Computationally efficient real-time interpolation algorithm for non-uniform sampled biosignals.

PubMed

Guven, Onur; Eftekhar, Amir; Kindt, Wilko; Constandinou, Timothy G

2016-06-01

This Letter presents a novel, computationally efficient interpolation method that has been optimised for use in electrocardiogram baseline drift removal. In the authors' previous Letter three isoelectric baseline points per heartbeat are detected, and here utilised as interpolation points. As an extension from linear interpolation, their algorithm segments the interpolation interval and utilises different piecewise linear equations. Thus, the algorithm produces a linear curvature that is computationally efficient while interpolating non-uniform samples. The proposed algorithm is tested using sinusoids with different fundamental frequencies from 0.05 to 0.7 Hz and also validated with real baseline wander data acquired from the Massachusetts Institute of Technology University and Boston's Beth Israel Hospital (MIT-BIH) Noise Stress Database. The synthetic data results show an root mean square (RMS) error of 0.9 μV (mean), 0.63 μV (median) and 0.6 μV (standard deviation) per heartbeat on a 1 mVp-p 0.1 Hz sinusoid. On real data, they obtain an RMS error of 10.9 μV (mean), 8.5 μV (median) and 9.0 μV (standard deviation) per heartbeat. Cubic spline interpolation and linear interpolation on the other hand shows 10.7 μV, 11.6 μV (mean), 7.8 μV, 8.9 μV (median) and 9.8 μV, 9.3 μV (standard deviation) per heartbeat.

Turbulent current drive mechanisms

NASA Astrophysics Data System (ADS)

McDevitt, Christopher J.; Tang, Xian-Zhu; Guo, Zehua

2017-08-01

Mechanisms through which plasma microturbulence can drive a mean electron plasma current are derived. The efficiency through which these turbulent contributions can drive deviations from neoclassical predictions of the electron current profile is computed by employing a linearized Coulomb collision operator. It is found that a non-diffusive contribution to the electron momentum flux as well as an anomalous electron-ion momentum exchange term provide the most efficient means through which turbulence can modify the mean electron current for the cases considered. Such turbulent contributions appear as an effective EMF within Ohm's law and hence provide an ideal means for driving deviations from neoclassical predictions.

Approximate, computationally efficient online learning in Bayesian spiking neurons.

PubMed

Kuhlmann, Levin; Hauser-Raspe, Michael; Manton, Jonathan H; Grayden, David B; Tapson, Jonathan; van Schaik, André

2014-03-01

Bayesian spiking neurons (BSNs) provide a probabilistic interpretation of how neurons perform inference and learning. Online learning in BSNs typically involves parameter estimation based on maximum-likelihood expectation-maximization (ML-EM) which is computationally slow and limits the potential of studying networks of BSNs. An online learning algorithm, fast learning (FL), is presented that is more computationally efficient than the benchmark ML-EM for a fixed number of time steps as the number of inputs to a BSN increases (e.g., 16.5 times faster run times for 20 inputs). Although ML-EM appears to converge 2.0 to 3.6 times faster than FL, the computational cost of ML-EM means that ML-EM takes longer to simulate to convergence than FL. FL also provides reasonable convergence performance that is robust to initialization of parameter estimates that are far from the true parameter values. However, parameter estimation depends on the range of true parameter values. Nevertheless, for a physiologically meaningful range of parameter values, FL gives very good average estimation accuracy, despite its approximate nature. The FL algorithm therefore provides an efficient tool, complementary to ML-EM, for exploring BSN networks in more detail in order to better understand their biological relevance. Moreover, the simplicity of the FL algorithm means it can be easily implemented in neuromorphic VLSI such that one can take advantage of the energy-efficient spike coding of BSNs.

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.

Genten: Software for Generalized Tensor Decompositions v. 1.0.0

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

Phipps, Eric T.; Kolda, Tamara G.; Dunlavy, Daniel

Tensors, or multidimensional arrays, are a powerful mathematical means of describing multiway data. This software provides computational means for decomposing or approximating a given tensor in terms of smaller tensors of lower dimension, focusing on decomposition of large, sparse tensors. These techniques have applications in many scientific areas, including signal processing, linear algebra, computer vision, numerical analysis, data mining, graph analysis, neuroscience and more. The software is designed to take advantage of parallelism present emerging computer architectures such has multi-core CPUs, many-core accelerators such as the Intel Xeon Phi, and computation-oriented GPUs to enable efficient processing of large tensors.

Nonlinear Detection, Estimation, and Control for Free-Space Optical Communication

DTIC Science & Technology

2008-08-17

original message. The promising features of this communication scheme such as high-bandwidth, power efficiency, and security, render it a viable means...bandwidth, power efficiency, and security, render it a viable means for high data rate point-to-point communication. In this dissertation, we adopt a...Department of Electrical and Computer Engineering In free-space optical communication, the intensity of a laser beam is modulated by a message, the beam

Semiannual Report October 1, 1999 through March 31, 2000

DTIC Science & Technology

2000-04-01

Mark Carpenter (NASA Langley). Textbook Multigrid Efficiency for the Navier-Stokes Equations Boris Diskin A typical modern Reynolds-Averaged...defined as textbook multigrid efficiency (TME), meaning the solutions to the governing system of equations are attained in a computational work...basic elements of the barriers to be overcome in extending textbook efficiencies to the compressible RANS equations, namely entering flows, far wake

A Stochastic Total Least Squares Solution of Adaptive Filtering Problem

PubMed Central

Ahmad, Noor Atinah

2014-01-01

An efficient and computationally linear algorithm is derived for total least squares solution of adaptive filtering problem, when both input and output signals are contaminated by noise. The proposed total least mean squares (TLMS) algorithm is designed by recursively computing an optimal solution of adaptive TLS problem by minimizing instantaneous value of weighted cost function. Convergence analysis of the algorithm is given to show the global convergence of the proposed algorithm, provided that the stepsize parameter is appropriately chosen. The TLMS algorithm is computationally simpler than the other TLS algorithms and demonstrates a better performance as compared with the least mean square (LMS) and normalized least mean square (NLMS) algorithms. It provides minimum mean square deviation by exhibiting better convergence in misalignment for unknown system identification under noisy inputs. PMID:24688412

Two-part models with stochastic processes for modelling longitudinal semicontinuous data: Computationally efficient inference and modelling the overall marginal mean.

PubMed

Yiu, Sean; Tom, Brian Dm

2017-01-01

Several researchers have described two-part models with patient-specific stochastic processes for analysing longitudinal semicontinuous data. In theory, such models can offer greater flexibility than the standard two-part model with patient-specific random effects. However, in practice, the high dimensional integrations involved in the marginal likelihood (i.e. integrated over the stochastic processes) significantly complicates model fitting. Thus, non-standard computationally intensive procedures based on simulating the marginal likelihood have so far only been proposed. In this paper, we describe an efficient method of implementation by demonstrating how the high dimensional integrations involved in the marginal likelihood can be computed efficiently. Specifically, by using a property of the multivariate normal distribution and the standard marginal cumulative distribution function identity, we transform the marginal likelihood so that the high dimensional integrations are contained in the cumulative distribution function of a multivariate normal distribution, which can then be efficiently evaluated. Hence, maximum likelihood estimation can be used to obtain parameter estimates and asymptotic standard errors (from the observed information matrix) of model parameters. We describe our proposed efficient implementation procedure for the standard two-part model parameterisation and when it is of interest to directly model the overall marginal mean. The methodology is applied on a psoriatic arthritis data set concerning functional disability.

Algorithms for Zonal Methods and Development of Three Dimensional Mesh Generation Procedures.

DTIC Science & Technology

1984-02-01

a r-re complete set of equations is used, but their effect is imposed by means of a right hand side forcing function, not by means of a zonal boundary...modifications of flow-simulation algorithms The explicit finite-difference code of Magnus and are discussed. Computational tests in two dimensions...used to simplify the task of grid generation without an adverse achieve computational efficiency. More recently, effect on flow-field algorithms and

A coarse-to-fine kernel matching approach for mean-shift based visual tracking

NASA Astrophysics Data System (ADS)

Liangfu, L.; Zuren, F.; Weidong, C.; Ming, J.

2009-03-01

Mean shift is an efficient pattern match algorithm. It is widely used in visual tracking fields since it need not perform whole search in the image space. It employs gradient optimization method to reduce the time of feature matching and realize rapid object localization, and uses Bhattacharyya coefficient as the similarity measure between object template and candidate template. This thesis presents a mean shift algorithm based on coarse-to-fine search for the best kernel matching. This paper researches for object tracking with large motion area based on mean shift. To realize efficient tracking of such an object, we present a kernel matching method from coarseness to fine. If the motion areas of the object between two frames are very large and they are not overlapped in image space, then the traditional mean shift method can only obtain local optimal value by iterative computing in the old object window area, so the real tracking position cannot be obtained and the object tracking will be disabled. Our proposed algorithm can efficiently use a similarity measure function to realize the rough location of motion object, then use mean shift method to obtain the accurate local optimal value by iterative computing, which successfully realizes object tracking with large motion. Experimental results show its good performance in accuracy and speed when compared with background-weighted histogram algorithm in the literature.

Computer program for prediction of the deposition of material released from fixed and rotary wing aircraft

NASA Technical Reports Server (NTRS)

Teske, M. E.

1984-01-01

This is a user manual for the computer code ""AGDISP'' (AGricultural DISPersal) which has been developed to predict the deposition of material released from fixed and rotary wing aircraft in a single-pass, computationally efficient manner. The formulation of the code is novel in that the mean particle trajectory and the variance about the mean resulting from turbulent fluid fluctuations are simultaneously predicted. The code presently includes the capability of assessing the influence of neutral atmospheric conditions, inviscid wake vortices, particle evaporation, plant canopy and terrain on the deposition pattern.

Turbulent current drive mechanisms

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

McDevitt, Christopher J.; Tang, Xian-Zhu; Guo, Zehua

Mechanisms through which plasma microturbulence can drive a mean electron plasma current are derived. The efficiency through which these turbulent contributions can drive deviations from neoclassical predictions of the electron current profile is computed by employing a linearized Coulomb collision operator. It is found that a non-diffusive contribution to the electron momentum flux as well as an anomalous electron-ion momentum exchange term provide the most efficient means through which turbulence can modify the mean electron current for the cases considered. Such turbulent contributions appear as an effective EMF within Ohm’s law, and hence provide an ideal means for driving deviationsmore » from neoclassical predictions.« less

Turbulent current drive mechanisms

DOE PAGES

McDevitt, Christopher J.; Tang, Xian-Zhu; Guo, Zehua

2017-07-01

Mechanisms through which plasma microturbulence can drive a mean electron plasma current are derived. The efficiency through which these turbulent contributions can drive deviations from neoclassical predictions of the electron current profile is computed by employing a linearized Coulomb collision operator. It is found that a non-diffusive contribution to the electron momentum flux as well as an anomalous electron-ion momentum exchange term provide the most efficient means through which turbulence can modify the mean electron current for the cases considered. Such turbulent contributions appear as an effective EMF within Ohm’s law, and hence provide an ideal means for driving deviationsmore » from neoclassical predictions.« less

Time-Domain Computation Of Electromagnetic Fields In MMICs

NASA Technical Reports Server (NTRS)

Lansing, Faiza S.; Rascoe, Daniel L.

1995-01-01

Maxwell's equations solved on three-dimensional, conformed orthogonal grids by finite-difference techniques. Method of computing frequency-dependent electrical parameters of monolithic microwave integrated circuit (MMIC) involves time-domain computation of propagation of electromagnetic field in response to excitation by single pulse at input terminal, followed by computation of Fourier transforms to obtain frequency-domain response from time-domain response. Parameters computed include electric and magnetic fields, voltages, currents, impedances, scattering parameters, and effective dielectric constants. Powerful and efficient means for analyzing performance of even complicated MMIC.

Computing the Expected Cost of an Appointment Schedule for Statistically Identical Customers with Probabilistic Service Times

PubMed Central

Dietz, Dennis C.

2014-01-01

A cogent method is presented for computing the expected cost of an appointment schedule where customers are statistically identical, the service time distribution has known mean and variance, and customer no-shows occur with time-dependent probability. The approach is computationally efficient and can be easily implemented to evaluate candidate schedules within a schedule optimization algorithm. PMID:24605070

The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce

NASA Astrophysics Data System (ADS)

Chen, Xi; Zhou, Liqing

2015-12-01

With the development of satellite remote sensing technology and the remote sensing image data, traditional remote sensing image segmentation technology cannot meet the massive remote sensing image processing and storage requirements. This article put cloud computing and parallel computing technology in remote sensing image segmentation process, and build a cheap and efficient computer cluster system that uses parallel processing to achieve MeanShift algorithm of remote sensing image segmentation based on the MapReduce model, not only to ensure the quality of remote sensing image segmentation, improved split speed, and better meet the real-time requirements. The remote sensing image segmentation MeanShift algorithm parallel processing algorithm based on MapReduce shows certain significance and a realization of value.

An efficient approach for computing the geometrical optics field reflected from a numerically specified surface

NASA Technical Reports Server (NTRS)

Mittra, R.; Rushdi, A.

1979-01-01

An approach for computing the geometrical optic fields reflected from a numerically specified surface is presented. The approach includes the step of deriving a specular point and begins with computing the reflected rays off the surface at the points where their coordinates, as well as the partial derivatives (or equivalently, the direction of the normal), are numerically specified. Then, a cluster of three adjacent rays are chosen to define a 'mean ray' and the divergence factor associated with this mean ray. Finally, the ampilitude, phase, and vector direction of the reflected field at a given observation point are derived by associating this point with the nearest mean ray and determining its position relative to such a ray.

A Genetic Algorithm That Exchanges Neighboring Centers for Fuzzy c-Means Clustering

ERIC Educational Resources Information Center

Chahine, Firas Safwan

2012-01-01

Clustering algorithms are widely used in pattern recognition and data mining applications. Due to their computational efficiency, partitional clustering algorithms are better suited for applications with large datasets than hierarchical clustering algorithms. K-means is among the most popular partitional clustering algorithm, but has a major…

Environmental effects of dredging. Documentation of the dyecon module for ADDAMS: Determining the hydraulic retention and efficiency of confined disposal facilities. Technical note

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

Hayes, D.F.; Schroeder, P.R.; Engler, R.M.

This technical note describes procedures for determining mean hydraulic retention time and efficiency of a confined disposal facility (CDF) from a dye tracer slug test. These parameters are required to properly design a CDF for solids retention and for effluent quality considerations. Detailed information on conduct and analysis of dye tracer studies can be found in Engineer Manual 1110-2-5027, Confined Dredged Material Disposal. This technical note documents the DYECON computer program which facilitates the analysis of dye tracer concentration data and computes the hydraulic efficiency of a CDF as part of the Automated Dredging and Disposal Alternatives Management System (ADDAMS).

Two-Dimensional Grids About Airfoils and Other Shapes

NASA Technical Reports Server (NTRS)

Sorenson, R.

1982-01-01

GRAPE computer program generates two-dimensional finite-difference grids about airfoils and other shapes by use of Poisson differential equation. GRAPE can be used with any boundary shape, even one specified by tabulated points and including limited number of sharp corners. Numerically stable and computationally fast, GRAPE provides aerodynamic analyst with efficient and consistant means of grid generation.

Lessons Learned in Designing and Implementing a Computer-Adaptive Test for English

ERIC Educational Resources Information Center

Burston, Jack; Neophytou, Maro

2014-01-01

This paper describes the lessons learned in designing and implementing a computer-adaptive test (CAT) for English. The early identification of students with weak L2 English proficiency is of critical importance in university settings that have compulsory English language course graduation requirements. The most efficient means of diagnosing the L2…

Enhancing Arithmetic and Word-Problem Solving Skills Efficiently by Individualized Computer-Assisted Practice

ERIC Educational Resources Information Center

Schoppek, Wolfgang; Tulis, Maria

2010-01-01

The fluency of basic arithmetical operations is a precondition for mathematical problem solving. However, the training of skills plays a minor role in contemporary mathematics instruction. The authors proposed individualization of practice as a means to improve its efficiency, so that the time spent with the training of skills is minimized. As a…

Simultaneous Inference For The Mean Function Based on Dense Functional Data

PubMed Central

Cao, Guanqun; Yang, Lijian; Todem, David

2012-01-01

A polynomial spline estimator is proposed for the mean function of dense functional data together with a simultaneous confidence band which is asymptotically correct. In addition, the spline estimator and its accompanying confidence band enjoy oracle efficiency in the sense that they are asymptotically the same as if all random trajectories are observed entirely and without errors. The confidence band is also extended to the difference of mean functions of two populations of functional data. Simulation experiments provide strong evidence that corroborates the asymptotic theory while computing is efficient. The confidence band procedure is illustrated by analyzing the near infrared spectroscopy data. PMID:22665964

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Meyer, Kerry G.; Platnick, Steven; Oreopoulos, Lazaros; Lee, Dongmin; Yu, Hongbin

2014-01-01

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table based on radiative transfer calculations. We verify that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 1:30PM local time) shortwave DRE of above cloud aerosol (ACA) that generally agrees with more rigorous pixel-level computation within 4 percent. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeast Atlantic Ocean would increase, from the original value of 6.4 W m(-2) based on operational CALIOP AOD to 9.6 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 5 as suggested in (Jethva et al., 2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m(-2) AOD(-1), suggesting a near linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets, as well as climate model outputs.

A new framework for comprehensive, robust, and efficient global sensitivity analysis: 1. Theory

NASA Astrophysics Data System (ADS)

Razavi, Saman; Gupta, Hoshin V.

2016-01-01

Computer simulation models are continually growing in complexity with increasingly more factors to be identified. Sensitivity Analysis (SA) provides an essential means for understanding the role and importance of these factors in producing model responses. However, conventional approaches to SA suffer from (1) an ambiguous characterization of sensitivity, and (2) poor computational efficiency, particularly as the problem dimension grows. Here, we present a new and general sensitivity analysis framework (called VARS), based on an analogy to "variogram analysis," that provides an intuitive and comprehensive characterization of sensitivity across the full spectrum of scales in the factor space. We prove, theoretically, that Morris (derivative-based) and Sobol (variance-based) methods and their extensions are special cases of VARS, and that their SA indices can be computed as by-products of the VARS framework. Synthetic functions that resemble actual model response surfaces are used to illustrate the concepts, and show VARS to be as much as two orders of magnitude more computationally efficient than the state-of-the-art Sobol approach. In a companion paper, we propose a practical implementation strategy, and demonstrate the effectiveness, efficiency, and reliability (robustness) of the VARS framework on real-data case studies.

Computer Aided Design of Computer Generated Holograms for electron beam fabrication

NASA Technical Reports Server (NTRS)

Urquhart, Kristopher S.; Lee, Sing H.; Guest, Clark C.; Feldman, Michael R.; Farhoosh, Hamid

1989-01-01

Computer Aided Design (CAD) systems that have been developed for electrical and mechanical design tasks are also effective tools for the process of designing Computer Generated Holograms (CGHs), particularly when these holograms are to be fabricated using electron beam lithography. CAD workstations provide efficient and convenient means of computing, storing, displaying, and preparing for fabrication many of the features that are common to CGH designs. Experience gained in the process of designing CGHs with various types of encoding methods is presented. Suggestions are made so that future workstations may further accommodate the CGH design process.

Efficient method for the calculation of mean extinction. II. Analyticity of the complex extinction efficiency of homogeneous spheroids and finite cylinders.

PubMed

Xing, Z F; Greenberg, J M

1994-08-20

The analyticity of the complex extinction efficiency is examined numerically in the size-parameter domain for homogeneous prolate and oblate spheroids and finite cylinders. The T-matrix code, which is the most efficient program available to date, is employed to calculate the individual particle-extinction efficiencies. Because of its computational limitations in the size-parameter range, a slightly modified Hilbert-transform algorithm is required to establish the analyticity numerically. The findings concerning analyticity that we reported for spheres (Astrophys. J. 399, 164-175, 1992) apply equally to these nonspherical particles.

R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization

PubMed Central

Dazard, Jean-Eudes; Xu, Hua; Rao, J. Sunil

2015-01-01

We present an implementation in the R language for statistical computing of our recent non-parametric joint adaptive mean-variance regularization and variance stabilization procedure. The method is specifically suited for handling difficult problems posed by high-dimensional multivariate datasets (p ≫ n paradigm), such as in ‘omics’-type data, among which are that the variance is often a function of the mean, variable-specific estimators of variances are not reliable, and tests statistics have low powers due to a lack of degrees of freedom. The implementation offers a complete set of features including: (i) normalization and/or variance stabilization function, (ii) computation of mean-variance-regularized t and F statistics, (iii) generation of diverse diagnostic plots, (iv) synthetic and real ‘omics’ test datasets, (v) computationally efficient implementation, using C interfacing, and an option for parallel computing, (vi) manual and documentation on how to setup a cluster. To make each feature as user-friendly as possible, only one subroutine per functionality is to be handled by the end-user. It is available as an R package, called MVR (‘Mean-Variance Regularization’), downloadable from the CRAN. PMID:26819572

A straightforward method to compute average stochastic oscillations from data samples.

PubMed

Júlvez, Jorge

2015-10-19

Many biological systems exhibit sustained stochastic oscillations in their steady state. Assessing these oscillations is usually a challenging task due to the potential variability of the amplitude and frequency of the oscillations over time. As a result of this variability, when several stochastic replications are averaged, the oscillations are flattened and can be overlooked. This can easily lead to the erroneous conclusion that the system reaches a constant steady state. This paper proposes a straightforward method to detect and asses stochastic oscillations. The basis of the method is in the use of polar coordinates for systems with two species, and cylindrical coordinates for systems with more than two species. By slightly modifying these coordinate systems, it is possible to compute the total angular distance run by the system and the average Euclidean distance to a reference point. This allows us to compute confidence intervals, both for the average angular speed and for the distance to a reference point, from a set of replications. The use of polar (or cylindrical) coordinates provides a new perspective of the system dynamics. The mean trajectory that can be obtained by averaging the usual cartesian coordinates of the samples informs about the trajectory of the center of mass of the replications. In contrast to such a mean cartesian trajectory, the mean polar trajectory can be used to compute the average circular motion of those replications, and therefore, can yield evidence about sustained steady state oscillations. Both, the coordinate transformation and the computation of confidence intervals, can be carried out efficiently. This results in an efficient method to evaluate stochastic oscillations.

Teaching Ionic Solvation Structure with a Monte Carlo Liquid Simulation Program

ERIC Educational Resources Information Center

Serrano, Agostinho; Santos, Flavia M. T.; Greca, Ileana M.

2004-01-01

The use of molecular dynamics and Monte Carlo methods has provided efficient means to stimulate the behavior of molecular liquids and solutions. A Monte Carlo simulation program is used to compute the structure of liquid water and of water as a solvent to Na(super +), Cl(super -), and Ar on a personal computer to show that it is easily feasible to…

Intranasal dexmedetomidine for sedation for pediatric computed tomography imaging.

PubMed

Mekitarian Filho, Eduardo; Robinson, Fay; de Carvalho, Werther Brunow; Gilio, Alfredo Elias; Mason, Keira P

2015-05-01

This prospective observational pilot study evaluated the aerosolized intranasal route for dexmedetomidine as a safe, effective, and efficient option for infant and pediatric sedation for computed tomography imaging. The mean time to sedation was 13.4 minutes, with excellent image quality, no failed sedations, or significant adverse events. Registered with ClinicalTrials.gov: NCT01900405. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Efficient fuzzy C-means architecture for image segmentation.

PubMed

Li, Hui-Ya; Hwang, Wen-Jyi; Chang, Chia-Yen

2011-01-01

This paper presents a novel VLSI architecture for image segmentation. The architecture is based on the fuzzy c-means algorithm with spatial constraint for reducing the misclassification rate. In the architecture, the usual iterative operations for updating the membership matrix and cluster centroid are merged into one single updating process to evade the large storage requirement. In addition, an efficient pipelined circuit is used for the updating process for accelerating the computational speed. Experimental results show that the the proposed circuit is an effective alternative for real-time image segmentation with low area cost and low misclassification rate.

Unobtrusive measurement of daily computer use to detect mild cognitive impairment

PubMed Central

Kaye, Jeffrey; Mattek, Nora; Dodge, Hiroko H; Campbell, Ian; Hayes, Tamara; Austin, Daniel; Hatt, William; Wild, Katherine; Jimison, Holly; Pavel, Michael

2013-01-01

Background Mild disturbances of higher order activities of daily living are present in people diagnosed with mild cognitive impairment (MCI). These deficits may be difficult to detect among those still living independently. Unobtrusive continuous assessment of a complex activity such as home computer use may detect mild functional changes and identify MCI. We sought to determine whether long-term changes in remotely monitored computer use differ in persons with MCI in comparison to cognitively intact volunteers. Methods Participants enrolled in a longitudinal cohort study of unobtrusive in-home technologies to detect cognitive and motor decline in independently living seniors were assessed for computer usage (number of days with use, mean daily usage and coefficient of variation of use) measured by remotely monitoring computer session start and end times. Results Over 230,000 computer sessions from 113 computer users (mean age, 85; 38 with MCI) were acquired during a mean of 36 months. In mixed effects models there was no difference in computer usage at baseline between MCI and intact participants controlling for age, sex, education, race and computer experience. However, over time, between MCI and intact participants, there was a significant decrease in number of days with use (p=0.01), mean daily usage (~1% greater decrease/month; p=0.009) and an increase in day-to-day use variability (p=0.002). Conclusions Computer use change can be unobtrusively monitored and indicate individuals with MCI. With 79% of those 55–64 years old now online, this may be an ecologically valid and efficient approach to track subtle clinically meaningful change with aging. PMID:23688576

Assessing the relationship between computational speed and precision: a case study comparing an interpreted versus compiled programming language using a stochastic simulation model in diabetes care.

PubMed

McEwan, Phil; Bergenheim, Klas; Yuan, Yong; Tetlow, Anthony P; Gordon, Jason P

2010-01-01

Simulation techniques are well suited to modelling diseases yet can be computationally intensive. This study explores the relationship between modelled effect size, statistical precision, and efficiency gains achieved using variance reduction and an executable programming language. A published simulation model designed to model a population with type 2 diabetes mellitus based on the UKPDS 68 outcomes equations was coded in both Visual Basic for Applications (VBA) and C++. Efficiency gains due to the programming language were evaluated, as was the impact of antithetic variates to reduce variance, using predicted QALYs over a 40-year time horizon. The use of C++ provided a 75- and 90-fold reduction in simulation run time when using mean and sampled input values, respectively. For a series of 50 one-way sensitivity analyses, this would yield a total run time of 2 minutes when using C++, compared with 155 minutes for VBA when using mean input values. The use of antithetic variates typically resulted in a 53% reduction in the number of simulation replications and run time required. When drawing all input values to the model from distributions, the use of C++ and variance reduction resulted in a 246-fold improvement in computation time compared with VBA - for which the evaluation of 50 scenarios would correspondingly require 3.8 hours (C++) and approximately 14.5 days (VBA). The choice of programming language used in an economic model, as well as the methods for improving precision of model output can have profound effects on computation time. When constructing complex models, more computationally efficient approaches such as C++ and variance reduction should be considered; concerns regarding model transparency using compiled languages are best addressed via thorough documentation and model validation.

Efficient Monte Carlo Estimation of the Expected Value of Sample Information Using Moment Matching.

PubMed

Heath, Anna; Manolopoulou, Ioanna; Baio, Gianluca

2018-02-01

The Expected Value of Sample Information (EVSI) is used to calculate the economic value of a new research strategy. Although this value would be important to both researchers and funders, there are very few practical applications of the EVSI. This is due to computational difficulties associated with calculating the EVSI in practical health economic models using nested simulations. We present an approximation method for the EVSI that is framed in a Bayesian setting and is based on estimating the distribution of the posterior mean of the incremental net benefit across all possible future samples, known as the distribution of the preposterior mean. Specifically, this distribution is estimated using moment matching coupled with simulations that are available for probabilistic sensitivity analysis, which is typically mandatory in health economic evaluations. This novel approximation method is applied to a health economic model that has previously been used to assess the performance of other EVSI estimators and accurately estimates the EVSI. The computational time for this method is competitive with other methods. We have developed a new calculation method for the EVSI which is computationally efficient and accurate. This novel method relies on some additional simulation so can be expensive in models with a large computational cost.

Some Implications for Afro-American Culture: Rationalism and Western Music

ERIC Educational Resources Information Center

Walton, Ortiz M.

1973-01-01

Will the computer or instruments powered by electrical energy become the most efficient means by which to produce Western music, replacing the live performer? If so, what will be the effects of electronic, mechanical music on society? (Author/RJ)

Beyond mean-field approximations for accurate and computationally efficient models of on-lattice chemical kinetics

NASA Astrophysics Data System (ADS)

Pineda, M.; Stamatakis, M.

2017-07-01

Modeling the kinetics of surface catalyzed reactions is essential for the design of reactors and chemical processes. The majority of microkinetic models employ mean-field approximations, which lead to an approximate description of catalytic kinetics by assuming spatially uncorrelated adsorbates. On the other hand, kinetic Monte Carlo (KMC) methods provide a discrete-space continuous-time stochastic formulation that enables an accurate treatment of spatial correlations in the adlayer, but at a significant computation cost. In this work, we use the so-called cluster mean-field approach to develop higher order approximations that systematically increase the accuracy of kinetic models by treating spatial correlations at a progressively higher level of detail. We further demonstrate our approach on a reduced model for NO oxidation incorporating first nearest-neighbor lateral interactions and construct a sequence of approximations of increasingly higher accuracy, which we compare with KMC and mean-field. The latter is found to perform rather poorly, overestimating the turnover frequency by several orders of magnitude for this system. On the other hand, our approximations, while more computationally intense than the traditional mean-field treatment, still achieve tremendous computational savings compared to KMC simulations, thereby opening the way for employing them in multiscale modeling frameworks.

Rapid road repair vehicle

DOEpatents

Mara, Leo M.

1999-01-01

Disclosed are improvments to a rapid road repair vehicle comprising an improved cleaning device arrangement, two dispensing arrays for filling defects more rapidly and efficiently, an array of pre-heaters to heat the road way surface in order to help the repair material better bond to the repaired surface, a means for detecting, measuring, and computing the number, location and volume of each of the detected surface imperfection, and a computer means schema for controlling the operation of the plurality of vehicle subsystems. The improved vehicle is, therefore, better able to perform its intended function of filling surface imperfections while moving over those surfaces at near normal traffic speeds.

Predicting organ toxicity using in vitro bioactivity data and chemical structure

EPA Science Inventory

Animal testing alone cannot practically evaluate the health hazard posed by tens of thousands of environmental chemicals. Computational approaches together with high-throughput experimental data may provide more efficient means to predict chemical toxicity. Here, we use a superv...

Decoupled CFD-based optimization of efficiency and cavitation performance of a double-suction pump

NASA Astrophysics Data System (ADS)

Škerlavaj, A.; Morgut, M.; Jošt, D.; Nobile, E.

2017-04-01

In this study the impeller geometry of a double-suction pump ensuring the best performances in terms of hydraulic efficiency and reluctance of cavitation is determined using an optimization strategy, which was driven by means of the modeFRONTIER optimization platform. The different impeller shapes (designs) are modified according to the optimization parameters and tested with a computational fluid dynamics (CFD) software, namely ANSYS CFX. The simulations are performed using a decoupled approach, where only the impeller domain region is numerically investigated for computational convenience. The flow losses in the volute are estimated on the base of the velocity distribution at the impeller outlet. The best designs are then validated considering the computationally more expensive full geometry CFD model. The overall results show that the proposed approach is suitable for quick impeller shape optimization.

Algebraic model checking for Boolean gene regulatory networks.

PubMed

Tran, Quoc-Nam

2011-01-01

We present a computational method in which modular and Groebner bases (GB) computation in Boolean rings are used for solving problems in Boolean gene regulatory networks (BN). In contrast to other known algebraic approaches, the degree of intermediate polynomials during the calculation of Groebner bases using our method will never grow resulting in a significant improvement in running time and memory space consumption. We also show how calculation in temporal logic for model checking can be done by means of our direct and efficient Groebner basis computation in Boolean rings. We present our experimental results in finding attractors and control strategies of Boolean networks to illustrate our theoretical arguments. The results are promising. Our algebraic approach is more efficient than the state-of-the-art model checker NuSMV on BNs. More importantly, our approach finds all solutions for the BN problems.

PHYSICO: An UNIX based Standalone Procedure for Computation of Individual and Group Properties of Protein Sequences.

PubMed

Gupta, Parth Sarthi Sen; Banerjee, Shyamashree; Islam, Rifat Nawaz Ul; Mondal, Sudipta; Mondal, Buddhadev; Bandyopadhyay, Amal K

2014-01-01

In the genomic and proteomic era, efficient and automated analyses of sequence properties of protein have become an important task in bioinformatics. There are general public licensed (GPL) software tools to perform a part of the job. However, computations of mean properties of large number of orthologous sequences are not possible from the above mentioned GPL sets. Further, there is no GPL software or server which can calculate window dependent sequence properties for a large number of sequences in a single run. With a view to overcome above limitations, we have developed a standalone procedure i.e. PHYSICO, which performs various stages of computation in a single run based on the type of input provided either in RAW-FASTA or BLOCK-FASTA format and makes excel output for: a) Composition, Class composition, Mean molecular weight, Isoelectic point, Aliphatic index and GRAVY, b) column based compositions, variability and difference matrix, c) 25 kinds of window dependent sequence properties. The program is fast, efficient, error free and user friendly. Calculation of mean and standard deviation of homologous sequences sets, for comparison purpose when relevant, is another attribute of the program; a property seldom seen in existing GPL softwares. PHYSICO is freely available for non-commercial/academic user in formal request to the corresponding author akbanerjee@biotech.buruniv.ac.in.

PHYSICO: An UNIX based Standalone Procedure for Computation of Individual and Group Properties of Protein Sequences

PubMed Central

Gupta, Parth Sarthi Sen; Banerjee, Shyamashree; Islam, Rifat Nawaz Ul; Mondal, Sudipta; Mondal, Buddhadev; Bandyopadhyay, Amal K

2014-01-01

In the genomic and proteomic era, efficient and automated analyses of sequence properties of protein have become an important task in bioinformatics. There are general public licensed (GPL) software tools to perform a part of the job. However, computations of mean properties of large number of orthologous sequences are not possible from the above mentioned GPL sets. Further, there is no GPL software or server which can calculate window dependent sequence properties for a large number of sequences in a single run. With a view to overcome above limitations, we have developed a standalone procedure i.e. PHYSICO, which performs various stages of computation in a single run based on the type of input provided either in RAW-FASTA or BLOCK-FASTA format and makes excel output for: a) Composition, Class composition, Mean molecular weight, Isoelectic point, Aliphatic index and GRAVY, b) column based compositions, variability and difference matrix, c) 25 kinds of window dependent sequence properties. The program is fast, efficient, error free and user friendly. Calculation of mean and standard deviation of homologous sequences sets, for comparison purpose when relevant, is another attribute of the program; a property seldom seen in existing GPL softwares. Availability PHYSICO is freely available for non-commercial/academic user in formal request to the corresponding author akbanerjee@biotech.buruniv.ac.in PMID:24616564

Unobtrusive measurement of daily computer use to detect mild cognitive impairment.

PubMed

Kaye, Jeffrey; Mattek, Nora; Dodge, Hiroko H; Campbell, Ian; Hayes, Tamara; Austin, Daniel; Hatt, William; Wild, Katherine; Jimison, Holly; Pavel, Michael

2014-01-01

Mild disturbances of higher order activities of daily living are present in people diagnosed with mild cognitive impairment (MCI). These deficits may be difficult to detect among those still living independently. Unobtrusive continuous assessment of a complex activity such as home computer use may detect mild functional changes and identify MCI. We sought to determine whether long-term changes in remotely monitored computer use differ in persons with MCI in comparison with cognitively intact volunteers. Participants enrolled in a longitudinal cohort study of unobtrusive in-home technologies to detect cognitive and motor decline in independently living seniors were assessed for computer use (number of days with use, mean daily use, and coefficient of variation of use) measured by remotely monitoring computer session start and end times. More than 230,000 computer sessions from 113 computer users (mean age, 85 years; 38 with MCI) were acquired during a mean of 36 months. In mixed-effects models, there was no difference in computer use at baseline between MCI and intact participants controlling for age, sex, education, race, and computer experience. However, over time, between MCI and intact participants, there was a significant decrease in number of days with use (P = .01), mean daily use (∼1% greater decrease/month; P = .009), and an increase in day-to-day use variability (P = .002). Computer use change can be monitored unobtrusively and indicates individuals with MCI. With 79% of those 55 to 64 years old now online, this may be an ecologically valid and efficient approach to track subtle, clinically meaningful change with aging. Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Electrooptical adaptive switching network for the hypercube computer

NASA Technical Reports Server (NTRS)

Chow, E.; Peterson, J.

1988-01-01

An all-optical network design for the hyperswitch network using regular free-space interconnects between electronic processor nodes is presented. The adaptive routing model used is described, and an adaptive routing control example is presented. The design demonstrates that existing electrooptical techniques are sufficient for implementing efficient parallel architectures without the need for more complex means of implementing arbitrary interconnection schemes. The electrooptical hyperswitch network significantly improves the communication performance of the hypercube computer.

Medical image denoising via optimal implementation of non-local means on hybrid parallel architecture.

PubMed

Nguyen, Tuan-Anh; Nakib, Amir; Nguyen, Huy-Nam

2016-06-01

The Non-local means denoising filter has been established as gold standard for image denoising problem in general and particularly in medical imaging due to its efficiency. However, its computation time limited its applications in real world application, especially in medical imaging. In this paper, a distributed version on parallel hybrid architecture is proposed to solve the computation time problem and a new method to compute the filters' coefficients is also proposed, where we focused on the implementation and the enhancement of filters' parameters via taking the neighborhood of the current voxel more accurately into account. In terms of implementation, our key contribution consists in reducing the number of shared memory accesses. The different tests of the proposed method were performed on the brain-web database for different levels of noise. Performances and the sensitivity were quantified in terms of speedup, peak signal to noise ratio, execution time, the number of floating point operations. The obtained results demonstrate the efficiency of the proposed method. Moreover, the implementation is compared to that of other techniques, recently published in the literature. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A filtering approach to edge preserving MAP estimation of images.

PubMed

Humphrey, David; Taubman, David

2011-05-01

The authors present a computationally efficient technique for maximum a posteriori (MAP) estimation of images in the presence of both blur and noise. The image is divided into statistically independent regions. Each region is modelled with a WSS Gaussian prior. Classical Wiener filter theory is used to generate a set of convex sets in the solution space, with the solution to the MAP estimation problem lying at the intersection of these sets. The proposed algorithm uses an underlying segmentation of the image, and a means of determining the segmentation and refining it are described. The algorithm is suitable for a range of image restoration problems, as it provides a computationally efficient means to deal with the shortcomings of Wiener filtering without sacrificing the computational simplicity of the filtering approach. The algorithm is also of interest from a theoretical viewpoint as it provides a continuum of solutions between Wiener filtering and Inverse filtering depending upon the segmentation used. We do not attempt to show here that the proposed method is the best general approach to the image reconstruction problem. However, related work referenced herein shows excellent performance in the specific problem of demosaicing.

Developing the fuzzy c-means clustering algorithm based on maximum entropy for multitarget tracking in a cluttered environment

NASA Astrophysics Data System (ADS)

Chen, Xiao; Li, Yaan; Yu, Jing; Li, Yuxing

2018-01-01

For fast and more effective implementation of tracking multiple targets in a cluttered environment, we propose a multiple targets tracking (MTT) algorithm called maximum entropy fuzzy c-means clustering joint probabilistic data association that combines fuzzy c-means clustering and the joint probabilistic data association (PDA) algorithm. The algorithm uses the membership value to express the probability of the target originating from measurement. The membership value is obtained through fuzzy c-means clustering objective function optimized by the maximum entropy principle. When considering the effect of the public measurement, we use a correction factor to adjust the association probability matrix to estimate the state of the target. As this algorithm avoids confirmation matrix splitting, it can solve the high computational load problem of the joint PDA algorithm. The results of simulations and analysis conducted for tracking neighbor parallel targets and cross targets in a different density cluttered environment show that the proposed algorithm can realize MTT quickly and efficiently in a cluttered environment. Further, the performance of the proposed algorithm remains constant with increasing process noise variance. The proposed algorithm has the advantages of efficiency and low computational load, which can ensure optimum performance when tracking multiple targets in a dense cluttered environment.

Time-variant random interval natural frequency analysis of structures

NASA Astrophysics Data System (ADS)

Wu, Binhua; Wu, Di; Gao, Wei; Song, Chongmin

2018-02-01

This paper presents a new robust method namely, unified interval Chebyshev-based random perturbation method, to tackle hybrid random interval structural natural frequency problem. In the proposed approach, random perturbation method is implemented to furnish the statistical features (i.e., mean and standard deviation) and Chebyshev surrogate model strategy is incorporated to formulate the statistical information of natural frequency with regards to the interval inputs. The comprehensive analysis framework combines the superiority of both methods in a way that computational cost is dramatically reduced. This presented method is thus capable of investigating the day-to-day based time-variant natural frequency of structures accurately and efficiently under concrete intrinsic creep effect with probabilistic and interval uncertain variables. The extreme bounds of the mean and standard deviation of natural frequency are captured through the embedded optimization strategy within the analysis procedure. Three particularly motivated numerical examples with progressive relationship in perspective of both structure type and uncertainty variables are demonstrated to justify the computational applicability, accuracy and efficiency of the proposed method.

Image Segmentation Method Using Fuzzy C Mean Clustering Based on Multi-Objective Optimization

NASA Astrophysics Data System (ADS)

Chen, Jinlin; Yang, Chunzhi; Xu, Guangkui; Ning, Li

2018-04-01

Image segmentation is not only one of the hottest topics in digital image processing, but also an important part of computer vision applications. As one kind of image segmentation algorithms, fuzzy C-means clustering is an effective and concise segmentation algorithm. However, the drawback of FCM is that it is sensitive to image noise. To solve the problem, this paper designs a novel fuzzy C-mean clustering algorithm based on multi-objective optimization. We add a parameter λ to the fuzzy distance measurement formula to improve the multi-objective optimization. The parameter λ can adjust the weights of the pixel local information. In the algorithm, the local correlation of neighboring pixels is added to the improved multi-objective mathematical model to optimize the clustering cent. Two different experimental results show that the novel fuzzy C-means approach has an efficient performance and computational time while segmenting images by different type of noises.

Multitasking a three-dimensional Navier-Stokes algorithm on the Cray-2

NASA Technical Reports Server (NTRS)

Swisshelm, Julie M.

1989-01-01

A three-dimensional computational aerodynamics algorithm has been multitasked for efficient parallel execution on the Cray-2. It provides a means for examining the multitasking performance of a complete CFD application code. An embedded zonal multigrid scheme is used to solve the Reynolds-averaged Navier-Stokes equations for an internal flow model problem. The explicit nature of each component of the method allows a spatial partitioning of the computational domain to achieve a well-balanced task load for MIMD computers with vector-processing capability. Experiments have been conducted with both two- and three-dimensional multitasked cases. The best speedup attained by an individual task group was 3.54 on four processors of the Cray-2, while the entire solver yielded a speedup of 2.67 on four processors for the three-dimensional case. The multiprocessing efficiency of various types of computational tasks is examined, performance on two Cray-2s with different memory access speeds is compared, and extrapolation to larger problems is discussed.

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.

Estimating Skin Cancer Risk: Evaluating Mobile Computer-Adaptive Testing.

PubMed

Djaja, Ngadiman; Janda, Monika; Olsen, Catherine M; Whiteman, David C; Chien, Tsair-Wei

2016-01-22

Response burden is a major detriment to questionnaire completion rates. Computer adaptive testing may offer advantages over non-adaptive testing, including reduction of numbers of items required for precise measurement. Our aim was to compare the efficiency of non-adaptive (NAT) and computer adaptive testing (CAT) facilitated by Partial Credit Model (PCM)-derived calibration to estimate skin cancer risk. We used a random sample from a population-based Australian cohort study of skin cancer risk (N=43,794). All 30 items of the skin cancer risk scale were calibrated with the Rasch PCM. A total of 1000 cases generated following a normal distribution (mean [SD] 0 [1]) were simulated using three Rasch models with three fixed-item (dichotomous, rating scale, and partial credit) scenarios, respectively. We calculated the comparative efficiency and precision of CAT and NAT (shortening of questionnaire length and the count difference number ratio less than 5% using independent t tests). We found that use of CAT led to smaller person standard error of the estimated measure than NAT, with substantially higher efficiency but no loss of precision, reducing response burden by 48%, 66%, and 66% for dichotomous, Rating Scale Model, and PCM models, respectively. CAT-based administrations of the skin cancer risk scale could substantially reduce participant burden without compromising measurement precision. A mobile computer adaptive test was developed to help people efficiently assess their skin cancer risk.

Effects of combined dimension reduction and tabulation on the simulations of a turbulent premixed flame using a large-eddy simulation/probability density function method

NASA Astrophysics Data System (ADS)

Kim, Jeonglae; Pope, Stephen B.

2014-05-01

A turbulent lean-premixed propane-air flame stabilised by a triangular cylinder as a flame-holder is simulated to assess the accuracy and computational efficiency of combined dimension reduction and tabulation of chemistry. The computational condition matches the Volvo rig experiments. For the reactive simulation, the Lagrangian Large-Eddy Simulation/Probability Density Function (LES/PDF) formulation is used. A novel two-way coupling approach between LES and PDF is applied to obtain resolved density to reduce its statistical fluctuations. Composition mixing is evaluated by the modified Interaction-by-Exchange with the Mean (IEM) model. A baseline case uses In Situ Adaptive Tabulation (ISAT) to calculate chemical reactions efficiently. Its results demonstrate good agreement with the experimental measurements in turbulence statistics, temperature, and minor species mass fractions. For dimension reduction, 11 and 16 represented species are chosen and a variant of Rate Controlled Constrained Equilibrium (RCCE) is applied in conjunction with ISAT to each case. All the quantities in the comparison are indistinguishable from the baseline results using ISAT only. The combined use of RCCE/ISAT reduces the computational time for chemical reaction by more than 50%. However, for the current turbulent premixed flame, chemical reaction takes only a minor portion of the overall computational cost, in contrast to non-premixed flame simulations using LES/PDF, presumably due to the restricted manifold of purely premixed flame in the composition space. Instead, composition mixing is the major contributor to cost reduction since the mean-drift term, which is computationally expensive, is computed for the reduced representation. Overall, a reduction of more than 15% in the computational cost is obtained.

The ToxCast Chemical Prioritization Program at the US EPA (UCLA Molecular Toxicology Program)

EPA Science Inventory

To meet the needs of chemical regulators reviewing large numbers of data-poor chemicals for safety, the EPA's National Center for Computational Toxicology is developing a means of efficiently testing thousands of compounds for potential toxicity. High-throughput bioactivity profi...

Parallel computing method for simulating hydrological processesof large rivers under climate change

NASA Astrophysics Data System (ADS)

Wang, H.; Chen, Y.

2016-12-01

Climate change is one of the proverbial global environmental problems in the world.Climate change has altered the watershed hydrological processes in time and space distribution, especially in worldlarge rivers.Watershed hydrological process simulation based on physically based distributed hydrological model can could have better results compared with the lumped models.However, watershed hydrological process simulation includes large amount of calculations, especially in large rivers, thus needing huge computing resources that may not be steadily available for the researchers or at high expense, this seriously restricted the research and application. To solve this problem, the current parallel method are mostly parallel computing in space and time dimensions.They calculate the natural features orderly thatbased on distributed hydrological model by grid (unit, a basin) from upstream to downstream.This articleproposes ahigh-performancecomputing method of hydrological process simulation with high speedratio and parallel efficiency.It combinedthe runoff characteristics of time and space of distributed hydrological model withthe methods adopting distributed data storage, memory database, distributed computing, parallel computing based on computing power unit.The method has strong adaptability and extensibility,which means it canmake full use of the computing and storage resources under the condition of limited computing resources, and the computing efficiency can be improved linearly with the increase of computing resources .This method can satisfy the parallel computing requirements ofhydrological process simulation in small, medium and large rivers.

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

Aliaga, José I., E-mail: aliaga@uji.es; Alonso, Pedro; Badía, José M.

We introduce a new iterative Krylov subspace-based eigensolver for the simulation of macromolecular motions on desktop multithreaded platforms equipped with multicore processors and, possibly, a graphics accelerator (GPU). The method consists of two stages, with the original problem first reduced into a simpler band-structured form by means of a high-performance compute-intensive procedure. This is followed by a memory-intensive but low-cost Krylov iteration, which is off-loaded to be computed on the GPU by means of an efficient data-parallel kernel. The experimental results reveal the performance of the new eigensolver. Concretely, when applied to the simulation of macromolecules with a few thousandsmore » degrees of freedom and the number of eigenpairs to be computed is small to moderate, the new solver outperforms other methods implemented as part of high-performance numerical linear algebra packages for multithreaded architectures.« less

Computer code for preliminary sizing analysis of axial-flow turbines

NASA Technical Reports Server (NTRS)

Glassman, Arthur J.

1992-01-01

This mean diameter flow analysis uses a stage average velocity diagram as the basis for the computational efficiency. Input design requirements include power or pressure ratio, flow rate, temperature, pressure, and rotative speed. Turbine designs are generated for any specified number of stages and for any of three types of velocity diagrams (symmetrical, zero exit swirl, or impulse) or for any specified stage swirl split. Exit turning vanes can be included in the design. The program output includes inlet and exit annulus dimensions, exit temperature and pressure, total and static efficiencies, flow angles, and last stage absolute and relative Mach numbers. An analysis is presented along with a description of the computer program input and output with sample cases. The analysis and code presented herein are modifications of those described in NASA-TN-D-6702. These modifications improve modeling rigor and extend code applicability.

Hospital mainframe computer documentation of pharmacist interventions.

PubMed

Schumock, G T; Guenette, A J; Clark, T; McBride, J M

1993-07-01

The hospital mainframe computer pharmacist intervention documentation system described has successfully facilitated the recording, communication, analysis, and reporting of interventions at our hospital. It has proven to be time efficient, accessible, and user-friendly from the standpoint of both the pharmacist and administrator. The advantages of this system greatly outweigh manual documentation and justify the initial time investment in its design and development. In the future, it is hoped that the system can have even broader impact. Intervention/recommendations documented can be made accessible to medical and nursing staff, and as such further increase interdepartmental communication. As pharmacists embrace the pharmaceutical care mandate, documenting interventions in patient care will continue to grow in importance. Complete documentation is essential if pharmacists are to assume responsibility for patient outcomes. With time being an ever-increasing premium, and with economic and human resources dwindling, an efficient and effective means of recording and tracking pharmacist interventions will become imperative for survival in the fiscally challenged health care arena. Documentation of pharmacist intervention using a hospital mainframe computer at UIH has proven both efficient and effective.

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.

An implicit scheme with memory reduction technique for steady state solutions of DVBE in all flow regimes

NASA Astrophysics Data System (ADS)

Yang, L. M.; Shu, C.; Yang, W. M.; Wu, J.

2018-04-01

High consumption of memory and computational effort is the major barrier to prevent the widespread use of the discrete velocity method (DVM) in the simulation of flows in all flow regimes. To overcome this drawback, an implicit DVM with a memory reduction technique for solving a steady discrete velocity Boltzmann equation (DVBE) is presented in this work. In the method, the distribution functions in the whole discrete velocity space do not need to be stored, and they are calculated from the macroscopic flow variables. As a result, its memory requirement is in the same order as the conventional Euler/Navier-Stokes solver. In the meantime, it is more efficient than the explicit DVM for the simulation of various flows. To make the method efficient for solving flow problems in all flow regimes, a prediction step is introduced to estimate the local equilibrium state of the DVBE. In the prediction step, the distribution function at the cell interface is calculated by the local solution of DVBE. For the flow simulation, when the cell size is less than the mean free path, the prediction step has almost no effect on the solution. However, when the cell size is much larger than the mean free path, the prediction step dominates the solution so as to provide reasonable results in such a flow regime. In addition, to further improve the computational efficiency of the developed scheme in the continuum flow regime, the implicit technique is also introduced into the prediction step. Numerical results showed that the proposed implicit scheme can provide reasonable results in all flow regimes and increase significantly the computational efficiency in the continuum flow regime as compared with the existing DVM solvers.

Findings in resting-state fMRI by differences from K-means clustering.

PubMed

Chyzhyk, Darya; Graña, Manuel

2014-01-01

Resting state fMRI has growing number of studies with diverse aims, always centered on some kind of functional connectivity biomarker obtained from correlation regarding seed regions, or by analytical decomposition of the signal towards the localization of the spatial distribution of functional connectivity patterns. In general, studies are computationally costly and very sensitive to noise and preprocessing of data. In this paper we consider clustering by K-means as a exploratory procedure which can provide some results with little computational effort, due to efficient implementations that are readily available. We demonstrate the approach on a dataset of schizophrenia patients, finding differences between patients with and without auditory hallucinations.

Adolescent substance use screening in primary care: validity of computer self-administered vs. clinician-administered screening

PubMed Central

Harris, Sion Kim; Knight, John R; Van Hook, Shari; Sherritt, Lon; Brooks, Traci; Kulig, John W; Nordt, Christina; Saitz, Richard

2015-01-01

Background Computer self-administration may help busy pediatricians’ offices increase adolescent substance use screening rates efficiently and effectively, if proven to yield valid responses. The CRAFFT screening protocol for adolescents has demonstrated validity as an interview, but a computer self-entry approach needs validity testing. The aim of this study was to evaluate the criterion validity and time efficiency of a computerized adolescent substance use screening protocol implemented by self-administration or clinician-administration. Methods 12- to 17-year-old patients coming for routine care at three primary care clinics completed the computerized screen by both self-administration and clinician-administration during their visit. To account for order effects, we randomly assigned participants to self-administer the screen either before or after seeing their clinician. Both were conducted using a tablet computer and included identical items (any past-12-month use of tobacco, alcohol, drugs; past-3-months frequency of each; and six CRAFFT items). The criterion measure for substance use was the Timeline Follow-Back, and for alcohol/drug use disorder, the Adolescent Diagnostic Interview, both conducted by confidential research assistant-interview after the visit. Tobacco dependence risk was assessed with the self-administered Hooked on Nicotine Checklist (HONC). Analyses accounted for the multi-site cluster sampling design. Results Among 136 participants, mean age was 15.0±1.5 yrs, 54% were girls, 53% were Black or Hispanic, and 67% had ≥3 prior visits with their clinician. Twenty-seven percent reported any substance use (including tobacco) in the past 12 months, 7% met criteria for an alcohol or cannabis use disorder, and 4% were HONC-positive. Sensitivity/specificity of the screener were high for detecting past-12-month use or disorder and did not differ between computer and clinician. Mean completion time was 49 seconds (95%CI 44-54) for computer and 74 seconds (95%CI 68-87) for clinician (paired comparison p<0.001). Conclusions Substance use screening by computer self-entry is a valid and time-efficient alternative to clinician-administered screening. PMID:25774878

The multimedia computer for low-literacy patient education: a pilot project of cancer risk perceptions.

PubMed

Wofford, J L; Currin, D; Michielutte, R; Wofford, M M

2001-04-20

Inadequate reading literacy is a major barrier to better educating patients. Despite its high prevalence, practical solutions for detecting and overcoming low literacy in a busy clinical setting remain elusive. In exploring the potential role for the multimedia computer in improving office-based patient education, we compared the accuracy of information captured from audio-computer interviewing of patients with that obtained from subsequent verbal questioning. Adult medicine clinic, urban community health center Convenience sample of patients awaiting clinic appointments (n = 59). Exclusion criteria included obvious psychoneurologic impairment or primary language other than English. A multimedia computer presentation that used audio-computer interviewing with localized imagery and voices to elicit responses to 4 questions on prior computer use and cancer risk perceptions. Three patients refused or were unable to interact with the computer at all, and 3 patients required restarting the presentation from the beginning but ultimately completed the computerized survey. Of the 51 evaluable patients (72.5% African-American, 66.7% female, mean age 47.5 [+/- 18.1]), the mean time in the computer presentation was significantly longer with older age and with no prior computer use but did not differ by gender or race. Despite a high proportion of no prior computer use (60.8%), there was a high rate of agreement (88.7% overall) between audio-computer interviewing and subsequent verbal questioning. Audio-computer interviewing is feasible in this urban community health center. The computer offers a partial solution for overcoming literacy barriers inherent in written patient education materials and provides an efficient means of data collection that can be used to better target patients' educational needs.

CFD comparison with centrifugal compressor measurements on a wide operating range

NASA Astrophysics Data System (ADS)

Le Sausse, P.; Fabrie, P.; Arnou, D.; Clunet, F.

2013-04-01

Centrifugal compressors are widely used in industrial applications thanks to their high efficiency. They are able to provide a wide operating range before reaching the flow barrier or surge limits. Performances and range are described by compressor maps obtained experimentally. After a description of performance test rig, this article compares measured centrifugal compressor performances with computational fluid dynamics results. These computations are performed at steady conditions with R134a refrigerant as fluid. Navier-Stokes equations, coupled with k-ɛ turbulence model, are solved by the commercial software ANSYS-CFX by means of volume finite method. Input conditions are varied in order to calculate several speed lines. Theoretical isentropic efficiency and theoretical surge line are finally compared to experimental data.

Efficient approach to obtain free energy gradient using QM/MM MD simulation

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

Asada, Toshio; Koseki, Shiro; The Research Institute for Molecular Electronic Devices

2015-12-31

The efficient computational approach denoted as charge and atom dipole response kernel (CDRK) model to consider polarization effects of the quantum mechanical (QM) region is described using the charge response and the atom dipole response kernels for free energy gradient (FEG) calculations in the quantum mechanical/molecular mechanical (QM/MM) method. CDRK model can reasonably reproduce energies and also energy gradients of QM and MM atoms obtained by expensive QM/MM calculations in a drastically reduced computational time. This model is applied on the acylation reaction in hydrated trypsin-BPTI complex to optimize the reaction path on the free energy surface by means ofmore » FEG and the nudged elastic band (NEB) method.« less

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…

Computational methods for structural load and resistance modeling

NASA Technical Reports Server (NTRS)

Thacker, B. H.; Millwater, H. R.; Harren, S. V.

1991-01-01

An automated capability for computing structural reliability considering uncertainties in both load and resistance variables is presented. The computations are carried out using an automated Advanced Mean Value iteration algorithm (AMV +) with performance functions involving load and resistance variables obtained by both explicit and implicit methods. A complete description of the procedures used is given as well as several illustrative examples, verified by Monte Carlo Analysis. In particular, the computational methods described in the paper are shown to be quite accurate and efficient for a material nonlinear structure considering material damage as a function of several primitive random variables. The results show clearly the effectiveness of the algorithms for computing the reliability of large-scale structural systems with a maximum number of resolutions.

Multi-Party Privacy-Preserving Set Intersection with Quasi-Linear Complexity

NASA Astrophysics Data System (ADS)

Cheon, Jung Hee; Jarecki, Stanislaw; Seo, Jae Hong

Secure computation of the set intersection functionality allows n parties to find the intersection between their datasets without revealing anything else about them. An efficient protocol for such a task could have multiple potential applications in commerce, health care, and security. However, all currently known secure set intersection protocols for n>2 parties have computational costs that are quadratic in the (maximum) number of entries in the dataset contributed by each party, making secure computation of the set intersection only practical for small datasets. In this paper, we describe the first multi-party protocol for securely computing the set intersection functionality with both the communication and the computation costs that are quasi-linear in the size of the datasets. For a fixed security parameter, our protocols require O(n2k) bits of communication and Õ(n2k) group multiplications per player in the malicious adversary setting, where k is the size of each dataset. Our protocol follows the basic idea of the protocol proposed by Kissner and Song, but we gain efficiency by using different representations of the polynomials associated with users' datasets and careful employment of algorithms that interpolate or evaluate polynomials on multiple points more efficiently. Moreover, the proposed protocol is robust. This means that the protocol outputs the desired result even if some corrupted players leave during the execution of the protocol.

Design synthesis and optimization of permanent magnet synchronous machines based on computationally-efficient finite element analysis

NASA Astrophysics Data System (ADS)

Sizov, Gennadi Y.

In this dissertation, a model-based multi-objective optimal design of permanent magnet ac machines, supplied by sine-wave current regulated drives, is developed and implemented. The design procedure uses an efficient electromagnetic finite element-based solver to accurately model nonlinear material properties and complex geometric shapes associated with magnetic circuit design. Application of an electromagnetic finite element-based solver allows for accurate computation of intricate performance parameters and characteristics. The first contribution of this dissertation is the development of a rapid computational method that allows accurate and efficient exploration of large multi-dimensional design spaces in search of optimum design(s). The computationally efficient finite element-based approach developed in this work provides a framework of tools that allow rapid analysis of synchronous electric machines operating under steady-state conditions. In the developed modeling approach, major steady-state performance parameters such as, winding flux linkages and voltages, average, cogging and ripple torques, stator core flux densities, core losses, efficiencies and saturated machine winding inductances, are calculated with minimum computational effort. In addition, the method includes means for rapid estimation of distributed stator forces and three-dimensional effects of stator and/or rotor skew on the performance of the machine. The second contribution of this dissertation is the development of the design synthesis and optimization method based on a differential evolution algorithm. The approach relies on the developed finite element-based modeling method for electromagnetic analysis and is able to tackle large-scale multi-objective design problems using modest computational resources. Overall, computational time savings of up to two orders of magnitude are achievable, when compared to current and prevalent state-of-the-art methods. These computational savings allow one to expand the optimization problem to achieve more complex and comprehensive design objectives. The method is used in the design process of several interior permanent magnet industrial motors. The presented case studies demonstrate that the developed finite element-based approach practically eliminates the need for using less accurate analytical and lumped parameter equivalent circuit models for electric machine design optimization. The design process and experimental validation of the case-study machines are detailed in the dissertation.

