at study start and finish. Proportion of lung occupied by ground glass, ground glass-reticular (GGR), honeycombing, emphysema, and normal lung densities were measured by AMFM and three radiologists, documenting baseline disease extent and postbaseline change. Disease progression includes composite mortality, hospitalization, and 10% FVC decline. Agreement between visual and AMFM measurements was moderate for GGR (Pearson's correlation r = 0.60, P fibrosis (as measured by GGR densities) is independently associated with elevated hazard for disease progression. Postbaseline change in AMFM-measured and visually measured GGR densities are modestly correlated with change in FVC. AMFM-measured fibrosis is an automated adjunct to existing prognostic markers and may allow for study enrichment with subjects at increased disease progression risk.