Using MATLAB Software on the Peregrine System | High-Performance Computing

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| NREL MATLAB Software on the Peregrine System Using MATLAB Software on the Peregrine System Learn how to use MATLAB software on the Peregrine system. Running MATLAB in Batch Mode Using the node. Understanding Versions and Licenses Learn about the MATLAB software versions and licenses

An introduction to MATLAB.

PubMed

Sobie, Eric A

2011-09-13

This two-part lecture introduces students to the scientific computing language MATLAB. Prior computer programming experience is not required. The lectures present basic concepts of computer programming logic that tend to cause difficulties for beginners in addition to concepts that relate specifically to the MATLAB language syntax. The lectures begin with a discussion of vectors, matrices, and arrays. Because many types of biological data, such as fluorescence images and DNA microarrays, are stored as two-dimensional objects, processing these data is a form of array manipulation, and MATLAB is especially adept at handling such array objects. The students are introduced to basic commands in MATLAB, as well as built-in functions that provide useful shortcuts. The second lecture focuses on the differences between MATLAB scripts and MATLAB functions and describes when one method of programming organization might be preferable to the other. The principles are illustrated through the analysis of experimental data, specifically measurements of intracellular calcium concentration in live cells obtained using confocal microscopy.

An Introduction to MATLAB

PubMed Central

Sobie, Eric A.

2014-01-01

This two-part lecture introduces students to the scientific computing language MATLAB. Prior computer programming experience is not required. The lectures present basic concepts of computer programming logic that tend to cause difficulties for beginners in addition to concepts that relate specifically to the MATLAB language syntax. The lectures begin with a discussion of vectors, matrices, and arrays. Because many types of biological data, such as fluorescence images and DNA microarrays, are stored as two-dimensional objects, processing these data is a form of array manipulation, and MATLAB is especially adept at handling such array objects. The students are introduced to basic commands in MATLAB, as well as built-in functions that provide useful shortcuts. The second lecture focuses on the differences between MATLAB scripts and MATLAB functions and describes when one method of programming organization might be preferable to the other. The principles are illustrated through the analysis of experimental data, specifically measurements of intracellular calcium concentration in live cells obtained using confocal microscopy. PMID:21934110

Slow Orbit Feedback at the ALS Using Matlab

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

Portmann, G.

1999-03-25

The third generation Advanced Light Source (ALS) produces extremely bright and finely focused photon beams using undulatory, wigglers, and bend magnets. In order to position the photon beams accurately, a slow global orbit feedback system has been developed. The dominant causes of orbit motion at the ALS are temperature variation and insertion device motion. This type of motion can be removed using slow global orbit feedback with a data rate of a few Hertz. The remaining orbit motion in the ALS is only 1-3 micron rms. Slow orbit feedback does not require high computational throughput. At the ALS, the globalmore » orbit feedback algorithm, based on the singular valued decomposition method, is coded in MATLAB and runs on a control room workstation. Using the MATLAB environment to develop, test, and run the storage ring control algorithms has proven to be a fast and efficient way to operate the ALS.« less

OMPC: an Open-Source MATLAB-to-Python Compiler.

PubMed

Jurica, Peter; van Leeuwen, Cees

2009-01-01

Free access to scientific information facilitates scientific progress. Open-access scientific journals are a first step in this direction; a further step is to make auxiliary and supplementary materials that accompany scientific publications, such as methodological procedures and data-analysis tools, open and accessible to the scientific community. To this purpose it is instrumental to establish a software base, which will grow toward a comprehensive free and open-source language of technical and scientific computing. Endeavors in this direction are met with an important obstacle. MATLAB((R)), the predominant computation tool in many fields of research, is a closed-source commercial product. To facilitate the transition to an open computation platform, we propose Open-source MATLAB((R))-to-Python Compiler (OMPC), a platform that uses syntax adaptation and emulation to allow transparent import of existing MATLAB((R)) functions into Python programs. The imported MATLAB((R)) modules will run independently of MATLAB((R)), relying on Python's numerical and scientific libraries. Python offers a stable and mature open source platform that, in many respects, surpasses commonly used, expensive commercial closed source packages. The proposed software will therefore facilitate the transparent transition towards a free and general open-source lingua franca for scientific computation, while enabling access to the existing methods and algorithms of technical computing already available in MATLAB((R)). OMPC is available at http://ompc.juricap.com.

An algorithm for fast elastic wave simulation using a vectorized finite difference operator

NASA Astrophysics Data System (ADS)

Malkoti, Ajay; Vedanti, Nimisha; Tiwari, Ram Krishna

2018-07-01

Modern geophysical imaging techniques exploit the full wavefield information which can be simulated numerically. These numerical simulations are computationally expensive due to several factors, such as a large number of time steps and nodes, big size of the derivative stencil and huge model size. Besides these constraints, it is also important to reformulate the numerical derivative operator for improved efficiency. In this paper, we have introduced a vectorized derivative operator over the staggered grid with shifted coordinate systems. The operator increases the efficiency of simulation by exploiting the fact that each variable can be represented in the form of a matrix. This operator allows updating all nodes of a variable defined on the staggered grid, in a manner similar to the collocated grid scheme and thereby reducing the computational run-time considerably. Here we demonstrate an application of this operator to simulate the seismic wave propagation in elastic media (Marmousi model), by discretizing the equations on a staggered grid. We have compared the performance of this operator on three programming languages, which reveals that it can increase the execution speed by a factor of at least 2-3 times for FORTRAN and MATLAB; and nearly 100 times for Python. We have further carried out various tests in MATLAB to analyze the effect of model size and the number of time steps on total simulation run-time. We find that there is an additional, though small, computational overhead for each step and it depends on total number of time steps used in the simulation. A MATLAB code package, 'FDwave', for the proposed simulation scheme is available upon request.

mGrid: A load-balanced distributed computing environment for the remote execution of the user-defined Matlab code

PubMed Central

Karpievitch, Yuliya V; Almeida, Jonas S

2006-01-01

Background Matlab, a powerful and productive language that allows for rapid prototyping, modeling and simulation, is widely used in computational biology. Modeling and simulation of large biological systems often require more computational resources then are available on a single computer. Existing distributed computing environments like the Distributed Computing Toolbox, MatlabMPI, Matlab*G and others allow for the remote (and possibly parallel) execution of Matlab commands with varying support for features like an easy-to-use application programming interface, load-balanced utilization of resources, extensibility over the wide area network, and minimal system administration skill requirements. However, all of these environments require some level of access to participating machines to manually distribute the user-defined libraries that the remote call may invoke. Results mGrid augments the usual process distribution seen in other similar distributed systems by adding facilities for user code distribution. mGrid's client-side interface is an easy-to-use native Matlab toolbox that transparently executes user-defined code on remote machines (i.e. the user is unaware that the code is executing somewhere else). Run-time variables are automatically packed and distributed with the user-defined code and automated load-balancing of remote resources enables smooth concurrent execution. mGrid is an open source environment. Apart from the programming language itself, all other components are also open source, freely available tools: light-weight PHP scripts and the Apache web server. Conclusion Transparent, load-balanced distribution of user-defined Matlab toolboxes and rapid prototyping of many simple parallel applications can now be done with a single easy-to-use Matlab command. Because mGrid utilizes only Matlab, light-weight PHP scripts and the Apache web server, installation and configuration are very simple. Moreover, the web-based infrastructure of mGrid allows for it to be easily extensible over the Internet. PMID:16539707

mGrid: a load-balanced distributed computing environment for the remote execution of the user-defined Matlab code.

PubMed

Karpievitch, Yuliya V; Almeida, Jonas S

2006-03-15

Matlab, a powerful and productive language that allows for rapid prototyping, modeling and simulation, is widely used in computational biology. Modeling and simulation of large biological systems often require more computational resources then are available on a single computer. Existing distributed computing environments like the Distributed Computing Toolbox, MatlabMPI, Matlab*G and others allow for the remote (and possibly parallel) execution of Matlab commands with varying support for features like an easy-to-use application programming interface, load-balanced utilization of resources, extensibility over the wide area network, and minimal system administration skill requirements. However, all of these environments require some level of access to participating machines to manually distribute the user-defined libraries that the remote call may invoke. mGrid augments the usual process distribution seen in other similar distributed systems by adding facilities for user code distribution. mGrid's client-side interface is an easy-to-use native Matlab toolbox that transparently executes user-defined code on remote machines (i.e. the user is unaware that the code is executing somewhere else). Run-time variables are automatically packed and distributed with the user-defined code and automated load-balancing of remote resources enables smooth concurrent execution. mGrid is an open source environment. Apart from the programming language itself, all other components are also open source, freely available tools: light-weight PHP scripts and the Apache web server. Transparent, load-balanced distribution of user-defined Matlab toolboxes and rapid prototyping of many simple parallel applications can now be done with a single easy-to-use Matlab command. Because mGrid utilizes only Matlab, light-weight PHP scripts and the Apache web server, installation and configuration are very simple. Moreover, the web-based infrastructure of mGrid allows for it to be easily extensible over the Internet.

Sampling and sensitivity analyses tools (SaSAT) for computational modelling

PubMed Central

Hoare, Alexander; Regan, David G; Wilson, David P

2008-01-01

SaSAT (Sampling and Sensitivity Analysis Tools) is a user-friendly software package for applying uncertainty and sensitivity analyses to mathematical and computational models of arbitrary complexity and context. The toolbox is built in Matlab®, a numerical mathematical software package, and utilises algorithms contained in the Matlab® Statistics Toolbox. However, Matlab® is not required to use SaSAT as the software package is provided as an executable file with all the necessary supplementary files. The SaSAT package is also designed to work seamlessly with Microsoft Excel but no functionality is forfeited if that software is not available. A comprehensive suite of tools is provided to enable the following tasks to be easily performed: efficient and equitable sampling of parameter space by various methodologies; calculation of correlation coefficients; regression analysis; factor prioritisation; and graphical output of results, including response surfaces, tornado plots, and scatterplots. Use of SaSAT is exemplified by application to a simple epidemic model. To our knowledge, a number of the methods available in SaSAT for performing sensitivity analyses have not previously been used in epidemiological modelling and their usefulness in this context is demonstrated. PMID:18304361

Accelerating Computation of DCM for ERP in MATLAB by External Function Calls to the GPU.

PubMed

Wang, Wei-Jen; Hsieh, I-Fan; Chen, Chun-Chuan

2013-01-01

This study aims to improve the performance of Dynamic Causal Modelling for Event Related Potentials (DCM for ERP) in MATLAB by using external function calls to a graphics processing unit (GPU). DCM for ERP is an advanced method for studying neuronal effective connectivity. DCM utilizes an iterative procedure, the expectation maximization (EM) algorithm, to find the optimal parameters given a set of observations and the underlying probability model. As the EM algorithm is computationally demanding and the analysis faces possible combinatorial explosion of models to be tested, we propose a parallel computing scheme using the GPU to achieve a fast estimation of DCM for ERP. The computation of DCM for ERP is dynamically partitioned and distributed to threads for parallel processing, according to the DCM model complexity and the hardware constraints. The performance efficiency of this hardware-dependent thread arrangement strategy was evaluated using the synthetic data. The experimental data were used to validate the accuracy of the proposed computing scheme and quantify the time saving in practice. The simulation results show that the proposed scheme can accelerate the computation by a factor of 155 for the parallel part. For experimental data, the speedup factor is about 7 per model on average, depending on the model complexity and the data. This GPU-based implementation of DCM for ERP gives qualitatively the same results as the original MATLAB implementation does at the group level analysis. In conclusion, we believe that the proposed GPU-based implementation is very useful for users as a fast screen tool to select the most likely model and may provide implementation guidance for possible future clinical applications such as online diagnosis.

Accelerating Computation of DCM for ERP in MATLAB by External Function Calls to the GPU

PubMed Central

Wang, Wei-Jen; Hsieh, I-Fan; Chen, Chun-Chuan

2013-01-01

This study aims to improve the performance of Dynamic Causal Modelling for Event Related Potentials (DCM for ERP) in MATLAB by using external function calls to a graphics processing unit (GPU). DCM for ERP is an advanced method for studying neuronal effective connectivity. DCM utilizes an iterative procedure, the expectation maximization (EM) algorithm, to find the optimal parameters given a set of observations and the underlying probability model. As the EM algorithm is computationally demanding and the analysis faces possible combinatorial explosion of models to be tested, we propose a parallel computing scheme using the GPU to achieve a fast estimation of DCM for ERP. The computation of DCM for ERP is dynamically partitioned and distributed to threads for parallel processing, according to the DCM model complexity and the hardware constraints. The performance efficiency of this hardware-dependent thread arrangement strategy was evaluated using the synthetic data. The experimental data were used to validate the accuracy of the proposed computing scheme and quantify the time saving in practice. The simulation results show that the proposed scheme can accelerate the computation by a factor of 155 for the parallel part. For experimental data, the speedup factor is about 7 per model on average, depending on the model complexity and the data. This GPU-based implementation of DCM for ERP gives qualitatively the same results as the original MATLAB implementation does at the group level analysis. In conclusion, we believe that the proposed GPU-based implementation is very useful for users as a fast screen tool to select the most likely model and may provide implementation guidance for possible future clinical applications such as online diagnosis. PMID:23840507

Sparse Matrices in MATLAB: Design and Implementation

NASA Technical Reports Server (NTRS)

Gilbert, John R.; Moler, Cleve; Schreiber, Robert

1992-01-01

The matrix computation language and environment MATLAB is extended to include sparse matrix storage and operations. The only change to the outward appearance of the MATLAB language is a pair of commands to create full or sparse matrices. Nearly all the operations of MATLAB now apply equally to full or sparse matrices, without any explicit action by the user. The sparse data structure represents a matrix in space proportional to the number of nonzero entries, and most of the operations compute sparse results in time proportional to the number of arithmetic operations on nonzeros.