Sensitivity Analysis and Optimization of Enclosure Radiation with Applications to Crystal Growth

NASA Technical Reports Server (NTRS)

Tiller, Michael M.

1995-01-01

In engineering, simulation software is often used as a convenient means for carrying out experiments to evaluate physical systems. The benefit of using simulations as 'numerical' experiments is that the experimental conditions can be easily modified and repeated at much lower cost than the comparable physical experiment. The goal of these experiments is to 'improve' the process or result of the experiment. In most cases, the computational experiments employ the same trial and error approach as their physical counterparts. When using this approach for complex systems, the cause and effect relationship of the system may never be fully understood and efficient strategies for improvement never utilized. However, it is possible when running simulations to accurately and efficiently determine the sensitivity of the system results with respect to simulation to accurately and efficiently determine the sensitivity of the system results with respect to simulation parameters (e.g., initial conditions, boundary conditions, and material properties) by manipulating the underlying computations. This results in a better understanding of the system dynamics and gives us efficient means to improve processing conditions. We begin by discussing the steps involved in performing simulations. Then we consider how sensitivity information about simulation results can be obtained and ways this information may be used to improve the process or result of the experiment. Next, we discuss optimization and the efficient algorithms which use sensitivity information. We draw on all this information to propose a generalized approach for integrating simulation and optimization, with an emphasis on software programming issues. After discussing our approach to simulation and optimization we consider an application involving crystal growth. This application is interesting because it includes radiative heat transfer. We discuss the computation of radiative new factors and the impact this mode of heat transfer has on our approach. Finally, we will demonstrate the results of our optimization.

A hydrological emulator for global applications - HE v1.0.0

NASA Astrophysics Data System (ADS)

Liu, Yaling; Hejazi, Mohamad; Li, Hongyi; Zhang, Xuesong; Leng, Guoyong

2018-03-01

While global hydrological models (GHMs) are very useful in exploring water resources and interactions between the Earth and human systems, their use often requires numerous model inputs, complex model calibration, and high computation costs. To overcome these challenges, we construct an efficient open-source and ready-to-use hydrological emulator (HE) that can mimic complex GHMs at a range of spatial scales (e.g., basin, region, globe). More specifically, we construct both a lumped and a distributed scheme of the HE based on the monthly abcd model to explore the tradeoff between computational cost and model fidelity. Model predictability and computational efficiency are evaluated in simulating global runoff from 1971 to 2010 with both the lumped and distributed schemes. The results are compared against the runoff product from the widely used Variable Infiltration Capacity (VIC) model. Our evaluation indicates that the lumped and distributed schemes present comparable results regarding annual total quantity, spatial pattern, and temporal variation of the major water fluxes (e.g., total runoff, evapotranspiration) across the global 235 basins (e.g., correlation coefficient r between the annual total runoff from either of these two schemes and the VIC is > 0.96), except for several cold (e.g., Arctic, interior Tibet), dry (e.g., North Africa) and mountainous (e.g., Argentina) regions. Compared against the monthly total runoff product from the VIC (aggregated from daily runoff), the global mean Kling-Gupta efficiencies are 0.75 and 0.79 for the lumped and distributed schemes, respectively, with the distributed scheme better capturing spatial heterogeneity. Notably, the computation efficiency of the lumped scheme is 2 orders of magnitude higher than the distributed one and 7 orders more efficient than the VIC model. A case study of uncertainty analysis for the world's 16 basins with top annual streamflow is conducted using 100 000 model simulations, and it demonstrates the lumped scheme's extraordinary advantage in computational efficiency. Our results suggest that the revised lumped abcd model can serve as an efficient and reasonable HE for complex GHMs and is suitable for broad practical use, and the distributed scheme is also an efficient alternative if spatial heterogeneity is of more interest.

Automated land-use mapping from spacecraft data. [Oakland County, Michigan

NASA Technical Reports Server (NTRS)

Chase, P. E. (Principal Investigator); Rogers, R. H.; Reed, L. E.

1974-01-01

The author has identified the following significant results. In response to the need for a faster, more economical means of producing land use maps, this study evaluated the suitability of using ERTS-1 computer compatible tape (CCT) data as a basis for automatic mapping. Significant findings are: (1) automatic classification accuracy greater than 90% is achieved on categories of deep and shallow water, tended grass, rangeland, extractive (bare earth), urban, forest land, and nonforested wet lands; (2) computer-generated printouts by target class provide a quantitative measure of land use; and (3) the generation of map overlays showing land use from ERTS-1 CCTs offers a significant breakthrough in the rate at which land use maps are generated. Rather than uncorrected classified imagery or computer line printer outputs, the processing results in geometrically-corrected computer-driven pen drawing of land categories, drawn on a transparent material at a scale specified by the operator. These map overlays are economically produced and provide an efficient means of rapidly updating maps showing land use.

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.

Genomic cloud computing: legal and ethical points to consider

PubMed Central

Dove, Edward S; Joly, Yann; Tassé, Anne-Marie; Burton, Paul; Chisholm, Rex; Fortier, Isabel; Goodwin, Pat; Harris, Jennifer; Hveem, Kristian; Kaye, Jane; Kent, Alistair; Knoppers, Bartha Maria; Lindpaintner, Klaus; Little, Julian; Riegman, Peter; Ripatti, Samuli; Stolk, Ronald; Bobrow, Martin; Cambon-Thomsen, Anne; Dressler, Lynn; Joly, Yann; Kato, Kazuto; Knoppers, Bartha Maria; Rodriguez, Laura Lyman; McPherson, Treasa; Nicolás, Pilar; Ouellette, Francis; Romeo-Casabona, Carlos; Sarin, Rajiv; Wallace, Susan; Wiesner, Georgia; Wilson, Julia; Zeps, Nikolajs; Simkevitz, Howard; De Rienzo, Assunta; Knoppers, Bartha M

2015-01-01

The biggest challenge in twenty-first century data-intensive genomic science, is developing vast computer infrastructure and advanced software tools to perform comprehensive analyses of genomic data sets for biomedical research and clinical practice. Researchers are increasingly turning to cloud computing both as a solution to integrate data from genomics, systems biology and biomedical data mining and as an approach to analyze data to solve biomedical problems. Although cloud computing provides several benefits such as lower costs and greater efficiency, it also raises legal and ethical issues. In this article, we discuss three key ‘points to consider' (data control; data security, confidentiality and transfer; and accountability) based on a preliminary review of several publicly available cloud service providers' Terms of Service. These ‘points to consider' should be borne in mind by genomic research organizations when negotiating legal arrangements to store genomic data on a large commercial cloud service provider's servers. Diligent genomic cloud computing means leveraging security standards and evaluation processes as a means to protect data and entails many of the same good practices that researchers should always consider in securing their local infrastructure. PMID:25248396

Genomic cloud computing: legal and ethical points to consider.

PubMed

Dove, Edward S; Joly, Yann; Tassé, Anne-Marie; Knoppers, Bartha M

2015-10-01

The biggest challenge in twenty-first century data-intensive genomic science, is developing vast computer infrastructure and advanced software tools to perform comprehensive analyses of genomic data sets for biomedical research and clinical practice. Researchers are increasingly turning to cloud computing both as a solution to integrate data from genomics, systems biology and biomedical data mining and as an approach to analyze data to solve biomedical problems. Although cloud computing provides several benefits such as lower costs and greater efficiency, it also raises legal and ethical issues. In this article, we discuss three key 'points to consider' (data control; data security, confidentiality and transfer; and accountability) based on a preliminary review of several publicly available cloud service providers' Terms of Service. These 'points to consider' should be borne in mind by genomic research organizations when negotiating legal arrangements to store genomic data on a large commercial cloud service provider's servers. Diligent genomic cloud computing means leveraging security standards and evaluation processes as a means to protect data and entails many of the same good practices that researchers should always consider in securing their local infrastructure.

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.

Decision and function problems based on boson sampling

NASA Astrophysics Data System (ADS)

Nikolopoulos, Georgios M.; Brougham, Thomas

2016-07-01

Boson sampling is a mathematical problem that is strongly believed to be intractable for classical computers, whereas passive linear interferometers can produce samples efficiently. So far, the problem remains a computational curiosity, and the possible usefulness of boson-sampling devices is mainly limited to the proof of quantum supremacy. The purpose of this work is to investigate whether boson sampling can be used as a resource of decision and function problems that are computationally hard, and may thus have cryptographic applications. After the definition of a rather general theoretical framework for the design of such problems, we discuss their solution by means of a brute-force numerical approach, as well as by means of nonboson samplers. Moreover, we estimate the sample sizes required for their solution by passive linear interferometers, and it is shown that they are independent of the size of the Hilbert space.

Variational calculation of macrostate transition rates

NASA Astrophysics Data System (ADS)

Ulitsky, Alex; Shalloway, David

1998-08-01

We develop the macrostate variational method (MVM) for computing reaction rates of diffusive conformational transitions in multidimensional systems by a variational coarse-grained "macrostate" decomposition of the Smoluchowski equation. MVM uses multidimensional Gaussian packets to identify and focus computational effort on the "transition region," a localized, self-consistently determined region in conformational space positioned roughly between the macrostates. It also determines the "transition direction" which optimally specifies the projected potential of mean force for mean first-passage time calculations. MVM is complementary to variational transition state theory in that it can efficiently solve multidimensional problems but does not accommodate memory-friction effects. It has been tested on model 1- and 2-dimensional potentials and on the 12-dimensional conformational transition between the isoforms of a microcluster of six-atoms having only van der Waals interactions. Comparison with Brownian dynamics calculations shows that MVM obtains equivalent results at a fraction of the computational cost.

VLSI implementation of a new LMS-based algorithm for noise removal in ECG signal

NASA Astrophysics Data System (ADS)

Satheeskumaran, S.; Sabrigiriraj, M.

2016-06-01

Least mean square (LMS)-based adaptive filters are widely deployed for removing artefacts in electrocardiogram (ECG) due to less number of computations. But they posses high mean square error (MSE) under noisy environment. The transform domain variable step-size LMS algorithm reduces the MSE at the cost of computational complexity. In this paper, a variable step-size delayed LMS adaptive filter is used to remove the artefacts from the ECG signal for improved feature extraction. The dedicated digital Signal processors provide fast processing, but they are not flexible. By using field programmable gate arrays, the pipelined architectures can be used to enhance the system performance. The pipelined architecture can enhance the operation efficiency of the adaptive filter and save the power consumption. This technique provides high signal-to-noise ratio and low MSE with reduced computational complexity; hence, it is a useful method for monitoring patients with heart-related problem.

Time-Efficiency Analysis Comparing Digital and Conventional Workflows for Implant Crowns: A Prospective Clinical Crossover Trial.

PubMed

Joda, Tim; Brägger, Urs

2015-01-01

To compare time-efficiency in the production of implant crowns using a digital workflow versus the conventional pathway. This prospective clinical study used a crossover design that included 20 study participants receiving single-tooth replacements in posterior sites. Each patient received a customized titanium abutment plus a computer-aided design/computer-assisted manufacture (CAD/CAM) zirconia suprastructure (for those in the test group, using digital workflow) and a standardized titanium abutment plus a porcelain-fused-to-metal crown (for those in the control group, using a conventional pathway). The start of the implant prosthetic treatment was established as the baseline. Time-efficiency analysis was defined as the primary outcome, and was measured for every single clinical and laboratory work step in minutes. Statistical analysis was calculated with the Wilcoxon rank sum test. All crowns could be provided within two clinical appointments, independent of the manufacturing process. The mean total production time, as the sum of clinical plus laboratory work steps, was significantly different. The mean ± standard deviation (SD) time was 185.4 ± 17.9 minutes for the digital workflow process and 223.0 ± 26.2 minutes for the conventional pathway (P = .0001). Therefore, digital processing for overall treatment was 16% faster. Detailed analysis for the clinical treatment revealed a significantly reduced mean ± SD chair time of 27.3 ± 3.4 minutes for the test group compared with 33.2 ± 4.9 minutes for the control group (P = .0001). Similar results were found for the mean laboratory work time, with a significant decrease of 158.1 ± 17.2 minutes for the test group vs 189.8 ± 25.3 minutes for the control group (P = .0001). Only a few studies have investigated efficiency parameters of digital workflows compared with conventional pathways in implant dental medicine. This investigation shows that the digital workflow seems to be more time-efficient than the established conventional production pathway for fixed implant-supported crowns. Both clinical chair time and laboratory manufacturing steps could be effectively shortened with the digital process of intraoral scanning plus CAD/CAM technology.

An efficient method for the calculation of mean extinction. I - The analyticity of the complex extinction efficiency of homogeneous spheres

NASA Astrophysics Data System (ADS)

Xing, Zhang-Fan; Greenberg, J. M.

1992-11-01

Results of an investigation of the analyticity of the complex extinction efficiency Q-tilde(ext) in different parameter domains are presented. In the size parameter domain, x = omega(a/c), numerical Hilbert transforms are used to study the analyticity properties of Q-tilde(ext) for homogeneous spheres. Q-tilde(ext) is found to be analytic in the entire lower complex x-tilde-plane when the refractive index, m, is fixed as a real constant (pure scattering) or infinity (perfect conductor); poles, however, appear in the left side of the lower complex x-tilde-plane as m becomes complex. The computation of the mean extinction produced by an extended size distribution of particles may be conveniently and accurately approximated using only a few values of the complex extinction evaluated in the complex plane.

Numerical studies of the deposition of material released from fixed and rotary wing aircraft

NASA Technical Reports Server (NTRS)

Bilanin, A. J.; Teske, M. E.

1984-01-01

The computer code AGDISP (AGricultural DISPersal) has been developed to predict the deposition of material released from fixed and rotary wing aircraft in a single-pass, computationally efficient manner. The formulation of the code is novel in that the mean particle trajectory and the variance about the mean resulting from turbulent fluid fluctuations are simultaneously predicted. The code presently includes the capability of assessing the influence of neutral atmospheric conditions, inviscid wake vortices, particle evaporation, plant canopy and terrain on the deposition pattern. In this report, the equations governing the motion of aerially released particles are developed, including a description of the evaporation model used. A series of case studies, using AGDISP, are included.

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

General Training System; GENTRAS. Final Report.

ERIC Educational Resources Information Center

International Business Machines Corp., Gaithersburg, MD. Federal Systems Div.

GENTRAS (General Training System) is a computer-based training model for the Marine Corps which makes use of a systems approach. The model defines the skill levels applicable for career growth and classifies and defines the training needed for this growth. It also provides a training cost subsystem which will provide a more efficient means of…

Semantic Grammar: An Engineering Technique for Constructing Natural Language Understanding Systems.

ERIC Educational Resources Information Center

Burton, Richard R.

In an attempt to overcome the lack of natural means of communication between student and computer, this thesis addresses the problem of developing a system which can understand natural language within an educational problem-solving environment. The nature of the environment imposes efficiency, habitability, self-teachability, and awareness of…

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.

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.

Adaptive CFD schemes for aerospace propulsion

NASA Astrophysics Data System (ADS)

Ferrero, A.; Larocca, F.

2017-05-01

The flow fields which can be observed inside several components of aerospace propulsion systems are characterised by the presence of very localised phenomena (boundary layers, shock waves,...) which can deeply influence the performances of the system. In order to accurately evaluate these effects by means of Computational Fluid Dynamics (CFD) simulations, it is necessary to locally refine the computational mesh. In this way the degrees of freedom related to the discretisation are focused in the most interesting regions and the computational cost of the simulation remains acceptable. In the present work, a discontinuous Galerkin (DG) discretisation is used to numerically solve the equations which describe the flow field. The local nature of the DG reconstruction makes it possible to efficiently exploit several adaptive schemes in which the size of the elements (h-adaptivity) and the order of reconstruction (p-adaptivity) are locally changed. After a review of the main adaptation criteria, some examples related to compressible flows in turbomachinery are presented. An hybrid hp-adaptive algorithm is also proposed and compared with a standard h-adaptive scheme in terms of computational efficiency.

A Scatter-Based Prototype Framework and Multi-Class Extension of Support Vector Machines

PubMed Central

Jenssen, Robert; Kloft, Marius; Zien, Alexander; Sonnenburg, Sören; Müller, Klaus-Robert

2012-01-01

We provide a novel interpretation of the dual of support vector machines (SVMs) in terms of scatter with respect to class prototypes and their mean. As a key contribution, we extend this framework to multiple classes, providing a new joint Scatter SVM algorithm, at the level of its binary counterpart in the number of optimization variables. This enables us to implement computationally efficient solvers based on sequential minimal and chunking optimization. As a further contribution, the primal problem formulation is developed in terms of regularized risk minimization and the hinge loss, revealing the score function to be used in the actual classification of test patterns. We investigate Scatter SVM properties related to generalization ability, computational efficiency, sparsity and sensitivity maps, and report promising results. PMID:23118845

Particle Hydrodynamics with Material Strength for Multi-Layer Orbital Debris Shield Design

NASA Technical Reports Server (NTRS)

Fahrenthold, Eric P.

1999-01-01

Three dimensional simulation of oblique hypervelocity impact on orbital debris shielding places extreme demands on computer resources. Research to date has shown that particle models provide the most accurate and efficient means for computer simulation of shield design problems. In order to employ a particle based modeling approach to the wall plate impact portion of the shield design problem, it is essential that particle codes be augmented to represent strength effects. This report describes augmentation of a Lagrangian particle hydrodynamics code developed by the principal investigator, to include strength effects, allowing for the entire shield impact problem to be represented using a single computer code.

Analysis and application of minimum variance discrete time system identification

NASA Technical Reports Server (NTRS)

Kaufman, H.; Kotob, S.

1975-01-01

An on-line minimum variance parameter identifier is developed which embodies both accuracy and computational efficiency. The formulation results in a linear estimation problem with both additive and multiplicative noise. The resulting filter which utilizes both the covariance of the parameter vector itself and the covariance of the error in identification is proven to be mean square convergent and mean square consistent. The MV parameter identification scheme is then used to construct a stable state and parameter estimation algorithm.

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

Yamankaradeniz, R.; Horuz, I.

In this study, the characteristics of solar assisted heat pump are investigated theoretically and experimentally for clear days during the seven months of the winter season in Istanbul/Turkey. A theoretical model was developed and a computer program was written on this basis. The characteristics such as: daily average collector efficiency and solar radiation, monthly average heat transfer at the condenser, monthly average cooling capacity, the mean COP and the mean COP for total system were examined. The theoretical results were found to be in good agreement with the experimental values.

Interval versions of statistical techniques with applications to environmental analysis, bioinformatics, and privacy in statistical databases

NASA Astrophysics Data System (ADS)

Kreinovich, Vladik; Longpre, Luc; Starks, Scott A.; Xiang, Gang; Beck, Jan; Kandathi, Raj; Nayak, Asis; Ferson, Scott; Hajagos, Janos

2007-02-01

In many areas of science and engineering, it is desirable to estimate statistical characteristics (mean, variance, covariance, etc.) under interval uncertainty. For example, we may want to use the measured values x(t) of a pollution level in a lake at different moments of time to estimate the average pollution level; however, we do not know the exact values x(t)--e.g., if one of the measurement results is 0, this simply means that the actual (unknown) value of x(t) can be anywhere between 0 and the detection limit (DL). We must, therefore, modify the existing statistical algorithms to process such interval data. Such a modification is also necessary to process data from statistical databases, where, in order to maintain privacy, we only keep interval ranges instead of the actual numeric data (e.g., a salary range instead of the actual salary). Most resulting computational problems are NP-hard--which means, crudely speaking, that in general, no computationally efficient algorithm can solve all particular cases of the corresponding problem. In this paper, we overview practical situations in which computationally efficient algorithms exist: e.g., situations when measurements are very accurate, or when all the measurements are done with one (or few) instruments. As a case study, we consider a practical problem from bioinformatics: to discover the genetic difference between the cancer cells and the healthy cells, we must process the measurements results and find the concentrations c and h of a given gene in cancer and in healthy cells. This is a particular case of a general situation in which, to estimate states or parameters which are not directly accessible by measurements, we must solve a system of equations in which coefficients are only known with interval uncertainty. We show that in general, this problem is NP-hard, and we describe new efficient algorithms for solving this problem in practically important situations.

An efficient method for computing unsteady transonic aerodynamics of swept wings with control surfaces

NASA Technical Reports Server (NTRS)

Liu, D. D.; Kao, Y. F.; Fung, K. Y.

1989-01-01

A transonic equivalent strip (TES) method was further developed for unsteady flow computations of arbitrary wing planforms. The TES method consists of two consecutive correction steps to a given nonlinear code such as LTRAN2; namely, the chordwise mean flow correction and the spanwise phase correction. The computation procedure requires direct pressure input from other computed or measured data. Otherwise, it does not require airfoil shape or grid generation for given planforms. To validate the computed results, four swept wings of various aspect ratios, including those with control surfaces, are selected as computational examples. Overall trends in unsteady pressures are established with those obtained by XTRAN3S codes, Isogai's full potential code and measured data by NLR and RAE. In comparison with these methods, the TES has achieved considerable saving in computer time and reasonable accuracy which suggests immediate industrial applications.

Efficient architecture for spike sorting in reconfigurable hardware.

PubMed

Hwang, Wen-Jyi; Lee, Wei-Hao; Lin, Shiow-Jyu; Lai, Sheng-Ying

2013-11-01

This paper presents a novel hardware architecture for fast spike sorting. The architecture is able to perform both the feature extraction and clustering in hardware. The generalized Hebbian algorithm (GHA) and fuzzy C-means (FCM) algorithm are used for feature extraction and clustering, respectively. The employment of GHA allows efficient computation of principal components for subsequent clustering operations. The FCM is able to achieve near optimal clustering for spike sorting. Its performance is insensitive to the selection of initial cluster centers. The hardware implementations of GHA and FCM feature low area costs and high throughput. In the GHA architecture, the computation of different weight vectors share the same circuit for lowering the area costs. Moreover, in the FCM hardware implementation, the usual iterative operations for updating the membership matrix and cluster centroid are merged into one single updating process to evade the large storage requirement. To show the effectiveness of the circuit, the proposed architecture is physically implemented by field programmable gate array (FPGA). It is embedded in a System-on-Chip (SOC) platform for performance measurement. Experimental results show that the proposed architecture is an efficient spike sorting design for attaining high classification correct rate and high speed computation.

Data Structures for Extreme Scale Computing

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

Kahan, Simon

As computing problems of national importance grow, the government meets the increased demand by funding the development of ever larger systems. The overarching goal of the work supported in part by this grant is to increase efficiency of programming and performing computations on these large computing systems. In past work, we have demonstrated that some of these computations once thought to require expensive hardware designs and/or complex, special-purpose programming may be executed efficiently on low-cost commodity cluster computing systems using a general-purpose “latency-tolerant” programming framework. One important developed application of the ideas underlying this framework is graph database technology supportingmore » social network pattern matching used by US intelligence agencies to more quickly identify potential terrorist threats. This database application has been spun out by the Pacific Northwest National Laboratory, a Department of Energy Laboratory, into a commercial start-up, Trovares Inc. We explore an alternative application of the same underlying ideas to a well-studied challenge arising in engineering: solving unstructured sparse linear equations. Solving these equations is key to predicting the behavior of large electronic circuits before they are fabricated. Predicting that behavior ahead of fabrication means that designs can optimized and errors corrected ahead of the expense of manufacture.« less

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.

Free Energy Reconstruction from Logarithmic Mean-Force Dynamics Using Multiple Nonequilibrium Trajectories.

PubMed

Morishita, Tetsuya; Yonezawa, Yasushige; Ito, Atsushi M

2017-07-11

Efficient and reliable estimation of the mean force (MF), the derivatives of the free energy with respect to a set of collective variables (CVs), has been a challenging problem because free energy differences are often computed by integrating the MF. Among various methods for computing free energy differences, logarithmic mean-force dynamics (LogMFD) [ Morishita et al., Phys. Rev. E 2012 , 85 , 066702 ] invokes the conservation law in classical mechanics to integrate the MF, which allows us to estimate the free energy profile along the CVs on-the-fly. Here, we present a method called parallel dynamics, which improves the estimation of the MF by employing multiple replicas of the system and is straightforwardly incorporated in LogMFD or a related method. In the parallel dynamics, the MF is evaluated by a nonequilibrium path-ensemble using the multiple replicas based on the Crooks-Jarzynski nonequilibrium work relation. Thanks to the Crooks relation, realizing full-equilibrium states is no longer mandatory for estimating the MF. Additionally, sampling in the hidden subspace orthogonal to the CV space is highly improved with appropriate weights for each metastable state (if any), which is hardly achievable by typical free energy computational methods. We illustrate how to implement parallel dynamics by combining it with LogMFD, which we call logarithmic parallel dynamics (LogPD). Biosystems of alanine dipeptide and adenylate kinase in explicit water are employed as benchmark systems to which LogPD is applied to demonstrate the effect of multiple replicas on the accuracy and efficiency in estimating the free energy profiles using parallel dynamics.

Space Radiation Transport Methods Development

NASA Technical Reports Server (NTRS)

Wilson, J. W.; Tripathi, R. K.; Qualls, G. D.; Cucinotta, F. A.; Prael, R. E.; Norbury, J. W.; Heinbockel, J. H.; Tweed, J.

2002-01-01

Improved spacecraft shield design requires early entry of radiation constraints into the design process to maximize performance and minimize costs. As a result, we have been investigating high-speed computational procedures to allow shield analysis from the preliminary design concepts to the final design. In particular, we will discuss the progress towards a full three-dimensional and computationally efficient deterministic code for which the current HZETRN evaluates the lowest order asymptotic term. HZETRN is the first deterministic solution to the Boltzmann equation allowing field mapping within the International Space Station (ISS) in tens of minutes using standard Finite Element Method (FEM) geometry common to engineering design practice enabling development of integrated multidisciplinary design optimization methods. A single ray trace in ISS FEM geometry requires 14 milliseconds and severely limits application of Monte Carlo methods to such engineering models. A potential means of improving the Monte Carlo efficiency in coupling to spacecraft geometry is given in terms of reconfigurable computing and could be utilized in the final design as verification of the deterministic method optimized design.

Initial comparison of single cylinder Stirling engine computer model predictions with test results

NASA Technical Reports Server (NTRS)

Tew, R. C., Jr.; Thieme, L. G.; Miao, D.

1979-01-01

A NASA developed digital computer code for a Stirling engine, modelling the performance of a single cylinder rhombic drive ground performance unit (GPU), is presented and its predictions are compared to test results. The GPU engine incorporates eight regenerator/cooler units and the engine working space is modelled by thirteen control volumes. The model calculates indicated power and efficiency for a given engine speed, mean pressure, heater and expansion space metal temperatures and cooler water inlet temperature and flow rate. Comparison of predicted and observed powers implies that the reference pressure drop calculations underestimate actual pressure drop, possibly due to oil contamination in the regenerator/cooler units, methane contamination in the working gas or the underestimation of mechanical loss. For a working gas of hydrogen, the predicted values of brake power are from 0 to 6% higher than experimental values, and brake efficiency is 6 to 16% higher, while for helium the predicted brake power and efficiency are 2 to 15% higher than the experimental.

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.

A New Framework for Effective and Efficient Global Sensitivity Analysis of Earth and Environmental Systems Models

NASA Astrophysics Data System (ADS)

Razavi, Saman; Gupta, Hoshin

2015-04-01

Earth and Environmental Systems (EES) models are essential components of research, development, and decision-making in science and engineering disciplines. With continuous advances in understanding and computing power, such models are becoming more complex with increasingly more factors to be specified (model parameters, forcings, boundary conditions, etc.). To facilitate better understanding of the role and importance of different factors in producing the model responses, the procedure known as 'Sensitivity Analysis' (SA) can be very helpful. Despite the availability of a large body of literature on the development and application of various SA approaches, two issues continue to pose major challenges: (1) Ambiguous Definition of Sensitivity - Different SA methods are based in different philosophies and theoretical definitions of sensitivity, and can result in different, even conflicting, assessments of the underlying sensitivities for a given problem, (2) Computational Cost - The cost of carrying out SA can be large, even excessive, for high-dimensional problems and/or computationally intensive models. In this presentation, we propose a new approach to sensitivity analysis that addresses the dual aspects of 'effectiveness' and 'efficiency'. By effective, we mean achieving an assessment that is both meaningful and clearly reflective of the objective of the analysis (the first challenge above), while by efficiency we mean achieving statistically robust results with minimal computational cost (the second challenge above). Based on this approach, we develop a 'global' sensitivity analysis framework that efficiently generates a newly-defined set of sensitivity indices that characterize a range of important properties of metric 'response surfaces' encountered when performing SA on EES models. Further, we show how this framework embraces, and is consistent with, a spectrum of different concepts regarding 'sensitivity', and that commonly-used SA approaches (e.g., Sobol, Morris, etc.) are actually limiting cases of our approach under specific conditions. Multiple case studies are used to demonstrate the value of the new framework. The results show that the new framework provides a fundamental understanding of the underlying sensitivities for any given problem, while requiring orders of magnitude fewer model runs.

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.

Time Division Multiplexing of Semiconductor Qubits

NASA Astrophysics Data System (ADS)

Jarratt, Marie Claire; Hornibrook, John; Croot, Xanthe; Watson, John; Gardner, Geoff; Fallahi, Saeed; Manfra, Michael; Reilly, David

Readout chains, comprising resonators, amplifiers, and demodulators, are likely to be precious resources in quantum computing architectures. The potential to share readout resources is contingent on realising efficient means of time-division multiplexing (TDM) schemes that are compatible with quantum computing. Here, we demonstrate TDM using a GaAs quantum dot device with multiple charge sensors. Our device incorporates chip-level switches that do not load the impedance matching network. When used in conjunction with frequency multiplexing, each frequency tone addresses multiple time-multiplexed qubits, vastly increasing the capacity of a single readout line.

Generalized recursion relations for correlators in the gauge-gravity correspondence.

PubMed

Raju, Suvrat

2011-03-04

We show that a generalization of the Britto-Cachazo-Feng-Witten recursion relations gives a new and efficient method of computing correlation functions of the stress tensor or conserved currents in conformal field theories with an (d+1)-dimensional anti-de Sitter space dual, for d≥4, in the limit where the bulk theory is approximated by tree-level Yang-Mills theory or gravity. In supersymmetric theories, additional correlators of operators that live in the same multiplet as a conserved current or stress tensor can be computed by these means.

Application of Computer Simulation to Identify Erosion Resistance of Materials of Wet-steam Turbine Blades

NASA Astrophysics Data System (ADS)

Korostelyov, D. A.; Dergachyov, K. V.

2017-10-01

A problem of identifying the efficiency of using materials, coatings, linings and solderings of wet-steam turbine rotor blades by means of computer simulation is considered. Numerical experiments to define erosion resistance of materials of wet-steam turbine blades are described. Kinetic curves for erosion area and weight of the worn rotor blade material of turbines K-300-240 LMP and atomic icebreaker “Lenin” have been defined. The conclusion about the effectiveness of using different erosion-resistant materials and protection configuration of rotor blades is also made.

A highly efficient multi-core algorithm for clustering extremely large datasets

PubMed Central

2010-01-01

Background In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput technologies. This demand is likely to increase. Standard algorithms for analyzing data, such as cluster algorithms, need to be parallelized for fast processing. Unfortunately, most approaches for parallelizing algorithms largely rely on network communication protocols connecting and requiring multiple computers. One answer to this problem is to utilize the intrinsic capabilities in current multi-core hardware to distribute the tasks among the different cores of one computer. Results We introduce a multi-core parallelization of the k-means and k-modes cluster algorithms based on the design principles of transactional memory for clustering gene expression microarray type data and categorial SNP data. Our new shared memory parallel algorithms show to be highly efficient. We demonstrate their computational power and show their utility in cluster stability and sensitivity analysis employing repeated runs with slightly changed parameters. Computation speed of our Java based algorithm was increased by a factor of 10 for large data sets while preserving computational accuracy compared to single-core implementations and a recently published network based parallelization. Conclusions Most desktop computers and even notebooks provide at least dual-core processors. Our multi-core algorithms show that using modern algorithmic concepts, parallelization makes it possible to perform even such laborious tasks as cluster sensitivity and cluster number estimation on the laboratory computer. PMID:20370922

Comparison of Water Management in Container-Grown Nursery Crops using Leaching Fraction or Weight-Based On Demand Irrigation Control.

USDA-ARS?s Scientific Manuscript database

Water management should be the foundation of container nursery production as it is linked directly to both water and nutrient uptake efficiency and ultimately, environmental impact. In this study gravimetric water management technique was used by means of load cell/computer interface to determine i...

Predicting Aircraft Spray Patterns on Crops

NASA Technical Reports Server (NTRS)

Teske, M. E.; Bilanin, A. J.

1986-01-01

Agricultural Dispersion Prediction (AGDISP) system developed to predict deposition of agricultural material released from rotary- and fixed-wing aircraft. AGDISP computes ensemble average mean motion resulting from turbulent fluid fluctuations. Used to examine ways of making dispersal process more efficient by insuring uniformity, reducing waste, and saving money. Programs in AGDISP system written in FORTRAN IV for interactive execution.

Benchmarking undedicated cloud computing providers for analysis of genomic datasets.

PubMed

Yazar, Seyhan; Gooden, George E C; Mackey, David A; Hewitt, Alex W

2014-01-01

A major bottleneck in biological discovery is now emerging at the computational level. Cloud computing offers a dynamic means whereby small and medium-sized laboratories can rapidly adjust their computational capacity. We benchmarked two established cloud computing services, Amazon Web Services Elastic MapReduce (EMR) on Amazon EC2 instances and Google Compute Engine (GCE), using publicly available genomic datasets (E.coli CC102 strain and a Han Chinese male genome) and a standard bioinformatic pipeline on a Hadoop-based platform. Wall-clock time for complete assembly differed by 52.9% (95% CI: 27.5-78.2) for E.coli and 53.5% (95% CI: 34.4-72.6) for human genome, with GCE being more efficient than EMR. The cost of running this experiment on EMR and GCE differed significantly, with the costs on EMR being 257.3% (95% CI: 211.5-303.1) and 173.9% (95% CI: 134.6-213.1) more expensive for E.coli and human assemblies respectively. Thus, GCE was found to outperform EMR both in terms of cost and wall-clock time. Our findings confirm that cloud computing is an efficient and potentially cost-effective alternative for analysis of large genomic datasets. In addition to releasing our cost-effectiveness comparison, we present available ready-to-use scripts for establishing Hadoop instances with Ganglia monitoring on EC2 or GCE.

Benchmarking Undedicated Cloud Computing Providers for Analysis of Genomic Datasets

PubMed Central

Yazar, Seyhan; Gooden, George E. C.; Mackey, David A.; Hewitt, Alex W.

2014-01-01

A major bottleneck in biological discovery is now emerging at the computational level. Cloud computing offers a dynamic means whereby small and medium-sized laboratories can rapidly adjust their computational capacity. We benchmarked two established cloud computing services, Amazon Web Services Elastic MapReduce (EMR) on Amazon EC2 instances and Google Compute Engine (GCE), using publicly available genomic datasets (E.coli CC102 strain and a Han Chinese male genome) and a standard bioinformatic pipeline on a Hadoop-based platform. Wall-clock time for complete assembly differed by 52.9% (95% CI: 27.5–78.2) for E.coli and 53.5% (95% CI: 34.4–72.6) for human genome, with GCE being more efficient than EMR. The cost of running this experiment on EMR and GCE differed significantly, with the costs on EMR being 257.3% (95% CI: 211.5–303.1) and 173.9% (95% CI: 134.6–213.1) more expensive for E.coli and human assemblies respectively. Thus, GCE was found to outperform EMR both in terms of cost and wall-clock time. Our findings confirm that cloud computing is an efficient and potentially cost-effective alternative for analysis of large genomic datasets. In addition to releasing our cost-effectiveness comparison, we present available ready-to-use scripts for establishing Hadoop instances with Ganglia monitoring on EC2 or GCE. PMID:25247298

Piece-wise quadratic approximations of arbitrary error functions for fast and robust machine learning.

PubMed

Gorban, A N; Mirkes, E M; Zinovyev, A

2016-12-01

Most of machine learning approaches have stemmed from the application of minimizing the mean squared distance principle, based on the computationally efficient quadratic optimization methods. However, when faced with high-dimensional and noisy data, the quadratic error functionals demonstrated many weaknesses including high sensitivity to contaminating factors and dimensionality curse. Therefore, a lot of recent applications in machine learning exploited properties of non-quadratic error functionals based on L 1 norm or even sub-linear potentials corresponding to quasinorms L p (0

Blazing Signature Filter: a library for fast pairwise similarity comparisons

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

Lee, Joon-Yong; Fujimoto, Grant M.; Wilson, Ryan

Identifying similarities between datasets is a fundamental task in data mining and has become an integral part of modern scientific investigation. Whether the task is to identify co-expressed genes in large-scale expression surveys or to predict combinations of gene knockouts which would elicit a similar phenotype, the underlying computational task is often a multi-dimensional similarity test. As datasets continue to grow, improvements to the efficiency, sensitivity or specificity of such computation will have broad impacts as it allows scientists to more completely explore the wealth of scientific data. A significant practical drawback of large-scale data mining is the vast majoritymore » of pairwise comparisons are unlikely to be relevant, meaning that they do not share a signature of interest. It is therefore essential to efficiently identify these unproductive comparisons as rapidly as possible and exclude them from more time-intensive similarity calculations. The Blazing Signature Filter (BSF) is a highly efficient pairwise similarity algorithm which enables extensive data mining within a reasonable amount of time. The algorithm transforms datasets into binary metrics, allowing it to utilize the computationally efficient bit operators and provide a coarse measure of similarity. As a result, the BSF can scale to high dimensionality and rapidly filter unproductive pairwise comparison. Two bioinformatics applications of the tool are presented to demonstrate the ability to scale to billions of pairwise comparisons and the usefulness of this approach.« less

Efficient Decoding With Steady-State Kalman Filter in Neural Interface Systems

PubMed Central

Malik, Wasim Q.; Truccolo, Wilson; Brown, Emery N.; Hochberg, Leigh R.

2011-01-01

The Kalman filter is commonly used in neural interface systems to decode neural activity and estimate the desired movement kinematics. We analyze a low-complexity Kalman filter implementation in which the filter gain is approximated by its steady-state form, computed offline before real-time decoding commences. We evaluate its performance using human motor cortical spike train data obtained from an intracortical recording array as part of an ongoing pilot clinical trial. We demonstrate that the standard Kalman filter gain converges to within 95% of the steady-state filter gain in 1.5 ± 0.5 s (mean ± s.d.). The difference in the intended movement velocity decoded by the two filters vanishes within 5 s, with a correlation coefficient of 0.99 between the two decoded velocities over the session length. We also find that the steady-state Kalman filter reduces the computational load (algorithm execution time) for decoding the firing rates of 25 ± 3 single units by a factor of 7.0 ± 0.9. We expect that the gain in computational efficiency will be much higher in systems with larger neural ensembles. The steady-state filter can thus provide substantial runtime efficiency at little cost in terms of estimation accuracy. This far more efficient neural decoding approach will facilitate the practical implementation of future large-dimensional, multisignal neural interface systems. PMID:21078582

A hydrological emulator for global applications – HE v1.0.0

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

Liu, Yaling; Hejazi, Mohamad; Li, Hongyi

While global hydrological models (GHMs) are very useful in exploring water resources and interactions between the Earth and human systems, their use often requires numerous model inputs, complex model calibration, and high computation costs. To overcome these challenges, we construct an efficient open-source and ready-to-use hydrological emulator (HE) that can mimic complex GHMs at a range of spatial scales (e.g., basin, region, globe). More specifically, we construct both a lumped and a distributed scheme of the HE based on the monthly abcd model to explore the tradeoff between computational cost and model fidelity. Model predictability and computational efficiency are evaluatedmore » in simulating global runoff from 1971 to 2010 with both the lumped and distributed schemes. The results are compared against the runoff product from the widely used Variable Infiltration Capacity (VIC) model. Our evaluation indicates that the lumped and distributed schemes present comparable results regarding annual total quantity, spatial pattern, and temporal variation of the major water fluxes (e.g., total runoff, evapotranspiration) across the global 235 basins (e.g., correlation coefficient r between the annual total runoff from either of these two schemes and the VIC is > 0.96), except for several cold (e.g., Arctic, interior Tibet), dry (e.g., North Africa) and mountainous (e.g., Argentina) regions. Compared against the monthly total runoff product from the VIC (aggregated from daily runoff), the global mean Kling–Gupta efficiencies are 0.75 and 0.79 for the lumped and distributed schemes, respectively, with the distributed scheme better capturing spatial heterogeneity. Notably, the computation efficiency of the lumped scheme is 2 orders of magnitude higher than the distributed one and 7 orders more efficient than the VIC model. A case study of uncertainty analysis for the world's 16 basins with top annual streamflow is conducted using 100 000 model simulations, and it demonstrates the lumped scheme's extraordinary advantage in computational efficiency. Lastly, our results suggest that the revised lumped abcd model can serve as an efficient and reasonable HE for complex GHMs and is suitable for broad practical use, and the distributed scheme is also an efficient alternative if spatial heterogeneity is of more interest.« less

Discriminative Hierarchical K-Means Tree for Large-Scale Image Classification.

PubMed

Chen, Shizhi; Yang, Xiaodong; Tian, Yingli

2015-09-01

A key challenge in large-scale image classification is how to achieve efficiency in terms of both computation and memory without compromising classification accuracy. The learning-based classifiers achieve the state-of-the-art accuracies, but have been criticized for the computational complexity that grows linearly with the number of classes. The nonparametric nearest neighbor (NN)-based classifiers naturally handle large numbers of categories, but incur prohibitively expensive computation and memory costs. In this brief, we present a novel classification scheme, i.e., discriminative hierarchical K-means tree (D-HKTree), which combines the advantages of both learning-based and NN-based classifiers. The complexity of the D-HKTree only grows sublinearly with the number of categories, which is much better than the recent hierarchical support vector machines-based methods. The memory requirement is the order of magnitude less than the recent Naïve Bayesian NN-based approaches. The proposed D-HKTree classification scheme is evaluated on several challenging benchmark databases and achieves the state-of-the-art accuracies, while with significantly lower computation cost and memory requirement.

Unveiling the Atomic-Level Determinants of Acylase-Ligand Complexes: An Experimental and Computational Study.

PubMed

Mollica, Luca; Conti, Gianluca; Pollegioni, Loredano; Cavalli, Andrea; Rosini, Elena

2015-10-26

The industrial production of higher-generation semisynthetic cephalosporins starts from 7-aminocephalosporanic acid (7-ACA), which is obtained by deacylation of the naturally occurring antibiotic cephalosporin C (CephC). The enzymatic process in which CephC is directly converted into 7-ACA by a cephalosporin C acylase has attracted industrial interest because of the prospects of simplifying the process and reducing costs. We recently enhanced the catalytic efficiency on CephC of a glutaryl acylase from Pseudomonas N176 (named VAC) by a protein engineering approach and solved the crystal structures of wild-type VAC and the H57βS-H70βS VAC double variant. In the present work, experimental measurements on several CephC derivatives and six VAC variants were carried out, and the binding of ligands into the VAC active site was investigated at an atomistic level by means of molecular docking and molecular dynamics simulations and analyzed on the basis of the molecular geometry of encounter complex formation and protein-ligand potential of mean force profiles. The observed significant correlation between the experimental data and estimated binding energies highlights the predictive power of our computational method to identify the ligand binding mode. The present experimental-computational study is well-suited both to provide deep insight into the reaction mechanism of cephalosporin C acylase and to improve the efficiency of the corresponding industrial process.

Gate sequence for continuous variable one-way quantum computation

PubMed Central

Su, Xiaolong; Hao, Shuhong; Deng, Xiaowei; Ma, Lingyu; Wang, Meihong; Jia, Xiaojun; Xie, Changde; Peng, Kunchi

2013-01-01

Measurement-based one-way quantum computation using cluster states as resources provides an efficient model to perform computation and information processing of quantum codes. Arbitrary Gaussian quantum computation can be implemented sufficiently by long single-mode and two-mode gate sequences. However, continuous variable gate sequences have not been realized so far due to an absence of cluster states larger than four submodes. Here we present the first continuous variable gate sequence consisting of a single-mode squeezing gate and a two-mode controlled-phase gate based on a six-mode cluster state. The quantum property of this gate sequence is confirmed by the fidelities and the quantum entanglement of two output modes, which depend on both the squeezing and controlled-phase gates. The experiment demonstrates the feasibility of implementing Gaussian quantum computation by means of accessible gate sequences.

Design of efficient stiffened shells of revolution

NASA Technical Reports Server (NTRS)

Majumder, D. K.; Thornton, W. A.

1976-01-01

A method to produce efficient piecewise uniform stiffened shells of revolution is presented. The approach uses a first order differential equation formulation for the shell prebuckling and buckling analyses and the necessary conditions for an optimum design are derived by a variational approach. A variety of local yielding and buckling constraints and the general buckling constraint are included in the design process. The local constraints are treated by means of an interior penalty function and the general buckling load is treated by means of an exterior penalty function. This allows the general buckling constraint to be included in the design process only when it is violated. The self-adjoint nature of the prebuckling and buckling formulations is used to reduce the computational effort. Results for four conical shells and one spherical shell are given.

Computations of Unsteady Viscous Compressible Flows Using Adaptive Mesh Refinement in Curvilinear Body-fitted Grid Systems

NASA Technical Reports Server (NTRS)

Steinthorsson, E.; Modiano, David; Colella, Phillip

1994-01-01

A methodology for accurate and efficient simulation of unsteady, compressible flows is presented. The cornerstones of the methodology are a special discretization of the Navier-Stokes equations on structured body-fitted grid systems and an efficient solution-adaptive mesh refinement technique for structured grids. The discretization employs an explicit multidimensional upwind scheme for the inviscid fluxes and an implicit treatment of the viscous terms. The mesh refinement technique is based on the AMR algorithm of Berger and Colella. In this approach, cells on each level of refinement are organized into a small number of topologically rectangular blocks, each containing several thousand cells. The small number of blocks leads to small overhead in managing data, while their size and regular topology means that a high degree of optimization can be achieved on computers with vector processors.

Multiple Concentric Cylinder Model (MCCM) user's guide

NASA Technical Reports Server (NTRS)

Williams, Todd O.; Pindera, Marek-Jerzy

1994-01-01

A user's guide for the computer program mccm.f is presented. The program is based on a recently developed solution methodology for the inelastic response of an arbitrarily layered, concentric cylinder assemblage under thermomechanical loading which is used to model the axisymmetric behavior of unidirectional metal matrix composites in the presence of various microstructural details. These details include the layered morphology of certain types of ceramic fibers, as well as multiple fiber/matrix interfacial layers recently proposed as a means of reducing fabrication-induced, and in-service, residual stress. The computer code allows efficient characterization and evaluation of new fibers and/or new coating systems on existing fibers with a minimum of effort, taking into account inelastic and temperature-dependent properties and different morphologies of the fiber and the interfacial region. It also facilitates efficient design of engineered interfaces for unidirectional metal matrix composites.

WTO — a deterministic approach to 4-fermion physics

NASA Astrophysics Data System (ADS)

Passarino, Giampiero

1996-09-01

The program WTO, which is designed for computing cross sections and other relevant observables in the e+e- annihilation into four fermions, is described. The various quantities are computed over both a completely inclusive experimental set-up and a realistic one, i.e. with cuts on the final state energies, final state angles, scattering angles and final state invariant masses. Initial state QED corrections are included by means of the structure function approach while final state QCD corrections are applicable in their naive formulation. A gauge restoring mechanism is included according to the Fermion-Loop scheme. The program structure is highly modular and particular care has been devoted to computing efficiency and speed.

Convolution of large 3D images on GPU and its decomposition

NASA Astrophysics Data System (ADS)

Karas, Pavel; Svoboda, David

2011-12-01

In this article, we propose a method for computing convolution of large 3D images. The convolution is performed in a frequency domain using a convolution theorem. The algorithm is accelerated on a graphic card by means of the CUDA parallel computing model. Convolution is decomposed in a frequency domain using the decimation in frequency algorithm. We pay attention to keeping our approach efficient in terms of both time and memory consumption and also in terms of memory transfers between CPU and GPU which have a significant inuence on overall computational time. We also study the implementation on multiple GPUs and compare the results between the multi-GPU and multi-CPU implementations.

An Improved Clustering Algorithm of Tunnel Monitoring Data for Cloud Computing

PubMed Central

Zhong, Luo; Tang, KunHao; Li, Lin; Yang, Guang; Ye, JingJing

2014-01-01

With the rapid development of urban construction, the number of urban tunnels is increasing and the data they produce become more and more complex. It results in the fact that the traditional clustering algorithm cannot handle the mass data of the tunnel. To solve this problem, an improved parallel clustering algorithm based on k-means has been proposed. It is a clustering algorithm using the MapReduce within cloud computing that deals with data. It not only has the advantage of being used to deal with mass data but also is more efficient. Moreover, it is able to compute the average dissimilarity degree of each cluster in order to clean the abnormal data. PMID:24982971

Optimal Energy Efficiency Fairness of Nodes in Wireless Powered Communication Networks.

PubMed

Zhang, Jing; Zhou, Qingjie; Ng, Derrick Wing Kwan; Jo, Minho

2017-09-15

In wireless powered communication networks (WPCNs), it is essential to research energy efficiency fairness in order to evaluate the balance of nodes for receiving information and harvesting energy. In this paper, we propose an efficient iterative algorithm for optimal energy efficiency proportional fairness in WPCN. The main idea is to use stochastic geometry to derive the mean proportionally fairness utility function with respect to user association probability and receive threshold. Subsequently, we prove that the relaxed proportionally fairness utility function is a concave function for user association probability and receive threshold, respectively. At the same time, a sub-optimal algorithm by exploiting alternating optimization approach is proposed. Through numerical simulations, we demonstrate that our sub-optimal algorithm can obtain a result close to optimal energy efficiency proportional fairness with significant reduction of computational complexity.

Optimal Energy Efficiency Fairness of Nodes in Wireless Powered Communication Networks

PubMed Central

Zhou, Qingjie; Ng, Derrick Wing Kwan; Jo, Minho

2017-01-01

In wireless powered communication networks (WPCNs), it is essential to research energy efficiency fairness in order to evaluate the balance of nodes for receiving information and harvesting energy. In this paper, we propose an efficient iterative algorithm for optimal energy efficiency proportional fairness in WPCN. The main idea is to use stochastic geometry to derive the mean proportionally fairness utility function with respect to user association probability and receive threshold. Subsequently, we prove that the relaxed proportionally fairness utility function is a concave function for user association probability and receive threshold, respectively. At the same time, a sub-optimal algorithm by exploiting alternating optimization approach is proposed. Through numerical simulations, we demonstrate that our sub-optimal algorithm can obtain a result close to optimal energy efficiency proportional fairness with significant reduction of computational complexity. PMID:28914818

Computer-assisted photogrammetric mapping systems for geologic studies-A progress report

USGS Publications Warehouse

Pillmore, C.L.; Dueholm, K.S.; Jepsen, H.S.; Schuch, C.H.

1981-01-01

Photogrammetry has played an important role in geologic mapping for many years; however, only recently have attempts been made to automate mapping functions for geology. Computer-assisted photogrammetric mapping systems for geologic studies have been developed and are currently in use in offices of the Geological Survey of Greenland at Copenhagen, Denmark, and the U.S. Geological Survey at Denver, Colorado. Though differing somewhat, the systems are similar in that they integrate Kern PG-2 photogrammetric plotting instruments and small desk-top computers that are programmed to perform special geologic functions and operate flat-bed plotters by means of specially designed hardware and software. A z-drive capability, in which stepping motors control the z-motions of the PG-2 plotters, is an integral part of both systems. This feature enables the computer to automatically position the floating mark on computer-calculated, previously defined geologic planes, such as contacts or the base of coal beds, throughout the stereoscopic model in order to improve the mapping capabilities of the instrument and to aid in correlation and tracing of geologic units. The common goal is to enhance the capabilities of the PG-2 plotter and provide a means by which geologists can make conventional geologic maps more efficiently and explore ways to apply computer technology to geologic studies. ?? 1981.

Ultrafast and scalable cone-beam CT reconstruction using MapReduce in a cloud computing environment.

PubMed

Meng, Bowen; Pratx, Guillem; Xing, Lei

2011-12-01

Four-dimensional CT (4DCT) and cone beam CT (CBCT) are widely used in radiation therapy for accurate tumor target definition and localization. However, high-resolution and dynamic image reconstruction is computationally demanding because of the large amount of data processed. Efficient use of these imaging techniques in the clinic requires high-performance computing. The purpose of this work is to develop a novel ultrafast, scalable and reliable image reconstruction technique for 4D CBCT∕CT using a parallel computing framework called MapReduce. We show the utility of MapReduce for solving large-scale medical physics problems in a cloud computing environment. In this work, we accelerated the Feldcamp-Davis-Kress (FDK) algorithm by porting it to Hadoop, an open-source MapReduce implementation. Gated phases from a 4DCT scans were reconstructed independently. Following the MapReduce formalism, Map functions were used to filter and backproject subsets of projections, and Reduce function to aggregate those partial backprojection into the whole volume. MapReduce automatically parallelized the reconstruction process on a large cluster of computer nodes. As a validation, reconstruction of a digital phantom and an acquired CatPhan 600 phantom was performed on a commercial cloud computing environment using the proposed 4D CBCT∕CT reconstruction algorithm. Speedup of reconstruction time is found to be roughly linear with the number of nodes employed. For instance, greater than 10 times speedup was achieved using 200 nodes for all cases, compared to the same code executed on a single machine. Without modifying the code, faster reconstruction is readily achievable by allocating more nodes in the cloud computing environment. Root mean square error between the images obtained using MapReduce and a single-threaded reference implementation was on the order of 10(-7). Our study also proved that cloud computing with MapReduce is fault tolerant: the reconstruction completed successfully with identical results even when half of the nodes were manually terminated in the middle of the process. An ultrafast, reliable and scalable 4D CBCT∕CT reconstruction method was developed using the MapReduce framework. Unlike other parallel computing approaches, the parallelization and speedup required little modification of the original reconstruction code. MapReduce provides an efficient and fault tolerant means of solving large-scale computing problems in a cloud computing environment.

Ultrafast and scalable cone-beam CT reconstruction using MapReduce in a cloud computing environment

PubMed Central

Meng, Bowen; Pratx, Guillem; Xing, Lei

2011-01-01

Purpose: Four-dimensional CT (4DCT) and cone beam CT (CBCT) are widely used in radiation therapy for accurate tumor target definition and localization. However, high-resolution and dynamic image reconstruction is computationally demanding because of the large amount of data processed. Efficient use of these imaging techniques in the clinic requires high-performance computing. The purpose of this work is to develop a novel ultrafast, scalable and reliable image reconstruction technique for 4D CBCT/CT using a parallel computing framework called MapReduce. We show the utility of MapReduce for solving large-scale medical physics problems in a cloud computing environment. Methods: In this work, we accelerated the Feldcamp–Davis–Kress (FDK) algorithm by porting it to Hadoop, an open-source MapReduce implementation. Gated phases from a 4DCT scans were reconstructed independently. Following the MapReduce formalism, Map functions were used to filter and backproject subsets of projections, and Reduce function to aggregate those partial backprojection into the whole volume. MapReduce automatically parallelized the reconstruction process on a large cluster of computer nodes. As a validation, reconstruction of a digital phantom and an acquired CatPhan 600 phantom was performed on a commercial cloud computing environment using the proposed 4D CBCT/CT reconstruction algorithm. Results: Speedup of reconstruction time is found to be roughly linear with the number of nodes employed. For instance, greater than 10 times speedup was achieved using 200 nodes for all cases, compared to the same code executed on a single machine. Without modifying the code, faster reconstruction is readily achievable by allocating more nodes in the cloud computing environment. Root mean square error between the images obtained using MapReduce and a single-threaded reference implementation was on the order of 10−7. Our study also proved that cloud computing with MapReduce is fault tolerant: the reconstruction completed successfully with identical results even when half of the nodes were manually terminated in the middle of the process. Conclusions: An ultrafast, reliable and scalable 4D CBCT/CT reconstruction method was developed using the MapReduce framework. Unlike other parallel computing approaches, the parallelization and speedup required little modification of the original reconstruction code. MapReduce provides an efficient and fault tolerant means of solving large-scale computing problems in a cloud computing environment. PMID:22149842

Sparse approximation of currents for statistics on curves and surfaces.

PubMed

Durrleman, Stanley; Pennec, Xavier; Trouvé, Alain; Ayache, Nicholas

2008-01-01

Computing, processing, visualizing statistics on shapes like curves or surfaces is a real challenge with many applications ranging from medical image analysis to computational geometry. Modelling such geometrical primitives with currents avoids feature-based approach as well as point-correspondence method. This framework has been proved to be powerful to register brain surfaces or to measure geometrical invariants. However, if the state-of-the-art methods perform efficiently pairwise registrations, new numerical schemes are required to process groupwise statistics due to an increasing complexity when the size of the database is growing. Statistics such as mean and principal modes of a set of shapes often have a heavy and highly redundant representation. We propose therefore to find an adapted basis on which mean and principal modes have a sparse decomposition. Besides the computational improvement, this sparse representation offers a way to visualize and interpret statistics on currents. Experiments show the relevance of the approach on 34 sets of 70 sulcal lines and on 50 sets of 10 meshes of deep brain structures.

Quantum analogue computing.

PubMed

Kendon, Vivien M; Nemoto, Kae; Munro, William J

2010-08-13

We briefly review what a quantum computer is, what it promises to do for us and why it is so hard to build one. Among the first applications anticipated to bear fruit is the quantum simulation of quantum systems. While most quantum computation is an extension of classical digital computation, quantum simulation differs fundamentally in how the data are encoded in the quantum computer. To perform a quantum simulation, the Hilbert space of the system to be simulated is mapped directly onto the Hilbert space of the (logical) qubits in the quantum computer. This type of direct correspondence is how data are encoded in a classical analogue computer. There is no binary encoding, and increasing precision becomes exponentially costly: an extra bit of precision doubles the size of the computer. This has important consequences for both the precision and error-correction requirements of quantum simulation, and significant open questions remain about its practicality. It also means that the quantum version of analogue computers, continuous-variable quantum computers, becomes an equally efficient architecture for quantum simulation. Lessons from past use of classical analogue computers can help us to build better quantum simulators in future.

Documentation for the machine-readable version of the Survey of the Astrographic Catalogue From 1 to 31 Degrees of Northern Declination (Fresneau 1983)

NASA Technical Reports Server (NTRS)

Warren, W. H., Jr.

1983-01-01

A description of the machine readable catalog, including detailed format and tape file characteristics, is given. The machine file is a computation of mean values for position and magnitude at a mean epoch of observation for each unique star in the Oxford, Paris, Bordeaux, Toulouse and Northern Hemisphere Algiers zone. The format was changed to effect more efficient data searching by position and additional duplicate entries were removed. The final catalog contains data for 997311 stars.

Extending Moore's Law via Computationally Error Tolerant Computing.

DOE PAGES

Deng, Bobin; Srikanth, Sriseshan; Hein, Eric R.; ...

2018-03-01

Dennard scaling has ended. Lowering the voltage supply (V dd) to sub-volt levels causes intermittent losses in signal integrity, rendering further scaling (down) no longer acceptable as a means to lower the power required by a processor core. However, it is possible to correct the occasional errors caused due to lower V dd in an efficient manner and effectively lower power. By deploying the right amount and kind of redundancy, we can strike a balance between overhead incurred in achieving reliability and energy savings realized by permitting lower V dd. One promising approach is the Redundant Residue Number System (RRNS)more » representation. Unlike other error correcting codes, RRNS has the important property of being closed under addition, subtraction and multiplication, thus enabling computational error correction at a fraction of an overhead compared to conventional approaches. We use the RRNS scheme to design a Computationally-Redundant, Energy-Efficient core, including the microarchitecture, Instruction Set Architecture (ISA) and RRNS centered algorithms. Finally, from the simulation results, this RRNS system can reduce the energy-delay-product by about 3× for multiplication intensive workloads and by about 2× in general, when compared to a non-error-correcting binary core.« less

Extending Moore's Law via Computationally Error Tolerant Computing.

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

Deng, Bobin; Srikanth, Sriseshan; Hein, Eric R.

