Epidemic modeling in complex realities.

PubMed

Colizza, Vittoria; Barthélemy, Marc; Barrat, Alain; Vespignani, Alessandro

2007-04-01

In our global world, the increasing complexity of social relations and transport infrastructures are key factors in the spread of epidemics. In recent years, the increasing availability of computer power has enabled both to obtain reliable data allowing one to quantify the complexity of the networks on which epidemics may propagate and to envision computational tools able to tackle the analysis of such propagation phenomena. These advances have put in evidence the limits of homogeneous assumptions and simple spatial diffusion approaches, and stimulated the inclusion of complex features and heterogeneities relevant in the description of epidemic diffusion. In this paper, we review recent progresses that integrate complex systems and networks analysis with epidemic modelling and focus on the impact of the various complex features of real systems on the dynamics of epidemic spreading.

ADAM: analysis of discrete models of biological systems using computer algebra.

PubMed

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics.

Quantitative ROESY analysis of computational models: structural studies of citalopram and β-cyclodextrin complexes by (1) H-NMR and computational methods.

PubMed

Ali, Syed Mashhood; Shamim, Shazia

2015-07-01

Complexation of racemic citalopram with β-cyclodextrin (β-CD) in aqueous medium was investigated to determine atom-accurate structure of the inclusion complexes. (1) H-NMR chemical shift change data of β-CD cavity protons in the presence of citalopram confirmed the formation of 1 : 1 inclusion complexes. ROESY spectrum confirmed the presence of aromatic ring in the β-CD cavity but whether one of the two or both rings was not clear. Molecular mechanics and molecular dynamic calculations showed the entry of fluoro-ring from wider side of β-CD cavity as the most favored mode of inclusion. Minimum energy computational models were analyzed for their accuracy in atomic coordinates by comparison of calculated and experimental intermolecular ROESY peak intensities, which were not found in agreement. Several least energy computational models were refined and analyzed till calculated and experimental intensities were compatible. The results demonstrate that computational models of CD complexes need to be analyzed for atom-accuracy and quantitative ROESY analysis is a promising method. Moreover, the study also validates that the quantitative use of ROESY is feasible even with longer mixing times if peak intensity ratios instead of absolute intensities are used. Copyright © 2015 John Wiley & Sons, Ltd.

Modeling Cognitive Strategies during Complex Task Performing Process

ERIC Educational Resources Information Center

Mazman, Sacide Guzin; Altun, Arif

2012-01-01

The purpose of this study is to examine individuals' computer based complex task performing processes and strategies in order to determine the reasons of failure by cognitive task analysis method and cued retrospective think aloud with eye movement data. Study group was five senior students from Computer Education and Instructional Technologies…

Using Microcomputers for Assessment and Error Analysis. Monograph #23.

ERIC Educational Resources Information Center

Hasselbring, Ted S.; And Others

This monograph provides an overview of computer-based assessment and error analysis in the instruction of elementary students with complex medical, learning, and/or behavioral problems. Information on generating and scoring tests using the microcomputer is offered, as are ideas for using computers in the analysis of mathematical strategies and…

An Approach to Experimental Design for the Computer Analysis of Complex Phenomenon

NASA Technical Reports Server (NTRS)

Rutherford, Brian

2000-01-01

The ability to make credible system assessments, predictions and design decisions related to engineered systems and other complex phenomenon is key to a successful program for many large-scale investigations in government and industry. Recently, many of these large-scale analyses have turned to computational simulation to provide much of the required information. Addressing specific goals in the computer analysis of these complex phenomenon is often accomplished through the use of performance measures that are based on system response models. The response models are constructed using computer-generated responses together with physical test results where possible. They are often based on probabilistically defined inputs and generally require estimation of a set of response modeling parameters. As a consequence, the performance measures are themselves distributed quantities reflecting these variabilities and uncertainties. Uncertainty in the values of the performance measures leads to uncertainties in predicted performance and can cloud the decisions required of the analysis. A specific goal of this research has been to develop methodology that will reduce this uncertainty in an analysis environment where limited resources and system complexity together restrict the number of simulations that can be performed. An approach has been developed that is based on evaluation of the potential information provided for each "intelligently selected" candidate set of computer runs. Each candidate is evaluated by partitioning the performance measure uncertainty into two components - one component that could be explained through the additional computational simulation runs and a second that would remain uncertain. The portion explained is estimated using a probabilistic evaluation of likely results for the additional computational analyses based on what is currently known about the system. The set of runs indicating the largest potential reduction in uncertainty is then selected and the computational simulations are performed. Examples are provided to demonstrate this approach on small scale problems. These examples give encouraging results. Directions for further research are indicated.

Overset grid applications on distributed memory MIMD computers

NASA Technical Reports Server (NTRS)

Chawla, Kalpana; Weeratunga, Sisira

1994-01-01

Analysis of modern aerospace vehicles requires the computation of flowfields about complex three dimensional geometries composed of regions with varying spatial resolution requirements. Overset grid methods allow the use of proven structured grid flow solvers to address the twin issues of geometrical complexity and the resolution variation by decomposing the complex physical domain into a collection of overlapping subdomains. This flexibility is accompanied by the need for irregular intergrid boundary communication among the overlapping component grids. This study investigates a strategy for implementing such a static overset grid implicit flow solver on distributed memory, MIMD computers; i.e., the 128 node Intel iPSC/860 and the 208 node Intel Paragon. Performance data for two composite grid configurations characteristic of those encountered in present day aerodynamic analysis are also presented.

ASIC For Complex Fixed-Point Arithmetic

NASA Technical Reports Server (NTRS)

Petilli, Stephen G.; Grimm, Michael J.; Olson, Erlend M.

1995-01-01

Application-specific integrated circuit (ASIC) performs 24-bit, fixed-point arithmetic operations on arrays of complex-valued input data. High-performance, wide-band arithmetic logic unit (ALU) designed for use in computing fast Fourier transforms (FFTs) and for performing ditigal filtering functions. Other applications include general computations involved in analysis of spectra and digital signal processing.

Sensitivity analysis of dynamic biological systems with time-delays.

PubMed

Wu, Wu Hsiung; Wang, Feng Sheng; Chang, Maw Shang

2010-10-15

Mathematical modeling has been applied to the study and analysis of complex biological systems for a long time. Some processes in biological systems, such as the gene expression and feedback control in signal transduction networks, involve a time delay. These systems are represented as delay differential equation (DDE) models. Numerical sensitivity analysis of a DDE model by the direct method requires the solutions of model and sensitivity equations with time-delays. The major effort is the computation of Jacobian matrix when computing the solution of sensitivity equations. The computation of partial derivatives of complex equations either by the analytic method or by symbolic manipulation is time consuming, inconvenient, and prone to introduce human errors. To address this problem, an automatic approach to obtain the derivatives of complex functions efficiently and accurately is necessary. We have proposed an efficient algorithm with an adaptive step size control to compute the solution and dynamic sensitivities of biological systems described by ordinal differential equations (ODEs). The adaptive direct-decoupled algorithm is extended to solve the solution and dynamic sensitivities of time-delay systems describing by DDEs. To save the human effort and avoid the human errors in the computation of partial derivatives, an automatic differentiation technique is embedded in the extended algorithm to evaluate the Jacobian matrix. The extended algorithm is implemented and applied to two realistic models with time-delays: the cardiovascular control system and the TNF-α signal transduction network. The results show that the extended algorithm is a good tool for dynamic sensitivity analysis on DDE models with less user intervention. By comparing with direct-coupled methods in theory, the extended algorithm is efficient, accurate, and easy to use for end users without programming background to do dynamic sensitivity analysis on complex biological systems with time-delays.

Computational structural mechanics methods research using an evolving framework

NASA Technical Reports Server (NTRS)

Knight, N. F., Jr.; Lotts, C. G.; Gillian, R. E.

1990-01-01

Advanced structural analysis and computational methods that exploit high-performance computers are being developed in a computational structural mechanics research activity sponsored by the NASA Langley Research Center. These new methods are developed in an evolving framework and applied to representative complex structural analysis problems from the aerospace industry. An overview of the methods development environment is presented, and methods research areas are described. Selected application studies are also summarized.

Applications of Computer Technology in Complex Craniofacial Reconstruction.

PubMed

Day, Kristopher M; Gabrick, Kyle S; Sargent, Larry A

2018-03-01

To demonstrate our use of advanced 3-dimensional (3D) computer technology in the analysis, virtual surgical planning (VSP), 3D modeling (3DM), and treatment of complex congenital and acquired craniofacial deformities. We present a series of craniofacial defects treated at a tertiary craniofacial referral center utilizing state-of-the-art 3D computer technology. All patients treated at our center using computer-assisted VSP, prefabricated custom-designed 3DMs, and/or 3D printed custom implants (3DPCI) in the reconstruction of craniofacial defects were included in this analysis. We describe the use of 3D computer technology to precisely analyze, plan, and reconstruct 31 craniofacial deformities/syndromes caused by: Pierre-Robin (7), Treacher Collins (5), Apert's (2), Pfeiffer (2), Crouzon (1) Syndromes, craniosynostosis (6), hemifacial microsomia (2), micrognathia (2), multiple facial clefts (1), and trauma (3). In select cases where the available bone was insufficient for skeletal reconstruction, 3DPCIs were fabricated using 3D printing. We used VSP in 30, 3DMs in all 31, distraction osteogenesis in 16, and 3DPCIs in 13 cases. Utilizing these technologies, the above complex craniofacial defects were corrected without significant complications and with excellent aesthetic results. Modern 3D technology allows the surgeon to better analyze complex craniofacial deformities, precisely plan surgical correction with computer simulation of results, customize osteotomies, plan distractions, and print 3DPCI, as needed. The use of advanced 3D computer technology can be applied safely and potentially improve aesthetic and functional outcomes after complex craniofacial reconstruction. These techniques warrant further study and may be reproducible in various centers of care.

Graphics Flutter Analysis Methods, an interactive computing system at Lockheed-California Company

NASA Technical Reports Server (NTRS)

Radovcich, N. A.

1975-01-01

An interactive computer graphics system, Graphics Flutter Analysis Methods (GFAM), was developed to complement FAMAS, a matrix-oriented batch computing system, and other computer programs in performing complex numerical calculations using a fully integrated data management system. GFAM has many of the matrix operation capabilities found in FAMAS, but on a smaller scale, and is utilized when the analysis requires a high degree of interaction between the engineer and computer, and schedule constraints exclude the use of batch entry programs. Applications of GFAM to a variety of preliminary design, development design, and project modification programs suggest that interactive flutter analysis using matrix representations is a feasible and cost effective computing tool.

A new decision sciences for complex systems.

PubMed

Lempert, Robert J

2002-05-14

Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an approach to decision-making under conditions of deep uncertainty that is ideally suited to applying complex systems to policy analysis. The article demonstrates the approach on the policy problem of global climate change, with a particular focus on the role of technology policies in a robust, adaptive strategy for greenhouse gas abatement.

Modeling And Simulation Of Bar Code Scanners Using Computer Aided Design Software

NASA Astrophysics Data System (ADS)

Hellekson, Ron; Campbell, Scott

1988-06-01

Many optical systems have demanding requirements to package the system in a small 3 dimensional space. The use of computer graphic tools can be a tremendous aid to the designer in analyzing the optical problems created by smaller and less costly systems. The Spectra Physics grocery store bar code scanner employs an especially complex 3 dimensional scan pattern to read bar code labels. By using a specially written program which interfaces with a computer aided design system, we have simulated many of the functions of this complex optical system. In this paper we will illustrate how a recent version of the scanner has been designed. We will discuss the use of computer graphics in the design process including interactive tweaking of the scan pattern, analysis of collected light, analysis of the scan pattern density, and analysis of the manufacturing tolerances used to build the scanner.

The Difficult Process of Scientific Modelling: An Analysis Of Novices' Reasoning During Computer-Based Modelling

ERIC Educational Resources Information Center

Sins, Patrick H. M.; Savelsbergh, Elwin R.; van Joolingen, Wouter R.

2005-01-01

Although computer modelling is widely advocated as a way to offer students a deeper understanding of complex phenomena, the process of modelling is rather complex itself and needs scaffolding. In order to offer adequate support, a thorough understanding of the reasoning processes students employ and of difficulties they encounter during a…

Fast computation of derivative based sensitivities of PSHA models via algorithmic differentiation

NASA Astrophysics Data System (ADS)

Leövey, Hernan; Molkenthin, Christian; Scherbaum, Frank; Griewank, Andreas; Kuehn, Nicolas; Stafford, Peter

2015-04-01

Probabilistic seismic hazard analysis (PSHA) is the preferred tool for estimation of potential ground-shaking hazard due to future earthquakes at a site of interest. A modern PSHA represents a complex framework which combines different models with possible many inputs. Sensitivity analysis is a valuable tool for quantifying changes of a model output as inputs are perturbed, identifying critical input parameters and obtaining insight in the model behavior. Differential sensitivity analysis relies on calculating first-order partial derivatives of the model output with respect to its inputs. Moreover, derivative based global sensitivity measures (Sobol' & Kucherenko '09) can be practically used to detect non-essential inputs of the models, thus restricting the focus of attention to a possible much smaller set of inputs. Nevertheless, obtaining first-order partial derivatives of complex models with traditional approaches can be very challenging, and usually increases the computation complexity linearly with the number of inputs appearing in the models. In this study we show how Algorithmic Differentiation (AD) tools can be used in a complex framework such as PSHA to successfully estimate derivative based sensitivities, as is the case in various other domains such as meteorology or aerodynamics, without no significant increase in the computation complexity required for the original computations. First we demonstrate the feasibility of the AD methodology by comparing AD derived sensitivities to analytically derived sensitivities for a basic case of PSHA using a simple ground-motion prediction equation. In a second step, we derive sensitivities via AD for a more complex PSHA study using a ground motion attenuation relation based on a stochastic method to simulate strong motion. The presented approach is general enough to accommodate more advanced PSHA studies of higher complexity.

USSR and Eastern Europe Scientific Abstracts, Cybernetics, Computers and Automation Technology, Number 29.

DTIC Science & Technology

1978-01-17

approach to designing computers: Formal mathematical methods were applied and computers themselves began to be widely used in designing other...capital, labor resources and the funds of consumers. Analysis of the model indicates that at the present time the average complexity of production of...ALGORITHMIC COMPLETENESS AND COMPLEXITY OF MICROPROGRAMS Kiev KIBERNETIKA in Russian No 3, May/Jun 77 pp 1-15 manuscript received 22 Dec 76 G0LUNK0V

PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows

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

Deelman, Ewa; Carothers, Christopher; Mandal, Anirban

Here we report that computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Therefore, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation andmore » data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.« less

PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows

DOE PAGES

Deelman, Ewa; Carothers, Christopher; Mandal, Anirban; ...

2015-07-14

Here we report that computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Therefore, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation andmore » data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.« less

ADAM: Analysis of Discrete Models of Biological Systems Using Computer Algebra

PubMed Central

2011-01-01

Background Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. Results We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Conclusions Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics. PMID:21774817

Advanced complex trait analysis.

PubMed

Gray, A; Stewart, I; Tenesa, A

2012-12-01

The Genome-wide Complex Trait Analysis (GCTA) software package can quantify the contribution of genetic variation to phenotypic variation for complex traits. However, as those datasets of interest continue to increase in size, GCTA becomes increasingly computationally prohibitive. We present an adapted version, Advanced Complex Trait Analysis (ACTA), demonstrating dramatically improved performance. We restructure the genetic relationship matrix (GRM) estimation phase of the code and introduce the highly optimized parallel Basic Linear Algebra Subprograms (BLAS) library combined with manual parallelization and optimization. We introduce the Linear Algebra PACKage (LAPACK) library into the restricted maximum likelihood (REML) analysis stage. For a test case with 8999 individuals and 279,435 single nucleotide polymorphisms (SNPs), we reduce the total runtime, using a compute node with two multi-core Intel Nehalem CPUs, from ∼17 h to ∼11 min. The source code is fully available under the GNU Public License, along with Linux binaries. For more information see http://www.epcc.ed.ac.uk/software-products/acta. a.gray@ed.ac.uk Supplementary data are available at Bioinformatics online.

Discrete Fourier Transform Analysis in a Complex Vector Space

NASA Technical Reports Server (NTRS)

Dean, Bruce H.

2009-01-01

Alternative computational strategies for the Discrete Fourier Transform (DFT) have been developed using analysis of geometric manifolds. This approach provides a general framework for performing DFT calculations, and suggests a more efficient implementation of the DFT for applications using iterative transform methods, particularly phase retrieval. The DFT can thus be implemented using fewer operations when compared to the usual DFT counterpart. The software decreases the run time of the DFT in certain applications such as phase retrieval that iteratively call the DFT function. The algorithm exploits a special computational approach based on analysis of the DFT as a transformation in a complex vector space. As such, this approach has the potential to realize a DFT computation that approaches N operations versus Nlog(N) operations for the equivalent Fast Fourier Transform (FFT) calculation.

Reliability/safety analysis of a fly-by-wire system

NASA Technical Reports Server (NTRS)

Brock, L. D.; Goddman, H. A.

1980-01-01

An analysis technique has been developed to estimate the reliability of a very complex, safety-critical system by constructing a diagram of the reliability equations for the total system. This diagram has many of the characteristics of a fault-tree or success-path diagram, but is much easier to construct for complex redundant systems. The diagram provides insight into system failure characteristics and identifies the most likely failure modes. A computer program aids in the construction of the diagram and the computation of reliability. Analysis of the NASA F-8 Digital Fly-by-Wire Flight Control System is used to illustrate the technique.

Metagram Software - A New Perspective on the Art of Computation.

DTIC Science & Technology

1981-10-01

numober) Computer Programming Information and Analysis Metagramming Philosophy Intelligence Information Systefs Abstraction & Metasystems Metagranmming...control would also serve well in the analysis of military and political intelligence, and in other areas where highly abstract methods of thought serve...needed in intelligence because several levels of abstraction are involved in a political or military system, because analysis entails a complex interplay

Large-scale structural analysis: The structural analyst, the CSM Testbed and the NAS System

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Mccleary, Susan L.; Macy, Steven C.; Aminpour, Mohammad A.

1989-01-01

The Computational Structural Mechanics (CSM) activity is developing advanced structural analysis and computational methods that exploit high-performance computers. Methods are developed in the framework of the CSM testbed software system and applied to representative complex structural analysis problems from the aerospace industry. An overview of the CSM testbed methods development environment is presented and some numerical methods developed on a CRAY-2 are described. Selected application studies performed on the NAS CRAY-2 are also summarized.

Research in Computational Astrobiology

NASA Technical Reports Server (NTRS)

Chaban, Galina; Colombano, Silvano; Scargle, Jeff; New, Michael H.; Pohorille, Andrew; Wilson, Michael A.

2003-01-01

We report on several projects in the field of computational astrobiology, which is devoted to advancing our understanding of the origin, evolution and distribution of life in the Universe using theoretical and computational tools. Research projects included modifying existing computer simulation codes to use efficient, multiple time step algorithms, statistical methods for analysis of astrophysical data via optimal partitioning methods, electronic structure calculations on water-nuclei acid complexes, incorporation of structural information into genomic sequence analysis methods and calculations of shock-induced formation of polycylic aromatic hydrocarbon compounds.

Biomechanics of compensatory mechanisms in spinal-pelvic complex

NASA Astrophysics Data System (ADS)

Ivanov, D. V.; Hominets, V. V.; Kirillova, I. V.; Kossovich, L. Yu; Kudyashev, A. L.; Teremshonok, A. V.

2018-04-01

3D geometric solid computer model of spinal-pelvic complex was constructed on the basis of computed tomography and full body X-ray in standing position data. The constructed model was used for biomechanical analysis of compensatory mechanisms arising in the spine with anteversion and retroversion of the pelvis. The results of numerical biomechanical 3D modeling are in good agreement with the clinical data.

Computer analysis of potentiometric data of complexes formation in the solution

NASA Astrophysics Data System (ADS)

Jastrzab, Renata; Kaczmarek, Małgorzata T.; Tylkowski, Bartosz; Odani, Akira

2018-02-01

The determination of equilibrium constants is an important process for many branches of chemistry. In this review we provide the readers with a discussion on computer methods which have been applied for elaboration of potentiometric experimental data generated during complexes formation in solution. The review describes both: general basis of modeling tools and examples of the use of calculated stability constants.

SIGMA--A Graphical Approach to Teaching Simulation.

ERIC Educational Resources Information Center

Schruben, Lee W.

1992-01-01

SIGMA (Simulation Graphical Modeling and Analysis) is a computer graphics environment for building, testing, and experimenting with discrete event simulation models on personal computers. It uses symbolic representations (computer animation) to depict the logic of large, complex discrete event systems for easier understanding and has proven itself…

Synthesizing Results from Empirical Research on Computer-Based Scaffolding in STEM Education: A Meta-Analysis

ERIC Educational Resources Information Center

Belland, Brian R.; Walker, Andrew E.; Kim, Nam Ju; Lefler, Mason

2017-01-01

Computer-based scaffolding assists students as they generate solutions to complex problems, goals, or tasks, helping increase and integrate their higher order skills in the process. However, despite decades of research on scaffolding in STEM (science, technology, engineering, and mathematics) education, no existing comprehensive meta-analysis has…

Hierarchical coordinate systems for understanding complexity and its evolution, with applications to genetic regulatory networks.

PubMed

Egri-Nagy, Attila; Nehaniv, Chrystopher L

2008-01-01

Beyond complexity measures, sometimes it is worthwhile in addition to investigate how complexity changes structurally, especially in artificial systems where we have complete knowledge about the evolutionary process. Hierarchical decomposition is a useful way of assessing structural complexity changes of organisms modeled as automata, and we show how recently developed computational tools can be used for this purpose, by computing holonomy decompositions and holonomy complexity. To gain insight into the evolution of complexity, we investigate the smoothness of the landscape structure of complexity under minimal transitions. As a proof of concept, we illustrate how the hierarchical complexity analysis reveals symmetries and irreversible structure in biological networks by applying the methods to the lac operon mechanism in the genetic regulatory network of Escherichia coli.

[Automated procedures for microscopic analyses of blood smears: medical testing a MECOS-Ts2 complex].

PubMed

Pliasunova, S A; Balugian, R Sh; Khmel'nitskiĭ, K E; Medovyĭ, V S; Parpara, A A; Piatnitskiĭ, A M; Sokolinskiĭ, B Z; Dem'ianov, V L; Nikolaenko, D S

2006-10-01

The paper presents the results of medical tests of a group of computer-aided procedures for microscopic analysis by means of a MECOS-Ts2 complex (ZAO "MECOS", Russia), which have been conducted at the Republican Children's Clinical Hospital, the Research Institute of Emergency Pediatric Surgery and Traumatology, and Moscow City Clinical Hospital No. 23. Computer-aided procedures for calculating the differential count and for analyzing the morphology of red blood cells were tested on blood smears from a total of 443 patients and donors, computer-aided calculation of the count of reticulocytes was tested on 318 smears. The tests were carried out under the US standard NCCLS-H20A. Manual microscopy (443 smears) and flow blood analysis on a Coulter GEN*S (125 smears) were used as reference methods. The quality of collection of samples and laboriousness were additionally assessed. The certified MECOS-Ts2 subsystems were additionally used as reference tools. The tests indicated the advantage of computer-aided MECOS-Tsl2 complex microscopy over manual microscopy.

Bayesian linkage and segregation analysis: factoring the problem.

PubMed

Matthysse, S

2000-01-01

Complex segregation analysis and linkage methods are mathematical techniques for the genetic dissection of complex diseases. They are used to delineate complex modes of familial transmission and to localize putative disease susceptibility loci to specific chromosomal locations. The computational problem of Bayesian linkage and segregation analysis is one of integration in high-dimensional spaces. In this paper, three available techniques for Bayesian linkage and segregation analysis are discussed: Markov Chain Monte Carlo (MCMC), importance sampling, and exact calculation. The contribution of each to the overall integration will be explicitly discussed.

Annual Research Briefs - 2006

DTIC Science & Technology

2006-12-01

IACCARINO AND Q. WANG 3 Strain and stress analysis of uncertain engineering systems . D. GHOSH, C. FARHAT AND P. AVERY 17 Separated flow in a three...research in predictive science in complex systems , CTR has strived to maintain a critical mass in numerical analysis , computer science and physics based... analysis for a linear problem: heat conduction The design and analysis of complex engineering systems is challenging not only be- cause of the physical

Dynamic properties of epidemic spreading on finite size complex networks

NASA Astrophysics Data System (ADS)

Li, Ying; Liu, Yang; Shan, Xiu-Ming; Ren, Yong; Jiao, Jian; Qiu, Ben

2005-11-01

The Internet presents a complex topological structure, on which computer viruses can easily spread. By using theoretical analysis and computer simulation methods, the dynamic process of disease spreading on finite size networks with complex topological structure is investigated. On the finite size networks, the spreading process of SIS (susceptible-infected-susceptible) model is a finite Markov chain with an absorbing state. Two parameters, the survival probability and the conditional infecting probability, are introduced to describe the dynamic properties of disease spreading on finite size networks. Our results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks. Also, knowledge about the dynamic character of virus spreading is helpful for adopting immunity policy.

Comparative phyloinformatics of virus genes at micro and macro levels in a distributed computing environment.

PubMed

Singh, Dadabhai T; Trehan, Rahul; Schmidt, Bertil; Bretschneider, Timo

2008-01-01

Preparedness for a possible global pandemic caused by viruses such as the highly pathogenic influenza A subtype H5N1 has become a global priority. In particular, it is critical to monitor the appearance of any new emerging subtypes. Comparative phyloinformatics can be used to monitor, analyze, and possibly predict the evolution of viruses. However, in order to utilize the full functionality of available analysis packages for large-scale phyloinformatics studies, a team of computer scientists, biostatisticians and virologists is needed--a requirement which cannot be fulfilled in many cases. Furthermore, the time complexities of many algorithms involved leads to prohibitive runtimes on sequential computer platforms. This has so far hindered the use of comparative phyloinformatics as a commonly applied tool in this area. In this paper the graphical-oriented workflow design system called Quascade and its efficient usage for comparative phyloinformatics are presented. In particular, we focus on how this task can be effectively performed in a distributed computing environment. As a proof of concept, the designed workflows are used for the phylogenetic analysis of neuraminidase of H5N1 isolates (micro level) and influenza viruses (macro level). The results of this paper are hence twofold. Firstly, this paper demonstrates the usefulness of a graphical user interface system to design and execute complex distributed workflows for large-scale phyloinformatics studies of virus genes. Secondly, the analysis of neuraminidase on different levels of complexity provides valuable insights of this virus's tendency for geographical based clustering in the phylogenetic tree and also shows the importance of glycan sites in its molecular evolution. The current study demonstrates the efficiency and utility of workflow systems providing a biologist friendly approach to complex biological dataset analysis using high performance computing. In particular, the utility of the platform Quascade for deploying distributed and parallelized versions of a variety of computationally intensive phylogenetic algorithms has been shown. Secondly, the analysis of the utilized H5N1 neuraminidase datasets at macro and micro levels has clearly indicated a pattern of spatial clustering of the H5N1 viral isolates based on geographical distribution rather than temporal or host range based clustering.

CSM research: Methods and application studies

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.

1989-01-01

Computational mechanics is that discipline of applied science and engineering devoted to the study of physical phenomena by means of computational methods based on mathematical modeling and simulation, utilizing digital computers. The discipline combines theoretical and applied mechanics, approximation theory, numerical analysis, and computer science. Computational mechanics has had a major impact on engineering analysis and design. When applied to structural mechanics, the discipline is referred to herein as computational structural mechanics. Complex structures being considered by NASA for the 1990's include composite primary aircraft structures and the space station. These structures will be much more difficult to analyze than today's structures and necessitate a major upgrade in computerized structural analysis technology. NASA has initiated a research activity in structural analysis called Computational Structural Mechanics (CSM). The broad objective of the CSM activity is to develop advanced structural analysis technology that will exploit modern and emerging computers, such as those with vector and/or parallel processing capabilities. Here, the current research directions for the Methods and Application Studies Team of the Langley CSM activity are described.

Enabling Predictive Simulation and UQ of Complex Multiphysics PDE Systems by the Development of Goal-Oriented Variational Sensitivity Analysis and a-Posteriori Error Estimation Methods

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

Estep, Donald

2015-11-30

This project addressed the challenge of predictive computational analysis of strongly coupled, highly nonlinear multiphysics systems characterized by multiple physical phenomena that span a large range of length- and time-scales. Specifically, the project was focused on computational estimation of numerical error and sensitivity analysis of computational solutions with respect to variations in parameters and data. In addition, the project investigated the use of accurate computational estimates to guide efficient adaptive discretization. The project developed, analyzed and evaluated new variational adjoint-based techniques for integration, model, and data error estimation/control and sensitivity analysis, in evolutionary multiphysics multiscale simulations.

Image analysis and modeling in medical image computing. Recent developments and advances.

PubMed

Handels, H; Deserno, T M; Meinzer, H-P; Tolxdorff, T

2012-01-01

Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body. Hence, model-based image computing methods are important tools to improve medical diagnostics and patient treatment in future.

Design and implementation of spatial knowledge grid for integrated spatial analysis

NASA Astrophysics Data System (ADS)

Liu, Xiangnan; Guan, Li; Wang, Ping

2006-10-01

Supported by spatial information grid(SIG), the spatial knowledge grid (SKG) for integrated spatial analysis utilizes the middleware technology in constructing the spatial information grid computation environment and spatial information service system, develops spatial entity oriented spatial data organization technology, carries out the profound computation of the spatial structure and spatial process pattern on the basis of Grid GIS infrastructure, spatial data grid and spatial information grid (specialized definition). At the same time, it realizes the complex spatial pattern expression and the spatial function process simulation by taking the spatial intelligent agent as the core to establish space initiative computation. Moreover through the establishment of virtual geographical environment with man-machine interactivity and blending, complex spatial modeling, network cooperation work and spatial community decision knowledge driven are achieved. The framework of SKG is discussed systematically in this paper. Its implement flow and the key technology with examples of overlay analysis are proposed as well.

Research in Parallel Algorithms and Software for Computational Aerosciences

DOT National Transportation Integrated Search

1996-04-01

Phase I is complete for the development of a Computational Fluid Dynamics : with automatic grid generation and adaptation for the Euler : analysis of flow over complex geometries. SPLITFLOW, an unstructured Cartesian : grid code developed at Lockheed...

Reproducible research in vadose zone sciences

USDA-ARS?s Scientific Manuscript database

A significant portion of present-day soil and Earth science research is computational, involving complex data analysis pipelines, advanced mathematical and statistical models, and sophisticated computer codes. Opportunities for scientific progress are greatly diminished if reproducing and building o...

Self-Directed Student Research through Analysis of Microarray Datasets: A Computer-Based Functional Genomics Practical Class for Masters-Level Students

ERIC Educational Resources Information Center

Grenville-Briggs, Laura J.; Stansfield, Ian

2011-01-01

This report describes a linked series of Masters-level computer practical workshops. They comprise an advanced functional genomics investigation, based upon analysis of a microarray dataset probing yeast DNA damage responses. The workshops require the students to analyse highly complex transcriptomics datasets, and were designed to stimulate…

High performance computing enabling exhaustive analysis of higher order single nucleotide polymorphism interaction in Genome Wide Association Studies.

PubMed

Goudey, Benjamin; Abedini, Mani; Hopper, John L; Inouye, Michael; Makalic, Enes; Schmidt, Daniel F; Wagner, John; Zhou, Zeyu; Zobel, Justin; Reumann, Matthias

2015-01-01

Genome-wide association studies (GWAS) are a common approach for systematic discovery of single nucleotide polymorphisms (SNPs) which are associated with a given disease. Univariate analysis approaches commonly employed may miss important SNP associations that only appear through multivariate analysis in complex diseases. However, multivariate SNP analysis is currently limited by its inherent computational complexity. In this work, we present a computational framework that harnesses supercomputers. Based on our results, we estimate a three-way interaction analysis on 1.1 million SNP GWAS data requiring over 5.8 years on the full "Avoca" IBM Blue Gene/Q installation at the Victorian Life Sciences Computation Initiative. This is hundreds of times faster than estimates for other CPU based methods and four times faster than runtimes estimated for GPU methods, indicating how the improvement in the level of hardware applied to interaction analysis may alter the types of analysis that can be performed. Furthermore, the same analysis would take under 3 months on the currently largest IBM Blue Gene/Q supercomputer "Sequoia" at the Lawrence Livermore National Laboratory assuming linear scaling is maintained as our results suggest. Given that the implementation used in this study can be further optimised, this runtime means it is becoming feasible to carry out exhaustive analysis of higher order interaction studies on large modern GWAS.

Computational modeling in melanoma for novel drug discovery.

PubMed

Pennisi, Marzio; Russo, Giulia; Di Salvatore, Valentina; Candido, Saverio; Libra, Massimo; Pappalardo, Francesco

2016-06-01

There is a growing body of evidence highlighting the applications of computational modeling in the field of biomedicine. It has recently been applied to the in silico analysis of cancer dynamics. In the era of precision medicine, this analysis may allow the discovery of new molecular targets useful for the design of novel therapies and for overcoming resistance to anticancer drugs. According to its molecular behavior, melanoma represents an interesting tumor model in which computational modeling can be applied. Melanoma is an aggressive tumor of the skin with a poor prognosis for patients with advanced disease as it is resistant to current therapeutic approaches. This review discusses the basics of computational modeling in melanoma drug discovery and development. Discussion includes the in silico discovery of novel molecular drug targets, the optimization of immunotherapies and personalized medicine trials. Mathematical and computational models are gradually being used to help understand biomedical data produced by high-throughput analysis. The use of advanced computer models allowing the simulation of complex biological processes provides hypotheses and supports experimental design. The research in fighting aggressive cancers, such as melanoma, is making great strides. Computational models represent the key component to complement these efforts. Due to the combinatorial complexity of new drug discovery, a systematic approach based only on experimentation is not possible. Computational and mathematical models are necessary for bringing cancer drug discovery into the era of omics, big data and personalized medicine.

Multiscale computing.

PubMed

Kobayashi, M; Irino, T; Sweldens, W

2001-10-23

Multiscale computing (MSC) involves the computation, manipulation, and analysis of information at different resolution levels. Widespread use of MSC algorithms and the discovery of important relationships between different approaches to implementation were catalyzed, in part, by the recent interest in wavelets. We present two examples that demonstrate how MSC can help scientists understand complex data. The first is from acoustical signal processing and the second is from computer graphics.

Analysis of Selected Enhancements to the En Route Central Computing Complex

DOT National Transportation Integrated Search

1981-09-01

This report analyzes selected hardware enhancements that could improve the performance of the 9020 computer systems, which are used to provide en route air traffic control services. These enhancements could be implemented quickly, would be relatively...

Using multi-criteria analysis of simulation models to understand complex biological systems

Treesearch

Maureen C. Kennedy; E. David Ford

2011-01-01

Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...

AstroGrid: Taverna in the Virtual Observatory .

NASA Astrophysics Data System (ADS)

Benson, K. M.; Walton, N. A.

This paper reports on the implementation of the Taverna workbench by AstroGrid, a tool for designing and executing workflows of tasks in the Virtual Observatory. The workflow approach helps astronomers perform complex task sequences with little technical effort. Visual approach to workflow construction streamlines highly complex analysis over public and private data and uses computational resources as minimal as a desktop computer. Some integration issues and future work are discussed in this article.

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

PubMed

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2016-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

Rapid solution of large-scale systems of equations

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.

1994-01-01

The analysis and design of complex aerospace structures requires the rapid solution of large systems of linear and nonlinear equations, eigenvalue extraction for buckling, vibration and flutter modes, structural optimization and design sensitivity calculation. Computers with multiple processors and vector capabilities can offer substantial computational advantages over traditional scalar computer for these analyses. These computers fall into two categories: shared memory computers and distributed memory computers. This presentation covers general-purpose, highly efficient algorithms for generation/assembly or element matrices, solution of systems of linear and nonlinear equations, eigenvalue and design sensitivity analysis and optimization. All algorithms are coded in FORTRAN for shared memory computers and many are adapted to distributed memory computers. The capability and numerical performance of these algorithms will be addressed.

Analysis of Multilayered Printed Circuit Boards using Computed Tomography

DTIC Science & Technology

2014-05-01

complex PCBs that present a challenge for any testing or fault analysis. Set-to- work testing and fault analysis of any electronic circuit require...Electronic Warfare and Radar Division in December 2010. He is currently in Electro- Optic Countermeasures Group. Samuel works on embedded system design...and software optimisation of complex electro-optical systems, including the set to work and characterisation of these systems. He has a Bachelor of

Influences of Gender and Computer Gaming Experience in Occupational Desktop Virtual Environments: A Cross-Case Analysis Study

ERIC Educational Resources Information Center

Ausburn, Lynna J.; Ausburn, Floyd B.; Kroutter, Paul J.

2013-01-01

This study used a cross-case analysis methodology to compare four line-of-inquiry studies of desktop virtual environments (DVEs) to examine the relationships of gender and computer gaming experience to learning performance and perceptions. Comparison was made of learning patterns in a general non-technical DVE with patterns in technically complex,…

Comparing DNA damage-processing pathways by computer analysis of chromosome painting data.

PubMed

Levy, Dan; Vazquez, Mariel; Cornforth, Michael; Loucas, Bradford; Sachs, Rainer K; Arsuaga, Javier

2004-01-01

Chromosome aberrations are large-scale illegitimate rearrangements of the genome. They are indicative of DNA damage and informative about damage processing pathways. Despite extensive investigations over many years, the mechanisms underlying aberration formation remain controversial. New experimental assays such as multiplex fluorescent in situ hybridyzation (mFISH) allow combinatorial "painting" of chromosomes and are promising for elucidating aberration formation mechanisms. Recently observed mFISH aberration patterns are so complex that computer and graph-theoretical methods are needed for their full analysis. An important part of the analysis is decomposing a chromosome rearrangement process into "cycles." A cycle of order n, characterized formally by the cyclic graph with 2n vertices, indicates that n chromatin breaks take part in a single irreducible reaction. We here describe algorithms for computing cycle structures from experimentally observed or computer-simulated mFISH aberration patterns. We show that analyzing cycles quantitatively can distinguish between different aberration formation mechanisms. In particular, we show that homology-based mechanisms do not generate the large number of complex aberrations, involving higher-order cycles, observed in irradiated human lymphocytes.

High throughput computing: a solution for scientific analysis

USGS Publications Warehouse

O'Donnell, M.

2011-01-01

handle job failures due to hardware, software, or network interruptions (obviating the need to manually resubmit the job after each stoppage); be affordable; and most importantly, allow us to complete very large, complex analyses that otherwise would not even be possible. In short, we envisioned a job-management system that would take advantage of unused FORT CPUs within a local area network (LAN) to effectively distribute and run highly complex analytical processes. What we found was a solution that uses High Throughput Computing (HTC) and High Performance Computing (HPC) systems to do exactly that (Figure 1).

Coordination characteristics of uranyl BBP complexes: Insights from an electronic structure analysis

DOE PAGES

Pemmaraju, Chaitanya Das; Copping, Roy; Smiles, Danil E.; ...

2017-03-21

Here, organic ligand complexes of lanthanide/actinide ions have been studied extensively for applications in nuclear fuel storage and recycling. Several complexes of 2,6-bis(2-benzimidazyl)pyridine (H2BBP) featuring the uranyl moiety have been reported recently, and the present study investigates the coordination characteristics of these complexes using density functional theory-based electronic structure analysis. In particular, with the aid of several computational models, the nonplanar equatorial coordination about uranyl, observed in some of the compounds, is studied and its origin traced to steric effects.

NGScloud: RNA-seq analysis of non-model species using cloud computing.

PubMed

Mora-Márquez, Fernando; Vázquez-Poletti, José Luis; López de Heredia, Unai

2018-05-03

RNA-seq analysis usually requires large computing infrastructures. NGScloud is a bioinformatic system developed to analyze RNA-seq data using the cloud computing services of Amazon that permit the access to ad hoc computing infrastructure scaled according to the complexity of the experiment, so its costs and times can be optimized. The application provides a user-friendly front-end to operate Amazon's hardware resources, and to control a workflow of RNA-seq analysis oriented to non-model species, incorporating the cluster concept, which allows parallel runs of common RNA-seq analysis programs in several virtual machines for faster analysis. NGScloud is freely available at https://github.com/GGFHF/NGScloud/. A manual detailing installation and how-to-use instructions is available with the distribution. unai.lopezdeheredia@upm.es.

Structural system reliability calculation using a probabilistic fault tree analysis method

NASA Technical Reports Server (NTRS)

Torng, T. Y.; Wu, Y.-T.; Millwater, H. R.

1992-01-01

The development of a new probabilistic fault tree analysis (PFTA) method for calculating structural system reliability is summarized. The proposed PFTA procedure includes: developing a fault tree to represent the complex structural system, constructing an approximation function for each bottom event, determining a dominant sampling sequence for all bottom events, and calculating the system reliability using an adaptive importance sampling method. PFTA is suitable for complicated structural problems that require computer-intensive computer calculations. A computer program has been developed to implement the PFTA.

Condor-COPASI: high-throughput computing for biochemical networks

PubMed Central

2012-01-01

Background Mathematical modelling has become a standard technique to improve our understanding of complex biological systems. As models become larger and more complex, simulations and analyses require increasing amounts of computational power. Clusters of computers in a high-throughput computing environment can help to provide the resources required for computationally expensive model analysis. However, exploiting such a system can be difficult for users without the necessary expertise. Results We present Condor-COPASI, a server-based software tool that integrates COPASI, a biological pathway simulation tool, with Condor, a high-throughput computing environment. Condor-COPASI provides a web-based interface, which makes it extremely easy for a user to run a number of model simulation and analysis tasks in parallel. Tasks are transparently split into smaller parts, and submitted for execution on a Condor pool. Result output is presented to the user in a number of formats, including tables and interactive graphical displays. Conclusions Condor-COPASI can effectively use a Condor high-throughput computing environment to provide significant gains in performance for a number of model simulation and analysis tasks. Condor-COPASI is free, open source software, released under the Artistic License 2.0, and is suitable for use by any institution with access to a Condor pool. Source code is freely available for download at http://code.google.com/p/condor-copasi/, along with full instructions on deployment and usage. PMID:22834945

Human performance cognitive-behavioral modeling: a benefit for occupational safety.

PubMed

Gore, Brian F

2002-01-01

Human Performance Modeling (HPM) is a computer-aided job analysis software methodology used to generate predictions of complex human-automation integration and system flow patterns with the goal of improving operator and system safety. The use of HPM tools has recently been increasing due to reductions in computational cost, augmentations in the tools' fidelity, and usefulness in the generated output. An examination of an Air Man-machine Integration Design and Analysis System (Air MIDAS) model evaluating complex human-automation integration currently underway at NASA Ames Research Center will highlight the importance to occupational safety of considering both cognitive and physical aspects of performance when researching human error.

Towards practical multiscale approach for analysis of reinforced concrete structures

NASA Astrophysics Data System (ADS)

Moyeda, Arturo; Fish, Jacob

2017-12-01

We present a novel multiscale approach for analysis of reinforced concrete structural elements that overcomes two major hurdles in utilization of multiscale technologies in practice: (1) coupling between material and structural scales due to consideration of large representative volume elements (RVE), and (2) computational complexity of solving complex nonlinear multiscale problems. The former is accomplished using a variant of computational continua framework that accounts for sizeable reinforced concrete RVEs by adjusting the location of quadrature points. The latter is accomplished by means of reduced order homogenization customized for structural elements. The proposed multiscale approach has been verified against direct numerical simulations and validated against experimental results.

Human performance cognitive-behavioral modeling: a benefit for occupational safety

NASA Technical Reports Server (NTRS)

Gore, Brian F.

2002-01-01

Human Performance Modeling (HPM) is a computer-aided job analysis software methodology used to generate predictions of complex human-automation integration and system flow patterns with the goal of improving operator and system safety. The use of HPM tools has recently been increasing due to reductions in computational cost, augmentations in the tools' fidelity, and usefulness in the generated output. An examination of an Air Man-machine Integration Design and Analysis System (Air MIDAS) model evaluating complex human-automation integration currently underway at NASA Ames Research Center will highlight the importance to occupational safety of considering both cognitive and physical aspects of performance when researching human error.

A computational image analysis glossary for biologists.

PubMed

Roeder, Adrienne H K; Cunha, Alexandre; Burl, Michael C; Meyerowitz, Elliot M

2012-09-01

Recent advances in biological imaging have resulted in an explosion in the quality and quantity of images obtained in a digital format. Developmental biologists are increasingly acquiring beautiful and complex images, thus creating vast image datasets. In the past, patterns in image data have been detected by the human eye. Larger datasets, however, necessitate high-throughput objective analysis tools to computationally extract quantitative information from the images. These tools have been developed in collaborations between biologists, computer scientists, mathematicians and physicists. In this Primer we present a glossary of image analysis terms to aid biologists and briefly discuss the importance of robust image analysis in developmental studies.

New technologies for advanced three-dimensional optimum shape design in aeronautics

NASA Astrophysics Data System (ADS)

Dervieux, Alain; Lanteri, Stéphane; Malé, Jean-Michel; Marco, Nathalie; Rostaing-Schmidt, Nicole; Stoufflet, Bruno

1999-05-01

The analysis of complex flows around realistic aircraft geometries is becoming more and more predictive. In order to obtain this result, the complexity of flow analysis codes has been constantly increasing, involving more refined fluid models and sophisticated numerical methods. These codes can only run on top computers, exhausting their memory and CPU capabilities. It is, therefore, difficult to introduce best analysis codes in a shape optimization loop: most previous works in the optimum shape design field used only simplified analysis codes. Moreover, as the most popular optimization methods are the gradient-based ones, the more complex the flow solver, the more difficult it is to compute the sensitivity code. However, emerging technologies are contributing to make such an ambitious project, of including a state-of-the-art flow analysis code into an optimisation loop, feasible. Among those technologies, there are three important issues that this paper wishes to address: shape parametrization, automated differentiation and parallel computing. Shape parametrization allows faster optimization by reducing the number of design variable; in this work, it relies on a hierarchical multilevel approach. The sensitivity code can be obtained using automated differentiation. The automated approach is based on software manipulation tools, which allow the differentiation to be quick and the resulting differentiated code to be rather fast and reliable. In addition, the parallel algorithms implemented in this work allow the resulting optimization software to run on increasingly larger geometries. Copyright

Training Knowledge Bots for Physics-Based Simulations Using Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.; Wong, Jay Ming

2014-01-01

Millions of complex physics-based simulations are required for design of an aerospace vehicle. These simulations are usually performed by highly trained and skilled analysts, who execute, monitor, and steer each simulation. Analysts rely heavily on their broad experience that may have taken 20-30 years to accumulate. In addition, the simulation software is complex in nature, requiring significant computational resources. Simulations of system of systems become even more complex and are beyond human capacity to effectively learn their behavior. IBM has developed machines that can learn and compete successfully with a chess grandmaster and most successful jeopardy contestants. These machines are capable of learning some complex problems much faster than humans can learn. In this paper, we propose using artificial neural network to train knowledge bots to identify the idiosyncrasies of simulation software and recognize patterns that can lead to successful simulations. We examine the use of knowledge bots for applications of computational fluid dynamics (CFD), trajectory analysis, commercial finite-element analysis software, and slosh propellant dynamics. We will show that machine learning algorithms can be used to learn the idiosyncrasies of computational simulations and identify regions of instability without including any additional information about their mathematical form or applied discretization approaches.

Hiding in Plain Sight: Identifying Computational Thinking in the Ontario Elementary School Curriculum

ERIC Educational Resources Information Center

Hennessey, Eden J. V.; Mueller, Julie; Beckett, Danielle; Fisher, Peter A.

2017-01-01

Given a growing digital economy with complex problems, demands are being made for education to address computational thinking (CT)--an approach to problem solving that draws on the tenets of computer science. We conducted a comprehensive content analysis of the Ontario elementary school curriculum documents for 44 CT-related terms to examine the…

NASA Applications for Computational Electromagnetic Analysis

NASA Technical Reports Server (NTRS)

Lewis, Catherine C.; Trout, Dawn H.; Krome, Mark E.; Perry, Thomas A.

2011-01-01

Computational Electromagnetic Software is used by NASA to analyze the compatibility of systems too large or too complex for testing. Recent advances in software packages and computer capabilities have made it possible to determine the effects of a transmitter inside a launch vehicle fairing, better analyze the environment threats, and perform on-orbit replacements with assured electromagnetic compatibility.

Sorting on STAR. [CDC computer algorithm timing comparison

NASA Technical Reports Server (NTRS)

Stone, H. S.

1978-01-01

Timing comparisons are given for three sorting algorithms written for the CDC STAR computer. One algorithm is Hoare's (1962) Quicksort, which is the fastest or nearly the fastest sorting algorithm for most computers. A second algorithm is a vector version of Quicksort that takes advantage of the STAR's vector operations. The third algorithm is an adaptation of Batcher's (1968) sorting algorithm, which makes especially good use of vector operations but has a complexity of N(log N)-squared as compared with a complexity of N log N for the Quicksort algorithms. In spite of its worse complexity, Batcher's sorting algorithm is competitive with the serial version of Quicksort for vectors up to the largest that can be treated by STAR. Vector Quicksort outperforms the other two algorithms and is generally preferred. These results indicate that unusual instruction sets can introduce biases in program execution time that counter results predicted by worst-case asymptotic complexity analysis.

Computational methods to predict railcar response to track cross-level variations

DOT National Transportation Integrated Search

1976-09-01

The rocking response of railroad freight cars to track cross-level variations is studied using: (1) a reduced complexity digital simulation model, and (2) a quasi-linear describing function analysis. The reduced complexity digital simulation model em...

Energy conservation and analysis and evaluation. [specifically at Slidell Computer Complex

NASA Technical Reports Server (NTRS)

1976-01-01

The survey assembled and made recommendations directed at conserving utilities and reducing the use of energy at the Slidell Computer Complex. Specific items included were: (1) scheduling and controlling the use of gas and electricity, (2) building modifications to reduce energy, (3) replacement of old, inefficient equipment, (4) modifications to control systems, (5) evaluations of economizer cycles in HVAC systems, and (6) corrective settings for thermostats, ductstats, and other temperature and pressure control devices.

Development of spectral analysis math models and software program and spectral analyzer, digital converter interface equipment design

NASA Technical Reports Server (NTRS)

Hayden, W. L.; Robinson, L. H.

1972-01-01

Spectral analyses of angle-modulated communication systems is studied by: (1) performing a literature survey of candidate power spectrum computational techniques, determining the computational requirements, and formulating a mathematical model satisfying these requirements; (2) implementing the model on UNIVAC 1230 digital computer as the Spectral Analysis Program (SAP); and (3) developing the hardware specifications for a data acquisition system which will acquire an input modulating signal for SAP. The SAP computational technique uses extended fast Fourier transform and represents a generalized approach for simple and complex modulating signals.

Applications in Data-Intensive Computing

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

Shah, Anuj R.; Adkins, Joshua N.; Baxter, Douglas J.

2010-04-01

This book chapter, to be published in Advances in Computers, Volume 78, in 2010 describes applications of data intensive computing (DIC). This is an invited chapter resulting from a previous publication on DIC. This work summarizes efforts coming out of the PNNL's Data Intensive Computing Initiative. Advances in technology have empowered individuals with the ability to generate digital content with mouse clicks and voice commands. Digital pictures, emails, text messages, home videos, audio, and webpages are common examples of digital content that are generated on a regular basis. Data intensive computing facilitates human understanding of complex problems. Data-intensive applications providemore » timely and meaningful analytical results in response to exponentially growing data complexity and associated analysis requirements through the development of new classes of software, algorithms, and hardware.« less

Introducing computational thinking through hands-on projects using R with applications to calculus, probability and data analysis

NASA Astrophysics Data System (ADS)

Benakli, Nadia; Kostadinov, Boyan; Satyanarayana, Ashwin; Singh, Satyanand

2017-04-01

The goal of this paper is to promote computational thinking among mathematics, engineering, science and technology students, through hands-on computer experiments. These activities have the potential to empower students to learn, create and invent with technology, and they engage computational thinking through simulations, visualizations and data analysis. We present nine computer experiments and suggest a few more, with applications to calculus, probability and data analysis, which engage computational thinking through simulations, visualizations and data analysis. We are using the free (open-source) statistical programming language R. Our goal is to give a taste of what R offers rather than to present a comprehensive tutorial on the R language. In our experience, these kinds of interactive computer activities can be easily integrated into a smart classroom. Furthermore, these activities do tend to keep students motivated and actively engaged in the process of learning, problem solving and developing a better intuition for understanding complex mathematical concepts.

Sensitivity analysis and multidisciplinary optimization for aircraft design: Recent advances and results

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw

1988-01-01

Optimization by decomposition, complex system sensitivity analysis, and a rapid growth of disciplinary sensitivity analysis are some of the recent developments that hold promise of a quantum jump in the support engineers receive from computers in the quantitative aspects of design. Review of the salient points of these techniques is given and illustrated by examples from aircraft design as a process that combines the best of human intellect and computer power to manipulate data.

76 FR 64330 - Advanced Scientific Computing Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-18

... talks on HPC Reliability, Diffusion on Complex Networks, and Reversible Software Execution Systems Report from Applied Math Workshop on Mathematics for the Analysis, Simulation, and Optimization of Complex Systems Report from ASCR-BES Workshop on Data Challenges from Next Generation Facilities Public...

An Attractor-Based Complexity Measurement for Boolean Recurrent Neural Networks

PubMed Central

Cabessa, Jérémie; Villa, Alessandro E. P.

2014-01-01

We provide a novel refined attractor-based complexity measurement for Boolean recurrent neural networks that represents an assessment of their computational power in terms of the significance of their attractor dynamics. This complexity measurement is achieved by first proving a computational equivalence between Boolean recurrent neural networks and some specific class of -automata, and then translating the most refined classification of -automata to the Boolean neural network context. As a result, a hierarchical classification of Boolean neural networks based on their attractive dynamics is obtained, thus providing a novel refined attractor-based complexity measurement for Boolean recurrent neural networks. These results provide new theoretical insights to the computational and dynamical capabilities of neural networks according to their attractive potentialities. An application of our findings is illustrated by the analysis of the dynamics of a simplified model of the basal ganglia-thalamocortical network simulated by a Boolean recurrent neural network. This example shows the significance of measuring network complexity, and how our results bear new founding elements for the understanding of the complexity of real brain circuits. PMID:24727866

The Nash Equilibrium Revisited: Chaos and Complexity Hidden in Simplicity

NASA Astrophysics Data System (ADS)

Fellman, Philip V.

The Nash Equilibrium is a much discussed, deceptively complex, method for the analysis of non-cooperative games (McLennan and Berg, 2005). If one reads many of the commonly available definitions the description of the Nash Equilibrium is deceptively simple in appearance. Modern research has discovered a number of new and important complex properties of the Nash Equilibrium, some of which remain as contemporary conundrums of extraordinary difficulty and complexity (Quint and Shubik, 1997). Among the recently discovered features which the Nash Equilibrium exhibits under various conditions are heteroclinic Hamiltonian dynamics, a very complex asymptotic structure in the context of two-player bi-matrix games and a number of computationally complex or computationally intractable features in other settings (Sato, Akiyama and Farmer, 2002). This paper reviews those findings and then suggests how they may inform various market prediction strategies.

Indices of Complexity and Interpretation: Their Computation and Uses in Factor Analysis.

ERIC Educational Resources Information Center

Hofmann, Richard J.

In this methodological paper two indices are developed: a complexity index and an interpretation index. The complexity index is a positive number indicating on the average how many factors are used to explain each variable in a factor solution. The interpretation index will be positive ranging from zero to unity; unity representing a perfect…

Visual Computing Environment Workshop

NASA Technical Reports Server (NTRS)

Lawrence, Charles (Compiler)

1998-01-01

The Visual Computing Environment (VCE) is a framework for intercomponent and multidisciplinary computational simulations. Many current engineering analysis codes simulate various aspects of aircraft engine operation. For example, existing computational fluid dynamics (CFD) codes can model the airflow through individual engine components such as the inlet, compressor, combustor, turbine, or nozzle. Currently, these codes are run in isolation, making intercomponent and complete system simulations very difficult to perform. In addition, management and utilization of these engineering codes for coupled component simulations is a complex, laborious task, requiring substantial experience and effort. To facilitate multicomponent aircraft engine analysis, the CFD Research Corporation (CFDRC) is developing the VCE system. This system, which is part of NASA's Numerical Propulsion Simulation System (NPSS) program, can couple various engineering disciplines, such as CFD, structural analysis, and thermal analysis.

An experimental and computational investigation of flow in a radial inlet of an industrial pipeline centrifugal compressor

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

Flathers, M.B.; Bache, G.E.; Rainsberger, R.

1996-04-01

The flow field of a complex three-dimensional radial inlet for an industrial pipeline centrifugal compressor has been experimentally determined on a half-scale model. Based on the experimental results, inlet guide vanes have been designed to correct pressure and swirl angle distribution deficiencies. The unvaned and vaned inlets are analyzed with a commercially available fully three-dimensional viscous Navier-Stokes code. Since experimental results were available prior to the numerical study, the unvaned analysis is considered a postdiction while the vaned analysis is considered a prediction. The computational results of the unvaned inlet have been compared to the previously obtained experimental results. Themore » experimental method utilized for the unvaned inlet is repeated for the vaned inlet and the data have been used to verify the computational results. The paper will discuss experimental, design, and computational procedures, grid generation, boundary conditions, and experimental versus computational methods. Agreement between experimental and computational results is very good, both in prediction and postdiction modes. The results of this investigation indicate that CFD offers a measurable advantage in design, schedule, and cost and can be applied to complex, three-dimensional radial inlets.« less

Improving the Aircraft Design Process Using Web-Based Modeling and Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Follen, Gregory J.; Afjeh, Abdollah A.; Follen, Gregory J. (Technical Monitor)

2000-01-01

Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and multifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.