Using MATLAB Software on the Peregrine System | High-Performance Computing

Science.gov Websites

Learn how to run MATLAB software in batch mode on the Peregrine system. Below is an example MATLAB job in batch (non-interactive) mode. To try the example out, create both matlabTest.sub and /$USER. In this example, it is also the directory into which MATLAB will write the output file x.dat

A general spectral method for the numerical simulation of one-dimensional interacting fermions

NASA Astrophysics Data System (ADS)

Clason, Christian; von Winckel, Gregory

2012-08-01

This software implements a general framework for the direct numerical simulation of systems of interacting fermions in one spatial dimension. The approach is based on a specially adapted nodal spectral Galerkin method, where the basis functions are constructed to obey the antisymmetry relations of fermionic wave functions. An efficient Matlab program for the assembly of the stiffness and potential matrices is presented, which exploits the combinatorial structure of the sparsity pattern arising from this discretization to achieve optimal run-time complexity. This program allows the accurate discretization of systems with multiple fermions subject to arbitrary potentials, e.g., for verifying the accuracy of multi-particle approximations such as Hartree-Fock in the few-particle limit. It can be used for eigenvalue computations or numerical solutions of the time-dependent Schrödinger equation. The new version includes a Python implementation of the presented approach. New version program summaryProgram title: assembleFermiMatrix Catalogue identifier: AEKO_v1_1 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKO_v1_1.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 332 No. of bytes in distributed program, including test data, etc.: 5418 Distribution format: tar.gz Programming language: MATLAB/GNU Octave, Python Computer: Any architecture supported by MATLAB, GNU Octave or Python Operating system: Any supported by MATLAB, GNU Octave or Python RAM: Depends on the data Classification: 4.3, 2.2. External routines: Python 2.7+, NumPy 1.3+, SciPy 0.10+ Catalogue identifier of previous version: AEKO_v1_0 Journal reference of previous version: Comput. Phys. Commun. 183 (2012) 405 Does the new version supersede the previous version?: Yes Nature of problem: The direct numerical solution of the multi-particle one-dimensional Schrödinger equation in a quantum well is challenging due to the exponential growth in the number of degrees of freedom with increasing particles. Solution method: A nodal spectral Galerkin scheme is used where the basis functions are constructed to obey the antisymmetry relations of the fermionic wave function. The assembly of these matrices is performed efficiently by exploiting the combinatorial structure of the sparsity patterns. Reasons for new version: A Python implementation is now included. Summary of revisions: Added a Python implementation; small documentation fixes in Matlab implementation. No change in features of the package. Restrictions: Only one-dimensional computational domains with homogeneous Dirichlet or periodic boundary conditions are supported. Running time: Seconds to minutes.

Bistatic passive radar simulator with spatial filtering subsystem

NASA Astrophysics Data System (ADS)

Hossa, Robert; Szlachetko, Boguslaw; Lewandowski, Andrzej; Górski, Maksymilian

2009-06-01

The purpose of this paper is to briefly introduce the structure and features of the developed virtual passive FM radar implemented in Matlab system of numerical computations and to present many alternative ways of its performance. An idea of the proposed solution is based on analytic representation of transmitted direct signals and reflected echo signals. As a spatial filtering subsystem a beamforming network of ULA and UCA dipole configuration dedicated to bistatic radar concept is considered and computationally efficient procedures are presented in details. Finally, exemplary results of the computer simulations of the elaborated virtual simulator are provided and discussed.

MPBEC, a Matlab Program for Biomolecular Electrostatic Calculations

NASA Astrophysics Data System (ADS)

Vergara-Perez, Sandra; Marucho, Marcelo

2016-01-01

One of the most used and efficient approaches to compute electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation. There are several software packages available that solve the PB equation for molecules in aqueous electrolyte solutions. Most of these software packages are useful for scientists with specialized training and expertise in computational biophysics. However, the user is usually required to manually take several important choices, depending on the complexity of the biological system, to successfully obtain the numerical solution of the PB equation. This may become an obstacle for researchers, experimentalists, even students with no special training in computational methodologies. Aiming to overcome this limitation, in this article we present MPBEC, a free, cross-platform, open-source software that provides non-experts in the field an easy and efficient way to perform biomolecular electrostatic calculations on single processor computers. MPBEC is a Matlab script based on the Adaptative Poisson-Boltzmann Solver, one of the most popular approaches used to solve the PB equation. MPBEC does not require any user programming, text editing or extensive statistical skills, and comes with detailed user-guide documentation. As a unique feature, MPBEC includes a useful graphical user interface (GUI) application which helps and guides users to configure and setup the optimal parameters and approximations to successfully perform the required biomolecular electrostatic calculations. The GUI also incorporates visualization tools to facilitate users pre- and post-analysis of structural and electrical properties of biomolecules.

MPBEC, a Matlab Program for Biomolecular Electrostatic Calculations

PubMed Central

Vergara-Perez, Sandra; Marucho, Marcelo

2015-01-01

One of the most used and efficient approaches to compute electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation. There are several software packages available that solve the PB equation for molecules in aqueous electrolyte solutions. Most of these software packages are useful for scientists with specialized training and expertise in computational biophysics. However, the user is usually required to manually take several important choices, depending on the complexity of the biological system, to successfully obtain the numerical solution of the PB equation. This may become an obstacle for researchers, experimentalists, even students with no special training in computational methodologies. Aiming to overcome this limitation, in this article we present MPBEC, a free, cross-platform, open-source software that provides non-experts in the field an easy and efficient way to perform biomolecular electrostatic calculations on single processor computers. MPBEC is a Matlab script based on the Adaptative Poisson Boltzmann Solver, one of the most popular approaches used to solve the PB equation. MPBEC does not require any user programming, text editing or extensive statistical skills, and comes with detailed user-guide documentation. As a unique feature, MPBEC includes a useful graphical user interface (GUI) application which helps and guides users to configure and setup the optimal parameters and approximations to successfully perform the required biomolecular electrostatic calculations. The GUI also incorporates visualization tools to facilitate users pre- and post- analysis of structural and electrical properties of biomolecules. PMID:26924848

MPBEC, a Matlab Program for Biomolecular Electrostatic Calculations.

PubMed

Vergara-Perez, Sandra; Marucho, Marcelo

2016-01-01

One of the most used and efficient approaches to compute electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation. There are several software packages available that solve the PB equation for molecules in aqueous electrolyte solutions. Most of these software packages are useful for scientists with specialized training and expertise in computational biophysics. However, the user is usually required to manually take several important choices, depending on the complexity of the biological system, to successfully obtain the numerical solution of the PB equation. This may become an obstacle for researchers, experimentalists, even students with no special training in computational methodologies. Aiming to overcome this limitation, in this article we present MPBEC, a free, cross-platform, open-source software that provides non-experts in the field an easy and efficient way to perform biomolecular electrostatic calculations on single processor computers. MPBEC is a Matlab script based on the Adaptative Poisson Boltzmann Solver, one of the most popular approaches used to solve the PB equation. MPBEC does not require any user programming, text editing or extensive statistical skills, and comes with detailed user-guide documentation. As a unique feature, MPBEC includes a useful graphical user interface (GUI) application which helps and guides users to configure and setup the optimal parameters and approximations to successfully perform the required biomolecular electrostatic calculations. The GUI also incorporates visualization tools to facilitate users pre- and post- analysis of structural and electrical properties of biomolecules.

MOSES: A Matlab-based open-source stochastic epidemic simulator.

PubMed

Varol, Huseyin Atakan

2016-08-01

This paper presents an open-source stochastic epidemic simulator. Discrete Time Markov Chain based simulator is implemented in Matlab. The simulator capable of simulating SEQIJR (susceptible, exposed, quarantined, infected, isolated and recovered) model can be reduced to simpler models by setting some of the parameters (transition probabilities) to zero. Similarly, it can be extended to more complicated models by editing the source code. It is designed to be used for testing different control algorithms to contain epidemics. The simulator is also designed to be compatible with a network based epidemic simulator and can be used in the network based scheme for the simulation of a node. Simulations show the capability of reproducing different epidemic model behaviors successfully in a computationally efficient manner.

Sensitivity of surface meteorological analyses to observation networks

NASA Astrophysics Data System (ADS)

Tyndall, Daniel Paul

A computationally efficient variational analysis system for two-dimensional meteorological fields is developed and described. This analysis approach is most efficient when the number of analysis grid points is much larger than the number of available observations, such as for large domain mesoscale analyses. The analysis system is developed using MATLAB software and can take advantage of multiple processors or processor cores. A version of the analysis system has been exported as a platform independent application (i.e., can be run on Windows, Linux, or Macintosh OS X desktop computers without a MATLAB license) with input/output operations handled by commonly available internet software combined with data archives at the University of Utah. The impact of observation networks on the meteorological analyses is assessed by utilizing a percentile ranking of individual observation sensitivity and impact, which is computed by using the adjoint of the variational surface assimilation system. This methodology is demonstrated using a case study of the analysis from 1400 UTC 27 October 2010 over the entire contiguous United States domain. The sensitivity of this approach to the dependence of the background error covariance on observation density is examined. Observation sensitivity and impact provide insight on the influence of observations from heterogeneous observing networks as well as serve as objective metrics for quality control procedures that may help to identify stations with significant siting, reporting, or representativeness issues.

Matpar: Parallel Extensions for MATLAB

NASA Technical Reports Server (NTRS)

Springer, P. L.

1998-01-01

Matpar is a set of client/server software that allows a MATLAB user to take advantage of a parallel computer for very large problems. The user can replace calls to certain built-in MATLAB functions with calls to Matpar functions.

PLATSIM: An efficient linear simulation and analysis package for large-order flexible systems

NASA Technical Reports Server (NTRS)

Maghami, Periman; Kenny, Sean P.; Giesy, Daniel P.

1995-01-01

PLATSIM is a software package designed to provide efficient time and frequency domain analysis of large-order generic space platforms implemented with any linear time-invariant control system. Time domain analysis provides simulations of the overall spacecraft response levels due to either onboard or external disturbances. The time domain results can then be processed by the jitter analysis module to assess the spacecraft's pointing performance in a computationally efficient manner. The resulting jitter analysis algorithms have produced an increase in speed of several orders of magnitude over the brute force approach of sweeping minima and maxima. Frequency domain analysis produces frequency response functions for uncontrolled and controlled platform configurations. The latter represents an enabling technology for large-order flexible systems. PLATSIM uses a sparse matrix formulation for the spacecraft dynamics model which makes both the time and frequency domain operations quite efficient, particularly when a large number of modes are required to capture the true dynamics of the spacecraft. The package is written in MATLAB script language. A graphical user interface (GUI) is included in the PLATSIM software package. This GUI uses MATLAB's Handle graphics to provide a convenient way for setting simulation and analysis parameters.

Enhancing Student Writing and Computer Programming with LATEX and MATLAB in Multivariable Calculus

ERIC Educational Resources Information Center

Sullivan, Eric; Melvin, Timothy

2016-01-01

Written communication and computer programming are foundational components of an undergraduate degree in the mathematical sciences. All lower-division mathematics courses at our institution are paired with computer-based writing, coding, and problem-solving activities. In multivariable calculus we utilize MATLAB and LATEX to have students explore…

Vectorized algorithms for spiking neural network simulation.

PubMed

Brette, Romain; Goodman, Dan F M

2011-06-01

High-level languages (Matlab, Python) are popular in neuroscience because they are flexible and accelerate development. However, for simulating spiking neural networks, the cost of interpretation is a bottleneck. We describe a set of algorithms to simulate large spiking neural networks efficiently with high-level languages using vector-based operations. These algorithms constitute the core of Brian, a spiking neural network simulator written in the Python language. Vectorized simulation makes it possible to combine the flexibility of high-level languages with the computational efficiency usually associated with compiled languages.

A Summary of the Naval Postgraduate School Research Program and Recent Publications

DTIC Science & Technology

1990-09-01

principles to divide the spectrum of MATLAB computer program on a 386-type a wide-band spread-spectrum signal into sub- computer. Because of the high rf...original in time and a large data sample was required. An signal. Effects due the fiber optic pickup array extended version of MATLAB that allows and...application, such as orbital mechanics and weather prediction. Professor Gragg has also developed numerous MATLAB programs for linear programming problems

A GPU accelerated and error-controlled solver for the unbounded Poisson equation in three dimensions

NASA Astrophysics Data System (ADS)

Exl, Lukas

2017-12-01

An efficient solver for the three dimensional free-space Poisson equation is presented. The underlying numerical method is based on finite Fourier series approximation. While the error of all involved approximations can be fully controlled, the overall computation error is driven by the convergence of the finite Fourier series of the density. For smooth and fast-decaying densities the proposed method will be spectrally accurate. The method scales with O(N log N) operations, where N is the total number of discretization points in the Cartesian grid. The majority of the computational costs come from fast Fourier transforms (FFT), which makes it ideal for GPU computation. Several numerical computations on CPU and GPU validate the method and show efficiency and convergence behavior. Tests are performed using the Vienna Scientific Cluster 3 (VSC3). A free MATLAB implementation for CPU and GPU is provided to the interested community.