Dennard scaling has ended. Lowering the voltage supply (V dd) to sub-volt levels causes intermittent losses in signal integrity, rendering further scaling (down) no longer acceptable as a means to lower the power required by a processor core. However, it is possible to correct the occasional errors caused due to lower V dd in an efficient manner and effectively lower power. By deploying the right amount and kind of redundancy, we can strike a balance between overhead incurred in achieving reliability and energy savings realized by permitting lower V dd. One promising approach is the Redundant Residue Number System (RRNS)more » representation. Unlike other error correcting codes, RRNS has the important property of being closed under addition, subtraction and multiplication, thus enabling computational error correction at a fraction of an overhead compared to conventional approaches. We use the RRNS scheme to design a Computationally-Redundant, Energy-Efficient core, including the microarchitecture, Instruction Set Architecture (ISA) and RRNS centered algorithms. Finally, from the simulation results, this RRNS system can reduce the energy-delay-product by about 3× for multiplication intensive workloads and by about 2× in general, when compared to a non-error-correcting binary core.« less

Hierarchical layered and semantic-based image segmentation using ergodicity map

NASA Astrophysics Data System (ADS)

Yadegar, Jacob; Liu, Xiaoqing

2010-04-01

Image segmentation plays a foundational role in image understanding and computer vision. Although great strides have been made and progress achieved on automatic/semi-automatic image segmentation algorithms, designing a generic, robust, and efficient image segmentation algorithm is still challenging. Human vision is still far superior compared to computer vision, especially in interpreting semantic meanings/objects in images. We present a hierarchical/layered semantic image segmentation algorithm that can automatically and efficiently segment images into hierarchical layered/multi-scaled semantic regions/objects with contextual topological relationships. The proposed algorithm bridges the gap between high-level semantics and low-level visual features/cues (such as color, intensity, edge, etc.) through utilizing a layered/hierarchical ergodicity map, where ergodicity is computed based on a space filling fractal concept and used as a region dissimilarity measurement. The algorithm applies a highly scalable, efficient, and adaptive Peano- Cesaro triangulation/tiling technique to decompose the given image into a set of similar/homogenous regions based on low-level visual cues in a top-down manner. The layered/hierarchical ergodicity map is built through a bottom-up region dissimilarity analysis. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level of detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanisms for contextual topological object/region relationship generation. Experiments have been conducted within the maritime image environment where the segmented layered semantic objects include the basic level objects (i.e. sky/land/water) and deeper level objects in the sky/land/water surfaces. Experimental results demonstrate the proposed algorithm has the capability to robustly and efficiently segment images into layered semantic objects/regions with contextual topological relationships.

Using the U.S. Bureau of the Census CD-ROM Test Disc 2: A Note.

ERIC Educational Resources Information Center

Staninger, Steven W.

1991-01-01

This evaluation of means of accessing data on the U.S. Census Bureau CD-ROM Test Disc 2 describes computer hardware configurations considered in determining the most efficient method of manipulating the data, and mentions software options. Two dBASE configurations are compared, and it is concluded that the 80386 is essential for efficient…

A quick transcribing technique for oral data

USGS Publications Warehouse

Schleicher, David

1972-01-01

Stenographic techniques offer a means for transcribing oral data accurately and efficiently. In one such application, during five Appolo lunar missions, a rough but helpful transcript was produced within minutes. Similarly, lectures, conferences, and audio tapes can be accurately transcribed as promptly as necessary. Computer programs for translating shorthand notes are being developed; they will increase both speed and accuracy of translation.

Wisconsin Title I Migrant Education. Section 143 Project: Development of an Item Bank. Summary Report.

ERIC Educational Resources Information Center

Brown, Frank N.; And Others

The successful Wisconsin Title 1 project item bank offers a valid, flexible, and efficient means of providing migrant student tests in reading and mathematics tailored to instructor curricula. The item bank system consists of nine PASCAL computer programs which maintain, search, and select from approximately 1,000 test items stored on floppy disks…

Efficiency Evaluation of Handling of Geologic-Geophysical Information by Means of Computer Systems

NASA Astrophysics Data System (ADS)

Nuriyahmetova, S. M.; Demyanova, O. V.; Zabirova, L. M.; Gataullin, I. I.; Fathutdinova, O. A.; Kaptelinina, E. A.

2018-05-01

Development of oil and gas resources, considering difficult geological, geographical and economic conditions, requires considerable finance costs; therefore their careful reasons, application of the most perspective directions and modern technologies from the point of view of cost efficiency of planned activities are necessary. For ensuring high precision of regional and local forecasts and modeling of reservoirs of fields of hydrocarbonic raw materials, it is necessary to analyze huge arrays of the distributed information which is constantly changing spatial. The solution of this task requires application of modern remote methods of a research of the perspective oil-and-gas territories, complex use of materials remote, nondestructive the environment of geologic-geophysical and space methods of sounding of Earth and the most perfect technologies of their handling. In the article, the authors considered experience of handling of geologic-geophysical information by means of computer systems by the Russian and foreign companies. Conclusions that the multidimensional analysis of geologicgeophysical information space, effective planning and monitoring of exploration works requires broad use of geoinformation technologies as one of the most perspective directions in achievement of high profitability of an oil and gas industry are drawn.

Nested polynomial trends for the improvement of Gaussian process-based predictors

NASA Astrophysics Data System (ADS)

Perrin, G.; Soize, C.; Marque-Pucheu, S.; Garnier, J.

2017-10-01

The role of simulation keeps increasing for the sensitivity analysis and the uncertainty quantification of complex systems. Such numerical procedures are generally based on the processing of a huge amount of code evaluations. When the computational cost associated with one particular evaluation of the code is high, such direct approaches based on the computer code only, are not affordable. Surrogate models have therefore to be introduced to interpolate the information given by a fixed set of code evaluations to the whole input space. When confronted to deterministic mappings, the Gaussian process regression (GPR), or kriging, presents a good compromise between complexity, efficiency and error control. Such a method considers the quantity of interest of the system as a particular realization of a Gaussian stochastic process, whose mean and covariance functions have to be identified from the available code evaluations. In this context, this work proposes an innovative parametrization of this mean function, which is based on the composition of two polynomials. This approach is particularly relevant for the approximation of strongly non linear quantities of interest from very little information. After presenting the theoretical basis of this method, this work compares its efficiency to alternative approaches on a series of examples.

Free-energy-based lattice Boltzmann model for the simulation of multiphase flows with density contrast.

PubMed

Shao, J Y; Shu, C; Huang, H B; Chew, Y T

2014-03-01

A free-energy-based phase-field lattice Boltzmann method is proposed in this work to simulate multiphase flows with density contrast. The present method is to improve the Zheng-Shu-Chew (ZSC) model [Zheng, Shu, and Chew, J. Comput. Phys. 218, 353 (2006)] for correct consideration of density contrast in the momentum equation. The original ZSC model uses the particle distribution function in the lattice Boltzmann equation (LBE) for the mean density and momentum, which cannot properly consider the effect of local density variation in the momentum equation. To correctly consider it, the particle distribution function in the LBE must be for the local density and momentum. However, when the LBE of such distribution function is solved, it will encounter a severe numerical instability. To overcome this difficulty, a transformation, which is similar to the one used in the Lee-Lin (LL) model [Lee and Lin, J. Comput. Phys. 206, 16 (2005)] is introduced in this work to change the particle distribution function for the local density and momentum into that for the mean density and momentum. As a result, the present model still uses the particle distribution function for the mean density and momentum, and in the meantime, considers the effect of local density variation in the LBE as a forcing term. Numerical examples demonstrate that both the present model and the LL model can correctly simulate multiphase flows with density contrast, and the present model has an obvious improvement over the ZSC model in terms of solution accuracy. In terms of computational time, the present model is less efficient than the ZSC model, but is much more efficient than the LL model.

Experimental and Computational Analysis of Unidirectional Flow Through Stirling Engine Heater Head

NASA Technical Reports Server (NTRS)

Wilson, Scott D.; Dyson, Rodger W.; Tew, Roy C.; Demko, Rikako

2006-01-01

A high efficiency Stirling Radioisotope Generator (SRG) is being developed for possible use in long-duration space science missions. NASA s advanced technology goals for next generation Stirling convertors include increasing the Carnot efficiency and percent of Carnot efficiency. To help achieve these goals, a multi-dimensional Computational Fluid Dynamics (CFD) code is being developed to numerically model unsteady fluid flow and heat transfer phenomena of the oscillating working gas inside Stirling convertors. In the absence of transient pressure drop data for the zero mean oscillating multi-dimensional flows present in the Technology Demonstration Convertors on test at NASA Glenn Research Center, unidirectional flow pressure drop test data is used to compare against 2D and 3D computational solutions. This study focuses on tracking pressure drop and mass flow rate data for unidirectional flow though a Stirling heater head using a commercial CFD code (CFD-ACE). The commercial CFD code uses a porous-media model which is dependent on permeability and the inertial coefficient present in the linear and nonlinear terms of the Darcy-Forchheimer equation. Permeability and inertial coefficient were calculated from unidirectional flow test data. CFD simulations of the unidirectional flow test were validated using the porous-media model input parameters which increased simulation accuracy by 14 percent on average.

Analysis of an all-digital maximum likelihood carrier phase and clock timing synchronizer for eight phase-shift keying modulation

NASA Astrophysics Data System (ADS)

Degaudenzi, Riccardo; Vanghi, Vieri

1994-02-01

In all-digital Trellis-Coded 8PSK (TC-8PSK) demodulator well suited for VLSI implementation, including maximum likelihood estimation decision-directed (MLE-DD) carrier phase and clock timing recovery, is introduced and analyzed. By simply removing the trellis decoder the demodulator can efficiently cope with uncoded 8PSK signals. The proposed MLE-DD synchronization algorithm requires one sample for the phase and two samples per symbol for the timing loop. The joint phase and timing discriminator characteristics are analytically derived and numerical results checked by means of computer simulations. An approximated expression for steady-state carrier phase and clock timing mean square error has been derived and successfully checked with simulation findings. Synchronizer deviation from the Cramer Rao bound is also discussed. Mean acquisition time for the digital synchronizer has also been computed and checked, using the Monte Carlo simulation technique. Finally, TC-8PSK digital demodulator performance in terms of bit error rate and mean time to lose lock, including digital interpolators and synchronization loops, is presented.

Chemotherapy appointment scheduling under uncertainty using mean-risk stochastic integer programming.

PubMed

Alvarado, Michelle; Ntaimo, Lewis

2018-03-01

Oncology clinics are often burdened with scheduling large volumes of cancer patients for chemotherapy treatments under limited resources such as the number of nurses and chairs. These cancer patients require a series of appointments over several weeks or months and the timing of these appointments is critical to the treatment's effectiveness. Additionally, the appointment duration, the acuity levels of each appointment, and the availability of clinic nurses are uncertain. The timing constraints, stochastic parameters, rising treatment costs, and increased demand of outpatient oncology clinic services motivate the need for efficient appointment schedules and clinic operations. In this paper, we develop three mean-risk stochastic integer programming (SIP) models, referred to as SIP-CHEMO, for the problem of scheduling individual chemotherapy patient appointments and resources. These mean-risk models are presented and an algorithm is devised to improve computational speed. Computational results were conducted using a simulation model and results indicate that the risk-averse SIP-CHEMO model with the expected excess mean-risk measure can decrease patient waiting times and nurse overtime when compared to deterministic scheduling algorithms by 42 % and 27 %, respectively.

Geometry definition and grid generation for a complete fighter aircraft

NASA Technical Reports Server (NTRS)

Edwards, T. A.

1986-01-01

Recent advances in computing power and numerical solution procedures have enabled computational fluid dynamicists to attempt increasingly difficult problems. In particular, efforts are focusing on computations of complex three-dimensional flow fields about realistic aerodynamic bodies. To perform such computations, a very accurate and detailed description of the surface geometry must be provided, and a three-dimensional grid must be generated in the space around the body. The geometry must be supplied in a format compatible with the grid generation requirements, and must be verified to be free of inconsistencies. This paper presents a procedure for performing the geometry definition of a fighter aircraft that makes use of a commercial computer-aided design/computer-aided manufacturing system. Furthermore, visual representations of the geometry are generated using a computer graphics system for verification of the body definition. Finally, the three-dimensional grids for fighter-like aircraft are generated by means of an efficient new parabolic grid generation method. This method exhibits good control of grid quality.

Geometry definition and grid generation for a complete fighter aircraft

NASA Technical Reports Server (NTRS)

Edwards, Thomas A.

1986-01-01

Recent advances in computing power and numerical solution procedures have enabled computational fluid dynamicists to attempt increasingly difficult problems. In particular, efforts are focusing on computations of complex three-dimensional flow fields about realistic aerodynamic bodies. To perform such computations, a very accurate and detailed description of the surface geometry must be provided, and a three-dimensional grid must be generated in the space around the body. The geometry must be supplied in a format compatible with the grid generation requirements, and must be verified to be free of inconsistencies. A procedure for performing the geometry definition of a fighter aircraft that makes use of a commercial computer-aided design/computer-aided manufacturing system is presented. Furthermore, visual representations of the geometry are generated using a computer graphics system for verification of the body definition. Finally, the three-dimensional grids for fighter-like aircraft are generated by means of an efficient new parabolic grid generation method. This method exhibits good control of grid quality.

Formulation and implementation of a practical algorithm for parameter estimation with process and measurement noise

NASA Technical Reports Server (NTRS)

Maine, R. E.; Iliff, K. W.

1980-01-01

A new formulation is proposed for the problem of parameter estimation of dynamic systems with both process and measurement noise. The formulation gives estimates that are maximum likelihood asymptotically in time. The means used to overcome the difficulties encountered by previous formulations are discussed. It is then shown how the proposed formulation can be efficiently implemented in a computer program. A computer program using the proposed formulation is available in a form suitable for routine application. Examples with simulated and real data are given to illustrate that the program works well.

Retrospective indexing (RI) - A computer-aided indexing technique

NASA Technical Reports Server (NTRS)

Buchan, Ronald L.

1990-01-01

An account is given of a method for data base-updating designated 'computer-aided indexing' (CAI) which has been very efficiently implemented at NASA's Scientific and Technical Information Facility by means of retrospective indexing. Novel terms added to the NASA Thesaurus will therefore proceed directly into both the NASA-RECON aerospace information system and its portion of the ESA-Information Retrieval Service, giving users full access to material thus indexed. If a given term appears in the title of a record, it is given special weight. An illustrative graphic representation of the CAI search strategy is presented.

The use of computer-generated color graphic images for transient thermal analysis. [for hypersonic aircraft

NASA Technical Reports Server (NTRS)

Edwards, C. L. W.; Meissner, F. T.; Hall, J. B.

1979-01-01

Color computer graphics techniques were investigated as a means of rapidly scanning and interpreting large sets of transient heating data. The data presented were generated to support the conceptual design of a heat-sink thermal protection system (TPS) for a hypersonic research airplane. Color-coded vector and raster displays of the numerical geometry used in the heating calculations were employed to analyze skin thicknesses and surface temperatures of the heat-sink TPS under a variety of trajectory flight profiles. Both vector and raster displays proved to be effective means for rapidly identifying heat-sink mass concentrations, regions of high heating, and potentially adverse thermal gradients. The color-coded (raster) surface displays are a very efficient means for displaying surface-temperature and heating histories, and thereby the more stringent design requirements can quickly be identified. The related hardware and software developments required to implement both the vector and the raster displays for this application are also discussed.

Next generation communications satellites: multiple access and network studies

NASA Technical Reports Server (NTRS)

Meadows, H. E.; Schwartz, M.; Stern, T. E.; Ganguly, S.; Kraimeche, B.; Matsuo, K.; Gopal, I.

1982-01-01

Efficient resource allocation and network design for satellite systems serving heterogeneous user populations with large numbers of small direct-to-user Earth stations are discussed. Focus is on TDMA systems involving a high degree of frequency reuse by means of satellite-switched multiple beams (SSMB) with varying degrees of onboard processing. Algorithms for the efficient utilization of the satellite resources were developed. The effect of skewed traffic, overlapping beams and batched arrivals in packet-switched SSMB systems, integration of stream and bursty traffic, and optimal circuit scheduling in SSMB systems: performance bounds and computational complexity are discussed.

Hierarchical Poly Tree Configurations for the Solution of Dynamically Refined Finte Element Models

NASA Technical Reports Server (NTRS)

Gute, G. D.; Padovan, J.

1993-01-01

This paper demonstrates how a multilevel substructuring technique, called the Hierarchical Poly Tree (HPT), can be used to integrate a localized mesh refinement into the original finite element model more efficiently. The optimal HPT configurations for solving isoparametrically square h-, p-, and hp-extensions on single and multiprocessor computers is derived. In addition, the reduced number of stiffness matrix elements that must be stored when employing this type of solution strategy is quantified. Moreover, the HPT inherently provides localize 'error-trapping' and a logical, efficient means with which to isolate physically anomalous and analytically singular behavior.

Highway-runoff quality, and treatment efficiencies of a hydrodynamic-settling device and a stormwater-filtration device in Milwaukee, Wisconsin

USGS Publications Warehouse

Horwatich, Judy A.; Bannerman, Roger T.; Pearson, Robert

2011-01-01

The treatment efficiencies of two prefabricated stormwater-treatment devices were tested at a freeway site in a high-density urban part of Milwaukee, Wisconsin. One treatment device is categorized as a hydrodynamic-settling device (HSD), which removes pollutants by sedimentation and flotation. The other treatment device is categorized as a stormwater-filtration device (SFD), which removes pollutants by filtration and sedimentation. During runoff events, flow measurements were recorded and water-quality samples were collected at the inlet and outlet of each device. Efficiency-ratio and summation-of-load (SOL) calculations were used to estimate the treatment efficiency of each device. Event-mean concentrations and loads that were decreased by passing through the HSD include total suspended solids (TSS), suspended sediment (SS), total phosphorus (TP), total copper (TCu), and total zinc (TZn). The efficiency ratios for these constituents were 42, 57, 17, 33, and 23 percent, respectively. The SOL removal rates for these constituents were 25, 49, 10, 27, and 16 percent, respectively. Event-mean concentrations and loads that increased by passing through the HSD include chloride (Cl), total dissolved solids (TDS), and dissolved zinc (DZn). The efficiency ratios for these constituents were -347, -177, and 20 percent, respectively. Four constituents—dissolved phosphorus (DP), chemical oxygen demand (COD), total polycyclic aromatic hydrocarbon (PAH), and dissolved copper (DCu)—are not included in the list of computed efficiency ratio and SOL because the variability between sampled inlet and outlet pairs were not significantly different. Event-mean concentrations and loads that decreased by passing through the SFD include TSS, SS, TP, DCu, TCu, DZn, TZn, and COD. The efficiency ratios for these constituents were 59, 90, 40, 21, 66, 23, 66, and 18, respectively. The SOLs for these constituents were 50, 89, 37, 19, 60, 20, 65, and 21, respectively. Two constituents—DP and PAH—are not included in the lists of computed efficiency ratio and SOL because the variability between sampled inlet and outlet pairs were not significantly different. Similar to the HSD, the average efficiency ratios and SOLs for TDS and Cl were negative. Flow rates, high concentrations of SS, and particle-size distributions (PSD) can affect the treatment efficacies of the two devices. Flow rates equal to or greater than the design flow rate of the HSD had minimal or negative removal efficiencies for TSS and SS loads. Similar TSS removal efficiencies were observed at the SFD, but SS was consistently removed throughout the flow regime. Removal efficiencies were high for both devices when concentrations of SS and TSS approached 200 mg/L. A small number of runoff events were analyzed for PSD; the average sand content at the HSD was 33 percent and at the SFD was 71 percent. The 71-percent sand content may reflect the 90-percent removal efficiency of SS at the SFD. Particles retained at the bottom of both devices were largely sand-size or greater.

Small target detection using objectness and saliency

NASA Astrophysics Data System (ADS)

Zhang, Naiwen; Xiao, Yang; Fang, Zhiwen; Yang, Jian; Wang, Li; Li, Tao

2017-10-01

We are motived by the need for generic object detection algorithm which achieves high recall for small targets in complex scenes with acceptable computational efficiency. We propose a novel object detection algorithm, which has high localization quality with acceptable computational cost. Firstly, we obtain the objectness map as in BING[1] and use NMS to get the top N points. Then, k-means algorithm is used to cluster them into K classes according to their location. We set the center points of the K classes as seed points. For each seed point, an object potential region is extracted. Finally, a fast salient object detection algorithm[2] is applied to the object potential regions to highlight objectlike pixels, and a series of efficient post-processing operations are proposed to locate the targets. Our method runs at 5 FPS on 1000*1000 images, and significantly outperforms previous methods on small targets in cluttered background.

A Proposal of a Fast Computation Method for Thermal Capacity and Voltage ATC by Means of Homotopy Functions

NASA Astrophysics Data System (ADS)

Zoka, Yoshifumi; Yorino, Naoto; Kawano, Koki; Suenari, Hiroyasu

This paper proposes a fast computation method for Available Transfer Capability (ATC) with respect to thermal and voltage magnitude limits. In the paper, ATC is formulated as an optimization problem. In order to obtain the efficiency for the N-1 outage contingency calculations, linear sensitivity methods are applied for screening and ranking all contingency selections with respect to the thermal and voltage magnitude limits margin to identify the severest case. In addition, homotopy functions are used for the generator QV constrains to reduce the maximum error of the linear estimation. Then, the Primal-Dual Interior Point Method (PDIPM) is used to solve the optimization problem for the severest case only, in which the solutions of ATC can be obtained efficiently. The effectiveness of the proposed method is demonstrated through IEEE 30, 57, 118-bus systems.

An efficient variational method to study the denaturation of DNA induced by superhelical stress

NASA Astrophysics Data System (ADS)

Jost, Daniel; Everaers, Ralf

2010-03-01

Many fundamental biological processes, like transcription or replication, need the opening of the double-stranded DNA. One common way to control the local denaturation is to impose superhelical stress to the DNA using protein machineries. To describe superhelical effect for circular molecules, Benham introduced a model where the standard thermodynamic description of base-pairing is coupled with torsional stress energetics. Here, we introduce an efficient mean-field approximation of the Benham model. Our self-consistent solution is confident and computationally-fast, compared to the full treatment of the model. In particular, our formulation allows to compute the probability of bubble formation for given length and position along the sequence. Evolution of this probability as a function of the superhelical stress could inform us on the ability for organisms to control the strength of superhelicity acting on their genomes.

Fast adaptive flat-histogram ensemble to enhance the sampling in large systems

NASA Astrophysics Data System (ADS)

Xu, Shun; Zhou, Xin; Jiang, Yi; Wang, YanTing

2015-09-01

An efficient novel algorithm was developed to estimate the Density of States (DOS) for large systems by calculating the ensemble means of an extensive physical variable, such as the potential energy, U, in generalized canonical ensembles to interpolate the interior reverse temperature curve , where S( U) is the logarithm of the DOS. This curve is computed with different accuracies in different energy regions to capture the dependence of the reverse temperature on U without setting prior grid in the U space. By combining with a U-compression transformation, we decrease the computational complexity from O( N 3/2) in the normal Wang Landau type method to O( N 1/2) in the current algorithm, as the degrees of freedom of system N. The efficiency of the algorithm is demonstrated by applying to Lennard Jones fluids with various N, along with its ability to find different macroscopic states, including metastable states.

Diallel analysis for sex-linked and maternal effects.

PubMed

Zhu, J; Weir, B S

1996-01-01

Genetic models including sex-linked and maternal effects as well as autosomal gene effects are described. Monte Carlo simulations were conducted to compare efficiencies of estimation by minimum norm quadratic unbiased estimation (MINQUE) and restricted maximum likelihood (REML) methods. MINQUE(1), which has 1 for all prior values, has a similar efficiency to MINQUE(θ), which requires prior estimates of parameter values. MINQUE(1) has the advantage over REML of unbiased estimation and convenient computation. An adjusted unbiased prediction (AUP) method is developed for predicting random genetic effects. AUP is desirable for its easy computation and unbiasedness of both mean and variance of predictors. The jackknife procedure is appropriate for estimating the sampling variances of estimated variances (or covariances) and of predicted genetic effects. A t-test based on jackknife variances is applicable for detecting significance of variation. Worked examples from mice and silkworm data are given in order to demonstrate variance and covariance estimation and genetic effect prediction.

On Using Surrogates with Genetic Programming.

PubMed

Hildebrandt, Torsten; Branke, Jürgen

2015-01-01

One way to accelerate evolutionary algorithms with expensive fitness evaluations is to combine them with surrogate models. Surrogate models are efficiently computable approximations of the fitness function, derived by means of statistical or machine learning techniques from samples of fully evaluated solutions. But these models usually require a numerical representation, and therefore cannot be used with the tree representation of genetic programming (GP). In this paper, we present a new way to use surrogate models with GP. Rather than using the genotype directly as input to the surrogate model, we propose using a phenotypic characterization. This phenotypic characterization can be computed efficiently and allows us to define approximate measures of equivalence and similarity. Using a stochastic, dynamic job shop scenario as an example of simulation-based GP with an expensive fitness evaluation, we show how these ideas can be used to construct surrogate models and improve the convergence speed and solution quality of GP.

An Information Theoretic Characterisation of Auditory Encoding

PubMed Central

Overath, Tobias; Cusack, Rhodri; Kumar, Sukhbinder; von Kriegstein, Katharina; Warren, Jason D; Grube, Manon; Carlyon, Robert P; Griffiths, Timothy D

2007-01-01

The entropy metric derived from information theory provides a means to quantify the amount of information transmitted in acoustic streams like speech or music. By systematically varying the entropy of pitch sequences, we sought brain areas where neural activity and energetic demands increase as a function of entropy. Such a relationship is predicted to occur in an efficient encoding mechanism that uses less computational resource when less information is present in the signal: we specifically tested the hypothesis that such a relationship is present in the planum temporale (PT). In two convergent functional MRI studies, we demonstrated this relationship in PT for encoding, while furthermore showing that a distributed fronto-parietal network for retrieval of acoustic information is independent of entropy. The results establish PT as an efficient neural engine that demands less computational resource to encode redundant signals than those with high information content. PMID:17958472

An Efficient Local Correlation Matrix Decomposition Approach for the Localization Implementation of Ensemble-Based Assimilation Methods

NASA Astrophysics Data System (ADS)

Zhang, Hongqin; Tian, Xiangjun

2018-04-01

Ensemble-based data assimilation methods often use the so-called localization scheme to improve the representation of the ensemble background error covariance (Be). Extensive research has been undertaken to reduce the computational cost of these methods by using the localized ensemble samples to localize Be by means of a direct decomposition of the local correlation matrix C. However, the computational costs of the direct decomposition of the local correlation matrix C are still extremely high due to its high dimension. In this paper, we propose an efficient local correlation matrix decomposition approach based on the concept of alternating directions. This approach is intended to avoid direct decomposition of the correlation matrix. Instead, we first decompose the correlation matrix into 1-D correlation matrices in the three coordinate directions, then construct their empirical orthogonal function decomposition at low resolution. This procedure is followed by the 1-D spline interpolation process to transform the above decompositions to the high-resolution grid. Finally, an efficient correlation matrix decomposition is achieved by computing the very similar Kronecker product. We conducted a series of comparison experiments to illustrate the validity and accuracy of the proposed local correlation matrix decomposition approach. The effectiveness of the proposed correlation matrix decomposition approach and its efficient localization implementation of the nonlinear least-squares four-dimensional variational assimilation are further demonstrated by several groups of numerical experiments based on the Advanced Research Weather Research and Forecasting model.

Efficient and robust relaxation procedures for multi-component mixtures including phase transition

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

Han, Ee, E-mail: eehan@math.uni-bremen.de; Hantke, Maren, E-mail: maren.hantke@ovgu.de; Müller, Siegfried, E-mail: mueller@igpm.rwth-aachen.de

We consider a thermodynamic consistent multi-component model in multi-dimensions that is a generalization of the classical two-phase flow model of Baer and Nunziato. The exchange of mass, momentum and energy between the phases is described by additional source terms. Typically these terms are handled by relaxation procedures. Available relaxation procedures suffer from efficiency and robustness resulting in very costly computations that in general only allow for one-dimensional computations. Therefore we focus on the development of new efficient and robust numerical methods for relaxation processes. We derive exact procedures to determine mechanical and thermal equilibrium states. Further we introduce a novelmore » iterative method to treat the mass transfer for a three component mixture. All new procedures can be extended to an arbitrary number of inert ideal gases. We prove existence, uniqueness and physical admissibility of the resulting states and convergence of our new procedures. Efficiency and robustness of the procedures are verified by means of numerical computations in one and two space dimensions. - Highlights: • We develop novel relaxation procedures for a generalized, thermodynamically consistent Baer–Nunziato type model. • Exact procedures for mechanical and thermal relaxation procedures avoid artificial parameters. • Existence, uniqueness and physical admissibility of the equilibrium states are proven for special mixtures. • A novel iterative method for mass transfer is introduced for a three component mixture providing a unique and admissible equilibrium state.« less

Computationally efficient multibody simulations

NASA Technical Reports Server (NTRS)

Ramakrishnan, Jayant; Kumar, Manoj

1994-01-01

Computationally efficient approaches to the solution of the dynamics of multibody systems are presented in this work. The computational efficiency is derived from both the algorithmic and implementational standpoint. Order(n) approaches provide a new formulation of the equations of motion eliminating the assembly and numerical inversion of a system mass matrix as required by conventional algorithms. Computational efficiency is also gained in the implementation phase by the symbolic processing and parallel implementation of these equations. Comparison of this algorithm with existing multibody simulation programs illustrates the increased computational efficiency.

A space radiation transport method development

NASA Technical Reports Server (NTRS)

Wilson, J. W.; Tripathi, R. K.; Qualls, G. D.; Cucinotta, F. A.; Prael, R. E.; Norbury, J. W.; Heinbockel, J. H.; Tweed, J.

2004-01-01

Improved spacecraft shield design requires early entry of radiation constraints into the design process to maximize performance and minimize costs. As a result, we have been investigating high-speed computational procedures to allow shield analysis from the preliminary design concepts to the final design. In particular, we will discuss the progress towards a full three-dimensional and computationally efficient deterministic code for which the current HZETRN evaluates the lowest-order asymptotic term. HZETRN is the first deterministic solution to the Boltzmann equation allowing field mapping within the International Space Station (ISS) in tens of minutes using standard finite element method (FEM) geometry common to engineering design practice enabling development of integrated multidisciplinary design optimization methods. A single ray trace in ISS FEM geometry requires 14 ms and severely limits application of Monte Carlo methods to such engineering models. A potential means of improving the Monte Carlo efficiency in coupling to spacecraft geometry is given in terms of re-configurable computing and could be utilized in the final design as verification of the deterministic method optimized design. Published by Elsevier Ltd on behalf of COSPAR.

An efficient solution technique for shockwave-boundary layer interactions with flow separation and slot suction effects

NASA Technical Reports Server (NTRS)

Edwards, Jack R.; Mcrae, D. Scott

1991-01-01

An efficient method for computing two-dimensional compressible Navier-Stokes flow fields is presented. The solution algorithm is a fully-implicit approximate factorization technique based on an unsymmetric line Gauss-Seidel splitting of the equation system Jacobian matrix. Convergence characteristics are improved by the addition of acceleration techniques based on Shamanskii's method for nonlinear equations and Broyden's quasi-Newton update. Characteristic-based differencing of the equations is provided by means of Van Leer's flux vector splitting. In this investigation, emphasis is placed on the fast and accurate computation of shock-wave-boundary layer interactions with and without slot suction effects. In the latter context, a set of numerical boundary conditions for simulating the transpiration flow in an open slot is devised. Both laminar and turbulent cases are considered, with turbulent closure provided by a modified Cebeci-Smith algebraic model. Comparisons with computational and experimental data sets are presented for a variety of interactions, and a fully-coupled simulation of a plenum chamber/inlet flowfield with shock interaction and suction is also shown and discussed.

Modeling of the WSTF frictional heating apparatus in high pressure systems

NASA Technical Reports Server (NTRS)

Skowlund, Christopher T.

1992-01-01

In order to develop a computer program able to model the frictional heating of metals in high pressure oxygen or nitrogen a number of additions have been made to the frictional heating model originally developed for tests in low pressure helium. These additions include: (1) a physical property package for the gases to account for departures from the ideal gas state; (2) two methods for spatial discretization (finite differences with quadratic interpolation or orthogonal collocation on finite elements) which substantially reduce the computer time required to solve the transient heat balance; (3) more efficient programs for the integration of the ordinary differential equations resulting from the discretization of the partial differential equations; and (4) two methods for determining the best-fit parameters via minimization of the mean square error (either a direct search multivariable simplex method or a modified Levenburg-Marquardt algorithm). The resulting computer program has been shown to be accurate, efficient and robust for determining the heat flux or friction coefficient vs. time at the interface of the stationary and rotating samples.

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.

Fast two-stream method for computing diurnal-mean actinic flux in vertically inhomogeneous atmospheres

NASA Technical Reports Server (NTRS)

Filyushkin, V. V.; Madronich, S.; Brasseur, G. P.; Petropavlovskikh, I. V.

1994-01-01

Based on a derivation of the two-stream daytime-mean equations of radiative flux transfer, a method for computing the daytime-mean actinic fluxes in the absorbing and scattering vertically inhomogeneous atmosphere is suggested. The method applies direct daytime integration of the particular solutions of the two-stream approximations or the source functions. It is valid for any duration of period of averaging. The merit of the method is that the multiple scattering computation is carried out only once for the whole averaging period. It can be implemented with a number of widely used two-stream approximations. The method agrees with the results obtained with 200-point multiple scattering calculations. The method was also tested in runs with a 1-km cloud layer with optical depth of 10, as well as with aerosol background. Comparison of the results obtained for a cloud subdivided into 20 layers with those obtained for a one-layer cloud with the same optical parameters showed that direct integration of particular solutions possesses an 'analytical' accuracy. In the case of the source function interpolation, the actinic fluxes calculated above the one-layer and 20-layer clouds agreed within 1%-1.5%, while below the cloud they may differ up to 5% (in the worst case). The ways of enhancing the accuracy (in a 'two-stream sense') and computational efficiency of the method are discussed.

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.

A fast mass spring model solver for high-resolution elastic objects

NASA Astrophysics Data System (ADS)

Zheng, Mianlun; Yuan, Zhiyong; Zhu, Weixu; Zhang, Guian

2017-03-01

Real-time simulation of elastic objects is of great importance for computer graphics and virtual reality applications. The fast mass spring model solver can achieve visually realistic simulation in an efficient way. Unfortunately, this method suffers from resolution limitations and lack of mechanical realism for a surface geometry model, which greatly restricts its application. To tackle these problems, in this paper we propose a fast mass spring model solver for high-resolution elastic objects. First, we project the complex surface geometry model into a set of uniform grid cells as cages through *cages mean value coordinate method to reflect its internal structure and mechanics properties. Then, we replace the original Cholesky decomposition method in the fast mass spring model solver with a conjugate gradient method, which can make the fast mass spring model solver more efficient for detailed surface geometry models. Finally, we propose a graphics processing unit accelerated parallel algorithm for the conjugate gradient method. Experimental results show that our method can realize efficient deformation simulation of 3D elastic objects with visual reality and physical fidelity, which has a great potential for applications in computer animation.

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.

Efficient implementation of one- and two-component analytical energy gradients in exact two-component theory

NASA Astrophysics Data System (ADS)

Franzke, Yannick J.; Middendorf, Nils; Weigend, Florian

2018-03-01

We present an efficient algorithm for one- and two-component analytical energy gradients with respect to nuclear displacements in the exact two-component decoupling approach to the one-electron Dirac equation (X2C). Our approach is a generalization of the spin-free ansatz by Cheng and Gauss [J. Chem. Phys. 135, 084114 (2011)], where the perturbed one-electron Hamiltonian is calculated by solving a first-order response equation. Computational costs are drastically reduced by applying the diagonal local approximation to the unitary decoupling transformation (DLU) [D. Peng and M. Reiher, J. Chem. Phys. 136, 244108 (2012)] to the X2C Hamiltonian. The introduced error is found to be almost negligible as the mean absolute error of the optimized structures amounts to only 0.01 pm. Our implementation in TURBOMOLE is also available within the finite nucleus model based on a Gaussian charge distribution. For a X2C/DLU gradient calculation, computational effort scales cubically with the molecular size, while storage increases quadratically. The efficiency is demonstrated in calculations of large silver clusters and organometallic iridium complexes.

Observations on computational methodologies for use in large-scale, gradient-based, multidisciplinary design incorporating advanced CFD codes

NASA Technical Reports Server (NTRS)

Newman, P. A.; Hou, G. J.-W.; Jones, H. E.; Taylor, A. C., III; Korivi, V. M.

1992-01-01

How a combination of various computational methodologies could reduce the enormous computational costs envisioned in using advanced CFD codes in gradient based optimized multidisciplinary design (MdD) procedures is briefly outlined. Implications of these MdD requirements upon advanced CFD codes are somewhat different than those imposed by a single discipline design. A means for satisfying these MdD requirements for gradient information is presented which appear to permit: (1) some leeway in the CFD solution algorithms which can be used; (2) an extension to 3-D problems; and (3) straightforward use of other computational methodologies. Many of these observations have previously been discussed as possibilities for doing parts of the problem more efficiently; the contribution here is observing how they fit together in a mutually beneficial way.

Fast Image Texture Classification Using Decision Trees

NASA Technical Reports Server (NTRS)

Thompson, David R.

2011-01-01

Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.

Improved object optimal synthetic description, modeling, learning, and discrimination by GEOGINE computational kernel

NASA Astrophysics Data System (ADS)

Fiorini, Rodolfo A.; Dacquino, Gianfranco

2005-03-01

GEOGINE (GEOmetrical enGINE), a state-of-the-art OMG (Ontological Model Generator) based on n-D Tensor Invariants for n-Dimensional shape/texture optimal synthetic representation, description and learning, was presented in previous conferences elsewhere recently. Improved computational algorithms based on the computational invariant theory of finite groups in Euclidean space and a demo application is presented. Progressive model automatic generation is discussed. GEOGINE can be used as an efficient computational kernel for fast reliable application development and delivery in advanced biomedical engineering, biometric, intelligent computing, target recognition, content image retrieval, data mining technological areas mainly. Ontology can be regarded as a logical theory accounting for the intended meaning of a formal dictionary, i.e., its ontological commitment to a particular conceptualization of the world object. According to this approach, "n-D Tensor Calculus" can be considered a "Formal Language" to reliably compute optimized "n-Dimensional Tensor Invariants" as specific object "invariant parameter and attribute words" for automated n-Dimensional shape/texture optimal synthetic object description by incremental model generation. The class of those "invariant parameter and attribute words" can be thought as a specific "Formal Vocabulary" learned from a "Generalized Formal Dictionary" of the "Computational Tensor Invariants" language. Even object chromatic attributes can be effectively and reliably computed from object geometric parameters into robust colour shape invariant characteristics. As a matter of fact, any highly sophisticated application needing effective, robust object geometric/colour invariant attribute capture and parameterization features, for reliable automated object learning and discrimination can deeply benefit from GEOGINE progressive automated model generation computational kernel performance. Main operational advantages over previous, similar approaches are: 1) Progressive Automated Invariant Model Generation, 2) Invariant Minimal Complete Description Set for computational efficiency, 3) Arbitrary Model Precision for robust object description and identification.

Training Technology Handbook Development. Phase I. Annotated Literature Review.

DTIC Science & Technology

1981-08-01

chief means for currently influencing the students , learning is through the sequencing of instruction . Use of the findings, models, and theories from...determine what aspects of the learning experience might influence student attitudes toward computer-assisted instruction (CAI). Sixty-four randomly...learners seem to learn most efficiently when left alone with the instructional objective and the necessary materials. The middle aptitude trainees appear to

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.

Hierarchical parallelisation of functional renormalisation group calculations - hp-fRG

NASA Astrophysics Data System (ADS)

Rohe, Daniel

2016-10-01

The functional renormalisation group (fRG) has evolved into a versatile tool in condensed matter theory for studying important aspects of correlated electron systems. Practical applications of the method often involve a high numerical effort, motivating the question in how far High Performance Computing (HPC) can leverage the approach. In this work we report on a multi-level parallelisation of the underlying computational machinery and show that this can speed up the code by several orders of magnitude. This in turn can extend the applicability of the method to otherwise inaccessible cases. We exploit three levels of parallelisation: Distributed computing by means of Message Passing (MPI), shared-memory computing using OpenMP, and vectorisation by means of SIMD units (single-instruction-multiple-data). Results are provided for two distinct High Performance Computing (HPC) platforms, namely the IBM-based BlueGene/Q system JUQUEEN and an Intel Sandy-Bridge-based development cluster. We discuss how certain issues and obstacles were overcome in the course of adapting the code. Most importantly, we conclude that this vast improvement can actually be accomplished by introducing only moderate changes to the code, such that this strategy may serve as a guideline for other researcher to likewise improve the efficiency of their codes.

Lyapunov exponents, covariant vectors and shadowing sensitivity analysis of 3D wakes: from laminar to chaotic regimes

NASA Astrophysics Data System (ADS)

Wang, Qiqi; Rigas, Georgios; Esclapez, Lucas; Magri, Luca; Blonigan, Patrick

2016-11-01

Bluff body flows are of fundamental importance to many engineering applications involving massive flow separation and in particular the transport industry. Coherent flow structures emanating in the wake of three-dimensional bluff bodies, such as cars, trucks and lorries, are directly linked to increased aerodynamic drag, noise and structural fatigue. For low Reynolds laminar and transitional regimes, hydrodynamic stability theory has aided the understanding and prediction of the unstable dynamics. In the same framework, sensitivity analysis provides the means for efficient and optimal control, provided the unstable modes can be accurately predicted. However, these methodologies are limited to laminar regimes where only a few unstable modes manifest. Here we extend the stability analysis to low-dimensional chaotic regimes by computing the Lyapunov covariant vectors and their associated Lyapunov exponents. We compare them to eigenvectors and eigenvalues computed in traditional hydrodynamic stability analysis. Computing Lyapunov covariant vectors and Lyapunov exponents also enables the extension of sensitivity analysis to chaotic flows via the shadowing method. We compare the computed shadowing sensitivities to traditional sensitivity analysis. These Lyapunov based methodologies do not rely on mean flow assumptions, and are mathematically rigorous for calculating sensitivities of fully unsteady flow simulations.

TU-H-CAMPUS-IeP1-01: Bias and Computational Efficiency of Variance Reduction Methods for the Monte Carlo Simulation of Imaging Detectors

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

Sharma, D; Badano, A; Sempau, J

Purpose: Variance reduction techniques (VRTs) are employed in Monte Carlo simulations to obtain estimates with reduced statistical uncertainty for a given simulation time. In this work, we study the bias and efficiency of a VRT for estimating the response of imaging detectors. Methods: We implemented Directed Sampling (DS), preferentially directing a fraction of emitted optical photons directly towards the detector by altering the isotropic model. The weight of each optical photon is appropriately modified to maintain simulation estimates unbiased. We use a Monte Carlo tool called fastDETECT2 (part of the hybridMANTIS open-source package) for optical transport, modified for VRT. Themore » weight of each photon is calculated as the ratio of original probability (no VRT) and the new probability for a particular direction. For our analysis of bias and efficiency, we use pulse height spectra, point response functions, and Swank factors. We obtain results for a variety of cases including analog (no VRT, isotropic distribution), and DS with 0.2 and 0.8 optical photons directed towards the sensor plane. We used 10,000, 25-keV primaries. Results: The Swank factor for all cases in our simplified model converged fast (within the first 100 primaries) to a stable value of 0.9. The root mean square error per pixel for DS VRT for the point response function between analog and VRT cases was approximately 5e-4. Conclusion: Our preliminary results suggest that DS VRT does not affect the estimate of the mean for the Swank factor. Our findings indicate that it may be possible to design VRTs for imaging detector simulations to increase computational efficiency without introducing bias.« less

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.

Mass fluctuation kinetics: Capturing stochastic effects in systems of chemical reactions through coupled mean-variance computations

NASA Astrophysics Data System (ADS)

Gómez-Uribe, Carlos A.; Verghese, George C.

2007-01-01

The intrinsic stochastic effects in chemical reactions, and particularly in biochemical networks, may result in behaviors significantly different from those predicted by deterministic mass action kinetics (MAK). Analyzing stochastic effects, however, is often computationally taxing and complex. The authors describe here the derivation and application of what they term the mass fluctuation kinetics (MFK), a set of deterministic equations to track the means, variances, and covariances of the concentrations of the chemical species in the system. These equations are obtained by approximating the dynamics of the first and second moments of the chemical master equation. Apart from needing knowledge of the system volume, the MFK description requires only the same information used to specify the MAK model, and is not significantly harder to write down or apply. When the effects of fluctuations are negligible, the MFK description typically reduces to MAK. The MFK equations are capable of describing the average behavior of the network substantially better than MAK, because they incorporate the effects of fluctuations on the evolution of the means. They also account for the effects of the means on the evolution of the variances and covariances, to produce quite accurate uncertainty bands around the average behavior. The MFK computations, although approximate, are significantly faster than Monte Carlo methods for computing first and second moments in systems of chemical reactions. They may therefore be used, perhaps along with a few Monte Carlo simulations of sample state trajectories, to efficiently provide a detailed picture of the behavior of a chemical system.

Benchmark Lisp And Ada Programs

NASA Technical Reports Server (NTRS)

Davis, Gloria; Galant, David; Lim, Raymond; Stutz, John; Gibson, J.; Raghavan, B.; Cheesema, P.; Taylor, W.

1992-01-01

Suite of nonparallel benchmark programs, ELAPSE, designed for three tests: comparing efficiency of computer processing via Lisp vs. Ada; comparing efficiencies of several computers processing via Lisp; or comparing several computers processing via Ada. Tests efficiency which computer executes routines in each language. Available for computer equipped with validated Ada compiler and/or Common Lisp system.

Efficient Numeric and Geometric Computations using Heterogeneous Shared Memory Architectures

DTIC Science & Technology

2017-10-04

Report: Efficient Numeric and Geometric Computations using Heterogeneous Shared Memory Architectures The views, opinions and/or findings contained in this...Chapel Hill Title: Efficient Numeric and Geometric Computations using Heterogeneous Shared Memory Architectures Report Term: 0-Other Email: dm...algorithms for scientific and geometric computing by exploiting the power and performance efficiency of heterogeneous shared memory architectures . These

Damage level prediction of non-reshaped berm breakwater using ANN, SVM and ANFIS models

NASA Astrophysics Data System (ADS)

Mandal, Sukomal; Rao, Subba; N., Harish; Lokesha

2012-06-01

The damage analysis of coastal structure is very important as it involves many design parameters to be considered for the better and safe design of structure. In the present study experimental data for non-reshaped berm breakwater are collected from Marine Structures Laboratory, Department of Applied Mechanics and Hydraulics, NITK, Surathkal, India. Soft computing techniques like Artificial Neural Network (ANN), Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference system (ANFIS) models are constructed using experimental data sets to predict the damage level of non-reshaped berm breakwater. The experimental data are used to train ANN, SVM and ANFIS models and results are determined in terms of statistical measures like mean square error, root mean square error, correla-tion coefficient and scatter index. The result shows that soft computing techniques i.e., ANN, SVM and ANFIS can be efficient tools in predicting damage levels of non reshaped berm breakwater.

Topological phases in the Haldane model with spin–spin on-site interactions

NASA Astrophysics Data System (ADS)

Rubio-García, A.; García-Ripoll, J. J.

2018-04-01

Ultracold atom experiments allow the study of topological insulators, such as the non-interacting Haldane model. In this work we study a generalization of the Haldane model with spin–spin on-site interactions that can be implemented on such experiments. We focus on measuring the winding number, a topological invariant, of the ground state, which we compute using a mean-field calculation that effectively captures long-range correlations and a matrix product state computation in a lattice with 64 sites. Our main result is that we show how the topological phases present in the non-interacting model survive until the interactions are comparable to the kinetic energy. We also demonstrate the accuracy of our mean-field approach in efficiently capturing long-range correlations. Based on state-of-the-art ultracold atom experiments, we propose an implementation of our model that can give information about the topological phases.

Behavioral and computational aspects of language and its acquisition

NASA Astrophysics Data System (ADS)

Edelman, Shimon; Waterfall, Heidi

2007-12-01

One of the greatest challenges facing the cognitive sciences is to explain what it means to know a language, and how the knowledge of language is acquired. The dominant approach to this challenge within linguistics has been to seek an efficient characterization of the wealth of documented structural properties of language in terms of a compact generative grammar-ideally, the minimal necessary set of innate, universal, exception-less, highly abstract rules that jointly generate all and only the observed phenomena and are common to all human languages. We review developmental, behavioral, and computational evidence that seems to favor an alternative view of language, according to which linguistic structures are generated by a large, open set of constructions of varying degrees of abstraction and complexity, which embody both form and meaning and are acquired through socially situated experience in a given language community, by probabilistic learning algorithms that resemble those at work in other cognitive modalities.

Tertiary structure-based analysis of microRNA–target interactions

PubMed Central

Gan, Hin Hark; Gunsalus, Kristin C.

2013-01-01

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

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.

Genotype Imputation with Millions of Reference Samples

PubMed Central

Browning, Brian L.; Browning, Sharon R.

2016-01-01

We present a genotype imputation method that scales to millions of reference samples. The imputation method, based on the Li and Stephens model and implemented in Beagle v.4.1, is parallelized and memory efficient, making it well suited to multi-core computer processors. It achieves fast, accurate, and memory-efficient genotype imputation by restricting the probability model to markers that are genotyped in the target samples and by performing linear interpolation to impute ungenotyped variants. We compare Beagle v.4.1 with Impute2 and Minimac3 by using 1000 Genomes Project data, UK10K Project data, and simulated data. All three methods have similar accuracy but different memory requirements and different computation times. When imputing 10 Mb of sequence data from 50,000 reference samples, Beagle’s throughput was more than 100× greater than Impute2’s throughput on our computer servers. When imputing 10 Mb of sequence data from 200,000 reference samples in VCF format, Minimac3 consumed 26× more memory per computational thread and 15× more CPU time than Beagle. We demonstrate that Beagle v.4.1 scales to much larger reference panels by performing imputation from a simulated reference panel having 5 million samples and a mean marker density of one marker per four base pairs. PMID:26748515

Efficient visibility-driven medical image visualisation via adaptive binned visibility histogram.

PubMed

Jung, Younhyun; Kim, Jinman; Kumar, Ashnil; Feng, David Dagan; Fulham, Michael

2016-07-01

'Visibility' is a fundamental optical property that represents the observable, by users, proportion of the voxels in a volume during interactive volume rendering. The manipulation of this 'visibility' improves the volume rendering processes; for instance by ensuring the visibility of regions of interest (ROIs) or by guiding the identification of an optimal rendering view-point. The construction of visibility histograms (VHs), which represent the distribution of all the visibility of all voxels in the rendered volume, enables users to explore the volume with real-time feedback about occlusion patterns among spatially related structures during volume rendering manipulations. Volume rendered medical images have been a primary beneficiary of VH given the need to ensure that specific ROIs are visible relative to the surrounding structures, e.g. the visualisation of tumours that may otherwise be occluded by neighbouring structures. VH construction and its subsequent manipulations, however, are computationally expensive due to the histogram binning of the visibilities. This limits the real-time application of VH to medical images that have large intensity ranges and volume dimensions and require a large number of histogram bins. In this study, we introduce an efficient adaptive binned visibility histogram (AB-VH) in which a smaller number of histogram bins are used to represent the visibility distribution of the full VH. We adaptively bin medical images by using a cluster analysis algorithm that groups the voxels according to their intensity similarities into a smaller subset of bins while preserving the distribution of the intensity range of the original images. We increase efficiency by exploiting the parallel computation and multiple render targets (MRT) extension of the modern graphical processing units (GPUs) and this enables efficient computation of the histogram. We show the application of our method to single-modality computed tomography (CT), magnetic resonance (MR) imaging and multi-modality positron emission tomography-CT (PET-CT). In our experiments, the AB-VH markedly improved the computational efficiency for the VH construction and thus improved the subsequent VH-driven volume manipulations. This efficiency was achieved without major degradation in the VH visually and numerical differences between the AB-VH and its full-bin counterpart. We applied several variants of the K-means clustering algorithm with varying Ks (the number of clusters) and found that higher values of K resulted in better performance at a lower computational gain. The AB-VH also had an improved performance when compared to the conventional method of down-sampling of the histogram bins (equal binning) for volume rendering visualisation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Efficient Mean Field Variational Algorithm for Data Assimilation (Invited)

NASA Astrophysics Data System (ADS)

Vrettas, M. D.; Cornford, D.; Opper, M.

2013-12-01

Data assimilation algorithms combine available observations of physical systems with the assumed model dynamics in a systematic manner, to produce better estimates of initial conditions for prediction. Broadly they can be categorized in three main approaches: (a) sequential algorithms, (b) sampling methods and (c) variational algorithms which transform the density estimation problem to an optimization problem. However, given finite computational resources, only a handful of ensemble Kalman filters and 4DVar algorithms have been applied operationally to very high dimensional geophysical applications, such as weather forecasting. In this paper we present a recent extension to our variational Bayesian algorithm which seeks the ';optimal' posterior distribution over the continuous time states, within a family of non-stationary Gaussian processes. Our initial work on variational Bayesian approaches to data assimilation, unlike the well-known 4DVar method which seeks only the most probable solution, computes the best time varying Gaussian process approximation to the posterior smoothing distribution for dynamical systems that can be represented by stochastic differential equations. This approach was based on minimising the Kullback-Leibler divergence, over paths, between the true posterior and our Gaussian process approximation. Whilst the observations were informative enough to keep the posterior smoothing density close to Gaussian the algorithm proved very effective on low dimensional systems (e.g. O(10)D). However for higher dimensional systems, the high computational demands make the algorithm prohibitively expensive. To overcome the difficulties presented in the original framework and make our approach more efficient in higher dimensional systems we have been developing a new mean field version of the algorithm which treats the state variables at any given time as being independent in the posterior approximation, while still accounting for their relationships in the mean solution arising from the original system dynamics. Here we present this new mean field approach, illustrating its performance on a range of benchmark data assimilation problems whose dimensionality varies from O(10) to O(10^3)D. We emphasise that the variational Bayesian approach we adopt, unlike other variational approaches, provides a natural bound on the marginal likelihood of the observations given the model parameters which also allows for inference of (hyper-) parameters such as observational errors, parameters in the dynamical model and model error representation. We also stress that since our approach is intrinsically parallel it can be implemented very efficiently to address very long data assimilation time windows. Moreover, like most traditional variational approaches our Bayesian variational method has the benefit of being posed as an optimisation problem therefore its complexity can be tuned to the available computational resources. We finish with a sketch of possible future directions.

Internal air flow analysis of a bladeless micro aerial vehicle hemisphere body using computational fluid dynamic

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

Othman, M. N. K., E-mail: najibkhir86@gmail.com, E-mail: zuradzman@unimap.edu.my, E-mail: hazry@unimap.edu.my, E-mail: khairunizam@unimap.edu.my, E-mail: shahriman@unimap.edu.my, E-mail: s.yaacob@unimap.edu.my, E-mail: syedfaiz@unimap.edu.my, E-mail: abadal@unimap.edu.my; Zuradzman, M. Razlan, E-mail: najibkhir86@gmail.com, E-mail: zuradzman@unimap.edu.my, E-mail: hazry@unimap.edu.my, E-mail: khairunizam@unimap.edu.my, E-mail: shahriman@unimap.edu.my, E-mail: s.yaacob@unimap.edu.my, E-mail: syedfaiz@unimap.edu.my, E-mail: abadal@unimap.edu.my; Hazry, D., E-mail: najibkhir86@gmail.com, E-mail: zuradzman@unimap.edu.my, E-mail: hazry@unimap.edu.my, E-mail: khairunizam@unimap.edu.my, E-mail: shahriman@unimap.edu.my, E-mail: s.yaacob@unimap.edu.my, E-mail: syedfaiz@unimap.edu.my, E-mail: abadal@unimap.edu.my

2014-12-04

This paper explain the analysis of internal air flow velocity of a bladeless vertical takeoff and landing (VTOL) Micro Aerial Vehicle (MAV) hemisphere body. In mechanical design, before produce a prototype model, several analyses should be done to ensure the product's effectiveness and efficiency. There are two types of analysis method can be done in mechanical design; mathematical modeling and computational fluid dynamic. In this analysis, I used computational fluid dynamic (CFD) by using SolidWorks Flow Simulation software. The idea came through to overcome the problem of ordinary quadrotor UAV which has larger size due to using four rotors andmore » the propellers are exposed to environment. The bladeless MAV body is designed to protect all electronic parts, which means it can be used in rainy condition. It also has been made to increase the thrust produced by the ducted propeller compare to exposed propeller. From the analysis result, the air flow velocity at the ducted area increased to twice the inlet air. This means that the duct contribute to the increasing of air velocity.« less

Internal air flow analysis of a bladeless micro aerial vehicle hemisphere body using computational fluid dynamic

NASA Astrophysics Data System (ADS)

Othman, M. N. K.; Zuradzman, M. Razlan; Hazry, D.; Khairunizam, Wan; Shahriman, A. B.; Yaacob, S.; Ahmed, S. Faiz; Hussain, Abadalsalam T.

2014-12-01

This paper explain the analysis of internal air flow velocity of a bladeless vertical takeoff and landing (VTOL) Micro Aerial Vehicle (MAV) hemisphere body. In mechanical design, before produce a prototype model, several analyses should be done to ensure the product's effectiveness and efficiency. There are two types of analysis method can be done in mechanical design; mathematical modeling and computational fluid dynamic. In this analysis, I used computational fluid dynamic (CFD) by using SolidWorks Flow Simulation software. The idea came through to overcome the problem of ordinary quadrotor UAV which has larger size due to using four rotors and the propellers are exposed to environment. The bladeless MAV body is designed to protect all electronic parts, which means it can be used in rainy condition. It also has been made to increase the thrust produced by the ducted propeller compare to exposed propeller. From the analysis result, the air flow velocity at the ducted area increased to twice the inlet air. This means that the duct contribute to the increasing of air velocity.

Inherent Conservatism in Deterministic Quasi-Static Structural Analysis

NASA Technical Reports Server (NTRS)

Verderaime, V.

1997-01-01

The cause of the long-suspected excessive conservatism in the prevailing structural deterministic safety factor has been identified as an inherent violation of the error propagation laws when reducing statistical data to deterministic values and then combining them algebraically through successive structural computational processes. These errors are restricted to the applied stress computations, and because mean and variations of the tolerance limit format are added, the errors are positive, serially cumulative, and excessively conservative. Reliability methods circumvent these errors and provide more efficient and uniform safe structures. The document is a tutorial on the deficiencies and nature of the current safety factor and of its improvement and transition to absolute reliability.

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

Jacob, Reed B.; Ding, Feng; Ye, Dongmei

Organophosphates are widely used for peaceful (agriculture) and military purposes (chemical warfare agents). The extraordinary toxicity of organophosphates and the risk of deployment, make it critical to develop means for their rapid and efficient deactivation. Organophosphate hydrolase (OPH) already plays an important role in organophosphate remediation, but is insufficient for therapeutic or prophylactic purposes primarily due to low substrate affinity. Current efforts focus on directly modifying the active site to differentiate substrate specificity and increase catalytic activity. Here, we present a novel strategy for enhancing the general catalytic efficiency of OPH through computational redesign of the residues that are allostericallymore » coupled to the active site and validated our design by mutagenesis. Specifically, we identify five such hot-spot residues for allosteric regulation and assay these mutants for hydrolysis activity against paraoxon, a chemical-weapons simulant. A high percentage of the predicted mutants exhibit enhanced activity over wild-type (k cat =16.63 s -1), such as T199I/T54I (899.5 s -1) and C227V/T199I/T54I (848 s -1), while the Km remains relatively unchanged in our high-throughput cell-free expression system. Further computational studies of protein dynamics reveal four distinct distal regions coupled to the active site that display significant changes in conformation dynamics upon these identified mutations. These results validate a computational design method that is both efficient and easily adapted as a general procedure for enzymatic enhancement.« less

Analytic energy gradients for orbital-optimized MP3 and MP2.5 with the density-fitting approximation: An efficient implementation.

