Efficient computation of PDF-based characteristics from diffusion MR signal.

PubMed

Assemlal, Haz-Edine; Tschumperlé, David; Brun, Luc

2008-01-01

We present a general method for the computation of PDF-based characteristics of the tissue micro-architecture in MR imaging. The approach relies on the approximation of the MR signal by a series expansion based on Spherical Harmonics and Laguerre-Gaussian functions, followed by a simple projection step that is efficiently done in a finite dimensional space. The resulting algorithm is generic, flexible and is able to compute a large set of useful characteristics of the local tissues structure. We illustrate the effectiveness of this approach by showing results on synthetic and real MR datasets acquired in a clinical time-frame.

Simple and powerful visual stimulus generator.

PubMed

Kremlácek, J; Kuba, M; Kubová, Z; Vít, F

1999-02-01

We describe a cheap, simple, portable and efficient approach to visual stimulation for neurophysiology which does not need any special hardware equipment. The method based on an animation technique uses the FLI autodesk animator format. This form of the animation is replayed by a special program ('player') providing synchronisation pulses toward recording system via parallel port. The 'player is running on an IBM compatible personal computer under MS-DOS operation system and stimulus is displayed on a VGA computer monitor. Various stimuli created with this technique for visual evoked potentials (VEPs) are presented.

Estimating aquifer transmissivity from specific capacity using MATLAB.

PubMed

McLin, Stephen G

2005-01-01

Historically, specific capacity information has been used to calculate aquifer transmissivity when pumping test data are unavailable. This paper presents a simple computer program written in the MATLAB programming language that estimates transmissivity from specific capacity data while correcting for aquifer partial penetration and well efficiency. The program graphically plots transmissivity as a function of these factors so that the user can visually estimate their relative importance in a particular application. The program is compatible with any computer operating system running MATLAB, including Windows, Macintosh OS, Linux, and Unix. Two simple examples illustrate program usage.

Dynamic modeling of parallel robots for computed-torque control implementation

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

Codourey, A.

1998-12-01

In recent years, increased interest in parallel robots has been observed. Their control with modern theory, such as the computed-torque method, has, however, been restrained, essentially due to the difficulty in establishing a simple dynamic model that can be calculated in real time. In this paper, a simple method based on the virtual work principle is proposed for modeling parallel robots. The mass matrix of the robot, needed for decoupling control strategies, does not explicitly appear in the formulation; however, it can be computed separately, based on kinetic energy considerations. The method is applied to the DELTA parallel robot, leadingmore » to a very efficient model that has been implemented in a real-time computed-torque control algorithm.« less

Fitting mechanistic epidemic models to data: A comparison of simple Markov chain Monte Carlo approaches.

PubMed

Li, Michael; Dushoff, Jonathan; Bolker, Benjamin M

2018-07-01

Simple mechanistic epidemic models are widely used for forecasting and parameter estimation of infectious diseases based on noisy case reporting data. Despite the widespread application of models to emerging infectious diseases, we know little about the comparative performance of standard computational-statistical frameworks in these contexts. Here we build a simple stochastic, discrete-time, discrete-state epidemic model with both process and observation error and use it to characterize the effectiveness of different flavours of Bayesian Markov chain Monte Carlo (MCMC) techniques. We use fits to simulated data, where parameters (and future behaviour) are known, to explore the limitations of different platforms and quantify parameter estimation accuracy, forecasting accuracy, and computational efficiency across combinations of modeling decisions (e.g. discrete vs. continuous latent states, levels of stochasticity) and computational platforms (JAGS, NIMBLE, Stan).

A Computationally Efficient Method for Polyphonic Pitch Estimation

NASA Astrophysics Data System (ADS)

Zhou, Ruohua; Reiss, Joshua D.; Mattavelli, Marco; Zoia, Giorgio

2009-12-01

This paper presents a computationally efficient method for polyphonic pitch estimation. The method employs the Fast Resonator Time-Frequency Image (RTFI) as the basic time-frequency analysis tool. The approach is composed of two main stages. First, a preliminary pitch estimation is obtained by means of a simple peak-picking procedure in the pitch energy spectrum. Such spectrum is calculated from the original RTFI energy spectrum according to harmonic grouping principles. Then the incorrect estimations are removed according to spectral irregularity and knowledge of the harmonic structures of the music notes played on commonly used music instruments. The new approach is compared with a variety of other frame-based polyphonic pitch estimation methods, and results demonstrate the high performance and computational efficiency of the approach.

Simple model of hydrophobic hydration.

PubMed

Lukšič, Miha; Urbic, Tomaz; Hribar-Lee, Barbara; Dill, Ken A

2012-05-31

Water is an unusual liquid in its solvation properties. Here, we model the process of transferring a nonpolar solute into water. Our goal was to capture the physical balance between water's hydrogen bonding and van der Waals interactions in a model that is simple enough to be nearly analytical and not heavily computational. We develop a 2-dimensional Mercedes-Benz-like model of water with which we compute the free energy, enthalpy, entropy, and the heat capacity of transfer as a function of temperature, pressure, and solute size. As validation, we find that this model gives the same trends as Monte Carlo simulations of the underlying 2D model and gives qualitative agreement with experiments. The advantages of this model are that it gives simple insights and that computational time is negligible. It may provide a useful starting point for developing more efficient and more realistic 3D models of aqueous solvation.

The efficient simulation of separated three-dimensional viscous flows using the boundary-layer equations

NASA Technical Reports Server (NTRS)

Van Dalsem, W. R.; Steger, J. L.

1985-01-01

A simple and computationally efficient algorithm for solving the unsteady three-dimensional boundary-layer equations in the time-accurate or relaxation mode is presented. Results of the new algorithm are shown to be in quantitative agreement with detailed experimental data for flow over a swept infinite wing. The separated flow over a 6:1 ellipsoid at angle of attack, and the transonic flow over a finite-wing with shock-induced 'mushroom' separation are also computed and compared with available experimental data. It is concluded that complex, separated, three-dimensional viscous layers can be economically and routinely computed using a time-relaxation boundary-layer algorithm.

Efficient dynamic simulation for multiple chain robotic mechanisms

NASA Technical Reports Server (NTRS)

Lilly, Kathryn W.; Orin, David E.

1989-01-01

An efficient O(mN) algorithm for dynamic simulation of simple closed-chain robotic mechanisms is presented, where m is the number of chains, and N is the number of degrees of freedom for each chain. It is based on computation of the operational space inertia matrix (6 x 6) for each chain as seen by the body, load, or object. Also, computation of the chain dynamics, when opened at one end, is required, and the most efficient algorithm is used for this purpose. Parallel implementation of the dynamics for each chain results in an O(N) + O(log sub 2 m+1) algorithm.

Fisher classifier and its probability of error estimation

NASA Technical Reports Server (NTRS)

Chittineni, C. B.

1979-01-01

Computationally efficient expressions are derived for estimating the probability of error using the leave-one-out method. The optimal threshold for the classification of patterns projected onto Fisher's direction is derived. A simple generalization of the Fisher classifier to multiple classes is presented. Computational expressions are developed for estimating the probability of error of the multiclass Fisher classifier.

A Comparison of Wavetable and FM Data Reduction Methods for Resynthesis of Musical Sounds

NASA Astrophysics Data System (ADS)

Horner, Andrew

An ideal music-synthesis technique provides both high-level spectral control and efficient computation. Simple playback of recorded samples lacks spectral control, while additive sine-wave synthesis is inefficient. Wavetable and frequencymodulation synthesis, however, are two popular synthesis techniques that are very efficient and use only a few control parameters.

WEBSLIDE: A "Virtual" Slide Projector Based on World Wide Web.

ERIC Educational Resources Information Center

Barra, Maria; Ferrandino, Salvatore; Scarano, Vittorio

1999-01-01

Presents the key design concepts of a software project whose objective is to provide a simple, cheap, and efficient solution for showing slides during lessons in computer labs. Contains 26 references. (DDR)

Accurate Monotonicity - Preserving Schemes With Runge-Kutta Time Stepping

NASA Technical Reports Server (NTRS)

Suresh, A.; Huynh, H. T.

1997-01-01

A new class of high-order monotonicity-preserving schemes for the numerical solution of conservation laws is presented. The interface value in these schemes is obtained by limiting a higher-order polynominal reconstruction. The limiting is designed to preserve accuracy near extrema and to work well with Runge-Kutta time stepping. Computational efficiency is enhanced by a simple test that determines whether the limiting procedure is needed. For linear advection in one dimension, these schemes are shown as well as the Euler equations also confirm their high accuracy, good shock resolution, and computational efficiency.

Computationally Efficient Resampling of Nonuniform Oversampled SAR Data

DTIC Science & Technology

2010-05-01

noncoherently . The resample data is calculated using both a simple average and a weighted average of the demodulated data. The average nonuniform...trials with randomly varying accelerations. The results are shown in Fig. 5 for the noncoherent power difference and Fig. 6 for and coherent power...simple average. Figure 5. Noncoherent difference between SAR imagery generated with uniform sampling and nonuniform sampling that was resampled

Bubble nucleation in simple and molecular liquids via the largest spherical cavity method

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

Gonzalez, Miguel A., E-mail: m.gonzalez12@imperial.ac.uk; Department of Chemistry, Imperial College London, London SW7 2AZ; Abascal, José L. F.

2015-04-21

In this work, we propose a methodology to compute bubble nucleation free energy barriers using trajectories generated via molecular dynamics simulations. We follow the bubble nucleation process by means of a local order parameter, defined by the volume of the largest spherical cavity (LSC) formed in the nucleating trajectories. This order parameter simplifies considerably the monitoring of the nucleation events, as compared with the previous approaches which require ad hoc criteria to classify the atoms and molecules as liquid or vapor. The combination of the LSC and the mean first passage time technique can then be used to obtain themore » free energy curves. Upon computation of the cavity distribution function the nucleation rate and free-energy barrier can then be computed. We test our method against recent computations of bubble nucleation in simple liquids and water at negative pressures. We obtain free-energy barriers in good agreement with the previous works. The LSC method provides a versatile and computationally efficient route to estimate the volume of critical bubbles the nucleation rate and to compute bubble nucleation free-energies in both simple and molecular liquids.« less

Aggregative Learning Method and Its Application for Communication Quality Evaluation

NASA Astrophysics Data System (ADS)

Akhmetov, Dauren F.; Kotaki, Minoru

2007-12-01

In this paper, so-called Aggregative Learning Method (ALM) is proposed to improve and simplify the learning and classification abilities of different data processing systems. It provides a universal basis for design and analysis of mathematical models of wide class. A procedure was elaborated for time series model reconstruction and analysis for linear and nonlinear cases. Data approximation accuracy (during learning phase) and data classification quality (during recall phase) are estimated from introduced statistic parameters. The validity and efficiency of the proposed approach have been demonstrated through its application for monitoring of wireless communication quality, namely, for Fixed Wireless Access (FWA) system. Low memory and computation resources were shown to be needed for the procedure realization, especially for data classification (recall) stage. Characterized with high computational efficiency and simple decision making procedure, the derived approaches can be useful for simple and reliable real-time surveillance and control system design.

Fitting neuron models to spike trains.

PubMed

Rossant, Cyrille; Goodman, Dan F M; Fontaine, Bertrand; Platkiewicz, Jonathan; Magnusson, Anna K; Brette, Romain

2011-01-01

Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input-output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model.

On-Line Method and Apparatus for Coordinated Mobility and Manipulation of Mobile Robots

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1996-01-01

A simple and computationally efficient approach is disclosed for on-line coordinated control of mobile robots consisting of a manipulator arm mounted on a mobile base. The effect of base mobility on the end-effector manipulability index is discussed. The base mobility and arm manipulation degrees-of-freedom are treated equally as the joints of a kinematically redundant composite robot. The redundancy introduced by the mobile base is exploited to satisfy a set of user-defined additional tasks during the end-effector motion. A simple on-line control scheme is proposed which allows the user to assign weighting factors to individual degrees-of-mobility and degrees-of-manipulation, as well as to each task specification. The computational efficiency of the control algorithm makes it particularly suitable for real-time implementations. Four case studies are discussed in detail to demonstrate the application of the coordinated control scheme to various mobile robots.

Smart Swarms of Bacteria-Inspired Agents with Performance Adaptable Interactions

PubMed Central

Shklarsh, Adi; Ariel, Gil; Schneidman, Elad; Ben-Jacob, Eshel

2011-01-01

Collective navigation and swarming have been studied in animal groups, such as fish schools, bird flocks, bacteria, and slime molds. Computer modeling has shown that collective behavior of simple agents can result from simple interactions between the agents, which include short range repulsion, intermediate range alignment, and long range attraction. Here we study collective navigation of bacteria-inspired smart agents in complex terrains, with adaptive interactions that depend on performance. More specifically, each agent adjusts its interactions with the other agents according to its local environment – by decreasing the peers' influence while navigating in a beneficial direction, and increasing it otherwise. We show that inclusion of such performance dependent adaptable interactions significantly improves the collective swarming performance, leading to highly efficient navigation, especially in complex terrains. Notably, to afford such adaptable interactions, each modeled agent requires only simple computational capabilities with short-term memory, which can easily be implemented in simple swarming robots. PMID:21980274

Smart swarms of bacteria-inspired agents with performance adaptable interactions.

PubMed

Shklarsh, Adi; Ariel, Gil; Schneidman, Elad; Ben-Jacob, Eshel

2011-09-01

Collective navigation and swarming have been studied in animal groups, such as fish schools, bird flocks, bacteria, and slime molds. Computer modeling has shown that collective behavior of simple agents can result from simple interactions between the agents, which include short range repulsion, intermediate range alignment, and long range attraction. Here we study collective navigation of bacteria-inspired smart agents in complex terrains, with adaptive interactions that depend on performance. More specifically, each agent adjusts its interactions with the other agents according to its local environment--by decreasing the peers' influence while navigating in a beneficial direction, and increasing it otherwise. We show that inclusion of such performance dependent adaptable interactions significantly improves the collective swarming performance, leading to highly efficient navigation, especially in complex terrains. Notably, to afford such adaptable interactions, each modeled agent requires only simple computational capabilities with short-term memory, which can easily be implemented in simple swarming robots.

Simplicity and efficiency of integrate-and-fire neuron models.

PubMed

Plesser, Hans E; Diesmann, Markus

2009-02-01

Lovelace and Cios (2008) recently proposed a very simple spiking neuron (VSSN) model for simulations of large neuronal networks as an efficient replacement for the integrate-and-fire neuron model. We argue that the VSSN model falls behind key advances in neuronal network modeling over the past 20 years, in particular, techniques that permit simulators to compute the state of the neuron without repeated summation over the history of input spikes and to integrate the subthreshold dynamics exactly. State-of-the-art solvers for networks of integrate-and-fire model neurons are substantially more efficient than the VSSN simulator and allow routine simulations of networks of some 10(5) neurons and 10(9) connections on moderate computer clusters.

Engine Evaluation of Advanced Technology Control Components

DTIC Science & Technology

1976-08-01

producer turbine rotor blades. This is a very desirable control feature, because protecting turbine blades from overtemperature is particularly...centrifugal boost stage operating back to back on a common drive shaft that is direct driven through the alter- nator rotor shaft. The main stage is an...computation makes this simple dynamic pumping machine possible. The pen- alty of this simple design is lower overall efficiency as com- pared to a

Metrics for comparing neuronal tree shapes based on persistent homology.

PubMed

Li, Yanjie; Wang, Dingkang; Ascoli, Giorgio A; Mitra, Partha; Wang, Yusu

2017-01-01

As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and FlyCircuit.org, the need to develop computational tools to facilitate automatic knowledge discovery from such large datasets becomes more urgent. One fundamental question is how best to compare neuron structures, for instance to organize and classify large collection of neurons. We aim to develop a flexible yet powerful framework to support comparison and classification of large collection of neuron structures efficiently. Specifically we propose to use a topological persistence-based feature vectorization framework. Existing methods to vectorize a neuron (i.e, convert a neuron to a feature vector so as to support efficient comparison and/or searching) typically rely on statistics or summaries of morphometric information, such as the average or maximum local torque angle or partition asymmetry. These simple summaries have limited power in encoding global tree structures. Based on the concept of topological persistence recently developed in the field of computational topology, we vectorize each neuron structure into a simple yet informative summary. In particular, each type of information of interest can be represented as a descriptor function defined on the neuron tree, which is then mapped to a simple persistence-signature. Our framework can encode both local and global tree structure, as well as other information of interest (electrophysiological or dynamical measures), by considering multiple descriptor functions on the neuron. The resulting persistence-based signature is potentially more informative than simple statistical summaries (such as average/mean/max) of morphometric quantities-Indeed, we show that using a certain descriptor function will give a persistence-based signature containing strictly more information than the classical Sholl analysis. At the same time, our framework retains the efficiency associated with treating neurons as points in a simple Euclidean feature space, which would be important for constructing efficient searching or indexing structures over them. We present preliminary experimental results to demonstrate the effectiveness of our persistence-based neuronal feature vectorization framework.

Metrics for comparing neuronal tree shapes based on persistent homology

PubMed Central

Li, Yanjie; Wang, Dingkang; Ascoli, Giorgio A.; Mitra, Partha

2017-01-01

As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and FlyCircuit.org, the need to develop computational tools to facilitate automatic knowledge discovery from such large datasets becomes more urgent. One fundamental question is how best to compare neuron structures, for instance to organize and classify large collection of neurons. We aim to develop a flexible yet powerful framework to support comparison and classification of large collection of neuron structures efficiently. Specifically we propose to use a topological persistence-based feature vectorization framework. Existing methods to vectorize a neuron (i.e, convert a neuron to a feature vector so as to support efficient comparison and/or searching) typically rely on statistics or summaries of morphometric information, such as the average or maximum local torque angle or partition asymmetry. These simple summaries have limited power in encoding global tree structures. Based on the concept of topological persistence recently developed in the field of computational topology, we vectorize each neuron structure into a simple yet informative summary. In particular, each type of information of interest can be represented as a descriptor function defined on the neuron tree, which is then mapped to a simple persistence-signature. Our framework can encode both local and global tree structure, as well as other information of interest (electrophysiological or dynamical measures), by considering multiple descriptor functions on the neuron. The resulting persistence-based signature is potentially more informative than simple statistical summaries (such as average/mean/max) of morphometric quantities—Indeed, we show that using a certain descriptor function will give a persistence-based signature containing strictly more information than the classical Sholl analysis. At the same time, our framework retains the efficiency associated with treating neurons as points in a simple Euclidean feature space, which would be important for constructing efficient searching or indexing structures over them. We present preliminary experimental results to demonstrate the effectiveness of our persistence-based neuronal feature vectorization framework. PMID:28809960

A Recursive Method for Calculating Certain Partition Functions.

ERIC Educational Resources Information Center

Woodrum, Luther; And Others

1978-01-01

Describes a simple recursive method for calculating the partition function and average energy of a system consisting of N electrons and L energy levels. Also, presents an efficient APL computer program to utilize the recursion relation. (Author/GA)

An efficient higher order family of root finders

NASA Astrophysics Data System (ADS)

Petkovic, Ljiljana D.; Rancic, Lidija; Petkovic, Miodrag S.

2008-06-01

A one parameter family of iterative methods for the simultaneous approximation of simple complex zeros of a polynomial, based on a cubically convergent Hansen-Patrick's family, is studied. We show that the convergence of the basic family of the fourth order can be increased to five and six using Newton's and Halley's corrections, respectively. Since these corrections use the already calculated values, the computational efficiency of the accelerated methods is significantly increased. Further acceleration is achieved by applying the Gauss-Seidel approach (single-step mode). One of the most important problems in solving nonlinear equations, the construction of initial conditions which provide both the guaranteed and fast convergence, is considered for the proposed accelerated family. These conditions are computationally verifiable; they depend only on the polynomial coefficients, its degree and initial approximations, which is of practical importance. Some modifications of the considered family, providing the computation of multiple zeros of polynomials and simple zeros of a wide class of analytic functions, are also studied. Numerical examples demonstrate the convergence properties of the presented family of root-finding methods.

Validation of a pair of computer codes for estimation and optimization of subsonic aerodynamic performance of simple hinged-flap systems for thin swept wings

NASA Technical Reports Server (NTRS)

Carlson, Harry W.; Darden, Christine M.

1988-01-01

Extensive correlations of computer code results with experimental data are employed to illustrate the use of linearized theory attached flow methods for the estimation and optimization of the aerodynamic performance of simple hinged flap systems. Use of attached flow methods is based on the premise that high levels of aerodynamic efficiency require a flow that is as nearly attached as circumstances permit. A variety of swept wing configurations are considered ranging from fighters to supersonic transports, all with leading- and trailing-edge flaps for enhancement of subsonic aerodynamic efficiency. The results indicate that linearized theory attached flow computer code methods provide a rational basis for the estimation and optimization of flap system aerodynamic performance at subsonic speeds. The analysis also indicates that vortex flap design is not an opposing approach but is closely related to attached flow design concepts. The successful vortex flap design actually suppresses the formation of detached vortices to produce a small vortex which is restricted almost entirely to the leading edge flap itself.

A Novel Shape Parameterization Approach

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.

1999-01-01

This paper presents a novel parameterization approach for complex shapes suitable for a multidisciplinary design optimization application. The approach consists of two basic concepts: (1) parameterizing the shape perturbations rather than the geometry itself and (2) performing the shape deformation by means of the soft objects animation algorithms used in computer graphics. Because the formulation presented in this paper is independent of grid topology, we can treat computational fluid dynamics and finite element grids in a similar manner. The proposed approach is simple, compact, and efficient. Also, the analytical sensitivity derivatives are easily computed for use in a gradient-based optimization. This algorithm is suitable for low-fidelity (e.g., linear aerodynamics and equivalent laminated plate structures) and high-fidelity analysis tools (e.g., nonlinear computational fluid dynamics and detailed finite element modeling). This paper contains the implementation details of parameterizing for planform, twist, dihedral, thickness, and camber. The results are presented for a multidisciplinary design optimization application consisting of nonlinear computational fluid dynamics, detailed computational structural mechanics, performance, and a simple propulsion module.

Multidisciplinary Aerodynamic-Structural Shape Optimization Using Deformation (MASSOUD)

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.

2000-01-01

This paper presents a multidisciplinary shape parameterization approach. The approach consists of two basic concepts: (1) parameterizing the shape perturbations rather than the geometry itself and (2) performing the shape deformation by means of the soft object animation algorithms used in computer graphics. Because the formulation presented in this paper is independent of grid topology, we can treat computational fluid dynamics and finite element grids in the same manner. The proposed approach is simple, compact, and efficient. Also, the analytical sensitivity derivatives are easily computed for use in a gradient-based optimization. This algorithm is suitable for low-fidelity (e.g., linear aerodynamics and equivalent laminate plate structures) and high-fidelity (e.g., nonlinear computational fluid dynamics and detailed finite element modeling) analysis tools. This paper contains the implementation details of parameterizing for planform, twist, dihedral, thickness, camber, and free-form surface. Results are presented for a multidisciplinary application consisting of nonlinear computational fluid dynamics, detailed computational structural mechanics, and a simple performance module.

Multidisciplinary Aerodynamic-Structural Shape Optimization Using Deformation (MASSOUD)

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.

2000-01-01

This paper presents a multidisciplinary shape parameterization approach. The approach consists of two basic concepts: (1) parameterizing the shape perturbations rather than the geometry itself and (2) performing the shape deformation by means of the soft object animation algorithms used in computer graphics. Because the formulation presented in this paper is independent of grid topology, we can treat computational fluid dynamics and finite element grids in a similar manner. The proposed approach is simple, compact, and efficient. Also, the analytical sensitivity derivatives are easily computed for use in a gradient-based optimization. This algorithm is suitable for low-fidelity (e.g., linear aerodynamics and equivalent laminated plate structures) and high-fidelity (e.g., nonlinear computational fluid dynamics and detailed finite element modeling analysis tools. This paper contains the implementation details of parameterizing for planform, twist, dihedral, thickness, camber, and free-form surface. Results are presented for a multidisciplinary design optimization application consisting of nonlinear computational fluid dynamics, detailed computational structural mechanics, and a simple performance module.

Analog synthetic biology.

PubMed

Sarpeshkar, R

2014-03-28

We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic and hybrid analog-digital computational approaches; otherwise, even relatively simple synthetic computations in cells such as addition will exceed energy and molecular-count budgets. We present schematics for efficiently representing analog DNA-protein computation in cells. Analog electronic flow in subthreshold transistors and analog molecular flux in chemical reactions obey Boltzmann exponential laws of thermodynamics and are described by astoundingly similar logarithmic electrochemical potentials. Therefore, cytomorphic circuits can help to map circuit designs between electronic and biochemical domains. We review recent work that uses positive-feedback linearization circuits to architect wide-dynamic-range logarithmic analog computation in Escherichia coli using three transcription factors, nearly two orders of magnitude more efficient in parts than prior digital implementations.

Analog synthetic biology

PubMed Central

Sarpeshkar, R.

2014-01-01

We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic and hybrid analog–digital computational approaches; otherwise, even relatively simple synthetic computations in cells such as addition will exceed energy and molecular-count budgets. We present schematics for efficiently representing analog DNA–protein computation in cells. Analog electronic flow in subthreshold transistors and analog molecular flux in chemical reactions obey Boltzmann exponential laws of thermodynamics and are described by astoundingly similar logarithmic electrochemical potentials. Therefore, cytomorphic circuits can help to map circuit designs between electronic and biochemical domains. We review recent work that uses positive-feedback linearization circuits to architect wide-dynamic-range logarithmic analog computation in Escherichia coli using three transcription factors, nearly two orders of magnitude more efficient in parts than prior digital implementations. PMID:24567476

Improved numerical methods for turbulent viscous flows aerothermal modeling program, phase 2

NASA Technical Reports Server (NTRS)

Karki, K. C.; Patankar, S. V.; Runchal, A. K.; Mongia, H. C.

1988-01-01

The details of a study to develop accurate and efficient numerical schemes to predict complex flows are described. In this program, several discretization schemes were evaluated using simple test cases. This assessment led to the selection of three schemes for an in-depth evaluation based on two-dimensional flows. The scheme with the superior overall performance was incorporated in a computer program for three-dimensional flows. To improve the computational efficiency, the selected discretization scheme was combined with a direct solution approach in which the fluid flow equations are solved simultaneously rather than sequentially.

Preliminary study of the use of the STAR-100 computer for transonic flow calculations

NASA Technical Reports Server (NTRS)

Keller, J. D.; Jameson, A.

1977-01-01

An explicit method for solving the transonic small-disturbance potential equation is presented. This algorithm, which is suitable for the new vector-processor computers such as the CDC STAR-100, is compared to successive line over-relaxation (SLOR) on a simple test problem. The convergence rate of the explicit scheme is slower than that of SLOR, however, the efficiency of the explicit scheme on the STAR-100 computer is sufficient to overcome the slower convergence rate and allow an overall speedup compared to SLOR on the CYBER 175 computer.

Efficient computation of the genomic relationship matrix and other matrices used in single-step evaluation.

PubMed

Aguilar, I; Misztal, I; Legarra, A; Tsuruta, S

2011-12-01

Genomic evaluations can be calculated using a unified procedure that combines phenotypic, pedigree and genomic information. Implementation of such a procedure requires the inverse of the relationship matrix based on pedigree and genomic relationships. The objective of this study was to investigate efficient computing options to create relationship matrices based on genomic markers and pedigree information as well as their inverses. SNP maker information was simulated for a panel of 40 K SNPs, with the number of genotyped animals up to 30 000. Matrix multiplication in the computation of the genomic relationship was by a simple 'do' loop, by two optimized versions of the loop, and by a specific matrix multiplication subroutine. Inversion was by a generalized inverse algorithm and by a LAPACK subroutine. With the most efficient choices and parallel processing, creation of matrices for 30 000 animals would take a few hours. Matrices required to implement a unified approach can be computed efficiently. Optimizations can be either by modifications of existing code or by the use of efficient automatic optimizations provided by open source or third-party libraries. © 2011 Blackwell Verlag GmbH.

A Comparative Study of Multi-material Data Structures for Computational Physics Applications

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

Garimella, Rao Veerabhadra; Robey, Robert W.

The data structures used to represent the multi-material state of a computational physics application can have a drastic impact on the performance of the application. We look at efficient data structures for sparse applications where there may be many materials, but only one or few in most computational cells. We develop simple performance models for use in selecting possible data structures and programming patterns. We verify the analytic models of performance through a small test program of the representative cases.

Queueing Network Models for Parallel Processing of Task Systems: an Operational Approach

NASA Technical Reports Server (NTRS)

Mak, Victor W. K.

1986-01-01

Computer performance modeling of possibly complex computations running on highly concurrent systems is considered. Earlier works in this area either dealt with a very simple program structure or resulted in methods with exponential complexity. An efficient procedure is developed to compute the performance measures for series-parallel-reducible task systems using queueing network models. The procedure is based on the concept of hierarchical decomposition and a new operational approach. Numerical results for three test cases are presented and compared to those of simulations.

Further reduction of minimal first-met bad markings for the computationally efficient synthesis of a maximally permissive controller

NASA Astrophysics Data System (ADS)

Liu, GaiYun; Chao, Daniel Yuh

2015-08-01

To date, research on the supervisor design for flexible manufacturing systems focuses on speeding up the computation of optimal (maximally permissive) liveness-enforcing controllers. Recent deadlock prevention policies for systems of simple sequential processes with resources (S3PR) reduce the computation burden by considering only the minimal portion of all first-met bad markings (FBMs). Maximal permissiveness is ensured by not forbidding any live state. This paper proposes a method to further reduce the size of minimal set of FBMs to efficiently solve integer linear programming problems while maintaining maximal permissiveness using a vector-covering approach. This paper improves the previous work and achieves the simplest structure with the minimal number of monitors.

Growth and yield models for central hardwoods

Treesearch

Martin E. Dale; Donald E. Hilt

1989-01-01

Over the last 20 years computers have become an efficient tool to estimate growth and yield. Computerized yield estimates vary from simple approximation or interpolation of traditional normal yield tables to highly sophisticated programs that simulate the growth and yield of each individual tree.

A parallel computing engine for a class of time critical processes.

PubMed

Nabhan, T M; Zomaya, A Y

1997-01-01

This paper focuses on the efficient parallel implementation of systems of numerically intensive nature over loosely coupled multiprocessor architectures. These analytical models are of significant importance to many real-time systems that have to meet severe time constants. A parallel computing engine (PCE) has been developed in this work for the efficient simplification and the near optimal scheduling of numerical models over the different cooperating processors of the parallel computer. First, the analytical system is efficiently coded in its general form. The model is then simplified by using any available information (e.g., constant parameters). A task graph representing the interconnections among the different components (or equations) is generated. The graph can then be compressed to control the computation/communication requirements. The task scheduler employs a graph-based iterative scheme, based on the simulated annealing algorithm, to map the vertices of the task graph onto a Multiple-Instruction-stream Multiple-Data-stream (MIMD) type of architecture. The algorithm uses a nonanalytical cost function that properly considers the computation capability of the processors, the network topology, the communication time, and congestion possibilities. Moreover, the proposed technique is simple, flexible, and computationally viable. The efficiency of the algorithm is demonstrated by two case studies with good results.

Computationally Aided Absolute Stereochemical Determination of Enantioenriched Amines.

PubMed

Zhang, Jun; Gholami, Hadi; Ding, Xinliang; Chun, Minji; Vasileiou, Chrysoula; Nehira, Tatsuo; Borhan, Babak

2017-03-17

A simple and efficient protocol for sensing the absolute stereochemistry and enantiomeric excess of chiral monoamines is reported. Preparation of the sample requires a single-step reaction of the 1,1'-(bromomethylene)dinaphthalene (BDN) with the chiral amine. Analysis of the exciton coupled circular dichroism generated from the BDN-derivatized chiral amine sample, along with comparison to conformational analysis performed computationally, yields the absolute stereochemistry of the parent chiral monoamine.

Fitting Neuron Models to Spike Trains

PubMed Central

Rossant, Cyrille; Goodman, Dan F. M.; Fontaine, Bertrand; Platkiewicz, Jonathan; Magnusson, Anna K.; Brette, Romain

2011-01-01

Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input–output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model. PMID:21415925

An algorithm for automatic reduction of complex signal flow graphs

NASA Technical Reports Server (NTRS)

Young, K. R.; Hoberock, L. L.; Thompson, J. G.

1976-01-01

A computer algorithm is developed that provides efficient means to compute transmittances directly from a signal flow graph or a block diagram. Signal flow graphs are cast as directed graphs described by adjacency matrices. Nonsearch computation, designed for compilers without symbolic capability, is used to identify all arcs that are members of simple cycles for use with Mason's gain formula. The routine does not require the visual acumen of an interpreter to reduce the topology of the graph, and it is particularly useful for analyzing control systems described for computer analyses by means of interactive graphics.

A simple Lagrangian forecast system with aviation forecast potential

NASA Technical Reports Server (NTRS)

Petersen, R. A.; Homan, J. H.

1983-01-01

A trajectory forecast procedure is developed which uses geopotential tendency fields obtained from a simple, multiple layer, potential vorticity conservative isentropic model. This model can objectively account for short-term advective changes in the mass field when combined with fine-scale initial analyses. This procedure for producing short-term, upper-tropospheric trajectory forecasts employs a combination of a detailed objective analysis technique, an efficient mass advection model, and a diagnostically proven trajectory algorithm, none of which require extensive computer resources. Results of initial tests are presented, which indicate an exceptionally good agreement for trajectory paths entering the jet stream and passing through an intensifying trough. It is concluded that this technique not only has potential for aiding in route determination, fuel use estimation, and clear air turbulence detection, but also provides an example of the types of short range forecasting procedures which can be applied at local forecast centers using simple algorithms and a minimum of computer resources.

Noise studies of communication systems using the SYSTID computer aided analysis program

NASA Technical Reports Server (NTRS)

Tranter, W. H.; Dawson, C. T.

1973-01-01

SYSTID computer aided design is a simple program for simulating data systems and communication links. A trial of the efficiency of the method was carried out by simulating a linear analog communication system to determine its noise performance and by comparing the SYSTID result with the result arrived at by theoretical calculation. It is shown that the SYSTID program is readily applicable to the analysis of these types of systems.

Sequential decision making in computational sustainability via adaptive submodularity

USGS Publications Warehouse

Krause, Andreas; Golovin, Daniel; Converse, Sarah J.

2015-01-01

Many problems in computational sustainability require making a sequence of decisions in complex, uncertain environments. Such problems are generally notoriously difficult. In this article, we review the recently discovered notion of adaptive submodularity, an intuitive diminishing returns condition that generalizes the classical notion of submodular set functions to sequential decision problems. Problems exhibiting the adaptive submodularity property can be efficiently and provably near-optimally solved using simple myopic policies. We illustrate this concept in several case studies of interest in computational sustainability: First, we demonstrate how it can be used to efficiently plan for resolving uncertainty in adaptive management scenarios. Secondly, we show how it applies to dynamic conservation planning for protecting endangered species, a case study carried out in collaboration with the US Geological Survey and the US Fish and Wildlife Service.

Optical testing of aspheres based on photochromic computer-generated holograms

NASA Astrophysics Data System (ADS)

Pariani, Giorgio; Bianco, Andrea; Bertarelli, Chiara; Spanó, Paolo; Molinari, Emilio

2010-07-01

Aspherical optics are widely used in modern optical telescopes and instrumentation because of their ability to reduce aberrations with a simple optical system. Testing their optical quality through null interferometry is not trivial as reference optics are not available. Computer-Generated Holograms (CGHs) are efficient devices that allow to generate a well-defined optical wavefront. We developed rewritable Computer Generated Holograms for the interferometric test of aspheres based on photochromic layers. These photochromic holograms are cost-effective and the method of production does not need any post exposure process.

Inverse kinematics of a dual linear actuator pitch/roll heliostat

NASA Astrophysics Data System (ADS)

Freeman, Joshua; Shankar, Balakrishnan; Sundaram, Ganesh

2017-06-01

This work presents a simple, computationally efficient inverse kinematics solution for a pitch/roll heliostat using two linear actuators. The heliostat design and kinematics have been developed, modeled and tested using computer simulation software. A physical heliostat prototype was fabricated to validate the theoretical computations and data. Pitch/roll heliostats have numerous advantages including reduced cost potential and reduced space requirements, with a primary disadvantage being the significantly more complicated kinematics, which are solved here. Novel methods are applied to simplify the inverse kinematics problem which could be applied to other similar problems.

A parallel computational model for GATE simulations.

PubMed

Rannou, F R; Vega-Acevedo, N; El Bitar, Z

2013-12-01

GATE/Geant4 Monte Carlo simulations are computationally demanding applications, requiring thousands of processor hours to produce realistic results. The classical strategy of distributing the simulation of individual events does not apply efficiently for Positron Emission Tomography (PET) experiments, because it requires a centralized coincidence processing and large communication overheads. We propose a parallel computational model for GATE that handles event generation and coincidence processing in a simple and efficient way by decentralizing event generation and processing but maintaining a centralized event and time coordinator. The model is implemented with the inclusion of a new set of factory classes that can run the same executable in sequential or parallel mode. A Mann-Whitney test shows that the output produced by this parallel model in terms of number of tallies is equivalent (but not equal) to its sequential counterpart. Computational performance evaluation shows that the software is scalable and well balanced. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

In Search of Speedier Searches.

ERIC Educational Resources Information Center

Peterson, Ivars

1984-01-01

Methods to make computer searching as simple and efficient as possible have led to the development of various data structures. Data structures specify the items involved in searching and what can be done to them. The nature and advantages of using "self-adjusting" data structures (self-adjusting binary search trees) are discussed. (JN)

Computer supplies insulation recipe for Cookie Company Roof

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

Not Available

Roofing contractors no longer have to rely on complicated calculations and educated guesses to determine cost-efficient levels of roof insulation. A simple hand-held calculator and printer offers seven different programs for fast figuring insulation thickness based on job type, roof size, tax rates, and heating and cooling cost factors.

Division of Attention Relative to Response Between Attended and Unattended Stimuli.

ERIC Educational Resources Information Center

Kantowitz, Barry H.

Research was conducted to investigate two general classes of human attention models, early-selection models which claim that attentional selecting precedes memory and meaning extraction mechanisms, and late-selection models which posit the reverse. This research involved two components: (1) the development of simple, efficient, computer-oriented…

A high-speed linear algebra library with automatic parallelism

NASA Technical Reports Server (NTRS)

Boucher, Michael L.

1994-01-01

Parallel or distributed processing is key to getting highest performance workstations. However, designing and implementing efficient parallel algorithms is difficult and error-prone. It is even more difficult to write code that is both portable to and efficient on many different computers. Finally, it is harder still to satisfy the above requirements and include the reliability and ease of use required of commercial software intended for use in a production environment. As a result, the application of parallel processing technology to commercial software has been extremely small even though there are numerous computationally demanding programs that would significantly benefit from application of parallel processing. This paper describes DSSLIB, which is a library of subroutines that perform many of the time-consuming computations in engineering and scientific software. DSSLIB combines the high efficiency and speed of parallel computation with a serial programming model that eliminates many undesirable side-effects of typical parallel code. The result is a simple way to incorporate the power of parallel processing into commercial software without compromising maintainability, reliability, or ease of use. This gives significant advantages over less powerful non-parallel entries in the market.

Adaptive reduction of constitutive model-form error using a posteriori error estimation techniques

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

Bishop, Joseph E.; Brown, Judith Alice

In engineering practice, models are typically kept as simple as possible for ease of setup and use, computational efficiency, maintenance, and overall reduced complexity to achieve robustness. In solid mechanics, a simple and efficient constitutive model may be favored over one that is more predictive, but is difficult to parameterize, is computationally expensive, or is simply not available within a simulation tool. In order to quantify the modeling error due to the choice of a relatively simple and less predictive constitutive model, we adopt the use of a posteriori model-form error-estimation techniques. Based on local error indicators in the energymore » norm, an algorithm is developed for reducing the modeling error by spatially adapting the material parameters in the simpler constitutive model. The resulting material parameters are not material properties per se, but depend on the given boundary-value problem. As a first step to the more general nonlinear case, we focus here on linear elasticity in which the “complex” constitutive model is general anisotropic elasticity and the chosen simpler model is isotropic elasticity. As a result, the algorithm for adaptive error reduction is demonstrated using two examples: (1) A transversely-isotropic plate with hole subjected to tension, and (2) a transversely-isotropic tube with two side holes subjected to torsion.« less

Adaptive reduction of constitutive model-form error using a posteriori error estimation techniques

DOE PAGES

Bishop, Joseph E.; Brown, Judith Alice

2018-06-15

In engineering practice, models are typically kept as simple as possible for ease of setup and use, computational efficiency, maintenance, and overall reduced complexity to achieve robustness. In solid mechanics, a simple and efficient constitutive model may be favored over one that is more predictive, but is difficult to parameterize, is computationally expensive, or is simply not available within a simulation tool. In order to quantify the modeling error due to the choice of a relatively simple and less predictive constitutive model, we adopt the use of a posteriori model-form error-estimation techniques. Based on local error indicators in the energymore » norm, an algorithm is developed for reducing the modeling error by spatially adapting the material parameters in the simpler constitutive model. The resulting material parameters are not material properties per se, but depend on the given boundary-value problem. As a first step to the more general nonlinear case, we focus here on linear elasticity in which the “complex” constitutive model is general anisotropic elasticity and the chosen simpler model is isotropic elasticity. As a result, the algorithm for adaptive error reduction is demonstrated using two examples: (1) A transversely-isotropic plate with hole subjected to tension, and (2) a transversely-isotropic tube with two side holes subjected to torsion.« less

Study of CdTe/CdS solar cell at low power density for low-illumination applications

NASA Astrophysics Data System (ADS)

Devi, Nisha; Aziz, Anver; Datta, Shouvik

2016-05-01

In this paper, we numerically investigate CdTe/CdS PV cell properties using a simulation program Solar Cell Capacitance Simulator in 1D (SCAPS-1D). A simple structure of CdTe PV cell has been optimized to study the effect of temperature, absorber thickness and work function at very low incident power. Objective of this research paper is to build an efficient and cost effective solar cell for portable electronic devices such as portable computers and cell phones that work at low incident power because most of such devices work at diffused and reflected sunlight. In this report, we simulated a simple CdTe PV cell at very low incident power, which gives good efficiency.

Efficient integration method for fictitious domain approaches

NASA Astrophysics Data System (ADS)

Duczek, Sascha; Gabbert, Ulrich

2015-10-01

In the current article, we present an efficient and accurate numerical method for the integration of the system matrices in fictitious domain approaches such as the finite cell method (FCM). In the framework of the FCM, the physical domain is embedded in a geometrically larger domain of simple shape which is discretized using a regular Cartesian grid of cells. Therefore, a spacetree-based adaptive quadrature technique is normally deployed to resolve the geometry of the structure. Depending on the complexity of the structure under investigation this method accounts for most of the computational effort. To reduce the computational costs for computing the system matrices an efficient quadrature scheme based on the divergence theorem (Gauß-Ostrogradsky theorem) is proposed. Using this theorem the dimension of the integral is reduced by one, i.e. instead of solving the integral for the whole domain only its contour needs to be considered. In the current paper, we present the general principles of the integration method and its implementation. The results to several two-dimensional benchmark problems highlight its properties. The efficiency of the proposed method is compared to conventional spacetree-based integration techniques.

Efficient Jacobian inversion for the control of simple robot manipulators

NASA Technical Reports Server (NTRS)

Fijany, Amir; Bejczy, Antal K.

1988-01-01

Symbolic inversion of the Jacobian matrix for spherical wrist arms is investigated. It is shown that, taking advantage of the simple geometry of these arms, the closed-form solution of the system Q = J-1X, representing a transformation from task space to joint space, can be obtained very efficiently. The solutions for PUMA, Stanford, and a six-revolute-joint coplanar arm, along with all singular points, are presented. The solution for each joint variable is found as an explicit function of the singular points which provides a better insight into the effect of different singular points on the motion and force exertion of each individual joint. For the above arms, the computation cost of the solution is on the same order as the cost of forward kinematic solution and it is significantly reduced if forward kinematic solution is already obtained. A comparison with previous methods shows that this method is the most efficient to date.

On the study of control effectiveness and computational efficiency of reduced Saint-Venant model in model predictive control of open channel flow

NASA Astrophysics Data System (ADS)

Xu, M.; van Overloop, P. J.; van de Giesen, N. C.

2011-02-01

Model predictive control (MPC) of open channel flow is becoming an important tool in water management. The complexity of the prediction model has a large influence on the MPC application in terms of control effectiveness and computational efficiency. The Saint-Venant equations, called SV model in this paper, and the Integrator Delay (ID) model are either accurate but computationally costly, or simple but restricted to allowed flow changes. In this paper, a reduced Saint-Venant (RSV) model is developed through a model reduction technique, Proper Orthogonal Decomposition (POD), on the SV equations. The RSV model keeps the main flow dynamics and functions over a large flow range but is easier to implement in MPC. In the test case of a modeled canal reach, the number of states and disturbances in the RSV model is about 45 and 16 times less than the SV model, respectively. The computational time of MPC with the RSV model is significantly reduced, while the controller remains effective. Thus, the RSV model is a promising means to balance the control effectiveness and computational efficiency.

Automated Reporting of DXA Studies Using a Custom-Built Computer Program.

PubMed

England, Joseph R; Colletti, Patrick M

2018-06-01

Dual-energy x-ray absorptiometry (DXA) scans are a critical population health tool and relatively simple to interpret but can be time consuming to report, often requiring manual transfer of bone mineral density and associated statistics into commercially available dictation systems. We describe here a custom-built computer program for automated reporting of DXA scans using Pydicom, an open-source package built in the Python computer language, and regular expressions to mine DICOM tags for patient information and bone mineral density statistics. This program, easy to emulate by any novice computer programmer, has doubled our efficiency at reporting DXA scans and has eliminated dictation errors.

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. These approaches are implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

High efficiency coherent optical memory with warm rubidium vapour

PubMed Central

Hosseini, M.; Sparkes, B.M.; Campbell, G.; Lam, P.K.; Buchler, B.C.

2011-01-01

By harnessing aspects of quantum mechanics, communication and information processing could be radically transformed. Promising forms of quantum information technology include optical quantum cryptographic systems and computing using photons for quantum logic operations. As with current information processing systems, some form of memory will be required. Quantum repeaters, which are required for long distance quantum key distribution, require quantum optical memory as do deterministic logic gates for optical quantum computing. Here, we present results from a coherent optical memory based on warm rubidium vapour and show 87% efficient recall of light pulses, the highest efficiency measured to date for any coherent optical memory suitable for quantum information applications. We also show storage and recall of up to 20 pulses from our system. These results show that simple warm atomic vapour systems have clear potential as a platform for quantum memory. PMID:21285952

High efficiency coherent optical memory with warm rubidium vapour.

PubMed

Hosseini, M; Sparkes, B M; Campbell, G; Lam, P K; Buchler, B C

2011-02-01

By harnessing aspects of quantum mechanics, communication and information processing could be radically transformed. Promising forms of quantum information technology include optical quantum cryptographic systems and computing using photons for quantum logic operations. As with current information processing systems, some form of memory will be required. Quantum repeaters, which are required for long distance quantum key distribution, require quantum optical memory as do deterministic logic gates for optical quantum computing. Here, we present results from a coherent optical memory based on warm rubidium vapour and show 87% efficient recall of light pulses, the highest efficiency measured to date for any coherent optical memory suitable for quantum information applications. We also show storage and recall of up to 20 pulses from our system. These results show that simple warm atomic vapour systems have clear potential as a platform for quantum memory.

Computer-Assisted Experiments with a Laser Diode

ERIC Educational Resources Information Center

Kraftmakher, Yaakov

2011-01-01

A laser diode from an inexpensive laser pen (laser pointer) is used in simple experiments. The radiant output power and efficiency of the laser are measured, and polarization of the light beam is shown. The "h/e" ratio is available from the threshold of spontaneous emission. The lasing threshold is found using several methods. With a…

Spherical-wave expansions of piston-radiator fields.

PubMed

Wittmann, R C; Yaghjian, A D

1991-09-01

Simple spherical-wave expansions of the continuous-wave fields of a circular piston radiator in a rigid baffle are derived. These expansions are valid throughout the illuminated half-space and are useful for efficient numerical computation in the near-field region. Multipole coefficients are given by closed-form expressions which can be evaluated recursively.

Efficient Parallel Engineering Computing on Linux Workstations

NASA Technical Reports Server (NTRS)

Lou, John Z.

2010-01-01

A C software module has been developed that creates lightweight processes (LWPs) dynamically to achieve parallel computing performance in a variety of engineering simulation and analysis applications to support NASA and DoD project tasks. The required interface between the module and the application it supports is simple, minimal and almost completely transparent to the user applications, and it can achieve nearly ideal computing speed-up on multi-CPU engineering workstations of all operating system platforms. The module can be integrated into an existing application (C, C++, Fortran and others) either as part of a compiled module or as a dynamically linked library (DLL).

On the use and computation of the Jordan canonical form in system theory

NASA Technical Reports Server (NTRS)

Sridhar, B.; Jordan, D.

1974-01-01

This paper investigates various aspects of the application of the Jordan canonical form of a matrix in system theory and develops a computational approach to determining the Jordan form for a given matrix. Applications include pole placement, controllability and observability studies, serving as an intermediate step in yielding other canonical forms, and theorem proving. The computational method developed in this paper is both simple and efficient. The method is based on the definition of a generalized eigenvector and a natural extension of Gauss elimination techniques. Examples are included for demonstration purposes.

Memory management in genome-wide association studies

PubMed Central

2009-01-01

Genome-wide association is a powerful tool for the identification of genes that underlie common diseases. Genome-wide association studies generate billions of genotypes and pose significant computational challenges for most users including limited computer memory. We applied a recently developed memory management tool to two analyses of North American Rheumatoid Arthritis Consortium studies and measured the performance in terms of central processing unit and memory usage. We conclude that our memory management approach is simple, efficient, and effective for genome-wide association studies. PMID:20018047

Efficient characterisation of large deviations using population dynamics

NASA Astrophysics Data System (ADS)

Brewer, Tobias; Clark, Stephen R.; Bradford, Russell; Jack, Robert L.

2018-05-01

We consider population dynamics as implemented by the cloning algorithm for analysis of large deviations of time-averaged quantities. We use the simple symmetric exclusion process with periodic boundary conditions as a prototypical example and investigate the convergence of the results with respect to the algorithmic parameters, focussing on the dynamical phase transition between homogeneous and inhomogeneous states, where convergence is relatively difficult to achieve. We discuss how the performance of the algorithm can be optimised, and how it can be efficiently exploited on parallel computing platforms.

A Simple and Efficient Computational Approach to Chafed Cable Time-Domain Reflectometry Signature Prediction

NASA Technical Reports Server (NTRS)

Kowalski, Marc Edward

2009-01-01

A method for the prediction of time-domain signatures of chafed coaxial cables is presented. The method is quasi-static in nature, and is thus efficient enough to be included in inference and inversion routines. Unlike previous models proposed, no restriction on the geometry or size of the chafe is required in the present approach. The model is validated and its speed is illustrated via comparison to simulations from a commercial, three-dimensional electromagnetic simulator.

Squid - a simple bioinformatics grid.

PubMed

Carvalho, Paulo C; Glória, Rafael V; de Miranda, Antonio B; Degrave, Wim M

2005-08-03

BLAST is a widely used genetic research tool for analysis of similarity between nucleotide and protein sequences. This paper presents a software application entitled "Squid" that makes use of grid technology. The current version, as an example, is configured for BLAST applications, but adaptation for other computing intensive repetitive tasks can be easily accomplished in the open source version. This enables the allocation of remote resources to perform distributed computing, making large BLAST queries viable without the need of high-end computers. Most distributed computing / grid solutions have complex installation procedures requiring a computer specialist, or have limitations regarding operating systems. Squid is a multi-platform, open-source program designed to "keep things simple" while offering high-end computing power for large scale applications. Squid also has an efficient fault tolerance and crash recovery system against data loss, being able to re-route jobs upon node failure and recover even if the master machine fails. Our results show that a Squid application, working with N nodes and proper network resources, can process BLAST queries almost N times faster than if working with only one computer. Squid offers high-end computing, even for the non-specialist, and is freely available at the project web site. Its open-source and binary Windows distributions contain detailed instructions and a "plug-n-play" instalation containing a pre-configured example.

Study of CdTe/CdS solar cell at low power density for low-illumination applications

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

Devi, Nisha, E-mail: nishatanwer1989@gmail.com; Aziz, Anver, E-mail: aaziz@jmi.ac.in; Datta, Shouvik

In this paper, we numerically investigate CdTe/CdS PV cell properties using a simulation program Solar Cell Capacitance Simulator in 1D (SCAPS-1D). A simple structure of CdTe PV cell has been optimized to study the effect of temperature, absorber thickness and work function at very low incident power. Objective of this research paper is to build an efficient and cost effective solar cell for portable electronic devices such as portable computers and cell phones that work at low incident power because most of such devices work at diffused and reflected sunlight. In this report, we simulated a simple CdTe PV cellmore » at very low incident power, which gives good efficiency.« less

Recognizing simple polyhedron from a perspective drawing

NASA Astrophysics Data System (ADS)

Zhang, Guimei; Chu, Jun; Miao, Jun

2009-10-01

Existed methods can't be used for recognizing simple polyhedron. In this paper, three problems are researched. First, a method for recognizing triangle and quadrilateral is introduced based on geometry and angle constraint. Then Attribute Relation Graph (ARG) is employed to describe simple polyhedron and line drawing. Last, a new method is presented to recognize simple polyhedron from a line drawing. The method filters the candidate database before matching line drawing and model, thus the recognition efficiency is improved greatly. We introduced the geometrical characteristics and topological characteristics to describe each node of ARG, so the algorithm can not only recognize polyhedrons with different shape but also distinguish between polyhedrons with the same shape but with different sizes and proportions. Computer simulations demonstrate the effectiveness of the method preliminarily.

Improving multivariate Horner schemes with Monte Carlo tree search

NASA Astrophysics Data System (ADS)

Kuipers, J.; Plaat, A.; Vermaseren, J. A. M.; van den Herik, H. J.

2013-11-01

Optimizing the cost of evaluating a polynomial is a classic problem in computer science. For polynomials in one variable, Horner's method provides a scheme for producing a computationally efficient form. For multivariate polynomials it is possible to generalize Horner's method, but this leaves freedom in the order of the variables. Traditionally, greedy schemes like most-occurring variable first are used. This simple textbook algorithm has given remarkably efficient results. Finding better algorithms has proved difficult. In trying to improve upon the greedy scheme we have implemented Monte Carlo tree search, a recent search method from the field of artificial intelligence. This results in better Horner schemes and reduces the cost of evaluating polynomials, sometimes by factors up to two.

A self-synchronized high speed computational ghost imaging system: A leap towards dynamic capturing

NASA Astrophysics Data System (ADS)

Suo, Jinli; Bian, Liheng; Xiao, Yudong; Wang, Yongjin; Zhang, Lei; Dai, Qionghai

2015-11-01

High quality computational ghost imaging needs to acquire a large number of correlated measurements between the to-be-imaged scene and different reference patterns, thus ultra-high speed data acquisition is of crucial importance in real applications. To raise the acquisition efficiency, this paper reports a high speed computational ghost imaging system using a 20 kHz spatial light modulator together with a 2 MHz photodiode. Technically, the synchronization between such high frequency illumination and bucket detector needs nanosecond trigger precision, so the development of synchronization module is quite challenging. To handle this problem, we propose a simple and effective computational self-synchronization scheme by building a general mathematical model and introducing a high precision synchronization technique. The resulted efficiency is around 14 times faster than state-of-the-arts, and takes an important step towards ghost imaging of dynamic scenes. Besides, the proposed scheme is a general approach with high flexibility for readily incorporating other illuminators and detectors.

CONC/11: A computer program for calculating the performance of dish-type solar thermal collectors and power systems

NASA Technical Reports Server (NTRS)

Jaffe, L. D.

1984-01-01

The CONC/11 computer program designed for calculating the performance of dish-type solar thermal collectors and power systems is discussed. This program is intended to aid the system or collector designer in evaluating the performance to be expected with possible design alternatives. From design or test data on the characteristics of the various subsystems, CONC/11 calculates the efficiencies of the collector and the overall power system as functions of the receiver temperature for a specified insolation. If desired, CONC/11 will also determine the receiver aperture and the receiver temperature that will provide the highest efficiencies at a given insolation. The program handles both simple and compound concentrators. The CONC/11 is written in Athena Extended FORTRAN (similar to FORTRAN 77) to operate primarily in an interactive mode on a Sperry 1100/81 computer. It could also be used on many small computers. A user's manual is also provided for this program.

Workflow computing. Improving management and efficiency of pathology diagnostic services.

PubMed

Buffone, G J; Moreau, D; Beck, J R

1996-04-01

Traditionally, information technology in health care has helped practitioners to collect, store, and present information and also to add a degree of automation to simple tasks (instrument interfaces supporting result entry, for example). Thus commercially available information systems do little to support the need to model, execute, monitor, coordinate, and revise the various complex clinical processes required to support health-care delivery. Workflow computing, which is already implemented and improving the efficiency of operations in several nonmedical industries, can address the need to manage complex clinical processes. Workflow computing not only provides a means to define and manage the events, roles, and information integral to health-care delivery but also supports the explicit implementation of policy or rules appropriate to the process. This article explains how workflow computing may be applied to health-care and the inherent advantages of the technology, and it defines workflow system requirements for use in health-care delivery with special reference to diagnostic pathology.

A network of spiking neurons for computing sparse representations in an energy efficient way

PubMed Central

Hu, Tao; Genkin, Alexander; Chklovskii, Dmitri B.

2013-01-01

Computing sparse redundant representations is an important problem both in applied mathematics and neuroscience. In many applications, this problem must be solved in an energy efficient way. Here, we propose a hybrid distributed algorithm (HDA), which solves this problem on a network of simple nodes communicating via low-bandwidth channels. HDA nodes perform both gradient-descent-like steps on analog internal variables and coordinate-descent-like steps via quantized external variables communicated to each other. Interestingly, such operation is equivalent to a network of integrate-and-fire neurons, suggesting that HDA may serve as a model of neural computation. We compare the numerical performance of HDA with existing algorithms and show that in the asymptotic regime the representation error of HDA decays with time, t, as 1/t. We show that HDA is stable against time-varying noise, specifically, the representation error decays as 1/t for Gaussian white noise. PMID:22920853

A network of spiking neurons for computing sparse representations in an energy-efficient way.