The Dynamo package for tomography and subtomogram averaging: components for MATLAB, GPU computing and EC2 Amazon Web Services

PubMed Central

Castaño-Díez, Daniel

2017-01-01

Dynamo is a package for the processing of tomographic data. As a tool for subtomogram averaging, it includes different alignment and classification strategies. Furthermore, its data-management module allows experiments to be organized in groups of tomograms, while offering specialized three-dimensional tomographic browsers that facilitate visualization, location of regions of interest, modelling and particle extraction in complex geometries. Here, a technical description of the package is presented, focusing on its diverse strategies for optimizing computing performance. Dynamo is built upon mbtools (middle layer toolbox), a general-purpose MATLAB library for object-oriented scientific programming specifically developed to underpin Dynamo but usable as an independent tool. Its structure intertwines a flexible MATLAB codebase with precompiled C++ functions that carry the burden of numerically intensive operations. The package can be delivered as a precompiled standalone ready for execution without a MATLAB license. Multicore parallelization on a single node is directly inherited from the high-level parallelization engine provided for MATLAB, automatically imparting a balanced workload among the threads in computationally intense tasks such as alignment and classification, but also in logistic-oriented tasks such as tomogram binning and particle extraction. Dynamo supports the use of graphical processing units (GPUs), yielding considerable speedup factors both for native Dynamo procedures (such as the numerically intensive subtomogram alignment) and procedures defined by the user through its MATLAB-based GPU library for three-dimensional operations. Cloud-based virtual computing environments supplied with a pre-installed version of Dynamo can be publicly accessed through the Amazon Elastic Compute Cloud (EC2), enabling users to rent GPU computing time on a pay-as-you-go basis, thus avoiding upfront investments in hardware and longterm software maintenance. PMID:28580909

The Dynamo package for tomography and subtomogram averaging: components for MATLAB, GPU computing and EC2 Amazon Web Services.

PubMed

Castaño-Díez, Daniel

2017-06-01

Dynamo is a package for the processing of tomographic data. As a tool for subtomogram averaging, it includes different alignment and classification strategies. Furthermore, its data-management module allows experiments to be organized in groups of tomograms, while offering specialized three-dimensional tomographic browsers that facilitate visualization, location of regions of interest, modelling and particle extraction in complex geometries. Here, a technical description of the package is presented, focusing on its diverse strategies for optimizing computing performance. Dynamo is built upon mbtools (middle layer toolbox), a general-purpose MATLAB library for object-oriented scientific programming specifically developed to underpin Dynamo but usable as an independent tool. Its structure intertwines a flexible MATLAB codebase with precompiled C++ functions that carry the burden of numerically intensive operations. The package can be delivered as a precompiled standalone ready for execution without a MATLAB license. Multicore parallelization on a single node is directly inherited from the high-level parallelization engine provided for MATLAB, automatically imparting a balanced workload among the threads in computationally intense tasks such as alignment and classification, but also in logistic-oriented tasks such as tomogram binning and particle extraction. Dynamo supports the use of graphical processing units (GPUs), yielding considerable speedup factors both for native Dynamo procedures (such as the numerically intensive subtomogram alignment) and procedures defined by the user through its MATLAB-based GPU library for three-dimensional operations. Cloud-based virtual computing environments supplied with a pre-installed version of Dynamo can be publicly accessed through the Amazon Elastic Compute Cloud (EC2), enabling users to rent GPU computing time on a pay-as-you-go basis, thus avoiding upfront investments in hardware and longterm software maintenance.

Efficient simulation of intrinsic, extrinsic and external noise in biochemical systems

PubMed Central

Pischel, Dennis; Sundmacher, Kai; Flassig, Robert J.

2017-01-01

Abstract Motivation: Biological cells operate in a noisy regime influenced by intrinsic, extrinsic and external noise, which leads to large differences of individual cell states. Stochastic effects must be taken into account to characterize biochemical kinetics accurately. Since the exact solution of the chemical master equation, which governs the underlying stochastic process, cannot be derived for most biochemical systems, approximate methods are used to obtain a solution. Results: In this study, a method to efficiently simulate the various sources of noise simultaneously is proposed and benchmarked on several examples. The method relies on the combination of the sigma point approach to describe extrinsic and external variability and the τ-leaping algorithm to account for the stochasticity due to probabilistic reactions. The comparison of our method to extensive Monte Carlo calculations demonstrates an immense computational advantage while losing an acceptable amount of accuracy. Additionally, the application to parameter optimization problems in stochastic biochemical reaction networks is shown, which is rarely applied due to its huge computational burden. To give further insight, a MATLAB script is provided including the proposed method applied to a simple toy example of gene expression. Availability and implementation: MATLAB code is available at Bioinformatics online. Contact: flassig@mpi-magdeburg.mpg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28881987

A Comparison of Approaches for Solving Hard Graph-Theoretic Problems

DTIC Science & Technology

2015-05-01

collaborative effort “ Adiabatic Quantum Computing Applications Research” (14-RI-CRADA-02) between the Information Directorate and Lock- 3 Algorithm 3...using Matlab, a quantum annealing approach using the D-Wave computer , and lastly using satisfiability modulo theory (SMT) and corresponding SMT...methods are explored and consist of a parallel computing approach using Matlab, a quantum annealing approach using the D-Wave computer , and lastly using

Simulation Concept - How to Exploit Tools for Computing Hybrids

DTIC Science & Technology

2010-06-01

biomolecular reactions ................................................................ 42  Figure 30: Overview of MATLAB Implementation...Figure 50: Adenine graphed using MATLAB (left) and OpenGL (right) ........................ 70  Figure 51: An overhead view of a thymine and adenine base...93  Figure 68: Response frequency solution from MATLAB

MatLab Script and Functional Programming

NASA Technical Reports Server (NTRS)

Shaykhian, Gholam Ali

2007-01-01

MatLab Script and Functional Programming: MatLab is one of the most widely used very high level programming languages for scientific and engineering computations. It is very user-friendly and needs practically no formal programming knowledge. Presented here are MatLab programming aspects and not just the MatLab commands for scientists and engineers who do not have formal programming training and also have no significant time to spare for learning programming to solve their real world problems. Specifically provided are programs for visualization. The MatLab seminar covers the functional and script programming aspect of MatLab language. Specific expectations are: a) Recognize MatLab commands, script and function. b) Create, and run a MatLab function. c) Read, recognize, and describe MatLab syntax. d) Recognize decisions, loops and matrix operators. e) Evaluate scope among multiple files, and multiple functions within a file. f) Declare, define and use scalar variables, vectors and matrices.

Parallel Computation of the Jacobian Matrix for Nonlinear Equation Solvers Using MATLAB

NASA Technical Reports Server (NTRS)

Rose, Geoffrey K.; Nguyen, Duc T.; Newman, Brett A.

2017-01-01

Demonstrating speedup for parallel code on a multicore shared memory PC can be challenging in MATLAB due to underlying parallel operations that are often opaque to the user. This can limit potential for improvement of serial code even for the so-called embarrassingly parallel applications. One such application is the computation of the Jacobian matrix inherent to most nonlinear equation solvers. Computation of this matrix represents the primary bottleneck in nonlinear solver speed such that commercial finite element (FE) and multi-body-dynamic (MBD) codes attempt to minimize computations. A timing study using MATLAB's Parallel Computing Toolbox was performed for numerical computation of the Jacobian. Several approaches for implementing parallel code were investigated while only the single program multiple data (spmd) method using composite objects provided positive results. Parallel code speedup is demonstrated but the goal of linear speedup through the addition of processors was not achieved due to PC architecture.

An Innovative Learning Model for Computation in First Year Mathematics

ERIC Educational Resources Information Center

Tonkes, E. J.; Loch, B. I.; Stace, A. W.

2005-01-01

MATLAB is a sophisticated software tool for numerical analysis and visualization. The University of Queensland has adopted Matlab as its official teaching package across large first year mathematics courses. In the past, the package has met severe resistance from students who have not appreciated their computational experience. Several main…

A MATLAB-Aided Method for Teaching Calculus-Based Business Mathematics

ERIC Educational Resources Information Center

Liang, Jiajuan; Pan, William S. Y.

2009-01-01

MATLAB is a powerful package for numerical computation. MATLAB contains a rich pool of mathematical functions and provides flexible plotting functions for illustrating mathematical solutions. The course of calculus-based business mathematics consists of two major topics: 1) derivative and its applications in business; and 2) integration and its…

Using Matlab in a Multivariable Calculus Course.

ERIC Educational Resources Information Center

Schlatter, Mark D.

The benefits of high-level mathematics packages such as Matlab include both a computer algebra system and the ability to provide students with concrete visual examples. This paper discusses how both capabilities of Matlab were used in a multivariate calculus class. Graphical user interfaces which display three-dimensional surfaces, contour plots,…

High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System

PubMed Central

Saikia, Manob Jyoti; Kanhirodan, Rajan; Mohan Vasu, Ram

2014-01-01

We have developed a graphics processor unit (GPU-) based high-speed fully 3D system for diffuse optical tomography (DOT). The reduction in execution time of 3D DOT algorithm, a severely ill-posed problem, is made possible through the use of (1) an algorithmic improvement that uses Broyden approach for updating the Jacobian matrix and thereby updating the parameter matrix and (2) the multinode multithreaded GPU and CUDA (Compute Unified Device Architecture) software architecture. Two different GPU implementations of DOT programs are developed in this study: (1) conventional C language program augmented by GPU CUDA and CULA routines (C GPU), (2) MATLAB program supported by MATLAB parallel computing toolkit for GPU (MATLAB GPU). The computation time of the algorithm on host CPU and the GPU system is presented for C and Matlab implementations. The forward computation uses finite element method (FEM) and the problem domain is discretized into 14610, 30823, and 66514 tetrahedral elements. The reconstruction time, so achieved for one iteration of the DOT reconstruction for 14610 elements, is 0.52 seconds for a C based GPU program for 2-plane measurements. The corresponding MATLAB based GPU program took 0.86 seconds. The maximum number of reconstructed frames so achieved is 2 frames per second. PMID:24891848

High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System.

PubMed

Saikia, Manob Jyoti; Kanhirodan, Rajan; Mohan Vasu, Ram

2014-01-01

We have developed a graphics processor unit (GPU-) based high-speed fully 3D system for diffuse optical tomography (DOT). The reduction in execution time of 3D DOT algorithm, a severely ill-posed problem, is made possible through the use of (1) an algorithmic improvement that uses Broyden approach for updating the Jacobian matrix and thereby updating the parameter matrix and (2) the multinode multithreaded GPU and CUDA (Compute Unified Device Architecture) software architecture. Two different GPU implementations of DOT programs are developed in this study: (1) conventional C language program augmented by GPU CUDA and CULA routines (C GPU), (2) MATLAB program supported by MATLAB parallel computing toolkit for GPU (MATLAB GPU). The computation time of the algorithm on host CPU and the GPU system is presented for C and Matlab implementations. The forward computation uses finite element method (FEM) and the problem domain is discretized into 14610, 30823, and 66514 tetrahedral elements. The reconstruction time, so achieved for one iteration of the DOT reconstruction for 14610 elements, is 0.52 seconds for a C based GPU program for 2-plane measurements. The corresponding MATLAB based GPU program took 0.86 seconds. The maximum number of reconstructed frames so achieved is 2 frames per second.

MatLab Programming for Engineers Having No Formal Programming Knowledge

NASA Technical Reports Server (NTRS)

Shaykhian, Linda H.; Shaykhian, Gholam Ali

2007-01-01

MatLab is one of the most widely used very high level programming languages for Scientific and engineering computations. It is very user-friendly and needs practically no formal programming knowledge. Presented here are MatLab programming aspects and not just the MatLab commands for scientists and engineers who do not have formal programming training and also have no significant time to spare for learning programming to solve their real world problems. Specifically provided are programs for visualization. Also, stated are the current limitations of the MatLab, which possibly can be taken care of by Mathworks Inc. in a future version to make MatLab more versatile.