Improving the Aircraft Design Process Using Web-based Modeling and Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Follen, Gregory J.; Afjeh, Abdollah A.

2003-01-01

Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and muitifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.

On Target Localization Using Combined RSS and AoA Measurements

PubMed Central

Beko, Marko; Dinis, Rui

2018-01-01

This work revises existing solutions for a problem of target localization in wireless sensor networks (WSNs), utilizing integrated measurements, namely received signal strength (RSS) and angle of arrival (AoA). The problem of RSS/AoA-based target localization became very popular in the research community recently, owing to its great applicability potential and relatively low implementation cost. Therefore, here, a comprehensive study of the state-of-the-art (SoA) solutions and their detailed analysis is presented. The beginning of this work starts by considering the SoA approaches based on convex relaxation techniques (more computationally complex in general), and it goes through other (less computationally complex) approaches, as well, such as the ones based on the generalized trust region sub-problems framework and linear least squares. Furthermore, a detailed analysis of the computational complexity of each solution is reviewed. Furthermore, an extensive set of simulation results is presented. Finally, the main conclusions are summarized, and a set of future aspects and trends that might be interesting for future research in this area is identified. PMID:29671832

Network Community Detection based on the Physarum-inspired Computational Framework.

PubMed

Gao, Chao; Liang, Mingxin; Li, Xianghua; Zhang, Zili; Wang, Zhen; Zhou, Zhili

2016-12-13

Community detection is a crucial and essential problem in the structure analytics of complex networks, which can help us understand and predict the characteristics and functions of complex networks. Many methods, ranging from the optimization-based algorithms to the heuristic-based algorithms, have been proposed for solving such a problem. Due to the inherent complexity of identifying network structure, how to design an effective algorithm with a higher accuracy and a lower computational cost still remains an open problem. Inspired by the computational capability and positive feedback mechanism in the wake of foraging process of Physarum, which is a large amoeba-like cell consisting of a dendritic network of tube-like pseudopodia, a general Physarum-based computational framework for community detection is proposed in this paper. Based on the proposed framework, the inter-community edges can be identified from the intra-community edges in a network and the positive feedback of solving process in an algorithm can be further enhanced, which are used to improve the efficiency of original optimization-based and heuristic-based community detection algorithms, respectively. Some typical algorithms (e.g., genetic algorithm, ant colony optimization algorithm, and Markov clustering algorithm) and real-world datasets have been used to estimate the efficiency of our proposed computational framework. Experiments show that the algorithms optimized by Physarum-inspired computational framework perform better than the original ones, in terms of accuracy and computational cost. Moreover, a computational complexity analysis verifies the scalability of our framework.

Deepthi Vaidhynathan | NREL

Science.gov Websites

Complex Systems Simulation and Optimization Group on performance analysis and benchmarking latest . Research Interests High Performance Computing|Embedded System |Microprocessors & Microcontrollers

Energy-density field approach for low- and medium-frequency vibroacoustic analysis of complex structures using a statistical computational model

NASA Astrophysics Data System (ADS)

Kassem, M.; Soize, C.; Gagliardini, L.

2009-06-01

In this paper, an energy-density field approach applied to the vibroacoustic analysis of complex industrial structures in the low- and medium-frequency ranges is presented. This approach uses a statistical computational model. The analyzed system consists of an automotive vehicle structure coupled with its internal acoustic cavity. The objective of this paper is to make use of the statistical properties of the frequency response functions of the vibroacoustic system observed from previous experimental and numerical work. The frequency response functions are expressed in terms of a dimensionless matrix which is estimated using the proposed energy approach. Using this dimensionless matrix, a simplified vibroacoustic model is proposed.

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME

PubMed Central

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2017-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments. PMID:28190948

Introduction to the Application of the Dynalist Computer Program to the Analysis of Rail Systems Dynamics

DOT National Transportation Integrated Search

1974-08-01

DYNALIST, a computer program that extracts complex eigenvalues and eigenvectors for dynamic systems described in terms of matrix equations of motion, has been acquired and made operational at TSC. In this report, simple dynamic systems are used to de...

The portable UNIX programming system (PUPS) and CANTOR: a computational environment for dynamical representation and analysis of complex neurobiological data.

PubMed

O'Neill, M A; Hilgetag, C C

2001-08-29

Many problems in analytical biology, such as the classification of organisms, the modelling of macromolecules, or the structural analysis of metabolic or neural networks, involve complex relational data. Here, we describe a software environment, the portable UNIX programming system (PUPS), which has been developed to allow efficient computational representation and analysis of such data. The system can also be used as a general development tool for database and classification applications. As the complexity of analytical biology problems may lead to computation times of several days or weeks even on powerful computer hardware, the PUPS environment gives support for persistent computations by providing mechanisms for dynamic interaction and homeostatic protection of processes. Biological objects and their interrelations are also represented in a homeostatic way in PUPS. Object relationships are maintained and updated by the objects themselves, thus providing a flexible, scalable and current data representation. Based on the PUPS environment, we have developed an optimization package, CANTOR, which can be applied to a wide range of relational data and which has been employed in different analyses of neuroanatomical connectivity. The CANTOR package makes use of the PUPS system features by modifying candidate arrangements of objects within the system's database. This restructuring is carried out via optimization algorithms that are based on user-defined cost functions, thus providing flexible and powerful tools for the structural analysis of the database content. The use of stochastic optimization also enables the CANTOR system to deal effectively with incomplete and inconsistent data. Prototypical forms of PUPS and CANTOR have been coded and used successfully in the analysis of anatomical and functional mammalian brain connectivity, involving complex and inconsistent experimental data. In addition, PUPS has been used for solving multivariate engineering optimization problems and to implement the digital identification system (DAISY), a system for the automated classification of biological objects. PUPS is implemented in ANSI-C under the POSIX.1 standard and is to a great extent architecture- and operating-system independent. The software is supported by systems libraries that allow multi-threading (the concurrent processing of several database operations), as well as the distribution of the dynamic data objects and library operations over clusters of computers. These attributes make the system easily scalable, and in principle allow the representation and analysis of arbitrarily large sets of relational data. PUPS and CANTOR are freely distributed (http://www.pups.org.uk) as open-source software under the GNU license agreement.

The portable UNIX programming system (PUPS) and CANTOR: a computational environment for dynamical representation and analysis of complex neurobiological data.

PubMed Central

O'Neill, M A; Hilgetag, C C

2001-01-01

Many problems in analytical biology, such as the classification of organisms, the modelling of macromolecules, or the structural analysis of metabolic or neural networks, involve complex relational data. Here, we describe a software environment, the portable UNIX programming system (PUPS), which has been developed to allow efficient computational representation and analysis of such data. The system can also be used as a general development tool for database and classification applications. As the complexity of analytical biology problems may lead to computation times of several days or weeks even on powerful computer hardware, the PUPS environment gives support for persistent computations by providing mechanisms for dynamic interaction and homeostatic protection of processes. Biological objects and their interrelations are also represented in a homeostatic way in PUPS. Object relationships are maintained and updated by the objects themselves, thus providing a flexible, scalable and current data representation. Based on the PUPS environment, we have developed an optimization package, CANTOR, which can be applied to a wide range of relational data and which has been employed in different analyses of neuroanatomical connectivity. The CANTOR package makes use of the PUPS system features by modifying candidate arrangements of objects within the system's database. This restructuring is carried out via optimization algorithms that are based on user-defined cost functions, thus providing flexible and powerful tools for the structural analysis of the database content. The use of stochastic optimization also enables the CANTOR system to deal effectively with incomplete and inconsistent data. Prototypical forms of PUPS and CANTOR have been coded and used successfully in the analysis of anatomical and functional mammalian brain connectivity, involving complex and inconsistent experimental data. In addition, PUPS has been used for solving multivariate engineering optimization problems and to implement the digital identification system (DAISY), a system for the automated classification of biological objects. PUPS is implemented in ANSI-C under the POSIX.1 standard and is to a great extent architecture- and operating-system independent. The software is supported by systems libraries that allow multi-threading (the concurrent processing of several database operations), as well as the distribution of the dynamic data objects and library operations over clusters of computers. These attributes make the system easily scalable, and in principle allow the representation and analysis of arbitrarily large sets of relational data. PUPS and CANTOR are freely distributed (http://www.pups.org.uk) as open-source software under the GNU license agreement. PMID:11545702

Ammonia Oxidation by Abstraction of Three Hydrogen Atoms from a Mo–NH 3 Complex

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

Bhattacharya, Papri; Heiden, Zachariah M.; Wiedner, Eric S.

We report ammonia oxidation by homolytic cleavage of all three H atoms from a Mo-15NH3 complex using the 2,4,6-tri-tert-butylphenoxyl radical to afford a Mo-alkylimido (Mo=15NR) complex (R = 2,4,6-tri-t-butylcyclohexa-2,5-dien-1-one). Reductive cleavage of Mo=15NR generates a terminal Mo≡N nitride, and a [Mo-15NH]+ complex is formed by protonation. Computational analysis describes the energetic profile for the stepwise removal of three H atoms from the Mo-15NH3 complex and the formation of Mo=15NR. Acknowledgment. This work was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Re-search Center funded by the U.S. Department of Energy (U.S. DOE), Office of Science, Officemore » of Basic Energy Sciences. EPR and mass spectrometry experiments were performed using EMSL, a national scientific user facility sponsored by the DOE’s Office of Biological and Environmental Research and located at PNNL. The authors thank Dr. Eric D. Walter and Dr. Rosalie Chu for assistance in performing EPR and mass spectroscopy analysis, respectively. Computational resources provided by the National Energy Re-search Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory. Pacific North-west National Laboratory is operated by Battelle for the U.S. DOE.« less

Insight and analysis problem solving in microbes to machines.

PubMed

Clark, Kevin B

2015-11-01

A key feature for obtaining solutions to difficult problems, insight is oftentimes vaguely regarded as a special discontinuous intellectual process and/or a cognitive restructuring of problem representation or goal approach. However, this nearly century-old state of art devised by the Gestalt tradition to explain the non-analytical or non-trial-and-error, goal-seeking aptitude of primate mentality tends to neglect problem-solving capabilities of lower animal phyla, Kingdoms other than Animalia, and advancing smart computational technologies built from biological, artificial, and composite media. Attempting to provide an inclusive, precise definition of insight, two major criteria of insight, discontinuous processing and problem restructuring, are here reframed using terminology and statistical mechanical properties of computational complexity classes. Discontinuous processing becomes abrupt state transitions in algorithmic/heuristic outcomes or in types of algorithms/heuristics executed by agents using classical and/or quantum computational models. And problem restructuring becomes combinatorial reorganization of resources, problem-type substitution, and/or exchange of computational models. With insight bounded by computational complexity, humans, ciliated protozoa, and complex technological networks, for example, show insight when restructuring time requirements, combinatorial complexity, and problem type to solve polynomial and nondeterministic polynomial decision problems. Similar effects are expected from other problem types, supporting the idea that insight might be an epiphenomenon of analytical problem solving and consequently a larger information processing framework. Thus, this computational complexity definition of insight improves the power, external and internal validity, and reliability of operational parameters with which to classify, investigate, and produce the phenomenon for computational agents ranging from microbes to man-made devices. Copyright © 2015 Elsevier Ltd. All rights reserved.

CSM Testbed Development and Large-Scale Structural Applications

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Gillian, R. E.; Mccleary, Susan L.; Lotts, C. G.; Poole, E. L.; Overman, A. L.; Macy, S. C.

1989-01-01

A research activity called Computational Structural Mechanics (CSM) conducted at the NASA Langley Research Center is described. This activity is developing advanced structural analysis and computational methods that exploit high-performance computers. Methods are developed in the framework of the CSM Testbed software system and applied to representative complex structural analysis problems from the aerospace industry. An overview of the CSM Testbed methods development environment is presented and some new numerical methods developed on a CRAY-2 are described. Selected application studies performed on the NAS CRAY-2 are also summarized.

Tertiary structure-based analysis of microRNA–target interactions

PubMed Central

Gan, Hin Hark; Gunsalus, Kristin C.

2013-01-01

Current computational analysis of microRNA interactions is based largely on primary and secondary structure analysis. Computationally efficient tertiary structure-based methods are needed to enable more realistic modeling of the molecular interactions underlying miRNA-mediated translational repression. We incorporate algorithms for predicting duplex RNA structures, ionic strength effects, duplex entropy and free energy, and docking of duplex–Argonaute protein complexes into a pipeline to model and predict miRNA–target duplex binding energies. To ensure modeling accuracy and computational efficiency, we use an all-atom description of RNA and a continuum description of ionic interactions using the Poisson–Boltzmann equation. Our method predicts the conformations of two constructs of Caenorhabditis elegans let-7 miRNA–target duplexes to an accuracy of ∼3.8 Å root mean square distance of their NMR structures. We also show that the computed duplex formation enthalpies, entropies, and free energies for eight miRNA–target duplexes agree with titration calorimetry data. Analysis of duplex–Argonaute docking shows that structural distortions arising from single-base-pair mismatches in the seed region influence the activity of the complex by destabilizing both duplex hybridization and its association with Argonaute. Collectively, these results demonstrate that tertiary structure-based modeling of miRNA interactions can reveal structural mechanisms not accessible with current secondary structure-based methods. PMID:23417009

LXtoo: an integrated live Linux distribution for the bioinformatics community

PubMed Central

2012-01-01

Background Recent advances in high-throughput technologies dramatically increase biological data generation. However, many research groups lack computing facilities and specialists. This is an obstacle that remains to be addressed. Here, we present a Linux distribution, LXtoo, to provide a flexible computing platform for bioinformatics analysis. Findings Unlike most of the existing live Linux distributions for bioinformatics limiting their usage to sequence analysis and protein structure prediction, LXtoo incorporates a comprehensive collection of bioinformatics software, including data mining tools for microarray and proteomics, protein-protein interaction analysis, and computationally complex tasks like molecular dynamics. Moreover, most of the programs have been configured and optimized for high performance computing. Conclusions LXtoo aims to provide well-supported computing environment tailored for bioinformatics research, reducing duplication of efforts in building computing infrastructure. LXtoo is distributed as a Live DVD and freely available at http://bioinformatics.jnu.edu.cn/LXtoo. PMID:22813356

LXtoo: an integrated live Linux distribution for the bioinformatics community.

PubMed

Yu, Guangchuang; Wang, Li-Gen; Meng, Xiao-Hua; He, Qing-Yu

2012-07-19

Recent advances in high-throughput technologies dramatically increase biological data generation. However, many research groups lack computing facilities and specialists. This is an obstacle that remains to be addressed. Here, we present a Linux distribution, LXtoo, to provide a flexible computing platform for bioinformatics analysis. Unlike most of the existing live Linux distributions for bioinformatics limiting their usage to sequence analysis and protein structure prediction, LXtoo incorporates a comprehensive collection of bioinformatics software, including data mining tools for microarray and proteomics, protein-protein interaction analysis, and computationally complex tasks like molecular dynamics. Moreover, most of the programs have been configured and optimized for high performance computing. LXtoo aims to provide well-supported computing environment tailored for bioinformatics research, reducing duplication of efforts in building computing infrastructure. LXtoo is distributed as a Live DVD and freely available at http://bioinformatics.jnu.edu.cn/LXtoo.

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

Lingerfelt, Eric J; Endeve, Eirik; Hui, Yawei

Improvements in scientific instrumentation allow imaging at mesoscopic to atomic length scales, many spectroscopic modes, and now--with the rise of multimodal acquisition systems and the associated processing capability--the era of multidimensional, informationally dense data sets has arrived. Technical issues in these combinatorial scientific fields are exacerbated by computational challenges best summarized as a necessity for drastic improvement in the capability to transfer, store, and analyze large volumes of data. The Bellerophon Environment for Analysis of Materials (BEAM) platform provides material scientists the capability to directly leverage the integrated computational and analytical power of High Performance Computing (HPC) to perform scalablemore » data analysis and simulation and manage uploaded data files via an intuitive, cross-platform client user interface. This framework delivers authenticated, "push-button" execution of complex user workflows that deploy data analysis algorithms and computational simulations utilizing compute-and-data cloud infrastructures and HPC environments like Titan at the Oak Ridge Leadershp Computing Facility (OLCF).« less

Identification and addressing reduction-related misconceptions

NASA Astrophysics Data System (ADS)

Gal-Ezer, Judith; Trakhtenbrot, Mark

2016-07-01

Reduction is one of the key techniques used for problem-solving in computer science. In particular, in the theory of computation and complexity (TCC), mapping and polynomial reductions are used for analysis of decidability and computational complexity of problems, including the core concept of NP-completeness. Reduction is a highly abstract technique that involves revealing close non-trivial connections between problems that often seem to have nothing in common. As a result, proper understanding and application of reduction is a serious challenge for students and a source of numerous misconceptions. The main contribution of this paper is detection of such misconceptions, analysis of their roots, and proposing a way to address them in an undergraduate TCC course. Our observations suggest that the main source of the misconceptions is the false intuitive rule "the bigger is a set/problem, the harder it is to solve". Accordingly, we developed a series of exercises for proactive prevention of these misconceptions.

Intra-organizational Computation and Complexity

DTIC Science & Technology

2003-01-01

models. New methodologies, centered on understanding algorithmic complexity, are being developed that may enable us to better handle network data ...tractability of data analysis, and enable more precise theorization. A variety of measures of algorithmic complexity, e.g., Kolmogorov-Chaitin, and a...variety of proxies exist (which are often turned to for pragmatic reasons) ( Lempel and Ziv ,1976). For the most part, social and organizational

Comparative analysis of techniques for evaluating the effectiveness of aircraft computing systems

NASA Technical Reports Server (NTRS)

Hitt, E. F.; Bridgman, M. S.; Robinson, A. C.

1981-01-01

Performability analysis is a technique developed for evaluating the effectiveness of fault-tolerant computing systems in multiphase missions. Performability was evaluated for its accuracy, practical usefulness, and relative cost. The evaluation was performed by applying performability and the fault tree method to a set of sample problems ranging from simple to moderately complex. The problems involved as many as five outcomes, two to five mission phases, permanent faults, and some functional dependencies. Transient faults and software errors were not considered. A different analyst was responsible for each technique. Significantly more time and effort were required to learn performability analysis than the fault tree method. Performability is inherently as accurate as fault tree analysis. For the sample problems, fault trees were more practical and less time consuming to apply, while performability required less ingenuity and was more checkable. Performability offers some advantages for evaluating very complex problems.

Visualizing Parallel Computer System Performance

NASA Technical Reports Server (NTRS)

Malony, Allen D.; Reed, Daniel A.

1988-01-01

Parallel computer systems are among the most complex of man's creations, making satisfactory performance characterization difficult. Despite this complexity, there are strong, indeed, almost irresistible, incentives to quantify parallel system performance using a single metric. The fallacy lies in succumbing to such temptations. A complete performance characterization requires not only an analysis of the system's constituent levels, it also requires both static and dynamic characterizations. Static or average behavior analysis may mask transients that dramatically alter system performance. Although the human visual system is remarkedly adept at interpreting and identifying anomalies in false color data, the importance of dynamic, visual scientific data presentation has only recently been recognized Large, complex parallel system pose equally vexing performance interpretation problems. Data from hardware and software performance monitors must be presented in ways that emphasize important events while eluding irrelevant details. Design approaches and tools for performance visualization are the subject of this paper.

ComplexQuant: high-throughput computational pipeline for the global quantitative analysis of endogenous soluble protein complexes using high resolution protein HPLC and precision label-free LC/MS/MS.

PubMed

Wan, Cuihong; Liu, Jian; Fong, Vincent; Lugowski, Andrew; Stoilova, Snejana; Bethune-Waddell, Dylan; Borgeson, Blake; Havugimana, Pierre C; Marcotte, Edward M; Emili, Andrew

2013-04-09

The experimental isolation and characterization of stable multi-protein complexes are essential to understanding the molecular systems biology of a cell. To this end, we have developed a high-throughput proteomic platform for the systematic identification of native protein complexes based on extensive fractionation of soluble protein extracts by multi-bed ion exchange high performance liquid chromatography (IEX-HPLC) combined with exhaustive label-free LC/MS/MS shotgun profiling. To support these studies, we have built a companion data analysis software pipeline, termed ComplexQuant. Proteins present in the hundreds of fractions typically collected per experiment are first identified by exhaustively interrogating MS/MS spectra using multiple database search engines within an integrative probabilistic framework, while accounting for possible post-translation modifications. Protein abundance is then measured across the fractions based on normalized total spectral counts and precursor ion intensities using a dedicated tool, PepQuant. This analysis allows co-complex membership to be inferred based on the similarity of extracted protein co-elution profiles. Each computational step has been optimized for processing large-scale biochemical fractionation datasets, and the reliability of the integrated pipeline has been benchmarked extensively. This article is part of a Special Issue entitled: From protein structures to clinical applications. Copyright © 2012 Elsevier B.V. All rights reserved.

Interaction between transition metals and phenylalanine: a combined experimental and computational study.

PubMed

Elius Hossain, Md; Mahmudul Hasan, Md; Halim, M E; Ehsan, M Q; Halim, Mohammad A

2015-03-05

Some transition metal complexes of phenylalanine of general formula [M(C9H10NO2)2]; where M=Mn(II), Co(II), Ni(II), Cu(II) and Zn(II) are prepared in aqueous medium and characterized by spectroscopic, thermo-gravimetric (TG) and magnetic susceptibility analysis. Density functional theory (DFT) has been employed calculating the equilibrium geometries and vibrational frequencies of those complexes at B3LYP level of theory using 6-31G(d) and SDD basis sets. In addition, frontier molecular orbital and time-dependent density functional theory (TD-DFT) calculations are performed with CAM-B3LYP/6-31+G(d,p) and B3LYP/SDD level of theories. Thermo-gravimetric analysis confirms the composition of the complexes by comparing the experimental and calculated data for C, H, N and metals. Experimental and computed IR results predict a significant change in vibrational frequencies of metal-phenylalanine complexes compared to free ligand. DFT calculation confirms that Mn, Co, Ni and Cu complexes form square planar structure whereas Zn adopts distorted tetrahedral geometry. The metal-oxygen bonds in the optimized geometry of all complexes are shorter compared to the metal-nitrogen bonds which is consistent with a previous study. Cation-binding energy, enthalpy and Gibbs free energy indicates that these complexes are thermodynamically stable. UV-vis and TD-DFT studies reveal that these complexes demonstrate representative metal-to-ligand charge transfer (MLCT) and d-d transitions bands. TG analysis and IR spectra of the metal complexes strongly support the absence of water in crystallization. Magnetic susceptibility data of the complexes exhibits that all except Zn(II) complex are high spin paramagnetic. Copyright © 2014 Elsevier B.V. All rights reserved.

An evaluation of superminicomputers for thermal analysis

NASA Technical Reports Server (NTRS)

Storaasli, O. O.; Vidal, J. B.; Jones, G. K.

1982-01-01

The use of superminicomputers for solving a series of increasingly complex thermal analysis problems is investigated. The approach involved (1) installation and verification of the SPAR thermal analyzer software on superminicomputers at Langley Research Center and Goddard Space Flight Center, (2) solution of six increasingly complex thermal problems on this equipment, and (3) comparison of solution (accuracy, CPU time, turnaround time, and cost) with solutions on large mainframe computers.

Verification of Space Station Secondary Power System Stability Using Design of Experiment

NASA Technical Reports Server (NTRS)

Karimi, Kamiar J.; Booker, Andrew J.; Mong, Alvin C.; Manners, Bruce

1998-01-01

This paper describes analytical methods used in verification of large DC power systems with applications to the International Space Station (ISS). Large DC power systems contain many switching power converters with negative resistor characteristics. The ISS power system presents numerous challenges with respect to system stability such as complex sources and undefined loads. The Space Station program has developed impedance specifications for sources and loads. The overall approach to system stability consists of specific hardware requirements coupled with extensive system analysis and testing. Testing of large complex distributed power systems is not practical due to size and complexity of the system. Computer modeling has been extensively used to develop hardware specifications as well as to identify system configurations for lab testing. The statistical method of Design of Experiments (DoE) is used as an analysis tool for verification of these large systems. DOE reduces the number of computer runs which are necessary to analyze the performance of a complex power system consisting of hundreds of DC/DC converters. DoE also provides valuable information about the effect of changes in system parameters on the performance of the system. DoE provides information about various operating scenarios and identification of the ones with potential for instability. In this paper we will describe how we have used computer modeling to analyze a large DC power system. A brief description of DoE is given. Examples using applications of DoE to analysis and verification of the ISS power system are provided.

Minimized state complexity of quantum-encoded cryptic processes

NASA Astrophysics Data System (ADS)

Riechers, Paul M.; Mahoney, John R.; Aghamohammadi, Cina; Crutchfield, James P.

2016-05-01

The predictive information required for proper trajectory sampling of a stochastic process can be more efficiently transmitted via a quantum channel than a classical one. This recent discovery allows quantum information processing to drastically reduce the memory necessary to simulate complex classical stochastic processes. It also points to a new perspective on the intrinsic complexity that nature must employ in generating the processes we observe. The quantum advantage increases with codeword length: the length of process sequences used in constructing the quantum communication scheme. In analogy with the classical complexity measure, statistical complexity, we use this reduced communication cost as an entropic measure of state complexity in the quantum representation. Previously difficult to compute, the quantum advantage is expressed here in closed form using spectral decomposition. This allows for efficient numerical computation of the quantum-reduced state complexity at all encoding lengths, including infinite. Additionally, it makes clear how finite-codeword reduction in state complexity is controlled by the classical process's cryptic order, and it allows asymptotic analysis of infinite-cryptic-order processes.

Applications of Automation Methods for Nonlinear Fracture Test Analysis

NASA Technical Reports Server (NTRS)

Allen, Phillip A.; Wells, Douglas N.

2013-01-01

Using automated and standardized computer tools to calculate the pertinent test result values has several advantages such as: 1. allowing high-fidelity solutions to complex nonlinear phenomena that would be impractical to express in written equation form, 2. eliminating errors associated with the interpretation and programing of analysis procedures from the text of test standards, 3. lessening the need for expertise in the areas of solid mechanics, fracture mechanics, numerical methods, and/or finite element modeling, to achieve sound results, 4. and providing one computer tool and/or one set of solutions for all users for a more "standardized" answer. In summary, this approach allows a non-expert with rudimentary training to get the best practical solution based on the latest understanding with minimum difficulty.Other existing ASTM standards that cover complicated phenomena use standard computer programs: 1. ASTM C1340/C1340M-10- Standard Practice for Estimation of Heat Gain or Loss Through Ceilings Under Attics Containing Radiant Barriers by Use of a Computer Program 2. ASTM F 2815 - Standard Practice for Chemical Permeation through Protective Clothing Materials: Testing Data Analysis by Use of a Computer Program 3. ASTM E2807 - Standard Specification for 3D Imaging Data Exchange, Version 1.0 The verification, validation, and round-robin processes required of a computer tool closely parallel the methods that are used to ensure the solution validity for equations included in test standard. The use of automated analysis tools allows the creation and practical implementation of advanced fracture mechanics test standards that capture the physics of a nonlinear fracture mechanics problem without adding undue burden or expense to the user. The presented approach forms a bridge between the equation-based fracture testing standards of today and the next generation of standards solving complex problems through analysis automation.

Dynamical analysis of the global business-cycle synchronization

PubMed Central

2018-01-01

This paper reports the dynamical analysis of the business cycles of 12 (developed and developing) countries over the last 56 years by applying computational techniques used for tackling complex systems. They reveal long-term convergence and country-level interconnections because of close contagion effects caused by bilateral networking exposure. Interconnectivity determines the magnitude of cross-border impacts. Local features and shock propagation complexity also may be true engines for local configuration of cycles. The algorithmic modeling proves to represent a solid approach to study the complex dynamics involved in the world economies. PMID:29408909

Dynamical analysis of the global business-cycle synchronization.

PubMed

Lopes, António M; Tenreiro Machado, J A; Huffstot, John S; Mata, Maria Eugénia

2018-01-01

This paper reports the dynamical analysis of the business cycles of 12 (developed and developing) countries over the last 56 years by applying computational techniques used for tackling complex systems. They reveal long-term convergence and country-level interconnections because of close contagion effects caused by bilateral networking exposure. Interconnectivity determines the magnitude of cross-border impacts. Local features and shock propagation complexity also may be true engines for local configuration of cycles. The algorithmic modeling proves to represent a solid approach to study the complex dynamics involved in the world economies.

BioVLAB-MMIA: a cloud environment for microRNA and mRNA integrated analysis (MMIA) on Amazon EC2.

PubMed

Lee, Hyungro; Yang, Youngik; Chae, Heejoon; Nam, Seungyoon; Choi, Donghoon; Tangchaisin, Patanachai; Herath, Chathura; Marru, Suresh; Nephew, Kenneth P; Kim, Sun

2012-09-01

MicroRNAs, by regulating the expression of hundreds of target genes, play critical roles in developmental biology and the etiology of numerous diseases, including cancer. As a vast amount of microRNA expression profile data are now publicly available, the integration of microRNA expression data sets with gene expression profiles is a key research problem in life science research. However, the ability to conduct genome-wide microRNA-mRNA (gene) integration currently requires sophisticated, high-end informatics tools, significant expertise in bioinformatics and computer science to carry out the complex integration analysis. In addition, increased computing infrastructure capabilities are essential in order to accommodate large data sets. In this study, we have extended the BioVLAB cloud workbench to develop an environment for the integrated analysis of microRNA and mRNA expression data, named BioVLAB-MMIA. The workbench facilitates computations on the Amazon EC2 and S3 resources orchestrated by the XBaya Workflow Suite. The advantages of BioVLAB-MMIA over the web-based MMIA system include: 1) readily expanded as new computational tools become available; 2) easily modifiable by re-configuring graphic icons in the workflow; 3) on-demand cloud computing resources can be used on an "as needed" basis; 4) distributed orchestration supports complex and long running workflows asynchronously. We believe that BioVLAB-MMIA will be an easy-to-use computing environment for researchers who plan to perform genome-wide microRNA-mRNA (gene) integrated analysis tasks.

Computationally efficient algorithm for high sampling-frequency operation of active noise control

NASA Astrophysics Data System (ADS)

Rout, Nirmal Kumar; Das, Debi Prasad; Panda, Ganapati

2015-05-01

In high sampling-frequency operation of active noise control (ANC) system the length of the secondary path estimate and the ANC filter are very long. This increases the computational complexity of the conventional filtered-x least mean square (FXLMS) algorithm. To reduce the computational complexity of long order ANC system using FXLMS algorithm, frequency domain block ANC algorithms have been proposed in past. These full block frequency domain ANC algorithms are associated with some disadvantages such as large block delay, quantization error due to computation of large size transforms and implementation difficulties in existing low-end DSP hardware. To overcome these shortcomings, the partitioned block ANC algorithm is newly proposed where the long length filters in ANC are divided into a number of equal partitions and suitably assembled to perform the FXLMS algorithm in the frequency domain. The complexity of this proposed frequency domain partitioned block FXLMS (FPBFXLMS) algorithm is quite reduced compared to the conventional FXLMS algorithm. It is further reduced by merging one fast Fourier transform (FFT)-inverse fast Fourier transform (IFFT) combination to derive the reduced structure FPBFXLMS (RFPBFXLMS) algorithm. Computational complexity analysis for different orders of filter and partition size are presented. Systematic computer simulations are carried out for both the proposed partitioned block ANC algorithms to show its accuracy compared to the time domain FXLMS algorithm.

Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit.

PubMed

Eriksson, O; Brinne, B; Zhou, Y; Björkegren, J; Tegnér, J

2009-03-01

Complex regulatory dynamics is ubiquitous in molecular networks composed of genes and proteins. Recent progress in computational biology and its application to molecular data generate a growing number of complex networks. Yet, it has been difficult to understand the governing principles of these networks beyond graphical analysis or extensive numerical simulations. Here the authors exploit several simplifying biological circumstances which thereby enable to directly detect the underlying dynamical regularities driving periodic oscillations in a dynamical nonlinear computational model of a protein-protein network. System analysis is performed using the cell cycle, a mathematically well-described complex regulatory circuit driven by external signals. By introducing an explicit time delay and using a 'tearing-and-zooming' approach the authors reduce the system to a piecewise linear system with two variables that capture the dynamics of this complex network. A key step in the analysis is the identification of functional subsystems by identifying the relations between state-variables within the model. These functional subsystems are referred to as dynamical modules operating as sensitive switches in the original complex model. By using reduced mathematical representations of the subsystems the authors derive explicit conditions on how the cell cycle dynamics depends on system parameters, and can, for the first time, analyse and prove global conditions for system stability. The approach which includes utilising biological simplifying conditions, identification of dynamical modules and mathematical reduction of the model complexity may be applicable to other well-characterised biological regulatory circuits. [Includes supplementary material].

Computational science: shifting the focus from tools to models

PubMed Central

Hinsen, Konrad

2014-01-01

Computational techniques have revolutionized many aspects of scientific research over the last few decades. Experimentalists use computation for data analysis, processing ever bigger data sets. Theoreticians compute predictions from ever more complex models. However, traditional articles do not permit the publication of big data sets or complex models. As a consequence, these crucial pieces of information no longer enter the scientific record. Moreover, they have become prisoners of scientific software: many models exist only as software implementations, and the data are often stored in proprietary formats defined by the software. In this article, I argue that this emphasis on software tools over models and data is detrimental to science in the long term, and I propose a means by which this can be reversed. PMID:25309728

Remote sensing image ship target detection method based on visual attention model

NASA Astrophysics Data System (ADS)

Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

2017-11-01

The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

Availability Analysis of Dual Mode Systems

DOT National Transportation Integrated Search

1974-04-01

The analytical procedures presented define a method of evaluating the effects of failures in a complex dual-mode system based on a worst case steady-state analysis. The computed result is an availability figure of merit and not an absolute prediction...

Estimating Sobol Sensitivity Indices Using Correlations

EPA Science Inventory

Sensitivity analysis is a crucial tool in the development and evaluation of complex mathematical models. Sobol's method is a variance-based global sensitivity analysis technique that has been applied to computational models to assess the relative importance of input parameters on...

The value and cost of complexity in predictive modelling: role of tissue anisotropic conductivity and fibre tracts in neuromodulation

NASA Astrophysics Data System (ADS)

Salman Shahid, Syed; Bikson, Marom; Salman, Humaira; Wen, Peng; Ahfock, Tony

2014-06-01

Objectives. Computational methods are increasingly used to optimize transcranial direct current stimulation (tDCS) dose strategies and yet complexities of existing approaches limit their clinical access. Since predictive modelling indicates the relevance of subject/pathology based data and hence the need for subject specific modelling, the incremental clinical value of increasingly complex modelling methods must be balanced against the computational and clinical time and costs. For example, the incorporation of multiple tissue layers and measured diffusion tensor (DTI) based conductivity estimates increase model precision but at the cost of clinical and computational resources. Costs related to such complexities aggregate when considering individual optimization and the myriad of potential montages. Here, rather than considering if additional details change current-flow prediction, we consider when added complexities influence clinical decisions. Approach. Towards developing quantitative and qualitative metrics of value/cost associated with computational model complexity, we considered field distributions generated by two 4 × 1 high-definition montages (m1 = 4 × 1 HD montage with anode at C3 and m2 = 4 × 1 HD montage with anode at C1) and a single conventional (m3 = C3-Fp2) tDCS electrode montage. We evaluated statistical methods, including residual error (RE) and relative difference measure (RDM), to consider the clinical impact and utility of increased complexities, namely the influence of skull, muscle and brain anisotropic conductivities in a volume conductor model. Main results. Anisotropy modulated current-flow in a montage and region dependent manner. However, significant statistical changes, produced within montage by anisotropy, did not change qualitative peak and topographic comparisons across montages. Thus for the examples analysed, clinical decision on which dose to select would not be altered by the omission of anisotropic brain conductivity. Significance. Results illustrate the need to rationally balance the role of model complexity, such as anisotropy in detailed current flow analysis versus value in clinical dose design. However, when extending our analysis to include axonal polarization, the results provide presumably clinically meaningful information. Hence the importance of model complexity may be more relevant with cellular level predictions of neuromodulation.

Computed Tomography Inspection and Analysis for Additive Manufacturing Components

NASA Technical Reports Server (NTRS)

Beshears, Ronald D.

2016-01-01

Computed tomography (CT) inspection was performed on test articles additively manufactured from metallic materials. Metallic AM and machined wrought alloy test articles with programmed flaws were inspected using a 2MeV linear accelerator based CT system. Performance of CT inspection on identically configured wrought and AM components and programmed flaws was assessed using standard image analysis techniques to determine the impact of additive manufacturing on inspectability of objects with complex geometries.

Air Defense: A Computer Game for Research in Human Performance.

DTIC Science & Technology

1981-07-01

warfare (ANW) threat analysis. M’ajor elements of the threat analysis problem \\\\,erc eoibedded in an interactive air detoense game controlled by a...The game requires sustained attention to a complex and interactive "hostile" environment, provides proper experimental control of relevant variables...AD-A102 725 NAVY PERSONNEL RESEARCH AND DEVELOPMENT CENTER SAN DETC F/6 5/10 AIR DEFENSE: A COMPUTER GAME FOR RESEARCH IN HUMAN PERFORMANCE.(U) JUL

Automating Embedded Analysis Capabilities and Managing Software Complexity in Multiphysics Simulation, Part I: Template-Based Generic Programming

DOE PAGES

Pawlowski, Roger P.; Phipps, Eric T.; Salinger, Andrew G.

2012-01-01

An approach for incorporating embedded simulation and analysis capabilities in complex simulation codes through template-based generic programming is presented. This approach relies on templating and operator overloading within the C++ language to transform a given calculation into one that can compute a variety of additional quantities that are necessary for many state-of-the-art simulation and analysis algorithms. An approach for incorporating these ideas into complex simulation codes through general graph-based assembly is also presented. These ideas have been implemented within a set of packages in the Trilinos framework and are demonstrated on a simple problem from chemical engineering.

Fusing Symbolic and Numerical Diagnostic Computations

NASA Technical Reports Server (NTRS)

James, Mark

2007-01-01

X-2000 Anomaly Detection Language denotes a developmental computing language, and the software that establishes and utilizes the language, for fusing two diagnostic computer programs, one implementing a numerical analysis method, the other implementing a symbolic analysis method into a unified event-based decision analysis software system for realtime detection of events (e.g., failures) in a spacecraft, aircraft, or other complex engineering system. The numerical analysis method is performed by beacon-based exception analysis for multi-missions (BEAMs), which has been discussed in several previous NASA Tech Briefs articles. The symbolic analysis method is, more specifically, an artificial-intelligence method of the knowledge-based, inference engine type, and its implementation is exemplified by the Spacecraft Health Inference Engine (SHINE) software. The goal in developing the capability to fuse numerical and symbolic diagnostic components is to increase the depth of analysis beyond that previously attainable, thereby increasing the degree of confidence in the computed results. In practical terms, the sought improvement is to enable detection of all or most events, with no or few false alarms.

An efficient hybrid technique in RCS predictions of complex targets at high frequencies

NASA Astrophysics Data System (ADS)

Algar, María-Jesús; Lozano, Lorena; Moreno, Javier; González, Iván; Cátedra, Felipe

2017-09-01

Most computer codes in Radar Cross Section (RCS) prediction use Physical Optics (PO) and Physical theory of Diffraction (PTD) combined with Geometrical Optics (GO) and Geometrical Theory of Diffraction (GTD). The latter approaches are computationally cheaper and much more accurate for curved surfaces, but not applicable for the computation of the RCS of all surfaces of a complex object due to the presence of caustic problems in the analysis of concave surfaces or flat surfaces in the far field. The main contribution of this paper is the development of a hybrid method based on a new combination of two asymptotic techniques: GTD and PO, considering the advantages and avoiding the disadvantages of each of them. A very efficient and accurate method to analyze the RCS of complex structures at high frequencies is obtained with the new combination. The proposed new method has been validated comparing RCS results obtained for some simple cases using the proposed approach and RCS using the rigorous technique of Method of Moments (MoM). Some complex cases have been examined at high frequencies contrasting the results with PO. This study shows the accuracy and the efficiency of the hybrid method and its suitability for the computation of the RCS at really large and complex targets at high frequencies.

Symbolic-numeric interface: A review

NASA Technical Reports Server (NTRS)

Ng, E. W.

1980-01-01

A survey of the use of a combination of symbolic and numerical calculations is presented. Symbolic calculations primarily refer to the computer processing of procedures from classical algebra, analysis, and calculus. Numerical calculations refer to both numerical mathematics research and scientific computation. This survey is intended to point out a large number of problem areas where a cooperation of symbolic and numerical methods is likely to bear many fruits. These areas include such classical operations as differentiation and integration, such diverse activities as function approximations and qualitative analysis, and such contemporary topics as finite element calculations and computation complexity. It is contended that other less obvious topics such as the fast Fourier transform, linear algebra, nonlinear analysis and error analysis would also benefit from a synergistic approach.

CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing.

PubMed

Angiuoli, Samuel V; Matalka, Malcolm; Gussman, Aaron; Galens, Kevin; Vangala, Mahesh; Riley, David R; Arze, Cesar; White, James R; White, Owen; Fricke, W Florian

2011-08-30

Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.

Fast hydrological model calibration based on the heterogeneous parallel computing accelerated shuffled complex evolution method

NASA Astrophysics Data System (ADS)

Kan, Guangyuan; He, Xiaoyan; Ding, Liuqian; Li, Jiren; Hong, Yang; Zuo, Depeng; Ren, Minglei; Lei, Tianjie; Liang, Ke

2018-01-01

Hydrological model calibration has been a hot issue for decades. The shuffled complex evolution method developed at the University of Arizona (SCE-UA) has been proved to be an effective and robust optimization approach. However, its computational efficiency deteriorates significantly when the amount of hydrometeorological data increases. In recent years, the rise of heterogeneous parallel computing has brought hope for the acceleration of hydrological model calibration. This study proposed a parallel SCE-UA method and applied it to the calibration of a watershed rainfall-runoff model, the Xinanjiang model. The parallel method was implemented on heterogeneous computing systems using OpenMP and CUDA. Performance testing and sensitivity analysis were carried out to verify its correctness and efficiency. Comparison results indicated that heterogeneous parallel computing-accelerated SCE-UA converged much more quickly than the original serial version and possessed satisfactory accuracy and stability for the task of fast hydrological model calibration.

Three-dimensional transonic potential flow about complex 3-dimensional configurations

NASA Technical Reports Server (NTRS)

Reyhner, T. A.

1984-01-01

An analysis has been developed and a computer code written to predict three-dimensional subsonic or transonic potential flow fields about lifting or nonlifting configurations. Possible condfigurations include inlets, nacelles, nacelles with ground planes, S-ducts, turboprop nacelles, wings, and wing-pylon-nacelle combinations. The solution of the full partial differential equation for compressible potential flow written in terms of a velocity potential is obtained using finite differences, line relaxation, and multigrid. The analysis uses either a cylindrical or Cartesian coordinate system. The computational mesh is not body fitted. The analysis has been programmed in FORTRAN for both the CDC CYBER 203 and the CRAY-1 computers. Comparisons of computed results with experimental measurement are presented. Descriptions of the program input and output formats are included.

[AERA. Dream machines and computing practices at the Mathematical Center].

PubMed

Alberts, Gerard; De Beer, Huub T

2008-01-01

Dream machines may be just as effective as the ones materialised. Their symbolic thrust can be quite powerful. The Amsterdam 'Mathematisch Centrum' (Mathematical Center), founded February 11, 1946, created a Computing Department in an effort to realise its goal of serving society. When Aad van Wijngaarden was appointed as head of the Computing Department, however, he claimed space for scientific research and computer construction, next to computing as a service. Still, the computing service following the five stage style of Hartree's numerical analysis remained a dominant characteristic of the work of the Computing Department. The high level of ambition held by Aad van Wijngaarden lead to ever renewed projections of big automatic computers, symbolised by the never-built AERA. Even a machine that was actually constructed, the ARRA which followed A.D. Booth's design of the ARC, never made it into real operation. It did serve Van Wijngaarden to bluff his way into the computer age by midsummer 1952. Not until January 1954 did the computing department have a working stored program computer, which for reasons of policy went under the same name: ARRA. After just one other machine, the ARMAC, had been produced, a separate company, Electrologica, was set up for the manufacture of computers, which produced the rather successful X1 computer. The combination of ambition and absence of a working machine lead to a high level of work on programming, way beyond the usual ideas of libraries of subroutines. Edsger W. Dijkstra in particular led the way to an emphasis on the duties of the programmer within the pattern of numerical analysis. Programs generating programs, known elsewhere as autocoding systems, were at the 'Mathematisch Centrum' called 'superprograms'. Practical examples were usually called a 'complex', in Dutch, where in English one might say 'system'. Historically, this is where software begins. Dekker's matrix complex, Dijkstra's interrupt system, Dijkstra and Zonneveld's ALGOL compiler--which for housekeeping contained 'the complex'--were actual examples of such super programs. In 1960 this compiler gave the Mathematical Center a leading edge in the early development of software.

The effects of syntactic complexity on the human-computer interaction

NASA Technical Reports Server (NTRS)

Chechile, R. A.; Fleischman, R. N.; Sadoski, D. M.

1986-01-01

Three divided-attention experiments were performed to evaluate the effectiveness of a syntactic analysis of the primary task of editing flight route-way-point information. For all editing conditions, a formal syntactic expression was developed for the operator's interaction with the computer. In terms of the syntactic expression, four measures of syntactic were examined. Increased syntactic complexity did increase the time to train operators, but once the operators were trained, syntactic complexity did not influence the divided-attention performance. However, the number of memory retrievals required of the operator significantly accounted for the variation in the accuracy, workload, and task completion time found on the different editing tasks under attention-sharing conditions.

Combustion and Magnetohydrodynamic Processes in Advanced Pulse Detonation Rocket Engines

DTIC Science & Technology

2012-10-01

use of high-order numerical methods can also be a powerful tool in the analysis of such complex flows, but we need to understand the interaction of...computational physics, 43(2):357372, 1981. [47] B. Einfeldt. On godunov-type methods for gas dynamics . SIAM Journal on Numerical Analysis , pages 294...dimensional effects with complex reaction kinetics, the simple one-dimensional detonation structure provides a rich spectrum of dynamical features which are

On the equivalence of Gaussian elimination and Gauss-Jordan reduction in solving linear equations

NASA Technical Reports Server (NTRS)

Tsao, Nai-Kuan

1989-01-01

A novel general approach to round-off error analysis using the error complexity concepts is described. This is applied to the analysis of the Gaussian Elimination and Gauss-Jordan scheme for solving linear equations. The results show that the two algorithms are equivalent in terms of our error complexity measures. Thus the inherently parallel Gauss-Jordan scheme can be implemented with confidence if parallel computers are available.

Programming Pluralism: Using Learning Analytics to Detect Patterns in the Learning of Computer Programming

ERIC Educational Resources Information Center

Blikstein, Paulo; Worsley, Marcelo; Piech, Chris; Sahami, Mehran; Cooper, Steven; Koller, Daphne

2014-01-01

New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…

Computational Simulation and Analysis of Mutations: Nucleotide Fixation, Allelic Age and Rare Genetic Variations in Population

ERIC Educational Resources Information Center

Qiu, Shuhao

2015-01-01

In order to investigate the complexity of mutations, a computational approach named Genome Evolution by Matrix Algorithms ("GEMA") has been implemented. GEMA models genomic changes, taking into account hundreds of mutations within each individual in a population. By modeling of entire human chromosomes, GEMA precisely mimics real…

An Undergraduate Research Experience Studying Ras and Ras Mutants

ERIC Educational Resources Information Center

Griffeth, Nancy; Batista, Naralys; Grosso, Terri; Arianna, Gianluca; Bhatia, Ravnit; Boukerche, Faiza; Crispi, Nicholas; Fuller, Neno; Gauza, Piotr; Kingsbury, Lyle; Krynski, Kamil; Levine, Alina; Ma, Rui Yan; Nam, Jennifer; Pearl, Eitan; Rosa, Alessandro; Salarbux, Stephanie; Sun, Dylan

2016-01-01

Each January from 2010 to 2014, an undergraduate workshop on modeling biological systems was held at Lehman College of the City University of New York. The workshops were funded by a National Science Foundation (NSF) Expedition in Computing, "Computational Modeling and Analysis of Complex Systems (CMACS)." The primary goal was to…

Lumber Grading With A Computer Vision System

Treesearch

Richard W. Conners; Tai-Hoon Cho; Philip A. Araman

1989-01-01

Over the past few years significant progress has been made in developing a computer vision system for locating and identifying defects on surfaced hardwood lumber. Unfortunately, until September of 1988 little research had gone into developing methods for analyzing rough lumber. This task is arguably more complex than the analysis of surfaced lumber. The prime...

Multimodal Learning Analytics and Education Data Mining: Using Computational Technologies to Measure Complex Learning Tasks

ERIC Educational Resources Information Center

Blikstein, Paulo; Worsley, Marcelo

2016-01-01

New high-frequency multimodal data collection technologies and machine learning analysis techniques could offer new insights into learning, especially when students have the opportunity to generate unique, personalized artifacts, such as computer programs, robots, and solutions engineering challenges. To date most of the work on learning analytics…

Micro-computed tomography of pupal metamorphosis in the solitary bee Megachile rotundata

USDA-ARS?s Scientific Manuscript database

Insect metamorphosis involves a complex change in form and function, but most of these changes are internal and treated as a black box. In this study, we examined development of the solitary bee, Megachile rotundata, using micro-computed tomography (µCT) and digital volume analysis. We describe deve...

Program Helps To Determine Chemical-Reaction Mechanisms

NASA Technical Reports Server (NTRS)

Bittker, D. A.; Radhakrishnan, K.

1995-01-01

General Chemical Kinetics and Sensitivity Analysis (LSENS) computer code developed for use in solving complex, homogeneous, gas-phase, chemical-kinetics problems. Provides for efficient and accurate chemical-kinetics computations and provides for sensitivity analysis for variety of problems, including problems involving honisothermal conditions. Incorporates mathematical models for static system, steady one-dimensional inviscid flow, reaction behind incident shock wave (with boundary-layer correction), and perfectly stirred reactor. Computations of equilibrium properties performed for following assigned states: enthalpy and pressure, temperature and pressure, internal energy and volume, and temperature and volume. Written in FORTRAN 77 with exception of NAMELIST extensions used for input.

Development of an Efficient Binaural Simulation for the Analysis of Structural Acoustic Data

NASA Technical Reports Server (NTRS)

Lalime, Aimee L.; Johnson, Marty E.; Rizzi, Stephen A. (Technical Monitor)

2002-01-01

Binaural or "virtual acoustic" representation has been proposed as a method of analyzing acoustic and vibroacoustic data. Unfortunately, this binaural representation can require extensive computer power to apply the Head Related Transfer Functions (HRTFs) to a large number of sources, as with a vibrating structure. This work focuses on reducing the number of real-time computations required in this binaural analysis through the use of Singular Value Decomposition (SVD) and Equivalent Source Reduction (ESR). The SVD method reduces the complexity of the HRTF computations by breaking the HRTFs into dominant singular values (and vectors). The ESR method reduces the number of sources to be analyzed in real-time computation by replacing sources on the scale of a structural wavelength with sources on the scale of an acoustic wavelength. It is shown that the effectiveness of the SVD and ESR methods improves as the complexity of the source increases. In addition, preliminary auralization tests have shown that the results from both the SVD and ESR methods are indistinguishable from the results found with the exhaustive method.

Multirate-based fast parallel algorithms for 2-D DHT-based real-valued discrete Gabor transform.

PubMed

Tao, Liang; Kwan, Hon Keung

2012-07-01

Novel algorithms for the multirate and fast parallel implementation of the 2-D discrete Hartley transform (DHT)-based real-valued discrete Gabor transform (RDGT) and its inverse transform are presented in this paper. A 2-D multirate-based analysis convolver bank is designed for the 2-D RDGT, and a 2-D multirate-based synthesis convolver bank is designed for the 2-D inverse RDGT. The parallel channels in each of the two convolver banks have a unified structure and can apply the 2-D fast DHT algorithm to speed up their computations. The computational complexity of each parallel channel is low and is independent of the Gabor oversampling rate. All the 2-D RDGT coefficients of an image are computed in parallel during the analysis process and can be reconstructed in parallel during the synthesis process. The computational complexity and time of the proposed parallel algorithms are analyzed and compared with those of the existing fastest algorithms for 2-D discrete Gabor transforms. The results indicate that the proposed algorithms are the fastest, which make them attractive for real-time image processing.

PEM-PCA: a parallel expectation-maximization PCA face recognition architecture.

PubMed

Rujirakul, Kanokmon; So-In, Chakchai; Arnonkijpanich, Banchar

2014-01-01

Principal component analysis or PCA has been traditionally used as one of the feature extraction techniques in face recognition systems yielding high accuracy when requiring a small number of features. However, the covariance matrix and eigenvalue decomposition stages cause high computational complexity, especially for a large database. Thus, this research presents an alternative approach utilizing an Expectation-Maximization algorithm to reduce the determinant matrix manipulation resulting in the reduction of the stages' complexity. To improve the computational time, a novel parallel architecture was employed to utilize the benefits of parallelization of matrix computation during feature extraction and classification stages including parallel preprocessing, and their combinations, so-called a Parallel Expectation-Maximization PCA architecture. Comparing to a traditional PCA and its derivatives, the results indicate lower complexity with an insignificant difference in recognition precision leading to high speed face recognition systems, that is, the speed-up over nine and three times over PCA and Parallel PCA.

A review on recent contribution of meshfree methods to structure and fracture mechanics applications.

PubMed

Daxini, S D; Prajapati, J M

2014-01-01

Meshfree methods are viewed as next generation computational techniques. With evident limitations of conventional grid based methods, like FEM, in dealing with problems of fracture mechanics, large deformation, and simulation of manufacturing processes, meshfree methods have gained much attention by researchers. A number of meshfree methods have been proposed till now for analyzing complex problems in various fields of engineering. Present work attempts to review recent developments and some earlier applications of well-known meshfree methods like EFG and MLPG to various types of structure mechanics and fracture mechanics applications like bending, buckling, free vibration analysis, sensitivity analysis and topology optimization, single and mixed mode crack problems, fatigue crack growth, and dynamic crack analysis and some typical applications like vibration of cracked structures, thermoelastic crack problems, and failure transition in impact problems. Due to complex nature of meshfree shape functions and evaluation of integrals in domain, meshless methods are computationally expensive as compared to conventional mesh based methods. Some improved versions of original meshfree methods and other techniques suggested by researchers to improve computational efficiency of meshfree methods are also reviewed here.

Multilayer modeling and analysis of human brain networks

PubMed Central

2017-01-01

Abstract Understanding how the human brain is structured, and how its architecture is related to function, is of paramount importance for a variety of applications, including but not limited to new ways to prevent, deal with, and cure brain diseases, such as Alzheimer’s or Parkinson’s, and psychiatric disorders, such as schizophrenia. The recent advances in structural and functional neuroimaging, together with the increasing attitude toward interdisciplinary approaches involving computer science, mathematics, and physics, are fostering interesting results from computational neuroscience that are quite often based on the analysis of complex network representation of the human brain. In recent years, this representation experienced a theoretical and computational revolution that is breaching neuroscience, allowing us to cope with the increasing complexity of the human brain across multiple scales and in multiple dimensions and to model structural and functional connectivity from new perspectives, often combined with each other. In this work, we will review the main achievements obtained from interdisciplinary research based on magnetic resonance imaging and establish de facto, the birth of multilayer network analysis and modeling of the human brain. PMID:28327916

The STAGS computer code

NASA Technical Reports Server (NTRS)

Almroth, B. O.; Brogan, F. A.

1978-01-01

Basic information about the computer code STAGS (Structural Analysis of General Shells) is presented to describe to potential users the scope of the code and the solution procedures that are incorporated. Primarily, STAGS is intended for analysis of shell structures, although it has been extended to more complex shell configurations through the inclusion of springs and beam elements. The formulation is based on a variational approach in combination with local two dimensional power series representations of the displacement components. The computer code includes options for analysis of linear or nonlinear static stress, stability, vibrations, and transient response. Material as well as geometric nonlinearities are included. A few examples of applications of the code are presented for further illustration of its scope.

A general computation model based on inverse analysis principle used for rheological analysis of W/O rapeseed and soybean oil emulsions

NASA Astrophysics Data System (ADS)

Vintila, Iuliana; Gavrus, Adinel

2017-10-01

The present research paper proposes the validation of a rigorous computation model used as a numerical tool to identify rheological behavior of complex emulsions W/O. Considering a three-dimensional description of a general viscoplastic flow it is detailed the thermo-mechanical equations used to identify fluid or soft material's rheological laws starting from global experimental measurements. Analyses are conducted for complex emulsions W/O having generally a Bingham behavior using the shear stress - strain rate dependency based on a power law and using an improved analytical model. Experimental results are investigated in case of rheological behavior for crude and refined rapeseed/soybean oils and four types of corresponding W/O emulsions using different physical-chemical composition. The rheological behavior model was correlated with the thermo-mechanical analysis of a plane-plane rheometer, oil content, chemical composition, particle size and emulsifier's concentration. The parameters of rheological laws describing the industrial oils and the W/O concentrated emulsions behavior were computed from estimated shear stresses using a non-linear regression technique and from experimental torques using the inverse analysis tool designed by A. Gavrus (1992-2000).