PubMed

Hu, Tao; Genkin, Alexander; Chklovskii, Dmitri B

2012-11-01

Computing sparse redundant representations is an important problem in both applied mathematics and neuroscience. In many applications, this problem must be solved in an energy-efficient way. Here, we propose a hybrid distributed algorithm (HDA), which solves this problem on a network of simple nodes communicating by low-bandwidth channels. HDA nodes perform both gradient-descent-like steps on analog internal variables and coordinate-descent-like steps via quantized external variables communicated to each other. Interestingly, the operation is equivalent to a network of integrate-and-fire neurons, suggesting that HDA may serve as a model of neural computation. We show that the numerical performance of HDA is on par with existing algorithms. In the asymptotic regime, the representation error of HDA decays with time, t, as 1/t. HDA is stable against time-varying noise; specifically, the representation error decays as 1/√t for gaussian white noise.

Perspective: Ring-polymer instanton theory

NASA Astrophysics Data System (ADS)

Richardson, Jeremy O.

2018-05-01

Since the earliest explorations of quantum mechanics, it has been a topic of great interest that quantum tunneling allows particles to penetrate classically insurmountable barriers. Instanton theory provides a simple description of these processes in terms of dominant tunneling pathways. Using a ring-polymer discretization, an efficient computational method is obtained for applying this theory to compute reaction rates and tunneling splittings in molecular systems. Unlike other quantum-dynamics approaches, the method scales well with the number of degrees of freedom, and for many polyatomic systems, the method may provide the most accurate predictions which can be practically computed. Instanton theory thus has the capability to produce useful data for many fields of low-temperature chemistry including spectroscopy, atmospheric and astrochemistry, as well as surface science. There is however still room for improvement in the efficiency of the numerical algorithms, and new theories are under development for describing tunneling in nonadiabatic transitions.

On optimal infinite impulse response edge detection filters

NASA Technical Reports Server (NTRS)

Sarkar, Sudeep; Boyer, Kim L.

1991-01-01

The authors outline the design of an optimal, computationally efficient, infinite impulse response edge detection filter. The optimal filter is computed based on Canny's high signal to noise ratio, good localization criteria, and a criterion on the spurious response of the filter to noise. An expression for the width of the filter, which is appropriate for infinite-length filters, is incorporated directly in the expression for spurious responses. The three criteria are maximized using the variational method and nonlinear constrained optimization. The optimal filter parameters are tabulated for various values of the filter performance criteria. A complete methodology for implementing the optimal filter using approximating recursive digital filtering is presented. The approximating recursive digital filter is separable into two linear filters operating in two orthogonal directions. The implementation is very simple and computationally efficient, has a constant time of execution for different sizes of the operator, and is readily amenable to real-time hardware implementation.

The origins of informatics.

PubMed Central

Collen, M F

1994-01-01

This article summarizes the origins of informatics, which is based on the science, engineering, and technology of computer hardware, software, and communications. In just four decades, from the 1950s to the 1990s, computer technology has progressed from slow, first-generation vacuum tubes, through the invention of the transistor and its incorporation into microprocessor chips, and ultimately, to fast, fourth-generation very-large-scale-integrated silicon chips. Programming has undergone a parallel transformation, from cumbersome, first-generation, machine languages to efficient, fourth-generation application-oriented languages. Communication has evolved from simple copper wires to complex fiberoptic cables in computer-linked networks. The digital computer has profound implications for the development and practice of clinical medicine. PMID:7719803

SURE reliability analysis: Program and mathematics

NASA Technical Reports Server (NTRS)

Butler, Ricky W.; White, Allan L.

1988-01-01

The SURE program is a new reliability analysis tool for ultrareliable computer system architectures. The computational methods on which the program is based provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been provEn effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. Several approaches that have proven effective for other evolutionary algorithms are modified and implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for standard test optimization problems and for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

De-quantisation

NASA Astrophysics Data System (ADS)

Gruska, Jozef

2012-06-01

One of the most basic tasks in quantum information processing, communication and security (QIPCC) research, theoretically deep and practically important, is to find bounds on how really important are inherently quantum resources for speeding up computations. This area of research is bringing a variety of results that imply, often in a very unexpected and counter-intuitive way, that: (a) surprisingly large classes of quantum circuits and algorithms can be efficiently simulated on classical computers; (b) the border line between quantum processes that can and cannot be efficiently simulated on classical computers is often surprisingly thin; (c) the addition of a seemingly very simple resource or a tool often enormously increases the power of available quantum tools. These discoveries have put also a new light on our understanding of quantum phenomena and quantum physics and on the potential of its inherently quantum and often mysteriously looking phenomena. The paper motivates and surveys research and its outcomes in the area of de-quantisation, especially presents various approaches and their outcomes concerning efficient classical simulations of various families of quantum circuits and algorithms. To motivate this area of research some outcomes in the area of de-randomization of classical randomized computations.

Improving robustness and computational efficiency using modern C++

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

Paterno, M.; Kowalkowski, J.; Green, C.

2014-01-01

For nearly two decades, the C++ programming language has been the dominant programming language for experimental HEP. The publication of ISO/IEC 14882:2011, the current version of the international standard for the C++ programming language, makes available a variety of language and library facilities for improving the robustness, expressiveness, and computational efficiency of C++ code. However, much of the C++ written by the experimental HEP community does not take advantage of the features of the language to obtain these benefits, either due to lack of familiarity with these features or concern that these features must somehow be computationally inefficient. In thismore » paper, we address some of the features of modern C+-+, and show how they can be used to make programs that are both robust and computationally efficient. We compare and contrast simple yet realistic examples of some common implementation patterns in C, currently-typical C++, and modern C++, and show (when necessary, down to the level of generated assembly language code) the quality of the executable code produced by recent C++ compilers, with the aim of allowing the HEP community to make informed decisions on the costs and benefits of the use of modern C++.« less

QUEST - A Bayesian adaptive psychometric method

NASA Technical Reports Server (NTRS)

Watson, A. B.; Pelli, D. G.

1983-01-01

An adaptive psychometric procedure that places each trial at the current most probable Bayesian estimate of threshold is described. The procedure takes advantage of the common finding that the human psychometric function is invariant in form when expressed as a function of log intensity. The procedure is simple, fast, and efficient, and may be easily implemented on any computer.

Intelligent Control of Flexible-Joint Robotic Manipulators

NASA Technical Reports Server (NTRS)

Colbaugh, R.; Gallegos, G.

1997-01-01

This paper considers the trajectory tracking problem for uncertain rigid-link. flexible.joint manipulators, and presents a new intelligent controller as a solution to this problem. The proposed control strategy is simple and computationally efficient, requires little information concerning either the manipulator or actuator/transmission models and ensures uniform boundedness of all signals and arbitrarily accurate task-space trajectory tracking.

Implementation of real-time digital signal processing systems

NASA Technical Reports Server (NTRS)

Narasimha, M.; Peterson, A.; Narayan, S.

1978-01-01

Special purpose hardware implementation of DFT Computers and digital filters is considered in the light of newly introduced algorithms and IC devices. Recent work by Winograd on high-speed convolution techniques for computing short length DFT's, has motivated the development of more efficient algorithms, compared to the FFT, for evaluating the transform of longer sequences. Among these, prime factor algorithms appear suitable for special purpose hardware implementations. Architectural considerations in designing DFT computers based on these algorithms are discussed. With the availability of monolithic multiplier-accumulators, a direct implementation of IIR and FIR filters, using random access memories in place of shift registers, appears attractive. The memory addressing scheme involved in such implementations is discussed. A simple counter set-up to address the data memory in the realization of FIR filters is also described. The combination of a set of simple filters (weighting network) and a DFT computer is shown to realize a bank of uniform bandpass filters. The usefulness of this concept in arriving at a modular design for a million channel spectrum analyzer, based on microprocessors, is discussed.

Fast-SNP: a fast matrix pre-processing algorithm for efficient loopless flux optimization of metabolic models

PubMed Central

Saa, Pedro A.; Nielsen, Lars K.

2016-01-01

Motivation: Computation of steady-state flux solutions in large metabolic models is routinely performed using flux balance analysis based on a simple LP (Linear Programming) formulation. A minimal requirement for thermodynamic feasibility of the flux solution is the absence of internal loops, which are enforced using ‘loopless constraints’. The resulting loopless flux problem is a substantially harder MILP (Mixed Integer Linear Programming) problem, which is computationally expensive for large metabolic models. Results: We developed a pre-processing algorithm that significantly reduces the size of the original loopless problem into an easier and equivalent MILP problem. The pre-processing step employs a fast matrix sparsification algorithm—Fast- sparse null-space pursuit (SNP)—inspired by recent results on SNP. By finding a reduced feasible ‘loop-law’ matrix subject to known directionalities, Fast-SNP considerably improves the computational efficiency in several metabolic models running different loopless optimization problems. Furthermore, analysis of the topology encoded in the reduced loop matrix enabled identification of key directional constraints for the potential permanent elimination of infeasible loops in the underlying model. Overall, Fast-SNP is an effective and simple algorithm for efficient formulation of loop-law constraints, making loopless flux optimization feasible and numerically tractable at large scale. Availability and Implementation: Source code for MATLAB including examples is freely available for download at http://www.aibn.uq.edu.au/cssb-resources under Software. Optimization uses Gurobi, CPLEX or GLPK (the latter is included with the algorithm). Contact: lars.nielsen@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27559155

Fast approximation for joint optimization of segmentation, shape, and location priors, and its application in gallbladder segmentation.

PubMed

Saito, Atsushi; Nawano, Shigeru; Shimizu, Akinobu

2017-05-01

This paper addresses joint optimization for segmentation and shape priors, including translation, to overcome inter-subject variability in the location of an organ. Because a simple extension of the previous exact optimization method is too computationally complex, we propose a fast approximation for optimization. The effectiveness of the proposed approximation is validated in the context of gallbladder segmentation from a non-contrast computed tomography (CT) volume. After spatial standardization and estimation of the posterior probability of the target organ, simultaneous optimization of the segmentation, shape, and location priors is performed using a branch-and-bound method. Fast approximation is achieved by combining sampling in the eigenshape space to reduce the number of shape priors and an efficient computational technique for evaluating the lower bound. Performance was evaluated using threefold cross-validation of 27 CT volumes. Optimization in terms of translation of the shape prior significantly improved segmentation performance. The proposed method achieved a result of 0.623 on the Jaccard index in gallbladder segmentation, which is comparable to that of state-of-the-art methods. The computational efficiency of the algorithm is confirmed to be good enough to allow execution on a personal computer. Joint optimization of the segmentation, shape, and location priors was proposed, and it proved to be effective in gallbladder segmentation with high computational efficiency.

Toward the design of alkynylimidazole fluorophores: computational and experimental characterization of spectroscopic features in solution and in poly(methyl methacrylate).

PubMed

Barone, Vincenzo; Bellina, Fabio; Biczysko, Malgorzata; Bloino, Julien; Fornaro, Teresa; Latouche, Camille; Lessi, Marco; Marianetti, Giulia; Minei, Pierpaolo; Panattoni, Alessandro; Pucci, Andrea

2015-10-28

The possibilities offered by organic fluorophores in the preparation of advanced plastic materials have been increased by designing novel alkynylimidazole dyes, featuring different push and pull groups. This new family of fluorescent dyes was synthesized by means of a one-pot sequential bromination-alkynylation of the heteroaromatic core, and their optical properties were investigated in tetrahydrofuran and in poly(methyl methacrylate). An efficient in silico pre-screening scheme was devised as consisting of a step-by-step procedure employing computational methodologies by simulation of electronic spectra within simple vertical energy and more sophisticated vibronic approaches. Such an approach was also extended to efficiently simulate one-photon absorption and emission spectra of the dyes in the polymer environment for their potential application in luminescent solar concentrators. Besides the specific applications of this novel material, the integration of computational and experimental techniques reported here provides an efficient protocol that can be applied to make a selection among similar dye candidates, which constitute the essential responsive part of those fluorescent plastic materials.

Theory and applications of a deterministic approximation to the coalescent model

PubMed Central

Jewett, Ethan M.; Rosenberg, Noah A.

2014-01-01

Under the coalescent model, the random number nt of lineages ancestral to a sample is nearly deterministic as a function of time when nt is moderate to large in value, and it is well approximated by its expectation E[nt]. In turn, this expectation is well approximated by simple deterministic functions that are easy to compute. Such deterministic functions have been applied to estimate allele age, effective population size, and genetic diversity, and they have been used to study properties of models of infectious disease dynamics. Although a number of simple approximations of E[nt] have been derived and applied to problems of population-genetic inference, the theoretical accuracy of the formulas and the inferences obtained using these approximations is not known, and the range of problems to which they can be applied is not well understood. Here, we demonstrate general procedures by which the approximation nt ≈ E[nt] can be used to reduce the computational complexity of coalescent formulas, and we show that the resulting approximations converge to their true values under simple assumptions. Such approximations provide alternatives to exact formulas that are computationally intractable or numerically unstable when the number of sampled lineages is moderate or large. We also extend an existing class of approximations of E[nt] to the case of multiple populations of time-varying size with migration among them. Our results facilitate the use of the deterministic approximation nt ≈ E[nt] for deriving functionally simple, computationally efficient, and numerically stable approximations of coalescent formulas under complicated demographic scenarios. PMID:24412419

Economics and computer science of a radio spectrum reallocation.

PubMed

Leyton-Brown, Kevin; Milgrom, Paul; Segal, Ilya

2017-07-11

The recent "incentive auction" of the US Federal Communications Commission was the first auction to reallocate radio frequencies between two different kinds of uses: from broadcast television to wireless Internet access. The design challenge was not just to choose market rules to govern a fixed set of potential trades but also, to determine the broadcasters' property rights, the goods to be exchanged, the quantities to be traded, the computational procedures, and even some of the performance objectives. An essential and unusual challenge was to make the auction simple enough for human participants while still ensuring that the computations would be tractable and capable of delivering nearly efficient outcomes.

Phase-unwrapping algorithm by a rounding-least-squares approach

NASA Astrophysics Data System (ADS)

Juarez-Salazar, Rigoberto; Robledo-Sanchez, Carlos; Guerrero-Sanchez, Fermin

2014-02-01

A simple and efficient phase-unwrapping algorithm based on a rounding procedure and a global least-squares minimization is proposed. Instead of processing the gradient of the wrapped phase, this algorithm operates over the gradient of the phase jumps by a robust and noniterative scheme. Thus, the residue-spreading and over-smoothing effects are reduced. The algorithm's performance is compared with four well-known phase-unwrapping methods: minimum cost network flow (MCNF), fast Fourier transform (FFT), quality-guided, and branch-cut. A computer simulation and experimental results show that the proposed algorithm reaches a high-accuracy level than the MCNF method by a low-computing time similar to the FFT phase-unwrapping method. Moreover, since the proposed algorithm is simple, fast, and user-free, it could be used in metrological interferometric and fringe-projection automatic real-time applications.

Intrinsic dimensionality predicts the saliency of natural dynamic scenes.

PubMed

Vig, Eleonora; Dorr, Michael; Martinetz, Thomas; Barth, Erhardt

2012-06-01

Since visual attention-based computer vision applications have gained popularity, ever more complex, biologically inspired models seem to be needed to predict salient locations (or interest points) in naturalistic scenes. In this paper, we explore how far one can go in predicting eye movements by using only basic signal processing, such as image representations derived from efficient coding principles, and machine learning. To this end, we gradually increase the complexity of a model from simple single-scale saliency maps computed on grayscale videos to spatiotemporal multiscale and multispectral representations. Using a large collection of eye movements on high-resolution videos, supervised learning techniques fine-tune the free parameters whose addition is inevitable with increasing complexity. The proposed model, although very simple, demonstrates significant improvement in predicting salient locations in naturalistic videos over four selected baseline models and two distinct data labeling scenarios.

PROPOSAL FOR A SIMPLE AND EFFICIENT MONTHLY QUALITY MANAGEMENT PROGRAM ASSESSING THE CONSISTENCY OF ROBOTIC IMAGE-GUIDED SMALL ANIMAL RADIATION SYSTEMS

PubMed Central

Brodin, N. Patrik; Guha, Chandan; Tomé, Wolfgang A.

2015-01-01

Modern pre-clinical radiation therapy (RT) research requires high precision and accurate dosimetry to facilitate the translation of research findings into clinical practice. Several systems are available that provide precise delivery and on-board imaging capabilities, highlighting the need for a quality management program (QMP) to ensure consistent and accurate radiation dose delivery. An ongoing, simple, and efficient QMP for image-guided robotic small animal irradiators used in pre-clinical RT research is described. Protocols were developed and implemented to assess the dose output constancy (based on the AAPM TG-61 protocol), cone-beam computed tomography (CBCT) image quality and object representation accuracy (using a custom-designed imaging phantom), CBCT-guided target localization accuracy and consistency of the CBCT-based dose calculation. To facilitate an efficient read-out and limit the user dependence of the QMP data analysis, a semi-automatic image analysis and data representation program was developed using the technical computing software MATLAB. The results of the first six months experience using the suggested QMP for a Small Animal Radiation Research Platform (SARRP) are presented, with data collected on a bi-monthly basis. The dosimetric output constancy was established to be within ±1 %, the consistency of the image resolution was within ±0.2 mm, the accuracy of CBCT-guided target localization was within ±0.5 mm, and dose calculation consistency was within ±2 s (± 3 %) per treatment beam. Based on these results, this simple quality assurance program allows for the detection of inconsistencies in dosimetric or imaging parameters that are beyond the acceptable variability for a reliable and accurate pre-clinical RT system, on a monthly or bi-monthly basis. PMID:26425981

Proposal for a Simple and Efficient Monthly Quality Management Program Assessing the Consistency of Robotic Image-Guided Small Animal Radiation Systems.

PubMed

Brodin, N Patrik; Guha, Chandan; Tomé, Wolfgang A

2015-11-01

Modern pre-clinical radiation therapy (RT) research requires high precision and accurate dosimetry to facilitate the translation of research findings into clinical practice. Several systems are available that provide precise delivery and on-board imaging capabilities, highlighting the need for a quality management program (QMP) to ensure consistent and accurate radiation dose delivery. An ongoing, simple, and efficient QMP for image-guided robotic small animal irradiators used in pre-clinical RT research is described. Protocols were developed and implemented to assess the dose output constancy (based on the AAPM TG-61 protocol), cone-beam computed tomography (CBCT) image quality and object representation accuracy (using a custom-designed imaging phantom), CBCT-guided target localization accuracy and consistency of the CBCT-based dose calculation. To facilitate an efficient read-out and limit the user dependence of the QMP data analysis, a semi-automatic image analysis and data representation program was developed using the technical computing software MATLAB. The results of the first 6-mo experience using the suggested QMP for a Small Animal Radiation Research Platform (SARRP) are presented, with data collected on a bi-monthly basis. The dosimetric output constancy was established to be within ±1 %, the consistency of the image resolution was within ±0.2 mm, the accuracy of CBCT-guided target localization was within ±0.5 mm, and dose calculation consistency was within ±2 s (±3%) per treatment beam. Based on these results, this simple quality assurance program allows for the detection of inconsistencies in dosimetric or imaging parameters that are beyond the acceptable variability for a reliable and accurate pre-clinical RT system, on a monthly or bi-monthly basis.

Integration of Openstack cloud resources in BES III computing cluster

NASA Astrophysics Data System (ADS)

Li, Haibo; Cheng, Yaodong; Huang, Qiulan; Cheng, Zhenjing; Shi, Jingyan

2017-10-01

Cloud computing provides a new technical means for data processing of high energy physics experiment. However, the resource of each queue is fixed and the usage of the resource is static in traditional job management system. In order to make it simple and transparent for physicist to use, we developed a virtual cluster system (vpmanager) to integrate IHEPCloud and different batch systems such as Torque and HTCondor. Vpmanager provides dynamic virtual machines scheduling according to the job queue. The BES III use case results show that resource efficiency is greatly improved.

An efficient computer based wavelets approximation method to solve Fuzzy boundary value differential equations

NASA Astrophysics Data System (ADS)

Alam Khan, Najeeb; Razzaq, Oyoon Abdul

2016-03-01

In the present work a wavelets approximation method is employed to solve fuzzy boundary value differential equations (FBVDEs). Essentially, a truncated Legendre wavelets series together with the Legendre wavelets operational matrix of derivative are utilized to convert FB- VDE into a simple computational problem by reducing it into a system of fuzzy algebraic linear equations. The capability of scheme is investigated on second order FB- VDE considered under generalized H-differentiability. Solutions are represented graphically showing competency and accuracy of this method.

Simple expression for the quantum Fisher information matrix

NASA Astrophysics Data System (ADS)

Šafránek, Dominik

2018-04-01

Quantum Fisher information matrix (QFIM) is a cornerstone of modern quantum metrology and quantum information geometry. Apart from optimal estimation, it finds applications in description of quantum speed limits, quantum criticality, quantum phase transitions, coherence, entanglement, and irreversibility. We derive a surprisingly simple formula for this quantity, which, unlike previously known general expression, does not require diagonalization of the density matrix, and is provably at least as efficient. With a minor modification, this formula can be used to compute QFIM for any finite-dimensional density matrix. Because of its simplicity, it could also shed more light on the quantum information geometry in general.

Provably Secure Password-based Authentication in TLS

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

Abdalla, Michel; Emmanuel, Bresson; Chevassut, Olivier

2005-12-20

In this paper, we show how to design an efficient, provably secure password-based authenticated key exchange mechanism specifically for the TLS (Transport Layer Security) protocol. The goal is to provide a technique that allows users to employ (short) passwords to securely identify themselves to servers. As our main contribution, we describe a new password-based technique for user authentication in TLS, called Simple Open Key Exchange (SOKE). Loosely speaking, the SOKE ciphersuites are unauthenticated Diffie-Hellman ciphersuites in which the client's Diffie-Hellman ephemeral public value is encrypted using a simple mask generation function. The mask is simply a constant value raised tomore » the power of (a hash of) the password.The SOKE ciphersuites, in advantage over previous pass-word-based authentication ciphersuites for TLS, combine the following features. First, SOKE has formal security arguments; the proof of security based on the computational Diffie-Hellman assumption is in the random oracle model, and holds for concurrent executions and for arbitrarily large password dictionaries. Second, SOKE is computationally efficient; in particular, it only needs operations in a sufficiently large prime-order subgroup for its Diffie-Hellman computations (no safe primes). Third, SOKE provides good protocol flexibility because the user identity and password are only required once a SOKE ciphersuite has actually been negotiated, and after the server has sent a server identity.« less

Mathematical modelling of risk reduction in reinsurance

NASA Astrophysics Data System (ADS)

Balashov, R. B.; Kryanev, A. V.; Sliva, D. E.

2017-01-01

The paper presents a mathematical model of efficient portfolio formation in the reinsurance markets. The presented approach provides the optimal ratio between the expected value of return and the risk of yield values below a certain level. The uncertainty in the return values is conditioned by use of expert evaluations and preliminary calculations, which result in expected return values and the corresponding risk levels. The proposed method allows for implementation of computationally simple schemes and algorithms for numerical calculation of the numerical structure of the efficient portfolios of reinsurance contracts of a given insurance company.

Scalable Track Detection in SAR CCD Images

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

Chow, James G; Quach, Tu-Thach

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images ta ken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are often too simple to capture natural track features such as continuity and parallelism. We present a simple convolutional network architecture consisting of a series of 3-by-3 convolutions to detect tracks. The network is trained end-to-end to learn natural track features entirely from data. The network is computationally efficient and improves the F-score on a standard dataset to 0.988,more » up fr om 0.907 obtained by the current state-of-the-art method.« less

A Lightweight Protocol for Secure Video Streaming

PubMed Central

Morkevicius, Nerijus; Bagdonas, Kazimieras

2018-01-01

The Internet of Things (IoT) introduces many new challenges which cannot be solved using traditional cloud and host computing models. A new architecture known as fog computing is emerging to address these technological and security gaps. Traditional security paradigms focused on providing perimeter-based protections and client/server point to point protocols (e.g., Transport Layer Security (TLS)) are no longer the best choices for addressing new security challenges in fog computing end devices, where energy and computational resources are limited. In this paper, we present a lightweight secure streaming protocol for the fog computing “Fog Node-End Device” layer. This protocol is lightweight, connectionless, supports broadcast and multicast operations, and is able to provide data source authentication, data integrity, and confidentiality. The protocol is based on simple and energy efficient cryptographic methods, such as Hash Message Authentication Codes (HMAC) and symmetrical ciphers, and uses modified User Datagram Protocol (UDP) packets to embed authentication data into streaming data. Data redundancy could be added to improve reliability in lossy networks. The experimental results summarized in this paper confirm that the proposed method efficiently uses energy and computational resources and at the same time provides security properties on par with the Datagram TLS (DTLS) standard. PMID:29757988

A Lightweight Protocol for Secure Video Streaming.

PubMed

Venčkauskas, Algimantas; Morkevicius, Nerijus; Bagdonas, Kazimieras; Damaševičius, Robertas; Maskeliūnas, Rytis

2018-05-14

The Internet of Things (IoT) introduces many new challenges which cannot be solved using traditional cloud and host computing models. A new architecture known as fog computing is emerging to address these technological and security gaps. Traditional security paradigms focused on providing perimeter-based protections and client/server point to point protocols (e.g., Transport Layer Security (TLS)) are no longer the best choices for addressing new security challenges in fog computing end devices, where energy and computational resources are limited. In this paper, we present a lightweight secure streaming protocol for the fog computing "Fog Node-End Device" layer. This protocol is lightweight, connectionless, supports broadcast and multicast operations, and is able to provide data source authentication, data integrity, and confidentiality. The protocol is based on simple and energy efficient cryptographic methods, such as Hash Message Authentication Codes (HMAC) and symmetrical ciphers, and uses modified User Datagram Protocol (UDP) packets to embed authentication data into streaming data. Data redundancy could be added to improve reliability in lossy networks. The experimental results summarized in this paper confirm that the proposed method efficiently uses energy and computational resources and at the same time provides security properties on par with the Datagram TLS (DTLS) standard.

Expansion of Tabulated Scattering Matrices in Generalized Spherical Functions

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Geogdzhayev, Igor V.; Yang, Ping

2016-01-01

An efficient way to solve the vector radiative transfer equation for plane-parallel turbid media is to Fourier-decompose it in azimuth. This methodology is typically based on the analytical computation of the Fourier components of the phase matrix and is predicated on the knowledge of the coefficients appearing in the expansion of the normalized scattering matrix in generalized spherical functions. Quite often the expansion coefficients have to be determined from tabulated values of the scattering matrix obtained from measurements or calculated by solving the Maxwell equations. In such cases one needs an efficient and accurate computer procedure converting a tabulated scattering matrix into the corresponding set of expansion coefficients. This short communication summarizes the theoretical basis of this procedure and serves as the user guide to a simple public-domain FORTRAN program.

A Randomized Trial of a Computer-Assisted Tutoring Program Targeting Letter-Sound Expression

ERIC Educational Resources Information Center

DuBois, Matthew R.; Volpe, Robert J.; Hemphill, Elizabeth M.

2014-01-01

Given that many schools have limited resources and a high proportion of students who present with deficits in early literacy skills, supports aimed at preventing reading failure must be simple and efficient and generate meaningful changes in student learning. We used a randomized group design with a wait-list control to extend the work of Volpe,…

Global Contrast Based Salient Region Detection.

PubMed

Cheng, Ming-Ming; Mitra, Niloy J; Huang, Xiaolei; Torr, Philip H S; Hu, Shi-Min

2015-03-01

Automatic estimation of salient object regions across images, without any prior assumption or knowledge of the contents of the corresponding scenes, enhances many computer vision and computer graphics applications. We introduce a regional contrast based salient object detection algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence scores. The proposed algorithm is simple, efficient, naturally multi-scale, and produces full-resolution, high-quality saliency maps. These saliency maps are further used to initialize a novel iterative version of GrabCut, namely SaliencyCut, for high quality unsupervised salient object segmentation. We extensively evaluated our algorithm using traditional salient object detection datasets, as well as a more challenging Internet image dataset. Our experimental results demonstrate that our algorithm consistently outperforms 15 existing salient object detection and segmentation methods, yielding higher precision and better recall rates. We also show that our algorithm can be used to efficiently extract salient object masks from Internet images, enabling effective sketch-based image retrieval (SBIR) via simple shape comparisons. Despite such noisy internet images, where the saliency regions are ambiguous, our saliency guided image retrieval achieves a superior retrieval rate compared with state-of-the-art SBIR methods, and additionally provides important target object region information.

The SURE reliability analysis program

NASA Technical Reports Server (NTRS)

Butler, R. W.

1986-01-01

The SURE program is a new reliability tool for ultrareliable computer system architectures. The program is based on computational methods recently developed for the NASA Langley Research Center. These methods provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.

The SURE Reliability Analysis Program

NASA Technical Reports Server (NTRS)

Butler, R. W.

1986-01-01

The SURE program is a new reliability analysis tool for ultrareliable computer system architectures. The program is based on computational methods recently developed for the NASA Langley Research Center. These methods provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.

Acoustic environmental accuracy requirements for response determination

NASA Technical Reports Server (NTRS)

Pettitt, M. R.

1983-01-01

A general purpose computer program was developed for the prediction of vehicle interior noise. This program, named VIN, has both modal and statistical energy analysis capabilities for structural/acoustic interaction analysis. The analytic models and their computer implementation were verified through simple test cases with well-defined experimental results. The model was also applied in a space shuttle payload bay launch acoustics prediction study. The computer program processes large and small problems with equal efficiency because all arrays are dynamically sized by program input variables at run time. A data base is built and easily accessed for design studies. The data base significantly reduces the computational costs of such studies by allowing the reuse of the still-valid calculated parameters of previous iterations.

An Exact Efficiency Formula for Holographic Heat Engines

DOE PAGES

Johnson, Clifford

2016-03-31

Further consideration is given to the efficiency of a class of black hole heat engines that perform mechanical work via the pdV terms present in the First Law of extended gravitational thermodynamics. It is noted that, when the engine cycle is a rectangle with sides parallel to the (p,V) axes, the efficiency can be written simply in terms of the mass of the black hole evaluated at the corners. Since an arbitrary cycle can be approximated to any desired accuracy by a tiling of rectangles, a general geometrical algorithm for computing the efficiency of such a cycle follows. Finally, amore » simple generalization of the algorithm renders it applicable to broader classes of heat engine, even beyond the black hole context.« less

Differential theory of learning for efficient neural network pattern recognition

NASA Astrophysics Data System (ADS)

Hampshire, John B., II; Vijaya Kumar, Bhagavatula

1993-09-01

We describe a new theory of differential learning by which a broad family of pattern classifiers (including many well-known neural network paradigms) can learn stochastic concepts efficiently. We describe the relationship between a classifier's ability to generate well to unseen test examples and the efficiency of the strategy by which it learns. We list a series of proofs that differential learning is efficient in its information and computational resource requirements, whereas traditional probabilistic learning strategies are not. The proofs are illustrated by a simple example that lends itself to closed-form analysis. We conclude with an optical character recognition task for which three different types of differentially generated classifiers generalize significantly better than their probabilistically generated counterparts.

Differential theory of learning for efficient neural network pattern recognition

NASA Astrophysics Data System (ADS)

Hampshire, John B., II; Vijaya Kumar, Bhagavatula

1993-08-01

We describe a new theory of differential learning by which a broad family of pattern classifiers (including many well-known neural network paradigms) can learn stochastic concepts efficiently. We describe the relationship between a classifier's ability to generalize well to unseen test examples and the efficiency of the strategy by which it learns. We list a series of proofs that differential learning is efficient in its information and computational resource requirements, whereas traditional probabilistic learning strategies are not. The proofs are illustrated by a simple example that lends itself to closed-form analysis. We conclude with an optical character recognition task for which three different types of differentially generated classifiers generalize significantly better than their probabilistically generated counterparts.

Recipient design in human communication: simple heuristics or perspective taking?

PubMed

Blokpoel, Mark; van Kesteren, Marlieke; Stolk, Arjen; Haselager, Pim; Toni, Ivan; van Rooij, Iris

2012-01-01

Humans have a remarkable capacity for tuning their communicative behaviors to different addressees, a phenomenon also known as recipient design. It remains unclear how this tuning of communicative behavior is implemented during live human interactions. Classical theories of communication postulate that recipient design involves perspective taking, i.e., the communicator selects her behavior based on her hypotheses about beliefs and knowledge of the recipient. More recently, researchers have argued that perspective taking is computationally too costly to be a plausible mechanism in everyday human communication. These researchers propose that computationally simple mechanisms, or heuristics, are exploited to perform recipient design. Such heuristics may be able to adapt communicative behavior to an addressee with no consideration for the addressee's beliefs and knowledge. To test whether the simpler of the two mechanisms is sufficient for explaining the "how" of recipient design we studied communicators' behaviors in the context of a non-verbal communicative task (the Tacit Communication Game, TCG). We found that the specificity of the observed trial-by-trial adjustments made by communicators is parsimoniously explained by perspective taking, but not by simple heuristics. This finding is important as it suggests that humans do have a computationally efficient way of taking beliefs and knowledge of a recipient into account.

Recipient design in human communication: simple heuristics or perspective taking?

PubMed Central

Blokpoel, Mark; van Kesteren, Marlieke; Stolk, Arjen; Haselager, Pim; Toni, Ivan; van Rooij, Iris

2012-01-01

Humans have a remarkable capacity for tuning their communicative behaviors to different addressees, a phenomenon also known as recipient design. It remains unclear how this tuning of communicative behavior is implemented during live human interactions. Classical theories of communication postulate that recipient design involves perspective taking, i.e., the communicator selects her behavior based on her hypotheses about beliefs and knowledge of the recipient. More recently, researchers have argued that perspective taking is computationally too costly to be a plausible mechanism in everyday human communication. These researchers propose that computationally simple mechanisms, or heuristics, are exploited to perform recipient design. Such heuristics may be able to adapt communicative behavior to an addressee with no consideration for the addressee's beliefs and knowledge. To test whether the simpler of the two mechanisms is sufficient for explaining the “how” of recipient design we studied communicators' behaviors in the context of a non-verbal communicative task (the Tacit Communication Game, TCG). We found that the specificity of the observed trial-by-trial adjustments made by communicators is parsimoniously explained by perspective taking, but not by simple heuristics. This finding is important as it suggests that humans do have a computationally efficient way of taking beliefs and knowledge of a recipient into account. PMID:23055960

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.

Generalized Born Models of Macromolecular Solvation Effects

NASA Astrophysics Data System (ADS)

Bashford, Donald; Case, David A.

2000-10-01

It would often be useful in computer simulations to use a simple description of solvation effects, instead of explicitly representing the individual solvent molecules. Continuum dielectric models often work well in describing the thermodynamic aspects of aqueous solvation, and approximations to such models that avoid the need to solve the Poisson equation are attractive because of their computational efficiency. Here we give an overview of one such approximation, the generalized Born model, which is simple and fast enough to be used for molecular dynamics simulations of proteins and nucleic acids. We discuss its strengths and weaknesses, both for its fidelity to the underlying continuum model and for its ability to replace explicit consideration of solvent molecules in macromolecular simulations. We focus particularly on versions of the generalized Born model that have a pair-wise analytical form, and therefore fit most naturally into conventional molecular mechanics calculations.

A novel patient-specific model to compute coronary fractional flow reserve.

PubMed

Kwon, Soon-Sung; Chung, Eui-Chul; Park, Jin-Seo; Kim, Gook-Tae; Kim, Jun-Woo; Kim, Keun-Hong; Shin, Eun-Seok; Shim, Eun Bo

2014-09-01

The fractional flow reserve (FFR) is a widely used clinical index to evaluate the functional severity of coronary stenosis. A computer simulation method based on patients' computed tomography (CT) data is a plausible non-invasive approach for computing the FFR. This method can provide a detailed solution for the stenosed coronary hemodynamics by coupling computational fluid dynamics (CFD) with the lumped parameter model (LPM) of the cardiovascular system. In this work, we have implemented a simple computational method to compute the FFR. As this method uses only coronary arteries for the CFD model and includes only the LPM of the coronary vascular system, it provides simpler boundary conditions for the coronary geometry and is computationally more efficient than existing approaches. To test the efficacy of this method, we simulated a three-dimensional straight vessel using CFD coupled with the LPM. The computed results were compared with those of the LPM. To validate this method in terms of clinically realistic geometry, a patient-specific model of stenosed coronary arteries was constructed from CT images, and the computed FFR was compared with clinically measured results. We evaluated the effect of a model aorta on the computed FFR and compared this with a model without the aorta. Computationally, the model without the aorta was more efficient than that with the aorta, reducing the CPU time required for computing a cardiac cycle to 43.4%. Copyright © 2014. Published by Elsevier Ltd.

Efficient control schemes with limited computation complexity for Tomographic AO systems on VLTs and ELTs

NASA Astrophysics Data System (ADS)

Petit, C.; Le Louarn, M.; Fusco, T.; Madec, P.-Y.

2011-09-01

Various tomographic control solutions have been proposed during the last decades to ensure efficient or even optimal closed-loop correction to tomographic Adaptive Optics (AO) concepts such as Laser Tomographic AO (LTAO), Multi-Conjugate AO (MCAO). The optimal solution, based on Linear Quadratic Gaussian (LQG) approach, as well as suboptimal but efficient solutions such as Pseudo-Open Loop Control (POLC) require multiple Matrix Vector Multiplications (MVM). Disregarding their respective performance, these efficient control solutions thus exhibit strong increase of on-line complexity and their implementation may become difficult in demanding cases. Among them, two cases are of particular interest. First, the system Real-Time Computer architecture and implementation is derived from past or present solutions and does not support multiple MVM. This is the case of the AO Facility which RTC architecture is derived from the SPARTA platform and inherits its simple MVM architecture, which does not fit with LTAO control solutions for instance. Second, considering future systems such as Extremely Large Telescopes, the number of degrees of freedom is twenty to one hundred times bigger than present systems. In these conditions, tomographic control solutions can hardly be used in their standard form and optimized implementation shall be considered. Single MVM tomographic control solutions represent a potential solution, and straightforward solutions such as Virtual Deformable Mirrors have been already proposed for LTAO but with tuning issues. We investigate in this paper the possibility to derive from tomographic control solutions, such as POLC or LQG, simplified control solutions ensuring simple MVM architecture and that could be thus implemented on nowadays systems or future complex systems. We theoretically derive various solutions and analyze their respective performance on various systems thanks to numerical simulation. We discuss the optimization of their performance and stability issues with respect to classic control solutions. We finally discuss off-line computation and implementation constraints.

A simple quantum mechanical treatment of scattering in nanoscale transistors

NASA Astrophysics Data System (ADS)

Venugopal, R.; Paulsson, M.; Goasguen, S.; Datta, S.; Lundstrom, M. S.

2003-05-01

We present a computationally efficient, two-dimensional quantum mechanical simulation scheme for modeling dissipative electron transport in thin body, fully depleted, n-channel, silicon-on-insulator transistors. The simulation scheme, which solves the nonequilibrium Green's function equations self consistently with Poisson's equation, treats the effect of scattering using a simple approximation inspired by the "Büttiker probes," often used in mesoscopic physics. It is based on an expansion of the active device Hamiltonian in decoupled mode space. Simulation results are used to highlight quantum effects, discuss the physics of scattering and to relate the quantum mechanical quantities used in our model to experimentally measured low field mobilities. Additionally, quantum boundary conditions are rigorously derived and the effects of strong off-equilibrium transport are examined. This paper shows that our approximate treatment of scattering, is an efficient and useful simulation method for modeling electron transport in nanoscale, silicon-on-insulator transistors.

Graphical tensor product reduction scheme for the Lie algebras so(5) = sp(2) , su(3) , and g(2)

NASA Astrophysics Data System (ADS)

Vlasii, N. D.; von Rütte, F.; Wiese, U.-J.

2016-08-01

We develop in detail a graphical tensor product reduction scheme, first described by Antoine and Speiser, for the simple rank 2 Lie algebras so(5) = sp(2) , su(3) , and g(2) . This leads to an efficient practical method to reduce tensor products of irreducible representations into sums of such representations. For this purpose, the 2-dimensional weight diagram of a given representation is placed in a ;landscape; of irreducible representations. We provide both the landscapes and the weight diagrams for a large number of representations for the three simple rank 2 Lie algebras. We also apply the algebraic ;girdle; method, which is much less efficient for calculations by hand for moderately large representations. Computer code for reducing tensor products, based on the graphical method, has been developed as well and is available from the authors upon request.

A Simple Secure Hash Function Scheme Using Multiple Chaotic Maps

NASA Astrophysics Data System (ADS)

Ahmad, Musheer; Khurana, Shruti; Singh, Sushmita; AlSharari, Hamed D.

2017-06-01

The chaotic maps posses high parameter sensitivity, random-like behavior and one-way computations, which favor the construction of cryptographic hash functions. In this paper, we propose to present a novel hash function scheme which uses multiple chaotic maps to generate efficient variable-sized hash functions. The message is divided into four parts, each part is processed by a different 1D chaotic map unit yielding intermediate hash code. The four codes are concatenated to two blocks, then each block is processed through 2D chaotic map unit separately. The final hash value is generated by combining the two partial hash codes. The simulation analyses such as distribution of hashes, statistical properties of confusion and diffusion, message and key sensitivity, collision resistance and flexibility are performed. The results reveal that the proposed anticipated hash scheme is simple, efficient and holds comparable capabilities when compared with some recent chaos-based hash algorithms.

Computational fluid dynamics uses in fluid dynamics/aerodynamics education

NASA Technical Reports Server (NTRS)

Holst, Terry L.

1994-01-01

The field of computational fluid dynamics (CFD) has advanced to the point where it can now be used for the purpose of fluid dynamics physics education. Because of the tremendous wealth of information available from numerical simulation, certain fundamental concepts can be efficiently communicated using an interactive graphical interrogation of the appropriate numerical simulation data base. In other situations, a large amount of aerodynamic information can be communicated to the student by interactive use of simple CFD tools on a workstation or even in a personal computer environment. The emphasis in this presentation is to discuss ideas for how this process might be implemented. Specific examples, taken from previous publications, will be used to highlight the presentation.

Economics and computer science of a radio spectrum reallocation

PubMed Central

Leyton-Brown, Kevin; Segal, Ilya

2017-01-01

The recent “incentive auction” of the US Federal Communications Commission was the first auction to reallocate radio frequencies between two different kinds of uses: from broadcast television to wireless Internet access. The design challenge was not just to choose market rules to govern a fixed set of potential trades but also, to determine the broadcasters’ property rights, the goods to be exchanged, the quantities to be traded, the computational procedures, and even some of the performance objectives. An essential and unusual challenge was to make the auction simple enough for human participants while still ensuring that the computations would be tractable and capable of delivering nearly efficient outcomes. PMID:28652335

Applications of multiple-constraint matrix updates to the optimal control of large structures

NASA Technical Reports Server (NTRS)

Smith, S. W.; Walcott, B. L.

1992-01-01

Low-authority control or vibration suppression in large, flexible space structures can be formulated as a linear feedback control problem requiring computation of displacement and velocity feedback gain matrices. To ensure stability in the uncontrolled modes, these gain matrices must be symmetric and positive definite. In this paper, efficient computation of symmetric, positive-definite feedback gain matrices is accomplished through the use of multiple-constraint matrix update techniques originally developed for structural identification applications. Two systems were used to illustrate the application: a simple spring-mass system and a planar truss. From these demonstrations, use of this multiple-constraint technique is seen to provide a straightforward approach for computing the low-authority gains.

TLD efficiency calculations for heavy ions: an analytical approach

DOE PAGES

Boscolo, Daria; Scifoni, Emanuele; Carlino, Antonio; ...

2015-12-18

The use of thermoluminescent dosimeters (TLDs) in heavy charged particles’ dosimetry is limited by their non-linear dose response curve and by their response dependence on the radiation quality. Thus, in order to use TLDs with particle beams, a model that can reproduce the behavior of these detectors under different conditions is needed. Here a new, simple and completely analytical algorithm for the calculation of the relative TL-efficiency depending on the ion charge Z and energy E is presented. In addition, the detector response is evaluated starting from the single ion case, where the computed effectiveness values have been compared withmore » experimental data as well as with predictions from a different method. The main advantage of this approach is that, being fully analytical, it is computationally fast and can be efficiently integrated into treatment planning verification tools. In conclusion, the calculated efficiency values have been then implemented in the treatment planning code TRiP98 and dose calculations on a macroscopic target irradiated with an extended carbon ion field have been performed and verified against experimental data.« less

Measurement of Air Flow Characteristics Using Seven-Hole Cone Probes

NASA Technical Reports Server (NTRS)

Takahashi, Timothy T.

1997-01-01

The motivation for this work has been the development of a wake survey system. A seven-hole probe can measure the distribution of static pressure, total pressure, and flow angularity in a wind tunnel environment. The author describes the development of a simple, very efficient algorithm to compute flow properties from probe tip pressures. Its accuracy and applicability to unsteady, turbulent flow are discussed.

Molecular dynamics simulations in hybrid particle-continuum schemes: Pitfalls and caveats

NASA Astrophysics Data System (ADS)

Stalter, S.; Yelash, L.; Emamy, N.; Statt, A.; Hanke, M.; Lukáčová-Medvid'ová, M.; Virnau, P.

2018-03-01

Heterogeneous multiscale methods (HMM) combine molecular accuracy of particle-based simulations with the computational efficiency of continuum descriptions to model flow in soft matter liquids. In these schemes, molecular simulations typically pose a computational bottleneck, which we investigate in detail in this study. We find that it is preferable to simulate many small systems as opposed to a few large systems, and that a choice of a simple isokinetic thermostat is typically sufficient while thermostats such as Lowe-Andersen allow for simulations at elevated viscosity. We discuss suitable choices for time steps and finite-size effects which arise in the limit of very small simulation boxes. We also argue that if colloidal systems are considered as opposed to atomistic systems, the gap between microscopic and macroscopic simulations regarding time and length scales is significantly smaller. We propose a novel reduced-order technique for the coupling to the macroscopic solver, which allows us to approximate a non-linear stress-strain relation efficiently and thus further reduce computational effort of microscopic simulations.

Automated problem scheduling and reduction of synchronization delay effects

NASA Technical Reports Server (NTRS)

Saltz, Joel H.

1987-01-01

It is anticipated that in order to make effective use of many future high performance architectures, programs will have to exhibit at least a medium grained parallelism. A framework is presented for partitioning very sparse triangular systems of linear equations that is designed to produce favorable preformance results in a wide variety of parallel architectures. Efficient methods for solving these systems are of interest because: (1) they provide a useful model problem for use in exploring heuristics for the aggregation, mapping and scheduling of relatively fine grained computations whose data dependencies are specified by directed acrylic graphs, and (2) because such efficient methods can find direct application in the development of parallel algorithms for scientific computation. Simple expressions are derived that describe how to schedule computational work with varying degrees of granularity. The Encore Multimax was used as a hardware simulator to investigate the performance effects of using the partitioning techniques presented in shared memory architectures with varying relative synchronization costs.

A versatile model for soft patchy particles with various patch arrangements.

PubMed

Li, Zhan-Wei; Zhu, You-Liang; Lu, Zhong-Yuan; Sun, Zhao-Yan

2016-01-21

We propose a simple and general mesoscale soft patchy particle model, which can felicitously describe the deformable and surface-anisotropic characteristics of soft patchy particles. This model can be used in dynamics simulations to investigate the aggregation behavior and mechanism of various types of soft patchy particles with tunable number, size, direction, and geometrical arrangement of the patches. To improve the computational efficiency of this mesoscale model in dynamics simulations, we give the simulation algorithm that fits the compute unified device architecture (CUDA) framework of NVIDIA graphics processing units (GPUs). The validation of the model and the performance of the simulations using GPUs are demonstrated by simulating several benchmark systems of soft patchy particles with 1 to 4 patches in a regular geometrical arrangement. Because of its simplicity and computational efficiency, the soft patchy particle model will provide a powerful tool to investigate the aggregation behavior of soft patchy particles, such as patchy micelles, patchy microgels, and patchy dendrimers, over larger spatial and temporal scales.

Vehicle trajectory linearisation to enable efficient optimisation of the constant speed racing line

NASA Astrophysics Data System (ADS)

Timings, Julian P.; Cole, David J.

2012-06-01

A driver model is presented capable of optimising the trajectory of a simple dynamic nonlinear vehicle, at constant forward speed, so that progression along a predefined track is maximised as a function of time. In doing so, the model is able to continually operate a vehicle at its lateral-handling limit, maximising vehicle performance. The technique used forms a part of the solution to the motor racing objective of minimising lap time. A new approach of formulating the minimum lap time problem is motivated by the need for a more computationally efficient and robust tool-set for understanding on-the-limit driving behaviour. This has been achieved through set point-dependent linearisation of the vehicle model and coupling the vehicle-track system using an intrinsic coordinate description. Through this, the geometric vehicle trajectory had been linearised relative to the track reference, leading to new path optimisation algorithm which can be formed as a computationally efficient convex quadratic programming problem.

Cross-label Suppression: a Discriminative and Fast Dictionary Learning with Group Regularization.

PubMed

Wang, Xiudong; Gu, Yuantao

2017-05-10

This paper addresses image classification through learning a compact and discriminative dictionary efficiently. Given a structured dictionary with each atom (columns in the dictionary matrix) related to some label, we propose crosslabel suppression constraint to enlarge the difference among representations for different classes. Meanwhile, we introduce group regularization to enforce representations to preserve label properties of original samples, meaning the representations for the same class are encouraged to be similar. Upon the cross-label suppression, we don't resort to frequently-used `0-norm or `1- norm for coding, and obtain computational efficiency without losing the discriminative power for categorization. Moreover, two simple classification schemes are also developed to take full advantage of the learnt dictionary. Extensive experiments on six data sets including face recognition, object categorization, scene classification, texture recognition and sport action categorization are conducted, and the results show that the proposed approach can outperform lots of recently presented dictionary algorithms on both recognition accuracy and computational efficiency.

Synthetic analog computation in living cells.

PubMed

Daniel, Ramiz; Rubens, Jacob R; Sarpeshkar, Rahul; Lu, Timothy K

2013-05-30

A central goal of synthetic biology is to achieve multi-signal integration and processing in living cells for diagnostic, therapeutic and biotechnology applications. Digital logic has been used to build small-scale circuits, but other frameworks may be needed for efficient computation in the resource-limited environments of cells. Here we demonstrate that synthetic analog gene circuits can be engineered to execute sophisticated computational functions in living cells using just three transcription factors. Such synthetic analog gene circuits exploit feedback to implement logarithmically linear sensing, addition, ratiometric and power-law computations. The circuits exhibit Weber's law behaviour as in natural biological systems, operate over a wide dynamic range of up to four orders of magnitude and can be designed to have tunable transfer functions. Our circuits can be composed to implement higher-order functions that are well described by both intricate biochemical models and simple mathematical functions. By exploiting analog building-block functions that are already naturally present in cells, this approach efficiently implements arithmetic operations and complex functions in the logarithmic domain. Such circuits may lead to new applications for synthetic biology and biotechnology that require complex computations with limited parts, need wide-dynamic-range biosensing or would benefit from the fine control of gene expression.

A space efficient flexible pivot selection approach to evaluate determinant and inverse of a matrix.

PubMed

Jafree, Hafsa Athar; Imtiaz, Muhammad; Inayatullah, Syed; Khan, Fozia Hanif; Nizami, Tajuddin

2014-01-01

This paper presents new simple approaches for evaluating determinant and inverse of a matrix. The choice of pivot selection has been kept arbitrary thus they reduce the error while solving an ill conditioned system. Computation of determinant of a matrix has been made more efficient by saving unnecessary data storage and also by reducing the order of the matrix at each iteration, while dictionary notation [1] has been incorporated for computing the matrix inverse thereby saving unnecessary calculations. These algorithms are highly class room oriented, easy to use and implemented by students. By taking the advantage of flexibility in pivot selection, one may easily avoid development of the fractions by most. Unlike the matrix inversion method [2] and [3], the presented algorithms obviate the use of permutations and inverse permutations.

Evaluation of Preduster in Cement Industry Based on Computational Fluid Dynamic

NASA Astrophysics Data System (ADS)

Septiani, E. L.; Widiyastuti, W.; Djafaar, A.; Ghozali, I.; Pribadi, H. M.

2017-10-01

Ash-laden hot air from clinker in cement industry is being used to reduce water contain in coal, however it may contain large amount of ash even though it was treated by a preduster. This study investigated preduster performance as a cyclone separator in the cement industry by Computational Fluid Dynamic method. In general, the best performance of cyclone is it have relatively high efficiency with the low pressure drop. The most accurate and simple turbulence model, Reynold Average Navier Stokes (RANS), standard k-ε, and combination with Lagrangian model as particles tracking model were used to solve the problem. The measurement in simulation result are flow pattern in the cyclone, pressure outlet and collection efficiency of preduster. The applied model well predicted by comparing with the most accurate empirical model and pressure outlet in experimental measurement.

Multiscale Methods, Parallel Computation, and Neural Networks for Real-Time Computer Vision.

NASA Astrophysics Data System (ADS)

Battiti, Roberto

1990-01-01

This thesis presents new algorithms for low and intermediate level computer vision. The guiding ideas in the presented approach are those of hierarchical and adaptive processing, concurrent computation, and supervised learning. Processing of the visual data at different resolutions is used not only to reduce the amount of computation necessary to reach the fixed point, but also to produce a more accurate estimation of the desired parameters. The presented adaptive multiple scale technique is applied to the problem of motion field estimation. Different parts of the image are analyzed at a resolution that is chosen in order to minimize the error in the coefficients of the differential equations to be solved. Tests with video-acquired images show that velocity estimation is more accurate over a wide range of motion with respect to the homogeneous scheme. In some cases introduction of explicit discontinuities coupled to the continuous variables can be used to avoid propagation of visual information from areas corresponding to objects with different physical and/or kinematic properties. The human visual system uses concurrent computation in order to process the vast amount of visual data in "real -time." Although with different technological constraints, parallel computation can be used efficiently for computer vision. All the presented algorithms have been implemented on medium grain distributed memory multicomputers with a speed-up approximately proportional to the number of processors used. A simple two-dimensional domain decomposition assigns regions of the multiresolution pyramid to the different processors. The inter-processor communication needed during the solution process is proportional to the linear dimension of the assigned domain, so that efficiency is close to 100% if a large region is assigned to each processor. Finally, learning algorithms are shown to be a viable technique to engineer computer vision systems for different applications starting from multiple-purpose modules. In the last part of the thesis a well known optimization method (the Broyden-Fletcher-Goldfarb-Shanno memoryless quasi -Newton method) is applied to simple classification problems and shown to be superior to the "error back-propagation" algorithm for numerical stability, automatic selection of parameters, and convergence properties.

A computational framework for automation of point defect calculations

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

Goyal, Anuj; Gorai, Prashun; Peng, Haowei

We have developed a complete and rigorously validated open-source Python framework to automate point defect calculations using density functional theory. Furthermore, the framework provides an effective and efficient method for defect structure generation, and creation of simple yet customizable workflows to analyze defect calculations. This package provides the capability to compute widely-accepted correction schemes to overcome finite-size effects, including (1) potential alignment, (2) image-charge correction, and (3) band filling correction to shallow defects. Using Si, ZnO and In2O3 as test examples, we demonstrate the package capabilities and validate the methodology.

Probability, statistics, and computational science.

PubMed

Beerenwinkel, Niko; Siebourg, Juliane

2012-01-01

In this chapter, we review basic concepts from probability theory and computational statistics that are fundamental to evolutionary genomics. We provide a very basic introduction to statistical modeling and discuss general principles, including maximum likelihood and Bayesian inference. Markov chains, hidden Markov models, and Bayesian network models are introduced in more detail as they occur frequently and in many variations in genomics applications. In particular, we discuss efficient inference algorithms and methods for learning these models from partially observed data. Several simple examples are given throughout the text, some of which point to models that are discussed in more detail in subsequent chapters.

A computational framework for automation of point defect calculations

DOE PAGES

Goyal, Anuj; Gorai, Prashun; Peng, Haowei; ...

2017-01-13

We have developed a complete and rigorously validated open-source Python framework to automate point defect calculations using density functional theory. Furthermore, the framework provides an effective and efficient method for defect structure generation, and creation of simple yet customizable workflows to analyze defect calculations. This package provides the capability to compute widely-accepted correction schemes to overcome finite-size effects, including (1) potential alignment, (2) image-charge correction, and (3) band filling correction to shallow defects. Using Si, ZnO and In2O3 as test examples, we demonstrate the package capabilities and validate the methodology.

Computation of marginal distributions of peak-heights in electropherograms for analysing single source and mixture STR DNA samples.

PubMed

Cowell, Robert G

2018-05-04

Current models for single source and mixture samples, and probabilistic genotyping software based on them used for analysing STR electropherogram data, assume simple probability distributions, such as the gamma distribution, to model the allelic peak height variability given the initial amount of DNA prior to PCR amplification. Here we illustrate how amplicon number distributions, for a model of the process of sample DNA collection and PCR amplification, may be efficiently computed by evaluating probability generating functions using discrete Fourier transforms. Copyright © 2018 Elsevier B.V. All rights reserved.

Prediction of sound radiated from different practical jet engine inlets

NASA Technical Reports Server (NTRS)

Zinn, B. T.; Meyer, W. L.

1980-01-01

Existing computer codes for calculating the far field radiation patterns surrounding various practical jet engine inlet configurations under different excitation conditions were upgraded. The computer codes were refined and expanded so that they are now more efficient computationally by a factor of about three and they are now capable of producing accurate results up to nondimensional wave numbers of twenty. Computer programs were also developed to help generate accurate geometrical representations of the inlets to be investigated. This data is required as input for the computer programs which calculate the sound fields. This new geometry generating computer program considerably reduces the time required to generate the input data which was one of the most time consuming steps in the process. The results of sample runs using the NASA-Lewis QCSEE inlet are presented and comparison of run times and accuracy are made between the old and upgraded computer codes. The overall accuracy of the computations is determined by comparison of the results of the computations with simple source solutions.