PubMed

Bozkaya, Uğur

2018-03-15

Efficient implementations of analytic gradients for the orbital-optimized MP3 and MP2.5 and their standard versions with the density-fitting approximation, which are denoted as DF-MP3, DF-MP2.5, DF-OMP3, and DF-OMP2.5, are presented. The DF-MP3, DF-MP2.5, DF-OMP3, and DF-OMP2.5 methods are applied to a set of alkanes and noncovalent interaction complexes to compare the computational cost with the conventional MP3, MP2.5, OMP3, and OMP2.5. Our results demonstrate that density-fitted perturbation theory (DF-MP) methods considered substantially reduce the computational cost compared to conventional MP methods. The efficiency of our DF-MP methods arise from the reduced input/output (I/O) time and the acceleration of gradient related terms, such as computations of particle density and generalized Fock matrices (PDMs and GFM), solution of the Z-vector equation, back-transformations of PDMs and GFM, and evaluation of analytic gradients in the atomic orbital basis. Further, application results show that errors introduced by the DF approach are negligible. Mean absolute errors for bond lengths of a molecular set, with the cc-pCVQZ basis set, is 0.0001-0.0002 Å. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Flagged uniform particle splitting for variance reduction in proton and carbon ion track-structure simulations

NASA Astrophysics Data System (ADS)

Ramos-Méndez, José; Schuemann, Jan; Incerti, Sebastien; Paganetti, Harald; Schulte, Reinhard; Faddegon, Bruce

2017-08-01

Flagged uniform particle splitting was implemented with two methods to improve the computational efficiency of Monte Carlo track structure simulations with TOPAS-nBio by enhancing the production of secondary electrons in ionization events. In method 1 the Geant4 kernel was modified. In method 2 Geant4 was not modified. In both methods a unique flag number assigned to each new split electron was inherited by its progeny, permitting reclassification of the split events as if produced by independent histories. Computational efficiency and accuracy were evaluated for simulations of 0.5-20 MeV protons and 1-20 MeV u-1 carbon ions for three endpoints: (1) mean of the ionization cluster size distribution, (2) mean number of DNA single-strand breaks (SSBs) and double-strand breaks (DSBs) classified with DBSCAN, and (3) mean number of SSBs and DSBs classified with a geometry-based algorithm. For endpoint (1), simulation efficiency was 3 times lower when splitting electrons generated by direct ionization events of primary particles than when splitting electrons generated by the first ionization events of secondary electrons. The latter technique was selected for further investigation. The following results are for method 2, with relative efficiencies about 4.5 times lower for method 1. For endpoint (1), relative efficiency at 128 split electrons approached maximum, increasing with energy from 47.2  ±  0.2 to 66.9  ±  0.2 for protons, decreasing with energy from 51.3  ±  0.4 to 41.7  ±  0.2 for carbon. For endpoint (2), relative efficiency increased with energy, from 20.7  ±  0.1 to 50.2  ±  0.3 for protons, 15.6  ±  0.1 to 20.2  ±  0.1 for carbon. For endpoint (3) relative efficiency increased with energy, from 31.0  ±  0.2 to 58.2  ±  0.4 for protons, 23.9  ±  0.1 to 26.2  ±  0.2 for carbon. Simulation results with and without splitting agreed within 1% (2 standard deviations) for endpoints (1) and (2), within 2% (1 standard deviation) for endpoint (3). In conclusion, standard particle splitting variance reduction techniques can be successfully implemented in Monte Carlo track structure codes.

Methodological Foundations for Designing Intelligent Computer-Based Training

DTIC Science & Technology

1991-09-03

student models, graphic forms, version control data structures, flowcharts , etc. Circuit simulations are an obvious case. A circuit, after all, can... flowcharts as a basic data structure, and we were able to generalize our tools to create a flowchart drawing tool for inputting both the appearance and...the meaning of flowcharts efficiently. For the Sherlock work, we built a tool that permitted inputting of information about front panels and

A Fast Algorithm for Lattice Hyperonic Potentials

NASA Astrophysics Data System (ADS)

Nemura, Hidekatsu; Aoki, Sinya; Doi, Takumi; Gongyo, Shinya; Hatsuda, Tetsuo; Ikeda, Yoichi; Inoue, Takashi; Iritani, Takumi; Ishii, Noriyoshi; Miyamoto, Takaya; Murano, Keiko; Sasaki, Kenji

We describe an efficient algorithm to compute a large number of baryon-baryon interactions from NN to ΞΞ by means of HAL QCD method, which lays the groundwork for the nearly physical point lattice QCD calculation with volume (96a)4 ≈ (8.2 fm)4. Preliminary results of ΛN potential calculated with quark masses corresponding to (mπ, mK) ≈ (146,525) MeV are presented.

Groundwater management under uncertainty using a stochastic multi-cell model

NASA Astrophysics Data System (ADS)

Joodavi, Ata; Zare, Mohammad; Ziaei, Ali Naghi; Ferré, Ty P. A.

2017-08-01

The optimization of spatially complex groundwater management models over long time horizons requires the use of computationally efficient groundwater flow models. This paper presents a new stochastic multi-cell lumped-parameter aquifer model that explicitly considers uncertainty in groundwater recharge. To achieve this, the multi-cell model is combined with the constrained-state formulation method. In this method, the lower and upper bounds of groundwater heads are incorporated into the mass balance equation using indicator functions. This provides expressions for the means, variances and covariances of the groundwater heads, which can be included in the constraint set in an optimization model. This method was used to formulate two separate stochastic models: (i) groundwater flow in a two-cell aquifer model with normal and non-normal distributions of groundwater recharge; and (ii) groundwater management in a multiple cell aquifer in which the differences between groundwater abstractions and water demands are minimized. The comparison between the results obtained from the proposed modeling technique with those from Monte Carlo simulation demonstrates the capability of the proposed models to approximate the means, variances and covariances. Significantly, considering covariances between the heads of adjacent cells allows a more accurate estimate of the variances of the groundwater heads. Moreover, this modeling technique requires no discretization of state variables, thus offering an efficient alternative to computationally demanding methods.

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.

Optimal focal-plane restoration

NASA Technical Reports Server (NTRS)

Reichenbach, Stephen E.; Park, Stephen K.

1989-01-01

Image restoration can be implemented efficiently by calculating the convolution of the digital image and a small kernel during image acquisition. Processing the image in the focal-plane in this way requires less computation than traditional Fourier-transform-based techniques such as the Wiener filter and constrained least-squares filter. Here, the values of the convolution kernel that yield the restoration with minimum expected mean-square error are determined using a frequency analysis of the end-to-end imaging system. This development accounts for constraints on the size and shape of the spatial kernel and all the components of the imaging system. Simulation results indicate the technique is effective and efficient.

Influence of panel fastening on the acoustic performance of light-weight building elements: Study by sound transmission and laser scanning vibrometry

NASA Astrophysics Data System (ADS)

Roozen, N. B.; Muellner, H.; Labelle, L.; Rychtáriková, M.; Glorieux, C.

2015-06-01

Structural details and workmanship can cause considerable differences in sound insulation properties of timber frame partitions. In this study, the influence of panel fastening is investigated experimentally by means of standardized sound reduction index measurements, supported by detailed scanning laser Doppler vibrometry. In particular the effect of the number of screws used to fasten the panels to the studs, and the tightness of the screws, is studied using seven different configurations of lightweight timber frame building elements. In the frequency range from 300 to 4000 Hz, differences in the weighted sound reduction index RW as large as 10 dB were measured, suggesting that the method of fastening can have a large impact on the acoustic performance of building elements. Using the measured vibrational responses of the element, its acoustic radiation efficiency was computed numerically by means of a Rayleigh integral. The increased radiation efficiency partly explains the reduced sound reduction index. Loosening the screws, or reducing the number of screws, lowers the radiation efficiency, and significantly increases the sound reduction index of the partition.

Zipf's Law of Abbreviation and the Principle of Least Effort: Language users optimise a miniature lexicon for efficient communication.

PubMed

Kanwal, Jasmeen; Smith, Kenny; Culbertson, Jennifer; Kirby, Simon

2017-08-01

The linguist George Kingsley Zipf made a now classic observation about the relationship between a word's length and its frequency; the more frequent a word is, the shorter it tends to be. He claimed that this "Law of Abbreviation" is a universal structural property of language. The Law of Abbreviation has since been documented in a wide range of human languages, and extended to animal communication systems and even computer programming languages. Zipf hypothesised that this universal design feature arises as a result of individuals optimising form-meaning mappings under competing pressures to communicate accurately but also efficiently-his famous Principle of Least Effort. In this study, we use a miniature artificial language learning paradigm to provide direct experimental evidence for this explanatory hypothesis. We show that language users optimise form-meaning mappings only when pressures for accuracy and efficiency both operate during a communicative task, supporting Zipf's conjecture that the Principle of Least Effort can explain this universal feature of word length distributions. Copyright © 2017 Elsevier B.V. All rights reserved.

Computational Issues in Damping Identification for Large Scale Problems

NASA Technical Reports Server (NTRS)

Pilkey, Deborah L.; Roe, Kevin P.; Inman, Daniel J.

1997-01-01

Two damping identification methods are tested for efficiency in large-scale applications. One is an iterative routine, and the other a least squares method. Numerical simulations have been performed on multiple degree-of-freedom models to test the effectiveness of the algorithm and the usefulness of parallel computation for the problems. High Performance Fortran is used to parallelize the algorithm. Tests were performed using the IBM-SP2 at NASA Ames Research Center. The least squares method tested incurs high communication costs, which reduces the benefit of high performance computing. This method's memory requirement grows at a very rapid rate meaning that larger problems can quickly exceed available computer memory. The iterative method's memory requirement grows at a much slower pace and is able to handle problems with 500+ degrees of freedom on a single processor. This method benefits from parallelization, and significant speedup can he seen for problems of 100+ degrees-of-freedom.

Ribbon synapses compute temporal contrast and encode luminance in retinal rod bipolar cells

PubMed Central

Oesch, Nicholas W.; Diamond, Jeffrey S.

2011-01-01

Contrast is computed throughout the nervous system to encode changing inputs efficiently. The retina encodes luminance and contrast over a wide range of visual conditions and so must adapt its responses to maintain sensitivity and avoid saturation. Here we show how one type of adaptation allows individual synapses to compute contrast and encode luminance in biphasic responses to step changes in light levels. Light-evoked depletion of the readily releasable vesicle pool (RRP) at rod bipolar cell (RBC) ribbon synapses in rat retina limits the dynamic range available to encode transient but not sustained responses, thereby allowing the transient and sustained components of release to compute temporal contrast and encode mean light levels, respectively. A release/replenishment model shows that a single, homogeneous pool of synaptic vesicles is sufficient to generate this behavior and reveals that the dominant mechanism shaping the biphasic contrast/luminance response is the partial depletion of the RRP. PMID:22019730

All-Particle Multiscale Computation of Hypersonic Rarefied Flow

NASA Astrophysics Data System (ADS)

Jun, E.; Burt, J. M.; Boyd, I. D.

2011-05-01

This study examines a new hybrid particle scheme used as an alternative means of multiscale flow simulation. The hybrid particle scheme employs the direct simulation Monte Carlo (DSMC) method in rarefied flow regions and the low diffusion (LD) particle method in continuum flow regions. The numerical procedures of the low diffusion particle method are implemented within an existing DSMC algorithm. The performance of the LD-DSMC approach is assessed by studying Mach 10 nitrogen flow over a sphere with a global Knudsen number of 0.002. The hybrid scheme results show good overall agreement with results from standard DSMC and CFD computation. Subcell procedures are utilized to improve computational efficiency and reduce sensitivity to DSMC cell size in the hybrid scheme. This makes it possible to perform the LD-DSMC simulation on a much coarser mesh that leads to a significant reduction in computation time.

Vortex flow structures and interactions for the optimum thrust efficiency of a heaving airfoil at different mean angles of attack

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

Martín-Alcántara, A.; Fernandez-Feria, R.; Sanmiguel-Rojas, E.

The thrust efficiency of a two-dimensional heaving airfoil is studied computationally for a low Reynolds number using a vortex force decomposition. The auxiliary potentials that separate the total vortex force into lift and drag (or thrust) are obtained analytically by using an elliptic airfoil. With these auxiliary potentials, the added-mass components of the lift and drag (or thrust) coefficients are also obtained analytically for any heaving motion of the airfoil and for any value of the mean angle of attack α. The contributions of the leading- and trailing-edge vortices to the thrust during their down- and up-stroke evolutions are computedmore » quantitatively with this formulation for different dimensionless frequencies and heave amplitudes (St{sub c} and St{sub a}) and for several values of α. Very different types of flows, periodic, quasi-periodic, and chaotic described as St{sub c}, St{sub a}, and α, are varied. The optimum values of these parameters for maximum thrust efficiency are obtained and explained in terms of the interactions between the vortices and the forces exerted by them on the airfoil. As in previous numerical and experimental studies on flapping flight at low Reynolds numbers, the optimum thrust efficiency is reached for intermediate frequencies (St{sub c} slightly smaller than one) and a heave amplitude corresponding to an advance ratio close to unity. The optimal mean angle of attack found is zero. The corresponding flow is periodic, but it becomes chaotic and with smaller average thrust efficiency as |α| becomes slightly different from zero.« less

The research of computer multimedia assistant in college English listening

NASA Astrophysics Data System (ADS)

Zhang, Qian

2012-04-01

With the technology development of network information, there exists more and more seriously questions to our education. Computer multimedia application breaks the traditional foreign language teaching and brings new challenges and opportunities for the education. Through the multiple media application, the teaching process is full of animation, image, voice, and characters. This can improve the learning initiative and objective with great development of learning efficiency. During the traditional foreign language teaching, people use characters learning. However, through this method, the theory performance is good but the practical application is low. During the long time computer multimedia application in the foreign language teaching, many teachers still have prejudice. Therefore, the method is not obtaining the effect. After all the above, the research has significant meaning for improving the teaching quality of foreign language.

Indirect addressing and load balancing for faster solution to Mandelbrot Set on SIMD architectures

NASA Technical Reports Server (NTRS)

Tomboulian, Sherryl

1989-01-01

SIMD computers with local indirect addressing allow programs to have queues and buffers, making certain kinds of problems much more efficient. Examined here are a class of problems characterized by computations on data points where the computation is identical, but the convergence rate is data dependent. Normally, in this situation, the algorithm time is governed by the maximum number of iterations required by each point. Using indirect addressing allows a processor to proceed to the next data point when it is done, reducing the overall number of iterations required to approach the mean convergence rate when a sufficiently large problem set is solved. Load balancing techniques can be applied for additional performance improvement. Simulations of this technique applied to solving Mandelbrot Sets indicate significant performance gains.

Singular value decomposition for collaborative filtering on a GPU

NASA Astrophysics Data System (ADS)

Kato, Kimikazu; Hosino, Tikara

2010-06-01

A collaborative filtering predicts customers' unknown preferences from known preferences. In a computation of the collaborative filtering, a singular value decomposition (SVD) is needed to reduce the size of a large scale matrix so that the burden for the next phase computation will be decreased. In this application, SVD means a roughly approximated factorization of a given matrix into smaller sized matrices. Webb (a.k.a. Simon Funk) showed an effective algorithm to compute SVD toward a solution of an open competition called "Netflix Prize". The algorithm utilizes an iterative method so that the error of approximation improves in each step of the iteration. We give a GPU version of Webb's algorithm. Our algorithm is implemented in the CUDA and it is shown to be efficient by an experiment.

Study of the stability of a SEIRS model for computer worm propagation

NASA Astrophysics Data System (ADS)

Hernández Guillén, J. D.; Martín del Rey, A.; Hernández Encinas, L.

2017-08-01

Nowadays, malware is the most important threat to information security. In this sense, several mathematical models to simulate malware spreading have appeared. They are compartmental models where the population of devices is classified into different compartments: susceptible, exposed, infectious, recovered, etc. The main goal of this work is to propose an improved SEIRS (Susceptible-Exposed-Infectious-Recovered-Susceptible) mathematical model to simulate computer worm propagation. It is a continuous model whose dynamic is ruled by means of a system of ordinary differential equations. It considers more realistic parameters related to the propagation; in fact, a modified incidence rate has been used. Moreover, the equilibrium points are computed and their local and global stability analyses are studied. From the explicit expression of the basic reproductive number, efficient control measures are also obtained.

Economic evaluation of alternative crossbreeding systems involving four breeds of swine. I. The simulation model.

PubMed

McLaren, D G; Buchanan, D S; Williams, J E

1987-10-01

A static, deterministic computer model, programmed in Microsoft Basic for IBM PC and Apple Macintosh computers, was developed to calculate production efficiency (cost per kg of product) for nine alternative types of crossbreeding system involving four breeds of swine. The model simulates efficiencies for four purebred and 60 alternative two-, three- and four-breed rotation, rotaterminal, backcross and static cross systems. Crossbreeding systems were defined as including all purebred, crossbred and commercial matings necessary to maintain a total of 10,000 farrowings. Driving variables for the model are mean conception rate at first service and for an 8-wk breeding season, litter size born, preweaning survival rate, postweaning average daily gain, feed-to-gain ratio and carcass backfat. Predictions are computed using breed direct genetic and maternal effects for the four breeds, plus individual, maternal and paternal specific heterosis values, input by the user. Inputs required to calculate the number of females farrowing in each sub-system include the proportion of males and females replaced each breeding cycle in purebred and crossbred populations, the proportion of male and female offspring in seedstock herds that become breeding animals, and the number of females per boar. Inputs required to calculate the efficiency of terminal production (cost-to-product ratio) for each sub-system include breeding herd feed intake, gilt development costs, feed costs and labor and overhead costs. Crossbreeding system efficiency is calculated as the weighted average of sub-system cost-to-product ratio values, weighting by the number of females farrowing in each sub-system.

Multimodal Word Meaning Induction From Minimal Exposure to Natural Text.

PubMed

Lazaridou, Angeliki; Marelli, Marco; Baroni, Marco

2017-04-01

By the time they reach early adulthood, English speakers are familiar with the meaning of thousands of words. In the last decades, computational simulations known as distributional semantic models (DSMs) have demonstrated that it is possible to induce word meaning representations solely from word co-occurrence statistics extracted from a large amount of text. However, while these models learn in batch mode from large corpora, human word learning proceeds incrementally after minimal exposure to new words. In this study, we run a set of experiments investigating whether minimal distributional evidence from very short passages suffices to trigger successful word learning in subjects, testing their linguistic and visual intuitions about the concepts associated with new words. After confirming that subjects are indeed very efficient distributional learners even from small amounts of evidence, we test a DSM on the same multimodal task, finding that it behaves in a remarkable human-like way. We conclude that DSMs provide a convincing computational account of word learning even at the early stages in which a word is first encountered, and the way they build meaning representations can offer new insights into human language acquisition. Copyright © 2017 Cognitive Science Society, Inc.

Bayesian statistical ionospheric tomography improved by incorporating ionosonde measurements

NASA Astrophysics Data System (ADS)

Norberg, Johannes; Virtanen, Ilkka I.; Roininen, Lassi; Vierinen, Juha; Orispää, Mikko; Kauristie, Kirsti; Lehtinen, Markku S.

2016-04-01

We validate two-dimensional ionospheric tomography reconstructions against EISCAT incoherent scatter radar measurements. Our tomography method is based on Bayesian statistical inversion with prior distribution given by its mean and covariance. We employ ionosonde measurements for the choice of the prior mean and covariance parameters and use the Gaussian Markov random fields as a sparse matrix approximation for the numerical computations. This results in a computationally efficient tomographic inversion algorithm with clear probabilistic interpretation. We demonstrate how this method works with simultaneous beacon satellite and ionosonde measurements obtained in northern Scandinavia. The performance is compared with results obtained with a zero-mean prior and with the prior mean taken from the International Reference Ionosphere 2007 model. In validating the results, we use EISCAT ultra-high-frequency incoherent scatter radar measurements as the ground truth for the ionization profile shape. We find that in comparison to the alternative prior information sources, ionosonde measurements improve the reconstruction by adding accurate information about the absolute value and the altitude distribution of electron density. With an ionosonde at continuous disposal, the presented method enhances stand-alone near-real-time ionospheric tomography for the given conditions significantly.

Potentials of Mean Force With Ab Initio Mixed Hamiltonian Models of Solvation

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

Dupuis, Michel; Schenter, Gregory K.; Garrett, Bruce C.

2003-08-01

We give an account of a computationally tractable and efficient procedure for the calculation of potentials of mean force using mixed Hamiltonian models of electronic structure where quantum subsystems are described with computationally intensive ab initio wavefunctions. The mixed Hamiltonian is mapped into an all-classical Hamiltonian that is amenable to a thermodynamic perturbation treatment for the calculation of free energies. A small number of statistically uncorrelated (solute-solvent) configurations are selected from the Monte Carlo random walk generated with the all-classical Hamiltonian approximation. Those are used in the averaging of the free energy using the mixed quantum/classical Hamiltonian. The methodology ismore » illustrated for the micro-solvated SN2 substitution reaction of methyl chloride by hydroxide. We also compare the potential of mean force calculated with the above protocol with an approximate formalism, one in which the potential of mean force calculated with the all-classical Hamiltonian is simply added to the energy of the isolated (non-solvated) solute along the reaction path. Interestingly the latter approach is found to be in semi-quantitative agreement with the full mixed Hamiltonian approximation.« less

The Effect of Computer Automation on Institutional Review Board (IRB) Office Efficiency

ERIC Educational Resources Information Center

Oder, Karl; Pittman, Stephanie

2015-01-01

Companies purchase computer systems to make their processes more efficient through automation. Some academic medical centers (AMC) have purchased computer systems for their institutional review boards (IRB) to increase efficiency and compliance with regulations. IRB computer systems are expensive to purchase, deploy, and maintain. An AMC should…

Efficient Redundancy Techniques in Cloud and Desktop Grid Systems using MAP/G/c-type Queues

NASA Astrophysics Data System (ADS)

Chakravarthy, Srinivas R.; Rumyantsev, Alexander

2018-03-01

Cloud computing is continuing to prove its flexibility and versatility in helping industries and businesses as well as academia as a way of providing needed computing capacity. As an important alternative to cloud computing, desktop grids allow to utilize the idle computer resources of an enterprise/community by means of distributed computing system, providing a more secure and controllable environment with lower operational expenses. Further, both cloud computing and desktop grids are meant to optimize limited resources and at the same time to decrease the expected latency for users. The crucial parameter for optimization both in cloud computing and in desktop grids is the level of redundancy (replication) for service requests/workunits. In this paper we study the optimal replication policies by considering three variations of Fork-Join systems in the context of a multi-server queueing system with a versatile point process for the arrivals. For services we consider phase type distributions as well as shifted exponential and Weibull. We use both analytical and simulation approach in our analysis and report some interesting qualitative results.

Cyber physical systems based on cloud computing and internet of things for energy efficiency

NASA Astrophysics Data System (ADS)

Suciu, George; Butca, Cristina; Suciu, Victor; Cretu, Alexandru; Fratu, Octavian

2016-12-01

Cyber Physical Systems (CPS) and energy efficiency play a major role in the context of industry expansion. Management practices for improving efficiency in the field of energy consumption became a priority of many major industries who are inefficient in terms of exploitation costs. The effort of adopting energy management means in an organization is quite challenging due to the lack of resources and expertise. One major problem consists in the lack of knowledge for energy management and practices. This paper aims to present authors' concept in creating a Cyber Physical Energy System (CPES) that will change organizations' way of consuming energy, by making them aware of their use. The presented concept will consider the security of the whole system and the easy integration with the existing electric network infrastructure.

Efficient proof of ownership for cloud storage systems

NASA Astrophysics Data System (ADS)

Zhong, Weiwei; Liu, Zhusong

2017-08-01

Cloud storage system through the deduplication technology to save disk space and bandwidth, but the use of this technology has appeared targeted security attacks: the attacker can deceive the server to obtain ownership of the file by get the hash value of original file. In order to solve the above security problems and the different security requirements of the files in the cloud storage system, an efficient and information-theoretical secure proof of ownership sceme is proposed to support the file rating. Through the K-means algorithm to implement file rating, and use random seed technology and pre-calculation method to achieve safe and efficient proof of ownership scheme. Finally, the scheme is information-theoretical secure, and achieve better performance in the most sensitive areas of client-side I/O and computation.

Improving the sampling efficiency of Monte Carlo molecular simulations: an evolutionary approach

NASA Astrophysics Data System (ADS)

Leblanc, Benoit; Braunschweig, Bertrand; Toulhoat, Hervé; Lutton, Evelyne

We present a new approach in order to improve the convergence of Monte Carlo (MC) simulations of molecular systems belonging to complex energetic landscapes: the problem is redefined in terms of the dynamic allocation of MC move frequencies depending on their past efficiency, measured with respect to a relevant sampling criterion. We introduce various empirical criteria with the aim of accounting for the proper convergence in phase space sampling. The dynamic allocation is performed over parallel simulations by means of a new evolutionary algorithm involving 'immortal' individuals. The method is bench marked with respect to conventional procedures on a model for melt linear polyethylene. We record significant improvement in sampling efficiencies, thus in computational load, while the optimal sets of move frequencies are liable to allow interesting physical insights into the particular systems simulated. This last aspect should provide a new tool for designing more efficient new MC moves.

Visualizing turbulent mixing of gases and particles

NASA Technical Reports Server (NTRS)

Ma, Kwan-Liu; Smith, Philip J.; Jain, Sandeep

1995-01-01

A physical model and interactive computer graphics techniques have been developed for the visualization of the basic physical process of stochastic dispersion and mixing from steady-state CFD calculations. The mixing of massless particles and inertial particles is visualized by transforming the vector field from a traditionally Eulerian reference frame into a Lagrangian reference frame. Groups of particles are traced through the vector field for the mean path as well as their statistical dispersion about the mean position by using added scalar information about the root mean square value of the vector field and its Lagrangian time scale. In this way, clouds of particles in a turbulent environment are traced, not just mean paths. In combustion simulations of many industrial processes, good mixing is required to achieve a sufficient degree of combustion efficiency. The ability to visualize this multiphase mixing can not only help identify poor mixing but also explain the mechanism for poor mixing. The information gained from the visualization can be used to improve the overall combustion efficiency in utility boilers or propulsion devices. We have used this technique to visualize steady-state simulations of the combustion performance in several furnace designs.

On efficiency of fire simulation realization: parallelization with greater number of computational meshes

NASA Astrophysics Data System (ADS)

Valasek, Lukas; Glasa, Jan

2017-12-01

Current fire simulation systems are capable to utilize advantages of high-performance computer (HPC) platforms available and to model fires efficiently in parallel. In this paper, efficiency of a corridor fire simulation on a HPC computer cluster is discussed. The parallel MPI version of Fire Dynamics Simulator is used for testing efficiency of selected strategies of allocation of computational resources of the cluster using a greater number of computational cores. Simulation results indicate that if the number of cores used is not equal to a multiple of the total number of cluster node cores there are allocation strategies which provide more efficient calculations.

An effective support system of emergency medical services with tablet computers.

PubMed

Yamada, Kosuke C; Inoue, Satoshi; Sakamoto, Yuichiro

2015-02-27

There were over 5,000,000 ambulance dispatches during 2010 in Japan, and the time for transportation has been increasing, it took over 37 minutes from dispatch to the hospitals. A way to reduce transportation time by ambulance is to shorten the time of searching for an appropriate facility/hospital during the prehospital phase. Although the information system of medical institutions and emergency medical service (EMS) was established in 2003 in Saga Prefecture, Japan, it has not been utilized efficiently. The Saga Prefectural Government renewed the previous system in an effort to make it the real-time support system that can efficiently manage emergency demand and acceptance for the first time in Japan in April 2011. The objective of this study was to evaluate if the new system promotes efficient emergency transportation for critically ill patients and provides valuable epidemiological data. The new system has provided both emergency personnel in the ambulance, or at the scene, and the medical staff in each hospital to be able to share up-to-date information about available hospitals by means of cloud computing. All 55 ambulances in Saga are equipped with tablet computers through third generation/long term evolution networks. When the emergency personnel arrive on the scene and discern the type of patient's illness, they can search for an appropriate facility/hospital with their tablet computer based on the patient's symptoms and available medical specialists. Data were collected prospectively over a three-year period from April 1, 2011 to March 31, 2013. The transportation time by ambulance in Saga was shortened for the first time since the statistics were first kept in 1999; the mean time was 34.3 minutes in 2010 (based on administrative statistics) and 33.9 minutes (95% CI 33.6-34.1) in 2011. The ratio of transportation to the tertiary care facilities in Saga has decreased by 3.12% from the year before, 32.7% in 2010 (regional average) and 29.58% (9085/30,709) in 2011. The system entry completion rate by the emergency personnel was 100.00% (93,110/93,110) and by the medical staff was 46.11% (14,159/30,709) to 47.57% (14,639/30,772) over a three-year period. Finally, the new system reduced the operational costs by 40,000,000 yen (about $400,000 US dollars) a year. The transportation time by ambulance was shorter following the implementation of the tablet computer in the current support system of EMS in Saga Prefecture, Japan. The cloud computing reduced the cost of the EMS system.

Research on the digital education resources of sharing pattern in independent colleges based on cloud computing environment

NASA Astrophysics Data System (ADS)

Xiong, Ting; He, Zhiwen

2017-06-01

Cloud computing was first proposed by Google Company in the United States, which was based on the Internet center, providing a standard and open network sharing service approach. With the rapid development of the higher education in China, the educational resources provided by colleges and universities had greatly gap in the actual needs of teaching resources. therefore, Cloud computing of using the Internet technology to provide shared methods liked the timely rain, which had become an important means of the Digital Education on sharing applications in the current higher education. Based on Cloud computing environment, the paper analyzed the existing problems about the sharing of digital educational resources in Jiangxi Province Independent Colleges. According to the sharing characteristics of mass storage, efficient operation and low input about Cloud computing, the author explored and studied the design of the sharing model about the digital educational resources of higher education in Independent College. Finally, the design of the shared model was put into the practical applications.

Computing daily mean streamflow at ungaged locations in Iowa by using the Flow Anywhere and Flow Duration Curve Transfer statistical methods

USGS Publications Warehouse

Linhart, S. Mike; Nania, Jon F.; Sanders, Curtis L.; Archfield, Stacey A.

2012-01-01

The U.S. Geological Survey (USGS) maintains approximately 148 real-time streamgages in Iowa for which daily mean streamflow information is available, but daily mean streamflow data commonly are needed at locations where no streamgages are present. Therefore, the USGS conducted a study as part of a larger project in cooperation with the Iowa Department of Natural Resources to develop methods to estimate daily mean streamflow at locations in ungaged watersheds in Iowa by using two regression-based statistical methods. The regression equations for the statistical methods were developed from historical daily mean streamflow and basin characteristics from streamgages within the study area, which includes the entire State of Iowa and adjacent areas within a 50-mile buffer of Iowa in neighboring states. Results of this study can be used with other techniques to determine the best method for application in Iowa and can be used to produce a Web-based geographic information system tool to compute streamflow estimates automatically. The Flow Anywhere statistical method is a variation of the drainage-area-ratio method, which transfers same-day streamflow information from a reference streamgage to another location by using the daily mean streamflow at the reference streamgage and the drainage-area ratio of the two locations. The Flow Anywhere method modifies the drainage-area-ratio method in order to regionalize the equations for Iowa and determine the best reference streamgage from which to transfer same-day streamflow information to an ungaged location. Data used for the Flow Anywhere method were retrieved for 123 continuous-record streamgages located in Iowa and within a 50-mile buffer of Iowa. The final regression equations were computed by using either left-censored regression techniques with a low limit threshold set at 0.1 cubic feet per second (ft3/s) and the daily mean streamflow for the 15th day of every other month, or by using an ordinary-least-squares multiple linear regression method and the daily mean streamflow for the 15th day of every other month. The Flow Duration Curve Transfer method was used to estimate unregulated daily mean streamflow from the physical and climatic characteristics of gaged basins. For the Flow Duration Curve Transfer method, daily mean streamflow quantiles at the ungaged site were estimated with the parameter-based regression model, which results in a continuous daily flow-duration curve (the relation between exceedance probability and streamflow for each day of observed streamflow) at the ungaged site. By the use of a reference streamgage, the Flow Duration Curve Transfer is converted to a time series. Data used in the Flow Duration Curve Transfer method were retrieved for 113 continuous-record streamgages in Iowa and within a 50-mile buffer of Iowa. The final statewide regression equations for Iowa were computed by using a weighted-least-squares multiple linear regression method and were computed for the 0.01-, 0.05-, 0.10-, 0.15-, 0.20-, 0.30-, 0.40-, 0.50-, 0.60-, 0.70-, 0.80-, 0.85-, 0.90-, and 0.95-exceedance probability statistics determined from the daily mean streamflow with a reporting limit set at 0.1 ft3/s. The final statewide regression equation for Iowa computed by using left-censored regression techniques was computed for the 0.99-exceedance probability statistic determined from the daily mean streamflow with a low limit threshold and a reporting limit set at 0.1 ft3/s. For the Flow Anywhere method, results of the validation study conducted by using six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 1,016 to 138 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 1,690 to 237 ft3/s. Values of the percent root-mean-square error ranged from 115 percent to 26.2 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 13.0 to 5.3 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.80 to 0.40. Percent-bias values ranged from 25.4 to 4.0 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.35. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.86 to 0.56. For the streamgage with the best agreement between observed and estimated streamflow, higher streamflows appear to be underestimated. For the streamgage with the worst agreement between observed and estimated streamflow, low flows appear to be overestimated whereas higher flows seem to be underestimated. Estimated cumulative streamflows for the period October 1, 2004, to September 30, 2009, are underestimated by -25.8 and -7.4 percent for the closest and poorest comparisons, respectively. For the Flow Duration Curve Transfer method, results of the validation study conducted by using the same six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 437 to 93.9 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 906 to 169 ft3/s. Values of the percent root-mean-square-error ranged from 67.0 to 25.6 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 12.5 to 4.4 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.79 to 0.40. Percent-bias values ranged from 22.7 to 0.94 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.38. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.89 to 0.48. For the streamgage with the closest agreement between observed and estimated streamflow, there is relatively good agreement between observed and estimated streamflows. For the streamgage with the poorest agreement between observed and estimated streamflow, streamflows appear to be substantially underestimated for much of the time period. Estimated cumulative streamflow for the period October 1, 2004, to September 30, 2009, are underestimated by -9.3 and -22.7 percent for the closest and poorest comparisons, respectively.

Identifying influential data points in hydrological model calibration and their impact on streamflow predictions

NASA Astrophysics Data System (ADS)

Wright, David; Thyer, Mark; Westra, Seth

2015-04-01

Highly influential data points are those that have a disproportionately large impact on model performance, parameters and predictions. However, in current hydrological modelling practice the relative influence of individual data points on hydrological model calibration is not commonly evaluated. This presentation illustrates and evaluates several influence diagnostics tools that hydrological modellers can use to assess the relative influence of data. The feasibility and importance of including influence detection diagnostics as a standard tool in hydrological model calibration is discussed. Two classes of influence diagnostics are evaluated: (1) computationally demanding numerical "case deletion" diagnostics; and (2) computationally efficient analytical diagnostics, based on Cook's distance. These diagnostics are compared against hydrologically orientated diagnostics that describe changes in the model parameters (measured through the Mahalanobis distance), performance (objective function displacement) and predictions (mean and maximum streamflow). These influence diagnostics are applied to two case studies: a stage/discharge rating curve model, and a conceptual rainfall-runoff model (GR4J). Removing a single data point from the calibration resulted in differences to mean flow predictions of up to 6% for the rating curve model, and differences to mean and maximum flow predictions of up to 10% and 17%, respectively, for the hydrological model. When using the Nash-Sutcliffe efficiency in calibration, the computationally cheaper Cook's distance metrics produce similar results to the case-deletion metrics at a fraction of the computational cost. However, Cooks distance is adapted from linear regression with inherit assumptions on the data and is therefore less flexible than case deletion. Influential point detection diagnostics show great potential to improve current hydrological modelling practices by identifying highly influential data points. The findings of this study establish the feasibility and importance of including influential point detection diagnostics as a standard tool in hydrological model calibration. They provide the hydrologist with important information on whether model calibration is susceptible to a small number of highly influent data points. This enables the hydrologist to make a more informed decision of whether to (1) remove/retain the calibration data; (2) adjust the calibration strategy and/or hydrological model to reduce the susceptibility of model predictions to a small number of influential observations.

Advanced scoring method of eco-efficiency in European cities.

PubMed

Moutinho, Victor; Madaleno, Mara; Robaina, Margarita; Villar, José

2018-01-01

This paper analyzes a set of selected German and French cities' performance in terms of the relative behavior of their eco-efficiencies, computed as the ratio of their gross domestic product (GDP) over their CO 2 emissions. For this analysis, eco-efficiency scores of the selected cities are computed using the data envelopment analysis (DEA) technique, taking the eco-efficiencies as outputs, and the inputs being the energy consumption, the population density, the labor productivity, the resource productivity, and the patents per inhabitant. Once DEA results are analyzed, the Malmquist productivity indexes (MPI) are used to assess the time evolution of the technical efficiency, technological efficiency, and productivity of the cities over the window periods 2000 to 2005 and 2005 to 2008. Some of the main conclusions are that (1) most of the analyzed cities seem to have suboptimal scales, being one of the causes of their inefficiency; (2) there is evidence that high GDP over CO 2 emissions does not imply high eco-efficiency scores, meaning that DEA like approaches are useful to complement more simplistic ranking procedures, pointing out potential inefficiencies at the input levels; (3) efficiencies performed worse during the period 2000-2005 than during the period 2005-2008, suggesting the possibility of corrective actions taken during or at the end of the first period but impacting only on the second period, probably due to an increasing environmental awareness of policymakers and governors; and (4) MPI analysis shows a positive technological evolution of all cities, according to the general technological evolution of the reference cities, reflecting a generalized convergence of most cities to their technological frontier and therefore an evolution in the right direction.

Uncertainty importance analysis using parametric moment ratio functions.

PubMed

Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen

2014-02-01

This article presents a new importance analysis framework, called parametric moment ratio function, for measuring the reduction of model output uncertainty when the distribution parameters of inputs are changed, and the emphasis is put on the mean and variance ratio functions with respect to the variances of model inputs. The proposed concepts efficiently guide the analyst to achieve a targeted reduction on the model output mean and variance by operating on the variances of model inputs. The unbiased and progressive unbiased Monte Carlo estimators are also derived for the parametric mean and variance ratio functions, respectively. Only a set of samples is needed for implementing the proposed importance analysis by the proposed estimators, thus the computational cost is free of input dimensionality. An analytical test example with highly nonlinear behavior is introduced for illustrating the engineering significance of the proposed importance analysis technique and verifying the efficiency and convergence of the derived Monte Carlo estimators. Finally, the moment ratio function is applied to a planar 10-bar structure for achieving a targeted 50% reduction of the model output variance. © 2013 Society for Risk Analysis.

ICF target 2D modeling using Monte Carlo SNB electron thermal transport in DRACO

NASA Astrophysics Data System (ADS)

Chenhall, Jeffrey; Cao, Duc; Moses, Gregory

2016-10-01

The iSNB (implicit Schurtz Nicolai Busquet multigroup diffusion electron thermal transport method is adapted into a Monte Carlo (MC) transport method to better model angular and long mean free path non-local effects. The MC model was first implemented in the 1D LILAC code to verify consistency with the iSNB model. Implementation of the MC SNB model in the 2D DRACO code enables higher fidelity non-local thermal transport modeling in 2D implosions such as polar drive experiments on NIF. The final step is to optimize the MC model by hybridizing it with a MC version of the iSNB diffusion method. The hybrid method will combine the efficiency of a diffusion method in intermediate mean free path regions with the accuracy of a transport method in long mean free path regions allowing for improved computational efficiency while maintaining accuracy. Work to date on the method will be presented. This work was supported by Sandia National Laboratories and the Univ. of Rochester Laboratory for Laser Energetics.

Nonlinear empirical model of gas humidity-related voltage dynamics of a polymer-electrolyte-membrane fuel cell stack

NASA Astrophysics Data System (ADS)

Meiler, M.; Andre, D.; Schmid, O.; Hofer, E. P.

Intelligent energy management is a cost-effective key path to realize efficient automotive drive trains [R. O'Hayre, S.W. Cha, W. Colella, F.B. Prinz. Fuel Cell Fundamentals, John Wiley & Sons, Hoboken, 2006]. To develop operating strategy in fuel cell drive trains, precise and computational efficient models of all system components, especially the fuel cell stack, are needed. Should these models further be used in diagnostic or control applications, then some major requirements must be fulfilled. First, the model must predict the mean fuel cell voltage very precisely in all possible operating conditions, even during transients. The model output should be as smooth as possible to support best efficient optimization strategies of the complete system. At least, the model must be computational efficient. For most applications, a difference between real fuel cell voltage and model output of less than 10 mV and 1000 calculations per second will be sufficient. In general, empirical models based on system identification offer a better accuracy and consume less calculation resources than detailed models derived from theoretical considerations [J. Larminie, A. Dicks. Fuel Cell Systems Explained, John Wiley & Sons, West Sussex, 2003]. In this contribution, the dynamic behaviour of the mean cell voltage of a polymer-electrolyte-membrane fuel cell (PEMFC) stack due to variations in humidity of cell's reactant gases is investigated. The validity of the overall model structure, a so-called general Hammerstein model (or Uryson model), was introduced recently in [M. Meiler, O. Schmid, M. Schudy, E.P. Hofer. Dynamic fuel cell stack model for real-time simulation based on system identification, J. Power Sources 176 (2007) 523-528]. Fuel cell mean voltage is calculated as the sum of a stationary and a dynamic voltage component. The stationary component of cell voltage is represented by a lookup-table and the dynamic voltage by a parallel placed, nonlinear transfer function. A suitable experimental setup to apply fast variations of gas humidity is introduced and is used to investigate a 10 cell PEMFC stack under various operation conditions. Using methods like stepwise multiple-regression a good mathematical description with reduced free parameters is achieved.

Google-Earth Based Visualizations for Environmental Flows and Pollutant Dispersion in Urban Areas

PubMed Central

Liu, Daoming; Kenjeres, Sasa

2017-01-01

In the present study, we address the development and application of an efficient tool for conversion of results obtained by an integrated computational fluid dynamics (CFD) and computational reaction dynamics (CRD) approach and their visualization in the Google Earth. We focus on results typical for environmental fluid mechanics studies at a city scale that include characteristic wind flow patterns and dispersion of reactive scalars. This is achieved by developing a code based on the Java language, which converts the typical four-dimensional structure (spatial and temporal dependency) of data results in the Keyhole Markup Language (KML) format. The visualization techniques most often used are revisited and implemented into the conversion tool. The potential of the tool is demonstrated in a case study of smog formation due to an intense traffic emission in Rotterdam (The Netherlands). It is shown that the Google Earth can provide a computationally efficient and user-friendly means of data representation. This feature can be very useful for visualization of pollution at street levels, which is of great importance for the city residents. Various meteorological and traffic emissions can be easily visualized and analyzed, providing a powerful, user-friendly tool for traffic regulations and urban climate adaptations. PMID:28257078

Three-dimensional computational fluid dynamics modeling of particle uptake by an occupational air sampler using manually-scaled and adaptive grids

PubMed Central

Landázuri, Andrea C.; Sáez, A. Eduardo; Anthony, T. Renée

2016-01-01

This work presents fluid flow and particle trajectory simulation studies to determine the aspiration efficiency of a horizontally oriented occupational air sampler using computational fluid dynamics (CFD). Grid adaption and manual scaling of the grids were applied to two sampler prototypes based on a 37-mm cassette. The standard k–ε model was used to simulate the turbulent air flow and a second order streamline-upwind discretization scheme was used to stabilize convective terms of the Navier–Stokes equations. Successively scaled grids for each configuration were created manually and by means of grid adaption using the velocity gradient in the main flow direction. Solutions were verified to assess iterative convergence, grid independence and monotonic convergence. Particle aspiration efficiencies determined for both prototype samplers were undistinguishable, indicating that the porous filter does not play a noticeable role in particle aspiration. Results conclude that grid adaption is a powerful tool that allows to refine specific regions that require lots of detail and therefore better resolve flow detail. It was verified that adaptive grids provided a higher number of locations with monotonic convergence than the manual grids and required the least computational effort. PMID:26949268

A computer program for analyzing channel geometry

USGS Publications Warehouse

Regan, R.S.; Schaffranek, R.W.

1985-01-01

The Channel Geometry Analysis Program (CGAP) provides the capability to process, analyze, and format cross-sectional data for input to flow/transport simulation models or other computational programs. CGAP allows for a variety of cross-sectional data input formats through use of variable format specification. The program accepts data from various computer media and provides for modification of machine-stored parameter values. CGAP has been devised to provide a rapid and efficient means of computing and analyzing the physical properties of an open-channel reach defined by a sequence of cross sections. CGAP 's 16 options provide a wide range of methods by which to analyze and depict a channel reach and its individual cross-sectional properties. The primary function of the program is to compute the area, width, wetted perimeter, and hydraulic radius of cross sections at successive increments of water surface elevation (stage) from data that consist of coordinate pairs of cross-channel distances and land surface or channel bottom elevations. Longitudinal rates-of-change of cross-sectional properties are also computed, as are the mean properties of a channel reach. Output products include tabular lists of cross-sectional area, channel width, wetted perimeter, hydraulic radius, average depth, and cross-sectional symmetry computed as functions of stage; plots of cross sections; plots of cross-sectional area and (or) channel width as functions of stage; tabular lists of cross-sectional area and channel width computed as functions of stage for subdivisions of a cross section; plots of cross sections in isometric projection; and plots of cross-sectional area at a fixed stage as a function of longitudinal distance along an open-channel reach. A Command Procedure Language program and Job Control Language procedure exist to facilitate program execution on the U.S. Geological Survey Prime and Amdahl computer systems respectively. (Lantz-PTT)

Improved transition path sampling methods for simulation of rare events

NASA Astrophysics Data System (ADS)

Chopra, Manan; Malshe, Rohit; Reddy, Allam S.; de Pablo, J. J.

2008-04-01

The free energy surfaces of a wide variety of systems encountered in physics, chemistry, and biology are characterized by the existence of deep minima separated by numerous barriers. One of the central aims of recent research in computational chemistry and physics has been to determine how transitions occur between deep local minima on rugged free energy landscapes, and transition path sampling (TPS) Monte-Carlo methods have emerged as an effective means for numerical investigation of such transitions. Many of the shortcomings of TPS-like approaches generally stem from their high computational demands. Two new algorithms are presented in this work that improve the efficiency of TPS simulations. The first algorithm uses biased shooting moves to render the sampling of reactive trajectories more efficient. The second algorithm is shown to substantially improve the accuracy of the transition state ensemble by introducing a subset of local transition path simulations in the transition state. The system considered in this work consists of a two-dimensional rough energy surface that is representative of numerous systems encountered in applications. When taken together, these algorithms provide gains in efficiency of over two orders of magnitude when compared to traditional TPS simulations.

An efficient computational method for characterizing the effects of random surface errors on the average power pattern of reflectors

NASA Technical Reports Server (NTRS)

Rahmat-Samii, Y.

1983-01-01

Based on the works of Ruze (1966) and Vu (1969), a novel mathematical model has been developed to determine efficiently the average power pattern degradations caused by random surface errors. In this model, both nonuniform root mean square (rms) surface errors and nonuniform illumination functions are employed. In addition, the model incorporates the dependence on F/D in the construction of the solution. The mathematical foundation of the model rests on the assumption that in each prescribed annular region of the antenna, the geometrical rms surface value is known. It is shown that closed-form expressions can then be derived, which result in a very efficient computational method for the average power pattern. Detailed parametric studies are performed with these expressions to determine the effects of different random errors and illumination tapers on parameters such as gain loss and sidelobe levels. The results clearly demonstrate that as sidelobe levels decrease, their dependence on the surface rms/wavelength becomes much stronger and, for a specified tolerance level, a considerably smaller rms/wavelength is required to maintain the low sidelobes within the required bounds.

Method for computationally efficient design of dielectric laser accelerator structures

DOE PAGES

Hughes, Tyler; Veronis, Georgios; Wootton, Kent P.; ...

2017-06-22

Here, dielectric microstructures have generated much interest in recent years as a means of accelerating charged particles when powered by solid state lasers. The acceleration gradient (or particle energy gain per unit length) is an important figure of merit. To design structures with high acceleration gradients, we explore the adjoint variable method, a highly efficient technique used to compute the sensitivity of an objective with respect to a large number of parameters. With this formalism, the sensitivity of the acceleration gradient of a dielectric structure with respect to its entire spatial permittivity distribution is calculated by the use of onlymore » two full-field electromagnetic simulations, the original and ‘adjoint’. The adjoint simulation corresponds physically to the reciprocal situation of a point charge moving through the accelerator gap and radiating. Using this formalism, we perform numerical optimizations aimed at maximizing acceleration gradients, which generate fabricable structures of greatly improved performance in comparison to previously examined geometries.« less

Distributed energy storage systems on the basis of electric-vehicle fleets

NASA Astrophysics Data System (ADS)

Zhuk, A. Z.; Buzoverov, E. A.; Sheindlin, A. E.

2015-01-01

Several power technologies directed to solving the problem of covering nonuniform loads in power systems are developed at the Joint Institute of High Temperatures, Russian Academy of Sciences (JIHT RAS). One direction of investigations is the use of storage batteries of electric vehicles to compensate load peaks in the power system (V2G—vehicle-to-grid technology). The efficiency of energy storage systems based on electric vehicles with traditional energy-saving technologies is compared in the article by means of performing computations. The comparison is performed by the minimum-cost criterion for the peak energy supply to the system. Computations show that the distributed storage systems based on fleets of electric cars are efficient economically with their usage regime to 1 h/day. In contrast to traditional methods, the prime cost of regulation of the loads in the power system based on V2G technology is independent of the duration of the load compensation period (the duration of the consumption peak).

Data mining techniques for scientific computing: Application to asymptotic paraxial approximations to model ultrarelativistic particles

NASA Astrophysics Data System (ADS)

Assous, Franck; Chaskalovic, Joël

2011-06-01

We propose a new approach that consists in using data mining techniques for scientific computing. Indeed, data mining has proved to be efficient in other contexts which deal with huge data like in biology, medicine, marketing, advertising and communications. Our aim, here, is to deal with the important problem of the exploitation of the results produced by any numerical method. Indeed, more and more data are created today by numerical simulations. Thus, it seems necessary to look at efficient tools to analyze them. In this work, we focus our presentation to a test case dedicated to an asymptotic paraxial approximation to model ultrarelativistic particles. Our method directly deals with numerical results of simulations and try to understand what each order of the asymptotic expansion brings to the simulation results over what could be obtained by other lower-order or less accurate means. This new heuristic approach offers new potential applications to treat numerical solutions to mathematical models.

The absorption of energetic electrons by molecular hydrogen gas

NASA Technical Reports Server (NTRS)

Cravens, T. E.; Victor, G. A.; Dalgarno, A.

1975-01-01

The processes by which energetic electrons lose energy in a weakly ionized gas of molecular hydrogen are analyzed, and calculations are carried out taking into account the discrete nature of the excitation processes. The excitation, ionization, and heating efficiencies are computed for electrons with energies up to 100 eV absorbed in a gas with fractional ionizations up to 0.01, and the mean energy per pair of neutral hydrogen atoms is calculated.

A Combined Experimental and Computational Study on the Stability of Nanofluids Containing Metal Organic Frameworks

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

Annapureddy, Harsha Vardhan Reddy; Nune, Satish K.; Motkuri, Radha K.

2015-01-08

Computational studies on nanofluids composed of metal organic frameworks (MOFs) were performed using molecular modeling techniques. Grand Canonical Monte Carlo (GCMC) simulations were used to study adsorption behavior of 1,1,1,3,3-pentafluoropropane (R-245fa) in a MIL-101 MOF at various temperatures. To understand the stability of the nanofluid composed of MIL-101 particles, we performed molecular dynamics simulations to compute potentials of mean force between hypothetical MIL-101 fragments terminated with two different kinds of modulators in R-245fa and water. Our computed potentials of mean force results indicate that the MOF particles tend to disperse better in water than in R-245fa. The reasons for thismore » observation were analyzed and discussed. Our results agree with experimental results indicating that the employed potential models and modeling approaches provide good description of molecular interactions and the reliabilities. Work performed by LXD was supported by the U.S. Department of Energy (DOE), Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. Work performed by HVRA, SKN, RKM, and PBM was supported by the Office of Energy Efficiency and Renewable Energy, Geothermal Technologies Program. Pacific Northwest National Laboratory is a multiprogram national laboratory operated for DOE by Battelle.« less

Analytical Cost Metrics : Days of Future Past

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

Prajapati, Nirmal; Rajopadhye, Sanjay; Djidjev, Hristo Nikolov

As we move towards the exascale era, the new architectures must be capable of running the massive computational problems efficiently. Scientists and researchers are continuously investing in tuning the performance of extreme-scale computational problems. These problems arise in almost all areas of computing, ranging from big data analytics, artificial intelligence, search, machine learning, virtual/augmented reality, computer vision, image/signal processing to computational science and bioinformatics. With Moore’s law driving the evolution of hardware platforms towards exascale, the dominant performance metric (time efficiency) has now expanded to also incorporate power/energy efficiency. Therefore the major challenge that we face in computing systems researchmore » is: “how to solve massive-scale computational problems in the most time/power/energy efficient manner?”« less

Energy Use and Power Levels in New Monitors and Personal Computers

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

Roberson, Judy A.; Homan, Gregory K.; Mahajan, Akshay

2002-07-23

Our research was conducted in support of the EPA ENERGY STAR Office Equipment program, whose goal is to reduce the amount of electricity consumed by office equipment in the U.S. The most energy-efficient models in each office equipment category are eligible for the ENERGY STAR label, which consumers can use to identify and select efficient products. As the efficiency of each category improves over time, the ENERGY STAR criteria need to be revised accordingly. The purpose of this study was to provide reliable data on the energy consumption of the newest personal computers and monitors that the EPA can usemore » to evaluate revisions to current ENERGY STAR criteria as well as to improve the accuracy of ENERGY STAR program savings estimates. We report the results of measuring the power consumption and power management capabilities of a sample of new monitors and computers. These results will be used to improve estimates of program energy savings and carbon emission reductions, and to inform rev isions of the ENERGY STAR criteria for these products. Our sample consists of 35 monitors and 26 computers manufactured between July 2000 and October 2001; it includes cathode ray tube (CRT) and liquid crystal display (LCD) monitors, Macintosh and Intel-architecture computers, desktop and laptop computers, and integrated computer systems, in which power consumption of the computer and monitor cannot be measured separately. For each machine we measured power consumption when off, on, and in each low-power level. We identify trends in and opportunities to reduce power consumption in new personal computers and monitors. Our results include a trend among monitor manufacturers to provide a single very low low-power level, well below the current ENERGY STAR criteria for sleep power consumption. These very low sleep power results mean that energy consumed when monitors are off or in active use has become more important in terms of contribution to the overall unit energy consumption (UEC). Cur rent ENERGY STAR monitor and computer criteria do not specify off or on power, but our results suggest opportunities for saving energy in these modes. Also, significant differences between CRT and LCD technology, and between field-measured and manufacturer-reported power levels reveal the need for standard methods and metrics for measuring and comparing monitor power consumption.« less

Integrative Sparse K-Means With Overlapping Group Lasso in Genomic Applications for Disease Subtype Discovery

PubMed Central

Huo, Zhiguang; Tseng, George

2017-01-01

Cancer subtypes discovery is the first step to deliver personalized medicine to cancer patients. With the accumulation of massive multi-level omics datasets and established biological knowledge databases, omics data integration with incorporation of rich existing biological knowledge is essential for deciphering a biological mechanism behind the complex diseases. In this manuscript, we propose an integrative sparse K-means (is-K means) approach to discover disease subtypes with the guidance of prior biological knowledge via sparse overlapping group lasso. An algorithm using an alternating direction method of multiplier (ADMM) will be applied for fast optimization. Simulation and three real applications in breast cancer and leukemia will be used to compare is-K means with existing methods and demonstrate its superior clustering accuracy, feature selection, functional annotation of detected molecular features and computing efficiency. PMID:28959370

Integrative Sparse K-Means With Overlapping Group Lasso in Genomic Applications for Disease Subtype Discovery.

PubMed

Huo, Zhiguang; Tseng, George

2017-06-01

Cancer subtypes discovery is the first step to deliver personalized medicine to cancer patients. With the accumulation of massive multi-level omics datasets and established biological knowledge databases, omics data integration with incorporation of rich existing biological knowledge is essential for deciphering a biological mechanism behind the complex diseases. In this manuscript, we propose an integrative sparse K -means (is- K means) approach to discover disease subtypes with the guidance of prior biological knowledge via sparse overlapping group lasso. An algorithm using an alternating direction method of multiplier (ADMM) will be applied for fast optimization. Simulation and three real applications in breast cancer and leukemia will be used to compare is- K means with existing methods and demonstrate its superior clustering accuracy, feature selection, functional annotation of detected molecular features and computing efficiency.

Computationally efficient characterization of potential energy surfaces based on fingerprint distances

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

Schaefer, Bastian; Goedecker, Stefan, E-mail: stefan.goedecker@unibas.ch

2016-07-21

An analysis of the network defined by the potential energy minima of multi-atomic systems and their connectivity via reaction pathways that go through transition states allows us to understand important characteristics like thermodynamic, dynamic, and structural properties. Unfortunately computing the transition states and reaction pathways in addition to the significant energetically low-lying local minima is a computationally demanding task. We here introduce a computationally efficient method that is based on a combination of the minima hopping global optimization method and the insight that uphill barriers tend to increase with increasing structural distances of the educt and product states. This methodmore » allows us to replace the exact connectivity information and transition state energies with alternative and approximate concepts. Without adding any significant additional cost to the minima hopping global optimization approach, this method allows us to generate an approximate network of the minima, their connectivity, and a rough measure for the energy needed for their interconversion. This can be used to obtain a first qualitative idea on important physical and chemical properties by means of a disconnectivity graph analysis. Besides the physical insight obtained by such an analysis, the gained knowledge can be used to make a decision if it is worthwhile or not to invest computational resources for an exact computation of the transition states and the reaction pathways. Furthermore it is demonstrated that the here presented method can be used for finding physically reasonable interconversion pathways that are promising input pathways for methods like transition path sampling or discrete path sampling.« less

Ecosystem-level water-use efficiency inferred from eddy covariance data: definitions, patterns and spatial up-scaling

NASA Astrophysics Data System (ADS)

Reichstein, M.; Beer, C.; Kuglitsch, F.; Papale, D.; Soussana, J. A.; Janssens, I.; Ciais, P.; Baldocchi, D.; Buchmann, N.; Verbeeck, H.; Ceulemans, R.; Moors, E.; Köstner, B.; Schulze, D.; Knohl, A.; Law, B. E.

2007-12-01

In this presentation we discuss ways to infer and to interpret water-use efficiency at ecosystem level (WUEe) from eddy covariance flux data and possibilities for scaling these patterns to regional and continental scale. In particular we convey the following: WUEe may be computed as a ratio of integrated fluxes or as the slope of carbon versus water fluxes offering different chances for interpretation. If computed from net ecosystem exchange and evapotranspiration on has to take of counfounding effects of respiration and soil evaporation. WUEe time-series at diurnal and seasonal scale is a valuable ecosystem physiological diagnostic for example about ecosystem-level responses to drought. Most often WUEe decreases during dry periods. The mean growing season ecosystem water-use efficiency of gross carbon uptake (WUEGPP) is highest in temperate broad-leaved deciduous forests, followed by temperate mixed forests, temperate evergreen conifers, Mediterranean broad-leaved deciduous forests, Mediterranean broad-leaved evergreen forests and Mediterranean evergreen conifers and boreal, grassland and tundra ecosystems. Water-use efficiency exhibits a temporally quite conservative relation with atmospheric water vapor pressure deficit (VPD) that is modified between sites by leaf area index (LAI) and soil quality, such that WUEe increases with LAI and soil water holding capacity which is related to texture. This property and tight coupling between carbon and water cycles is used to estimate catchment-scale water-use efficiency and primary productivity by integration of space-borne earth observation and river discharge data.

Experimental Realization of High-Efficiency Counterfactual Computation.

PubMed

Kong, Fei; Ju, Chenyong; Huang, Pu; Wang, Pengfei; Kong, Xi; Shi, Fazhan; Jiang, Liang; Du, Jiangfeng

2015-08-21

Counterfactual computation (CFC) exemplifies the fascinating quantum process by which the result of a computation may be learned without actually running the computer. In previous experimental studies, the counterfactual efficiency is limited to below 50%. Here we report an experimental realization of the generalized CFC protocol, in which the counterfactual efficiency can break the 50% limit and even approach unity in principle. The experiment is performed with the spins of a negatively charged nitrogen-vacancy color center in diamond. Taking advantage of the quantum Zeno effect, the computer can remain in the not-running subspace due to the frequent projection by the environment, while the computation result can be revealed by final detection. The counterfactual efficiency up to 85% has been demonstrated in our experiment, which opens the possibility of many exciting applications of CFC, such as high-efficiency quantum integration and imaging.

Experimental Realization of High-Efficiency Counterfactual Computation

NASA Astrophysics Data System (ADS)

Kong, Fei; Ju, Chenyong; Huang, Pu; Wang, Pengfei; Kong, Xi; Shi, Fazhan; Jiang, Liang; Du, Jiangfeng

2015-08-01

Counterfactual computation (CFC) exemplifies the fascinating quantum process by which the result of a computation may be learned without actually running the computer. In previous experimental studies, the counterfactual efficiency is limited to below 50%. Here we report an experimental realization of the generalized CFC protocol, in which the counterfactual efficiency can break the 50% limit and even approach unity in principle. The experiment is performed with the spins of a negatively charged nitrogen-vacancy color center in diamond. Taking advantage of the quantum Zeno effect, the computer can remain in the not-running subspace due to the frequent projection by the environment, while the computation result can be revealed by final detection. The counterfactual efficiency up to 85% has been demonstrated in our experiment, which opens the possibility of many exciting applications of CFC, such as high-efficiency quantum integration and imaging.

Exploiting multicore compute resources in the CMS experiment

NASA Astrophysics Data System (ADS)

Ramírez, J. E.; Pérez-Calero Yzquierdo, A.; Hernández, J. M.; CMS Collaboration

2016-10-01

CMS has developed a strategy to efficiently exploit the multicore architecture of the compute resources accessible to the experiment. A coherent use of the multiple cores available in a compute node yields substantial gains in terms of resource utilization. The implemented approach makes use of the multithreading support of the event processing framework and the multicore scheduling capabilities of the resource provisioning system. Multicore slots are acquired and provisioned by means of multicore pilot agents which internally schedule and execute single and multicore payloads. Multicore scheduling and multithreaded processing are currently used in production for online event selection and prompt data reconstruction. More workflows are being adapted to run in multicore mode. This paper presents a review of the experience gained in the deployment and operation of the multicore scheduling and processing system, the current status and future plans.