Automated Measurement of Patient-Specific Tibial Slopes from MRI

PubMed Central

Amerinatanzi, Amirhesam; Summers, Rodney K.; Ahmadi, Kaveh; Goel, Vijay K.; Hewett, Timothy E.; Nyman, Edward

2017-01-01

Background: Multi-planar proximal tibial slopes may be associated with increased likelihood of osteoarthritis and anterior cruciate ligament injury, due in part to their role in checking the anterior-posterior stability of the knee. Established methods suffer repeatability limitations and lack computational efficiency for intuitive clinical adoption. The aims of this study were to develop a novel automated approach and to compare the repeatability and computational efficiency of the approach against previously established methods. Methods: Tibial slope geometries were obtained via MRI and measured using an automated Matlab-based approach. Data were compared for repeatability and evaluated for computational efficiency. Results: Mean lateral tibial slope (LTS) for females (7.2°) was greater than for males (1.66°). Mean LTS in the lateral concavity zone was greater for females (7.8° for females, 4.2° for males). Mean medial tibial slope (MTS) for females was greater (9.3° vs. 4.6°). Along the medial concavity zone, female subjects demonstrated greater MTS. Conclusion: The automated method was more repeatable and computationally efficient than previously identified methods and may aid in the clinical assessment of knee injury risk, inform surgical planning, and implant design efforts. PMID:28952547

Image processing and pattern recognition with CVIPtools MATLAB toolbox: automatic creation of masks for veterinary thermographic images

NASA Astrophysics Data System (ADS)

Mishra, Deependra K.; Umbaugh, Scott E.; Lama, Norsang; Dahal, Rohini; Marino, Dominic J.; Sackman, Joseph

2016-09-01

CVIPtools is a software package for the exploration of computer vision and image processing developed in the Computer Vision and Image Processing Laboratory at Southern Illinois University Edwardsville. CVIPtools is available in three variants - a) CVIPtools Graphical User Interface, b) CVIPtools C library and c) CVIPtools MATLAB toolbox, which makes it accessible to a variety of different users. It offers students, faculty, researchers and any user a free and easy way to explore computer vision and image processing techniques. Many functions have been implemented and are updated on a regular basis, the library has reached a level of sophistication that makes it suitable for both educational and research purposes. In this paper, the detail list of the functions available in the CVIPtools MATLAB toolbox are presented and how these functions can be used in image analysis and computer vision applications. The CVIPtools MATLAB toolbox allows the user to gain practical experience to better understand underlying theoretical problems in image processing and pattern recognition. As an example application, the algorithm for the automatic creation of masks for veterinary thermographic images is presented.

A smart grid simulation testbed using Matlab/Simulink

NASA Astrophysics Data System (ADS)

Mallapuram, Sriharsha; Moulema, Paul; Yu, Wei

2014-06-01

The smart grid is the integration of computing and communication technologies into a power grid with a goal of enabling real time control, and a reliable, secure, and efficient energy system [1]. With the increased interest of the research community and stakeholders towards the smart grid, a number of solutions and algorithms have been developed and proposed to address issues related to smart grid operations and functions. Those technologies and solutions need to be tested and validated before implementation using software simulators. In this paper, we developed a general smart grid simulation model in the MATLAB/Simulink environment, which integrates renewable energy resources, energy storage technology, load monitoring and control capability. To demonstrate and validate the effectiveness of our simulation model, we created simulation scenarios and performed simulations using a real-world data set provided by the Pecan Street Research Institute.

Identification of Computational and Experimental Reduced-Order Models

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Hong, Moeljo S.; Bartels, Robert E.; Piatak, David J.; Scott, Robert C.

2003-01-01

The identification of computational and experimental reduced-order models (ROMs) for the analysis of unsteady aerodynamic responses and for efficient aeroelastic analyses is presented. For the identification of a computational aeroelastic ROM, the CFL3Dv6.0 computational fluid dynamics (CFD) code is used. Flutter results for the AGARD 445.6 Wing and for a Rigid Semispan Model (RSM) computed using CFL3Dv6.0 are presented, including discussion of associated computational costs. Modal impulse responses of the unsteady aerodynamic system are computed using the CFL3Dv6.0 code and transformed into state-space form. The unsteady aerodynamic state-space ROM is then combined with a state-space model of the structure to create an aeroelastic simulation using the MATLAB/SIMULINK environment. The MATLAB/SIMULINK ROM is then used to rapidly compute aeroelastic transients, including flutter. The ROM shows excellent agreement with the aeroelastic analyses computed using the CFL3Dv6.0 code directly. For the identification of experimental unsteady pressure ROMs, results are presented for two configurations: the RSM and a Benchmark Supercritical Wing (BSCW). Both models were used to acquire unsteady pressure data due to pitching oscillations on the Oscillating Turntable (OTT) system at the Transonic Dynamics Tunnel (TDT). A deconvolution scheme involving a step input in pitch and the resultant step response in pressure, for several pressure transducers, is used to identify the unsteady pressure impulse responses. The identified impulse responses are then used to predict the pressure responses due to pitching oscillations at several frequencies. Comparisons with the experimental data are then presented.

FALCON: a toolbox for the fast contextualization of logical networks

PubMed Central

De Landtsheer, Sébastien; Trairatphisan, Panuwat; Lucarelli, Philippe; Sauter, Thomas

2017-01-01

Abstract Motivation Mathematical modelling of regulatory networks allows for the discovery of knowledge at the system level. However, existing modelling tools are often computation-heavy and do not offer intuitive ways to explore the model, to test hypotheses or to interpret the results biologically. Results We have developed a computational approach to contextualize logical models of regulatory networks with biological measurements based on a probabilistic description of rule-based interactions between the different molecules. Here, we propose a Matlab toolbox, FALCON, to automatically and efficiently build and contextualize networks, which includes a pipeline for conducting parameter analysis, knockouts and easy and fast model investigation. The contextualized models could then provide qualitative and quantitative information about the network and suggest hypotheses about biological processes. Availability and implementation FALCON is freely available for non-commercial users on GitHub under the GPLv3 licence. The toolbox, installation instructions, full documentation and test datasets are available at https://github.com/sysbiolux/FALCON. FALCON runs under Matlab (MathWorks) and requires the Optimization Toolbox. Contact thomas.sauter@uni.lu Supplementary information Supplementary data are available at Bioinformatics online. PMID:28673016

FALCON: a toolbox for the fast contextualization of logical networks.

PubMed

De Landtsheer, Sébastien; Trairatphisan, Panuwat; Lucarelli, Philippe; Sauter, Thomas

2017-11-01

Mathematical modelling of regulatory networks allows for the discovery of knowledge at the system level. However, existing modelling tools are often computation-heavy and do not offer intuitive ways to explore the model, to test hypotheses or to interpret the results biologically. We have developed a computational approach to contextualize logical models of regulatory networks with biological measurements based on a probabilistic description of rule-based interactions between the different molecules. Here, we propose a Matlab toolbox, FALCON, to automatically and efficiently build and contextualize networks, which includes a pipeline for conducting parameter analysis, knockouts and easy and fast model investigation. The contextualized models could then provide qualitative and quantitative information about the network and suggest hypotheses about biological processes. FALCON is freely available for non-commercial users on GitHub under the GPLv3 licence. The toolbox, installation instructions, full documentation and test datasets are available at https://github.com/sysbiolux/FALCON. FALCON runs under Matlab (MathWorks) and requires the Optimization Toolbox. thomas.sauter@uni.lu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Automatic and efficient methods applied to the binarization of a subway map

NASA Astrophysics Data System (ADS)

Durand, Philippe; Ghorbanzadeh, Dariush; Jaupi, Luan

2015-12-01

The purpose of this paper is the study of efficient methods for image binarization. The objective of the work is the metro maps binarization. the goal is to binarize, avoiding noise to disturb the reading of subway stations. Different methods have been tested. By this way, a method given by Otsu gives particularly interesting results. The difficulty of the binarization is the choice of this threshold in order to reconstruct. Image sticky as possible to reality. Vectorization is a step subsequent to that of the binarization. It is to retrieve the coordinates points containing information and to store them in the two matrices X and Y. Subsequently, these matrices can be exported to a file format 'CSV' (Comma Separated Value) enabling us to deal with them in a variety of software including Excel. The algorithm uses quite a time calculation in Matlab because it is composed of two "for" loops nested. But the "for" loops are poorly supported by Matlab, especially in each other. This therefore penalizes the computation time, but seems the only method to do this.

The Julia programming language: the future of scientific computing

NASA Astrophysics Data System (ADS)

Gibson, John

2017-11-01

Julia is an innovative new open-source programming language for high-level, high-performance numerical computing. Julia combines the general-purpose breadth and extensibility of Python, the ease-of-use and numeric focus of Matlab, the speed of C and Fortran, and the metaprogramming power of Lisp. Julia uses type inference and just-in-time compilation to compile high-level user code to machine code on the fly. A rich set of numeric types and extensive numerical libraries are built-in. As a result, Julia is competitive with Matlab for interactive graphical exploration and with C and Fortran for high-performance computing. This talk interactively demonstrates Julia's numerical features and benchmarks Julia against C, C++, Fortran, Matlab, and Python on a spectral time-stepping algorithm for a 1d nonlinear partial differential equation. The Julia code is nearly as compact as Matlab and nearly as fast as Fortran. This material is based upon work supported by the National Science Foundation under Grant No. 1554149.

Memory-Efficient Analysis of Dense Functional Connectomes.

PubMed

Loewe, Kristian; Donohue, Sarah E; Schoenfeld, Mircea A; Kruse, Rudolf; Borgelt, Christian

2016-01-01

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to insufficient memory. An open source software package containing the created programs is available for download.

Memory-Efficient Analysis of Dense Functional Connectomes

PubMed Central

Loewe, Kristian; Donohue, Sarah E.; Schoenfeld, Mircea A.; Kruse, Rudolf; Borgelt, Christian

2016-01-01

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to insufficient memory. An open source software package containing the created programs is available for download. PMID:27965565

Meshfree and efficient modeling of swimming cells

NASA Astrophysics Data System (ADS)

Gallagher, Meurig T.; Smith, David J.

2018-05-01

Locomotion in Stokes flow is an intensively studied problem because it describes important biological phenomena such as the motility of many species' sperm, bacteria, algae, and protozoa. Numerical computations can be challenging, particularly in three dimensions, due to the presence of moving boundaries and complex geometries; methods which combine ease of implementation and computational efficiency are therefore needed. A recently proposed method to discretize the regularized Stokeslet boundary integral equation without the need for a connected mesh is applied to the inertialess locomotion problem in Stokes flow. The mathematical formulation and key aspects of the computational implementation in matlab® or GNU Octave are described, followed by numerical experiments with biflagellate algae and multiple uniflagellate sperm swimming between no-slip surfaces, for which both swimming trajectories and flow fields are calculated. These computational experiments required minutes of time on modest hardware; an extensible implementation is provided in a GitHub repository. The nearest-neighbor discretization dramatically improves convergence and robustness, a key challenge in extending the regularized Stokeslet method to complicated three-dimensional biological fluid problems.

Efficient simulation of intrinsic, extrinsic and external noise in biochemical systems.

PubMed

Pischel, Dennis; Sundmacher, Kai; Flassig, Robert J

2017-07-15

Biological cells operate in a noisy regime influenced by intrinsic, extrinsic and external noise, which leads to large differences of individual cell states. Stochastic effects must be taken into account to characterize biochemical kinetics accurately. Since the exact solution of the chemical master equation, which governs the underlying stochastic process, cannot be derived for most biochemical systems, approximate methods are used to obtain a solution. In this study, a method to efficiently simulate the various sources of noise simultaneously is proposed and benchmarked on several examples. The method relies on the combination of the sigma point approach to describe extrinsic and external variability and the τ -leaping algorithm to account for the stochasticity due to probabilistic reactions. The comparison of our method to extensive Monte Carlo calculations demonstrates an immense computational advantage while losing an acceptable amount of accuracy. Additionally, the application to parameter optimization problems in stochastic biochemical reaction networks is shown, which is rarely applied due to its huge computational burden. To give further insight, a MATLAB script is provided including the proposed method applied to a simple toy example of gene expression. MATLAB code is available at Bioinformatics online. flassig@mpi-magdeburg.mpg.de. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

OXlearn: a new MATLAB-based simulation tool for connectionist models.

PubMed

Ruh, Nicolas; Westermann, Gert

2009-11-01

OXlearn is a free, platform-independent MATLAB toolbox in which standard connectionist neural network models can be set up, run, and analyzed by means of a user-friendly graphical interface. Due to its seamless integration with the MATLAB programming environment, the inner workings of the simulation tool can be easily inspected and/or extended using native MATLAB commands or components. This combination of usability, transparency, and extendability makes OXlearn an efficient tool for the implementation of basic research projects or the prototyping of more complex research endeavors, as well as for teaching. Both the MATLAB toolbox and a compiled version that does not require access to MATLAB can be downloaded from http://psych.brookes.ac.uk/oxlearn/.

Measuring modules for the research of compensators of reactive power with voltage stabilization in MATLAB

NASA Astrophysics Data System (ADS)

Vlasayevsky, Stanislav; Klimash, Stepan; Klimash, Vladimir

2017-10-01

A set of mathematical modules was developed for evaluation the energy performance in the research of electrical systems and complexes in the MatLab. In the electrotechnical library SimPowerSystems of the MatLab software, there are no measuring modules of energy coefficients characterizing the quality of electricity and the energy efficiency of electrical apparatus. Modules are designed to calculate energy coefficients characterizing the quality of electricity (current distortion and voltage distortion) and energy efficiency indicators (power factor and efficiency) are presented. There are described the methods and principles of building the modules. The detailed schemes of modules built on the elements of the Simulink Library are presented, in this connection, these modules are compatible with mathematical models of electrical systems and complexes in the MatLab. Also there are presented the results of the testing of the developed modules and the results of their verification on the schemes that have analytical expressions of energy indicators.