Zero-multipole summation method for efficiently estimating electrostatic interactions in molecular system.

PubMed

Fukuda, Ikuo

2013-11-07

The zero-multipole summation method has been developed to efficiently evaluate the electrostatic Coulombic interactions of a point charge system. This summation prevents the electrically non-neutral multipole states that may artificially be generated by a simple cutoff truncation, which often causes large amounts of energetic noise and significant artifacts. The resulting energy function is represented by a constant term plus a simple pairwise summation, using a damped or undamped Coulombic pair potential function along with a polynomial of the distance between each particle pair. Thus, the implementation is straightforward and enables facile applications to high-performance computations. Any higher-order multipole moment can be taken into account in the neutrality principle, and it only affects the degree and coefficients of the polynomial and the constant term. The lowest and second moments correspond respectively to the Wolf zero-charge scheme and the zero-dipole summation scheme, which was previously proposed. Relationships with other non-Ewald methods are discussed, to validate the current method in their contexts. Good numerical efficiencies were easily obtained in the evaluation of Madelung constants of sodium chloride and cesium chloride crystals.

SASS: A symmetry adapted stochastic search algorithm exploiting site symmetry

NASA Astrophysics Data System (ADS)

Wheeler, Steven E.; Schleyer, Paul v. R.; Schaefer, Henry F.

2007-03-01

A simple symmetry adapted search algorithm (SASS) exploiting point group symmetry increases the efficiency of systematic explorations of complex quantum mechanical potential energy surfaces. In contrast to previously described stochastic approaches, which do not employ symmetry, candidate structures are generated within simple point groups, such as C2, Cs, and C2v. This facilitates efficient sampling of the 3N-6 Pople's dimensional configuration space and increases the speed and effectiveness of quantum chemical geometry optimizations. Pople's concept of framework groups [J. Am. Chem. Soc. 102, 4615 (1980)] is used to partition the configuration space into structures spanning all possible distributions of sets of symmetry equivalent atoms. This provides an efficient means of computing all structures of a given symmetry with minimum redundancy. This approach also is advantageous for generating initial structures for global optimizations via genetic algorithm and other stochastic global search techniques. Application of the SASS method is illustrated by locating 14 low-lying stationary points on the cc-pwCVDZ ROCCSD(T) potential energy surface of Li5H2. The global minimum structure is identified, along with many unique, nonintuitive, energetically favorable isomers.

Computation in generalised probabilisitic theories

NASA Astrophysics Data System (ADS)

Lee, Ciarán M.; Barrett, Jonathan

2015-08-01

From the general difficulty of simulating quantum systems using classical systems, and in particular the existence of an efficient quantum algorithm for factoring, it is likely that quantum computation is intrinsically more powerful than classical computation. At present, the best upper bound known for the power of quantum computation is that {{BQP}}\\subseteq {{AWPP}}, where {{AWPP}} is a classical complexity class (known to be included in {{PP}}, hence {{PSPACE}}). This work investigates limits on computational power that are imposed by simple physical, or information theoretic, principles. To this end, we define a circuit-based model of computation in a class of operationally-defined theories more general than quantum theory, and ask: what is the minimal set of physical assumptions under which the above inclusions still hold? We show that given only an assumption of tomographic locality (roughly, that multipartite states and transformations can be characterized by local measurements), efficient computations are contained in {{AWPP}}. This inclusion still holds even without assuming a basic notion of causality (where the notion is, roughly, that probabilities for outcomes cannot depend on future measurement choices). Following Aaronson, we extend the computational model by allowing post-selection on measurement outcomes. Aaronson showed that the corresponding quantum complexity class, {{PostBQP}}, is equal to {{PP}}. Given only the assumption of tomographic locality, the inclusion in {{PP}} still holds for post-selected computation in general theories. Hence in a world with post-selection, quantum theory is optimal for computation in the space of all operational theories. We then consider whether one can obtain relativized complexity results for general theories. It is not obvious how to define a sensible notion of a computational oracle in the general framework that reduces to the standard notion in the quantum case. Nevertheless, it is possible to define computation relative to a ‘classical oracle’. Then, we show there exists a classical oracle relative to which efficient computation in any theory satisfying the causality assumption does not include {{NP}}.

The efficiency of geophysical adjoint codes generated by automatic differentiation tools

NASA Astrophysics Data System (ADS)

Vlasenko, A. V.; Köhl, A.; Stammer, D.

2016-02-01

The accuracy of numerical models that describe complex physical or chemical processes depends on the choice of model parameters. Estimating an optimal set of parameters by optimization algorithms requires knowledge of the sensitivity of the process of interest to model parameters. Typically the sensitivity computation involves differentiation of the model, which can be performed by applying algorithmic differentiation (AD) tools to the underlying numerical code. However, existing AD tools differ substantially in design, legibility and computational efficiency. In this study we show that, for geophysical data assimilation problems of varying complexity, the performance of adjoint codes generated by the existing AD tools (i) Open_AD, (ii) Tapenade, (iii) NAGWare and (iv) Transformation of Algorithms in Fortran (TAF) can be vastly different. Based on simple test problems, we evaluate the efficiency of each AD tool with respect to computational speed, accuracy of the adjoint, the efficiency of memory usage, and the capability of each AD tool to handle modern FORTRAN 90-95 elements such as structures and pointers, which are new elements that either combine groups of variables or provide aliases to memory addresses, respectively. We show that, while operator overloading tools are the only ones suitable for modern codes written in object-oriented programming languages, their computational efficiency lags behind source transformation by orders of magnitude, rendering the application of these modern tools to practical assimilation problems prohibitive. In contrast, the application of source transformation tools appears to be the most efficient choice, allowing handling even large geophysical data assimilation problems. However, they can only be applied to numerical models written in earlier generations of programming languages. Our study indicates that applying existing AD tools to realistic geophysical problems faces limitations that urgently need to be solved to allow the continuous use of AD tools for solving geophysical problems on modern computer architectures.

Achieving Helicopter Modernization with Advanced Technology Turbine Engines

DTIC Science & Technology

1999-04-01

computer modeling of compressor and turbine aerody- digital engine control ( FADEC ) with manual backup. namics. Modern directionally solidified and single...controlled by a dual RAH.66A M channel FADEC , and features a very simple installation "" Improved Gross Weight and significantly reduced pilot...air separation efficiencies as an "advanced technology" engine. Technological meas- high as 97.5%. The FADEC improves acceleration, ures include but

A Unified Approach to Motion Control of Motion Robots

NASA Technical Reports Server (NTRS)

Seraji, H.

1994-01-01

This paper presents a simple on-line approach for motion control of mobile robots made up of a manipulator arm mounted on a mobile base. The proposed approach is equally applicable to nonholonomic mobile robots, such as rover-mounted manipulators and to holonomic mobile robots such as tracked robots or compound manipulators. The computational efficiency of the proposed control scheme makes it particularly suitable for real-time implementation.

Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback.

PubMed

Orhan, A Emin; Ma, Wei Ji

2017-07-26

Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.

Noise Radiation Of A Strongly Pulsating Tailpipe Exhaust

NASA Astrophysics Data System (ADS)

Peizi, Li; Genhua, Dai; Zhichi, Zhu

1993-11-01

The method of characteristics is used to solve the problem of the propagation of a strongly pulsating flow in an exhaust system tailpipe. For a strongly pulsating exhaust, the flow may shock at the pipe's open end at some point in a pulsating where the flow pressure exceeds its critical value. The method fails if one insists on setting the flow pressure equal to the atmospheric pressure as the pipe end boundary condition. To solve the problem, we set the Mach number equal to 1 as the boundary condition when the flow pressure exceeds its critical value. For a strongly pulsating flow, the fluctuations of flow variables may be much higher than their respective time averages. Therefore, the acoustic radiation method would fail in the computation of the noise radiation from the pipe's open end. We simulate the exhaust flow out of the open end as a simple sound source to compute the noise radiation, which has been successfully applied in reference [1]. The simple sound source strength is proportional to the volume acceleration of exhaust gas. Also computed is the noise radiation from the turbulence of the exhaust flow, as was done in reference [1]. Noise from a reciprocating valve simulator has been treated in detail. The radiation efficiency is very low for the pressure range considered and is about 10 -5. The radiation efficiency coefficient increases with the square of the frequency. Computation of the pipe length dependence of the noise radiation and mass flux allows us to design a suitable length for an aerodynamic noise generator or a reciprocating internal combustion engine. For the former, powerful noise radiation is preferable. For the latter, maximum mass flux is desired because a freer exhaust is preferable.

Free energy calculations: an efficient adaptive biasing potential method.

PubMed

Dickson, Bradley M; Legoll, Frédéric; Lelièvre, Tony; Stoltz, Gabriel; Fleurat-Lessard, Paul

2010-05-06

We develop an efficient sampling and free energy calculation technique within the adaptive biasing potential (ABP) framework. By mollifying the density of states we obtain an approximate free energy and an adaptive bias potential that is computed directly from the population along the coordinates of the free energy. Because of the mollifier, the bias potential is "nonlocal", and its gradient admits a simple analytic expression. A single observation of the reaction coordinate can thus be used to update the approximate free energy at every point within a neighborhood of the observation. This greatly reduces the equilibration time of the adaptive bias potential. This approximation introduces two parameters: strength of mollification and the zero of energy of the bias potential. While we observe that the approximate free energy is a very good estimate of the actual free energy for a large range of mollification strength, we demonstrate that the errors associated with the mollification may be removed via deconvolution. The zero of energy of the bias potential, which is easy to choose, influences the speed of convergence but not the limiting accuracy. This method is simple to apply to free energy or mean force computation in multiple dimensions and does not involve second derivatives of the reaction coordinates, matrix manipulations nor on-the-fly adaptation of parameters. For the alanine dipeptide test case, the new method is found to gain as much as a factor of 10 in efficiency as compared to two basic implementations of the adaptive biasing force methods, and it is shown to be as efficient as well-tempered metadynamics with the postprocess deconvolution giving a clear advantage to the mollified density of states method.

Unsteady three-dimensional thermal field prediction in turbine blades using nonlinear BEM

NASA Technical Reports Server (NTRS)

Martin, Thomas J.; Dulikravich, George S.

1993-01-01

A time-and-space accurate and computationally efficient fully three dimensional unsteady temperature field analysis computer code has been developed for truly arbitrary configurations. It uses boundary element method (BEM) formulation based on an unsteady Green's function approach, multi-point Gaussian quadrature spatial integration on each panel, and a highly clustered time-step integration. The code accepts either temperatures or heat fluxes as boundary conditions that can vary in time on a point-by-point basis. Comparisons of the BEM numerical results and known analytical unsteady results for simple shapes demonstrate very high accuracy and reliability of the algorithm. An example of computed three dimensional temperature and heat flux fields in a realistically shaped internally cooled turbine blade is also discussed.

A fast bottom-up algorithm for computing the cut sets of noncoherent fault trees

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

Corynen, G.C.

1987-11-01

An efficient procedure for finding the cut sets of large fault trees has been developed. Designed to address coherent or noncoherent systems, dependent events, shared or common-cause events, the method - called SHORTCUT - is based on a fast algorithm for transforming a noncoherent tree into a quasi-coherent tree (COHERE), and on a new algorithm for reducing cut sets (SUBSET). To assure sufficient clarity and precision, the procedure is discussed in the language of simple sets, which is also developed in this report. Although the new method has not yet been fully implemented on the computer, we report theoretical worst-casemore » estimates of its computational complexity. 12 refs., 10 figs.« less

Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learning.

PubMed

Xu, Zhoubing; Burke, Ryan P; Lee, Christopher P; Baucom, Rebeccah B; Poulose, Benjamin K; Abramson, Richard G; Landman, Bennett A

2015-08-01

Abdominal segmentation on clinically acquired computed tomography (CT) has been a challenging problem given the inter-subject variance of human abdomens and complex 3-D relationships among organs. Multi-atlas segmentation (MAS) provides a potentially robust solution by leveraging label atlases via image registration and statistical fusion. We posit that the efficiency of atlas selection requires further exploration in the context of substantial registration errors. The selective and iterative method for performance level estimation (SIMPLE) method is a MAS technique integrating atlas selection and label fusion that has proven effective for prostate radiotherapy planning. Herein, we revisit atlas selection and fusion techniques for segmenting 12 abdominal structures using clinically acquired CT. Using a re-derived SIMPLE algorithm, we show that performance on multi-organ classification can be improved by accounting for exogenous information through Bayesian priors (so called context learning). These innovations are integrated with the joint label fusion (JLF) approach to reduce the impact of correlated errors among selected atlases for each organ, and a graph cut technique is used to regularize the combined segmentation. In a study of 100 subjects, the proposed method outperformed other comparable MAS approaches, including majority vote, SIMPLE, JLF, and the Wolz locally weighted vote technique. The proposed technique provides consistent improvement over state-of-the-art approaches (median improvement of 7.0% and 16.2% in DSC over JLF and Wolz, respectively) and moves toward efficient segmentation of large-scale clinically acquired CT data for biomarker screening, surgical navigation, and data mining. Copyright © 2015 Elsevier B.V. All rights reserved.

Towards a Certified Lightweight Array Bound Checker for Java Bytecode

NASA Technical Reports Server (NTRS)

Pichardie, David

2009-01-01

Dynamic array bound checks are crucial elements for the security of a Java Virtual Machines. These dynamic checks are however expensive and several static analysis techniques have been proposed to eliminate explicit bounds checks. Such analyses require advanced numerical and symbolic manipulations that 1) penalize bytecode loading or dynamic compilation, 2) complexify the trusted computing base. Following the Foundational Proof Carrying Code methodology, our goal is to provide a lightweight bytecode verifier for eliminating array bound checks that is both efficient and trustable. In this work, we define a generic relational program analysis for an imperative, stackoriented byte code language with procedures, arrays and global variables and instantiate it with a relational abstract domain as polyhedra. The analysis has automatic inference of loop invariants and method pre-/post-conditions, and efficient checking of analysis results by a simple checker. Invariants, which can be large, can be specialized for proving a safety policy using an automatic pruning technique which reduces their size. The result of the analysis can be checked efficiently by annotating the program with parts of the invariant together with certificates of polyhedral inclusions. The resulting checker is sufficiently simple to be entirely certified within the Coq proof assistant for a simple fragment of the Java bytecode language. During the talk, we will also report on our ongoing effort to scale this approach for the full sequential JVM.

Sensitivity derivatives for advanced CFD algorithm and viscous modelling parameters via automatic differentiation

NASA Technical Reports Server (NTRS)

Green, Lawrence L.; Newman, Perry A.; Haigler, Kara J.

1993-01-01

The computational technique of automatic differentiation (AD) is applied to a three-dimensional thin-layer Navier-Stokes multigrid flow solver to assess the feasibility and computational impact of obtaining exact sensitivity derivatives typical of those needed for sensitivity analyses. Calculations are performed for an ONERA M6 wing in transonic flow with both the Baldwin-Lomax and Johnson-King turbulence models. The wing lift, drag, and pitching moment coefficients are differentiated with respect to two different groups of input parameters. The first group consists of the second- and fourth-order damping coefficients of the computational algorithm, whereas the second group consists of two parameters in the viscous turbulent flow physics modelling. Results obtained via AD are compared, for both accuracy and computational efficiency with the results obtained with divided differences (DD). The AD results are accurate, extremely simple to obtain, and show significant computational advantage over those obtained by DD for some cases.

SLIC superpixels compared to state-of-the-art superpixel methods.

PubMed

Achanta, Radhakrishna; Shaji, Appu; Smith, Kevin; Lucchi, Aurelien; Fua, Pascal; Süsstrunk, Sabine

2012-11-01

Computer vision applications have come to rely increasingly on superpixels in recent years, but it is not always clear what constitutes a good superpixel algorithm. In an effort to understand the benefits and drawbacks of existing methods, we empirically compare five state-of-the-art superpixel algorithms for their ability to adhere to image boundaries, speed, memory efficiency, and their impact on segmentation performance. We then introduce a new superpixel algorithm, simple linear iterative clustering (SLIC), which adapts a k-means clustering approach to efficiently generate superpixels. Despite its simplicity, SLIC adheres to boundaries as well as or better than previous methods. At the same time, it is faster and more memory efficient, improves segmentation performance, and is straightforward to extend to supervoxel generation.

Fast and Accurate Poisson Denoising With Trainable Nonlinear Diffusion.

PubMed

Feng, Wensen; Qiao, Peng; Chen, Yunjin; Wensen Feng; Peng Qiao; Yunjin Chen; Feng, Wensen; Chen, Yunjin; Qiao, Peng

2018-06-01

The degradation of the acquired signal by Poisson noise is a common problem for various imaging applications, such as medical imaging, night vision, and microscopy. Up to now, many state-of-the-art Poisson denoising techniques mainly concentrate on achieving utmost performance, with little consideration for the computation efficiency. Therefore, in this paper we aim to propose an efficient Poisson denoising model with both high computational efficiency and recovery quality. To this end, we exploit the newly developed trainable nonlinear reaction diffusion (TNRD) model which has proven an extremely fast image restoration approach with performance surpassing recent state-of-the-arts. However, the straightforward direct gradient descent employed in the original TNRD-based denoising task is not applicable in this paper. To solve this problem, we resort to the proximal gradient descent method. We retrain the model parameters, including the linear filters and influence functions by taking into account the Poisson noise statistics, and end up with a well-trained nonlinear diffusion model specialized for Poisson denoising. The trained model provides strongly competitive results against state-of-the-art approaches, meanwhile bearing the properties of simple structure and high efficiency. Furthermore, our proposed model comes along with an additional advantage, that the diffusion process is well-suited for parallel computation on graphics processing units (GPUs). For images of size , our GPU implementation takes less than 0.1 s to produce state-of-the-art Poisson denoising performance.

Lane Detection on the iPhone

NASA Astrophysics Data System (ADS)

Ren, Feixiang; Huang, Jinsheng; Terauchi, Mutsuhiro; Jiang, Ruyi; Klette, Reinhard

A robust and efficient lane detection system is an essential component of Lane Departure Warning Systems, which are commonly used in many vision-based Driver Assistance Systems (DAS) in intelligent transportation. Various computation platforms have been proposed in the past few years for the implementation of driver assistance systems (e.g., PC, laptop, integrated chips, PlayStation, and so on). In this paper, we propose a new platform for the implementation of lane detection, which is based on a mobile phone (the iPhone). Due to physical limitations of the iPhone w.r.t. memory and computing power, a simple and efficient lane detection algorithm using a Hough transform is developed and implemented on the iPhone, as existing algorithms developed based on the PC platform are not suitable for mobile phone devices (currently). Experiments of the lane detection algorithm are made both on PC and on iPhone.

3D Space Radiation Transport in a Shielded ICRU Tissue Sphere

NASA Technical Reports Server (NTRS)

Wilson, John W.; Slaba, Tony C.; Badavi, Francis F.; Reddell, Brandon D.; Bahadori, Amir A.

2014-01-01

A computationally efficient 3DHZETRN code capable of simulating High Charge (Z) and Energy (HZE) and light ions (including neutrons) under space-like boundary conditions with enhanced neutron and light ion propagation was recently developed for a simple homogeneous shield object. Monte Carlo benchmarks were used to verify the methodology in slab and spherical geometry, and the 3D corrections were shown to provide significant improvement over the straight-ahead approximation in some cases. In the present report, the new algorithms with well-defined convergence criteria are extended to inhomogeneous media within a shielded tissue slab and a shielded tissue sphere and tested against Monte Carlo simulation to verify the solution methods. The 3D corrections are again found to more accurately describe the neutron and light ion fluence spectra as compared to the straight-ahead approximation. These computationally efficient methods provide a basis for software capable of space shield analysis and optimization.

Efficient reliability analysis of structures with the rotational quasi-symmetric point- and the maximum entropy methods

NASA Astrophysics Data System (ADS)

Xu, Jun; Dang, Chao; Kong, Fan

2017-10-01

This paper presents a new method for efficient structural reliability analysis. In this method, a rotational quasi-symmetric point method (RQ-SPM) is proposed for evaluating the fractional moments of the performance function. Then, the derivation of the performance function's probability density function (PDF) is carried out based on the maximum entropy method in which constraints are specified in terms of fractional moments. In this regard, the probability of failure can be obtained by a simple integral over the performance function's PDF. Six examples, including a finite element-based reliability analysis and a dynamic system with strong nonlinearity, are used to illustrate the efficacy of the proposed method. All the computed results are compared with those by Monte Carlo simulation (MCS). It is found that the proposed method can provide very accurate results with low computational effort.

Efficient parallel architecture for highly coupled real-time linear system applications

NASA Technical Reports Server (NTRS)

Carroll, Chester C.; Homaifar, Abdollah; Barua, Soumavo

1988-01-01

A systematic procedure is developed for exploiting the parallel constructs of computation in a highly coupled, linear system application. An overall top-down design approach is adopted. Differential equations governing the application under consideration are partitioned into subtasks on the basis of a data flow analysis. The interconnected task units constitute a task graph which has to be computed in every update interval. Multiprocessing concepts utilizing parallel integration algorithms are then applied for efficient task graph execution. A simple scheduling routine is developed to handle task allocation while in the multiprocessor mode. Results of simulation and scheduling are compared on the basis of standard performance indices. Processor timing diagrams are developed on the basis of program output accruing to an optimal set of processors. Basic architectural attributes for implementing the system are discussed together with suggestions for processing element design. Emphasis is placed on flexible architectures capable of accommodating widely varying application specifics.

Efficient computation paths for the systematic analysis of sensitivities

NASA Astrophysics Data System (ADS)

Greppi, Paolo; Arato, Elisabetta

2013-01-01

A systematic sensitivity analysis requires computing the model on all points of a multi-dimensional grid covering the domain of interest, defined by the ranges of variability of the inputs. The issues to efficiently perform such analyses on algebraic models are handling solution failures within and close to the feasible region and minimizing the total iteration count. Scanning the domain in the obvious order is sub-optimal in terms of total iterations and is likely to cause many solution failures. The problem of choosing a better order can be translated geometrically into finding Hamiltonian paths on certain grid graphs. This work proposes two paths, one based on a mixed-radix Gray code and the other, a quasi-spiral path, produced by a novel heuristic algorithm. Some simple, easy-to-visualize examples are presented, followed by performance results for the quasi-spiral algorithm and the practical application of the different paths in a process simulation tool.

Manyscale Computing for Sensor Processing in Support of Space Situational Awareness

NASA Astrophysics Data System (ADS)

Schmalz, M.; Chapman, W.; Hayden, E.; Sahni, S.; Ranka, S.

2014-09-01

Increasing image and signal data burden associated with sensor data processing in support of space situational awareness implies continuing computational throughput growth beyond the petascale regime. In addition to growing applications data burden and diversity, the breadth, diversity and scalability of high performance computing architectures and their various organizations challenge the development of a single, unifying, practicable model of parallel computation. Therefore, models for scalable parallel processing have exploited architectural and structural idiosyncrasies, yielding potential misapplications when legacy programs are ported among such architectures. In response to this challenge, we have developed a concise, efficient computational paradigm and software called Manyscale Computing to facilitate efficient mapping of annotated application codes to heterogeneous parallel architectures. Our theory, algorithms, software, and experimental results support partitioning and scheduling of application codes for envisioned parallel architectures, in terms of work atoms that are mapped (for example) to threads or thread blocks on computational hardware. Because of the rigor, completeness, conciseness, and layered design of our manyscale approach, application-to-architecture mapping is feasible and scalable for architectures at petascales, exascales, and above. Further, our methodology is simple, relying primarily on a small set of primitive mapping operations and support routines that are readily implemented on modern parallel processors such as graphics processing units (GPUs) and hybrid multi-processors (HMPs). In this paper, we overview the opportunities and challenges of manyscale computing for image and signal processing in support of space situational awareness applications. We discuss applications in terms of a layered hardware architecture (laboratory > supercomputer > rack > processor > component hierarchy). Demonstration applications include performance analysis and results in terms of execution time as well as storage, power, and energy consumption for bus-connected and/or networked architectures. The feasibility of the manyscale paradigm is demonstrated by addressing four principal challenges: (1) architectural/structural diversity, parallelism, and locality, (2) masking of I/O and memory latencies, (3) scalability of design as well as implementation, and (4) efficient representation/expression of parallel applications. Examples will demonstrate how manyscale computing helps solve these challenges efficiently on real-world computing systems.

Tunable, Flexible and Efficient Optimization of Control Pulses for Superconducting Qubits, part I - Theory

NASA Astrophysics Data System (ADS)

Machnes, Shai; AsséMat, Elie; Tannor, David; Wilhelm, Frank

Quantum computation places very stringent demands on gate fidelities, and experimental implementations require both the controls and the resultant dynamics to conform to hardware-specific ansatzes and constraints. Superconducting qubits present the additional requirement that pulses have simple parametrizations, so they can be further calibrated in the experiment, to compensate for uncertainties in system characterization. We present a novel, conceptually simple and easy-to-implement gradient-based optimal control algorithm, GOAT, which satisfies all the above requirements. In part II we shall demonstrate the algorithm's capabilities, by using GOAT to optimize fast high-accuracy pulses for two leading superconducting qubits architectures - Xmons and IBM's flux-tunable couplers.

Optimal protocols for slowly driven quantum systems.

PubMed

Zulkowski, Patrick R; DeWeese, Michael R

2015-09-01

The design of efficient quantum information processing will rely on optimal nonequilibrium transitions of driven quantum systems. Building on a recently developed geometric framework for computing optimal protocols for classical systems driven in finite time, we construct a general framework for optimizing the average information entropy for driven quantum systems. Geodesics on the parameter manifold endowed with a positive semidefinite metric correspond to protocols that minimize the average information entropy production in finite time. We use this framework to explicitly compute the optimal entropy production for a simple two-state quantum system coupled to a heat bath of bosonic oscillators, which has applications to quantum annealing.

Adjoint shape optimization for fluid-structure interaction of ducted flows

NASA Astrophysics Data System (ADS)

Heners, J. P.; Radtke, L.; Hinze, M.; Düster, A.

2018-03-01

Based on the coupled problem of time-dependent fluid-structure interaction, equations for an appropriate adjoint problem are derived by the consequent use of the formal Lagrange calculus. Solutions of both primal and adjoint equations are computed in a partitioned fashion and enable the formulation of a surface sensitivity. This sensitivity is used in the context of a steepest descent algorithm for the computation of the required gradient of an appropriate cost functional. The efficiency of the developed optimization approach is demonstrated by minimization of the pressure drop in a simple two-dimensional channel flow and in a three-dimensional ducted flow surrounded by a thin-walled structure.

Robust efficient estimation of heart rate pulse from video.

PubMed

Xu, Shuchang; Sun, Lingyun; Rohde, Gustavo Kunde

2014-04-01

We describe a simple but robust algorithm for estimating the heart rate pulse from video sequences containing human skin in real time. Based on a model of light interaction with human skin, we define the change of blood concentration due to arterial pulsation as a pixel quotient in log space, and successfully use the derived signal for computing the pulse heart rate. Various experiments with different cameras, different illumination condition, and different skin locations were conducted to demonstrate the effectiveness and robustness of the proposed algorithm. Examples computed with normal illumination show the algorithm is comparable with pulse oximeter devices both in accuracy and sensitivity.

Robust efficient estimation of heart rate pulse from video

PubMed Central

Xu, Shuchang; Sun, Lingyun; Rohde, Gustavo Kunde

2014-01-01

We describe a simple but robust algorithm for estimating the heart rate pulse from video sequences containing human skin in real time. Based on a model of light interaction with human skin, we define the change of blood concentration due to arterial pulsation as a pixel quotient in log space, and successfully use the derived signal for computing the pulse heart rate. Various experiments with different cameras, different illumination condition, and different skin locations were conducted to demonstrate the effectiveness and robustness of the proposed algorithm. Examples computed with normal illumination show the algorithm is comparable with pulse oximeter devices both in accuracy and sensitivity. PMID:24761294

A universal quantum module for quantum communication, computation, and metrology

NASA Astrophysics Data System (ADS)

Hanks, Michael; Lo Piparo, Nicolò; Trupke, Michael; Schmiedmayer, Jorg; Munro, William J.; Nemoto, Kae

2017-08-01

In this work, we describe a simple module that could be ubiquitous for quantum information based applications. The basic modules comprises a single NV- center in diamond embedded in an optical cavity, where the cavity mediates interactions between photons and the electron spin (enabling entanglement distribution and efficient readout), while the nuclear spins constitutes a long-lived quantum memories capable of storing and processing quantum information. We discuss how a network of connected modules can be used for distributed metrology, communication and computation applications. Finally, we investigate the possible use of alternative diamond centers (SiV/GeV) within the module and illustrate potential advantages.

Dynamic Deployment Simulations of Inflatable Space Structures

NASA Technical Reports Server (NTRS)

Wang, John T.

2005-01-01

The feasibility of using Control Volume (CV) method and the Arbitrary Lagrangian Eulerian (ALE) method in LSDYNA to simulate the dynamic deployment of inflatable space structures is investigated. The CV and ALE methods were used to predict the inflation deployments of three folded tube configurations. The CV method was found to be a simple and computationally efficient method that may be adequate for modeling slow inflation deployment sine the inertia of the inflation gas can be neglected. The ALE method was found to be very computationally intensive since it involves the solving of three conservative equations of fluid as well as dealing with complex fluid structure interactions.

Computer Vision Photogrammetry for Underwater Archaeological Site Recording in a Low-Visibility Environment

NASA Astrophysics Data System (ADS)

Van Damme, T.

2015-04-01

Computer Vision Photogrammetry allows archaeologists to accurately record underwater sites in three dimensions using simple twodimensional picture or video sequences, automatically processed in dedicated software. In this article, I share my experience in working with one such software package, namely PhotoScan, to record a Dutch shipwreck site. In order to demonstrate the method's reliability and flexibility, the site in question is reconstructed from simple GoPro footage, captured in low-visibility conditions. Based on the results of this case study, Computer Vision Photogrammetry compares very favourably to manual recording methods both in recording efficiency, and in the quality of the final results. In a final section, the significance of Computer Vision Photogrammetry is then assessed from a historical perspective, by placing the current research in the wider context of about half a century of successful use of Analytical and later Digital photogrammetry in the field of underwater archaeology. I conclude that while photogrammetry has been used in our discipline for several decades now, for various reasons the method was only ever used by a relatively small percentage of projects. This is likely to change in the near future since, compared to the `traditional' photogrammetry approaches employed in the past, today Computer Vision Photogrammetry is easier to use, more reliable and more affordable than ever before, while at the same time producing more accurate and more detailed three-dimensional results.

Computational complexity of ecological and evolutionary spatial dynamics

PubMed Central

Ibsen-Jensen, Rasmus; Chatterjee, Krishnendu; Nowak, Martin A.

2015-01-01

There are deep, yet largely unexplored, connections between computer science and biology. Both disciplines examine how information proliferates in time and space. Central results in computer science describe the complexity of algorithms that solve certain classes of problems. An algorithm is deemed efficient if it can solve a problem in polynomial time, which means the running time of the algorithm is a polynomial function of the length of the input. There are classes of harder problems for which the fastest possible algorithm requires exponential time. Another criterion is the space requirement of the algorithm. There is a crucial distinction between algorithms that can find a solution, verify a solution, or list several distinct solutions in given time and space. The complexity hierarchy that is generated in this way is the foundation of theoretical computer science. Precise complexity results can be notoriously difficult. The famous question whether polynomial time equals nondeterministic polynomial time (i.e., P = NP) is one of the hardest open problems in computer science and all of mathematics. Here, we consider simple processes of ecological and evolutionary spatial dynamics. The basic question is: What is the probability that a new invader (or a new mutant) will take over a resident population? We derive precise complexity results for a variety of scenarios. We therefore show that some fundamental questions in this area cannot be answered by simple equations (assuming that P is not equal to NP). PMID:26644569

A Review of Hemolysis Prediction Models for Computational Fluid Dynamics.

PubMed

Yu, Hai; Engel, Sebastian; Janiga, Gábor; Thévenin, Dominique

2017-07-01

Flow-induced hemolysis is a crucial issue for many biomedical applications; in particular, it is an essential issue for the development of blood-transporting devices such as left ventricular assist devices, and other types of blood pumps. In order to estimate red blood cell (RBC) damage in blood flows, many models have been proposed in the past. Most models have been validated by their respective authors. However, the accuracy and the validity range of these models remains unclear. In this work, the most established hemolysis models compatible with computational fluid dynamics of full-scale devices are described and assessed by comparing two selected reference experiments: a simple rheometric flow and a more complex hemodialytic flow through a needle. The quantitative comparisons show very large deviations concerning hemolysis predictions, depending on the model and model parameter. In light of the current results, two simple power-law models deliver the best compromise between computational efficiency and obtained accuracy. Finally, hemolysis has been computed in an axial blood pump. The reconstructed geometry of a HeartMate II shows that hemolysis occurs mainly at the tip and leading edge of the rotor blades, as well as at the leading edge of the diffusor vanes. © 2017 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

An efficient algorithm for generating random number pairs drawn from a bivariate normal distribution

NASA Technical Reports Server (NTRS)

Campbell, C. W.

1983-01-01

An efficient algorithm for generating random number pairs from a bivariate normal distribution was developed. Any desired value of the two means, two standard deviations, and correlation coefficient can be selected. Theoretically the technique is exact and in practice its accuracy is limited only by the quality of the uniform distribution random number generator, inaccuracies in computer function evaluation, and arithmetic. A FORTRAN routine was written to check the algorithm and good accuracy was obtained. Some small errors in the correlation coefficient were observed to vary in a surprisingly regular manner. A simple model was developed which explained the qualities aspects of the errors.

The indexed time table approach for planning and acting

NASA Technical Reports Server (NTRS)

Ghallab, Malik; Alaoui, Amine Mounir

1989-01-01

A representation is discussed of symbolic temporal relations, called IxTeT, that is both powerful enough at the reasoning level for tasks such as plan generation, refinement and modification, and efficient enough for dealing with real time constraints in action monitoring and reactive planning. Such representation for dealing with time is needed in a teleoperated space robot. After a brief survey of known approaches, the proposed representation shows its computational efficiency for managing a large data base of temporal relations. Reactive planning with IxTeT is described and exemplified through the problem of mission planning and modification for a simple surveying satellite.

A Computational Efficient Physics Based Methodology for Modeling Ceramic Matrix Composites (Preprint)

DTIC Science & Technology

2011-11-01

elastic range, and with some simple forms of progressing damage . However, a general physics-based methodology to assess the initial and lifetime... damage evolution in the RVE for all possible load histories. Microstructural data on initial configuration and damage progression in CMCs were...the damaged elements will have changed, hence, a progressive damage model. The crack opening for each crack type in each element is stored as a

Solving Constraint Satisfaction Problems with Networks of Spiking Neurons

PubMed Central

Jonke, Zeno; Habenschuss, Stefan; Maass, Wolfgang

2016-01-01

Network of neurons in the brain apply—unlike processors in our current generation of computer hardware—an event-based processing strategy, where short pulses (spikes) are emitted sparsely by neurons to signal the occurrence of an event at a particular point in time. Such spike-based computations promise to be substantially more power-efficient than traditional clocked processing schemes. However, it turns out to be surprisingly difficult to design networks of spiking neurons that can solve difficult computational problems on the level of single spikes, rather than rates of spikes. We present here a new method for designing networks of spiking neurons via an energy function. Furthermore, we show how the energy function of a network of stochastically firing neurons can be shaped in a transparent manner by composing the networks of simple stereotypical network motifs. We show that this design approach enables networks of spiking neurons to produce approximate solutions to difficult (NP-hard) constraint satisfaction problems from the domains of planning/optimization and verification/logical inference. The resulting networks employ noise as a computational resource. Nevertheless, the timing of spikes plays an essential role in their computations. Furthermore, networks of spiking neurons carry out for the Traveling Salesman Problem a more efficient stochastic search for good solutions compared with stochastic artificial neural networks (Boltzmann machines) and Gibbs sampling. PMID:27065785

Simple extrapolation method to predict the electronic structure of conjugated polymers from calculations on oligomers

DOE PAGES

Larsen, Ross E.

2016-04-12

In this study, we introduce two simple tight-binding models, which we call fragment frontier orbital extrapolations (FFOE), to extrapolate important electronic properties to the polymer limit using electronic structure calculations on only a few small oligomers. In particular, we demonstrate by comparison to explicit density functional theory calculations that for long oligomers the energies of the highest occupied molecular orbital (HOMO), the lowest unoccupied molecular orbital (LUMO), and of the first electronic excited state are accurately described as a function of number of repeat units by a simple effective Hamiltonian parameterized from electronic structure calculations on monomers, dimers and, optionally,more » tetramers. For the alternating copolymer materials that currently comprise some of the most efficient polymer organic photovoltaic devices one can use these simple but rigorous models to extrapolate computed properties to the polymer limit based on calculations on a small number of low-molecular-weight oligomers.« less

Implementation and performance of FDPS: a framework for developing parallel particle simulation codes

NASA Astrophysics Data System (ADS)

Iwasawa, Masaki; Tanikawa, Ataru; Hosono, Natsuki; Nitadori, Keigo; Muranushi, Takayuki; Makino, Junichiro

2016-08-01

We present the basic idea, implementation, measured performance, and performance model of FDPS (Framework for Developing Particle Simulators). FDPS is an application-development framework which helps researchers to develop simulation programs using particle methods for large-scale distributed-memory parallel supercomputers. A particle-based simulation program for distributed-memory parallel computers needs to perform domain decomposition, exchange of particles which are not in the domain of each computing node, and gathering of the particle information in other nodes which are necessary for interaction calculation. Also, even if distributed-memory parallel computers are not used, in order to reduce the amount of computation, algorithms such as the Barnes-Hut tree algorithm or the Fast Multipole Method should be used in the case of long-range interactions. For short-range interactions, some methods to limit the calculation to neighbor particles are required. FDPS provides all of these functions which are necessary for efficient parallel execution of particle-based simulations as "templates," which are independent of the actual data structure of particles and the functional form of the particle-particle interaction. By using FDPS, researchers can write their programs with the amount of work necessary to write a simple, sequential and unoptimized program of O(N2) calculation cost, and yet the program, once compiled with FDPS, will run efficiently on large-scale parallel supercomputers. A simple gravitational N-body program can be written in around 120 lines. We report the actual performance of these programs and the performance model. The weak scaling performance is very good, and almost linear speed-up was obtained for up to the full system of the K computer. The minimum calculation time per timestep is in the range of 30 ms (N = 107) to 300 ms (N = 109). These are currently limited by the time for the calculation of the domain decomposition and communication necessary for the interaction calculation. We discuss how we can overcome these bottlenecks.

Elastic constants from microscopic strain fluctuations

PubMed

Sengupta; Nielaba; Rao; Binder

2000-02-01

Fluctuations of the instantaneous local Lagrangian strain epsilon(ij)(r,t), measured with respect to a static "reference" lattice, are used to obtain accurate estimates of the elastic constants of model solids from atomistic computer simulations. The measured strains are systematically coarse-grained by averaging them within subsystems (of size L(b)) of a system (of total size L) in the canonical ensemble. Using a simple finite size scaling theory we predict the behavior of the fluctuations as a function of L(b)/L and extract elastic constants of the system in the thermodynamic limit at nonzero temperature. Our method is simple to implement, efficient, and general enough to be able to handle a wide class of model systems, including those with singular potentials without any essential modification. We illustrate the technique by computing isothermal elastic constants of "hard" and "soft" disk triangular solids in two dimensions from Monte Carlo and molecular dynamics simulations. We compare our results with those from earlier simulations and theory.

A simple low-computation-intensity model for approximating the distribution function of a sum of non-identical lognormals for financial applications

NASA Astrophysics Data System (ADS)

Messica, A.

2016-10-01

The probability distribution function of a weighted sum of non-identical lognormal random variables is required in various fields of science and engineering and specifically in finance for portfolio management as well as exotic options valuation. Unfortunately, it has no known closed form and therefore has to be approximated. Most of the approximations presented to date are complex as well as complicated for implementation. This paper presents a simple, and easy to implement, approximation method via modified moments matching and a polynomial asymptotic series expansion correction for a central limit theorem of a finite sum. The method results in an intuitively-appealing and computation-efficient approximation for a finite sum of lognormals of at least ten summands and naturally improves as the number of summands increases. The accuracy of the method is tested against the results of Monte Carlo simulationsand also compared against the standard central limit theorem andthe commonly practiced Markowitz' portfolio equations.

Simple, Efficient Estimators of Treatment Effects in Randomized Trials Using Generalized Linear Models to Leverage Baseline Variables

PubMed Central

Rosenblum, Michael; van der Laan, Mark J.

2010-01-01

Models, such as logistic regression and Poisson regression models, are often used to estimate treatment effects in randomized trials. These models leverage information in variables collected before randomization, in order to obtain more precise estimates of treatment effects. However, there is the danger that model misspecification will lead to bias. We show that certain easy to compute, model-based estimators are asymptotically unbiased even when the working model used is arbitrarily misspecified. Furthermore, these estimators are locally efficient. As a special case of our main result, we consider a simple Poisson working model containing only main terms; in this case, we prove the maximum likelihood estimate of the coefficient corresponding to the treatment variable is an asymptotically unbiased estimator of the marginal log rate ratio, even when the working model is arbitrarily misspecified. This is the log-linear analog of ANCOVA for linear models. Our results demonstrate one application of targeted maximum likelihood estimation. PMID:20628636

Proportional Topology Optimization: A New Non-Sensitivity Method for Solving Stress Constrained and Minimum Compliance Problems and Its Implementation in MATLAB

PubMed Central

Biyikli, Emre; To, Albert C.

2015-01-01

A new topology optimization method called the Proportional Topology Optimization (PTO) is presented. As a non-sensitivity method, PTO is simple to understand, easy to implement, and is also efficient and accurate at the same time. It is implemented into two MATLAB programs to solve the stress constrained and minimum compliance problems. Descriptions of the algorithm and computer programs are provided in detail. The method is applied to solve three numerical examples for both types of problems. The method shows comparable efficiency and accuracy with an existing optimality criteria method which computes sensitivities. Also, the PTO stress constrained algorithm and minimum compliance algorithm are compared by feeding output from one algorithm to the other in an alternative manner, where the former yields lower maximum stress and volume fraction but higher compliance compared to the latter. Advantages and disadvantages of the proposed method and future works are discussed. The computer programs are self-contained and publicly shared in the website www.ptomethod.org. PMID:26678849

Development and application of an analysis of axisymmetric body effects on helicopter rotor aerodynamics using modified slender body theory

NASA Technical Reports Server (NTRS)

Yamauchi, G.; Johnson, W.

1984-01-01

A computationally efficient body analysis designed to couple with a comprehensive helicopter analysis is developed in order to calculate the body-induced aerodynamic effects on rotor performance and loads. A modified slender body theory is used as the body model. With the objective of demonstrating the accuracy, efficiency, and application of the method, the analysis at this stage is restricted to axisymmetric bodies at zero angle of attack. By comparing with results from an exact analysis for simple body shapes, it is found that the modified slender body theory provides an accurate potential flow solution for moderately thick bodies, with only a 10%-20% increase in computational effort over that of an isolated rotor analysis. The computational ease of this method provides a means for routine assessment of body-induced effects on a rotor. Results are given for several configurations that typify those being used in the Ames 40- by 80-Foot Wind Tunnel and in the rotor-body aerodynamic interference tests being conducted at Ames. A rotor-hybrid airship configuration is also analyzed.

Computationally efficient stochastic optimization using multiple realizations

NASA Astrophysics Data System (ADS)

Bayer, P.; Bürger, C. M.; Finkel, M.

2008-02-01

The presented study is concerned with computationally efficient methods for solving stochastic optimization problems involving multiple equally probable realizations of uncertain parameters. A new and straightforward technique is introduced that is based on dynamically ordering the stack of realizations during the search procedure. The rationale is that a small number of critical realizations govern the output of a reliability-based objective function. By utilizing a problem, which is typical to designing a water supply well field, several variants of this "stack ordering" approach are tested. The results are statistically assessed, in terms of optimality and nominal reliability. This study demonstrates that the simple ordering of a given number of 500 realizations while applying an evolutionary search algorithm can save about half of the model runs without compromising the optimization procedure. More advanced variants of stack ordering can, if properly configured, save up to more than 97% of the computational effort that would be required if the entire number of realizations were considered. The findings herein are promising for similar problems of water management and reliability-based design in general, and particularly for non-convex problems that require heuristic search techniques.

Efficient and accurate two-scale FE-FFT-based prediction of the effective material behavior of elasto-viscoplastic polycrystals

NASA Astrophysics Data System (ADS)

Kochmann, Julian; Wulfinghoff, Stephan; Ehle, Lisa; Mayer, Joachim; Svendsen, Bob; Reese, Stefanie

2018-06-01

Recently, two-scale FE-FFT-based methods (e.g., Spahn et al. in Comput Methods Appl Mech Eng 268:871-883, 2014; Kochmann et al. in Comput Methods Appl Mech Eng 305:89-110, 2016) have been proposed to predict the microscopic and overall mechanical behavior of heterogeneous materials. The purpose of this work is the extension to elasto-viscoplastic polycrystals, efficient and robust Fourier solvers and the prediction of micromechanical fields during macroscopic deformation processes. Assuming scale separation, the macroscopic problem is solved using the finite element method. The solution of the microscopic problem, which is embedded as a periodic unit cell (UC) in each macroscopic integration point, is found by employing fast Fourier transforms, fixed-point and Newton-Krylov methods. The overall material behavior is defined by the mean UC response. In order to ensure spatially converged micromechanical fields as well as feasible overall CPU times, an efficient but simple solution strategy for two-scale simulations is proposed. As an example, the constitutive behavior of 42CrMo4 steel is predicted during macroscopic three-point bending tests.

Quantum dynamical framework for Brownian heat engines

NASA Astrophysics Data System (ADS)

Agarwal, G. S.; Chaturvedi, S.

2013-07-01

We present a self-contained formalism modeled after the Brownian motion of a quantum harmonic oscillator for describing the performance of microscopic Brownian heat engines such as Carnot, Stirling, and Otto engines. Our theory, besides reproducing the standard thermodynamics results in the steady state, enables us to study the role dissipation plays in determining the efficiency of Brownian heat engines under actual laboratory conditions. In particular, we analyze in detail the dynamics associated with decoupling a system in equilibrium with one bath and recoupling it to another bath and obtain exact analytical results, which are shown to have significant ramifications on the efficiencies of engines involving such a step. We also develop a simple yet powerful technique for computing corrections to the steady state results arising from finite operation time and use it to arrive at the thermodynamic complementarity relations for various operating conditions and also to compute the efficiencies of the three engines cited above at maximum power. Some of the methods and exactly solvable models presented here are interesting in their own right and could find useful applications in other contexts as well.

Efficient and accurate two-scale FE-FFT-based prediction of the effective material behavior of elasto-viscoplastic polycrystals

NASA Astrophysics Data System (ADS)

Kochmann, Julian; Wulfinghoff, Stephan; Ehle, Lisa; Mayer, Joachim; Svendsen, Bob; Reese, Stefanie

2017-09-01

Recently, two-scale FE-FFT-based methods (e.g., Spahn et al. in Comput Methods Appl Mech Eng 268:871-883, 2014; Kochmann et al. in Comput Methods Appl Mech Eng 305:89-110, 2016) have been proposed to predict the microscopic and overall mechanical behavior of heterogeneous materials. The purpose of this work is the extension to elasto-viscoplastic polycrystals, efficient and robust Fourier solvers and the prediction of micromechanical fields during macroscopic deformation processes. Assuming scale separation, the macroscopic problem is solved using the finite element method. The solution of the microscopic problem, which is embedded as a periodic unit cell (UC) in each macroscopic integration point, is found by employing fast Fourier transforms, fixed-point and Newton-Krylov methods. The overall material behavior is defined by the mean UC response. In order to ensure spatially converged micromechanical fields as well as feasible overall CPU times, an efficient but simple solution strategy for two-scale simulations is proposed. As an example, the constitutive behavior of 42CrMo4 steel is predicted during macroscopic three-point bending tests.

An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks

PubMed Central

Pirbhulal, Sandeep; Zhang, Heye; Mukhopadhyay, Subhas Chandra; Li, Chunyue; Wang, Yumei; Li, Guanglin; Wu, Wanqing; Zhang, Yuan-Ting

2015-01-01

Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption. PMID:26131666

An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks.

PubMed

Pirbhulal, Sandeep; Zhang, Heye; Mukhopadhyay, Subhas Chandra; Li, Chunyue; Wang, Yumei; Li, Guanglin; Wu, Wanqing; Zhang, Yuan-Ting

2015-06-26

Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.

A Development of Lightweight Grid Interface

NASA Astrophysics Data System (ADS)

Iwai, G.; Kawai, Y.; Sasaki, T.; Watase, Y.

2011-12-01

In order to help a rapid development of Grid/Cloud aware applications, we have developed API to abstract the distributed computing infrastructures based on SAGA (A Simple API for Grid Applications). SAGA, which is standardized in the OGF (Open Grid Forum), defines API specifications to access distributed computing infrastructures, such as Grid, Cloud and local computing resources. The Universal Grid API (UGAPI), which is a set of command line interfaces (CLI) and APIs, aims to offer simpler API to combine several SAGA interfaces with richer functionalities. These CLIs of the UGAPI offer typical functionalities required by end users for job management and file access to the different distributed computing infrastructures as well as local computing resources. We have also built a web interface for the particle therapy simulation and demonstrated the large scale calculation using the different infrastructures at the same time. In this paper, we would like to present how the web interface based on UGAPI and SAGA achieve more efficient utilization of computing resources over the different infrastructures with technical details and practical experiences.

Cloud Computing for the Grid: GridControl: A Software Platform to Support the Smart Grid

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

None

GENI Project: Cornell University is creating a new software platform for grid operators called GridControl that will utilize cloud computing to more efficiently control the grid. In a cloud computing system, there are minimal hardware and software demands on users. The user can tap into a network of computers that is housed elsewhere (the cloud) and the network runs computer applications for the user. The user only needs interface software to access all of the cloud’s data resources, which can be as simple as a web browser. Cloud computing can reduce costs, facilitate innovation through sharing, empower users, and improvemore » the overall reliability of a dispersed system. Cornell’s GridControl will focus on 4 elements: delivering the state of the grid to users quickly and reliably; building networked, scalable grid-control software; tailoring services to emerging smart grid uses; and simulating smart grid behavior under various conditions.« less

An approach to multivariable control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

The paper presents simple schemes for multivariable control of multiple-joint robot manipulators in joint and Cartesian coordinates. The joint control scheme consists of two independent multivariable feedforward and feedback controllers. The feedforward controller is the minimal inverse of the linearized model of robot dynamics and contains only proportional-double-derivative (PD2) terms - implying feedforward from the desired position, velocity and acceleration. This controller ensures that the manipulator joint angles track any reference trajectories. The feedback controller is of proportional-integral-derivative (PID) type and is designed to achieve pole placement. This controller reduces any initial tracking error to zero as desired and also ensures that robust steady-state tracking of step-plus-exponential trajectories is achieved by the joint angles. Simple and explicit expressions of computation of the feedforward and feedback gains are obtained based on the linearized model of robot dynamics. This leads to computationally efficient schemes for either on-line gain computation or off-line gain scheduling to account for variations in the linearized robot model due to changes in the operating point. The joint control scheme is extended to direct control of the end-effector motion in Cartesian space. Simulation results are given for illustration.

Quantitative vibro-acoustography of tissue-like objects by measurement of resonant modes

NASA Astrophysics Data System (ADS)

Mazumder, Dibbyan; Umesh, Sharath; Mohan Vasu, Ram; Roy, Debasish; Kanhirodan, Rajan; Asokan, Sundarrajan

2017-01-01

We demonstrate a simple and computationally efficient method to recover the shear modulus pertaining to the focal volume of an ultrasound transducer from the measured vibro-acoustic spectral peaks. A model that explains the transport of local deformation information with the acoustic wave acting as a carrier is put forth. It is also shown that the peaks correspond to the natural frequencies of vibration of the focal volume, which may be readily computed by solving an eigenvalue problem associated with the vibrating region. Having measured the first natural frequency with a fibre Bragg grating sensor, and armed with an expedient means of computing the same, we demonstrate a simple procedure, based on the method of bisection, to recover the average shear modulus of the object in the ultrasound focal volume. We demonstrate this recovery for four homogeneous agarose slabs of different stiffness and verify the accuracy of the recovery using independent rheometer-based measurements. Extension of the method to anisotropic samples through the measurement of a more complete set of resonant modes and the recovery of an elasticity tensor distribution, as is done in resonant ultrasound spectroscopy, is suggested.

A computer code for three-dimensional incompressible flows using nonorthogonal body-fitted coordinate systems

NASA Technical Reports Server (NTRS)

Chen, Y. S.

1986-01-01

In this report, a numerical method for solving the equations of motion of three-dimensional incompressible flows in nonorthogonal body-fitted coordinate (BFC) systems has been developed. The equations of motion are transformed to a generalized curvilinear coordinate system from which the transformed equations are discretized using finite difference approximations in the transformed domain. The hybrid scheme is used to approximate the convection terms in the governing equations. Solutions of the finite difference equations are obtained iteratively by using a pressure-velocity correction algorithm (SIMPLE-C). Numerical examples of two- and three-dimensional, laminar and turbulent flow problems are employed to evaluate the accuracy and efficiency of the present computer code. The user's guide and computer program listing of the present code are also included.

Multiple-grid convergence acceleration of viscous and inviscid flow computations

NASA Technical Reports Server (NTRS)

Johnson, G. M.

1983-01-01

A multiple-grid algorithm for use in efficiently obtaining steady solution to the Euler and Navier-Stokes equations is presented. The convergence of a simple, explicit fine-grid solution procedure is accelerated on a sequence of successively coarser grids by a coarse-grid information propagation method which rapidly eliminates transients from the computational domain. This use of multiple-gridding to increase the convergence rate results in substantially reduced work requirements for the numerical solution of a wide range of flow problems. Computational results are presented for subsonic and transonic inviscid flows and for laminar and turbulent, attached and separated, subsonic viscous flows. Work reduction factors as large as eight, in comparison to the basic fine-grid algorithm, were obtained. Possibilities for further performance improvement are discussed.

A Matrix-Free Algorithm for Multidisciplinary Design Optimization

NASA Astrophysics Data System (ADS)

Lambe, Andrew Borean

Multidisciplinary design optimization (MDO) is an approach to engineering design that exploits the coupling between components or knowledge disciplines in a complex system to improve the final product. In aircraft design, MDO methods can be used to simultaneously design the outer shape of the aircraft and the internal structure, taking into account the complex interaction between the aerodynamic forces and the structural flexibility. Efficient strategies are needed to solve such design optimization problems and guarantee convergence to an optimal design. This work begins with a comprehensive review of MDO problem formulations and solution algorithms. First, a fundamental MDO problem formulation is defined from which other formulations may be obtained through simple transformations. Using these fundamental problem formulations, decomposition methods from the literature are reviewed and classified. All MDO methods are presented in a unified mathematical notation to facilitate greater understanding. In addition, a novel set of diagrams, called extended design structure matrices, are used to simultaneously visualize both data communication and process flow between the many software components of each method. For aerostructural design optimization, modern decomposition-based MDO methods cannot efficiently handle the tight coupling between the aerodynamic and structural states. This fact motivates the exploration of methods that can reduce the computational cost. A particular structure in the direct and adjoint methods for gradient computation motivates the idea of a matrix-free optimization method. A simple matrix-free optimizer is developed based on the augmented Lagrangian algorithm. This new matrix-free optimizer is tested on two structural optimization problems and one aerostructural optimization problem. The results indicate that the matrix-free optimizer is able to efficiently solve structural and multidisciplinary design problems with thousands of variables and constraints. On the aerostructural test problem formulated with thousands of constraints, the matrix-free optimizer is estimated to reduce the total computational time by up to 90% compared to conventional optimizers.

A Matrix-Free Algorithm for Multidisciplinary Design Optimization

NASA Astrophysics Data System (ADS)

Lambe, Andrew Borean

Multidisciplinary design optimization (MDO) is an approach to engineering design that exploits the coupling between components or knowledge disciplines in a complex system to improve the final product. In aircraft design, MDO methods can be used to simultaneously design the outer shape of the aircraft and the internal structure, taking into account the complex interaction between the aerodynamic forces and the structural flexibility. Efficient strategies are needed to solve such design optimization problems and guarantee convergence to an optimal design. This work begins with a comprehensive review of MDO problem formulations and solution algorithms. First, a fundamental MDO problem formulation is defined from which other formulations may be obtained through simple transformations. Using these fundamental problem formulations, decomposition methods from the literature are reviewed and classified. All MDO methods are presented in a unified mathematical notation to facilitate greater understanding. In addition, a novel set of diagrams, called extended design structure matrices, are used to simultaneously visualize both data communication and process flow between the many software components of each method. For aerostructural design optimization, modern decomposition-based MDO methods cannot efficiently handle the tight coupling between the aerodynamic and structural states. This fact motivates the exploration of methods that can reduce the computational cost. A particular structure in the direct and adjoint methods for gradient computation. motivates the idea of a matrix-free optimization method. A simple matrix-free optimizer is developed based on the augmented Lagrangian algorithm. This new matrix-free optimizer is tested on two structural optimization problems and one aerostructural optimization problem. The results indicate that the matrix-free optimizer is able to efficiently solve structural and multidisciplinary design problems with thousands of variables and constraints. On the aerostructural test problem formulated with thousands of constraints, the matrix-free optimizer is estimated to reduce the total computational time by up to 90% compared to conventional optimizers.