Addressing Curse of Dimensionality in Sensitivity Analysis: How Can We Handle High-Dimensional Problems?

NASA Astrophysics Data System (ADS)

Safaei, S.; Haghnegahdar, A.; Razavi, S.

2016-12-01

Complex environmental models are now the primary tool to inform decision makers for the current or future management of environmental resources under the climate and environmental changes. These complex models often contain a large number of parameters that need to be determined by a computationally intensive calibration procedure. Sensitivity analysis (SA) is a very useful tool that not only allows for understanding the model behavior, but also helps in reducing the number of calibration parameters by identifying unimportant ones. The issue is that most global sensitivity techniques are highly computationally demanding themselves for generating robust and stable sensitivity metrics over the entire model response surface. Recently, a novel global sensitivity analysis method, Variogram Analysis of Response Surfaces (VARS), is introduced that can efficiently provide a comprehensive assessment of global sensitivity using the Variogram concept. In this work, we aim to evaluate the effectiveness of this highly efficient GSA method in saving computational burden, when applied to systems with extra-large number of input factors ( 100). We use a test function and a hydrological modelling case study to demonstrate the capability of VARS method in reducing problem dimensionality by identifying important vs unimportant input factors.

Encapsulating model complexity and landscape-scale analyses of state-and-transition simulation models: an application of ecoinformatics and juniper encroachment in sagebrush steppe ecosystems

USGS Publications Warehouse

O'Donnell, Michael

2015-01-01

State-and-transition simulation modeling relies on knowledge of vegetation composition and structure (states) that describe community conditions, mechanistic feedbacks such as fire that can affect vegetation establishment, and ecological processes that drive community conditions as well as the transitions between these states. However, as the need for modeling larger and more complex landscapes increase, a more advanced awareness of computing resources becomes essential. The objectives of this study include identifying challenges of executing state-and-transition simulation models, identifying common bottlenecks of computing resources, developing a workflow and software that enable parallel processing of Monte Carlo simulations, and identifying the advantages and disadvantages of different computing resources. To address these objectives, this study used the ApexRMS® SyncroSim software and embarrassingly parallel tasks of Monte Carlo simulations on a single multicore computer and on distributed computing systems. The results demonstrated that state-and-transition simulation models scale best in distributed computing environments, such as high-throughput and high-performance computing, because these environments disseminate the workloads across many compute nodes, thereby supporting analysis of larger landscapes, higher spatial resolution vegetation products, and more complex models. Using a case study and five different computing environments, the top result (high-throughput computing versus serial computations) indicated an approximate 96.6% decrease of computing time. With a single, multicore compute node (bottom result), the computing time indicated an 81.8% decrease relative to using serial computations. These results provide insight into the tradeoffs of using different computing resources when research necessitates advanced integration of ecoinformatics incorporating large and complicated data inputs and models. - See more at: http://aimspress.com/aimses/ch/reader/view_abstract.aspx?file_no=Environ2015030&flag=1#sthash.p1XKDtF8.dpuf

[Analysis of Conformational Features of Watson-Crick Duplex Fragments by Molecular Mechanics and Quantum Mechanics Methods].

PubMed

Poltev, V I; Anisimov, V M; Sanchez, C; Deriabina, A; Gonzalez, E; Garcia, D; Rivas, F; Polteva, N A

2016-01-01

It is generally accepted that the important characteristic features of the Watson-Crick duplex originate from the molecular structure of its subunits. However, it still remains to elucidate what properties of each subunit are responsible for the significant characteristic features of the DNA structure. The computations of desoxydinucleoside monophosphates complexes with Na-ions using density functional theory revealed a pivotal role of DNA conformational properties of single-chain minimal fragments in the development of unique features of the Watson-Crick duplex. We found that directionality of the sugar-phosphate backbone and the preferable ranges of its torsion angles, combined with the difference between purines and pyrimidines. in ring bases, define the dependence of three-dimensional structure of the Watson-Crick duplex on nucleotide base sequence. In this work, we extended these density functional theory computations to the minimal' fragments of DNA duplex, complementary desoxydinucleoside monophosphates complexes with Na-ions. Using several computational methods and various functionals, we performed a search for energy minima of BI-conformation for complementary desoxydinucleoside monophosphates complexes with different nucleoside sequences. Two sequences are optimized using ab initio method at the MP2/6-31++G** level of theory. The analysis of torsion angles, sugar ring puckering and mutual base positions of optimized structures demonstrates that the conformational characteristic features of complementary desoxydinucleoside monophosphates complexes with Na-ions remain within BI ranges and become closer to the corresponding characteristic features of the Watson-Crick duplex crystals. Qualitatively, the main characteristic features of each studied complementary desoxydinucleoside monophosphates complex remain invariant when different computational methods are used, although the quantitative values of some conformational parameters could vary lying within the limits typical for the corresponding family. We observe that popular functionals in density functional theory calculations lead to the overestimated distances between base pairs, while MP2 computations and the newer complex functionals produce the structures that have too close atom-atom contacts. A detailed study of some complementary desoxydinucleoside monophosphate complexes with Na-ions highlights the existence of several energy minima corresponding to BI-conformations, in other words, the complexity of the relief pattern of the potential energy surface of complementary desoxydinucleoside monophosphate complexes. This accounts for variability of conformational parameters of duplex fragments with the same base sequence. Popular molecular mechanics force fields AMBER and CHARMM reproduce most of the conformational characteristics of desoxydinucleoside monophosphates and their complementary complexes with Na-ions but fail to reproduce some details of the dependence of the Watson-Crick duplex conformation on the nucleotide sequence.

SMV⊥: Simplex of maximal volume based upon the Gram-Schmidt process

NASA Astrophysics Data System (ADS)

Salazar-Vazquez, Jairo; Mendez-Vazquez, Andres

2015-10-01

In recent years, different algorithms for Hyperspectral Image (HI) analysis have been introduced. The high spectral resolution of these images allows to develop different algorithms for target detection, material mapping, and material identification for applications in Agriculture, Security and Defense, Industry, etc. Therefore, from the computer science's point of view, there is fertile field of research for improving and developing algorithms in HI analysis. In some applications, the spectral pixels of a HI can be classified using laboratory spectral signatures. Nevertheless, for many others, there is no enough available prior information or spectral signatures, making any analysis a difficult task. One of the most popular algorithms for the HI analysis is the N-FINDR because it is easy to understand and provides a way to unmix the original HI in the respective material compositions. The N-FINDR is computationally expensive and its performance depends on a random initialization process. This paper proposes a novel idea to reduce the complexity of the N-FINDR by implementing a bottom-up approach based in an observation from linear algebra and the use of the Gram-Schmidt process. Therefore, the Simplex of Maximal Volume Perpendicular (SMV⊥) algorithm is proposed for fast endmember extraction in hyperspectral imagery. This novel algorithm has complexity O(n) with respect to the number of pixels. In addition, the evidence shows that SMV⊥ calculates a bigger volume, and has lower computational time complexity than other poular algorithms on synthetic and real scenarios.

Potential Flow Theory and Operation Guide for the Panel Code PMARC. Version 14

NASA Technical Reports Server (NTRS)

Ashby, Dale L.

1999-01-01

The theoretical basis for PMARC, a low-order panel code for modeling complex three-dimensional bodies, in potential flow, is outlined. PMARC can be run on a wide variety of computer platforms, including desktop machines, workstations, and supercomputers. Execution times for PMARC vary tremendously depending on the computer resources used, but typically range from several minutes for simple or moderately complex cases to several hours for very large complex cases. Several of the advanced features currently included in the code, such as internal flow modeling, boundary layer analysis, and time-dependent flow analysis, including problems involving relative motion, are discussed in some detail. The code is written in Fortran77, using adjustable-size arrays so that it can be easily redimensioned to match problem requirements and computer hardware constraints. An overview of the program input is presented. A detailed description of the input parameters is provided in the appendices. PMARC results for several test cases are presented along with analytic or experimental data, where available. The input files for these test cases are given in the appendices. PMARC currently supports plotfile output formats for several commercially available graphics packages. The supported graphics packages are Plot3D, Tecplot, and PmarcViewer.

Urban Typologies: Towards an ORNL Urban Information System (UrbIS)

NASA Astrophysics Data System (ADS)

KC, B.; King, A. W.; Sorokine, A.; Crow, M. C.; Devarakonda, R.; Hilbert, N. L.; Karthik, R.; Patlolla, D.; Surendran Nair, S.

2016-12-01

Urban environments differ in a large number of key attributes; these include infrastructure, morphology, demography, and economic and social variables, among others. These attributes determine many urban properties such as energy and water consumption, greenhouse gas emissions, air quality, public health, sustainability, and vulnerability and resilience to climate change. Characterization of urban environments by a single property such as population size does not sufficiently capture this complexity. In addressing this multivariate complexity one typically faces such problems as disparate and scattered data, challenges of big data management, spatial searching, insufficient computational capacity for data-driven analysis and modelling, and the lack of tools to quickly visualize the data and compare the analytical results across different cities and regions. We have begun the development of an Urban Information System (UrbIS) to address these issues, one that embraces the multivariate "big data" of urban areas and their environments across the United States utilizing the Big Data as a Service (BDaaS) concept. With technological roots in High-performance Computing (HPC), BDaaS is based on the idea of outsourcing computations to different computing paradigms, scalable to super-computers. UrbIS aims to incorporate federated metadata search, integrated modeling and analysis, and geovisualization into a single seamless workflow. The system includes web-based 2D/3D visualization with an iGlobe interface, fast cloud-based and server-side data processing and analysis, and a metadata search engine based on the Mercury data search system developed at Oak Ridge National Laboratory (ORNL). Results of analyses will be made available through web services. We are implementing UrbIS in ORNL's Compute and Data Environment for Science (CADES) and are leveraging ORNL experience in complex data and geospatial projects. The development of UrbIS is being guided by an investigation of urban heat islands (UHI) using high-dimensional clustering and statistics to define urban typologies (types of cities) in an investigation of how UHI vary with urban type across the United States.

Acceleration of the matrix multiplication of Radiance three phase daylighting simulations with parallel computing on heterogeneous hardware of personal computer

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

Zuo, Wangda; McNeil, Andrew; Wetter, Michael

2013-05-23

Building designers are increasingly relying on complex fenestration systems to reduce energy consumed for lighting and HVAC in low energy buildings. Radiance, a lighting simulation program, has been used to conduct daylighting simulations for complex fenestration systems. Depending on the configurations, the simulation can take hours or even days using a personal computer. This paper describes how to accelerate the matrix multiplication portion of a Radiance three-phase daylight simulation by conducting parallel computing on heterogeneous hardware of a personal computer. The algorithm was optimized and the computational part was implemented in parallel using OpenCL. The speed of new approach wasmore » evaluated using various daylighting simulation cases on a multicore central processing unit and a graphics processing unit. Based on the measurements and analysis of the time usage for the Radiance daylighting simulation, further speedups can be achieved by using fast I/O devices and storing the data in a binary format.« less

A 3D puzzle approach to building protein-DNA structures.

PubMed

Hinton, Deborah M

2017-03-15

Despite recent advances in structural analysis, it is still challenging to obtain a high-resolution structure for a complex of RNA polymerase, transcriptional factors, and DNA. However, using biochemical constraints, 3D printed models of available structures, and computer modeling, one can build biologically relevant models of such supramolecular complexes.

Syntheses, structural, computational, and thermal analysis of acid-base complexes of picric acid with N-heterocyclic bases.

PubMed

Goel, Nidhi; Singh, Udai P

2013-10-10

Four new acid-base complexes using picric acid [(OH)(NO2)3C6H2] (PA) and N-heterocyclic bases (1,10-phenanthroline (phen)/2,2';6',2"-terpyridine (terpy)/hexamethylenetetramine (hmta)/2,4,6-tri(2-pyridyl)-1,3,5-triazine (tptz)) were prepared and characterized by elemental analysis, IR, NMR and X-ray crystallography. Crystal structures provide detailed information of the noncovalent interactions present in different complexes. The optimized structures of the complexes were calculated in terms of the density functional theory. The thermolysis of these complexes was investigated by TG-DSC and ignition delay measurements. The model-free isoconversional and model-fitting kinetic approaches have been applied to isothermal TG data for kinetics investigation of thermal decomposition of these complexes.

Multithreaded Model for Dynamic Load Balancing Parallel Adaptive PDE Computations

NASA Technical Reports Server (NTRS)

Chrisochoides, Nikos

1995-01-01

We present a multithreaded model for the dynamic load-balancing of numerical, adaptive computations required for the solution of Partial Differential Equations (PDE's) on multiprocessors. Multithreading is used as a means of exploring concurrency in the processor level in order to tolerate synchronization costs inherent to traditional (non-threaded) parallel adaptive PDE solvers. Our preliminary analysis for parallel, adaptive PDE solvers indicates that multithreading can be used an a mechanism to mask overheads required for the dynamic balancing of processor workloads with computations required for the actual numerical solution of the PDE's. Also, multithreading can simplify the implementation of dynamic load-balancing algorithms, a task that is very difficult for traditional data parallel adaptive PDE computations. Unfortunately, multithreading does not always simplify program complexity, often makes code re-usability not an easy task, and increases software complexity.

Engineering computer graphics in gas turbine engine design, analysis and manufacture

NASA Technical Reports Server (NTRS)

Lopatka, R. S.

1975-01-01

A time-sharing and computer graphics facility designed to provide effective interactive tools to a large number of engineering users with varied requirements was described. The application of computer graphics displays at several levels of hardware complexity and capability is discussed, with examples of graphics systems tracing gas turbine product development, beginning with preliminary design through manufacture. Highlights of an operating system stylized for interactive engineering graphics is described.

Streamwise Vorticity Generation in Laminar and Turbulent Jets

NASA Technical Reports Server (NTRS)

Demuren, Aodeji O.; Wilson, Robert V.

1999-01-01

Complex streamwise vorticity fields are observed in the evolution of non-circular jets. Generation mechanisms are investigated via Reynolds-averaged (RANS), large-eddy (LES) and direct numerical (DNS) simulations of laminar and turbulent rectangular jets. Complex vortex interactions are found in DNS of laminar jets, but axis-switching is observed only when a single instability mode is present in the incoming mixing layer. With several modes present, the structures are not coherent and no axis-switching occurs, RANS computations also produce no axis-switching. On the other hand, LES of high Reynolds number turbulent jets produce axis-switching even for cases with several instability modes in the mixing layer. Analysis of the source terms of the mean streamwise vorticity equation through post-processing of the instantaneous results shows that, complex interactions of gradients of the normal and shear Reynolds stresses are responsible for the generation of streamwise vorticity which leads to axis-switching. RANS computations confirm these results. k - epsilon turbulence model computations fail to reproduce the phenomenon, whereas algebraic Reynolds stress model (ASM) computations, in which the secondary normal and shear stresses are computed explicitly, succeeded in reproducing the phenomenon accurately.

Northwest Trajectory Analysis Capability: A Platform for Enhancing Computational Biophysics Analysis

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

Peterson, Elena S.; Stephan, Eric G.; Corrigan, Abigail L.

2008-07-30

As computational resources continue to increase, the ability of computational simulations to effectively complement, and in some cases replace, experimentation in scientific exploration also increases. Today, large-scale simulations are recognized as an effective tool for scientific exploration in many disciplines including chemistry and biology. A natural side effect of this trend has been the need for an increasingly complex analytical environment. In this paper, we describe Northwest Trajectory Analysis Capability (NTRAC), an analytical software suite developed to enhance the efficiency of computational biophysics analyses. Our strategy is to layer higher-level services and introduce improved tools within the user’s familiar environmentmore » without preventing researchers from using traditional tools and methods. Our desire is to share these experiences to serve as an example for effectively analyzing data intensive large scale simulation data.« less

EXTENDING THE REALM OF OPTIMIZATION FOR COMPLEX SYSTEMS: UNCERTAINTY, COMPETITION, AND DYNAMICS

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

Shanbhag, Uday V; Basar, Tamer; Meyn, Sean

Research reported addressed these topics: the development of analytical and algorithmic tools for distributed computation of Nash equilibria; synchronization in mean-field oscillator games, with an emphasis on learning and efficiency analysis; questions that combine learning and computation; questions including stochastic and mean-field games; modeling and control in the context of power markets.

Flow induction by pressure forces

NASA Technical Reports Server (NTRS)

Garris, C. A.; Toh, K. H.; Amin, S.

1992-01-01

A dual experimental/computational approach to the fluid mechanics of complex interactions that take place in a rotary-jet ejector is presented. The long-range goal is to perform both detailed flow mapping and finite element computational analysis. The described work represents an initial finding on the experimental mapping program. Test results on the hubless rotary-jet are discussed.

The Roles of Internal Representation and Processing in Problem Solving Involving Insight: A Computational Complexity Perspective

ERIC Educational Resources Information Center

Wareham, Todd

2017-01-01

In human problem solving, there is a wide variation between individuals in problem solution time and success rate, regardless of whether or not this problem solving involves insight. In this paper, we apply computational and parameterized analysis to a plausible formalization of extended representation change theory (eRCT), an integration of…

A Simple and Computationally Efficient Sampling Approach to Covariate Adjustment for Multifactor Dimensionality Reduction Analysis of Epistasis

PubMed Central

Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

2010-01-01

Epistasis or gene-gene interaction is a fundamental component of the genetic architecture of complex traits such as disease susceptibility. Multifactor dimensionality reduction (MDR) was developed as a nonparametric and model-free method to detect epistasis when there are no significant marginal genetic effects. However, in many studies of complex disease, other covariates like age of onset and smoking status could have a strong main effect and may potentially interfere with MDR's ability to achieve its goal. In this paper, we present a simple and computationally efficient sampling method to adjust for covariate effects in MDR. We use simulation to show that after adjustment, MDR has sufficient power to detect true gene-gene interactions. We also compare our method with the state-of-art technique in covariate adjustment. The results suggest that our proposed method performs similarly, but is more computationally efficient. We then apply this new method to an analysis of a population-based bladder cancer study in New Hampshire. PMID:20924193

Optimization Techniques for Analysis of Biological and Social Networks

DTIC Science & Technology

2012-03-28

analyzing a new metaheuristic technique, variable objective search. 3. Experimentation and application: Implement the proposed algorithms , test and fine...alternative mathematical programming formulations, their theoretical analysis, the development of exact algorithms , and heuristics. Originally, clusters...systematic fashion under a unifying theoretical and algorithmic framework. Optimization, Complex Networks, Social Network Analysis, Computational

Intermolecular interaction in nucleobases and dimethyl sulfoxide/water molecules: A DFT, NBO, AIM and NCI analysis.

PubMed

Venkataramanan, Natarajan Sathiyamoorthy; Suvitha, Ambigapathy; Kawazoe, Yoshiyuki

2017-11-01

This study aims to cast light on the physico-chemical nature and energetics of interactions between the nucleobases and water/DMSO molecules which occurs through the non-conventional CH⋯O/N-H bonds using a comprehensive quantum-chemical approach. The computed interaction energies do not show any appreciable change for all the nucleobase-solvent complexes, conforming the experimental findings on the hydration enthalpies. Compared to water, DMSO form complexes with high interaction energies. The quantitative molecular electrostatic potentials display a charge transfer during the complexation. NBO analysis shows the nucleobase-DMSO complexes, have higher stabilization energy values than the nucleobase-water complexes. AIM analysis illustrates that the in the nucleobase-DMSO complexes, SO⋯H-N type interaction have strongest hydrogen bond strength with high E HB values. Furthermore, the Laplacian of electron density and total electron density were negative indicating the partial covalent nature of bonding in these systems, while the other bonds are classified as noncovalent interactions. EDA analysis indicates, the electrostatic interaction is more pronounced in the case of nucleobase-water complexes, while the dispersion contribution is more dominant in nucleobase-DMSO complexes. NCI-RDG analysis proves the existence of strong hydrogen bonding in nucleobase-DMSO complex, which supports the AIM results. Copyright © 2017 Elsevier Inc. All rights reserved.

The Dynamics of the Human Leukocyte Antigen Head Domain Modulates Its Recognition by the T-Cell Receptor.

PubMed

García-Guerrero, Estefanía; Pérez-Simón, José Antonio; Sánchez-Abarca, Luis Ignacio; Díaz-Moreno, Irene; De la Rosa, Miguel A; Díaz-Quintana, Antonio

2016-01-01

Generating the immune response requires the discrimination of peptides presented by the human leukocyte antigen complex (HLA) through the T-cell receptor (TCR). However, how a single amino acid substitution in the antigen bonded to HLA affects the response of T cells remains uncertain. Hence, we used molecular dynamics computations to analyze the molecular interactions between peptides, HLA and TCR. We compared immunologically reactive complexes with non-reactive and weakly reactive complexes. MD trajectories were produced to simulate the behavior of isolated components of the various p-HLA-TCR complexes. Analysis of the fluctuations showed that p-HLA binding barely restrains TCR motions, and mainly affects the CDR3 loops. Conversely, inactive p-HLA complexes displayed significant drop in their dynamics when compared with its free versus ternary forms (p-HLA-TCR). In agreement, the free non-reactive p-HLA complexes showed a lower amount of salt bridges than the responsive ones. This resulted in differences between the electrostatic potentials of reactive and inactive p-HLA species and larger vibrational entropies in non-elicitor complexes. Analysis of the ternary p-HLA-TCR complexes also revealed a larger number of salt bridges in the responsive complexes. To summarize, our computations indicate that the affinity of each p-HLA complex towards TCR is intimately linked to both, the dynamics of its free species and its ability to form specific intermolecular salt-bridges in the ternary complexes. Of outstanding interest is the emerging concept of antigen reactivity involving its interplay with the HLA head sidechain dynamics by rearranging its salt-bridges.

Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks

PubMed Central

Kaltenbacher, Barbara; Hasenauer, Jan

2017-01-01

Mechanistic mathematical modeling of biochemical reaction networks using ordinary differential equation (ODE) models has improved our understanding of small- and medium-scale biological processes. While the same should in principle hold for large- and genome-scale processes, the computational methods for the analysis of ODE models which describe hundreds or thousands of biochemical species and reactions are missing so far. While individual simulations are feasible, the inference of the model parameters from experimental data is computationally too intensive. In this manuscript, we evaluate adjoint sensitivity analysis for parameter estimation in large scale biochemical reaction networks. We present the approach for time-discrete measurement and compare it to state-of-the-art methods used in systems and computational biology. Our comparison reveals a significantly improved computational efficiency and a superior scalability of adjoint sensitivity analysis. The computational complexity is effectively independent of the number of parameters, enabling the analysis of large- and genome-scale models. Our study of a comprehensive kinetic model of ErbB signaling shows that parameter estimation using adjoint sensitivity analysis requires a fraction of the computation time of established methods. The proposed method will facilitate mechanistic modeling of genome-scale cellular processes, as required in the age of omics. PMID:28114351

STARS: An Integrated, Multidisciplinary, Finite-Element, Structural, Fluids, Aeroelastic, and Aeroservoelastic Analysis Computer Program

NASA Technical Reports Server (NTRS)

Gupta, K. K.

1997-01-01

A multidisciplinary, finite element-based, highly graphics-oriented, linear and nonlinear analysis capability that includes such disciplines as structures, heat transfer, linear aerodynamics, computational fluid dynamics, and controls engineering has been achieved by integrating several new modules in the original STARS (STructural Analysis RoutineS) computer program. Each individual analysis module is general-purpose in nature and is effectively integrated to yield aeroelastic and aeroservoelastic solutions of complex engineering problems. Examples of advanced NASA Dryden Flight Research Center projects analyzed by the code in recent years include the X-29A, F-18 High Alpha Research Vehicle/Thrust Vectoring Control System, B-52/Pegasus Generic Hypersonics, National AeroSpace Plane (NASP), SR-71/Hypersonic Launch Vehicle, and High Speed Civil Transport (HSCT) projects. Extensive graphics capabilities exist for convenient model development and postprocessing of analysis results. The program is written in modular form in standard FORTRAN language to run on a variety of computers, such as the IBM RISC/6000, SGI, DEC, Cray, and personal computer; associated graphics codes use OpenGL and IBM/graPHIGS language for color depiction. This program is available from COSMIC, the NASA agency for distribution of computer programs.

Spectrally formulated user-defined element in conventional finite element environment for wave motion analysis in 2-D composite structures

NASA Astrophysics Data System (ADS)

Khalili, Ashkan; Jha, Ratneshwar; Samaratunga, Dulip

2016-11-01

Wave propagation analysis in 2-D composite structures is performed efficiently and accurately through the formulation of a User-Defined Element (UEL) based on the wavelet spectral finite element (WSFE) method. The WSFE method is based on the first-order shear deformation theory which yields accurate results for wave motion at high frequencies. The 2-D WSFE model is highly efficient computationally and provides a direct relationship between system input and output in the frequency domain. The UEL is formulated and implemented in Abaqus (commercial finite element software) for wave propagation analysis in 2-D composite structures with complexities. Frequency domain formulation of WSFE leads to complex valued parameters, which are decoupled into real and imaginary parts and presented to Abaqus as real values. The final solution is obtained by forming a complex value using the real number solutions given by Abaqus. Five numerical examples are presented in this article, namely undamaged plate, impacted plate, plate with ply drop, folded plate and plate with stiffener. Wave motions predicted by the developed UEL correlate very well with Abaqus simulations. The results also show that the UEL largely retains computational efficiency of the WSFE method and extends its ability to model complex features.

AMMOS2: a web server for protein-ligand-water complexes refinement via molecular mechanics.

PubMed

Labbé, Céline M; Pencheva, Tania; Jereva, Dessislava; Desvillechabrol, Dimitri; Becot, Jérôme; Villoutreix, Bruno O; Pajeva, Ilza; Miteva, Maria A

2017-07-03

AMMOS2 is an interactive web server for efficient computational refinement of protein-small organic molecule complexes. The AMMOS2 protocol employs atomic-level energy minimization of a large number of experimental or modeled protein-ligand complexes. The web server is based on the previously developed standalone software AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening). AMMOS utilizes the physics-based force field AMMP sp4 and performs optimization of protein-ligand interactions at five levels of flexibility of the protein receptor. The new version 2 of AMMOS implemented in the AMMOS2 web server allows the users to include explicit water molecules and individual metal ions in the protein-ligand complexes during minimization. The web server provides comprehensive analysis of computed energies and interactive visualization of refined protein-ligand complexes. The ligands are ranked by the minimized binding energies allowing the users to perform additional analysis for drug discovery or chemical biology projects. The web server has been extensively tested on 21 diverse protein-ligand complexes. AMMOS2 minimization shows consistent improvement over the initial complex structures in terms of minimized protein-ligand binding energies and water positions optimization. The AMMOS2 web server is freely available without any registration requirement at the URL: http://drugmod.rpbs.univ-paris-diderot.fr/ammosHome.php. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

AMMOS2: a web server for protein–ligand–water complexes refinement via molecular mechanics

PubMed Central

Labbé, Céline M.; Pencheva, Tania; Jereva, Dessislava; Desvillechabrol, Dimitri; Becot, Jérôme; Villoutreix, Bruno O.; Pajeva, Ilza

2017-01-01

Abstract AMMOS2 is an interactive web server for efficient computational refinement of protein–small organic molecule complexes. The AMMOS2 protocol employs atomic-level energy minimization of a large number of experimental or modeled protein–ligand complexes. The web server is based on the previously developed standalone software AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening). AMMOS utilizes the physics-based force field AMMP sp4 and performs optimization of protein–ligand interactions at five levels of flexibility of the protein receptor. The new version 2 of AMMOS implemented in the AMMOS2 web server allows the users to include explicit water molecules and individual metal ions in the protein–ligand complexes during minimization. The web server provides comprehensive analysis of computed energies and interactive visualization of refined protein–ligand complexes. The ligands are ranked by the minimized binding energies allowing the users to perform additional analysis for drug discovery or chemical biology projects. The web server has been extensively tested on 21 diverse protein–ligand complexes. AMMOS2 minimization shows consistent improvement over the initial complex structures in terms of minimized protein–ligand binding energies and water positions optimization. The AMMOS2 web server is freely available without any registration requirement at the URL: http://drugmod.rpbs.univ-paris-diderot.fr/ammosHome.php. PMID:28486703

Multiscale entropy-based methods for heart rate variability complexity analysis

NASA Astrophysics Data System (ADS)

Silva, Luiz Eduardo Virgilio; Cabella, Brenno Caetano Troca; Neves, Ubiraci Pereira da Costa; Murta Junior, Luiz Otavio

2015-03-01

Physiologic complexity is an important concept to characterize time series from biological systems, which associated to multiscale analysis can contribute to comprehension of many complex phenomena. Although multiscale entropy has been applied to physiological time series, it measures irregularity as function of scale. In this study we purpose and evaluate a set of three complexity metrics as function of time scales. Complexity metrics are derived from nonadditive entropy supported by generation of surrogate data, i.e. SDiffqmax, qmax and qzero. In order to access accuracy of proposed complexity metrics, receiver operating characteristic (ROC) curves were built and area under the curves was computed for three physiological situations. Heart rate variability (HRV) time series in normal sinus rhythm, atrial fibrillation, and congestive heart failure data set were analyzed. Results show that proposed metric for complexity is accurate and robust when compared to classic entropic irregularity metrics. Furthermore, SDiffqmax is the most accurate for lower scales, whereas qmax and qzero are the most accurate when higher time scales are considered. Multiscale complexity analysis described here showed potential to assess complex physiological time series and deserves further investigation in wide context.

CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing

PubMed Central

2011-01-01

Background Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. Results We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. Conclusion The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing. PMID:21878105

Computational analysis of the Phanerochaete chrysosporium v2.0 genome database and mass spectrometry identiWcation of peptides in ligninolytic cultures reveal complex mixtures of secreted proteins

Treesearch

Amber Vanden Wymelenberg; Patrick Minges; Grzegorz Sabat; Diego Martinez; Andrea Aerts; Asaf Salamov; Igor Grigoriev; Harris Shapiro; Nik Putnam; Paula Belinky; Carlos Dosoretz; Jill Gaskell; Phil Kersten; Dan Cullen

2006-01-01

The white-rot basidiomycete Phanerochaete chrysosporium employs extracellular enzymes to completely degrade the major polymers of wood: cellulose, hemicellulose, and lignin. Analysis of a total of 10,048 v2.1 gene models predicts 769 secreted proteins, a substantial increase over the 268 models identified in the earlier database (v1.0). Within the v2.1 ‘computational...

Computational structure analysis of biomacromolecule complexes by interface geometry.

PubMed

Mahdavi, Sedigheh; Salehzadeh-Yazdi, Ali; Mohades, Ali; Masoudi-Nejad, Ali

2013-12-01

The ability to analyze and compare protein-nucleic acid and protein-protein interaction interface has critical importance in understanding the biological function and essential processes occurring in the cells. Since high-resolution three-dimensional (3D) structures of biomacromolecule complexes are available, computational characterizing of the interface geometry become an important research topic in the field of molecular biology. In this study, the interfaces of a set of 180 protein-nucleic acid and protein-protein complexes are computed to understand the principles of their interactions. The weighted Voronoi diagram of the atoms and the Alpha complex has provided an accurate description of the interface atoms. Our method is implemented in the presence and absence of water molecules. A comparison among the three types of interaction interfaces show that RNA-protein complexes have the largest size of an interface. The results show a high correlation coefficient between our method and the PISA server in the presence and absence of water molecules in the Voronoi model and the traditional model based on solvent accessibility and the high validation parameters in comparison to the classical model. Copyright © 2013 Elsevier Ltd. All rights reserved.

Numerical information processing under the global rule expressed by the Euler-Riemann ζ function defined in the complex plane

NASA Astrophysics Data System (ADS)

Chatelin, Françoise

2010-09-01

When nonzero, the ζ function is intimately connected with numerical information processing. Two other functions play a key role, namely, η(s )=∑n ≥1(-1)n +1/ns and λ(s )=∑n ≥01/(2n+1)s. The paper opens on a survey of some of the seminal work of Euler [Mémoires Acad. Sci., Berlin 1768, 83 (1749)] and of the amazing theorem by Voronin [Math. USSR, Izv. 9, 443 (1975)] Then, as a follow-up of Chatelin [Qualitative Computing. A Computational Journey into Nonlinearity (World Scientific, Singapore, in press)], we present a fresh look at the triple (η ,ζ,λ) which suggests an elementary analysis based on the distances of the three complex numbers z, z /2, and 2/z to 0 and 1. This metric approach is used to contextualize any nonlinear computation when it is observed at a point describing a complex plane. The results applied to ζ, η, and λ shed a new epistemological light about the critical line. The suggested interpretation related to ζ carries computational significance.

Experimental and Computational Study of Sonic and Supersonic Jet Plumes

NASA Technical Reports Server (NTRS)

Venkatapathy, E.; Naughton, J. W.; Fletcher, D. G.; Edwards, Thomas A. (Technical Monitor)

1994-01-01

Study of sonic and supersonic jet plumes are relevant to understanding such phenomenon as jet-noise, plume signatures, and rocket base-heating and radiation. Jet plumes are simple to simulate and yet, have complex flow structures such as Mach disks, triple points, shear-layers, barrel shocks, shock-shear-layer interaction, etc. Experimental and computational simulation of sonic and supersonic jet plumes have been performed for under- and over-expanded, axisymmetric plume conditions. The computational simulation compare very well with the experimental observations of schlieren pictures. Experimental data such as temperature measurements with hot-wire probes are yet to be measured and will be compared with computed values. Extensive analysis of the computational simulations presents a clear picture of how the complex flow structure develops and the conditions under which self-similar flow structures evolve. From the computations, the plume structure can be further classified into many sub-groups. In the proposed paper, detail results from the experimental and computational simulations for single, axisymmetric, under- and over-expanded, sonic and supersonic plumes will be compared and the fluid dynamic aspects of flow structures will be discussed.

Understanding the Electronic Structure of 4d Metal Complexes: From Molecular Spinors to L-Edge Spectra of a di-Ru Catalyst

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

Alperovich, Igor; Smolentsev, Grigory; Moonshiram, Dooshaye

2015-09-17

L{sub 2,3}-edge X-ray absorption spectroscopy (XAS) has demonstrated unique capabilities for the analysis of the electronic structure of di-Ru complexes such as the blue dimer cis,cis-[Ru{sub 2}{sup III}O(H{sub 2}O){sub 2}(bpy){sub 4}]{sup 4+} water oxidation catalyst. Spectra of the blue dimer and the monomeric [Ru(NH{sub 3}){sub 6}]{sup 3+} model complex show considerably different splitting of the Ru L{sub 2,3} absorption edge, which reflects changes in the relative energies of the Ru 4d orbitals caused by hybridization with a bridging ligand and spin-orbit coupling effects. To aid the interpretation of spectroscopic data, we developed a new approach, which computes L{sub 2,3}-edges XASmore » spectra as dipole transitions between molecular spinors of 4d transition metal complexes. This allows for careful inclusion of the spin-orbit coupling effects and the hybridization of the Ru 4d and ligand orbitals. The obtained theoretical Ru L{sub 2,3}-edge spectra are in close agreement with experiment. Critically, existing single-electron methods (FEFF, FDMNES) broadly used to simulate XAS could not reproduce the experimental Ru L-edge spectra for the [Ru(NH{sub 3}){sub 6}]{sup 3+} model complex nor for the blue dimer, while charge transfer multiplet (CTM) calculations were not applicable due to the complexity and low symmetry of the blue dimer water oxidation catalyst. We demonstrated that L-edge spectroscopy is informative for analysis of bridging metal complexes. The developed computational approach enhances L-edge spectroscopy as a tool for analysis of the electronic structures of complexes, materials, catalysts, and reactive intermediates with 4d transition metals.« less

Applications of complex systems theory in nursing education, research, and practice.

PubMed

Clancy, Thomas R; Effken, Judith A; Pesut, Daniel

2008-01-01

The clinical and administrative processes in today's healthcare environment are becoming increasingly complex. Multiple providers, new technology, competition, and the growing ubiquity of information all contribute to the notion of health care as a complex system. A complex system (CS) is characterized by a highly connected network of entities (e.g., physical objects, people or groups of people) from which higher order behavior emerges. Research in the transdisciplinary field of CS has focused on the use of computational modeling and simulation as a methodology for analyzing CS behavior. The creation of virtual worlds through computer simulation allows researchers to analyze multiple variables simultaneously and begin to understand behaviors that are common regardless of the discipline. The application of CS principles, mediated through computer simulation, informs nursing practice of the benefits and drawbacks of new procedures, protocols and practices before having to actually implement them. The inclusion of new computational tools and their applications in nursing education is also gaining attention. For example, education in CSs and applied computational applications has been endorsed by The Institute of Medicine, the American Organization of Nurse Executives and the American Association of Colleges of Nursing as essential training of nurse leaders. The purpose of this article is to review current research literature regarding CS science within the context of expert practice and implications for the education of nurse leadership roles. The article focuses on 3 broad areas: CS defined, literature review and exemplars from CS research and applications of CS theory in nursing leadership education. The article also highlights the key role nursing informaticists play in integrating emerging computational tools in the analysis of complex nursing systems.

Effects of Image Compression on Automatic Count of Immunohistochemically Stained Nuclei in Digital Images

PubMed Central

López, Carlos; Lejeune, Marylène; Escrivà, Patricia; Bosch, Ramón; Salvadó, Maria Teresa; Pons, Lluis E.; Baucells, Jordi; Cugat, Xavier; Álvaro, Tomás; Jaén, Joaquín

2008-01-01

This study investigates the effects of digital image compression on automatic quantification of immunohistochemical nuclear markers. We examined 188 images with a previously validated computer-assisted analysis system. A first group was composed of 47 images captured in TIFF format, and other three contained the same images converted from TIFF to JPEG format with 3×, 23× and 46× compression. Counts of TIFF format images were compared with the other three groups. Overall, differences in the count of the images increased with the percentage of compression. Low-complexity images (≤100 cells/field, without clusters or with small-area clusters) had small differences (<5 cells/field in 95–100% of cases) and high-complexity images showed substantial differences (<35–50 cells/field in 95–100% of cases). Compression does not compromise the accuracy of immunohistochemical nuclear marker counts obtained by computer-assisted analysis systems for digital images with low complexity and could be an efficient method for storing these images. PMID:18755997

Identification of Nanoparticle Prototypes and Archetypes.

PubMed

Fernandez, Michael; Barnard, Amanda S

2015-12-22

High-throughput (HT) computational characterization of nanomaterials is poised to accelerate novel material breakthroughs. The number of possible nanomaterials is increasing exponentially along with their complexity, and so statistical and information technology will play a fundamental role in rationalizing nanomaterials HT data. We demonstrate that multivariate statistical analysis of heterogeneous ensembles can identify the truly significant nanoparticles and their most relevant properties. Virtual samples of diamond nanoparticles and graphene nanoflakes are characterized using clustering and archetypal analysis, where we find that saturated particles are defined by their geometry, while nonsaturated nanoparticles are defined by their carbon chemistry. At the complex hull of the nanostructure spaces, a combination of complex archetypes can efficiency describe a large number of members of the ensembles, whereas the regular shapes that are typically assumed to be representative can only describe a small set of the most regular morphologies. This approach provides a route toward the characterization of computationally intractable virtual nanomaterial spaces, which can aid nanomaterials discovery in the foreseen big data scenario.

MORPH-I (Ver 1.0) a software package for the analysis of scanning electron micrograph (binary formatted) images for the assessment of the fractal dimension of enclosed pore surfaces

USGS Publications Warehouse

Mossotti, Victor G.; Eldeeb, A. Raouf; Oscarson, Robert

1998-01-01

MORPH-I is a set of C-language computer programs for the IBM PC and compatible minicomputers. The programs in MORPH-I are used for the fractal analysis of scanning electron microscope and electron microprobe images of pore profiles exposed in cross-section. The program isolates and traces the cross-sectional profiles of exposed pores and computes the Richardson fractal dimension for each pore. Other programs in the set provide for image calibration, display, and statistical analysis of the computed dimensions for highly complex porous materials. Requirements: IBM PC or compatible; minimum 640 K RAM; mathcoprocessor; SVGA graphics board providing mode 103 display.

Modeling of a Sequential Two-Stage Combustor

NASA Technical Reports Server (NTRS)

Hendricks, R. C.; Liu, N.-S.; Gallagher, J. R.; Ryder, R. C.; Brankovic, A.; Hendricks, J. A.

2005-01-01

A sequential two-stage, natural gas fueled power generation combustion system is modeled to examine the fundamental aerodynamic and combustion characteristics of the system. The modeling methodology includes CAD-based geometry definition, and combustion computational fluid dynamics analysis. Graphical analysis is used to examine the complex vortical patterns in each component, identifying sources of pressure loss. The simulations demonstrate the importance of including the rotating high-pressure turbine blades in the computation, as this results in direct computation of combustion within the first turbine stage, and accurate simulation of the flow in the second combustion stage. The direct computation of hot-streaks through the rotating high-pressure turbine stage leads to improved understanding of the aerodynamic relationships between the primary and secondary combustors and the turbomachinery.

Advances in computational design and analysis of airbreathing propulsion systems

NASA Technical Reports Server (NTRS)

Klineberg, John M.

1989-01-01

The development of commercial and military aircraft depends, to a large extent, on engine manufacturers being able to achieve significant increases in propulsion capability through improved component aerodynamics, materials, and structures. The recent history of propulsion has been marked by efforts to develop computational techniques that can speed up the propulsion design process and produce superior designs. The availability of powerful supercomputers, such as the NASA Numerical Aerodynamic Simulator, and the potential for even higher performance offered by parallel computer architectures, have opened the door to the use of multi-dimensional simulations to study complex physical phenomena in propulsion systems that have previously defied analysis or experimental observation. An overview of several NASA Lewis research efforts is provided that are contributing toward the long-range goal of a numerical test-cell for the integrated, multidisciplinary design, analysis, and optimization of propulsion systems. Specific examples in Internal Computational Fluid Mechanics, Computational Structural Mechanics, Computational Materials Science, and High Performance Computing are cited and described in terms of current capabilities, technical challenges, and future research directions.

Agent Interaction with Human Systems in Complex Environments: Requirements for Automating the Function of CapCom in Apollo 17

NASA Technical Reports Server (NTRS)

Clancey, William J.

2003-01-01

A human-centered approach to computer systems design involves reframing analysis in terms of people interacting with each other, not only human-machine interaction. The primary concern is not how people can interact with computers, but how shall we design computers to help people work together? An analysis of astronaut interactions with CapCom on Earth during one traverse of Apollo 17 shows what kind of information was conveyed and what might be automated today. A variety of agent and robotic technologies are proposed that deal with recurrent problems in communication and coordination during the analyzed traverse.

Wave processes in the human cardiovascular system: The measuring complex, computing models, and diagnostic analysis

NASA Astrophysics Data System (ADS)

Ganiev, R. F.; Reviznikov, D. L.; Rogoza, A. N.; Slastushenskiy, Yu. V.; Ukrainskiy, L. E.

2017-03-01

A description of a complex approach to investigation of nonlinear wave processes in the human cardiovascular system based on a combination of high-precision methods of measuring a pulse wave, mathematical methods of processing the empirical data, and methods of direct numerical modeling of hemodynamic processes in an arterial tree is given.

QALMA: A computational toolkit for the analysis of quality protocols for medical linear accelerators in radiation therapy

NASA Astrophysics Data System (ADS)

Rahman, Md Mushfiqur; Lei, Yu; Kalantzis, Georgios

2018-01-01

Quality Assurance (QA) for medical linear accelerator (linac) is one of the primary concerns in external beam radiation Therapy. Continued advancements in clinical accelerators and computer control technology make the QA procedures more complex and time consuming which often, adequate software accompanied with specific phantoms is required. To ameliorate that matter, we introduce QALMA (Quality Assurance for Linac with MATLAB), a MALAB toolkit which aims to simplify the quantitative analysis of QA for linac which includes Star-Shot analysis, Picket Fence test, Winston-Lutz test, Multileaf Collimator (MLC) log file analysis and verification of light & radiation field coincidence test.

An efficient formulation of robot arm dynamics for control and computer simulation

NASA Astrophysics Data System (ADS)

Lee, C. S. G.; Nigam, R.

This paper describes an efficient formulation of the dynamic equations of motion of industrial robots based on the Lagrange formulation of d'Alembert's principle. This formulation, as applied to a PUMA robot arm, results in a set of closed form second order differential equations with cross product terms. They are not as efficient in computation as those formulated by the Newton-Euler method, but provide a better analytical model for control analysis and computer simulation. Computational complexities of this dynamic model together with other models are tabulated for discussion.

Research on phone contacts online status based on mobile cloud computing

NASA Astrophysics Data System (ADS)

Wang, Wen-jinga; Ge, Weib

2013-03-01

Because the limited ability of storage space, CPU processing on mobile phone, it is difficult to realize complex applications on mobile phones, but along with the development of cloud computing, we can place the computing and storage in the clouds, provide users with rich cloud services, helping users complete various function through the browser has become the trend for future mobile communication. This article is taking the mobile phone contacts online status as an example to analysis the development and application of mobile cloud computing.

Texture functions in image analysis: A computationally efficient solution

NASA Technical Reports Server (NTRS)

Cox, S. C.; Rose, J. F.

1983-01-01

A computationally efficient means for calculating texture measurements from digital images by use of the co-occurrence technique is presented. The calculation of the statistical descriptors of image texture and a solution that circumvents the need for calculating and storing a co-occurrence matrix are discussed. The results show that existing efficient algorithms for calculating sums, sums of squares, and cross products can be used to compute complex co-occurrence relationships directly from the digital image input.

Method and system for knowledge discovery using non-linear statistical analysis and a 1st and 2nd tier computer program

DOEpatents

Hively, Lee M [Philadelphia, TN

2011-07-12

The invention relates to a method and apparatus for simultaneously processing different sources of test data into informational data and then processing different categories of informational data into knowledge-based data. The knowledge-based data can then be communicated between nodes in a system of multiple computers according to rules for a type of complex, hierarchical computer system modeled on a human brain.

Analysis and design of algorithm-based fault-tolerant systems

NASA Technical Reports Server (NTRS)

Nair, V. S. Sukumaran

1990-01-01

An important consideration in the design of high performance multiprocessor systems is to ensure the correctness of the results computed in the presence of transient and intermittent failures. Concurrent error detection and correction have been applied to such systems in order to achieve reliability. Algorithm Based Fault Tolerance (ABFT) was suggested as a cost-effective concurrent error detection scheme. The research was motivated by the complexity involved in the analysis and design of ABFT systems. To that end, a matrix-based model was developed and, based on that, algorithms for both the design and analysis of ABFT systems are formulated. These algorithms are less complex than the existing ones. In order to reduce the complexity further, a hierarchical approach is developed for the analysis of large systems.

General Methodology Combining Engineering Optimization of Primary HVAC and R Plants with Decision Analysis Methods--Part II: Uncertainty and Decision Analysis

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

Jiang, Wei; Reddy, T. A.; Gurian, Patrick

2007-01-31

A companion paper to Jiang and Reddy that presents a general and computationally efficient methodology for dyanmic scheduling and optimal control of complex primary HVAC&R plants using a deterministic engineering optimization approach.

Cost Analysis of Online Courses. AIR 2000 Annual Forum Paper.

ERIC Educational Resources Information Center

Milam, John H., Jr.

This paper presents a complex, hybrid, method of cost analysis of online courses, which incorporates data on expenditures; student/course enrollment; departmental consumption/contribution; space utilization/opportunity costs; direct non-personnel costs; computing support; faculty/staff workload; administrative overhead at the department, dean, and…

Verification, Validation and Sensitivity Studies in Computational Biomechanics

PubMed Central

Anderson, Andrew E.; Ellis, Benjamin J.; Weiss, Jeffrey A.

2012-01-01

Computational techniques and software for the analysis of problems in mechanics have naturally moved from their origins in the traditional engineering disciplines to the study of cell, tissue and organ biomechanics. Increasingly complex models have been developed to describe and predict the mechanical behavior of such biological systems. While the availability of advanced computational tools has led to exciting research advances in the field, the utility of these models is often the subject of criticism due to inadequate model verification and validation. The objective of this review is to present the concepts of verification, validation and sensitivity studies with regard to the construction, analysis and interpretation of models in computational biomechanics. Specific examples from the field are discussed. It is hoped that this review will serve as a guide to the use of verification and validation principles in the field of computational biomechanics, thereby improving the peer acceptance of studies that use computational modeling techniques. PMID:17558646

Transonic Flow Field Analysis for Wing-Fuselage Configurations

NASA Technical Reports Server (NTRS)

Boppe, C. W.

1980-01-01

A computational method for simulating the aerodynamics of wing-fuselage configurations at transonic speeds is developed. The finite difference scheme is characterized by a multiple embedded mesh system coupled with a modified or extended small disturbance flow equation. This approach permits a high degree of computational resolution in addition to coordinate system flexibility for treating complex realistic aircraft shapes. To augment the analysis method and permit applications to a wide range of practical engineering design problems, an arbitrary fuselage geometry modeling system is incorporated as well as methodology for computing wing viscous effects. Configuration drag is broken down into its friction, wave, and lift induced components. Typical computed results for isolated bodies, isolated wings, and wing-body combinations are presented. The results are correlated with experimental data. A computer code which employs this methodology is described.

Hot-spot analysis for drug discovery targeting protein-protein interactions.

PubMed

Rosell, Mireia; Fernández-Recio, Juan

2018-04-01

Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

Draper Station Analysis Tool

NASA Technical Reports Server (NTRS)

Bedrossian, Nazareth; Jang, Jiann-Woei; McCants, Edward; Omohundro, Zachary; Ring, Tom; Templeton, Jeremy; Zoss, Jeremy; Wallace, Jonathan; Ziegler, Philip

2011-01-01

Draper Station Analysis Tool (DSAT) is a computer program, built on commercially available software, for simulating and analyzing complex dynamic systems. Heretofore used in designing and verifying guidance, navigation, and control systems of the International Space Station, DSAT has a modular architecture that lends itself to modification for application to spacecraft or terrestrial systems. DSAT consists of user-interface, data-structures, simulation-generation, analysis, plotting, documentation, and help components. DSAT automates the construction of simulations and the process of analysis. DSAT provides a graphical user interface (GUI), plus a Web-enabled interface, similar to the GUI, that enables a remotely located user to gain access to the full capabilities of DSAT via the Internet and Webbrowser software. Data structures are used to define the GUI, the Web-enabled interface, simulations, and analyses. Three data structures define the type of analysis to be performed: closed-loop simulation, frequency response, and/or stability margins. DSAT can be executed on almost any workstation, desktop, or laptop computer. DSAT provides better than an order of magnitude improvement in cost, schedule, and risk assessment for simulation based design and verification of complex dynamic systems.

A Path Analysis of Pre-Service Teachers' Attitudes to Computer Use: Applying and Extending the Technology Acceptance Model in an Educational Context

ERIC Educational Resources Information Center

Teo, Timothy

2010-01-01

The purpose of this study is to examine pre-service teachers' attitudes to computers. This study extends the technology acceptance model (TAM) framework by adding subjective norm, facilitating conditions, and technological complexity as external variables. Results show that the TAM and subjective norm, facilitating conditions, and technological…

Analysis of the Harrier forebody/inlet design using computational techniques

NASA Technical Reports Server (NTRS)

Chow, Chuen-Yen

1993-01-01

Under the support of this Cooperative Agreement, computations of transonic flow past the complex forebody/inlet configuration of the AV-8B Harrier II have been performed. The actual aircraft configuration was measured and its surface and surrounding domain were defined using computational structured grids. The thin-layer Navier-Stokes equations were used to model the flow along with the Chimera embedded multi-grid technique. A fully conservative, alternating direction implicit (ADI), approximately-factored, partially flux-split algorithm was employed to perform the computation. An existing code was altered to conform with the needs of the study, and some special engine face boundary conditions were developed. The algorithm incorporated the Chimera technique and an algebraic turbulence model in order to deal with the embedded multi-grids and viscous governing equations. Comparison with experimental data has yielded good agreement for the simplifications incorporated into the analysis. The aim of the present research was to provide a methodology for the numerical solution of complex, combined external/internal flows. This is the first time-dependent Navier-Stokes solution for a geometry in which the fuselage and inlet share a wall. The results indicate the methodology used here is a viable tool for transonic aircraft modeling.

Anomaly Detection in Moving-Camera Video Sequences Using Principal Subspace Analysis

DOE PAGES

Thomaz, Lucas A.; Jardim, Eric; da Silva, Allan F.; ...

2017-10-16

This study presents a family of algorithms based on sparse decompositions that detect anomalies in video sequences obtained from slow moving cameras. These algorithms start by computing the union of subspaces that best represents all the frames from a reference (anomaly free) video as a low-rank projection plus a sparse residue. Then, they perform a low-rank representation of a target (possibly anomalous) video by taking advantage of both the union of subspaces and the sparse residue computed from the reference video. Such algorithms provide good detection results while at the same time obviating the need for previous video synchronization. However,more » this is obtained at the cost of a large computational complexity, which hinders their applicability. Another contribution of this paper approaches this problem by using intrinsic properties of the obtained data representation in order to restrict the search space to the most relevant subspaces, providing computational complexity gains of up to two orders of magnitude. The developed algorithms are shown to cope well with videos acquired in challenging scenarios, as verified by the analysis of 59 videos from the VDAO database that comprises videos with abandoned objects in a cluttered industrial scenario.« less

Anomaly Detection in Moving-Camera Video Sequences Using Principal Subspace Analysis

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

Thomaz, Lucas A.; Jardim, Eric; da Silva, Allan F.

This study presents a family of algorithms based on sparse decompositions that detect anomalies in video sequences obtained from slow moving cameras. These algorithms start by computing the union of subspaces that best represents all the frames from a reference (anomaly free) video as a low-rank projection plus a sparse residue. Then, they perform a low-rank representation of a target (possibly anomalous) video by taking advantage of both the union of subspaces and the sparse residue computed from the reference video. Such algorithms provide good detection results while at the same time obviating the need for previous video synchronization. However,more » this is obtained at the cost of a large computational complexity, which hinders their applicability. Another contribution of this paper approaches this problem by using intrinsic properties of the obtained data representation in order to restrict the search space to the most relevant subspaces, providing computational complexity gains of up to two orders of magnitude. The developed algorithms are shown to cope well with videos acquired in challenging scenarios, as verified by the analysis of 59 videos from the VDAO database that comprises videos with abandoned objects in a cluttered industrial scenario.« less

Three-dimensional computer simulation of radiostereometric analysis (RSA) in distal radius fractures.

PubMed

Madanat, Rami; Moritz, Niko; Aro, Hannu T

2007-01-01

Physical phantom models have conventionally been used to determine the accuracy and precision of radiostereometric analysis (RSA) in various orthopaedic applications. Using a phantom model of a fracture of the distal radius it has previously been shown that RSA is a highly accurate and precise method for measuring both translation and rotation in three-dimensions (3-D). The main shortcoming of a physical phantom model is its inability to mimic complex 3-D motion. The goal of this study was to create a realistic computer model for preoperative planning of RSA studies and to test the accuracy of RSA in measuring complex movements in fractures of the distal radius using this new model. The 3-D computer model was created from a set of tomographic scans. The simulation of the radiographic imaging was performed using ray-tracing software (POV-Ray). RSA measurements were performed according to standard protocol. Using a two-part fracture model (AO/ASIF type A2), it was found that for simple movements in one axis, translations in the range of 25microm-2mm could be measured with an accuracy of +/-2microm. Rotations ranging from 16 degrees to 2 degrees could be measured with an accuracy of +/-0.015 degrees . Using a three-part fracture model the corresponding values of accuracy were found to be +/-4microm and +/-0.031 degrees for translation and rotation, respectively. For complex 3-D motion in a three-part fracture model (AO/ASIF type C1) the accuracy was +/-6microm for translation and +/-0.120 degrees for rotation. The use of 3-D computer modelling can provide a method for preoperative planning of RSA studies in complex fractures of the distal radius and in other clinical situations in which the RSA method is applicable.

An affinity-structure database of helix-turn-helix: DNA complexes with a universal coordinate system.

PubMed

AlQuraishi, Mohammed; Tang, Shengdong; Xia, Xide

2015-11-19

Molecular interactions between proteins and DNA molecules underlie many cellular processes, including transcriptional regulation, chromosome replication, and nucleosome positioning. Computational analyses of protein-DNA interactions rely on experimental data characterizing known protein-DNA interactions structurally and biochemically. While many databases exist that contain either structural or biochemical data, few integrate these two data sources in a unified fashion. Such integration is becoming increasingly critical with the rapid growth of structural and biochemical data, and the emergence of algorithms that rely on the synthesis of multiple data types to derive computational models of molecular interactions. We have developed an integrated affinity-structure database in which the experimental and quantitative DNA binding affinities of helix-turn-helix proteins are mapped onto the crystal structures of the corresponding protein-DNA complexes. This database provides access to: (i) protein-DNA structures, (ii) quantitative summaries of protein-DNA binding affinities using position weight matrices, and (iii) raw experimental data of protein-DNA binding instances. Critically, this database establishes a correspondence between experimental structural data and quantitative binding affinity data at the single basepair level. Furthermore, we present a novel alignment algorithm that structurally aligns the protein-DNA complexes in the database and creates a unified residue-level coordinate system for comparing the physico-chemical environments at the interface between complexes. Using this unified coordinate system, we compute the statistics of atomic interactions at the protein-DNA interface of helix-turn-helix proteins. We provide an interactive website for visualization, querying, and analyzing this database, and a downloadable version to facilitate programmatic analysis. This database will facilitate the analysis of protein-DNA interactions and the development of programmatic computational methods that capitalize on integration of structural and biochemical datasets. The database can be accessed at http://ProteinDNA.hms.harvard.edu.