Hybrid transport and diffusion modeling using electron thermal transport Monte Carlo SNB in DRACO

NASA Astrophysics Data System (ADS)

Chenhall, Jeffrey; Moses, Gregory

2017-10-01

The iSNB (implicit Schurtz Nicolai Busquet) multigroup diffusion electron thermal transport method is adapted into an Electron Thermal Transport Monte Carlo (ETTMC) transport method to better model angular and long mean free path non-local effects. Previously, the ETTMC model had been implemented in the 2D DRACO multiphysics code and found to produce consistent results with the iSNB method. Current work is focused on a hybridization of the computationally slower but higher fidelity ETTMC transport method with the computationally faster iSNB diffusion method in order to maximize computational efficiency. Furthermore, effects on the energy distribution of the heat flux divergence are studied. Work to date on the hybrid method will be presented. This work was supported by Sandia National Laboratories and the Univ. of Rochester Laboratory for Laser Energetics.

Efficient computation of co-transcriptional RNA-ligand interaction dynamics.

PubMed

Wolfinger, Michael T; Flamm, Christoph; Hofacker, Ivo L

2018-05-04

Riboswitches form an abundant class of cis-regulatory RNA elements that mediate gene expression by binding a small metabolite. For synthetic biology applications, they are becoming cheap and accessible systems for selectively triggering transcription or translation of downstream genes. Many riboswitches are kinetically controlled, hence knowledge of their co-transcriptional mechanisms is essential. We present here an efficient implementation for analyzing co-transcriptional RNA-ligand interaction dynamics. This approach allows for the first time to model concentration-dependent metabolite binding/unbinding kinetics. We exemplify this novel approach by means of the recently studied I-A 2 ' -deoxyguanosine (2 ' dG)-sensing riboswitch from Mesoplasma florum. Copyright © 2018 Elsevier Inc. All rights reserved.

Optical trapping forces of a focused azimuthally polarized Bessel-Gaussian beam on a double-layered sphere

NASA Astrophysics Data System (ADS)

Wu, F. P.; Zhang, B.; Liu, Z. L.; Tang, Y.; Zhang, N.

2017-12-01

We calculate the trapping forces exerted by a highly focused Bessel-Gaussian beam on a double-layered sphere by means of vector diffraction integral, T-matrix method and Maxwell stress tensor integral. The Bessel-Gaussian beam is azimuthally polarized. Numerical results predicate that the double-layered sphere with air core can be stably trapped in three-dimensions. The trapping forces and efficiencies are dependent on the refraction index and size of the inner core. The trapping efficiency can be optimized by choosing the refraction indices of the inner core and outer layer. Our computational method can be easily modified for other laser beams and particles with arbitrary geometries and multilayers.

Approximate Joint Diagonalization and Geometric Mean of Symmetric Positive Definite Matrices

PubMed Central

Congedo, Marco; Afsari, Bijan; Barachant, Alexandre; Moakher, Maher

2015-01-01

We explore the connection between two problems that have arisen independently in the signal processing and related fields: the estimation of the geometric mean of a set of symmetric positive definite (SPD) matrices and their approximate joint diagonalization (AJD). Today there is a considerable interest in estimating the geometric mean of a SPD matrix set in the manifold of SPD matrices endowed with the Fisher information metric. The resulting mean has several important invariance properties and has proven very useful in diverse engineering applications such as biomedical and image data processing. While for two SPD matrices the mean has an algebraic closed form solution, for a set of more than two SPD matrices it can only be estimated by iterative algorithms. However, none of the existing iterative algorithms feature at the same time fast convergence, low computational complexity per iteration and guarantee of convergence. For this reason, recently other definitions of geometric mean based on symmetric divergence measures, such as the Bhattacharyya divergence, have been considered. The resulting means, although possibly useful in practice, do not satisfy all desirable invariance properties. In this paper we consider geometric means of covariance matrices estimated on high-dimensional time-series, assuming that the data is generated according to an instantaneous mixing model, which is very common in signal processing. We show that in these circumstances we can approximate the Fisher information geometric mean by employing an efficient AJD algorithm. Our approximation is in general much closer to the Fisher information geometric mean as compared to its competitors and verifies many invariance properties. Furthermore, convergence is guaranteed, the computational complexity is low and the convergence rate is quadratic. The accuracy of this new geometric mean approximation is demonstrated by means of simulations. PMID:25919667

Efficient statistical mapping of avian count data

USGS Publications Warehouse

Royle, J. Andrew; Wikle, C.K.

2005-01-01

We develop a spatial modeling framework for count data that is efficient to implement in high-dimensional prediction problems. We consider spectral parameterizations for the spatially varying mean of a Poisson model. The spectral parameterization of the spatial process is very computationally efficient, enabling effective estimation and prediction in large problems using Markov chain Monte Carlo techniques. We apply this model to creating avian relative abundance maps from North American Breeding Bird Survey (BBS) data. Variation in the ability of observers to count birds is modeled as spatially independent noise, resulting in over-dispersion relative to the Poisson assumption. This approach represents an improvement over existing approaches used for spatial modeling of BBS data which are either inefficient for continental scale modeling and prediction or fail to accommodate important distributional features of count data thus leading to inaccurate accounting of prediction uncertainty.

A transfer function type of simplified electrochemical model with modified boundary conditions and Padé approximation for Li-ion battery: Part 1. lithium concentration estimation

NASA Astrophysics Data System (ADS)

Yuan, Shifei; Jiang, Lei; Yin, Chengliang; Wu, Hongjie; Zhang, Xi

2017-06-01

To guarantee the safety, high efficiency and long lifetime for lithium-ion battery, an advanced battery management system requires a physics-meaningful yet computationally efficient battery model. The pseudo-two dimensional (P2D) electrochemical model can provide physical information about the lithium concentration and potential distributions across the cell dimension. However, the extensive computation burden caused by the temporal and spatial discretization limits its real-time application. In this research, we propose a new simplified electrochemical model (SEM) by modifying the boundary conditions for electrolyte diffusion equations, which significantly facilitates the analytical solving process. Then to obtain a reduced order transfer function, the Padé approximation method is adopted to simplify the derived transcendental impedance solution. The proposed model with the reduced order transfer function can be briefly computable and preserve physical meanings through the presence of parameters such as the solid/electrolyte diffusion coefficients (Ds&De) and particle radius. The simulation illustrates that the proposed simplified model maintains high accuracy for electrolyte phase concentration (Ce) predictions, saying 0.8% and 0.24% modeling error respectively, when compared to the rigorous model under 1C-rate pulse charge/discharge and urban dynamometer driving schedule (UDDS) profiles. Meanwhile, this simplified model yields significantly reduced computational burden, which benefits its real-time application.

Genotype Imputation with Millions of Reference Samples.

PubMed

Browning, Brian L; Browning, Sharon R

2016-01-07

We present a genotype imputation method that scales to millions of reference samples. The imputation method, based on the Li and Stephens model and implemented in Beagle v.4.1, is parallelized and memory efficient, making it well suited to multi-core computer processors. It achieves fast, accurate, and memory-efficient genotype imputation by restricting the probability model to markers that are genotyped in the target samples and by performing linear interpolation to impute ungenotyped variants. We compare Beagle v.4.1 with Impute2 and Minimac3 by using 1000 Genomes Project data, UK10K Project data, and simulated data. All three methods have similar accuracy but different memory requirements and different computation times. When imputing 10 Mb of sequence data from 50,000 reference samples, Beagle's throughput was more than 100× greater than Impute2's throughput on our computer servers. When imputing 10 Mb of sequence data from 200,000 reference samples in VCF format, Minimac3 consumed 26× more memory per computational thread and 15× more CPU time than Beagle. We demonstrate that Beagle v.4.1 scales to much larger reference panels by performing imputation from a simulated reference panel having 5 million samples and a mean marker density of one marker per four base pairs. Copyright © 2016 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

An accurate and computationally efficient algorithm for ground peak identification in large footprint waveform LiDAR data

NASA Astrophysics Data System (ADS)

Zhuang, Wei; Mountrakis, Giorgos

2014-09-01

Large footprint waveform LiDAR sensors have been widely used for numerous airborne studies. Ground peak identification in a large footprint waveform is a significant bottleneck in exploring full usage of the waveform datasets. In the current study, an accurate and computationally efficient algorithm was developed for ground peak identification, called Filtering and Clustering Algorithm (FICA). The method was evaluated on Land, Vegetation, and Ice Sensor (LVIS) waveform datasets acquired over Central NY. FICA incorporates a set of multi-scale second derivative filters and a k-means clustering algorithm in order to avoid detecting false ground peaks. FICA was tested in five different land cover types (deciduous trees, coniferous trees, shrub, grass and developed area) and showed more accurate results when compared to existing algorithms. More specifically, compared with Gaussian decomposition, the RMSE ground peak identification by FICA was 2.82 m (5.29 m for GD) in deciduous plots, 3.25 m (4.57 m for GD) in coniferous plots, 2.63 m (2.83 m for GD) in shrub plots, 0.82 m (0.93 m for GD) in grass plots, and 0.70 m (0.51 m for GD) in plots of developed areas. FICA performance was also relatively consistent under various slope and canopy coverage (CC) conditions. In addition, FICA showed better computational efficiency compared to existing methods. FICA's major computational and accuracy advantage is a result of the adopted multi-scale signal processing procedures that concentrate on local portions of the signal as opposed to the Gaussian decomposition that uses a curve-fitting strategy applied in the entire signal. The FICA algorithm is a good candidate for large-scale implementation on future space-borne waveform LiDAR sensors.

More efficient optimization of long-term water supply portfolios

NASA Astrophysics Data System (ADS)

Kirsch, Brian R.; Characklis, Gregory W.; Dillard, Karen E. M.; Kelley, C. T.

2009-03-01

The use of temporary transfers, such as options and leases, has grown as utilities attempt to meet increases in demand while reducing dependence on the expansion of costly infrastructure capacity (e.g., reservoirs). Earlier work has been done to construct optimal portfolios comprising firm capacity and transfers, using decision rules that determine the timing and volume of transfers. However, such work has only focused on the short-term (e.g., 1-year scenarios), which limits the utility of these planning efforts. Developing multiyear portfolios can lead to the exploration of a wider range of alternatives but also increases the computational burden. This work utilizes a coupled hydrologic-economic model to simulate the long-term performance of a city's water supply portfolio. This stochastic model is linked with an optimization search algorithm that is designed to handle the high-frequency, low-amplitude noise inherent in many simulations, particularly those involving expected values. This noise is detrimental to the accuracy and precision of the optimized solution and has traditionally been controlled by investing greater computational effort in the simulation. However, the increased computational effort can be substantial. This work describes the integration of a variance reduction technique (control variate method) within the simulation/optimization as a means of more efficiently identifying minimum cost portfolios. Random variation in model output (i.e., noise) is moderated using knowledge of random variations in stochastic input variables (e.g., reservoir inflows, demand), thereby reducing the computing time by 50% or more. Using these efficiency gains, water supply portfolios are evaluated over a 10-year period in order to assess their ability to reduce costs and adapt to demand growth, while still meeting reliability goals. As a part of the evaluation, several multiyear option contract structures are explored and compared.

Computationally efficient algorithms for Brownian dynamics simulation of long flexible macromolecules modeled as bead-rod chains

NASA Astrophysics Data System (ADS)

Moghani, Mahdy Malekzadeh; Khomami, Bamin

2017-02-01

The computational efficiency of Brownian dynamics (BD) simulation of the constrained model of a polymeric chain (bead-rod) with n beads and in the presence of hydrodynamic interaction (HI) is reduced to the order of n2 via an efficient algorithm which utilizes the conjugate-gradient (CG) method within a Picard iteration scheme. Moreover, the utility of the Barnes and Hut (BH) multipole method in BD simulation of polymeric solutions in the presence of HI, with regard to computational cost, scaling, and accuracy, is discussed. Overall, it is determined that this approach leads to a scaling of O (n1.2) . Furthermore, a stress algorithm is developed which accurately captures the transient stress growth in the startup of flow for the bead-rod model with HI and excluded volume (EV) interaction. Rheological properties of the chains up to n =350 in the presence of EV and HI are computed via the former algorithm. The result depicts qualitative differences in shear thinning behavior of the polymeric solutions in the intermediate values of the Weissenburg number (10

Combining cell-based hydrodynamics with hybrid particle-field simulations: efficient and realistic simulation of structuring dynamics.

PubMed

Sevink, G J A; Schmid, F; Kawakatsu, T; Milano, G

2017-02-22

We have extended an existing hybrid MD-SCF simulation technique that employs a coarsening step to enhance the computational efficiency of evaluating non-bonded particle interactions. This technique is conceptually equivalent to the single chain in mean-field (SCMF) method in polymer physics, in the sense that non-bonded interactions are derived from the non-ideal chemical potential in self-consistent field (SCF) theory, after a particle-to-field projection. In contrast to SCMF, however, MD-SCF evolves particle coordinates by the usual Newton's equation of motion. Since collisions are seriously affected by the softening of non-bonded interactions that originates from their evaluation at the coarser continuum level, we have devised a way to reinsert the effect of collisions on the structural evolution. Merging MD-SCF with multi-particle collision dynamics (MPCD), we mimic particle collisions at the level of computational cells and at the same time properly account for the momentum transfer that is important for a realistic system evolution. The resulting hybrid MD-SCF/MPCD method was validated for a particular coarse-grained model of phospholipids in aqueous solution, against reference full-particle simulations and the original MD-SCF model. We additionally implemented and tested an alternative and more isotropic finite difference gradient. Our results show that efficiency is improved by merging MD-SCF with MPCD, as properly accounting for hydrodynamic interactions considerably speeds up the phase separation dynamics, with negligible additional computational costs compared to efficient MD-SCF. This new method enables realistic simulations of large-scale systems that are needed to investigate the applications of self-assembled structures of lipids in nanotechnologies.

Autonomous Electrothermal Facility for Oil Recovery Intensification Fed by Wind Driven Power Unit

NASA Astrophysics Data System (ADS)

Belsky, Aleksey A.; Dobush, Vasiliy S.

2017-10-01

This paper describes the structure of autonomous facility fed by wind driven power unit for intensification of viscous and heavy crude oil recovery by means of heat impact on productive strata. Computer based service simulation of this facility was performed. Operational energy characteristics were obtained for various operational modes of facility. The optimal resistance of heating element of the downhole heater was determined for maximum operating efficiency of wind power unit.

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.

The efficacy of a novel mobile phone application for goldmann ptosis visual field interpretation.

PubMed

Maamari, Robi N; D'Ambrosio, Michael V; Joseph, Jeffrey M; Tao, Jeremiah P

2014-01-01

To evaluate the efficacy of a novel mobile phone application that calculates superior visual field defects on Goldmann visual field charts. Experimental study in which the mobile phone application and 14 oculoplastic surgeons interpreted the superior visual field defect in 10 Goldmann charts. Percent error of the mobile phone application and the oculoplastic surgeons' estimates were calculated compared with computer software computation of the actual defects. Precision and time efficiency of the application were evaluated by processing the same Goldmann visual field chart 10 repeated times. The mobile phone application was associated with a mean percent error of 1.98% (95% confidence interval[CI], 0.87%-3.10%) in superior visual field defect calculation. The average mean percent error of the oculoplastic surgeons' visual estimates was 19.75% (95% CI, 14.39%-25.11%). Oculoplastic surgeons, on average, underestimated the defect in all 10 Goldmann charts. There was high interobserver variance among oculoplastic surgeons. The percent error of the 10 repeated measurements on a single chart was 0.93% (95% CI, 0.40%-1.46%). The average time to process 1 chart was 12.9 seconds (95% CI, 10.9-15.0 seconds). The mobile phone application was highly accurate, precise, and time-efficient in calculating the percent superior visual field defect using Goldmann charts. Oculoplastic surgeon visual interpretations were highly inaccurate, highly variable, and usually underestimated the field vision loss.

Hydrodynamic evaluation of a full-scale facultative pond by computational fluid dynamics (CFD) and field measurements.

PubMed

Passos, Ricardo Gomes; von Sperling, Marcos; Ribeiro, Thiago Bressani

2014-01-01

Knowledge of the hydraulic behaviour is very important in the characterization of a stabilization pond, since pond hydrodynamics plays a fundamental role in treatment efficiency. An advanced hydrodynamics characterization may be achieved by carrying out measurements with tracers, dyes and drogues or using mathematical simulation employing computational fluid dynamics (CFD). The current study involved experimental determinations and mathematical simulations of a full-scale facultative pond in Brazil. A 3D CFD model showed major flow lines, degree of dispersion, dead zones and short circuit regions in the pond. Drogue tracking, wind measurements and dye dispersion were also used in order to obtain information about the actual flow in the pond and as a means of assessing the performance of the CFD model. The drogue, designed and built as part of this research, and which included a geographical positioning system (GPS), presented very satisfactory results. The CFD modelling has proven to be very useful in the evaluation of the hydrodynamic conditions of the facultative pond. A virtual tracer test allowed an estimation of the real mean hydraulic retention time and mixing conditions in the pond. The computational model in CFD corresponded well to what was verified in the field.

Molecular simulation of small Knudsen number flows

NASA Astrophysics Data System (ADS)

Fei, Fei; Fan, Jing

2012-11-01

The direct simulation Monte Carlo (DSMC) method is a powerful particle-based method for modeling gas flows. It works well for relatively large Knudsen (Kn) numbers, typically larger than 0.01, but quickly becomes computationally intensive as Kn decreases due to its time step and cell size limitations. An alternative approach was proposed to relax or remove these limitations, based on replacing pairwise collisions with a stochastic model corresponding to the Fokker-Planck equation [J. Comput. Phys., 229, 1077 (2010); J. Fluid Mech., 680, 574 (2011)]. Similar to the DSMC method, the downside of that approach suffers from computationally statistical noise. To solve the problem, a diffusion-based information preservation (D-IP) method has been developed. The main idea is to track the motion of a simulated molecule from the diffusive standpoint, and obtain the flow velocity and temperature through sampling and averaging the IP quantities. To validate the idea and the corresponding model, several benchmark problems with Kn ˜ 10-3-10-4 have been investigated. It is shown that the IP calculations are not only accurate, but also efficient because they make possible using a time step and cell size over an order of magnitude larger than the mean collision time and mean free path, respectively.

Fast mean and variance computation of the diffuse sound transmission through finite-sized thick and layered wall and floor systems

NASA Astrophysics Data System (ADS)

Decraene, Carolina; Dijckmans, Arne; Reynders, Edwin P. B.

2018-05-01

A method is developed for computing the mean and variance of the diffuse field sound transmission loss of finite-sized layered wall and floor systems that consist of solid, fluid and/or poroelastic layers. This is achieved by coupling a transfer matrix model of the wall or floor to statistical energy analysis subsystem models of the adjacent room volumes. The modal behavior of the wall is approximately accounted for by projecting the wall displacement onto a set of sinusoidal lateral basis functions. This hybrid modal transfer matrix-statistical energy analysis method is validated on multiple wall systems: a thin steel plate, a polymethyl methacrylate panel, a thick brick wall, a sandwich panel, a double-leaf wall with poro-elastic material in the cavity, and a double glazing. The predictions are compared with experimental data and with results obtained using alternative prediction methods such as the transfer matrix method with spatial windowing, the hybrid wave based-transfer matrix method, and the hybrid finite element-statistical energy analysis method. These comparisons confirm the prediction accuracy of the proposed method and the computational efficiency against the conventional hybrid finite element-statistical energy analysis method.

Computer aided diagnosis based on medical image processing and artificial intelligence methods

NASA Astrophysics Data System (ADS)

Stoitsis, John; Valavanis, Ioannis; Mougiakakou, Stavroula G.; Golemati, Spyretta; Nikita, Alexandra; Nikita, Konstantina S.

2006-12-01

Advances in imaging technology and computer science have greatly enhanced interpretation of medical images, and contributed to early diagnosis. The typical architecture of a Computer Aided Diagnosis (CAD) system includes image pre-processing, definition of region(s) of interest, features extraction and selection, and classification. In this paper, the principles of CAD systems design and development are demonstrated by means of two examples. The first one focuses on the differentiation between symptomatic and asymptomatic carotid atheromatous plaques. For each plaque, a vector of texture and motion features was estimated, which was then reduced to the most robust ones by means of ANalysis of VAriance (ANOVA). Using fuzzy c-means, the features were then clustered into two classes. Clustering performances of 74%, 79%, and 84% were achieved for texture only, motion only, and combinations of texture and motion features, respectively. The second CAD system presented in this paper supports the diagnosis of focal liver lesions and is able to characterize liver tissue from Computed Tomography (CT) images as normal, hepatic cyst, hemangioma, and hepatocellular carcinoma. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of neural network classifiers. The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.

When the mean is not enough: Calculating fixation time distributions in birth-death processes.

PubMed

Ashcroft, Peter; Traulsen, Arne; Galla, Tobias

2015-10-01

Studies of fixation dynamics in Markov processes predominantly focus on the mean time to absorption. This may be inadequate if the distribution is broad and skewed. We compute the distribution of fixation times in one-step birth-death processes with two absorbing states. These are expressed in terms of the spectrum of the process, and we provide different representations as forward-only processes in eigenspace. These allow efficient sampling of fixation time distributions. As an application we study evolutionary game dynamics, where invading mutants can reach fixation or go extinct. We also highlight the median fixation time as a possible analog of mixing times in systems with small mutation rates and no absorbing states, whereas the mean fixation time has no such interpretation.

A computable expression of closure to efficient causation.

PubMed

Mossio, Matteo; Longo, Giuseppe; Stewart, John

2009-04-07

In this paper, we propose a mathematical expression of closure to efficient causation in terms of lambda-calculus; we argue that this opens up the perspective of developing principled computer simulations of systems closed to efficient causation in an appropriate programming language. An important implication of our formulation is that, by exhibiting an expression in lambda-calculus, which is a paradigmatic formalism for computability and programming, we show that there are no conceptual or principled problems in realizing a computer simulation or model of closure to efficient causation. We conclude with a brief discussion of the question whether closure to efficient causation captures all relevant properties of living systems. We suggest that it might not be the case, and that more complex definitions could indeed create crucial some obstacles to computability.

Heliostat control

DOEpatents

Kaehler, James A.

1984-01-01

An improvement in a system and method of controlling heliostat in which the heliostat is operable in azimuth and elevation by respective stepper motors and including the respective steps or means for calculating the position for the heliostat to be at a commanded position, determining the number of steps in azimuth and elevation for each respective motor to get to the commanded position and energizing both the azimuth and elevation stepper motors to run in parallel until predetermined number of steps away from the closest commanded position in azimuth and elevation so that the closest position has been achieved, and thereafter energizing only the remaining motor to bring it to its commanded position. In this way, the heliostat can be started from a stowed position in the morning and operated by a computer means to its commanded position and kept correctly oriented throughout the day using only the time of the day without requiring the usual sensors and feedback apparatus. A computer, or microprocessor, can then control a plurality of many heliostats easily and efficiently throughout the day.

Boundary methods for mode estimation

NASA Astrophysics Data System (ADS)

Pierson, William E., Jr.; Ulug, Batuhan; Ahalt, Stanley C.

1999-08-01

This paper investigates the use of Boundary Methods (BMs), a collection of tools used for distribution analysis, as a method for estimating the number of modes associated with a given data set. Model order information of this type is required by several pattern recognition applications. The BM technique provides a novel approach to this parameter estimation problem and is comparable in terms of both accuracy and computations to other popular mode estimation techniques currently found in the literature and automatic target recognition applications. This paper explains the methodology used in the BM approach to mode estimation. Also, this paper quickly reviews other common mode estimation techniques and describes the empirical investigation used to explore the relationship of the BM technique to other mode estimation techniques. Specifically, the accuracy and computational efficiency of the BM technique are compared quantitatively to the a mixture of Gaussian (MOG) approach and a k-means approach to model order estimation. The stopping criteria of the MOG and k-means techniques is the Akaike Information Criteria (AIC).

Adaptively combined FIR and functional link artificial neural network equalizer for nonlinear communication channel.

PubMed

Zhao, Haiquan; Zhang, Jiashu

2009-04-01

This paper proposes a novel computational efficient adaptive nonlinear equalizer based on combination of finite impulse response (FIR) filter and functional link artificial neural network (CFFLANN) to compensate linear and nonlinear distortions in nonlinear communication channel. This convex nonlinear combination results in improving the speed while retaining the lower steady-state error. In addition, since the CFFLANN needs not the hidden layers, which exist in conventional neural-network-based equalizers, it exhibits a simpler structure than the traditional neural networks (NNs) and can require less computational burden during the training mode. Moreover, appropriate adaptation algorithm for the proposed equalizer is derived by the modified least mean square (MLMS). Results obtained from the simulations clearly show that the proposed equalizer using the MLMS algorithm can availably eliminate various intensity linear and nonlinear distortions, and be provided with better anti-jamming performance. Furthermore, comparisons of the mean squared error (MSE), the bit error rate (BER), and the effect of eigenvalue ratio (EVR) of input correlation matrix are presented.

Atomic Cholesky decompositions: a route to unbiased auxiliary basis sets for density fitting approximation with tunable accuracy and efficiency.

PubMed

Aquilante, Francesco; Gagliardi, Laura; Pedersen, Thomas Bondo; Lindh, Roland

2009-04-21

Cholesky decomposition of the atomic two-electron integral matrix has recently been proposed as a procedure for automated generation of auxiliary basis sets for the density fitting approximation [F. Aquilante et al., J. Chem. Phys. 127, 114107 (2007)]. In order to increase computational performance while maintaining accuracy, we propose here to reduce the number of primitive Gaussian functions of the contracted auxiliary basis functions by means of a second Cholesky decomposition. Test calculations show that this procedure is most beneficial in conjunction with highly contracted atomic orbital basis sets such as atomic natural orbitals, and that the error resulting from the second decomposition is negligible. We also demonstrate theoretically as well as computationally that the locality of the fitting coefficients can be controlled by means of the decomposition threshold even with the long-ranged Coulomb metric. Cholesky decomposition-based auxiliary basis sets are thus ideally suited for local density fitting approximations.

Atomic Cholesky decompositions: A route to unbiased auxiliary basis sets for density fitting approximation with tunable accuracy and efficiency

NASA Astrophysics Data System (ADS)

Aquilante, Francesco; Gagliardi, Laura; Pedersen, Thomas Bondo; Lindh, Roland

2009-04-01

Cholesky decomposition of the atomic two-electron integral matrix has recently been proposed as a procedure for automated generation of auxiliary basis sets for the density fitting approximation [F. Aquilante et al., J. Chem. Phys. 127, 114107 (2007)]. In order to increase computational performance while maintaining accuracy, we propose here to reduce the number of primitive Gaussian functions of the contracted auxiliary basis functions by means of a second Cholesky decomposition. Test calculations show that this procedure is most beneficial in conjunction with highly contracted atomic orbital basis sets such as atomic natural orbitals, and that the error resulting from the second decomposition is negligible. We also demonstrate theoretically as well as computationally that the locality of the fitting coefficients can be controlled by means of the decomposition threshold even with the long-ranged Coulomb metric. Cholesky decomposition-based auxiliary basis sets are thus ideally suited for local density fitting approximations.

Demonstration of a small programmable quantum computer with atomic qubits.

PubMed

Debnath, S; Linke, N M; Figgatt, C; Landsman, K A; Wright, K; Monroe, C

2016-08-04

Quantum computers can solve certain problems more efficiently than any possible conventional computer. Small quantum algorithms have been demonstrated on multiple quantum computing platforms, many specifically tailored in hardware to implement a particular algorithm or execute a limited number of computational paths. Here we demonstrate a five-qubit trapped-ion quantum computer that can be programmed in software to implement arbitrary quantum algorithms by executing any sequence of universal quantum logic gates. We compile algorithms into a fully connected set of gate operations that are native to the hardware and have a mean fidelity of 98 per cent. Reconfiguring these gate sequences provides the flexibility to implement a variety of algorithms without altering the hardware. As examples, we implement the Deutsch-Jozsa and Bernstein-Vazirani algorithms with average success rates of 95 and 90 per cent, respectively. We also perform a coherent quantum Fourier transform on five trapped-ion qubits for phase estimation and period finding with average fidelities of 62 and 84 per cent, respectively. This small quantum computer can be scaled to larger numbers of qubits within a single register, and can be further expanded by connecting several such modules through ion shuttling or photonic quantum channels.

Demonstration of a small programmable quantum computer with atomic qubits

NASA Astrophysics Data System (ADS)

Debnath, S.; Linke, N. M.; Figgatt, C.; Landsman, K. A.; Wright, K.; Monroe, C.

2016-08-01

Quantum computers can solve certain problems more efficiently than any possible conventional computer. Small quantum algorithms have been demonstrated on multiple quantum computing platforms, many specifically tailored in hardware to implement a particular algorithm or execute a limited number of computational paths. Here we demonstrate a five-qubit trapped-ion quantum computer that can be programmed in software to implement arbitrary quantum algorithms by executing any sequence of universal quantum logic gates. We compile algorithms into a fully connected set of gate operations that are native to the hardware and have a mean fidelity of 98 per cent. Reconfiguring these gate sequences provides the flexibility to implement a variety of algorithms without altering the hardware. As examples, we implement the Deutsch-Jozsa and Bernstein-Vazirani algorithms with average success rates of 95 and 90 per cent, respectively. We also perform a coherent quantum Fourier transform on five trapped-ion qubits for phase estimation and period finding with average fidelities of 62 and 84 per cent, respectively. This small quantum computer can be scaled to larger numbers of qubits within a single register, and can be further expanded by connecting several such modules through ion shuttling or photonic quantum channels.

Efficient non-hydrostatic modelling of 3D wave-induced currents using a subgrid approach

NASA Astrophysics Data System (ADS)

Rijnsdorp, Dirk P.; Smit, Pieter B.; Zijlema, Marcel; Reniers, Ad J. H. M.

2017-08-01

Wave-induced currents are an ubiquitous feature in coastal waters that can spread material over the surf zone and the inner shelf. These currents are typically under resolved in non-hydrostatic wave-flow models due to computational constraints. Specifically, the low vertical resolutions adequate to describe the wave dynamics - and required to feasibly compute at the scales of a field site - are too coarse to account for the relevant details of the three-dimensional (3D) flow field. To describe the relevant dynamics of both wave and currents, while retaining a model framework that can be applied at field scales, we propose a two grid approach to solve the governing equations. With this approach, the vertical accelerations and non-hydrostatic pressures are resolved on a relatively coarse vertical grid (which is sufficient to accurately resolve the wave dynamics), whereas the horizontal velocities and turbulent stresses are resolved on a much finer subgrid (of which the resolution is dictated by the vertical scale of the mean flows). This approach ensures that the discrete pressure Poisson equation - the solution of which dominates the computational effort - is evaluated on the coarse grid scale, thereby greatly improving efficiency, while providing a fine vertical resolution to resolve the vertical variation of the mean flow. This work presents the general methodology, and discusses the numerical implementation in the SWASH wave-flow model. Model predictions are compared with observations of three flume experiments to demonstrate that the subgrid approach captures both the nearshore evolution of the waves, and the wave-induced flows like the undertow profile and longshore current. The accuracy of the subgrid predictions is comparable to fully resolved 3D simulations - but at much reduced computational costs. The findings of this work thereby demonstrate that the subgrid approach has the potential to make 3D non-hydrostatic simulations feasible at the scale of a realistic coastal region.

A new approach for solving seismic tomography problems and assessing the uncertainty through the use of graph theory and direct methods

NASA Astrophysics Data System (ADS)

Bogiatzis, P.; Ishii, M.; Davis, T. A.

2016-12-01

Seismic tomography inverse problems are among the largest high-dimensional parameter estimation tasks in Earth science. We show how combinatorics and graph theory can be used to analyze the structure of such problems, and to effectively decompose them into smaller ones that can be solved efficiently by means of the least squares method. In combination with recent high performance direct sparse algorithms, this reduction in dimensionality allows for an efficient computation of the model resolution and covariance matrices using limited resources. Furthermore, we show that a new sparse singular value decomposition method can be used to obtain the complete spectrum of the singular values. This procedure provides the means for more objective regularization and further dimensionality reduction of the problem. We apply this methodology to a moderate size, non-linear seismic tomography problem to image the structure of the crust and the upper mantle beneath Japan using local deep earthquakes recorded by the High Sensitivity Seismograph Network stations.

Fast GPU-based computation of spatial multigrid multiframe LMEM for PET.

PubMed

Nassiri, Moulay Ali; Carrier, Jean-François; Després, Philippe

2015-09-01

Significant efforts were invested during the last decade to accelerate PET list-mode reconstructions, notably with GPU devices. However, the computation time per event is still relatively long, and the list-mode efficiency on the GPU is well below the histogram-mode efficiency. Since list-mode data are not arranged in any regular pattern, costly accesses to the GPU global memory can hardly be optimized and geometrical symmetries cannot be used. To overcome obstacles that limit the acceleration of reconstruction from list-mode on the GPU, a multigrid and multiframe approach of an expectation-maximization algorithm was developed. The reconstruction process is started during data acquisition, and calculations are executed concurrently on the GPU and the CPU, while the system matrix is computed on-the-fly. A new convergence criterion also was introduced, which is computationally more efficient on the GPU. The implementation was tested on a Tesla C2050 GPU device for a Gemini GXL PET system geometry. The results show that the proposed algorithm (multigrid and multiframe list-mode expectation-maximization, MGMF-LMEM) converges to the same solution as the LMEM algorithm more than three times faster. The execution time of the MGMF-LMEM algorithm was 1.1 s per million of events on the Tesla C2050 hardware used, for a reconstructed space of 188 x 188 x 57 voxels of 2 x 2 x 3.15 mm3. For 17- and 22-mm simulated hot lesions, the MGMF-LMEM algorithm led on the first iteration to contrast recovery coefficients (CRC) of more than 75 % of the maximum CRC while achieving a minimum in the relative mean square error. Therefore, the MGMF-LMEM algorithm can be used as a one-pass method to perform real-time reconstructions for low-count acquisitions, as in list-mode gated studies. The computation time for one iteration and 60 millions of events was approximately 66 s.

Integration of active pauses and pattern of muscular activity during computer work.

PubMed

St-Onge, Nancy; Samani, Afshin; Madeleine, Pascal

2017-09-01

Submaximal isometric muscle contractions have been reported to increase variability of muscle activation during computer work; however, other types of active contractions may be more beneficial. Our objective was to determine which type of active pause vs. rest is more efficient in changing muscle activity pattern during a computer task. Asymptomatic regular computer users performed a standardised 20-min computer task four times, integrating a different type of pause: sub-maximal isometric contraction, dynamic contraction, postural exercise and rest. Surface electromyographic (SEMG) activity was recorded bilaterally from five neck/shoulder muscles. Root-mean-square decreased with isometric pauses in the cervical paraspinals, upper trapezius and middle trapezius, whereas it increased with rest. Variability in the pattern of muscular activity was not affected by any type of pause. Overall, no detrimental effects on the level of SEMG during active pauses were found suggesting that they could be implemented without a cost on activation level or variability. Practitioner Summary: We aimed to determine which type of active pause vs. rest is best in changing muscle activity pattern during a computer task. Asymptomatic computer users performed a standardised computer task integrating different types of pauses. Muscle activation decreased with isometric pauses in neck/shoulder muscles, suggesting their implementation during computer work.

Combustion of hydrogen injected into a supersonic airstream (the SHIP computer program)

NASA Technical Reports Server (NTRS)

Markatos, N. C.; Spalding, D. B.; Tatchell, D. G.

1977-01-01

The mathematical and physical basis of the SHIP computer program which embodies a finite-difference, implicit numerical procedure for the computation of hydrogen injected into a supersonic airstream at an angle ranging from normal to parallel to the airstream main flow direction is described. The physical hypotheses built into the program include: a two-equation turbulence model, and a chemical equilibrium model for the hydrogen-oxygen reaction. Typical results for equilibrium combustion are presented and exhibit qualitatively plausible behavior. The computer time required for a given case is approximately 1 minute on a CDC 7600 machine. A discussion of the assumption of parabolic flow in the injection region is given which suggests that improvement in calculation in this region could be obtained by use of the partially parabolic procedure of Pratap and Spalding. It is concluded that the technique described herein provides the basis for an efficient and reliable means for predicting the effects of hydrogen injection into supersonic airstreams and of its subsequent combustion.

Merging K-means with hierarchical clustering for identifying general-shaped groups.

PubMed

Peterson, Anna D; Ghosh, Arka P; Maitra, Ranjan

2018-01-01

Clustering partitions a dataset such that observations placed together in a group are similar but different from those in other groups. Hierarchical and K -means clustering are two approaches but have different strengths and weaknesses. For instance, hierarchical clustering identifies groups in a tree-like structure but suffers from computational complexity in large datasets while K -means clustering is efficient but designed to identify homogeneous spherically-shaped clusters. We present a hybrid non-parametric clustering approach that amalgamates the two methods to identify general-shaped clusters and that can be applied to larger datasets. Specifically, we first partition the dataset into spherical groups using K -means. We next merge these groups using hierarchical methods with a data-driven distance measure as a stopping criterion. Our proposal has the potential to reveal groups with general shapes and structure in a dataset. We demonstrate good performance on several simulated and real datasets.

F--Ray: A new algorithm for efficient transport of ionizing radiation

NASA Astrophysics Data System (ADS)

Mao, Yi; Zhang, J.; Wandelt, B. D.; Shapiro, P. R.; Iliev, I. T.

2014-04-01

We present a new algorithm for the 3D transport of ionizing radiation, called F2-Ray (Fast Fourier Ray-tracing method). The transfer of ionizing radiation with long mean free path in diffuse intergalactic gas poses a special challenge to standard numerical methods which transport the radiation in position space. Standard methods usually trace each individual ray until it is fully absorbed by the intervening gas. If the mean free path is long, the computational cost and memory load are likely to be prohibitive. We have developed an algorithm that overcomes these limitations and is, therefore, significantly more efficient. The method calculates the transfer of radiation collectively, using the Fast Fourier Transform to convert radiation between position and Fourier spaces, so the computational cost will not increase with the number of ionizing sources. The method also automatically combines parallel rays with the same frequency at the same grid cell, thereby minimizing the memory requirement. The method is explicitly photon-conserving, i.e. the depletion of ionizing photons is guaranteed to equal the photoionizations they caused, and explicitly obeys the periodic boundary condition, i.e. the escape of ionizing photons from one side of a simulation volume is guaranteed to be compensated by emitting the same amount of photons into the volume through the opposite side. Together, these features make it possible to numerically simulate the transfer of ionizing photons more efficiently than previous methods. Since ionizing radiation such as the X-ray is responsible for heating the intergalactic gas when first stars and quasars form at high redshifts, our method can be applied to simulate thermal distribution, in addition to cosmic reionization, in three-dimensional inhomogeneous cosmological density field.

Generalized Radiative Transfer as an Efficient Computational Tool for Spatial and/or Spectral Integration over Unresolved Variability in Multi-Angle Observations

NASA Astrophysics Data System (ADS)

Davis, A. B.; Xu, F.; Diner, D. J.

2017-12-01

Two perennial problems in applied theoretical and computational radiative transfer (RT) are: (1) the impact of unresolved spatial variability on large-scale fluxes (in climate models) or radiances (in remote sensing); and (2) efficient-yet-accurate estimation of broadband spectral integrals in radiant energy budget estimation as well as in remote sensing, in particular, of trace gases.Generalized RT (GRT) is a modification of classic RT in an optical medium with uniform extinction where Beer's exponential law for direct transmission is replaced by a monotonically decreasing function with a slower power-law decay. In a convenient parameterized version of GRT, mean extinction replaces the uniform value and just one new property is introduced. As a non-dimensional metric for the unresolved variability, we use the square of the mean extinction coefficient divided by its variance. This parameter is also the exponent of the power-law tail of the modified transmission law.This specific form of sub-exponential transmission has explored for almost two decades in application to spatial variability in the presence of long-range correlations, much like in turbulent media such as clouds, with a focus on multiple scattering. It has also been proposed by Conley and Collins (JQSRT, 112, 1525-, 2011) to improve on the standard (weak-line) implementation of the correlated-k technique for efficient spectral integration.We have merged these two applications within a rigorous formulation of the combined problem, and solve the new integral RT equations in the single-scattering limit. The result is illustrated by addressing practical problems in multi-angle remote sensing of aerosols using the O2 A-band, an emerging methodology for passive profiling of coarse aerosols and clouds.

Effective EUVL mask cleaning technology solutions for mask manufacturing and in-fab mask maintenance

NASA Astrophysics Data System (ADS)

Dietze, Uwe; Dress, Peter; Waehler, Tobias; Singh, Sherjang; Jonckheere, Rik; Baudemprez, Bart

2011-03-01

Extreme Ultraviolet Lithography (EUVL) is considered the leading lithography technology choice for semiconductor devices at 16nm HP node and beyond. However, before EUV Lithography can enter into High Volume Manufacturing (HVM) of advanced semiconductor devices, the ability to guarantee mask integrity at point-of-exposure must be established. Highly efficient, damage free mask cleaning plays a critical role during the mask manufacturing cycle and throughout the life of the mask, where the absence of a pellicle to protect the EUV mask increases the risk of contamination during storage, handling and use. In this paper, we will present effective EUVL mask cleaning technology solutions for mask manufacturing and in-fab mask maintenance, which employs an intelligent, holistic approach to maximize Mean Time Between Cleans (MBTC) and extend the useful life span of the reticle. The data presented will demonstrate the protection of the capping and absorber layers, preservation of pattern integrity as well as optical and mechanical properties to avoid unpredictable CD-linewidth and overlay shifts. Experiments were performed on EUV blanks and pattern masks using various process conditions. Conditions showing high particle removal efficiency (PRE) and minimum surface layer impact were then selected for durability studies. Surface layer impact was evaluated over multiple cleaning cycles by means of UV reflectivity metrology XPS analysis and wafer prints. Experimental results were compared to computational models. Mask life time predictions where made using the same computational models. The paper will provide a generic overview of the cleaning sequence which yielded best results, but will also provide recommendations for an efficient in-fab mask maintenance scheme, addressing handling, storage, cleaning and inspection.

TOPMODEL simulations of streamflow and depth to water table in Fishing Brook Watershed, New York, 2007-09

USGS Publications Warehouse

Nystrom, Elizabeth A.; Burns, Douglas A.

2011-01-01

TOPMODEL uses a topographic wetness index computed from surface-elevation data to simulate streamflow and subsurface-saturation state, represented by the saturation deficit. Depth to water table was computed from simulated saturation-deficit values using computed soil properties. In the Fishing Brook Watershed, TOPMODEL was calibrated to the natural logarithm of streamflow at the study area outlet and depth to water table at Sixmile Wetland using a combined multiple-objective function. Runoff and depth to water table responded differently to some of the model parameters, and the combined multiple-objective function balanced the goodness-of-fit of the model realizations with respect to these parameters. Results show that TOPMODEL reasonably simulated runoff and depth to water table during the study period. The simulated runoff had a Nash-Sutcliffe efficiency of 0.738, but the model underpredicted total runoff by 14 percent. Depth to water table computed from simulated saturation-deficit values matched observed water-table depth moderately well; the root mean squared error of absolute depth to water table was 91 millimeters (mm), compared to the mean observed depth to water table of 205 mm. The correlation coefficient for temporal depth-to-water-table fluctuations was 0.624. The variability of the TOPMODEL simulations was assessed using prediction intervals grouped using the combined multiple-objective function. The calibrated TOPMODEL results for the entire study area were applied to several subwatersheds within the study area using computed hydrogeomorphic properties of the subwatersheds.

Evaluation of the efficiency of heat and moisture exchangers during paediatric anaesthesia.

PubMed

Luchetti, M; Pigna, A; Gentili, A; Marraro, G

1999-01-01

This study evaluates the efficiency of heat and moisture exchangers (HMEs) in allowing adequate humidification and warming during anaesthesia in children. Eighteen paediatric patients undergoing anaesthesia were divided into two groups: group A ten patients: infants up to 10 kg-->Hygrobaby HME; group B 8 patients: children above 10 kg-->Hygroboy HME. The following parameters were evaluated: body temperature (bT), room temperature (rT), fresh gas temperature, HME warm-up time, inspired and expired gases temperature and humidity, conserving efficiency, and duration of anaesthesia. Gas temperatures were recorded by means of a recorder fitted with four thermal probes. Humidity values were mathematically derived. The correlation between efficiency and rT, bT, and fresh gas temperature was computed. In both groups the inspired gases temperatures were below 30 degrees C. Inspired absolute humidity was never more than 28 mgH2O.l(-1). The conserving efficiency was good (0.93 in both groups). A positive correlation was found between efficiency and fresh gas temperature. HMEs did not meet the minimum standards for humidity and heating during anaesthesia in children, although their conserving efficiency was found to be satisfactory.

Recovery Act - CAREER: Sustainable Silicon -- Energy-Efficient VLSI Interconnect for Extreme-Scale Computing

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

Chiang, Patrick

2014-01-31

The research goal of this CAREER proposal is to develop energy-efficient, VLSI interconnect circuits and systems that will facilitate future massively-parallel, high-performance computing. Extreme-scale computing will exhibit massive parallelism on multiple vertical levels, from thou­ sands of computational units on a single processor to thousands of processors in a single data center. Unfortunately, the energy required to communicate between these units at every level (on­ chip, off-chip, off-rack) will be the critical limitation to energy efficiency. Therefore, the PI's career goal is to become a leading researcher in the design of energy-efficient VLSI interconnect for future computing systems.

The thermodynamic efficiency of computations made in cells across the range of life

NASA Astrophysics Data System (ADS)

Kempes, Christopher P.; Wolpert, David; Cohen, Zachary; Pérez-Mercader, Juan

2017-11-01

Biological organisms must perform computation as they grow, reproduce and evolve. Moreover, ever since Landauer's bound was proposed, it has been known that all computation has some thermodynamic cost-and that the same computation can be achieved with greater or smaller thermodynamic cost depending on how it is implemented. Accordingly an important issue concerning the evolution of life is assessing the thermodynamic efficiency of the computations performed by organisms. This issue is interesting both from the perspective of how close life has come to maximally efficient computation (presumably under the pressure of natural selection), and from the practical perspective of what efficiencies we might hope that engineered biological computers might achieve, especially in comparison with current computational systems. Here we show that the computational efficiency of translation, defined as free energy expended per amino acid operation, outperforms the best supercomputers by several orders of magnitude, and is only about an order of magnitude worse than the Landauer bound. However, this efficiency depends strongly on the size and architecture of the cell in question. In particular, we show that the useful efficiency of an amino acid operation, defined as the bulk energy per amino acid polymerization, decreases for increasing bacterial size and converges to the polymerization cost of the ribosome. This cost of the largest bacteria does not change in cells as we progress through the major evolutionary shifts to both single- and multicellular eukaryotes. However, the rates of total computation per unit mass are non-monotonic in bacteria with increasing cell size, and also change across different biological architectures, including the shift from unicellular to multicellular eukaryotes. This article is part of the themed issue 'Reconceptualizing the origins of life'.

Application of Linear and Non-Linear Harmonic Methods for Unsteady Transonic Flow

NASA Astrophysics Data System (ADS)

Gundevia, Rayomand

This thesis explores linear and non-linear computational methods for solving unsteady flow. The eventual goal is to apply these methods to two-dimensional and three-dimensional flutter predictions. In this study the quasi-one-dimensional nozzle is used as a framework for understanding these methods and their limitations. Subsonic and transonic cases are explored as the back-pressure is forced to oscillate with known amplitude and frequency. A steady harmonic approach is used to solve this unsteady problem for which perturbations are said to be small in comparison to the mean flow. The use of a linearized Euler equations (LEE) scheme is good at capturing the flow characteristics but is limited by accuracy to relatively small amplitude perturbations. The introduction of time-averaged second-order terms in the Non-Linear Harmonic (NLH) method means that a better approximation of the mean-valued solution, upon which the linearization is based, can be made. The nonlinear time-accurate Euler solutions are used for comparison and to establish the regimes of unsteadiness for which these schemes fails. The usefulness of the LEE and NLH methods lie in the gains in computational efficiency over the full equations.

3D nonrigid registration via optimal mass transport on the GPU.

PubMed

Ur Rehman, Tauseef; Haber, Eldad; Pryor, Gallagher; Melonakos, John; Tannenbaum, Allen

2009-12-01

In this paper, we present a new computationally efficient numerical scheme for the minimizing flow approach for optimal mass transport (OMT) with applications to non-rigid 3D image registration. The approach utilizes all of the gray-scale data in both images, and the optimal mapping from image A to image B is the inverse of the optimal mapping from B to A. Further, no landmarks need to be specified, and the minimizer of the distance functional involved is unique. Our implementation also employs multigrid, and parallel methodologies on a consumer graphics processing unit (GPU) for fast computation. Although computing the optimal map has been shown to be computationally expensive in the past, we show that our approach is orders of magnitude faster then previous work and is capable of finding transport maps with optimality measures (mean curl) previously unattainable by other works (which directly influences the accuracy of registration). We give results where the algorithm was used to compute non-rigid registrations of 3D synthetic data as well as intra-patient pre-operative and post-operative 3D brain MRI datasets.

Intricacies of modern supercomputing illustrated with recent advances in simulations of strongly correlated electron systems

NASA Astrophysics Data System (ADS)

Schulthess, Thomas C.

2013-03-01

The continued thousand-fold improvement in sustained application performance per decade on modern supercomputers keeps opening new opportunities for scientific simulations. But supercomputers have become very complex machines, built with thousands or tens of thousands of complex nodes consisting of multiple CPU cores or, most recently, a combination of CPU and GPU processors. Efficient simulations on such high-end computing systems require tailored algorithms that optimally map numerical methods to particular architectures. These intricacies will be illustrated with simulations of strongly correlated electron systems, where the development of quantum cluster methods, Monte Carlo techniques, as well as their optimal implementation by means of algorithms with improved data locality and high arithmetic density have gone hand in hand with evolving computer architectures. The present work would not have been possible without continued access to computing resources at the National Center for Computational Science of Oak Ridge National Laboratory, which is funded by the Facilities Division of the Office of Advanced Scientific Computing Research, and the Swiss National Supercomputing Center (CSCS) that is funded by ETH Zurich.

Multi-institutional Quantitative Evaluation and Clinical Validation of Smart Probabilistic Image Contouring Engine (SPICE) Autosegmentation of Target Structures and Normal Tissues on Computer Tomography Images in the Head and Neck, Thorax, Liver, and Male Pelvis Areas

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

Zhu, Mingyao; Bzdusek, Karl; Brink, Carsten

2013-11-15

Purpose: Clinical validation and quantitative evaluation of computed tomography (CT) image autosegmentation using Smart Probabilistic Image Contouring Engine (SPICE). Methods and Materials: CT images of 125 treated patients (32 head and neck [HN], 40 thorax, 23 liver, and 30 prostate) in 7 independent institutions were autosegmented using SPICE and computational times were recorded. The number of structures autocontoured were 25 for the HN, 7 for the thorax, 3 for the liver, and 6 for the male pelvis regions. Using the clinical contours as reference, autocontours of 22 selected structures were quantitatively evaluated using Dice Similarity Coefficient (DSC) and Mean Slice-wisemore » Hausdorff Distance (MSHD). All 40 autocontours were evaluated by a radiation oncologist from the institution that treated the patients. Results: The mean computational times to autosegment all the structures using SPICE were 3.1 to 11.1 minutes per patient. For the HN region, the mean DSC was >0.70 for all evaluated structures, and the MSHD ranged from 3.2 to 10.0 mm. For the thorax region, the mean DSC was 0.95 for the lungs and 0.90 for the heart, and the MSHD ranged from 2.8 to 12.8 mm. For the liver region, the mean DSC was >0.92 for all structures, and the MSHD ranged from 5.2 to 15.9 mm. For the male pelvis region, the mean DSC was >0.76 for all structures, and the MSHD ranged from 4.8 to 10.5 mm. Out of the 40 autocontoured structures reviews by experts, 25 were scored useful as autocontoured or with minor edits for at least 90% of the patients and 33 were scored useful autocontoured or with minor edits for at least 80% of the patients. Conclusions: Compared with manual contouring, autosegmentation using SPICE for the HN, thorax, liver, and male pelvis regions is efficient and shows significant promise for clinical utility.« less

Use of Nonequilibrium Work Methods to Compute Free Energy Differences Between Molecular Mechanical and Quantum Mechanical Representations of Molecular Systems.

PubMed

Hudson, Phillip S; Woodcock, H Lee; Boresch, Stefan

2015-12-03

Carrying out free energy simulations (FES) using quantum mechanical (QM) Hamiltonians remains an attractive, albeit elusive goal. Renewed efforts in this area have focused on using "indirect" thermodynamic cycles to connect "low level" simulation results to "high level" free energies. The main obstacle to computing converged free energy results between molecular mechanical (MM) and QM (ΔA(MM→QM)), as recently demonstrated by us and others, is differences in the so-called "stiff" degrees of freedom (e.g., bond stretching) between the respective energy surfaces. Herein, we demonstrate that this problem can be efficiently circumvented using nonequilibrium work (NEW) techniques, i.e., Jarzynski's and Crooks' equations. Initial applications of computing ΔA(NEW)(MM→QM), for blocked amino acids alanine and serine as well as to generate butane's potentials of mean force via the indirect QM/MM FES method, showed marked improvement over traditional FES approaches.

Robust Optimization Design for Turbine Blade-Tip Radial Running Clearance using Hierarchically Response Surface Method

NASA Astrophysics Data System (ADS)

Zhiying, Chen; Ping, Zhou

2017-11-01

Considering the robust optimization computational precision and efficiency for complex mechanical assembly relationship like turbine blade-tip radial running clearance, a hierarchically response surface robust optimization algorithm is proposed. The distribute collaborative response surface method is used to generate assembly system level approximation model of overall parameters and blade-tip clearance, and then a set samples of design parameters and objective response mean and/or standard deviation is generated by using system approximation model and design of experiment method. Finally, a new response surface approximation model is constructed by using those samples, and this approximation model is used for robust optimization process. The analyses results demonstrate the proposed method can dramatic reduce the computational cost and ensure the computational precision. The presented research offers an effective way for the robust optimization design of turbine blade-tip radial running clearance.

Study of sensor spectral responses and data processing algorithms and architectures for onboard feature identification

NASA Technical Reports Server (NTRS)

Huck, F. O.; Davis, R. E.; Fales, C. L.; Aherron, R. M.

1982-01-01

A computational model of the deterministic and stochastic processes involved in remote sensing is used to study spectral feature identification techniques for real-time onboard processing of data acquired with advanced earth-resources sensors. Preliminary results indicate that: Narrow spectral responses are advantageous; signal normalization improves mean-square distance (MSD) classification accuracy but tends to degrade maximum-likelihood (MLH) classification accuracy; and MSD classification of normalized signals performs better than the computationally more complex MLH classification when imaging conditions change appreciably from those conditions during which reference data were acquired. The results also indicate that autonomous categorization of TM signals into vegetation, bare land, water, snow and clouds can be accomplished with adequate reliability for many applications over a reasonably wide range of imaging conditions. However, further analysis is required to develop computationally efficient boundary approximation algorithms for such categorization.

Combustion of hydrogen injected into a supersonic airstream (a guide to the HISS computer program)

NASA Technical Reports Server (NTRS)

Dyer, D. F.; Maples, G.; Spalding, D. B.

1976-01-01

A computer program based on a finite-difference, implicit numerical integration scheme is described for the prediction of hydrogen injected into a supersonic airstream at an angle ranging from normal to parallel to the airstream main flow direction. Results of calculations for flow and thermal property distributions were compared with 'cold flow data' taken by NASA/Langley and show excellent correlation. Typical results for equilibrium combustion are presented and exhibit qualitatively plausible behavior. Computer time required for a given case is approximately one minute on a CDC 7600. A discussion of the assumption of parabolic flow in the injection region is given which demonstrates that improvement in calculation in this region could be obtained by a partially-parabolic procedure which has been developed. It is concluded that the technique described provides an efficient and reliable means for analyzing hydrogen injection into supersonic airstreams and the subsequent combustion.

Matrix-vector multiplication using digital partitioning for more accurate optical computing

NASA Technical Reports Server (NTRS)

Gary, C. K.

1992-01-01

Digital partitioning offers a flexible means of increasing the accuracy of an optical matrix-vector processor. This algorithm can be implemented with the same architecture required for a purely analog processor, which gives optical matrix-vector processors the ability to perform high-accuracy calculations at speeds comparable with or greater than electronic computers as well as the ability to perform analog operations at a much greater speed. Digital partitioning is compared with digital multiplication by analog convolution, residue number systems, and redundant number representation in terms of the size and the speed required for an equivalent throughput as well as in terms of the hardware requirements. Digital partitioning and digital multiplication by analog convolution are found to be the most efficient alogrithms if coding time and hardware are considered, and the architecture for digital partitioning permits the use of analog computations to provide the greatest throughput for a single processor.

3D noise-resistant segmentation and tracking of unknown and occluded objects using integral imaging

NASA Astrophysics Data System (ADS)

Aloni, Doron; Jung, Jae-Hyun; Yitzhaky, Yitzhak

2017-10-01

Three dimensional (3D) object segmentation and tracking can be useful in various computer vision applications, such as: object surveillance for security uses, robot navigation, etc. We present a method for 3D multiple-object tracking using computational integral imaging, based on accurate 3D object segmentation. The method does not employ object detection by motion analysis in a video as conventionally performed (such as background subtraction or block matching). This means that the movement properties do not significantly affect the detection quality. The object detection is performed by analyzing static 3D image data obtained through computational integral imaging With regard to previous works that used integral imaging data in such a scenario, the proposed method performs the 3D tracking of objects without prior information about the objects in the scene, and it is found efficient under severe noise conditions.

Active Flash: Out-of-core Data Analytics on Flash Storage

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

Boboila, Simona; Kim, Youngjae; Vazhkudai, Sudharshan S

2012-01-01

Next generation science will increasingly come to rely on the ability to perform efficient, on-the-fly analytics of data generated by high-performance computing (HPC) simulations, modeling complex physical phenomena. Scientific computing workflows are stymied by the traditional chaining of simulation and data analysis, creating multiple rounds of redundant reads and writes to the storage system, which grows in cost with the ever-increasing gap between compute and storage speeds in HPC clusters. Recent HPC acquisitions have introduced compute node-local flash storage as a means to alleviate this I/O bottleneck. We propose a novel approach, Active Flash, to expedite data analysis pipelines bymore » migrating to the location of the data, the flash device itself. We argue that Active Flash has the potential to enable true out-of-core data analytics by freeing up both the compute core and the associated main memory. By performing analysis locally, dependence on limited bandwidth to a central storage system is reduced, while allowing this analysis to proceed in parallel with the main application. In addition, offloading work from the host to the more power-efficient controller reduces peak system power usage, which is already in the megawatt range and poses a major barrier to HPC system scalability. We propose an architecture for Active Flash, explore energy and performance trade-offs in moving computation from host to storage, demonstrate the ability of appropriate embedded controllers to perform data analysis and reduction tasks at speeds sufficient for this application, and present a simulation study of Active Flash scheduling policies. These results show the viability of the Active Flash model, and its capability to potentially have a transformative impact on scientific data analysis.« less

Evaluation of the discrete vortex wake cross flow model using vector computers. Part 1: Theory and application

NASA Technical Reports Server (NTRS)

1979-01-01

The current program had the objective to modify a discrete vortex wake method to efficiently compute the aerodynamic forces and moments on high fineness ratio bodies (f approximately 10.0). The approach is to increase computational efficiency by structuring the program to take advantage of new computer vector software and by developing new algorithms when vector software can not efficiently be used. An efficient program was written and substantial savings achieved. Several test cases were run for fineness ratios up to f = 16.0 and angles of attack up to 50 degrees.

On a turbulent wall model to predict hemolysis numerically in medical devices

NASA Astrophysics Data System (ADS)

Lee, Seunghun; Chang, Minwook; Kang, Seongwon; Hur, Nahmkeon; Kim, Wonjung

2017-11-01

Analyzing degradation of red blood cells is very important for medical devices with blood flows. The blood shear stress has been recognized as the most dominant factor for hemolysis in medical devices. Compared to laminar flows, turbulent flows have higher shear stress values in the regions near the wall. In case of predicting hemolysis numerically, this phenomenon can require a very fine mesh and large computational resources. In order to resolve this issue, the purpose of this study is to develop a turbulent wall model to predict the hemolysis more efficiently. In order to decrease the numerical error of hemolysis prediction in a coarse grid resolution, we divided the computational domain into two regions and applied different approaches to each region. In the near-wall region with a steep velocity gradient, an analytic approach using modeled velocity profile is applied to reduce a numerical error to allow a coarse grid resolution. We adopt the Van Driest law as a model for the mean velocity profile. In a region far from the wall, a regular numerical discretization is applied. The proposed turbulent wall model is evaluated for a few turbulent flows inside a cannula and centrifugal pumps. The results present that the proposed turbulent wall model for hemolysis improves the computational efficiency significantly for engineering applications. Corresponding author.

Semi-implicit finite difference methods for three-dimensional shallow water flow

USGS Publications Warehouse

Casulli, Vincenzo; Cheng, Ralph T.