An Approximation of the Error Backpropagation Algorithm in a Predictive Coding Network with Local Hebbian Synaptic Plasticity

PubMed Central

Whittington, James C. R.; Bogacz, Rafal

2017-01-01

To efficiently learn from feedback, cortical networks need to update synaptic weights on multiple levels of cortical hierarchy. An effective and well-known algorithm for computing such changes in synaptic weights is the error backpropagation algorithm. However, in this algorithm, the change in synaptic weights is a complex function of weights and activities of neurons not directly connected with the synapse being modified, whereas the changes in biological synapses are determined only by the activity of presynaptic and postsynaptic neurons. Several models have been proposed that approximate the backpropagation algorithm with local synaptic plasticity, but these models require complex external control over the network or relatively complex plasticity rules. Here we show that a network developed in the predictive coding framework can efficiently perform supervised learning fully autonomously, employing only simple local Hebbian plasticity. Furthermore, for certain parameters, the weight change in the predictive coding model converges to that of the backpropagation algorithm. This suggests that it is possible for cortical networks with simple Hebbian synaptic plasticity to implement efficient learning algorithms in which synapses in areas on multiple levels of hierarchy are modified to minimize the error on the output. PMID:28333583

An Approximation of the Error Backpropagation Algorithm in a Predictive Coding Network with Local Hebbian Synaptic Plasticity.

PubMed

Whittington, James C R; Bogacz, Rafal

2017-05-01

To efficiently learn from feedback, cortical networks need to update synaptic weights on multiple levels of cortical hierarchy. An effective and well-known algorithm for computing such changes in synaptic weights is the error backpropagation algorithm. However, in this algorithm, the change in synaptic weights is a complex function of weights and activities of neurons not directly connected with the synapse being modified, whereas the changes in biological synapses are determined only by the activity of presynaptic and postsynaptic neurons. Several models have been proposed that approximate the backpropagation algorithm with local synaptic plasticity, but these models require complex external control over the network or relatively complex plasticity rules. Here we show that a network developed in the predictive coding framework can efficiently perform supervised learning fully autonomously, employing only simple local Hebbian plasticity. Furthermore, for certain parameters, the weight change in the predictive coding model converges to that of the backpropagation algorithm. This suggests that it is possible for cortical networks with simple Hebbian synaptic plasticity to implement efficient learning algorithms in which synapses in areas on multiple levels of hierarchy are modified to minimize the error on the output.

Simple and Efficient Single Photon Filter for a Rb-based Quantum Memory

NASA Astrophysics Data System (ADS)

Stack, Daniel; Li, Xiao; Quraishi, Qudsia

2015-05-01

Distribution of entangled quantum states over significant distances is important to the development of future quantum technologies such as long-distance cryptography, networks of atomic clocks, distributed quantum computing, etc. Long-lived quantum memories and single photons are building blocks for systems capable of realizing such applications. The ability to store and retrieve quantum information while filtering unwanted light signals is critical to the operation of quantum memories based on neutral-atom ensembles. We report on an efficient frequency filter which uses a glass cell filled with 85Rb vapor to attenuate noise photons by an order of magnitude with little loss to the single photons associated with the operation of our cold 87Rb quantum memory. An Ar buffer gas is required to differentiate between signal and noise photons or similar statement. Our simple, passive filter requires no optical pumping or external frequency references and provides an additional 18 dB attenuation of our pump laser for every 1 dB loss of the single photon signal. We observe improved non-classical correlations and our data shows that the addition of a frequency filter increases the non-classical correlations and readout efficiency of our quantum memory by ~ 35%.

Numerical prediction of the energy efficiency of the three-dimensional fish school using the discretized Adomian decomposition method

NASA Astrophysics Data System (ADS)

Lin, Yinwei

2018-06-01

A three-dimensional modeling of fish school performed by a modified Adomian decomposition method (ADM) discretized by the finite difference method is proposed. To our knowledge, few studies of the fish school are documented due to expensive cost of numerical computing and tedious three-dimensional data analysis. Here, we propose a simple model replied on the Adomian decomposition method to estimate the efficiency of energy saving of the flow motion of the fish school. First, the analytic solutions of Navier-Stokes equations are used for numerical validation. The influences of the distance between the side-by-side two fishes are studied on the energy efficiency of the fish school. In addition, the complete error analysis for this method is presented.

Exploring the Conformational Transitions of Biomolecular Systems Using a Simple Two-State Anisotropic Network Model

PubMed Central

Jo, Sunhwan; Bahar, Ivet; Roux, Benoît

2014-01-01

Biomolecular conformational transitions are essential to biological functions. Most experimental methods report on the long-lived functional states of biomolecules, but information about the transition pathways between these stable states is generally scarce. Such transitions involve short-lived conformational states that are difficult to detect experimentally. For this reason, computational methods are needed to produce plausible hypothetical transition pathways that can then be probed experimentally. Here we propose a simple and computationally efficient method, called ANMPathway, for constructing a physically reasonable pathway between two endpoints of a conformational transition. We adopt a coarse-grained representation of the protein and construct a two-state potential by combining two elastic network models (ENMs) representative of the experimental structures resolved for the endpoints. The two-state potential has a cusp hypersurface in the configuration space where the energies from both the ENMs are equal. We first search for the minimum energy structure on the cusp hypersurface and then treat it as the transition state. The continuous pathway is subsequently constructed by following the steepest descent energy minimization trajectories starting from the transition state on each side of the cusp hypersurface. Application to several systems of broad biological interest such as adenylate kinase, ATP-driven calcium pump SERCA, leucine transporter and glutamate transporter shows that ANMPathway yields results in good agreement with those from other similar methods and with data obtained from all-atom molecular dynamics simulations, in support of the utility of this simple and efficient approach. Notably the method provides experimentally testable predictions, including the formation of non-native contacts during the transition which we were able to detect in two of the systems we studied. An open-access web server has been created to deliver ANMPathway results. PMID:24699246

Three dimensional PNS solutions of hypersonic internal flows with equilibrium chemistry

NASA Technical Reports Server (NTRS)

Liou, May-Fun

1989-01-01

An implicit procedure for solving parabolized Navier-Stokes equations under the assumption of a general equation of state for a gas in chemical equilibrium is given. A general and consistent approach for the evaluation of Jacobian matrices in the implicit operator avoids the use of unnecessary auxiliary quantities and approximations, and leads to a simple expression. Applications to two- and three-dimensional flow problems show efficiency in computer time and economy in storage.

The Beneficial Role of Random Strategies in Social and Financial Systems

NASA Astrophysics Data System (ADS)

Biondo, Alessio Emanuele; Pluchino, Alessandro; Rapisarda, Andrea

2013-05-01

In this paper we focus on the beneficial role of random strategies in social sciences by means of simple mathematical and computational models. We briefly review recent results obtained by two of us in previous contributions for the case of the Peter principle and the efficiency of a Parliament. Then, we develop a new application of random strategies to the case of financial trading and discuss in detail our findings about forecasts of markets dynamics.

Bidirectional Reflectance of Flat, Optically Thick Particulate Layers: An Efficient Radiative Transfer Solution and Applications to Snow and Soil Surfaces

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Dlugach, Janna M.; Yanovitsku, Edgard G.; Zakharova, Nadia T.

1999-01-01

We describe a simple and highly efficient and accurate radiative transfer technique for computing bidirectional reflectance of a macroscopically flat scattering layer composed of nonabsorbing or weakly absorbing, arbitrarily shaped, randomly oriented and randomly distributed particles. The layer is assumed to be homogeneous and optically semi-infinite, and the bidirectional reflection function (BRF) is found by a simple iterative solution of the Ambartsumian's nonlinear integral equation. As an exact Solution of the radiative transfer equation, the reflection function thus obtained fully obeys the fundamental physical laws of energy conservation and reciprocity. Since this technique bypasses the computation of the internal radiation field, it is by far the fastest numerical approach available and can be used as an ideal input for Monte Carlo procedures calculating BRFs of scattering layers with macroscopically rough surfaces. Although the effects of packing density and coherent backscattering are currently neglected, they can also be incorporated. The FORTRAN implementation of the technique is available on the World Wide Web at http://ww,,v.giss.nasa.gov/-crmim/brf.html and can be applied to a wide range of remote sensing, engineering, and biophysical problems. We also examine the potential effect of ice crystal shape on the bidirectional reflectance of flat snow surfaces and the applicability of the Henyey-Greenstein phase function and the 6-Eddington approximation in calculations for soil surfaces.

Analysis of multigrid methods on massively parallel computers: Architectural implications

NASA Technical Reports Server (NTRS)

Matheson, Lesley R.; Tarjan, Robert E.

1993-01-01

We study the potential performance of multigrid algorithms running on massively parallel computers with the intent of discovering whether presently envisioned machines will provide an efficient platform for such algorithms. We consider the domain parallel version of the standard V cycle algorithm on model problems, discretized using finite difference techniques in two and three dimensions on block structured grids of size 10(exp 6) and 10(exp 9), respectively. Our models of parallel computation were developed to reflect the computing characteristics of the current generation of massively parallel multicomputers. These models are based on an interconnection network of 256 to 16,384 message passing, 'workstation size' processors executing in an SPMD mode. The first model accomplishes interprocessor communications through a multistage permutation network. The communication cost is a logarithmic function which is similar to the costs in a variety of different topologies. The second model allows single stage communication costs only. Both models were designed with information provided by machine developers and utilize implementation derived parameters. With the medium grain parallelism of the current generation and the high fixed cost of an interprocessor communication, our analysis suggests an efficient implementation requires the machine to support the efficient transmission of long messages, (up to 1000 words) or the high initiation cost of a communication must be significantly reduced through an alternative optimization technique. Furthermore, with variable length message capability, our analysis suggests the low diameter multistage networks provide little or no advantage over a simple single stage communications network.

Design and implementation of an efficient single layer five input majority voter gate in quantum-dot cellular automata.

PubMed

Bahar, Ali Newaz; Waheed, Sajjad

2016-01-01

The fundamental logical element of a quantum-dot cellular automata (QCA) circuit is majority voter gate (MV). The efficiency of a QCA circuit is depends on the efficiency of the MV. This paper presents an efficient single layer five-input majority voter gate (MV5). The structure of proposed MV5 is very simple and easy to implement in any logical circuit. This proposed MV5 reduce number of cells and use conventional QCA cells. However, using MV5 a multilayer 1-bit full-adder (FA) is designed. The functional accuracy of the proposed MV5 and FA are confirmed by QCADesigner a well-known QCA layout design and verification tools. Furthermore, the power dissipation of proposed circuits are estimated, which shows that those circuits dissipate extremely small amount of energy and suitable for reversible computing. The simulation outcomes demonstrate the superiority of the proposed circuit.

A simple and efficient method for predicting protein-protein interaction sites.

PubMed

Higa, R H; Tozzi, C L

2008-09-23

Computational methods for predicting protein-protein interaction sites based on structural data are characterized by an accuracy between 70 and 80%. Some experimental studies indicate that only a fraction of the residues, forming clusters in the center of the interaction site, are energetically important for binding. In addition, the analysis of amino acid composition has shown that residues located in the center of the interaction site can be better discriminated from the residues in other parts of the protein surface. In the present study, we implement a simple method to predict interaction site residues exploiting this fact and show that it achieves a very competitive performance compared to other methods using the same dataset and criteria for performance evaluation (success rate of 82.1%).

A simple filter circuit for denoising biomechanical impact signals.

PubMed

Subramaniam, Suba R; Georgakis, Apostolos

2009-01-01

We present a simple scheme for denoising non-stationary biomechanical signals with the aim of accurately estimating their second derivative (acceleration). The method is based on filtering in fractional Fourier domains using well-known low-pass filters in a way that amounts to a time-varying cut-off threshold. The resulting algorithm is linear and its design is facilitated by the relationship between the fractional Fourier transform and joint time-frequency representations. The implemented filter circuit employs only three low-order filters while its efficiency is further supported by the low computational complexity of the fractional Fourier transform. The results demonstrate that the proposed method can denoise the signals effectively and is more robust against noise as compared to conventional low-pass filters.

Finite volume solution of the compressible boundary-layer equations

NASA Technical Reports Server (NTRS)

Loyd, B.; Murman, E. M.

1986-01-01

A box-type finite volume discretization is applied to the integral form of the compressible boundary layer equations. Boundary layer scaling is introduced through the grid construction: streamwise grid lines follow eta = y/h = const., where y is the normal coordinate and h(x) is a scale factor proportional to the boundary layer thickness. With this grid, similarity can be applied explicity to calculate initial conditions. The finite volume method preserves the physical transparency of the integral equations in the discrete approximation. The resulting scheme is accurate, efficient, and conceptually simple. Computations for similar and non-similar flows show excellent agreement with tabulated results, solutions computed with Keller's Box scheme, and experimental data.

Valuation of exotic options in the framework of Levy processes

NASA Astrophysics Data System (ADS)

Milev, Mariyan; Georgieva, Svetla; Markovska, Veneta

2013-12-01

In this paper we explore a straightforward procedure to price derivatives by using the Monte Carlo approach when the underlying process is a jump-diffusion. We have compared the Black-Scholes model with one of its extensions that is the Merton model. The latter model is better in capturing the market's phenomena and is comparative to stochastic volatility models in terms of pricing accuracy. We have presented simulations of asset paths and pricing of barrier options for both Geometric Brownian motion and exponential Levy processes as it is the concrete case of the Merton model. A desired level of accuracy is obtained with simple computer operations in MATLAB for efficient computational time.

Simple and Effective Algorithms: Computer-Adaptive Testing.

ERIC Educational Resources Information Center

Linacre, John Michael

Computer-adaptive testing (CAT) allows improved security, greater scoring accuracy, shorter testing periods, quicker availability of results, and reduced guessing and other undesirable test behavior. Simple approaches can be applied by the classroom teacher, or other content specialist, who possesses simple computer equipment and elementary…

Optimisation by hierarchical search

NASA Astrophysics Data System (ADS)

Zintchenko, Ilia; Hastings, Matthew; Troyer, Matthias

2015-03-01

Finding optimal values for a set of variables relative to a cost function gives rise to some of the hardest problems in physics, computer science and applied mathematics. Although often very simple in their formulation, these problems have a complex cost function landscape which prevents currently known algorithms from efficiently finding the global optimum. Countless techniques have been proposed to partially circumvent this problem, but an efficient method is yet to be found. We present a heuristic, general purpose approach to potentially improve the performance of conventional algorithms or special purpose hardware devices by optimising groups of variables in a hierarchical way. We apply this approach to problems in combinatorial optimisation, machine learning and other fields.

Capture zones for simple aquifers

USGS Publications Warehouse

McElwee, Carl D.

1991-01-01

Capture zones showing the area influenced by a well within a certain time are useful for both aquifer protection and cleanup. If hydrodynamic dispersion is neglected, a deterministic curve defines the capture zone. Analytical expressions for the capture zones can be derived for simple aquifers. However, the capture zone equations are transcendental and cannot be explicitly solved for the coordinates of the capture zone boundary. Fortunately, an iterative scheme allows the solution to proceed quickly and efficiently even on a modest personal computer. Three forms of the analytical solution must be used in an iterative scheme to cover the entire region of interest, after the extreme values of the x coordinate are determined by an iterative solution. The resulting solution is a discrete one, and usually 100-1000 intervals along the x-axis are necessary for a smooth definition of the capture zone. The presented program is written in FORTRAN and has been used in a variety of computing environments. No graphics capability is included with the program; it is assumed the user has access to a commercial package. The superposition of capture zones for multiple wells is expected to be satisfactory if the spacing is not too close. Because this program deals with simple aquifers, the results rarely will be the final word in a real application.

Simulation of Combustion Systems with Realistic g-jitter

NASA Technical Reports Server (NTRS)

Mell, William E.; McGrattan, Kevin B.; Baum, Howard R.

2003-01-01

In this project a transient, fully three-dimensional computer simulation code was developed to simulate the effects of realistic g-jitter on a number of combustion systems. The simulation code is capable of simulating flame spread on a solid and nonpremixed or premixed gaseous combustion in nonturbulent flow with simple combustion models. Simple combustion models were used to preserve computational efficiency since this is meant to be an engineering code. Also, the use of sophisticated turbulence models was not pursued (a simple Smagorinsky type model can be implemented if deemed appropriate) because if flow velocities are large enough for turbulence to develop in a reduced gravity combustion scenario it is unlikely that g-jitter disturbances (in NASA's reduced gravity facilities) will play an important role in the flame dynamics. Acceleration disturbances of realistic orientation, magnitude, and time dependence can be easily included in the simulation. The simulation algorithm was based on techniques used in an existing large eddy simulation code which has successfully simulated fire dynamics in complex domains. A series of simulations with measured and predicted acceleration disturbances on the International Space Station (ISS) are presented. The results of this series of simulations suggested a passive isolation system and appropriate scheduling of crew activity would provide a sufficiently "quiet" acceleration environment for spherical diffusion flames.

Automating NEURON Simulation Deployment in Cloud Resources.

PubMed

Stockton, David B; Santamaria, Fidel

2017-01-01

Simulations in neuroscience are performed on local servers or High Performance Computing (HPC) facilities. Recently, cloud computing has emerged as a potential computational platform for neuroscience simulation. In this paper we compare and contrast HPC and cloud resources for scientific computation, then report how we deployed NEURON, a widely used simulator of neuronal activity, in three clouds: Chameleon Cloud, a hybrid private academic cloud for cloud technology research based on the OpenStack software; Rackspace, a public commercial cloud, also based on OpenStack; and Amazon Elastic Cloud Computing, based on Amazon's proprietary software. We describe the manual procedures and how to automate cloud operations. We describe extending our simulation automation software called NeuroManager (Stockton and Santamaria, Frontiers in Neuroinformatics, 2015), so that the user is capable of recruiting private cloud, public cloud, HPC, and local servers simultaneously with a simple common interface. We conclude by performing several studies in which we examine speedup, efficiency, total session time, and cost for sets of simulations of a published NEURON model.

Automating NEURON Simulation Deployment in Cloud Resources

PubMed Central

Santamaria, Fidel

2016-01-01

Simulations in neuroscience are performed on local servers or High Performance Computing (HPC) facilities. Recently, cloud computing has emerged as a potential computational platform for neuroscience simulation. In this paper we compare and contrast HPC and cloud resources for scientific computation, then report how we deployed NEURON, a widely used simulator of neuronal activity, in three clouds: Chameleon Cloud, a hybrid private academic cloud for cloud technology research based on the Open-Stack software; Rackspace, a public commercial cloud, also based on OpenStack; and Amazon Elastic Cloud Computing, based on Amazon’s proprietary software. We describe the manual procedures and how to automate cloud operations. We describe extending our simulation automation software called NeuroManager (Stockton and Santamaria, Frontiers in Neuroinformatics, 2015), so that the user is capable of recruiting private cloud, public cloud, HPC, and local servers simultaneously with a simple common interface. We conclude by performing several studies in which we examine speedup, efficiency, total session time, and cost for sets of simulations of a published NEURON model. PMID:27655341

An Expressive, Lightweight and Secure Construction of Key Policy Attribute-Based Cloud Data Sharing Access Control

NASA Astrophysics Data System (ADS)

Lin, Guofen; Hong, Hanshu; Xia, Yunhao; Sun, Zhixin

2017-10-01

Attribute-based encryption (ABE) is an interesting cryptographic technique for flexible cloud data sharing access control. However, some open challenges hinder its practical application. In previous schemes, all attributes are considered as in the same status while they are not in most of practical scenarios. Meanwhile, the size of access policy increases dramatically with the raise of its expressiveness complexity. In addition, current research hardly notices that mobile front-end devices, such as smartphones, are poor in computational performance while too much bilinear pairing computation is needed for ABE. In this paper, we propose a key-policy weighted attribute-based encryption without bilinear pairing computation (KP-WABE-WB) for secure cloud data sharing access control. A simple weighted mechanism is presented to describe different importance of each attribute. We introduce a novel construction of ABE without executing any bilinear pairing computation. Compared to previous schemes, our scheme has a better performance in expressiveness of access policy and computational efficiency.

A CUMULATIVE MIGRATION METHOD FOR COMPUTING RIGOROUS TRANSPORT CROSS SECTIONS AND DIFFUSION COEFFICIENTS FOR LWR LATTICES WITH MONTE CARLO

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

Zhaoyuan Liu; Kord Smith; Benoit Forget

2016-05-01

A new method for computing homogenized assembly neutron transport cross sections and dif- fusion coefficients that is both rigorous and computationally efficient is proposed in this paper. In the limit of a homogeneous hydrogen slab, the new method is equivalent to the long-used, and only-recently-published CASMO transport method. The rigorous method is used to demonstrate the sources of inaccuracy in the commonly applied “out-scatter” transport correction. It is also demonstrated that the newly developed method is directly applicable to lattice calculations per- formed by Monte Carlo and is capable of computing rigorous homogenized transport cross sections for arbitrarily heterogeneous lattices.more » Comparisons of several common transport cross section ap- proximations are presented for a simple problem of infinite medium hydrogen. The new method has also been applied in computing 2-group diffusion data for an actual PWR lattice from BEAVRS benchmark.« less

Contextuality supplies the 'magic' for quantum computation.

PubMed

Howard, Mark; Wallman, Joel; Veitch, Victor; Emerson, Joseph

2014-06-19

Quantum computers promise dramatic advantages over their classical counterparts, but the source of the power in quantum computing has remained elusive. Here we prove a remarkable equivalence between the onset of contextuality and the possibility of universal quantum computation via 'magic state' distillation, which is the leading model for experimentally realizing a fault-tolerant quantum computer. This is a conceptually satisfying link, because contextuality, which precludes a simple 'hidden variable' model of quantum mechanics, provides one of the fundamental characterizations of uniquely quantum phenomena. Furthermore, this connection suggests a unifying paradigm for the resources of quantum information: the non-locality of quantum theory is a particular kind of contextuality, and non-locality is already known to be a critical resource for achieving advantages with quantum communication. In addition to clarifying these fundamental issues, this work advances the resource framework for quantum computation, which has a number of practical applications, such as characterizing the efficiency and trade-offs between distinct theoretical and experimental schemes for achieving robust quantum computation, and putting bounds on the overhead cost for the classical simulation of quantum algorithms.

Reversible simulation of irreversible computation

NASA Astrophysics Data System (ADS)

Li, Ming; Tromp, John; Vitányi, Paul

1998-09-01

Computer computations are generally irreversible while the laws of physics are reversible. This mismatch is penalized by among other things generating excess thermic entropy in the computation. Computing performance has improved to the extent that efficiency degrades unless all algorithms are executed reversibly, for example by a universal reversible simulation of irreversible computations. All known reversible simulations are either space hungry or time hungry. The leanest method was proposed by Bennett and can be analyzed using a simple ‘reversible’ pebble game. The reachable reversible simulation instantaneous descriptions (pebble configurations) of such pebble games are characterized completely. As a corollary we obtain the reversible simulation by Bennett and, moreover, show that it is a space-optimal pebble game. We also introduce irreversible steps and give a theorem on the tradeoff between the number of allowed irreversible steps and the memory gain in the pebble game. In this resource-bounded setting the limited erasing needs to be performed at precise instants during the simulation. The reversible simulation can be modified so that it is applicable also when the simulated computation time is unknown.

Using Alice 2.0 to Design Games for People with Stroke.

PubMed

Proffitt, Rachel; Kelleher, Caitlin; Baum, M Carolyn; Engsberg, Jack

2012-08-01

Computer and videogames are gaining in popularity as rehabilitation tools. Unfortunately, most systems still require extensive programming/engineering knowledge to create, something that therapists, as novice programmers, do not possess. There is software designed to allow novice programmers to create storyboard and games through simple drag-and-drop formats; however, the applications for therapeutic game development have not been studied. The purpose of this study was to have an occupational therapy (OT) student with no prior computer programming experience learn how to create computer games for persons with stroke using Alice 2.0, a drag-and-drop editor, designed by Carnegie Mellon University (Pittsburgh, PA). The OT student learned how to use Alice 2.0 through a textbook, tutorials, and assistance from computer science students. She kept a journal of her process, detailing her successes and challenges. The OT student created three games for people with stroke using Alice 2.0. She found that although there were many supports in Alice for creating stories, it lacked critical pieces necessary for game design. Her recommendations for a future programming environment for therapists were that it (1) be efficient, (2) include basic game design pieces so therapists do not have to create them, (3) provide technical support, and (4) be simple. With the incorporation of these recommendations, a future programming environment for therapists will be an effective tool for therapeutic game development.

Evolution of the cerebellum as a neuronal machine for Bayesian state estimation

NASA Astrophysics Data System (ADS)

Paulin, M. G.

2005-09-01

The cerebellum evolved in association with the electric sense and vestibular sense of the earliest vertebrates. Accurate information provided by these sensory systems would have been essential for precise control of orienting behavior in predation. A simple model shows that individual spikes in electrosensory primary afferent neurons can be interpreted as measurements of prey location. Using this result, I construct a computational neural model in which the spatial distribution of spikes in a secondary electrosensory map forms a Monte Carlo approximation to the Bayesian posterior distribution of prey locations given the sense data. The neural circuit that emerges naturally to perform this task resembles the cerebellar-like hindbrain electrosensory filtering circuitry of sharks and other electrosensory vertebrates. The optimal filtering mechanism can be extended to handle dynamical targets observed from a dynamical platform; that is, to construct an optimal dynamical state estimator using spiking neurons. This may provide a generic model of cerebellar computation. Vertebrate motion-sensing neurons have specific fractional-order dynamical characteristics that allow Bayesian state estimators to be implemented elegantly and efficiently, using simple operations with asynchronous pulses, i.e. spikes. The computational neural models described in this paper represent a novel kind of particle filter, using spikes as particles. The models are specific and make testable predictions about computational mechanisms in cerebellar circuitry, while providing a plausible explanation of cerebellar contributions to aspects of motor control, perception and cognition.

A Semi-Vectorization Algorithm to Synthesis of Gravitational Anomaly Quantities on the Earth

NASA Astrophysics Data System (ADS)

Abdollahzadeh, M.; Eshagh, M.; Najafi Alamdari, M.

2009-04-01

The Earth's gravitational potential can be expressed by the well-known spherical harmonic expansion. The computational time of summing up this expansion is an important practical issue which can be reduced by an efficient numerical algorithm. This paper proposes such a method for block-wise synthesizing the anomaly quantities on the Earth surface using vectorization. Fully-vectorization means transformation of the summations to the simple matrix and vector products. It is not a practical for the matrices with large dimensions. Here a semi-vectorization algorithm is proposed to avoid working with large vectors and matrices. It speeds up the computations by using one loop for the summation either on degrees or on orders. The former is a good option to synthesize the anomaly quantities on the Earth surface considering a digital elevation model (DEM). This approach is more efficient than the two-step method which computes the quantities on the reference ellipsoid and continues them upward to the Earth surface. The algorithm has been coded in MATLAB which synthesizes a global grid of 5′Ã- 5′ (corresponding 9 million points) of gravity anomaly or geoid height using a geopotential model to degree 360 in 10000 seconds by an ordinary computer with 2G RAM.

Phase quality map based on local multi-unwrapped results for two-dimensional phase unwrapping.

PubMed

Zhong, Heping; Tang, Jinsong; Zhang, Sen

2015-02-01

The efficiency of a phase unwrapping algorithm and the reliability of the corresponding unwrapped result are two key problems in reconstructing the digital elevation model of a scene from its interferometric synthetic aperture radar (InSAR) or interferometric synthetic aperture sonar (InSAS) data. In this paper, a new phase quality map is designed and implemented in a graphic processing unit (GPU) environment, which greatly accelerates the unwrapping process of the quality-guided algorithm and enhances the correctness of the unwrapped result. In a local wrapped phase window, the center point is selected as the reference point, and then two unwrapped results are computed by integrating in two different simple ways. After the two local unwrapped results are computed, the total difference of the two unwrapped results is regarded as the phase quality value of the center point. In order to accelerate the computing process of the new proposed quality map, we have implemented it in a GPU environment. The wrapped phase data are first uploaded to the memory of a device, and then the kernel function is called in the device to compute the phase quality in parallel by blocks of threads. Unwrapping tests performed on the simulated and real InSAS data confirm the accuracy and efficiency of the proposed method.

Efficient Simultaneous Reconstruction of Time-Varying Images and Electrode Contact Impedances in Electrical Impedance Tomography.

PubMed

Boverman, Gregory; Isaacson, David; Newell, Jonathan C; Saulnier, Gary J; Kao, Tzu-Jen; Amm, Bruce C; Wang, Xin; Davenport, David M; Chong, David H; Sahni, Rakesh; Ashe, Jeffrey M

2017-04-01

In electrical impedance tomography (EIT), we apply patterns of currents on a set of electrodes at the external boundary of an object, measure the resulting potentials at the electrodes, and, given the aggregate dataset, reconstruct the complex conductivity and permittivity within the object. It is possible to maximize sensitivity to internal conductivity changes by simultaneously applying currents and measuring potentials on all electrodes but this approach also maximizes sensitivity to changes in impedance at the interface. We have, therefore, developed algorithms to assess contact impedance changes at the interface as well as to efficiently and simultaneously reconstruct internal conductivity/permittivity changes within the body. We use simple linear algebraic manipulations, the generalized singular value decomposition, and a dual-mesh finite-element-based framework to reconstruct images in real time. We are also able to efficiently compute the linearized reconstruction for a wide range of regularization parameters and to compute both the generalized cross-validation parameter as well as the L-curve, objective approaches to determining the optimal regularization parameter, in a similarly efficient manner. Results are shown using data from a normal subject and from a clinical intensive care unit patient, both acquired with the GE GENESIS prototype EIT system, demonstrating significantly reduced boundary artifacts due to electrode drift and motion artifact.

Balancing accuracy, efficiency, and flexibility in a radiative transfer parameterization for dynamical models

NASA Astrophysics Data System (ADS)

Pincus, R.; Mlawer, E. J.

2017-12-01

Radiation is key process in numerical models of the atmosphere. The problem is well-understood and the parameterization of radiation has seen relatively few conceptual advances in the past 15 years. It is nonthelss often the single most expensive component of all physical parameterizations despite being computed less frequently than other terms. This combination of cost and maturity suggests value in a single radiation parameterization that could be shared across models; devoting effort to a single parameterization might allow for fine tuning for efficiency. The challenge lies in the coupling of this parameterization to many disparate representations of clouds and aerosols. This talk will describe RRTMGP, a new radiation parameterization that seeks to balance efficiency and flexibility. This balance is struck by isolating computational tasks in "kernels" that expose as much fine-grained parallelism as possible. These have simple interfaces and are interoperable across programming languages so that they might be repalced by alternative implementations in domain-specific langauges. Coupling to the host model makes use of object-oriented features of Fortran 2003, minimizing branching within the kernels and the amount of data that must be transferred. We will show accuracy and efficiency results for a globally-representative set of atmospheric profiles using a relatively high-resolution spectral discretization.

Spherical Tensor Calculus for Local Adaptive Filtering

NASA Astrophysics Data System (ADS)

Reisert, Marco; Burkhardt, Hans

In 3D image processing tensors play an important role. While rank-1 and rank-2 tensors are well understood and commonly used, higher rank tensors are rare. This is probably due to their cumbersome rotation behavior which prevents a computationally efficient use. In this chapter we want to introduce the notion of a spherical tensor which is based on the irreducible representations of the 3D rotation group. In fact, any ordinary cartesian tensor can be decomposed into a sum of spherical tensors, while each spherical tensor has a quite simple rotation behavior. We introduce so called tensorial harmonics that provide an orthogonal basis for spherical tensor fields of any rank. It is just a generalization of the well known spherical harmonics. Additionally we propose a spherical derivative which connects spherical tensor fields of different degree by differentiation. Based on the proposed theory we present two applications. We propose an efficient algorithm for dense tensor voting in 3D, which makes use of tensorial harmonics decomposition of the tensor-valued voting field. In this way it is possible to perform tensor voting by linear-combinations of convolutions in an efficient way. Secondly, we propose an anisotropic smoothing filter that uses a local shape and orientation adaptive filter kernel which can be computed efficiently by the use spherical derivatives.

Current trends for customized biomedical software tools.

PubMed

Khan, Haseeb Ahmad

2017-01-01

In the past, biomedical scientists were solely dependent on expensive commercial software packages for various applications. However, the advent of user-friendly programming languages and open source platforms has revolutionized the development of simple and efficient customized software tools for solving specific biomedical problems. Many of these tools are designed and developed by biomedical scientists independently or with the support of computer experts and often made freely available for the benefit of scientific community. The current trends for customized biomedical software tools are highlighted in this short review.

Time dependent density functional calculation of plasmon response in clusters

NASA Astrophysics Data System (ADS)

Wang, Feng; Zhang, Feng-Shou; Eric, Suraud

2003-02-01

We have introduced a theoretical scheme for the efficient description of the optical response of a cluster based on the time-dependent density functional theory. The practical implementation is done by means of the fully fledged time-dependent local density approximation scheme, which is solved directly in the time domain without any linearization. As an example we consider the simple Na2 cluster and compute its surface plasmon photoabsorption cross section, which is in good agreement with the experiments.

Recent Improvements in the FDNS CFD Code and its Associated Process

NASA Technical Reports Server (NTRS)

West, Jeff S.; Dorney, Suzanne M.; Turner, Jim (Technical Monitor)

2002-01-01

This viewgraph presentation gives an overview on recent improvements in the Finite Difference Navier Stokes (FDNS) computational fluid dynamics (CFD) code and its associated process. The development of a utility, PreViewer, has essentially eliminated the creeping of simple human error into the FDNS Solution process. Extension of PreViewer to encapsulate the Domain Decompression process has made practical the routine use of parallel processing. The combination of CVS source control and ATS consistency validation significantly increases the efficiency of the CFD process.

Distribution of thermal neutrons in a temperature gradient

NASA Astrophysics Data System (ADS)

Molinari, V. G.; Pollachini, L.

A method to determine the spatial distribution of the thermal spectrum of neutrons in heterogeneous systems is presented. The method is based on diffusion concepts and has a simple mathematical structure which increases computing efficiency. The application of this theory to the neutron thermal diffusion induced by a temperature gradient, as found in nuclear reactors, is described. After introducing approximations, a nonlinear equation system representing the neutron temperature is given. Values of the equation parameters and its dependence on geometrical factors and media characteristics are discussed.

Simulation methods to estimate design power: an overview for applied research.

PubMed

Arnold, Benjamin F; Hogan, Daniel R; Colford, John M; Hubbard, Alan E

2011-06-20

Estimating the required sample size and statistical power for a study is an integral part of study design. For standard designs, power equations provide an efficient solution to the problem, but they are unavailable for many complex study designs that arise in practice. For such complex study designs, computer simulation is a useful alternative for estimating study power. Although this approach is well known among statisticians, in our experience many epidemiologists and social scientists are unfamiliar with the technique. This article aims to address this knowledge gap. We review an approach to estimate study power for individual- or cluster-randomized designs using computer simulation. This flexible approach arises naturally from the model used to derive conventional power equations, but extends those methods to accommodate arbitrarily complex designs. The method is universally applicable to a broad range of designs and outcomes, and we present the material in a way that is approachable for quantitative, applied researchers. We illustrate the method using two examples (one simple, one complex) based on sanitation and nutritional interventions to improve child growth. We first show how simulation reproduces conventional power estimates for simple randomized designs over a broad range of sample scenarios to familiarize the reader with the approach. We then demonstrate how to extend the simulation approach to more complex designs. Finally, we discuss extensions to the examples in the article, and provide computer code to efficiently run the example simulations in both R and Stata. Simulation methods offer a flexible option to estimate statistical power for standard and non-traditional study designs and parameters of interest. The approach we have described is universally applicable for evaluating study designs used in epidemiologic and social science research.

Simulation methods to estimate design power: an overview for applied research

PubMed Central

2011-01-01

Background Estimating the required sample size and statistical power for a study is an integral part of study design. For standard designs, power equations provide an efficient solution to the problem, but they are unavailable for many complex study designs that arise in practice. For such complex study designs, computer simulation is a useful alternative for estimating study power. Although this approach is well known among statisticians, in our experience many epidemiologists and social scientists are unfamiliar with the technique. This article aims to address this knowledge gap. Methods We review an approach to estimate study power for individual- or cluster-randomized designs using computer simulation. This flexible approach arises naturally from the model used to derive conventional power equations, but extends those methods to accommodate arbitrarily complex designs. The method is universally applicable to a broad range of designs and outcomes, and we present the material in a way that is approachable for quantitative, applied researchers. We illustrate the method using two examples (one simple, one complex) based on sanitation and nutritional interventions to improve child growth. Results We first show how simulation reproduces conventional power estimates for simple randomized designs over a broad range of sample scenarios to familiarize the reader with the approach. We then demonstrate how to extend the simulation approach to more complex designs. Finally, we discuss extensions to the examples in the article, and provide computer code to efficiently run the example simulations in both R and Stata. Conclusions Simulation methods offer a flexible option to estimate statistical power for standard and non-traditional study designs and parameters of interest. The approach we have described is universally applicable for evaluating study designs used in epidemiologic and social science research. PMID:21689447

Tchebichef moment transform on image dithering for mobile applications

NASA Astrophysics Data System (ADS)

Ernawan, Ferda; Abu, Nur Azman; Rahmalan, Hidayah

2012-04-01

Currently, mobile image applications spend a lot of computing process to display images. A true color raw image contains billions of colors and it consumes high computational power in most mobile image applications. At the same time, mobile devices are only expected to be equipped with lower computing process and minimum storage space. Image dithering is a popular technique to reduce the numbers of bit per pixel at the expense of lower quality image displays. This paper proposes a novel approach on image dithering using 2x2 Tchebichef moment transform (TMT). TMT integrates a simple mathematical framework technique using matrices. TMT coefficients consist of real rational numbers. An image dithering based on TMT has the potential to provide better efficiency and simplicity. The preliminary experiment shows a promising result in term of error reconstructions and image visual textures.

The Gain of Resource Delegation in Distributed Computing Environments

NASA Astrophysics Data System (ADS)

Fölling, Alexander; Grimme, Christian; Lepping, Joachim; Papaspyrou, Alexander

In this paper, we address job scheduling in Distributed Computing Infrastructures, that is a loosely coupled network of autonomous acting High Performance Computing systems. In contrast to the common approach of mutual workload exchange, we consider the more intuitive operator's viewpoint of load-dependent resource reconfiguration. In case of a site's over-utilization, the scheduling system is able to lease resources from other sites to keep up service quality for its local user community. Contrary, the granting of idle resources can increase utilization in times of low local workload and thus ensure higher efficiency. The evaluation considers real workload data and is done with respect to common service quality indicators. For two simple resource exchange policies and three basic setups we show the possible gain of this approach and analyze the dynamics in workload-adaptive reconfiguration behavior.

Extinction by a Homogeneous Spherical Particle in an Absorbing Medium

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Videen, Gorden; Yang, Ping

2017-01-01

We use a recent computer implementation of the first principles theory of electromagnetic scattering to compute far-field extinction by a spherical particle embedded in an absorbing unbounded host. Our results show that the suppressing effect of increasing absorption inside the host medium on the ripple structure of the extinction efficiency factor as a function of the size parameter is similar to the well-known effect of increasing absorption inside a particle embedded in a nonabsorbing host. However, the accompanying effects on the interference structure of the extinction efficiency curves are diametrically opposite. As a result, sufficiently large absorption inside the host medium can cause negative particulate extinction. We offer a simple physical explanation of the phenomenon of negative extinction consistent with the interpretation of the interference structure as being the result of interference of the field transmitted by the particle and the diffracted field due to an incomplete wave front resulting from the blockage of the incident plane wave by the particle's geometrical projection.

Convolutional networks for vehicle track segmentation

NASA Astrophysics Data System (ADS)

Quach, Tu-Thach

2017-10-01

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple and fast models to label track pixels. These models, however, are unable to capture natural track features, such as continuity and parallelism. More powerful but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3×3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate in low power and have limited training data. As a result, we aim for small and efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our six-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.

Efficient electron open boundaries for simulating electrochemical cells

NASA Astrophysics Data System (ADS)

Zauchner, Mario G.; Horsfield, Andrew P.; Todorov, Tchavdar N.

2018-01-01

Nonequilibrium electrochemistry raises new challenges for atomistic simulation: we need to perform molecular dynamics for the nuclear degrees of freedom with an explicit description of the electrons, which in turn must be free to enter and leave the computational cell. Here we present a limiting form for electron open boundaries that we expect to apply when the magnitude of the electric current is determined by the drift and diffusion of ions in a solution and which is sufficiently computationally efficient to be used with molecular dynamics. We present tight-binding simulations of a parallel-plate capacitor with nothing, a dimer, or an atomic wire situated in the space between the plates. These simulations demonstrate that this scheme can be used to perform molecular dynamics simulations when there is an applied bias between two metal plates with, at most, weak electronic coupling between them. This simple system captures some of the essential features of an electrochemical cell, suggesting this approach might be suitable for simulations of electrochemical cells out of equilibrium.

Efficiently computing and deriving topological relation matrices between complex regions with broad boundaries

NASA Astrophysics Data System (ADS)

Du, Shihong; Guo, Luo; Wang, Qiao; Qin, Qimin

The extended 9-intersection matrix is used to formalize topological relations between uncertain regions while it is designed to satisfy the requirements at a concept level, and to deal with the complex regions with broad boundaries (CBBRs) as a whole without considering their hierarchical structures. In contrast to simple regions with broad boundaries, CBBRs have complex hierarchical structures. Therefore, it is necessary to take into account the complex hierarchical structure and to represent the topological relations between all regions in CBBRs as a relation matrix, rather than using the extended 9-intersection matrix to determine topological relations. In this study, a tree model is first used to represent the intrinsic configuration of CBBRs hierarchically. Then, the reasoning tables are presented for deriving topological relations between child, parent and sibling regions from the relations between two given regions in CBBRs. Finally, based on the reasoning, efficient methods are proposed to compute and derive the topological relation matrix. The proposed methods can be incorporated into spatial databases to facilitate geometric-oriented applications.

Using hybrid implicit Monte Carlo diffusion to simulate gray radiation hydrodynamics

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

Cleveland, Mathew A., E-mail: cleveland7@llnl.gov; Gentile, Nick

This work describes how to couple a hybrid Implicit Monte Carlo Diffusion (HIMCD) method with a Lagrangian hydrodynamics code to evaluate the coupled radiation hydrodynamics equations. This HIMCD method dynamically applies Implicit Monte Carlo Diffusion (IMD) [1] to regions of a problem that are opaque and diffusive while applying standard Implicit Monte Carlo (IMC) [2] to regions where the diffusion approximation is invalid. We show that this method significantly improves the computational efficiency as compared to a standard IMC/Hydrodynamics solver, when optically thick diffusive material is present, while maintaining accuracy. Two test cases are used to demonstrate the accuracy andmore » performance of HIMCD as compared to IMC and IMD. The first is the Lowrie semi-analytic diffusive shock [3]. The second is a simple test case where the source radiation streams through optically thin material and heats a thick diffusive region of material causing it to rapidly expand. We found that HIMCD proves to be accurate, robust, and computationally efficient for these test problems.« less

A Novel Latin Hypercube Algorithm via Translational Propagation

PubMed Central

Pan, Guang; Ye, Pengcheng

2014-01-01

Metamodels have been widely used in engineering design to facilitate analysis and optimization of complex systems that involve computationally expensive simulation programs. The accuracy of metamodels is directly related to the experimental designs used. Optimal Latin hypercube designs are frequently used and have been shown to have good space-filling and projective properties. However, the high cost in constructing them limits their use. In this paper, a methodology for creating novel Latin hypercube designs via translational propagation and successive local enumeration algorithm (TPSLE) is developed without using formal optimization. TPSLE algorithm is based on the inspiration that a near optimal Latin Hypercube design can be constructed by a simple initial block with a few points generated by algorithm SLE as a building block. In fact, TPSLE algorithm offers a balanced trade-off between the efficiency and sampling performance. The proposed algorithm is compared to two existing algorithms and is found to be much more efficient in terms of the computation time and has acceptable space-filling and projective properties. PMID:25276844

Underworld: What we set out to do, How far did we get, What did we Learn ? (Invited)

NASA Astrophysics Data System (ADS)

Moresi, L. N.

2013-12-01

Underworld was conceived as a tool for modelling 3D lithospheric deformation coupled with the underlying / surrounding mantle flow. The challenges involved were to find a method capable of representing the complicated, non-linear, history dependent rheology of the near surface as well as being able to model mantle convection, and, simultaneously, to be able to solve the numerical system efficiently. Underworld is a hybrid particle / mesh code reminiscent of the particle-in-cell techniques from the early 1960s. The Underworld team (*) was not the first to use this approach, nor the last, but the team does have considerable experience and much has been learned along the way. The use of a finite element method as the underlying "cell" in which the Lagrangian particles are embedded considerably reduces errors associated with mapping material properties to the cells. The particles are treated as moving quadrature points in computing the stiffness matrix integrals. The decoupling of deformation markers from computation points allows the use of structured meshes, efficient parallel decompositions, and simple-to-code geometric multigrid solution methods. For a 3D code such efficiencies are very important. The elegance of the method is that it can be completely described in a couple of sentences. However, there are some limitations: it is not obvious how to retain this elegance for unstructured or adaptive meshes, arbitrary element types are not sufficiently well integrated by the simple quadrature approach, and swarms of particles representing volumes are usually an inefficient representation of surfaces. This will be discussed ! (*) Although not formally constituted, my co-conspirators in this exercise are listed as the Underworld team and I will reveal their true identities on the day.

A Round-Efficient Authenticated Key Agreement Scheme Based on Extended Chaotic Maps for Group Cloud Meeting.

PubMed

Lin, Tsung-Hung; Tsung, Chen-Kun; Lee, Tian-Fu; Wang, Zeng-Bo

2017-12-03

The security is a critical issue for business purposes. For example, the cloud meeting must consider strong security to maintain the communication privacy. Considering the scenario with cloud meeting, we apply extended chaotic map to present passwordless group authentication key agreement, termed as Passwordless Group Authentication Key Agreement (PL-GAKA). PL-GAKA improves the computation efficiency for the simple group password-based authenticated key agreement (SGPAKE) proposed by Lee et al. in terms of computing the session key. Since the extended chaotic map has equivalent security level to the Diffie-Hellman key exchange scheme applied by SGPAKE, the security of PL-GAKA is not sacrificed when improving the computation efficiency. Moreover, PL-GAKA is a passwordless scheme, so the password maintenance is not necessary. Short-term authentication is considered, hence the communication security is stronger than other protocols by dynamically generating session key in each cloud meeting. In our analysis, we first prove that each meeting member can get the correct information during the meeting. We analyze common security issues for the proposed PL-GAKA in terms of session key security, mutual authentication, perfect forward security, and data integrity. Moreover, we also demonstrate that communicating in PL-GAKA is secure when suffering replay attacks, impersonation attacks, privileged insider attacks, and stolen-verifier attacks. Eventually, an overall comparison is given to show the performance between PL-GAKA, SGPAKE and related solutions.

A semi-Lagrangian transport method for kinetic problems with application to dense-to-dilute polydisperse reacting spray flows

NASA Astrophysics Data System (ADS)

Doisneau, François; Arienti, Marco; Oefelein, Joseph C.

2017-01-01

For sprays, as described by a kinetic disperse phase model strongly coupled to the Navier-Stokes equations, the resolution strategy is constrained by accuracy objectives, robustness needs, and the computing architecture. In order to leverage the good properties of the Eulerian formalism, we introduce a deterministic particle-based numerical method to solve transport in physical space, which is simple to adapt to the many types of closures and moment systems. The method is inspired by the semi-Lagrangian schemes, developed for Gas Dynamics. We show how semi-Lagrangian formulations are relevant for a disperse phase far from equilibrium and where the particle-particle coupling barely influences the transport; i.e., when particle pressure is negligible. The particle behavior is indeed close to free streaming. The new method uses the assumption of parcel transport and avoids to compute fluxes and their limiters, which makes it robust. It is a deterministic resolution method so that it does not require efforts on statistical convergence, noise control, or post-processing. All couplings are done among data under the form of Eulerian fields, which allows one to use efficient algorithms and to anticipate the computational load. This makes the method both accurate and efficient in the context of parallel computing. After a complete verification of the new transport method on various academic test cases, we demonstrate the overall strategy's ability to solve a strongly-coupled liquid jet with fine spatial resolution and we apply it to the case of high-fidelity Large Eddy Simulation of a dense spray flow. A fuel spray is simulated after atomization at Diesel engine combustion chamber conditions. The large, parallel, strongly coupled computation proves the efficiency of the method for dense, polydisperse, reacting spray flows.

A semi-Lagrangian transport method for kinetic problems with application to dense-to-dilute polydisperse reacting spray flows

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

Doisneau, François, E-mail: fdoisne@sandia.gov; Arienti, Marco, E-mail: marient@sandia.gov; Oefelein, Joseph C., E-mail: oefelei@sandia.gov

For sprays, as described by a kinetic disperse phase model strongly coupled to the Navier–Stokes equations, the resolution strategy is constrained by accuracy objectives, robustness needs, and the computing architecture. In order to leverage the good properties of the Eulerian formalism, we introduce a deterministic particle-based numerical method to solve transport in physical space, which is simple to adapt to the many types of closures and moment systems. The method is inspired by the semi-Lagrangian schemes, developed for Gas Dynamics. We show how semi-Lagrangian formulations are relevant for a disperse phase far from equilibrium and where the particle–particle coupling barelymore » influences the transport; i.e., when particle pressure is negligible. The particle behavior is indeed close to free streaming. The new method uses the assumption of parcel transport and avoids to compute fluxes and their limiters, which makes it robust. It is a deterministic resolution method so that it does not require efforts on statistical convergence, noise control, or post-processing. All couplings are done among data under the form of Eulerian fields, which allows one to use efficient algorithms and to anticipate the computational load. This makes the method both accurate and efficient in the context of parallel computing. After a complete verification of the new transport method on various academic test cases, we demonstrate the overall strategy's ability to solve a strongly-coupled liquid jet with fine spatial resolution and we apply it to the case of high-fidelity Large Eddy Simulation of a dense spray flow. A fuel spray is simulated after atomization at Diesel engine combustion chamber conditions. The large, parallel, strongly coupled computation proves the efficiency of the method for dense, polydisperse, reacting spray flows.« less

Fast Simulation of Membrane Filtration by Combining Particle Retention Mechanisms and Network Models

NASA Astrophysics Data System (ADS)

Krupp, Armin; Griffiths, Ian; Please, Colin

2016-11-01

Porous membranes are used for their particle retention capabilities in a wide range of industrial filtration processes. The underlying mechanisms for particle retention are complex and often change during the filtration process, making it hard to predict the change in permeability of the membrane during the process. Recently, stochastic network models have been shown to predict the change in permeability based on retention mechanisms, but remain computationally intensive. We show that the averaged behaviour of such a stochastic network model can efficiently be computed using a simple partial differential equation. Moreover, we also show that the geometric structure of the underlying membrane and particle-size distribution can be represented in our model, making it suitable for modelling particle retention in interconnected membranes as well. We conclude by demonstrating the particular application to microfluidic filtration, where the model can be used to efficiently compute a probability density for flux measurements based on the geometry of the pores and particles. A. U. K. is grateful for funding from Pall Corporation and the Mathematical Institute, University of Oxford. I.M.G. gratefully acknowledges support from the Royal Society through a University Research Fellowship.

Spectral Regularization Algorithms for Learning Large Incomplete Matrices.

PubMed

Mazumder, Rahul; Hastie, Trevor; Tibshirani, Robert

2010-03-01

We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we provide a simple and very efficient convex algorithm for minimizing the reconstruction error subject to a bound on the nuclear norm. Our algorithm Soft-Impute iteratively replaces the missing elements with those obtained from a soft-thresholded SVD. With warm starts this allows us to efficiently compute an entire regularization path of solutions on a grid of values of the regularization parameter. The computationally intensive part of our algorithm is in computing a low-rank SVD of a dense matrix. Exploiting the problem structure, we show that the task can be performed with a complexity linear in the matrix dimensions. Our semidefinite-programming algorithm is readily scalable to large matrices: for example it can obtain a rank-80 approximation of a 10(6) × 10(6) incomplete matrix with 10(5) observed entries in 2.5 hours, and can fit a rank 40 approximation to the full Netflix training set in 6.6 hours. Our methods show very good performance both in training and test error when compared to other competitive state-of-the art techniques.

Spectral Regularization Algorithms for Learning Large Incomplete Matrices

PubMed Central

Mazumder, Rahul; Hastie, Trevor; Tibshirani, Robert

2010-01-01

We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we provide a simple and very efficient convex algorithm for minimizing the reconstruction error subject to a bound on the nuclear norm. Our algorithm Soft-Impute iteratively replaces the missing elements with those obtained from a soft-thresholded SVD. With warm starts this allows us to efficiently compute an entire regularization path of solutions on a grid of values of the regularization parameter. The computationally intensive part of our algorithm is in computing a low-rank SVD of a dense matrix. Exploiting the problem structure, we show that the task can be performed with a complexity linear in the matrix dimensions. Our semidefinite-programming algorithm is readily scalable to large matrices: for example it can obtain a rank-80 approximation of a 106 × 106 incomplete matrix with 105 observed entries in 2.5 hours, and can fit a rank 40 approximation to the full Netflix training set in 6.6 hours. Our methods show very good performance both in training and test error when compared to other competitive state-of-the art techniques. PMID:21552465

Computational Relativistic Astrophysics Using the Flowfield-Dependent Variation Theory

NASA Technical Reports Server (NTRS)

Richardson, G. A.; Chung, T. J.; Whitaker, Ann F. (Technical Monitor)

2001-01-01

Theoretical models, observations and measurements have preoccupied astrophysicists for many centuries. Only in recent years, has the theory of relativity as applied to astrophysical flows met the challenges of how the governing equations can be solved numerically with accuracy and efficiency. Even without the effects of relativity, the physics of magnetohydrodynamic flow instability, turbulence, radiation, and enhanced transport in accretion disks has not been completely resolved. Relativistic effects become pronounced in such cases as jet formation from black hole magnetized accretion disks and also in the study of Gamma-Ray bursts (GRB). Thus, our concern in this paper is to reexamine existing numerical simulation tools as to the accuracy and efficiency of computations and introduce a new approach known as the flowfield-dependent variation (FDV) method. The main feature of the FDV method consists of accommodating discontinuities of shock waves and high gradients of flow variables such as occur in turbulence and unstable motions. In this paper, the physics involved in the solution of relativistic hydrodynamics and solution strategies of the FDV theory are elaborated. The general relativistic astrophysical flow and shock solver (GRAFSS) is introduced, and some simple example problems for Computational Relativistic Astrophysics (CRA) are demonstrated.

Low rank approach to computing first and higher order derivatives using automatic differentiation

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

Reed, J. A.; Abdel-Khalik, H. S.; Utke, J.

2012-07-01

This manuscript outlines a new approach for increasing the efficiency of applying automatic differentiation (AD) to large scale computational models. By using the principles of the Efficient Subspace Method (ESM), low rank approximations of the derivatives for first and higher orders can be calculated using minimized computational resources. The output obtained from nuclear reactor calculations typically has a much smaller numerical rank compared to the number of inputs and outputs. This rank deficiency can be exploited to reduce the number of derivatives that need to be calculated using AD. The effective rank can be determined according to ESM by computingmore » derivatives with AD at random inputs. Reduced or pseudo variables are then defined and new derivatives are calculated with respect to the pseudo variables. Two different AD packages are used: OpenAD and Rapsodia. OpenAD is used to determine the effective rank and the subspace that contains the derivatives. Rapsodia is then used to calculate derivatives with respect to the pseudo variables for the desired order. The overall approach is applied to two simple problems and to MATWS, a safety code for sodium cooled reactors. (authors)« less

3D Boolean operations in virtual surgical planning.

PubMed

Charton, Jerome; Laurentjoye, Mathieu; Kim, Youngjun

2017-10-01

Boolean operations in computer-aided design or computer graphics are a set of operations (e.g. intersection, union, subtraction) between two objects (e.g. a patient model and an implant model) that are important in performing accurate and reproducible virtual surgical planning. This requires accurate and robust techniques that can handle various types of data, such as a surface extracted from volumetric data, synthetic models, and 3D scan data. This article compares the performance of the proposed method (Boolean operations by a robust, exact, and simple method between two colliding shells (BORES)) and an existing method based on the Visualization Toolkit (VTK). In all tests presented in this article, BORES could handle complex configurations as well as report impossible configurations of the input. In contrast, the VTK implementations were unstable, do not deal with singular edges and coplanar collisions, and have created several defects. The proposed method of Boolean operations, BORES, is efficient and appropriate for virtual surgical planning. Moreover, it is simple and easy to implement. In future work, we will extend the proposed method to handle non-colliding components.

A simple algorithm to improve the performance of the WENO scheme on non-uniform grids

NASA Astrophysics Data System (ADS)

Huang, Wen-Feng; Ren, Yu-Xin; Jiang, Xiong

2018-02-01

This paper presents a simple approach for improving the performance of the weighted essentially non-oscillatory (WENO) finite volume scheme on non-uniform grids. This technique relies on the reformulation of the fifth-order WENO-JS (WENO scheme presented by Jiang and Shu in J. Comput. Phys. 126:202-228, 1995) scheme designed on uniform grids in terms of one cell-averaged value and its left and/or right interfacial values of the dependent variable. The effect of grid non-uniformity is taken into consideration by a proper interpolation of the interfacial values. On non-uniform grids, the proposed scheme is much more accurate than the original WENO-JS scheme, which was designed for uniform grids. When the grid is uniform, the resulting scheme reduces to the original WENO-JS scheme. In the meantime, the proposed scheme is computationally much more efficient than the fifth-order WENO scheme designed specifically for the non-uniform grids. A number of numerical test cases are simulated to verify the performance of the present scheme.

Gradient optimization of finite projected entangled pair states

NASA Astrophysics Data System (ADS)

Liu, Wen-Yuan; Dong, Shao-Jun; Han, Yong-Jian; Guo, Guang-Can; He, Lixin

2017-05-01

Projected entangled pair states (PEPS) methods have been proven to be powerful tools to solve strongly correlated quantum many-body problems in two dimensions. However, due to the high computational scaling with the virtual bond dimension D , in a practical application, PEPS are often limited to rather small bond dimensions, which may not be large enough for some highly entangled systems, for instance, frustrated systems. Optimization of the ground state using the imaginary time evolution method with a simple update scheme may go to a larger bond dimension. However, the accuracy of the rough approximation to the environment of the local tensors is questionable. Here, we demonstrate that by combining the imaginary time evolution method with a simple update, Monte Carlo sampling techniques and gradient optimization will offer an efficient method to calculate the PEPS ground state. By taking advantage of massive parallel computing, we can study quantum systems with larger bond dimensions up to D =10 without resorting to any symmetry. Benchmark tests of the method on the J1-J2 model give impressive accuracy compared with exact results.