MCR Container Tools

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

Haas, Nicholas Q; Gillen, Robert E; Karnowski, Thomas P

MathWorks' MATLAB is widely used in academia and industry for prototyping, data analysis, data processing, etc. Many users compile their programs using the MATLAB Compiler to run on workstations/computing clusters via the free MATLAB Compiler Runtime (MCR). The MCR facilitates the execution of code calling Application Programming Interfaces (API) functions from both base MATLAB and MATLAB toolboxes. In a Linux environment, a sizable number of third-party runtime dependencies (i.e. shared libraries) are necessary. Unfortunately, to the MTLAB community's knowledge, these dependencies are not documented, leaving system administrators and/or end-users to find/install the necessary libraries either as runtime errors resulting frommore » them missing or by inspecting the header information of Executable and Linkable Format (ELF) libraries of the MCR to determine which ones are missing from the system. To address various shortcomings, Docker Images based on Community Enterprise Operating System (CentOS) 7, a derivative of Redhat Enterprise Linux (RHEL) 7, containing recent (2015-2017) MCR releases and their dependencies were created. These images, along with a provided sample Docker Compose YAML Script, can be used to create a simulated computing cluster where MATLAB Compiler created binaries can be executed using a sample Slurm Workload Manager script.« less

Operating a Geiger-Muller Tube Using a PC Sound Card

ERIC Educational Resources Information Center

Azooz, A. A.

2009-01-01

In this paper, a simple MATLAB-based PC program that enables the computer to function as a replacement for the electronic scalar-counter system associated with a Geiger-Muller (GM) tube is described. The program utilizes the ability of MATLAB to acquire data directly from the computer sound card. The signal from the GM tube is applied to the…

CELES: CUDA-accelerated simulation of electromagnetic scattering by large ensembles of spheres

NASA Astrophysics Data System (ADS)

Egel, Amos; Pattelli, Lorenzo; Mazzamuto, Giacomo; Wiersma, Diederik S.; Lemmer, Uli

2017-09-01

CELES is a freely available MATLAB toolbox to simulate light scattering by many spherical particles. Aiming at high computational performance, CELES leverages block-diagonal preconditioning, a lookup-table approach to evaluate costly functions and massively parallel execution on NVIDIA graphics processing units using the CUDA computing platform. The combination of these techniques allows to efficiently address large electrodynamic problems (>104 scatterers) on inexpensive consumer hardware. In this paper, we validate near- and far-field distributions against the well-established multi-sphere T-matrix (MSTM) code and discuss the convergence behavior for ensembles of different sizes, including an exemplary system comprising 105 particles.

Engineering and Scientific Applications: Using MatLab(Registered Trademark) for Data Processing and Visualization

NASA Technical Reports Server (NTRS)

Sen, Syamal K.; Shaykhian, Gholam Ali

2011-01-01

MatLab(TradeMark)(MATrix LABoratory) is a numerical computation and simulation tool that is used by thousands Scientists and Engineers in many countries. MatLab does purely numerical calculations, which can be used as a glorified calculator or interpreter programming language; its real strength is in matrix manipulations. Computer algebra functionalities are achieved within the MatLab environment using "symbolic" toolbox. This feature is similar to computer algebra programs, provided by Maple or Mathematica to calculate with mathematical equations using symbolic operations. MatLab in its interpreter programming language form (command interface) is similar with well known programming languages such as C/C++, support data structures and cell arrays to define classes in object oriented programming. As such, MatLab is equipped with most of the essential constructs of a higher programming language. MatLab is packaged with an editor and debugging functionality useful to perform analysis of large MatLab programs and find errors. We believe there are many ways to approach real-world problems; prescribed methods to ensure foregoing solutions are incorporated in design and analysis of data processing and visualization can benefit engineers and scientist in gaining wider insight in actual implementation of their perspective experiments. This presentation will focus on data processing and visualizations aspects of engineering and scientific applications. Specifically, it will discuss methods and techniques to perform intermediate-level data processing covering engineering and scientific problems. MatLab programming techniques including reading various data files formats to produce customized publication-quality graphics, importing engineering and/or scientific data, organizing data in tabular format, exporting data to be used by other software programs such as Microsoft Excel, data presentation and visualization will be discussed.

MATLAB Software Versions and Licenses for the Peregrine System |

Science.gov Websites

: Feature usage info: Users of MATLAB: (Total of 6 licenses issued; Total of ... licenses in use) Users of Compiler: (Total of 1 license issued; Total of ... licenses in use) Users of Distrib_Computing_Toolbox : (Total of 4 licenses issued; Total of ... licenses in use) Users of MATLAB_Distrib_Comp_Engine: (Total of

The GMT/MATLAB Toolbox

NASA Astrophysics Data System (ADS)

Wessel, Paul; Luis, Joaquim F.

2017-02-01

The GMT/MATLAB toolbox is a basic interface between MATLAB® (or Octave) and GMT, the Generic Mapping Tools, which allows MATLAB users full access to all GMT modules. Data may be passed between the two programs using intermediate MATLAB structures that organize the metadata needed; these are produced when GMT modules are run. In addition, standard MATLAB matrix data can be used directly as input to GMT modules. The toolbox improves interoperability between two widely used tools in the geosciences and extends the capability of both tools: GMT gains access to the powerful computational capabilities of MATLAB while the latter gains the ability to access specialized gridding algorithms and can produce publication-quality PostScript-based illustrations. The toolbox is available on all platforms and may be downloaded from the GMT website.

Effective approach to spectroscopy and spectral analysis techniques using Matlab

NASA Astrophysics Data System (ADS)

Li, Xiang; Lv, Yong

2017-08-01

With the development of electronic information, computer and network, modern education technology has entered new era, which would give a great impact on teaching process. Spectroscopy and spectral analysis is an elective course for Optoelectronic Information Science and engineering. The teaching objective of this course is to master the basic concepts and principles of spectroscopy, spectral analysis and testing of basic technical means. Then, let the students learn the principle and technology of the spectrum to study the structure and state of the material and the developing process of the technology. MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and fourth-generation programming language. A proprietary programming language developed by MathWorks, MATLAB allows matrix manipulations, plotting of functions and data, Based on the teaching practice, this paper summarizes the new situation of applying Matlab to the teaching of spectroscopy. This would be suitable for most of the current school multimedia assisted teaching

Improve Problem Solving Skills through Adapting Programming Tools

NASA Technical Reports Server (NTRS)

Shaykhian, Linda H.; Shaykhian, Gholam Ali

2007-01-01

There are numerous ways for engineers and students to become better problem-solvers. The use of command line and visual programming tools can help to model a problem and formulate a solution through visualization. The analysis of problem attributes and constraints provide insight into the scope and complexity of the problem. The visualization aspect of the problem-solving approach tends to make students and engineers more systematic in their thought process and help them catch errors before proceeding too far in the wrong direction. The problem-solver identifies and defines important terms, variables, rules, and procedures required for solving a problem. Every step required to construct the problem solution can be defined in program commands that produce intermediate output. This paper advocates improved problem solving skills through using a programming tool. MatLab created by MathWorks, is an interactive numerical computing environment and programming language. It is a matrix-based system that easily lends itself to matrix manipulation, and plotting of functions and data. MatLab can be used as an interactive command line or a sequence of commands that can be saved in a file as a script or named functions. Prior programming experience is not required to use MatLab commands. The GNU Octave, part of the GNU project, a free computer program for performing numerical computations, is comparable to MatLab. MatLab visual and command programming are presented here.

Image Algebra Matlab language version 2.3 for image processing and compression research

NASA Astrophysics Data System (ADS)

Schmalz, Mark S.; Ritter, Gerhard X.; Hayden, Eric

2010-08-01

Image algebra is a rigorous, concise notation that unifies linear and nonlinear mathematics in the image domain. Image algebra was developed under DARPA and US Air Force sponsorship at University of Florida for over 15 years beginning in 1984. Image algebra has been implemented in a variety of programming languages designed specifically to support the development of image processing and computer vision algorithms and software. The University of Florida has been associated with development of the languages FORTRAN, Ada, Lisp, and C++. The latter implementation involved a class library, iac++, that supported image algebra programming in C++. Since image processing and computer vision are generally performed with operands that are array-based, the Matlab™ programming language is ideal for implementing the common subset of image algebra. Objects include sets and set operations, images and operations on images, as well as templates and image-template convolution operations. This implementation, called Image Algebra Matlab (IAM), has been found to be useful for research in data, image, and video compression, as described herein. Due to the widespread acceptance of the Matlab programming language in the computing community, IAM offers exciting possibilities for supporting a large group of users. The control over an object's computational resources provided to the algorithm designer by Matlab means that IAM programs can employ versatile representations for the operands and operations of the algebra, which are supported by the underlying libraries written in Matlab. In a previous publication, we showed how the functionality of IAC++ could be carried forth into a Matlab implementation, and provided practical details of a prototype implementation called IAM Version 1. In this paper, we further elaborate the purpose and structure of image algebra, then present a maturing implementation of Image Algebra Matlab called IAM Version 2.3, which extends the previous implementation of IAM to include polymorphic operations over different point sets, as well as recursive convolution operations and functional composition. We also show how image algebra and IAM can be employed in image processing and compression research, as well as algorithm development and analysis.

Advances in Engineering Software for Lift Transportation Systems

NASA Astrophysics Data System (ADS)

Kazakoff, Alexander Borisoff

2012-03-01

In this paper an attempt is performed at computer modelling of ropeway ski lift systems. The logic in these systems is based on a travel form between the two terminals, which operates with high capacity cabins, chairs, gondolas or draw-bars. Computer codes AUTOCAD, MATLAB and Compaq-Visual Fortran - version 6.6 are used in the computer modelling. The rope systems computer modelling is organized in two stages in this paper. The first stage is organization of the ground relief profile and a design of the lift system as a whole, according to the terrain profile and the climatic and atmospheric conditions. The ground profile is prepared by the geodesists and is presented in an AUTOCAD view. The next step is the design of the lift itself which is performed by programmes using the computer code MATLAB. The second stage of the computer modelling is performed after the optimization of the co-ordinates and the lift profile using the computer code MATLAB. Then the co-ordinates and the parameters are inserted into a program written in Compaq Visual Fortran - version 6.6., which calculates 171 lift parameters, organized in 42 tables. The objective of the work presented in this paper is an attempt at computer modelling of the design and parameters derivation of the rope way systems and their computer variation and optimization.

Hybrid photovoltaic/thermal (PV/T) solar systems simulation with Simulink/Matlab

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

da Silva, R.M.; Fernandes, J.L.M.

The purpose of this work consists in thermodynamic modeling of hybrid photovoltaic-thermal (PV/T) solar systems, pursuing a modular strategy approach provided by Simulink/Matlab. PV/T solar systems are a recently emerging solar technology that allows for the simultaneous conversion of solar energy into both electricity and heat. This type of technology present some interesting advantages over the conventional ''side-by-side'' thermal and PV solar systems, such as higher combined electrical/thermal energy outputs per unit area, and a more uniform and aesthetical pleasant roof area. Despite the fact that early research on PV/T systems can be traced back to the seventies, only recentlymore » it has gained a renewed impetus. In this work, parametric studies and annual transient simulations of PV/T systems are undertaken in Simulink/Matlab. The obtained results show an average annual solar fraction of 67%, and a global overall efficiency of 24% (i.e. 15% thermal and 9% electrical), for a typical four-person single-family residence in Lisbon, with p-Si cells, and a collector area of 6 m{sup 2}. A sensitivity analysis performed on the PV/T collector suggests that the most important variable that should be addressed to improve thermal performance is the photovoltaic (PV) module emittance. Based on those results, some additional improvements are proposed, such as the use of vacuum, or a noble gas at low-pressure, to allow for the removal of PV cells encapsulation without air oxidation and degradation, and thus reducing the PV module emittance. Preliminary results show that this option allows for an 8% increase on optical thermal efficiency, and a substantial reduction of thermal losses, suggesting the possibility of working at higher fluid temperatures. The higher working temperatures negative effect in electrical efficiency was negligible, due to compensation by improved optical properties. The simulation results are compared with experimental data obtained from other authors and perform reasonably well. The Simulink modeling platform has been mainly used worldwide on simulation of control systems, digital signal processing and electric circuits, but there are very few examples of application to solar energy systems modeling. This work uses the modular environment of Simulink/Matlab to model individual PV/T system components, and to assemble the entire installation layout. The results show that the modular approach strategy provided by Matlab/Simulink environment is applicable to solar systems modeling, providing good code scalability, faster developing time, and simpler integration with external computational tools, when compared with traditional imperative-oriented programming languages. (author)« less

Valuation of exotic options in the framework of Levy processes

NASA Astrophysics Data System (ADS)

Milev, Mariyan; Georgieva, Svetla; Markovska, Veneta

2013-12-01

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

A MATLAB based 3D modeling and inversion code for MT data

NASA Astrophysics Data System (ADS)

Singh, Arun; Dehiya, Rahul; Gupta, Pravin K.; Israil, M.

2017-07-01

The development of a MATLAB based computer code, AP3DMT, for modeling and inversion of 3D Magnetotelluric (MT) data is presented. The code comprises two independent components: grid generator code and modeling/inversion code. The grid generator code performs model discretization and acts as an interface by generating various I/O files. The inversion code performs core computations in modular form - forward modeling, data functionals, sensitivity computations and regularization. These modules can be readily extended to other similar inverse problems like Controlled-Source EM (CSEM). The modular structure of the code provides a framework useful for implementation of new applications and inversion algorithms. The use of MATLAB and its libraries makes it more compact and user friendly. The code has been validated on several published models. To demonstrate its versatility and capabilities the results of inversion for two complex models are presented.

FocusStack and StimServer: a new open source MATLAB toolchain for visual stimulation and analysis of two-photon calcium neuronal imaging data.