1992-01-01

A semi-implicit finite difference method for the numerical solution of three-dimensional shallow water flows is presented and discussed. The governing equations are the primitive three-dimensional turbulent mean flow equations where the pressure distribution in the vertical has been assumed to be hydrostatic. In the method of solution a minimal degree of implicitness has been adopted in such a fashion that the resulting algorithm is stable and gives a maximal computational efficiency at a minimal computational cost. At each time step the numerical method requires the solution of one large linear system which can be formally decomposed into a set of small three-diagonal systems coupled with one five-diagonal system. All these linear systems are symmetric and positive definite. Thus the existence and uniquencess of the numerical solution are assured. When only one vertical layer is specified, this method reduces as a special case to a semi-implicit scheme for solving the corresponding two-dimensional shallow water equations. The resulting two- and three-dimensional algorithm has been shown to be fast, accurate and mass-conservative and can also be applied to simulate flooding and drying of tidal mud-flats in conjunction with three-dimensional flows. Furthermore, the resulting algorithm is fully vectorizable for an efficient implementation on modern vector computers.

Group implicit concurrent algorithms in nonlinear structural dynamics

NASA Technical Reports Server (NTRS)

Ortiz, M.; Sotelino, E. D.

1989-01-01

During the 70's and 80's, considerable effort was devoted to developing efficient and reliable time stepping procedures for transient structural analysis. Mathematically, the equations governing this type of problems are generally stiff, i.e., they exhibit a wide spectrum in the linear range. The algorithms best suited to this type of applications are those which accurately integrate the low frequency content of the response without necessitating the resolution of the high frequency modes. This means that the algorithms must be unconditionally stable, which in turn rules out explicit integration. The most exciting possibility in the algorithms development area in recent years has been the advent of parallel computers with multiprocessing capabilities. So, this work is mainly concerned with the development of parallel algorithms in the area of structural dynamics. A primary objective is to devise unconditionally stable and accurate time stepping procedures which lend themselves to an efficient implementation in concurrent machines. Some features of the new computer architecture are summarized. A brief survey of current efforts in the area is presented. A new class of concurrent procedures, or Group Implicit algorithms is introduced and analyzed. The numerical simulation shows that GI algorithms hold considerable promise for application in coarse grain as well as medium grain parallel computers.

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

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

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

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

An accurate and efficient laser-envelope solver for the modeling of laser-plasma accelerators

DOE PAGES

Benedetti, C.; Schroeder, C. B.; Geddes, C. G. R.; ...

2017-10-17

Detailed and reliable numerical modeling of laser-plasma accelerators (LPAs), where a short and intense laser pulse interacts with an underdense plasma over distances of up to a meter, is a formidably challenging task. This is due to the great disparity among the length scales involved in the modeling, ranging from the micron scale of the laser wavelength to the meter scale of the total laser-plasma interaction length. The use of the time-averaged ponderomotive force approximation, where the laser pulse is described by means of its envelope, enables efficient modeling of LPAs by removing the need to model the details ofmore » electron motion at the laser wavelength scale. Furthermore, it allows simulations in cylindrical geometry which captures relevant 3D physics at 2D computational cost. A key element of any code based on the time-averaged ponderomotive force approximation is the laser envelope solver. In this paper we present the accurate and efficient envelope solver used in the code INF & RNO (INtegrated Fluid & paRticle simulatioN cOde). The features of the INF & RNO laser solver enable an accurate description of the laser pulse evolution deep into depletion even at a reasonably low resolution, resulting in significant computational speed-ups.« less

An accurate and efficient laser-envelope solver for the modeling of laser-plasma accelerators

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

Benedetti, C.; Schroeder, C. B.; Geddes, C. G. R.

Detailed and reliable numerical modeling of laser-plasma accelerators (LPAs), where a short and intense laser pulse interacts with an underdense plasma over distances of up to a meter, is a formidably challenging task. This is due to the great disparity among the length scales involved in the modeling, ranging from the micron scale of the laser wavelength to the meter scale of the total laser-plasma interaction length. The use of the time-averaged ponderomotive force approximation, where the laser pulse is described by means of its envelope, enables efficient modeling of LPAs by removing the need to model the details ofmore » electron motion at the laser wavelength scale. Furthermore, it allows simulations in cylindrical geometry which captures relevant 3D physics at 2D computational cost. A key element of any code based on the time-averaged ponderomotive force approximation is the laser envelope solver. In this paper we present the accurate and efficient envelope solver used in the code INF & RNO (INtegrated Fluid & paRticle simulatioN cOde). The features of the INF & RNO laser solver enable an accurate description of the laser pulse evolution deep into depletion even at a reasonably low resolution, resulting in significant computational speed-ups.« less

An accurate and efficient laser-envelope solver for the modeling of laser-plasma accelerators

NASA Astrophysics Data System (ADS)

Benedetti, C.; Schroeder, C. B.; Geddes, C. G. R.; Esarey, E.; Leemans, W. P.

2018-01-01

Detailed and reliable numerical modeling of laser-plasma accelerators (LPAs), where a short and intense laser pulse interacts with an underdense plasma over distances of up to a meter, is a formidably challenging task. This is due to the great disparity among the length scales involved in the modeling, ranging from the micron scale of the laser wavelength to the meter scale of the total laser-plasma interaction length. The use of the time-averaged ponderomotive force approximation, where the laser pulse is described by means of its envelope, enables efficient modeling of LPAs by removing the need to model the details of electron motion at the laser wavelength scale. Furthermore, it allows simulations in cylindrical geometry which captures relevant 3D physics at 2D computational cost. A key element of any code based on the time-averaged ponderomotive force approximation is the laser envelope solver. In this paper we present the accurate and efficient envelope solver used in the code INF&RNO (INtegrated Fluid & paRticle simulatioN cOde). The features of the INF&RNO laser solver enable an accurate description of the laser pulse evolution deep into depletion even at a reasonably low resolution, resulting in significant computational speed-ups.

Mid-infrared coincidence measurements on twin photons at room temperature

PubMed Central

Mancinelli, M.; Trenti, A.; Piccione, S.; Fontana, G.; Dam, J. S.; Tidemand-Lichtenberg, P.; Pedersen, C.; Pavesi, L.

2017-01-01

Quantum measurements using single-photon detectors are opening interesting new perspectives in diverse fields such as remote sensing, quantum cryptography and quantum computing. A particularly demanding class of applications relies on the simultaneous detection of correlated single photons. In the visible and near infrared wavelength ranges suitable single-photon detectors do exist. However, low detector quantum efficiency or excessive noise has hampered their mid-infrared (MIR) counterpart. Fast and highly efficient single-photon detectors are thus highly sought after for MIR applications. Here we pave the way to quantum measurements in the MIR by the demonstration of a room temperature coincidence measurement with non-degenerate twin photons at about 3.1 μm. The experiment is based on the spectral translation of MIR radiation into the visible region, by means of efficient up-converter modules. The up-converted pairs are then detected with low-noise silicon avalanche photodiodes without the need for cryogenic cooling. PMID:28504244

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.

A fast and accurate frequency estimation algorithm for sinusoidal signal with harmonic components

NASA Astrophysics Data System (ADS)

Hu, Jinghua; Pan, Mengchun; Zeng, Zhidun; Hu, Jiafei; Chen, Dixiang; Tian, Wugang; Zhao, Jianqiang; Du, Qingfa

2016-10-01

Frequency estimation is a fundamental problem in many applications, such as traditional vibration measurement, power system supervision, and microelectromechanical system sensors control. In this paper, a fast and accurate frequency estimation algorithm is proposed to deal with low efficiency problem in traditional methods. The proposed algorithm consists of coarse and fine frequency estimation steps, and we demonstrate that it is more efficient than conventional searching methods to achieve coarse frequency estimation (location peak of FFT amplitude) by applying modified zero-crossing technique. Thus, the proposed estimation algorithm requires less hardware and software sources and can achieve even higher efficiency when the experimental data increase. Experimental results with modulated magnetic signal show that the root mean square error of frequency estimation is below 0.032 Hz with the proposed algorithm, which has lower computational complexity and better global performance than conventional frequency estimation methods.

A third-order approximation method for three-dimensional wheel-rail contact

NASA Astrophysics Data System (ADS)

Negretti, Daniele

2012-03-01

Multibody train analysis is used increasingly by railway operators whenever a reliable and time-efficient method to evaluate the contact between wheel and rail is needed; particularly, the wheel-rail contact is one of the most important aspects that affects a reliable and time-efficient vehicle dynamics computation. The focus of the approach proposed here is to carry out such tasks by means of online wheel-rail elastic contact detection. In order to improve efficiency and save time, a main analytical approach is used for the definition of wheel and rail surfaces as well as for contact detection, then a final numerical evaluation is used to locate contact. The final numerical procedure consists in finding the zeros of a nonlinear function in a single variable. The overall method is based on the approximation of the wheel surface, which does not influence the contact location significantly, as shown in the paper.

Knowledge representation and user interface concepts to support mixed-initiative diagnosis

NASA Technical Reports Server (NTRS)

Sobelman, Beverly H.; Holtzblatt, Lester J.

1989-01-01

The Remote Maintenance Monitoring System (RMMS) provides automated support for the maintenance and repair of ModComp computer systems used in the Launch Processing System (LPS) at Kennedy Space Center. RMMS supports manual and automated diagnosis of intermittent hardware failures, providing an efficient means for accessing and analyzing the data generated by catastrophic failure recovery procedures. This paper describes the design and functionality of the user interface for interactive analysis of memory dump data, relating it to the underlying declarative representation of memory dumps.

Generalizing the Nonlocal-Means to Super-Resolution Reconstruction

DTIC Science & Technology

2008-12-12

Image Process., vol. 5, no. 6, pp. 996–1011, Jun. 1996. [7] A. J. Patti, M. I. Sezan, and M. A. Tekalp, “ Superresolution video reconstruction with...computationally efficient image superresolution algorithm,” IEEE Trans. Image Process., vol. 10, no. 4, pp. 573–583, Apr. 2001. [13] M. Elad and Y...pp. 21–36, May 2003. [18] S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, “Robust shift and add approach to superresolution ,” in Proc. SPIE Conf

Training trajectories by continuous recurrent multilayer networks.

PubMed

Leistritz, L; Galicki, M; Witte, H; Kochs, E

2002-01-01

This paper addresses the problem of training trajectories by means of continuous recurrent neural networks whose feedforward parts are multilayer perceptrons. Such networks can approximate a general nonlinear dynamic system with arbitrary accuracy. The learning process is transformed into an optimal control framework where the weights are the controls to be determined. A training algorithm based upon a variational formulation of Pontryagin's maximum principle is proposed for such networks. Computer examples demonstrating the efficiency of the given approach are also presented.

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.

Users manual for linear Time-Varying Helicopter Simulation (Program TVHIS)

NASA Technical Reports Server (NTRS)

Burns, M. R.

1979-01-01

A linear time-varying helicopter simulation program (TVHIS) is described. The program is designed as a realistic yet efficient helicopter simulation. It is based on a linear time-varying helicopter model which includes rotor, actuator, and sensor models, as well as a simulation of flight computer logic. The TVHIS can generate a mean trajectory simulation along a nominal trajectory, or propagate covariance of helicopter states, including rigid-body, turbulence, control command, controller states, and rigid-body state estimates.

Newton's method applied to finite-difference approximations for the steady-state compressible Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Bailey, Harry E.; Beam, Richard M.

1991-01-01

Finite-difference approximations for steady-state compressible Navier-Stokes equations, whose two spatial dimensions are written in generalized curvilinear coordinates and strong conservation-law form, are presently solved by means of Newton's method in order to obtain a lifting-airfoil flow field under subsonic and transonnic conditions. In addition to ascertaining the computational requirements of an initial guess ensuring convergence and the degree of computational efficiency obtainable via the approximate Newton method's freezing of the Jacobian matrices, attention is given to the need for auxiliary methods assessing the temporal stability of steady-state solutions. It is demonstrated that nonunique solutions of the finite-difference equations are obtainable by Newton's method in conjunction with a continuation method.

Buffer management for sequential decoding. [block erasure probability reduction

NASA Technical Reports Server (NTRS)

Layland, J. W.

1974-01-01

Sequential decoding has been found to be an efficient means of communicating at low undetected error rates from deep space probes, but erasure or computational overflow remains a significant problem. Erasure of a block occurs when the decoder has not finished decoding that block at the time that it must be output. By drawing upon analogies in computer time sharing, this paper develops a buffer-management strategy which reduces the decoder idle time to a negligible level, and therefore improves the erasure probability of a sequential decoder. For a decoder with a speed advantage of ten and a buffer size of ten blocks, operating at an erasure rate of .01, use of this buffer-management strategy reduces the erasure rate to less than .0001.

CCOMP: An efficient algorithm for complex roots computation of determinantal equations

NASA Astrophysics Data System (ADS)

Zouros, Grigorios P.

2018-01-01

In this paper a free Python algorithm, entitled CCOMP (Complex roots COMPutation), is developed for the efficient computation of complex roots of determinantal equations inside a prescribed complex domain. The key to the method presented is the efficient determination of the candidate points inside the domain which, in their close neighborhood, a complex root may lie. Once these points are detected, the algorithm proceeds to a two-dimensional minimization problem with respect to the minimum modulus eigenvalue of the system matrix. In the core of CCOMP exist three sub-algorithms whose tasks are the efficient estimation of the minimum modulus eigenvalues of the system matrix inside the prescribed domain, the efficient computation of candidate points which guarantee the existence of minima, and finally, the computation of minima via bound constrained minimization algorithms. Theoretical results and heuristics support the development and the performance of the algorithm, which is discussed in detail. CCOMP supports general complex matrices, and its efficiency, applicability and validity is demonstrated to a variety of microwave applications.

Adolescents' technology and face-to-face time use predict objective sleep outcomes.

PubMed

Tavernier, Royette; Heissel, Jennifer A; Sladek, Michael R; Grant, Kathryn E; Adam, Emma K

2017-08-01

The present study examined both within- and between-person associations between adolescents' time use (technology-based activities and face-to-face interactions with friends and family) and sleep behaviors. We also assessed whether age moderated associations between adolescents' time use with friends and family and sleep. Adolescents wore an actigraph monitor and completed brief evening surveys daily for 3 consecutive days. Adolescents (N=71; mean age=14.50 years old, SD=1.84; 43.7% female) were recruited from 3 public high schools in the Midwest. We assessed 8 technology-based activities (eg, texting, working on a computer), as well as time spent engaged in face-to-face interactions with friends and family, via questions on adolescents' evening surveys. Actigraph monitors assessed 3 sleep behaviors: sleep latency, sleep hours, and sleep efficiency. Hierarchical linear models indicated that texting and working on the computer were associated with shorter sleep, whereas time spent talking on the phone predicted longer sleep. Time spent with friends predicted shorter sleep latencies, while family time predicted longer sleep latencies. Age moderated the association between time spent with friends and sleep efficiency, as well as between family time and sleep efficiency. Specifically, longer time spent interacting with friends was associated with higher sleep efficiency but only among younger adolescents. Furthermore, longer family time was associated with higher sleep efficiency but only for older adolescents. Findings are discussed in terms of the importance of regulating adolescents' technology use and improving opportunities for face-to-face interactions with friends, particularly for younger adolescents. Copyright © 2017 National Sleep Foundation. Published by Elsevier Inc. All rights reserved.

Automating tasks in protein structure determination with the clipper python module

PubMed Central

McNicholas, Stuart; Croll, Tristan; Burnley, Tom; Palmer, Colin M.; Hoh, Soon Wen; Jenkins, Huw T.; Dodson, Eleanor

2017-01-01

Abstract Scripting programming languages provide the fastest means of prototyping complex functionality. Those with a syntax and grammar resembling human language also greatly enhance the maintainability of the produced source code. Furthermore, the combination of a powerful, machine‐independent scripting language with binary libraries tailored for each computer architecture allows programs to break free from the tight boundaries of efficiency traditionally associated with scripts. In the present work, we describe how an efficient C++ crystallographic library such as Clipper can be wrapped, adapted and generalized for use in both crystallographic and electron cryo‐microscopy applications, scripted with the Python language. We shall also place an emphasis on best practices in automation, illustrating how this can be achieved with this new Python module. PMID:28901669

How Automation Can Help Alleviate the Budget Crunch in Public Health Research.

PubMed

Muennig, Peter A

2015-09-01

In an era of severe funding constraints for public health research, more efficient means of conducting research will be needed if scientific progress is to continue. At present major funders, such as the National Institutes of Health, do not provide specific instructions to grant authors or to reviewers regarding the cost efficiency of the research that they conduct. Doing so could potentially allow more research to be funded within current budgetary constraints and reduce waste. I describe how a blinded randomized trial was conducted for $ 275,000 by completely automating the consent and data collection processes. The study used the participants' own computer equipment, relied on big data for outcomes, and outsourced some costly tasks, potentially saving $1 million in research costs.

Characteristics of microstrip muscle-loaded single-arm Archimedean spiral antennas as investigated by FDTD numerical computations.

PubMed

Jacobsen, Svein; Rolfsnes, Hans Olav; Stauffer, Paul R

2005-02-01

The radiation characteristics and mode of operation of single-arm, groundplane backed, Archimedean spiral antennas are investigated by means of conformal finite difference time domain numerical analysis. It is shown that this antenna type may be categorized as a well-matched, broadband, circularly polarized traveling wave structure that can be fed directly by nonbalanced coaxial networks. The study further concentrates on relevant design and description features parameterized in terms of measures like radiation efficiency, sensing depth, directivity, and axial ratio of complementary polarizations. We document that an antenna of only 30-mm transverse size produces circularly polarized waves in a two-octave frequency span (2-8 GHz) with acceptable radiation efficiency (76%-94%) when loaded by muscle-like tissue.

Computational Science: A Research Methodology for the 21st Century

NASA Astrophysics Data System (ADS)

Orbach, Raymond L.

2004-03-01

Computational simulation - a means of scientific discovery that employs computer systems to simulate a physical system according to laws derived from theory and experiment - has attained peer status with theory and experiment. Important advances in basic science are accomplished by a new "sociology" for ultrascale scientific computing capability (USSCC), a fusion of sustained advances in scientific models, mathematical algorithms, computer architecture, and scientific software engineering. Expansion of current capabilities by factors of 100 - 1000 open up new vistas for scientific discovery: long term climatic variability and change, macroscopic material design from correlated behavior at the nanoscale, design and optimization of magnetic confinement fusion reactors, strong interactions on a computational lattice through quantum chromodynamics, and stellar explosions and element production. The "virtual prototype," made possible by this expansion, can markedly reduce time-to-market for industrial applications such as jet engines and safer, more fuel efficient cleaner cars. In order to develop USSCC, the National Energy Research Scientific Computing Center (NERSC) announced the competition "Innovative and Novel Computational Impact on Theory and Experiment" (INCITE), with no requirement for current DOE sponsorship. Fifty nine proposals for grand challenge scientific problems were submitted for a small number of awards. The successful grants, and their preliminary progress, will be described.

Applications of quantum measurement techniques: Counterfactual quantum computation, spin hall effect of light, and atomic-vapor-based photon detectors

NASA Astrophysics Data System (ADS)

Hosten, Onur

This dissertation investigates several physical phenomena in atomic and optical physics, and quantum information science, by utilizing various types and techniques of quantum measurements. It is the deeper concepts of these measurements, and the way they are integrated into the seemingly unrelated topics investigated, which binds together the research presented here. The research comprises three different topics: Counterfactual quantum computation, the spin Hall effect of light, and ultra-high-efficiency photon detectors based on atomic vapors. Counterfactual computation entails obtaining answers from a quantum computer without actually running it, and is accomplished by preparing the computer as a whole into a superposition of being activated and not activated. The first experimental demonstration is presented, including the best performing implementation of Grover's quantum search algorithm to date. In addition, we develop new counterfactual computation protocols that enable unconditional and completely deterministic operation. These methods stimulated a debate in the literature, on the meaning of counterfactuality in quantum processes, which we also discuss. The spin Hall effect of light entails tiny spin-dependent displacements, unsuspected until 2004, of a beam of light when it changes propagation direction. The first experimental demonstration of the effect during refraction at an air-glass interface is presented, together with a novel enabling metrological tool relying on the concepts of quantum weak measurements. Extensions of the effect to smoothly varying media are also presented, along with utilization of a time-varying version of the weak measurement techniques. Our approach to ultra-high-efficiency photon detection develops and extends a recent novel non-solid-state scheme for photo-detection based on atomic vapors. This approach is in principle capable of resolving the number of photons in a pulse, can be extended to non-destructive detection of photons, and most importantly is proposed to operate with single-photon detection efficiencies exceeding 99%, ideally without dark counts. Such a detector would have tremendous implications, e.g., for optical quantum information processing. The feasibility of operation of this approach at the desired level is studied theoretically and several promising physical systems are investigated.

Memristive Mixed-Signal Neuromorphic Systems: Energy-Efficient Learning at the Circuit-Level

DOE PAGES

Chakma, Gangotree; Adnan, Md Musabbir; Wyer, Austin R.; ...

2017-11-23

Neuromorphic computing is non-von Neumann computer architecture for the post Moore’s law era of computing. Since a main focus of the post Moore’s law era is energy-efficient computing with fewer resources and less area, neuromorphic computing contributes effectively in this research. Here in this paper, we present a memristive neuromorphic system for improved power and area efficiency. Our particular mixed-signal approach implements neural networks with spiking events in a synchronous way. Moreover, the use of nano-scale memristive devices saves both area and power in the system. We also provide device-level considerations that make the system more energy-efficient. The proposed systemmore » additionally includes synchronous digital long term plasticity, an online learning methodology that helps the system train the neural networks during the operation phase and improves the efficiency in learning considering the power consumption and area overhead.« less

Memristive Mixed-Signal Neuromorphic Systems: Energy-Efficient Learning at the Circuit-Level

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

Chakma, Gangotree; Adnan, Md Musabbir; Wyer, Austin R.

Neuromorphic computing is non-von Neumann computer architecture for the post Moore’s law era of computing. Since a main focus of the post Moore’s law era is energy-efficient computing with fewer resources and less area, neuromorphic computing contributes effectively in this research. Here in this paper, we present a memristive neuromorphic system for improved power and area efficiency. Our particular mixed-signal approach implements neural networks with spiking events in a synchronous way. Moreover, the use of nano-scale memristive devices saves both area and power in the system. We also provide device-level considerations that make the system more energy-efficient. The proposed systemmore » additionally includes synchronous digital long term plasticity, an online learning methodology that helps the system train the neural networks during the operation phase and improves the efficiency in learning considering the power consumption and area overhead.« less

GPU-based cloud service for Smith-Waterman algorithm using frequency distance filtration scheme.

PubMed

Lee, Sheng-Ta; Lin, Chun-Yuan; Hung, Che Lun

2013-01-01

As the conventional means of analyzing the similarity between a query sequence and database sequences, the Smith-Waterman algorithm is feasible for a database search owing to its high sensitivity. However, this algorithm is still quite time consuming. CUDA programming can improve computations efficiently by using the computational power of massive computing hardware as graphics processing units (GPUs). This work presents a novel Smith-Waterman algorithm with a frequency-based filtration method on GPUs rather than merely accelerating the comparisons yet expending computational resources to handle such unnecessary comparisons. A user friendly interface is also designed for potential cloud server applications with GPUs. Additionally, two data sets, H1N1 protein sequences (query sequence set) and human protein database (database set), are selected, followed by a comparison of CUDA-SW and CUDA-SW with the filtration method, referred to herein as CUDA-SWf. Experimental results indicate that reducing unnecessary sequence alignments can improve the computational time by up to 41%. Importantly, by using CUDA-SWf as a cloud service, this application can be accessed from any computing environment of a device with an Internet connection without time constraints.

Bioleaching of gold, copper and nickel from waste cellular phone PCBs and computer goldfinger motherboards by two Aspergillus nigerstrains

PubMed Central

Madrigal-Arias, Jorge Enrique; Argumedo-Delira, Rosalba; Alarcón, Alejandro; Mendoza-López, Ma. Remedios; García-Barradas, Oscar; Cruz-Sánchez, Jesús Samuel; Ferrera-Cerrato, Ronald; Jiménez-Fernández, Maribel

2015-01-01

In an effort to develop alternate techniques to recover metals from waste electrical and electronic equipment (WEEE), this research evaluated the bioleaching efficiency of gold (Au), copper (Cu) and nickel (Ni) by two strains of Aspergillus niger in the presence of gold-plated finger integrated circuits found in computer motherboards (GFICMs) and cellular phone printed circuit boards (PCBs). These three metals were analyzed for their commercial value and their diverse applications in the industry. Au-bioleaching ranged from 42 to 1% for Aspergillus niger strain MXPE6; with the combination of Aspergillus niger MXPE6 + Aspergillus niger MX7, the Au-bioleaching was 87 and 28% for PCBs and GFICMs, respectively. In contrast, the bioleaching of Cu by Aspergillus niger MXPE6 was 24 and 5%; using the combination of both strains, the values were 0.2 and 29% for PCBs and GFICMs, respectively. Fungal Ni-leaching was only found for PCBs, but with no significant differences among treatments. Improvement of the metal recovery efficiency by means of fungal metabolism is also discussed. PMID:26413051

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.

Fine grained event processing on HPCs with the ATLAS Yoda system

NASA Astrophysics Data System (ADS)

Calafiura, Paolo; De, Kaushik; Guan, Wen; Maeno, Tadashi; Nilsson, Paul; Oleynik, Danila; Panitkin, Sergey; Tsulaia, Vakhtang; Van Gemmeren, Peter; Wenaus, Torre

2015-12-01

High performance computing facilities present unique challenges and opportunities for HEP event processing. The massive scale of many HPC systems means that fractionally small utilization can yield large returns in processing throughput. Parallel applications which can dynamically and efficiently fill any scheduling opportunities the resource presents benefit both the facility (maximal utilization) and the (compute-limited) science. The ATLAS Yoda system provides this capability to HEP-like event processing applications by implementing event-level processing in an MPI-based master-client model that integrates seamlessly with the more broadly scoped ATLAS Event Service. Fine grained, event level work assignments are intelligently dispatched to parallel workers to sustain full utilization on all cores, with outputs streamed off to destination object stores in near real time with similarly fine granularity, such that processing can proceed until termination with full utilization. The system offers the efficiency and scheduling flexibility of preemption without requiring the application actually support or employ check-pointing. We will present the new Yoda system, its motivations, architecture, implementation, and applications in ATLAS data processing at several US HPC centers.

Fluid-structure analysis of a flexible flapping airfoil at low Reynolds number flow

NASA Astrophysics Data System (ADS)

Unger, Ralf; Haupt, Matthias C.; Horst, Peter; Radespiel, Rolf

2012-01-01

In this paper, a coupling simulation methodology is applied to investigate the fluid flow around a light and flexible airfoil based on a handfoil of a seagull. A finite element model of the flexible airfoil is fully coupled to the flow solver by using a load and displacement transfer as well as a fluid grid deformation algorithm. The flow field is characterized by a laminar-turbulent transition at a Reynolds number of Re=100 000, which takes place along a laminar separation bubble. An unsteady Reynolds-averaged Navier-Stokes flow solver is used to take this transition process into account by comparison of a critical N-factor with the N-factor computed by the eN-method. Results of computations have shown that the flexibility of the airfoil has a major influence on the thrust efficiency, the mean drag and lift, and the location of laminar-turbulent transition. The thrust efficiency can be considerably improved by increasing the plunging amplitude and by using a time dependent airfoil stiffness, inspired by the muscle contraction of birds.

Linear homotopy solution of nonlinear systems of equations in geodesy

NASA Astrophysics Data System (ADS)

Paláncz, Béla; Awange, Joseph L.; Zaletnyik, Piroska; Lewis, Robert H.

2010-01-01

A fundamental task in geodesy is solving systems of equations. Many geodetic problems are represented as systems of multivariate polynomials. A common problem in solving such systems is improper initial starting values for iterative methods, leading to convergence to solutions with no physical meaning, or to convergence that requires global methods. Though symbolic methods such as Groebner bases or resultants have been shown to be very efficient, i.e., providing solutions for determined systems such as 3-point problem of 3D affine transformation, the symbolic algebra can be very time consuming, even with special Computer Algebra Systems (CAS). This study proposes the Linear Homotopy method that can be implemented easily in high-level computer languages like C++ and Fortran that are faster than CAS by at least two orders of magnitude. Using Mathematica, the power of Homotopy is demonstrated in solving three nonlinear geodetic problems: resection, GPS positioning, and affine transformation. The method enlarging the domain of convergence is found to be efficient, less sensitive to rounding of numbers, and has lower complexity compared to other local methods like Newton-Raphson.

Exploiting the chaotic behaviour of atmospheric models with reconfigurable architectures

NASA Astrophysics Data System (ADS)

Russell, Francis P.; Düben, Peter D.; Niu, Xinyu; Luk, Wayne; Palmer, T. N.

2017-12-01

Reconfigurable architectures are becoming mainstream: Amazon, Microsoft and IBM are supporting such architectures in their data centres. The computationally intensive nature of atmospheric modelling is an attractive target for hardware acceleration using reconfigurable computing. Performance of hardware designs can be improved through the use of reduced-precision arithmetic, but maintaining appropriate accuracy is essential. We explore reduced-precision optimisation for simulating chaotic systems, targeting atmospheric modelling, in which even minor changes in arithmetic behaviour will cause simulations to diverge quickly. The possibility of equally valid simulations having differing outcomes means that standard techniques for comparing numerical accuracy are inappropriate. We use the Hellinger distance to compare statistical behaviour between reduced-precision CPU implementations to guide reconfigurable designs of a chaotic system, then analyse accuracy, performance and power efficiency of the resulting implementations. Our results show that with only a limited loss in accuracy corresponding to less than 10% uncertainty in input parameters, the throughput and energy efficiency of a single-precision chaotic system implemented on a Xilinx Virtex-6 SX475T Field Programmable Gate Array (FPGA) can be more than doubled.

Water droplet impingement on airfoils and aircraft engine inlets for icing analysis

NASA Technical Reports Server (NTRS)

Papadakis, Michael; Elangovan, R.; Freund, George A., Jr.; Breer, Marlin D.

1991-01-01

This paper includes the results of a significant research program for verification of computer trajectory codes used in aircraft icing analysis. Experimental water droplet impingement data have been obtained in the NASA Lewis Research Center Icing Research Tunnel for a wide range of aircraft geometries and test conditions. The body whose impingement characteristics are required is covered at strategic locations by thin strips of moisture absorbing (blotter) paper and then exposed to an airstream containing a dyed-water spray cloud. Water droplet impingement data are extracted from the dyed blotter strips by measuring the optical reflectance of the dye deposit on the strips with an automated reflectometer. Impingement characteristics for all test geometries have also been calculated using two recently developed trajectory computer codes. Good agreement is obtained with experimental data. The experimental and analytical data show that maximum impingement efficiency and impingement limits increase with mean volumetric diameter for all geometries tested. For all inlet geometries tested, as the inlet mass flow is reduced, the maximum impingement efficiency is reduced and the location of the maximum impingement shifts toward the inlet inner cowl.

Automatic diagnosis of tuberculosis disease based on Plasmonic ELISA and color-based image classification.

PubMed

AbuHassan, Kamal J; Bakhori, Noremylia M; Kusnin, Norzila; Azmi, Umi Z M; Tania, Marzia H; Evans, Benjamin A; Yusof, Nor A; Hossain, M A

2017-07-01

Tuberculosis (TB) remains one of the most devastating infectious diseases and its treatment efficiency is majorly influenced by the stage at which infection with the TB bacterium is diagnosed. The available methods for TB diagnosis are either time consuming, costly or not efficient. This study employs a signal generation mechanism for biosensing, known as Plasmonic ELISA, and computational intelligence to facilitate automatic diagnosis of TB. Plasmonic ELISA enables the detection of a few molecules of analyte by the incorporation of smart nanomaterials for better sensitivity of the developed detection system. The computational system uses k-means clustering and thresholding for image segmentation. This paper presents the results of the classification performance of the Plasmonic ELISA imaging data by using various types of classifiers. The five-fold cross-validation results show high accuracy rate (>97%) in classifying TB images using the entire data set. Future work will focus on developing an intelligent mobile-enabled expert system to diagnose TB in real-time. The intelligent system will be clinically validated and tested in collaboration with healthcare providers in Malaysia.

Freud: a software suite for high-throughput simulation analysis

NASA Astrophysics Data System (ADS)

Harper, Eric; Spellings, Matthew; Anderson, Joshua; Glotzer, Sharon

Computer simulation is an indispensable tool for the study of a wide variety of systems. As simulations scale to fill petascale and exascale supercomputing clusters, so too does the size of the data produced, as well as the difficulty in analyzing these data. We present Freud, an analysis software suite for efficient analysis of simulation data. Freud makes no assumptions about the system being analyzed, allowing for general analysis methods to be applied to nearly any type of simulation. Freud includes standard analysis methods such as the radial distribution function, as well as new methods including the potential of mean force and torque and local crystal environment analysis. Freud combines a Python interface with fast, parallel C + + analysis routines to run efficiently on laptops, workstations, and supercomputing clusters. Data analysis on clusters reduces data transfer requirements, a prohibitive cost for petascale computing. Used in conjunction with simulation software, Freud allows for smart simulations that adapt to the current state of the system, enabling the study of phenomena such as nucleation and growth, intelligent investigation of phases and phase transitions, and determination of effective pair potentials.

Bioleaching of gold, copper and nickel from waste cellular phone PCBs and computer goldfinger motherboards by two Aspergillus nigerstrains.

PubMed

Madrigal-Arias, Jorge Enrique; Argumedo-Delira, Rosalba; Alarcón, Alejandro; Mendoza-López, Ma Remedios; García-Barradas, Oscar; Cruz-Sánchez, Jesús Samuel; Ferrera-Cerrato, Ronald; Jiménez-Fernández, Maribel

2015-01-01

In an effort to develop alternate techniques to recover metals from waste electrical and electronic equipment (WEEE), this research evaluated the bioleaching efficiency of gold (Au), copper (Cu) and nickel (Ni) by two strains of Aspergillus niger in the presence of gold-plated finger integrated circuits found in computer motherboards (GFICMs) and cellular phone printed circuit boards (PCBs). These three metals were analyzed for their commercial value and their diverse applications in the industry. Au-bioleaching ranged from 42 to 1% for Aspergillus niger strain MXPE6; with the combination of Aspergillus niger MXPE6 + Aspergillus niger MX7, the Au-bioleaching was 87 and 28% for PCBs and GFICMs, respectively. In contrast, the bioleaching of Cu by Aspergillus niger MXPE6 was 24 and 5%; using the combination of both strains, the values were 0.2 and 29% for PCBs and GFICMs, respectively. Fungal Ni-leaching was only found for PCBs, but with no significant differences among treatments. Improvement of the metal recovery efficiency by means of fungal metabolism is also discussed.

PDF modeling of turbulent flows on unstructured grids

NASA Astrophysics Data System (ADS)

Bakosi, Jozsef

In probability density function (PDF) methods of turbulent flows, the joint PDF of several flow variables is computed by numerically integrating a system of stochastic differential equations for Lagrangian particles. Because the technique solves a transport equation for the PDF of the velocity and scalars, a mathematically exact treatment of advection, viscous effects and arbitrarily complex chemical reactions is possible; these processes are treated without closure assumptions. A set of algorithms is proposed to provide an efficient solution of the PDF transport equation modeling the joint PDF of turbulent velocity, frequency and concentration of a passive scalar in geometrically complex configurations. An unstructured Eulerian grid is employed to extract Eulerian statistics, to solve for quantities represented at fixed locations of the domain and to track particles. All three aspects regarding the grid make use of the finite element method. Compared to hybrid methods, the current methodology is stand-alone, therefore it is consistent both numerically and at the level of turbulence closure without the use of consistency conditions. Since both the turbulent velocity and scalar concentration fields are represented in a stochastic way, the method allows for a direct and close interaction between these fields, which is beneficial in computing accurate scalar statistics. Boundary conditions implemented along solid bodies are of the free-slip and no-slip type without the need for ghost elements. Boundary layers at no-slip boundaries are either fully resolved down to the viscous sublayer, explicitly modeling the high anisotropy and inhomogeneity of the low-Reynolds-number wall region without damping or wall-functions or specified via logarithmic wall-functions. As in moment closures and large eddy simulation, these wall-treatments provide the usual trade-off between resolution and computational cost as required by the given application. Particular attention is focused on modeling the dispersion of passive scalars in inhomogeneous turbulent flows. Two different micromixing models are investigated that incorporate the effect of small scale mixing on the transported scalar: the widely used interaction by exchange with the mean and the interaction by exchange with the conditional mean model. An adaptive algorithm to compute the velocity-conditioned scalar mean is proposed that homogenizes the statistical error over the sample space with no assumption on the shape of the underlying velocity PDF. The development also concentrates on a generally applicable micromixing timescale for complex flow domains. Several newly developed algorithms are described in detail that facilitate a stable numerical solution in arbitrarily complex flow geometries, including a stabilized mean-pressure projection scheme, the estimation of conditional and unconditional Eulerian statistics and their derivatives from stochastic particle fields employing finite element shapefunctions, particle tracking through unstructured grids, an efficient particle redistribution procedure and techniques related to efficient random number generation. The algorithm is validated and tested by computing three different turbulent flows: the fully developed turbulent channel flow, a street canyon (or cavity) flow and the turbulent wake behind a circular cylinder at a sub-critical Reynolds number. The solver has been parallelized and optimized for shared memory and multi-core architectures using the OpenMP standard. Relevant aspects of performance and parallelism on cache-based shared memory machines are discussed and presented in detail. The methodology shows great promise in the simulation of high-Reynolds-number incompressible inert or reactive turbulent flows in realistic configurations.

Application of a computationally efficient method to approximate gap model results with a probabilistic approach

NASA Astrophysics Data System (ADS)

Scherstjanoi, M.; Kaplan, J. O.; Lischke, H.

2014-02-01

To be able to simulate climate change effects on forest dynamics over the whole of Switzerland, we adapted the second generation DGVM LPJ-GUESS to the Alpine environment. We modified model functions, tuned model parameters, and implemented new tree species to represent the potential natural vegetation of Alpine landscapes. Furthermore, we increased the computational efficiency of the model to enable area-covering simulations in a fine resolution (1 km) sufficient for the complex topography of the Alps, which resulted in more than 32 000 simulation grid cells. To this aim, we applied the recently developed method GAPPARD (Scherstjanoi et al., 2013) to LPJ-GUESS. GAPPARD derives mean output values from a combination of simulation runs without disturbances and a patch age distribution defined by the disturbance frequency. With this computationally efficient method, that increased the model's speed by approximately the factor 8, we were able to faster detect shortcomings of LPJ-GUESS functions and parameters. We used the adapted LPJ-GUESS together with GAPPARD to assess the influence of one climate change scenario on dynamics of tree species composition and biomass throughout the 21st century in Switzerland. To allow for comparison with the original model, we additionally simulated forest dynamics along a north-south-transect through Switzerland. The results from this transect confirmed the high value of the GAPPARD method despite some limitations towards extreme climatic events. It allowed for the first time to obtain area-wide, detailed high resolution LPJ-GUESS simulation results for a large part of the Alpine region.

Geospatial Representation, Analysis and Computing Using Bandlimited Functions

DTIC Science & Technology

2010-02-19

navigation of aircraft and missiles require detailed representations of gravity and efficient methods for determining orbits and trajectories. However, many...efficient on today’s computers. Under this grant new, computationally efficient, localized representations of gravity have been developed and tested. As a...step in developing a new approach to estimating gravitational potentials, a multiresolution representation for gravity estimation has been proposed

Efficient Computational Prototyping of Mixed Technology Microfluidic Components and Systems

DTIC Science & Technology

2002-08-01

AFRL-IF-RS-TR-2002-190 Final Technical Report August 2002 EFFICIENT COMPUTATIONAL PROTOTYPING OF MIXED TECHNOLOGY MICROFLUIDIC...SUBTITLE EFFICIENT COMPUTATIONAL PROTOTYPING OF MIXED TECHNOLOGY MICROFLUIDIC COMPONENTS AND SYSTEMS 6. AUTHOR(S) Narayan R. Aluru, Jacob White...Aided Design (CAD) tools for microfluidic components and systems were developed in this effort. Innovative numerical methods and algorithms for mixed

Cloud based emergency health care information service in India.

PubMed

Karthikeyan, N; Sukanesh, R

2012-12-01

A hospital is a health care organization providing patient treatment by expert physicians, surgeons and equipments. A report from a health care accreditation group says that miscommunication between patients and health care providers is the reason for the gap in providing emergency medical care to people in need. In developing countries, illiteracy is the major key root for deaths resulting from uncertain diseases constituting a serious public health problem. Mentally affected, differently abled and unconscious patients can't communicate about their medical history to the medical practitioners. Also, Medical practitioners can't edit or view DICOM images instantly. Our aim is to provide palm vein pattern recognition based medical record retrieval system, using cloud computing for the above mentioned people. Distributed computing technology is coming in the new forms as Grid computing and Cloud computing. These new forms are assured to bring Information Technology (IT) as a service. In this paper, we have described how these new forms of distributed computing will be helpful for modern health care industries. Cloud Computing is germinating its benefit to industrial sectors especially in medical scenarios. In Cloud Computing, IT-related capabilities and resources are provided as services, via the distributed computing on-demand. This paper is concerned with sprouting software as a service (SaaS) by means of Cloud computing with an aim to bring emergency health care sector in an umbrella with physical secured patient records. In framing the emergency healthcare treatment, the crucial thing considered necessary to decide about patients is their previous health conduct records. Thus a ubiquitous access to appropriate records is essential. Palm vein pattern recognition promises a secured patient record access. Likewise our paper reveals an efficient means to view, edit or transfer the DICOM images instantly which was a challenging task for medical practitioners in the past years. We have developed two services for health care. 1. Cloud based Palm vein recognition system 2. Distributed Medical image processing tools for medical practitioners.

An efficient surrogate-based simulation-optimization method for calibrating a regional MODFLOW model

NASA Astrophysics Data System (ADS)

Chen, Mingjie; Izady, Azizallah; Abdalla, Osman A.

2017-01-01

Simulation-optimization method entails a large number of model simulations, which is computationally intensive or even prohibitive if the model simulation is extremely time-consuming. Statistical models have been examined as a surrogate of the high-fidelity physical model during simulation-optimization process to tackle this problem. Among them, Multivariate Adaptive Regression Splines (MARS), a non-parametric adaptive regression method, is superior in overcoming problems of high-dimensions and discontinuities of the data. Furthermore, the stability and accuracy of MARS model can be improved by bootstrap aggregating methods, namely, bagging. In this paper, Bagging MARS (BMARS) method is integrated to a surrogate-based simulation-optimization framework to calibrate a three-dimensional MODFLOW model, which is developed to simulate the groundwater flow in an arid hardrock-alluvium region in northwestern Oman. The physical MODFLOW model is surrogated by the statistical model developed using BMARS algorithm. The surrogate model, which is fitted and validated using training dataset generated by the physical model, can approximate solutions rapidly. An efficient Sobol' method is employed to calculate global sensitivities of head outputs to input parameters, which are used to analyze their importance for the model outputs spatiotemporally. Only sensitive parameters are included in the calibration process to further improve the computational efficiency. Normalized root mean square error (NRMSE) between measured and simulated heads at observation wells is used as the objective function to be minimized during optimization. The reasonable history match between the simulated and observed heads demonstrated feasibility of this high-efficient calibration framework.

Tree-space statistics and approximations for large-scale analysis of anatomical trees.

PubMed

Feragen, Aasa; Owen, Megan; Petersen, Jens; Wille, Mathilde M W; Thomsen, Laura H; Dirksen, Asger; de Bruijne, Marleen

2013-01-01

Statistical analysis of anatomical trees is hard to perform due to differences in the topological structure of the trees. In this paper we define statistical properties of leaf-labeled anatomical trees with geometric edge attributes by considering the anatomical trees as points in the geometric space of leaf-labeled trees. This tree-space is a geodesic metric space where any two trees are connected by a unique shortest path, which corresponds to a tree deformation. However, tree-space is not a manifold, and the usual strategy of performing statistical analysis in a tangent space and projecting onto tree-space is not available. Using tree-space and its shortest paths, a variety of statistical properties, such as mean, principal component, hypothesis testing and linear discriminant analysis can be defined. For some of these properties it is still an open problem how to compute them; others (like the mean) can be computed, but efficient alternatives are helpful in speeding up algorithms that use means iteratively, like hypothesis testing. In this paper, we take advantage of a very large dataset (N = 8016) to obtain computable approximations, under the assumption that the data trees parametrize the relevant parts of tree-space well. Using the developed approximate statistics, we illustrate how the structure and geometry of airway trees vary across a population and show that airway trees with Chronic Obstructive Pulmonary Disease come from a different distribution in tree-space than healthy ones. Software is available from http://image.diku.dk/aasa/software.php.

Assessing eco-efficiency: A metafrontier directional distance function approach using life cycle analysis

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

Beltrán-Esteve, Mercedes, E-mail: mercedes.beltran@uv.es; Reig-Martínez, Ernest; Estruch-Guitart, Vicent

Sustainability analysis requires a joint assessment of environmental, social and economic aspects of production processes. Here we propose the use of Life Cycle Analysis (LCA), a metafrontier (MF) directional distance function (DDF) approach, and Data Envelopment Analysis (DEA), to assess technological and managerial differences in eco-efficiency between production systems. We use LCA to compute six environmental and health impacts associated with the production processes of nearly 200 Spanish citrus farms belonging to organic and conventional farming systems. DEA is then employed to obtain joint economic-environmental farm's scores that we refer to as eco-efficiency. DDF allows us to determine farms' globalmore » eco-efficiency scores, as well as eco-efficiency scores with respect to specific environmental impacts. Furthermore, the use of an MF helps us to disentangle technological and managerial eco-inefficiencies by comparing the eco-efficiency of both farming systems with regards to a common benchmark. Our core results suggest that the shift from conventional to organic farming technology would allow a potential reduction in environmental impacts of 80% without resulting in any decline in economic performance. In contrast, as regards farmers' managerial capacities, both systems display quite similar mean scores.« less

Exact and efficient simulation of concordant computation

NASA Astrophysics Data System (ADS)

Cable, Hugo; Browne, Daniel E.

2015-11-01

Concordant computation is a circuit-based model of quantum computation for mixed states, that assumes that all correlations within the register are discord-free (i.e. the correlations are essentially classical) at every step of the computation. The question of whether concordant computation always admits efficient simulation by a classical computer was first considered by Eastin in arXiv:quant-ph/1006.4402v1, where an answer in the affirmative was given for circuits consisting only of one- and two-qubit gates. Building on this work, we develop the theory of classical simulation of concordant computation. We present a new framework for understanding such computations, argue that a larger class of concordant computations admit efficient simulation, and provide alternative proofs for the main results of arXiv:quant-ph/1006.4402v1 with an emphasis on the exactness of simulation which is crucial for this model. We include detailed analysis of the arithmetic complexity for solving equations in the simulation, as well as extensions to larger gates and qudits. We explore the limitations of our approach, and discuss the challenges faced in developing efficient classical simulation algorithms for all concordant computations.

Efficient computation of the Grünwald-Letnikov fractional diffusion derivative using adaptive time step memory

NASA Astrophysics Data System (ADS)

MacDonald, Christopher L.; Bhattacharya, Nirupama; Sprouse, Brian P.; Silva, Gabriel A.

2015-09-01

Computing numerical solutions to fractional differential equations can be computationally intensive due to the effect of non-local derivatives in which all previous time points contribute to the current iteration. In general, numerical approaches that depend on truncating part of the system history while efficient, can suffer from high degrees of error and inaccuracy. Here we present an adaptive time step memory method for smooth functions applied to the Grünwald-Letnikov fractional diffusion derivative. This method is computationally efficient and results in smaller errors during numerical simulations. Sampled points along the system's history at progressively longer intervals are assumed to reflect the values of neighboring time points. By including progressively fewer points backward in time, a temporally 'weighted' history is computed that includes contributions from the entire past of the system, maintaining accuracy, but with fewer points actually calculated, greatly improving computational efficiency.

An efficient algorithm to compute marginal posterior genotype probabilities for every member of a pedigree with loops

PubMed Central

2009-01-01

Background Marginal posterior genotype probabilities need to be computed for genetic analyses such as geneticcounseling in humans and selective breeding in animal and plant species. Methods In this paper, we describe a peeling based, deterministic, exact algorithm to compute efficiently genotype probabilities for every member of a pedigree with loops without recourse to junction-tree methods from graph theory. The efficiency in computing the likelihood by peeling comes from storing intermediate results in multidimensional tables called cutsets. Computing marginal genotype probabilities for individual i requires recomputing the likelihood for each of the possible genotypes of individual i. This can be done efficiently by storing intermediate results in two types of cutsets called anterior and posterior cutsets and reusing these intermediate results to compute the likelihood. Examples A small example is used to illustrate the theoretical concepts discussed in this paper, and marginal genotype probabilities are computed at a monogenic disease locus for every member in a real cattle pedigree. PMID:19958551

Methods for Computationally Efficient Structured CFD Simulations of Complex Turbomachinery Flows

NASA Technical Reports Server (NTRS)

Herrick, Gregory P.; Chen, Jen-Ping

2012-01-01

This research presents more efficient computational methods by which to perform multi-block structured Computational Fluid Dynamics (CFD) simulations of turbomachinery, thus facilitating higher-fidelity solutions of complicated geometries and their associated flows. This computational framework offers flexibility in allocating resources to balance process count and wall-clock computation time, while facilitating research interests of simulating axial compressor stall inception with more complete gridding of the flow passages and rotor tip clearance regions than is typically practiced with structured codes. The paradigm presented herein facilitates CFD simulation of previously impractical geometries and flows. These methods are validated and demonstrate improved computational efficiency when applied to complicated geometries and flows.

What to Do When K-Means Clustering Fails: A Simple yet Principled Alternative Algorithm.

PubMed

Raykov, Yordan P; Boukouvalas, Alexis; Baig, Fahd; Little, Max A

The K-means algorithm is one of the most popular clustering algorithms in current use as it is relatively fast yet simple to understand and deploy in practice. Nevertheless, its use entails certain restrictive assumptions about the data, the negative consequences of which are not always immediately apparent, as we demonstrate. While more flexible algorithms have been developed, their widespread use has been hindered by their computational and technical complexity. Motivated by these considerations, we present a flexible alternative to K-means that relaxes most of the assumptions, whilst remaining almost as fast and simple. This novel algorithm which we call MAP-DP (maximum a-posteriori Dirichlet process mixtures), is statistically rigorous as it is based on nonparametric Bayesian Dirichlet process mixture modeling. This approach allows us to overcome most of the limitations imposed by K-means. The number of clusters K is estimated from the data instead of being fixed a-priori as in K-means. In addition, while K-means is restricted to continuous data, the MAP-DP framework can be applied to many kinds of data, for example, binary, count or ordinal data. Also, it can efficiently separate outliers from the data. This additional flexibility does not incur a significant computational overhead compared to K-means with MAP-DP convergence typically achieved in the order of seconds for many practical problems. Finally, in contrast to K-means, since the algorithm is based on an underlying statistical model, the MAP-DP framework can deal with missing data and enables model testing such as cross validation in a principled way. We demonstrate the simplicity and effectiveness of this algorithm on the health informatics problem of clinical sub-typing in a cluster of diseases known as parkinsonism.

What to Do When K-Means Clustering Fails: A Simple yet Principled Alternative Algorithm

PubMed Central

Baig, Fahd; Little, Max A.

2016-01-01

The K-means algorithm is one of the most popular clustering algorithms in current use as it is relatively fast yet simple to understand and deploy in practice. Nevertheless, its use entails certain restrictive assumptions about the data, the negative consequences of which are not always immediately apparent, as we demonstrate. While more flexible algorithms have been developed, their widespread use has been hindered by their computational and technical complexity. Motivated by these considerations, we present a flexible alternative to K-means that relaxes most of the assumptions, whilst remaining almost as fast and simple. This novel algorithm which we call MAP-DP (maximum a-posteriori Dirichlet process mixtures), is statistically rigorous as it is based on nonparametric Bayesian Dirichlet process mixture modeling. This approach allows us to overcome most of the limitations imposed by K-means. The number of clusters K is estimated from the data instead of being fixed a-priori as in K-means. In addition, while K-means is restricted to continuous data, the MAP-DP framework can be applied to many kinds of data, for example, binary, count or ordinal data. Also, it can efficiently separate outliers from the data. This additional flexibility does not incur a significant computational overhead compared to K-means with MAP-DP convergence typically achieved in the order of seconds for many practical problems. Finally, in contrast to K-means, since the algorithm is based on an underlying statistical model, the MAP-DP framework can deal with missing data and enables model testing such as cross validation in a principled way. We demonstrate the simplicity and effectiveness of this algorithm on the health informatics problem of clinical sub-typing in a cluster of diseases known as parkinsonism. PMID:27669525

Efficiency improvement in proton dose calculations with an equivalent restricted stopping power formalism

NASA Astrophysics Data System (ADS)

Maneval, Daniel; Bouchard, Hugo; Ozell, Benoît; Després, Philippe

2018-01-01

The equivalent restricted stopping power formalism is introduced for proton mean energy loss calculations under the continuous slowing down approximation. The objective is the acceleration of Monte Carlo dose calculations by allowing larger steps while preserving accuracy. The fractional energy loss per step length ɛ was obtained with a secant method and a Gauss-Kronrod quadrature estimation of the integral equation relating the mean energy loss to the step length. The midpoint rule of the Newton-Cotes formulae was then used to solve this equation, allowing the creation of a lookup table linking ɛ to the equivalent restricted stopping power L eq, used here as a key physical quantity. The mean energy loss for any step length was simply defined as the product of the step length with L eq. Proton inelastic collisions with electrons were added to GPUMCD, a GPU-based Monte Carlo dose calculation code. The proton continuous slowing-down was modelled with the L eq formalism. GPUMCD was compared to Geant4 in a validation study where ionization processes alone were activated and a voxelized geometry was used. The energy straggling was first switched off to validate the L eq formalism alone. Dose differences between Geant4 and GPUMCD were smaller than 0.31% for the L eq formalism. The mean error and the standard deviation were below 0.035% and 0.038% respectively. 99.4 to 100% of GPUMCD dose points were consistent with a 0.3% dose tolerance. GPUMCD 80% falloff positions (R80 ) matched Geant’s R80 within 1 μm. With the energy straggling, dose differences were below 2.7% in the Bragg peak falloff and smaller than 0.83% elsewhere. The R80 positions matched within 100 μm. The overall computation times to transport one million protons with GPUMCD were 31-173 ms. Under similar conditions, Geant4 computation times were 1.4-20 h. The L eq formalism led to an intrinsic efficiency gain factor ranging between 30-630, increasing with the prescribed accuracy of simulations. The L eq formalism allows larger steps leading to a O(constant) algorithmic time complexity. It significantly accelerates Monte Carlo proton transport while preserving accuracy. It therefore constitutes a promising variance reduction technique for computing proton dose distributions in a clinical context.

Performance comparison of an active matrix flat panel imager, computed radiography system, and a screen-film system at four standard radiation qualities.

PubMed

Monnin, P; Gutierrez, D; Bulling, S; Lepori, D; Valley, J F; Verdun, F R

2005-02-01

Four standard radiation qualities (from RQA 3 to RQA 9) were used to compare the imaging performance of a computed radiography (CR) system (general purpose and high resolution phosphor plates of a Kodak CR 9000 system), a selenium-based direct flat panel detector (Kodak Direct View DR 9000), and a conventional screen-film system (Kodak T-MAT L/RA film with a 3M Trimax Regular screen of speed 400) in conventional radiography. Reference exposure levels were chosen according to the manufacturer's recommendations to be representative of clinical practice (exposure index of 1700 for digital systems and a film optical density of 1.4). With the exception of the RQA 3 beam quality, the exposure levels needed to produce a mean digital signal of 1700 were higher than those needed to obtain a mean film optical density of 1.4. In spite of intense developments in the field of digital detectors, screen-film systems are still very efficient detectors for most of the beam qualities used in radiology. An important outcome of this study is the behavior of the detective quantum efficiency of the digital radiography (DR) system as a function of beam energy. The practice of users to increase beam energy when switching from a screen-film system to a CR system, in order to improve the compromise between patient dose and image quality, might not be appropriate when switching from screen-film to selenium-based DR systems.

Quantifying aggregated uncertainty in Plasmodium falciparum malaria prevalence and populations at risk via efficient space-time geostatistical joint simulation.

PubMed

Gething, Peter W; Patil, Anand P; Hay, Simon I

2010-04-01

Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncertainty that enhances their utility for decision-makers. In many settings, decision-makers require spatially aggregated measures over large regions such as the mean prevalence within a country or administrative region, or national populations living under different levels of risk. Existing MBG mapping approaches provide suitable metrics of local uncertainty--the fidelity of predictions at each mapped pixel--but have not been adapted for measuring uncertainty over large areas, due largely to a series of fundamental computational constraints. Here the authors present a new efficient approximating algorithm that can generate for the first time the necessary joint simulation of prevalence values across the very large prediction spaces needed for global scale mapping. This new approach is implemented in conjunction with an established model for P. falciparum allowing robust estimates of mean prevalence at any specified level of spatial aggregation. The model is used to provide estimates of national populations at risk under three policy-relevant prevalence thresholds, along with accompanying model-based measures of uncertainty. By overcoming previously unchallenged computational barriers, this study illustrates how MBG approaches, already at the forefront of infectious disease mapping, can be extended to provide large-scale aggregate measures appropriate for decision-makers.

Study of basic computer competence among public health nurses in Taiwan.

PubMed

Yang, Kuei-Feng; Yu, Shu; Lin, Ming-Sheng; Hsu, Chia-Ling

2004-03-01

Rapid advances in information technology and media have made distance learning on the Internet possible. This new model of learning allows greater efficiency and flexibility in knowledge acquisition. Since basic computer competence is a prerequisite for this new learning model, this study was conducted to examine the basic computer competence of public health nurses in Taiwan and explore factors influencing computer competence. A national cross-sectional randomized study was conducted with 329 public health nurses. A questionnaire was used to collect data and was delivered by mail. Results indicate that basic computer competence of public health nurses in Taiwan is still needs to be improved (mean = 57.57 +- 2.83, total score range from 26-130). Among the five most frequently used software programs, nurses were most knowledgeable about Word and least knowledgeable about PowerPoint. Stepwise multiple regression analysis revealed eight variables (weekly number of hours spent online at home, weekly amount of time spent online at work, weekly frequency of computer use at work, previous computer training, computer at workplace and Internet access, job position, education level, and age) that significantly influenced computer competence, which accounted for 39.0 % of the variance. In conclusion, greater computer competence, broader educational programs regarding computer technology, and a greater emphasis on computers at work are necessary to increase the usefulness of distance learning via the Internet in Taiwan. Building a user-friendly environment is important in developing this new media model of learning for the future.

High Performance Computing Meets Energy Efficiency - Continuum Magazine |

Science.gov Websites

NREL High Performance Computing Meets Energy Efficiency High Performance Computing Meets Energy turbines. Simulation by Patrick J. Moriarty and Matthew J. Churchfield, NREL The new High Performance Computing Data Center at the National Renewable Energy Laboratory (NREL) hosts high-speed, high-volume data

An alternative low-loss stack topology for vanadium redox flow battery: Comparative assessment

NASA Astrophysics Data System (ADS)

Moro, Federico; Trovò, Andrea; Bortolin, Stefano; Del, Davide, , Col; Guarnieri, Massimo

2017-02-01

Two vanadium redox flow battery topologies have been compared. In the conventional series stack, bipolar plates connect cells electrically in series and hydraulically in parallel. The alternative topology consists of cells connected in parallel inside stacks by means of monopolar plates in order to reduce shunt currents along channels and manifolds. Channelled and flat current collectors interposed between cells were considered in both topologies. In order to compute the stack losses, an equivalent circuit model of a VRFB cell was built from a 2D FEM multiphysics numerical model based on Comsol®, accounting for coupled electrical, electrochemical, and charge and mass transport phenomena. Shunt currents were computed inside the cells with 3D FEM models and in the piping and manifolds by means of equivalent circuits solved with Matlab®. Hydraulic losses were computed with analytical models in piping and manifolds and with 3D numerical analyses based on ANSYS Fluent® in the cell porous electrodes. Total losses in the alternative topology resulted one order of magnitude lower than in an equivalent conventional battery. The alternative topology with channelled current collectors exhibits the lowest shunt currents and hydraulic losses, with round-trip efficiency higher by about 10%, as compared to the conventional topology.

A diffusive information preservation method for small Knudsen number flows

NASA Astrophysics Data System (ADS)

Fei, Fei; Fan, Jing

2013-06-01

The direct simulation Monte Carlo (DSMC) method is a powerful particle-based method for modeling gas flows. It works well for relatively large Knudsen (Kn) numbers, typically larger than 0.01, but quickly becomes computationally intensive as Kn decreases due to its time step and cell size limitations. An alternative approach was proposed to relax or remove these limitations, based on replacing pairwise collisions with a stochastic model corresponding to the Fokker-Planck equation [J. Comput. Phys., 229, 1077 (2010); J. Fluid Mech., 680, 574 (2011)]. Similar to the DSMC method, the downside of that approach suffers from computationally statistical noise. To solve the problem, a diffusion-based information preservation (D-IP) method has been developed. The main idea is to track the motion of a simulated molecule from the diffusive standpoint, and obtain the flow velocity and temperature through sampling and averaging the IP quantities. To validate the idea and the corresponding model, several benchmark problems with Kn ˜ 10-3-10-4 have been investigated. It is shown that the IP calculations are not only accurate, but also efficient because they make possible using a time step and cell size over an order of magnitude larger than the mean collision time and mean free path, respectively.