Turbomachinery computational fluid dynamics: asymptotes and paradigm shifts.

PubMed

Dawes, W N

2007-10-15

This paper reviews the development of computational fluid dynamics (CFD) specifically for turbomachinery simulations and with a particular focus on application to problems with complex geometry. The review is structured by considering this development as a series of paradigm shifts, followed by asymptotes. The original S1-S2 blade-blade-throughflow model is briefly described, followed by the development of two-dimensional then three-dimensional blade-blade analysis. This in turn evolved from inviscid to viscous analysis and then from steady to unsteady flow simulations. This development trajectory led over a surprisingly small number of years to an accepted approach-a 'CFD orthodoxy'. A very important current area of intense interest and activity in turbomachinery simulation is in accounting for real geometry effects, not just in the secondary air and turbine cooling systems but also associated with the primary path. The requirements here are threefold: capturing and representing these geometries in a computer model; making rapid design changes to these complex geometries; and managing the very large associated computational models on PC clusters. Accordingly, the challenges in the application of the current CFD orthodoxy to complex geometries are described in some detail. The main aim of this paper is to argue that the current CFD orthodoxy is on a new asymptote and is not in fact suited for application to complex geometries and that a paradigm shift must be sought. In particular, the new paradigm must be geometry centric and inherently parallel without serial bottlenecks. The main contribution of this paper is to describe such a potential paradigm shift, inspired by the animation industry, based on a fundamental shift in perspective from explicit to implicit geometry and then illustrate this with a number of applications to turbomachinery.

In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms, a State-of-the-art (STAR) Report

DOE PAGES

Bethel, EW; Bauer, A; Abbasi, H; ...

2016-06-10

The considerable interest in the high performance computing (HPC) community regarding analyzing and visualization data without first writing to disk, i.e., in situ processing, is due to several factors. First is an I/O cost savings, where data is analyzed /visualized while being generated, without first storing to a filesystem. Second is the potential for increased accuracy, where fine temporal sampling of transient analysis might expose some complex behavior missed in coarse temporal sampling. Third is the ability to use all available resources, CPU’s and accelerators, in the computation of analysis products. This STAR paper brings together researchers, developers and practitionersmore » using in situ methods in extreme-scale HPC with the goal to present existing methods, infrastructures, and a range of computational science and engineering applications using in situ analysis and visualization.« less

Combinatorial complexity of pathway analysis in metabolic networks.

PubMed

Klamt, Steffen; Stelling, Jörg

2002-01-01

Elementary flux mode analysis is a promising approach for a pathway-oriented perspective of metabolic networks. However, in larger networks it is hampered by the combinatorial explosion of possible routes. In this work we give some estimations on the combinatorial complexity including theoretical upper bounds for the number of elementary flux modes in a network of a given size. In a case study, we computed the elementary modes in the central metabolism of Escherichia coli while utilizing four different substrates. Interestingly, although the number of modes occurring in this complex network can exceed half a million, it is still far below the upper bound. Hence, to a certain extent, pathway analysis of central catabolism is feasible to assess network properties such as flexibility and functionality.

Software analysis handbook: Software complexity analysis and software reliability estimation and prediction

NASA Technical Reports Server (NTRS)

Lee, Alice T.; Gunn, Todd; Pham, Tuan; Ricaldi, Ron

1994-01-01

This handbook documents the three software analysis processes the Space Station Software Analysis team uses to assess space station software, including their backgrounds, theories, tools, and analysis procedures. Potential applications of these analysis results are also presented. The first section describes how software complexity analysis provides quantitative information on code, such as code structure and risk areas, throughout the software life cycle. Software complexity analysis allows an analyst to understand the software structure, identify critical software components, assess risk areas within a software system, identify testing deficiencies, and recommend program improvements. Performing this type of analysis during the early design phases of software development can positively affect the process, and may prevent later, much larger, difficulties. The second section describes how software reliability estimation and prediction analysis, or software reliability, provides a quantitative means to measure the probability of failure-free operation of a computer program, and describes the two tools used by JSC to determine failure rates and design tradeoffs between reliability, costs, performance, and schedule.

Parallelization of Nullspace Algorithm for the computation of metabolic pathways

PubMed Central

Jevremović, Dimitrije; Trinh, Cong T.; Srienc, Friedrich; Sosa, Carlos P.; Boley, Daniel

2011-01-01

Elementary mode analysis is a useful metabolic pathway analysis tool in understanding and analyzing cellular metabolism, since elementary modes can represent metabolic pathways with unique and minimal sets of enzyme-catalyzed reactions of a metabolic network under steady state conditions. However, computation of the elementary modes of a genome- scale metabolic network with 100–1000 reactions is very expensive and sometimes not feasible with the commonly used serial Nullspace Algorithm. In this work, we develop a distributed memory parallelization of the Nullspace Algorithm to handle efficiently the computation of the elementary modes of a large metabolic network. We give an implementation in C++ language with the support of MPI library functions for the parallel communication. Our proposed algorithm is accompanied with an analysis of the complexity and identification of major bottlenecks during computation of all possible pathways of a large metabolic network. The algorithm includes methods to achieve load balancing among the compute-nodes and specific communication patterns to reduce the communication overhead and improve efficiency. PMID:22058581

Computational analysis of forebody tangential slot blowing

NASA Technical Reports Server (NTRS)

Gee, Ken; Agosta-Greenman, Roxana M.; Rizk, Yehia M.; Schiff, Lewis B.; Cummings, Russell M.

1994-01-01

An overview of the computational effort to analyze forebody tangential slot blowing is presented. Tangential slot blowing generates side force and yawing moment which may be used to control an aircraft flying at high-angle-of-attack. Two different geometries are used in the analysis: (1) The High Alpha Research Vehicle; and (2) a generic chined forebody. Computations using the isolated F/A-18 forebody are obtained at full-scale wind tunnel test conditions for direct comparison with available experimental data. The effects of over- and under-blowing on force and moment production are analyzed. Time-accurate solutions using the isolated forebody are obtained to study the force onset timelag of tangential slot blowing. Computations using the generic chined forebody are obtained at experimental wind tunnel conditions, and the results compared with available experimental data. This computational analysis compliments the experimental results and provides a detailed understanding of the effects of tangential slot blowing on the flow field about simple and complex geometries.

A Scheme for Text Analysis Using Fortran.

ERIC Educational Resources Information Center

Koether, Mary E.; Coke, Esther U.

Using string-manipulation algorithms, FORTRAN computer programs were designed for analysis of written material. The programs measure length of a text and its complexity in terms of the average length of words and sentences, map the occurrences of keywords or phrases, calculate word frequency distribution and certain indicators of style. Trials of…

Abstraction and model evaluation in category learning.

PubMed

Vanpaemel, Wolf; Storms, Gert

2010-05-01

Thirty previously published data sets, from seminal category learning tasks, are reanalyzed using the varying abstraction model (VAM). Unlike a prototype-versus-exemplar analysis, which focuses on extreme levels of abstraction only, a VAM analysis also considers the possibility of partial abstraction. Whereas most data sets support no abstraction when only the extreme possibilities are considered, we show that evidence for abstraction can be provided using the broader view on abstraction provided by the VAM. The present results generalize earlier demonstrations of partial abstraction (Vanpaemel & Storms, 2008), in which only a small number of data sets was analyzed. Following the dominant modus operandi in category learning research, Vanpaemel and Storms evaluated the models on their best fit, a practice known to ignore the complexity of the models under consideration. In the present study, in contrast, model evaluation not only relies on the maximal likelihood, but also on the marginal likelihood, which is sensitive to model complexity. Finally, using a large recovery study, it is demonstrated that, across the 30 data sets, complexity differences between the models in the VAM family are small. This indicates that a (computationally challenging) complexity-sensitive model evaluation method is uncalled for, and that the use of a (computationally straightforward) complexity-insensitive model evaluation method is justified.

Channel Model Optimization with Reflection Residual Component for Indoor MIMO-VLC System

NASA Astrophysics Data System (ADS)

Chen, Yong; Li, Tengfei; Liu, Huanlin; Li, Yichao

2017-12-01

A fast channel modeling method is studied to solve the problem of reflection channel gain for multiple input multiple output-visible light communications (MIMO-VLC) in the paper. For reducing the computational complexity when associating with the reflection times, no more than 3 reflections are taken into consideration in VLC. We think that higher order reflection link consists of corresponding many times line of sight link and firstly present reflection residual component to characterize higher reflection (more than 2 reflections). We perform computer simulation results for point-to-point channel impulse response, receiving optical power and receiving signal to noise ratio. Based on theoretical analysis and simulation results, the proposed method can effectively reduce the computational complexity of higher order reflection in channel modeling.

Absolute Configuration of 3-METHYLCYCLOHEXANONE by Chiral Tag Rotational Spectroscopy and Vibrational Circular Dichroism

NASA Astrophysics Data System (ADS)

Evangelisti, Luca; Holdren, Martin S.; Mayer, Kevin J.; Smart, Taylor; West, Channing; Pate, Brooks

2017-06-01

The absolute configuration of 3-methylcyclohexanone was established by chiral tag rotational spectroscopy measurements using 3-butyn-2-ol as the tag partner. This molecule was chosen because it is a benchmark measurement for vibrational circular dichroism (VCD). A comparison of the analysis approaches of chiral tag rotational spectroscopy and VCD will be presented. One important issue in chiral analysis by both methods is the conformational flexibility of the molecule being analyzed. The analysis of conformational composition of samples will be illustrated. In this case, the high spectral resolution of molecular rotational spectroscopy and potential for spectral simplification by conformational cooling in the pulsed jet expansion are advantages for chiral tag spectroscopy. The computational chemistry requirements for the two methods will also be discussed. In this case, the need to perform conformer searches for weakly bound complexes and to perform reasonably high level quantum chemistry geometry optimizations on these complexes makes the computational time requirements less favorable for chiral tag rotational spectroscopy. Finally, the issue of reliability of the determination of the absolute configuration will be considered. In this case, rotational spectroscopy offers a "gold standard" analysis method through the determination of the ^{13}C-subsitution structure of the complex between 3-methylcyclohexanone and an enantiopure sample of the 3-butyn-2-ol tag.

Applications of Phase-Based Motion Processing

NASA Technical Reports Server (NTRS)

Branch, Nicholas A.; Stewart, Eric C.

2018-01-01

Image pyramids provide useful information in determining structural response at low cost using commercially available cameras. The current effort applies previous work on the complex steerable pyramid to analyze and identify imperceptible linear motions in video. Instead of implicitly computing motion spectra through phase analysis of the complex steerable pyramid and magnifying the associated motions, instead present a visual technique and the necessary software to display the phase changes of high frequency signals within video. The present technique quickly identifies regions of largest motion within a video with a single phase visualization and without the artifacts of motion magnification, but requires use of the computationally intensive Fourier transform. While Riesz pyramids present an alternative to the computationally intensive complex steerable pyramid for motion magnification, the Riesz formulation contains significant noise, and motion magnification still presents large amounts of data that cannot be quickly assessed by the human eye. Thus, user-friendly software is presented for quickly identifying structural response through optical flow and phase visualization in both Python and MATLAB.

GESA--a two-dimensional processing system using knowledge base techniques.

PubMed

Rowlands, D G; Flook, A; Payne, P I; van Hoff, A; Niblett, T; McKee, S

1988-12-01

The successful analysis of two-dimensional (2-D) polyacrylamide electrophoresis gels demands considerable experience and understanding of the protein system under investigation as well as knowledge of the separation technique itself. The present work concerns the development of a computer system for analysing 2-D electrophoretic separations which incorporates concepts derived from artificial intelligence research such that non-experts can use the technique as a diagnostic or identification tool. Automatic analysis of 2-D gel separations has proved to be extremely difficult using statistical methods. Non-reproducibility of gel separations is also difficult to overcome using automatic systems. However, the human eye is extremely good at recognising patterns in images, and human intervention in semi-automatic computer systems can reduce the computational complexities of fully automatic systems. Moreover, the expertise and understanding of an "expert" is invaluable in reducing system complexity if it can be encapsulated satisfactorily in an expert system. The combination of user-intervention in the computer system together with the encapsulation of expert knowledge characterises the present system. The domain within which the system has been developed is that of wheat grain storage proteins (gliadins) which exhibit polymorphism to such an extent that cultivars can be uniquely identified by their gliadin patterns. The system can be adapted to other domains where a range of polymorpic protein sub-units exist. In its generalised form, the system can also be used for comparing more complex 2-D gel electrophoretic separations.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics.

PubMed

Wu, Xiao-Lin; Sun, Chuanyu; Beissinger, Timothy M; Rosa, Guilherme Jm; Weigel, Kent A; Gatti, Natalia de Leon; Gianola, Daniel

2012-09-25

Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics

PubMed Central

2012-01-01

Background Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Results Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Conclusions Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs. PMID:23009363

Computer-aided analysis of Skylab scanner data for land use mapping, forestry and water resource applications

NASA Technical Reports Server (NTRS)

Hoffer, R. M.

1975-01-01

Skylab data were obtained over a mountainous test site containing a complex association of cover types and rugged topography. The application of computer-aided analysis techniques to the multispectral scanner data produced a number of significant results. Techniques were developed to digitally overlay topographic data (elevation, slope, and aspect) onto the S-192 MSS data to provide a method for increasing the effectiveness and accuracy of computer-aided analysis techniques for cover type mapping. The S-192 MSS data were analyzed using computer techniques developed at Laboratory for Applications of Remote Sensing (LARS), Purdue University. Land use maps, forest cover type maps, snow cover maps, and area tabulations were obtained and evaluated. These results compared very well with information obtained by conventional techniques. Analysis of the spectral characteristics of Skylab data has conclusively proven the value of the middle infrared portion of the spectrum (about 1.3-3.0 micrometers), a wavelength region not previously available in multispectral satellite data.

Sonic and Supersonic Jet Plumes

NASA Technical Reports Server (NTRS)

Venkatapathy, E.; Naughton, J. W.; Flethcher, D. G.; Edwards, Thomas A. (Technical Monitor)

1994-01-01

Study of sonic and supersonic jet plumes are relevant to understanding such phenomenon as jet-noise, plume signatures, and rocket base-heating and radiation. Jet plumes are simple to simulate and yet, have complex flow structures such as Mach disks, triple points, shear-layers, barrel shocks, shock- shear- layer interaction, etc. Experimental and computational simulation of sonic and supersonic jet plumes have been performed for under- and over-expanded, axisymmetric plume conditions. The computational simulation compare very well with the experimental observations of schlieren pictures. Experimental data such as temperature measurements with hot-wire probes are yet to be measured and will be compared with computed values. Extensive analysis of the computational simulations presents a clear picture of how the complex flow structure develops and the conditions under which self-similar flow structures evolve. From the computations, the plume structure can be further classified into many sub-groups. In the proposed paper, detail results from the experimental and computational simulations for single, axisymmetric, under- and over-expanded, sonic and supersonic plumes will be compared and the fluid dynamic aspects of flow structures will be discussed.

Characterization and analysis of Porous, Brittle solid structures by X-ray micro computed tomography

NASA Astrophysics Data System (ADS)

Lin, C. L.; Videla, A. R.; Yu, Q.; Miller, J. D.

2010-12-01

The internal structure of porous, brittle solid structures, such as porous rock, foam metal and wallboard, is extremely complex. For example, in the case of wallboard, the air bubble size and the thickness/composition of the wall structure are spatial parameters that vary significantly and influence mechanical, thermal, and acoustical properties. In this regard, the complex geometry and the internal texture of material, such as wallboard, is characterized and analyzed in 3-D using cone beam x-ray micro computed tomography. Geometrical features of the porous brittle structure are quantitatively analyzed based on calibration of the x-ray linear attenuation coefficient, use of a 3-D watershed algorithm, and use of a 3-D skeletonization procedure. Several examples of the 3-D analysis for porous, wallboard structures are presented and the results discussed.

Integrating GIS and ABM to Explore Spatiotemporal Dynamics

NASA Astrophysics Data System (ADS)

Sun, M.; Jiang, Y.; Yang, C.

2013-12-01

Agent-based modeling as a methodology for the bottom-up exploration with the account of adaptive behavior and heterogeneity of system components can help discover the development and pattern of the complex social and environmental system. However, ABM is a computationally intensive process especially when the number of system components becomes large and the agent-agent/agent-environmental interaction is modeled very complex. Most of traditional ABM frameworks developed based on CPU do not have a satisfying computing capacity. To address the problem and as the emergence of advanced techniques, GPU computing with CUDA can provide powerful parallel structure to enable the complex simulation of spatiotemporal dynamics. In this study, we first develop a GPU-based ABM system. Secondly, in order to visualize the dynamics generated from the movement of agent and the change of agent/environmental attributes during the simulation, we integrate GIS into the ABM system. Advanced geovisualization technologies can be utilized for representing the spatiotemporal change events, such as proper 2D/3D maps with state-of-the-art symbols, space-time cube and multiple layers each of which presents pattern in one time-stamp, etc. Thirdly, visual analytics which include interactive tools (e.g. grouping, filtering, linking, etc.) is included in our ABM-GIS system to help users conduct real-time data exploration during the progress of simulation. Analysis like flow analysis and spatial cluster analysis can be integrated according to the geographical problem we want to explore.

A network-based multi-target computational estimation scheme for anticoagulant activities of compounds.

PubMed

Li, Qian; Li, Xudong; Li, Canghai; Chen, Lirong; Song, Jun; Tang, Yalin; Xu, Xiaojie

2011-03-22

Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking.

A Network-Based Multi-Target Computational Estimation Scheme for Anticoagulant Activities of Compounds

PubMed Central

Li, Canghai; Chen, Lirong; Song, Jun; Tang, Yalin; Xu, Xiaojie

2011-01-01

Background Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. Methodology We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. Conclusions This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking. PMID:21445339

A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling

NASA Astrophysics Data System (ADS)

Dai, Heng; Chen, Xingyuan; Ye, Ming; Song, Xuehang; Zachara, John M.

2017-05-01

Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study, we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multilayer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially distributed input variables.

A Geostatistics-Informed Hierarchical Sensitivity Analysis Method for Complex Groundwater Flow and Transport Modeling

NASA Astrophysics Data System (ADS)

Dai, H.; Chen, X.; Ye, M.; Song, X.; Zachara, J. M.

2017-12-01

Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multi-layer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed input variables.

Information Leakage Analysis by Abstract Interpretation

NASA Astrophysics Data System (ADS)

Zanioli, Matteo; Cortesi, Agostino

Protecting the confidentiality of information stored in a computer system or transmitted over a public network is a relevant problem in computer security. The approach of information flow analysis involves performing a static analysis of the program with the aim of proving that there will not be leaks of sensitive information. In this paper we propose a new domain that combines variable dependency analysis, based on propositional formulas, and variables' value analysis, based on polyhedra. The resulting analysis is strictly more accurate than the state of the art abstract interpretation based analyses for information leakage detection. Its modular construction allows to deal with the tradeoff between efficiency and accuracy by tuning the granularity of the abstraction and the complexity of the abstract operators.

Computational complexity of algorithms for sequence comparison, short-read assembly and genome alignment.

PubMed

Baichoo, Shakuntala; Ouzounis, Christos A

A multitude of algorithms for sequence comparison, short-read assembly and whole-genome alignment have been developed in the general context of molecular biology, to support technology development for high-throughput sequencing, numerous applications in genome biology and fundamental research on comparative genomics. The computational complexity of these algorithms has been previously reported in original research papers, yet this often neglected property has not been reviewed previously in a systematic manner and for a wider audience. We provide a review of space and time complexity of key sequence analysis algorithms and highlight their properties in a comprehensive manner, in order to identify potential opportunities for further research in algorithm or data structure optimization. The complexity aspect is poised to become pivotal as we will be facing challenges related to the continuous increase of genomic data on unprecedented scales and complexity in the foreseeable future, when robust biological simulation at the cell level and above becomes a reality. Copyright © 2017 Elsevier B.V. All rights reserved.

Aeropropulsion 1987. Session 2: Aeropropulsion Structures Research

NASA Technical Reports Server (NTRS)

1987-01-01

Aeropropulsion systems present unique problems to the structural engineer. The extremes in operating temperatures, rotational effects, and behaviors of advanced material systems combine into complexities that require advances in many scientific disciplines involved in structural analysis and design procedures. This session provides an overview of the complexities of aeropropulsion structures and the theoretical, computational, and experimental research conducted to achieve the needed advances.

Utilisation of three-dimensional printed heart models for operative planning of complex congenital heart defects.

PubMed

Olejník, Peter; Nosal, Matej; Havran, Tomas; Furdova, Adriana; Cizmar, Maros; Slabej, Michal; Thurzo, Andrej; Vitovic, Pavol; Klvac, Martin; Acel, Tibor; Masura, Jozef

2017-01-01

To evaluate the accuracy of the three-dimensional (3D) printing of cardiovascular structures. To explore whether utilisation of 3D printed heart replicas can improve surgical and catheter interventional planning in patients with complex congenital heart defects. Between December 2014 and November 2015 we fabricated eight cardiovascular models based on computed tomography data in patients with complex spatial anatomical relationships of cardiovascular structures. A Bland-Altman analysis was used to assess the accuracy of 3D printing by comparing dimension measurements at analogous anatomical locations between the printed models and digital imagery data, as well as between printed models and in vivo surgical findings. The contribution of 3D printed heart models for perioperative planning improvement was evaluated in the four most representative patients. Bland-Altman analysis confirmed the high accuracy of 3D cardiovascular printing. Each printed model offered an improved spatial anatomical orientation of cardiovascular structures. Current 3D printers can produce authentic copies of patients` cardiovascular systems from computed tomography data. The use of 3D printed models can facilitate surgical or catheter interventional procedures in patients with complex congenital heart defects due to better preoperative planning and intraoperative orientation.

Probabilistic analysis of tsunami hazards

USGS Publications Warehouse

Geist, E.L.; Parsons, T.

2006-01-01

Determining the likelihood of a disaster is a key component of any comprehensive hazard assessment. This is particularly true for tsunamis, even though most tsunami hazard assessments have in the past relied on scenario or deterministic type models. We discuss probabilistic tsunami hazard analysis (PTHA) from the standpoint of integrating computational methods with empirical analysis of past tsunami runup. PTHA is derived from probabilistic seismic hazard analysis (PSHA), with the main difference being that PTHA must account for far-field sources. The computational methods rely on numerical tsunami propagation models rather than empirical attenuation relationships as in PSHA in determining ground motions. Because a number of source parameters affect local tsunami runup height, PTHA can become complex and computationally intensive. Empirical analysis can function in one of two ways, depending on the length and completeness of the tsunami catalog. For site-specific studies where there is sufficient tsunami runup data available, hazard curves can primarily be derived from empirical analysis, with computational methods used to highlight deficiencies in the tsunami catalog. For region-wide analyses and sites where there are little to no tsunami data, a computationally based method such as Monte Carlo simulation is the primary method to establish tsunami hazards. Two case studies that describe how computational and empirical methods can be integrated are presented for Acapulco, Mexico (site-specific) and the U.S. Pacific Northwest coastline (region-wide analysis).

In Silico Analysis for the Study of Botulinum Toxin Structure

NASA Astrophysics Data System (ADS)

Suzuki, Tomonori; Miyazaki, Satoru

2010-01-01

Protein-protein interactions play many important roles in biological function. Knowledge of protein-protein complex structure is required for understanding the function. The determination of protein-protein complex structure by experimental studies remains difficult, therefore computational prediction of protein structures by structure modeling and docking studies is valuable method. In addition, MD simulation is also one of the most popular methods for protein structure modeling and characteristics. Here, we attempt to predict protein-protein complex structure and property using some of bioinformatic methods, and we focus botulinum toxin complex as target structure.

Lewis hybrid computing system, users manual

NASA Technical Reports Server (NTRS)

Bruton, W. M.; Cwynar, D. S.

1979-01-01

The Lewis Research Center's Hybrid Simulation Lab contains a collection of analog, digital, and hybrid (combined analog and digital) computing equipment suitable for the dynamic simulation and analysis of complex systems. This report is intended as a guide to users of these computing systems. The report describes the available equipment' and outlines procedures for its use. Particular is given to the operation of the PACER 100 digital processor. System software to accomplish the usual digital tasks such as compiling, editing, etc. and Lewis-developed special purpose software are described.

An Object-Oriented Approach to Writing Computational Electromagnetics Codes

NASA Technical Reports Server (NTRS)

Zimmerman, Martin; Mallasch, Paul G.

1996-01-01

Presently, most computer software development in the Computational Electromagnetics (CEM) community employs the structured programming paradigm, particularly using the Fortran language. Other segments of the software community began switching to an Object-Oriented Programming (OOP) paradigm in recent years to help ease design and development of highly complex codes. This paper examines design of a time-domain numerical analysis CEM code using the OOP paradigm, comparing OOP code and structured programming code in terms of software maintenance, portability, flexibility, and speed.

Segmentation of Unstructured Datasets

NASA Technical Reports Server (NTRS)

Bhat, Smitha

1996-01-01

Datasets generated by computer simulations and experiments in Computational Fluid Dynamics tend to be extremely large and complex. It is difficult to visualize these datasets using standard techniques like Volume Rendering and Ray Casting. Object Segmentation provides a technique to extract and quantify regions of interest within these massive datasets. This thesis explores basic algorithms to extract coherent amorphous regions from two-dimensional and three-dimensional scalar unstructured grids. The techniques are applied to datasets from Computational Fluid Dynamics and from Finite Element Analysis.

CFD Analysis and Design Optimization Using Parallel Computers

NASA Technical Reports Server (NTRS)

Martinelli, Luigi; Alonso, Juan Jose; Jameson, Antony; Reuther, James

1997-01-01

A versatile and efficient multi-block method is presented for the simulation of both steady and unsteady flow, as well as aerodynamic design optimization of complete aircraft configurations. The compressible Euler and Reynolds Averaged Navier-Stokes (RANS) equations are discretized using a high resolution scheme on body-fitted structured meshes. An efficient multigrid implicit scheme is implemented for time-accurate flow calculations. Optimum aerodynamic shape design is achieved at very low cost using an adjoint formulation. The method is implemented on parallel computing systems using the MPI message passing interface standard to ensure portability. The results demonstrate that, by combining highly efficient algorithms with parallel computing, it is possible to perform detailed steady and unsteady analysis as well as automatic design for complex configurations using the present generation of parallel computers.

Rotordynamic analysis using the Complex Transfer Matrix: An application to elastomer supports using the viscoelastic correspondence principle

NASA Astrophysics Data System (ADS)

Varney, Philip; Green, Itzhak

2014-11-01

Numerous methods are available to calculate rotordynamic whirl frequencies, including analytic methods, finite element analysis, and the transfer matrix method. The typical real-valued transfer matrix (RTM) suffers from several deficiencies, including lengthy computation times and the inability to distinguish forward and backward whirl. Though application of complex coordinates in rotordynamic analysis is not novel per se, specific advantages gained from using such coordinates in a transfer matrix analysis have yet to be elucidated. The present work employs a complex coordinate redefinition of the transfer matrix to obtain reduced forms of the elemental transfer matrices in inertial and rotating reference frames, including external stiffness and damping. Application of the complex-valued state variable redefinition results in a reduction of the 8×8 RTM to the 4×4 Complex Transfer Matrix (CTM). The CTM is advantageous in that it intrinsically separates forward and backward whirl, eases symbolic manipulation by halving the transfer matrices’ dimension, and provides significant improvement in computation time. A symbolic analysis is performed on a simple overhung rotor to demonstrate the mathematical motivation for whirl frequency separation. The CTM's utility is further shown by analyzing a rotordynamic system supported by viscoelastic elastomer rings. Viscoelastic elastomer ring supports can provide significant damping while reducing the cost and complexity associated with conventional components such as squeeze film dampers. The stiffness and damping of a viscoelastic damper ring are determined herein as a function of whirl frequency using the viscoelastic correspondence principle and a constitutive fractional calculus viscoelasticity model. The CTM is then employed to obtain the characteristic equation, where the whirl frequency dependent stiffness and damping of the elastomer supports are included. The Campbell diagram is shown, demonstrating the CTM's ability to intrinsically separate synchronous whirl direction for a non-trivial rotordynamic system. Good agreement is found between the CTM results and previously obtained analytic and experimental results for the elastomer ring supported rotordynamic system.

An efficient pseudomedian filter for tiling microrrays.

PubMed

Royce, Thomas E; Carriero, Nicholas J; Gerstein, Mark B

2007-06-07

Tiling microarrays are becoming an essential technology in the functional genomics toolbox. They have been applied to the tasks of novel transcript identification, elucidation of transcription factor binding sites, detection of methylated DNA and several other applications in several model organisms. These experiments are being conducted at increasingly finer resolutions as the microarray technology enjoys increasingly greater feature densities. The increased densities naturally lead to increased data analysis requirements. Specifically, the most widely employed algorithm for tiling array analysis involves smoothing observed signals by computing pseudomedians within sliding windows, a O(n2logn) calculation in each window. This poor time complexity is an issue for tiling array analysis and could prove to be a real bottleneck as tiling microarray experiments become grander in scope and finer in resolution. We therefore implemented Monahan's HLQEST algorithm that reduces the runtime complexity for computing the pseudomedian of n numbers to O(nlogn) from O(n2logn). For a representative tiling microarray dataset, this modification reduced the smoothing procedure's runtime by nearly 90%. We then leveraged the fact that elements within sliding windows remain largely unchanged in overlapping windows (as one slides across genomic space) to further reduce computation by an additional 43%. This was achieved by the application of skip lists to maintaining a sorted list of values from window to window. This sorted list could be maintained with simple O(log n) inserts and deletes. We illustrate the favorable scaling properties of our algorithms with both time complexity analysis and benchmarking on synthetic datasets. Tiling microarray analyses that rely upon a sliding window pseudomedian calculation can require many hours of computation. We have eased this requirement significantly by implementing efficient algorithms that scale well with genomic feature density. This result not only speeds the current standard analyses, but also makes possible ones where many iterations of the filter may be required, such as might be required in a bootstrap or parameter estimation setting. Source code and executables are available at http://tiling.gersteinlab.org/pseudomedian/.

An efficient pseudomedian filter for tiling microrrays

PubMed Central

Royce, Thomas E; Carriero, Nicholas J; Gerstein, Mark B

2007-01-01

Background Tiling microarrays are becoming an essential technology in the functional genomics toolbox. They have been applied to the tasks of novel transcript identification, elucidation of transcription factor binding sites, detection of methylated DNA and several other applications in several model organisms. These experiments are being conducted at increasingly finer resolutions as the microarray technology enjoys increasingly greater feature densities. The increased densities naturally lead to increased data analysis requirements. Specifically, the most widely employed algorithm for tiling array analysis involves smoothing observed signals by computing pseudomedians within sliding windows, a O(n2logn) calculation in each window. This poor time complexity is an issue for tiling array analysis and could prove to be a real bottleneck as tiling microarray experiments become grander in scope and finer in resolution. Results We therefore implemented Monahan's HLQEST algorithm that reduces the runtime complexity for computing the pseudomedian of n numbers to O(nlogn) from O(n2logn). For a representative tiling microarray dataset, this modification reduced the smoothing procedure's runtime by nearly 90%. We then leveraged the fact that elements within sliding windows remain largely unchanged in overlapping windows (as one slides across genomic space) to further reduce computation by an additional 43%. This was achieved by the application of skip lists to maintaining a sorted list of values from window to window. This sorted list could be maintained with simple O(log n) inserts and deletes. We illustrate the favorable scaling properties of our algorithms with both time complexity analysis and benchmarking on synthetic datasets. Conclusion Tiling microarray analyses that rely upon a sliding window pseudomedian calculation can require many hours of computation. We have eased this requirement significantly by implementing efficient algorithms that scale well with genomic feature density. This result not only speeds the current standard analyses, but also makes possible ones where many iterations of the filter may be required, such as might be required in a bootstrap or parameter estimation setting. Source code and executables are available at . PMID:17555595

Computational vibrational study on coordinated nicotinamide

NASA Astrophysics Data System (ADS)

Bolukbasi, Olcay; Akyuz, Sevim

2005-06-01

The molecular structure and vibrational spectra of zinc (II) halide complexes of nicotinamide (ZnX 2(NIA) 2; X=Cl or Br; NIA=Nicotinamide) were investigated by computational vibrational study and scaled quantum mechanical (SQM) analysis. The geometry optimisation and vibrational wavenumber calculations of zinc halide complexes of nicotinamide were carried out by using the DFT/RB3LYP level of theory with 6-31G(d,p) basis set. The calculated wavenumbers were scaled by using scaled quantum mechanical (SQM) force field method. The fundamental vibrational modes were characterised by their total energy distribution. The coordination effects on nicotinamide through the ring nitrogen were discussed.

Computational analysis of liquid hypergolic propellant rocket engines

NASA Technical Reports Server (NTRS)

Krishnan, A.; Przekwas, A. J.; Gross, K. W.

1992-01-01

The combustion process in liquid rocket engines depends on a number of complex phenomena such as atomization, vaporization, spray dynamics, mixing, and reaction mechanisms. A computational tool to study their mutual interactions is developed to help analyze these processes with a view of improving existing designs and optimizing future designs of the thrust chamber. The focus of the article is on the analysis of the Variable Thrust Engine for the Orbit Maneuvering Vehicle. This engine uses a hypergolic liquid bipropellant combination of monomethyl hydrazine as fuel and nitrogen tetroxide as oxidizer.

Parallel Flux Tensor Analysis for Efficient Moving Object Detection

DTIC Science & Technology

2011-07-01

computing as well as parallelization to enable real time performance in analyzing complex video [3, 4 ]. There are a number of challenging computer vision... 4 . TITLE AND SUBTITLE Parallel Flux Tensor Analysis for Efficient Moving Object Detection 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT...We use the trace of the flux tensor matrix, referred to as Tr JF , that is defined below, Tr JF = ∫ Ω W (x− y)(I2xt(y) + I2yt(y) + I2tt(y))dy ( 4 ) as

Application of machine learning methods in bioinformatics

NASA Astrophysics Data System (ADS)

Yang, Haoyu; An, Zheng; Zhou, Haotian; Hou, Yawen

2018-05-01

Faced with the development of bioinformatics, high-throughput genomic technology have enabled biology to enter the era of big data. [1] Bioinformatics is an interdisciplinary, including the acquisition, management, analysis, interpretation and application of biological information, etc. It derives from the Human Genome Project. The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets.[2]. This paper analyzes and compares various algorithms of machine learning and their applications in bioinformatics.

Comsat Antenna

NASA Technical Reports Server (NTRS)

1978-01-01

The antenna shown is the new, multiple-beam, Unattended Earth Terminal, located at COMSAT Laboratories in Clarksburg, Maryland. Seemingly simple, it is actually a complex structure capable of maintaining contact with several satellites simultaneously (conventional Earth station antennas communicate with only one satellite at a time). In developing the antenna, COMSAT Laboratories used NASTRAN, NASA's structural analysis computer program, together with BANDIT, a companion program. The computer programs were used to model several structural configurations and determine the most suitable, The speed and accuracy of the computerized design analysis afforded appreciable savings in time and money.

A novel potential/viscous flow coupling technique for computing helicopter flow fields

NASA Technical Reports Server (NTRS)

Summa, J. Michael; Strash, Daniel J.; Yoo, Sungyul

1990-01-01

Because of the complexity of helicopter flow field, a zonal method of analysis of computational aerodynamics is required. Here, a new procedure for coupling potential and viscous flow is proposed. An overlapping, velocity coupling technique is to be developed with the unique feature that the potential flow surface singularity strengths are obtained directly from the Navier-Stokes at a smoother inner fluid boundary. The closed-loop iteration method proceeds until the velocity field is converged. This coupling should provide the means of more accurate viscous computations of the near-body and rotor flow fields with resultant improved analysis of such important performance parameters as helicopter fuselage drag and rotor airloads.

Quantity and location of aortic valve complex calcification predicts severity and location of paravalvular regurgitation and frequency of post-dilation after balloon-expandable transcatheter aortic valve replacement.

PubMed

Khalique, Omar K; Hahn, Rebecca T; Gada, Hemal; Nazif, Tamim M; Vahl, Torsten P; George, Isaac; Kalesan, Bindu; Forster, Molly; Williams, Mathew B; Leon, Martin B; Einstein, Andrew J; Pulerwitz, Todd C; Pearson, Gregory D N; Kodali, Susheel K

2014-08-01

This study sought to determine the impact of quantity and location of aortic valve calcification (AVC) on paravalvular regurgitation (PVR) and rates of post-dilation (PD) immediately after transcatheter aortic valve replacement (TAVR). The impact of AVC in different locations within the aortic valve complex is incompletely understood. This study analyzed 150 patients with severe, symptomatic aortic stenosis who underwent TAVR. Total AVC volume scores were calculated from contrast-enhanced multidetector row computed tomography imaging. AVC was divided by leaflet sector and region (Leaflet, Annulus, left ventricular outflow tract [LVOT]), and a combination of LVOT and Annulus (AnnulusLVOT). Asymmetry was assessed. Receiver-operating characteristic analysis was performed with greater than or equal to mild PVR and PD as classification variables. Logistic regression was performed. Quantity of and asymmetry of AVC for all regions of the aortic valve complex predicted greater than or equal to mild PVR by receiver-operating characteristic analysis (area under the curve = 0.635 to 0.689), except Leaflet asymmetry. Receiver-operating characteristic analysis for PD was significant for quantity and asymmetry of AVC in all regions, with higher area under the curve values than for PVR (area under the curve = 0.648 to 0.741). On multivariable analysis, Leaflet and AnnulusLVOT calcification were independent predictors of both PVR and PD regardless of multidetector row computed tomography area cover index. Quantity and asymmetry of AVC in all regions of the aortic valve complex predict greater than or equal to mild PVR and performance of PD, with the exception of Leaflet asymmetry. Quantity of AnnulusLVOT and Leaflet calcification independently predict PVR and PD when taking into account multidetector row computed tomography area cover index. Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

CMEIAS color segmentation: an improved computing technology to process color images for quantitative microbial ecology studies at single-cell resolution.

PubMed

Gross, Colin A; Reddy, Chandan K; Dazzo, Frank B

2010-02-01

Quantitative microscopy and digital image analysis are underutilized in microbial ecology largely because of the laborious task to segment foreground object pixels from background, especially in complex color micrographs of environmental samples. In this paper, we describe an improved computing technology developed to alleviate this limitation. The system's uniqueness is its ability to edit digital images accurately when presented with the difficult yet commonplace challenge of removing background pixels whose three-dimensional color space overlaps the range that defines foreground objects. Image segmentation is accomplished by utilizing algorithms that address color and spatial relationships of user-selected foreground object pixels. Performance of the color segmentation algorithm evaluated on 26 complex micrographs at single pixel resolution had an overall pixel classification accuracy of 99+%. Several applications illustrate how this improved computing technology can successfully resolve numerous challenges of complex color segmentation in order to produce images from which quantitative information can be accurately extracted, thereby gain new perspectives on the in situ ecology of microorganisms. Examples include improvements in the quantitative analysis of (1) microbial abundance and phylotype diversity of single cells classified by their discriminating color within heterogeneous communities, (2) cell viability, (3) spatial relationships and intensity of bacterial gene expression involved in cellular communication between individual cells within rhizoplane biofilms, and (4) biofilm ecophysiology based on ribotype-differentiated radioactive substrate utilization. The stand-alone executable file plus user manual and tutorial images for this color segmentation computing application are freely available at http://cme.msu.edu/cmeias/ . This improved computing technology opens new opportunities of imaging applications where discriminating colors really matter most, thereby strengthening quantitative microscopy-based approaches to advance microbial ecology in situ at individual single-cell resolution.

Development of a Aerothermoelastic-Acoustics Simulation Capability of Flight Vehicles

NASA Technical Reports Server (NTRS)

Gupta, K. K.; Choi, S. B.; Ibrahim, A.

2010-01-01

A novel numerical, finite element based analysis methodology is presented in this paper suitable for accurate and efficient simulation of practical, complex flight vehicles. An associated computer code, developed in this connection, is also described in some detail. Thermal effects of high speed flow obtained from a heat conduction analysis are incorporated in the modal analysis which in turn affects the unsteady flow arising out of interaction of elastic structures with the air. Numerical examples pertaining to representative problems are given in much detail testifying to the efficacy of the advocated techniques. This is a unique implementation of temperature effects in a finite element CFD based multidisciplinary simulation analysis capability involving large scale computations.

Comparative analysis of two discretizations of Ricci curvature for complex networks.

PubMed

Samal, Areejit; Sreejith, R P; Gu, Jiao; Liu, Shiping; Saucan, Emil; Jost, Jürgen

2018-06-05

We have performed an empirical comparison of two distinct notions of discrete Ricci curvature for graphs or networks, namely, the Forman-Ricci curvature and Ollivier-Ricci curvature. Importantly, these two discretizations of the Ricci curvature were developed based on different properties of the classical smooth notion, and thus, the two notions shed light on different aspects of network structure and behavior. Nevertheless, our extensive computational analysis in a wide range of both model and real-world networks shows that the two discretizations of Ricci curvature are highly correlated in many networks. Moreover, we show that if one considers the augmented Forman-Ricci curvature which also accounts for the two-dimensional simplicial complexes arising in graphs, the observed correlation between the two discretizations is even higher, especially, in real networks. Besides the potential theoretical implications of these observations, the close relationship between the two discretizations has practical implications whereby Forman-Ricci curvature can be employed in place of Ollivier-Ricci curvature for faster computation in larger real-world networks whenever coarse analysis suffices.

Physically elastic analysis of a cylindrical ring as a unit cell of a complete composite under applied stress in the complex plane using cubic polynomials

NASA Astrophysics Data System (ADS)

Monfared, Vahid

2018-03-01

Elastic analysis is analytically presented to predict the behaviors of the stress and displacement components in the cylindrical ring as a unit cell of a complete composite under applied stress in the complex plane using cubic polynomials. This analysis is based on the complex computation of the stress functions in the complex plane and polar coordinates. Also, suitable boundary conditions are considered and assumed to analyze along with the equilibrium equations and bi-harmonic equation. This method has some important applications in many fields of engineering such as mechanical, civil and material engineering generally. One of the applications of this research work is in composite design and designing the cylindrical devices under various loadings. Finally, it is founded that the convergence and accuracy of the results are suitable and acceptable through comparing the results.

ProteMiner-SSM: a web server for efficient analysis of similar protein tertiary substructures.

PubMed

Chang, Darby Tien-Hau; Chen, Chien-Yu; Chung, Wen-Chin; Oyang, Yen-Jen; Juan, Hsueh-Fen; Huang, Hsuan-Cheng

2004-07-01

Analysis of protein-ligand interactions is a fundamental issue in drug design. As the detailed and accurate analysis of protein-ligand interactions involves calculation of binding free energy based on thermodynamics and even quantum mechanics, which is highly expensive in terms of computing time, conformational and structural analysis of proteins and ligands has been widely employed as a screening process in computer-aided drug design. In this paper, a web server called ProteMiner-SSM designed for efficient analysis of similar protein tertiary substructures is presented. In one experiment reported in this paper, the web server has been exploited to obtain some clues about a biochemical hypothesis. The main distinction in the software design of the web server is the filtering process incorporated to expedite the analysis. The filtering process extracts the residues located in the caves of the protein tertiary structure for analysis and operates with O(nlogn) time complexity, where n is the number of residues in the protein. In comparison, the alpha-hull algorithm, which is a widely used algorithm in computer graphics for identifying those instances that are on the contour of a three-dimensional object, features O(n2) time complexity. Experimental results show that the filtering process presented in this paper is able to speed up the analysis by a factor ranging from 3.15 to 9.37 times. The ProteMiner-SSM web server can be found at http://proteminer.csie.ntu.edu.tw/. There is a mirror site at http://p4.sbl.bc.sinica.edu.tw/proteminer/.

Developments in the application of the geometrical theory of diffraction and computer graphics to aircraft inter-antenna coupling analysis

NASA Astrophysics Data System (ADS)

Bogusz, Michael

1993-01-01

The need for a systematic methodology for the analysis of aircraft electromagnetic compatibility (EMC) problems is examined. The available computer aids used in aircraft EMC analysis are assessed and a theoretical basis is established for the complex algorithms which identify and quantify electromagnetic interactions. An overview is presented of one particularly well established aircraft antenna to antenna EMC analysis code, the Aircraft Inter-Antenna Propagation with Graphics (AAPG) Version 07 software. The specific new algorithms created to compute cone geodesics and their associated path losses and to graph the physical coupling path are discussed. These algorithms are validated against basic principles. Loss computations apply the uniform geometrical theory of diffraction and are subsequently compared to measurement data. The increased modelling and analysis capabilities of the newly developed AAPG Version 09 are compared to those of Version 07. Several models of real aircraft, namely the Electronic Systems Trainer Challenger, are generated and provided as a basis for this preliminary comparative assessment. Issues such as software reliability, algorithm stability, and quality of hardcopy output are also discussed.

Programmable calculator software for computation of the plasma binding of ligands.

PubMed

Conner, D P; Rocci, M L; Larijani, G E

1986-01-01

The computation of the extent of plasma binding of a ligand to plasma constituents using radiolabeled ligand and equilibrium dialysis is complex and tedious. A computer program for the HP-41C Handheld Computer Series (Hewlett-Packard) was developed to perform these calculations. The first segment of the program constructs a standard curve for quench correction of post-dialysis plasma and buffer samples, using either external standard ratio (ESR) or sample channels ratio (SCR) techniques. The remainder of the program uses the counts per minute, SCR or ESR, and post-dialysis volume of paired plasma and buffer samples generated from the dialysis procedure to compute the extent of binding after correction for background radiation, counting efficiency, and intradialytic shifts of fluid between plasma and buffer compartments during dialysis. This program greatly simplifies the analysis of equilibrium dialysis data and has been employed in the analysis of dexamethasone binding in normal and uremic sera.

Grammatical Analysis as a Distributed Neurobiological Function

PubMed Central

Bozic, Mirjana; Fonteneau, Elisabeth; Su, Li; Marslen-Wilson, William D

2015-01-01

Language processing engages large-scale functional networks in both hemispheres. Although it is widely accepted that left perisylvian regions have a key role in supporting complex grammatical computations, patient data suggest that some aspects of grammatical processing could be supported bilaterally. We investigated the distribution and the nature of grammatical computations across language processing networks by comparing two types of combinatorial grammatical sequences—inflectionally complex words and minimal phrases—and contrasting them with grammatically simple words. Novel multivariate analyses revealed that they engage a coalition of separable subsystems: inflected forms triggered left-lateralized activation, dissociable into dorsal processes supporting morphophonological parsing and ventral, lexically driven morphosyntactic processes. In contrast, simple phrases activated a consistently bilateral pattern of temporal regions, overlapping with inflectional activations in L middle temporal gyrus. These data confirm the role of the left-lateralized frontotemporal network in supporting complex grammatical computations. Critically, they also point to the capacity of bilateral temporal regions to support simple, linear grammatical computations. This is consistent with a dual neurobiological framework where phylogenetically older bihemispheric systems form part of the network that supports language function in the modern human, and where significant capacities for language comprehension remain intact even following severe left hemisphere damage. PMID:25421880

Enabling Large-Scale Biomedical Analysis in the Cloud

PubMed Central

Lin, Ying-Chih; Yu, Chin-Sheng; Lin, Yen-Jen

2013-01-01

Recent progress in high-throughput instrumentations has led to an astonishing growth in both volume and complexity of biomedical data collected from various sources. The planet-size data brings serious challenges to the storage and computing technologies. Cloud computing is an alternative to crack the nut because it gives concurrent consideration to enable storage and high-performance computing on large-scale data. This work briefly introduces the data intensive computing system and summarizes existing cloud-based resources in bioinformatics. These developments and applications would facilitate biomedical research to make the vast amount of diversification data meaningful and usable. PMID:24288665

Three-dimensional geoelectric modelling with optimal work/accuracy rate using an adaptive wavelet algorithm

NASA Astrophysics Data System (ADS)

Plattner, A.; Maurer, H. R.; Vorloeper, J.; Dahmen, W.

2010-08-01

Despite the ever-increasing power of modern computers, realistic modelling of complex 3-D earth models is still a challenging task and requires substantial computing resources. The overwhelming majority of current geophysical modelling approaches includes either finite difference or non-adaptive finite element algorithms and variants thereof. These numerical methods usually require the subsurface to be discretized with a fine mesh to accurately capture the behaviour of the physical fields. However, this may result in excessive memory consumption and computing times. A common feature of most of these algorithms is that the modelled data discretizations are independent of the model complexity, which may be wasteful when there are only minor to moderate spatial variations in the subsurface parameters. Recent developments in the theory of adaptive numerical solvers have the potential to overcome this problem. Here, we consider an adaptive wavelet-based approach that is applicable to a large range of problems, also including nonlinear problems. In comparison with earlier applications of adaptive solvers to geophysical problems we employ here a new adaptive scheme whose core ingredients arose from a rigorous analysis of the overall asymptotically optimal computational complexity, including in particular, an optimal work/accuracy rate. Our adaptive wavelet algorithm offers several attractive features: (i) for a given subsurface model, it allows the forward modelling domain to be discretized with a quasi minimal number of degrees of freedom, (ii) sparsity of the associated system matrices is guaranteed, which makes the algorithm memory efficient and (iii) the modelling accuracy scales linearly with computing time. We have implemented the adaptive wavelet algorithm for solving 3-D geoelectric problems. To test its performance, numerical experiments were conducted with a series of conductivity models exhibiting varying degrees of structural complexity. Results were compared with a non-adaptive finite element algorithm, which incorporates an unstructured mesh to best-fitting subsurface boundaries. Such algorithms represent the current state-of-the-art in geoelectric modelling. An analysis of the numerical accuracy as a function of the number of degrees of freedom revealed that the adaptive wavelet algorithm outperforms the finite element solver for simple and moderately complex models, whereas the results become comparable for models with high spatial variability of electrical conductivities. The linear dependence of the modelling error and the computing time proved to be model-independent. This feature will allow very efficient computations using large-scale models as soon as our experimental code is optimized in terms of its implementation.

Algorithm for detection the QRS complexes based on support vector machine

NASA Astrophysics Data System (ADS)

Van, G. V.; Podmasteryev, K. V.

2017-11-01

The efficiency of computer ECG analysis depends on the accurate detection of QRS-complexes. This paper presents an algorithm for QRS complex detection based of support vector machine (SVM). The proposed algorithm is evaluated on annotated standard databases such as MIT-BIH Arrhythmia database. The QRS detector obtained a sensitivity Se = 98.32% and specificity Sp = 95.46% for MIT-BIH Arrhythmia database. This algorithm can be used as the basis for the software to diagnose electrical activity of the heart.

Managing large-scale workflow execution from resource provisioning to provenance tracking: The CyberShake example

USGS Publications Warehouse

Deelman, E.; Callaghan, S.; Field, E.; Francoeur, H.; Graves, R.; Gupta, N.; Gupta, V.; Jordan, T.H.; Kesselman, C.; Maechling, P.; Mehringer, J.; Mehta, G.; Okaya, D.; Vahi, K.; Zhao, L.

2006-01-01

This paper discusses the process of building an environment where large-scale, complex, scientific analysis can be scheduled onto a heterogeneous collection of computational and storage resources. The example application is the Southern California Earthquake Center (SCEC) CyberShake project, an analysis designed to compute probabilistic seismic hazard curves for sites in the Los Angeles area. We explain which software tools were used to build to the system, describe their functionality and interactions. We show the results of running the CyberShake analysis that included over 250,000 jobs using resources available through SCEC and the TeraGrid. ?? 2006 IEEE.

Photofragmentation of Gas-Phase Lanthanide Cyclopentadienyl Complexes: Experimental and Time-Dependent Excited-State Molecular Dynamics

PubMed Central

2015-01-01

Unimolecular gas-phase laser-photodissociation reaction mechanisms of open-shell lanthanide cyclopentadienyl complexes, Ln(Cp)3 and Ln(TMCp)3, are analyzed from experimental and computational perspectives. The most probable pathways for the photoreactions are inferred from photoionization time-of-flight mass spectrometry (PI-TOF-MS), which provides the sequence of reaction intermediates and the distribution of final products. Time-dependent excited-state molecular dynamics (TDESMD) calculations provide insight into the electronic mechanisms for the individual steps of the laser-driven photoreactions for Ln(Cp)3. Computational analysis correctly predicts several key reaction products as well as the observed branching between two reaction pathways: (1) ligand ejection and (2) ligand cracking. Simulations support our previous assertion that both reaction pathways are initiated via a ligand-to-metal charge-transfer (LMCT) process. For the more complex chemistry of the tetramethylcyclopentadienyl complexes Ln(TMCp)3, TMESMD is less tractable, but computational geometry optimization reveals the structures of intermediates deduced from PI-TOF-MS, including several classic “tuck-in” structures and products of Cp ring expansion. The results have important implications for metal–organic catalysis and laser-assisted metal–organic chemical vapor deposition (LCVD) of insulators with high dielectric constants. PMID:24910492

ULg Spectra: An Interactive Software Tool to Improve Undergraduate Students' Structural Analysis Skills

ERIC Educational Resources Information Center

Agnello, Armelinda; Carre, Cyril; Billen, Roland; Leyh, Bernard; De Pauw, Edwin; Damblon, Christian

2018-01-01

The analysis of spectroscopic data to solve chemical structures requires practical skills and drills. In this context, we have developed ULg Spectra, a computer-based tool designed to improve the ability of learners to perform complex reasoning. The identification of organic chemical compounds involves gathering and interpreting complementary…

An Analysis Method for Superconducting Resonator Parameter Extraction with Complex Baseline Removal

NASA Technical Reports Server (NTRS)

Cataldo, Giuseppe

2014-01-01

A new semi-empirical model is proposed for extracting the quality (Q) factors of arrays of superconducting microwave kinetic inductance detectors (MKIDs). The determination of the total internal and coupling Q factors enables the computation of the loss in the superconducting transmission lines. The method used allows the simultaneous analysis of multiple interacting discrete resonators with the presence of a complex spectral baseline arising from reflections in the system. The baseline removal allows an unbiased estimate of the device response as measured in a cryogenic instrumentation setting.

The ASSIST: Bringing Information and Software Together for Scientists

NASA Technical Reports Server (NTRS)

Mandel, Eric

1997-01-01

The ASSIST was developed as a step toward overcoming the problems faced by researchers when trying to utilize complex and often conflicting astronomical data analysis systems. It implements a uniform graphical interface to analysis systems, documentation, data, and organizational memory. It is layered on top of the Answer Garden Substrate (AGS), a system specially designed to facilitate the collection and dissemination of organizational memory. Under the AISRP program, we further developed the ASSIST to make it even easier for researchers to overcome the difficulties of accessing software and information in a complex computer environment.

DFT and TD-DFT computation of charge transfer complex between o-phenylenediamine and 3,5-dinitrosalicylic acid

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

Afroz, Ziya; Zulkarnain,; Ahmad, Afaq, E-mail: afaqahmad3@gmail.com

2016-05-23

DFT and TD-DFT studies of o-phenylenediamine (PDA), 3,5-dinitrosalicylic acid (DNSA) and their charge transfer complex have been carried out at B3LYP/6-311G(d,p) level of theory. Molecular geometry and various other molecular properties like natural atomic charges, ionization potential, electron affinity, band gap, natural bond orbital (NBO) and frontier molecular analysis have been presented at same level of theory. Frontier molecular orbital and natural bond orbital analysis show the charge delocalization from PDA to DNSA.

Parallel Multivariate Spatio-Temporal Clustering of Large Ecological Datasets on Hybrid Supercomputers

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

Sreepathi, Sarat; Kumar, Jitendra; Mills, Richard T.

A proliferation of data from vast networks of remote sensing platforms (satellites, unmanned aircraft systems (UAS), airborne etc.), observational facilities (meteorological, eddy covariance etc.), state-of-the-art sensors, and simulation models offer unprecedented opportunities for scientific discovery. Unsupervised classification is a widely applied data mining approach to derive insights from such data. However, classification of very large data sets is a complex computational problem that requires efficient numerical algorithms and implementations on high performance computing (HPC) platforms. Additionally, increasing power, space, cooling and efficiency requirements has led to the deployment of hybrid supercomputing platforms with complex architectures and memory hierarchies like themore » Titan system at Oak Ridge National Laboratory. The advent of such accelerated computing architectures offers new challenges and opportunities for big data analytics in general and specifically, large scale cluster analysis in our case. Although there is an existing body of work on parallel cluster analysis, those approaches do not fully meet the needs imposed by the nature and size of our large data sets. Moreover, they had scaling limitations and were mostly limited to traditional distributed memory computing platforms. We present a parallel Multivariate Spatio-Temporal Clustering (MSTC) technique based on k-means cluster analysis that can target hybrid supercomputers like Titan. We developed a hybrid MPI, CUDA and OpenACC implementation that can utilize both CPU and GPU resources on computational nodes. We describe performance results on Titan that demonstrate the scalability and efficacy of our approach in processing large ecological data sets.« less

Simulating and mapping spatial complexity using multi-scale techniques

USGS Publications Warehouse

De Cola, L.