PubMed

Muir, Dylan R; Kampa, Björn M

2014-01-01

Two-photon calcium imaging of neuronal responses is an increasingly accessible technology for probing population responses in cortex at single cell resolution, and with reasonable and improving temporal resolution. However, analysis of two-photon data is usually performed using ad-hoc solutions. To date, no publicly available software exists for straightforward analysis of stimulus-triggered two-photon imaging experiments. In addition, the increasing data rates of two-photon acquisition systems imply increasing cost of computing hardware required for in-memory analysis. Here we present a Matlab toolbox, FocusStack, for simple and efficient analysis of two-photon calcium imaging stacks on consumer-level hardware, with minimal memory footprint. We also present a Matlab toolbox, StimServer, for generation and sequencing of visual stimuli, designed to be triggered over a network link from a two-photon acquisition system. FocusStack is compatible out of the box with several existing two-photon acquisition systems, and is simple to adapt to arbitrary binary file formats. Analysis tools such as stack alignment for movement correction, automated cell detection and peri-stimulus time histograms are already provided, and further tools can be easily incorporated. Both packages are available as publicly-accessible source-code repositories.

FocusStack and StimServer: a new open source MATLAB toolchain for visual stimulation and analysis of two-photon calcium neuronal imaging data

PubMed Central

Muir, Dylan R.; Kampa, Björn M.

2015-01-01

Two-photon calcium imaging of neuronal responses is an increasingly accessible technology for probing population responses in cortex at single cell resolution, and with reasonable and improving temporal resolution. However, analysis of two-photon data is usually performed using ad-hoc solutions. To date, no publicly available software exists for straightforward analysis of stimulus-triggered two-photon imaging experiments. In addition, the increasing data rates of two-photon acquisition systems imply increasing cost of computing hardware required for in-memory analysis. Here we present a Matlab toolbox, FocusStack, for simple and efficient analysis of two-photon calcium imaging stacks on consumer-level hardware, with minimal memory footprint. We also present a Matlab toolbox, StimServer, for generation and sequencing of visual stimuli, designed to be triggered over a network link from a two-photon acquisition system. FocusStack is compatible out of the box with several existing two-photon acquisition systems, and is simple to adapt to arbitrary binary file formats. Analysis tools such as stack alignment for movement correction, automated cell detection and peri-stimulus time histograms are already provided, and further tools can be easily incorporated. Both packages are available as publicly-accessible source-code repositories1. PMID:25653614

Nuclear Fuel Depletion Analysis Using Matlab Software

NASA Astrophysics Data System (ADS)

Faghihi, F.; Nematollahi, M. R.

Coupled first order IVPs are frequently used in many parts of engineering and sciences. In this article, we presented a code including three computer programs which are joint with the Matlab software to solve and plot the solutions of the first order coupled stiff or non-stiff IVPs. Some engineering and scientific problems related to IVPs are given and fuel depletion (production of the 239Pu isotope) in a Pressurized Water Nuclear Reactor (PWR) are computed by the present code.

URDME: a modular framework for stochastic simulation of reaction-transport processes in complex geometries.

PubMed

Drawert, Brian; Engblom, Stefan; Hellander, Andreas

2012-06-22

Experiments in silico using stochastic reaction-diffusion models have emerged as an important tool in molecular systems biology. Designing computational software for such applications poses several challenges. Firstly, realistic lattice-based modeling for biological applications requires a consistent way of handling complex geometries, including curved inner- and outer boundaries. Secondly, spatiotemporal stochastic simulations are computationally expensive due to the fast time scales of individual reaction- and diffusion events when compared to the biological phenomena of actual interest. We therefore argue that simulation software needs to be both computationally efficient, employing sophisticated algorithms, yet in the same time flexible in order to meet present and future needs of increasingly complex biological modeling. We have developed URDME, a flexible software framework for general stochastic reaction-transport modeling and simulation. URDME uses Unstructured triangular and tetrahedral meshes to resolve general geometries, and relies on the Reaction-Diffusion Master Equation formalism to model the processes under study. An interface to a mature geometry and mesh handling external software (Comsol Multiphysics) provides for a stable and interactive environment for model construction. The core simulation routines are logically separated from the model building interface and written in a low-level language for computational efficiency. The connection to the geometry handling software is realized via a Matlab interface which facilitates script computing, data management, and post-processing. For practitioners, the software therefore behaves much as an interactive Matlab toolbox. At the same time, it is possible to modify and extend URDME with newly developed simulation routines. Since the overall design effectively hides the complexity of managing the geometry and meshes, this means that newly developed methods may be tested in a realistic setting already at an early stage of development. In this paper we demonstrate, in a series of examples with high relevance to the molecular systems biology community, that the proposed software framework is a useful tool for both practitioners and developers of spatial stochastic simulation algorithms. Through the combined efforts of algorithm development and improved modeling accuracy, increasingly complex biological models become feasible to study through computational methods. URDME is freely available at http://www.urdme.org.

GenSSI 2.0: multi-experiment structural identifiability analysis of SBML models.

PubMed

Ligon, Thomas S; Fröhlich, Fabian; Chis, Oana T; Banga, Julio R; Balsa-Canto, Eva; Hasenauer, Jan

2018-04-15

Mathematical modeling using ordinary differential equations is used in systems biology to improve the understanding of dynamic biological processes. The parameters of ordinary differential equation models are usually estimated from experimental data. To analyze a priori the uniqueness of the solution of the estimation problem, structural identifiability analysis methods have been developed. We introduce GenSSI 2.0, an advancement of the software toolbox GenSSI (Generating Series for testing Structural Identifiability). GenSSI 2.0 is the first toolbox for structural identifiability analysis to implement Systems Biology Markup Language import, state/parameter transformations and multi-experiment structural identifiability analysis. In addition, GenSSI 2.0 supports a range of MATLAB versions and is computationally more efficient than its previous version, enabling the analysis of more complex models. GenSSI 2.0 is an open-source MATLAB toolbox and available at https://github.com/genssi-developer/GenSSI. thomas.ligon@physik.uni-muenchen.de or jan.hasenauer@helmholtz-muenchen.de. Supplementary data are available at Bioinformatics online.

Operating a Geiger Müller tube using a PC sound card

NASA Astrophysics Data System (ADS)

Azooz, A. A.

2009-01-01

In this paper, a simple MATLAB-based PC program that enables the computer to function as a replacement for the electronic scalar-counter system associated with a Geiger-Müller (GM) tube is described. The program utilizes the ability of MATLAB to acquire data directly from the computer sound card. The signal from the GM tube is applied to the computer sound card via the line in port. All standard GM experiments, pulse shape and statistical analysis experiments can be carried out using this system. A new visual demonstration of dead time effects is also presented.

Switch of Sensitivity Dynamics Revealed with DyGloSA Toolbox for Dynamical Global Sensitivity Analysis as an Early Warning for System's Critical Transition

PubMed Central

Baumuratova, Tatiana; Dobre, Simona; Bastogne, Thierry; Sauter, Thomas

2013-01-01

Systems with bifurcations may experience abrupt irreversible and often unwanted shifts in their performance, called critical transitions. For many systems like climate, economy, ecosystems it is highly desirable to identify indicators serving as early warnings of such regime shifts. Several statistical measures were recently proposed as early warnings of critical transitions including increased variance, autocorrelation and skewness of experimental or model-generated data. The lack of automatized tool for model-based prediction of critical transitions led to designing DyGloSA – a MATLAB toolbox for dynamical global parameter sensitivity analysis (GPSA) of ordinary differential equations models. We suggest that the switch in dynamics of parameter sensitivities revealed by our toolbox is an early warning that a system is approaching a critical transition. We illustrate the efficiency of our toolbox by analyzing several models with bifurcations and predicting the time periods when systems can still avoid going to a critical transition by manipulating certain parameter values, which is not detectable with the existing SA techniques. DyGloSA is based on the SBToolbox2 and contains functions, which compute dynamically the global sensitivity indices of the system by applying four main GPSA methods: eFAST, Sobol's ANOVA, PRCC and WALS. It includes parallelized versions of the functions enabling significant reduction of the computational time (up to 12 times). DyGloSA is freely available as a set of MATLAB scripts at http://bio.uni.lu/systems_biology/software/dyglosa. It requires installation of MATLAB (versions R2008b or later) and the Systems Biology Toolbox2 available at www.sbtoolbox2.org. DyGloSA can be run on Windows and Linux systems, -32 and -64 bits. PMID:24367574

Switch of sensitivity dynamics revealed with DyGloSA toolbox for dynamical global sensitivity analysis as an early warning for system's critical transition.

PubMed

Baumuratova, Tatiana; Dobre, Simona; Bastogne, Thierry; Sauter, Thomas

2013-01-01

Systems with bifurcations may experience abrupt irreversible and often unwanted shifts in their performance, called critical transitions. For many systems like climate, economy, ecosystems it is highly desirable to identify indicators serving as early warnings of such regime shifts. Several statistical measures were recently proposed as early warnings of critical transitions including increased variance, autocorrelation and skewness of experimental or model-generated data. The lack of automatized tool for model-based prediction of critical transitions led to designing DyGloSA - a MATLAB toolbox for dynamical global parameter sensitivity analysis (GPSA) of ordinary differential equations models. We suggest that the switch in dynamics of parameter sensitivities revealed by our toolbox is an early warning that a system is approaching a critical transition. We illustrate the efficiency of our toolbox by analyzing several models with bifurcations and predicting the time periods when systems can still avoid going to a critical transition by manipulating certain parameter values, which is not detectable with the existing SA techniques. DyGloSA is based on the SBToolbox2 and contains functions, which compute dynamically the global sensitivity indices of the system by applying four main GPSA methods: eFAST, Sobol's ANOVA, PRCC and WALS. It includes parallelized versions of the functions enabling significant reduction of the computational time (up to 12 times). DyGloSA is freely available as a set of MATLAB scripts at http://bio.uni.lu/systems_biology/software/dyglosa. It requires installation of MATLAB (versions R2008b or later) and the Systems Biology Toolbox2 available at www.sbtoolbox2.org. DyGloSA can be run on Windows and Linux systems, -32 and -64 bits.

Modeling of diatomic molecule using the Morse potential and the Verlet algorithm

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

Fidiani, Elok

Performing molecular modeling usually uses special software for Molecular Dynamics (MD) such as: GROMACS, NAMD, JMOL etc. Molecular dynamics is a computational method to calculate the time dependent behavior of a molecular system. In this work, MATLAB was used as numerical method for a simple modeling of some diatomic molecules: HCl, H{sub 2} and O{sub 2}. MATLAB is a matrix based numerical software, in order to do numerical analysis, all the functions and equations describing properties of atoms and molecules must be developed manually in MATLAB. In this work, a Morse potential was generated to describe the bond interaction betweenmore » the two atoms. In order to analyze the simultaneous motion of molecules, the Verlet Algorithm derived from Newton’s Equations of Motion (classical mechanics) was operated. Both the Morse potential and the Verlet algorithm were integrated using MATLAB to derive physical properties and the trajectory of the molecules. The data computed by MATLAB is always in the form of a matrix. To visualize it, Visualized Molecular Dynamics (VMD) was performed. Such method is useful for development and testing some types of interaction on a molecular scale. Besides, this can be very helpful for describing some basic principles of molecular interaction for educational purposes.« less

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-06-26

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

Engineering and Scientific Applications: Using MatLab(Registered Trademark) for Data Processing and Visualization

NASA Technical Reports Server (NTRS)

Sen, Syamal K.; Shaykhian, Gholam Ali

2011-01-01

MatLab(R) (MATrix LABoratory) is a numerical computation and simulation tool that is used by thousands Scientists and Engineers in many cou ntries. MatLab does purely numerical calculations, which can be used as a glorified calculator or interpreter programming language; its re al strength is in matrix manipulations. Computer algebra functionalities are achieved within the MatLab environment using "symbolic" toolbo x. This feature is similar to computer algebra programs, provided by Maple or Mathematica to calculate with mathematical equations using s ymbolic operations. MatLab in its interpreter programming language fo rm (command interface) is similar with well known programming languag es such as C/C++, support data structures and cell arrays to define c lasses in object oriented programming. As such, MatLab is equipped with most ofthe essential constructs of a higher programming language. M atLab is packaged with an editor and debugging functionality useful t o perform analysis of large MatLab programs and find errors. We belie ve there are many ways to approach real-world problems; prescribed methods to ensure foregoing solutions are incorporated in design and ana lysis of data processing and visualization can benefit engineers and scientist in gaining wider insight in actual implementation of their perspective experiments. This presentation will focus on data processing and visualizations aspects of engineering and scientific applicati ons. Specifically, it will discuss methods and techniques to perform intermediate-level data processing covering engineering and scientifi c problems. MatLab programming techniques including reading various data files formats to produce customized publication-quality graphics, importing engineering and/or scientific data, organizing data in tabu lar format, exporting data to be used by other software programs such as Microsoft Excel, data presentation and visualization will be discussed. The presentation will emphasize creating practIcal scripts (pro grams) that extend the basic features of MatLab TOPICS mclude (1) Ma trix and vector analysis and manipulations (2) Mathematical functions (3) Symbolic calculations & functions (4) Import/export data files (5) Program lOgic and flow control (6) Writing function and passing parameters (7) Test application programs

Scilab and Maxima Environment: Towards Free Software in Numerical Analysis

ERIC Educational Resources Information Center

Mora, Angel; Galan, Jose Luis; Aguilera, Gabriel; Fernandez, Alvaro; Merida, Enrique; Rodriguez, Pedro

2010-01-01

In this work we will present the ScilabUMA environment we have developed as an alternative to Matlab. This environment connects Scilab (for numerical analysis) and Maxima (for symbolic computations). Furthermore, the developed interface is, in our opinion at least, as powerful as the interface of Matlab. (Contains 3 figures.)