The Automatic Recognition of the Abnormal Sky-subtraction Spectra Based on Hadoop

NASA Astrophysics Data System (ADS)

An, An; Pan, Jingchang

2017-10-01

The skylines, superimposing on the target spectrum as a main noise, If the spectrum still contains a large number of high strength skylight residuals after sky-subtraction processing, it will not be conducive to the follow-up analysis of the target spectrum. At the same time, the LAMOST can observe a quantity of spectroscopic data in every night. We need an efficient platform to proceed the recognition of the larger numbers of abnormal sky-subtraction spectra quickly. Hadoop, as a distributed parallel data computing platform, can deal with large amounts of data effectively. In this paper, we conduct the continuum normalization firstly and then a simple and effective method will be presented to automatic recognize the abnormal sky-subtraction spectra based on Hadoop platform. Obtain through the experiment, the Hadoop platform can implement the recognition with more speed and efficiency, and the simple method can recognize the abnormal sky-subtraction spectra and find the abnormal skyline positions of different residual strength effectively, can be applied to the automatic detection of abnormal sky-subtraction of large number of spectra.

Numerical Computation of Homogeneous Slope Stability

PubMed Central

Xiao, Shuangshuang; Li, Kemin; Ding, Xiaohua; Liu, Tong

2015-01-01

To simplify the computational process of homogeneous slope stability, improve computational accuracy, and find multiple potential slip surfaces of a complex geometric slope, this study utilized the limit equilibrium method to derive expression equations of overall and partial factors of safety. This study transformed the solution of the minimum factor of safety (FOS) to solving of a constrained nonlinear programming problem and applied an exhaustive method (EM) and particle swarm optimization algorithm (PSO) to this problem. In simple slope examples, the computational results using an EM and PSO were close to those obtained using other methods. Compared to the EM, the PSO had a small computation error and a significantly shorter computation time. As a result, the PSO could precisely calculate the slope FOS with high efficiency. The example of the multistage slope analysis indicated that this slope had two potential slip surfaces. The factors of safety were 1.1182 and 1.1560, respectively. The differences between these and the minimum FOS (1.0759) were small, but the positions of the slip surfaces were completely different than the critical slip surface (CSS). PMID:25784927

Numerical computation of homogeneous slope stability.

PubMed

Xiao, Shuangshuang; Li, Kemin; Ding, Xiaohua; Liu, Tong

2015-01-01

To simplify the computational process of homogeneous slope stability, improve computational accuracy, and find multiple potential slip surfaces of a complex geometric slope, this study utilized the limit equilibrium method to derive expression equations of overall and partial factors of safety. This study transformed the solution of the minimum factor of safety (FOS) to solving of a constrained nonlinear programming problem and applied an exhaustive method (EM) and particle swarm optimization algorithm (PSO) to this problem. In simple slope examples, the computational results using an EM and PSO were close to those obtained using other methods. Compared to the EM, the PSO had a small computation error and a significantly shorter computation time. As a result, the PSO could precisely calculate the slope FOS with high efficiency. The example of the multistage slope analysis indicated that this slope had two potential slip surfaces. The factors of safety were 1.1182 and 1.1560, respectively. The differences between these and the minimum FOS (1.0759) were small, but the positions of the slip surfaces were completely different than the critical slip surface (CSS).

Design of a fault tolerant airborne digital computer. Volume 1: Architecture

NASA Technical Reports Server (NTRS)

Wensley, J. H.; Levitt, K. N.; Green, M. W.; Goldberg, J.; Neumann, P. G.

1973-01-01

This volume is concerned with the architecture of a fault tolerant digital computer for an advanced commercial aircraft. All of the computations of the aircraft, including those presently carried out by analogue techniques, are to be carried out in this digital computer. Among the important qualities of the computer are the following: (1) The capacity is to be matched to the aircraft environment. (2) The reliability is to be selectively matched to the criticality and deadline requirements of each of the computations. (3) The system is to be readily expandable. contractible, and (4) The design is to appropriate to post 1975 technology. Three candidate architectures are discussed and assessed in terms of the above qualities. Of the three candidates, a newly conceived architecture, Software Implemented Fault Tolerance (SIFT), provides the best match to the above qualities. In addition SIFT is particularly simple and believable. The other candidates, Bus Checker System (BUCS), also newly conceived in this project, and the Hopkins multiprocessor are potentially more efficient than SIFT in the use of redundancy, but otherwise are not as attractive.

Tunable, Flexible, and Efficient Optimization of Control Pulses for Practical Qubits

NASA Astrophysics Data System (ADS)

Machnes, Shai; Assémat, Elie; Tannor, David; Wilhelm, Frank K.

2018-04-01

Quantum computation places very stringent demands on gate fidelities, and experimental implementations require both the controls and the resultant dynamics to conform to hardware-specific constraints. Superconducting qubits present the additional requirement that pulses must have simple parameterizations, so they can be further calibrated in the experiment, to compensate for uncertainties in system parameters. Other quantum technologies, such as sensing, require extremely high fidelities. We present a novel, conceptually simple and easy-to-implement gradient-based optimal control technique named gradient optimization of analytic controls (GOAT), which satisfies all the above requirements, unlike previous approaches. To demonstrate GOAT's capabilities, with emphasis on flexibility and ease of subsequent calibration, we optimize fast coherence-limited pulses for two leading superconducting qubits architectures—flux-tunable transmons and fixed-frequency transmons with tunable couplers.

Comparison of different approaches of modelling in a masonry building

NASA Astrophysics Data System (ADS)

Saba, M.; Meloni, D.

2017-12-01

The present work has the objective to model a simple masonry building, through two different modelling methods in order to assess their validity in terms of evaluation of static stresses. Have been chosen two of the most commercial software used to address this kind of problem, which are of S.T.A. Data S.r.l. and Sismicad12 of Concrete S.r.l. While the 3Muri software adopts the Frame by Macro Elements Method (FME), which should be more schematic and more efficient, Sismicad12 software uses the Finite Element Method (FEM), which guarantees accurate results, with greater computational burden. Remarkably differences of the static stresses, for such a simple structure between the two approaches have been found, and an interesting comparison and analysis of the reasons is proposed.

Numerical Study of Boundary Layer Interaction with Shocks: Method Improvement and Test Computation

NASA Technical Reports Server (NTRS)

Adams, N. A.

1995-01-01

The objective is the development of a high-order and high-resolution method for the direct numerical simulation of shock turbulent-boundary-layer interaction. Details concerning the spatial discretization of the convective terms can be found in Adams and Shariff (1995). The computer code based on this method as introduced in Adams (1994) was formulated in Cartesian coordinates and thus has been limited to simple rectangular domains. For more general two-dimensional geometries, as a compression corner, an extension to generalized coordinates is necessary. To keep the requirements or limitations for grid generation low, the extended formulation should allow for non-orthogonal grids. Still, for simplicity and cost efficiency, periodicity can be assumed in one cross-flow direction. For easy vectorization, the compact-ENO coupling algorithm as used in Adams (1994) treated whole planes normal to the derivative direction with the ENO scheme whenever at least one point of this plane satisfied the detection criterion. This is apparently too restrictive for more general geometries and more complex shock patterns. Here we introduce a localized compact-ENO coupling algorithm, which is efficient as long as the overall number of grid points treated by the ENO scheme is small compared to the total number of grid points. Validation and test computations with the final code are performed to assess the efficiency and suitability of the computer code for the problems of interest. We define a set of parameters where a direct numerical simulation of a turbulent boundary layer along a compression corner with reasonably fine resolution is affordable.

Comparison of rigorous and simple vibrational models for the CO2 gasdynamic laser

NASA Technical Reports Server (NTRS)

Monson, D. J.

1977-01-01

The accuracy of a simple vibrational model for computing the gain in a CO2 gasdynamic laser is assessed by comparing results computed from it with results computed from a rigorous vibrational model. The simple model is that of Anderson et al. (1971), in which the vibrational kinetics are modeled by grouping the nonequilibrium vibrational degrees of freedom into two modes, to each of which there corresponds an equation describing vibrational relaxation. The two models agree fairly well in the computed gain at low temperatures, but the simple model predicts too high a gain at the higher temperatures of current interest. The sources of error contributing to the overestimation given by the simple model are determined by examining the simplified relaxation equations.

SSR_pipeline: a bioinformatic infrastructure for identifying microsatellites from paired-end Illumina high-throughput DNA sequencing data

USGS Publications Warehouse

Miller, Mark P.; Knaus, Brian J.; Mullins, Thomas D.; Haig, Susan M.

2013-01-01

SSR_pipeline is a flexible set of programs designed to efficiently identify simple sequence repeats (e.g., microsatellites) from paired-end high-throughput Illumina DNA sequencing data. The program suite contains 3 analysis modules along with a fourth control module that can automate analyses of large volumes of data. The modules are used to 1) identify the subset of paired-end sequences that pass Illumina quality standards, 2) align paired-end reads into a single composite DNA sequence, and 3) identify sequences that possess microsatellites (both simple and compound) conforming to user-specified parameters. The microsatellite search algorithm is extremely efficient, and we have used it to identify repeats with motifs from 2 to 25bp in length. Each of the 3 analysis modules can also be used independently to provide greater flexibility or to work with FASTQ or FASTA files generated from other sequencing platforms (Roche 454, Ion Torrent, etc.). We demonstrate use of the program with data from the brine fly Ephydra packardi (Diptera: Ephydridae) and provide empirical timing benchmarks to illustrate program performance on a common desktop computer environment. We further show that the Illumina platform is capable of identifying large numbers of microsatellites, even when using unenriched sample libraries and a very small percentage of the sequencing capacity from a single DNA sequencing run. All modules from SSR_pipeline are implemented in the Python programming language and can therefore be used from nearly any computer operating system (Linux, Macintosh, and Windows).

Multiagent optimization system for solving the traveling salesman problem (TSP).

PubMed

Xie, Xiao-Feng; Liu, Jiming

2009-04-01

The multiagent optimization system (MAOS) is a nature-inspired method, which supports cooperative search by the self-organization of a group of compact agents situated in an environment with certain sharing public knowledge. Moreover, each agent in MAOS is an autonomous entity with personal declarative memory and behavioral components. In this paper, MAOS is refined for solving the traveling salesman problem (TSP), which is a classic hard computational problem. Based on a simplified MAOS version, in which each agent manipulates on extremely limited declarative knowledge, some simple and efficient components for solving TSP, including two improving heuristics based on a generalized edge assembly recombination, are implemented. Compared with metaheuristics in adaptive memory programming, MAOS is particularly suitable for supporting cooperative search. The experimental results on two TSP benchmark data sets show that MAOS is competitive as compared with some state-of-the-art algorithms, including the Lin-Kernighan-Helsgaun, IBGLK, PHGA, etc., although MAOS does not use any explicit local search during the runtime. The contributions of MAOS components are investigated. It indicates that certain clues can be positive for making suitable selections before time-consuming computation. More importantly, it shows that the cooperative search of agents can achieve an overall good performance with a macro rule in the switch mode, which deploys certain alternate search rules with the offline performance in negative correlations. Using simple alternate rules may prevent the high difficulty of seeking an omnipotent rule that is efficient for a large data set.

SSR_pipeline: a bioinformatic infrastructure for identifying microsatellites from paired-end Illumina high-throughput DNA sequencing data.

PubMed

Miller, Mark P; Knaus, Brian J; Mullins, Thomas D; Haig, Susan M

2013-01-01

SSR_pipeline is a flexible set of programs designed to efficiently identify simple sequence repeats (e.g., microsatellites) from paired-end high-throughput Illumina DNA sequencing data. The program suite contains 3 analysis modules along with a fourth control module that can automate analyses of large volumes of data. The modules are used to 1) identify the subset of paired-end sequences that pass Illumina quality standards, 2) align paired-end reads into a single composite DNA sequence, and 3) identify sequences that possess microsatellites (both simple and compound) conforming to user-specified parameters. The microsatellite search algorithm is extremely efficient, and we have used it to identify repeats with motifs from 2 to 25 bp in length. Each of the 3 analysis modules can also be used independently to provide greater flexibility or to work with FASTQ or FASTA files generated from other sequencing platforms (Roche 454, Ion Torrent, etc.). We demonstrate use of the program with data from the brine fly Ephydra packardi (Diptera: Ephydridae) and provide empirical timing benchmarks to illustrate program performance on a common desktop computer environment. We further show that the Illumina platform is capable of identifying large numbers of microsatellites, even when using unenriched sample libraries and a very small percentage of the sequencing capacity from a single DNA sequencing run. All modules from SSR_pipeline are implemented in the Python programming language and can therefore be used from nearly any computer operating system (Linux, Macintosh, and Windows).

Fast algorithms for transforming back and forth between a signed permutation and its equivalent simple permutation.

PubMed

Gog, Simon; Bader, Martin

2008-10-01

The problem of sorting signed permutations by reversals is a well-studied problem in computational biology. The first polynomial time algorithm was presented by Hannenhalli and Pevzner in 1995. The algorithm was improved several times, and nowadays the most efficient algorithm has a subquadratic running time. Simple permutations played an important role in the development of these algorithms. Although the latest result of Tannier et al. does not require simple permutations, the preliminary version of their algorithm as well as the first polynomial time algorithm of Hannenhalli and Pevzner use the structure of simple permutations. More precisely, the latter algorithms require a precomputation that transforms a permutation into an equivalent simple permutation. To the best of our knowledge, all published algorithms for this transformation have at least a quadratic running time. For further investigations on genome rearrangement problems, the existence of a fast algorithm for the transformation could be crucial. Another important task is the back transformation, i.e. if we have a sorting on the simple permutation, transform it into a sorting on the original permutation. Again, the naive approach results in an algorithm with quadratic running time. In this paper, we present a linear time algorithm for transforming a permutation into an equivalent simple permutation, and an O(n log n) algorithm for the back transformation of the sorting sequence.

Selected computations of transonic cavity flows

NASA Technical Reports Server (NTRS)

Atwood, Christopher A.

1993-01-01

An efficient diagonal scheme implemented in an overset mesh framework has permitted the analysis of geometrically complex cavity flows via the Reynolds averaged Navier-Stokes equations. Use of rapid hyperbolic and algebraic grid methods has allowed simple specification of critical turbulent regions with an algebraic turbulence model. Comparisons between numerical and experimental results are made in two dimensions for the following problems: a backward-facing step; a resonating cavity; and two quieted cavity configurations. In three-dimensions the flow about three early concepts of the stratospheric Observatory For Infrared Astronomy (SOFIA) are compared to wind-tunnel data. Shedding frequencies of resolved shear layer structures are compared against experiment for the quieted cavities. The results demonstrate the progress of computational assessment of configuration safety and performance.

GCALIGNER 1.0: an alignment program to compute a multiple sample comparison data matrix from large eco-chemical datasets obtained by GC.

PubMed

Dellicour, Simon; Lecocq, Thomas

2013-10-01

GCALIGNER 1.0 is a computer program designed to perform a preliminary data comparison matrix of chemical data obtained by GC without MS information. The alignment algorithm is based on the comparison between the retention times of each detected compound in a sample. In this paper, we test the GCALIGNER efficiency on three datasets of the chemical secretions of bumble bees. The algorithm performs the alignment with a low error rate (<3%). GCALIGNER 1.0 is a useful, simple and free program based on an algorithm that enables the alignment of table-type data from GC. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Solid particle dynamic behavior through twisted blade rows

NASA Technical Reports Server (NTRS)

Hamed, A.

1982-01-01

The particle trajectory calculations provide the essential information which is required for predicting the pattern and intensity of turbomachinery erosion. Consequently, the evaluation of the machine performance deterioration due to erosion is extremely sensitive to the accuracy of the flow field and blade geometry representation in the trajectory computational model. A model is presented that is simple and efficient yet versatile and general to be applicable to axial, radial and mixed flow machines, and to inlets, nozzles, return passages and separators. The results of the computations are presented for the particle trajectories through a row of twisted vanes in the inlet flow field. The effect of the particle size on their trajectories, blade impacts, and on their redistribution and separation are discussed.

Data-driven indexing mechanism for the recognition of polyhedral objects

NASA Astrophysics Data System (ADS)

McLean, Stewart; Horan, Peter; Caelli, Terry M.

1992-02-01

This paper is concerned with the problem of searching large model databases. To date, most object recognition systems have concentrated on the problem of matching using simple searching algorithms. This is quite acceptable when the number of object models is small. However, in the future, general purpose computer vision systems will be required to recognize hundreds or perhaps thousands of objects and, in such circumstances, efficient searching algorithms will be needed. The problem of searching a large model database is one which must be addressed if future computer vision systems are to be at all effective. In this paper we present a method we call data-driven feature-indexed hypothesis generation as one solution to the problem of searching large model databases.

Building a computer-aided design capability using a standard time share operating system

NASA Technical Reports Server (NTRS)

Sobieszczanski, J.

1975-01-01

The paper describes how an integrated system of engineering computer programs can be built using a standard commercially available operating system. The discussion opens with an outline of the auxiliary functions that an operating system can perform for a team of engineers involved in a large and complex task. An example of a specific integrated system is provided to explain how the standard operating system features can be used to organize the programs into a simple and inexpensive but effective system. Applications to an aircraft structural design study are discussed to illustrate the use of an integrated system as a flexible and efficient engineering tool. The discussion concludes with an engineer's assessment of an operating system's capabilities and desirable improvements.

Gas-fired duplex free-piston Stirling refrigerator

NASA Astrophysics Data System (ADS)

Urieli, L.

1984-03-01

The duplex free-piston Stirling refrigerator is a potentially high efficiency, high reliability device which is ideally suited to the home appliance field, in particular as a gas-fired refrigerator. It has significant advantages over other equivalent devices including freedom from halogenated hydrocarbons, extremely low temperatures available at a high efficiency, integrated water heating, and simple burner system control. The design and development of a portable working demonstration gas-fired duplex Stirling refrigeration unit is described. A unique combination of computer aided development and experimental development was used, enabling a continued interaction between the theoretical analysis and practical testing and evaluation. A universal test rig was developed in order to separately test and evaluate major subunits, enabling a smooth system integration phase.

A subthreshold aVLSI implementation of the Izhikevich simple neuron model.

PubMed

Rangan, Venkat; Ghosh, Abhishek; Aparin, Vladimir; Cauwenberghs, Gert

2010-01-01

We present a circuit architecture for compact analog VLSI implementation of the Izhikevich neuron model, which efficiently describes a wide variety of neuron spiking and bursting dynamics using two state variables and four adjustable parameters. Log-domain circuit design utilizing MOS transistors in subthreshold results in high energy efficiency, with less than 1pJ of energy consumed per spike. We also discuss the effects of parameter variations on the dynamics of the equations, and present simulation results that replicate several types of neural dynamics. The low power operation and compact analog VLSI realization make the architecture suitable for human-machine interface applications in neural prostheses and implantable bioelectronics, as well as large-scale neural emulation tools for computational neuroscience.

An Economical Semi-Analytical Orbit Theory for Retarded Satellite Motion About an Oblate Planet

NASA Technical Reports Server (NTRS)

Gordon, R. A.

1980-01-01

Brouwer and Brouwer-Lyddanes' use of the Von Zeipel-Delaunay method is employed to develop an efficient analytical orbit theory suitable for microcomputers. A succinctly simple pseudo-phenomenologically conceptualized algorithm is introduced which accurately and economically synthesizes modeling of drag effects. The method epitomizes and manifests effortless efficient computer mechanization. Simulated trajectory data is employed to illustrate the theory's ability to accurately accommodate oblateness and drag effects for microcomputer ground based or onboard predicted orbital representation. Real tracking data is used to demonstrate that the theory's orbit determination and orbit prediction capabilities are favorably adaptable to and are comparable with results obtained utilizing complex definitive Cowell method solutions on satellites experiencing significant drag effects.

Demonstration of an ac Josephson junction laser

NASA Astrophysics Data System (ADS)

Cassidy, M. C.; Bruno, A.; Rubbert, S.; Irfan, M.; Kammhuber, J.; Schouten, R. N.; Akhmerov, A. R.; Kouwenhoven, L. P.

2017-03-01

Superconducting electronic devices have reemerged as contenders for both classical and quantum computing due to their fast operation speeds, low dissipation, and long coherence times. An ultimate demonstration of coherence is lasing. We use one of the fundamental aspects of superconductivity, the ac Josephson effect, to demonstrate a laser made from a Josephson junction strongly coupled to a multimode superconducting cavity. A dc voltage bias applied across the junction provides a source of microwave photons, and the circuit’s nonlinearity allows for efficient down-conversion of higher-order Josephson frequencies to the cavity’s fundamental mode. The simple fabrication and operation allows for easy integration with a range of quantum devices, allowing for efficient on-chip generation of coherent microwave photons at low temperatures.

FLUT - A program for aeroelastic stability analysis. [of aircraft structures in subsonic flow

NASA Technical Reports Server (NTRS)

Johnson, E. H.

1977-01-01

A computer program (FLUT) that can be used to evaluate the aeroelastic stability of aircraft structures in subsonic flow is described. The algorithm synthesizes data from a structural vibration analysis with an unsteady aerodynamics analysis and then performs a complex eigenvalue analysis to assess the system stability. The theoretical basis of the program is discussed with special emphasis placed on some innovative techniques which improve the efficiency of the analysis. User information needed to efficiently and successfully utilize the program is provided. In addition to identifying the required input, the flow of the program execution and some possible sources of difficulty are included. The use of the program is demonstrated with a listing of the input and output for a simple example.

Shared resource control between human and computer

NASA Technical Reports Server (NTRS)

Hendler, James; Wilson, Reid

1989-01-01

The advantages of an AI system of actively monitoring human control of a shared resource (such as a telerobotic manipulator) are presented. A system is described in which a simple AI planning program gains efficiency by monitoring human actions and recognizing when the actions cause a change in the system's assumed state of the world. This enables the planner to recognize when an interaction occurs between human actions and system goals, and allows maintenance of an up-to-date knowledge of the state of the world and thus informs the operator when human action would undo a goal achieved by the system, when an action would render a system goal unachievable, and efficiently replans the establishment of goals after human intervention.

Peptides at Membrane Surfaces and their Role in the Origin of Life

NASA Technical Reports Server (NTRS)

Pohorille, Andrew; Wilson, Michael A.; DeVincenzi, D. (Technical Monitor)

2002-01-01

All ancestors of contemporary cells (protocells) had to transport ions and organic matter across membranous walls, capture and utilize energy and transduce environmental signals. In modern organisms, all these functions are preformed by membrane proteins. We make the parsimonious assumption that in the protobiological milieu the same functions were carried out by their simple analogs - peptides. This, however, required that simple peptides could self-organize into ordered, functional structures. In a series of detailed, molecular-level computer simulations we demonstrated how this is possible. One example is the peptide (LSLLLSL)3 which forms a trameric bundle capable of transporting protons across membranes. Another example is the transmembrane pore of the influenza M2 protein. This aggregate of four identical alpha-helices, each built of 25 amino acids, forms an efficient and selective voltage-gated proton channel. Our simulations explain the gating mechanism in this channel. The channel can be re-engineered into a simple proton pump.

Segmentation by fusion of histogram-based k-means clusters in different color spaces.

PubMed

Mignotte, Max

2008-05-01

This paper presents a new, simple, and efficient segmentation approach, based on a fusion procedure which aims at combining several segmentation maps associated to simpler partition models in order to finally get a more reliable and accurate segmentation result. The different label fields to be fused in our application are given by the same and simple (K-means based) clustering technique on an input image expressed in different color spaces. Our fusion strategy aims at combining these segmentation maps with a final clustering procedure using as input features, the local histogram of the class labels, previously estimated and associated to each site and for all these initial partitions. This fusion framework remains simple to implement, fast, general enough to be applied to various computer vision applications (e.g., motion detection and segmentation), and has been successfully applied on the Berkeley image database. The experiments herein reported in this paper illustrate the potential of this approach compared to the state-of-the-art segmentation methods recently proposed in the literature.

Preliminary skyshine calculations for the Poloidal Diverter Tokamak Experiment

NASA Astrophysics Data System (ADS)

Nigg, D. W.; Wheeler, F. J.

1981-01-01

A calculational model is presented to estimate the radiation dose, due to the skyshine effect, in the control room and at the site boundary of the Poloidal Diverter Experiment (PDX) facility at Princeton University which requires substantial radiation shielding. The required composition and thickness of a water-filled roof shield that would reduce this effect to an acceptable level is computed, using an efficient one-dimensional model with an Sn calculation in slab geometry. The actual neutron skyshine dose is computed using a Monte Carlo model with the neutron source at the roof surface obtained from the slab Sn calculation, and the capture gamma dose is computed using a simple point-kernel single-scatter method. It is maintained that the slab model provides the exact probability of leakage out the top surface of the roof and that it is nearly as accurate as and much less costly than multi-dimensional techniques.

Preliminary skyshine calculations for the Poloidal Diverter Tokamak Experiment

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

Nigg, D.W.; Wheeler, F.J.

1981-01-01

A calculational model is presented to estimate the radiation dose, due to the skyshine effect, in the control room and at the site boundary of the Poloidal Diverter Experiment (PDX) facility at Princeton University which requires substantial radiation shielding. The required composition and thickness of a water-filled roof shield that would reduce this effect to an acceptable level is computed, using an efficient one-dimensional model with an Sn calculation in slab geometry. The actual neutron skyshine dose is computed using a Monte Carlo model with the neutron source at the roof surface obtained from the slab Sn calculation, and themore » capture gamma dose is computed using a simple point-kernel single-scatter method. It is maintained that the slab model provides the exact probability of leakage out the top surface of the roof and that it is nearly as accurate as and much less costly than multi-dimensional techniques.« less

Modeling molecule-plasmon interactions using quantized radiation fields within time-dependent electronic structure theory

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

Nascimento, Daniel R.; DePrince, A. Eugene, E-mail: deprince@chem.fsu.edu

2015-12-07

We present a combined cavity quantum electrodynamics/ab initio electronic structure approach for simulating plasmon-molecule interactions in the time domain. The simple Jaynes-Cummings-type model Hamiltonian typically utilized in such simulations is replaced with one in which the molecular component of the coupled system is treated in a fully ab initio way, resulting in a computationally efficient description of general plasmon-molecule interactions. Mutual polarization effects are easily incorporated within a standard ground-state Hartree-Fock computation, and time-dependent simulations carry the same formal computational scaling as real-time time-dependent Hartree-Fock theory. As a proof of principle, we apply this generalized method to the emergence ofmore » a Fano-like resonance in coupled molecule-plasmon systems; this feature is quite sensitive to the nanoparticle-molecule separation and the orientation of the molecule relative to the polarization of the external electric field.« less

Computational Relativistic Astrophysics Using the Flow Field-Dependent Variation Theory

NASA Technical Reports Server (NTRS)

Richardson, G. A.; Chung, T. J.

2002-01-01

We present our method for solving general relativistic nonideal hydrodynamics. Relativistic effects become pronounced in such cases as jet formation from black hole magnetized accretion disks which may lead to the study of gamma-ray bursts. Nonideal flows are present where radiation, magnetic forces, viscosities, and turbulence play an important role. Our concern in this paper is to reexamine existing numerical simulation tools as to the accuracy and efficiency of computations and introduce a new approach known as the flow field-dependent variation (FDV) method. The main feature of the FDV method consists of accommodating discontinuities of shock waves and high gradients of flow variables such as occur in turbulence and unstable motions. In this paper, the physics involved in the solution of relativistic hydrodynamics and solution strategies of the FDV theory are elaborated. The general relativistic astrophysical flow and shock solver (GRAFSS) is introduced, and some simple example problems for computational relativistic astrophysics (CRA) are demonstrated.

A novel neural network for the synthesis of antennas and microwave devices.

PubMed

Delgado, Heriberto Jose; Thursby, Michael H; Ham, Fredric M

2005-11-01

A novel artificial neural network (SYNTHESIS-ANN) is presented, which has been designed for computationally intensive problems and applied to the optimization of antennas and microwave devices. The antenna example presented is optimized with respect to voltage standing-wave ratio, bandwidth, and frequency of operation. A simple microstrip transmission line problem is used to further describe the ANN effectiveness, in which microstrip line width is optimized with respect to line impedance. The ANNs exploit a unique number representation of input and output data in conjunction with a more standard neural network architecture. An ANN consisting of a heteroassociative memory provided a very efficient method of computing necessary geometrical values for the antenna when used in conjunction with a new randomization process. The number representation used provides significant insight into this new method of fault-tolerant computing. Further work is needed to evaluate the potential of this new paradigm.

Magnetic skyrmion-based artificial neuron device

NASA Astrophysics Data System (ADS)

Li, Sai; Kang, Wang; Huang, Yangqi; Zhang, Xichao; Zhou, Yan; Zhao, Weisheng

2017-08-01

Neuromorphic computing, inspired by the biological nervous system, has attracted considerable attention. Intensive research has been conducted in this field for developing artificial synapses and neurons, attempting to mimic the behaviors of biological synapses and neurons, which are two basic elements of a human brain. Recently, magnetic skyrmions have been investigated as promising candidates in neuromorphic computing design owing to their topologically protected particle-like behaviors, nanoscale size and low driving current density. In one of our previous studies, a skyrmion-based artificial synapse was proposed, with which both short-term plasticity and long-term potentiation functions have been demonstrated. In this work, we further report on a skyrmion-based artificial neuron by exploiting the tunable current-driven skyrmion motion dynamics, mimicking the leaky-integrate-fire function of a biological neuron. With a simple single-device implementation, this proposed artificial neuron may enable us to build a dense and energy-efficient spiking neuromorphic computing system.

Multi-Scale Surface Descriptors

PubMed Central

Cipriano, Gregory; Phillips, George N.; Gleicher, Michael

2010-01-01

Local shape descriptors compactly characterize regions of a surface, and have been applied to tasks in visualization, shape matching, and analysis. Classically, curvature has be used as a shape descriptor; however, this differential property characterizes only an infinitesimal neighborhood. In this paper, we provide shape descriptors for surface meshes designed to be multi-scale, that is, capable of characterizing regions of varying size. These descriptors capture statistically the shape of a neighborhood around a central point by fitting a quadratic surface. They therefore mimic differential curvature, are efficient to compute, and encode anisotropy. We show how simple variants of mesh operations can be used to compute the descriptors without resorting to expensive parameterizations, and additionally provide a statistical approximation for reduced computational cost. We show how these descriptors apply to a number of uses in visualization, analysis, and matching of surfaces, particularly to tasks in protein surface analysis. PMID:19834190

Optimizing Integrated Terminal Airspace Operations Under Uncertainty

NASA Technical Reports Server (NTRS)

Bosson, Christabelle; Xue, Min; Zelinski, Shannon

2014-01-01

In the terminal airspace, integrated departures and arrivals have the potential to increase operations efficiency. Recent research has developed geneticalgorithm- based schedulers for integrated arrival and departure operations under uncertainty. This paper presents an alternate method using a machine jobshop scheduling formulation to model the integrated airspace operations. A multistage stochastic programming approach is chosen to formulate the problem and candidate solutions are obtained by solving sample average approximation problems with finite sample size. Because approximate solutions are computed, the proposed algorithm incorporates the computation of statistical bounds to estimate the optimality of the candidate solutions. A proof-ofconcept study is conducted on a baseline implementation of a simple problem considering a fleet mix of 14 aircraft evolving in a model of the Los Angeles terminal airspace. A more thorough statistical analysis is also performed to evaluate the impact of the number of scenarios considered in the sampled problem. To handle extensive sampling computations, a multithreading technique is introduced.

A High-Performance Genetic Algorithm: Using Traveling Salesman Problem as a Case

PubMed Central

Tsai, Chun-Wei; Tseng, Shih-Pang; Yang, Chu-Sing

2014-01-01

This paper presents a simple but efficient algorithm for reducing the computation time of genetic algorithm (GA) and its variants. The proposed algorithm is motivated by the observation that genes common to all the individuals of a GA have a high probability of surviving the evolution and ending up being part of the final solution; as such, they can be saved away to eliminate the redundant computations at the later generations of a GA. To evaluate the performance of the proposed algorithm, we use it not only to solve the traveling salesman problem but also to provide an extensive analysis on the impact it may have on the quality of the end result. Our experimental results indicate that the proposed algorithm can significantly reduce the computation time of GA and GA-based algorithms while limiting the degradation of the quality of the end result to a very small percentage compared to traditional GA. PMID:24892038

A high-performance genetic algorithm: using traveling salesman problem as a case.

PubMed

Tsai, Chun-Wei; Tseng, Shih-Pang; Chiang, Ming-Chao; Yang, Chu-Sing; Hong, Tzung-Pei

2014-01-01

This paper presents a simple but efficient algorithm for reducing the computation time of genetic algorithm (GA) and its variants. The proposed algorithm is motivated by the observation that genes common to all the individuals of a GA have a high probability of surviving the evolution and ending up being part of the final solution; as such, they can be saved away to eliminate the redundant computations at the later generations of a GA. To evaluate the performance of the proposed algorithm, we use it not only to solve the traveling salesman problem but also to provide an extensive analysis on the impact it may have on the quality of the end result. Our experimental results indicate that the proposed algorithm can significantly reduce the computation time of GA and GA-based algorithms while limiting the degradation of the quality of the end result to a very small percentage compared to traditional GA.

Modelling parallel programs and multiprocessor architectures with AXE

NASA Technical Reports Server (NTRS)

Yan, Jerry C.; Fineman, Charles E.

1991-01-01

AXE, An Experimental Environment for Parallel Systems, was designed to model and simulate for parallel systems at the process level. It provides an integrated environment for specifying computation models, multiprocessor architectures, data collection, and performance visualization. AXE is being used at NASA-Ames for developing resource management strategies, parallel problem formulation, multiprocessor architectures, and operating system issues related to the High Performance Computing and Communications Program. AXE's simple, structured user-interface enables the user to model parallel programs and machines precisely and efficiently. Its quick turn-around time keeps the user interested and productive. AXE models multicomputers. The user may easily modify various architectural parameters including the number of sites, connection topologies, and overhead for operating system activities. Parallel computations in AXE are represented as collections of autonomous computing objects known as players. Their use and behavior is described. Performance data of the multiprocessor model can be observed on a color screen. These include CPU and message routing bottlenecks, and the dynamic status of the software.

The development of computer networks: First results from a microeconomic model

NASA Astrophysics Data System (ADS)

Maier, Gunther; Kaufmann, Alexander

Computer networks like the Internet are gaining importance in social and economic life. The accelerating pace of the adoption of network technologies for business purposes is a rather recent phenomenon. Many applications are still in the early, sometimes even experimental, phase. Nevertheless, it seems to be certain that networks will change the socioeconomic structures we know today. This is the background for our special interest in the development of networks, in the role of spatial factors influencing the formation of networks, and consequences of networks on spatial structures, and in the role of externalities. This paper discusses a simple economic model - based on a microeconomic calculus - that incorporates the main factors that generate the growth of computer networks. The paper provides analytic results about the generation of computer networks. The paper discusses (1) under what conditions economic factors will initiate the process of network formation, (2) the relationship between individual and social evaluation, and (3) the efficiency of a network that is generated based on economic mechanisms.

Automated flight path planning for virtual endoscopy.

PubMed

Paik, D S; Beaulieu, C F; Jeffrey, R B; Rubin, G D; Napel, S

1998-05-01

In this paper, a novel technique for rapid and automatic computation of flight paths for guiding virtual endoscopic exploration of three-dimensional medical images is described. While manually planning flight paths is a tedious and time consuming task, our algorithm is automated and fast. Our method for positioning the virtual camera is based on the medial axis transform but is much more computationally efficient. By iteratively correcting a path toward the medial axis, the necessity of evaluating simple point criteria during morphological thinning is eliminated. The virtual camera is also oriented in a stable viewing direction, avoiding sudden twists and turns. We tested our algorithm on volumetric data sets of eight colons, one aorta and one bronchial tree. The algorithm computed the flight paths in several minutes per volume on an inexpensive workstation with minimal computation time added for multiple paths through branching structures (10%-13% per extra path). The results of our algorithm are smooth, centralized paths that aid in the task of navigation in virtual endoscopic exploration of three-dimensional medical images.

Massively parallel algorithms for real-time wavefront control of a dense adaptive optics system

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

Fijany, A.; Milman, M.; Redding, D.

1994-12-31

In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. The authors have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although, this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. They develop a novel algorithm,more » designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, this algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures. The authors also discuss two massively parallel, algorithmically specialized, architectures for low-cost and optimal implementation of the Fast Invariant Imbedding algorithm.« less

GIGA: a simple, efficient algorithm for gene tree inference in the genomic age

PubMed Central

2010-01-01

Background Phylogenetic relationships between genes are not only of theoretical interest: they enable us to learn about human genes through the experimental work on their relatives in numerous model organisms from bacteria to fruit flies and mice. Yet the most commonly used computational algorithms for reconstructing gene trees can be inaccurate for numerous reasons, both algorithmic and biological. Additional information beyond gene sequence data has been shown to improve the accuracy of reconstructions, though at great computational cost. Results We describe a simple, fast algorithm for inferring gene phylogenies, which makes use of information that was not available prior to the genomic age: namely, a reliable species tree spanning much of the tree of life, and knowledge of the complete complement of genes in a species' genome. The algorithm, called GIGA, constructs trees agglomeratively from a distance matrix representation of sequences, using simple rules to incorporate this genomic age information. GIGA makes use of a novel conceptualization of gene trees as being composed of orthologous subtrees (containing only speciation events), which are joined by other evolutionary events such as gene duplication or horizontal gene transfer. An important innovation in GIGA is that, at every step in the agglomeration process, the tree is interpreted/reinterpreted in terms of the evolutionary events that created it. Remarkably, GIGA performs well even when using a very simple distance metric (pairwise sequence differences) and no distance averaging over clades during the tree construction process. Conclusions GIGA is efficient, allowing phylogenetic reconstruction of very large gene families and determination of orthologs on a large scale. It is exceptionally robust to adding more gene sequences, opening up the possibility of creating stable identifiers for referring to not only extant genes, but also their common ancestors. We compared trees produced by GIGA to those in the TreeFam database, and they were very similar in general, with most differences likely due to poor alignment quality. However, some remaining differences are algorithmic, and can be explained by the fact that GIGA tends to put a larger emphasis on minimizing gene duplication and deletion events. PMID:20534164

GIGA: a simple, efficient algorithm for gene tree inference in the genomic age.

PubMed

Thomas, Paul D

2010-06-09

Phylogenetic relationships between genes are not only of theoretical interest: they enable us to learn about human genes through the experimental work on their relatives in numerous model organisms from bacteria to fruit flies and mice. Yet the most commonly used computational algorithms for reconstructing gene trees can be inaccurate for numerous reasons, both algorithmic and biological. Additional information beyond gene sequence data has been shown to improve the accuracy of reconstructions, though at great computational cost. We describe a simple, fast algorithm for inferring gene phylogenies, which makes use of information that was not available prior to the genomic age: namely, a reliable species tree spanning much of the tree of life, and knowledge of the complete complement of genes in a species' genome. The algorithm, called GIGA, constructs trees agglomeratively from a distance matrix representation of sequences, using simple rules to incorporate this genomic age information. GIGA makes use of a novel conceptualization of gene trees as being composed of orthologous subtrees (containing only speciation events), which are joined by other evolutionary events such as gene duplication or horizontal gene transfer. An important innovation in GIGA is that, at every step in the agglomeration process, the tree is interpreted/reinterpreted in terms of the evolutionary events that created it. Remarkably, GIGA performs well even when using a very simple distance metric (pairwise sequence differences) and no distance averaging over clades during the tree construction process. GIGA is efficient, allowing phylogenetic reconstruction of very large gene families and determination of orthologs on a large scale. It is exceptionally robust to adding more gene sequences, opening up the possibility of creating stable identifiers for referring to not only extant genes, but also their common ancestors. We compared trees produced by GIGA to those in the TreeFam database, and they were very similar in general, with most differences likely due to poor alignment quality. However, some remaining differences are algorithmic, and can be explained by the fact that GIGA tends to put a larger emphasis on minimizing gene duplication and deletion events.

Some practical universal noiseless coding techniques, part 2

NASA Technical Reports Server (NTRS)

Rice, R. F.; Lee, J. J.

1983-01-01

This report is an extension of earlier work (Part 1) which provided practical adaptive techniques for the efficient noiseless coding of a broad class of data sources characterized by only partially known and varying statistics (JPL Publication 79-22). The results here, while still claiming such general applicability, focus primarily on the noiseless coding of image data. A fairly complete and self-contained treatment is provided. Particular emphasis is given to the requirements of the forthcoming Voyager II encounters of Uranus and Neptune. Performance evaluations are supported both graphically and pictorially. Expanded definitions of the algorithms in Part 1 yield a computationally improved set of options for applications requiring efficient performance at entropies above 4 bits/sample. These expanded definitions include as an important subset, a somewhat less efficient but extremely simple "FAST' compressor which will be used at the Voyager Uranus encounter. Additionally, options are provided which enhance performance when atypical data spikes may be present.

Computer modelling of aluminum-gallium arsenide/gallium arsenide multilayer photovoltaics. M.S. Thesis

NASA Technical Reports Server (NTRS)

Wagner, Michael Broderick

1987-01-01

The modeled cascade cells offer an alternative to conventional series cascade designs that require a monolithic intercell ohmic contact. Selective electrodes provide a simple means of fabricating three-terminal devices, which can be configured in complementary pairs to circumvent the attendant losses and fabrication complexities of intercell ohmic contacts. Moreover, selective electrodes allow incorporation of additional layers in the upper subcell which can improve spectral response and increase radiation tolerance. Realistic simulations of such cells operating under one-sun AMO conditions show that the seven-layer structure is optimum from the standpoint of beginning-of-life efficiency and radiation tolerance. Projected efficiencies exceed 26 percent. Under higher concentration factors, it should be possible to achieve efficiencies beyond 30 percent. However, to simulate operation at high concentration will require a model for resistive losses. Overall, these devices appear to be a promising contender for future space applications.

Too Good to be True? Ideomotor Theory from a Computational Perspective

PubMed Central

Herbort, Oliver; Butz, Martin V.

2012-01-01

In recent years, Ideomotor Theory has regained widespread attention and sparked the development of a number of theories on goal-directed behavior and learning. However, there are two issues with previous studies’ use of Ideomotor Theory. Although Ideomotor Theory is seen as very general, it is often studied in settings that are considerably more simplistic than most natural situations. Moreover, Ideomotor Theory’s claim that effect anticipations directly trigger actions and that action-effect learning is based on the formation of direct action-effect associations is hard to address empirically. We address these points from a computational perspective. A simple computational model of Ideomotor Theory was tested in tasks with different degrees of complexity. The model evaluation showed that Ideomotor Theory is a computationally feasible approach for understanding efficient action-effect learning for goal-directed behavior if the following preconditions are met: (1) The range of potential actions and effects has to be restricted. (2) Effects have to follow actions within a short time window. (3) Actions have to be simple and may not require sequencing. The first two preconditions also limit human performance and thus support Ideomotor Theory. The last precondition can be circumvented by extending the model with more complex, indirect action generation processes. In conclusion, we suggest that Ideomotor Theory offers a comprehensive framework to understand action-effect learning. However, we also suggest that additional processes may mediate the conversion of effect anticipations into actions in many situations. PMID:23162524

Local coding based matching kernel method for image classification.

PubMed

Song, Yan; McLoughlin, Ian Vince; Dai, Li-Rong

2014-01-01

This paper mainly focuses on how to effectively and efficiently measure visual similarity for local feature based representation. Among existing methods, metrics based on Bag of Visual Word (BoV) techniques are efficient and conceptually simple, at the expense of effectiveness. By contrast, kernel based metrics are more effective, but at the cost of greater computational complexity and increased storage requirements. We show that a unified visual matching framework can be developed to encompass both BoV and kernel based metrics, in which local kernel plays an important role between feature pairs or between features and their reconstruction. Generally, local kernels are defined using Euclidean distance or its derivatives, based either explicitly or implicitly on an assumption of Gaussian noise. However, local features such as SIFT and HoG often follow a heavy-tailed distribution which tends to undermine the motivation behind Euclidean metrics. Motivated by recent advances in feature coding techniques, a novel efficient local coding based matching kernel (LCMK) method is proposed. This exploits the manifold structures in Hilbert space derived from local kernels. The proposed method combines advantages of both BoV and kernel based metrics, and achieves a linear computational complexity. This enables efficient and scalable visual matching to be performed on large scale image sets. To evaluate the effectiveness of the proposed LCMK method, we conduct extensive experiments with widely used benchmark datasets, including 15-Scenes, Caltech101/256, PASCAL VOC 2007 and 2011 datasets. Experimental results confirm the effectiveness of the relatively efficient LCMK method.

Integral Images: Efficient Algorithms for Their Computation and Storage in Resource-Constrained Embedded Vision Systems

PubMed Central

Ehsan, Shoaib; Clark, Adrian F.; ur Rehman, Naveed; McDonald-Maier, Klaus D.

2015-01-01

The integral image, an intermediate image representation, has found extensive use in multi-scale local feature detection algorithms, such as Speeded-Up Robust Features (SURF), allowing fast computation of rectangular features at constant speed, independent of filter size. For resource-constrained real-time embedded vision systems, computation and storage of integral image presents several design challenges due to strict timing and hardware limitations. Although calculation of the integral image only consists of simple addition operations, the total number of operations is large owing to the generally large size of image data. Recursive equations allow substantial decrease in the number of operations but require calculation in a serial fashion. This paper presents two new hardware algorithms that are based on the decomposition of these recursive equations, allowing calculation of up to four integral image values in a row-parallel way without significantly increasing the number of operations. An efficient design strategy is also proposed for a parallel integral image computation unit to reduce the size of the required internal memory (nearly 35% for common HD video). Addressing the storage problem of integral image in embedded vision systems, the paper presents two algorithms which allow substantial decrease (at least 44.44%) in the memory requirements. Finally, the paper provides a case study that highlights the utility of the proposed architectures in embedded vision systems. PMID:26184211

Methods for Efficiently and Accurately Computing Quantum Mechanical Free Energies for Enzyme Catalysis.

PubMed

Kearns, F L; Hudson, P S; Boresch, S; Woodcock, H L

2016-01-01

Enzyme activity is inherently linked to free energies of transition states, ligand binding, protonation/deprotonation, etc.; these free energies, and thus enzyme function, can be affected by residue mutations, allosterically induced conformational changes, and much more. Therefore, being able to predict free energies associated with enzymatic processes is critical to understanding and predicting their function. Free energy simulation (FES) has historically been a computational challenge as it requires both the accurate description of inter- and intramolecular interactions and adequate sampling of all relevant conformational degrees of freedom. The hybrid quantum mechanical molecular mechanical (QM/MM) framework is the current tool of choice when accurate computations of macromolecular systems are essential. Unfortunately, robust and efficient approaches that employ the high levels of computational theory needed to accurately describe many reactive processes (ie, ab initio, DFT), while also including explicit solvation effects and accounting for extensive conformational sampling are essentially nonexistent. In this chapter, we will give a brief overview of two recently developed methods that mitigate several major challenges associated with QM/MM FES: the QM non-Boltzmann Bennett's acceptance ratio method and the QM nonequilibrium work method. We will also describe usage of these methods to calculate free energies associated with (1) relative properties and (2) along reaction paths, using simple test cases with relevance to enzymes examples. © 2016 Elsevier Inc. All rights reserved.

Users manual for updated computer code for axial-flow compressor conceptual design

NASA Technical Reports Server (NTRS)

Glassman, Arthur J.

1992-01-01

An existing computer code that determines the flow path for an axial-flow compressor either for a given number of stages or for a given overall pressure ratio was modified for use in air-breathing engine conceptual design studies. This code uses a rapid approximate design methodology that is based on isentropic simple radial equilibrium. Calculations are performed at constant-span-fraction locations from tip to hub. Energy addition per stage is controlled by specifying the maximum allowable values for several aerodynamic design parameters. New modeling was introduced to the code to overcome perceived limitations. Specific changes included variable rather than constant tip radius, flow path inclination added to the continuity equation, input of mass flow rate directly rather than indirectly as inlet axial velocity, solution for the exact value of overall pressure ratio rather than for any value that met or exceeded it, and internal computation of efficiency rather than the use of input values. The modified code was shown to be capable of computing efficiencies that are compatible with those of five multistage compressors and one fan that were tested experimentally. This report serves as a users manual for the revised code, Compressor Spanline Analysis (CSPAN). The modeling modifications, including two internal loss correlations, are presented. Program input and output are described. A sample case for a multistage compressor is included.

LightWAVE: Waveform and Annotation Viewing and Editing in a Web Browser.

PubMed

Moody, George B

2013-09-01

This paper describes LightWAVE, recently-developed open-source software for viewing ECGs and other physiologic waveforms and associated annotations (event markers). It supports efficient interactive creation and modification of annotations, capabilities that are essential for building new collections of physiologic signals and time series for research. LightWAVE is constructed of components that interact in simple ways, making it straightforward to enhance or replace any of them. The back end (server) is a common gateway interface (CGI) application written in C for speed and efficiency. It retrieves data from its data repository (PhysioNet's open-access PhysioBank archives by default, or any set of files or web pages structured as in PhysioBank) and delivers them in response to requests generated by the front end. The front end (client) is a web application written in JavaScript. It runs within any modern web browser and does not require installation on the user's computer, tablet, or phone. Finally, LightWAVE's scribe is a tiny CGI application written in Perl, which records the user's edits in annotation files. LightWAVE's data repository, back end, and front end can be located on the same computer or on separate computers. The data repository may be split across multiple computers. For compatibility with the standard browser security model, the front end and the scribe must be loaded from the same domain.

Integral Images: Efficient Algorithms for Their Computation and Storage in Resource-Constrained Embedded Vision Systems.

PubMed

Ehsan, Shoaib; Clark, Adrian F; Naveed ur Rehman; McDonald-Maier, Klaus D

2015-07-10

The integral image, an intermediate image representation, has found extensive use in multi-scale local feature detection algorithms, such as Speeded-Up Robust Features (SURF), allowing fast computation of rectangular features at constant speed, independent of filter size. For resource-constrained real-time embedded vision systems, computation and storage of integral image presents several design challenges due to strict timing and hardware limitations. Although calculation of the integral image only consists of simple addition operations, the total number of operations is large owing to the generally large size of image data. Recursive equations allow substantial decrease in the number of operations but require calculation in a serial fashion. This paper presents two new hardware algorithms that are based on the decomposition of these recursive equations, allowing calculation of up to four integral image values in a row-parallel way without significantly increasing the number of operations. An efficient design strategy is also proposed for a parallel integral image computation unit to reduce the size of the required internal memory (nearly 35% for common HD video). Addressing the storage problem of integral image in embedded vision systems, the paper presents two algorithms which allow substantial decrease (at least 44.44%) in the memory requirements. Finally, the paper provides a case study that highlights the utility of the proposed architectures in embedded vision systems.

Finding all solutions of nonlinear equations using the dual simplex method

NASA Astrophysics Data System (ADS)

Yamamura, Kiyotaka; Fujioka, Tsuyoshi

2003-03-01

Recently, an efficient algorithm has been proposed for finding all solutions of systems of nonlinear equations using linear programming. This algorithm is based on a simple test (termed the LP test) for nonexistence of a solution to a system of nonlinear equations using the dual simplex method. In this letter, an improved version of the LP test algorithm is proposed. By numerical examples, it is shown that the proposed algorithm could find all solutions of a system of 300 nonlinear equations in practical computation time.

Trinary signed-digit arithmetic using an efficient encoding scheme

NASA Astrophysics Data System (ADS)

Salim, W. Y.; Alam, M. S.; Fyath, R. S.; Ali, S. A.

2000-09-01

The trinary signed-digit (TSD) number system is of interest for ultrafast optoelectronic computing systems since it permits parallel carry-free addition and borrow-free subtraction of two arbitrary length numbers in constant time. In this paper, a simple coding scheme is proposed to encode the decimal number directly into the TSD form. The coding scheme enables one to perform parallel one-step TSD arithmetic operation. The proposed coding scheme uses only a 5-combination coding table instead of the 625-combination table reported recently for recoded TSD arithmetic technique.

One-step trinary signed-digit arithmetic using an efficient encoding scheme

NASA Astrophysics Data System (ADS)

Salim, W. Y.; Fyath, R. S.; Ali, S. A.; Alam, Mohammad S.

2000-11-01

The trinary signed-digit (TSD) number system is of interest for ultra fast optoelectronic computing systems since it permits parallel carry-free addition and borrow-free subtraction of two arbitrary length numbers in constant time. In this paper, a simple coding scheme is proposed to encode the decimal number directly into the TSD form. The coding scheme enables one to perform parallel one-step TSD arithmetic operation. The proposed coding scheme uses only a 5-combination coding table instead of the 625-combination table reported recently for recoded TSD arithmetic technique.

Alternating Direction Implicit (ADI) schemes for a PDE-based image osmosis model

NASA Astrophysics Data System (ADS)

Calatroni, L.; Estatico, C.; Garibaldi, N.; Parisotto, S.

2017-10-01

We consider Alternating Direction Implicit (ADI) splitting schemes to compute efficiently the numerical solution of the PDE osmosis model considered by Weickert et al. in [10] for several imaging applications. The discretised scheme is shown to preserve analogous properties to the continuous model. The dimensional splitting strategy traduces numerically into the solution of simple tridiagonal systems for which standard matrix factorisation techniques can be used to improve upon the performance of classical implicit methods, even for large time steps. Applications to the shadow removal problem are presented.

Faster Heavy Ion Transport for HZETRN

NASA Technical Reports Server (NTRS)

Slaba, Tony C.

2013-01-01

The deterministic particle transport code HZETRN was developed to enable fast and accurate space radiation transport through materials. As more complex transport solutions are implemented for neutrons, light ions (Z < 2), mesons, and leptons, it is important to maintain overall computational efficiency. In this work, the heavy ion (Z > 2) transport algorithm in HZETRN is reviewed, and a simple modification is shown to provide an approximate 5x decrease in execution time for galactic cosmic ray transport. Convergence tests and other comparisons are carried out to verify that numerical accuracy is maintained in the new algorithm.

Symbolic computation of equivalence transformations and parameter reduction for nonlinear physical models

NASA Astrophysics Data System (ADS)

Cheviakov, Alexei F.

2017-11-01

An efficient systematic procedure is provided for symbolic computation of Lie groups of equivalence transformations and generalized equivalence transformations of systems of differential equations that contain arbitrary elements (arbitrary functions and/or arbitrary constant parameters), using the software package GeM for Maple. Application of equivalence transformations to the reduction of the number of arbitrary elements in a given system of equations is discussed, and several examples are considered. The first computational example of generalized equivalence transformations where the transformation of the dependent variable involves an arbitrary constitutive function is presented. As a detailed physical example, a three-parameter family of nonlinear wave equations describing finite anti-plane shear displacements of an incompressible hyperelastic fiber-reinforced medium is considered. Equivalence transformations are computed and employed to radically simplify the model for an arbitrary fiber direction, invertibly reducing the model to a simple form that corresponds to a special fiber direction, and involves no arbitrary elements. The presented computation algorithm is applicable to wide classes of systems of differential equations containing arbitrary elements.

Towards a cyber-physical era: soft computing framework based multi-sensor array for water quality monitoring

NASA Astrophysics Data System (ADS)

Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Gupta, Rajiv

2018-02-01

New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.

Influence of urban pattern on inundation flow in floodplains of lowland rivers.

PubMed

Bruwier, M; Mustafa, A; Aliaga, D G; Archambeau, P; Erpicum, S; Nishida, G; Zhang, X; Pirotton, M; Teller, J; Dewals, B

2018-05-01

The objective of this paper is to investigate the respective influence of various urban pattern characteristics on inundation flow. A set of 2000 synthetic urban patterns were generated using an urban procedural model providing locations and shapes of streets and buildings over a square domain of 1×1km 2 . Steady two-dimensional hydraulic computations were performed over the 2000 urban patterns with identical hydraulic boundary conditions. To run such a large amount of simulations, the computational efficiency of the hydraulic model was improved by using an anisotropic porosity model. This model computes on relatively coarse computational cells, but preserves information from the detailed topographic data through porosity parameters. Relationships between urban characteristics and the computed inundation water depths have been based on multiple linear regressions. Finally, a simple mechanistic model based on two district-scale porosity parameters, combining several urban characteristics, is shown to capture satisfactorily the influence of urban characteristics on inundation water depths. The findings of this study give guidelines for more flood-resilient urban planning. Copyright © 2017 Elsevier B.V. All rights reserved.

A Round-Efficient Authenticated Key Agreement Scheme Based on Extended Chaotic Maps for Group Cloud Meeting

PubMed Central

Lee, Tian-Fu; Wang, Zeng-Bo

2017-01-01

The security is a critical issue for business purposes. For example, the cloud meeting must consider strong security to maintain the communication privacy. Considering the scenario with cloud meeting, we apply extended chaotic map to present passwordless group authentication key agreement, termed as Passwordless Group Authentication Key Agreement (PL-GAKA). PL-GAKA improves the computation efficiency for the simple group password-based authenticated key agreement (SGPAKE) proposed by Lee et al. in terms of computing the session key. Since the extended chaotic map has equivalent security level to the Diffie–Hellman key exchange scheme applied by SGPAKE, the security of PL-GAKA is not sacrificed when improving the computation efficiency. Moreover, PL-GAKA is a passwordless scheme, so the password maintenance is not necessary. Short-term authentication is considered, hence the communication security is stronger than other protocols by dynamically generating session key in each cloud meeting. In our analysis, we first prove that each meeting member can get the correct information during the meeting. We analyze common security issues for the proposed PL-GAKA in terms of session key security, mutual authentication, perfect forward security, and data integrity. Moreover, we also demonstrate that communicating in PL-GAKA is secure when suffering replay attacks, impersonation attacks, privileged insider attacks, and stolen-verifier attacks. Eventually, an overall comparison is given to show the performance between PL-GAKA, SGPAKE and related solutions. PMID:29207509

Learning Optimized Local Difference Binaries for Scalable Augmented Reality on Mobile Devices.