1994-01-01

A central problem in spatial analysis is the mapping of data for complex spatial fields using relatively simple data structures, such as those of a conventional GIS. This complexity can be measured using such indices as multi-scale variance, which reflects spatial autocorrelation, and multi-fractal dimension, which characterizes the values of fields. These indices are computed for three spatial processes: Gaussian noise, a simple mathematical function, and data for a random walk. Fractal analysis is then used to produce a vegetation map of the central region of California based on a satellite image. This analysis suggests that real world data lie on a continuum between the simple and the random, and that a major GIS challenge is the scientific representation and understanding of rapidly changing multi-scale fields. -Author

Finite Dimensional Approximations for Continuum Multiscale Problems

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

Berlyand, Leonid

2017-01-24

The completed research project concerns the development of novel computational techniques for modeling nonlinear multiscale physical and biological phenomena. Specifically, it addresses the theoretical development and applications of the homogenization theory (coarse graining) approach to calculation of the effective properties of highly heterogenous biological and bio-inspired materials with many spatial scales and nonlinear behavior. This theory studies properties of strongly heterogeneous media in problems arising in materials science, geoscience, biology, etc. Modeling of such media raises fundamental mathematical questions, primarily in partial differential equations (PDEs) and calculus of variations, the subject of the PI’s research. The focus of completed researchmore » was on mathematical models of biological and bio-inspired materials with the common theme of multiscale analysis and coarse grain computational techniques. Biological and bio-inspired materials offer the unique ability to create environmentally clean functional materials used for energy conversion and storage. These materials are intrinsically complex, with hierarchical organization occurring on many nested length and time scales. The potential to rationally design and tailor the properties of these materials for broad energy applications has been hampered by the lack of computational techniques, which are able to bridge from the molecular to the macroscopic scale. The project addressed the challenge of computational treatments of such complex materials by the development of a synergistic approach that combines innovative multiscale modeling/analysis techniques with high performance computing.« less

On Learning Cluster Coefficient of Private Networks

PubMed Central

Wang, Yue; Wu, Xintao; Zhu, Jun; Xiang, Yang

2013-01-01

Enabling accurate analysis of social network data while preserving differential privacy has been challenging since graph features such as clustering coefficient or modularity often have high sensitivity, which is different from traditional aggregate functions (e.g., count and sum) on tabular data. In this paper, we treat a graph statistics as a function f and develop a divide and conquer approach to enforce differential privacy. The basic procedure of this approach is to first decompose the target computation f into several less complex unit computations f1, …, fm connected by basic mathematical operations (e.g., addition, subtraction, multiplication, division), then perturb the output of each fi with Laplace noise derived from its own sensitivity value and the distributed privacy threshold εi, and finally combine those perturbed fi as the perturbed output of computation f. We examine how various operations affect the accuracy of complex computations. When unit computations have large global sensitivity values, we enforce the differential privacy by calibrating noise based on the smooth sensitivity, rather than the global sensitivity. By doing this, we achieve the strict differential privacy guarantee with smaller magnitude noise. We illustrate our approach by using clustering coefficient, which is a popular statistics used in social network analysis. Empirical evaluations on five real social networks and various synthetic graphs generated from three random graph models show the developed divide and conquer approach outperforms the direct approach. PMID:24429843

Numerical Simulation of Pollutants' Transport and Fate in AN Unsteady Flow in Lower Bear River, Box Elder County, Utah

NASA Astrophysics Data System (ADS)

Salha, A. A.; Stevens, D. K.

2013-12-01

This study presents numerical application and statistical development of Stream Water Quality Modeling (SWQM) as a tool to investigate, manage, and research the transport and fate of water pollutants in Lower Bear River, Box elder County, Utah. The concerned segment under study is the Bear River starting from Cutler Dam to its confluence with the Malad River (Subbasin HUC 16010204). Water quality problems arise primarily from high phosphorus and total suspended sediment concentrations that were caused by five permitted point source discharges and complex network of canals and ducts of varying sizes and carrying capacities that transport water (for farming and agriculture uses) from Bear River and then back to it. Utah Department of Environmental Quality (DEQ) has designated the entire reach of the Bear River between Cutler Reservoir and Great Salt Lake as impaired. Stream water quality modeling (SWQM) requires specification of an appropriate model structure and process formulation according to nature of study area and purpose of investigation. The current model is i) one dimensional (1D), ii) numerical, iii) unsteady, iv) mechanistic, v) dynamic, and vi) spatial (distributed). The basic principle during the study is using mass balance equations and numerical methods (Fickian advection-dispersion approach) for solving the related partial differential equations. Model error decreases and sensitivity increases as a model becomes more complex, as such: i) uncertainty (in parameters, data input and model structure), and ii) model complexity, will be under investigation. Watershed data (water quality parameters together with stream flow, seasonal variations, surrounding landscape, stream temperature, and points/nonpoint sources) were obtained majorly using the HydroDesktop which is a free and open source GIS enabled desktop application to find, download, visualize, and analyze time series of water and climate data registered with the CUAHSI Hydrologic Information System. Processing, assessment of validity, and distribution of time-series data was explored using the GNU R language (statistical computing and graphics environment). Physical, chemical, and biological processes equations were written in FORTRAN codes (High Performance Fortran) in order to compute and solve their hyperbolic and parabolic complexities. Post analysis of results conducted using GNU R language. High performance computing (HPC) will be introduced to expedite solving complex computational processes using parallel programming. It is expected that the model will assess nonpoint sources and specific point sources data to understand pollutants' causes, transfer, dispersion, and concentration in different locations of Bear River. Investigation the impact of reduction/removal in non-point nutrient loading to Bear River water quality management could be addressed. Keywords: computer modeling; numerical solutions; sensitivity analysis; uncertainty analysis; ecosystem processes; high Performance computing; water quality.

Multivariate Complexity Analysis of Swap Bribery

NASA Astrophysics Data System (ADS)

Dorn, Britta; Schlotter, Ildikó

We consider the computational complexity of a problem modeling bribery in the context of voting systems. In the scenario of Swap Bribery, each voter assigns a certain price for swapping the positions of two consecutive candidates in his preference ranking. The question is whether it is possible, without exceeding a given budget, to bribe the voters in a way that the preferred candidate wins in the election.

Towards human-computer synergetic analysis of large-scale biological data.

PubMed

Singh, Rahul; Yang, Hui; Dalziel, Ben; Asarnow, Daniel; Murad, William; Foote, David; Gormley, Matthew; Stillman, Jonathan; Fisher, Susan

2013-01-01

Advances in technology have led to the generation of massive amounts of complex and multifarious biological data in areas ranging from genomics to structural biology. The volume and complexity of such data leads to significant challenges in terms of its analysis, especially when one seeks to generate hypotheses or explore the underlying biological processes. At the state-of-the-art, the application of automated algorithms followed by perusal and analysis of the results by an expert continues to be the predominant paradigm for analyzing biological data. This paradigm works well in many problem domains. However, it also is limiting, since domain experts are forced to apply their instincts and expertise such as contextual reasoning, hypothesis formulation, and exploratory analysis after the algorithm has produced its results. In many areas where the organization and interaction of the biological processes is poorly understood and exploratory analysis is crucial, what is needed is to integrate domain expertise during the data analysis process and use it to drive the analysis itself. In context of the aforementioned background, the results presented in this paper describe advancements along two methodological directions. First, given the context of biological data, we utilize and extend a design approach called experiential computing from multimedia information system design. This paradigm combines information visualization and human-computer interaction with algorithms for exploratory analysis of large-scale and complex data. In the proposed approach, emphasis is laid on: (1) allowing users to directly visualize, interact, experience, and explore the data through interoperable visualization-based and algorithmic components, (2) supporting unified query and presentation spaces to facilitate experimentation and exploration, (3) providing external contextual information by assimilating relevant supplementary data, and (4) encouraging user-directed information visualization, data exploration, and hypotheses formulation. Second, to illustrate the proposed design paradigm and measure its efficacy, we describe two prototype web applications. The first, called XMAS (Experiential Microarray Analysis System) is designed for analysis of time-series transcriptional data. The second system, called PSPACE (Protein Space Explorer) is designed for holistic analysis of structural and structure-function relationships using interactive low-dimensional maps of the protein structure space. Both these systems promote and facilitate human-computer synergy, where cognitive elements such as domain knowledge, contextual reasoning, and purpose-driven exploration, are integrated with a host of powerful algorithmic operations that support large-scale data analysis, multifaceted data visualization, and multi-source information integration. The proposed design philosophy, combines visualization, algorithmic components and cognitive expertise into a seamless processing-analysis-exploration framework that facilitates sense-making, exploration, and discovery. Using XMAS, we present case studies that analyze transcriptional data from two highly complex domains: gene expression in the placenta during human pregnancy and reaction of marine organisms to heat stress. With PSPACE, we demonstrate how complex structure-function relationships can be explored. These results demonstrate the novelty, advantages, and distinctions of the proposed paradigm. Furthermore, the results also highlight how domain insights can be combined with algorithms to discover meaningful knowledge and formulate evidence-based hypotheses during the data analysis process. Finally, user studies against comparable systems indicate that both XMAS and PSPACE deliver results with better interpretability while placing lower cognitive loads on the users. XMAS is available at: http://tintin.sfsu.edu:8080/xmas. PSPACE is available at: http://pspace.info/.

Towards human-computer synergetic analysis of large-scale biological data

PubMed Central

2013-01-01

Background Advances in technology have led to the generation of massive amounts of complex and multifarious biological data in areas ranging from genomics to structural biology. The volume and complexity of such data leads to significant challenges in terms of its analysis, especially when one seeks to generate hypotheses or explore the underlying biological processes. At the state-of-the-art, the application of automated algorithms followed by perusal and analysis of the results by an expert continues to be the predominant paradigm for analyzing biological data. This paradigm works well in many problem domains. However, it also is limiting, since domain experts are forced to apply their instincts and expertise such as contextual reasoning, hypothesis formulation, and exploratory analysis after the algorithm has produced its results. In many areas where the organization and interaction of the biological processes is poorly understood and exploratory analysis is crucial, what is needed is to integrate domain expertise during the data analysis process and use it to drive the analysis itself. Results In context of the aforementioned background, the results presented in this paper describe advancements along two methodological directions. First, given the context of biological data, we utilize and extend a design approach called experiential computing from multimedia information system design. This paradigm combines information visualization and human-computer interaction with algorithms for exploratory analysis of large-scale and complex data. In the proposed approach, emphasis is laid on: (1) allowing users to directly visualize, interact, experience, and explore the data through interoperable visualization-based and algorithmic components, (2) supporting unified query and presentation spaces to facilitate experimentation and exploration, (3) providing external contextual information by assimilating relevant supplementary data, and (4) encouraging user-directed information visualization, data exploration, and hypotheses formulation. Second, to illustrate the proposed design paradigm and measure its efficacy, we describe two prototype web applications. The first, called XMAS (Experiential Microarray Analysis System) is designed for analysis of time-series transcriptional data. The second system, called PSPACE (Protein Space Explorer) is designed for holistic analysis of structural and structure-function relationships using interactive low-dimensional maps of the protein structure space. Both these systems promote and facilitate human-computer synergy, where cognitive elements such as domain knowledge, contextual reasoning, and purpose-driven exploration, are integrated with a host of powerful algorithmic operations that support large-scale data analysis, multifaceted data visualization, and multi-source information integration. Conclusions The proposed design philosophy, combines visualization, algorithmic components and cognitive expertise into a seamless processing-analysis-exploration framework that facilitates sense-making, exploration, and discovery. Using XMAS, we present case studies that analyze transcriptional data from two highly complex domains: gene expression in the placenta during human pregnancy and reaction of marine organisms to heat stress. With PSPACE, we demonstrate how complex structure-function relationships can be explored. These results demonstrate the novelty, advantages, and distinctions of the proposed paradigm. Furthermore, the results also highlight how domain insights can be combined with algorithms to discover meaningful knowledge and formulate evidence-based hypotheses during the data analysis process. Finally, user studies against comparable systems indicate that both XMAS and PSPACE deliver results with better interpretability while placing lower cognitive loads on the users. XMAS is available at: http://tintin.sfsu.edu:8080/xmas. PSPACE is available at: http://pspace.info/. PMID:24267485

Transcriptional Network Analysis in Muscle Reveals AP-1 as a Partner of PGC-1α in the Regulation of the Hypoxic Gene Program

PubMed Central

Baresic, Mario; Salatino, Silvia; Kupr, Barbara

2014-01-01

Skeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here, we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1α and gene expression upon PGC-1α overexpression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto-underestimated number of transcription factor partners involved in mediating PGC-1α action. In particular, principal component analysis of TFBSs at PGC-1α binding regions predicts that, besides the well-known role of the estrogen-related receptor α (ERRα), the activator protein 1 complex (AP-1) plays a major role in regulating the PGC-1α-controlled gene program of the hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1α. PMID:24912679

Single-trial detection of visual evoked potentials by common spatial patterns and wavelet filtering for brain-computer interface.

PubMed

Tu, Yiheng; Huang, Gan; Hung, Yeung Sam; Hu, Li; Hu, Yong; Zhang, Zhiguo

2013-01-01

Event-related potentials (ERPs) are widely used in brain-computer interface (BCI) systems as input signals conveying a subject's intention. A fast and reliable single-trial ERP detection method can be used to develop a BCI system with both high speed and high accuracy. However, most of single-trial ERP detection methods are developed for offline EEG analysis and thus have a high computational complexity and need manual operations. Therefore, they are not applicable to practical BCI systems, which require a low-complexity and automatic ERP detection method. This work presents a joint spatial-time-frequency filter that combines common spatial patterns (CSP) and wavelet filtering (WF) for improving the signal-to-noise (SNR) of visual evoked potentials (VEP), which can lead to a single-trial ERP-based BCI.

Spatial aliasing for efficient direction-of-arrival estimation based on steering vector reconstruction

NASA Astrophysics Data System (ADS)

Yan, Feng-Gang; Cao, Bin; Rong, Jia-Jia; Shen, Yi; Jin, Ming

2016-12-01

A new technique is proposed to reduce the computational complexity of the multiple signal classification (MUSIC) algorithm for direction-of-arrival (DOA) estimate using a uniform linear array (ULA). The steering vector of the ULA is reconstructed as the Kronecker product of two other steering vectors, and a new cost function with spatial aliasing at hand is derived. Thanks to the estimation ambiguity of this spatial aliasing, mirror angles mathematically relating to the true DOAs are generated, based on which the full spectral search involved in the MUSIC algorithm is highly compressed into a limited angular sector accordingly. Further complexity analysis and performance studies are conducted by computer simulations, which demonstrate that the proposed estimator requires an extremely reduced computational burden while it shows a similar accuracy to the standard MUSIC.

Experimental analysis of bidirectional reflectance distribution function cross section conversion term in direction cosine space.

PubMed

Butler, Samuel D; Nauyoks, Stephen E; Marciniak, Michael A

2015-06-01

Of the many classes of bidirectional reflectance distribution function (BRDF) models, two popular classes of models are the microfacet model and the linear systems diffraction model. The microfacet model has the benefit of speed and simplicity, as it uses geometric optics approximations, while linear systems theory uses a diffraction approach to compute the BRDF, at the expense of greater computational complexity. In this Letter, nongrazing BRDF measurements of rough and polished surface-reflecting materials at multiple incident angles are scaled by the microfacet cross section conversion term, but in the linear systems direction cosine space, resulting in great alignment of BRDF data at various incident angles in this space. This results in a predictive BRDF model for surface-reflecting materials at nongrazing angles, while avoiding some of the computational complexities in the linear systems diffraction model.

Bioinformatics/biostatistics: microarray analysis.

PubMed

Eichler, Gabriel S

2012-01-01

The quantity and complexity of the molecular-level data generated in both research and clinical settings require the use of sophisticated, powerful computational interpretation techniques. It is for this reason that bioinformatic analysis of complex molecular profiling data has become a fundamental technology in the development of personalized medicine. This chapter provides a high-level overview of the field of bioinformatics and outlines several, classic bioinformatic approaches. The highlighted approaches can be aptly applied to nearly any sort of high-dimensional genomic, proteomic, or metabolomic experiments. Reviewed technologies in this chapter include traditional clustering analysis, the Gene Expression Dynamics Inspector (GEDI), GoMiner (GoMiner), Gene Set Enrichment Analysis (GSEA), and the Learner of Functional Enrichment (LeFE).

A Modular Environment for Geophysical Inversion and Run-time Autotuning using Heterogeneous Computing Systems

NASA Astrophysics Data System (ADS)

Myre, Joseph M.

Heterogeneous computing systems have recently come to the forefront of the High-Performance Computing (HPC) community's interest. HPC computer systems that incorporate special purpose accelerators, such as Graphics Processing Units (GPUs), are said to be heterogeneous. Large scale heterogeneous computing systems have consistently ranked highly on the Top500 list since the beginning of the heterogeneous computing trend. By using heterogeneous computing systems that consist of both general purpose processors and special- purpose accelerators, the speed and problem size of many simulations could be dramatically increased. Ultimately this results in enhanced simulation capabilities that allows, in some cases for the first time, the execution of parameter space and uncertainty analyses, model optimizations, and other inverse modeling techniques that are critical for scientific discovery and engineering analysis. However, simplifying the usage and optimization of codes for heterogeneous computing systems remains a challenge. This is particularly true for scientists and engineers for whom understanding HPC architectures and undertaking performance analysis may not be primary research objectives. To enable scientists and engineers to remain focused on their primary research objectives, a modular environment for geophysical inversion and run-time autotuning on heterogeneous computing systems is presented. This environment is composed of three major components: 1) CUSH---a framework for reducing the complexity of programming heterogeneous computer systems, 2) geophysical inversion routines which can be used to characterize physical systems, and 3) run-time autotuning routines designed to determine configurations of heterogeneous computing systems in an attempt to maximize the performance of scientific and engineering codes. Using three case studies, a lattice-Boltzmann method, a non-negative least squares inversion, and a finite-difference fluid flow method, it is shown that this environment provides scientists and engineers with means to reduce the programmatic complexity of their applications, to perform geophysical inversions for characterizing physical systems, and to determine high-performing run-time configurations of heterogeneous computing systems using a run-time autotuner.

Rapid architecture alternative modeling (RAAM): A framework for capability-based analysis of system of systems architectures

NASA Astrophysics Data System (ADS)

Iacobucci, Joseph V.

The research objective for this manuscript is to develop a Rapid Architecture Alternative Modeling (RAAM) methodology to enable traceable Pre-Milestone A decision making during the conceptual phase of design of a system of systems. Rather than following current trends that place an emphasis on adding more analysis which tends to increase the complexity of the decision making problem, RAAM improves on current methods by reducing both runtime and model creation complexity. RAAM draws upon principles from computer science, system architecting, and domain specific languages to enable the automatic generation and evaluation of architecture alternatives. For example, both mission dependent and mission independent metrics are considered. Mission dependent metrics are determined by the performance of systems accomplishing a task, such as Probability of Success. In contrast, mission independent metrics, such as acquisition cost, are solely determined and influenced by the other systems in the portfolio. RAAM also leverages advances in parallel computing to significantly reduce runtime by defining executable models that are readily amendable to parallelization. This allows the use of cloud computing infrastructures such as Amazon's Elastic Compute Cloud and the PASTEC cluster operated by the Georgia Institute of Technology Research Institute (GTRI). Also, the amount of data that can be generated when fully exploring the design space can quickly exceed the typical capacity of computational resources at the analyst's disposal. To counter this, specific algorithms and techniques are employed. Streaming algorithms and recursive architecture alternative evaluation algorithms are used that reduce computer memory requirements. Lastly, a domain specific language is created to provide a reduction in the computational time of executing the system of systems models. A domain specific language is a small, usually declarative language that offers expressive power focused on a particular problem domain by establishing an effective means to communicate the semantics from the RAAM framework. These techniques make it possible to include diverse multi-metric models within the RAAM framework in addition to system and operational level trades. A canonical example was used to explore the uses of the methodology. The canonical example contains all of the features of a full system of systems architecture analysis study but uses fewer tasks and systems. Using RAAM with the canonical example it was possible to consider both system and operational level trades in the same analysis. Once the methodology had been tested with the canonical example, a Suppression of Enemy Air Defenses (SEAD) capability model was developed. Due to the sensitive nature of analyses on that subject, notional data was developed. The notional data has similar trends and properties to realistic Suppression of Enemy Air Defenses data. RAAM was shown to be traceable and provided a mechanism for a unified treatment of a variety of metrics. The SEAD capability model demonstrated lower computer runtimes and reduced model creation complexity as compared to methods currently in use. To determine the usefulness of the implementation of the methodology on current computing hardware, RAAM was tested with system of system architecture studies of different sizes. This was necessary since system of systems may be called upon to accomplish thousands of tasks. It has been clearly demonstrated that RAAM is able to enumerate and evaluate the types of large, complex design spaces usually encountered in capability based design, oftentimes providing the ability to efficiently search the entire decision space. The core algorithms for generation and evaluation of alternatives scale linearly with expected problem sizes. The SEAD capability model outputs prompted the discovery a new issue, the data storage and manipulation requirements for an analysis. Two strategies were developed to counter large data sizes, the use of portfolio views and top 'n' analysis. This proved the usefulness of the RAAM framework and methodology during Pre-Milestone A capability based analysis. (Abstract shortened by UMI.).

PROVAT: a tool for Voronoi tessellation analysis of protein structures and complexes.

PubMed

Gore, Swanand P; Burke, David F; Blundell, Tom L

2005-08-01

Voronoi tessellation has proved to be a useful tool in protein structure analysis. We have developed PROVAT, a versatile public domain software that enables computation and visualization of Voronoi tessellations of proteins and protein complexes. It is a set of Python scripts that integrate freely available specialized software (Qhull, Pymol etc.) into a pipeline. The calculation component of the tool computes Voronoi tessellation of a given protein system in a way described by a user-supplied XML recipe and stores resulting neighbourhood information as text files with various styles. The Python pickle file generated in the process is used by the visualization component, a Pymol plug-in, that offers a GUI to explore the tessellation visually. PROVAT source code can be downloaded from http://raven.bioc.cam.ac.uk/~swanand/Provat1, which also provides a webserver for its calculation component, documentation and examples.

Finite element analysis of TAVI: Impact of native aortic root computational modeling strategies on simulation outcomes.

PubMed

Finotello, Alice; Morganti, Simone; Auricchio, Ferdinando

2017-09-01

In the last few years, several studies, each with different aim and modeling detail, have been proposed to investigate transcatheter aortic valve implantation (TAVI) with finite elements. The present work focuses on the patient-specific finite element modeling of the aortic valve complex. In particular, we aim at investigating how different modeling strategies in terms of material models/properties and discretization procedures can impact analysis results. Four different choices both for the mesh size (from  20 k elements to  200 k elements) and for the material model (from rigid to hyperelastic anisotropic) are considered. Different approaches for modeling calcifications are also taken into account. Post-operative CT data of the real implant are used as reference solution with the aim of outlining a trade-off between computational model complexity and reliability of the results. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Research on image complexity evaluation method based on color information

NASA Astrophysics Data System (ADS)

Wang, Hao; Duan, Jin; Han, Xue-hui; Xiao, Bo

2017-11-01

In order to evaluate the complexity of a color image more effectively and find the connection between image complexity and image information, this paper presents a method to compute the complexity of image based on color information.Under the complexity ,the theoretical analysis first divides the complexity from the subjective level, divides into three levels: low complexity, medium complexity and high complexity, and then carries on the image feature extraction, finally establishes the function between the complexity value and the color characteristic model. The experimental results show that this kind of evaluation method can objectively reconstruct the complexity of the image from the image feature research. The experimental results obtained by the method of this paper are in good agreement with the results of human visual perception complexity,Color image complexity has a certain reference value.

Dramatic Influence of an Anionic Donor on the Oxygen-Atom Transfer Reactivity of a MnV–Oxo Complex

PubMed Central

Neu, Heather M; Quesne, Matthew G; Yang, Tzuhsiung; Prokop-Prigge, Katharine A; Lancaster, Kyle M; Donohoe, James; DeBeer, Serena; de Visser, Sam P; Goldberg, David P

2014-01-01

Addition of an anionic donor to an MnV(O) porphyrinoid complex causes a dramatic increase in 2-electron oxygen-atom-transfer (OAT) chemistry. The 6-coordinate [MnV(O)(TBP8Cz)(CN)]− was generated from addition of Bu4N+CN− to the 5-coordinate MnV(O) precursor. The cyanide-ligated complex was characterized for the first time by Mn K-edge X-ray absorption spectroscopy (XAS) and gives Mn–O=1.53 Å, Mn–CN=2.21 Å. In combination with computational studies these distances were shown to correlate with a singlet ground state. Reaction of the CN− complex with thioethers results in OAT to give the corresponding sulfoxide and a 2e−-reduced MnIII(CN)− complex. Kinetic measurements reveal a dramatic rate enhancement for OAT of approximately 24 000-fold versus the same reaction for the parent 5-coordinate complex. An Eyring analysis gives ΔH≠=14 kcal mol−1, ΔS≠=−10 cal mol−1 K−1. Computational studies fully support the structures, spin states, and relative reactivity of the 5- and 6-coordinate MnV(O) complexes. PMID:25256417

Theoretical study of optical activity of 1:1 hydrogen bond complexes of water with S-warfarin

NASA Astrophysics Data System (ADS)

Dadsetani, Mehrdad; Abdolmaleki, Ahmad; Zabardasti, Abedin

2016-11-01

The molecular interaction between S-warfarin (SW) and a single water molecule was investigated using the B3LYP method at 6-311 ++G(d,p) basis set. The vibrational spectra of the optimized complexes have been investigated for stabilization checking. Quantum theories of atoms in molecules, natural bond orbitals, molecular electrostatic potentials and energy decomposition analysis methods have been applied to analyze the intermolecular interactions. The intermolecular charge transfer in the most stable complex is in the opposite direction from those in the other complexes. The optical spectra and the hyperpolarizabilities of SW-water hydrogen bond complexes have been computed.

Response surface method in geotechnical/structural analysis, phase 1

NASA Astrophysics Data System (ADS)

Wong, F. S.

1981-02-01

In the response surface approach, an approximating function is fit to a long running computer code based on a limited number of code calculations. The approximating function, called the response surface, is then used to replace the code in subsequent repetitive computations required in a statistical analysis. The procedure of the response surface development and feasibility of the method are shown using a sample problem in slop stability which is based on data from centrifuge experiments of model soil slopes and involves five random soil parameters. It is shown that a response surface can be constructed based on as few as four code calculations and that the response surface is computationally extremely efficient compared to the code calculation. Potential applications of this research include probabilistic analysis of dynamic, complex, nonlinear soil/structure systems such as slope stability, liquefaction, and nuclear reactor safety.

Synthesis, spectroscopic characterization, electrochemical behavior and computational analysis of mixed diamine ligand gold(III) complexes: antiproliferative and in vitro cytotoxic evaluations against human cancer cell lines.

PubMed

Al-Jaroudi, Said S; Monim-ul-Mehboob, M; Altaf, Muhammad; Al-Saadi, Abdulaziz A; Wazeer, Mohammed I M; Altuwaijri, Saleh; Isab, Anvarhusein A

2014-12-01

The gold(III) complexes of the type [(DACH)Au(en)]Cl3, 1,2-Diaminocyclohexane ethylenediamine gold(III) chloride [where 1,2-DACH = cis-, trans-1,2- and S,S-1,2diaminocyclohexane and en = ethylenediamine] have been synthesized and characterized using various analytical and spectroscopic techniques including elemental analysis, UV-Vis and FTIR spectra; and solution as well as solid-state NMR measurements. The solid-state (13)C NMR shows that 1,2-diaminocyclohexane (1,2-DACH) and ethylenediamine (en) are strongly bound to the gold(III) center via N donor atoms. The stability of the mixed diamine ligand gold(III) was determined by (1)H and (13)C NMR spectra. Their electrochemical behavior was studied by cyclic voltammetry. The structural details and relative stabilities of the four possible isomers of the complexes were also reported at the B3LYP/LANL2DZ level of theory. The coordination sphere of these complexes around gold(III) center adopts distorted square planar geometry. The computational study also demonstrates that trans- conformations is slightly more stable than the cis-conformations. The antiproliferative effects and cytotoxic properties of the mixed diamine ligand gold(III) complexes were evaluated in vitro on human gastric SGC7901 and prostate PC3 cancer cells using MTT assay. The antiproliferative study of the gold(III) complexes on PC3 and SGC7901 cells indicate that complex 1 is the most effective antiproliferative agent among mixed ligand based gold(III) complexes 1-3. The IC50 data reveal that the in vitro cytotoxicity of complexes 1 and 3 against SGC7901 cancer cells are fairly better than that of cisplatin.

a Chiral Tag Study of the Absolute Configuration of Camphor

NASA Astrophysics Data System (ADS)

Pratt, David; Evangelisti, Luca; Smart, Taylor; Holdren, Martin S.; Mayer, Kevin J.; West, Channing; Pate, Brooks

2017-06-01

The chiral tagging method for rotational spectroscopy uses an established approach in chiral analysis of creating a complex with an enantiopure tag so that enantiomers of the molecule of interest are converted to diastereomer complexes. Since the diastereomers have distinct structure, they give distinguishable rotational spectra. Camphor was chosen as an example for the chiral tag method because it has spectral properties that could pose challenges to the use of three wave mixing rotational spectroscopy to establish absolute configuration. Specifically, one of the dipole moment components of camphor is small making three wave mixing measurements challenging and placing high accuracy requirements on computational chemistry for calculating the dipole moment direction in the principal axis system. The chiral tag measurements of camphor used the hydrogen bond donor 3-butyn-2-ol. Quantum chemistry calculations using the B3LYP-D3BJ method and the def2TZVP basis set identified 7 low energy isomers of the chiral complex. The two lowest energy complexes of the homochiral and heterochiral complexes are observed in a measurement using racemic tag. Absolute configuration is confirmed by the use of an enantiopure tag sample. Spectra with ^{13}C-sensitivity were acquired so that the carbon substitution structure of the complex could be obtained to provide a structure of camphor with correct stereochemistry. The chiral tag complex spectra can also be used to estimate the enantiomeric excess of the sample and analysis of the broadband spectrum indicates that the sample enantiopurity is higher than 99.5%. The structure of the complex is analyzed to determine the extent of geometry modification that occurs upon formation of the complex. These results show that initial isomer searches with fixed geometries will be accurate. The reduction in computation time from fixed geometry assumptions will be discussed.

Efficient and accurate Greedy Search Methods for mining functional modules in protein interaction networks.

PubMed

He, Jieyue; Li, Chaojun; Ye, Baoliu; Zhong, Wei

2012-06-25

Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures. In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules. The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms. Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the computational time significantly while keeping high prediction accuracy.

Computed Tomography Inspection and Analysis for Additive Manufacturing Components

NASA Technical Reports Server (NTRS)

Beshears, Ronald D.

2017-01-01

Computed tomography (CT) inspection was performed on test articles additively manufactured from metallic materials. Metallic AM and machined wrought alloy test articles with programmed flaws and geometric features were inspected using a 2-megavolt linear accelerator based CT system. Performance of CT inspection on identically configured wrought and AM components and programmed flaws was assessed to determine the impact of additive manufacturing on inspectability of objects with complex geometries.

Design of a Computer-Adaptive Test to Measure English Literacy and Numeracy in the Singapore Workforce: Considerations, Benefits, and Implications

ERIC Educational Resources Information Center

Jacobsen, Jared; Ackermann, Richard; Eguez, Jane; Ganguli, Debalina; Rickard, Patricia; Taylor, Linda

2011-01-01

A computer adaptive test (CAT) is a delivery methodology that serves the larger goals of the assessment system in which it is embedded. A thorough analysis of the assessment system for which a CAT is being designed is critical to ensure that the delivery platform is appropriate and addresses all relevant complexities. As such, a CAT engine must be…

On Algorithms for Generating Computationally Simple Piecewise Linear Classifiers

DTIC Science & Technology

1989-05-01

suffers. - Waveform classification, e.g. speech recognition, seismic analysis (i.e. discrimination between earthquakes and nuclear explosions), target...assuming Gaussian distributions (B-G) d) Bayes classifier with probability densities estimated with the k-N-N method (B- kNN ) e) The -arest neighbour...range of classifiers are chosen including a fast, easy computable and often used classifier (B-G), reliable and complex classifiers (B- kNN and NNR

Fluid-Structure Interaction Analysis of Ruptured Mitral Chordae Tendineae.

PubMed

Toma, Milan; Bloodworth, Charles H; Pierce, Eric L; Einstein, Daniel R; Cochran, Richard P; Yoganathan, Ajit P; Kunzelman, Karyn S

2017-03-01

The chordal structure is a part of mitral valve geometry that has been commonly neglected or simplified in computational modeling due to its complexity. However, these simplifications cannot be used when investigating the roles of individual chordae tendineae in mitral valve closure. For the first time, advancements in imaging, computational techniques, and hardware technology make it possible to create models of the mitral valve without simplifications to its complex geometry, and to quickly run validated computer simulations that more realistically capture its function. Such simulations can then be used for a detailed analysis of chordae-related diseases. In this work, a comprehensive model of a subject-specific mitral valve with detailed chordal structure is used to analyze the distinct role played by individual chordae in closure of the mitral valve leaflets. Mitral closure was simulated for 51 possible chordal rupture points. Resultant regurgitant orifice area and strain change in the chordae at the papillary muscle tips were then calculated to examine the role of each ruptured chorda in the mitral valve closure. For certain subclassifications of chordae, regurgitant orifice area was found to trend positively with ruptured chordal diameter, and strain changes correlated negatively with regurgitant orifice area. Further advancements in clinical imaging modalities, coupled with the next generation of computational techniques will enable more physiologically realistic simulations.

Fluid-Structure Interaction Analysis of Ruptured Mitral Chordae Tendineae

PubMed Central

Toma, Milan; Bloodworth, Charles H.; Pierce, Eric L.; Einstein, Daniel R.; Cochran, Richard P.; Yoganathan, Ajit P.; Kunzelman, Karyn S.

2016-01-01

The chordal structure is a part of mitral valve geometry that has been commonly neglected or simplified in computational modeling due to its complexity. However, these simplifications cannot be used when investigating the roles of individual chordae tendineae in mitral valve closure. For the first time, advancements in imaging, computational techniques, and hardware technology make it possible to create models of the mitral valve without simplifications to its complex geometry, and to quickly run validated computer simulations that more realistically capture its function. Such simulations can then be used for a detailed analysis of chordae-related diseases. In this work, a comprehensive model of a subject-specific mitral valve with detailed chordal structure is used to analyze the distinct role played by individual chordae in closure of the mitral valve leaflets. Mitral closure was simulated for 51 possible chordal rupture points. Resultant regurgitant orifice area and strain change in the chordae at the papillary muscle tips were then calculated to examine the role of each ruptured chorda in the mitral valve closure. For certain subclassifications of chordae, regurgitant orifice area was found to trend positively with ruptured chordal diameter, and strain changes correlated negatively with regurgitant orifice area. Further advancements in clinical imaging modalities, coupled with the next generation of computational techniques will enable more physiologically realistic simulations. PMID:27624659

Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches

PubMed Central

Beatty, Perrin H.; Klein, Matthias S.; Fischer, Jeffrey J.; Lewis, Ian A.; Muench, Douglas G.; Good, Allen G.

2016-01-01

A comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE) in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms that affect NUE in agricultural settings. However, an exciting collection of computational and experimental approaches has begun to elucidate whole-plant nitrogen usage and provides an avenue for connecting nitrogen-related phenotypes to genes. Herein, we describe how metabolomics, computational models of metabolism, and flux balance analysis have been harnessed to advance our understanding of plant nitrogen metabolism. We introduce a model describing the complex flow of nitrogen through crops in a real-world agricultural setting and describe how experimental metabolomics data, such as isotope labeling rates and analyses of nutrient uptake, can be used to refine these models. In summary, the metabolomics/computational approach offers an exciting mechanism for understanding NUE that may ultimately lead to more effective crop management and engineered plants with higher yields. PMID:27735856

The role of real-time in biomedical science: a meta-analysis on computational complexity, delay and speedup.

PubMed

Faust, Oliver; Yu, Wenwei; Rajendra Acharya, U

2015-03-01

The concept of real-time is very important, as it deals with the realizability of computer based health care systems. In this paper we review biomedical real-time systems with a meta-analysis on computational complexity (CC), delay (Δ) and speedup (Sp). During the review we found that, in the majority of papers, the term real-time is part of the thesis indicating that a proposed system or algorithm is practical. However, these papers were not considered for detailed scrutiny. Our detailed analysis focused on papers which support their claim of achieving real-time, with a discussion on CC or Sp. These papers were analyzed in terms of processing system used, application area (AA), CC, Δ, Sp, implementation/algorithm (I/A) and competition. The results show that the ideas of parallel processing and algorithm delay were only recently introduced and journal papers focus more on Algorithm (A) development than on implementation (I). Most authors compete on big O notation (O) and processing time (PT). Based on these results, we adopt the position that the concept of real-time will continue to play an important role in biomedical systems design. We predict that parallel processing considerations, such as Sp and algorithm scaling, will become more important. Copyright © 2015 Elsevier Ltd. All rights reserved.

Complexity Level Analysis Revisited: What Can 30 Years of Hindsight Tell Us about How the Brain Might Represent Visual Information?

PubMed Central

Tsotsos, John K.

2017-01-01

Much has been written about how the biological brain might represent and process visual information, and how this might inspire and inform machine vision systems. Indeed, tremendous progress has been made, and especially during the last decade in the latter area. However, a key question seems too often, if not mostly, be ignored. This question is simply: do proposed solutions scale with the reality of the brain's resources? This scaling question applies equally to brain and to machine solutions. A number of papers have examined the inherent computational difficulty of visual information processing using theoretical and empirical methods. The main goal of this activity had three components: to understand the deep nature of the computational problem of visual information processing; to discover how well the computational difficulty of vision matches to the fixed resources of biological seeing systems; and, to abstract from the matching exercise the key principles that lead to the observed characteristics of biological visual performance. This set of components was termed complexity level analysis in Tsotsos (1987) and was proposed as an important complement to Marr's three levels of analysis. This paper revisits that work with the advantage that decades of hindsight can provide. PMID:28848458

Complexity Level Analysis Revisited: What Can 30 Years of Hindsight Tell Us about How the Brain Might Represent Visual Information?

PubMed

Tsotsos, John K

2017-01-01

Much has been written about how the biological brain might represent and process visual information, and how this might inspire and inform machine vision systems. Indeed, tremendous progress has been made, and especially during the last decade in the latter area. However, a key question seems too often, if not mostly, be ignored. This question is simply: do proposed solutions scale with the reality of the brain's resources? This scaling question applies equally to brain and to machine solutions. A number of papers have examined the inherent computational difficulty of visual information processing using theoretical and empirical methods. The main goal of this activity had three components: to understand the deep nature of the computational problem of visual information processing; to discover how well the computational difficulty of vision matches to the fixed resources of biological seeing systems; and, to abstract from the matching exercise the key principles that lead to the observed characteristics of biological visual performance. This set of components was termed complexity level analysis in Tsotsos (1987) and was proposed as an important complement to Marr's three levels of analysis. This paper revisits that work with the advantage that decades of hindsight can provide.

A Geometry Based Infra-structure for Computational Analysis and Design

NASA Technical Reports Server (NTRS)

Haimes, Robert

1997-01-01

The computational steps traditionally taken for most engineering analysis (CFD, structural analysis, and etc.) are: Surface Generation - usually by employing a CAD system; Grid Generation - preparing the volume for the simulation; Flow Solver - producing the results at the specified operational point; and Post-processing Visualization - interactively attempting to understand the results For structural analysis, integrated systems can be obtained from a number of commercial vendors. For CFD, these steps have worked well in the past for simple steady-state simulations at the expense of much user interaction. The data was transmitted between phases via files. Specifically the problems with this procedure are: (1) File based. Information flows from one step to the next via data files with formats specified for that procedure. (2) 'Good' Geometry. A bottleneck in getting results from a solver is the construction of proper geometry to be fed to the grid generator. With 'good' geometry a grid can be constructed in tens of minutes (even with a complex configuration) using unstructured techniques. (3) One-Way communication. All information travels on from one phase to the next. Until this process can be automated, more complex problems such as multi-disciplinary analysis or using the above procedure for design becomes prohibitive.

A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling: GEOSTATISTICAL SENSITIVITY ANALYSIS

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

Dai, Heng; Chen, Xingyuan; Ye, Ming

Sensitivity analysis is an important tool for quantifying uncertainty in the outputs of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a hierarchical sensitivity analysis method that (1) constructs an uncertainty hierarchy by analyzing the input uncertainty sources, and (2) accounts for the spatial correlation among parameters at each level ofmore » the hierarchy using geostatistical tools. The contribution of uncertainty source at each hierarchy level is measured by sensitivity indices calculated using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport in model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally as driven by the dynamic interaction between groundwater and river water at the site. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed parameters.« less

Variogram Analysis of Response surfaces (VARS): A New Framework for Global Sensitivity Analysis of Earth and Environmental Systems Models

NASA Astrophysics Data System (ADS)

Razavi, S.; Gupta, H. V.

2015-12-01

Earth and environmental systems models (EESMs) are continually growing in complexity and dimensionality with continuous advances in understanding and computing power. Complexity and dimensionality are manifested by introducing many different factors in EESMs (i.e., model parameters, forcings, boundary conditions, etc.) to be identified. Sensitivity Analysis (SA) provides an essential means for characterizing the role and importance of such factors in producing the model responses. However, conventional approaches to SA suffer from (1) an ambiguous characterization of sensitivity, and (2) poor computational efficiency, particularly as the problem dimension grows. Here, we present a new and general sensitivity analysis framework (called VARS), based on an analogy to 'variogram analysis', that provides an intuitive and comprehensive characterization of sensitivity across the full spectrum of scales in the factor space. We prove, theoretically, that Morris (derivative-based) and Sobol (variance-based) methods and their extensions are limiting cases of VARS, and that their SA indices can be computed as by-products of the VARS framework. We also present a practical strategy for the application of VARS to real-world problems, called STAR-VARS, including a new sampling strategy, called "star-based sampling". Our results across several case studies show the STAR-VARS approach to provide reliable and stable assessments of "global" sensitivity across the full range of scales in the factor space, while being at least 1-2 orders of magnitude more efficient than the benchmark Morris and Sobol approaches.

Probabilistic Analysis Techniques Applied to Complex Spacecraft Power System Modeling

NASA Technical Reports Server (NTRS)

Hojnicki, Jeffrey S.; Rusick, Jeffrey J.

2005-01-01

Electric power system performance predictions are critical to spacecraft, such as the International Space Station (ISS), to ensure that sufficient power is available to support all the spacecraft s power needs. In the case of the ISS power system, analyses to date have been deterministic, meaning that each analysis produces a single-valued result for power capability because of the complexity and large size of the model. As a result, the deterministic ISS analyses did not account for the sensitivity of the power capability to uncertainties in model input variables. Over the last 10 years, the NASA Glenn Research Center has developed advanced, computationally fast, probabilistic analysis techniques and successfully applied them to large (thousands of nodes) complex structural analysis models. These same techniques were recently applied to large, complex ISS power system models. This new application enables probabilistic power analyses that account for input uncertainties and produce results that include variations caused by these uncertainties. Specifically, N&R Engineering, under contract to NASA, integrated these advanced probabilistic techniques with Glenn s internationally recognized ISS power system model, System Power Analysis for Capability Evaluation (SPACE).

Hierarchy and Assortativity as New Tools for Binding-Affinity Investigation: The Case of the TBA Aptamer-Ligand Complex.

PubMed

Cataldo, Rosella; Alfinito, Eleonora; Reggiani, Lino

2017-12-01

Aptamers are single stranded DNA, RNA, or peptide sequences having the ability to bind several specific targets (proteins, molecules as well as ions). Therefore, aptamer production and selection for therapeutic and diagnostic applications is very challenging. Usually, they are generated in vitro, although computational approaches have been recently developed for the in silico production. Despite these efforts, the mechanism of aptamer-ligand formation is not completely clear, and producing high-affinity aptamers is still quite difficult. This paper aims to develop a computational model able to describe aptamer-ligand affinity. Topological tools, such as the conventional degree distribution, the rank-degree distribution (hierarchy), and the node assortativity are employed. In doing so, the macromolecules tertiary-structures are mapped into appropriate graphs. These graphs reproduce the main topological features of the macromolecules, by preserving the distances between amino acids (nucleotides). Calculations are applied to the thrombin binding aptamer (TBA), and the TBA-thrombin complex produced in the presence of Na + or K + . The topological analysis is able to detect several differences between complexes obtained in the presence of the two cations, as expected by previous investigations. These results support graph analysis as a novel computational tool for testing affinity. Otherwise, starting from the graphs, an electrical network can be obtained by using the specific electrical properties of amino acids and nucleobases. Therefore, a further analysis concerns with the electrical response, revealing that the resistance is sensitively affected by the presence of sodium or potassium, thus suggesting resistance as a useful physical parameter for testing binding affinity.

Fast normal mode computations of capsid dynamics inspired by resonance

NASA Astrophysics Data System (ADS)

Na, Hyuntae; Song, Guang

2018-07-01

Increasingly more and larger structural complexes are being determined experimentally. The sizes of these systems pose a formidable computational challenge to the study of their vibrational dynamics by normal mode analysis. To overcome this challenge, this work presents a novel resonance-inspired approach. Tests on large shell structures of protein capsids demonstrate that there is a strong resonance between the vibrations of a whole capsid and those of individual capsomeres. We then show how this resonance can be taken advantage of to significantly speed up normal mode computations.

Numerical computation of linear instability of detonations

NASA Astrophysics Data System (ADS)

Kabanov, Dmitry; Kasimov, Aslan

2017-11-01

We propose a method to study linear stability of detonations by direct numerical computation. The linearized governing equations together with the shock-evolution equation are solved in the shock-attached frame using a high-resolution numerical algorithm. The computed results are processed by the Dynamic Mode Decomposition technique to generate dispersion relations. The method is applied to the reactive Euler equations with simple-depletion chemistry as well as more complex multistep chemistry. The results are compared with those known from normal-mode analysis. We acknowledge financial support from King Abdullah University of Science and Technology.

Computer aided drug design

NASA Astrophysics Data System (ADS)

Jain, A.

2017-08-01

Computer based method can help in discovery of leads and can potentially eliminate chemical synthesis and screening of many irrelevant compounds, and in this way, it save time as well as cost. Molecular modeling systems are powerful tools for building, visualizing, analyzing and storing models of complex molecular structure that can help to interpretate structure activity relationship. The use of various techniques of molecular mechanics and dynamics and software in Computer aided drug design along with statistics analysis is powerful tool for the medicinal chemistry to synthesis therapeutic and effective drugs with minimum side effect.

Damped gyroscopic effects and axial-flexural-torsional coupling using spinning finite elements for wind-turbine blades characterization

NASA Astrophysics Data System (ADS)

Velazquez, Antonio; Swartz, R. Andrew

2013-04-01

Renewable energy sources like wind are important technologies, useful to alleviate for the current fossil-fuel crisis. Capturing wind energy in a more efficient way has resulted in the emergence of more sophisticated designs of wind turbines, particularly Horizontal-Axis Wind Turbines (HAWTs). To promote efficiency, traditional finite element methods have been widely used to characterize the aerodynamics of these types of multi-body systems and improve their design. Given their aeroelastic behavior, tapered-swept blades offer the potential to optimize energy capture and decrease fatigue loads. Nevertheless, modeling special complex geometries requires huge computational efforts necessitating tradeoffs between faster computation times at lower cost, and reliability and numerical accuracy. Indeed, the computational cost and the numerical effort invested, using traditional FE methods, to reproduce dependable aerodynamics of these complex-shape beams are sometimes prohibitive. A condensed Spinning Finite Element (SFE) method scheme is presented in this study aimed to alleviate this issue by means of modeling wind-turbine rotor blades properly with tapered-swept cross-section variations of arbitrary order via Lagrangian equations. Axial-flexural-torsional coupling is carried out on axial deformation, torsion, in-plane bending and out-of-plane bending using super-convergent elements. In this study, special attention is paid for the case of damped yaw effects, expressed within the described skew-symmetric damped gyroscopic matrix. Dynamics of the model are analyzed by achieving modal analysis with complex-number eigen-frequencies. By means of mass, damped gyroscopic, and stiffness (axial-flexural-torsional coupling) matrix condensation (order reduction), numerical analysis is carried out for several prototypes with different tapered, swept, and curved variation intensities, and for a practical range of spinning velocities at different rotation angles. A convergence study for the resulting natural frequencies is performed to evaluate the dynamic collateral effects of tapered-swept blade profiles in spinning motion using this new model. Stability analysis in boundary conditions of the postulated model is achieved to test the convergence and integrity of the mathematical model. The proposed framework presumes to be particularly suitable to characterize models with complex-shape cross-sections at low computation cost.

Electromagnetic Compatibility Design of the Computer Circuits

NASA Astrophysics Data System (ADS)

Zitai, Hong

2018-02-01

Computers and the Internet have gradually penetrated into every aspect of people’s daily work. But with the improvement of electronic equipment as well as electrical system, the electromagnetic environment becomes much more complex. Electromagnetic interference has become an important factor to hinder the normal operation of electronic equipment. In order to analyse the computer circuit compatible with the electromagnetic compatibility, this paper starts from the computer electromagnetic and the conception of electromagnetic compatibility. And then, through the analysis of the main circuit and system of computer electromagnetic compatibility problems, we can design the computer circuits in term of electromagnetic compatibility. Finally, the basic contents and methods of EMC test are expounded in order to ensure the electromagnetic compatibility of equipment.

Mono and binuclear ruthenium(II) complexes containing 5-chlorothiophene-2-carboxylic acid ligands: Spectroscopic analysis and computational studies

NASA Astrophysics Data System (ADS)

Swarnalatha, Kalaiyar; Kamalesu, Subramaniam; Subramanian, Ramasamy

2016-11-01

New Ruthenium complexes I, II and III were synthesized using 5-chlorothiophene-2-carboxylic acid (5TPC), as ligand and the complexes were characterized by elemental analysis, FT-IR, 1H, 13C NMR, and mass spectroscopic techniques. Photophysical and electrochemical studies were carried out and the structures of the synthesized complex were optimized using density functional theory (DFT). The molecular geometry, the highest occupied molecular orbital (HOMO), the lowest unoccupied molecular orbital (LUMO) energies and Mulliken atomic charges of the molecules are determined at the B3LYP method and standard 6-311++G (d,p) basis set starting from optimized geometry. They possess excellent stabilities and their thermal decomposition temperatures are 185 °C, 180 °C and 200 °C respectively, indicating that the metal complexes are suitable for the fabrication processes of optoelectronic devices.

SAPNEW: Parallel finite element code for thin shell structures on the Alliant FX-80

NASA Astrophysics Data System (ADS)

Kamat, Manohar P.; Watson, Brian C.

1992-11-01

The finite element method has proven to be an invaluable tool for analysis and design of complex, high performance systems, such as bladed-disk assemblies in aircraft turbofan engines. However, as the problem size increase, the computation time required by conventional computers can be prohibitively high. Parallel processing computers provide the means to overcome these computation time limits. This report summarizes the results of a research activity aimed at providing a finite element capability for analyzing turbomachinery bladed-disk assemblies in a vector/parallel processing environment. A special purpose code, named with the acronym SAPNEW, has been developed to perform static and eigen analysis of multi-degree-of-freedom blade models built-up from flat thin shell elements. SAPNEW provides a stand alone capability for static and eigen analysis on the Alliant FX/80, a parallel processing computer. A preprocessor, named with the acronym NTOS, has been developed to accept NASTRAN input decks and convert them to the SAPNEW format to make SAPNEW more readily used by researchers at NASA Lewis Research Center.

Optical analysis of laser systems using interferometry

NASA Astrophysics Data System (ADS)

Viswanathan, V. K.; Liberman, I.; Lawrence, G.; Seery, B. D.

1980-06-01

It is noted that previous approaches of predicting focal spot parameters involved the digitization of interference patterns of the optical components and propagation of the complex amplitude and phase of the wave front throughout the system. The present paper describes an approach in which the computational procedure is extended to produce computer plots of the final emerging wave front. It is shown that this enables direct comparison with the experimentally produced wave front of the total system and makes possible the optical analysis, design, and possible optimization of laser systems. A description is given of the computational procedure and the Twyman-Green and Smartt IR interferometers constructed to verify this approach. Finally, consideration is given to the implications of the results.

Applications of genetic programming in cancer research.

PubMed

Worzel, William P; Yu, Jianjun; Almal, Arpit A; Chinnaiyan, Arul M

2009-02-01

The theory of Darwinian evolution is the fundamental keystones of modern biology. Late in the last century, computer scientists began adapting its principles, in particular natural selection, to complex computational challenges, leading to the emergence of evolutionary algorithms. The conceptual model of selective pressure and recombination in evolutionary algorithms allow scientists to efficiently search high dimensional space for solutions to complex problems. In the last decade, genetic programming has been developed and extensively applied for analysis of molecular data to classify cancer subtypes and characterize the mechanisms of cancer pathogenesis and development. This article reviews current successes using genetic programming and discusses its potential impact in cancer research and treatment in the near future.

The QuakeSim Project: Numerical Simulations for Active Tectonic Processes

NASA Technical Reports Server (NTRS)

Donnellan, Andrea; Parker, Jay; Lyzenga, Greg; Granat, Robert; Fox, Geoffrey; Pierce, Marlon; Rundle, John; McLeod, Dennis; Grant, Lisa; Tullis, Terry

2004-01-01

In order to develop a solid earth science framework for understanding and studying of active tectonic and earthquake processes, this task develops simulation and analysis tools to study the physics of earthquakes using state-of-the art modeling, data manipulation, and pattern recognition technologies. We develop clearly defined accessible data formats and code protocols as inputs to the simulations. these are adapted to high-performance computers because the solid earth system is extremely complex and nonlinear resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes.

Investigation of methods to search for the boundaries on the image and their use on lung hardware of methods finding saliency map

NASA Astrophysics Data System (ADS)

Semenishchev, E. A.; Marchuk, V. I.; Fedosov, V. P.; Stradanchenko, S. G.; Ruslyakov, D. V.

2015-05-01

This work aimed to study computationally simple method of saliency map calculation. Research in this field received increasing interest for the use of complex techniques in portable devices. A saliency map allows increasing the speed of many subsequent algorithms and reducing the computational complexity. The proposed method of saliency map detection based on both image and frequency space analysis. Several examples of test image from the Kodak dataset with different detalisation considered in this paper demonstrate the effectiveness of the proposed approach. We present experiments which show that the proposed method providing better results than the framework Salience Toolbox in terms of accuracy and speed.

LOCAL ORTHOGONAL CUTTING METHOD FOR COMPUTING MEDIAL CURVES AND ITS BIOMEDICAL APPLICATIONS

PubMed Central

Einstein, Daniel R.; Dyedov, Vladimir

2010-01-01

Medial curves have a wide range of applications in geometric modeling and analysis (such as shape matching) and biomedical engineering (such as morphometry and computer assisted surgery). The computation of medial curves poses significant challenges, both in terms of theoretical analysis and practical efficiency and reliability. In this paper, we propose a definition and analysis of medial curves and also describe an efficient and robust method called local orthogonal cutting (LOC) for computing medial curves. Our approach is based on three key concepts: a local orthogonal decomposition of objects into substructures, a differential geometry concept called the interior center of curvature (ICC), and integrated stability and consistency tests. These concepts lend themselves to robust numerical techniques and result in an algorithm that is efficient and noise resistant. We illustrate the effectiveness and robustness of our approach with some highly complex, large-scale, noisy biomedical geometries derived from medical images, including lung airways and blood vessels. We also present comparisons of our method with some existing methods. PMID:20628546

The change in critical technologies for computational physics

NASA Technical Reports Server (NTRS)

Watson, Val

1990-01-01

It is noted that the types of technology required for computational physics are changing as the field matures. Emphasis has shifted from computer technology to algorithm technology and, finally, to visual analysis technology as areas of critical research for this field. High-performance graphical workstations tied to a supercommunicator with high-speed communications along with the development of especially tailored visualization software has enabled analysis of highly complex fluid-dynamics simulations. Particular reference is made here to the development of visual analysis tools at NASA's Numerical Aerodynamics Simulation Facility. The next technology which this field requires is one that would eliminate visual clutter by extracting key features of simulations of physics and technology in order to create displays that clearly portray these key features. Research in the tuning of visual displays to human cognitive abilities is proposed. The immediate transfer of technology to all levels of computers, specifically the inclusion of visualization primitives in basic software developments for all work stations and PCs, is recommended.

A new tool called DISSECT for analysing large genomic data sets using a Big Data approach

PubMed Central

Canela-Xandri, Oriol; Law, Andy; Gray, Alan; Woolliams, John A.; Tenesa, Albert

2015-01-01

Large-scale genetic and genomic data are increasingly available and the major bottleneck in their analysis is a lack of sufficiently scalable computational tools. To address this problem in the context of complex traits analysis, we present DISSECT. DISSECT is a new and freely available software that is able to exploit the distributed-memory parallel computational architectures of compute clusters, to perform a wide range of genomic and epidemiologic analyses, which currently can only be carried out on reduced sample sizes or under restricted conditions. We demonstrate the usefulness of our new tool by addressing the challenge of predicting phenotypes from genotype data in human populations using mixed-linear model analysis. We analyse simulated traits from 470,000 individuals genotyped for 590,004 SNPs in ∼4 h using the combined computational power of 8,400 processor cores. We find that prediction accuracies in excess of 80% of the theoretical maximum could be achieved with large sample sizes. PMID:26657010

Adjoint Sensitivity Analysis for Scale-Resolving Turbulent Flow Solvers

NASA Astrophysics Data System (ADS)

Blonigan, Patrick; Garai, Anirban; Diosady, Laslo; Murman, Scott

2017-11-01

Adjoint-based sensitivity analysis methods are powerful design tools for engineers who use computational fluid dynamics. In recent years, these engineers have started to use scale-resolving simulations like large-eddy simulations (LES) and direct numerical simulations (DNS), which resolve more scales in complex flows with unsteady separation and jets than the widely-used Reynolds-averaged Navier-Stokes (RANS) methods. However, the conventional adjoint method computes large, unusable sensitivities for scale-resolving simulations, which unlike RANS simulations exhibit the chaotic dynamics inherent in turbulent flows. Sensitivity analysis based on least-squares shadowing (LSS) avoids the issues encountered by conventional adjoint methods, but has a high computational cost even for relatively small simulations. The following talk discusses a more computationally efficient formulation of LSS, ``non-intrusive'' LSS, and its application to turbulent flows simulated with a discontinuous-Galkerin spectral-element-method LES/DNS solver. Results are presented for the minimal flow unit, a turbulent channel flow with a limited streamwise and spanwise domain.