Monte Carlo errors with less errors

NASA Astrophysics Data System (ADS)

Wolff, Ulli; Alpha Collaboration

2004-01-01

We explain in detail how to estimate mean values and assess statistical errors for arbitrary functions of elementary observables in Monte Carlo simulations. The method is to estimate and sum the relevant autocorrelation functions, which is argued to produce more certain error estimates than binning techniques and hence to help toward a better exploitation of expensive simulations. An effective integrated autocorrelation time is computed which is suitable to benchmark efficiencies of simulation algorithms with regard to specific observables of interest. A Matlab code is offered for download that implements the method. It can also combine independent runs (replica) allowing to judge their consistency.

[Application of the mixed programming with Labview and Matlab in biomedical signal analysis].

PubMed

Yu, Lu; Zhang, Yongde; Sha, Xianzheng

2011-01-01

This paper introduces the method of mixed programming with Labview and Matlab, and applies this method in a pulse wave pre-processing and feature detecting system. The method has been proved suitable, efficient and accurate, which has provided a new kind of approach for biomedical signal analysis.

FAST SIMULATION OF SOLID TUMORS THERMAL ABLATION TREATMENTS WITH A 3D REACTION DIFFUSION MODEL *

PubMed Central

BERTACCINI, DANIELE; CALVETTI, DANIELA

2007-01-01

An efficient computational method for near real-time simulation of thermal ablation of tumors via radio frequencies is proposed. Model simulations of the temperature field in a 3D portion of tissue containing the tumoral mass for different patterns of source heating can be used to design the ablation procedure. The availability of a very efficient computational scheme makes it possible update the predicted outcome of the procedure in real time. In the algorithms proposed here a discretization in space of the governing equations is followed by an adaptive time integration based on implicit multistep formulas. A modification of the ode15s MATLAB function which uses Krylov space iterative methods for the solution of for the linear systems arising at each integration step makes it possible to perform the simulations on standard desktop for much finer grids than using the built-in ode15s. The proposed algorithm can be applied to a wide class of nonlinear parabolic differential equations. PMID:17173888

ALGORITHMS AND PROGRAMS FOR STRONG GRAVITATIONAL LENSING IN KERR SPACE-TIME INCLUDING POLARIZATION

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

Chen, Bin; Maddumage, Prasad; Kantowski, Ronald

2015-05-15

Active galactic nuclei (AGNs) and quasars are important astrophysical objects to understand. Recently, microlensing observations have constrained the size of the quasar X-ray emission region to be of the order of 10 gravitational radii of the central supermassive black hole. For distances within a few gravitational radii, light paths are strongly bent by the strong gravity field of the central black hole. If the central black hole has nonzero angular momentum (spin), then a photon’s polarization plane will be rotated by the gravitational Faraday effect. The observed X-ray flux and polarization will then be influenced significantly by the strong gravitymore » field near the source. Consequently, linear gravitational lensing theory is inadequate for such extreme circumstances. We present simple algorithms computing the strong lensing effects of Kerr black holes, including the effects on polarization. Our algorithms are realized in a program “KERTAP” in two versions: MATLAB and Python. The key ingredients of KERTAP are a graphic user interface, a backward ray-tracing algorithm, a polarization propagator dealing with gravitational Faraday rotation, and algorithms computing observables such as flux magnification and polarization angles. Our algorithms can be easily realized in other programming languages such as FORTRAN, C, and C++. The MATLAB version of KERTAP is parallelized using the MATLAB Parallel Computing Toolbox and the Distributed Computing Server. The Python code was sped up using Cython and supports full implementation of MPI using the “mpi4py” package. As an example, we investigate the inclination angle dependence of the observed polarization and the strong lensing magnification of AGN X-ray emission. We conclude that it is possible to perform complex numerical-relativity related computations using interpreted languages such as MATLAB and Python.« less

Algorithms and Programs for Strong Gravitational Lensing In Kerr Space-time Including Polarization

NASA Astrophysics Data System (ADS)

Chen, Bin; Kantowski, Ronald; Dai, Xinyu; Baron, Eddie; Maddumage, Prasad

2015-05-01

Active galactic nuclei (AGNs) and quasars are important astrophysical objects to understand. Recently, microlensing observations have constrained the size of the quasar X-ray emission region to be of the order of 10 gravitational radii of the central supermassive black hole. For distances within a few gravitational radii, light paths are strongly bent by the strong gravity field of the central black hole. If the central black hole has nonzero angular momentum (spin), then a photon’s polarization plane will be rotated by the gravitational Faraday effect. The observed X-ray flux and polarization will then be influenced significantly by the strong gravity field near the source. Consequently, linear gravitational lensing theory is inadequate for such extreme circumstances. We present simple algorithms computing the strong lensing effects of Kerr black holes, including the effects on polarization. Our algorithms are realized in a program “KERTAP” in two versions: MATLAB and Python. The key ingredients of KERTAP are a graphic user interface, a backward ray-tracing algorithm, a polarization propagator dealing with gravitational Faraday rotation, and algorithms computing observables such as flux magnification and polarization angles. Our algorithms can be easily realized in other programming languages such as FORTRAN, C, and C++. The MATLAB version of KERTAP is parallelized using the MATLAB Parallel Computing Toolbox and the Distributed Computing Server. The Python code was sped up using Cython and supports full implementation of MPI using the “mpi4py” package. As an example, we investigate the inclination angle dependence of the observed polarization and the strong lensing magnification of AGN X-ray emission. We conclude that it is possible to perform complex numerical-relativity related computations using interpreted languages such as MATLAB and Python.

Case studies on optimization problems in MATLAB and COMSOL multiphysics by means of the livelink

NASA Astrophysics Data System (ADS)

Ozana, Stepan; Pies, Martin; Docekal, Tomas

2016-06-01

LiveLink for COMSOL is a tool that integrates COMSOL Multiphysics with MATLAB to extend one's modeling with scripting programming in the MATLAB environment. It allows user to utilize the full power of MATLAB and its toolboxes in preprocessing, model manipulation, and post processing. At first, the head script launches COMSOL with MATLAB and defines initial value of all parameters, refers to the objective function J described in the objective function and creates and runs the defined optimization task. Once the task is launches, the COMSOL model is being called in the iteration loop (from MATLAB environment by use of API interface), changing defined optimization parameters so that the objective function is minimized, using fmincon function to find a local or global minimum of constrained linear or nonlinear multivariable function. Once the minimum is found, it returns exit flag, terminates optimization and returns the optimized values of the parameters. The cooperation with MATLAB via LiveLink enhances a powerful computational environment with complex multiphysics simulations. The paper will introduce using of the LiveLink for COMSOL for chosen case studies in the field of technical cybernetics and bioengineering.

P-HS-SFM: a parallel harmony search algorithm for the reproduction of experimental data in the continuous microscopic crowd dynamic models

NASA Astrophysics Data System (ADS)

Jaber, Khalid Mohammad; Alia, Osama Moh'd.; Shuaib, Mohammed Mahmod

2018-03-01

Finding the optimal parameters that can reproduce experimental data (such as the velocity-density relation and the specific flow rate) is a very important component of the validation and calibration of microscopic crowd dynamic models. Heavy computational demand during parameter search is a known limitation that exists in a previously developed model known as the Harmony Search-Based Social Force Model (HS-SFM). In this paper, a parallel-based mechanism is proposed to reduce the computational time and memory resource utilisation required to find these parameters. More specifically, two MATLAB-based multicore techniques (parfor and create independent jobs) using shared memory are developed by taking advantage of the multithreading capabilities of parallel computing, resulting in a new framework called the Parallel Harmony Search-Based Social Force Model (P-HS-SFM). The experimental results show that the parfor-based P-HS-SFM achieved a better computational time of about 26 h, an efficiency improvement of ? 54% and a speedup factor of 2.196 times in comparison with the HS-SFM sequential processor. The performance of the P-HS-SFM using the create independent jobs approach is also comparable to parfor with a computational time of 26.8 h, an efficiency improvement of about 30% and a speedup of 2.137 times.

Tensor Toolbox for MATLAB v. 3.0

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

Kola, Tamara; Bader, Brett W.; Acar Ataman, Evrim NMN

Tensors (also known as multidimensional arrays or N-way arrays) are used in a variety of applications ranging from chemometrics to network analysis. The Tensor Toolbox provides classes for manipulating dense, sparse, and structured tensors using MATLAB's object-oriented features. It also provides algorithms for tensor decomposition and factorization, algorithms for computing tensor eigenvalues, and methods for visualization of results.

Efficient numerical method of freeform lens design for arbitrary irradiance shaping

NASA Astrophysics Data System (ADS)

Wojtanowski, Jacek

2018-05-01

A computational method to design a lens with a flat entrance surface and a freeform exit surface that can transform a collimated, generally non-uniform input beam into a beam with a desired irradiance distribution of arbitrary shape is presented. The methodology is based on non-linear elliptic partial differential equations, known as Monge-Ampère PDEs. This paper describes an original numerical algorithm to solve this problem by applying the Gauss-Seidel method with simplified boundary conditions. A joint MATLAB-ZEMAX environment is used to implement and verify the method. To prove the efficiency of the proposed approach, an exemplary study where the designed lens is faced with the challenging illumination task is shown. An analysis of solution stability, iteration-to-iteration ray mapping evolution (attached in video format), depth of focus and non-zero étendue efficiency is performed.

Algorithm 971: An Implementation of a Randomized Algorithm for Principal Component Analysis

PubMed Central

LI, HUAMIN; LINDERMAN, GEORGE C.; SZLAM, ARTHUR; STANTON, KELLY P.; KLUGER, YUVAL; TYGERT, MARK

2017-01-01

Recent years have witnessed intense development of randomized methods for low-rank approximation. These methods target principal component analysis and the calculation of truncated singular value decompositions. The present article presents an essentially black-box, foolproof implementation for Mathworks’ MATLAB, a popular software platform for numerical computation. As illustrated via several tests, the randomized algorithms for low-rank approximation outperform or at least match the classical deterministic techniques (such as Lanczos iterations run to convergence) in basically all respects: accuracy, computational efficiency (both speed and memory usage), ease-of-use, parallelizability, and reliability. However, the classical procedures remain the methods of choice for estimating spectral norms and are far superior for calculating the least singular values and corresponding singular vectors (or singular subspaces). PMID:28983138

Generalized Simulation Model for a Switched-Mode Power Supply Design Course Using MATLAB/SIMULINK

ERIC Educational Resources Information Center

Liao, Wei-Hsin; Wang, Shun-Chung; Liu, Yi-Hua

2012-01-01

Switched-mode power supplies (SMPS) are becoming an essential part of many electronic systems as the industry drives toward miniaturization and energy efficiency. However, practical SMPS design courses are seldom offered. In this paper, a generalized MATLAB/SIMULINK modeling technique is first presented. A proposed practical SMPS design course at…

Multiagent Systems Based Modeling and Implementation of Dynamic Energy Management of Smart Microgrid Using MACSimJX.

PubMed

Raju, Leo; Milton, R S; Mahadevan, Senthilkumaran

The objective of this paper is implementation of multiagent system (MAS) for the advanced distributed energy management and demand side management of a solar microgrid. Initially, Java agent development environment (JADE) frame work is used to implement MAS based dynamic energy management of solar microgrid. Due to unstable nature of MATLAB, when dealing with multithreading environment, MAS operating in JADE is linked with the MATLAB using a middle ware called Multiagent Control Using Simulink with Jade Extension (MACSimJX). MACSimJX allows the solar microgrid components designed with MATLAB to be controlled by the corresponding agents of MAS. The microgrid environment variables are captured through sensors and given to agents through MATLAB/Simulink and after the agent operations in JADE, the results are given to the actuators through MATLAB for the implementation of dynamic operation in solar microgrid. MAS operating in JADE maximizes operational efficiency of solar microgrid by decentralized approach and increase in runtime efficiency due to JADE. Autonomous demand side management is implemented for optimizing the power exchange between main grid and microgrid with intermittent nature of solar power, randomness of load, and variation of noncritical load and grid price. These dynamics are considered for every time step and complex environment simulation is designed to emulate the distributed microgrid operations and evaluate the impact of agent operations.