Enhanced algorithms for stochastic programming

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

Krishna, Alamuru S.

1993-09-01

In this dissertation, we present some of the recent advances made in solving two-stage stochastic linear programming problems of large size and complexity. Decomposition and sampling are two fundamental components of techniques to solve stochastic optimization problems. We describe improvements to the current techniques in both these areas. We studied different ways of using importance sampling techniques in the context of Stochastic programming, by varying the choice of approximation functions used in this method. We have concluded that approximating the recourse function by a computationally inexpensive piecewise-linear function is highly efficient. This reduced the problem from finding the mean ofmore » a computationally expensive functions to finding that of a computationally inexpensive function. Then we implemented various variance reduction techniques to estimate the mean of a piecewise-linear function. This method achieved similar variance reductions in orders of magnitude less time than, when we directly applied variance-reduction techniques directly on the given problem. In solving a stochastic linear program, the expected value problem is usually solved before a stochastic solution and also to speed-up the algorithm by making use of the information obtained from the solution of the expected value problem. We have devised a new decomposition scheme to improve the convergence of this algorithm.« less

Propulsive efficiency of frog swimming with different feet and swimming patterns

PubMed Central

Jizhuang, Fan; Wei, Zhang; Bowen, Yuan; Gangfeng, Liu

2017-01-01

ABSTRACT Aquatic and terrestrial animals have different swimming performances and mechanical efficiencies based on their different swimming methods. To explore propulsion in swimming frogs, this study calculated mechanical efficiencies based on data describing aquatic and terrestrial webbed-foot shapes and swimming patterns. First, a simplified frog model and dynamic equation were established, and hydrodynamic forces on the foot were computed according to computational fluid dynamic calculations. Then, a two-link mechanism was used to stand in for the diverse and complicated hind legs found in different frog species, in order to simplify the input work calculation. Joint torques were derived based on the virtual work principle to compute the efficiency of foot propulsion. Finally, two feet and swimming patterns were combined to compute propulsive efficiency. The aquatic frog demonstrated a propulsive efficiency (43.11%) between those of drag-based and lift-based propulsions, while the terrestrial frog efficiency (29.58%) fell within the range of drag-based propulsion. The results illustrate the main factor of swimming patterns for swimming performance and efficiency. PMID:28302669

Deterministic absorbed dose estimation in computed tomography using a discrete ordinates method

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

Norris, Edward T.; Liu, Xin, E-mail: xinliu@mst.edu; Hsieh, Jiang

Purpose: Organ dose estimation for a patient undergoing computed tomography (CT) scanning is very important. Although Monte Carlo methods are considered gold-standard in patient dose estimation, the computation time required is formidable for routine clinical calculations. Here, the authors instigate a deterministic method for estimating an absorbed dose more efficiently. Methods: Compared with current Monte Carlo methods, a more efficient approach to estimating the absorbed dose is to solve the linear Boltzmann equation numerically. In this study, an axial CT scan was modeled with a software package, Denovo, which solved the linear Boltzmann equation using the discrete ordinates method. Themore » CT scanning configuration included 16 x-ray source positions, beam collimators, flat filters, and bowtie filters. The phantom was the standard 32 cm CT dose index (CTDI) phantom. Four different Denovo simulations were performed with different simulation parameters, including the number of quadrature sets and the order of Legendre polynomial expansions. A Monte Carlo simulation was also performed for benchmarking the Denovo simulations. A quantitative comparison was made of the simulation results obtained by the Denovo and the Monte Carlo methods. Results: The difference in the simulation results of the discrete ordinates method and those of the Monte Carlo methods was found to be small, with a root-mean-square difference of around 2.4%. It was found that the discrete ordinates method, with a higher order of Legendre polynomial expansions, underestimated the absorbed dose near the center of the phantom (i.e., low dose region). Simulations of the quadrature set 8 and the first order of the Legendre polynomial expansions proved to be the most efficient computation method in the authors’ study. The single-thread computation time of the deterministic simulation of the quadrature set 8 and the first order of the Legendre polynomial expansions was 21 min on a personal computer. Conclusions: The simulation results showed that the deterministic method can be effectively used to estimate the absorbed dose in a CTDI phantom. The accuracy of the discrete ordinates method was close to that of a Monte Carlo simulation, and the primary benefit of the discrete ordinates method lies in its rapid computation speed. It is expected that further optimization of this method in routine clinical CT dose estimation will improve its accuracy and speed.« less

A Fast Implementation of the ISOCLUS Algorithm

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; Mount, David M.; Netanyahu, Nathan S.; LeMoigne, Jacqueline

2003-01-01

Unsupervised clustering is a fundamental tool in numerous image processing and remote sensing applications. For example, unsupervised clustering is often used to obtain vegetation maps of an area of interest. This approach is useful when reliable training data are either scarce or expensive, and when relatively little a priori information about the data is available. Unsupervised clustering methods play a significant role in the pursuit of unsupervised classification. One of the most popular and widely used clustering schemes for remote sensing applications is the ISOCLUS algorithm, which is based on the ISODATA method. The algorithm is given a set of n data points (or samples) in d-dimensional space, an integer k indicating the initial number of clusters, and a number of additional parameters. The general goal is to compute a set of cluster centers in d-space. Although there is no specific optimization criterion, the algorithm is similar in spirit to the well known k-means clustering method in which the objective is to minimize the average squared distance of each point to its nearest center, called the average distortion. One significant feature of ISOCLUS over k-means is that clusters may be merged or split, and so the final number of clusters may be different from the number k supplied as part of the input. This algorithm will be described in later in this paper. The ISOCLUS algorithm can run very slowly, particularly on large data sets. Given its wide use in remote sensing, its efficient computation is an important goal. We have developed a fast implementation of the ISOCLUS algorithm. Our improvement is based on a recent acceleration to the k-means algorithm, the filtering algorithm, by Kanungo et al.. They showed that, by storing the data in a kd-tree, it was possible to significantly reduce the running time of k-means. We have adapted this method for the ISOCLUS algorithm. For technical reasons, which are explained later, it is necessary to make a minor modification to the ISOCLUS specification. We provide empirical evidence, on both synthetic and Landsat image data sets, that our algorithm's performance is essentially the same as that of ISOCLUS, but with significantly lower running times. We show that our algorithm runs from 3 to 30 times faster than a straightforward implementation of ISOCLUS. Our adaptation of the filtering algorithm involves the efficient computation of a number of cluster statistics that are needed for ISOCLUS, but not for k-means.

OFF, Open source Finite volume Fluid dynamics code: A free, high-order solver based on parallel, modular, object-oriented Fortran API

NASA Astrophysics Data System (ADS)

Zaghi, S.

2014-07-01

OFF, an open source (free software) code for performing fluid dynamics simulations, is presented. The aim of OFF is to solve, numerically, the unsteady (and steady) compressible Navier-Stokes equations of fluid dynamics by means of finite volume techniques: the research background is mainly focused on high-order (WENO) schemes for multi-fluids, multi-phase flows over complex geometries. To this purpose a highly modular, object-oriented application program interface (API) has been developed. In particular, the concepts of data encapsulation and inheritance available within Fortran language (from standard 2003) have been stressed in order to represent each fluid dynamics "entity" (e.g. the conservative variables of a finite volume, its geometry, etc…) by a single object so that a large variety of computational libraries can be easily (and efficiently) developed upon these objects. The main features of OFF can be summarized as follows: Programming LanguageOFF is written in standard (compliant) Fortran 2003; its design is highly modular in order to enhance simplicity of use and maintenance without compromising the efficiency; Parallel Frameworks Supported the development of OFF has been also targeted to maximize the computational efficiency: the code is designed to run on shared-memory multi-cores workstations and distributed-memory clusters of shared-memory nodes (supercomputers); the code's parallelization is based on Open Multiprocessing (OpenMP) and Message Passing Interface (MPI) paradigms; Usability, Maintenance and Enhancement in order to improve the usability, maintenance and enhancement of the code also the documentation has been carefully taken into account; the documentation is built upon comprehensive comments placed directly into the source files (no external documentation files needed): these comments are parsed by means of doxygen free software producing high quality html and latex documentation pages; the distributed versioning system referred as git has been adopted in order to facilitate the collaborative maintenance and improvement of the code; CopyrightsOFF is a free software that anyone can use, copy, distribute, study, change and improve under the GNU Public License version 3. The present paper is a manifesto of OFF code and presents the currently implemented features and ongoing developments. This work is focused on the computational techniques adopted and a detailed description of the main API characteristics is reported. OFF capabilities are demonstrated by means of one and two dimensional examples and a three dimensional real application.

Algorithms and analytical solutions for rapidly approximating long-term dispersion from line and area sources

NASA Astrophysics Data System (ADS)

Barrett, Steven R. H.; Britter, Rex E.

Predicting long-term mean pollutant concentrations in the vicinity of airports, roads and other industrial sources are frequently of concern in regulatory and public health contexts. Many emissions are represented geometrically as ground-level line or area sources. Well developed modelling tools such as AERMOD and ADMS are able to model dispersion from finite (i.e. non-point) sources with considerable accuracy, drawing upon an up-to-date understanding of boundary layer behaviour. Due to mathematical difficulties associated with line and area sources, computationally expensive numerical integration schemes have been developed. For example, some models decompose area sources into a large number of line sources orthogonal to the mean wind direction, for which an analytical (Gaussian) solution exists. Models also employ a time-series approach, which involves computing mean pollutant concentrations for every hour over one or more years of meteorological data. This can give rise to computer runtimes of several days for assessment of a site. While this may be acceptable for assessment of a single industrial complex, airport, etc., this level of computational cost precludes national or international policy assessments at the level of detail available with dispersion modelling. In this paper, we extend previous work [S.R.H. Barrett, R.E. Britter, 2008. Development of algorithms and approximations for rapid operational air quality modelling. Atmospheric Environment 42 (2008) 8105-8111] to line and area sources. We introduce approximations which allow for the development of new analytical solutions for long-term mean dispersion from line and area sources, based on hypergeometric functions. We describe how these solutions can be parameterized from a single point source run from an existing advanced dispersion model, thereby accounting for all processes modelled in the more costly algorithms. The parameterization method combined with the analytical solutions for long-term mean dispersion are shown to produce results several orders of magnitude more efficiently with a loss of accuracy small compared to the absolute accuracy of advanced dispersion models near sources. The method can be readily incorporated into existing dispersion models, and may allow for additional computation time to be expended on modelling dispersion processes more accurately in future, rather than on accounting for source geometry.

Heisenberg limit for displacements with semiclassical states

NASA Astrophysics Data System (ADS)

Luis, Alfredo

2004-04-01

We analyze the quantum limit to the sensitivity of the detection of small displacements. We focus on the case of free particles and harmonic oscillators as the systems experiencing the displacement. We show that the minimum displacement detectable is proportional to the inverse of the square root of the mean value of the energy in the state experiencing the displacement (Heisenberg limit). We present a measuring scheme that reaches this limit using semiclassical states. We examine the performance of this strategy under realistic practical conditions by computing the effect of imperfections such as losses and nonunit detection efficiencies. This analysis confirms the robustness of this measuring strategy by showing that the experimental imperfections can be suitably compensated by increasing the mean energy of the input state.

System statistical reliability model and analysis

NASA Technical Reports Server (NTRS)

Lekach, V. S.; Rood, H.

1973-01-01

A digital computer code was developed to simulate the time-dependent behavior of the 5-kwe reactor thermoelectric system. The code was used to determine lifetime sensitivity coefficients for a number of system design parameters, such as thermoelectric module efficiency and degradation rate, radiator absorptivity and emissivity, fuel element barrier defect constant, beginning-of-life reactivity, etc. A probability distribution (mean and standard deviation) was estimated for each of these design parameters. Then, error analysis was used to obtain a probability distribution for the system lifetime (mean = 7.7 years, standard deviation = 1.1 years). From this, the probability that the system will achieve the design goal of 5 years lifetime is 0.993. This value represents an estimate of the degradation reliability of the system.

An advanced probabilistic structural analysis method for implicit performance functions

NASA Technical Reports Server (NTRS)

Wu, Y.-T.; Millwater, H. R.; Cruse, T. A.

1989-01-01

In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.

Potentials of mean force for biomolecular simulations: Theory and test on alanine dipeptide

NASA Astrophysics Data System (ADS)

Pellegrini, Matteo; Grønbech-Jensen, Niels; Doniach, Sebastian

1996-06-01

We describe a technique for generating potentials of mean force (PMF) between solutes in an aqueous solution. We first generate solute-solvent correlation functions (CF) using Monte Carlo (MC) simulations in which we place a single atom solute in a periodic boundary box containing a few hundred water molecules. We then make use of the Kirkwood superposition approximation, where the 3-body correlation function is approximated as the product of 2-body CFs, to describe the mean water density around two solutes. Computing the force generated on the solutes by this average water density allows us to compute potentials of mean force between the two solutes. For charged solutes an additional approximation involving dielectric screening is made, by setting the dielectric constant of water to ɛ=80. These potentials account, in an approximate manner, for the average effect of water on the atoms. Following the work of Pettitt and Karplus [Chem. Phys. Lett. 121, 194 (1985)], we approximate the n-body potential of mean force as a sum of the pairwise potentials of mean force. This allows us to run simulations of biomolecules without introducing explicit water, hence gaining several orders of magnitude in efficiency with respect to standard molecular dynamics techniques. We demonstrate the validity of this technique by first comparing the PMFs for methane-methane and sodium-chloride generated with this procedure, with those calculated with a standard Monte Carlo simulation with explicit water. We then compare the results of the free energy profiles between the equilibria of alanine dipeptide generated by the two methods.

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

NASA Astrophysics Data System (ADS)

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

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

Modified Chebyshev Picard Iteration for Efficient Numerical Integration of Ordinary Differential Equations

NASA Astrophysics Data System (ADS)

Macomber, B.; Woollands, R. M.; Probe, A.; Younes, A.; Bai, X.; Junkins, J.

2013-09-01

Modified Chebyshev Picard Iteration (MCPI) is an iterative numerical method for approximating solutions of linear or non-linear Ordinary Differential Equations (ODEs) to obtain time histories of system state trajectories. Unlike other step-by-step differential equation solvers, the Runge-Kutta family of numerical integrators for example, MCPI approximates long arcs of the state trajectory with an iterative path approximation approach, and is ideally suited to parallel computation. Orthogonal Chebyshev Polynomials are used as basis functions during each path iteration; the integrations of the Picard iteration are then done analytically. Due to the orthogonality of the Chebyshev basis functions, the least square approximations are computed without matrix inversion; the coefficients are computed robustly from discrete inner products. As a consequence of discrete sampling and weighting adopted for the inner product definition, Runge phenomena errors are minimized near the ends of the approximation intervals. The MCPI algorithm utilizes a vector-matrix framework for computational efficiency. Additionally, all Chebyshev coefficients and integrand function evaluations are independent, meaning they can be simultaneously computed in parallel for further decreased computational cost. Over an order of magnitude speedup from traditional methods is achieved in serial processing, and an additional order of magnitude is achievable in parallel architectures. This paper presents a new MCPI library, a modular toolset designed to allow MCPI to be easily applied to a wide variety of ODE systems. Library users will not have to concern themselves with the underlying mathematics behind the MCPI method. Inputs are the boundary conditions of the dynamical system, the integrand function governing system behavior, and the desired time interval of integration, and the output is a time history of the system states over the interval of interest. Examples from the field of astrodynamics are presented to compare the output from the MCPI library to current state-of-practice numerical integration methods. It is shown that MCPI is capable of out-performing the state-of-practice in terms of computational cost and accuracy.

Dynamic Discharge Arc Driver. [computerized simulation

NASA Technical Reports Server (NTRS)

Dannenberg, R. E.; Slapnicar, P. I.

1975-01-01

A computer program using nonlinear RLC circuit analysis was developed to accurately model the electrical discharge performance of the Ames 1-MJ energy storage and arc-driver system. Solutions of circuit parameters are compared with experimental circuit data and related to shock speed measurements. Computer analysis led to the concept of a Dynamic Discharge Arc Driver (DDAD) capable of increasing the range of operation of shock-driven facilities. Utilization of mass addition of the driver gas offers a unique means of improving driver performance. Mass addition acts to increase the arc resistance, which results in better electrical circuit damping with more efficient Joule heating, producing stronger shock waves. Preliminary tests resulted in an increase in shock Mach number from 34 to 39 in air at an initial pressure of 2.5 torr.

Object extraction in photogrammetric computer vision

NASA Astrophysics Data System (ADS)

Mayer, Helmut

This paper discusses state and promising directions of automated object extraction in photogrammetric computer vision considering also practical aspects arising for digital photogrammetric workstations (DPW). A review of the state of the art shows that there are only few practically successful systems on the market. Therefore, important issues for a practical success of automated object extraction are identified. A sound and most important powerful theoretical background is the basis. Here, we particularly point to statistical modeling. Testing makes clear which of the approaches are suited best and how useful they are for praxis. A key for commercial success of a practical system is efficient user interaction. As the means for data acquisition are changing, new promising application areas such as extremely detailed three-dimensional (3D) urban models for virtual television or mission rehearsal evolve.

DVS-SOFTWARE: An Effective Tool for Applying Highly Parallelized Hardware To Computational Geophysics

NASA Astrophysics Data System (ADS)

Herrera, I.; Herrera, G. S.

2015-12-01

Most geophysical systems are macroscopic physical systems. The behavior prediction of such systems is carried out by means of computational models whose basic models are partial differential equations (PDEs) [1]. Due to the enormous size of the discretized version of such PDEs it is necessary to apply highly parallelized super-computers. For them, at present, the most efficient software is based on non-overlapping domain decomposition methods (DDM). However, a limiting feature of the present state-of-the-art techniques is due to the kind of discretizations used in them. Recently, I. Herrera and co-workers using 'non-overlapping discretizations' have produced the DVS-Software which overcomes this limitation [2]. The DVS-software can be applied to a great variety of geophysical problems and achieves very high parallel efficiencies (90%, or so [3]). It is therefore very suitable for effectively applying the most advanced parallel supercomputers available at present. In a parallel talk, in this AGU Fall Meeting, Graciela Herrera Z. will present how this software is being applied to advance MOD-FLOW. Key Words: Parallel Software for Geophysics, High Performance Computing, HPC, Parallel Computing, Domain Decomposition Methods (DDM)REFERENCES [1]. Herrera Ismael and George F. Pinder, Mathematical Modelling in Science and Engineering: An axiomatic approach", John Wiley, 243p., 2012. [2]. Herrera, I., de la Cruz L.M. and Rosas-Medina A. "Non Overlapping Discretization Methods for Partial, Differential Equations". NUMER METH PART D E, 30: 1427-1454, 2014, DOI 10.1002/num 21852. (Open source) [3]. Herrera, I., & Contreras Iván "An Innovative Tool for Effectively Applying Highly Parallelized Software To Problems of Elasticity". Geofísica Internacional, 2015 (In press)

A modified adaptive algorithm of dealing with the high chirp when chirped pulses propagating in optical fiber

NASA Astrophysics Data System (ADS)

Wu, Lianglong; Fu, Xiquan; Guo, Xing

2013-03-01

In this paper, we propose a modified adaptive algorithm (MAA) of dealing with the high chirp to efficiently simulate the propagation of chirped pulses along an optical fiber for the propagation distance shorter than the "temporal focal length". The basis of the MAA is that the chirp term of initial pulse is treated as the rapidly varying part by means of the idea of the slowly varying envelope approximation (SVEA). Numerical simulations show that the performance of the MAA is validated, and that the proposed method can decrease the number of sampling points by orders of magnitude. In addition, the computational efficiency of the MAA compared with the time-domain beam propagation method (BPM) can be enhanced with the increase of the chirp of initial pulse.

FPGA Implementation of Optimal 3D-Integer DCT Structure for Video Compression

PubMed Central

2015-01-01

A novel optimal structure for implementing 3D-integer discrete cosine transform (DCT) is presented by analyzing various integer approximation methods. The integer set with reduced mean squared error (MSE) and high coding efficiency are considered for implementation in FPGA. The proposed method proves that the least resources are utilized for the integer set that has shorter bit values. Optimal 3D-integer DCT structure is determined by analyzing the MSE, power dissipation, coding efficiency, and hardware complexity of different integer sets. The experimental results reveal that direct method of computing the 3D-integer DCT using the integer set [10, 9, 6, 2, 3, 1, 1] performs better when compared to other integer sets in terms of resource utilization and power dissipation. PMID:26601120

Accounting for quality in the measurement of hospital performance: evidence from Costa Rica.

PubMed

Arocena, Pablo; García-Prado, Ariadna

2007-07-01

This paper provides insights into how Costa Rican public hospitals responded to the pressure for increased efficiency and quality introduced by the reforms carried out over the period 1997-2001. To that purpose we compute a generalized output distance function by means of non-parametric mathematical programming to construct a productivity index, which accounts for productivity changes while controlling for quality of care. Our results show an improvement in hospital performance mainly driven by quality increases. The adoption of management contracts seems to have contributed to such enhancement, more notably for small hospitals. Further, productivity growth is primarily due to technical and scale efficiency change rather than technological change. A number of policy implications are drawn from these results. Copyright (c) 2006 John Wiley & Sons, Ltd.

How Automation Can Help Alleviate the Budget Crunch in Public Health Research

PubMed Central

2015-01-01

In an era of severe funding constraints for public health research, more efficient means of conducting research will be needed if scientific progress is to continue. At present major funders, such as the National Institutes of Health, do not provide specific instructions to grant authors or to reviewers regarding the cost efficiency of the research that they conduct. Doing so could potentially allow more research to be funded within current budgetary constraints and reduce waste. I describe how a blinded randomized trial was conducted for $275 000 by completely automating the consent and data collection processes. The study used the participants’ own computer equipment, relied on big data for outcomes, and outsourced some costly tasks, potentially saving $1 million in research costs. PMID:26180952

Theoretical and material studies of thin-film electroluminescent devices

NASA Technical Reports Server (NTRS)

Summers, C. J.

1989-01-01

Thin-film electroluminescent (TFEL) devices are studied for a possible means of achieving a high resolution, light weight, compact video display panel for computer terminals or television screens. The performance of TFEL devices depends upon the probability of an electron impact exciting a luminescent center which in turn depends upon the density of centers present in the semiconductor layer, the possibility of an electron achieving the impact excitation threshold energy, and the collision cross section itself. Efficiency of such a device is presently very poor. It can best be improved by increasing the number of hot electrons capable of impact exciting a center. Hot electron distributions and a method for increasing the efficiency and brightness of TFEL devices (with the additional advantage of low voltage direct current operation) are investigated.

A new controller for battery-powered electric vehicles

NASA Technical Reports Server (NTRS)

Belsterling, C. A.; Stone, J.

1980-01-01

This paper describes the development, under a NASA/DOE contract, of a new concept for efficient and reliable control of battery-powered vehicles. It avoids the detrimental effects of pulsed-power controllers like the SCR 'chopper' by using rotating machines to meter continuous currents to the traction motor. The concept is validated in a proof-of-principle demonstration system and a complete vehicle is simulated on an analog computer. Test results show exceptional promise for a full-scale system. Optimum control strategies to minimize controller weight are developed by means of the simulated vehicle. The design for an Engineering Model is then prepared in the form of a practical, compact two-bearing package with forced air cooling. Predicted performance is outstanding, with controller efficiency of over 90% at high speed.

Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons.

PubMed

Probst, Dimitri; Petrovici, Mihai A; Bytschok, Ilja; Bill, Johannes; Pecevski, Dejan; Schemmel, Johannes; Meier, Karlheinz

2015-01-01

The means by which cortical neural networks are able to efficiently solve inference problems remains an open question in computational neuroscience. Recently, abstract models of Bayesian computation in neural circuits have been proposed, but they lack a mechanistic interpretation at the single-cell level. In this article, we describe a complete theoretical framework for building networks of leaky integrate-and-fire neurons that can sample from arbitrary probability distributions over binary random variables. We test our framework for a model inference task based on a psychophysical phenomenon (the Knill-Kersten optical illusion) and further assess its performance when applied to randomly generated distributions. As the local computations performed by the network strongly depend on the interaction between neurons, we compare several types of couplings mediated by either single synapses or interneuron chains. Due to its robustness to substrate imperfections such as parameter noise and background noise correlations, our model is particularly interesting for implementation on novel, neuro-inspired computing architectures, which can thereby serve as a fast, low-power substrate for solving real-world inference problems.

New Parallel computing framework for radiation transport codes

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

Kostin, M.A.; /Michigan State U., NSCL; Mokhov, N.V.

A new parallel computing framework has been developed to use with general-purpose radiation transport codes. The framework was implemented as a C++ module that uses MPI for message passing. The module is significantly independent of radiation transport codes it can be used with, and is connected to the codes by means of a number of interface functions. The framework was integrated with the MARS15 code, and an effort is under way to deploy it in PHITS. Besides the parallel computing functionality, the framework offers a checkpoint facility that allows restarting calculations with a saved checkpoint file. The checkpoint facility canmore » be used in single process calculations as well as in the parallel regime. Several checkpoint files can be merged into one thus combining results of several calculations. The framework also corrects some of the known problems with the scheduling and load balancing found in the original implementations of the parallel computing functionality in MARS15 and PHITS. The framework can be used efficiently on homogeneous systems and networks of workstations, where the interference from the other users is possible.« less

Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons

PubMed Central

Probst, Dimitri; Petrovici, Mihai A.; Bytschok, Ilja; Bill, Johannes; Pecevski, Dejan; Schemmel, Johannes; Meier, Karlheinz

2015-01-01

The means by which cortical neural networks are able to efficiently solve inference problems remains an open question in computational neuroscience. Recently, abstract models of Bayesian computation in neural circuits have been proposed, but they lack a mechanistic interpretation at the single-cell level. In this article, we describe a complete theoretical framework for building networks of leaky integrate-and-fire neurons that can sample from arbitrary probability distributions over binary random variables. We test our framework for a model inference task based on a psychophysical phenomenon (the Knill-Kersten optical illusion) and further assess its performance when applied to randomly generated distributions. As the local computations performed by the network strongly depend on the interaction between neurons, we compare several types of couplings mediated by either single synapses or interneuron chains. Due to its robustness to substrate imperfections such as parameter noise and background noise correlations, our model is particularly interesting for implementation on novel, neuro-inspired computing architectures, which can thereby serve as a fast, low-power substrate for solving real-world inference problems. PMID:25729361

High-Performance Computational Analysis of Glioblastoma Pathology Images with Database Support Identifies Molecular and Survival Correlates.

PubMed

Kong, Jun; Wang, Fusheng; Teodoro, George; Cooper, Lee; Moreno, Carlos S; Kurc, Tahsin; Pan, Tony; Saltz, Joel; Brat, Daniel

2013-12-01

In this paper, we present a novel framework for microscopic image analysis of nuclei, data management, and high performance computation to support translational research involving nuclear morphometry features, molecular data, and clinical outcomes. Our image analysis pipeline consists of nuclei segmentation and feature computation facilitated by high performance computing with coordinated execution in multi-core CPUs and Graphical Processor Units (GPUs). All data derived from image analysis are managed in a spatial relational database supporting highly efficient scientific queries. We applied our image analysis workflow to 159 glioblastomas (GBM) from The Cancer Genome Atlas dataset. With integrative studies, we found statistics of four specific nuclear features were significantly associated with patient survival. Additionally, we correlated nuclear features with molecular data and found interesting results that support pathologic domain knowledge. We found that Proneural subtype GBMs had the smallest mean of nuclear Eccentricity and the largest mean of nuclear Extent, and MinorAxisLength. We also found gene expressions of stem cell marker MYC and cell proliferation maker MKI67 were correlated with nuclear features. To complement and inform pathologists of relevant diagnostic features, we queried the most representative nuclear instances from each patient population based on genetic and transcriptional classes. Our results demonstrate that specific nuclear features carry prognostic significance and associations with transcriptional and genetic classes, highlighting the potential of high throughput pathology image analysis as a complementary approach to human-based review and translational research.

Prediction of Undsteady Flows in Turbomachinery Using the Linearized Euler Equations on Deforming Grids

NASA Technical Reports Server (NTRS)

Clark, William S.; Hall, Kenneth C.

1994-01-01

A linearized Euler solver for calculating unsteady flows in turbomachinery blade rows due to both incident gusts and blade motion is presented. The model accounts for blade loading, blade geometry, shock motion, and wake motion. Assuming that the unsteadiness in the flow is small relative to the nonlinear mean solution, the unsteady Euler equations can be linearized about the mean flow. This yields a set of linear variable coefficient equations that describe the small amplitude harmonic motion of the fluid. These linear equations are then discretized on a computational grid and solved using standard numerical techniques. For transonic flows, however, one must use a linear discretization which is a conservative linearization of the non-linear discretized Euler equations to ensure that shock impulse loads are accurately captured. Other important features of this analysis include a continuously deforming grid which eliminates extrapolation errors and hence, increases accuracy, and a new numerically exact, nonreflecting far-field boundary condition treatment based on an eigenanalysis of the discretized equations. Computational results are presented which demonstrate the computational accuracy and efficiency of the method and demonstrate the effectiveness of the deforming grid, far-field nonreflecting boundary conditions, and shock capturing techniques. A comparison of the present unsteady flow predictions to other numerical, semi-analytical, and experimental methods shows excellent agreement. In addition, the linearized Euler method presented requires one or two orders-of-magnitude less computational time than traditional time marching techniques making the present method a viable design tool for aeroelastic analyses.

Probabilistic finite elements

NASA Technical Reports Server (NTRS)

Belytschko, Ted; Wing, Kam Liu

1987-01-01

In the Probabilistic Finite Element Method (PFEM), finite element methods have been efficiently combined with second-order perturbation techniques to provide an effective method for informing the designer of the range of response which is likely in a given problem. The designer must provide as input the statistical character of the input variables, such as yield strength, load magnitude, and Young's modulus, by specifying their mean values and their variances. The output then consists of the mean response and the variance in the response. Thus the designer is given a much broader picture of the predicted performance than with simply a single response curve. These methods are applicable to a wide class of problems, provided that the scale of randomness is not too large and the probabilistic density functions possess decaying tails. By incorporating the computational techniques we have developed in the past 3 years for efficiency, the probabilistic finite element methods are capable of handling large systems with many sources of uncertainties. Sample results for an elastic-plastic ten-bar structure and an elastic-plastic plane continuum with a circular hole subject to cyclic loadings with the yield stress on the random field are given.

Simultaneous deblending and interpolation using structure-oriented filters

NASA Astrophysics Data System (ADS)

Zhou, Yatong; Li, Song

2018-03-01

Simultaneous source shooting is a modern marine acquisition technology that accelerates field acquisition tremendously. However, we need to carefully remove the spike-like noise in the recorded seismic data, the process of which is called deblending. Considering the field obstacles, the recorded data may also contain missing traces. In this paper, we propose a very efficient way to simultaneously remove the spike-like noise to separate simultaneous sources and fill the data gaps in the recorded data. We propose to apply structure-oriented median and mean filters to reject the spike-like noise and restore the missing data. The commonly used median and mean filters guarantee the efficiency and convenience of the proposed algorithm framework. We use a robust slope estimation method to calculate the local slope of the structure patterns in the seismic data. Both synthetic and field data examples demonstrate the successful performance of the proposed algorithm. When compared with the state-of-the-art FK transform based projection onto convex sets (POCS) method, the presented method can obtain better performance with much less computational cost.

Detection of maize kernels breakage rate based on K-means clustering

NASA Astrophysics Data System (ADS)

Yang, Liang; Wang, Zhuo; Gao, Lei; Bai, Xiaoping

2017-04-01

In order to optimize the recognition accuracy of maize kernels breakage detection and improve the detection efficiency of maize kernels breakage, this paper using computer vision technology and detecting of the maize kernels breakage based on K-means clustering algorithm. First, the collected RGB images are converted into Lab images, then the original images clarity evaluation are evaluated by the energy function of Sobel 8 gradient. Finally, the detection of maize kernels breakage using different pixel acquisition equipments and different shooting angles. In this paper, the broken maize kernels are identified by the color difference between integrity kernels and broken kernels. The original images clarity evaluation and different shooting angles are taken to verify that the clarity and shooting angles of the images have a direct influence on the feature extraction. The results show that K-means clustering algorithm can distinguish the broken maize kernels effectively.

Modeling Sound Propagation Through Non-Axisymmetric Jets

NASA Technical Reports Server (NTRS)

Leib, Stewart J.

2014-01-01

A method for computing the far-field adjoint Green's function of the generalized acoustic analogy equations under a locally parallel mean flow approximation is presented. The method is based on expanding the mean-flow-dependent coefficients in the governing equation and the scalar Green's function in truncated Fourier series in the azimuthal direction and a finite difference approximation in the radial direction in circular cylindrical coordinates. The combined spectral/finite difference method yields a highly banded system of algebraic equations that can be efficiently solved using a standard sparse system solver. The method is applied to test cases, with mean flow specified by analytical functions, corresponding to two noise reduction concepts of current interest: the offset jet and the fluid shield. Sample results for the Green's function are given for these two test cases and recommendations made as to the use of the method as part of a RANS-based jet noise prediction code.

Application of Adaptive Neuro-Fuzzy Inference System for Prediction of Neutron Yield of IR-IECF Facility in High Voltages

NASA Astrophysics Data System (ADS)

Adineh-Vand, A.; Torabi, M.; Roshani, G. H.; Taghipour, M.; Feghhi, S. A. H.; Rezaei, M.; Sadati, S. M.

2013-09-01

This paper presents a soft computing based artificial intelligent technique, adaptive neuro-fuzzy inference system (ANFIS) to predict the neutron production rate (NPR) of IR-IECF device in wide discharge current and voltage ranges. A hybrid learning algorithm consists of back-propagation and least-squares estimation is used for training the ANFIS model. The performance of the proposed ANFIS model is tested using the experimental data using four performance measures: correlation coefficient, mean absolute error, mean relative error percentage (MRE%) and root mean square error. The obtained results show that the proposed ANFIS model has achieved good agreement with the experimental results. In comparison to the experimental data the proposed ANFIS model has MRE% <1.53 and 2.85 % for training and testing data respectively. Therefore, this model can be used as an efficient tool to predict the NPR in the IR-IECF device.

MC-GenomeKey: a multicloud system for the detection and annotation of genomic variants.

PubMed

Elshazly, Hatem; Souilmi, Yassine; Tonellato, Peter J; Wall, Dennis P; Abouelhoda, Mohamed

2017-01-20

Next Generation Genome sequencing techniques became affordable for massive sequencing efforts devoted to clinical characterization of human diseases. However, the cost of providing cloud-based data analysis of the mounting datasets remains a concerning bottleneck for providing cost-effective clinical services. To address this computational problem, it is important to optimize the variant analysis workflow and the used analysis tools to reduce the overall computational processing time, and concomitantly reduce the processing cost. Furthermore, it is important to capitalize on the use of the recent development in the cloud computing market, which have witnessed more providers competing in terms of products and prices. In this paper, we present a new package called MC-GenomeKey (Multi-Cloud GenomeKey) that efficiently executes the variant analysis workflow for detecting and annotating mutations using cloud resources from different commercial cloud providers. Our package supports Amazon, Google, and Azure clouds, as well as, any other cloud platform based on OpenStack. Our package allows different scenarios of execution with different levels of sophistication, up to the one where a workflow can be executed using a cluster whose nodes come from different clouds. MC-GenomeKey also supports scenarios to exploit the spot instance model of Amazon in combination with the use of other cloud platforms to provide significant cost reduction. To the best of our knowledge, this is the first solution that optimizes the execution of the workflow using computational resources from different cloud providers. MC-GenomeKey provides an efficient multicloud based solution to detect and annotate mutations. The package can run in different commercial cloud platforms, which enables the user to seize the best offers. The package also provides a reliable means to make use of the low-cost spot instance model of Amazon, as it provides an efficient solution to the sudden termination of spot machines as a result of a sudden price increase. The package has a web-interface and it is available for free for academic use.

A statistical state dynamics approach to wall turbulence.

PubMed

Farrell, B F; Gayme, D F; Ioannou, P J

2017-03-13

This paper reviews results obtained using statistical state dynamics (SSD) that demonstrate the benefits of adopting this perspective for understanding turbulence in wall-bounded shear flows. The SSD approach used in this work employs a second-order closure that retains only the interaction between the streamwise mean flow and the streamwise mean perturbation covariance. This closure restricts nonlinearity in the SSD to that explicitly retained in the streamwise constant mean flow together with nonlinear interactions between the mean flow and the perturbation covariance. This dynamical restriction, in which explicit perturbation-perturbation nonlinearity is removed from the perturbation equation, results in a simplified dynamics referred to as the restricted nonlinear (RNL) dynamics. RNL systems, in which a finite ensemble of realizations of the perturbation equation share the same mean flow, provide tractable approximations to the SSD, which is equivalent to an infinite ensemble RNL system. This infinite ensemble system, referred to as the stochastic structural stability theory system, introduces new analysis tools for studying turbulence. RNL systems provide computationally efficient means to approximate the SSD and produce self-sustaining turbulence exhibiting qualitative features similar to those observed in direct numerical simulations despite greatly simplified dynamics. The results presented show that RNL turbulence can be supported by as few as a single streamwise varying component interacting with the streamwise constant mean flow and that judicious selection of this truncated support or 'band-limiting' can be used to improve quantitative accuracy of RNL turbulence. These results suggest that the SSD approach provides new analytical and computational tools that allow new insights into wall turbulence.This article is part of the themed issue 'Toward the development of high-fidelity models of wall turbulence at large Reynolds number'. © 2017 The Author(s).

A statistical state dynamics approach to wall turbulence

PubMed Central

Gayme, D. F.; Ioannou, P. J.

2017-01-01

This paper reviews results obtained using statistical state dynamics (SSD) that demonstrate the benefits of adopting this perspective for understanding turbulence in wall-bounded shear flows. The SSD approach used in this work employs a second-order closure that retains only the interaction between the streamwise mean flow and the streamwise mean perturbation covariance. This closure restricts nonlinearity in the SSD to that explicitly retained in the streamwise constant mean flow together with nonlinear interactions between the mean flow and the perturbation covariance. This dynamical restriction, in which explicit perturbation–perturbation nonlinearity is removed from the perturbation equation, results in a simplified dynamics referred to as the restricted nonlinear (RNL) dynamics. RNL systems, in which a finite ensemble of realizations of the perturbation equation share the same mean flow, provide tractable approximations to the SSD, which is equivalent to an infinite ensemble RNL system. This infinite ensemble system, referred to as the stochastic structural stability theory system, introduces new analysis tools for studying turbulence. RNL systems provide computationally efficient means to approximate the SSD and produce self-sustaining turbulence exhibiting qualitative features similar to those observed in direct numerical simulations despite greatly simplified dynamics. The results presented show that RNL turbulence can be supported by as few as a single streamwise varying component interacting with the streamwise constant mean flow and that judicious selection of this truncated support or ‘band-limiting’ can be used to improve quantitative accuracy of RNL turbulence. These results suggest that the SSD approach provides new analytical and computational tools that allow new insights into wall turbulence. This article is part of the themed issue ‘Toward the development of high-fidelity models of wall turbulence at large Reynolds number’. PMID:28167577

Software for Acoustic Rendering

NASA Technical Reports Server (NTRS)

Miller, Joel D.

2003-01-01

SLAB is a software system that can be run on a personal computer to simulate an acoustic environment in real time. SLAB was developed to enable computational experimentation in which one can exert low-level control over a variety of signal-processing parameters, related to spatialization, for conducting psychoacoustic studies. Among the parameters that can be manipulated are the number and position of reflections, the fidelity (that is, the number of taps in finite-impulse-response filters), the system latency, and the update rate of the filters. Another goal in the development of SLAB was to provide an inexpensive means of dynamic synthesis of virtual audio over headphones, without need for special-purpose signal-processing hardware. SLAB has a modular, object-oriented design that affords the flexibility and extensibility needed to accommodate a variety of computational experiments and signal-flow structures. SLAB s spatial renderer has a fixed signal-flow architecture corresponding to a set of parallel signal paths from each source to a listener. This fixed architecture can be regarded as a compromise that optimizes efficiency at the expense of complete flexibility. Such a compromise is necessary, given the design goal of enabling computational psychoacoustic experimentation on inexpensive personal computers.

Progress in Computational Simulation of Earthquakes

NASA Technical Reports Server (NTRS)

Donnellan, Andrea; Parker, Jay; Lyzenga, Gregory; Judd, Michele; Li, P. Peggy; Norton, Charles; Tisdale, Edwin; Granat, Robert

2006-01-01

GeoFEST(P) is a computer program written for use in the QuakeSim project, which is devoted to development and improvement of means of computational simulation of earthquakes. GeoFEST(P) models interacting earthquake fault systems from the fault-nucleation to the tectonic scale. The development of GeoFEST( P) has involved coupling of two programs: GeoFEST and the Pyramid Adaptive Mesh Refinement Library. GeoFEST is a message-passing-interface-parallel code that utilizes a finite-element technique to simulate evolution of stress, fault slip, and plastic/elastic deformation in realistic materials like those of faulted regions of the crust of the Earth. The products of such simulations are synthetic observable time-dependent surface deformations on time scales from days to decades. Pyramid Adaptive Mesh Refinement Library is a software library that facilitates the generation of computational meshes for solving physical problems. In an application of GeoFEST(P), a computational grid can be dynamically adapted as stress grows on a fault. Simulations on workstations using a few tens of thousands of stress and displacement finite elements can now be expanded to multiple millions of elements with greater than 98-percent scaled efficiency on over many hundreds of parallel processors (see figure).

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/.

Real-Time Nonlocal Means-Based Despeckling.

PubMed

Breivik, Lars Hofsoy; Snare, Sten Roar; Steen, Erik Normann; Solberg, Anne H Schistad

2017-06-01

In this paper, we propose a multiscale nonlocal means-based despeckling method for medical ultrasound. The multiscale approach leads to large computational savings and improves despeckling results over single-scale iterative approaches. We present two variants of the method. The first, denoted multiscale nonlocal means (MNLM), yields uniform robust filtering of speckle both in structured and homogeneous regions. The second, denoted unnormalized MNLM (UMNLM), is more conservative in regions of structure assuring minimal disruption of salient image details. Due to the popularity of anisotropic diffusion-based methods in the despeckling literature, we review the connection between anisotropic diffusion and iterative variants of NLM. These iterative variants in turn relate to our multiscale variant. As part of our evaluation, we conduct a simulation study making use of ground truth phantoms generated from clinical B-mode ultrasound images. We evaluate our method against a set of popular methods from the despeckling literature on both fine and coarse speckle noise. In terms of computational efficiency, our method outperforms the other considered methods. Quantitatively on simulations and on a tissue-mimicking phantom, our method is found to be competitive with the state-of-the-art. On clinical B-mode images, our method is found to effectively smooth speckle while preserving low-contrast and highly localized salient image detail.

Quadratic String Method for Locating Instantons in Tunneling Splitting Calculations.

PubMed

Cvitaš, Marko T

2018-03-13

The ring-polymer instanton (RPI) method is an efficient technique for calculating approximate tunneling splittings in high-dimensional molecular systems. In the RPI method, tunneling splitting is evaluated from the properties of the minimum action path (MAP) connecting the symmetric wells, whereby the extensive sampling of the full potential energy surface of the exact quantum-dynamics methods is avoided. Nevertheless, the search for the MAP is usually the most time-consuming step in the standard numerical procedures. Recently, nudged elastic band (NEB) and string methods, originaly developed for locating minimum energy paths (MEPs), were adapted for the purpose of MAP finding with great efficiency gains [ J. Chem. Theory Comput. 2016 , 12 , 787 ]. In this work, we develop a new quadratic string method for locating instantons. The Euclidean action is minimized by propagating the initial guess (a path connecting two wells) over the quadratic potential energy surface approximated by means of updated Hessians. This allows the algorithm to take many minimization steps between the potential/gradient calls with further reductions in the computational effort, exploiting the smoothness of potential energy surface. The approach is general, as it uses Cartesian coordinates, and widely applicable, with computational effort of finding the instanton usually lower than that of determining the MEP. It can be combined with expensive potential energy surfaces or on-the-fly electronic-structure methods to explore a wide variety of molecular systems.

Structure-based non-canonical amino acid design to covalently crosslink an antibody–antigen complex

PubMed Central

Xu, Jianqing; Tack, Drew; Hughes, Randall A.; Ellington, Andrew D.; Gray, Jeffrey J.

2014-01-01

Engineering antibodies to utilize non-canonical amino acids (NCAA) should greatly expand the utility of an already important biological reagent. In particular, introducing crosslinking reagents into antibody complementarity determining regions (CDRs) should provide a means to covalently crosslink residues at the antibody–antigen interface. Unfortunately, finding the optimum position for crosslinking two proteins is often a matter of iterative guessing, even when the interface is known in atomic detail. Computer-aided antibody design can potentially greatly restrict the number of variants that must be explored in order to identify successful crosslinking sites. We have therefore used Rosetta to guide the introduction of an oxidizable crosslinking NCAA, l-3,4-dihydroxyphenylalanine (l-DOPA), into the CDRs of the anti-protective antigen scFv antibody M18, and have measured crosslinking to its cognate antigen, domain 4 of the anthrax protective antigen. Computed crosslinking distance, solvent accessibility, and interface energetics were three factors considered that could impact the efficiency of l-DOPA-mediated crosslinking. In the end, 10 variants were synthesized, and crosslinking efficiencies were generally 10% or higher, with the best variant crosslinking to 52% of the available antigen. The results suggest that computational analysis can be used in a pipeline for engineering crosslinking antibodies. The rules learned from l-DOPA crosslinking of antibodies may also be generalizable to the formation of other crosslinked interfaces and complexes. PMID:23680795

A comparison of algorithms for inference and learning in probabilistic graphical models.

PubMed

Frey, Brendan J; Jojic, Nebojsa

2005-09-01

Research into methods for reasoning under uncertainty is currently one of the most exciting areas of artificial intelligence, largely because it has recently become possible to record, store, and process large amounts of data. While impressive achievements have been made in pattern classification problems such as handwritten character recognition, face detection, speaker identification, and prediction of gene function, it is even more exciting that researchers are on the verge of introducing systems that can perform large-scale combinatorial analyses of data, decomposing the data into interacting components. For example, computational methods for automatic scene analysis are now emerging in the computer vision community. These methods decompose an input image into its constituent objects, lighting conditions, motion patterns, etc. Two of the main challenges are finding effective representations and models in specific applications and finding efficient algorithms for inference and learning in these models. In this paper, we advocate the use of graph-based probability models and their associated inference and learning algorithms. We review exact techniques and various approximate, computationally efficient techniques, including iterated conditional modes, the expectation maximization (EM) algorithm, Gibbs sampling, the mean field method, variational techniques, structured variational techniques and the sum-product algorithm ("loopy" belief propagation). We describe how each technique can be applied in a vision model of multiple, occluding objects and contrast the behaviors and performances of the techniques using a unifying cost function, free energy.

BRICK v0.2, a simple, accessible, and transparent model framework for climate and regional sea-level projections

NASA Astrophysics Data System (ADS)

Wong, Tony E.; Bakker, Alexander M. R.; Ruckert, Kelsey; Applegate, Patrick; Slangen, Aimée B. A.; Keller, Klaus

2017-07-01

Simple models can play pivotal roles in the quantification and framing of uncertainties surrounding climate change and sea-level rise. They are computationally efficient, transparent, and easy to reproduce. These qualities also make simple models useful for the characterization of risk. Simple model codes are increasingly distributed as open source, as well as actively shared and guided. Alas, computer codes used in the geosciences can often be hard to access, run, modify (e.g., with regards to assumptions and model components), and review. Here, we describe the simple model framework BRICK (Building blocks for Relevant Ice and Climate Knowledge) v0.2 and its underlying design principles. The paper adds detail to an earlier published model setup and discusses the inclusion of a land water storage component. The framework largely builds on existing models and allows for projections of global mean temperature as well as regional sea levels and coastal flood risk. BRICK is written in R and Fortran. BRICK gives special attention to the model values of transparency, accessibility, and flexibility in order to mitigate the above-mentioned issues while maintaining a high degree of computational efficiency. We demonstrate the flexibility of this framework through simple model intercomparison experiments. Furthermore, we demonstrate that BRICK is suitable for risk assessment applications by using a didactic example in local flood risk management.

Efficient universal blind quantum computation.

PubMed

Giovannetti, Vittorio; Maccone, Lorenzo; Morimae, Tomoyuki; Rudolph, Terry G

2013-12-06

We give a cheat sensitive protocol for blind universal quantum computation that is efficient in terms of computational and communication resources: it allows one party to perform an arbitrary computation on a second party's quantum computer without revealing either which computation is performed, or its input and output. The first party's computational capabilities can be extremely limited: she must only be able to create and measure single-qubit superposition states. The second party is not required to use measurement-based quantum computation. The protocol requires the (optimal) exchange of O(Jlog2(N)) single-qubit states, where J is the computational depth and N is the number of qubits needed for the computation.

Computational efficiency for the surface renewal method

NASA Astrophysics Data System (ADS)

Kelley, Jason; Higgins, Chad

2018-04-01

Measuring surface fluxes using the surface renewal (SR) method requires programmatic algorithms for tabulation, algebraic calculation, and data quality control. A number of different methods have been published describing automated calibration of SR parameters. Because the SR method utilizes high-frequency (10 Hz+) measurements, some steps in the flux calculation are computationally expensive, especially when automating SR to perform many iterations of these calculations. Several new algorithms were written that perform the required calculations more efficiently and rapidly, and that tested for sensitivity to length of flux averaging period, ability to measure over a large range of lag timescales, and overall computational efficiency. These algorithms utilize signal processing techniques and algebraic simplifications that demonstrate simple modifications that dramatically improve computational efficiency. The results here complement efforts by other authors to standardize a robust and accurate computational SR method. Increased speed of computation time grants flexibility to implementing the SR method, opening new avenues for SR to be used in research, for applied monitoring, and in novel field deployments.

Energy Efficiency Challenges of 5G Small Cell Networks.

PubMed

Ge, Xiaohu; Yang, Jing; Gharavi, Hamid; Sun, Yang

2017-05-01

The deployment of a large number of small cells poses new challenges to energy efficiency, which has often been ignored in fifth generation (5G) cellular networks. While massive multiple-input multiple outputs (MIMO) will reduce the transmission power at the expense of higher computational cost, the question remains as to which computation or transmission power is more important in the energy efficiency of 5G small cell networks. Thus, the main objective in this paper is to investigate the computation power based on the Landauer principle. Simulation results reveal that more than 50% of the energy is consumed by the computation power at 5G small cell base stations (BSs). Moreover, the computation power of 5G small cell BS can approach 800 watt when the massive MIMO (e.g., 128 antennas) is deployed to transmit high volume traffic. This clearly indicates that computation power optimization can play a major role in the energy efficiency of small cell networks.

Energy Efficiency Challenges of 5G Small Cell Networks

PubMed Central

Ge, Xiaohu; Yang, Jing; Gharavi, Hamid; Sun, Yang

2017-01-01

The deployment of a large number of small cells poses new challenges to energy efficiency, which has often been ignored in fifth generation (5G) cellular networks. While massive multiple-input multiple outputs (MIMO) will reduce the transmission power at the expense of higher computational cost, the question remains as to which computation or transmission power is more important in the energy efficiency of 5G small cell networks. Thus, the main objective in this paper is to investigate the computation power based on the Landauer principle. Simulation results reveal that more than 50% of the energy is consumed by the computation power at 5G small cell base stations (BSs). Moreover, the computation power of 5G small cell BS can approach 800 watt when the massive MIMO (e.g., 128 antennas) is deployed to transmit high volume traffic. This clearly indicates that computation power optimization can play a major role in the energy efficiency of small cell networks. PMID:28757670

Efficient computation of photonic crystal waveguide modes with dispersive material.

PubMed

Schmidt, Kersten; Kappeler, Roman

2010-03-29

The optimization of PhC waveguides is a key issue for successfully designing PhC devices. Since this design task is computationally expensive, efficient methods are demanded. The available codes for computing photonic bands are also applied to PhC waveguides. They are reliable but not very efficient, which is even more pronounced for dispersive material. We present a method based on higher order finite elements with curved cells, which allows to solve for the band structure taking directly into account the dispersiveness of the materials. This is accomplished by reformulating the wave equations as a linear eigenproblem in the complex wave-vectors k. For this method, we demonstrate the high efficiency for the computation of guided PhC waveguide modes by a convergence analysis.

Modeling of chemical reactions in micelle: water-mediated keto-enol interconversion as a case study.

PubMed

Marracino, Paolo; Amadei, Andrea; Apollonio, Francesca; d'Inzeo, Guglielmo; Liberti, Micaela; di Crescenzo, Antonello; Fontana, Antonella; Zappacosta, Romina; Aschi, Massimiliano

2011-06-30

The effect of a zwitterionic micelle environment on the efficiency of the keto-enol interconversion of 2-phenylacetylthiophene has been investigated by means of a joint application of experimental and theoretical/computational approaches. Results have revealed a reduction of the reaction rate constant if compared with bulk water essentially because of the different solvation conditions experienced by the reactant species, including water molecules, in the micelle environment. The slight inhibiting effect due to the application of a static electric field has also been theoretically investigated and presented.

Numerical Schemes and Computational Studies for Dynamically Orthogonal Equations (Multidisciplinary Simulation, Estimation, and Assimilation Systems: Reports in Ocean Science and Engineering)

DTIC Science & Technology

2011-08-01

heat transfers [49, 52]. However, the DO method has not yet been applied to Boussinesq flows, and the numerical challenges of the DO decomposition for...used a PCE scheme to study mixing in a two-dimensional (2D) microchannel and improved the efficiency of their solution scheme by decoupling the...to several Navier-Stokes flows and their stochastic dynamics has been studied, including mean-mode and mode-mode energy transfers for 2D flows and

Study of the filtration performance of a plain wave fabric filter using response surface methodology.

PubMed

Qian, Fuping; Wang, Haigang

2010-04-15

The gas-solid two-phase flows in the plain wave fabric filter were simulated by computational fluid dynamics (CFD) technology, and the warps and wefts of the fabric filter were made of filaments with different dimensions. The numerical solutions were carried out using commercial computational fluid dynamics (CFD) code Fluent 6.1. The filtration performances of the plain wave fabric filter with different geometry parameters and operating condition, including the horizontal distance, the vertical distance and the face velocity were calculated. The effects of geometry parameters and operating condition on filtration efficiency and pressure drop were studied using response surface methodology (RSM) by means of the statistical software (Minitab V14), and two second-order polynomial models were obtained with regard to the effect of the three factors as stated above. Moreover, the models were modified by dismissing the insignificant terms. The results show that the horizontal distance, vertical distance and the face velocity all play an important role in influencing the filtration efficiency and pressure drop of the plane wave fabric filters. The horizontal distance of 3.8 times the fiber diameter, the vertical distance of 4.0 times the fiber diameter and Reynolds number of 0.98 are found to be the optimal conditions to achieve the highest filtration efficiency at the same face velocity, while maintaining an acceptable pressure drop. 2009 Elsevier B.V. All rights reserved.

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

Greene, Samuel M., E-mail: samuel.greene@chem.ox.ac.uk; Shan, Xiao, E-mail: xiao.shan@chem.ox.ac.uk; Clary, David C., E-mail: david.clary@chem.ox.ac.u

Semiclassical Transition State Theory (SCTST), a method for calculating rate constants of chemical reactions, offers gains in computational efficiency relative to more accurate quantum scattering methods. In full-dimensional (FD) SCTST, reaction probabilities are calculated from third and fourth potential derivatives along all vibrational degrees of freedom. However, the computational cost of FD SCTST scales unfavorably with system size, which prohibits its application to larger systems. In this study, the accuracy and efficiency of 1-D SCTST, in which only third and fourth derivatives along the reaction mode are used, are investigated in comparison to those of FD SCTST. Potential derivatives aremore » obtained from numerical ab initio Hessian matrix calculations at the MP2/cc-pVTZ level of theory, and Richardson extrapolation is applied to improve the accuracy of these derivatives. Reaction barriers are calculated at the CCSD(T)/cc-pVTZ level. Results from FD SCTST agree with results from previous theoretical and experimental studies when Richardson extrapolation is applied. Results from our implementation of 1-D SCTST, which uses only 4 single-point MP2/cc-pVTZ energy calculations in addition to those for conventional TST, agree with FD results to within a factor of 5 at 250 K. This degree of agreement and the efficiency of the 1-D method suggest its potential as a means of approximating rate constants for systems too large for existing quantum scattering methods.« less

Efficiently characterizing the total error in quantum circuits

NASA Astrophysics Data System (ADS)

Carignan-Dugas, Arnaud; Wallman, Joel J.; Emerson, Joseph

A promising technological advancement meant to enlarge our computational means is the quantum computer. Such a device would harvest the quantum complexity of the physical world in order to unfold concrete mathematical problems more efficiently. However, the errors emerging from the implementation of quantum operations are likewise quantum, and hence share a similar level of intricacy. Fortunately, randomized benchmarking protocols provide an efficient way to characterize the operational noise within quantum devices. The resulting figures of merit, like the fidelity and the unitarity, are typically attached to a set of circuit components. While important, this doesn't fulfill the main goal: determining if the error rate of the total circuit is small enough in order to trust its outcome. In this work, we fill the gap by providing an optimal bound on the total fidelity of a circuit in terms of component-wise figures of merit. Our bound smoothly interpolates between the classical regime, in which the error rate grows linearly in the circuit's length, and the quantum regime, which can naturally allow quadratic growth. Conversely, our analysis substantially improves the bounds on single circuit element fidelities obtained through techniques such as interleaved randomized benchmarking. This research was supported by the U.S. Army Research Office through Grant W911NF- 14-1-0103, CIFAR, the Government of Ontario, and the Government of Canada through NSERC and Industry Canada.

Analytical prediction with multidimensional computer programs and experimental verification of the performance, at a variety of operating conditions, of two traveling wave tubes with depressed collectors

NASA Technical Reports Server (NTRS)

Dayton, J. A., Jr.; Kosmahl, H. G.; Ramins, P.; Stankiewicz, N.

1979-01-01

Experimental and analytical results are compared for two high performance, octave bandwidth TWT's that use depressed collectors (MDC's) to improve the efficiency. The computations were carried out with advanced, multidimensional computer programs that are described here in detail. These programs model the electron beam as a series of either disks or rings of charge and follow their multidimensional trajectories from the RF input of the ideal TWT, through the slow wave structure, through the magnetic refocusing system, to their points of impact in the depressed collector. Traveling wave tube performance, collector efficiency, and collector current distribution were computed and the results compared with measurements for a number of TWT-MDC systems. Power conservation and correct accounting of TWT and collector losses were observed. For the TWT's operating at saturation, very good agreement was obtained between the computed and measured collector efficiencies. For a TWT operating 3 and 6 dB below saturation, excellent agreement between computed and measured collector efficiencies was obtained in some cases but only fair agreement in others. However, deviations can largely be explained by small differences in the computed and actual spent beam energy distributions. The analytical tools used here appear to be sufficiently refined to design efficient collectors for this class of TWT. However, for maximum efficiency, some experimental optimization (e.g., collector voltages and aperture sizes) will most likely be required.

An efficient and accurate 3D displacements tracking strategy for digital volume correlation

NASA Astrophysics Data System (ADS)

Pan, Bing; Wang, Bo; Wu, Dafang; Lubineau, Gilles

2014-07-01

Owing to its inherent computational complexity, practical implementation of digital volume correlation (DVC) for internal displacement and strain mapping faces important challenges in improving its computational efficiency. In this work, an efficient and accurate 3D displacement tracking strategy is proposed for fast DVC calculation. The efficiency advantage is achieved by using three improvements. First, to eliminate the need of updating Hessian matrix in each iteration, an efficient 3D inverse compositional Gauss-Newton (3D IC-GN) algorithm is introduced to replace existing forward additive algorithms for accurate sub-voxel displacement registration. Second, to ensure the 3D IC-GN algorithm that converges accurately and rapidly and avoid time-consuming integer-voxel displacement searching, a generalized reliability-guided displacement tracking strategy is designed to transfer accurate and complete initial guess of deformation for each calculation point from its computed neighbors. Third, to avoid the repeated computation of sub-voxel intensity interpolation coefficients, an interpolation coefficient lookup table is established for tricubic interpolation. The computational complexity of the proposed fast DVC and the existing typical DVC algorithms are first analyzed quantitatively according to necessary arithmetic operations. Then, numerical tests are performed to verify the performance of the fast DVC algorithm in terms of measurement accuracy and computational efficiency. The experimental results indicate that, compared with the existing DVC algorithm, the presented fast DVC algorithm produces similar precision and slightly higher accuracy at a substantially reduced computational cost.