Statistical mechanics of complex neural systems and high dimensional data

NASA Astrophysics Data System (ADS)

Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya

2013-03-01

Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks.

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering.

PubMed

Groen, Nathalie; Guvendiren, Murat; Rabitz, Herschel; Welsh, William J; Kohn, Joachim; de Boer, Jan

2016-04-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. In this opinion paper, we postulate that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. Copyright © 2016. Published by Elsevier Ltd.

Modelling and simulation of complex sociotechnical systems: envisioning and analysing work environments

PubMed Central

Hettinger, Lawrence J.; Kirlik, Alex; Goh, Yang Miang; Buckle, Peter

2015-01-01

Accurate comprehension and analysis of complex sociotechnical systems is a daunting task. Empirically examining, or simply envisioning the structure and behaviour of such systems challenges traditional analytic and experimental approaches as well as our everyday cognitive capabilities. Computer-based models and simulations afford potentially useful means of accomplishing sociotechnical system design and analysis objectives. From a design perspective, they can provide a basis for a common mental model among stakeholders, thereby facilitating accurate comprehension of factors impacting system performance and potential effects of system modifications. From a research perspective, models and simulations afford the means to study aspects of sociotechnical system design and operation, including the potential impact of modifications to structural and dynamic system properties, in ways not feasible with traditional experimental approaches. This paper describes issues involved in the design and use of such models and simulations and describes a proposed path forward to their development and implementation. Practitioner Summary: The size and complexity of real-world sociotechnical systems can present significant barriers to their design, comprehension and empirical analysis. This article describes the potential advantages of computer-based models and simulations for understanding factors that impact sociotechnical system design and operation, particularly with respect to process and occupational safety. PMID:25761227

The Application of COMSOL Multiphysics Package on the Modelling of Complex 3-D Lithospheric Electrical Resistivity Structures - A Case Study from the Proterozoic Orogenic belt within the North China Craton

NASA Astrophysics Data System (ADS)

Guo, L.; Yin, Y.; Deng, M.; Guo, L.; Yan, J.

2017-12-01

At present, most magnetotelluric (MT) forward modelling and inversion codes are based on finite difference method. But its structured mesh gridding cannot be well adapted for the conditions with arbitrary topography or complex tectonic structures. By contrast, the finite element method is more accurate in calculating complex and irregular 3-D region and has lower requirement of function smoothness. However, the complexity of mesh gridding and limitation of computer capacity has been affecting its application. COMSOL Multiphysics is a cross-platform finite element analysis, solver and multiphysics full-coupling simulation software. It achieves highly accurate numerical simulations with high computational performance and outstanding multi-field bi-directional coupling analysis capability. In addition, its AC/DC and RF module can be used to easily calculate the electromagnetic responses of complex geological structures. Using the adaptive unstructured grid, the calculation is much faster. In order to improve the discretization technique of computing area, we use the combination of Matlab and COMSOL Multiphysics to establish a general procedure for calculating the MT responses for arbitrary resistivity models. The calculated responses include the surface electric and magnetic field components, impedance components, magnetic transfer functions and phase tensors. Then, the reliability of this procedure is certificated by 1-D, 2-D and 3-D and anisotropic forward modeling tests. Finally, we establish the 3-D lithospheric resistivity model for the Proterozoic Wutai-Hengshan Mts. within the North China Craton by fitting the real MT data collected there. The reliability of the model is also verified by induced vectors and phase tensors. Our model shows more details and better resolution, compared with the previously published 3-D model based on the finite difference method. In conclusion, COMSOL Multiphysics package is suitable for modeling the 3-D lithospheric resistivity structures under complex tectonic deformation backgrounds, which could be a good complement to the existing finite-difference inversion algorithms.

Knowledge-Base Semantic Gap Analysis for the Vulnerability Detection

NASA Astrophysics Data System (ADS)

Wu, Raymond; Seki, Keisuke; Sakamoto, Ryusuke; Hisada, Masayuki

Web security became an alert in internet computing. To cope with ever-rising security complexity, semantic analysis is proposed to fill-in the gap that the current approaches fail to commit. Conventional methods limit their focus to the physical source codes instead of the abstraction of semantics. It bypasses new types of vulnerability and causes tremendous business loss.

Solid rocket booster internal flow analysis by highly accurate adaptive computational methods

NASA Technical Reports Server (NTRS)

Huang, C. Y.; Tworzydlo, W.; Oden, J. T.; Bass, J. M.; Cullen, C.; Vadaketh, S.

1991-01-01

The primary objective of this project was to develop an adaptive finite element flow solver for simulating internal flows in the solid rocket booster. Described here is a unique flow simulator code for analyzing highly complex flow phenomena in the solid rocket booster. New methodologies and features incorporated into this analysis tool are described.

Vocoders and Speech Perception: Uses of Computer-Based Speech Analysis-Synthesis in Stimulus Generation.

ERIC Educational Resources Information Center

Tierney, Joseph; Mack, Molly

1987-01-01

Stimuli used in research on the perception of the speech signal have often been obtained from simple filtering and distortion of the speech waveform, sometimes accompanied by noise. However, for more complex stimulus generation, the parameters of speech can be manipulated, after analysis and before synthesis, using various types of algorithms to…

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection

PubMed Central

Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav

2015-01-01

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close “neighborhood” of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa. PMID:26327290

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection.

PubMed

Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav

2015-01-01

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close "neighborhood" of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa.

Noncovalent Interactions and Internal Dynamics in Pyridine-Ammonia: A Combined Quantum-Chemical and Microwave Spectroscopy Study.

PubMed

Spada, Lorenzo; Tasinato, Nicola; Vazart, Fanny; Barone, Vincenzo; Caminati, Walther; Puzzarini, Cristina

2017-04-06

The 1:1 complex of ammonia with pyridine is characterized by using state-of-the-art quantum-chemical computations combined with pulsed-jet Fourier-transform microwave spectroscopy. The computed potential energy landscape indicates the formation of a stable σ-type complex, which is confirmed experimentally: analysis of the rotational spectrum shows the presence of only one 1:1 pyridine-ammonia adduct. Each rotational transition is split into several components owing to the internal rotation of NH 3 around its C 3 axis and to the hyperfine structure of both 14 N quadrupolar nuclei, thus providing unequivocal proof that the two molecules form a σ-type complex involving both a N-H⋅⋅⋅N and a C-H⋅⋅⋅N hydrogen bond. The dissociation energy (BSSE- and ZPE-corrected) is estimated to be 11.5 kJ mol -1 . This work represents the first application of an accurate yet efficient computational scheme, designed for the investigation of small biomolecules, to a molecular cluster. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Non-Covalent Interactions and Internal Dynamics in Pyridine-Ammonia a Combined Quantum-Chemical and Microwave Spectroscopy Study

NASA Astrophysics Data System (ADS)

Spada, Lorenzo; Tasinato, Nicola; Vazart, Fanny; Barone, Vincenzo; Caminati, Walther; Puzzarini, Cristina

2017-06-01

The 1:1 complex of ammonia with pyridine has been characterized by using state-of-the-art quantum-chemical computations combined with pulsed-jet Fourier-Transform microwave spectroscopy. The computed potential energy landscape pointed out the formation of a stable σ-type complex, which has been confirmed experimentally: the analysis of the rotational spectrum showed the presence of only one 1:1 pyridine - ammonia adduct. Each rotational transition is split into several components due to the internal rotation of NH_3 around its C_3 axis and to the hyperfine structure of both ^{14}N quadrupolar nuclei, thus providing the unequivocal proof that the two molecules form a σ-type complex involving both a N-H\\cdotsN and a C-H\\cdotsN hydrogen bond. The dissociation energy (BSSE and ZPE corrected) has been estimated to be 11.5 kJ\\cdotmol^{-1}. This work represents the first application of an accurate, yet efficient computational scheme, designed for the investigation of small biomolecules, to a molecular cluster.

Petri net model for analysis of concurrently processed complex algorithms

NASA Technical Reports Server (NTRS)

Stoughton, John W.; Mielke, Roland R.

1986-01-01

This paper presents a Petri-net model suitable for analyzing the concurrent processing of computationally complex algorithms. The decomposed operations are to be processed in a multiple processor, data driven architecture. Of particular interest is the application of the model to both the description of the data/control flow of a particular algorithm, and to the general specification of the data driven architecture. A candidate architecture is also presented.

Turbulent Dispersion Modelling in a Complex Urban Environment - Data Analysis and Model Development

DTIC Science & Technology

2010-02-01

Technology Laboratory (Dstl) is used as a benchmark for comparison. Comparisons are also made with some more practically oriented computational fluid dynamics...predictions. To achieve clarity in the range of approaches available for practical models of con- taminant dispersion in urban areas, an overview of...complexity of those methods is simplified to a degree that allows straightforward practical implementation and application. Using these results as a

Local Orthogonal Cutting Method for Computing Medial Curves and Its Biomedical Applications

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

Jiao, Xiangmin; Einstein, Daniel R.; Dyedov, Volodymyr

2010-03-24

Medial curves have a wide range of applications in geometric modeling and analysis (such as shape matching) and biomedical engineering (such as morphometry and computer assisted surgery). The computation of medial curves poses significant challenges, both in terms of theoretical analysis and practical efficiency and reliability. In this paper, we propose a definition and analysis of medial curves and also describe an efficient and robust method for computing medial curves. Our approach is based on three key concepts: a local orthogonal decomposition of objects into substructures, a differential geometry concept called the interior center of curvature (ICC), and integrated stabilitymore » and consistency tests. These concepts lend themselves to robust numerical techniques including eigenvalue analysis, weighted least squares approximations, and numerical minimization, resulting in an algorithm that is efficient and noise resistant. We illustrate the effectiveness and robustness of our approach with some highly complex, large-scale, noisy biomedical geometries derived from medical images, including lung airways and blood vessels. We also present comparisons of our method with some existing methods.« less

Experimental demonstration of non-iterative interpolation-based partial ICI compensation in100G RGI-DP-CO-OFDM transport systems.

PubMed

Mousa-Pasandi, Mohammad E; Zhuge, Qunbi; Xu, Xian; Osman, Mohamed M; El-Sahn, Ziad A; Chagnon, Mathieu; Plant, David V

2012-07-02

We experimentally investigate the performance of a low-complexity non-iterative phase noise induced inter-carrier interference (ICI) compensation algorithm in reduced-guard-interval dual-polarization coherent-optical orthogonal-frequency-division-multiplexing (RGI-DP-CO-OFDM) transport systems. This interpolation-based ICI compensator estimates the time-domain phase noise samples by a linear interpolation between the CPE estimates of the consecutive OFDM symbols. We experimentally study the performance of this scheme for a 28 Gbaud QPSK RGI-DP-CO-OFDM employing a low cost distributed feedback (DFB) laser. Experimental results using a DFB laser with the linewidth of 2.6 MHz demonstrate 24% and 13% improvement in transmission reach with respect to the conventional equalizer (CE) in presence of weak and strong dispersion-enhanced-phase-noise (DEPN), respectively. A brief analysis of the computational complexity of this scheme in terms of the number of required complex multiplications is provided. This practical approach does not suffer from error propagation while enjoying low computational complexity.

Systematic theoretical investigation of the zero-field splitting in Gd(III) complexes: Wave function and density functional approaches

NASA Astrophysics Data System (ADS)

Khan, Shehryar; Kubica-Misztal, Aleksandra; Kruk, Danuta; Kowalewski, Jozef; Odelius, Michael

2015-01-01

The zero-field splitting (ZFS) of the electronic ground state in paramagnetic ions is a sensitive probe of the variations in the electronic and molecular structure with an impact on fields ranging from fundamental physical chemistry to medical applications. A detailed analysis of the ZFS in a series of symmetric Gd(III) complexes is presented in order to establish the applicability and accuracy of computational methods using multiconfigurational complete-active-space self-consistent field wave functions and of density functional theory calculations. The various computational schemes are then applied to larger complexes Gd(III)DOTA(H2O)-, Gd(III)DTPA(H2O)2-, and Gd(III)(H2O)83+ in order to analyze how the theoretical results compare to experimentally derived parameters. In contrast to approximations based on density functional theory, the multiconfigurational methods produce results for the ZFS of Gd(III) complexes on the correct order of magnitude.

TomoMiner and TomoMinerCloud: A software platform for large-scale subtomogram structural analysis

PubMed Central

Frazier, Zachary; Xu, Min; Alber, Frank

2017-01-01

SUMMARY Cryo-electron tomography (cryoET) captures the 3D electron density distribution of macromolecular complexes in close to native state. With the rapid advance of cryoET acquisition technologies, it is possible to generate large numbers (>100,000) of subtomograms, each containing a macromolecular complex. Often, these subtomograms represent a heterogeneous sample due to variations in structure and composition of a complex in situ form or because particles are a mixture of different complexes. In this case subtomograms must be classified. However, classification of large numbers of subtomograms is a time-intensive task and often a limiting bottleneck. This paper introduces an open source software platform, TomoMiner, for large-scale subtomogram classification, template matching, subtomogram averaging, and alignment. Its scalable and robust parallel processing allows efficient classification of tens to hundreds of thousands of subtomograms. Additionally, TomoMiner provides a pre-configured TomoMinerCloud computing service permitting users without sufficient computing resources instant access to TomoMiners high-performance features. PMID:28552576

The influence of computational assumptions on analysing abdominal aortic aneurysm haemodynamics.

PubMed

Ene, Florentina; Delassus, Patrick; Morris, Liam

2014-08-01

The variation in computational assumptions for analysing abdominal aortic aneurysm haemodynamics can influence the desired output results and computational cost. Such assumptions for abdominal aortic aneurysm modelling include static/transient pressures, steady/transient flows and rigid/compliant walls. Six computational methods and these various assumptions were simulated and compared within a realistic abdominal aortic aneurysm model with and without intraluminal thrombus. A full transient fluid-structure interaction was required to analyse the flow patterns within the compliant abdominal aortic aneurysms models. Rigid wall computational fluid dynamics overestimates the velocity magnitude by as much as 40%-65% and the wall shear stress by 30%-50%. These differences were attributed to the deforming walls which reduced the outlet volumetric flow rate for the transient fluid-structure interaction during the majority of the systolic phase. Static finite element analysis accurately approximates the deformations and von Mises stresses when compared with transient fluid-structure interaction. Simplifying the modelling complexity reduces the computational cost significantly. In conclusion, the deformation and von Mises stress can be approximately found by static finite element analysis, while for compliant models a full transient fluid-structure interaction analysis is required for acquiring the fluid flow phenomenon. © IMechE 2014.

Complexity Bounds for Quantum Computation

DTIC Science & Technology

2007-06-22

Programs Trustees of Boston University Boston, MA 02215 - Complexity Bounds for Quantum Computation REPORT DOCUMENTATION PAGE 18. SECURITY CLASSIFICATION...Complexity Bounds for Quantum Comp[utation Report Title ABSTRACT This project focused on upper and lower bounds for quantum computability using constant...classical computation models, particularly emphasizing new examples of where quantum circuits are more powerful than their classical counterparts. A second

Fluid/Structure Interaction Studies of Aircraft Using High Fidelity Equations on Parallel Computers

NASA Technical Reports Server (NTRS)

Guruswamy, Guru; VanDalsem, William (Technical Monitor)

1994-01-01

Abstract Aeroelasticity which involves strong coupling of fluids, structures and controls is an important element in designing an aircraft. Computational aeroelasticity using low fidelity methods such as the linear aerodynamic flow equations coupled with the modal structural equations are well advanced. Though these low fidelity approaches are computationally less intensive, they are not adequate for the analysis of modern aircraft such as High Speed Civil Transport (HSCT) and Advanced Subsonic Transport (AST) which can experience complex flow/structure interactions. HSCT can experience vortex induced aeroelastic oscillations whereas AST can experience transonic buffet associated structural oscillations. Both aircraft may experience a dip in the flutter speed at the transonic regime. For accurate aeroelastic computations at these complex fluid/structure interaction situations, high fidelity equations such as the Navier-Stokes for fluids and the finite-elements for structures are needed. Computations using these high fidelity equations require large computational resources both in memory and speed. Current conventional super computers have reached their limitations both in memory and speed. As a result, parallel computers have evolved to overcome the limitations of conventional computers. This paper will address the transition that is taking place in computational aeroelasticity from conventional computers to parallel computers. The paper will address special techniques needed to take advantage of the architecture of new parallel computers. Results will be illustrated from computations made on iPSC/860 and IBM SP2 computer by using ENSAERO code that directly couples the Euler/Navier-Stokes flow equations with high resolution finite-element structural equations.

Interactive computer graphics and its role in control system design of large space structures

NASA Technical Reports Server (NTRS)

Reddy, A. S. S. R.

1985-01-01

This paper attempts to show the relevance of interactive computer graphics in the design of control systems to maintain attitude and shape of large space structures to accomplish the required mission objectives. The typical phases of control system design, starting from the physical model such as modeling the dynamics, modal analysis, and control system design methodology are reviewed and the need of the interactive computer graphics is demonstrated. Typical constituent parts of large space structures such as free-free beams and free-free plates are used to demonstrate the complexity of the control system design and the effectiveness of the interactive computer graphics.

High-Performance Data Analysis Tools for Sun-Earth Connection Missions

NASA Technical Reports Server (NTRS)

Messmer, Peter

2011-01-01

The data analysis tool of choice for many Sun-Earth Connection missions is the Interactive Data Language (IDL) by ITT VIS. The increasing amount of data produced by these missions and the increasing complexity of image processing algorithms requires access to higher computing power. Parallel computing is a cost-effective way to increase the speed of computation, but algorithms oftentimes have to be modified to take advantage of parallel systems. Enhancing IDL to work on clusters gives scientists access to increased performance in a familiar programming environment. The goal of this project was to enable IDL applications to benefit from both computing clusters as well as graphics processing units (GPUs) for accelerating data analysis tasks. The tool suite developed in this project enables scientists now to solve demanding data analysis problems in IDL that previously required specialized software, and it allows them to be solved orders of magnitude faster than on conventional PCs. The tool suite consists of three components: (1) TaskDL, a software tool that simplifies the creation and management of task farms, collections of tasks that can be processed independently and require only small amounts of data communication; (2) mpiDL, a tool that allows IDL developers to use the Message Passing Interface (MPI) inside IDL for problems that require large amounts of data to be exchanged among multiple processors; and (3) GPULib, a tool that simplifies the use of GPUs as mathematical coprocessors from within IDL. mpiDL is unique in its support for the full MPI standard and its support of a broad range of MPI implementations. GPULib is unique in enabling users to take advantage of an inexpensive piece of hardware, possibly already installed in their computer, and achieve orders of magnitude faster execution time for numerically complex algorithms. TaskDL enables the simple setup and management of task farms on compute clusters. The products developed in this project have the potential to interact, so one can build a cluster of PCs, each equipped with a GPU, and use mpiDL to communicate between the nodes and GPULib to accelerate the computations on each node.

Medical image computing for computer-supported diagnostics and therapy. Advances and perspectives.

PubMed

Handels, H; Ehrhardt, J

2009-01-01

Medical image computing has become one of the most challenging fields in medical informatics. In image-based diagnostics of the future software assistance will become more and more important, and image analysis systems integrating advanced image computing methods are needed to extract quantitative image parameters to characterize the state and changes of image structures of interest (e.g. tumors, organs, vessels, bones etc.) in a reproducible and objective way. Furthermore, in the field of software-assisted and navigated surgery medical image computing methods play a key role and have opened up new perspectives for patient treatment. However, further developments are needed to increase the grade of automation, accuracy, reproducibility and robustness. Moreover, the systems developed have to be integrated into the clinical workflow. For the development of advanced image computing systems methods of different scientific fields have to be adapted and used in combination. The principal methodologies in medical image computing are the following: image segmentation, image registration, image analysis for quantification and computer assisted image interpretation, modeling and simulation as well as visualization and virtual reality. Especially, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients and will gain importance in diagnostic and therapy of the future. From a methodical point of view the authors identify the following future trends and perspectives in medical image computing: development of optimized application-specific systems and integration into the clinical workflow, enhanced computational models for image analysis and virtual reality training systems, integration of different image computing methods, further integration of multimodal image data and biosignals and advanced methods for 4D medical image computing. The development of image analysis systems for diagnostic support or operation planning is a complex interdisciplinary process. Image computing methods enable new insights into the patient's image data and have the future potential to improve medical diagnostics and patient treatment.

Multifractal analysis of information processing in hippocampal neural ensembles during working memory under Δ9-tetrahydrocannabinol administration

PubMed Central

Fetterhoff, Dustin; Opris, Ioan; Simpson, Sean L.; Deadwyler, Sam A.; Hampson, Robert E.; Kraft, Robert A.

2014-01-01

Background Multifractal analysis quantifies the time-scale-invariant properties in data by describing the structure of variability over time. By applying this analysis to hippocampal interspike interval sequences recorded during performance of a working memory task, a measure of long-range temporal correlations and multifractal dynamics can reveal single neuron correlates of information processing. New method Wavelet leaders-based multifractal analysis (WLMA) was applied to hippocampal interspike intervals recorded during a working memory task. WLMA can be used to identify neurons likely to exhibit information processing relevant to operation of brain–computer interfaces and nonlinear neuronal models. Results Neurons involved in memory processing (“Functional Cell Types” or FCTs) showed a greater degree of multifractal firing properties than neurons without task-relevant firing characteristics. In addition, previously unidentified FCTs were revealed because multifractal analysis suggested further functional classification. The cannabinoid-type 1 receptor partial agonist, tetrahydrocannabinol (THC), selectively reduced multifractal dynamics in FCT neurons compared to non-FCT neurons. Comparison with existing methods WLMA is an objective tool for quantifying the memory-correlated complexity represented by FCTs that reveals additional information compared to classification of FCTs using traditional z-scores to identify neuronal correlates of behavioral events. Conclusion z-Score-based FCT classification provides limited information about the dynamical range of neuronal activity characterized by WLMA. Increased complexity, as measured with multifractal analysis, may be a marker of functional involvement in memory processing. The level of multifractal attributes can be used to differentially emphasize neural signals to improve computational models and algorithms underlying brain–computer interfaces. PMID:25086297

Performance analysis of a dual-tree algorithm for computing spatial distance histograms

PubMed Central

Chen, Shaoping; Tu, Yi-Cheng; Xia, Yuni

2011-01-01

Many scientific and engineering fields produce large volume of spatiotemporal data. The storage, retrieval, and analysis of such data impose great challenges to database systems design. Analysis of scientific spatiotemporal data often involves computing functions of all point-to-point interactions. One such analytics, the Spatial Distance Histogram (SDH), is of vital importance to scientific discovery. Recently, algorithms for efficient SDH processing in large-scale scientific databases have been proposed. These algorithms adopt a recursive tree-traversing strategy to process point-to-point distances in the visited tree nodes in batches, thus require less time when compared to the brute-force approach where all pairwise distances have to be computed. Despite the promising experimental results, the complexity of such algorithms has not been thoroughly studied. In this paper, we present an analysis of such algorithms based on a geometric modeling approach. The main technique is to transform the analysis of point counts into a problem of quantifying the area of regions where pairwise distances can be processed in batches by the algorithm. From the analysis, we conclude that the number of pairwise distances that are left to be processed decreases exponentially with more levels of the tree visited. This leads to the proof of a time complexity lower than the quadratic time needed for a brute-force algorithm and builds the foundation for a constant-time approximate algorithm. Our model is also general in that it works for a wide range of point spatial distributions, histogram types, and space-partitioning options in building the tree. PMID:21804753

Machine learning applications in genetics and genomics.

PubMed

Libbrecht, Maxwell W; Noble, William Stafford

2015-06-01

The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets. Here, we provide an overview of machine learning applications for the analysis of genome sequencing data sets, including the annotation of sequence elements and epigenetic, proteomic or metabolomic data. We present considerations and recurrent challenges in the application of supervised, semi-supervised and unsupervised machine learning methods, as well as of generative and discriminative modelling approaches. We provide general guidelines to assist in the selection of these machine learning methods and their practical application for the analysis of genetic and genomic data sets.

Computer-assisted concept mapping: Visual aids for knowledge construction

PubMed Central

Mammen, Jennifer R.

2016-01-01

Background Concept mapping is a visual representation of ideas that facilitates critical thinking and is applicable to many areas of nursing education. Computer-Assisted Concept Maps are more flexible and less constrained than traditional paper methods, allowing for analysis and synthesis of complex topics and larger amounts of data. Ability to iteratively revise and collaboratively create computerized maps can contribute to enhanced interpersonal learning. However, there is limited awareness of free software that can support these types of applications. Discussion This educational brief examines affordances and limitations of Computer-Assisted Concept Maps and reviews free software for development of complex, collaborative malleable maps. Free software such as VUE, Xmind, MindMaple, and others can substantially contribute to utility of concept-mapping for nursing education. Conclusions Computerized concept-mapping is an important tool for nursing and is likely to hold greater benefit for students and faculty than traditional pen and paper methods alone. PMID:27351610

Fast dictionary generation and searching for magnetic resonance fingerprinting.

PubMed

Jun Xie; Mengye Lyu; Jian Zhang; Hui, Edward S; Wu, Ed X; Ze Wang

2017-07-01

A super-fast dictionary generation and searching (DGS) algorithm was developed for MR parameter quantification using magnetic resonance fingerprinting (MRF). MRF is a new technique for simultaneously quantifying multiple MR parameters using one temporally resolved MR scan. But it has a multiplicative computation complexity, resulting in a big burden of dictionary generating, saving, and retrieving, which can easily be intractable for any state-of-art computers. Based on retrospective analysis of the dictionary matching object function, a multi-scale ZOOM like DGS algorithm, dubbed as MRF-ZOOM, was proposed. MRF ZOOM is quasi-parameter-separable so the multiplicative computation complexity is broken into additive one. Evaluations showed that MRF ZOOM was hundreds or thousands of times faster than the original MRF parameter quantification method even without counting the dictionary generation time in. Using real data, it yielded nearly the same results as produced by the original method. MRF ZOOM provides a super-fast solution for MR parameter quantification.

Computer-assisted spinal osteotomy: a technical note and report of four cases.

PubMed

Fujibayashi, Shunsuke; Neo, Masashi; Takemoto, Mitsuru; Ota, Masato; Nakayama, Tomitaka; Toguchida, Junya; Nakamura, Takashi

2010-08-15

A report of 4 cases of spinal osteotomy performed under the guidance of a computer-assisted navigation system and a technical note about the use of the navigation system for spinal osteotomy. To document the surgical technique and usefulness of computer-assisted surgery for spinal osteotomy. A computer-assisted navigation system provides accurate 3-dimensional (3D) real-time surgical information during the operation. Although there are many reports on the accuracy and usefulness of a navigation system for pedicle screw placement, there are few reports on the application for spinal osteotomy. We report on 4 complex cases including 3 solitary malignant spinal tumors and 1 spinal kyphotic deformity of ankylosing spondylitis, which were treated surgically using a computer-assisted spinal osteotomy. The surgical technique and postoperative clinical and radiologic results are presented. 3D spinal osteotomy under the guidance of a computer-assisted navigation system was performed successfully in 4 patients. All malignant tumors were resected en bloc, and the spinal deformity was corrected precisely according to the preoperative plan. Pathologic analysis confirmed the en bloc resection without tumor exposure in the 3 patients with a spinal tumor. The use of a computer-assisted navigation system will help ensure the safety and efficacy of a complex 3D spinal osteotomy.

Three VO2+ complexes of the pyridoxal-derived Schiff bases: Synthesis, experimental and theoretical characterizations, and catalytic activity in a cyclocondensation reaction

NASA Astrophysics Data System (ADS)

Jafari-Moghaddam, Faezeh; Beyramabadi, S. Ali; Khashi, Maryam; Morsali, Ali

2018-02-01

Three oxovanadium(IV) complexes of the pyridoxal Schiff bases have been newly synthesized and characterized. The used Schiff bases were N,N‧-dipyridoxyl(ethylenediamine), N,N‧-dipyridoxyl(1,3-propanediamine) and N,N‧-dipyridoxyl(1,2-benzenediamine). Also, the optimized geometry, assignment of the IR bands and the Natural Bond Orbital (NBO) analysis of the complexes have been computed using the density functional theory (DFT) methods. Dianionic form of the Schiff bases (L2-) acts as a tetradentate N2O2 ligand. The coordinating atoms of the Schiff base are the phenolate oxygens and imine nitrogens, which occupy four base positions of the square-pyramidal geometry of the complexes. The oxo ligand occupies the apical position of the [VO(L)] complexes. In the optimized geometry of the complexes, the coordinated Schiff bases have more planar structure than their free form. Due to the high-energy gaps, all of the complexes are predicted to be stable. Good agreement between the experimental values and the DFT-computed results supports suitability of the optimized geometries for the complexes. The investigated complexes show high catalytic activities in synthesis of the tetrahydrobenzo[b]pyrans through a three-component cyclocondensation reaction of dimedone, malononitrile and some aromatic aldehydes. The complexes catalyzed the reaction in solvent free conditions and the catalysts were found to be reusable.

Characterising Complex Enzyme Reaction Data

PubMed Central

Rahman, Syed Asad; Thornton, Janet M.

2016-01-01

The relationship between enzyme-catalysed reactions and the Enzyme Commission (EC) number, the widely accepted classification scheme used to characterise enzyme activity, is complex and with the rapid increase in our knowledge of the reactions catalysed by enzymes needs revisiting. We present a manual and computational analysis to investigate this complexity and found that almost one-third of all known EC numbers are linked to more than one reaction in the secondary reaction databases (e.g., KEGG). Although this complexity is often resolved by defining generic, alternative and partial reactions, we have also found individual EC numbers with more than one reaction catalysing different types of bond changes. This analysis adds a new dimension to our understanding of enzyme function and might be useful for the accurate annotation of the function of enzymes and to study the changes in enzyme function during evolution. PMID:26840640

Examining the Use of Computers in Writing by Learners of Japanese as a Foreign Language: Analysis of Kanji in the Handwritten and Typed Domains

ERIC Educational Resources Information Center

Dixon, Michael

2012-01-01

This study compares second-year Japanese university students' strategies to write kanji by hand with their strategies to produce the kanji characters on a computer, taking into account factors such as accuracy in writing, the amount of kanji used, the complexity of the kanji used, as well as how the characters used compare with the sequence…

Programs for transferring data between a relational data base and a finite element structural analysis program

NASA Technical Reports Server (NTRS)

Johnson, S. C.

1982-01-01

An interface system for passing data between a relational information management (RIM) data base complex and engineering analysis language (EAL), a finite element structural analysis program is documented. The interface system, implemented on a CDC Cyber computer, is composed of two FORTRAN programs called RIM2EAL and EAL2RIM. The RIM2EAL reads model definition data from RIM and creates a file of EAL commands to define the model. The EAL2RIM reads model definition and EAL generated analysis data from EAL's data library and stores these data dirctly in a RIM data base. These two interface programs and the format for the RIM data complex are described.

Connecting People to Places : Spatiotemporal Analysis of Transit Supply Using Travel Time Cubes

DOT National Transportation Integrated Search

2016-06-01

Despite its importance, temporal measures of accessibility are rarely used in transit research or practice. This is primarily due to the inherent difficulty and complexity in computing time-based accessibility metrics. Estimating origin-to-destinatio...

Cayley transform on Stiefel manifolds

NASA Astrophysics Data System (ADS)

Macías-Virgós, Enrique; Pereira-Sáez, María José; Tanré, Daniel

2018-01-01

The Cayley transform for orthogonal groups is a well known construction with applications in real and complex analysis, linear algebra and computer science. In this work, we construct Cayley transforms on Stiefel manifolds. Applications to the Lusternik-Schnirelmann category and optimization problems are presented.

The trigonal prism in coordination chemistry.

PubMed

Cremades, Eduard; Echeverría, Jorge; Alvarez, Santiago

2010-09-10

Herein we analyze the accessibility of the trigonal-prismatic geometry to metal complexes with different electron configurations, as well as the ability of several hexadentate ligands to favor that coordination polyhedron. Our study combines i) a structural database analysis of the occurrence of the prismatic geometry throughout the transition-metal series, ii) a qualitative molecular orbital analysis of the distortions expected for a trigonal-prismatic geometry, and iii) a computational study of complexes of several transition-metal ions with different hexadentate ligands. Also the tendency of specific electron configurations to present a cis bond-stretch Jahn-Teller distortion is analyzed.

Qualitative analysis of a discrete thermostatted kinetic framework modeling complex adaptive systems

NASA Astrophysics Data System (ADS)

Bianca, Carlo; Mogno, Caterina

2018-01-01

This paper deals with the derivation of a new discrete thermostatted kinetic framework for the modeling of complex adaptive systems subjected to external force fields (nonequilibrium system). Specifically, in order to model nonequilibrium stationary states of the system, the external force field is coupled to a dissipative term (thermostat). The well-posedness of the related Cauchy problem is investigated thus allowing the new discrete thermostatted framework to be suitable for the derivation of specific models and the related computational analysis. Applications to crowd dynamics and future research directions are also discussed within the paper.

A Fast Method for Embattling Optimization of Ground-Based Radar Surveillance Network

NASA Astrophysics Data System (ADS)

Jiang, H.; Cheng, H.; Zhang, Y.; Liu, J.

A growing number of space activities have created an orbital debris environment that poses increasing impact risks to existing space systems and human space flight. For the safety of in-orbit spacecraft, a lot of observation facilities are needed to catalog space objects, especially in low earth orbit. Surveillance of Low earth orbit objects are mainly rely on ground-based radar, due to the ability limitation of exist radar facilities, a large number of ground-based radar need to build in the next few years in order to meet the current space surveillance demands. How to optimize the embattling of ground-based radar surveillance network is a problem to need to be solved. The traditional method for embattling optimization of ground-based radar surveillance network is mainly through to the detection simulation of all possible stations with cataloged data, and makes a comprehensive comparative analysis of various simulation results with the combinational method, and then selects an optimal result as station layout scheme. This method is time consuming for single simulation and high computational complexity for the combinational analysis, when the number of stations increases, the complexity of optimization problem will be increased exponentially, and cannot be solved with traditional method. There is no better way to solve this problem till now. In this paper, target detection procedure was simplified. Firstly, the space coverage of ground-based radar was simplified, a space coverage projection model of radar facilities in different orbit altitudes was built; then a simplified objects cross the radar coverage model was established according to the characteristics of space objects orbit motion; after two steps simplification, the computational complexity of the target detection was greatly simplified, and simulation results shown the correctness of the simplified results. In addition, the detection areas of ground-based radar network can be easily computed with the simplified model, and then optimized the embattling of ground-based radar surveillance network with the artificial intelligent algorithm, which can greatly simplifies the computational complexities. Comparing with the traditional method, the proposed method greatly improved the computational efficiency.

Grammatical analysis as a distributed neurobiological function.

PubMed

Bozic, Mirjana; Fonteneau, Elisabeth; Su, Li; Marslen-Wilson, William D

2015-03-01

Language processing engages large-scale functional networks in both hemispheres. Although it is widely accepted that left perisylvian regions have a key role in supporting complex grammatical computations, patient data suggest that some aspects of grammatical processing could be supported bilaterally. We investigated the distribution and the nature of grammatical computations across language processing networks by comparing two types of combinatorial grammatical sequences--inflectionally complex words and minimal phrases--and contrasting them with grammatically simple words. Novel multivariate analyses revealed that they engage a coalition of separable subsystems: inflected forms triggered left-lateralized activation, dissociable into dorsal processes supporting morphophonological parsing and ventral, lexically driven morphosyntactic processes. In contrast, simple phrases activated a consistently bilateral pattern of temporal regions, overlapping with inflectional activations in L middle temporal gyrus. These data confirm the role of the left-lateralized frontotemporal network in supporting complex grammatical computations. Critically, they also point to the capacity of bilateral temporal regions to support simple, linear grammatical computations. This is consistent with a dual neurobiological framework where phylogenetically older bihemispheric systems form part of the network that supports language function in the modern human, and where significant capacities for language comprehension remain intact even following severe left hemisphere damage. Copyright © 2014 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Local spatio-temporal analysis in vision systems

NASA Astrophysics Data System (ADS)

Geisler, Wilson S.; Bovik, Alan; Cormack, Lawrence; Ghosh, Joydeep; Gildeen, David

1994-07-01

The aims of this project are the following: (1) develop a physiologically and psychophysically based model of low-level human visual processing (a key component of which are local frequency coding mechanisms); (2) develop image models and image-processing methods based upon local frequency coding; (3) develop algorithms for performing certain complex visual tasks based upon local frequency representations, (4) develop models of human performance in certain complex tasks based upon our understanding of low-level processing; and (5) develop a computational testbed for implementing, evaluating and visualizing the proposed models and algorithms, using a massively parallel computer. Progress has been substantial on all aims. The highlights include the following: (1) completion of a number of psychophysical and physiological experiments revealing new, systematic and exciting properties of the primate (human and monkey) visual system; (2) further development of image models that can accurately represent the local frequency structure in complex images; (3) near completion in the construction of the Texas Active Vision Testbed; (4) development and testing of several new computer vision algorithms dealing with shape-from-texture, shape-from-stereo, and depth-from-focus; (5) implementation and evaluation of several new models of human visual performance; and (6) evaluation, purchase and installation of a MasPar parallel computer.

An affinity-structure database of helix-turn-helix: DNA complexes with a universal coordinate system

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

AlQuraishi, Mohammed; Tang, Shengdong; Xia, Xide

Molecular interactions between proteins and DNA molecules underlie many cellular processes, including transcriptional regulation, chromosome replication, and nucleosome positioning. Computational analyses of protein-DNA interactions rely on experimental data characterizing known protein-DNA interactions structurally and biochemically. While many databases exist that contain either structural or biochemical data, few integrate these two data sources in a unified fashion. Such integration is becoming increasingly critical with the rapid growth of structural and biochemical data, and the emergence of algorithms that rely on the synthesis of multiple data types to derive computational models of molecular interactions. We have developed an integrated affinity-structure database inmore » which the experimental and quantitative DNA binding affinities of helix-turn-helix proteins are mapped onto the crystal structures of the corresponding protein-DNA complexes. This database provides access to: (i) protein-DNA structures, (ii) quantitative summaries of protein-DNA binding affinities using position weight matrices, and (iii) raw experimental data of protein-DNA binding instances. Critically, this database establishes a correspondence between experimental structural data and quantitative binding affinity data at the single basepair level. Furthermore, we present a novel alignment algorithm that structurally aligns the protein-DNA complexes in the database and creates a unified residue-level coordinate system for comparing the physico-chemical environments at the interface between complexes. Using this unified coordinate system, we compute the statistics of atomic interactions at the protein-DNA interface of helix-turn-helix proteins. We provide an interactive website for visualization, querying, and analyzing this database, and a downloadable version to facilitate programmatic analysis. Lastly, this database will facilitate the analysis of protein-DNA interactions and the development of programmatic computational methods that capitalize on integration of structural and biochemical datasets. The database can be accessed at http://ProteinDNA.hms.harvard.edu.« less

An affinity-structure database of helix-turn-helix: DNA complexes with a universal coordinate system

DOE PAGES

AlQuraishi, Mohammed; Tang, Shengdong; Xia, Xide

2015-11-19

Molecular interactions between proteins and DNA molecules underlie many cellular processes, including transcriptional regulation, chromosome replication, and nucleosome positioning. Computational analyses of protein-DNA interactions rely on experimental data characterizing known protein-DNA interactions structurally and biochemically. While many databases exist that contain either structural or biochemical data, few integrate these two data sources in a unified fashion. Such integration is becoming increasingly critical with the rapid growth of structural and biochemical data, and the emergence of algorithms that rely on the synthesis of multiple data types to derive computational models of molecular interactions. We have developed an integrated affinity-structure database inmore » which the experimental and quantitative DNA binding affinities of helix-turn-helix proteins are mapped onto the crystal structures of the corresponding protein-DNA complexes. This database provides access to: (i) protein-DNA structures, (ii) quantitative summaries of protein-DNA binding affinities using position weight matrices, and (iii) raw experimental data of protein-DNA binding instances. Critically, this database establishes a correspondence between experimental structural data and quantitative binding affinity data at the single basepair level. Furthermore, we present a novel alignment algorithm that structurally aligns the protein-DNA complexes in the database and creates a unified residue-level coordinate system for comparing the physico-chemical environments at the interface between complexes. Using this unified coordinate system, we compute the statistics of atomic interactions at the protein-DNA interface of helix-turn-helix proteins. We provide an interactive website for visualization, querying, and analyzing this database, and a downloadable version to facilitate programmatic analysis. Lastly, this database will facilitate the analysis of protein-DNA interactions and the development of programmatic computational methods that capitalize on integration of structural and biochemical datasets. The database can be accessed at http://ProteinDNA.hms.harvard.edu.« less

Studies on the injection molding of polyvinyl chloride: Analysis of viscous heating and degradation in simple geometries

NASA Astrophysics Data System (ADS)

Garcia, Jose Luis

2000-10-01

In injection molding processes, computer aided engineering (CAE) allows processors to evaluate different process parameters in order to achieve complete filling of a cavity and, in some cases, it predicts shrinkage and warpage. However, because commercial computational packages are used to design complex geometries, detail in the thickness direction is limited. Approximations in the thickness direction lead to the solution of a 2½-D problem instead of a 3-D problem. These simplifications drastically reduce computational times and memory requirements. However, these approximations hinder the ability to predict thermal and/or mechanical degradation. The goal of this study was to determine the degree of degradation during PVC injection molding and to compare the results with a computational model. Instead of analyzing degradation in complex geometries, the computational analysis and injection molding trials were performed on typical sections found in complex geometries, such as flow in a tube, flow in a rectangular channel, and radial flow. This simplification reduces the flow problem to a 1-D problem and allows one to develop a computational model with a higher level of detail in the thickness direction, essential for the determination of degradation. Two different geometries were examined in this study: a spiral mold, in order to approximate the rectangular channel, and a center gated plate for the radial flow. Injection speed, melt temperature, and shot size were varied. Parts varying in degree of degradation, from no to severe degradation, were produced to determine possible transition points. Furthermore, two different PVC materials were used, low and high viscosity, M3800 and M4200, respectively (The Geon Company, Avon Lake, OH), to correlate the degree of degradation with the viscous heating observed during injection. It was found that a good agreement between experimental and computational results was obtained only if the reaction was assumed to be more thermally sensitive than found in literature. The results from this study show that, during injection, the activation energy for degradation was 65 kcal/mol, compared to 17--30 kcal/mol found in literature for quiescent systems.

A novel method for automated grid generation of ice shapes for local-flow analysis

NASA Astrophysics Data System (ADS)

Ogretim, Egemen; Huebsch, Wade W.

2004-02-01

Modelling a complex geometry, such as ice roughness, plays a key role for the computational flow analysis over rough surfaces. This paper presents two enhancement ideas in modelling roughness geometry for local flow analysis over an aerodynamic surface. The first enhancement is use of the leading-edge region of an airfoil as a perturbation to the parabola surface. The reasons for using a parabola as the base geometry are: it resembles the airfoil leading edge in the vicinity of its apex and it allows the use of a lower apparent Reynolds number. The second enhancement makes use of the Fourier analysis for modelling complex ice roughness on the leading edge of airfoils. This method of modelling provides an analytical expression, which describes the roughness geometry and the corresponding derivatives. The factors affecting the performance of the Fourier analysis were also investigated. It was shown that the number of sine-cosine terms and the number of control points are of importance. Finally, these enhancements are incorporated into an automated grid generation method over the airfoil ice accretion surface. The validations for both enhancements demonstrate that they can improve the current capability of grid generation and computational flow field analysis around airfoils with ice roughness.

Structured analysis and modeling of complex systems

NASA Technical Reports Server (NTRS)

Strome, David R.; Dalrymple, Mathieu A.

1992-01-01

The Aircrew Evaluation Sustained Operations Performance (AESOP) facility at Brooks AFB, Texas, combines the realism of an operational environment with the control of a research laboratory. In recent studies we collected extensive data from the Airborne Warning and Control Systems (AWACS) Weapons Directors subjected to high and low workload Defensive Counter Air Scenarios. A critical and complex task in this environment involves committing a friendly fighter against a hostile fighter. Structured Analysis and Design techniques and computer modeling systems were applied to this task as tools for analyzing subject performance and workload. This technology is being transferred to the Man-Systems Division of NASA Johnson Space Center for application to complex mission related tasks, such as manipulating the Shuttle grappler arm.

Recurrence Density Enhanced Complex Networks for Nonlinear Time Series Analysis

NASA Astrophysics Data System (ADS)

Costa, Diego G. De B.; Reis, Barbara M. Da F.; Zou, Yong; Quiles, Marcos G.; Macau, Elbert E. N.

We introduce a new method, which is entitled Recurrence Density Enhanced Complex Network (RDE-CN), to properly analyze nonlinear time series. Our method first transforms a recurrence plot into a figure of a reduced number of points yet preserving the main and fundamental recurrence properties of the original plot. This resulting figure is then reinterpreted as a complex network, which is further characterized by network statistical measures. We illustrate the computational power of RDE-CN approach by time series by both the logistic map and experimental fluid flows, which show that our method distinguishes different dynamics sufficiently well as the traditional recurrence analysis. Therefore, the proposed methodology characterizes the recurrence matrix adequately, while using a reduced set of points from the original recurrence plots.

Model-based spectral estimation of Doppler signals using parallel genetic algorithms.

PubMed

Solano González, J; Rodríguez Vázquez, K; García Nocetti, D F

2000-05-01

Conventional spectral analysis methods use a fast Fourier transform (FFT) on consecutive or overlapping windowed data segments. For Doppler ultrasound signals, this approach suffers from an inadequate frequency resolution due to the time segment duration and the non-stationarity characteristics of the signals. Parametric or model-based estimators can give significant improvements in the time-frequency resolution at the expense of a higher computational complexity. This work describes an approach which implements in real-time a parametric spectral estimator method using genetic algorithms (GAs) in order to find the optimum set of parameters for the adaptive filter that minimises the error function. The aim is to reduce the computational complexity of the conventional algorithm by using the simplicity associated to GAs and exploiting its parallel characteristics. This will allow the implementation of higher order filters, increasing the spectrum resolution, and opening a greater scope for using more complex methods.

Nonparametric estimation of stochastic differential equations with sparse Gaussian processes.

PubMed

García, Constantino A; Otero, Abraham; Félix, Paulo; Presedo, Jesús; Márquez, David G

2017-08-01

The application of stochastic differential equations (SDEs) to the analysis of temporal data has attracted increasing attention, due to their ability to describe complex dynamics with physically interpretable equations. In this paper, we introduce a nonparametric method for estimating the drift and diffusion terms of SDEs from a densely observed discrete time series. The use of Gaussian processes as priors permits working directly in a function-space view and thus the inference takes place directly in this space. To cope with the computational complexity that requires the use of Gaussian processes, a sparse Gaussian process approximation is provided. This approximation permits the efficient computation of predictions for the drift and diffusion terms by using a distribution over a small subset of pseudosamples. The proposed method has been validated using both simulated data and real data from economy and paleoclimatology. The application of the method to real data demonstrates its ability to capture the behavior of complex systems.

Progressive Damage and Failure Analysis of Composite Laminates

NASA Astrophysics Data System (ADS)

Joseph, Ashith P. K.

Composite materials are widely used in various industries for making structural parts due to higher strength to weight ratio, better fatigue life, corrosion resistance and material property tailorability. To fully exploit the capability of composites, it is required to know the load carrying capacity of the parts made of them. Unlike metals, composites are orthotropic in nature and fails in a complex manner under various loading conditions which makes it a hard problem to analyze. Lack of reliable and efficient failure analysis tools for composites have led industries to rely more on coupon and component level testing to estimate the design space. Due to the complex failure mechanisms, composite materials require a very large number of coupon level tests to fully characterize the behavior. This makes the entire testing process very time consuming and costly. The alternative is to use virtual testing tools which can predict the complex failure mechanisms accurately. This reduces the cost only to it's associated computational expenses making significant savings. Some of the most desired features in a virtual testing tool are - (1) Accurate representation of failure mechanism: Failure progression predicted by the virtual tool must be same as those observed in experiments. A tool has to be assessed based on the mechanisms it can capture. (2) Computational efficiency: The greatest advantages of a virtual tools are the savings in time and money and hence computational efficiency is one of the most needed features. (3) Applicability to a wide range of problems: Structural parts are subjected to a variety of loading conditions including static, dynamic and fatigue conditions. A good virtual testing tool should be able to make good predictions for all these different loading conditions. The aim of this PhD thesis is to develop a computational tool which can model the progressive failure of composite laminates under different quasi-static loading conditions. The analysis tool is validated by comparing the simulations against experiments for a selected number of quasi-static loading cases.

An image processing and analysis tool for identifying and analysing complex plant root systems in 3D soil using non-destructive analysis: Root1.

PubMed

Flavel, Richard J; Guppy, Chris N; Rabbi, Sheikh M R; Young, Iain M

2017-01-01

The objective of this study was to develop a flexible and free image processing and analysis solution, based on the Public Domain ImageJ platform, for the segmentation and analysis of complex biological plant root systems in soil from x-ray tomography 3D images. Contrasting root architectures from wheat, barley and chickpea root systems were grown in soil and scanned using a high resolution micro-tomography system. A macro (Root1) was developed that reliably identified with good to high accuracy complex root systems (10% overestimation for chickpea, 1% underestimation for wheat, 8% underestimation for barley) and provided analysis of root length and angle. In-built flexibility allowed the user interaction to (a) amend any aspect of the macro to account for specific user preferences, and (b) take account of computational limitations of the platform. The platform is free, flexible and accurate in analysing root system metrics.

[Computers in biomedical research: I. Analysis of bioelectrical signals].

PubMed

Vivaldi, E A; Maldonado, P

2001-08-01

A personal computer equipped with an analog-to-digital conversion card is able to input, store and display signals of biomedical interest. These signals can additionally be submitted to ad-hoc software for analysis and diagnosis. Data acquisition is based on the sampling of a signal at a given rate and amplitude resolution. The automation of signal processing conveys syntactic aspects (data transduction, conditioning and reduction); and semantic aspects (feature extraction to describe and characterize the signal and diagnostic classification). The analytical approach that is at the basis of computer programming allows for the successful resolution of apparently complex tasks. Two basic principles involved are the definition of simple fundamental functions that are then iterated and the modular subdivision of tasks. These two principles are illustrated, respectively, by presenting the algorithm that detects relevant elements for the analysis of a polysomnogram, and the task flow in systems that automate electrocardiographic reports.

Methods for simulation-based analysis of fluid-structure interaction.

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

Barone, Matthew Franklin; Payne, Jeffrey L.

2005-10-01

Methods for analysis of fluid-structure interaction using high fidelity simulations are critically reviewed. First, a literature review of modern numerical techniques for simulation of aeroelastic phenomena is presented. The review focuses on methods contained within the arbitrary Lagrangian-Eulerian (ALE) framework for coupling computational fluid dynamics codes to computational structural mechanics codes. The review treats mesh movement algorithms, the role of the geometric conservation law, time advancement schemes, wetted surface interface strategies, and some representative applications. The complexity and computational expense of coupled Navier-Stokes/structural dynamics simulations points to the need for reduced order modeling to facilitate parametric analysis. The proper orthogonalmore » decomposition (POD)/Galerkin projection approach for building a reduced order model (ROM) is presented, along with ideas for extension of the methodology to allow construction of ROMs based on data generated from ALE simulations.« less

An Application of Overset Grids to Payload/Fairing Three-Dimensional Internal Flow CFD Analysis

NASA Technical Reports Server (NTRS)

Kandula, Max; Nallasamy, R.; Schallhorn, P.; Duncil, L.

2007-01-01

The application of overset grids to the computational fluid dynamics analysis of three-dimensional internal flow in the payload/fairing of an expendable launch vehicle is described. In conjunction with the overset grid system, the flowfield in the payload/fairing configuration is obtained with the aid of OVERFLOW Navier-Stokes code. The solution exhibits a highly three dimensional complex flowfield with swirl, separation, and vortices. Some of the computed flow features are compared with the measured Laser-Doppler Velocimetry (LDV) data on a 1/5th scale model of the payload/fairing configuration. The counter-rotating vortex structures and the location of the saddle point predicted by the CFD analysis are in general agreement with the LDV data. Comparisons of the computed (CFD) velocity profiles on horizontal and vertical lines in the LDV measurement plane in the faring nose region show reasonable agreement with the LDV data.

Two-dimensional finite-element analyses of simulated rotor-fragment impacts against rings and beams compared with experiments

NASA Technical Reports Server (NTRS)

Stagliano, T. R.; Witmer, E. A.; Rodal, J. J. A.

1979-01-01

Finite element modeling alternatives as well as the utility and limitations of the two dimensional structural response computer code CIVM-JET 4B for predicting the transient, large deflection, elastic plastic, structural responses of two dimensional beam and/or ring structures which are subjected to rigid fragment impact were investigated. The applicability of the CIVM-JET 4B analysis and code for the prediction of steel containment ring response to impact by complex deformable fragments from a trihub burst of a T58 turbine rotor was studied. Dimensional analysis considerations were used in a parametric examination of data from engine rotor burst containment experiments and data from sphere beam impact experiments. The use of the CIVM-JET 4B computer code for making parametric structural response studies on both fragment-containment structure and fragment-deflector structure was illustrated. Modifications to the analysis/computation procedure were developed to alleviate restrictions.

Computer-aided molecular modeling techniques for predicting the stability of drug cyclodextrin inclusion complexes in aqueous solutions

NASA Astrophysics Data System (ADS)

Faucci, Maria Teresa; Melani, Fabrizio; Mura, Paola

2002-06-01

Molecular modeling was used to investigate factors influencing complex formation between cyclodextrins and guest molecules and predict their stability through a theoretical model based on the search for a correlation between experimental stability constants ( Ks) and some theoretical parameters describing complexation (docking energy, host-guest contact surfaces, intermolecular interaction fields) calculated from complex structures at a minimum conformational energy, obtained through stochastic methods based on molecular dynamic simulations. Naproxen, ibuprofen, ketoprofen and ibuproxam were used as model drug molecules. Multiple Regression Analysis allowed identification of the significant factors for the complex stability. A mathematical model ( r=0.897) related log Ks with complex docking energy and lipophilic molecular fields of cyclodextrin and drug.

Statistical Analysis of the First Passage Path Ensemble of Jump Processes

NASA Astrophysics Data System (ADS)

von Kleist, Max; Schütte, Christof; Zhang, Wei

2018-02-01

The transition mechanism of jump processes between two different subsets in state space reveals important dynamical information of the processes and therefore has attracted considerable attention in the past years. In this paper, we study the first passage path ensemble of both discrete-time and continuous-time jump processes on a finite state space. The main approach is to divide each first passage path into nonreactive and reactive segments and to study them separately. The analysis can be applied to jump processes which are non-ergodic, as well as continuous-time jump processes where the waiting time distributions are non-exponential. In the particular case that the jump processes are both Markovian and ergodic, our analysis elucidates the relations between the study of the first passage paths and the study of the transition paths in transition path theory. We provide algorithms to numerically compute statistics of the first passage path ensemble. The computational complexity of these algorithms scales with the complexity of solving a linear system, for which efficient methods are available. Several examples demonstrate the wide applicability of the derived results across research areas.

Scalable and cost-effective NGS genotyping in the cloud.

PubMed

Souilmi, Yassine; Lancaster, Alex K; Jung, Jae-Yoon; Rizzo, Ettore; Hawkins, Jared B; Powles, Ryan; Amzazi, Saaïd; Ghazal, Hassan; Tonellato, Peter J; Wall, Dennis P

2015-10-15

While next-generation sequencing (NGS) costs have plummeted in recent years, cost and complexity of computation remain substantial barriers to the use of NGS in routine clinical care. The clinical potential of NGS will not be realized until robust and routine whole genome sequencing data can be accurately rendered to medically actionable reports within a time window of hours and at scales of economy in the 10's of dollars. We take a step towards addressing this challenge, by using COSMOS, a cloud-enabled workflow management system, to develop GenomeKey, an NGS whole genome analysis workflow. COSMOS implements complex workflows making optimal use of high-performance compute clusters. Here we show that the Amazon Web Service (AWS) implementation of GenomeKey via COSMOS provides a fast, scalable, and cost-effective analysis of both public benchmarking and large-scale heterogeneous clinical NGS datasets. Our systematic benchmarking reveals important new insights and considerations to produce clinical turn-around of whole genome analysis optimization and workflow management including strategic batching of individual genomes and efficient cluster resource configuration.

Statistical Surrogate Modeling of Atmospheric Dispersion Events Using Bayesian Adaptive Splines

NASA Astrophysics Data System (ADS)

Francom, D.; Sansó, B.; Bulaevskaya, V.; Lucas, D. D.