PubMed

Xin Yang; Kwang-Ting Cheng

2014-06-01

The efficiency, robustness and distinctiveness of a feature descriptor are critical to the user experience and scalability of a mobile augmented reality (AR) system. However, existing descriptors are either too computationally expensive to achieve real-time performance on a mobile device such as a smartphone or tablet, or not sufficiently robust and distinctive to identify correct matches from a large database. As a result, current mobile AR systems still only have limited capabilities, which greatly restrict their deployment in practice. In this paper, we propose a highly efficient, robust and distinctive binary descriptor, called Learning-based Local Difference Binary (LLDB). LLDB directly computes a binary string for an image patch using simple intensity and gradient difference tests on pairwise grid cells within the patch. To select an optimized set of grid cell pairs, we densely sample grid cells from an image patch and then leverage a modified AdaBoost algorithm to automatically extract a small set of critical ones with the goal of maximizing the Hamming distance between mismatches while minimizing it between matches. Experimental results demonstrate that LLDB is extremely fast to compute and to match against a large database due to its high robustness and distinctiveness. Compared to the state-of-the-art binary descriptors, primarily designed for speed, LLDB has similar efficiency for descriptor construction, while achieving a greater accuracy and faster matching speed when matching over a large database with 2.3M descriptors on mobile devices.

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

Turner, A.; Davis, A.; University of Wisconsin-Madison, Madison, WI 53706

CCFE perform Monte-Carlo transport simulations on large and complex tokamak models such as ITER. Such simulations are challenging since streaming and deep penetration effects are equally important. In order to make such simulations tractable, both variance reduction (VR) techniques and parallel computing are used. It has been found that the application of VR techniques in such models significantly reduces the efficiency of parallel computation due to 'long histories'. VR in MCNP can be accomplished using energy-dependent weight windows. The weight window represents an 'average behaviour' of particles, and large deviations in the arriving weight of a particle give rise tomore » extreme amounts of splitting being performed and a long history. When running on parallel clusters, a long history can have a detrimental effect on the parallel efficiency - if one process is computing the long history, the other CPUs complete their batch of histories and wait idle. Furthermore some long histories have been found to be effectively intractable. To combat this effect, CCFE has developed an adaptation of MCNP which dynamically adjusts the WW where a large weight deviation is encountered. The method effectively 'de-optimises' the WW, reducing the VR performance but this is offset by a significant increase in parallel efficiency. Testing with a simple geometry has shown the method does not bias the result. This 'long history method' has enabled CCFE to significantly improve the performance of MCNP calculations for ITER on parallel clusters, and will be beneficial for any geometry combining streaming and deep penetration effects. (authors)« less

A Study of Neutron Leakage in Finite Objects

NASA Technical Reports Server (NTRS)

Wilson, John W.; Slaba, Tony C.; Badavi, Francis F.; Reddell, Brandon D.; Bahadori, Amir A.

2015-01-01

A computationally efficient 3DHZETRN code capable of simulating High charge (Z) and Energy (HZE) and light ions (including neutrons) under space-like boundary conditions with enhanced neutron and light ion propagation was recently developed for simple shielded objects. Monte Carlo (MC) benchmarks were used to verify the 3DHZETRN methodology in slab and spherical geometry, and it was shown that 3DHZETRN agrees with MC codes to the degree that various MC codes agree among themselves. One limitation in the verification process is that all of the codes (3DHZETRN and three MC codes) utilize different nuclear models/databases. In the present report, the new algorithm, with well-defined convergence criteria, is used to quantify the neutron leakage from simple geometries to provide means of verifying 3D effects and to provide guidance for further code development.

Modeling VLF signal modulation during solar flares with GEANT4 Monte Carlo simulation, a simple chemical model and LWPC

NASA Astrophysics Data System (ADS)

Palit, Sourav; Chakrabarti, Sandip Kumar; Pal, Sujay; Basak, Tamal

Extra ionization by X-rays during solar flares affects VLF signal propagation through D-region ionosphere. Ionization produced in the lower ionosphere due to X-ray spectra of solar flares are simulated with an efficient detector simulation program, GEANT4. The balancing between the ionization and loss processes, causing the lower ionosphere to settle back to its undisturbed state is handled with a simple chemical model consisting of four broad species of ion densities. Using the electron densities, modified VLF signal amplitude is then computed with LWPC code. VLF signal along NWC (Australia) to IERC/ICSP (India) propagation path is examined during a M and a X-type solar flares and observational deviations are compared with simulated results. The agreement is found to be excellent.

Computer Technology for Industry

NASA Technical Reports Server (NTRS)

1979-01-01

In this age of the computer, more and more business firms are automating their operations for increased efficiency in a great variety of jobs, from simple accounting to managing inventories, from precise machining to analyzing complex structures. In the interest of national productivity, NASA is providing assistance both to longtime computer users and newcomers to automated operations. Through a special technology utilization service, NASA saves industry time and money by making available already developed computer programs which have secondary utility. A computer program is essentially a set of instructions which tells the computer how to produce desired information or effect by drawing upon its stored input. Developing a new program from scratch can be costly and time-consuming. Very often, however, a program developed for one purpose can readily be adapted to a totally different application. To help industry take advantage of existing computer technology, NASA operates the Computer Software Management and Information Center (COSMIC)(registered TradeMark),located at the University of Georgia. COSMIC maintains a large library of computer programs developed for NASA, the Department of Defense, the Department of Energy and other technology-generating agencies of the government. The Center gets a continual flow of software packages, screens them for adaptability to private sector usage, stores them and informs potential customers of their availability.

Runtime and Architecture Support for Efficient Data Exchange in Multi-Accelerator Applications.

PubMed

Cabezas, Javier; Gelado, Isaac; Stone, John E; Navarro, Nacho; Kirk, David B; Hwu, Wen-Mei

2015-05-01

Heterogeneous parallel computing applications often process large data sets that require multiple GPUs to jointly meet their needs for physical memory capacity and compute throughput. However, the lack of high-level abstractions in previous heterogeneous parallel programming models force programmers to resort to multiple code versions, complex data copy steps and synchronization schemes when exchanging data between multiple GPU devices, which results in high software development cost, poor maintainability, and even poor performance. This paper describes the HPE runtime system, and the associated architecture support, which enables a simple, efficient programming interface for exchanging data between multiple GPUs through either interconnects or cross-node network interfaces. The runtime and architecture support presented in this paper can also be used to support other types of accelerators. We show that the simplified programming interface reduces programming complexity. The research presented in this paper started in 2009. It has been implemented and tested extensively in several generations of HPE runtime systems as well as adopted into the NVIDIA GPU hardware and drivers for CUDA 4.0 and beyond since 2011. The availability of real hardware that support key HPE features gives rise to a rare opportunity for studying the effectiveness of the hardware support by running important benchmarks on real runtime and hardware. Experimental results show that in a exemplar heterogeneous system, peer DMA and double-buffering, pinned buffers, and software techniques can improve the inter-accelerator data communication bandwidth by 2×. They can also improve the execution speed by 1.6× for a 3D finite difference, 2.5× for 1D FFT, and 1.6× for merge sort, all measured on real hardware. The proposed architecture support enables the HPE runtime to transparently deploy these optimizations under simple portable user code, allowing system designers to freely employ devices of different capabilities. We further argue that simple interfaces such as HPE are needed for most applications to benefit from advanced hardware features in practice.

Runtime and Architecture Support for Efficient Data Exchange in Multi-Accelerator Applications

PubMed Central

Cabezas, Javier; Gelado, Isaac; Stone, John E.; Navarro, Nacho; Kirk, David B.; Hwu, Wen-mei

2014-01-01

Heterogeneous parallel computing applications often process large data sets that require multiple GPUs to jointly meet their needs for physical memory capacity and compute throughput. However, the lack of high-level abstractions in previous heterogeneous parallel programming models force programmers to resort to multiple code versions, complex data copy steps and synchronization schemes when exchanging data between multiple GPU devices, which results in high software development cost, poor maintainability, and even poor performance. This paper describes the HPE runtime system, and the associated architecture support, which enables a simple, efficient programming interface for exchanging data between multiple GPUs through either interconnects or cross-node network interfaces. The runtime and architecture support presented in this paper can also be used to support other types of accelerators. We show that the simplified programming interface reduces programming complexity. The research presented in this paper started in 2009. It has been implemented and tested extensively in several generations of HPE runtime systems as well as adopted into the NVIDIA GPU hardware and drivers for CUDA 4.0 and beyond since 2011. The availability of real hardware that support key HPE features gives rise to a rare opportunity for studying the effectiveness of the hardware support by running important benchmarks on real runtime and hardware. Experimental results show that in a exemplar heterogeneous system, peer DMA and double-buffering, pinned buffers, and software techniques can improve the inter-accelerator data communication bandwidth by 2×. They can also improve the execution speed by 1.6× for a 3D finite difference, 2.5× for 1D FFT, and 1.6× for merge sort, all measured on real hardware. The proposed architecture support enables the HPE runtime to transparently deploy these optimizations under simple portable user code, allowing system designers to freely employ devices of different capabilities. We further argue that simple interfaces such as HPE are needed for most applications to benefit from advanced hardware features in practice. PMID:26180487

Cloud-Based Tools to Support High-Resolution Modeling (Invited)

NASA Astrophysics Data System (ADS)

Jones, N.; Nelson, J.; Swain, N.; Christensen, S.

2013-12-01

The majority of watershed models developed to support decision-making by water management agencies are simple, lumped-parameter models. Maturity in research codes and advances in the computational power from multi-core processors on desktop machines, commercial cloud-computing resources, and supercomputers with thousands of cores have created new opportunities for employing more accurate, high-resolution distributed models for routine use in decision support. The barriers for using such models on a more routine basis include massive amounts of spatial data that must be processed for each new scenario and lack of efficient visualization tools. In this presentation we will review a current NSF-funded project called CI-WATER that is intended to overcome many of these roadblocks associated with high-resolution modeling. We are developing a suite of tools that will make it possible to deploy customized web-based apps for running custom scenarios for high-resolution models with minimal effort. These tools are based on a software stack that includes 52 North, MapServer, PostGIS, HT Condor, CKAN, and Python. This open source stack provides a simple scripting environment for quickly configuring new custom applications for running high-resolution models as geoprocessing workflows. The HT Condor component facilitates simple access to local distributed computers or commercial cloud resources when necessary for stochastic simulations. The CKAN framework provides a powerful suite of tools for hosting such workflows in a web-based environment that includes visualization tools and storage of model simulations in a database to archival, querying, and sharing of model results. Prototype applications including land use change, snow melt, and burned area analysis will be presented. This material is based upon work supported by the National Science Foundation under Grant No. 1135482

Need for speed: An optimized gridding approach for spatially explicit disease simulations.

PubMed

Sellman, Stefan; Tsao, Kimberly; Tildesley, Michael J; Brommesson, Peter; Webb, Colleen T; Wennergren, Uno; Keeling, Matt J; Lindström, Tom

2018-04-01

Numerical models for simulating outbreaks of infectious diseases are powerful tools for informing surveillance and control strategy decisions. However, large-scale spatially explicit models can be limited by the amount of computational resources they require, which poses a problem when multiple scenarios need to be explored to provide policy recommendations. We introduce an easily implemented method that can reduce computation time in a standard Susceptible-Exposed-Infectious-Removed (SEIR) model without introducing any further approximations or truncations. It is based on a hierarchical infection process that operates on entire groups of spatially related nodes (cells in a grid) in order to efficiently filter out large volumes of susceptible nodes that would otherwise have required expensive calculations. After the filtering of the cells, only a subset of the nodes that were originally at risk are then evaluated for actual infection. The increase in efficiency is sensitive to the exact configuration of the grid, and we describe a simple method to find an estimate of the optimal configuration of a given landscape as well as a method to partition the landscape into a grid configuration. To investigate its efficiency, we compare the introduced methods to other algorithms and evaluate computation time, focusing on simulated outbreaks of foot-and-mouth disease (FMD) on the farm population of the USA, the UK and Sweden, as well as on three randomly generated populations with varying degree of clustering. The introduced method provided up to 500 times faster calculations than pairwise computation, and consistently performed as well or better than other available methods. This enables large scale, spatially explicit simulations such as for the entire continental USA without sacrificing realism or predictive power.

Need for speed: An optimized gridding approach for spatially explicit disease simulations

PubMed Central

Tildesley, Michael J.; Brommesson, Peter; Webb, Colleen T.; Wennergren, Uno; Lindström, Tom

2018-01-01

Numerical models for simulating outbreaks of infectious diseases are powerful tools for informing surveillance and control strategy decisions. However, large-scale spatially explicit models can be limited by the amount of computational resources they require, which poses a problem when multiple scenarios need to be explored to provide policy recommendations. We introduce an easily implemented method that can reduce computation time in a standard Susceptible-Exposed-Infectious-Removed (SEIR) model without introducing any further approximations or truncations. It is based on a hierarchical infection process that operates on entire groups of spatially related nodes (cells in a grid) in order to efficiently filter out large volumes of susceptible nodes that would otherwise have required expensive calculations. After the filtering of the cells, only a subset of the nodes that were originally at risk are then evaluated for actual infection. The increase in efficiency is sensitive to the exact configuration of the grid, and we describe a simple method to find an estimate of the optimal configuration of a given landscape as well as a method to partition the landscape into a grid configuration. To investigate its efficiency, we compare the introduced methods to other algorithms and evaluate computation time, focusing on simulated outbreaks of foot-and-mouth disease (FMD) on the farm population of the USA, the UK and Sweden, as well as on three randomly generated populations with varying degree of clustering. The introduced method provided up to 500 times faster calculations than pairwise computation, and consistently performed as well or better than other available methods. This enables large scale, spatially explicit simulations such as for the entire continental USA without sacrificing realism or predictive power. PMID:29624574

Novel patch modelling method for efficient simulation and prediction uncertainty analysis of multi-scale groundwater flow and transport processes

NASA Astrophysics Data System (ADS)

Sreekanth, J.; Moore, Catherine

2018-04-01

The application of global sensitivity and uncertainty analysis techniques to groundwater models of deep sedimentary basins are typically challenged by large computational burdens combined with associated numerical stability issues. The highly parameterized approaches required for exploring the predictive uncertainty associated with the heterogeneous hydraulic characteristics of multiple aquifers and aquitards in these sedimentary basins exacerbate these issues. A novel Patch Modelling Methodology is proposed for improving the computational feasibility of stochastic modelling analysis of large-scale and complex groundwater models. The method incorporates a nested groundwater modelling framework that enables efficient simulation of groundwater flow and transport across multiple spatial and temporal scales. The method also allows different processes to be simulated within different model scales. Existing nested model methodologies are extended by employing 'joining predictions' for extrapolating prediction-salient information from one model scale to the next. This establishes a feedback mechanism supporting the transfer of information from child models to parent models as well as parent models to child models in a computationally efficient manner. This feedback mechanism is simple and flexible and ensures that while the salient small scale features influencing larger scale prediction are transferred back to the larger scale, this does not require the live coupling of models. This method allows the modelling of multiple groundwater flow and transport processes using separate groundwater models that are built for the appropriate spatial and temporal scales, within a stochastic framework, while also removing the computational burden associated with live model coupling. The utility of the method is demonstrated by application to an actual large scale aquifer injection scheme in Australia.

A simple, robust and efficient high-order accurate shock-capturing scheme for compressible flows: Towards minimalism

NASA Astrophysics Data System (ADS)

Ohwada, Taku; Shibata, Yuki; Kato, Takuma; Nakamura, Taichi

2018-06-01

Developed is a high-order accurate shock-capturing scheme for the compressible Euler/Navier-Stokes equations; the formal accuracy is 5th order in space and 4th order in time. The performance and efficiency of the scheme are validated in various numerical tests. The main ingredients of the scheme are nothing special; they are variants of the standard numerical flux, MUSCL, the usual Lagrange's polynomial and the conventional Runge-Kutta method. The scheme can compute a boundary layer accurately with a rational resolution and capture a stationary contact discontinuity sharply without inner points. And yet it is endowed with high resistance against shock anomalies (carbuncle phenomenon, post-shock oscillations, etc.). A good balance between high robustness and low dissipation is achieved by blending three types of numerical fluxes according to physical situation in an intuitively easy-to-understand way. The performance of the scheme is largely comparable to that of WENO5-Rusanov, while its computational cost is 30-40% less than of that of the advanced scheme.

Development of the 3DHZETRN code for space radiation protection

NASA Astrophysics Data System (ADS)

Wilson, John; Badavi, Francis; Slaba, Tony; Reddell, Brandon; Bahadori, Amir; Singleterry, Robert

Space radiation protection requires computationally efficient shield assessment methods that have been verified and validated. The HZETRN code is the engineering design code used for low Earth orbit dosimetric analysis and astronaut record keeping with end-to-end validation to twenty percent in Space Shuttle and International Space Station operations. HZETRN treated diffusive leakage only at the distal surface limiting its application to systems with a large radius of curvature. A revision of HZETRN that included forward and backward diffusion allowed neutron leakage to be evaluated at both the near and distal surfaces. That revision provided a deterministic code of high computational efficiency that was in substantial agreement with Monte Carlo (MC) codes in flat plates (at least to the degree that MC codes agree among themselves). In the present paper, the 3DHZETRN formalism capable of evaluation in general geometry is described. Benchmarking will help quantify uncertainty with MC codes (Geant4, FLUKA, MCNP6, and PHITS) in simple shapes such as spheres within spherical shells and boxes. Connection of the 3DHZETRN to general geometry will be discussed.

Efficient Computing Budget Allocation for Finding Simplest Good Designs

PubMed Central

Jia, Qing-Shan; Zhou, Enlu; Chen, Chun-Hung

2012-01-01

In many applications some designs are easier to implement, require less training data and shorter training time, and consume less storage than the others. Such designs are called simple designs, and are usually preferred over complex ones when they all have good performance. Despite the abundant existing studies on how to find good designs in simulation-based optimization (SBO), there exist few studies on finding simplest good designs. We consider this important problem in this paper, and make the following contributions. First, we provide lower bounds for the probabilities of correctly selecting the m simplest designs with top performance, and selecting the best m such simplest good designs, respectively. Second, we develop two efficient computing budget allocation methods to find m simplest good designs and to find the best m such designs, respectively; and show their asymptotic optimalities. Third, we compare the performance of the two methods with equal allocations over 6 academic examples and a smoke detection problem in wireless sensor networks. We hope that this work brings insight to finding the simplest good designs in general. PMID:23687404

GW/Bethe-Salpeter calculations for charged and model systems from real-space DFT

NASA Astrophysics Data System (ADS)

Strubbe, David A.

GW and Bethe-Salpeter (GW/BSE) calculations use mean-field input from density-functional theory (DFT) calculations to compute excited states of a condensed-matter system. Many parts of a GW/BSE calculation are efficiently performed in a plane-wave basis, and extensive effort has gone into optimizing and parallelizing plane-wave GW/BSE codes for large-scale computations. Most straightforwardly, plane-wave DFT can be used as a starting point, but real-space DFT is also an attractive starting point: it is systematically convergeable like plane waves, can take advantage of efficient domain parallelization for large systems, and is well suited physically for finite and especially charged systems. The flexibility of a real-space grid also allows convenient calculations on non-atomic model systems. I will discuss the interfacing of a real-space (TD)DFT code (Octopus, www.tddft.org/programs/octopus) with a plane-wave GW/BSE code (BerkeleyGW, www.berkeleygw.org), consider performance issues and accuracy, and present some applications to simple and paradigmatic systems that illuminate fundamental properties of these approximations in many-body perturbation theory.

Convolutional networks for vehicle track segmentation

DOE PAGES

Quach, Tu-Thach

2017-08-19

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are unable to capture natural track features such as continuity and parallelism. More powerful, but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3-by-3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate inmore » low power and have limited training data. As a result, we aim for small, efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our 6-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.« less

A new multistage groundwater transport inverse method: presentation, evaluation, and implications

USGS Publications Warehouse

Anderman, Evan R.; Hill, Mary C.

1999-01-01

More computationally efficient methods of using concentration data are needed to estimate groundwater flow and transport parameters. This work introduces and evaluates a three‐stage nonlinear‐regression‐based iterative procedure in which trial advective‐front locations link decoupled flow and transport models. Method accuracy and efficiency are evaluated by comparing results to those obtained when flow‐ and transport‐model parameters are estimated simultaneously. The new method is evaluated as conclusively as possible by using a simple test case that includes distinct flow and transport parameters, but does not include any approximations that are problem dependent. The test case is analytical; the only flow parameter is a constant velocity, and the transport parameters are longitudinal and transverse dispersivity. Any difficulties detected using the new method in this ideal situation are likely to be exacerbated in practical problems. Monte‐Carlo analysis of observation error ensures that no specific error realization obscures the results. Results indicate that, while this, and probably other, multistage methods do not always produce optimal parameter estimates, the computational advantage may make them useful in some circumstances, perhaps as a precursor to using a simultaneous method.

Convolutional networks for vehicle track segmentation

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

Quach, Tu-Thach

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are unable to capture natural track features such as continuity and parallelism. More powerful, but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3-by-3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate inmore » low power and have limited training data. As a result, we aim for small, efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our 6-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.« less

Microsimulation Modeling for Health Decision Sciences Using R: A Tutorial.

PubMed

Krijkamp, Eline M; Alarid-Escudero, Fernando; Enns, Eva A; Jalal, Hawre J; Hunink, M G Myriam; Pechlivanoglou, Petros

2018-04-01

Microsimulation models are becoming increasingly common in the field of decision modeling for health. Because microsimulation models are computationally more demanding than traditional Markov cohort models, the use of computer programming languages in their development has become more common. R is a programming language that has gained recognition within the field of decision modeling. It has the capacity to perform microsimulation models more efficiently than software commonly used for decision modeling, incorporate statistical analyses within decision models, and produce more transparent models and reproducible results. However, no clear guidance for the implementation of microsimulation models in R exists. In this tutorial, we provide a step-by-step guide to build microsimulation models in R and illustrate the use of this guide on a simple, but transferable, hypothetical decision problem. We guide the reader through the necessary steps and provide generic R code that is flexible and can be adapted for other models. We also show how this code can be extended to address more complex model structures and provide an efficient microsimulation approach that relies on vectorization solutions.

Conservative Analytical Collision Probabilities for Orbital Formation Flying

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell

2004-01-01

The literature offers a number of approximations for analytically and/or efficiently computing the probability of collision between two space objects. However, only one of these techniques is a completely analytical approximation that is suitable for use in the preliminary design phase, when it is more important to quickly analyze a large segment of the trade space than it is to precisely compute collision probabilities. Unfortunately, among the types of formations that one might consider, some combine a range of conditions for which this analytical method is less suitable. This work proposes a simple, conservative approximation that produces reasonable upper bounds on the collision probability in such conditions. Although its estimates are much too conservative under other conditions, such conditions are typically well suited for use of the existing method.

A Computational Framework for Automation of Point Defect Calculations

NASA Astrophysics Data System (ADS)

Goyal, Anuj; Gorai, Prashun; Peng, Haowei; Lany, Stephan; Stevanovic, Vladan; National Renewable Energy Laboratory, Golden, Colorado 80401 Collaboration

A complete and rigorously validated open-source Python framework to automate point defect calculations using density functional theory has been developed. The framework provides an effective and efficient method for defect structure generation, and creation of simple yet customizable workflows to analyze defect calculations. The package provides the capability to compute widely accepted correction schemes to overcome finite-size effects, including (1) potential alignment, (2) image-charge correction, and (3) band filling correction to shallow defects. Using Si, ZnO and In2O3as test examples, we demonstrate the package capabilities and validate the methodology. We believe that a robust automated tool like this will enable the materials by design community to assess the impact of point defects on materials performance. National Renewable Energy Laboratory, Golden, Colorado 80401.

All two-loop maximally helicity-violating amplitudes in multi-Regge kinematics from applied symbology

NASA Astrophysics Data System (ADS)

Prygarin, Alexander; Spradlin, Marcus; Vergu, Cristian; Volovich, Anastasia

2012-04-01

Recent progress on scattering amplitudes has benefited from the mathematical technology of symbols for efficiently handling the types of polylogarithm functions which frequently appear in multiloop computations. The symbol for all two-loop maximally helicity violating amplitudes in planar supersymmetric Yang-Mills theory is known, but explicit analytic formulas for the amplitudes are hard to come by except in special limits where things simplify, such as multi-Regge kinematics. By applying symbology we obtain a formula for the leading behavior of the imaginary part (the Mandelstam cut contribution) of this amplitude in multi-Regge kinematics for any number of gluons. Our result predicts a simple recursive structure which agrees with a direct Balitsky-Fadin-Kuraev-Lipatov computation carried out in a parallel publication.

Conservative Analytical Collision Probability for Design of Orbital Formations

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell

2004-01-01

The literature offers a number of approximations for analytically and/or efficiently computing the probability of collision between two space objects. However, only one of these techniques is a completely analytical approximation that is suitable for use in the preliminary design phase, when it is more important to quickly analyze a large segment of the trade space than it is to precisely compute collision probabilities. Unfortunately, among the types of formations that one might consider, some combine a range of conditions for which this analytical method is less suitable. This work proposes a simple, conservative approximation that produces reasonable upper bounds on the collision probability in such conditions. Although its estimates are much too conservative under other conditions, such conditions are typically well suited for use of the existing method.

UDU/T/ covariance factorization for Kalman filtering

NASA Technical Reports Server (NTRS)

Thornton, C. L.; Bierman, G. J.

1980-01-01

There has been strong motivation to produce numerically stable formulations of the Kalman filter algorithms because it has long been known that the original discrete-time Kalman formulas are numerically unreliable. Numerical instability can be avoided by propagating certain factors of the estimate error covariance matrix rather than the covariance matrix itself. This paper documents filter algorithms that correspond to the covariance factorization P = UDU(T), where U is a unit upper triangular matrix and D is diagonal. Emphasis is on computational efficiency and numerical stability, since these properties are of key importance in real-time filter applications. The history of square-root and U-D covariance filters is reviewed. Simple examples are given to illustrate the numerical inadequacy of the Kalman covariance filter algorithms; these examples show how factorization techniques can give improved computational reliability.

High-frequency CAD-based scattering model: SERMAT

NASA Astrophysics Data System (ADS)

Goupil, D.; Boutillier, M.

1991-09-01

Specifications for an industrial radar cross section (RCS) calculation code are given: it must be able to exchange data with many computer aided design (CAD) systems, it must be fast, and it must have powerful graphic tools. Classical physical optics (PO) and equivalent currents (EC) techniques have proven their efficiency on simple objects for a long time. Difficult geometric problems occur when objects with very complex shapes have to be computed. Only a specific geometric code can solve these problems. We have established that, once these problems have been solved: (1) PO and EC give good results on complex objects of large size compared to wavelength; and (2) the implementation of these objects in a software package (SERMAT) allows fast and sufficiently precise domain RCS calculations to meet industry requirements in the domain of stealth.

High-Density Liquid-State Machine Circuitry for Time-Series Forecasting.

PubMed

Rosselló, Josep L; Alomar, Miquel L; Morro, Antoni; Oliver, Antoni; Canals, Vincent

2016-08-01

Spiking neural networks (SNN) are the last neural network generation that try to mimic the real behavior of biological neurons. Although most research in this area is done through software applications, it is in hardware implementations in which the intrinsic parallelism of these computing systems are more efficiently exploited. Liquid state machines (LSM) have arisen as a strategic technique to implement recurrent designs of SNN with a simple learning methodology. In this work, we show a new low-cost methodology to implement high-density LSM by using Boolean gates. The proposed method is based on the use of probabilistic computing concepts to reduce hardware requirements, thus considerably increasing the neuron count per chip. The result is a highly functional system that is applied to high-speed time series forecasting.

Advancements in RNASeqGUI towards a Reproducible Analysis of RNA-Seq Experiments

PubMed Central

Russo, Francesco; Righelli, Dario

2016-01-01

We present the advancements and novelties recently introduced in RNASeqGUI, a graphical user interface that helps biologists to handle and analyse large data collected in RNA-Seq experiments. This work focuses on the concept of reproducible research and shows how it has been incorporated in RNASeqGUI to provide reproducible (computational) results. The novel version of RNASeqGUI combines graphical interfaces with tools for reproducible research, such as literate statistical programming, human readable report, parallel executions, caching, and interactive and web-explorable tables of results. These features allow the user to analyse big datasets in a fast, efficient, and reproducible way. Moreover, this paper represents a proof of concept, showing a simple way to develop computational tools for Life Science in the spirit of reproducible research. PMID:26977414

LightAssembler: fast and memory-efficient assembly algorithm for high-throughput sequencing reads.

PubMed

El-Metwally, Sara; Zakaria, Magdi; Hamza, Taher

2016-11-01

The deluge of current sequenced data has exceeded Moore's Law, more than doubling every 2 years since the next-generation sequencing (NGS) technologies were invented. Accordingly, we will able to generate more and more data with high speed at fixed cost, but lack the computational resources to store, process and analyze it. With error prone high throughput NGS reads and genomic repeats, the assembly graph contains massive amount of redundant nodes and branching edges. Most assembly pipelines require this large graph to reside in memory to start their workflows, which is intractable for mammalian genomes. Resource-efficient genome assemblers combine both the power of advanced computing techniques and innovative data structures to encode the assembly graph efficiently in a computer memory. LightAssembler is a lightweight assembly algorithm designed to be executed on a desktop machine. It uses a pair of cache oblivious Bloom filters, one holding a uniform sample of [Formula: see text]-spaced sequenced [Formula: see text]-mers and the other holding [Formula: see text]-mers classified as likely correct, using a simple statistical test. LightAssembler contains a light implementation of the graph traversal and simplification modules that achieves comparable assembly accuracy and contiguity to other competing tools. Our method reduces the memory usage by [Formula: see text] compared to the resource-efficient assemblers using benchmark datasets from GAGE and Assemblathon projects. While LightAssembler can be considered as a gap-based sequence assembler, different gap sizes result in an almost constant assembly size and genome coverage. https://github.com/SaraEl-Metwally/LightAssembler CONTACT: sarah_almetwally4@mans.edu.egSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Sparse RNA folding revisited: space-efficient minimum free energy structure prediction.

PubMed

Will, Sebastian; Jabbari, Hosna

2016-01-01

RNA secondary structure prediction by energy minimization is the central computational tool for the analysis of structural non-coding RNAs and their interactions. Sparsification has been successfully applied to improve the time efficiency of various structure prediction algorithms while guaranteeing the same result; however, for many such folding problems, space efficiency is of even greater concern, particularly for long RNA sequences. So far, space-efficient sparsified RNA folding with fold reconstruction was solved only for simple base-pair-based pseudo-energy models. Here, we revisit the problem of space-efficient free energy minimization. Whereas the space-efficient minimization of the free energy has been sketched before, the reconstruction of the optimum structure has not even been discussed. We show that this reconstruction is not possible in trivial extension of the method for simple energy models. Then, we present the time- and space-efficient sparsified free energy minimization algorithm SparseMFEFold that guarantees MFE structure prediction. In particular, this novel algorithm provides efficient fold reconstruction based on dynamically garbage-collected trace arrows. The complexity of our algorithm depends on two parameters, the number of candidates Z and the number of trace arrows T; both are bounded by [Formula: see text], but are typically much smaller. The time complexity of RNA folding is reduced from [Formula: see text] to [Formula: see text]; the space complexity, from [Formula: see text] to [Formula: see text]. Our empirical results show more than 80 % space savings over RNAfold [Vienna RNA package] on the long RNAs from the RNA STRAND database (≥2500 bases). The presented technique is intentionally generalizable to complex prediction algorithms; due to their high space demands, algorithms like pseudoknot prediction and RNA-RNA-interaction prediction are expected to profit even stronger than "standard" MFE folding. SparseMFEFold is free software, available at http://www.bioinf.uni-leipzig.de/~will/Software/SparseMFEFold.

Communication devices in the operating room.

PubMed

Ruskin, Keith J

2006-12-01

Effective communication is essential to patient safety. Although radio pagers have been the cornerstone of medical communication, new devices such as cellular telephones, personal digital assistants (PDAs), and laptop or tablet computers can help anesthesiologists to get information quickly and reliably. Anesthesiologists can use these devices to speak with colleagues, access the medical record, or help a colleague in another location without having to leave a patient's side. Recent advances in communication technology offer anesthesiologists new ways to improve patient care. Anesthesiologists rely on a wide variety of information to make decisions, including vital signs, laboratory values, and entries in the medical record. Devices such as PDAs and computers with wireless networking can be used to access this information. Mobile telephones can be used to get help or ask for advice, and are more efficient than radio pagers. Voice over Internet protocol is a new technology that allows voice conversations to be routed over computer networks. It is widely believed that wireless devices can cause life-threatening interference with medical devices. The actual risk is very low, and is offset by a significant reduction in medical errors that results from more efficient communication. Using common technology like cellular telephones and wireless networks is a simple, cost-effective way to improve patient care.

Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition.

PubMed

Ding, Changxing; Choi, Jonghyun; Tao, Dacheng; Davis, Larry S

2016-03-01

To perform unconstrained face recognition robust to variations in illumination, pose and expression, this paper presents a new scheme to extract "Multi-Directional Multi-Level Dual-Cross Patterns" (MDML-DCPs) from face images. Specifically, the MDML-DCPs scheme exploits the first derivative of Gaussian operator to reduce the impact of differences in illumination and then computes the DCP feature at both the holistic and component levels. DCP is a novel face image descriptor inspired by the unique textural structure of human faces. It is computationally efficient and only doubles the cost of computing local binary patterns, yet is extremely robust to pose and expression variations. MDML-DCPs comprehensively yet efficiently encodes the invariant characteristics of a face image from multiple levels into patterns that are highly discriminative of inter-personal differences but robust to intra-personal variations. Experimental results on the FERET, CAS-PERL-R1, FRGC 2.0, and LFW databases indicate that DCP outperforms the state-of-the-art local descriptors (e.g., LBP, LTP, LPQ, POEM, tLBP, and LGXP) for both face identification and face verification tasks. More impressively, the best performance is achieved on the challenging LFW and FRGC 2.0 databases by deploying MDML-DCPs in a simple recognition scheme.

Principal component of explained variance: An efficient and optimal data dimension reduction framework for association studies.

PubMed

Turgeon, Maxime; Oualkacha, Karim; Ciampi, Antonio; Miftah, Hanane; Dehghan, Golsa; Zanke, Brent W; Benedet, Andréa L; Rosa-Neto, Pedro; Greenwood, Celia Mt; Labbe, Aurélie

2018-05-01

The genomics era has led to an increase in the dimensionality of data collected in the investigation of biological questions. In this context, dimension-reduction techniques can be used to summarise high-dimensional signals into low-dimensional ones, to further test for association with one or more covariates of interest. This paper revisits one such approach, previously known as principal component of heritability and renamed here as principal component of explained variance (PCEV). As its name suggests, the PCEV seeks a linear combination of outcomes in an optimal manner, by maximising the proportion of variance explained by one or several covariates of interest. By construction, this method optimises power; however, due to its computational complexity, it has unfortunately received little attention in the past. Here, we propose a general analytical PCEV framework that builds on the assets of the original method, i.e. conceptually simple and free of tuning parameters. Moreover, our framework extends the range of applications of the original procedure by providing a computationally simple strategy for high-dimensional outcomes, along with exact and asymptotic testing procedures that drastically reduce its computational cost. We investigate the merits of the PCEV using an extensive set of simulations. Furthermore, the use of the PCEV approach is illustrated using three examples taken from the fields of epigenetics and brain imaging.

Efficient generation of sum-of-products representations of high-dimensional potential energy surfaces based on multimode expansions

NASA Astrophysics Data System (ADS)

Ziegler, Benjamin; Rauhut, Guntram

2016-03-01

The transformation of multi-dimensional potential energy surfaces (PESs) from a grid-based multimode representation to an analytical one is a standard procedure in quantum chemical programs. Within the framework of linear least squares fitting, a simple and highly efficient algorithm is presented, which relies on a direct product representation of the PES and a repeated use of Kronecker products. It shows the same scalings in computational cost and memory requirements as the potfit approach. In comparison to customary linear least squares fitting algorithms, this corresponds to a speed-up and memory saving by several orders of magnitude. Different fitting bases are tested, namely, polynomials, B-splines, and distributed Gaussians. Benchmark calculations are provided for the PESs of a set of small molecules.

Efficient generation of sum-of-products representations of high-dimensional potential energy surfaces based on multimode expansions.

PubMed

Ziegler, Benjamin; Rauhut, Guntram

2016-03-21

The transformation of multi-dimensional potential energy surfaces (PESs) from a grid-based multimode representation to an analytical one is a standard procedure in quantum chemical programs. Within the framework of linear least squares fitting, a simple and highly efficient algorithm is presented, which relies on a direct product representation of the PES and a repeated use of Kronecker products. It shows the same scalings in computational cost and memory requirements as the potfit approach. In comparison to customary linear least squares fitting algorithms, this corresponds to a speed-up and memory saving by several orders of magnitude. Different fitting bases are tested, namely, polynomials, B-splines, and distributed Gaussians. Benchmark calculations are provided for the PESs of a set of small molecules.

Adaptive correlation filter-based video stabilization without accumulative global motion estimation

NASA Astrophysics Data System (ADS)

Koh, Eunjin; Lee, Chanyong; Jeong, Dong Gil

2014-12-01

We present a digital video stabilization approach that provides both robustness and efficiency for practical applications. In this approach, we adopt a stabilization model that maintains spatio-temporal information of past input frames efficiently and can track original stabilization position. Because of the stabilization model, the proposed method does not need accumulative global motion estimation and can recover the original position even if there is a failure in interframe motion estimation. It can also intelligently overcome the situation of damaged or interrupted video sequences. Moreover, because it is simple and suitable to parallel scheme, we implement it on a commercial field programmable gate array and a graphics processing unit board with compute unified device architecture in a breeze. Experimental results show that the proposed approach is both fast and robust.

Efficient Control Law Simulation for Multiple Mobile Robots

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

Driessen, B.J.; Feddema, J.T.; Kotulski, J.D.

1998-10-06

In this paper we consider the problem of simulating simple control laws involving large numbers of mobile robots. Such simulation can be computationally prohibitive if the number of robots is large enough, say 1 million, due to the 0(N2 ) cost of each time step. This work therefore uses hierarchical tree-based methods for calculating the control law. These tree-based approaches have O(NlogN) cost per time step, thus allowing for efficient simulation involving a large number of robots. For concreteness, a decentralized control law which involves only the distance and bearing to the closest neighbor robot will be considered. The timemore » to calculate the control law for each robot at each time step is demonstrated to be O(logN).« less

Simulating Progressive Damage of Notched Composite Laminates with Various Lamination Schemes

NASA Astrophysics Data System (ADS)

Mandal, B.; Chakrabarti, A.

2017-05-01

A three dimensional finite element based progressive damage model has been developed for the failure analysis of notched composite laminates. The material constitutive relations and the progressive damage algorithms are implemented into finite element code ABAQUS using user-defined subroutine UMAT. The existing failure criteria for the composite laminates are modified by including the failure criteria for fiber/matrix shear damage and delamination effects. The proposed numerical model is quite efficient and simple compared to other progressive damage models available in the literature. The efficiency of the present constitutive model and the computational scheme is verified by comparing the simulated results with the results available in the literature. A parametric study has been carried out to investigate the effect of change in lamination scheme on the failure behaviour of notched composite laminates.

20 CFR 725.608 - Interest.

Code of Federal Regulations, 2010 CFR

2010-04-01

... simple annual interest, computed from the date on which the benefits were due. The interest shall be... payment of retroactive benefits, the beneficiary shall also be entitled to simple annual interest on such... entitled to simple annual interest computed from the date upon which the beneficiary's right to additional...

FormTracer. A mathematica tracing package using FORM

NASA Astrophysics Data System (ADS)

Cyrol, Anton K.; Mitter, Mario; Strodthoff, Nils

2017-10-01

We present FormTracer, a high-performance, general purpose, easy-to-use Mathematica tracing package which uses FORM. It supports arbitrary space and spinor dimensions as well as an arbitrary number of simple compact Lie groups. While keeping the usability of the Mathematica interface, it relies on the efficiency of FORM. An additional performance gain is achieved by a decomposition algorithm that avoids redundant traces in the product tensors spaces. FormTracer supports a wide range of syntaxes which endows it with a high flexibility. Mathematica notebooks that automatically install the package and guide the user through performing standard traces in space-time, spinor and gauge-group spaces are provided. Program Files doi:http://dx.doi.org/10.17632/7rd29h4p3m.1 Licensing provisions: GPLv3 Programming language: Mathematica and FORM Nature of problem: Efficiently compute traces of large expressions Solution method: The expression to be traced is decomposed into its subspaces by a recursive Mathematica expansion algorithm. The result is subsequently translated to a FORM script that takes the traces. After FORM is executed, the final result is either imported into Mathematica or exported as optimized C/C++/Fortran code. Unusual features: The outstanding features of FormTracer are the simple interface, the capability to efficiently handle an arbitrary number of Lie groups in addition to Dirac and Lorentz tensors, and a customizable input-syntax.

FaCSI: A block parallel preconditioner for fluid-structure interaction in hemodynamics

NASA Astrophysics Data System (ADS)

Deparis, Simone; Forti, Davide; Grandperrin, Gwenol; Quarteroni, Alfio

2016-12-01

Modeling Fluid-Structure Interaction (FSI) in the vascular system is mandatory to reliably compute mechanical indicators in vessels undergoing large deformations. In order to cope with the computational complexity of the coupled 3D FSI problem after discretizations in space and time, a parallel solution is often mandatory. In this paper we propose a new block parallel preconditioner for the coupled linearized FSI system obtained after space and time discretization. We name it FaCSI to indicate that it exploits the Factorized form of the linearized FSI matrix, the use of static Condensation to formally eliminate the interface degrees of freedom of the fluid equations, and the use of a SIMPLE preconditioner for saddle-point problems. FaCSI is built upon a block Gauss-Seidel factorization of the FSI Jacobian matrix and it uses ad-hoc preconditioners for each physical component of the coupled problem, namely the fluid, the structure and the geometry. In the fluid subproblem, after operating static condensation of the interface fluid variables, we use a SIMPLE preconditioner on the reduced fluid matrix. Moreover, to efficiently deal with a large number of processes, FaCSI exploits efficient single field preconditioners, e.g., based on domain decomposition or the multigrid method. We measure the parallel performances of FaCSI on a benchmark cylindrical geometry and on a problem of physiological interest, namely the blood flow through a patient-specific femoropopliteal bypass. We analyze the dependence of the number of linear solver iterations on the cores count (scalability of the preconditioner) and on the mesh size (optimality).

Micro-Computed Tomography Detection of Gold Nanoparticle-Labelled Mesenchymal Stem Cells in the Rat Subretinal Layer.

PubMed

Mok, Pooi Ling; Leow, Sue Ngein; Koh, Avin Ee-Hwan; Mohd Nizam, Hairul Harun; Ding, Suet Lee Shirley; Luu, Chi; Ruhaslizan, Raduan; Wong, Hon Seng; Halim, Wan Haslina Wan Abdul; Ng, Min Hwei; Idrus, Ruszymah Binti Hj; Chowdhury, Shiplu Roy; Bastion, Catherine Mae-Lynn; Subbiah, Suresh Kumar; Higuchi, Akon; Alarfaj, Abdullah A; Then, Kong Yong

2017-02-08

Mesenchymal stem cells are widely used in many pre-clinical and clinical settings. Despite advances in molecular technology; the migration and homing activities of these cells in in vivo systems are not well understood. Labelling mesenchymal stem cells with gold nanoparticles has no cytotoxic effect and may offer suitable indications for stem cell tracking. Here, we report a simple protocol to label mesenchymal stem cells using 80 nm gold nanoparticles. Once the cells and particles were incubated together for 24 h, the labelled products were injected into the rat subretinal layer. Micro-computed tomography was then conducted on the 15th and 30th day post-injection to track the movement of these cells, as visualized by an area of hyperdensity from the coronal section images of the rat head. In addition, we confirmed the cellular uptake of the gold nanoparticles by the mesenchymal stem cells using transmission electron microscopy. As opposed to other methods, the current protocol provides a simple, less labour-intensive and more efficient labelling mechanism for real-time cell tracking. Finally, we discuss the potential manipulations of gold nanoparticles in stem cells for cell replacement and cancer therapy in ocular disorders or diseases.

Micro-Computed Tomography Detection of Gold Nanoparticle-Labelled Mesenchymal Stem Cells in the Rat Subretinal Layer

PubMed Central

Mok, Pooi Ling; Leow, Sue Ngein; Koh, Avin Ee-Hwan; Mohd Nizam, Hairul Harun; Ding, Suet Lee Shirley; Luu, Chi; Ruhaslizan, Raduan; Wong, Hon Seng; Halim, Wan Haslina Wan Abdul; Ng, Min Hwei; Idrus, Ruszymah Binti Hj.; Chowdhury, Shiplu Roy; Bastion, Catherine Mae-Lynn; Subbiah, Suresh Kumar; Higuchi, Akon; Alarfaj, Abdullah A.; Then, Kong Yong

2017-01-01

Mesenchymal stem cells are widely used in many pre-clinical and clinical settings. Despite advances in molecular technology; the migration and homing activities of these cells in in vivo systems are not well understood. Labelling mesenchymal stem cells with gold nanoparticles has no cytotoxic effect and may offer suitable indications for stem cell tracking. Here, we report a simple protocol to label mesenchymal stem cells using 80 nm gold nanoparticles. Once the cells and particles were incubated together for 24 h, the labelled products were injected into the rat subretinal layer. Micro-computed tomography was then conducted on the 15th and 30th day post-injection to track the movement of these cells, as visualized by an area of hyperdensity from the coronal section images of the rat head. In addition, we confirmed the cellular uptake of the gold nanoparticles by the mesenchymal stem cells using transmission electron microscopy. As opposed to other methods, the current protocol provides a simple, less labour-intensive and more efficient labelling mechanism for real-time cell tracking. Finally, we discuss the potential manipulations of gold nanoparticles in stem cells for cell replacement and cancer therapy in ocular disorders or diseases. PMID:28208719

The combination of circle topology and leaky integrator neurons remarkably improves the performance of echo state network on time series prediction.

PubMed

Xue, Fangzheng; Li, Qian; Li, Xiumin

2017-01-01

Recently, echo state network (ESN) has attracted a great deal of attention due to its high accuracy and efficient learning performance. Compared with the traditional random structure and classical sigmoid units, simple circle topology and leaky integrator neurons have more advantages on reservoir computing of ESN. In this paper, we propose a new model of ESN with both circle reservoir structure and leaky integrator units. By comparing the prediction capability on Mackey-Glass chaotic time series of four ESN models: classical ESN, circle ESN, traditional leaky integrator ESN, circle leaky integrator ESN, we find that our circle leaky integrator ESN shows significantly better performance than other ESNs with roughly 2 orders of magnitude reduction of the predictive error. Moreover, this model has stronger ability to approximate nonlinear dynamics and resist noise than conventional ESN and ESN with only simple circle structure or leaky integrator neurons. Our results show that the combination of circle topology and leaky integrator neurons can remarkably increase dynamical diversity and meanwhile decrease the correlation of reservoir states, which contribute to the significant improvement of computational performance of Echo state network on time series prediction.

Estimated Benefits of Variable-Geometry Wing Camber Control for Transport Aircraft

NASA Technical Reports Server (NTRS)

Bolonkin, Alexander; Gilyard, Glenn B.

1999-01-01

Analytical benefits of variable-camber capability on subsonic transport aircraft are explored. Using aerodynamic performance models, including drag as a function of deflection angle for control surfaces of interest, optimal performance benefits of variable camber are calculated. Results demonstrate that if all wing trailing-edge surfaces are available for optimization, drag can be significantly reduced at most points within the flight envelope. The optimization approach developed and illustrated for flight uses variable camber for optimization of aerodynamic efficiency (maximizing the lift-to-drag ratio). Most transport aircraft have significant latent capability in this area. Wing camber control that can affect performance optimization for transport aircraft includes symmetric use of ailerons and flaps. In this paper, drag characteristics for aileron and flap deflections are computed based on analytical and wind-tunnel data. All calculations based on predictions for the subject aircraft and the optimal surface deflection are obtained by simple interpolation for given conditions. An algorithm is also presented for computation of optimal surface deflection for given conditions. Benefits of variable camber for a transport configuration using a simple trailing-edge control surface system can approach more than 10 percent, especially for nonstandard flight conditions. In the cruise regime, the benefit is 1-3 percent.

Fast segmentation of satellite images using SLIC, WebGL and Google Earth Engine

NASA Astrophysics Data System (ADS)

Donchyts, Gennadii; Baart, Fedor; Gorelick, Noel; Eisemann, Elmar; van de Giesen, Nick

2017-04-01

Google Earth Engine (GEE) is a parallel geospatial processing platform, which harmonizes access to petabytes of freely available satellite images. It provides a very rich API, allowing development of dedicated algorithms to extract useful geospatial information from these images. At the same time, modern GPUs provide thousands of computing cores, which are mostly not utilized in this context. In the last years, WebGL became a popular and well-supported API, allowing fast image processing directly in web browsers. In this work, we will evaluate the applicability of WebGL to enable fast segmentation of satellite images. A new implementation of a Simple Linear Iterative Clustering (SLIC) algorithm using GPU shaders will be presented. SLIC is a simple and efficient method to decompose an image in visually homogeneous regions. It adapts a k-means clustering approach to generate superpixels efficiently. While this approach will be hard to scale, due to a significant amount of data to be transferred to the client, it should significantly improve exploratory possibilities and simplify development of dedicated algorithms for geoscience applications. Our prototype implementation will be used to improve surface water detection of the reservoirs using multispectral satellite imagery.

Synthetic biology: insights into biological computation.

PubMed

Manzoni, Romilde; Urrios, Arturo; Velazquez-Garcia, Silvia; de Nadal, Eulàlia; Posas, Francesc

2016-04-18

Organisms have evolved a broad array of complex signaling mechanisms that allow them to survive in a wide range of environmental conditions. They are able to sense external inputs and produce an output response by computing the information. Synthetic biology attempts to rationally engineer biological systems in order to perform desired functions. Our increasing understanding of biological systems guides this rational design, while the huge background in electronics for building circuits defines the methodology. In this context, biocomputation is the branch of synthetic biology aimed at implementing artificial computational devices using engineered biological motifs as building blocks. Biocomputational devices are defined as biological systems that are able to integrate inputs and return outputs following pre-determined rules. Over the last decade the number of available synthetic engineered devices has increased exponentially; simple and complex circuits have been built in bacteria, yeast and mammalian cells. These devices can manage and store information, take decisions based on past and present inputs, and even convert a transient signal into a sustained response. The field is experiencing a fast growth and every day it is easier to implement more complex biological functions. This is mainly due to advances in in vitro DNA synthesis, new genome editing tools, novel molecular cloning techniques, continuously growing part libraries as well as other technological advances. This allows that digital computation can now be engineered and implemented in biological systems. Simple logic gates can be implemented and connected to perform novel desired functions or to better understand and redesign biological processes. Synthetic biological digital circuits could lead to new therapeutic approaches, as well as new and efficient ways to produce complex molecules such as antibiotics, bioplastics or biofuels. Biological computation not only provides possible biomedical and biotechnological applications, but also affords a greater understanding of biological systems.

Computational model for perception of objects and motions.

PubMed

Yang, WenLu; Zhang, LiQing; Ma, LiBo

2008-06-01

Perception of objects and motions in the visual scene is one of the basic problems in the visual system. There exist 'What' and 'Where' pathways in the superior visual cortex, starting from the simple cells in the primary visual cortex. The former is able to perceive objects such as forms, color, and texture, and the latter perceives 'where', for example, velocity and direction of spatial movement of objects. This paper explores brain-like computational architectures of visual information processing. We propose a visual perceptual model and computational mechanism for training the perceptual model. The computational model is a three-layer network. The first layer is the input layer which is used to receive the stimuli from natural environments. The second layer is designed for representing the internal neural information. The connections between the first layer and the second layer, called the receptive fields of neurons, are self-adaptively learned based on principle of sparse neural representation. To this end, we introduce Kullback-Leibler divergence as the measure of independence between neural responses and derive the learning algorithm based on minimizing the cost function. The proposed algorithm is applied to train the basis functions, namely receptive fields, which are localized, oriented, and bandpassed. The resultant receptive fields of neurons in the second layer have the characteristics resembling that of simple cells in the primary visual cortex. Based on these basis functions, we further construct the third layer for perception of what and where in the superior visual cortex. The proposed model is able to perceive objects and their motions with a high accuracy and strong robustness against additive noise. Computer simulation results in the final section show the feasibility of the proposed perceptual model and high efficiency of the learning algorithm.

The Heterogeneous Investment Horizon and Dynamic Strategies for Asset Allocation

NASA Astrophysics Data System (ADS)

Xiong, Heping; Xu, Yiheng; Xiao, Yi

This paper discusses the influence of the portfolio rebalancing strategy on the efficiency of long-term investment portfolios under the assumption of independent stationary distribution of returns. By comparing the efficient sets of the stochastic rebalancing strategy, the simple rebalancing strategy and the buy-and-hold strategy with specific data examples, we find that the stochastic rebalancing strategy is optimal, while the simple rebalancing strategy is of the lowest efficiency. In addition, the simple rebalancing strategy lowers the efficiency of the portfolio instead of improving it.

Indoor Pedestrian Localization Using iBeacon and Improved Kalman Filter.

PubMed

Sung, Kwangjae; Lee, Dong Kyu 'Roy'; Kim, Hwangnam

2018-05-26

The reliable and accurate indoor pedestrian positioning is one of the biggest challenges for location-based systems and applications. Most pedestrian positioning systems have drift error and large bias due to low-cost inertial sensors and random motions of human being, as well as unpredictable and time-varying radio-frequency (RF) signals used for position determination. To solve this problem, many indoor positioning approaches that integrate the user's motion estimated by dead reckoning (DR) method and the location data obtained by RSS fingerprinting through Bayesian filter, such as the Kalman filter (KF), unscented Kalman filter (UKF), and particle filter (PF), have recently been proposed to achieve higher positioning accuracy in indoor environments. Among Bayesian filtering methods, PF is the most popular integrating approach and can provide the best localization performance. However, since PF uses a large number of particles for the high performance, it can lead to considerable computational cost. This paper presents an indoor positioning system implemented on a smartphone, which uses simple dead reckoning (DR), RSS fingerprinting using iBeacon and machine learning scheme, and improved KF. The core of the system is the enhanced KF called a sigma-point Kalman particle filter (SKPF), which localize the user leveraging both the unscented transform of UKF and the weighting method of PF. The SKPF algorithm proposed in this study is used to provide the enhanced positioning accuracy by fusing positional data obtained from both DR and fingerprinting with uncertainty. The SKPF algorithm can achieve better positioning accuracy than KF and UKF and comparable performance compared to PF, and it can provide higher computational efficiency compared with PF. iBeacon in our positioning system is used for energy-efficient localization and RSS fingerprinting. We aim to design the localization scheme that can realize the high positioning accuracy, computational efficiency, and energy efficiency through the SKPF and iBeacon indoors. Empirical experiments in real environments show that the use of the SKPF algorithm and iBeacon in our indoor localization scheme can achieve very satisfactory performance in terms of localization accuracy, computational cost, and energy efficiency.

Linearized self-consistent quasiparticle GW method: Application to semiconductors and simple metals

NASA Astrophysics Data System (ADS)

Kutepov, A. L.; Oudovenko, V. S.; Kotliar, G.

2017-10-01

We present a code implementing the linearized quasiparticle self-consistent GW method (LQSGW) in the LAPW basis. Our approach is based on the linearization of the self-energy around zero frequency which differs it from the existing implementations of the QSGW method. The linearization allows us to use Matsubara frequencies instead of working on the real axis. This results in efficiency gains by switching to the imaginary time representation in the same way as in the space time method. The all electron LAPW basis set eliminates the need for pseudopotentials. We discuss the advantages of our approach, such as its N3 scaling with the system size N, as well as its shortcomings. We apply our approach to study the electronic properties of selected semiconductors, insulators, and simple metals and show that our code produces the results very close to the previously published QSGW data. Our implementation is a good platform for further many body diagrammatic resummations such as the vertex-corrected GW approach and the GW+DMFT method. Program Files doi:http://dx.doi.org/10.17632/cpchkfty4w.1 Licensing provisions: GNU General Public License Programming language: Fortran 90 External routines/libraries: BLAS, LAPACK, MPI (optional) Nature of problem: Direct implementation of the GW method scales as N4 with the system size, which quickly becomes prohibitively time consuming even in the modern computers. Solution method: We implemented the GW approach using a method that switches between real space and momentum space representations. Some operations are faster in real space, whereas others are more computationally efficient in the reciprocal space. This makes our approach scale as N3. Restrictions: The limiting factor is usually the memory available in a computer. Using 10 GB/core of memory allows us to study the systems up to 15 atoms per unit cell.

Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks.

PubMed

Spirov, Alexander; Holloway, David

2013-07-15

This paper surveys modeling approaches for studying the evolution of gene regulatory networks (GRNs). Modeling of the design or 'wiring' of GRNs has become increasingly common in developmental and medical biology, as a means of quantifying gene-gene interactions, the response to perturbations, and the overall dynamic motifs of networks. Drawing from developments in GRN 'design' modeling, a number of groups are now using simulations to study how GRNs evolve, both for comparative genomics and to uncover general principles of evolutionary processes. Such work can generally be termed evolution in silico. Complementary to these biologically-focused approaches, a now well-established field of computer science is Evolutionary Computations (ECs), in which highly efficient optimization techniques are inspired from evolutionary principles. In surveying biological simulation approaches, we discuss the considerations that must be taken with respect to: (a) the precision and completeness of the data (e.g. are the simulations for very close matches to anatomical data, or are they for more general exploration of evolutionary principles); (b) the level of detail to model (we proceed from 'coarse-grained' evolution of simple gene-gene interactions to 'fine-grained' evolution at the DNA sequence level); (c) to what degree is it important to include the genome's cellular context; and (d) the efficiency of computation. With respect to the latter, we argue that developments in computer science EC offer the means to perform more complete simulation searches, and will lead to more comprehensive biological predictions. Copyright © 2013 Elsevier Inc. All rights reserved.