An exponential time-integrator scheme for steady and unsteady inviscid flows

NASA Astrophysics Data System (ADS)

Li, Shu-Jie; Luo, Li-Shi; Wang, Z. J.; Ju, Lili

2018-07-01

An exponential time-integrator scheme of second-order accuracy based on the predictor-corrector methodology, denoted PCEXP, is developed to solve multi-dimensional nonlinear partial differential equations pertaining to fluid dynamics. The effective and efficient implementation of PCEXP is realized by means of the Krylov method. The linear stability and truncation error are analyzed through a one-dimensional model equation. The proposed PCEXP scheme is applied to the Euler equations discretized with a discontinuous Galerkin method in both two and three dimensions. The effectiveness and efficiency of the PCEXP scheme are demonstrated for both steady and unsteady inviscid flows. The accuracy and efficiency of the PCEXP scheme are verified and validated through comparisons with the explicit third-order total variation diminishing Runge-Kutta scheme (TVDRK3), the implicit backward Euler (BE) and the implicit second-order backward difference formula (BDF2). For unsteady flows, the PCEXP scheme generates a temporal error much smaller than the BDF2 scheme does, while maintaining the expected acceleration at the same time. Moreover, the PCEXP scheme is also shown to achieve the computational efficiency comparable to the implicit schemes for steady flows.

An Efficient Data Compression Model Based on Spatial Clustering and Principal Component Analysis in Wireless Sensor Networks.

PubMed

Yin, Yihang; Liu, Fengzheng; Zhou, Xiang; Li, Quanzhong

2015-08-07

Wireless sensor networks (WSNs) have been widely used to monitor the environment, and sensors in WSNs are usually power constrained. Because inner-node communication consumes most of the power, efficient data compression schemes are needed to reduce the data transmission to prolong the lifetime of WSNs. In this paper, we propose an efficient data compression model to aggregate data, which is based on spatial clustering and principal component analysis (PCA). First, sensors with a strong temporal-spatial correlation are grouped into one cluster for further processing with a novel similarity measure metric. Next, sensor data in one cluster are aggregated in the cluster head sensor node, and an efficient adaptive strategy is proposed for the selection of the cluster head to conserve energy. Finally, the proposed model applies principal component analysis with an error bound guarantee to compress the data and retain the definite variance at the same time. Computer simulations show that the proposed model can greatly reduce communication and obtain a lower mean square error than other PCA-based algorithms.

Numerical determination of personal aerosol sampler aspiration efficiency.

PubMed

Lo Savio, Simone; Paradisi, Paolo; Tampieri, Francesco; Belosi, Franco; Morigi, Maria Pia; Agostini, Sergio

2003-04-01

In this work the determination of the aspiration efficiency of personal aerosol samplers, commonly used in occupational exposure assessment, is investigated by means of CFD techniques. Specifically, it will be described a code to calculate the particle trajectories in a given flow field. At the present state the code considers only the effects of the mean flow field on the particle motion, whereas the turbulent diffusion effects are neglected. Comparisons with experimental measurements are also given in the framework of a research contract, supported by the European Community, with several experimental contributions from the participants. The main objective of the European research is to develop a new approach to experimentation with airborne particle flows, working on a reduced scale. This methodology has the advantage of allowing real-time aerosol determination and use of small wind tunnels, with a better experimental control. In this article we describe how the methodology has been verified using computational fluid dynamics. Experimental and numerical aspiration efficiencies have been compared and the influence of gravity and turbulence intensity in full and reduced scale has been investigated. The numerical techniques described here are in agreement with previous similar research and allow at least qualitative predictions of aspiration efficiency for real samplers, taking care of orientation from the incoming air flow. The major discrepancies among predicted and experimental results may be a consequence of bounce effects, which are very difficult to eliminate also by greasing the sampler surface.

HAlign-II: efficient ultra-large multiple sequence alignment and phylogenetic tree reconstruction with distributed and parallel computing.

PubMed

Wan, Shixiang; Zou, Quan

2017-01-01

Multiple sequence alignment (MSA) plays a key role in biological sequence analyses, especially in phylogenetic tree construction. Extreme increase in next-generation sequencing results in shortage of efficient ultra-large biological sequence alignment approaches for coping with different sequence types. Distributed and parallel computing represents a crucial technique for accelerating ultra-large (e.g. files more than 1 GB) sequence analyses. Based on HAlign and Spark distributed computing system, we implement a highly cost-efficient and time-efficient HAlign-II tool to address ultra-large multiple biological sequence alignment and phylogenetic tree construction. The experiments in the DNA and protein large scale data sets, which are more than 1GB files, showed that HAlign II could save time and space. It outperformed the current software tools. HAlign-II can efficiently carry out MSA and construct phylogenetic trees with ultra-large numbers of biological sequences. HAlign-II shows extremely high memory efficiency and scales well with increases in computing resource. THAlign-II provides a user-friendly web server based on our distributed computing infrastructure. HAlign-II with open-source codes and datasets was established at http://lab.malab.cn/soft/halign.

A note on calculation of efficiency and emissions from wood and wood pellet stoves

NASA Astrophysics Data System (ADS)

Petrocelli, D.; Lezzi, A. M.

2015-11-01

In recent years, national laws and international regulations have introduced strict limits on efficiency and emissions from woody biomass appliances to promote the diffusion of models characterized by low emissions and high efficiency. The evaluation of efficiency and emissions is made during the certification process which consists in standardized tests. Standards prescribe the procedures to be followed during tests and the relations to be used to determine the mean value of efficiency and emissions. As a matter of fact these values are calculated using flue gas temperature and composition averaged over the whole test period, lasting from 1 to 6 hours. Typically, in wood appliances the fuel burning rate is not constant and this leads to a considerable variation in time of composition and flow rate of the flue gas. In this paper we show that this fact may cause significant differences between emission values calculated according to standards and those obtained integrating over the test period the instantaneous mass and energy balances. In addition, we propose some approximated relations and a method for wood stoves which supply more accurate results than those calculated according to standards. These relations can be easily implemented in a computer controlled data acquisition systems.

Application of a computationally efficient method to approximate gap model results with a probabilistic approach

NASA Astrophysics Data System (ADS)

Scherstjanoi, M.; Kaplan, J. O.; Lischke, H.

2014-07-01

To be able to simulate climate change effects on forest dynamics over the whole of Switzerland, we adapted the second-generation DGVM (dynamic global vegetation model) LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) to the Alpine environment. We modified model functions, tuned model parameters, and implemented new tree species to represent the potential natural vegetation of Alpine landscapes. Furthermore, we increased the computational efficiency of the model to enable area-covering simulations in a fine resolution (1 km) sufficient for the complex topography of the Alps, which resulted in more than 32 000 simulation grid cells. To this aim, we applied the recently developed method GAPPARD (approximating GAP model results with a Probabilistic Approach to account for stand Replacing Disturbances) (Scherstjanoi et al., 2013) to LPJ-GUESS. GAPPARD derives mean output values from a combination of simulation runs without disturbances and a patch age distribution defined by the disturbance frequency. With this computationally efficient method, which increased the model's speed by approximately the factor 8, we were able to faster detect the shortcomings of LPJ-GUESS functions and parameters. We used the adapted LPJ-GUESS together with GAPPARD to assess the influence of one climate change scenario on dynamics of tree species composition and biomass throughout the 21st century in Switzerland. To allow for comparison with the original model, we additionally simulated forest dynamics along a north-south transect through Switzerland. The results from this transect confirmed the high value of the GAPPARD method despite some limitations towards extreme climatic events. It allowed for the first time to obtain area-wide, detailed high-resolution LPJ-GUESS simulation results for a large part of the Alpine region.

Efficient computation of hashes

NASA Astrophysics Data System (ADS)

Lopes, Raul H. C.; Franqueira, Virginia N. L.; Hobson, Peter R.

2014-06-01

The sequential computation of hashes at the core of many distributed storage systems and found, for example, in grid services can hinder efficiency in service quality and even pose security challenges that can only be addressed by the use of parallel hash tree modes. The main contributions of this paper are, first, the identification of several efficiency and security challenges posed by the use of sequential hash computation based on the Merkle-Damgard engine. In addition, alternatives for the parallel computation of hash trees are discussed, and a prototype for a new parallel implementation of the Keccak function, the SHA-3 winner, is introduced.

Scientific Discovery through Advanced Computing (SciDAC-3) Partnership Project Annual Report

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

Hoffman, Forest M.; Bochev, Pavel B.; Cameron-Smith, Philip J..

The Applying Computationally Efficient Schemes for BioGeochemical Cycles ACES4BGC Project is advancing the predictive capabilities of Earth System Models (ESMs) by reducing two of the largest sources of uncertainty, aerosols and biospheric feedbacks, with a highly efficient computational approach. In particular, this project is implementing and optimizing new computationally efficient tracer advection algorithms for large numbers of tracer species; adding important biogeochemical interactions between the atmosphere, land, and ocean models; and applying uncertainty quanti cation (UQ) techniques to constrain process parameters and evaluate uncertainties in feedbacks between biogeochemical cycles and the climate system.

Projected role of advanced computational aerodynamic methods at the Lockheed-Georgia company

NASA Technical Reports Server (NTRS)

Lores, M. E.

1978-01-01

Experience with advanced computational methods being used at the Lockheed-Georgia Company to aid in the evaluation and design of new and modified aircraft indicates that large and specialized computers will be needed to make advanced three-dimensional viscous aerodynamic computations practical. The Numerical Aerodynamic Simulation Facility should be used to provide a tool for designing better aerospace vehicles while at the same time reducing development costs by performing computations using Navier-Stokes equations solution algorithms and permitting less sophisticated but nevertheless complex calculations to be made efficiently. Configuration definition procedures and data output formats can probably best be defined in cooperation with industry, therefore, the computer should handle many remote terminals efficiently. The capability of transferring data to and from other computers needs to be provided. Because of the significant amount of input and output associated with 3-D viscous flow calculations and because of the exceedingly fast computation speed envisioned for the computer, special attention should be paid to providing rapid, diversified, and efficient input and output.

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

NASA Astrophysics Data System (ADS)

Velazquez, Antonio; Swartz, R. Andrew

2013-04-01

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

An algorithm of discovering signatures from DNA databases on a computer cluster.

PubMed

Lee, Hsiao Ping; Sheu, Tzu-Fang

2014-10-05

Signatures are short sequences that are unique and not similar to any other sequence in a database that can be used as the basis to identify different species. Even though several signature discovery algorithms have been proposed in the past, these algorithms require the entirety of databases to be loaded in the memory, thus restricting the amount of data that they can process. It makes those algorithms unable to process databases with large amounts of data. Also, those algorithms use sequential models and have slower discovery speeds, meaning that the efficiency can be improved. In this research, we are debuting the utilization of a divide-and-conquer strategy in signature discovery and have proposed a parallel signature discovery algorithm on a computer cluster. The algorithm applies the divide-and-conquer strategy to solve the problem posed to the existing algorithms where they are unable to process large databases and uses a parallel computing mechanism to effectively improve the efficiency of signature discovery. Even when run with just the memory of regular personal computers, the algorithm can still process large databases such as the human whole-genome EST database which were previously unable to be processed by the existing algorithms. The algorithm proposed in this research is not limited by the amount of usable memory and can rapidly find signatures in large databases, making it useful in applications such as Next Generation Sequencing and other large database analysis and processing. The implementation of the proposed algorithm is available at http://www.cs.pu.edu.tw/~fang/DDCSDPrograms/DDCSD.htm.

Automatic and accurate reconstruction of distal humerus contours through B-Spline fitting based on control polygon deformation.

PubMed

Mostafavi, Kamal; Tutunea-Fatan, O Remus; Bordatchev, Evgueni V; Johnson, James A

2014-12-01

The strong advent of computer-assisted technologies experienced by the modern orthopedic surgery prompts for the expansion of computationally efficient techniques to be built on the broad base of computer-aided engineering tools that are readily available. However, one of the common challenges faced during the current developmental phase continues to remain the lack of reliable frameworks to allow a fast and precise conversion of the anatomical information acquired through computer tomography to a format that is acceptable to computer-aided engineering software. To address this, this study proposes an integrated and automatic framework capable to extract and then postprocess the original imaging data to a common planar and closed B-Spline representation. The core of the developed platform relies on the approximation of the discrete computer tomography data by means of an original two-step B-Spline fitting technique based on successive deformations of the control polygon. In addition to its rapidity and robustness, the developed fitting technique was validated to produce accurate representations that do not deviate by more than 0.2 mm with respect to alternate representations of the bone geometry that were obtained through different-contact-based-data acquisition or data processing methods. © IMechE 2014.

Cellular automata-based modelling and simulation of biofilm structure on multi-core computers.

PubMed

Skoneczny, Szymon

2015-01-01

The article presents a mathematical model of biofilm growth for aerobic biodegradation of a toxic carbonaceous substrate. Modelling of biofilm growth has fundamental significance in numerous processes of biotechnology and mathematical modelling of bioreactors. The process following double-substrate kinetics with substrate inhibition proceeding in a biofilm has not been modelled so far by means of cellular automata. Each process in the model proposed, i.e. diffusion of substrates, uptake of substrates, growth and decay of microorganisms and biofilm detachment, is simulated in a discrete manner. It was shown that for flat biofilm of constant thickness, the results of the presented model agree with those of a continuous model. The primary outcome of the study was to propose a mathematical model of biofilm growth; however a considerable amount of focus was also placed on the development of efficient algorithms for its solution. Two parallel algorithms were created, differing in the way computations are distributed. Computer programs were created using OpenMP Application Programming Interface for C++ programming language. Simulations of biofilm growth were performed on three high-performance computers. Speed-up coefficients of computer programs were compared. Both algorithms enabled a significant reduction of computation time. It is important, inter alia, in modelling and simulation of bioreactor dynamics.

A Computational Framework for Realistic Retina Modeling.

PubMed

Martínez-Cañada, Pablo; Morillas, Christian; Pino, Begoña; Ros, Eduardo; Pelayo, Francisco

2016-11-01

Computational simulations of the retina have led to valuable insights about the biophysics of its neuronal activity and processing principles. A great number of retina models have been proposed to reproduce the behavioral diversity of the different visual processing pathways. While many of these models share common computational stages, previous efforts have been more focused on fitting specific retina functions rather than generalizing them beyond a particular model. Here, we define a set of computational retinal microcircuits that can be used as basic building blocks for the modeling of different retina mechanisms. To validate the hypothesis that similar processing structures may be repeatedly found in different retina functions, we implemented a series of retina models simply by combining these computational retinal microcircuits. Accuracy of the retina models for capturing neural behavior was assessed by fitting published electrophysiological recordings that characterize some of the best-known phenomena observed in the retina: adaptation to the mean light intensity and temporal contrast, and differential motion sensitivity. The retinal microcircuits are part of a new software platform for efficient computational retina modeling from single-cell to large-scale levels. It includes an interface with spiking neural networks that allows simulation of the spiking response of ganglion cells and integration with models of higher visual areas.

Pruning a decision tree for selecting computer-related assistive devices for people with disabilities.

PubMed

Chi, Chia-Fen; Tseng, Li-Kai; Jang, Yuh

2012-07-01

Many disabled individuals lack extensive knowledge about assistive technology, which could help them use computers. In 1997, Denis Anson developed a decision tree of 49 evaluative questions designed to evaluate the functional capabilities of the disabled user and choose an appropriate combination of assistive devices, from a selection of 26, that enable the individual to use a computer. In general, occupational therapists guide the disabled users through this process. They often have to go over repetitive questions in order to find an appropriate device. A disabled user may require an alphanumeric entry device, a pointing device, an output device, a performance enhancement device, or some combination of these. Therefore, the current research eliminates redundant questions and divides Anson's decision tree into multiple independent subtrees to meet the actual demand of computer users with disabilities. The modified decision tree was tested by six disabled users to prove it can determine a complete set of assistive devices with a smaller number of evaluative questions. The means to insert new categories of computer-related assistive devices was included to ensure the decision tree can be expanded and updated. The current decision tree can help the disabled users and assistive technology practitioners to find appropriate computer-related assistive devices that meet with clients' individual needs in an efficient manner.

Navier-Stokes simulation with constraint forces: finite-difference method for particle-laden flows and complex geometries.

PubMed

Höfler, K; Schwarzer, S

2000-06-01

Building on an idea of Fogelson and Peskin [J. Comput. Phys. 79, 50 (1988)] we describe the implementation and verification of a simulation technique for systems of non-Brownian particles in fluids at Reynolds numbers up to about 20 on the particle scale. This direct simulation technique fills a gap between simulations in the viscous regime and high-Reynolds-number modeling. It also combines sufficient computational accuracy with numerical efficiency and allows studies of several thousand, in principle arbitrarily shaped, extended and hydrodynamically interacting particles on regular work stations. We verify the algorithm in two and three dimensions for (i) single falling particles and (ii) a fluid flowing through a bed of fixed spheres. In the context of sedimentation we compute the volume fraction dependence of the mean sedimentation velocity. The results are compared with experimental and other numerical results both in the viscous and inertial regime and we find very satisfactory agreement.

Validation of a Computational Fluid Dynamics (CFD) Code for Supersonic Axisymmetric Base Flow

NASA Technical Reports Server (NTRS)

Tucker, P. Kevin

1993-01-01

The ability to accurately and efficiently calculate the flow structure in the base region of bodies of revolution in supersonic flight is a significant step in CFD code validation for applications ranging from base heating for rockets to drag for protectives. The FDNS code is used to compute such a flow and the results are compared to benchmark quality experimental data. Flowfield calculations are presented for a cylindrical afterbody at M = 2.46 and angle of attack a = O. Grid independent solutions are compared to mean velocity profiles in the separated wake area and downstream of the reattachment point. Additionally, quantities such as turbulent kinetic energy and shear layer growth rates are compared to the data. Finally, the computed base pressures are compared to the measured values. An effort is made to elucidate the role of turbulence models in the flowfield predictions. The level of turbulent eddy viscosity, and its origin, are used to contrast the various turbulence models and compare the results to the experimental data.

An impulsive receptance technique for the time domain computation of the vibration of a whole aero-engine model with nonlinear bearings

NASA Astrophysics Data System (ADS)

Hai, Pham Minh; Bonello, Philip

2008-12-01

The direct study of the vibration of real engine structures with nonlinear bearings, particularly aero-engines, has been severely limited by the fact that current nonlinear computational techniques are not well-suited for complex large-order systems. This paper introduces a novel implicit "impulsive receptance method" (IRM) for the time domain analysis of such structures. The IRM's computational efficiency is largely immune to the number of modes used and dependent only on the number of nonlinear elements. This means that, apart from retaining numerical accuracy, a much more physically accurate solution is achievable within a short timeframe. Simulation tests on a realistically sized representative twin-spool aero-engine showed that the new method was around 40 times faster than a conventional implicit integration scheme. Preliminary results for a given rotor unbalance distribution revealed the varying degree of journal lift, orbit size and shape at the example engine's squeeze-film damper bearings, and the effect of end-sealing at these bearings.

Experimental comparison between performance of the PM and LPM methods in computed radiography

NASA Astrophysics Data System (ADS)

Kermani, Aboutaleb; Feghhi, Seyed Amir Hossein; Rokrok, Behrouz

2018-07-01

The scatter downgrades the image quality and reduces its information efficiency in quantitative measurement usages when creating projections with ionizing radiation. Therefore, the variety of methods have been applied for scatter reduction and correction of the undesirable effects. As new approaches, the ordinary and localized primary modulation methods have already been used individually through experiments and simulations in medical and industrial computed tomography, respectively. The aim of this study is the evaluation of capabilities and limitations of these methods in comparison with each other. For this mean, the ordinary primary modulation has been implemented in computed radiography for the first time and the potential of both methods has been assessed in thickness measurement as well as scatter to primary signal ratio determination. The comparison results, based on the experimental outputs which obtained using aluminum specimens and continuous X-ray spectra, are to the benefit of the localized primary modulation method because of improved accuracy and higher performance especially at the edges.

Solving Quantum Ground-State Problems with Nuclear Magnetic Resonance

PubMed Central

Li, Zhaokai; Yung, Man-Hong; Chen, Hongwei; Lu, Dawei; Whitfield, James D.; Peng, Xinhua; Aspuru-Guzik, Alán; Du, Jiangfeng

2011-01-01

Quantum ground-state problems are computationally hard problems for general many-body Hamiltonians; there is no classical or quantum algorithm known to be able to solve them efficiently. Nevertheless, if a trial wavefunction approximating the ground state is available, as often happens for many problems in physics and chemistry, a quantum computer could employ this trial wavefunction to project the ground state by means of the phase estimation algorithm (PEA). We performed an experimental realization of this idea by implementing a variational-wavefunction approach to solve the ground-state problem of the Heisenberg spin model with an NMR quantum simulator. Our iterative phase estimation procedure yields a high accuracy for the eigenenergies (to the 10−5 decimal digit). The ground-state fidelity was distilled to be more than 80%, and the singlet-to-triplet switching near the critical field is reliably captured. This result shows that quantum simulators can better leverage classical trial wave functions than classical computers PMID:22355607

Usability characteristics of self-administered computer-assisted interviewing in the emergency department: factors affecting ease of use, efficiency, and entry error.

PubMed

Herrick, D B; Nakhasi, A; Nelson, B; Rice, S; Abbott, P A; Saber Tehrani, A S; Rothman, R E; Lehmann, H P; Newman-Toker, D E

2013-01-01

Self-administered computer-assisted interviewing (SACAI) gathers accurate information from patients and could facilitate Emergency Department (ED) diagnosis. As part of an ongoing research effort whose long-range goal is to develop automated medical interviewing for diagnostic decision support, we explored usability attributes of SACAI in the ED. Cross-sectional study at two urban, academic EDs. Convenience sample recruited daily over six weeks. Adult, non-level I trauma patients were eligible. We collected data on ease of use (self-reported difficulty, researcher documented need for help), efficiency (mean time-per-click on a standardized interview segment), and error (self-report age mismatched with age derived from electronic health records) when using SACAI on three different instruments: Elo TouchSystems ESY15A2 (finger touch), Toshiba M200 (with digitizer pen), and Motion C5 (with digitizer pen). We calculated descriptive statistics and used regression analysis to evaluate the impact of patient and computer factors on time-per-click. 841 participants completed all SACAI questions. Few (<1%) thought using the touch computer to ascertain medical information was difficult. Most (86%) required no assistance. Participants needing help were older (54 ± 19 vs. 40 ± 15 years, p<0.001) and more often lacked internet at home (13.4% vs. 7.3%, p = 0.004). On multivariate analysis, female sex (p<0.001), White (p<0.001) and other (p = 0.05) race (vs. Black race), younger age (p<0.001), internet access at home (p<0.001), high school graduation (p = 0.04), and touch screen entry (vs. digitizer pen) (p = 0.01) were independent predictors of decreased time-per-click. Participant misclick errors were infrequent, but, in our sample, occurred only during interviews using a digitizer pen rather than a finger touch-screen interface (1.9% vs. 0%, p = 0.09). Our results support the facility of interactions between ED patients and SACAI. Demographic factors associated with need for assistance or slower interviews could serve as important triggers to offering human support for SACAI interviews during implementation. Understanding human-computer interactions in real-world clinical settings is essential to implementing automated interviewing as means to a larger long-term goal of enhancing clinical care, diagnostic accuracy, and patient safety.

Robust efficient video fingerprinting

NASA Astrophysics Data System (ADS)

Puri, Manika; Lubin, Jeffrey

2009-02-01

We have developed a video fingerprinting system with robustness and efficiency as the primary and secondary design criteria. In extensive testing, the system has shown robustness to cropping, letter-boxing, sub-titling, blur, drastic compression, frame rate changes, size changes and color changes, as well as to the geometric distortions often associated with camcorder capture in cinema settings. Efficiency is afforded by a novel two-stage detection process in which a fast matching process first computes a number of likely candidates, which are then passed to a second slower process that computes the overall best match with minimal false alarm probability. One key component of the algorithm is a maximally stable volume computation - a three-dimensional generalization of maximally stable extremal regions - that provides a content-centric coordinate system for subsequent hash function computation, independent of any affine transformation or extensive cropping. Other key features include an efficient bin-based polling strategy for initial candidate selection, and a final SIFT feature-based computation for final verification. We describe the algorithm and its performance, and then discuss additional modifications that can provide further improvement to efficiency and accuracy.

Parallel Computation of Unsteady Flows on a Network of Workstations

NASA Technical Reports Server (NTRS)

1997-01-01

Parallel computation of unsteady flows requires significant computational resources. The utilization of a network of workstations seems an efficient solution to the problem where large problems can be treated at a reasonable cost. This approach requires the solution of several problems: 1) the partitioning and distribution of the problem over a network of workstation, 2) efficient communication tools, 3) managing the system efficiently for a given problem. Of course, there is the question of the efficiency of any given numerical algorithm to such a computing system. NPARC code was chosen as a sample for the application. For the explicit version of the NPARC code both two- and three-dimensional problems were studied. Again both steady and unsteady problems were investigated. The issues studied as a part of the research program were: 1) how to distribute the data between the workstations, 2) how to compute and how to communicate at each node efficiently, 3) how to balance the load distribution. In the following, a summary of these activities is presented. Details of the work have been presented and published as referenced.

Computational performance of a smoothed particle hydrodynamics simulation for shared-memory parallel computing

NASA Astrophysics Data System (ADS)

Nishiura, Daisuke; Furuichi, Mikito; Sakaguchi, Hide

2015-09-01

The computational performance of a smoothed particle hydrodynamics (SPH) simulation is investigated for three types of current shared-memory parallel computer devices: many integrated core (MIC) processors, graphics processing units (GPUs), and multi-core CPUs. We are especially interested in efficient shared-memory allocation methods for each chipset, because the efficient data access patterns differ between compute unified device architecture (CUDA) programming for GPUs and OpenMP programming for MIC processors and multi-core CPUs. We first introduce several parallel implementation techniques for the SPH code, and then examine these on our target computer architectures to determine the most effective algorithms for each processor unit. In addition, we evaluate the effective computing performance and power efficiency of the SPH simulation on each architecture, as these are critical metrics for overall performance in a multi-device environment. In our benchmark test, the GPU is found to produce the best arithmetic performance as a standalone device unit, and gives the most efficient power consumption. The multi-core CPU obtains the most effective computing performance. The computational speed of the MIC processor on Xeon Phi approached that of two Xeon CPUs. This indicates that using MICs is an attractive choice for existing SPH codes on multi-core CPUs parallelized by OpenMP, as it gains computational acceleration without the need for significant changes to the source code.

Application of microarray analysis on computer cluster and cloud platforms.

PubMed

Bernau, C; Boulesteix, A-L; Knaus, J

2013-01-01

Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

Valuing uncertain cash flows from investments that enhance energy efficiency.

PubMed

Abadie, Luis M; Chamorro, José M; González-Eguino, Mikel

2013-02-15

There is a broad consensus that investments to enhance energy efficiency quickly pay for themselves in lower energy bills and spared emission allowances. However, investments that at first glance seem worthwhile usually are not undertaken. One of the plausible, non-excluding explanations is the numerous uncertainties that these investments face. This paper deals with the optimal time to invest in an energy efficiency enhancement at a facility already in place that consumes huge amounts of a fossil fuel (coal) and operates under carbon constraints. We follow the Real Options approach. Our model comprises three sources of uncertainty following different stochastic processes which allows for application in a broad range of settings. We assess the investment option by means of a three-dimensional binomial lattice. We compute the trigger investment cost, i.e., the threshold level below which immediate investment would be optimal. We analyze the major drivers of this decision thus aiming at the most promising policies in this regard. Copyright © 2012 Elsevier Ltd. All rights reserved.

Chance-constrained economic dispatch with renewable energy and storage

DOE PAGES

Cheng, Jianqiang; Chen, Richard Li-Yang; Najm, Habib N.; ...

2018-04-19

Increased penetration of renewables, along with uncertainties associated with them, have transformed how power systems are operated. High levels of uncertainty means that it is not longer possible to guarantee operational feasibility with certainty, instead constraints are required to be satisfied with high probability. We present a chance-constrained economic dispatch model that efficiently integrates energy storage and high renewable penetration to satisfy renewable portfolio requirements. Specifically, it is required that wind energy contributes at least a prespecified ratio of the total demand and that the scheduled wind energy is dispatchable with high probability. We develop an approximated partial sample averagemore » approximation (PSAA) framework to enable efficient solution of large-scale chanceconstrained economic dispatch problems. Computational experiments on the IEEE-24 bus system show that the proposed PSAA approach is more accurate, closer to the prescribed tolerance, and about 100 times faster than sample average approximation. Improved efficiency of our PSAA approach enables solution of WECC-240 system in minutes.« less

Chance-constrained economic dispatch with renewable energy and storage

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

Cheng, Jianqiang; Chen, Richard Li-Yang; Najm, Habib N.

Increased penetration of renewables, along with uncertainties associated with them, have transformed how power systems are operated. High levels of uncertainty means that it is not longer possible to guarantee operational feasibility with certainty, instead constraints are required to be satisfied with high probability. We present a chance-constrained economic dispatch model that efficiently integrates energy storage and high renewable penetration to satisfy renewable portfolio requirements. Specifically, it is required that wind energy contributes at least a prespecified ratio of the total demand and that the scheduled wind energy is dispatchable with high probability. We develop an approximated partial sample averagemore » approximation (PSAA) framework to enable efficient solution of large-scale chanceconstrained economic dispatch problems. Computational experiments on the IEEE-24 bus system show that the proposed PSAA approach is more accurate, closer to the prescribed tolerance, and about 100 times faster than sample average approximation. Improved efficiency of our PSAA approach enables solution of WECC-240 system in minutes.« less

An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT).

PubMed

Li, Ran; Duan, Xiaomeng; Li, Xu; He, Wei; Li, Yanling

2018-04-17

Aimed at a low-energy consumption of Green Internet of Things (IoT), this paper presents an energy-efficient compressive image coding scheme, which provides compressive encoder and real-time decoder according to Compressive Sensing (CS) theory. The compressive encoder adaptively measures each image block based on the block-based gradient field, which models the distribution of block sparse degree, and the real-time decoder linearly reconstructs each image block through a projection matrix, which is learned by Minimum Mean Square Error (MMSE) criterion. Both the encoder and decoder have a low computational complexity, so that they only consume a small amount of energy. Experimental results show that the proposed scheme not only has a low encoding and decoding complexity when compared with traditional methods, but it also provides good objective and subjective reconstruction qualities. In particular, it presents better time-distortion performance than JPEG. Therefore, the proposed compressive image coding is a potential energy-efficient scheme for Green IoT.

Efficient iteration in data-parallel programs with irregular and dynamically distributed data structures

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

Littlefield, R.J.

1990-02-01

To implement an efficient data-parallel program on a non-shared memory MIMD multicomputer, data and computations must be properly partitioned to achieve good load balance and locality of reference. Programs with irregular data reference patterns often require irregular partitions. Although good partitions may be easy to determine, they can be difficult or impossible to implement in programming languages that provide only regular data distributions, such as blocked or cyclic arrays. We are developing Onyx, a programming system that provides a shared memory model of distributed data structures and extends the concept of data distribution to include irregular and dynamic distributions. Thismore » provides a powerful means to specify irregular partitions. Perhaps surprisingly, programs using it can also execute efficiently. In this paper, we describe and evaluate the Onyx implementation of a model problem that repeatedly executes an irregular but fixed data reference pattern. On an NCUBE hypercube, the speed of the Onyx implementation is comparable to that of carefully handwritten message-passing code.« less

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

Uncertainty quantification-based robust aerodynamic optimization of laminar flow nacelle

NASA Astrophysics Data System (ADS)

Xiong, Neng; Tao, Yang; Liu, Zhiyong; Lin, Jun

2018-05-01

The aerodynamic performance of laminar flow nacelle is highly sensitive to uncertain working conditions, especially the surface roughness. An efficient robust aerodynamic optimization method on the basis of non-deterministic computational fluid dynamic (CFD) simulation and Efficient Global Optimization (EGO)algorithm was employed. A non-intrusive polynomial chaos method is used in conjunction with an existing well-verified CFD module to quantify the uncertainty propagation in the flow field. This paper investigates the roughness modeling behavior with the γ-Ret shear stress transport model including modeling flow transition and surface roughness effects. The roughness effects are modeled to simulate sand grain roughness. A Class-Shape Transformation-based parametrical description of the nacelle contour as part of an automatic design evaluation process is presented. A Design-of-Experiments (DoE) was performed and surrogate model by Kriging method was built. The new design nacelle process demonstrates that significant improvements of both mean and variance of the efficiency are achieved and the proposed method can be applied to laminar flow nacelle design successfully.

Development and application of a catchment scale pesticide fate and transport model for use in drinking water risk assessment.

PubMed

Pullan, S P; Whelan, M J; Rettino, J; Filby, K; Eyre, S; Holman, I P

2016-09-01

This paper describes the development and application of IMPT (Integrated Model for Pesticide Transport), a parameter-efficient tool for predicting diffuse-source pesticide concentrations in surface waters used for drinking water supply. The model was applied to a small UK headwater catchment with high frequency (8h) pesticide monitoring data and to five larger catchments (479-1653km(2)) with sampling approximately every 14days. Model performance was good for predictions of both flow (Nash Sutcliffe Efficiency generally >0.59 and PBIAS <10%) and pesticide concentrations, although low sampling frequency in the larger catchments is likely to mask the true episodic nature of exposure. The computational efficiency of the model, along with the fact that most of its parameters can be derived from existing national soil property data mean that it can be used to rapidly predict pesticide exposure in multiple surface water resources to support operational and strategic risk assessments. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Optimal size of stochastic Hodgkin-Huxley neuronal systems for maximal energy efficiency in coding pulse signals

NASA Astrophysics Data System (ADS)

Yu, Lianchun; Liu, Liwei

2014-03-01

The generation and conduction of action potentials (APs) represents a fundamental means of communication in the nervous system and is a metabolically expensive process. In this paper, we investigate the energy efficiency of neural systems in transferring pulse signals with APs. By analytically solving a bistable neuron model that mimics the AP generation with a particle crossing the barrier of a double well, we find the optimal number of ion channels that maximizes the energy efficiency of a neuron. We also investigate the energy efficiency of a neuron population in which the input pulse signals are represented with synchronized spikes and read out with a downstream coincidence detector neuron. We find an optimal number of neurons in neuron population, as well as the number of ion channels in each neuron that maximizes the energy efficiency. The energy efficiency also depends on the characters of the input signals, e.g., the pulse strength and the interpulse intervals. These results are confirmed by computer simulation of the stochastic Hodgkin-Huxley model with a detailed description of the ion channel random gating. We argue that the tradeoff between signal transmission reliability and energy cost may influence the size of the neural systems when energy use is constrained.

Optimal size of stochastic Hodgkin-Huxley neuronal systems for maximal energy efficiency in coding pulse signals.

PubMed

Yu, Lianchun; Liu, Liwei

2014-03-01

The generation and conduction of action potentials (APs) represents a fundamental means of communication in the nervous system and is a metabolically expensive process. In this paper, we investigate the energy efficiency of neural systems in transferring pulse signals with APs. By analytically solving a bistable neuron model that mimics the AP generation with a particle crossing the barrier of a double well, we find the optimal number of ion channels that maximizes the energy efficiency of a neuron. We also investigate the energy efficiency of a neuron population in which the input pulse signals are represented with synchronized spikes and read out with a downstream coincidence detector neuron. We find an optimal number of neurons in neuron population, as well as the number of ion channels in each neuron that maximizes the energy efficiency. The energy efficiency also depends on the characters of the input signals, e.g., the pulse strength and the interpulse intervals. These results are confirmed by computer simulation of the stochastic Hodgkin-Huxley model with a detailed description of the ion channel random gating. We argue that the tradeoff between signal transmission reliability and energy cost may influence the size of the neural systems when energy use is constrained.

Universal Linear Motor Driven Leg Press Dynamometer and Concept of Serial Stretch Loading.

PubMed

Hamar, Dušan

2015-08-24

Paper deals with backgrounds and principles of universal linear motor driven leg press dynamometer and concept of serial stretch loading. The device is based on two computer controlled linear motors mounted to the horizontal rails. As the motors can keep either constant resistance force in selected position or velocity in both directions, the system allows simulation of any mode of muscle contraction. In addition, it also can generate defined serial stretch stimuli in a form of repeated force peaks. This is achieved by short segments of reversed velocity (in concentric phase) or acceleration (in eccentric phase). Such stimuli, generated at the rate of 10 Hz, have proven to be a more efficient means for the improvement of rate of the force development. This capability not only affects performance in many sports, but also plays a substantial role in prevention of falls and their consequences. Universal linear motor driven and computer controlled dynamometer with its unique feature to generate serial stretch stimuli seems to be an efficient and useful tool for enhancing strength training effects on neuromuscular function not only in athletes, but as well as in senior population and rehabilitation patients.

A forward-advancing wave expansion method for numerical solution of large-scale sound propagation problems

NASA Astrophysics Data System (ADS)

Rolla, L. Barrera; Rice, H. J.

2006-09-01

In this paper a "forward-advancing" field discretization method suitable for solving the Helmholtz equation in large-scale problems is proposed. The forward wave expansion method (FWEM) is derived from a highly efficient discretization procedure based on interpolation of wave functions known as the wave expansion method (WEM). The FWEM computes the propagated sound field by means of an exclusively forward advancing solution, neglecting the backscattered field. It is thus analogous to methods such as the (one way) parabolic equation method (PEM) (usually discretized using standard finite difference or finite element methods). These techniques do not require the inversion of large system matrices and thus enable the solution of large-scale acoustic problems where backscatter is not of interest. Calculations using FWEM are presented for two propagation problems and comparisons to data computed with analytical and theoretical solutions and show this forward approximation to be highly accurate. Examples of sound propagation over a screen in upwind and downwind refracting atmospheric conditions at low nodal spacings (0.2 per wavelength in the propagation direction) are also included to demonstrate the flexibility and efficiency of the method.

Coarse-grained models using local-density potentials optimized with the relative entropy: Application to implicit solvation

NASA Astrophysics Data System (ADS)

Sanyal, Tanmoy; Shell, M. Scott

2016-07-01

Bottom-up multiscale techniques are frequently used to develop coarse-grained (CG) models for simulations at extended length and time scales but are often limited by a compromise between computational efficiency and accuracy. The conventional approach to CG nonbonded interactions uses pair potentials which, while computationally efficient, can neglect the inherently multibody contributions of the local environment of a site to its energy, due to degrees of freedom that were coarse-grained out. This effect often causes the CG potential to depend strongly on the overall system density, composition, or other properties, which limits its transferability to states other than the one at which it was parameterized. Here, we propose to incorporate multibody effects into CG potentials through additional nonbonded terms, beyond pair interactions, that depend in a mean-field manner on local densities of different atomic species. This approach is analogous to embedded atom and bond-order models that seek to capture multibody electronic effects in metallic systems. We show that the relative entropy coarse-graining framework offers a systematic route to parameterizing such local density potentials. We then characterize this approach in the development of implicit solvation strategies for interactions between model hydrophobes in an aqueous environment.

Computational and experimental study of airflow around a fan powered UVGI lamp

NASA Astrophysics Data System (ADS)

Kaligotla, Srikar; Tavakoli, Behtash; Glauser, Mark; Ahmadi, Goodarz

2011-11-01

The quality of indoor air environment is very important for improving the health of occupants and reducing personal exposure to hazardous pollutants. An effective way of controlling air quality is by eliminating the airborne bacteria and viruses or by reducing their emissions. Ultraviolet Germicidal Irradiation (UVGI) lamps can effectively reduce these bio-contaminants in an indoor environment, but the efficiency of these systems depends on airflow in and around the device. UVGI lamps would not be as effective in stagnant environments as they would be when the moving air brings the bio-contaminant in their irradiation region. Introducing a fan into the UVGI system would augment the efficiency of the system's kill rate. Airflows in ventilated spaces are quite complex due to the vast range of length and velocity scales. The purpose of this research is to study these complex airflows using CFD techniques and validate computational model with airflow measurements around the device using Particle Image Velocimetry measurements. The experimental results including mean velocities, length scales and RMS values of fluctuating velocities are used in the CFD validation. Comparison of these data at different locations around the device with the CFD model predictions are performed and good agreement was observed.

Accounting for receptor flexibility and enhanced sampling methods in computer-aided drug design.

PubMed

Sinko, William; Lindert, Steffen; McCammon, J Andrew

2013-01-01

Protein flexibility plays a major role in biomolecular recognition. In many cases, it is not obvious how molecular structure will change upon association with other molecules. In proteins, these changes can be major, with large deviations in overall backbone structure, or they can be more subtle as in a side-chain rotation. Either way the algorithms that predict the favorability of biomolecular association require relatively accurate predictions of the bound structure to give an accurate assessment of the energy involved in association. Here, we review a number of techniques that have been proposed to accommodate receptor flexibility in the simulation of small molecules binding to protein receptors. We investigate modifications to standard rigid receptor docking algorithms and also explore enhanced sampling techniques, and the combination of free energy calculations and enhanced sampling techniques. The understanding and allowance for receptor flexibility are helping to make computer simulations of ligand protein binding more accurate. These developments may help improve the efficiency of drug discovery and development. Efficiency will be essential as we begin to see personalized medicine tailored to individual patients, which means specific drugs are needed for each patient's genetic makeup. © 2012 John Wiley & Sons A/S.

Microphysical and optical properties of aerosol particles in urban zone during ESCOMPTE

NASA Astrophysics Data System (ADS)

Mallet, M.; Roger, J. C.; Despiau, S.; Dubovik, O.; Putaud, J. P.

2003-10-01

Microphysical and optical properties of the main aerosol species on a peri-urban site have been investigated during the ESCOMPTE experiment. Ammonium sulfate (AS), nitrate (N), black carbon (BC), particulate organic matter (POM), sea salt (SS) and mineral aerosol (D) size distributions have been used, associated with their refractive index, to compute, from the Mie theory, the key radiative aerosol properties as the extinction coefficient Kext, the mass extinction efficiencies σext, the single scattering albedo ω0 and the asymmetry parameter g at the wavelength of 550 nm. Optical computations show that 90% of the light extinction is due to anthropogenic aerosol and only 10% is due to natural aerosol (SS and D). 44±6% of the extinction is due to (AS) and 40±6% to carbonaceous particles (20±4% to BC and 21±4% to POM). Nitrate aerosol has a weak contribution of 5±2%. Computations of the mass extinction efficiencies σext, single scattering albedo ω0 and asymmetry parameter g indicate that the optical properties of the anthropogenic aerosol are often quite different from those yet published and generally used in global models. For example, the (AS) mean specific mass extinction presents a large difference with the value classically adopted at low relative humidity ( h<60%) (2.6±0.5 instead of 6 m 2 g -1 at 550 nm). The optical properties of the total aerosol layer, including all the aerosol species, indicate a mean observed single-scattering albedo ω0=0.85±0.05, leading to an important absorption of the solar radiation and an asymmetry parameter g=0.59±0.05 which are in a reasonably good agreements with the AERONET retrieval of ω0 (=0.86±0.05) and g (=0.64±0.05) at this wavelength.

SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering

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

Iliopoulos, AS; Sun, X; Floros, D

Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well asmore » histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial signal/noise variations. An efficient multi-scale computational mechanism is developed to curtail processing latency. Spatially adaptive filtering may impact subsequent processing tasks such as reconstruction and numerical gradient computations for deformable registration. NIH Grant No. R01-184173.« less

Greedy algorithms for diffuse optical tomography reconstruction

NASA Astrophysics Data System (ADS)

Dileep, B. P. V.; Das, Tapan; Dutta, Pranab K.

2018-03-01

Diffuse optical tomography (DOT) is a noninvasive imaging modality that reconstructs the optical parameters of a highly scattering medium. However, the inverse problem of DOT is ill-posed and highly nonlinear due to the zig-zag propagation of photons that diffuses through the cross section of tissue. The conventional DOT imaging methods iteratively compute the solution of forward diffusion equation solver which makes the problem computationally expensive. Also, these methods fail when the geometry is complex. Recently, the theory of compressive sensing (CS) has received considerable attention because of its efficient use in biomedical imaging applications. The objective of this paper is to solve a given DOT inverse problem by using compressive sensing framework and various Greedy algorithms such as orthogonal matching pursuit (OMP), compressive sampling matching pursuit (CoSaMP), and stagewise orthogonal matching pursuit (StOMP), regularized orthogonal matching pursuit (ROMP) and simultaneous orthogonal matching pursuit (S-OMP) have been studied to reconstruct the change in the absorption parameter i.e, Δα from the boundary data. Also, the Greedy algorithms have been validated experimentally on a paraffin wax rectangular phantom through a well designed experimental set up. We also have studied the conventional DOT methods like least square method and truncated singular value decomposition (TSVD) for comparison. One of the main features of this work is the usage of less number of source-detector pairs, which can facilitate the use of DOT in routine applications of screening. The performance metrics such as mean square error (MSE), normalized mean square error (NMSE), structural similarity index (SSIM), and peak signal to noise ratio (PSNR) have been used to evaluate the performance of the algorithms mentioned in this paper. Extensive simulation results confirm that CS based DOT reconstruction outperforms the conventional DOT imaging methods in terms of computational efficiency. The main advantage of this study is that the forward diffusion equation solver need not be repeatedly solved.

Efficient methods for implementation of multi-level nonrigid mass-preserving image registration on GPUs and multi-threaded CPUs.

PubMed

Ellingwood, Nathan D; Yin, Youbing; Smith, Matthew; Lin, Ching-Long

2016-04-01

Faster and more accurate methods for registration of images are important for research involved in conducting population-based studies that utilize medical imaging, as well as improvements for use in clinical applications. We present a novel computation- and memory-efficient multi-level method on graphics processing units (GPU) for performing registration of two computed tomography (CT) volumetric lung images. We developed a computation- and memory-efficient Diffeomorphic Multi-level B-Spline Transform Composite (DMTC) method to implement nonrigid mass-preserving registration of two CT lung images on GPU. The framework consists of a hierarchy of B-Spline control grids of increasing resolution. A similarity criterion known as the sum of squared tissue volume difference (SSTVD) was adopted to preserve lung tissue mass. The use of SSTVD consists of the calculation of the tissue volume, the Jacobian, and their derivatives, which makes its implementation on GPU challenging due to memory constraints. The use of the DMTC method enabled reduced computation and memory storage of variables with minimal communication between GPU and Central Processing Unit (CPU) due to ability to pre-compute values. The method was assessed on six healthy human subjects. Resultant GPU-generated displacement fields were compared against the previously validated CPU counterpart fields, showing good agreement with an average normalized root mean square error (nRMS) of 0.044±0.015. Runtime and performance speedup are compared between single-threaded CPU, multi-threaded CPU, and GPU algorithms. Best performance speedup occurs at the highest resolution in the GPU implementation for the SSTVD cost and cost gradient computations, with a speedup of 112 times that of the single-threaded CPU version and 11 times over the twelve-threaded version when considering average time per iteration using a Nvidia Tesla K20X GPU. The proposed GPU-based DMTC method outperforms its multi-threaded CPU version in terms of runtime. Total registration time reduced runtime to 2.9min on the GPU version, compared to 12.8min on twelve-threaded CPU version and 112.5min on a single-threaded CPU. Furthermore, the GPU implementation discussed in this work can be adapted for use of other cost functions that require calculation of the first derivatives. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Combining neural networks and signed particles to simulate quantum systems more efficiently

NASA Astrophysics Data System (ADS)

Sellier, Jean Michel

2018-04-01

Recently a new formulation of quantum mechanics has been suggested which describes systems by means of ensembles of classical particles provided with a sign. This novel approach mainly consists of two steps: the computation of the Wigner kernel, a multi-dimensional function describing the effects of the potential over the system, and the field-less evolution of the particles which eventually create new signed particles in the process. Although this method has proved to be extremely advantageous in terms of computational resources - as a matter of fact it is able to simulate in a time-dependent fashion many-body systems on relatively small machines - the Wigner kernel can represent the bottleneck of simulations of certain systems. Moreover, storing the kernel can be another issue as the amount of memory needed is cursed by the dimensionality of the system. In this work, we introduce a new technique which drastically reduces the computation time and memory requirement to simulate time-dependent quantum systems which is based on the use of an appropriately tailored neural network combined with the signed particle formalism. In particular, the suggested neural network is able to compute efficiently and reliably the Wigner kernel without any training as its entire set of weights and biases is specified by analytical formulas. As a consequence, the amount of memory for quantum simulations radically drops since the kernel does not need to be stored anymore as it is now computed by the neural network itself, only on the cells of the (discretized) phase-space which are occupied by particles. As its is clearly shown in the final part of this paper, not only this novel approach drastically reduces the computational time, it also remains accurate. The author believes this work opens the way towards effective design of quantum devices, with incredible practical implications.

A frequency domain linearized Navier-Stokes equations approach to acoustic propagation in flow ducts with sharp edges.

PubMed

Kierkegaard, Axel; Boij, Susann; Efraimsson, Gunilla

2010-02-01

Acoustic wave propagation in flow ducts is commonly modeled with time-domain non-linear Navier-Stokes equation methodologies. To reduce computational effort, investigations of a linearized approach in frequency domain are carried out. Calculations of sound wave propagation in a straight duct are presented with an orifice plate and a mean flow present. Results of transmission and reflections at the orifice are presented on a two-port scattering matrix form and are compared to measurements with good agreement. The wave propagation is modeled with a frequency domain linearized Navier-Stokes equation methodology. This methodology is found to be efficient for cases where the acoustic field does not alter the mean flow field, i.e., when whistling does not occur.

Solution of elliptic PDEs by fast Poisson solvers using a local relaxation factor

NASA Technical Reports Server (NTRS)

Chang, Sin-Chung

1986-01-01

A large class of two- and three-dimensional, nonseparable elliptic partial differential equations (PDEs) is presently solved by means of novel one-step (D'Yakanov-Gunn) and two-step (accelerated one-step) iterative procedures, using a local, discrete Fourier analysis. In addition to being easily implemented and applicable to a variety of boundary conditions, these procedures are found to be computationally efficient on the basis of the results of numerical comparison with other established methods, which lack the present one's: (1) insensitivity to grid cell size and aspect ratio, and (2) ease of convergence rate estimation by means of the coefficient of the PDE being solved. The two-step procedure is numerically demonstrated to outperform the one-step procedure in the case of PDEs with variable coefficients.

In Silico Template Selection of Short Antimicrobial Peptide Viscotoxin for Improving Its Antimicrobial Efficiency in Development of Potential Therapeutic Drugs.

PubMed

Senthilkumar, B; Rajasekaran, R

2017-03-01

Rapid increase in antibiotic resistance has posed a worldwide threat, due to increased mortality, morbidity, and expenditure caused by antibiotic-resistant microbes. Recent development of the antimicrobial peptides like viscotoxin (Vt) has been successfully comprehended as a substitute for classical antibiotics. A structurally stable peptide, Vt can enhance antimicrobial property and can be used for various developmental purposes. Thus, structural stability among the antimicrobial peptides, Vt A1 (3C8P), A2 (1JMN), A3 (1ED0), B (1JMP), and C (1ORL) of Viscus album was computationally analyzed. In specific, the static confirmation of VtA3 showed high number of intramolecular interactions, along with an increase in hydrophobicity than others comparatively. Further, conformational sampling was used to analyze various geometrical parameters such as root mean square deviation, root mean square fluctuation, radius of gyration, and ovality which also revealed the structural stability of VtA3. Moreover, the statistically validated contours of surface area, lipophilicity, and distance constraints of disulfide bonds also supported the priority of VtA3 with respect to stability. Finally, the functional activity of peptides was accessed by computing their free energy of membrane association and membrane interactions, which defined VtA3 as functionally stable. Currently, peptide-based antibiotics and nanoparticles have attracted the pharmaceutical industries for their potential therapeutic applications. Thereby, it is proposed that viscotoxin A3 (1ED0) could be used as a preeminent template for scaffolding potentially efficient antimicrobial peptide-based drugs and nanomaterials in future.

A critical analysis of the accuracy of several numerical techniques for combustion kinetic rate equations

NASA Technical Reports Server (NTRS)

Radhadrishnan, Krishnan

1993-01-01

A detailed analysis of the accuracy of several techniques recently developed for integrating stiff ordinary differential equations is presented. The techniques include two general-purpose codes EPISODE and LSODE developed for an arbitrary system of ordinary differential equations, and three specialized codes CHEMEQ, CREK1D, and GCKP4 developed specifically to solve chemical kinetic rate equations. The accuracy study is made by application of these codes to two practical combustion kinetics problems. Both problems describe adiabatic, homogeneous, gas-phase chemical reactions at constant pressure, and include all three combustion regimes: induction, heat release, and equilibration. To illustrate the error variation in the different combustion regimes the species are divided into three types (reactants, intermediates, and products), and error versus time plots are presented for each species type and the temperature. These plots show that CHEMEQ is the most accurate code during induction and early heat release. During late heat release and equilibration, however, the other codes are more accurate. A single global quantity, a mean integrated root-mean-square error, that measures the average error incurred in solving the complete problem is used to compare the accuracy of the codes. Among the codes examined, LSODE is the most accurate for solving chemical kinetics problems. It is also the most efficient code, in the sense that it requires the least computational work to attain a specified accuracy level. An important finding is that use of the algebraic enthalpy conservation equation to compute the temperature can be more accurate and efficient than integrating the temperature differential equation.

A hybrid finite element - statistical energy analysis approach to robust sound transmission modeling

NASA Astrophysics Data System (ADS)

Reynders, Edwin; Langley, Robin S.; Dijckmans, Arne; Vermeir, Gerrit

2014-09-01

When considering the sound transmission through a wall in between two rooms, in an important part of the audio frequency range, the local response of the rooms is highly sensitive to uncertainty in spatial variations in geometry, material properties and boundary conditions, which have a wave scattering effect, while the local response of the wall is rather insensitive to such uncertainty. For this mid-frequency range, a computationally efficient modeling strategy is adopted that accounts for this uncertainty. The partitioning wall is modeled deterministically, e.g. with finite elements. The rooms are modeled in a very efficient, nonparametric stochastic way, as in statistical energy analysis. All components are coupled by means of a rigorous power balance. This hybrid strategy is extended so that the mean and variance of the sound transmission loss can be computed as well as the transition frequency that loosely marks the boundary between low- and high-frequency behavior of a vibro-acoustic component. The method is first validated in a simulation study, and then applied for predicting the airborne sound insulation of a series of partition walls of increasing complexity: a thin plastic plate, a wall consisting of gypsum blocks, a thicker masonry wall and a double glazing. It is found that the uncertainty caused by random scattering is important except at very high frequencies, where the modal overlap of the rooms is very high. The results are compared with laboratory measurements, and both are found to agree within the prediction uncertainty in the considered frequency range.

An Intelligent Pictorial Information System

NASA Astrophysics Data System (ADS)

Lee, Edward T.; Chang, B.

1987-05-01

In examining the history of computer application, we discover that early computer systems were developed primarily for applications related to scientific computation, as in weather prediction, aerospace applications, and nuclear physics applications. At this stage, the computer system served as a big calculator to perform, in the main, manipulation of numbers. Then it was found that computer systems could also be used for business applications, information storage and retrieval, word processing, and report generation. The history of computer application is summarized in Table I. The complexity of pictures makes picture processing much more difficult than number and alphanumerical processing. Therefore, new techniques, new algorithms, and above all, new pictorial knowledge, [1] are needed to overcome the limitatins of existing computer systems. New frontiers in designing computer systems are the ways to handle the representation,[2,3] classification, manipulation, processing, storage, and retrieval of pictures. Especially, the ways to deal with similarity measures and the meaning of the word "approximate" and the phrase "approximate reasoning" are an important and an indispensable part of an intelligent pictorial information system. [4,5] The main objective of this paper is to investigate the mathematical foundation for the effective organization and efficient retrieval of pictures in similarity-directed pictorial databases, [6] based on similarity retrieval techniques [7] and fuzzy languages [8]. The main advantage of this approach is that similar pictures are stored logically close to each other by using quantitative similarity measures. Thus, for answering queries, the amount of picture data needed to be searched can be reduced and the retrieval time can be improved. In addition, in a pictorial database, very often it is desired to find pictures (or feature vectors, histograms, etc.) that are most similar to or most dissimilar [9] to a test picture (or feature vector). Using similarity measures, one can not only store similar pictures logically or physically close to each other in order to improve retrieval or updating efficiency, one can also use such similarity measures to answer fuzzy queries involving nonexact retrieval conditions. In this paper, similarity directed pictorial databases involving geometric figures, chromosome images, [10] leukocyte images, cardiomyopathy images, and satellite images [11] are presented as illustrative examples.

Dynamic Load-Balancing for Distributed Heterogeneous Computing of Parallel CFD Problems

NASA Technical Reports Server (NTRS)

Ecer, A.; Chien, Y. P.; Boenisch, T.; Akay, H. U.

2000-01-01

The developed methodology is aimed at improving the efficiency of executing block-structured algorithms on parallel, distributed, heterogeneous computers. The basic approach of these algorithms is to divide the flow domain into many sub- domains called blocks, and solve the governing equations over these blocks. Dynamic load balancing problem is defined as the efficient distribution of the blocks among the available processors over a period of several hours of computations. In environments with computers of different architecture, operating systems, CPU speed, memory size, load, and network speed, balancing the loads and managing the communication between processors becomes crucial. Load balancing software tools for mutually dependent parallel processes have been created to efficiently utilize an advanced computation environment and algorithms. These tools are dynamic in nature because of the chances in the computer environment during execution time. More recently, these tools were extended to a second operating system: NT. In this paper, the problems associated with this application will be discussed. Also, the developed algorithms were combined with the load sharing capability of LSF to efficiently utilize workstation clusters for parallel computing. Finally, results will be presented on running a NASA based code ADPAC to demonstrate the developed tools for dynamic load balancing.

Efficient conjugate gradient algorithms for computation of the manipulator forward dynamics

NASA Technical Reports Server (NTRS)

Fijany, Amir; Scheid, Robert E.

1989-01-01

The applicability of conjugate gradient algorithms for computation of the manipulator forward dynamics is investigated. The redundancies in the previously proposed conjugate gradient algorithm are analyzed. A new version is developed which, by avoiding these redundancies, achieves a significantly greater efficiency. A preconditioned conjugate gradient algorithm is also presented. A diagonal matrix whose elements are the diagonal elements of the inertia matrix is proposed as the preconditioner. In order to increase the computational efficiency, an algorithm is developed which exploits the synergism between the computation of the diagonal elements of the inertia matrix and that required by the conjugate gradient algorithm.

Least squares QR-based decomposition provides an efficient way of computing optimal regularization parameter in photoacoustic tomography.

PubMed

Shaw, Calvin B; Prakash, Jaya; Pramanik, Manojit; Yalavarthy, Phaneendra K

2013-08-01

A computationally efficient approach that computes the optimal regularization parameter for the Tikhonov-minimization scheme is developed for photoacoustic imaging. This approach is based on the least squares-QR decomposition which is a well-known dimensionality reduction technique for a large system of equations. It is shown that the proposed framework is effective in terms of quantitative and qualitative reconstructions of initial pressure distribution enabled via finding an optimal regularization parameter. The computational efficiency and performance of the proposed method are shown using a test case of numerical blood vessel phantom, where the initial pressure is exactly known for quantitative comparison.

Actions for productivity improvement in crew training

NASA Technical Reports Server (NTRS)

Miller, G. E.

1985-01-01

Improvement of the productivity of astronaut crew instructors in the Space Shuttle program and beyond is proposed. It is suggested that instructor certification plans should be established to shorten the time required for trainers to develop their skills and improve their ability to convey those skills. Members of the training cadre should be thoroughly cross trained in their task. This provides better understanding of the overall task and greater flexibility in instructor utilization. Improved facility access will give instructors the benefit of practical application experience. Former crews should be integrated into the training of upcoming crews to bridge some of the gap between simulated conditions and the real world. The information contained in lengthy and complex training manuals can be presented more clearly and efficiently as computer lessons. The illustration, animation and interactive capabilities of the computer combine an effective means of explanation.

Micro-computed tomography imaging and analysis in developmental biology and toxicology.

PubMed

Wise, L David; Winkelmann, Christopher T; Dogdas, Belma; Bagchi, Ansuman

2013-06-01

Micro-computed tomography (micro-CT) is a high resolution imaging technique that has expanded and strengthened in use since it was last reviewed in this journal in 2004. The technology has expanded to include more detailed analysis of bone, as well as soft tissues, by use of various contrast agents. It is increasingly applied to questions in developmental biology and developmental toxicology. Relatively high-throughput protocols now provide a powerful and efficient means to evaluate embryos and fetuses subjected to genetic manipulations or chemical exposures. This review provides an overview of the technology, including scanning, reconstruction, visualization, segmentation, and analysis of micro-CT generated images. This is followed by a review of more recent applications of the technology in some common laboratory species that highlight the diverse issues that can be addressed. Copyright © 2013 Wiley Periodicals, Inc.

Operating room integration and telehealth.

PubMed

Bucholz, Richard D; Laycock, Keith A; McDurmont, Leslie

2011-01-01

The increasing use of advanced automated and computer-controlled systems and devices in surgical procedures has resulted in problems arising from the crowding of the operating room with equipment and the incompatible control and communication standards associated with each system. This lack of compatibility between systems and centralized control means that the surgeon is frequently required to interact with multiple computer interfaces in order to obtain updates and exert control over the various devices at his disposal. To reduce this complexity and provide the surgeon with more complete and precise control of the operating room systems, a unified interface and communication network has been developed. In addition to improving efficiency, this network also allows the surgeon to grant remote access to consultants and observers at other institutions, enabling experts to participate in the procedure without having to travel to the site.