2016-12-01

Uncertainty in the inputs of complex computer models, including atmospheric dispersion and transport codes, is often assessed via statistical surrogate models. Surrogate models are computationally efficient statistical approximations of expensive computer models that enable uncertainty analysis. We introduce Bayesian adaptive spline methods for producing surrogate models that capture the major spatiotemporal patterns of the parent model, while satisfying all the necessities of flexibility, accuracy and computational feasibility. We present novel methodological and computational approaches motivated by a controlled atmospheric tracer release experiment conducted at the Diablo Canyon nuclear power plant in California. Traditional methods for building statistical surrogate models often do not scale well to experiments with large amounts of data. Our approach is well suited to experiments involving large numbers of model inputs, large numbers of simulations, and functional output for each simulation. Our approach allows us to perform global sensitivity analysis with ease. We also present an approach to calibration of simulators using field data.

Aerodynamic analysis for aircraft with nacelles, pylons, and winglets at transonic speeds

NASA Technical Reports Server (NTRS)

Boppe, Charles W.

1987-01-01

A computational method has been developed to provide an analysis for complex realistic aircraft configurations at transonic speeds. Wing-fuselage configurations with various combinations of pods, pylons, nacelles, and winglets can be analyzed along with simpler shapes such as airfoils, isolated wings, and isolated bodies. The flexibility required for the treatment of such diverse geometries is obtained by using a multiple nested grid approach in the finite-difference relaxation scheme. Aircraft components (and their grid systems) can be added or removed as required. As a result, the computational method can be used in the same manner as a wind tunnel to study high-speed aerodynamic interference effects. The multiple grid approach also provides high boundary point density/cost ratio. High resolution pressure distributions can be obtained. Computed results are correlated with wind tunnel and flight data using four different transport configurations. Experimental/computational component interference effects are included for cases where data are available. The computer code used for these comparisons is described in the appendices.

Aggregation and metal-complexation behaviour of THPP porphyrin in ethanol/water solutions as function of pH

NASA Astrophysics Data System (ADS)

Zannotti, Marco; Giovannetti, Rita; Minofar, Babak; Řeha, David; Plačková, Lydie; D'Amato, Chiara A.; Rommozzi, Elena; Dudko, Hanna V.; Kari, Nuerguli; Minicucci, Marco

2018-03-01

The effect of pH change on 5,10,15,20-Tetrakis(4-hydroxyphenyl)-21H,23H-porphine (THPP) with its aggregation as function of water-ethanol mixture was studied with UV-vis, fluorescence, Raman and computational analysis. In neutral pH, THPP was present as free-base and, increasing the water amount, aggregation occurred with the formation of H- and J-aggregates. The aggregation constant and the concentration of dimers were calculated, other information about the dimer aggregation were evaluated by computational study. In acidic pH, by the insertions of two hydrogens in the porphyrin rings, the porphyrin changed its geometry with a ring deformation confirmed by red-shifted spectrum and quenching in fluorescence; at this low pH, increasing the water amount, the acidic form (THPPH2)2 + resulted more stable due to a polar environment with stronger interaction by hydrogen bonding. In basic pH, reached by NH4OH, THPP porphyrin was able to react with alkali metals in order to form sitting-atop complex (M2THPP) confirmed by the typical absorption spectrum of metallo-porphyrin, Raman spectroscopy and by computational analysis.

Current Grid Generation Strategies and Future Requirements in Hypersonic Vehicle Design, Analysis and Testing

NASA Technical Reports Server (NTRS)

Papadopoulos, Periklis; Venkatapathy, Ethiraj; Prabhu, Dinesh; Loomis, Mark P.; Olynick, Dave; Arnold, James O. (Technical Monitor)

1998-01-01

Recent advances in computational power enable computational fluid dynamic modeling of increasingly complex configurations. A review of grid generation methodologies implemented in support of the computational work performed for the X-38 and X-33 are presented. In strategizing topological constructs and blocking structures factors considered are the geometric configuration, optimal grid size, numerical algorithms, accuracy requirements, physics of the problem at hand, computational expense, and the available computer hardware. Also addressed are grid refinement strategies, the effects of wall spacing, and convergence. The significance of grid is demonstrated through a comparison of computational and experimental results of the aeroheating environment experienced by the X-38 vehicle. Special topics on grid generation strategies are also addressed to model control surface deflections, and material mapping.

RAP: RNA-Seq Analysis Pipeline, a new cloud-based NGS web application

PubMed Central

2015-01-01

Background The study of RNA has been dramatically improved by the introduction of Next Generation Sequencing platforms allowing massive and cheap sequencing of selected RNA fractions, also providing information on strand orientation (RNA-Seq). The complexity of transcriptomes and of their regulative pathways make RNA-Seq one of most complex field of NGS applications, addressing several aspects of the expression process (e.g. identification and quantification of expressed genes and transcripts, alternative splicing and polyadenylation, fusion genes and trans-splicing, post-transcriptional events, etc.). Moreover, the huge volume of data generated by NGS platforms introduces unprecedented computational and technological challenges to efficiently analyze and store sequence data and results. Methods In order to provide researchers with an effective and friendly resource for analyzing RNA-Seq data, we present here RAP (RNA-Seq Analysis Pipeline), a cloud computing web application implementing a complete but modular analysis workflow. This pipeline integrates both state-of-the-art bioinformatics tools for RNA-Seq analysis and in-house developed scripts to offer to the user a comprehensive strategy for data analysis. RAP is able to perform quality checks (adopting FastQC and NGS QC Toolkit), identify and quantify expressed genes and transcripts (with Tophat, Cufflinks and HTSeq), detect alternative splicing events (using SpliceTrap) and chimeric transcripts (with ChimeraScan). This pipeline is also able to identify splicing junctions and constitutive or alternative polyadenylation sites (implementing custom analysis modules) and call for statistically significant differences in genes and transcripts expression, splicing pattern and polyadenylation site usage (using Cuffdiff2 and DESeq). Results Through a user friendly web interface, the RAP workflow can be suitably customized by the user and it is automatically executed on our cloud computing environment. This strategy allows to access to bioinformatics tools and computational resources without specific bioinformatics and IT skills. RAP provides a set of tabular and graphical results that can be helpful to browse, filter and export analyzed data, according to the user needs. PMID:26046471

External Aiding Methods for IMU-Based Navigation

DTIC Science & Technology

2016-11-26

Carlo simulation and particle filtering . This approach allows for the utilization of highly complex systems in a black box configuration with minimal...alternative method, which has the advantage of being less computationally demanding, is to use a Kalman filtering -based approach. The particular...Kalman filtering -based approach used here is known as linear covariance analysis. In linear covariance analysis, the nonlinear systems describing the

A simplified Forest Inventory and Analysis database: FIADB-Lite

Treesearch

Patrick D. Miles

2008-01-01

This publication is a simplified version of the Forest Inventory and Analysis Data Base (FIADB) for users who do not need to compute sampling errors and may find the FIADB unnecessarily complex. Possible users include GIS specialists who may be interested only in identifying and retrieving geographic information and per acre values for the set of plots used in...

Game Design Narrative for Learning: Appropriating Adventure Game Design Narrative Devices and Techniques for the Design of Interactive Learning Environments

ERIC Educational Resources Information Center

Dickey, Michele D.

2006-01-01

The purpose of this conceptual analysis is to investigate how contemporary video and computer games might inform instructional design by looking at how narrative devices and techniques support problem solving within complex, multimodal environments. Specifically, this analysis presents a brief overview of game genres and the role of narrative in…

Macro-Econophysics

NASA Astrophysics Data System (ADS)

Aoyama, Hideaki; Fujiwara, Yoshi; Ikeda, Yuichi; Iyetomi, Hiroshi; Souma, Wataru; Yoshikawa, Hiroshi

2017-07-01

Preface; Foreword, Acknowledgements, List of tables; List of figures, prologue, 1. Introduction: reconstructing macroeconomics; 2. Basic concepts in statistical physics and stochastic models; 3. Income and firm-size distributions; 4. Productivity distribution and related topics; 5. Multivariate time-series analysis; 6. Business cycles; 7. Price dynamics and inflation/deflation; 8. Complex network, community analysis, visualization; 9. Systemic risks; Appendix A: computer program for beginners; Epilogue; Bibliography; Index.

The GRASP 3: Graphical Reliability Analysis Simulation Program. Version 3: A users' manual and modelling guide

NASA Technical Reports Server (NTRS)

Phillips, D. T.; Manseur, B.; Foster, J. W.

1982-01-01

Alternate definitions of system failure create complex analysis for which analytic solutions are available only for simple, special cases. The GRASP methodology is a computer simulation approach for solving all classes of problems in which both failure and repair events are modeled according to the probability laws of the individual components of the system.

Computational ecology as an emerging science

PubMed Central

Petrovskii, Sergei; Petrovskaya, Natalia

2012-01-01

It has long been recognized that numerical modelling and computer simulations can be used as a powerful research tool to understand, and sometimes to predict, the tendencies and peculiarities in the dynamics of populations and ecosystems. It has been, however, much less appreciated that the context of modelling and simulations in ecology is essentially different from those that normally exist in other natural sciences. In our paper, we review the computational challenges arising in modern ecology in the spirit of computational mathematics, i.e. with our main focus on the choice and use of adequate numerical methods. Somewhat paradoxically, the complexity of ecological problems does not always require the use of complex computational methods. This paradox, however, can be easily resolved if we recall that application of sophisticated computational methods usually requires clear and unambiguous mathematical problem statement as well as clearly defined benchmark information for model validation. At the same time, many ecological problems still do not have mathematically accurate and unambiguous description, and available field data are often very noisy, and hence it can be hard to understand how the results of computations should be interpreted from the ecological viewpoint. In this scientific context, computational ecology has to deal with a new paradigm: conventional issues of numerical modelling such as convergence and stability become less important than the qualitative analysis that can be provided with the help of computational techniques. We discuss this paradigm by considering computational challenges arising in several specific ecological applications. PMID:23565336

Optimization Issues with Complex Rotorcraft Comprehensive Analysis

NASA Technical Reports Server (NTRS)

Walsh, Joanne L.; Young, Katherine C.; Tarzanin, Frank J.; Hirsh, Joel E.; Young, Darrell K.

1998-01-01

This paper investigates the use of the general purpose automatic differentiation (AD) tool called Automatic Differentiation of FORTRAN (ADIFOR) as a means of generating sensitivity derivatives for use in Boeing Helicopter's proprietary comprehensive rotor analysis code (VII). ADIFOR transforms an existing computer program into a new program that performs a sensitivity analysis in addition to the original analysis. In this study both the pros (exact derivatives, no step-size problems) and cons (more CPU, more memory) of ADIFOR are discussed. The size (based on the number of lines) of the VII code after ADIFOR processing increased by 70 percent and resulted in substantial computer memory requirements at execution. The ADIFOR derivatives took about 75 percent longer to compute than the finite-difference derivatives. However, the ADIFOR derivatives are exact and are not functions of step-size. The VII sensitivity derivatives generated by ADIFOR are compared with finite-difference derivatives. The ADIFOR and finite-difference derivatives are used in three optimization schemes to solve a low vibration rotor design problem.

Development of a Multi-Disciplinary Computing Environment (MDICE)

NASA Technical Reports Server (NTRS)

Kingsley, Gerry; Siegel, John M., Jr.; Harrand, Vincent J.; Lawrence, Charles; Luker, Joel J.

1999-01-01

The growing need for and importance of multi-component and multi-disciplinary engineering analysis has been understood for many years. For many applications, loose (or semi-implicit) coupling is optimal, and allows the use of various legacy codes without requiring major modifications. For this purpose, CFDRC and NASA LeRC have developed a computational environment to enable coupling between various flow analysis codes at several levels of fidelity. This has been referred to as the Visual Computing Environment (VCE), and is being successfully applied to the analysis of several aircraft engine components. Recently, CFDRC and AFRL/VAAC (WL) have extended the framework and scope of VCE to enable complex multi-disciplinary simulations. The chosen initial focus is on aeroelastic aircraft applications. The developed software is referred to as MDICE-AE, an extensible system suitable for integration of several engineering analysis disciplines. This paper describes the methodology, basic architecture, chosen software technologies, salient library modules, and the current status of and plans for MDICE. A fluid-structure interaction application is described in a separate companion paper.

High Performance Computing and Cutting-Edge Analysis Can Open New

Science.gov Websites

Realms March 1, 2018 Two people looking at a 3D interactive graphical data the Visualization Center in capabilities to visualize complex, 3D images of the wakes from multiple wind turbines so that we can better

Segmentation-free image processing and analysis of precipitate shapes in 2D and 3D

NASA Astrophysics Data System (ADS)

Bales, Ben; Pollock, Tresa; Petzold, Linda

2017-06-01

Segmentation based image analysis techniques are routinely employed for quantitative analysis of complex microstructures containing two or more phases. The primary advantage of these approaches is that spatial information on the distribution of phases is retained, enabling subjective judgements of the quality of the segmentation and subsequent analysis process. The downside is that computing micrograph segmentations with data from morphologically complex microstructures gathered with error-prone detectors is challenging and, if no special care is taken, the artifacts of the segmentation will make any subsequent analysis and conclusions uncertain. In this paper we demonstrate, using a two phase nickel-base superalloy microstructure as a model system, a new methodology for analysis of precipitate shapes using a segmentation-free approach based on the histogram of oriented gradients feature descriptor, a classic tool in image analysis. The benefits of this methodology for analysis of microstructure in two and three-dimensions are demonstrated.

Bayesian Latent Class Analysis Tutorial.

PubMed

Li, Yuelin; Lord-Bessen, Jennifer; Shiyko, Mariya; Loeb, Rebecca

2018-01-01

This article is a how-to guide on Bayesian computation using Gibbs sampling, demonstrated in the context of Latent Class Analysis (LCA). It is written for students in quantitative psychology or related fields who have a working knowledge of Bayes Theorem and conditional probability and have experience in writing computer programs in the statistical language R . The overall goals are to provide an accessible and self-contained tutorial, along with a practical computation tool. We begin with how Bayesian computation is typically described in academic articles. Technical difficulties are addressed by a hypothetical, worked-out example. We show how Bayesian computation can be broken down into a series of simpler calculations, which can then be assembled together to complete a computationally more complex model. The details are described much more explicitly than what is typically available in elementary introductions to Bayesian modeling so that readers are not overwhelmed by the mathematics. Moreover, the provided computer program shows how Bayesian LCA can be implemented with relative ease. The computer program is then applied in a large, real-world data set and explained line-by-line. We outline the general steps in how to extend these considerations to other methodological applications. We conclude with suggestions for further readings.

Domain decomposition for aerodynamic and aeroacoustic analyses, and optimization

NASA Technical Reports Server (NTRS)

Baysal, Oktay

1995-01-01

The overarching theme was the domain decomposition, which intended to improve the numerical solution technique for the partial differential equations at hand; in the present study, those that governed either the fluid flow, or the aeroacoustic wave propagation, or the sensitivity analysis for a gradient-based optimization. The role of the domain decomposition extended beyond the original impetus of discretizing geometrical complex regions or writing modular software for distributed-hardware computers. It induced function-space decompositions and operator decompositions that offered the valuable property of near independence of operator evaluation tasks. The objectives have gravitated about the extensions and implementations of either the previously developed or concurrently being developed methodologies: (1) aerodynamic sensitivity analysis with domain decomposition (SADD); (2) computational aeroacoustics of cavities; and (3) dynamic, multibody computational fluid dynamics using unstructured meshes.

Multiphysics Simulations: Challenges and Opportunities

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

Keyes, David; McInnes, Lois C.; Woodward, Carol

2013-02-12

We consider multiphysics applications from algorithmic and architectural perspectives, where ‘‘algorithmic’’ includes both mathematical analysis and computational complexity, and ‘‘architectural’’ includes both software and hardware environments. Many diverse multiphysics applications can be reduced, en route to their computational simulation, to a common algebraic coupling paradigm. Mathematical analysis of multiphysics coupling in this form is not always practical for realistic applications, but model problems representative of applications discussed herein can provide insight. A variety of software frameworks for multiphysics applications have been constructed and refined within disciplinary communities and executed on leading-edge computer systems. We examine several of these, expose somemore » commonalities among them, and attempt to extrapolate best practices to future systems. From our study, we summarize challenges and forecast opportunities.« less

DGSA: A Matlab toolbox for distance-based generalized sensitivity analysis of geoscientific computer experiments

NASA Astrophysics Data System (ADS)

Park, Jihoon; Yang, Guang; Satija, Addy; Scheidt, Céline; Caers, Jef

2016-12-01

Sensitivity analysis plays an important role in geoscientific computer experiments, whether for forecasting, data assimilation or model calibration. In this paper we focus on an extension of a method of regionalized sensitivity analysis (RSA) to applications typical in the Earth Sciences. Such applications involve the building of large complex spatial models, the application of computationally extensive forward modeling codes and the integration of heterogeneous sources of model uncertainty. The aim of this paper is to be practical: 1) provide a Matlab code, 2) provide novel visualization methods to aid users in getting a better understanding in the sensitivity 3) provide a method based on kernel principal component analysis (KPCA) and self-organizing maps (SOM) to account for spatial uncertainty typical in Earth Science applications and 4) provide an illustration on a real field case where the above mentioned complexities present themselves. We present methods that extend the original RSA method in several ways. First we present the calculation of conditional effects, defined as the sensitivity of a parameter given a level of another parameters. Second, we show how this conditional effect can be used to choose nominal values or ranges to fix insensitive parameters aiming to minimally affect uncertainty in the response. Third, we develop a method based on KPCA and SOM to assign a rank to spatial models in order to calculate the sensitivity on spatial variability in the models. A large oil/gas reservoir case is used as illustration of these ideas.

Unsteady flow simulations around complex geometries using stationary or rotating unstructured grids

NASA Astrophysics Data System (ADS)

Sezer-Uzol, Nilay

In this research, the computational analysis of three-dimensional, unsteady, separated, vortical flows around complex geometries is studied by using stationary or moving unstructured grids. Two main engineering problems are investigated. The first problem is the unsteady simulation of a ship airwake, where helicopter operations become even more challenging, by using stationary unstructured grids. The second problem is the unsteady simulation of wind turbine rotor flow fields by using moving unstructured grids which are rotating with the whole three-dimensional rigid rotor geometry. The three dimensional, unsteady, parallel, unstructured, finite volume flow solver, PUMA2, is used for the computational fluid dynamics (CFD) simulations considered in this research. The code is modified to have a moving grid capability to perform three-dimensional, time-dependent rotor simulations. An instantaneous log-law wall model for Large Eddy Simulations is also implemented in PUMA2 to investigate the very large Reynolds number flow fields of rotating blades. To verify the code modifications, several sample test cases are also considered. In addition, interdisciplinary studies, which are aiming to provide new tools and insights to the aerospace and wind energy scientific communities, are done during this research by focusing on the coupling of ship airwake CFD simulations with the helicopter flight dynamics and control analysis, the coupling of wind turbine rotor CFD simulations with the aeroacoustic analysis, and the analysis of these time-dependent and large-scale CFD simulations with the help of a computational monitoring, steering and visualization tool, POSSE.

IBiSA_Tools: A Computational Toolkit for Ion-Binding State Analysis in Molecular Dynamics Trajectories of Ion Channels.

PubMed

Kasahara, Kota; Kinoshita, Kengo

2016-01-01

Ion conduction mechanisms of ion channels are a long-standing conundrum. Although the molecular dynamics (MD) method has been extensively used to simulate ion conduction dynamics at the atomic level, analysis and interpretation of MD results are not straightforward due to complexity of the dynamics. In our previous reports, we proposed an analytical method called ion-binding state analysis to scrutinize and summarize ion conduction mechanisms by taking advantage of a variety of analytical protocols, e.g., the complex network analysis, sequence alignment, and hierarchical clustering. This approach effectively revealed the ion conduction mechanisms and their dependence on the conditions, i.e., ion concentration and membrane voltage. Here, we present an easy-to-use computational toolkit for ion-binding state analysis, called IBiSA_tools. This toolkit consists of a C++ program and a series of Python and R scripts. From the trajectory file of MD simulations and a structure file, users can generate several images and statistics of ion conduction processes. A complex network named ion-binding state graph is generated in a standard graph format (graph modeling language; GML), which can be visualized by standard network analyzers such as Cytoscape. As a tutorial, a trajectory of a 50 ns MD simulation of the Kv1.2 channel is also distributed with the toolkit. Users can trace the entire process of ion-binding state analysis step by step. The novel method for analysis of ion conduction mechanisms of ion channels can be easily used by means of IBiSA_tools. This software is distributed under an open source license at the following URL: http://www.ritsumei.ac.jp/~ktkshr/ibisa_tools/.

Free energy component analysis for drug design: a case study of HIV-1 protease-inhibitor binding.

PubMed

Kalra, P; Reddy, T V; Jayaram, B

2001-12-06

A theoretically rigorous and computationally tractable methodology for the prediction of the free energies of binding of protein-ligand complexes is presented. The method formulated involves developing molecular dynamics trajectories of the enzyme, the inhibitor, and the complex, followed by a free energy component analysis that conveys information on the physicochemical forces driving the protein-ligand complex formation and enables an elucidation of drug design principles for a given receptor from a thermodynamic perspective. The complexes of HIV-1 protease with two peptidomimetic inhibitors were taken as illustrative cases. Four-nanosecond-level all-atom molecular dynamics simulations using explicit solvent without any restraints were carried out on the protease-inhibitor complexes and the free proteases, and the trajectories were analyzed via a thermodynamic cycle to calculate the binding free energies. The computed free energies were seen to be in good accord with the reported data. It was noted that the net van der Waals and hydrophobic contributions were favorable to binding while the net electrostatics, entropies, and adaptation expense were unfavorable in these protease-inhibitor complexes. The hydrogen bond between the CH2OH group of the inhibitor at the scissile position and the catalytic aspartate was found to be favorable to binding. Various implicit solvent models were also considered and their shortcomings discussed. In addition, some plausible modifications to the inhibitor residues were attempted, which led to better binding affinities. The generality of the method and the transferability of the protocol with essentially no changes to any other protein-ligand system are emphasized.

Airport-Noise Levels and Annoyance Model (ALAMO) user's guide

NASA Technical Reports Server (NTRS)

Deloach, R.; Donaldson, J. L.; Johnson, M. J.

1986-01-01

A guide for the use of the Airport-Noise Level and Annoyance MOdel (ALAMO) at the Langley Research Center computer complex is provided. This document is divided into 5 primary sections, the introduction, the purpose of the model, and an in-depth description of the following subsystems: baseline, noise reduction simulation and track analysis. For each subsystem, the user is provided with a description of architecture, an explanation of subsystem use, sample results, and a case runner's check list. It is assumed that the user is familiar with the operations at the Langley Research Center (LaRC) computer complex, the Network Operating System (NOS 1.4) and CYBER Control Language. Incorporated within the ALAMO model is a census database system called SITE II.

Updated Lagrangian finite element formulations of various biological soft tissue non-linear material models: a comprehensive procedure and review.

PubMed

Townsend, Molly T; Sarigul-Klijn, Nesrin

2016-01-01

Simplified material models are commonly used in computational simulation of biological soft tissue as an approximation of the complicated material response and to minimize computational resources. However, the simulation of complex loadings, such as long-duration tissue swelling, necessitates complex models that are not easy to formulate. This paper strives to offer the updated Lagrangian formulation comprehensive procedure of various non-linear material models for the application of finite element analysis of biological soft tissues including a definition of the Cauchy stress and the spatial tangential stiffness. The relationships between water content, osmotic pressure, ionic concentration and the pore pressure stress of the tissue are discussed with the merits of these models and their applications.

Design synthesis and optimization of permanent magnet synchronous machines based on computationally-efficient finite element analysis

NASA Astrophysics Data System (ADS)

Sizov, Gennadi Y.

In this dissertation, a model-based multi-objective optimal design of permanent magnet ac machines, supplied by sine-wave current regulated drives, is developed and implemented. The design procedure uses an efficient electromagnetic finite element-based solver to accurately model nonlinear material properties and complex geometric shapes associated with magnetic circuit design. Application of an electromagnetic finite element-based solver allows for accurate computation of intricate performance parameters and characteristics. The first contribution of this dissertation is the development of a rapid computational method that allows accurate and efficient exploration of large multi-dimensional design spaces in search of optimum design(s). The computationally efficient finite element-based approach developed in this work provides a framework of tools that allow rapid analysis of synchronous electric machines operating under steady-state conditions. In the developed modeling approach, major steady-state performance parameters such as, winding flux linkages and voltages, average, cogging and ripple torques, stator core flux densities, core losses, efficiencies and saturated machine winding inductances, are calculated with minimum computational effort. In addition, the method includes means for rapid estimation of distributed stator forces and three-dimensional effects of stator and/or rotor skew on the performance of the machine. The second contribution of this dissertation is the development of the design synthesis and optimization method based on a differential evolution algorithm. The approach relies on the developed finite element-based modeling method for electromagnetic analysis and is able to tackle large-scale multi-objective design problems using modest computational resources. Overall, computational time savings of up to two orders of magnitude are achievable, when compared to current and prevalent state-of-the-art methods. These computational savings allow one to expand the optimization problem to achieve more complex and comprehensive design objectives. The method is used in the design process of several interior permanent magnet industrial motors. The presented case studies demonstrate that the developed finite element-based approach practically eliminates the need for using less accurate analytical and lumped parameter equivalent circuit models for electric machine design optimization. The design process and experimental validation of the case-study machines are detailed in the dissertation.

Parallelization of the Physical-Space Statistical Analysis System (PSAS)

NASA Technical Reports Server (NTRS)

Larson, J. W.; Guo, J.; Lyster, P. M.

1999-01-01

Atmospheric data assimilation is a method of combining observations with model forecasts to produce a more accurate description of the atmosphere than the observations or forecast alone can provide. Data assimilation plays an increasingly important role in the study of climate and atmospheric chemistry. The NASA Data Assimilation Office (DAO) has developed the Goddard Earth Observing System Data Assimilation System (GEOS DAS) to create assimilated datasets. The core computational components of the GEOS DAS include the GEOS General Circulation Model (GCM) and the Physical-space Statistical Analysis System (PSAS). The need for timely validation of scientific enhancements to the data assimilation system poses computational demands that are best met by distributed parallel software. PSAS is implemented in Fortran 90 using object-based design principles. The analysis portions of the code solve two equations. The first of these is the "innovation" equation, which is solved on the unstructured observation grid using a preconditioned conjugate gradient (CG) method. The "analysis" equation is a transformation from the observation grid back to a structured grid, and is solved by a direct matrix-vector multiplication. Use of a factored-operator formulation reduces the computational complexity of both the CG solver and the matrix-vector multiplication, rendering the matrix-vector multiplications as a successive product of operators on a vector. Sparsity is introduced to these operators by partitioning the observations using an icosahedral decomposition scheme. PSAS builds a large (approx. 128MB) run-time database of parameters used in the calculation of these operators. Implementing a message passing parallel computing paradigm into an existing yet developing computational system as complex as PSAS is nontrivial. One of the technical challenges is balancing the requirements for computational reproducibility with the need for high performance. The problem of computational reproducibility is well known in the parallel computing community. It is a requirement that the parallel code perform calculations in a fashion that will yield identical results on different configurations of processing elements on the same platform. In some cases this problem can be solved by sacrificing performance. Meeting this requirement and still achieving high performance is very difficult. Topics to be discussed include: current PSAS design and parallelization strategy; reproducibility issues; load balance vs. database memory demands, possible solutions to these problems.

Anti-tumor activity and mechanism of apoptosis of A549 induced by ruthenium complex.

PubMed

Sun, Dongdong; Mou, Zhipeng; Li, Nuan; Zhang, Weiwei; Wang, Yazhe; Yang, Endong; Wang, Weiyun

2016-12-01

Two new ruthenium (II) polypyridyl complexes [Ru(MeIm) 4 (pip)] 2+ (1) and [Ru(MeIm) 4 (4-npip)] 2+ (2) were synthesized under the guidance of computational studies (DFT). Their binding property to human telomeric G-quadruplex studied by UV-Vis absorption spectroscopy, the fluorescent resonance energy transfer (FRET) melting assay and circular dichroism (CD) spectroscopy for validating the theoretical prediction. Both of them were evaluated for their potential anti-proliferative activity against four human tumor cell lines. Complex 2 shows growth inhibition against all the cell lines tested, especially the human lung tumor cell (A549). The RTCA analysis not only validated the inhibition activity but also showed the ability of reducing A549 cells' migration. DNA-flow cytometric analysis, mitochondrial membrane potential (ΔΨm) and the scavenger measurements of reactive oxygen species (ROS) analysis carried out to investigate the mechanism of cell growth inhibition and apoptosis-inducing effect of complex 2. The results demonstrated that complex 2 induces tumor cells apoptosis by acting on both mitochondrial homeostasis destruction and death receptor signaling pathways. And those suggested that complex 2 could be a candidate for further evaluation as a chemotherapeutic agent against human tumor.

On the Achievable Throughput Over TVWS Sensor Networks

PubMed Central

Caleffi, Marcello; Cacciapuoti, Angela Sara

2016-01-01

In this letter, we study the throughput achievable by an unlicensed sensor network operating over TV white space spectrum in presence of coexistence interference. Through the letter, we first analytically derive the achievable throughput as a function of the channel ordering. Then, we show that the problem of deriving the maximum expected throughput through exhaustive search is computationally unfeasible. Finally, we derive a computational-efficient algorithm characterized by polynomial-time complexity to compute the channel set maximizing the expected throughput and, stemming from this, we derive a closed-form expression of the maximum expected throughput. Numerical simulations validate the theoretical analysis. PMID:27043565

Grid-converged solution and analysis of the unsteady viscous flow in a two-dimensional shock tube

NASA Astrophysics Data System (ADS)

Zhou, Guangzhao; Xu, Kun; Liu, Feng

2018-01-01

The flow in a shock tube is extremely complex with dynamic multi-scale structures of sharp fronts, flow separation, and vortices due to the interaction of the shock wave, the contact surface, and the boundary layer over the side wall of the tube. Prediction and understanding of the complex fluid dynamics are of theoretical and practical importance. It is also an extremely challenging problem for numerical simulation, especially at relatively high Reynolds numbers. Daru and Tenaud ["Evaluation of TVD high resolution schemes for unsteady viscous shocked flows," Comput. Fluids 30, 89-113 (2001)] proposed a two-dimensional model problem as a numerical test case for high-resolution schemes to simulate the flow field in a square closed shock tube. Though many researchers attempted this problem using a variety of computational methods, there is not yet an agreed-upon grid-converged solution of the problem at the Reynolds number of 1000. This paper presents a rigorous grid-convergence study and the resulting grid-converged solutions for this problem by using a newly developed, efficient, and high-order gas-kinetic scheme. Critical data extracted from the converged solutions are documented as benchmark data. The complex fluid dynamics of the flow at Re = 1000 are discussed and analyzed in detail. Major phenomena revealed by the numerical computations include the downward concentration of the fluid through the curved shock, the formation of the vortices, the mechanism of the shock wave bifurcation, the structure of the jet along the bottom wall, and the Kelvin-Helmholtz instability near the contact surface. Presentation and analysis of those flow processes provide important physical insight into the complex flow physics occurring in a shock tube.

Visualization, documentation, analysis, and communication of large scale gene regulatory networks

PubMed Central

Longabaugh, William J.R.; Davidson, Eric H.; Bolouri, Hamid

2009-01-01

Summary Genetic regulatory networks (GRNs) are complex, large-scale, and spatially and temporally distributed. These characteristics impose challenging demands on computational GRN modeling tools, and there is a need for custom modeling tools. In this paper, we report on our ongoing development of BioTapestry, an open source, freely available computational tool designed specifically for GRN modeling. We also outline our future development plans, and give some examples of current applications of BioTapestry. PMID:18757046

Quantum attack-resistent certificateless multi-receiver signcryption scheme.

PubMed

Li, Huixian; Chen, Xubao; Pang, Liaojun; Shi, Weisong

2013-01-01

The existing certificateless signcryption schemes were designed mainly based on the traditional public key cryptography, in which the security relies on the hard problems, such as factor decomposition and discrete logarithm. However, these problems will be easily solved by the quantum computing. So the existing certificateless signcryption schemes are vulnerable to the quantum attack. Multivariate public key cryptography (MPKC), which can resist the quantum attack, is one of the alternative solutions to guarantee the security of communications in the post-quantum age. Motivated by these concerns, we proposed a new construction of the certificateless multi-receiver signcryption scheme (CLMSC) based on MPKC. The new scheme inherits the security of MPKC, which can withstand the quantum attack. Multivariate quadratic polynomial operations, which have lower computation complexity than bilinear pairing operations, are employed in signcrypting a message for a certain number of receivers in our scheme. Security analysis shows that our scheme is a secure MPKC-based scheme. We proved its security under the hardness of the Multivariate Quadratic (MQ) problem and its unforgeability under the Isomorphism of Polynomials (IP) assumption in the random oracle model. The analysis results show that our scheme also has the security properties of non-repudiation, perfect forward secrecy, perfect backward secrecy and public verifiability. Compared with the existing schemes in terms of computation complexity and ciphertext length, our scheme is more efficient, which makes it suitable for terminals with low computation capacity like smart cards.

A Statistician's View of Upcoming Grand Challenges

NASA Astrophysics Data System (ADS)

Meng, Xiao Li

2010-01-01

In this session we have seen some snapshots of the broad spectrum of challenges, in this age of huge, complex, computer-intensive models, data, instruments,and questions. These challenges bridge astronomy at many wavelengths; basic physics; machine learning; -- and statistics. At one end of our spectrum, we think of 'compressing' the data with non-parametric methods. This raises the question of creating 'pseudo-replicas' of the data for uncertainty estimates. What would be involved in, e.g. boot-strap and related methods? Somewhere in the middle are these non-parametric methods for encapsulating the uncertainty information. At the far end, we find more model-based approaches, with the physics model embedded in the likelihood and analysis. The other distinctive problem is really the 'black-box' problem, where one has a complicated e.g. fundamental physics-based computer code, or 'black box', and one needs to know how changing the parameters at input -- due to uncertainties of any kind -- will map to changing the output. All of these connect to challenges in complexity of data and computation speed. Dr. Meng will highlight ways to 'cut corners' with advanced computational techniques, such as Parallel Tempering and Equal Energy methods. As well, there are cautionary tales of running automated analysis with real data -- where "30 sigma" outliers due to data artifacts can be more common than the astrophysical event of interest.

Challenges in reducing the computational time of QSTS simulations for distribution system analysis.

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

Deboever, Jeremiah; Zhang, Xiaochen; Reno, Matthew J.

The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modelling and impact analysis. Unlike conventional scenario - based studies , quasi - static time - series (QSTS) simulation s can realistically model time - dependent voltage controllers and the diversity of potential impacts that can occur at different times of year . However, to accurately model a distribution system with all its controllable devices, a yearlong simulation at 1 - second resolution is often required , which could take conventional computers a computational time of 10more » to 120 hours when an actual unbalanced distribution feeder is modeled . This computational burden is a clear l imitation to the adoption of QSTS simulation s in interconnection studies and for determining optimal control solutions for utility operations . Our ongoing research to improve the speed of QSTS simulation has revealed many unique aspects of distribution system modelling and sequential power flow analysis that make fast QSTS a very difficult problem to solve. In this report , the most relevant challenges in reducing the computational time of QSTS simulations are presented: number of power flows to solve, circuit complexity, time dependence between time steps, multiple valid power flow solutions, controllable element interactions, and extensive accurate simulation analysis.« less

Scope Complexity Options Risks Excursions (SCORE) Version 3.0 Mathematical Description.

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

Gearhart, Jared Lee; Samberson, Jonell Nicole; Shettigar, Subhasini

The purpose of the Scope, Complexity, Options, Risks, Excursions (SCORE) model is to estimate the relative complexity of design variants of future warhead options. The results of this model allow those considering these options to understand the complexity tradeoffs between proposed warhead options. The core idea of SCORE is to divide a warhead option into a well- defined set of scope elements and then estimate the complexity of each scope element against a well understood reference system. The uncertainty associated with estimates can also be captured. A weighted summation of the relative complexity of each scope element is used tomore » determine the total complexity of the proposed warhead option or portions of the warhead option (i.e., a National Work Breakdown Structure code). The SCORE analysis process is a growing multi-organizational Nuclear Security Enterprise (NSE) effort, under the management of the NA- 12 led Enterprise Modeling and Analysis Consortium (EMAC), that has provided the data elicitation, integration and computation needed to support the out-year Life Extension Program (LEP) cost estimates included in the Stockpile Stewardship Management Plan (SSMP).« less

Enabling Co-Design of Multi-Layer Exascale Storage Architectures

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

Carothers, Christopher

Growing demands for computing power in applications such as energy production, climate analysis, computational chemistry, and bioinformatics have propelled computing systems toward the exascale: systems with 10 18 floating-point operations per second. These systems, to be designed and constructed over the next decade, will create unprecedented challenges in component counts, power consumption, resource limitations, and system complexity. Data storage and access are an increasingly important and complex component in extreme-scale computing systems, and significant design work is needed to develop successful storage hardware and software architectures at exascale. Co-design of these systems will be necessary to find the best possiblemore » design points for exascale systems. The goal of this work has been to enable the exploration and co-design of exascale storage systems by providing a detailed, accurate, and highly parallel simulation of exascale storage and the surrounding environment. Specifically, this simulation has (1) portrayed realistic application checkpointing and analysis workloads, (2) captured the complexity, scale, and multilayer nature of exascale storage hardware and software, and (3) executed in a timeframe that enables “what if'” exploration of design concepts. We developed models of the major hardware and software components in an exascale storage system, as well as the application I/O workloads that drive them. We used our simulation system to investigate critical questions in reliability and concurrency at exascale, helping guide the design of future exascale hardware and software architectures. Additionally, we provided this system to interested vendors and researchers so that others can explore the design space. We validated the capabilities of our simulation environment by configuring the simulation to represent the Argonne Leadership Computing Facility Blue Gene/Q system and comparing simulation results for application I/O patterns to the results of executions of these I/O kernels on the actual system.« less

Zero-inflated spatio-temporal models for disease mapping.

PubMed

Torabi, Mahmoud

2017-05-01

In this paper, our aim is to analyze geographical and temporal variability of disease incidence when spatio-temporal count data have excess zeros. To that end, we consider random effects in zero-inflated Poisson models to investigate geographical and temporal patterns of disease incidence. Spatio-temporal models that employ conditionally autoregressive smoothing across the spatial dimension and B-spline smoothing over the temporal dimension are proposed. The analysis of these complex models is computationally difficult from the frequentist perspective. On the other hand, the advent of the Markov chain Monte Carlo algorithm has made the Bayesian analysis of complex models computationally convenient. Recently developed data cloning method provides a frequentist approach to mixed models that is also computationally convenient. We propose to use data cloning, which yields to maximum likelihood estimation, to conduct frequentist analysis of zero-inflated spatio-temporal modeling of disease incidence. One of the advantages of the data cloning approach is that the prediction and corresponding standard errors (or prediction intervals) of smoothing disease incidence over space and time is easily obtained. We illustrate our approach using a real dataset of monthly children asthma visits to hospital in the province of Manitoba, Canada, during the period April 2006 to March 2010. Performance of our approach is also evaluated through a simulation study. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation.

PubMed

Cornuet, Jean-Marie; Santos, Filipe; Beaumont, Mark A; Robert, Christian P; Marin, Jean-Michel; Balding, David J; Guillemaud, Thomas; Estoup, Arnaud

2008-12-01

Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. The software DIY ABC is freely available at http://www.montpellier.inra.fr/CBGP/diyabc.

CONVEX mini manual

NASA Technical Reports Server (NTRS)

Tennille, Geoffrey M.; Howser, Lona M.

1993-01-01

The use of the CONVEX computers that are an integral part of the Supercomputing Network Subsystems (SNS) of the Central Scientific Computing Complex of LaRC is briefly described. Features of the CONVEX computers that are significantly different than the CRAY supercomputers are covered, including: FORTRAN, C, architecture of the CONVEX computers, the CONVEX environment, batch job submittal, debugging, performance analysis, utilities unique to CONVEX, and documentation. This revision reflects the addition of the Applications Compiler and X-based debugger, CXdb. The document id intended for all CONVEX users as a ready reference to frequently asked questions and to more detailed information contained with the vendor manuals. It is appropriate for both the novice and the experienced user.

Sample-space-based feature extraction and class preserving projection for gene expression data.

PubMed

Wang, Wenjun

2013-01-01

In order to overcome the problems of high computational complexity and serious matrix singularity for feature extraction using Principal Component Analysis (PCA) and Fisher's Linear Discrinimant Analysis (LDA) in high-dimensional data, sample-space-based feature extraction is presented, which transforms the computation procedure of feature extraction from gene space to sample space by representing the optimal transformation vector with the weighted sum of samples. The technique is used in the implementation of PCA, LDA, Class Preserving Projection (CPP) which is a new method for discriminant feature extraction proposed, and the experimental results on gene expression data demonstrate the effectiveness of the method.

Fast linear feature detection using multiple directional non-maximum suppression.

PubMed

Sun, C; Vallotton, P

2009-05-01

The capacity to detect linear features is central to image analysis, computer vision and pattern recognition and has practical applications in areas such as neurite outgrowth detection, retinal vessel extraction, skin hair removal, plant root analysis and road detection. Linear feature detection often represents the starting point for image segmentation and image interpretation. In this paper, we present a new algorithm for linear feature detection using multiple directional non-maximum suppression with symmetry checking and gap linking. Given its low computational complexity, the algorithm is very fast. We show in several examples that it performs very well in terms of both sensitivity and continuity of detected linear features.

Thermodynamic cost of computation, algorithmic complexity and the information metric

NASA Technical Reports Server (NTRS)

Zurek, W. H.

1989-01-01

Algorithmic complexity is discussed as a computational counterpart to the second law of thermodynamics. It is shown that algorithmic complexity, which is a measure of randomness, sets limits on the thermodynamic cost of computations and casts a new light on the limitations of Maxwell's demon. Algorithmic complexity can also be used to define distance between binary strings.

Improving the first hyperpolarizability of anthracene through interaction with HX molecules (Xdbnd F, Cl, Br): A theoretical study

NASA Astrophysics Data System (ADS)

Abdolmaleki, Ahmad; Dadsetani, Mehrdad; Zabardasti, Abedin

2018-05-01

The variations in nonlinear optical activity (NLO) of anthracene (C14H10) was investigated via intermolecular interactions between C14H10 and HX molecules (Xdbnd F, Cl and Br) using B3LYP-D3 method at 6-311++G(d,p) basis set. The stabilization of those complexes was investigated via vibrational analysis, quantum theory of atoms in molecules, molecular electrostatic potential, natural bond orbitals and symmetry-adapted perturbation theory (SAPT) analysis. Furthermore, the optical spectra and the first hyperpolarizabilities of C14H10⋯HX complexes were computed. The adsorption of hydrogen halide through C14H10⋯HX complex formation, didn't change much the linear optical activities of C14H10 molecule, but the magnitude of the first hyperpolarizability of the C14H10⋯HX complexes to be as much as that of urea.

Cytobank: providing an analytics platform for community cytometry data analysis and collaboration.

PubMed

Chen, Tiffany J; Kotecha, Nikesh

2014-01-01

Cytometry is used extensively in clinical and laboratory settings to diagnose and track cell subsets in blood and tissue. High-throughput, single-cell approaches leveraging cytometry are developed and applied in the computational and systems biology communities by researchers, who seek to improve the diagnosis of human diseases, map the structures of cell signaling networks, and identify new cell types. Data analysis and management present a bottleneck in the flow of knowledge from bench to clinic. Multi-parameter flow and mass cytometry enable identification of signaling profiles of patient cell samples. Currently, this process is manual, requiring hours of work to summarize multi-dimensional data and translate these data for input into other analysis programs. In addition, the increase in the number and size of collaborative cytometry studies as well as the computational complexity of analytical tools require the ability to assemble sufficient and appropriately configured computing capacity on demand. There is a critical need for platforms that can be used by both clinical and basic researchers who routinely rely on cytometry. Recent advances provide a unique opportunity to facilitate collaboration and analysis and management of cytometry data. Specifically, advances in cloud computing and virtualization are enabling efficient use of large computing resources for analysis and backup. An example is Cytobank, a platform that allows researchers to annotate, analyze, and share results along with the underlying single-cell data.

Concurrent Probabilistic Simulation of High Temperature Composite Structural Response

NASA Technical Reports Server (NTRS)

Abdi, Frank

1996-01-01

A computational structural/material analysis and design tool which would meet industry's future demand for expedience and reduced cost is presented. This unique software 'GENOA' is dedicated to parallel and high speed analysis to perform probabilistic evaluation of high temperature composite response of aerospace systems. The development is based on detailed integration and modification of diverse fields of specialized analysis techniques and mathematical models to combine their latest innovative capabilities into a commercially viable software package. The technique is specifically designed to exploit the availability of processors to perform computationally intense probabilistic analysis assessing uncertainties in structural reliability analysis and composite micromechanics. The primary objectives which were achieved in performing the development were: (1) Utilization of the power of parallel processing and static/dynamic load balancing optimization to make the complex simulation of structure, material and processing of high temperature composite affordable; (2) Computational integration and synchronization of probabilistic mathematics, structural/material mechanics and parallel computing; (3) Implementation of an innovative multi-level domain decomposition technique to identify the inherent parallelism, and increasing convergence rates through high- and low-level processor assignment; (4) Creating the framework for Portable Paralleled architecture for the machine independent Multi Instruction Multi Data, (MIMD), Single Instruction Multi Data (SIMD), hybrid and distributed workstation type of computers; and (5) Market evaluation. The results of Phase-2 effort provides a good basis for continuation and warrants Phase-3 government, and industry partnership.

Tools and techniques for computational reproducibility.

PubMed

Piccolo, Stephen R; Frampton, Michael B

2016-07-11

When reporting research findings, scientists document the steps they followed so that others can verify and build upon the research. When those steps have been described in sufficient detail that others can retrace the steps and obtain similar results, the research is said to be reproducible. Computers play a vital role in many research disciplines and present both opportunities and challenges for reproducibility. Computers can be programmed to execute analysis tasks, and those programs can be repeated and shared with others. The deterministic nature of most computer programs means that the same analysis tasks, applied to the same data, will often produce the same outputs. However, in practice, computational findings often cannot be reproduced because of complexities in how software is packaged, installed, and executed-and because of limitations associated with how scientists document analysis steps. Many tools and techniques are available to help overcome these challenges; here we describe seven such strategies. With a broad scientific audience in mind, we describe the strengths and limitations of each approach, as well as the circumstances under which each might be applied. No single strategy is sufficient for every scenario; thus we emphasize that it is often useful to combine approaches.

A Computational Analysis of Complex Noun Phrases in Navy Messages

DTIC Science & Technology

1984-07-01

Hirschman. Automated Determination of Suhlanguage Syntactic Usage. Proc. COLING 84) (current volume). [Hirschman 1082 ] Hirsehman, L. Constraints on...Restricted Semantic Domains. de Grnyter New York, 1082 . [Levi 1078] Levi, J.N. The Syntaz and Semantics of Com- plez Nominals, Academic Press, New York

A micro-hydrology computation ordering algorithm

NASA Astrophysics Data System (ADS)

Croley, Thomas E.

1980-11-01

Discrete-distributed-parameter models are essential for watershed modelling where practical consideration of spatial variations in watershed properties and inputs is desired. Such modelling is necessary for analysis of detailed hydrologic impacts from management strategies and land-use effects. Trade-offs between model validity and model complexity exist in resolution of the watershed. Once these are determined, the watershed is then broken into sub-areas which each have essentially spatially-uniform properties. Lumped-parameter (micro-hydrology) models are applied to these sub-areas and their outputs are combined through the use of a computation ordering technique, as illustrated by many discrete-distributed-parameter hydrology models. Manual ordering of these computations requires fore-thought, and is tedious, error prone, sometimes storage intensive and least adaptable to changes in watershed resolution. A programmable algorithm for ordering micro-hydrology computations is presented that enables automatic ordering of computations within the computer via an easily understood and easily implemented "node" definition, numbering and coding scheme. This scheme and the algorithm are detailed in logic flow-charts and an example application is presented. Extensions and modifications of the algorithm are easily made for complex geometries or differing microhydrology models. The algorithm is shown to be superior to manual ordering techniques and has potential use in high-resolution studies.

An improved spanning tree approach for the reliability analysis of supply chain collaborative network

NASA Astrophysics Data System (ADS)

Lam, C. Y.; Ip, W. H.

2012-11-01

A higher degree of reliability in the collaborative network can increase the competitiveness and performance of an entire supply chain. As supply chain networks grow more complex, the consequences of unreliable behaviour become increasingly severe in terms of cost, effort and time. Moreover, it is computationally difficult to calculate the network reliability of a Non-deterministic Polynomial-time hard (NP-hard) all-terminal network using state enumeration, as this may require a huge number of iterations for topology optimisation. Therefore, this paper proposes an alternative approach of an improved spanning tree for reliability analysis to help effectively evaluate and analyse the reliability of collaborative networks in supply chains and reduce the comparative computational complexity of algorithms. Set theory is employed to evaluate and model the all-terminal reliability of the improved spanning tree algorithm and present a case study of a supply chain used in lamp production to illustrate the application of the proposed approach.

Vector spherical quasi-Gaussian vortex beams

NASA Astrophysics Data System (ADS)

Mitri, F. G.

2014-02-01

Model equations for describing and efficiently computing the radiation profiles of tightly spherically focused higher-order electromagnetic beams of vortex nature are derived stemming from a vectorial analysis with the complex-source-point method. This solution, termed as a high-order quasi-Gaussian (qG) vortex beam, exactly satisfies the vector Helmholtz and Maxwell's equations. It is characterized by a nonzero integer degree and order (n,m), respectively, an arbitrary waist w0, a diffraction convergence length known as the Rayleigh range zR, and an azimuthal phase dependency in the form of a complex exponential corresponding to a vortex beam. An attractive feature of the high-order solution is the rigorous description of strongly focused (or strongly divergent) vortex wave fields without the need of either the higher-order corrections or the numerically intensive methods. Closed-form expressions and computational results illustrate the analysis and some properties of the high-order qG vortex beams based on the axial and transverse polarization schemes of the vector potentials with emphasis on the beam waist.

Haplotag: Software for Haplotype-Based Genotyping-by-Sequencing Analysis

PubMed Central

Tinker, Nicholas A.; Bekele, Wubishet A.; Hattori, Jiro

2016-01-01

Genotyping-by-sequencing (GBS), and related methods, are based on high-throughput short-read sequencing of genomic complexity reductions followed by discovery of single nucleotide polymorphisms (SNPs) within sequence tags. This provides a powerful and economical approach to whole-genome genotyping, facilitating applications in genomics, diversity analysis, and molecular breeding. However, due to the complexity of analyzing large data sets, applications of GBS may require substantial time, expertise, and computational resources. Haplotag, the novel GBS software described here, is freely available, and operates with minimal user-investment on widely available computer platforms. Haplotag is unique in fulfilling the following set of criteria: (1) operates without a reference genome; (2) can be used in a polyploid species; (3) provides a discovery mode, and a production mode; (4) discovers polymorphisms based on a model of tag-level haplotypes within sequenced tags; (5) reports SNPs as well as haplotype-based genotypes; and (6) provides an intuitive visual “passport” for each inferred locus. Haplotag is optimized for use in a self-pollinating plant species. PMID:26818073

A Novel Interdisciplinary Approach to Socio-Technical Complexity

NASA Astrophysics Data System (ADS)

Bassetti, Chiara

The chapter presents a novel interdisciplinary approach that integrates micro-sociological analysis into computer-vision and pattern-recognition modeling and algorithms, the purpose being to tackle socio-technical complexity at a systemic yet micro-grounded level. The approach is empirically-grounded and both theoretically- and analytically-driven, yet systemic and multidimensional, semi-supervised and computable, and oriented towards large scale applications. The chapter describes the proposed approach especially as for its sociological foundations, and as applied to the analysis of a particular setting --i.e. sport-spectator crowds. Crowds, better defined as large gatherings, are almost ever-present in our societies, and capturing their dynamics is crucial. From social sciences to public safety management and emergency response, modeling and predicting large gatherings' presence and dynamics, thus possibly preventing critical situations and being able to properly react to them, is fundamental. This is where semi/automated technologies can make the difference. The work presented in this chapter is intended as a scientific step towards such an objective.

Euler/Navier-Stokes calculations of transonic flow past fixed- and rotary-wing aircraft configurations

NASA Technical Reports Server (NTRS)

Deese, J. E.; Agarwal, R. K.

1989-01-01

Computational fluid dynamics has an increasingly important role in the design and analysis of aircraft as computer hardware becomes faster and algorithms become more efficient. Progress is being made in two directions: more complex and realistic configurations are being treated and algorithms based on higher approximations to the complete Navier-Stokes equations are being developed. The literature indicates that linear panel methods can model detailed, realistic aircraft geometries in flow regimes where this approximation is valid. As algorithms including higher approximations to the Navier-Stokes equations are developed, computer resource requirements increase rapidly. Generation of suitable grids become more difficult and the number of grid points required to resolve flow features of interest increases. Recently, the development of large vector computers has enabled researchers to attempt more complex geometries with Euler and Navier-Stokes algorithms. The results of calculations for transonic flow about a typical transport and fighter wing-body configuration using thin layer Navier-Stokes equations are described along with flow about helicopter rotor blades using both Euler/Navier-Stokes equations.

High performance computing in biology: multimillion atom simulations of nanoscale systems

PubMed Central

Sanbonmatsu, K. Y.; Tung, C.-S.

2007-01-01

Computational methods have been used in biology for sequence analysis (bioinformatics), all-atom simulation (molecular dynamics and quantum calculations), and more recently for modeling biological networks (systems biology). Of these three techniques, all-atom simulation is currently the most computationally demanding, in terms of compute load, communication speed, and memory load. Breakthroughs in electrostatic force calculation and dynamic load balancing have enabled molecular dynamics simulations of large biomolecular complexes. Here, we report simulation results for the ribosome, using approximately 2.64 million atoms, the largest all-atom biomolecular simulation published to date. Several other nanoscale systems with different numbers of atoms were studied to measure the performance of the NAMD molecular dynamics simulation program on the Los Alamos National Laboratory Q Machine. We demonstrate that multimillion atom systems represent a 'sweet spot' for the NAMD code on large supercomputers. NAMD displays an unprecedented 85% parallel scaling efficiency for the ribosome system on 1024 CPUs. We also review recent targeted molecular dynamics simulations of the ribosome that prove useful for studying conformational changes of this large biomolecular complex in atomic detail. PMID:17187988

System analysis in rotorcraft design: The past decade

NASA Technical Reports Server (NTRS)

Galloway, Thomas L.

1988-01-01

Rapid advances in the technology of electronic digital computers and the need for an integrated synthesis approach in developing future rotorcraft programs has led to increased emphasis on system analysis techniques in rotorcraft design. The task in systems analysis is to deal with complex, interdependent, and conflicting requirements in a structured manner so rational and objective decisions can be made. Whether the results are wisdom or rubbish depends upon the validity and sometimes more importantly, the consistency of the inputs, the correctness of the analysis, and a sensible choice of measures of effectiveness to draw conclusions. In rotorcraft design this means combining design requirements, technology assessment, sensitivity analysis and reviews techniques currently in use by NASA and Army organizations in developing research programs and vehicle specifications for rotorcraft. These procedures span simple graphical approaches to comprehensive analysis on large mainframe computers. Examples of recent applications to military and civil missions are highlighted.

RAP: RNA-Seq Analysis Pipeline, a new cloud-based NGS web application.

PubMed

D'Antonio, Mattia; D'Onorio De Meo, Paolo; Pallocca, Matteo; Picardi, Ernesto; D'Erchia, Anna Maria; Calogero, Raffaele A; Castrignanò, Tiziana; Pesole, Graziano

2015-01-01

The study of RNA has been dramatically improved by the introduction of Next Generation Sequencing platforms allowing massive and cheap sequencing of selected RNA fractions, also providing information on strand orientation (RNA-Seq). The complexity of transcriptomes and of their regulative pathways make RNA-Seq one of most complex field of NGS applications, addressing several aspects of the expression process (e.g. identification and quantification of expressed genes and transcripts, alternative splicing and polyadenylation, fusion genes and trans-splicing, post-transcriptional events, etc.). In order to provide researchers with an effective and friendly resource for analyzing RNA-Seq data, we present here RAP (RNA-Seq Analysis Pipeline), a cloud computing web application implementing a complete but modular analysis workflow. This pipeline integrates both state-of-the-art bioinformatics tools for RNA-Seq analysis and in-house developed scripts to offer to the user a comprehensive strategy for data analysis. RAP is able to perform quality checks (adopting FastQC and NGS QC Toolkit), identify and quantify expressed genes and transcripts (with Tophat, Cufflinks and HTSeq), detect alternative splicing events (using SpliceTrap) and chimeric transcripts (with ChimeraScan). This pipeline is also able to identify splicing junctions and constitutive or alternative polyadenylation sites (implementing custom analysis modules) and call for statistically significant differences in genes and transcripts expression, splicing pattern and polyadenylation site usage (using Cuffdiff2 and DESeq). Through a user friendly web interface, the RAP workflow can be suitably customized by the user and it is automatically executed on our cloud computing environment. This strategy allows to access to bioinformatics tools and computational resources without specific bioinformatics and IT skills. RAP provides a set of tabular and graphical results that can be helpful to browse, filter and export analyzed data, according to the user needs.