Testing particle filters on convective scale dynamics

NASA Astrophysics Data System (ADS)

Haslehner, Mylene; Craig, George. C.; Janjic, Tijana

2014-05-01

Particle filters have been developed in recent years to deal with highly nonlinear dynamics and non Gaussian error statistics that also characterize data assimilation on convective scales. In this work we explore the use of the efficient particle filter (P.v. Leeuwen, 2011) for convective scale data assimilation application. The method is tested in idealized setting, on two stochastic models. The models were designed to reproduce some of the properties of convection, for example the rapid development and decay of convective clouds. The first model is a simple one-dimensional, discrete state birth-death model of clouds (Craig and Würsch, 2012). For this model, the efficient particle filter that includes nudging the variables shows significant improvement compared to Ensemble Kalman Filter and Sequential Importance Resampling (SIR) particle filter. The success of the combination of nudging and resampling, measured as RMS error with respect to the 'true state', is proportional to the nudging intensity. Significantly, even a very weak nudging intensity brings notable improvement over SIR. The second model is a modified version of a stochastic shallow water model (Würsch and Craig 2013), which contains more realistic dynamical characteristics of convective scale phenomena. Using the efficient particle filter and different combination of observations of the three field variables (wind, water 'height' and rain) allows the particle filter to be evaluated in comparison to a regime where only nudging is used. Sensitivity to the properties of the model error covariance is also considered. Finally, criteria are identified under which the efficient particle filter outperforms nudging alone. References: Craig, G. C. and M. Würsch, 2012: The impact of localization and observation averaging for convective-scale data assimilation in a simple stochastic model. Q. J. R. Meteorol. Soc.,139, 515-523. Van Leeuwen, P. J., 2011: Efficient non-linear data assimilation in geophysical fluid dynamics. - Computers and Fluids, doi:10,1016/j.compfluid.2010.11.011, 1096 2011. Würsch, M. and G. C. Craig, 2013: A simple dynamical model of cumulus convection for data assimilation research, submitted to Met. Zeitschrift.

Computing local edge probability in natural scenes from a population of oriented simple cells

PubMed Central

Ramachandra, Chaithanya A.; Mel, Bartlett W.

2013-01-01

A key computation in visual cortex is the extraction of object contours, where the first stage of processing is commonly attributed to V1 simple cells. The standard model of a simple cell—an oriented linear filter followed by a divisive normalization—fits a wide variety of physiological data, but is a poor performing local edge detector when applied to natural images. The brain's ability to finely discriminate edges from nonedges therefore likely depends on information encoded by local simple cell populations. To gain insight into the corresponding decoding problem, we used Bayes's rule to calculate edge probability at a given location/orientation in an image based on a surrounding filter population. Beginning with a set of ∼ 100 filters, we culled out a subset that were maximally informative about edges, and minimally correlated to allow factorization of the joint on- and off-edge likelihood functions. Key features of our approach include a new, efficient method for ground-truth edge labeling, an emphasis on achieving filter independence, including a focus on filters in the region orthogonal rather than tangential to an edge, and the use of a customized parametric model to represent the individual filter likelihood functions. The resulting population-based edge detector has zero parameters, calculates edge probability based on a sum of surrounding filter influences, is much more sharply tuned than the underlying linear filters, and effectively captures fine-scale edge structure in natural scenes. Our findings predict nonmonotonic interactions between cells in visual cortex, wherein a cell may for certain stimuli excite and for other stimuli inhibit the same neighboring cell, depending on the two cells' relative offsets in position and orientation, and their relative activation levels. PMID:24381295

Model Reduction of Computational Aerothermodynamics for Multi-Discipline Analysis in High Speed Flows

NASA Astrophysics Data System (ADS)

Crowell, Andrew Rippetoe

This dissertation describes model reduction techniques for the computation of aerodynamic heat flux and pressure loads for multi-disciplinary analysis of hypersonic vehicles. NASA and the Department of Defense have expressed renewed interest in the development of responsive, reusable hypersonic cruise vehicles capable of sustained high-speed flight and access to space. However, an extensive set of technical challenges have obstructed the development of such vehicles. These technical challenges are partially due to both the inability to accurately test scaled vehicles in wind tunnels and to the time intensive nature of high-fidelity computational modeling, particularly for the fluid using Computational Fluid Dynamics (CFD). The aim of this dissertation is to develop efficient and accurate models for the aerodynamic heat flux and pressure loads to replace the need for computationally expensive, high-fidelity CFD during coupled analysis. Furthermore, aerodynamic heating and pressure loads are systematically evaluated for a number of different operating conditions, including: simple two-dimensional flow over flat surfaces up to three-dimensional flows over deformed surfaces with shock-shock interaction and shock-boundary layer interaction. An additional focus of this dissertation is on the implementation and computation of results using the developed aerodynamic heating and pressure models in complex fluid-thermal-structural simulations. Model reduction is achieved using a two-pronged approach. One prong focuses on developing analytical corrections to isothermal, steady-state CFD flow solutions in order to capture flow effects associated with transient spatially-varying surface temperatures and surface pressures (e.g., surface deformation, surface vibration, shock impingements, etc.). The second prong is focused on minimizing the computational expense of computing the steady-state CFD solutions by developing an efficient surrogate CFD model. The developed two-pronged approach is found to exhibit balanced performance in terms of accuracy and computational expense, relative to several existing approaches. This approach enables CFD-based loads to be implemented into long duration fluid-thermal-structural simulations.

Comparison of missing value imputation methods in time series: the case of Turkish meteorological data

NASA Astrophysics Data System (ADS)

Yozgatligil, Ceylan; Aslan, Sipan; Iyigun, Cem; Batmaz, Inci

2013-04-01

This study aims to compare several imputation methods to complete the missing values of spatio-temporal meteorological time series. To this end, six imputation methods are assessed with respect to various criteria including accuracy, robustness, precision, and efficiency for artificially created missing data in monthly total precipitation and mean temperature series obtained from the Turkish State Meteorological Service. Of these methods, simple arithmetic average, normal ratio (NR), and NR weighted with correlations comprise the simple ones, whereas multilayer perceptron type neural network and multiple imputation strategy adopted by Monte Carlo Markov Chain based on expectation-maximization (EM-MCMC) are computationally intensive ones. In addition, we propose a modification on the EM-MCMC method. Besides using a conventional accuracy measure based on squared errors, we also suggest the correlation dimension (CD) technique of nonlinear dynamic time series analysis which takes spatio-temporal dependencies into account for evaluating imputation performances. Depending on the detailed graphical and quantitative analysis, it can be said that although computational methods, particularly EM-MCMC method, are computationally inefficient, they seem favorable for imputation of meteorological time series with respect to different missingness periods considering both measures and both series studied. To conclude, using the EM-MCMC algorithm for imputing missing values before conducting any statistical analyses of meteorological data will definitely decrease the amount of uncertainty and give more robust results. Moreover, the CD measure can be suggested for the performance evaluation of missing data imputation particularly with computational methods since it gives more precise results in meteorological time series.

Robust optical flow using adaptive Lorentzian filter for image reconstruction under noisy condition

NASA Astrophysics Data System (ADS)

Kesrarat, Darun; Patanavijit, Vorapoj

2017-02-01

In optical flow for motion allocation, the efficient result in Motion Vector (MV) is an important issue. Several noisy conditions may cause the unreliable result in optical flow algorithms. We discover that many classical optical flows algorithms perform better result under noisy condition when combined with modern optimized model. This paper introduces effective robust models of optical flow by using Robust high reliability spatial based optical flow algorithms using the adaptive Lorentzian norm influence function in computation on simple spatial temporal optical flows algorithm. Experiment on our proposed models confirm better noise tolerance in optical flow's MV under noisy condition when they are applied over simple spatial temporal optical flow algorithms as a filtering model in simple frame-to-frame correlation technique. We illustrate the performance of our models by performing an experiment on several typical sequences with differences in movement speed of foreground and background where the experiment sequences are contaminated by the additive white Gaussian noise (AWGN) at different noise decibels (dB). This paper shows very high effectiveness of noise tolerance models that they are indicated by peak signal to noise ratio (PSNR).

Topological determinants of self-sustained activity in a simple model of excitable dynamics on graphs

PubMed Central

Fretter, Christoph; Lesne, Annick; Hilgetag, Claus C.; Hütt, Marc-Thorsten

2017-01-01

Simple models of excitable dynamics on graphs are an efficient framework for studying the interplay between network topology and dynamics. This topic is of practical relevance to diverse fields, ranging from neuroscience to engineering. Here we analyze how a single excitation propagates through a random network as a function of the excitation threshold, that is, the relative amount of activity in the neighborhood required for the excitation of a node. We observe that two sharp transitions delineate a region of sustained activity. Using analytical considerations and numerical simulation, we show that these transitions originate from the presence of barriers to propagation and the excitation of topological cycles, respectively, and can be predicted from the network topology. Our findings are interpreted in the context of network reverberations and self-sustained activity in neural systems, which is a question of long-standing interest in computational neuroscience. PMID:28186182

Topological determinants of self-sustained activity in a simple model of excitable dynamics on graphs.

PubMed

Fretter, Christoph; Lesne, Annick; Hilgetag, Claus C; Hütt, Marc-Thorsten

2017-02-10

Simple models of excitable dynamics on graphs are an efficient framework for studying the interplay between network topology and dynamics. This topic is of practical relevance to diverse fields, ranging from neuroscience to engineering. Here we analyze how a single excitation propagates through a random network as a function of the excitation threshold, that is, the relative amount of activity in the neighborhood required for the excitation of a node. We observe that two sharp transitions delineate a region of sustained activity. Using analytical considerations and numerical simulation, we show that these transitions originate from the presence of barriers to propagation and the excitation of topological cycles, respectively, and can be predicted from the network topology. Our findings are interpreted in the context of network reverberations and self-sustained activity in neural systems, which is a question of long-standing interest in computational neuroscience.

Microstructure representations for sound absorbing fibrous media: 3D and 2D multiscale modelling and experiments

NASA Astrophysics Data System (ADS)

Zieliński, Tomasz G.

2017-11-01

The paper proposes and investigates computationally-efficient microstructure representations for sound absorbing fibrous media. Three-dimensional volume elements involving non-trivial periodic arrangements of straight fibres are examined as well as simple two-dimensional cells. It has been found that a simple 2D quasi-representative cell can provide similar predictions as a volume element which is in general much more geometrically accurate for typical fibrous materials. The multiscale modelling allowed to determine the effective speeds and damping of acoustic waves propagating in such media, which brings up a discussion on the correlation between the speed, penetration range and attenuation of sound waves. Original experiments on manufactured copper-wire samples are presented and the microstructure-based calculations of acoustic absorption are compared with the corresponding experimental results. In fact, the comparison suggested the microstructure modifications leading to representations with non-uniformly distributed fibres.

Using entropy measures to characterize human locomotion.

PubMed

Leverick, Graham; Szturm, Tony; Wu, Christine Q

2014-12-01

Entropy measures have been widely used to quantify the complexity of theoretical and experimental dynamical systems. In this paper, the value of using entropy measures to characterize human locomotion is demonstrated based on their construct validity, predictive validity in a simple model of human walking and convergent validity in an experimental study. Results show that four of the five considered entropy measures increase meaningfully with the increased probability of falling in a simple passive bipedal walker model. The same four entropy measures also experienced statistically significant increases in response to increasing age and gait impairment caused by cognitive interference in an experimental study. Of the considered entropy measures, the proposed quantized dynamical entropy (QDE) and quantization-based approximation of sample entropy (QASE) offered the best combination of sensitivity to changes in gait dynamics and computational efficiency. Based on these results, entropy appears to be a viable candidate for assessing the stability of human locomotion.

Temperature-dependent layer breathing modes in two-dimensional materials

NASA Astrophysics Data System (ADS)

Maity, Indrajit; Maiti, Prabal K.; Jain, Manish

2018-04-01

Relative out-of-plane displacements of the constituent layers of two-dimensional materials give rise to unique low-frequency breathing modes. By computing the height-height correlation functions from molecular dynamics simulations, we show that the layer breathing modes (LBMs) can be mapped consistently to vibrations of a simple linear chain model. Our calculated thickness dependence of LBM frequencies for few-layer (FL) graphene and molybdenum disulfide (MoS2) are in excellent agreement with available experiments. Our results show a redshift of LBM frequency with an increase in temperature, which is a direct consequence of anharmonicities present in the interlayer interaction. We also predict the thickness and temperature dependence of LBM frequencies for FL hexagonal boron nitride. Our Rapid Communication provides a simple and efficient way to probe the interlayer interaction for layered materials and their heterostructures with the inclusion of anharmonic effects.

Topological determinants of self-sustained activity in a simple model of excitable dynamics on graphs

NASA Astrophysics Data System (ADS)

Fretter, Christoph; Lesne, Annick; Hilgetag, Claus C.; Hütt, Marc-Thorsten

2017-02-01

Simple models of excitable dynamics on graphs are an efficient framework for studying the interplay between network topology and dynamics. This topic is of practical relevance to diverse fields, ranging from neuroscience to engineering. Here we analyze how a single excitation propagates through a random network as a function of the excitation threshold, that is, the relative amount of activity in the neighborhood required for the excitation of a node. We observe that two sharp transitions delineate a region of sustained activity. Using analytical considerations and numerical simulation, we show that these transitions originate from the presence of barriers to propagation and the excitation of topological cycles, respectively, and can be predicted from the network topology. Our findings are interpreted in the context of network reverberations and self-sustained activity in neural systems, which is a question of long-standing interest in computational neuroscience.

Toward all-carbon electronics: fabrication of graphene-based flexible electronic circuits and memory cards using maskless laser direct writing.

PubMed

Liang, Jiajie; Chen, Yongsheng; Xu, Yanfei; Liu, Zhibo; Zhang, Long; Zhao, Xin; Zhang, Xiaoliang; Tian, Jianguo; Huang, Yi; Ma, Yanfeng; Li, Feifei

2010-11-01

Owing to its extraordinary electronic property, chemical stability, and unique two-dimensional nanostructure, graphene is being considered as an ideal material for the highly expected all-carbon-based micro/nanoscale electronics. Herein, we present a simple yet versatile approach to constructing all-carbon micro/nanoelectronics using solution-processing graphene films directly. From these graphene films, various graphene-based microcosmic patterns and structures have been fabricated using maskless computer-controlled laser cutting. Furthermore, a complete system involving a prototype of a flexible write-once-read-many-times memory card and a fast data-reading system has been demonstrated, with infinite data retention time and high reliability. These results indicate that graphene could be the ideal material for fabricating the highly demanded all-carbon and flexible devices and electronics using the simple and efficient roll-to-roll printing process when combined with maskless direct data writing.

A Detailed Data-Driven Network Model of Prefrontal Cortex Reproduces Key Features of In Vivo Activity

PubMed Central

Hass, Joachim; Hertäg, Loreen; Durstewitz, Daniel

2016-01-01

The prefrontal cortex is centrally involved in a wide range of cognitive functions and their impairment in psychiatric disorders. Yet, the computational principles that govern the dynamics of prefrontal neural networks, and link their physiological, biochemical and anatomical properties to cognitive functions, are not well understood. Computational models can help to bridge the gap between these different levels of description, provided they are sufficiently constrained by experimental data and capable of predicting key properties of the intact cortex. Here, we present a detailed network model of the prefrontal cortex, based on a simple computationally efficient single neuron model (simpAdEx), with all parameters derived from in vitro electrophysiological and anatomical data. Without additional tuning, this model could be shown to quantitatively reproduce a wide range of measures from in vivo electrophysiological recordings, to a degree where simulated and experimentally observed activities were statistically indistinguishable. These measures include spike train statistics, membrane potential fluctuations, local field potentials, and the transmission of transient stimulus information across layers. We further demonstrate that model predictions are robust against moderate changes in key parameters, and that synaptic heterogeneity is a crucial ingredient to the quantitative reproduction of in vivo-like electrophysiological behavior. Thus, we have produced a physiologically highly valid, in a quantitative sense, yet computationally efficient PFC network model, which helped to identify key properties underlying spike time dynamics as observed in vivo, and can be harvested for in-depth investigation of the links between physiology and cognition. PMID:27203563

Calculation of absolute protein-ligand binding free energy using distributed replica sampling.

PubMed

Rodinger, Tomas; Howell, P Lynne; Pomès, Régis

2008-10-21

Distributed replica sampling [T. Rodinger et al., J. Chem. Theory Comput. 2, 725 (2006)] is a simple and general scheme for Boltzmann sampling of conformational space by computer simulation in which multiple replicas of the system undergo a random walk in reaction coordinate or temperature space. Individual replicas are linked through a generalized Hamiltonian containing an extra potential energy term or bias which depends on the distribution of all replicas, thus enforcing the desired sampling distribution along the coordinate or parameter of interest regardless of free energy barriers. In contrast to replica exchange methods, efficient implementation of the algorithm does not require synchronicity of the individual simulations. The algorithm is inherently suited for large-scale simulations using shared or heterogeneous computing platforms such as a distributed network. In this work, we build on our original algorithm by introducing Boltzmann-weighted jumping, which allows moves of a larger magnitude and thus enhances sampling efficiency along the reaction coordinate. The approach is demonstrated using a realistic and biologically relevant application; we calculate the standard binding free energy of benzene to the L99A mutant of T4 lysozyme. Distributed replica sampling is used in conjunction with thermodynamic integration to compute the potential of mean force for extracting the ligand from protein and solvent along a nonphysical spatial coordinate. Dynamic treatment of the reaction coordinate leads to faster statistical convergence of the potential of mean force than a conventional static coordinate, which suffers from slow transitions on a rugged potential energy surface.

Calculation of absolute protein-ligand binding free energy using distributed replica sampling

NASA Astrophysics Data System (ADS)

Rodinger, Tomas; Howell, P. Lynne; Pomès, Régis

2008-10-01

Distributed replica sampling [T. Rodinger et al., J. Chem. Theory Comput. 2, 725 (2006)] is a simple and general scheme for Boltzmann sampling of conformational space by computer simulation in which multiple replicas of the system undergo a random walk in reaction coordinate or temperature space. Individual replicas are linked through a generalized Hamiltonian containing an extra potential energy term or bias which depends on the distribution of all replicas, thus enforcing the desired sampling distribution along the coordinate or parameter of interest regardless of free energy barriers. In contrast to replica exchange methods, efficient implementation of the algorithm does not require synchronicity of the individual simulations. The algorithm is inherently suited for large-scale simulations using shared or heterogeneous computing platforms such as a distributed network. In this work, we build on our original algorithm by introducing Boltzmann-weighted jumping, which allows moves of a larger magnitude and thus enhances sampling efficiency along the reaction coordinate. The approach is demonstrated using a realistic and biologically relevant application; we calculate the standard binding free energy of benzene to the L99A mutant of T4 lysozyme. Distributed replica sampling is used in conjunction with thermodynamic integration to compute the potential of mean force for extracting the ligand from protein and solvent along a nonphysical spatial coordinate. Dynamic treatment of the reaction coordinate leads to faster statistical convergence of the potential of mean force than a conventional static coordinate, which suffers from slow transitions on a rugged potential energy surface.

Ultrathin nondoped emissive layers for efficient and simple monochrome and white organic light-emitting diodes.

PubMed

Zhao, Yongbiao; Chen, Jiangshan; Ma, Dongge

2013-02-01

In this paper, highly efficient and simple monochrome blue, green, orange, and red organic light emitting diodes (OLEDs) based on ultrathin nondoped emissive layers (EMLs) have been reported. The ultrathin nondoped EML was constructed by introducing a 0.1 nm thin layer of pure phosphorescent dyes between a hole transporting layer and an electron transporting layer. The maximum external quantum efficiencies (EQEs) reached 17.1%, 20.9%, 17.3%, and 19.2% for blue, green, orange, and red monochrome OLEDs, respectively, indicating the universality of the ultrathin nondoped EML for most phosphorescent dyes. On the basis of this, simple white OLED structures are also demonstrated. The demonstrated complementary blue/orange, three primary blue/green/red, and four color blue/green/orange/red white OLEDs show high efficiency and good white emission, indicating the advantage of ultrathin nondoped EMLs on constructing simple and efficient white OLEDs.

Cooperative high-performance storage in the accelerated strategic computing initiative

NASA Technical Reports Server (NTRS)

Gary, Mark; Howard, Barry; Louis, Steve; Minuzzo, Kim; Seager, Mark

1996-01-01

The use and acceptance of new high-performance, parallel computing platforms will be impeded by the absence of an infrastructure capable of supporting orders-of-magnitude improvement in hierarchical storage and high-speed I/O (Input/Output). The distribution of these high-performance platforms and supporting infrastructures across a wide-area network further compounds this problem. We describe an architectural design and phased implementation plan for a distributed, Cooperative Storage Environment (CSE) to achieve the necessary performance, user transparency, site autonomy, communication, and security features needed to support the Accelerated Strategic Computing Initiative (ASCI). ASCI is a Department of Energy (DOE) program attempting to apply terascale platforms and Problem-Solving Environments (PSEs) toward real-world computational modeling and simulation problems. The ASCI mission must be carried out through a unified, multilaboratory effort, and will require highly secure, efficient access to vast amounts of data. The CSE provides a logically simple, geographically distributed, storage infrastructure of semi-autonomous cooperating sites to meet the strategic ASCI PSE goal of highperformance data storage and access at the user desktop.

A programming language for composable DNA circuits

PubMed Central

Phillips, Andrew; Cardelli, Luca

2009-01-01

Recently, a range of information-processing circuits have been implemented in DNA by using strand displacement as their main computational mechanism. Examples include digital logic circuits and catalytic signal amplification circuits that function as efficient molecular detectors. As new paradigms for DNA computation emerge, the development of corresponding languages and tools for these paradigms will help to facilitate the design of DNA circuits and their automatic compilation to nucleotide sequences. We present a programming language for designing and simulating DNA circuits in which strand displacement is the main computational mechanism. The language includes basic elements of sequence domains, toeholds and branch migration, and assumes that strands do not possess any secondary structure. The language is used to model and simulate a variety of circuits, including an entropy-driven catalytic gate, a simple gate motif for synthesizing large-scale circuits and a scheme for implementing an arbitrary system of chemical reactions. The language is a first step towards the design of modelling and simulation tools for DNA strand displacement, which complements the emergence of novel implementation strategies for DNA computing. PMID:19535415

A programming language for composable DNA circuits.

PubMed

Phillips, Andrew; Cardelli, Luca

2009-08-06

Recently, a range of information-processing circuits have been implemented in DNA by using strand displacement as their main computational mechanism. Examples include digital logic circuits and catalytic signal amplification circuits that function as efficient molecular detectors. As new paradigms for DNA computation emerge, the development of corresponding languages and tools for these paradigms will help to facilitate the design of DNA circuits and their automatic compilation to nucleotide sequences. We present a programming language for designing and simulating DNA circuits in which strand displacement is the main computational mechanism. The language includes basic elements of sequence domains, toeholds and branch migration, and assumes that strands do not possess any secondary structure. The language is used to model and simulate a variety of circuits, including an entropy-driven catalytic gate, a simple gate motif for synthesizing large-scale circuits and a scheme for implementing an arbitrary system of chemical reactions. The language is a first step towards the design of modelling and simulation tools for DNA strand displacement, which complements the emergence of novel implementation strategies for DNA computing.

Design and function of biomimetic multilayer water purification membranes

PubMed Central

Ling, Shengjie; Qin, Zhao; Huang, Wenwen; Cao, Sufeng; Kaplan, David L.; Buehler, Markus J.

2017-01-01

Multilayer architectures in water purification membranes enable increased water throughput, high filter efficiency, and high molecular loading capacity. However, the preparation of membranes with well-organized multilayer structures, starting from the nanoscale to maximize filtration efficiency, remains a challenge. We report a complete strategy to fully realize a novel biomaterial-based multilayer nanoporous membrane via the integration of computational simulation and experimental fabrication. Our comparative computational simulations, based on coarse-grained models of protein nanofibrils and mineral plates, reveal that the multilayer structure can only form with weak interactions between nanofibrils and mineral plates. We demonstrate experimentally that silk nanofibril (SNF) and hydroxyapatite (HAP) can be used to fabricate highly ordered multilayer membranes with nanoporous features by combining protein self-assembly and in situ biomineralization. The production is optimized to be a simple and highly repeatable process that does not require sophisticated equipment and is suitable for scaled production of low-cost water purification membranes. These membranes not only show ultrafast water penetration but also exhibit broad utility and high efficiency of removal and even reuse (in some cases) of contaminants, including heavy metal ions, dyes, proteins, and other nanoparticles in water. Our biomimetic design and synthesis of these functional SNF/HAP materials have established a paradigm that could lead to the large-scale, low-cost production of multilayer materials with broad spectrum and efficiency for water purification, with applications in wastewater treatment, biomedicine, food industry, and the life sciences. PMID:28435877

Uvf - Unified Volume Format: A General System for Efficient Handling of Large Volumetric Datasets.

PubMed

Krüger, Jens; Potter, Kristin; Macleod, Rob S; Johnson, Christopher

2008-01-01

With the continual increase in computing power, volumetric datasets with sizes ranging from only a few megabytes to petascale are generated thousands of times per day. Such data may come from an ordinary source such as simple everyday medical imaging procedures, while larger datasets may be generated from cluster-based scientific simulations or measurements of large scale experiments. In computer science an incredible amount of work worldwide is put into the efficient visualization of these datasets. As researchers in the field of scientific visualization, we often have to face the task of handling very large data from various sources. This data usually comes in many different data formats. In medical imaging, the DICOM standard is well established, however, most research labs use their own data formats to store and process data. To simplify the task of reading the many different formats used with all of the different visualization programs, we present a system for the efficient handling of many types of large scientific datasets (see Figure 1 for just a few examples). While primarily targeted at structured volumetric data, UVF can store just about any type of structured and unstructured data. The system is composed of a file format specification with a reference implementation of a reader. It is not only a common, easy to implement format but also allows for efficient rendering of most datasets without the need to convert the data in memory.

Design and function of biomimetic multilayer water purification membranes.

PubMed

Ling, Shengjie; Qin, Zhao; Huang, Wenwen; Cao, Sufeng; Kaplan, David L; Buehler, Markus J

2017-04-01

Multilayer architectures in water purification membranes enable increased water throughput, high filter efficiency, and high molecular loading capacity. However, the preparation of membranes with well-organized multilayer structures, starting from the nanoscale to maximize filtration efficiency, remains a challenge. We report a complete strategy to fully realize a novel biomaterial-based multilayer nanoporous membrane via the integration of computational simulation and experimental fabrication. Our comparative computational simulations, based on coarse-grained models of protein nanofibrils and mineral plates, reveal that the multilayer structure can only form with weak interactions between nanofibrils and mineral plates. We demonstrate experimentally that silk nanofibril (SNF) and hydroxyapatite (HAP) can be used to fabricate highly ordered multilayer membranes with nanoporous features by combining protein self-assembly and in situ biomineralization. The production is optimized to be a simple and highly repeatable process that does not require sophisticated equipment and is suitable for scaled production of low-cost water purification membranes. These membranes not only show ultrafast water penetration but also exhibit broad utility and high efficiency of removal and even reuse (in some cases) of contaminants, including heavy metal ions, dyes, proteins, and other nanoparticles in water. Our biomimetic design and synthesis of these functional SNF/HAP materials have established a paradigm that could lead to the large-scale, low-cost production of multilayer materials with broad spectrum and efficiency for water purification, with applications in wastewater treatment, biomedicine, food industry, and the life sciences.

Static Extended Trailing Edge for Lift Enhancement: Experimental and Computational Studies

NASA Technical Reports Server (NTRS)

Liu, Tianshu; Montefort; Liou, William W.; Pantula, Srinivasa R.; Shams, Qamar A.

2007-01-01

A static extended trailing edge attached to a NACA0012 airfoil section is studied for achieving lift enhancement at a small drag penalty. It is indicated that the thin extended trailing edge can enhance the lift while the zero-lift drag is not significantly increased. Experiments and calculations are conducted to compare the aerodynamic characteristics of the extended trailing edge with those of Gurney flap and conventional flap. The extended trailing edge, as a simple mechanical device added on a wing without altering the basic configuration, has a good potential to improve the cruise flight efficiency.

Rapid calculation of radiative heating rates and photodissociation rates in inhomogeneous multiple scattering atmospheres

NASA Technical Reports Server (NTRS)

Toon, Owen B.; Mckay, C. P.; Ackerman, T. P.; Santhanam, K.

1989-01-01

The solution of the generalized two-stream approximation for radiative transfer in homogeneous multiple scattering atmospheres is extended to vertically inhomogeneous atmospheres in a manner which is numerically stable and computationally efficient. It is shown that solar energy deposition rates, photolysis rates, and infrared cooling rates all may be calculated with the simple modifications of a single algorithm. The accuracy of the algorithm is generally better than 10 percent, so that other uncertainties, such as in absorption coefficients, may often dominate the error in calculation of the quantities of interest to atmospheric studies.

Simulation Speed Analysis and Improvements of Modelica Models for Building Energy Simulation

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

Jorissen, Filip; Wetter, Michael; Helsen, Lieve

This paper presents an approach for speeding up Modelica models. Insight is provided into how Modelica models are solved and what determines the tool’s computational speed. Aspects such as algebraic loops, code efficiency and integrator choice are discussed. This is illustrated using simple building simulation examples and Dymola. The generality of the work is in some cases verified using OpenModelica. Using this approach, a medium sized office building including building envelope, heating ventilation and air conditioning (HVAC) systems and control strategy can be simulated at a speed five hundred times faster than real time.

Simple, accurate formula for the average bit error probability of multiple-input multiple-output free-space optical links over negative exponential turbulence channels.

PubMed

Peppas, Kostas P; Lazarakis, Fotis; Alexandridis, Antonis; Dangakis, Kostas

2012-08-01

In this Letter we investigate the error performance of multiple-input multiple-output free-space optical communication systems employing intensity modulation/direct detection and operating over strong atmospheric turbulence channels. Atmospheric-induced strong turbulence fading is modeled using the negative exponential distribution. For the considered system, an approximate yet accurate analytical expression for the average bit error probability is derived and an efficient method for its numerical evaluation is proposed. Numerically evaluated and computer simulation results are further provided to demonstrate the validity of the proposed mathematical analysis.

An underwater light attenuation scheme for marine ecosystem models.

PubMed

Penta, Bradley; Lee, Zhongping; Kudela, Raphael M; Palacios, Sherry L; Gray, Deric J; Jolliff, Jason K; Shulman, Igor G

2008-10-13

Simulation of underwater light is essential for modeling marine ecosystems. A new model of underwater light attenuation is presented and compared with previous models. In situ data collected in Monterey Bay, CA. during September 2006 are used for validation. It is demonstrated that while the new light model is computationally simple and efficient it maintains accuracy and flexibility. When this light model is incorporated into an ecosystem model, the correlation between modeled and observed coastal chlorophyll is improved over an eight-year time period. While the simulation of a deep chlorophyll maximum demonstrates the effect of the new model at depth.

Electrically reconfigurable logic array

NASA Technical Reports Server (NTRS)

Agarwal, R. K.

1982-01-01

To compose the complicated systems using algorithmically specialized logic circuits or processors, one solution is to perform relational computations such as union, division and intersection directly on hardware. These relations can be pipelined efficiently on a network of processors having an array configuration. These processors can be designed and implemented with a few simple cells. In order to determine the state-of-the-art in Electrically Reconfigurable Logic Array (ERLA), a survey of the available programmable logic array (PLA) and the logic circuit elements used in such arrays was conducted. Based on this survey some recommendations are made for ERLA devices.

An efficient temporal logic for robotic task planning

NASA Technical Reports Server (NTRS)

Becker, Jeffrey M.

1989-01-01

Computations required for temporal reasoning can be prohibitively expensive if fully general representations are used. Overly simple representations, such as totally ordered sequence of time points, are inadequate for use in a nonlinear task planning system. A middle ground is identified which is general enough to support a capable nonlinear task planner, but specialized enough that the system can support online task planning in real time. A Temporal Logic System (TLS) was developed during the Intelligent Task Automation (ITA) project to support robotic task planning. TLS is also used within the ITA system to support plan execution, monitoring, and exception handling.

Analysis of self-oscillating dc-to-dc converters

NASA Technical Reports Server (NTRS)

Burger, P.

1974-01-01

The basic operational characteristics of dc-to-dc converters are analyzed along with the basic physical characteristics of power converters. A simple class of dc-to-dc power converters are chosen which could satisfy any set of operating requirements, and three different controlling methods in this class are described in detail. Necessary conditions for the stability of these converters are measured through analog computer simulation whose curves are related to other operational characteristics, such as ripple and regulation. Further research is suggested for the solution of absolute stability and efficient physical design of this class of power converters.

Application of the probabilistic approximate analysis method to a turbopump blade analysis. [for Space Shuttle Main Engine

NASA Technical Reports Server (NTRS)

Thacker, B. H.; Mcclung, R. C.; Millwater, H. R.

1990-01-01

An eigenvalue analysis of a typical space propulsion system turbopump blade is presented using an approximate probabilistic analysis methodology. The methodology was developed originally to investigate the feasibility of computing probabilistic structural response using closed-form approximate models. This paper extends the methodology to structures for which simple closed-form solutions do not exist. The finite element method will be used for this demonstration, but the concepts apply to any numerical method. The results agree with detailed analysis results and indicate the usefulness of using a probabilistic approximate analysis in determining efficient solution strategies.

Complementary Reliability-Based Decodings of Binary Linear Block Codes

NASA Technical Reports Server (NTRS)

Fossorier, Marc P. C.; Lin, Shu

1997-01-01

This correspondence presents a hybrid reliability-based decoding algorithm which combines the reprocessing method based on the most reliable basis and a generalized Chase-type algebraic decoder based on the least reliable positions. It is shown that reprocessing with a simple additional algebraic decoding effort achieves significant coding gain. For long codes, the order of reprocessing required to achieve asymptotic optimum error performance is reduced by approximately 1/3. This significantly reduces the computational complexity, especially for long codes. Also, a more efficient criterion for stopping the decoding process is derived based on the knowledge of the algebraic decoding solution.

Efficient algorithms for the simulation of non-adiabatic electron transfer in complex molecular systems: application to DNA.

PubMed

Kubař, Tomáš; Elstner, Marcus

2013-04-28

In this work, a fragment-orbital density functional theory-based method is combined with two different non-adiabatic schemes for the propagation of the electronic degrees of freedom. This allows us to perform unbiased simulations of electron transfer processes in complex media, and the computational scheme is applied to the transfer of a hole in solvated DNA. It turns out that the mean-field approach, where the wave function of the hole is driven into a superposition of adiabatic states, leads to over-delocalization of the hole charge. This problem is avoided using a surface hopping scheme, resulting in a smaller rate of hole transfer. The method is highly efficient due to the on-the-fly computation of the coarse-grained DFT Hamiltonian for the nucleobases, which is coupled to the environment using a QM/MM approach. The computational efficiency and partial parallel character of the methodology make it possible to simulate electron transfer in systems of relevant biochemical size on a nanosecond time scale. Since standard non-polarizable force fields are applied in the molecular-mechanics part of the calculation, a simple scaling scheme was introduced into the electrostatic potential in order to simulate the effect of electronic polarization. It is shown that electronic polarization has an important effect on the features of charge transfer. The methodology is applied to two kinds of DNA sequences, illustrating the features of transfer along a flat energy landscape as well as over an energy barrier. The performance and relative merit of the mean-field scheme and the surface hopping for this application are discussed.

Single Spore Isolation as a Simple and Efficient Technique to obtain fungal pure culture

NASA Astrophysics Data System (ADS)

Noman, E.; Al-Gheethi, AA; Rahman, N. K.; Talip, B.; Mohamed, R.; H, N.; Kadir, O. A.

2018-04-01

The successful identification of fungi by phenotypic methods or molecular technique depends mainly on the using an advanced technique for purifying the isolates. The most efficient is the single spore technique due to the simple requirements and the efficiency in preventing the contamination by yeast, mites or bacteria. The method described in the present work is depends on the using of a light microscope to transfer one spore into a new culture medium. The present work describes a simple and efficient procedure for single spore isolation to purify of fungi recovered from the clinical wastes.

Spectral analysis of GEOS-3 altimeter data and frequency domain collocation. [to estimate gravity anomalies

NASA Technical Reports Server (NTRS)

Eren, K.

1980-01-01

The mathematical background in spectral analysis as applied to geodetic applications is summarized. The resolution (cut-off frequency) of the GEOS 3 altimeter data is examined by determining the shortest wavelength (corresponding to the cut-off frequency) recoverable. The data from some 18 profiles are used. The total power (variance) in the sea surface topography with respect to the reference ellipsoid as well as with respect to the GEM-9 surface is computed. A fast inversion algorithm for matrices of simple and block Toeplitz matrices and its application to least squares collocation is explained. This algorithm yields a considerable gain in computer time and storage in comparison with conventional least squares collocation. Frequency domain least squares collocation techniques are also introduced and applied to estimating gravity anomalies from GEOS 3 altimeter data. These techniques substantially reduce the computer time and requirements in storage associated with the conventional least squares collocation. Numerical examples given demonstrate the efficiency and speed of these techniques.

Mathematical and computational model for the analysis of micro hybrid rocket motor

NASA Astrophysics Data System (ADS)

Stoia-Djeska, Marius; Mingireanu, Florin

2012-11-01

The hybrid rockets use a two-phase propellant system. In the present work we first develop a simplified model of the coupling of the hybrid combustion process with the complete unsteady flow, starting from the combustion port and ending with the nozzle. The physical and mathematical model are adapted to the simulations of micro hybrid rocket motors. The flow model is based on the one-dimensional Euler equations with source terms. The flow equations and the fuel regression rate law are solved in a coupled manner. The platform of the numerical simulations is an implicit fourth-order Runge-Kutta second order cell-centred finite volume method. The numerical results obtained with this model show a good agreement with published experimental and numerical results. The computational model developed in this work is simple, computationally efficient and offers the advantage of taking into account a large number of functional and constructive parameters that are used by the engineers.

SeqBox: RNAseq/ChIPseq reproducible analysis on a consumer game computer.

PubMed

Beccuti, Marco; Cordero, Francesca; Arigoni, Maddalena; Panero, Riccardo; Amparore, Elvio G; Donatelli, Susanna; Calogero, Raffaele A

2018-03-01

Short reads sequencing technology has been used for more than a decade now. However, the analysis of RNAseq and ChIPseq data is still computational demanding and the simple access to raw data does not guarantee results reproducibility between laboratories. To address these two aspects, we developed SeqBox, a cheap, efficient and reproducible RNAseq/ChIPseq hardware/software solution based on NUC6I7KYK mini-PC (an Intel consumer game computer with a fast processor and a high performance SSD disk), and Docker container platform. In SeqBox the analysis of RNAseq and ChIPseq data is supported by a friendly GUI. This allows access to fast and reproducible analysis also to scientists with/without scripting experience. Docker container images, docker4seq package and the GUI are available at http://www.bioinformatica.unito.it/reproducibile.bioinformatics.html. beccuti@di.unito.it. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Fast and Accurate Circuit Design Automation through Hierarchical Model Switching.

PubMed

Huynh, Linh; Tagkopoulos, Ilias

2015-08-21

In computer-aided biological design, the trifecta of characterized part libraries, accurate models and optimal design parameters is crucial for producing reliable designs. As the number of parts and model complexity increase, however, it becomes exponentially more difficult for any optimization method to search the solution space, hence creating a trade-off that hampers efficient design. To address this issue, we present a hierarchical computer-aided design architecture that uses a two-step approach for biological design. First, a simple model of low computational complexity is used to predict circuit behavior and assess candidate circuit branches through branch-and-bound methods. Then, a complex, nonlinear circuit model is used for a fine-grained search of the reduced solution space, thus achieving more accurate results. Evaluation with a benchmark of 11 circuits and a library of 102 experimental designs with known characterization parameters demonstrates a speed-up of 3 orders of magnitude when compared to other design methods that provide optimality guarantees.

Using computer-aided drug design and medicinal chemistry strategies in the fight against diabetes.

PubMed

Semighini, Evandro P; Resende, Jonathan A; de Andrade, Peterson; Morais, Pedro A B; Carvalho, Ivone; Taft, Carlton A; Silva, Carlos H T P

2011-04-01

The aim of this work is to present a simple, practical and efficient protocol for drug design, in particular Diabetes, which includes selection of the illness, good choice of a target as well as a bioactive ligand and then usage of various computer aided drug design and medicinal chemistry tools to design novel potential drug candidates in different diseases. We have selected the validated target dipeptidyl peptidase IV (DPP-IV), whose inhibition contributes to reduce glucose levels in type 2 diabetes patients. The most active inhibitor with complex X-ray structure reported was initially extracted from the BindingDB database. By using molecular modification strategies widely used in medicinal chemistry, besides current state-of-the-art tools in drug design (including flexible docking, virtual screening, molecular interaction fields, molecular dynamics, ADME and toxicity predictions), we have proposed 4 novel potential DPP-IV inhibitors with drug properties for Diabetes control, which have been supported and validated by all the computational tools used herewith.

Parallel compression/decompression-based datapath architecture for multibeam mask writers

NASA Astrophysics Data System (ADS)

Chaudhary, Narendra; Savari, Serap A.

2017-06-01

Multibeam electron beam systems will be used in the future for mask writing and for complimentary lithography. The major challenges of the multibeam systems are in meeting throughput requirements and in handling the large data volumes associated with writing grayscale data on the wafer. In terms of future communications and computational requirements Amdahl's Law suggests that a simple increase of computation power and parallelism may not be a sustainable solution. We propose a parallel data compression algorithm to exploit the sparsity of mask data and a grayscale video-like representation of data. To improve the communication and computational efficiency of these systems at the write time we propose an alternate datapath architecture partly motivated by multibeam direct write lithography and partly motivated by the circuit testing literature, where parallel decompression reduces clock cycles. We explain a deflection plate architecture inspired by NuFlare Technology's multibeam mask writing system and how our datapath architecture can be easily added to it to improve performance.

Parallel compression/decompression-based datapath architecture for multibeam mask writers

NASA Astrophysics Data System (ADS)

Chaudhary, Narendra; Savari, Serap A.

2017-10-01

Multibeam electron beam systems will be used in the future for mask writing and for complementary lithography. The major challenges of the multibeam systems are in meeting throughput requirements and in handling the large data volumes associated with writing grayscale data on the wafer. In terms of future communications and computational requirements, Amdahl's law suggests that a simple increase of computation power and parallelism may not be a sustainable solution. We propose a parallel data compression algorithm to exploit the sparsity of mask data and a grayscale video-like representation of data. To improve the communication and computational efficiency of these systems at the write time, we propose an alternate datapath architecture partly motivated by multibeam direct-write lithography and partly motivated by the circuit testing literature, where parallel decompression reduces clock cycles. We explain a deflection plate architecture inspired by NuFlare Technology's multibeam mask writing system and how our datapath architecture can be easily added to it to improve performance.

Exploiting symmetries in the modeling and analysis of tires

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Andersen, Carl M.; Tanner, John A.

1987-01-01

A simple and efficient computational strategy for reducing both the size of a tire model and the cost of the analysis of tires in the presence of symmetry-breaking conditions (unsymmetry in the tire material, geometry, or loading) is presented. The strategy is based on approximating the unsymmetric response of the tire with a linear combination of symmetric and antisymmetric global approximation vectors (or modes). Details are presented for the three main elements of the computational strategy, which include: use of special three-field mixed finite-element models, use of operator splitting, and substantial reduction in the number of degrees of freedom. The proposed computational stategy is applied to three quasi-symmetric problems of tires: linear analysis of anisotropic tires, through use of semianalytic finite elements, nonlinear analysis of anisotropic tires through use of two-dimensional shell finite elements, and nonlinear analysis of orthotropic tires subjected to unsymmetric loading. Three basic types of symmetry (and their combinations) exhibited by the tire response are identified.

A physics-based algorithm for real-time simulation of electrosurgery procedures in minimally invasive surgery.

PubMed

Lu, Zhonghua; Arikatla, Venkata S; Han, Zhongqing; Allen, Brian F; De, Suvranu

2014-12-01

High-frequency electricity is used in the majority of surgical interventions. However, modern computer-based training and simulation systems rely on physically unrealistic models that fail to capture the interplay of the electrical, mechanical and thermal properties of biological tissue. We present a real-time and physically realistic simulation of electrosurgery by modelling the electrical, thermal and mechanical properties as three iteratively solved finite element models. To provide subfinite-element graphical rendering of vaporized tissue, a dual-mesh dynamic triangulation algorithm based on isotherms is proposed. The block compressed row storage (BCRS) structure is shown to be critical in allowing computationally efficient changes in the tissue topology due to vaporization. We have demonstrated our physics-based electrosurgery cutting algorithm through various examples. Our matrix manipulation algorithms designed for topology changes have shown low computational cost. Our simulator offers substantially greater physical fidelity compared to previous simulators that use simple geometry-based heat characterization. Copyright © 2013 John Wiley & Sons, Ltd.

Optical signal processing using photonic reservoir computing

NASA Astrophysics Data System (ADS)

Salehi, Mohammad Reza; Dehyadegari, Louiza

2014-10-01

As a new approach to recognition and classification problems, photonic reservoir computing has such advantages as parallel information processing, power efficient and high speed. In this paper, a photonic structure has been proposed for reservoir computing which is investigated using a simple, yet, non-partial noisy time series prediction task. This study includes the application of a suitable topology with self-feedbacks in a network of SOA's - which lends the system a strong memory - and leads to adjusting adequate parameters resulting in perfect recognition accuracy (100%) for noise-free time series, which shows a 3% improvement over previous results. For the classification of noisy time series, the rate of accuracy showed a 4% increase and amounted to 96%. Furthermore, an analytical approach was suggested to solve rate equations which led to a substantial decrease in the simulation time, which is an important parameter in classification of large signals such as speech recognition, and better results came up compared with previous works.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; A Recursive Maximum Likelihood Decoding

NASA Technical Reports Server (NTRS)

Lin, Shu; Fossorier, Marc

1998-01-01

The Viterbi algorithm is indeed a very simple and efficient method of implementing the maximum likelihood decoding. However, if we take advantage of the structural properties in a trellis section, other efficient trellis-based decoding algorithms can be devised. Recently, an efficient trellis-based recursive maximum likelihood decoding (RMLD) algorithm for linear block codes has been proposed. This algorithm is more efficient than the conventional Viterbi algorithm in both computation and hardware requirements. Most importantly, the implementation of this algorithm does not require the construction of the entire code trellis, only some special one-section trellises of relatively small state and branch complexities are needed for constructing path (or branch) metric tables recursively. At the end, there is only one table which contains only the most likely code-word and its metric for a given received sequence r = (r(sub 1), r(sub 2),...,r(sub n)). This algorithm basically uses the divide and conquer strategy. Furthermore, it allows parallel/pipeline processing of received sequences to speed up decoding.

Efficient Hardware Implementation of the Lightweight Block Encryption Algorithm LEA

PubMed Central

Lee, Donggeon; Kim, Dong-Chan; Kwon, Daesung; Kim, Howon

2014-01-01

Recently, due to the advent of resource-constrained trends, such as smartphones and smart devices, the computing environment is changing. Because our daily life is deeply intertwined with ubiquitous networks, the importance of security is growing. A lightweight encryption algorithm is essential for secure communication between these kinds of resource-constrained devices, and many researchers have been investigating this field. Recently, a lightweight block cipher called LEA was proposed. LEA was originally targeted for efficient implementation on microprocessors, as it is fast when implemented in software and furthermore, it has a small memory footprint. To reflect on recent technology, all required calculations utilize 32-bit wide operations. In addition, the algorithm is comprised of not complex S-Box-like structures but simple Addition, Rotation, and XOR operations. To the best of our knowledge, this paper is the first report on a comprehensive hardware implementation of LEA. We present various hardware structures and their implementation results according to key sizes. Even though LEA was originally targeted at software efficiency, it also shows high efficiency when implemented as hardware. PMID:24406859

Research on allocation efficiency of the daisy chain allocation algorithm

NASA Astrophysics Data System (ADS)

Shi, Jingping; Zhang, Weiguo

2013-03-01

With the improvement of the aircraft performance in reliability, maneuverability and survivability, the number of the control effectors increases a lot. How to distribute the three-axis moments into the control surfaces reasonably becomes an important problem. Daisy chain method is simple and easy to be carried out in the design of the allocation system. But it can not solve the allocation problem for entire attainable moment subset. For the lateral-directional allocation problem, the allocation efficiency of the daisy chain can be directly measured by the area of its subset of attainable moments. Because of the non-linear allocation characteristic, the subset of attainable moments of daisy-chain method is a complex non-convex polygon, and it is difficult to solve directly. By analyzing the two-dimensional allocation problems with a "micro-element" idea, a numerical calculation algorithm is proposed to compute the area of the non-convex polygon. In order to improve the allocation efficiency of the algorithm, a genetic algorithm with the allocation efficiency chosen as the fitness function is proposed to find the best pseudo-inverse matrix.

On the Use of Quartic Force Fields in Variational Calculations

NASA Technical Reports Server (NTRS)

Fortenberry, Ryan C.; Huang, Xinchuan; Yachmenev, Andrey; Thiel, Walter; Lee, Timothy J.

2013-01-01

The use of quartic force fields (QFFs) has been shown to be one of the most effective ways to efficiently compute vibrational frequencies for small molecules. In this paper we outline and discuss how the simple-internal or bond-length bond-angle (BLBA) coordinates can be transformed into Morse-cosine(-sine) coordinates which produce potential energy surfaces from QFFs that possess proper limiting behavior and can effectively describe the vibrational (or rovibrational) energy levels of an arbitrary molecular system. We investigate parameter scaling in the Morse coordinate, symmetry considerations, and examples of transformed QFFs making use of the MULTIMODE, TROVE, and VTET variational vibrational methods. Cases are referenced where variational computations coupled with transformed QFFs produce accuracies compared to experiment for fundamental frequencies on the order of 5 cm(exp -1) and often as good as 1 cm(exp -1).

Object-oriented analysis and design: a methodology for modeling the computer-based patient record.

PubMed

Egyhazy, C J; Eyestone, S M; Martino, J; Hodgson, C L

1998-08-01

The article highlights the importance of an object-oriented analysis and design (OOAD) methodology for the computer-based patient record (CPR) in the military environment. Many OOAD methodologies do not adequately scale up, allow for efficient reuse of their products, or accommodate legacy systems. A methodology that addresses these issues is formulated and used to demonstrate its applicability in a large-scale health care service system. During a period of 6 months, a team of object modelers and domain experts formulated an OOAD methodology tailored to the Department of Defense Military Health System and used it to produce components of an object model for simple order processing. This methodology and the lessons learned during its implementation are described. This approach is necessary to achieve broad interoperability among heterogeneous automated information systems.

Event detection and localization for small mobile robots using reservoir computing.

PubMed

Antonelo, E A; Schrauwen, B; Stroobandt, D

2008-08-01

Reservoir Computing (RC) techniques use a fixed (usually randomly created) recurrent neural network, or more generally any dynamic system, which operates at the edge of stability, where only a linear static readout output layer is trained by standard linear regression methods. In this work, RC is used for detecting complex events in autonomous robot navigation. This can be extended to robot localization tasks which are solely based on a few low-range, high-noise sensory data. The robot thus builds an implicit map of the environment (after learning) that is used for efficient localization by simply processing the input stream of distance sensors. These techniques are demonstrated in both a simple simulation environment and in the physically realistic Webots simulation of the commercially available e-puck robot, using several complex and even dynamic environments.

Young Children and Turtle Graphics Programming: Generating and Debugging Simple Turtle Programs.

ERIC Educational Resources Information Center

Cuneo, Diane O.

Turtle graphics is a popular vehicle for introducing children to computer programming. Children combine simple graphic commands to get a display screen cursor (called a turtle) to draw designs on the screen. The purpose of this study was to examine young children's abilities to function in a simple computer programming environment. Four- and…

Architectures for Quantum Simulation Showing a Quantum Speedup

NASA Astrophysics Data System (ADS)

Bermejo-Vega, Juan; Hangleiter, Dominik; Schwarz, Martin; Raussendorf, Robert; Eisert, Jens

2018-04-01

One of the main aims in the field of quantum simulation is to achieve a quantum speedup, often referred to as "quantum computational supremacy," referring to the experimental realization of a quantum device that computationally outperforms classical computers. In this work, we show that one can devise versatile and feasible schemes of two-dimensional, dynamical, quantum simulators showing such a quantum speedup, building on intermediate problems involving nonadaptive, measurement-based, quantum computation. In each of the schemes, an initial product state is prepared, potentially involving an element of randomness as in disordered models, followed by a short-time evolution under a basic translationally invariant Hamiltonian with simple nearest-neighbor interactions and a mere sampling measurement in a fixed basis. The correctness of the final-state preparation in each scheme is fully efficiently certifiable. We discuss experimental necessities and possible physical architectures, inspired by platforms of cold atoms in optical lattices and a number of others, as well as specific assumptions that enter the complexity-theoretic arguments. This work shows that benchmark settings exhibiting a quantum speedup may require little control, in contrast to universal quantum computing. Thus, our proposal puts a convincing experimental demonstration of a quantum speedup within reach in the near term.

Efficient Determination of Free Energy Landscapes in Multiple Dimensions from Biased Umbrella Sampling Simulations Using Linear Regression.

PubMed

Meng, Yilin; Roux, Benoît

2015-08-11

The weighted histogram analysis method (WHAM) is a standard protocol for postprocessing the information from biased umbrella sampling simulations to construct the potential of mean force with respect to a set of order parameters. By virtue of the WHAM equations, the unbiased density of state is determined by satisfying a self-consistent condition through an iterative procedure. While the method works very effectively when the number of order parameters is small, its computational cost grows rapidly in higher dimension. Here, we present a simple and efficient alternative strategy, which avoids solving the self-consistent WHAM equations iteratively. An efficient multivariate linear regression framework is utilized to link the biased probability densities of individual umbrella windows and yield an unbiased global free energy landscape in the space of order parameters. It is demonstrated with practical examples that free energy landscapes that are comparable in accuracy to WHAM can be generated at a small fraction of the cost.

Efficient Determination of Free Energy Landscapes in Multiple Dimensions from Biased Umbrella Sampling Simulations Using Linear Regression

PubMed Central

2015-01-01

The weighted histogram analysis method (WHAM) is a standard protocol for postprocessing the information from biased umbrella sampling simulations to construct the potential of mean force with respect to a set of order parameters. By virtue of the WHAM equations, the unbiased density of state is determined by satisfying a self-consistent condition through an iterative procedure. While the method works very effectively when the number of order parameters is small, its computational cost grows rapidly in higher dimension. Here, we present a simple and efficient alternative strategy, which avoids solving the self-consistent WHAM equations iteratively. An efficient multivariate linear regression framework is utilized to link the biased probability densities of individual umbrella windows and yield an unbiased global free energy landscape in the space of order parameters. It is demonstrated with practical examples that free energy landscapes that are comparable in accuracy to WHAM can be generated at a small fraction of the cost. PMID:26574437

Design of an efficient music-speech discriminator.

PubMed

Tardón, Lorenzo J; Sammartino, Simone; Barbancho, Isabel

2010-01-01

In this paper, the problem of the design of a simple and efficient music-speech discriminator for large audio data sets in which advanced music playing techniques are taught and voice and music are intrinsically interleaved is addressed. In the process, a number of features used in speech-music discrimination are defined and evaluated over the available data set. Specifically, the data set contains pieces of classical music played with different and unspecified instruments (or even lyrics) and the voice of a teacher (a top music performer) or even the overlapped voice of the translator and other persons. After an initial test of the performance of the features implemented, a selection process is started, which takes into account the type of classifier selected beforehand, to achieve good discrimination performance and computational efficiency, as shown in the experiments. The discrimination application has been defined and tested on a large data set supplied by Fundacion Albeniz, containing a large variety of classical music pieces played with different instrument, which include comments and speeches of famous performers.

A method for simulating a flux-locked DC SQUID

NASA Technical Reports Server (NTRS)

Gutt, G. M.; Kasdin, N. J.; Condron, M. R., II; Muhlfelder, B.; Lockhart, J. M.; Cromar, M. W.

1993-01-01

The authors describe a computationally efficient and accurate method for simulating a dc SQUID's V-Phi (voltage-flux) and I-V characteristics which has proven valuable in evaluating and improving various SQUID readout methods. The simulation of the SQUID is based on fitting of previously acquired data from either a real or a modeled device using the Fourier transform of the V-Phi curve. This method does not predict SQUID behavior, but rather is a way of replicating a known behavior efficiently with portability into various simulation programs such as SPICE. The authors discuss the methods used to simulate the SQUID and the flux-locking control electronics, and present specific examples of this approach. Results include an estimate of the slew rate and linearity of a simple flux-locked loop using a characterized dc SQUID.

Factorization-based texture segmentation

DOE PAGES

Yuan, Jiangye; Wang, Deliang; Cheriyadat, Anil M.

2015-06-17

This study introduces a factorization-based approach that efficiently segments textured images. We use local spectral histograms as features, and construct an M × N feature matrix using M-dimensional feature vectors in an N-pixel image. Based on the observation that each feature can be approximated by a linear combination of several representative features, we factor the feature matrix into two matrices-one consisting of the representative features and the other containing the weights of representative features at each pixel used for linear combination. The factorization method is based on singular value decomposition and nonnegative matrix factorization. The method uses local spectral histogramsmore » to discriminate region appearances in a computationally efficient way and at the same time accurately localizes region boundaries. Finally, the experiments conducted on public segmentation data sets show the promise of this simple yet powerful approach.« less

Thermodynamic efficiency limits of classical and bifacial multi-junction tandem solar cells: An analytical approach

NASA Astrophysics Data System (ADS)

Alam, Muhammad Ashraful; Khan, M. Ryyan

2016-10-01

Bifacial tandem cells promise to reduce three fundamental losses (i.e., above-bandgap, below bandgap, and the uncollected light between panels) inherent in classical single junction photovoltaic (PV) systems. The successive filtering of light through the bandgap cascade and the requirement of current continuity make optimization of tandem cells difficult and accessible only to numerical solution through computer modeling. The challenge is even more complicated for bifacial design. In this paper, we use an elegantly simple analytical approach to show that the essential physics of optimization is intuitively obvious, and deeply insightful results can be obtained with a few lines of algebra. This powerful approach reproduces, as special cases, all of the known results of conventional and bifacial tandem cells and highlights the asymptotic efficiency gain of these technologies.