Challenges in Visual Analysis of Ensembles

DOE PAGES

Crossno, Patricia

2018-04-12

Modeling physical phenomena through computational simulation increasingly relies on generating a collection of related runs, known as an ensemble. In this paper, we explore the challenges we face in developing analysis and visualization systems for large and complex ensemble data sets, which we seek to understand without having to view the results of every simulation run. Implementing approaches and ideas developed in response to this goal, we demonstrate the analysis of a 15K run material fracturing study using Slycat, our ensemble analysis system.

Challenges in Visual Analysis of Ensembles

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

Crossno, Patricia

Modeling physical phenomena through computational simulation increasingly relies on generating a collection of related runs, known as an ensemble. In this paper, we explore the challenges we face in developing analysis and visualization systems for large and complex ensemble data sets, which we seek to understand without having to view the results of every simulation run. Implementing approaches and ideas developed in response to this goal, we demonstrate the analysis of a 15K run material fracturing study using Slycat, our ensemble analysis system.

Environmental Sensing of Expert Knowledge in a Computational Evolution System for Complex Problem Solving in Human Genetics

NASA Astrophysics Data System (ADS)

Greene, Casey S.; Hill, Douglas P.; Moore, Jason H.

The relationship between interindividual variation in our genomes and variation in our susceptibility to common diseases is expected to be complex with multiple interacting genetic factors. A central goal of human genetics is to identify which DNA sequence variations predict disease risk in human populations. Our success in this endeavour will depend critically on the development and implementation of computational intelligence methods that are able to embrace, rather than ignore, the complexity of the genotype to phenotype relationship. To this end, we have developed a computational evolution system (CES) to discover genetic models of disease susceptibility involving complex relationships between DNA sequence variations. The CES approach is hierarchically organized and is capable of evolving operators of any arbitrary complexity. The ability to evolve operators distinguishes this approach from artificial evolution approaches using fixed operators such as mutation and recombination. Our previous studies have shown that a CES that can utilize expert knowledge about the problem in evolved operators significantly outperforms a CES unable to use this knowledge. This environmental sensing of external sources of biological or statistical knowledge is important when the search space is both rugged and large as in the genetic analysis of complex diseases. We show here that the CES is also capable of evolving operators which exploit one of several sources of expert knowledge to solve the problem. This is important for both the discovery of highly fit genetic models and because the particular source of expert knowledge used by evolved operators may provide additional information about the problem itself. This study brings us a step closer to a CES that can solve complex problems in human genetics in addition to discovering genetic models of disease.

Comprehensive Experimental and Computational Spectroscopic Study of Hexacyanoferrate Complexes in Water: From Infrared to X-ray Wavelengths.

PubMed

Ross, Matthew; Andersen, Amity; Fox, Zachary W; Zhang, Yu; Hong, Kiryong; Lee, Jae-Hyuk; Cordones, Amy; March, Anne Marie; Doumy, Gilles; Southworth, Stephen H; Marcus, Matthew A; Schoenlein, Robert W; Mukamel, Shaul; Govind, Niranjan; Khalil, Munira

2018-05-17

We present a joint experimental and computational study of the hexacyanoferrate aqueous complexes at equilibrium in the 250 meV to 7.15 keV regime. The experiments and the computations include the vibrational spectroscopy of the cyanide ligands, the valence electronic absorption spectra, and Fe 1s core hole spectra using element-specific-resonant X-ray absorption and emission techniques. Density functional theory-based quantum mechanics/molecular mechanics molecular dynamics simulations are performed to generate explicit solute-solvent configurations, which serve as inputs for the spectroscopy calculations of the experiments spanning the IR to X-ray wavelengths. The spectroscopy simulations are performed at the same level of theory across this large energy window, which allows for a systematic comparison of the effects of explicit solute-solvent interactions in the vibrational, valence electronic, and core-level spectra of hexacyanoferrate complexes in water. Although the spectroscopy of hexacyanoferrate complexes in solution has been the subject of several studies, most of the previous works have focused on a narrow energy window and have not accounted for explicit solute-solvent interactions in their spectroscopy simulations. In this work, we focus our analysis on identifying how the local solvation environment around the hexacyanoferrate complexes influences the intensity and line shape of specific spectroscopic features in the UV/vis, X-ray absorption, and valence-to-core X-ray emission spectra. The identification of these features and their relationship to solute-solvent interactions is important because hexacyanoferrate complexes serve as model systems for understanding the photochemistry and photophysics of a large class of Fe(II) and Fe(III) complexes in solution.

Multiobjective Optimal Control Methodology for the Analysis of Certain Sociodynamic Problems

DTIC Science & Technology

2009-03-01

but less expensive in both time and memory. 137 References [1] R. Albert and A-L Barabasi. Statistical mechanics of complex networks. Reviews of Modern...Review, E(51):4282–4286, 1995. [24] D. Helbing, P. Molnar, and F. Schweitzer . Computer simulation of pedestrian dynamics and trail formation. May 1998...Patterson AFB, OH, 2001. [49] F. Schweitzer . Brownian Agents and Active Particles. Springer, Santa Fe, NM, 2003. [50] P. Sen. Complexities of social

Four-dimensional computed tomography based respiratory-gated radiotherapy with respiratory guidance system: analysis of respiratory signals and dosimetric comparison.

PubMed

Lee, Jung Ae; Kim, Chul Yong; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Lee, Suk; Kim, Young Bum

2014-01-01

To investigate the effectiveness of respiratory guidance system in 4-dimensional computed tomography (4 DCT) based respiratory-gated radiation therapy (RGRT) by comparing respiratory signals and dosimetric analysis of treatment plans. The respiratory amplitude and period of the free, the audio device-guided, and the complex system-guided breathing were evaluated in eleven patients with lung or liver cancers. The dosimetric parameters were assessed by comparing free breathing CT plan and 4 DCT-based 30-70% maximal intensity projection (MIP) plan. The use of complex system-guided breathing showed significantly less variation in respiratory amplitude and period compared to the free or audio-guided breathing regarding the root mean square errors (RMSE) of full inspiration (P = 0.031), full expiration (P = 0.007), and period (P = 0.007). The dosimetric parameters including V(5 Gy), V(10 Gy), V(20 Gy), V(30 Gy), V(40 Gy), and V(50 Gy) of normal liver or lung in 4 DCT MIP plan were superior over free breathing CT plan. The reproducibility and regularity of respiratory amplitude and period were significantly improved with the complex system-guided breathing compared to the free or the audio-guided breathing. In addition, the treatment plan based on the 4D CT-based MIP images acquired with the complex system guided breathing showed better normal tissue sparing than that on the free breathing CT.

Spectroscopic, structural, electrochemical and computational studies of some new 2-thienyl-containing β-diketonate complexes of cobalt(II), nickel(II) and copper(II)

NASA Astrophysics Data System (ADS)

Ahumada, Guillermo; Fuentealba, Mauricio; Roisnel, Thierry; Kahlal, Samia; Córdova, Ricardo; Carrillo, David; Saillard, Jean-Yves; Hamon, Jean-René; Manzur, Carolina

2017-12-01

In this work, we present the synthesis of the unsymmetrical β-diketone 1-(2-thienyl)-3-(4-fluorophenyl)-propane-1,3-dione (HL) and its corresponding Co(II), Ni(II) and Cu(II) bis(β-diketonato) complexes 1-3, respectively. The four new compounds were isolated in good yields (65-70%), and characterized by mass spectrometry, elemental analysis, FT-IR and UV-Vis spectroscopy and, in the case of HL, by 1H, 13C and 19F NMR spectroscopy. In addition, the molecular identities and the geometries of the β-diketone HL and complex 3 were confirmed by X-ray diffraction analysis. The dicarbonyl derivative HL does exist as the diketo tautomeric form in DMSO solution and as its keto-enol tautomer in the solid-state with the sbnd OH group adjacent to the 4-fluorophenyl unit. The keto-enol isomer was computed to be more stable by 8.2 kcal/mol in free energy at room temperature. In 3, the Cu(II) center adopts a perfect square-planar geometry. Two reduction processes were observed in the cyclovoltammogram of 3 at -1.30 and -1.80 V vs. Fc/Fc+, with copper deposit on the surface of the electrode. DFT and TD-DFT calculations on HL and complex 3 allow rationalizing their stability, bonding and properties.

Finite difference method accelerated with sparse solvers for structural analysis of the metal-organic complexes

NASA Astrophysics Data System (ADS)

Guda, A. A.; Guda, S. A.; Soldatov, M. A.; Lomachenko, K. A.; Bugaev, A. L.; Lamberti, C.; Gawelda, W.; Bressler, C.; Smolentsev, G.; Soldatov, A. V.; Joly, Y.

2016-05-01

Finite difference method (FDM) implemented in the FDMNES software [Phys. Rev. B, 2001, 63, 125120] was revised. Thorough analysis shows, that the calculated diagonal in the FDM matrix consists of about 96% zero elements. Thus a sparse solver would be more suitable for the problem instead of traditional Gaussian elimination for the diagonal neighbourhood. We have tried several iterative sparse solvers and the direct one MUMPS solver with METIS ordering turned out to be the best. Compared to the Gaussian solver present method is up to 40 times faster and allows XANES simulations for complex systems already on personal computers. We show applicability of the software for metal-organic [Fe(bpy)3]2+ complex both for low spin and high spin states populated after laser excitation.

Scalable Algorithms for Clustering Large Geospatiotemporal Data Sets on Manycore Architectures

NASA Astrophysics Data System (ADS)

Mills, R. T.; Hoffman, F. M.; Kumar, J.; Sreepathi, S.; Sripathi, V.

2016-12-01

The increasing availability of high-resolution geospatiotemporal data sets from sources such as observatory networks, remote sensing platforms, and computational Earth system models has opened new possibilities for knowledge discovery using data sets fused from disparate sources. Traditional algorithms and computing platforms are impractical for the analysis and synthesis of data sets of this size; however, new algorithmic approaches that can effectively utilize the complex memory hierarchies and the extremely high levels of available parallelism in state-of-the-art high-performance computing platforms can enable such analysis. We describe a massively parallel implementation of accelerated k-means clustering and some optimizations to boost computational intensity and utilization of wide SIMD lanes on state-of-the art multi- and manycore processors, including the second-generation Intel Xeon Phi ("Knights Landing") processor based on the Intel Many Integrated Core (MIC) architecture, which includes several new features, including an on-package high-bandwidth memory. We also analyze the code in the context of a few practical applications to the analysis of climatic and remotely-sensed vegetation phenology data sets, and speculate on some of the new applications that such scalable analysis methods may enable.

GPU-based acceleration of computations in nonlinear finite element deformation analysis.

PubMed

Mafi, Ramin; Sirouspour, Shahin

2014-03-01

The physics of deformation for biological soft-tissue is best described by nonlinear continuum mechanics-based models, which then can be discretized by the FEM for a numerical solution. However, computational complexity of such models have limited their use in applications requiring real-time or fast response. In this work, we propose a graphic processing unit-based implementation of the FEM using implicit time integration for dynamic nonlinear deformation analysis. This is the most general formulation of the deformation analysis. It is valid for large deformations and strains and can account for material nonlinearities. The data-parallel nature and the intense arithmetic computations of nonlinear FEM equations make it particularly suitable for implementation on a parallel computing platform such as graphic processing unit. In this work, we present and compare two different designs based on the matrix-free and conventional preconditioned conjugate gradients algorithms for solving the FEM equations arising in deformation analysis. The speedup achieved with the proposed parallel implementations of the algorithms will be instrumental in the development of advanced surgical simulators and medical image registration methods involving soft-tissue deformation. Copyright © 2013 John Wiley & Sons, Ltd.

A new framework for comprehensive, robust, and efficient global sensitivity analysis: 1. Theory

NASA Astrophysics Data System (ADS)

Razavi, Saman; Gupta, Hoshin V.

2016-01-01

Computer simulation models are continually growing in complexity with increasingly more factors to be identified. Sensitivity Analysis (SA) provides an essential means for understanding the role and importance of these factors in producing model responses. However, conventional approaches to SA suffer from (1) an ambiguous characterization of sensitivity, and (2) poor computational efficiency, particularly as the problem dimension grows. Here, we present a new and general sensitivity analysis framework (called VARS), based on an analogy to "variogram analysis," that provides an intuitive and comprehensive characterization of sensitivity across the full spectrum of scales in the factor space. We prove, theoretically, that Morris (derivative-based) and Sobol (variance-based) methods and their extensions are special cases of VARS, and that their SA indices can be computed as by-products of the VARS framework. Synthetic functions that resemble actual model response surfaces are used to illustrate the concepts, and show VARS to be as much as two orders of magnitude more computationally efficient than the state-of-the-art Sobol approach. In a companion paper, we propose a practical implementation strategy, and demonstrate the effectiveness, efficiency, and reliability (robustness) of the VARS framework on real-data case studies.

Gene regulatory networks: a coarse-grained, equation-free approach to multiscale computation.

PubMed

Erban, Radek; Kevrekidis, Ioannis G; Adalsteinsson, David; Elston, Timothy C

2006-02-28

We present computer-assisted methods for analyzing stochastic models of gene regulatory networks. The main idea that underlies this equation-free analysis is the design and execution of appropriately initialized short bursts of stochastic simulations; the results of these are processed to estimate coarse-grained quantities of interest, such as mesoscopic transport coefficients. In particular, using a simple model of a genetic toggle switch, we illustrate the computation of an effective free energy Phi and of a state-dependent effective diffusion coefficient D that characterize an unavailable effective Fokker-Planck equation. Additionally we illustrate the linking of equation-free techniques with continuation methods for performing a form of stochastic "bifurcation analysis"; estimation of mean switching times in the case of a bistable switch is also implemented in this equation-free context. The accuracy of our methods is tested by direct comparison with long-time stochastic simulations. This type of equation-free analysis appears to be a promising approach to computing features of the long-time, coarse-grained behavior of certain classes of complex stochastic models of gene regulatory networks, circumventing the need for long Monte Carlo simulations.

Research on application of intelligent computation based LUCC model in urbanization process

NASA Astrophysics Data System (ADS)

Chen, Zemin

2007-06-01

Global change study is an interdisciplinary and comprehensive research activity with international cooperation, arising in 1980s, with the largest scopes. The interaction between land use and cover change, as a research field with the crossing of natural science and social science, has become one of core subjects of global change study as well as the front edge and hot point of it. It is necessary to develop research on land use and cover change in urbanization process and build an analog model of urbanization to carry out description, simulation and analysis on dynamic behaviors in urban development change as well as to understand basic characteristics and rules of urbanization process. This has positive practical and theoretical significance for formulating urban and regional sustainable development strategy. The effect of urbanization on land use and cover change is mainly embodied in the change of quantity structure and space structure of urban space, and LUCC model in urbanization process has been an important research subject of urban geography and urban planning. In this paper, based upon previous research achievements, the writer systematically analyzes the research on land use/cover change in urbanization process with the theories of complexity science research and intelligent computation; builds a model for simulating and forecasting dynamic evolution of urban land use and cover change, on the basis of cellular automation model of complexity science research method and multi-agent theory; expands Markov model, traditional CA model and Agent model, introduces complexity science research theory and intelligent computation theory into LUCC research model to build intelligent computation-based LUCC model for analog research on land use and cover change in urbanization research, and performs case research. The concrete contents are as follows: 1. Complexity of LUCC research in urbanization process. Analyze urbanization process in combination with the contents of complexity science research and the conception of complexity feature to reveal the complexity features of LUCC research in urbanization process. Urban space system is a complex economic and cultural phenomenon as well as a social process, is the comprehensive characterization of urban society, economy and culture, and is a complex space system formed by society, economy and nature. It has dissipative structure characteristics, such as opening, dynamics, self-organization, non-balance etc. Traditional model cannot simulate these social, economic and natural driving forces of LUCC including main feedback relation from LUCC to driving force. 2. Establishment of Markov extended model of LUCC analog research in urbanization process. Firstly, use traditional LUCC research model to compute change speed of regional land use through calculating dynamic degree, exploitation degree and consumption degree of land use; use the theory of fuzzy set to rewrite the traditional Markov model, establish structure transfer matrix of land use, forecast and analyze dynamic change and development trend of land use, and present noticeable problems and corresponding measures in urbanization process according to research results. 3. Application of intelligent computation research and complexity science research method in LUCC analog model in urbanization process. On the basis of detailed elaboration of the theory and the model of LUCC research in urbanization process, analyze the problems of existing model used in LUCC research (namely, difficult to resolve many complexity phenomena in complex urban space system), discuss possible structure realization forms of LUCC analog research in combination with the theories of intelligent computation and complexity science research. Perform application analysis on BP artificial neural network and genetic algorithms of intelligent computation and CA model and MAS technology of complexity science research, discuss their theoretical origins and their own characteristics in detail, elaborate the feasibility of them in LUCC analog research, and bring forward improvement methods and measures on existing problems of this kind of model. 4. Establishment of LUCC analog model in urbanization process based on theories of intelligent computation and complexity science. Based on the research on abovementioned BP artificial neural network, genetic algorithms, CA model and multi-agent technology, put forward improvement methods and application assumption towards their expansion on geography, build LUCC analog model in urbanization process based on CA model and Agent model, realize the combination of learning mechanism of BP artificial neural network and fuzzy logic reasoning, express the regulation with explicit formula, and amend the initial regulation through self study; optimize network structure of LUCC analog model and methods and procedures of model parameters with genetic algorithms. In this paper, I introduce research theory and methods of complexity science into LUCC analog research and presents LUCC analog model based upon CA model and MAS theory. Meanwhile, I carry out corresponding expansion on traditional Markov model and introduce the theory of fuzzy set into data screening and parameter amendment of improved model to improve the accuracy and feasibility of Markov model in the research on land use/cover change.

Nature and potency interactions of the hydrogen bond through the NBO analysis for charge transfer complex between 2-amino-4-hydroxy-6-methylpyrimidine and 2,3-pyrazinedicarboxylic acid

NASA Astrophysics Data System (ADS)

Faizan, Mohd; Afroz, Ziya; Alam, Mohammad Jane; Bhat, Sheeraz Ahmad; Ahmad, Shabbir; Ahmad, Afaq

2018-05-01

The intermolecular interactions in complex formation between 2-amino-4-hydroxy-6-methylpyrimidine (AHMP) and 2,3-pyrazinedicarboxylicacid (PDCA) have been explored using density functional theory calculations. The isolated 1:1 molecular geometry of proton transfer (PT) complex between AHMP and PDCA has been optimized on a counterpoise corrected potential energy surface (PES) at DFT-B3LYP/6-31G(d,p) level of theory in the gaseous phase. Further, the formation of hydrogen bonded charge transfer (HBCT) complex between PDCA and AHMP has been also discussed. PT energy barrier between two extremes is calculated using potential energy surface (PES) scan by varying bond length. The intermolecular interactions have been analyzed from theoretical perspective of natural bond orbital (NBO) analysis. In addition, the interaction energy between molecular fragments involved in the complex formation has been also computed by counterpoise procedure at same level of theory.

Global Analysis of Yeast Endosomal Transport Identifies the Vps55/68 Sorting Complex

PubMed Central

Schluter, Cayetana; Lam, Karen K.Y.; Brumm, Jochen; Wu, Bella W.; Saunders, Matthew; Stevens, Tom H.

2008-01-01

Endosomal transport is critical for cellular processes ranging from receptor down-regulation and retroviral budding to the immune response. A full understanding of endosome sorting requires a comprehensive picture of the multiprotein complexes that orchestrate vesicle formation and fusion. Here, we use unsupervised, large-scale phenotypic analysis and a novel computational approach for the global identification of endosomal transport factors. This technique effectively identifies components of known and novel protein assemblies. We report the characterization of a previously undescribed endosome sorting complex that contains two well-conserved proteins with four predicted membrane-spanning domains. Vps55p and Vps68p form a complex that acts with or downstream of ESCRT function to regulate endosomal trafficking. Loss of Vps68p disrupts recycling to the TGN as well as onward trafficking to the vacuole without preventing the formation of lumenal vesicles within the MVB. Our results suggest the Vps55/68 complex mediates a novel, conserved step in the endosomal maturation process. PMID:18216282

Introduction to the LaRC central scientific computing complex

NASA Technical Reports Server (NTRS)

Shoosmith, John N.

1993-01-01

The computers and associated equipment that make up the Central Scientific Computing Complex of the Langley Research Center are briefly described. The electronic networks that provide access to the various components of the complex and a number of areas that can be used by Langley and contractors staff for special applications (scientific visualization, image processing, software engineering, and grid generation) are also described. Flight simulation facilities that use the central computers are described. Management of the complex, procedures for its use, and available services and resources are discussed. This document is intended for new users of the complex, for current users who wish to keep appraised of changes, and for visitors who need to understand the role of central scientific computers at Langley.

Technology for Analysis of Student Interactions With Complex Programs. Final Report for Period January 1972-February 1973.

ERIC Educational Resources Information Center

Lukas, George; Feurzeig, Wallace

A description is provided of a computer system designed to aid in the analysis of student programing work. The first section of the report consists of an overview and user's guide. In it, the system input is described in terms of a "dribble file" which records all student inputs generated; also an introduction is given to the aids…

User's guide for ENSAERO: A multidisciplinary program for fluid/structural/control interaction studies of aircraft (release 1)

NASA Technical Reports Server (NTRS)

Guruswamy, Guru P.

1994-01-01

Strong interactions can occur between the flow about an aerospace vehicle and its structural components resulting in several important aeroelastic phenomena. These aeroelastic phenomena can significantly influence the performance of the vehicle. At present, closed-form solutions are available for aeroelastic computations when flows are in either the linear subsonic or supersonic range. However, for aeroelasticity involving complex nonlinear flows with shock waves, vortices, flow separations, and aerodynamic heating, computational methods are still under development. These complex aeroelastic interactions can be dangerous and limit the performance of aircraft. Examples of these detrimental effects are aircraft with highly swept wings experiencing vortex-induced aeroelastic oscillations, transonic regime at which the flutter speed is low, aerothermoelastic loads that play a critical role in the design of high-speed vehicles, and flow separations that often lead to buffeting with undesirable structural oscillations. The simulation of these complex aeroelastic phenomena requires an integrated analysis of fluids and structures. This report presents a summary of the development, applications, and procedures to use the multidisciplinary computer code ENSAERO. This code is based on the Euler/Navier-Stokes flow equations and modal/finite-element structural equations.

Navigating complex sample analysis using national survey data.

PubMed

Saylor, Jennifer; Friedmann, Erika; Lee, Hyeon Joo

2012-01-01

The National Center for Health Statistics conducts the National Health and Nutrition Examination Survey and other national surveys with probability-based complex sample designs. Goals of national surveys are to provide valid data for the population of the United States. Analyses of data from population surveys present unique challenges in the research process but are valuable avenues to study the health of the United States population. The aim of this study was to demonstrate the importance of using complex data analysis techniques for data obtained with complex multistage sampling design and provide an example of analysis using the SPSS Complex Samples procedure. Illustration of challenges and solutions specific to secondary data analysis of national databases are described using the National Health and Nutrition Examination Survey as the exemplar. Oversampling of small or sensitive groups provides necessary estimates of variability within small groups. Use of weights without complex samples accurately estimates population means and frequency from the sample after accounting for over- or undersampling of specific groups. Weighting alone leads to inappropriate population estimates of variability, because they are computed as if the measures were from the entire population rather than a sample in the data set. The SPSS Complex Samples procedure allows inclusion of all sampling design elements, stratification, clusters, and weights. Use of national data sets allows use of extensive, expensive, and well-documented survey data for exploratory questions but limits analysis to those variables included in the data set. The large sample permits examination of multiple predictors and interactive relationships. Merging data files, availability of data in several waves of surveys, and complex sampling are techniques used to provide a representative sample but present unique challenges. In sophisticated data analysis techniques, use of these data is optimized.

Patient-specific surgical planning and hemodynamic computational fluid dynamics optimization through free-form haptic anatomy editing tool (SURGEM).

PubMed

Pekkan, Kerem; Whited, Brian; Kanter, Kirk; Sharma, Shiva; de Zelicourt, Diane; Sundareswaran, Kartik; Frakes, David; Rossignac, Jarek; Yoganathan, Ajit P

2008-11-01

The first version of an anatomy editing/surgical planning tool (SURGEM) targeting anatomical complexity and patient-specific computational fluid dynamics (CFD) analysis is presented. Novel three-dimensional (3D) shape editing concepts and human-shape interaction technologies have been integrated to facilitate interactive surgical morphology alterations, grid generation and CFD analysis. In order to implement "manual hemodynamic optimization" at the surgery planning phase for patients with congenital heart defects, these tools are applied to design and evaluate possible modifications of patient-specific anatomies. In this context, anatomies involve complex geometric topologies and tortuous 3D blood flow pathways with multiple inlets and outlets. These tools make it possible to freely deform the lumen surface and to bend and position baffles through real-time, direct manipulation of the 3D models with both hands, thus eliminating the tedious and time-consuming phase of entering the desired geometry using traditional computer-aided design (CAD) systems. The 3D models of the modified anatomies are seamlessly exported and meshed for patient-specific CFD analysis. Free-formed anatomical modifications are quantified using an in-house skeletization based cross-sectional geometry analysis tool. Hemodynamic performance of the systematically modified anatomies is compared with the original anatomy using CFD. CFD results showed the relative importance of the various surgically created features such as pouch size, vena cave to pulmonary artery (PA) flare and PA stenosis. An interactive surgical-patch size estimator is also introduced. The combined design/analysis cycle time is used for comparing and optimizing surgical plans and improvements are tabulated. The reduced cost of patient-specific shape design and analysis process, made it possible to envision large clinical studies to assess the validity of predictive patient-specific CFD simulations. In this paper, model anatomical design studies are performed on a total of eight different complex patient specific anatomies. Using SURGEM, more than 30 new anatomical designs (or candidate configurations) are created, and the corresponding user times presented. CFD performances for eight of these candidate configurations are also presented.

Enabling Grid Computing resources within the KM3NeT computing model

NASA Astrophysics Data System (ADS)

Filippidis, Christos

2016-04-01

KM3NeT is a future European deep-sea research infrastructure hosting a new generation neutrino detectors that - located at the bottom of the Mediterranean Sea - will open a new window on the universe and answer fundamental questions both in particle physics and astrophysics. International collaborative scientific experiments, like KM3NeT, are generating datasets which are increasing exponentially in both complexity and volume, making their analysis, archival, and sharing one of the grand challenges of the 21st century. These experiments, in their majority, adopt computing models consisting of different Tiers with several computing centres and providing a specific set of services for the different steps of data processing such as detector calibration, simulation and data filtering, reconstruction and analysis. The computing requirements are extremely demanding and, usually, span from serial to multi-parallel or GPU-optimized jobs. The collaborative nature of these experiments demands very frequent WAN data transfers and data sharing among individuals and groups. In order to support the aforementioned demanding computing requirements we enabled Grid Computing resources, operated by EGI, within the KM3NeT computing model. In this study we describe our first advances in this field and the method for the KM3NeT users to utilize the EGI computing resources in a simulation-driven use-case.

Accelerating Computation of DCM for ERP in MATLAB by External Function Calls to the GPU.

PubMed

Wang, Wei-Jen; Hsieh, I-Fan; Chen, Chun-Chuan

2013-01-01

This study aims to improve the performance of Dynamic Causal Modelling for Event Related Potentials (DCM for ERP) in MATLAB by using external function calls to a graphics processing unit (GPU). DCM for ERP is an advanced method for studying neuronal effective connectivity. DCM utilizes an iterative procedure, the expectation maximization (EM) algorithm, to find the optimal parameters given a set of observations and the underlying probability model. As the EM algorithm is computationally demanding and the analysis faces possible combinatorial explosion of models to be tested, we propose a parallel computing scheme using the GPU to achieve a fast estimation of DCM for ERP. The computation of DCM for ERP is dynamically partitioned and distributed to threads for parallel processing, according to the DCM model complexity and the hardware constraints. The performance efficiency of this hardware-dependent thread arrangement strategy was evaluated using the synthetic data. The experimental data were used to validate the accuracy of the proposed computing scheme and quantify the time saving in practice. The simulation results show that the proposed scheme can accelerate the computation by a factor of 155 for the parallel part. For experimental data, the speedup factor is about 7 per model on average, depending on the model complexity and the data. This GPU-based implementation of DCM for ERP gives qualitatively the same results as the original MATLAB implementation does at the group level analysis. In conclusion, we believe that the proposed GPU-based implementation is very useful for users as a fast screen tool to select the most likely model and may provide implementation guidance for possible future clinical applications such as online diagnosis.

Superior model for fault tolerance computation in designing nano-sized circuit systems

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

Singh, N. S. S., E-mail: narinderjit@petronas.com.my; Muthuvalu, M. S., E-mail: msmuthuvalu@gmail.com; Asirvadam, V. S., E-mail: vijanth-sagayan@petronas.com.my

2014-10-24

As CMOS technology scales nano-metrically, reliability turns out to be a decisive subject in the design methodology of nano-sized circuit systems. As a result, several computational approaches have been developed to compute and evaluate reliability of desired nano-electronic circuits. The process of computing reliability becomes very troublesome and time consuming as the computational complexity build ups with the desired circuit size. Therefore, being able to measure reliability instantly and superiorly is fast becoming necessary in designing modern logic integrated circuits. For this purpose, the paper firstly looks into the development of an automated reliability evaluation tool based on the generalizationmore » of Probabilistic Gate Model (PGM) and Boolean Difference-based Error Calculator (BDEC) models. The Matlab-based tool allows users to significantly speed-up the task of reliability analysis for very large number of nano-electronic circuits. Secondly, by using the developed automated tool, the paper explores into a comparative study involving reliability computation and evaluation by PGM and, BDEC models for different implementations of same functionality circuits. Based on the reliability analysis, BDEC gives exact and transparent reliability measures, but as the complexity of the same functionality circuits with respect to gate error increases, reliability measure by BDEC tends to be lower than the reliability measure by PGM. The lesser reliability measure by BDEC is well explained in this paper using distribution of different signal input patterns overtime for same functionality circuits. Simulation results conclude that the reliability measure by BDEC depends not only on faulty gates but it also depends on circuit topology, probability of input signals being one or zero and also probability of error on signal lines.« less

MindEdit: A P300-based text editor for mobile devices.

PubMed

Elsawy, Amr S; Eldawlatly, Seif; Taher, Mohamed; Aly, Gamal M

2017-01-01

Practical application of Brain-Computer Interfaces (BCIs) requires that the whole BCI system be portable. The mobility of BCI systems involves two aspects: making the electroencephalography (EEG) recording devices portable, and developing software applications with low computational complexity to be able to run on low computational-power devices such as tablets and smartphones. This paper addresses the development of MindEdit; a P300-based text editor for Android-based devices. Given the limited resources of mobile devices and their limited computational power, a novel ensemble classifier is utilized that uses Principal Component Analysis (PCA) features to identify P300 evoked potentials from EEG recordings. PCA computations in the proposed method are channel-based as opposed to concatenating all channels as in traditional feature extraction methods; thus, this method has less computational complexity compared to traditional P300 detection methods. The performance of the method is demonstrated on data recorded from MindEdit on an Android tablet using the Emotiv wireless neuroheadset. Results demonstrate the capability of the introduced PCA ensemble classifier to classify P300 data with maximum average accuracy of 78.37±16.09% for cross-validation data and 77.5±19.69% for online test data using only 10 trials per symbol and a 33-character training dataset. Our analysis indicates that the introduced method outperforms traditional feature extraction methods. For a faster operation of MindEdit, a variable number of trials scheme is introduced that resulted in an online average accuracy of 64.17±19.6% and a maximum bitrate of 6.25bit/min. These results demonstrate the efficacy of using the developed BCI application with mobile devices. Copyright © 2016 Elsevier Ltd. All rights reserved.

Accelerating Computation of DCM for ERP in MATLAB by External Function Calls to the GPU

PubMed Central

Wang, Wei-Jen; Hsieh, I-Fan; Chen, Chun-Chuan

2013-01-01

This study aims to improve the performance of Dynamic Causal Modelling for Event Related Potentials (DCM for ERP) in MATLAB by using external function calls to a graphics processing unit (GPU). DCM for ERP is an advanced method for studying neuronal effective connectivity. DCM utilizes an iterative procedure, the expectation maximization (EM) algorithm, to find the optimal parameters given a set of observations and the underlying probability model. As the EM algorithm is computationally demanding and the analysis faces possible combinatorial explosion of models to be tested, we propose a parallel computing scheme using the GPU to achieve a fast estimation of DCM for ERP. The computation of DCM for ERP is dynamically partitioned and distributed to threads for parallel processing, according to the DCM model complexity and the hardware constraints. The performance efficiency of this hardware-dependent thread arrangement strategy was evaluated using the synthetic data. The experimental data were used to validate the accuracy of the proposed computing scheme and quantify the time saving in practice. The simulation results show that the proposed scheme can accelerate the computation by a factor of 155 for the parallel part. For experimental data, the speedup factor is about 7 per model on average, depending on the model complexity and the data. This GPU-based implementation of DCM for ERP gives qualitatively the same results as the original MATLAB implementation does at the group level analysis. In conclusion, we believe that the proposed GPU-based implementation is very useful for users as a fast screen tool to select the most likely model and may provide implementation guidance for possible future clinical applications such as online diagnosis. PMID:23840507

Empirical Requirements Analysis for Mars Surface Operations Using the Flashline Mars Arctic Research Station

NASA Technical Reports Server (NTRS)

Clancey, William J.; Lee, Pascal; Sierhuis, Maarten; Norvig, Peter (Technical Monitor)

2001-01-01

Living and working on Mars will require model-based computer systems for maintaining and controlling complex life support, communication, transportation, and power systems. This technology must work properly on the first three-year mission, augmenting human autonomy, without adding-yet more complexity to be diagnosed and repaired. One design method is to work with scientists in analog (mars-like) setting to understand how they prefer to work, what constrains will be imposed by the Mars environment, and how to ameliorate difficulties. We describe how we are using empirical requirements analysis to prototype model-based tools at a research station in the High Canadian Arctic.

Artificial intelligence applied to process signal analysis

NASA Technical Reports Server (NTRS)

Corsberg, Dan

1988-01-01

Many space station processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect of the human/machine interface is the analysis and display of process information. Human operators can be overwhelmed by large clusters of alarms that inhibit their ability to diagnose and respond to a disturbance. Using artificial intelligence techniques and a knowledge base approach to this problem, the power of the computer can be used to filter and analyze plant sensor data. This will provide operators with a better description of the process state. Once a process state is recognized, automatic action could be initiated and proper system response monitored.

Geo-Distinctive Comorbidity Networks of Pediatric Asthma.

PubMed

Shin, Eun Kyong; Shaban-Nejad, Arash

2018-01-01

Most pediatric asthma cases occur in complex interdependencies, exhibiting complex manifestation of multiple symptoms. Studying asthma comorbidities can help to better understand the etiology pathway of the disease. Albeit such relations of co-expressed symptoms and their interactions have been highlighted recently, empirical investigation has not been rigorously applied to pediatric asthma cases. In this study, we use computational network modeling and analysis to reveal the links and associations between commonly co-observed diseases/conditions with asthma among children in Memphis, Tennessee. We present a novel method for geo-parsed comorbidity network analysis to show the distinctive patterns of comorbidity networks in urban and suburban areas in Memphis.

Music video shot segmentation using independent component analysis and keyframe extraction based on image complexity

NASA Astrophysics Data System (ADS)

Li, Wei; Chen, Ting; Zhang, Wenjun; Shi, Yunyu; Li, Jun

2012-04-01

In recent years, Music video data is increasing at an astonishing speed. Shot segmentation and keyframe extraction constitute a fundamental unit in organizing, indexing, retrieving video content. In this paper a unified framework is proposed to detect the shot boundaries and extract the keyframe of a shot. Music video is first segmented to shots by illumination-invariant chromaticity histogram in independent component (IC) analysis feature space .Then we presents a new metric, image complexity, to extract keyframe in a shot which is computed by ICs. Experimental results show the framework is effective and has a good performance.

Computational oncology.

PubMed

Lefor, Alan T

2011-08-01

Oncology research has traditionally been conducted using techniques from the biological sciences. The new field of computational oncology has forged a new relationship between the physical sciences and oncology to further advance research. By applying physics and mathematics to oncologic problems, new insights will emerge into the pathogenesis and treatment of malignancies. One major area of investigation in computational oncology centers around the acquisition and analysis of data, using improved computing hardware and software. Large databases of cellular pathways are being analyzed to understand the interrelationship among complex biological processes. Computer-aided detection is being applied to the analysis of routine imaging data including mammography and chest imaging to improve the accuracy and detection rate for population screening. The second major area of investigation uses computers to construct sophisticated mathematical models of individual cancer cells as well as larger systems using partial differential equations. These models are further refined with clinically available information to more accurately reflect living systems. One of the major obstacles in the partnership between physical scientists and the oncology community is communications. Standard ways to convey information must be developed. Future progress in computational oncology will depend on close collaboration between clinicians and investigators to further the understanding of cancer using these new approaches.

Copper(II) complex with 6-methylpyridine-2-carboxyclic acid: Experimental and computational study on the XRD, FT-IR and UV-Vis spectra, refractive index, band gap and NLO parameters

NASA Astrophysics Data System (ADS)

Altürk, Sümeyye; Avcı, Davut; Başoğlu, Adil; Tamer, Ömer; Atalay, Yusuf; Dege, Necmi

2018-02-01

Crystal structure of the synthesized copper(II) complex with 6-methylpyridine-2-carboxylic acid, [Cu(6-Mepic)2·H2O]·H2O, was determined by XRD, FT-IR and UV-Vis spectroscopic techniques. Furthermore, the geometry optimization, harmonic vibration frequencies for the Cu(II) complex were carried out by using Density Functional Theory calculations with HSEh1PBE/6-311G(d,p)/LanL2DZ level. Electronic absorption wavelengths were obtained by using TD-DFT/HSEh1PBE/6-311G(d,p)/LanL2DZ level with CPCM model and major contributions were determined via Swizard/Chemissian program. Additionally, the refractive index, linear optical (LO) and non-nonlinear optical (NLO) parameters of the Cu(II) complex were calculated at HSEh1PBE/6-311G(d,p) level. The experimental and computed small energy gap shows the charge transfer in the Cu(II) complex. Finally, the hyperconjugative interactions and intramolecular charge transfer (ICT) were studied by performing of natural bond orbital (NBO) analysis.

Copper(II) complex with 6-methylpyridine-2-carboxyclic acid: Experimental and computational study on the XRD, FT-IR and UV-Vis spectra, refractive index, band gap and NLO parameters.

PubMed

Altürk, Sümeyye; Avcı, Davut; Başoğlu, Adil; Tamer, Ömer; Atalay, Yusuf; Dege, Necmi

2018-02-05

Crystal structure of the synthesized copper(II) complex with 6-methylpyridine-2-carboxylic acid, [Cu(6-Mepic) 2 ·H 2 O]·H 2 O, was determined by XRD, FT-IR and UV-Vis spectroscopic techniques. Furthermore, the geometry optimization, harmonic vibration frequencies for the Cu(II) complex were carried out by using Density Functional Theory calculations with HSEh1PBE/6-311G(d,p)/LanL2DZ level. Electronic absorption wavelengths were obtained by using TD-DFT/HSEh1PBE/6-311G(d,p)/LanL2DZ level with CPCM model and major contributions were determined via Swizard/Chemissian program. Additionally, the refractive index, linear optical (LO) and non-nonlinear optical (NLO) parameters of the Cu(II) complex were calculated at HSEh1PBE/6-311G(d,p) level. The experimental and computed small energy gap shows the charge transfer in the Cu(II) complex. Finally, the hyperconjugative interactions and intramolecular charge transfer (ICT) were studied by performing of natural bond orbital (NBO) analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Historical and contingent factors affect re-evolution of a complex feature lost during mass extinction in communities of digital organisms.

PubMed

Yedid, G; Ofria, C A; Lenski, R E

2008-09-01

Re-evolution of complex biological features following the extinction of taxa bearing them remains one of evolution's most interesting phenomena, but is not amenable to study in fossil taxa. We used communities of digital organisms (computer programs that self-replicate, mutate and evolve), subjected to periods of low resource availability, to study the evolution, loss and re-evolution of a complex computational trait, the function EQU (bit-wise logical equals). We focused our analysis on cases where the pre-extinction EQU clade had surviving descendents at the end of the extinction episode. To see if these clades retained the capacity to re-evolve EQU, we seeded one set of multiple subreplicate 'replay' populations using the most abundant survivor of the pre-extinction EQU clade, and another set with the actual end-extinction ancestor of the organism in which EQU re-evolved following the extinction episode. Our results demonstrate that stochastic, historical, genomic and ecological factors can lead to constraints on further adaptation, and facilitate or hinder re-evolution of a complex feature.

Vibrational analysis and quantum chemical calculations of 2,2‧-bipyridine Zinc(II) halide complexes

NASA Astrophysics Data System (ADS)

Ozel, Aysen E.; Kecel, Serda; Akyuz, Sevim

2007-05-01

In this study the molecular structure and vibrational spectra of Zn(2,2'-bipyridine)X 2 (X = Cl and Br) complexes were studied in their ground states by computational vibrational study and scaled quantum mechanical (SQM) analysis. The geometry optimization, vibrational wavenumber and intensity calculations of free and coordinated 2,2'-bipyridine were carried out with the Gaussian03 program package by using Hartree-Fock (HF) and Density Functional Theory (DFT) with B3LYP functional and 6-31G (d,p) basis set. The total energy distributions (TED) of the vibrational modes were calculated by using Scaled Quantum Mechanical (SQM) analysis. Fundamentals were characterised by their total energy distributions. Coordination sensitive modes of 2,2'-bipyridine were determined.

Computational Aeroelastic Modeling of Airframes and TurboMachinery: Progress and Challenges

NASA Technical Reports Server (NTRS)

Bartels, R. E.; Sayma, A. I.

2006-01-01

Computational analyses such as computational fluid dynamics and computational structural dynamics have made major advances toward maturity as engineering tools. Computational aeroelasticity is the integration of these disciplines. As computational aeroelasticity matures it too finds an increasing role in the design and analysis of aerospace vehicles. This paper presents a survey of the current state of computational aeroelasticity with a discussion of recent research, success and continuing challenges in its progressive integration into multidisciplinary aerospace design. This paper approaches computational aeroelasticity from the perspective of the two main areas of application: airframe and turbomachinery design. An overview will be presented of the different prediction methods used for each field of application. Differing levels of nonlinear modeling will be discussed with insight into accuracy versus complexity and computational requirements. Subjects will include current advanced methods (linear and nonlinear), nonlinear flow models, use of order reduction techniques and future trends in incorporating structural nonlinearity. Examples in which computational aeroelasticity is currently being integrated into the design of airframes and turbomachinery will be presented.

Rapid Global Fitting of Large Fluorescence Lifetime Imaging Microscopy Datasets

PubMed Central

Warren, Sean C.; Margineanu, Anca; Alibhai, Dominic; Kelly, Douglas J.; Talbot, Clifford; Alexandrov, Yuriy; Munro, Ian; Katan, Matilda

2013-01-01

Fluorescence lifetime imaging (FLIM) is widely applied to obtain quantitative information from fluorescence signals, particularly using Förster Resonant Energy Transfer (FRET) measurements to map, for example, protein-protein interactions. Extracting FRET efficiencies or population fractions typically entails fitting data to complex fluorescence decay models but such experiments are frequently photon constrained, particularly for live cell or in vivo imaging, and this leads to unacceptable errors when analysing data on a pixel-wise basis. Lifetimes and population fractions may, however, be more robustly extracted using global analysis to simultaneously fit the fluorescence decay data of all pixels in an image or dataset to a multi-exponential model under the assumption that the lifetime components are invariant across the image (dataset). This approach is often considered to be prohibitively slow and/or computationally expensive but we present here a computationally efficient global analysis algorithm for the analysis of time-correlated single photon counting (TCSPC) or time-gated FLIM data based on variable projection. It makes efficient use of both computer processor and memory resources, requiring less than a minute to analyse time series and multiwell plate datasets with hundreds of FLIM images on standard personal computers. This lifetime analysis takes account of repetitive excitation, including fluorescence photons excited by earlier pulses contributing to the fit, and is able to accommodate time-varying backgrounds and instrument response functions. We demonstrate that this global approach allows us to readily fit time-resolved fluorescence data to complex models including a four-exponential model of a FRET system, for which the FRET efficiencies of the two species of a bi-exponential donor are linked, and polarisation-resolved lifetime data, where a fluorescence intensity and bi-exponential anisotropy decay model is applied to the analysis of live cell homo-FRET data. A software package implementing this algorithm, FLIMfit, is available under an open source licence through the Open Microscopy Environment. PMID:23940626

Method for computing self-consistent solution in a gun code

DOEpatents

Nelson, Eric M

2014-09-23

Complex gun code computations can be made to converge more quickly based on a selection of one or more relaxation parameters. An eigenvalue analysis is applied to error residuals to identify two error eigenvalues that are associated with respective error residuals. Relaxation values can be selected based on these eigenvalues so that error residuals associated with each can be alternately reduced in successive iterations. In some examples, relaxation values that would be unstable if used alone can be used.

An XML-Based Protocol for Distributed Event Services

NASA Technical Reports Server (NTRS)

Smith, Warren; Gunter, Dan; Quesnel, Darcy; Biegel, Bryan (Technical Monitor)

2001-01-01

A recent trend in distributed computing is the construction of high-performance distributed systems called computational grids. One difficulty we have encountered is that there is no standard format for the representation of performance information and no standard protocol for transmitting this information. This limits the types of performance analysis that can be undertaken in complex distributed systems. To address this problem, we present an XML-based protocol for transmitting performance events in distributed systems and evaluate the performance of this protocol.

Structural Technology Evaluation and Analysis Program (STEAP). Delivery Order 0037: Prognosis-Based Control Reconfiguration for an Aircraft with Faulty Actuator to Enable Performance in a Degraded State

DTIC Science & Technology

2010-12-01

computers in 1953. HIL motion simulators were also built for the dynamic testing of vehicle com- ponents (e.g. suspensions, bodies ) with hydraulic or...complex, comprehensive mechanical systems can be simulated in real-time by parallel computers; examples include multi- body sys- tems, brake systems...hard constraints in a multivariable control framework. And the third aspect is the ability to perform online optimization. These aspects results in

Consequences of nonclassical measurement for the algorithmic description of continuous dynamical systems

NASA Technical Reports Server (NTRS)

Fields, Chris

1989-01-01

Continuous dynamical systems intuitively seem capable of more complex behavior than discrete systems. If analyzed in the framework of the traditional theory of computation, a continuous dynamical system with countably many quasistable states has at least the computational power of a universal Turing machine. Such an analysis assumes, however, the classical notion of measurement. If measurement is viewed nonclassically, a continuous dynamical system cannot, even in principle, exhibit behavior that cannot be simulated by a universal Turing machine.

Institute for Defense Analysis. Annual Report 1995.

DTIC Science & Technology

1995-01-01

staff have been involved in the community-wide development of MPI as well as in its application to specific NSA problems. 35 Parallel Groebner ...Basis Code — Symbolic Computing on Parallel Machines The Groebner basis method is a set of algorithms for reformulating very complex algebraic expres

Turbulence model development and application at Lockheed Fort Worth Company

NASA Technical Reports Server (NTRS)

Smith, Brian R.

1995-01-01

This viewgraph presentation demonstrates that computationally efficient k-l and k-kl turbulence models have been developed and implemented at Lockheed Fort Worth Company. Many years of experience have been gained applying two equation turbulence models to complex three-dimensional flows for design and analysis.

2D Automatic body-fitted structured mesh generation using advancing extraction method

USDA-ARS?s Scientific Manuscript database

This paper presents an automatic mesh generation algorithm for body-fitted structured meshes in Computational Fluids Dynamics (CFD) analysis using the Advancing Extraction Method (AEM). The method is applicable to two-dimensional domains with complex geometries, which have the hierarchical tree-like...

2D automatic body-fitted structured mesh generation using advancing extraction method

USDA-ARS?s Scientific Manuscript database

This paper presents an automatic mesh generation algorithm for body-fitted structured meshes in Computational Fluids Dynamics (CFD) analysis using the Advancing Extraction Method (AEM). The method is applicable to two-dimensional domains with complex geometries, which have the hierarchical tree-like...

The Case for Open Source Software: The Interactional Discourse Lab

ERIC Educational Resources Information Center

Choi, Seongsook

2016-01-01

Computational techniques and software applications for the quantitative content analysis of texts are now well established, and many qualitative data software applications enable the manipulation of input variables and the visualization of complex relations between them via interactive and informative graphical interfaces. Although advances in…

Computational Fluid Dynamics of Whole-Body Aircraft

NASA Astrophysics Data System (ADS)

Agarwal, Ramesh

1999-01-01

The current state of the art in computational aerodynamics for whole-body aircraft flowfield simulations is described. Recent advances in geometry modeling, surface and volume grid generation, and flow simulation algorithms have led to accurate flowfield predictions for increasingly complex and realistic configurations. As a result, computational aerodynamics has emerged as a crucial enabling technology for the design and development of flight vehicles. Examples illustrating the current capability for the prediction of transport and fighter aircraft flowfields are presented. Unfortunately, accurate modeling of turbulence remains a major difficulty in the analysis of viscosity-dominated flows. In the future, inverse design methods, multidisciplinary design optimization methods, artificial intelligence technology, and massively parallel computer technology will be incorporated into computational aerodynamics, opening up greater opportunities for improved product design at substantially reduced costs.

Module-based multiscale simulation of angiogenesis in skeletal muscle

PubMed Central

2011-01-01

Background Mathematical modeling of angiogenesis has been gaining momentum as a means to shed new light on the biological complexity underlying blood vessel growth. A variety of computational models have been developed, each focusing on different aspects of the angiogenesis process and occurring at different biological scales, ranging from the molecular to the tissue levels. Integration of models at different scales is a challenging and currently unsolved problem. Results We present an object-oriented module-based computational integration strategy to build a multiscale model of angiogenesis that links currently available models. As an example case, we use this approach to integrate modules representing microvascular blood flow, oxygen transport, vascular endothelial growth factor transport and endothelial cell behavior (sensing, migration and proliferation). Modeling methodologies in these modules include algebraic equations, partial differential equations and agent-based models with complex logical rules. We apply this integrated model to simulate exercise-induced angiogenesis in skeletal muscle. The simulation results compare capillary growth patterns between different exercise conditions for a single bout of exercise. Results demonstrate how the computational infrastructure can effectively integrate multiple modules by coordinating their connectivity and data exchange. Model parameterization offers simulation flexibility and a platform for performing sensitivity analysis. Conclusions This systems biology strategy can be applied to larger scale integration of computational models of angiogenesis in skeletal muscle, or other complex processes in other tissues under physiological and pathological conditions. PMID:21463529

Undecidability and Irreducibility Conditions for Open-Ended Evolution and Emergence.

PubMed

Hernández-Orozco, Santiago; Hernández-Quiroz, Francisco; Zenil, Hector

2018-01-01

Is undecidability a requirement for open-ended evolution (OEE)? Using methods derived from algorithmic complexity theory, we propose robust computational definitions of open-ended evolution and the adaptability of computable dynamical systems. Within this framework, we show that decidability imposes absolute limits on the stable growth of complexity in computable dynamical systems. Conversely, systems that exhibit (strong) open-ended evolution must be undecidable, establishing undecidability as a requirement for such systems. Complexity is assessed in terms of three measures: sophistication, coarse sophistication, and busy beaver logical depth. These three complexity measures assign low complexity values to random (incompressible) objects. As time grows, the stated complexity measures allow for the existence of complex states during the evolution of a computable dynamical system. We show, however, that finding these states involves undecidable computations. We conjecture that for similar complexity measures that assign low complexity values, decidability imposes comparable limits on the stable growth of complexity, and that such behavior is necessary for nontrivial evolutionary systems. We show that the undecidability of adapted states imposes novel and unpredictable behavior on the individuals or populations being modeled. Such behavior is irreducible. Finally, we offer an example of a system, first proposed by Chaitin, that exhibits strong OEE.

77 FR 50726 - Software Requirement Specifications for Digital Computer Software and Complex Electronics Used in...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-22

... Computer Software and Complex Electronics Used in Safety Systems of Nuclear Power Plants AGENCY: Nuclear...-1209, ``Software Requirement Specifications for Digital Computer Software and Complex Electronics used... Electronics Engineers (ANSI/IEEE) Standard 830-1998, ``IEEE Recommended Practice for Software Requirements...

Focal Cortical Dysplasia (FCD) lesion analysis with complex diffusion approach.

PubMed

Rajan, Jeny; Kannan, K; Kesavadas, C; Thomas, Bejoy

2009-10-01

Identification of Focal Cortical Dysplasia (FCD) can be difficult due to the subtle MRI changes. Though sequences like FLAIR (fluid attenuated inversion recovery) can detect a large majority of these lesions, there are smaller lesions without signal changes that can easily go unnoticed by the naked eye. The aim of this study is to improve the visibility of focal cortical dysplasia lesions in the T1 weighted brain MRI images. In the proposed method, we used a complex diffusion based approach for calculating the FCD affected areas. Based on the diffused image and thickness map, a complex map is created. From this complex map; FCD areas can be easily identified. MRI brains of 48 subjects selected by neuroradiologists were given to computer scientists who developed the complex map for identifying the cortical dysplasia. The scientists were blinded to the MRI interpretation result of the neuroradiologist. The FCD could be identified in all the patients in whom surgery was done, however three patients had false positive lesions. More lesions were identified in patients in whom surgery was not performed and lesions were seen in few of the controls. These were considered as false positive. This computer aided detection technique using complex diffusion approach can help detect focal cortical dysplasia in patients with epilepsy.

Statistical assessment on a combined analysis of GRYN-ROMN-UCBN upland vegetation vital signs

USGS Publications Warehouse

Irvine, Kathryn M.; Rodhouse, Thomas J.

2014-01-01

As of 2013, Rocky Mountain and Upper Columbia Basin Inventory and Monitoring Networks have multiple years of vegetation data and Greater Yellowstone Network has three years of vegetation data and monitoring is ongoing in all three networks. Our primary objective is to assess whether a combined analysis of these data aimed at exploring correlations with climate and weather data is feasible. We summarize the core survey design elements across protocols and point out the major statistical challenges for a combined analysis at present. The dissimilarity in response designs between ROMN and UCBN-GRYN network protocols presents a statistical challenge that has not been resolved yet. However, the UCBN and GRYN data are compatible as they implement a similar response design; therefore, a combined analysis is feasible and will be pursued in future. When data collected by different networks are combined, the survey design describing the merged dataset is (likely) a complex survey design. A complex survey design is the result of combining datasets from different sampling designs. A complex survey design is characterized by unequal probability sampling, varying stratification, and clustering (see Lohr 2010 Chapter 7 for general overview). Statistical analysis of complex survey data requires modifications to standard methods, one of which is to include survey design weights within a statistical model. We focus on this issue for a combined analysis of upland vegetation from these networks, leaving other topics for future research. We conduct a simulation study on the possible effects of equal versus unequal probability selection of points on parameter estimates of temporal trend using available packages within the R statistical computing package. We find that, as written, using lmer or lm for trend detection in a continuous response and clm and clmm for visually estimated cover classes with “raw” GRTS design weights specified for the weight argument leads to substantially different results and/or computational instability. However, when only fixed effects are of interest, the survey package (svyglm and svyolr) may be suitable for a model-assisted analysis for trend. We provide possible directions for future research into combined analysis for ordinal and continuous vital sign indictors.

Quantum computational complexity, Einstein's equations and accelerated expansion of the Universe

NASA Astrophysics Data System (ADS)

Ge, Xian-Hui; Wang, Bin

2018-02-01

We study the relation between quantum computational complexity and general relativity. The quantum computational complexity is proposed to be quantified by the shortest length of geodesic quantum curves. We examine the complexity/volume duality in a geodesic causal ball in the framework of Fermi normal coordinates and derive the full non-linear Einstein equation. Using insights from the complexity/action duality, we argue that the accelerated expansion of the universe could be driven by the quantum complexity and free from coincidence and fine-tunning problems.

Cloud Computing for Complex Performance Codes.

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

Appel, Gordon John; Hadgu, Teklu; Klein, Brandon Thorin

This report describes the use of cloud computing services for running complex public domain performance assessment problems. The work consisted of two phases: Phase 1 was to demonstrate complex codes, on several differently configured servers, could run and compute trivial small scale problems in a commercial cloud infrastructure. Phase 2 focused on proving non-trivial large scale problems could be computed in the commercial cloud environment. The cloud computing effort was successfully applied using codes of interest to the geohydrology and nuclear waste disposal modeling community.

A Multifaceted Mathematical Approach for Complex Systems

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

Alexander, F.; Anitescu, M.; Bell, J.

2012-03-07

Applied mathematics has an important role to play in developing the tools needed for the analysis, simulation, and optimization of complex problems. These efforts require the development of the mathematical foundations for scientific discovery, engineering design, and risk analysis based on a sound integrated approach for the understanding of complex systems. However, maximizing the impact of applied mathematics on these challenges requires a novel perspective on approaching the mathematical enterprise. Previous reports that have surveyed the DOE's research needs in applied mathematics have played a key role in defining research directions with the community. Although these reports have had significantmore » impact, accurately assessing current research needs requires an evaluation of today's challenges against the backdrop of recent advances in applied mathematics and computing. To address these needs, the DOE Applied Mathematics Program sponsored a Workshop for Mathematics for the Analysis, Simulation and Optimization of Complex Systems on September 13-14, 2011. The workshop had approximately 50 participants from both the national labs and academia. The goal of the workshop was to identify new research areas in applied mathematics that will complement and enhance the existing DOE ASCR Applied Mathematics Program efforts that are needed to address problems associated with complex systems. This report describes recommendations from the workshop and subsequent analysis of the workshop findings by the organizing committee.« less