Technique for Very High Order Nonlinear Simulation and Validation

NASA Technical Reports Server (NTRS)

Dyson, Rodger W.

2001-01-01

Finding the sources of sound in large nonlinear fields via direct simulation currently requires excessive computational cost. This paper describes a simple technique for efficiently solving the multidimensional nonlinear Euler equations that significantly reduces this cost and demonstrates a useful approach for validating high order nonlinear methods. Up to 15th order accuracy in space and time methods were compared and it is shown that an algorithm with a fixed design accuracy approaches its maximal utility and then its usefulness exponentially decays unless higher accuracy is used. It is concluded that at least a 7th order method is required to efficiently propagate a harmonic wave using the nonlinear Euler equations to a distance of 5 wavelengths while maintaining an overall error tolerance that is low enough to capture both the mean flow and the acoustics.

Efficient Resources Provisioning Based on Load Forecasting in Cloud

PubMed Central

Hu, Rongdong; Jiang, Jingfei; Liu, Guangming; Wang, Lixin

2014-01-01

Cloud providers should ensure QoS while maximizing resources utilization. One optimal strategy is to timely allocate resources in a fine-grained mode according to application's actual resources demand. The necessary precondition of this strategy is obtaining future load information in advance. We propose a multi-step-ahead load forecasting method, KSwSVR, based on statistical learning theory which is suitable for the complex and dynamic characteristics of the cloud computing environment. It integrates an improved support vector regression algorithm and Kalman smoother. Public trace data taken from multitypes of resources were used to verify its prediction accuracy, stability, and adaptability, comparing with AR, BPNN, and standard SVR. Subsequently, based on the predicted results, a simple and efficient strategy is proposed for resource provisioning. CPU allocation experiment indicated it can effectively reduce resources consumption while meeting service level agreements requirements. PMID:24701160

A Heuristic Probabilistic Approach to Estimating Size-Dependent Mobility of Nonuniform Sediment

NASA Astrophysics Data System (ADS)

Woldegiorgis, B. T.; Wu, F. C.; van Griensven, A.; Bauwens, W.

2017-12-01

Simulating the mechanism of bed sediment mobility is essential for modelling sediment dynamics. Despite the fact that many studies are carried out on this subject, they use complex mathematical formulations that are computationally expensive, and are often not easy for implementation. In order to present a simple and computationally efficient complement to detailed sediment mobility models, we developed a heuristic probabilistic approach to estimating the size-dependent mobilities of nonuniform sediment based on the pre- and post-entrainment particle size distributions (PSDs), assuming that the PSDs are lognormally distributed. The approach fits a lognormal probability density function (PDF) to the pre-entrainment PSD of bed sediment and uses the threshold particle size of incipient motion and the concept of sediment mixture to estimate the PSDs of the entrained sediment and post-entrainment bed sediment. The new approach is simple in physical sense and significantly reduces the complexity and computation time and resource required by detailed sediment mobility models. It is calibrated and validated with laboratory and field data by comparing to the size-dependent mobilities predicted with the existing empirical lognormal cumulative distribution function (CDF) approach. The novel features of the current approach are: (1) separating the entrained and non-entrained sediments by a threshold particle size, which is a modified critical particle size of incipient motion by accounting for the mixed-size effects, and (2) using the mixture-based pre- and post-entrainment PSDs to provide a continuous estimate of the size-dependent sediment mobility.

Carbohydrates as efficient catalysts for the hydration of α-amino nitriles.

PubMed

Chitale, Sampada; Derasp, Joshua S; Hussain, Bashir; Tanveer, Kashif; Beauchemin, André M

2016-11-01

Directed hydration of α-amino nitriles was achieved under mild conditions using simple carbohydrates as catalysts exploiting temporary intramolecularity. A broadly applicable procedure using both formaldehyde and NaOH as catalysts efficiently hydrated a variety of primary and secondary susbtrates, and allowed the hydration of enantiopure substrates to proceed without racemization. This work also provides a rare comparison of the catalytic activity of carbohydrates, and shows that the simple aldehydes at the basis of chemical evolution are efficient organocatalysts mimicking the function of hydratase enzymes. Optimal catalytic efficiency was observed with destabilized aldehydes, and with difficult substrates only simple carbohydrates such as formaldehyde and glycolaldehyde proved reliable.

Simple models for the simulation of submarine melt for a Greenland glacial system model

NASA Astrophysics Data System (ADS)

Beckmann, Johanna; Perrette, Mahé; Ganopolski, Andrey

2018-01-01

Two hundred marine-terminating Greenland outlet glaciers deliver more than half of the annually accumulated ice into the ocean and have played an important role in the Greenland ice sheet mass loss observed since the mid-1990s. Submarine melt may play a crucial role in the mass balance and position of the grounding line of these outlet glaciers. As the ocean warms, it is expected that submarine melt will increase, potentially driving outlet glaciers retreat and contributing to sea level rise. Projections of the future contribution of outlet glaciers to sea level rise are hampered by the necessity to use models with extremely high resolution of the order of a few hundred meters. That requirement in not only demanded when modeling outlet glaciers as a stand alone model but also when coupling them with high-resolution 3-D ocean models. In addition, fjord bathymetry data are mostly missing or inaccurate (errors of several hundreds of meters), which questions the benefit of using computationally expensive 3-D models for future predictions. Here we propose an alternative approach built on the use of a computationally efficient simple model of submarine melt based on turbulent plume theory. We show that such a simple model is in reasonable agreement with several available modeling studies. We performed a suite of experiments to analyze sensitivity of these simple models to model parameters and climate characteristics. We found that the computationally cheap plume model demonstrates qualitatively similar behavior as 3-D general circulation models. To match results of the 3-D models in a quantitative manner, a scaling factor of the order of 1 is needed for the plume models. We applied this approach to model submarine melt for six representative Greenland glaciers and found that the application of a line plume can produce submarine melt compatible with observational data. Our results show that the line plume model is more appropriate than the cone plume model for simulating the average submarine melting of real glaciers in Greenland.

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

NASA Astrophysics Data System (ADS)

Jin, Yulin; Lu, Kuan; Hou, Lei; Chen, Yushu

2017-12-01

The proper orthogonal decomposition (POD) method is a main and efficient tool for order reduction of high-dimensional complex systems in many research fields. However, the robustness problem of this method is always unsolved, although there are some modified POD methods which were proposed to solve this problem. In this paper, a new adaptive POD method called the interpolation Grassmann manifold (IGM) method is proposed to address the weakness of local property of the interpolation tangent-space of Grassmann manifold (ITGM) method in a wider parametric region. This method is demonstrated here by a nonlinear rotor system of 33-degrees of freedom (DOFs) with a pair of liquid-film bearings and a pedestal looseness fault. The motion region of the rotor system is divided into two parts: simple motion region and complex motion region. The adaptive POD method is compared with the ITGM method for the large and small spans of parameter in the two parametric regions to present the advantage of this method and disadvantage of the ITGM method. The comparisons of the responses are applied to verify the accuracy and robustness of the adaptive POD method, as well as the computational efficiency is also analyzed. As a result, the new adaptive POD method has a strong robustness and high computational efficiency and accuracy in a wide scope of parameter.

Optical Eigenvector.

DTIC Science & Technology

1984-10-01

it necessary and identify by blckci -. mbrr, ’At tile bneginninp, of this contract , bot], -,-j- .lc the rest of the optical community imagined * that...simple analog optical computer,, could produce satisfactory solutions to elgenproblems. Earl’ - in this contract we improved optical computing... contract both we and the rest of the optical community imagined that simple analog optical computers could produce . satisfactory solutions to

JobCenter: an open source, cross-platform, and distributed job queue management system optimized for scalability and versatility.

PubMed

Jaschob, Daniel; Riffle, Michael

2012-07-30

Laboratories engaged in computational biology or bioinformatics frequently need to run lengthy, multistep, and user-driven computational jobs. Each job can tie up a computer for a few minutes to several days, and many laboratories lack the expertise or resources to build and maintain a dedicated computer cluster. JobCenter is a client-server application and framework for job management and distributed job execution. The client and server components are both written in Java and are cross-platform and relatively easy to install. All communication with the server is client-driven, which allows worker nodes to run anywhere (even behind external firewalls or "in the cloud") and provides inherent load balancing. Adding a worker node to the worker pool is as simple as dropping the JobCenter client files onto any computer and performing basic configuration, which provides tremendous ease-of-use, flexibility, and limitless horizontal scalability. Each worker installation may be independently configured, including the types of jobs it is able to run. Executed jobs may be written in any language and may include multistep workflows. JobCenter is a versatile and scalable distributed job management system that allows laboratories to very efficiently distribute all computational work among available resources. JobCenter is freely available at http://code.google.com/p/jobcenter/.

Application of computational fluid dynamics (CFD) simulation in a vertical axis wind turbine (VAWT) system

NASA Astrophysics Data System (ADS)

Kao, Jui-Hsiang; Tseng, Po-Yuan

2018-01-01

The objective of this paper is to describe the application of CFD (Computational fluid dynamics) technology in the matching of turbine blades and generator to increase the efficiency of a vertical axis wind turbine (VAWT). A VAWT is treated as the study case here. The SST (Shear-Stress Transport) k-ω turbulence model with SIMPLE algorithm method in transient state is applied to solve the T (torque)-N (r/min) curves of the turbine blades at different wind speed. The T-N curves of the generator at different CV (constant voltage) model are measured. Thus, the T-N curves of the turbine blades at different wind speed can be matched by the T-N curves of the generator at different CV model to find the optimal CV model. As the optimal CV mode is selected, the characteristics of the operating points, such as tip speed ratio, revolutions per minute, blade torque, and efficiency, can be identified. The results show that, if the two systems are matched well, the final output power at a high wind speed of 9-10 m/s will be increased by 15%.

Multicategory Composite Least Squares Classifiers

PubMed Central

Park, Seo Young; Liu, Yufeng; Liu, Dacheng; Scholl, Paul

2010-01-01

Classification is a very useful statistical tool for information extraction. In particular, multicategory classification is commonly seen in various applications. Although binary classification problems are heavily studied, extensions to the multicategory case are much less so. In view of the increased complexity and volume of modern statistical problems, it is desirable to have multicategory classifiers that are able to handle problems with high dimensions and with a large number of classes. Moreover, it is necessary to have sound theoretical properties for the multicategory classifiers. In the literature, there exist several different versions of simultaneous multicategory Support Vector Machines (SVMs). However, the computation of the SVM can be difficult for large scale problems, especially for problems with large number of classes. Furthermore, the SVM cannot produce class probability estimation directly. In this article, we propose a novel efficient multicategory composite least squares classifier (CLS classifier), which utilizes a new composite squared loss function. The proposed CLS classifier has several important merits: efficient computation for problems with large number of classes, asymptotic consistency, ability to handle high dimensional data, and simple conditional class probability estimation. Our simulated and real examples demonstrate competitive performance of the proposed approach. PMID:21218128

Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics

DOE PAGES

Carlberg, Kevin; Tuminaro, Ray; Boggs, Paul

2015-03-11

Our work proposes a model-reduction methodology that preserves Lagrangian structure and achieves computational efficiency in the presence of high-order nonlinearities and arbitrary parameter dependence. As such, the resulting reduced-order model retains key properties such as energy conservation and symplectic time-evolution maps. We focus on parameterized simple mechanical systems subjected to Rayleigh damping and external forces, and consider an application to nonlinear structural dynamics. To preserve structure, the method first approximates the system's “Lagrangian ingredients''---the Riemannian metric, the potential-energy function, the dissipation function, and the external force---and subsequently derives reduced-order equations of motion by applying the (forced) Euler--Lagrange equation with thesemore » quantities. Moreover, from the algebraic perspective, key contributions include two efficient techniques for approximating parameterized reduced matrices while preserving symmetry and positive definiteness: matrix gappy proper orthogonal decomposition and reduced-basis sparsification. Our results for a parameterized truss-structure problem demonstrate the practical importance of preserving Lagrangian structure and illustrate the proposed method's merits: it reduces computation time while maintaining high accuracy and stability, in contrast to existing nonlinear model-reduction techniques that do not preserve structure.« less

Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics

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

Carlberg, Kevin; Tuminaro, Ray; Boggs, Paul

Our work proposes a model-reduction methodology that preserves Lagrangian structure and achieves computational efficiency in the presence of high-order nonlinearities and arbitrary parameter dependence. As such, the resulting reduced-order model retains key properties such as energy conservation and symplectic time-evolution maps. We focus on parameterized simple mechanical systems subjected to Rayleigh damping and external forces, and consider an application to nonlinear structural dynamics. To preserve structure, the method first approximates the system's “Lagrangian ingredients''---the Riemannian metric, the potential-energy function, the dissipation function, and the external force---and subsequently derives reduced-order equations of motion by applying the (forced) Euler--Lagrange equation with thesemore » quantities. Moreover, from the algebraic perspective, key contributions include two efficient techniques for approximating parameterized reduced matrices while preserving symmetry and positive definiteness: matrix gappy proper orthogonal decomposition and reduced-basis sparsification. Our results for a parameterized truss-structure problem demonstrate the practical importance of preserving Lagrangian structure and illustrate the proposed method's merits: it reduces computation time while maintaining high accuracy and stability, in contrast to existing nonlinear model-reduction techniques that do not preserve structure.« less

A Simple Algebraic Grid Adaptation Scheme with Applications to Two- and Three-dimensional Flow Problems

NASA Technical Reports Server (NTRS)

Hsu, Andrew T.; Lytle, John K.

1989-01-01

An algebraic adaptive grid scheme based on the concept of arc equidistribution is presented. The scheme locally adjusts the grid density based on gradients of selected flow variables from either finite difference or finite volume calculations. A user-prescribed grid stretching can be specified such that control of the grid spacing can be maintained in areas of known flowfield behavior. For example, the grid can be clustered near a wall for boundary layer resolution and made coarse near the outer boundary of an external flow. A grid smoothing technique is incorporated into the adaptive grid routine, which is found to be more robust and efficient than the weight function filtering technique employed by other researchers. Since the present algebraic scheme requires no iteration or solution of differential equations, the computer time needed for grid adaptation is trivial, making the scheme useful for three-dimensional flow problems. Applications to two- and three-dimensional flow problems show that a considerable improvement in flowfield resolution can be achieved by using the proposed adaptive grid scheme. Although the scheme was developed with steady flow in mind, it is a good candidate for unsteady flow computations because of its efficiency.

Computational path planner for product assembly in complex environments

NASA Astrophysics Data System (ADS)

Shang, Wei; Liu, Jianhua; Ning, Ruxin; Liu, Mi

2013-03-01

Assembly path planning is a crucial problem in assembly related design and manufacturing processes. Sampling based motion planning algorithms are used for computational assembly path planning. However, the performance of such algorithms may degrade much in environments with complex product structure, narrow passages or other challenging scenarios. A computational path planner for automatic assembly path planning in complex 3D environments is presented. The global planning process is divided into three phases based on the environment and specific algorithms are proposed and utilized in each phase to solve the challenging issues. A novel ray test based stochastic collision detection method is proposed to evaluate the intersection between two polyhedral objects. This method avoids fake collisions in conventional methods and degrades the geometric constraint when a part has to be removed with surface contact with other parts. A refined history based rapidly-exploring random tree (RRT) algorithm which bias the growth of the tree based on its planning history is proposed and employed in the planning phase where the path is simple but the space is highly constrained. A novel adaptive RRT algorithm is developed for the path planning problem with challenging scenarios and uncertain environment. With extending values assigned on each tree node and extending schemes applied, the tree can adapts its growth to explore complex environments more efficiently. Experiments on the key algorithms are carried out and comparisons are made between the conventional path planning algorithms and the presented ones. The comparing results show that based on the proposed algorithms, the path planner can compute assembly path in challenging complex environments more efficiently and with higher success. This research provides the references to the study of computational assembly path planning under complex environments.

Evaluating the Energetic Driving Force for Cocrystal Formation

PubMed Central

2017-01-01

We present a periodic density functional theory study of the stability of 350 organic cocrystals relative to their pure single-component structures, the largest study of cocrystals yet performed with high-level computational methods. Our calculations demonstrate that cocrystals are on average 8 kJ mol–1 more stable than their constituent single-component structures and are very rarely (<5% of cases) less stable; cocrystallization is almost always a thermodynamically favorable process. We consider the variation in stability between different categories of systems—hydrogen-bonded, halogen-bonded, and weakly bound cocrystals—finding that, contrary to chemical intuition, the presence of hydrogen or halogen bond interactions is not necessarily a good predictor of stability. Finally, we investigate the correlation of the relative stability with simple chemical descriptors: changes in packing efficiency and hydrogen bond strength. We find some broad qualitative agreement with chemical intuition—more densely packed cocrystals with stronger hydrogen bonding tend to be more stable—but the relationship is weak, suggesting that such simple descriptors do not capture the complex balance of interactions driving cocrystallization. Our conclusions suggest that while cocrystallization is often a thermodynamically favorable process, it remains difficult to formulate general rules to guide synthesis, highlighting the continued importance of high-level computation in predicting and rationalizing such systems. PMID:29445316

A Simple but Powerful Heuristic Method for Accelerating k-Means Clustering of Large-Scale Data in Life Science.

PubMed

Ichikawa, Kazuki; Morishita, Shinichi

2014-01-01

K-means clustering has been widely used to gain insight into biological systems from large-scale life science data. To quantify the similarities among biological data sets, Pearson correlation distance and standardized Euclidean distance are used most frequently; however, optimization methods have been largely unexplored. These two distance measurements are equivalent in the sense that they yield the same k-means clustering result for identical sets of k initial centroids. Thus, an efficient algorithm used for one is applicable to the other. Several optimization methods are available for the Euclidean distance and can be used for processing the standardized Euclidean distance; however, they are not customized for this context. We instead approached the problem by studying the properties of the Pearson correlation distance, and we invented a simple but powerful heuristic method for markedly pruning unnecessary computation while retaining the final solution. Tests using real biological data sets with 50-60K vectors of dimensions 10-2001 (~400 MB in size) demonstrated marked reduction in computation time for k = 10-500 in comparison with other state-of-the-art pruning methods such as Elkan's and Hamerly's algorithms. The BoostKCP software is available at http://mlab.cb.k.u-tokyo.ac.jp/~ichikawa/boostKCP/.

Large-scale computation of incompressible viscous flow by least-squares finite element method

NASA Technical Reports Server (NTRS)

Jiang, Bo-Nan; Lin, T. L.; Povinelli, Louis A.

1993-01-01

The least-squares finite element method (LSFEM) based on the velocity-pressure-vorticity formulation is applied to large-scale/three-dimensional steady incompressible Navier-Stokes problems. This method can accommodate equal-order interpolations and results in symmetric, positive definite algebraic system which can be solved effectively by simple iterative methods. The first-order velocity-Bernoulli function-vorticity formulation for incompressible viscous flows is also tested. For three-dimensional cases, an additional compatibility equation, i.e., the divergence of the vorticity vector should be zero, is included to make the first-order system elliptic. The simple substitution of the Newton's method is employed to linearize the partial differential equations, the LSFEM is used to obtain discretized equations, and the system of algebraic equations is solved using the Jacobi preconditioned conjugate gradient method which avoids formation of either element or global matrices (matrix-free) to achieve high efficiency. To show the validity of this scheme for large-scale computation, we give numerical results for 2D driven cavity problem at Re = 10000 with 408 x 400 bilinear elements. The flow in a 3D cavity is calculated at Re = 100, 400, and 1,000 with 50 x 50 x 50 trilinear elements. The Taylor-Goertler-like vortices are observed for Re = 1,000.

From Lévy to Brownian: a computational model based on biological fluctuation.

PubMed

Nurzaman, Surya G; Matsumoto, Yoshio; Nakamura, Yutaka; Shirai, Kazumichi; Koizumi, Satoshi; Ishiguro, Hiroshi

2011-02-03

Theoretical studies predict that Lévy walks maximizes the chance of encountering randomly distributed targets with a low density, but Brownian walks is favorable inside a patch of targets with high density. Recently, experimental data reports that some animals indeed show a Lévy and Brownian walk movement patterns when forage for foods in areas with low and high density. This paper presents a simple, Gaussian-noise utilizing computational model that can realize such behavior. We extend Lévy walks model of one of the simplest creature, Escherichia coli, based on biological fluctuation framework. We build a simulation of a simple, generic animal to observe whether Lévy or Brownian walks will be performed properly depends on the target density, and investigate the emergent behavior in a commonly faced patchy environment where the density alternates. Based on the model, animal behavior of choosing Lévy or Brownian walk movement patterns based on the target density is able to be generated, without changing the essence of the stochastic property in Escherichia coli physiological mechanism as explained by related researches. The emergent behavior and its benefits in a patchy environment are also discussed. The model provides a framework for further investigation on the role of internal noise in realizing adaptive and efficient foraging behavior.

Evaluating the Energetic Driving Force for Cocrystal Formation.

PubMed

Taylor, Christopher R; Day, Graeme M

2018-02-07

We present a periodic density functional theory study of the stability of 350 organic cocrystals relative to their pure single-component structures, the largest study of cocrystals yet performed with high-level computational methods. Our calculations demonstrate that cocrystals are on average 8 kJ mol -1 more stable than their constituent single-component structures and are very rarely (<5% of cases) less stable; cocrystallization is almost always a thermodynamically favorable process. We consider the variation in stability between different categories of systems-hydrogen-bonded, halogen-bonded, and weakly bound cocrystals-finding that, contrary to chemical intuition, the presence of hydrogen or halogen bond interactions is not necessarily a good predictor of stability. Finally, we investigate the correlation of the relative stability with simple chemical descriptors: changes in packing efficiency and hydrogen bond strength. We find some broad qualitative agreement with chemical intuition-more densely packed cocrystals with stronger hydrogen bonding tend to be more stable-but the relationship is weak, suggesting that such simple descriptors do not capture the complex balance of interactions driving cocrystallization. Our conclusions suggest that while cocrystallization is often a thermodynamically favorable process, it remains difficult to formulate general rules to guide synthesis, highlighting the continued importance of high-level computation in predicting and rationalizing such systems.

On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models

NASA Astrophysics Data System (ADS)

Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.

2017-12-01

Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.

Maximum Entropy Discrimination Poisson Regression for Software Reliability Modeling.

PubMed

Chatzis, Sotirios P; Andreou, Andreas S

2015-11-01

Reliably predicting software defects is one of the most significant tasks in software engineering. Two of the major components of modern software reliability modeling approaches are: 1) extraction of salient features for software system representation, based on appropriately designed software metrics and 2) development of intricate regression models for count data, to allow effective software reliability data modeling and prediction. Surprisingly, research in the latter frontier of count data regression modeling has been rather limited. More specifically, a lack of simple and efficient algorithms for posterior computation has made the Bayesian approaches appear unattractive, and thus underdeveloped in the context of software reliability modeling. In this paper, we try to address these issues by introducing a novel Bayesian regression model for count data, based on the concept of max-margin data modeling, effected in the context of a fully Bayesian model treatment with simple and efficient posterior distribution updates. Our novel approach yields a more discriminative learning technique, making more effective use of our training data during model inference. In addition, it allows of better handling uncertainty in the modeled data, which can be a significant problem when the training data are limited. We derive elegant inference algorithms for our model under the mean-field paradigm and exhibit its effectiveness using the publicly available benchmark data sets.

Sail Plan Configuration Optimization for a Modern Clipper Ship

NASA Astrophysics Data System (ADS)

Gerritsen, Margot; Doyle, Tyler; Iaccarino, Gianluca; Moin, Parviz

2002-11-01

We investigate the use of gradient-based and evolutionary algorithms for sail shape optimization. We present preliminary results for the optimization of sheeting angles for the rig of the future three-masted clipper yacht Maltese Falcon. This yacht will be equipped with square-rigged masts made up of yards of circular arc cross sections. This design is especially attractive for megayachts because it provides a large sail area while maintaining aerodynamic and structural efficiency. The rig remains almost rigid in a large range of wind conditions and therefore a simple geometrical model can be constructed without accounting for the true flying shape. The sheeting angle optimization studies are performed using both gradient-based cost function minimization and evolutionary algorithms. The fluid flow is modeled by the Reynolds-averaged Navier-Stokes equations with the Spallart-Allmaras turbulence model. Unstructured non-conforming grids are used to increase robustness and computational efficiency. The optimization process is automated by integrating the system components (geometry construction, grid generation, flow solver, force calculator, optimization). We compare the optimization results to those done previously by user-controlled parametric studies using simple cost functions and user intuition. We also investigate the effectiveness of various cost functions in the optimization (driving force maximization, ratio of driving force to heeling force maximization).

Development of Computer-Based Experiment Set on Simple Harmonic Motion of Mass on Springs

ERIC Educational Resources Information Center

Musik, Panjit

2017-01-01

The development of computer-based experiment set has become necessary in teaching physics in schools so that students can learn from their real experiences. The purpose of this study is to create and to develop the computer-based experiment set on simple harmonic motion of mass on springs for teaching and learning physics. The average period of…

The 'Biologically-Inspired Computing' Column

NASA Technical Reports Server (NTRS)

Hinchey, Mike

2006-01-01

The field of Biology changed dramatically in 1953, with the determination by Francis Crick and James Dewey Watson of the double helix structure of DNA. This discovery changed Biology for ever, allowing the sequencing of the human genome, and the emergence of a "new Biology" focused on DNA, genes, proteins, data, and search. Computational Biology and Bioinformatics heavily rely on computing to facilitate research into life and development. Simultaneously, an understanding of the biology of living organisms indicates a parallel with computing systems: molecules in living cells interact, grow, and transform according to the "program" dictated by DNA. Moreover, paradigms of Computing are emerging based on modelling and developing computer-based systems exploiting ideas that are observed in nature. This includes building into computer systems self-management and self-governance mechanisms that are inspired by the human body's autonomic nervous system, modelling evolutionary systems analogous to colonies of ants or other insects, and developing highly-efficient and highly-complex distributed systems from large numbers of (often quite simple) largely homogeneous components to reflect the behaviour of flocks of birds, swarms of bees, herds of animals, or schools of fish. This new field of "Biologically-Inspired Computing", often known in other incarnations by other names, such as: Autonomic Computing, Pervasive Computing, Organic Computing, Biomimetics, and Artificial Life, amongst others, is poised at the intersection of Computer Science, Engineering, Mathematics, and the Life Sciences. Successes have been reported in the fields of drug discovery, data communications, computer animation, control and command, exploration systems for space, undersea, and harsh environments, to name but a few, and augur much promise for future progress.

Localized-atlas-based segmentation of breast MRI in a decision-making framework.

PubMed

Fooladivanda, Aida; Shokouhi, Shahriar B; Ahmadinejad, Nasrin

2017-03-01

Breast-region segmentation is an important step for density estimation and Computer-Aided Diagnosis (CAD) systems in Magnetic Resonance Imaging (MRI). Detection of breast-chest wall boundary is often a difficult task due to similarity between gray-level values of fibroglandular tissue and pectoral muscle. This paper proposes a robust breast-region segmentation method which is applicable for both complex cases with fibroglandular tissue connected to the pectoral muscle, and simple cases with high contrast boundaries. We present a decision-making framework based on geometric features and support vector machine (SVM) to classify breasts in two main groups, complex and simple. For complex cases, breast segmentation is done using a combination of intensity-based and atlas-based techniques; however, only intensity-based operation is employed for simple cases. A novel atlas-based method, that is called localized-atlas, accomplishes the processes of atlas construction and registration based on the region of interest (ROI). Atlas-based segmentation is performed by relying on the chest wall template. Our approach is validated using a dataset of 210 cases. Based on similarity between automatic and manual segmentation results, the proposed method achieves Dice similarity coefficient, Jaccard coefficient, total overlap, false negative, and false positive values of 96.3, 92.9, 97.4, 2.61 and 4.77%, respectively. The localization error of the breast-chest wall boundary is 1.97 mm, in terms of averaged deviation distance. The achieved results prove that the suggested framework performs the breast segmentation with negligible errors and efficient computational time for different breasts from the viewpoints of size, shape, and density pattern.

Neuromodulation and Synaptic Plasticity for the Control of Fast Periodic Movement: Energy Efficiency in Coupled Compliant Joints via PCA.

PubMed

Stratmann, Philipp; Lakatos, Dominic; Albu-Schäffer, Alin

2016-01-01

There are multiple indications that the nervous system of animals tunes muscle output to exploit natural dynamics of the elastic locomotor system and the environment. This is an advantageous strategy especially in fast periodic movements, since the elastic elements store energy and increase energy efficiency and movement speed. Experimental evidence suggests that coordination among joints involves proprioceptive input and neuromodulatory influence originating in the brain stem. However, the neural strategies underlying the coordination of fast periodic movements remain poorly understood. Based on robotics control theory, we suggest that the nervous system implements a mechanism to accomplish coordination between joints by a linear coordinate transformation from the multi-dimensional space representing proprioceptive input at the joint level into a one-dimensional controller space. In this one-dimensional subspace, the movements of a whole limb can be driven by a single oscillating unit as simple as a reflex interneuron. The output of the oscillating unit is transformed back to joint space via the same transformation. The transformation weights correspond to the dominant principal component of the movement. In this study, we propose a biologically plausible neural network to exemplify that the central nervous system (CNS) may encode our controller design. Using theoretical considerations and computer simulations, we demonstrate that spike-timing-dependent plasticity (STDP) for the input mapping and serotonergic neuromodulation for the output mapping can extract the dominant principal component of sensory signals. Our simulations show that our network can reliably control mechanical systems of different complexity and increase the energy efficiency of ongoing cyclic movements. The proposed network is simple and consistent with previous biologic experiments. Thus, our controller could serve as a candidate to describe the neural control of fast, energy-efficient, periodic movements involving multiple coupled joints.

Neuromodulation and Synaptic Plasticity for the Control of Fast Periodic Movement: Energy Efficiency in Coupled Compliant Joints via PCA

PubMed Central

Stratmann, Philipp; Lakatos, Dominic; Albu-Schäffer, Alin

2016-01-01

There are multiple indications that the nervous system of animals tunes muscle output to exploit natural dynamics of the elastic locomotor system and the environment. This is an advantageous strategy especially in fast periodic movements, since the elastic elements store energy and increase energy efficiency and movement speed. Experimental evidence suggests that coordination among joints involves proprioceptive input and neuromodulatory influence originating in the brain stem. However, the neural strategies underlying the coordination of fast periodic movements remain poorly understood. Based on robotics control theory, we suggest that the nervous system implements a mechanism to accomplish coordination between joints by a linear coordinate transformation from the multi-dimensional space representing proprioceptive input at the joint level into a one-dimensional controller space. In this one-dimensional subspace, the movements of a whole limb can be driven by a single oscillating unit as simple as a reflex interneuron. The output of the oscillating unit is transformed back to joint space via the same transformation. The transformation weights correspond to the dominant principal component of the movement. In this study, we propose a biologically plausible neural network to exemplify that the central nervous system (CNS) may encode our controller design. Using theoretical considerations and computer simulations, we demonstrate that spike-timing-dependent plasticity (STDP) for the input mapping and serotonergic neuromodulation for the output mapping can extract the dominant principal component of sensory signals. Our simulations show that our network can reliably control mechanical systems of different complexity and increase the energy efficiency of ongoing cyclic movements. The proposed network is simple and consistent with previous biologic experiments. Thus, our controller could serve as a candidate to describe the neural control of fast, energy-efficient, periodic movements involving multiple coupled joints. PMID:27014051

Sequential visibility-graph motifs

NASA Astrophysics Data System (ADS)

Iacovacci, Jacopo; Lacasa, Lucas

2016-04-01

Visibility algorithms transform time series into graphs and encode dynamical information in their topology, paving the way for graph-theoretical time series analysis as well as building a bridge between nonlinear dynamics and network science. In this work we introduce and study the concept of sequential visibility-graph motifs, smaller substructures of n consecutive nodes that appear with characteristic frequencies. We develop a theory to compute in an exact way the motif profiles associated with general classes of deterministic and stochastic dynamics. We find that this simple property is indeed a highly informative and computationally efficient feature capable of distinguishing among different dynamics and robust against noise contamination. We finally confirm that it can be used in practice to perform unsupervised learning, by extracting motif profiles from experimental heart-rate series and being able, accordingly, to disentangle meditative from other relaxation states. Applications of this general theory include the automatic classification and description of physical, biological, and financial time series.

Statistical Emulation of Climate Model Projections Based on Precomputed GCM Runs*

DOE PAGES

Castruccio, Stefano; McInerney, David J.; Stein, Michael L.; ...

2014-02-24

The authors describe a new approach for emulating the output of a fully coupled climate model under arbitrary forcing scenarios that is based on a small set of precomputed runs from the model. Temperature and precipitation are expressed as simple functions of the past trajectory of atmospheric CO 2 concentrations, and a statistical model is fit using a limited set of training runs. The approach is demonstrated to be a useful and computationally efficient alternative to pattern scaling and captures the nonlinear evolution of spatial patterns of climate anomalies inherent in transient climates. The approach does as well as patternmore » scaling in all circumstances and substantially better in many; it is not computationally demanding; and, once the statistical model is fit, it produces emulated climate output effectively instantaneously. In conclusion, it may therefore find wide application in climate impacts assessments and other policy analyses requiring rapid climate projections.« less

Efficient image compression algorithm for computer-animated images

NASA Astrophysics Data System (ADS)

Yfantis, Evangelos A.; Au, Matthew Y.; Miel, G.

1992-10-01

An image compression algorithm is described. The algorithm is an extension of the run-length image compression algorithm and its implementation is relatively easy. This algorithm was implemented and compared with other existing popular compression algorithms and with the Lempel-Ziv (LZ) coding. The Lempel-Ziv algorithm is available as a utility in the UNIX operating system and is also referred to as the UNIX uncompress. Sometimes our algorithm is best in terms of saving memory space, and sometimes one of the competing algorithms is best. The algorithm is lossless, and the intent is for the algorithm to be used in computer graphics animated images. Comparisons made with the LZ algorithm indicate that the decompression time using our algorithm is faster than that using the LZ algorithm. Once the data are in memory, a relatively simple and fast transformation is applied to uncompress the file.

Modeling a surface-mounted Lamb wave emission-reception system: applications to structural health monitoring.

PubMed

Moulin, Emmanuel; Grondel, Sébastien; Assaad, Jamal; Duquenne, Laurent

2008-12-01

The work described in this paper is intended to present a simple and efficient way of modeling a full Lamb wave emission and reception system. The emitter behavior and the Lamb wave generation are predicted using a two-dimensional (2D) hybrid finite element-normal mode expansion model. Then the receiver electrical response is obtained from a finite element computation with prescribed displacements. A numerical correction is applied to the 2D results in order to account for the in-plane radiation divergence caused by the finite length of the emitter. The advantage of this modular approach is that realistic configurations can be simulated without performing cumbersome modeling and time-consuming computations. It also provides insight into the physical interpretation of the results. A good agreement is obtained between predicted and measured signals. The range of application of the method is discussed.

An efficient method for facial component detection in thermal images

NASA Astrophysics Data System (ADS)

Paul, Michael; Blanik, Nikolai; Blazek, Vladimir; Leonhardt, Steffen

2015-04-01

A method to detect certain regions in thermal images of human faces is presented. In this approach, the following steps are necessary to locate the periorbital and the nose regions: First, the face is segmented from the background by thresholding and morphological filtering. Subsequently, a search region within the face, around its center of mass, is evaluated. Automatically computed temperature thresholds are used per subject and image or image sequence to generate binary images, in which the periorbital regions are located by integral projections. Then, the located positions are used to approximate the nose position. It is possible to track features in the located regions. Therefore, these regions are interesting for different applications like human-machine interaction, biometrics and biomedical imaging. The method is easy to implement and does not rely on any training images or templates. Furthermore, the approach saves processing resources due to simple computations and restricted search regions.

Sparse PDF Volumes for Consistent Multi-Resolution Volume Rendering.

PubMed

Sicat, Ronell; Krüger, Jens; Möller, Torsten; Hadwiger, Markus

2014-12-01

This paper presents a new multi-resolution volume representation called sparse pdf volumes, which enables consistent multi-resolution volume rendering based on probability density functions (pdfs) of voxel neighborhoods. These pdfs are defined in the 4D domain jointly comprising the 3D volume and its 1D intensity range. Crucially, the computation of sparse pdf volumes exploits data coherence in 4D, resulting in a sparse representation with surprisingly low storage requirements. At run time, we dynamically apply transfer functions to the pdfs using simple and fast convolutions. Whereas standard low-pass filtering and down-sampling incur visible differences between resolution levels, the use of pdfs facilitates consistent results independent of the resolution level used. We describe the efficient out-of-core computation of large-scale sparse pdf volumes, using a novel iterative simplification procedure of a mixture of 4D Gaussians. Finally, our data structure is optimized to facilitate interactive multi-resolution volume rendering on GPUs.

A comparative study of Conroy and Monte Carlo methods applied to multiple quadratures and multiple scattering

NASA Technical Reports Server (NTRS)

Deepak, A.; Fluellen, A.

1978-01-01

An efficient numerical method of multiple quadratures, the Conroy method, is applied to the problem of computing multiple scattering contributions in the radiative transfer through realistic planetary atmospheres. A brief error analysis of the method is given and comparisons are drawn with the more familiar Monte Carlo method. Both methods are stochastic problem-solving models of a physical or mathematical process and utilize the sampling scheme for points distributed over a definite region. In the Monte Carlo scheme the sample points are distributed randomly over the integration region. In the Conroy method, the sample points are distributed systematically, such that the point distribution forms a unique, closed, symmetrical pattern which effectively fills the region of the multidimensional integration. The methods are illustrated by two simple examples: one, of multidimensional integration involving two independent variables, and the other, of computing the second order scattering contribution to the sky radiance.

Solute segregation kinetics and dislocation depinning in a binary alloy

NASA Astrophysics Data System (ADS)

Dontsova, E.; Rottler, J.; Sinclair, C. W.

2015-06-01

Static strain aging, a phenomenon caused by diffusion of solute atoms to dislocations, is an important contributor to the strength of substitutional alloys. Accurate modeling of this complex process requires both atomic spatial resolution and diffusional time scales, which is very challenging to achieve with commonly used atomistic computational methods. In this paper, we use the recently developed "diffusive molecular dynamics" (DMD) method that is capable of describing the kinetics of the solute segregation process at the atomic level while operating on diffusive time scales in a computationally efficient way. We study static strain aging in the Al-Mg system and calculate the depinning shear stress between edge and screw dislocations and their solute atmospheres formed for various waiting times with different solute content and for a range of temperatures. A simple phenomenological model is also proposed that describes the observed behavior of the critical shear stress as a function of segregation level.

Dislocation dynamics in non-convex domains using finite elements with embedded discontinuities

NASA Astrophysics Data System (ADS)

Romero, Ignacio; Segurado, Javier; LLorca, Javier

2008-04-01

The standard strategy developed by Van der Giessen and Needleman (1995 Modelling Simul. Mater. Sci. Eng. 3 689) to simulate dislocation dynamics in two-dimensional finite domains was modified to account for the effect of dislocations leaving the crystal through a free surface in the case of arbitrary non-convex domains. The new approach incorporates the displacement jumps across the slip segments of the dislocations that have exited the crystal within the finite element analysis carried out to compute the image stresses on the dislocations due to the finite boundaries. This is done in a simple computationally efficient way by embedding the discontinuities in the finite element solution, a strategy often used in the numerical simulation of crack propagation in solids. Two academic examples are presented to validate and demonstrate the extended model and its implementation within a finite element program is detailed in the appendix.

Barriers to Achieving Textbook Multigrid Efficiency (TME) in CFD

NASA Technical Reports Server (NTRS)

Brandt, Achi

1998-01-01

As a guide to attaining this optimal performance for general CFD problems, the table below lists every foreseen kind of computational difficulty for achieving that goal, together with the possible ways for resolving that difficulty, their current state of development, and references. Included in the table are staggered and nonstaggered, conservative and nonconservative discretizations of viscous and inviscid, incompressible and compressible flows at various Mach numbers, as well as a simple (algebraic) turbulence model and comments on chemically reacting flows. The listing of associated computational barriers involves: non-alignment of streamlines or sonic characteristics with the grids; recirculating flows; stagnation points; discretization and relaxation on and near shocks and boundaries; far-field artificial boundary conditions; small-scale singularities (meaning important features, such as the complete airplane, which are not visible on some of the coarse grids); large grid aspect ratios; boundary layer resolution; and grid adaption.

A second order discontinuous Galerkin fast sweeping method for Eikonal equations

NASA Astrophysics Data System (ADS)

Li, Fengyan; Shu, Chi-Wang; Zhang, Yong-Tao; Zhao, Hongkai

2008-09-01

In this paper, we construct a second order fast sweeping method with a discontinuous Galerkin (DG) local solver for computing viscosity solutions of a class of static Hamilton-Jacobi equations, namely the Eikonal equations. Our piecewise linear DG local solver is built on a DG method developed recently [Y. Cheng, C.-W. Shu, A discontinuous Galerkin finite element method for directly solving the Hamilton-Jacobi equations, Journal of Computational Physics 223 (2007) 398-415] for the time-dependent Hamilton-Jacobi equations. The causality property of Eikonal equations is incorporated into the design of this solver. The resulting local nonlinear system in the Gauss-Seidel iterations is a simple quadratic system and can be solved explicitly. The compactness of the DG method and the fast sweeping strategy lead to fast convergence of the new scheme for Eikonal equations. Extensive numerical examples verify efficiency, convergence and second order accuracy of the proposed method.

Anharmonic Vibrational Spectroscopy on Metal Transition Complexes

NASA Astrophysics Data System (ADS)

Latouche, Camille; Bloino, Julien; Barone, Vincenzo

2014-06-01

Advances in hardware performance and the availability of efficient and reliable computational models have made possible the application of computational spectroscopy to ever larger molecular systems. The systematic interpretation of experimental data and the full characterization of complex molecules can then be facilitated. Focusing on vibrational spectroscopy, several approaches have been proposed to simulate spectra beyond the double harmonic approximation, so that more details become available. However, a routine use of such tools requires the preliminary definition of a valid protocol with the most appropriate combination of electronic structure and nuclear calculation models. Several benchmark of anharmonic calculations frequency have been realized on organic molecules. Nevertheless, benchmarks of organometallics or inorganic metal complexes at this level are strongly lacking despite the interest of these systems due to their strong emission and vibrational properties. Herein we report the benchmark study realized with anharmonic calculations on simple metal complexes, along with some pilot applications on systems of direct technological or biological interest.

Extracting Social Information from Chemosensory Cues: Consideration of Several Scenarios and Their Functional Implications

PubMed Central

Ben-Shaul, Yoram

2015-01-01

Across all sensory modalities, stimuli can vary along multiple dimensions. Efficient extraction of information requires sensitivity to those stimulus dimensions that provide behaviorally relevant information. To derive social information from chemosensory cues, sensory systems must embed information about the relationships between behaviorally relevant traits of individuals and the distributions of the chemical cues that are informative about these traits. In simple cases, the mere presence of one particular compound is sufficient to guide appropriate behavior. However, more generally, chemosensory information is conveyed via relative levels of multiple chemical cues, in non-trivial ways. The computations and networks needed to derive information from multi-molecule stimuli are distinct from those required by single molecule cues. Our current knowledge about how socially relevant information is encoded by chemical blends, and how it is extracted by chemosensory systems is very limited. This manuscript explores several scenarios and the neuronal computations required to identify them. PMID:26635515

On the lower bound of monitor solutions of maximally permissive supervisors for a subclass α-S3PR of flexible manufacturing systems

NASA Astrophysics Data System (ADS)

Chao, Daniel Yuh

2015-01-01

Recently, a novel and computationally efficient method - based on a vector covering approach - to design optimal control places and an iteration approach that computes the reachability graph to obtain a maximally permissive liveness enforcing supervisor for FMS (flexible manufacturing systems) have been reported. However, it is unclear as to the relationship between the structure of the net and the minimal number of monitors required. This paper develops a theory to show that the minimal number of monitors required cannot be less than that of basic siphons in α-S3PR (systems of simple sequential processes with resources). This confirms that two of the three controlled systems by Chen et al. are of a minimal monitor configuration since they belong to α-S3PR and their number in each example equals that of basic siphons.

Accelerated Gaussian mixture model and its application on image segmentation

NASA Astrophysics Data System (ADS)

Zhao, Jianhui; Zhang, Yuanyuan; Ding, Yihua; Long, Chengjiang; Yuan, Zhiyong; Zhang, Dengyi

2013-03-01

Gaussian mixture model (GMM) has been widely used for image segmentation in recent years due to its superior adaptability and simplicity of implementation. However, traditional GMM has the disadvantage of high computational complexity. In this paper an accelerated GMM is designed, for which the following approaches are adopted: establish the lookup table for Gaussian probability matrix to avoid the repetitive probability calculations on all pixels, employ the blocking detection method on each block of pixels to further decrease the complexity, change the structure of lookup table from 3D to 1D with more simple data type to reduce the space requirement. The accelerated GMM is applied on image segmentation with the help of OTSU method to decide the threshold value automatically. Our algorithm has been tested through image segmenting of flames and faces from a set of real pictures, and the experimental results prove its efficiency in segmentation precision and computational cost.

Argumentation for coordinating shared activities

NASA Technical Reports Server (NTRS)

Clement, Bradley J.; Barrett, Anthony C.; Schaffer, Steven R.

2004-01-01

an increasing need for space missions to be able to collaboratively (and competitively) develop plans both within and across missions. In addition, interacting spacecraft that interleave onboard planning and execution must reach consensus on their commitments to each other prior to execution. In domains where missions have varying degrees of interaction and different constraints on communication and computation, the missions will require different coordination protocols in order to efficiently reach consensus with in their imposed deadlines. We describe a Shared Activity Coordination (SHAC) framework that provides a decentralized algorithm for negotiating the scheduling of shared activities over the lifetimes of multiple agents and a foundation for customizing protocols for negotiating planner interactions. We investigate variations of a few simple protocols based on argumentation and distributed constraints satisfaction techniques and evaluate their abilities to reach consistent solutions according to computation, time, and communication costs in an abstract domain where spacecraft propose joint measurements.

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data.

PubMed

Ching, Travers; Zhu, Xun; Garmire, Lana X

2018-04-01

Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet.

Simple-MSSM: a simple and efficient method for simultaneous multi-site saturation mutagenesis.

PubMed

Cheng, Feng; Xu, Jian-Miao; Xiang, Chao; Liu, Zhi-Qiang; Zhao, Li-Qing; Zheng, Yu-Guo

2017-04-01

To develop a practically simple and robust multi-site saturation mutagenesis (MSSM) method that enables simultaneously recombination of amino acid positions for focused mutant library generation. A general restriction enzyme-free and ligase-free MSSM method (Simple-MSSM) based on prolonged overlap extension PCR (POE-PCR) and Simple Cloning techniques. As a proof of principle of Simple-MSSM, the gene of eGFP (enhanced green fluorescent protein) was used as a template gene for simultaneous mutagenesis of five codons. Forty-eight randomly selected clones were sequenced. Sequencing revealed that all the 48 clones showed at least one mutant codon (mutation efficiency = 100%), and 46 out of the 48 clones had mutations at all the five codons. The obtained diversities at these five codons are 27, 24, 26, 26 and 22, respectively, which correspond to 84, 75, 81, 81, 69% of the theoretical diversity offered by NNK-degeneration (32 codons; NNK, K = T or G). The enzyme-free Simple-MSSM method can simultaneously and efficiently saturate five codons within one day, and therefore avoid missing interactions between residues in interacting amino acid networks.

Computational modeling of magnetic particle margination within blood flow through LAMMPS

NASA Astrophysics Data System (ADS)

Ye, Huilin; Shen, Zhiqiang; Li, Ying

2017-11-01

We develop a multiscale and multiphysics computational method to investigate the transport of magnetic particles as drug carriers in blood flow under influence of hydrodynamic interaction and external magnetic field. A hybrid coupling method is proposed to handle red blood cell (RBC)-fluid interface (CFI) and magnetic particle-fluid interface (PFI), respectively. Immersed boundary method (IBM)-based velocity coupling is used to account for CFI, which is validated by tank-treading and tumbling behaviors of a single RBC in simple shear flow. While PFI is captured by IBM-based force coupling, which is verified through movement of a single magnetic particle under non-uniform external magnetic field and breakup of a magnetic chain in rotating magnetic field. These two components are seamlessly integrated within the LAMMPS framework, which is a highly parallelized molecular dynamics solver. In addition, we also implement a parallelized lattice Boltzmann simulator within LAMMPS to handle the fluid flow simulation. Based on the proposed method, we explore the margination behaviors of magnetic particles and magnetic chains within blood flow. We find that the external magnetic field can be used to guide the motion of these magnetic materials and promote their margination to the vascular wall region. Moreover, the scaling performance and speedup test further confirm the high efficiency and robustness of proposed computational method. Therefore, it provides an efficient way to simulate the transport of nanoparticle-based drug carriers within blood flow in a large scale. The simulation results can be applied in the design of efficient drug delivery vehicles that optimally accumulate within diseased tissue, thus providing better imaging sensitivity, therapeutic efficacy and lower toxicity.

Reliability based design optimization: Formulations and methodologies

NASA Astrophysics Data System (ADS)

Agarwal, Harish

Modern products ranging from simple components to complex systems should be designed to be optimal and reliable. The challenge of modern engineering is to ensure that manufacturing costs are reduced and design cycle times are minimized while achieving requirements for performance and reliability. If the market for the product is competitive, improved quality and reliability can generate very strong competitive advantages. Simulation based design plays an important role in designing almost any kind of automotive, aerospace, and consumer products under these competitive conditions. Single discipline simulations used for analysis are being coupled together to create complex coupled simulation tools. This investigation focuses on the development of efficient and robust methodologies for reliability based design optimization in a simulation based design environment. Original contributions of this research are the development of a novel efficient and robust unilevel methodology for reliability based design optimization, the development of an innovative decoupled reliability based design optimization methodology, the application of homotopy techniques in unilevel reliability based design optimization methodology, and the development of a new framework for reliability based design optimization under epistemic uncertainty. The unilevel methodology for reliability based design optimization is shown to be mathematically equivalent to the traditional nested formulation. Numerical test problems show that the unilevel methodology can reduce computational cost by at least 50% as compared to the nested approach. The decoupled reliability based design optimization methodology is an approximate technique to obtain consistent reliable designs at lesser computational expense. Test problems show that the methodology is computationally efficient compared to the nested approach. A framework for performing reliability based design optimization under epistemic uncertainty is also developed. A trust region managed sequential approximate optimization methodology is employed for this purpose. Results from numerical test studies indicate that the methodology can be used for performing design optimization under severe uncertainty.

Small target pre-detection with an attention mechanism

NASA Astrophysics Data System (ADS)

Wang, Yuehuan; Zhang, Tianxu; Wang, Guoyou

2002-04-01

We introduce the concept of predetection based on an attention mechanism to improve the efficiency of small-target detection by limiting the image region of detection. According to the characteristics of small-target detection, local contrast is taken as the only feature in predetection and a nonlinear sampling model is adopted to make the predetection adaptive to detect small targets with different area sizes. To simplify the predetection itself and decrease the false alarm probability, neighboring nodes in the sampling grid are used to generate a saliency map, and a short-term memory is adopted to accelerate the `pop-out' of targets. We discuss the fact that the proposed approach is simple enough in computational complexity. In addition, even in a cluttered background, attention can be led to targets in a satisfying few iterations, which ensures that the detection efficiency will not be decreased due to false alarms. Experimental results are presented to demonstrate the applicability of the approach.

Kalman and particle filtering methods for full vehicle and tyre identification

NASA Astrophysics Data System (ADS)

Bogdanski, Karol; Best, Matthew C.

2018-05-01

This paper considers identification of all significant vehicle handling dynamics of a test vehicle, including identification of a combined-slip tyre model, using only those sensors currently available on most vehicle controller area network buses. Using an appropriately simple but efficient model structure, all of the independent parameters are found from test vehicle data, with the resulting model accuracy demonstrated on independent validation data. The paper extends previous work on augmented Kalman Filter state estimators to concentrate wholly on parameter identification. It also serves as a review of three alternative filtering methods; identifying forms of the unscented Kalman filter, extended Kalman filter and particle filter are proposed and compared for effectiveness, complexity and computational efficiency. All three filters are suited to applications of system identification and the Kalman Filters can also operate in real-time in on-line model predictive controllers or estimators.

Reducing and Analyzing the PHAT Survey with the Cloud

NASA Astrophysics Data System (ADS)

Williams, Benjamin F.; Olsen, Knut; Khan, Rubab; Pirone, Daniel; Rosema, Keith

2018-05-01

We discuss the technical challenges we faced and the techniques we used to overcome them when reducing the Panchromatic Hubble Andromeda Treasury (PHAT) photometric data set on the Amazon Elastic Compute Cloud (EC2). We first describe the architecture of our photometry pipeline, which we found particularly efficient for reducing the data in multiple ways for different purposes. We then describe the features of EC2 that make this architecture both efficient to use and challenging to implement. We describe the techniques we adopted to process our data, and suggest ways these techniques may be improved for those interested in trying such reductions in the future. Finally, we summarize the output photometry data products, which are now hosted publicly in two places in two formats. They are in simple fits tables in the high-level science products on MAST, and on a queryable database available through the NOAO Data Lab.

The economics of bootstrapping space industries - Development of an analytic computer model

NASA Technical Reports Server (NTRS)

Goldberg, A. H.; Criswell, D. R.

1982-01-01

A simple economic model of 'bootstrapping' industrial growth in space and on the Moon is presented. An initial space manufacturing facility (SMF) is assumed to consume lunar materials to enlarge the productive capacity in space. After reaching a predetermined throughput, the enlarged SMF is devoted to products which generate revenue continuously in proportion to the accumulated output mass (such as space solar power stations). Present discounted value and physical estimates for the general factors of production (transport, capital efficiency, labor, etc.) are combined to explore optimum growth in terms of maximized discounted revenues. It is found that 'bootstrapping' reduces the fractional cost to a space industry of transport off-Earth, permits more efficient use of a given transport fleet. It is concluded that more attention should be given to structuring 'bootstrapping' scenarios in which 'learning while doing' can be more fully incorporated in program analysis.

Translucent Radiosity: Efficiently Combining Diffuse Inter-Reflection and Subsurface Scattering.

PubMed

Sheng, Yu; Shi, Yulong; Wang, Lili; Narasimhan, Srinivasa G

2014-07-01

It is hard to efficiently model the light transport in scenes with translucent objects for interactive applications. The inter-reflection between objects and their environments and the subsurface scattering through the materials intertwine to produce visual effects like color bleeding, light glows, and soft shading. Monte-Carlo based approaches have demonstrated impressive results but are computationally expensive, and faster approaches model either only inter-reflection or only subsurface scattering. In this paper, we present a simple analytic model that combines diffuse inter-reflection and isotropic subsurface scattering. Our approach extends the classical work in radiosity by including a subsurface scattering matrix that operates in conjunction with the traditional form factor matrix. This subsurface scattering matrix can be constructed using analytic, measurement-based or simulation-based models and can capture both homogeneous and heterogeneous translucencies. Using a fast iterative solution to radiosity, we demonstrate scene relighting and dynamically varying object translucencies at near interactive rates.

Where neuroscience and dynamic system theory meet autonomous robotics: a contracting basal ganglia model for action selection.

PubMed

Girard, B; Tabareau, N; Pham, Q C; Berthoz, A; Slotine, J-J

2008-05-01

Action selection, the problem of choosing what to do next, is central to any autonomous agent architecture. We use here a multi-disciplinary approach at the convergence of neuroscience, dynamical system theory and autonomous robotics, in order to propose an efficient action selection mechanism based on a new model of the basal ganglia. We first describe new developments of contraction theory regarding locally projected dynamical systems. We exploit these results to design a stable computational model of the cortico-baso-thalamo-cortical loops. Based on recent anatomical data, we include usually neglected neural projections, which participate in performing accurate selection. Finally, the efficiency of this model as an autonomous robot action selection mechanism is assessed in a standard survival task. The model exhibits valuable dithering avoidance and energy-saving properties, when compared with a simple if-then-else decision rule.

Wavelet compression of multichannel ECG data by enhanced set partitioning in hierarchical trees algorithm.

PubMed

Sharifahmadian, Ershad

2006-01-01

The set partitioning in hierarchical trees (SPIHT) algorithm is very effective and computationally simple technique for image and signal compression. Here the author modified the algorithm which provides even better performance than the SPIHT algorithm. The enhanced set partitioning in hierarchical trees (ESPIHT) algorithm has performance faster than the SPIHT algorithm. In addition, the proposed algorithm reduces the number of bits in a bit stream which is stored or transmitted. I applied it to compression of multichannel ECG data. Also, I presented a specific procedure based on the modified algorithm for more efficient compression of multichannel ECG data. This method employed on selected records from the MIT-BIH arrhythmia database. According to experiments, the proposed method attained the significant results regarding compression of multichannel ECG data. Furthermore, in order to compress one signal which is stored for a long time, the proposed multichannel compression method can be utilized efficiently.

Visual display aid for orbital maneuvering - Design considerations

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.; Ellis, Stephen R.

1993-01-01

This paper describes the development of an interactive proximity operations planning system that allows on-site planning of fuel-efficient multiburn maneuvers in a potential multispacecraft environment. Although this display system most directly assists planning by providing visual feedback to aid visualization of the trajectories and constraints, its most significant features include: (1) the use of an 'inverse dynamics' algorithm that removes control nonlinearities facing the operator, and (2) a trajectory planning technique that separates, through a 'geometric spreadsheet', the normally coupled complex problems of planning orbital maneuvers and allows solution by an iterative sequence of simple independent actions. The visual feedback of trajectory shapes and operational constraints, provided by user-transparent and continuously active background computations, allows the operator to make fast, iterative design changes that rapidly converge to fuel-efficient solutions. The planning tool provides an example of operator-assisted optimization of nonlinear cost functions.