Multiagent Systems Based Modeling and Implementation of Dynamic Energy Management of Smart Microgrid Using MACSimJX

PubMed Central

Raju, Leo; Milton, R. S.; Mahadevan, Senthilkumaran

2016-01-01

The objective of this paper is implementation of multiagent system (MAS) for the advanced distributed energy management and demand side management of a solar microgrid. Initially, Java agent development environment (JADE) frame work is used to implement MAS based dynamic energy management of solar microgrid. Due to unstable nature of MATLAB, when dealing with multithreading environment, MAS operating in JADE is linked with the MATLAB using a middle ware called Multiagent Control Using Simulink with Jade Extension (MACSimJX). MACSimJX allows the solar microgrid components designed with MATLAB to be controlled by the corresponding agents of MAS. The microgrid environment variables are captured through sensors and given to agents through MATLAB/Simulink and after the agent operations in JADE, the results are given to the actuators through MATLAB for the implementation of dynamic operation in solar microgrid. MAS operating in JADE maximizes operational efficiency of solar microgrid by decentralized approach and increase in runtime efficiency due to JADE. Autonomous demand side management is implemented for optimizing the power exchange between main grid and microgrid with intermittent nature of solar power, randomness of load, and variation of noncritical load and grid price. These dynamics are considered for every time step and complex environment simulation is designed to emulate the distributed microgrid operations and evaluate the impact of agent operations. PMID:27127802

CMGTooL user's manual

USGS Publications Warehouse

Xu, Jingping; Lightsom, Fran; Noble, Marlene A.; Denham, Charles

2002-01-01

During the past several years, the sediment transport group in the Coastal and Marine Geology Program (CMGP) of the U. S. Geological Survey has made major revisions to its methodology of processing, analyzing, and maintaining the variety of oceanographic time-series data. First, CMGP completed the transition of the its oceanographic time-series database to a self-documenting NetCDF (Rew et al., 1997) data format. Second, CMGP’s oceanographic data variety and complexity have been greatly expanded from traditional 2-dimensional, single-point time-series measurements (e.g., Electro-magnetic current meters, transmissometers) to more advanced 3-dimensional and profiling time-series measurements due to many new acquisitions of modern instruments such as Acoustic Doppler Current Profiler (RDI, 1996), Acoustic Doppler Velocitimeter, Pulse-Coherence Acoustic Doppler Profiler (SonTek, 2001), Acoustic Bacscatter Sensor (Aquatec, 1001001001001001001). In order to accommodate the NetCDF format of data from the new instruments, a software package of processing, analyzing, and visualizing time-series oceanographic data was developed. It is named CMGTooL. The CMGTooL package contains two basic components: a user-friendly GUI for NetCDF file analysis, processing and manipulation; and a data analyzing program library. Most of the routines in the library are stand-alone programs suitable for batch processing. CMGTooL is written in MATLAB computing language (The Mathworks, 1997), therefore users must have MATLAB installed on their computer in order to use this software package. In addition, MATLAB’s Signal Processing Toolbox is also required by some CMGTooL’s routines. Like most MATLAB programs, all CMGTooL codes are compatible with different computing platforms including PC, MAC, and UNIX machines (Note: CMGTooL has been tested on different platforms that run MATLAB 5.2 (Release 10) or lower versions. Some of the commands related to MAC may not be compatible with later releases of MATLAB). The GUI and some of the library routines call low-level NetCDF file I/O, variable and attribute functions. These NetCDF exclusive functions are supported by a MATLAB toolbox named NetCDF, created by Dr. Charles Denham . This toolbox has to be installed in order to use the CMGTooL GUI. The CMGTooL GUI calls several routines that were initially developed by others. The authors would like to acknowledge the following scientists for their ideas and codes: Dr. Rich Signell (USGS), Dr. Chris Sherwood (USGS), and Dr. Bob Beardsley (WHOI). Many special terms that carry special meanings in either MATLAB or the NetCDF Toolbox are used in this manual. Users are encouraged to read the documents of MATLAB and NetCDF for references.

Computer-Aided Teaching Using MATLAB/Simulink for Enhancing an IM Course With Laboratory Tests

ERIC Educational Resources Information Center

Bentounsi, A.; Djeghloud, H.; Benalla, H.; Birem, T.; Amiar, H.

2011-01-01

This paper describes an automatic procedure using MATLAB software to plot the circle diagram for two induction motors (IMs), with wound and squirrel-cage rotors, from no-load and blocked-rotor tests. The advantage of this approach is that it avoids the need for a direct load test in predetermining the IM characteristics under reduced power.…

Computer Based Learning in an Undergraduate Physics Laboratory: Interfacing and Instrument Control Using Matlab

ERIC Educational Resources Information Center

Sharp, J. S.; Glover, P. M.; Moseley, W.

2007-01-01

In this paper we describe the recent changes to the curriculum of the second year practical laboratory course in the School of Physics and Astronomy at the University of Nottingham. In particular, we describe how Matlab has been implemented as a teaching tool and discuss both its pedagogical advantages and disadvantages in teaching undergraduate…

CAESY - COMPUTER AIDED ENGINEERING SYSTEM

NASA Technical Reports Server (NTRS)

Wette, M. R.

1994-01-01

Many developers of software and algorithms for control system design have recognized that current tools have limits in both flexibility and efficiency. Many forces drive the development of new tools including the desire to make complex system modeling design and analysis easier and the need for quicker turnaround time in analysis and design. Other considerations include the desire to make use of advanced computer architectures to help in control system design, adopt new methodologies in control, and integrate design processes (e.g., structure, control, optics). CAESY was developed to provide a means to evaluate methods for dealing with user needs in computer-aided control system design. It is an interpreter for performing engineering calculations and incorporates features of both Ada and MATLAB. It is designed to be reasonably flexible and powerful. CAESY includes internally defined functions and procedures, as well as user defined ones. Support for matrix calculations is provided in the same manner as MATLAB. However, the development of CAESY is a research project, and while it provides some features which are not found in commercially sold tools, it does not exhibit the robustness that many commercially developed tools provide. CAESY is written in C-language for use on Sun4 series computers running SunOS 4.1.1 and later. The program is designed to optionally use the LAPACK math library. The LAPACK math routines are available through anonymous ftp from research.att.com. CAESY requires 4Mb of RAM for execution. The standard distribution medium is a .25 inch streaming magnetic tape cartridge (QIC-24) in UNIX tar format. CAESY was developed in 1993 and is a copyrighted work with all copyright vested in NASA.

Three-dimensional rendering of segmented object using matlab - biomed 2010.

PubMed

Anderson, Jeffrey R; Barrett, Steven F

2010-01-01

The three-dimensional rendering of microscopic objects is a difficult and challenging task that often requires specialized image processing techniques. Previous work has been described of a semi-automatic segmentation process of fluorescently stained neurons collected as a sequence of slice images with a confocal laser scanning microscope. Once properly segmented, each individual object can be rendered and studied as a three-dimensional virtual object. This paper describes the work associated with the design and development of Matlab files to create three-dimensional images from the segmented object data previously mentioned. Part of the motivation for this work is to integrate both the segmentation and rendering processes into one software application, providing a seamless transition from the segmentation tasks to the rendering and visualization tasks. Previously these tasks were accomplished on two different computer systems, windows and Linux. This transition basically limits the usefulness of the segmentation and rendering applications to those who have both computer systems readily available. The focus of this work is to create custom Matlab image processing algorithms for object rendering and visualization, and merge these capabilities to the Matlab files that were developed especially for the image segmentation task. The completed Matlab application will contain both the segmentation and rendering processes in a single graphical user interface, or GUI. This process for rendering three-dimensional images in Matlab requires that a sequence of two-dimensional binary images, representing a cross-sectional slice of the object, be reassembled in a 3D space, and covered with a surface. Additional segmented objects can be rendered in the same 3D space. The surface properties of each object can be varied by the user to aid in the study and analysis of the objects. This inter-active process becomes a powerful visual tool to study and understand microscopic objects.

Maxis-A rezoning and remapping code in two dimensional cylindrical geometry

NASA Astrophysics Data System (ADS)

Lin, Zhiwei; Jiang, Shaoen; Zhang, Lu; Kuang, Longyu; Li, Hang

2018-06-01

This paper presents the new version of our code Maxis (Lin et al., 2011). Maxis is a local rezoning and remapping code in two dimensional cylindrical geometry, which can be employed to address the grid distortion problem of unstructured meshes. The new version of Maxis is mostly programmed in the C language which considerably improves its computational efficiency with respect to the former Matlab version. A new algorithm for determining the intersection of two arbitrary convex polygons is also incorporated into the new version. Some additional linking functions are further provided in the new version for the purpose of combining Maxis and MULTI2D.

Defining solar park location using shadow over time detection method

NASA Astrophysics Data System (ADS)

Martynov, Ivan; Kauranne, Tuomo

2016-06-01

There is nowadays a high demand for research on using renewable sources of energy including solar energy. The availability of stable and efficient solar energy is of paramount importance. Therefore, it is vital to install solar panels in locations which are most of the time not in shadow. To illustrate this idea we have developed a shadow identification method for digital elevation models (DEMs) using the computational means of MATLAB whose environment and tools allow fast and easy image processing. As a source of DEMs we use the Shuttle Radar Topography Mission (SRTM) database since it covers most of the terrain of our planet.

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.

Simulating electron energy loss spectroscopy with the MNPBEM toolbox

NASA Astrophysics Data System (ADS)

Hohenester, Ulrich

2014-03-01

Within the MNPBEM toolbox, we show how to simulate electron energy loss spectroscopy (EELS) of plasmonic nanoparticles using a boundary element method approach. The methodology underlying our approach closely follows the concepts developed by García de Abajo and coworkers (Garcia de Abajo, 2010). We introduce two classes eelsret and eelsstat that allow in combination with our recently developed MNPBEM toolbox for a simple, robust, and efficient computation of EEL spectra and maps. The classes are accompanied by a number of demo programs for EELS simulation of metallic nanospheres, nanodisks, and nanotriangles, and for electron trajectories passing by or penetrating through the metallic nanoparticles. We also discuss how to compute electric fields induced by the electron beam and cathodoluminescence. Catalogue identifier: AEKJ_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKJ_v2_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 38886 No. of bytes in distributed program, including test data, etc.: 1222650 Distribution format: tar.gz Programming language: Matlab 7.11.0 (R2010b). Computer: Any which supports Matlab 7.11.0 (R2010b). Operating system: Any which supports Matlab 7.11.0 (R2010b). RAM:≥1 GB Classification: 18. Catalogue identifier of previous version: AEKJ_v1_0 Journal reference of previous version: Comput. Phys. Comm. 183 (2012) 370 External routines: MESH2D available at www.mathworks.com Does the new version supersede the previous version?: Yes Nature of problem: Simulation of electron energy loss spectroscopy (EELS) for plasmonic nanoparticles. Solution method: Boundary element method using electromagnetic potentials. Reasons for new version: The new version of the toolbox includes two additional classes for the simulation of electron energy loss spectroscopy (EELS) of plasmonic nanoparticles, and corrects a few minor bugs and inconsistencies. Summary of revisions: New classes “eelsstat” and “eelsret” for the simulation of electron energy loss spectroscopy (EELS) of plasmonic nanoparticles have been added. A few minor errors in the implementation of dipole excitation have been corrected. Running time: Depending on surface discretization between seconds and hours.

MATLAB-implemented estimation procedure for model-based assessment of hepatic insulin degradation from standard intravenous glucose tolerance test data.

PubMed

Di Nardo, Francesco; Mengoni, Michele; Morettini, Micaela

2013-05-01

Present study provides a novel MATLAB-based parameter estimation procedure for individual assessment of hepatic insulin degradation (HID) process from standard frequently-sampled intravenous glucose tolerance test (FSIGTT) data. Direct access to the source code, offered by MATLAB, enabled us to design an optimization procedure based on the alternating use of Gauss-Newton's and Levenberg-Marquardt's algorithms, which assures the full convergence of the process and the containment of computational time. Reliability was tested by direct comparison with the application, in eighteen non-diabetic subjects, of well-known kinetic analysis software package SAAM II, and by application on different data. Agreement between MATLAB and SAAM II was warranted by intraclass correlation coefficients ≥0.73; no significant differences between corresponding mean parameter estimates and prediction of HID rate; and consistent residual analysis. Moreover, MATLAB optimization procedure resulted in a significant 51% reduction of CV% for the worst-estimated parameter by SAAM II and in maintaining all model-parameter CV% <20%. In conclusion, our MATLAB-based procedure was suggested as a suitable tool for the individual assessment of HID process. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Computational methods for yeast prion curing curves.

PubMed

Ridout, Martin S

2008-10-01

If the chemical guanidine hydrochloride is added to a dividing culture of yeast cells in which some of the protein Sup35p is in its prion form, the proportion of cells that carry replicating units of the prion, termed propagons, decreases gradually over time. Stochastic models to describe this process of 'curing' have been developed in earlier work. The present paper investigates the use of numerical methods of Laplace transform inversion to calculate curing curves and contrasts this with an alternative, more direct, approach that involves numerical integration. Transform inversion is found to provide a much more efficient computational approach that allows different models to be investigated with minimal programming effort. The method is used to investigate the robustness of the curing curve to changes in the assumed distribution of cell generation times. Matlab code is available for carrying out the calculations.

Resources and Approaches for Teaching Quantitative and Computational Skills in the Geosciences and Allied Fields

NASA Astrophysics Data System (ADS)

Orr, C. H.; Mcfadden, R. R.; Manduca, C. A.; Kempler, L. A.

2016-12-01

Teaching with data, simulations, and models in the geosciences can increase many facets of student success in the classroom, and in the workforce. Teaching undergraduates about programming and improving students' quantitative and computational skills expands their perception of Geoscience beyond field-based studies. Processing data and developing quantitative models are critically important for Geoscience students. Students need to be able to perform calculations, analyze data, create numerical models and visualizations, and more deeply understand complex systems—all essential aspects of modern science. These skills require students to have comfort and skill with languages and tools such as MATLAB. To achieve comfort and skill, computational and quantitative thinking must build over a 4-year degree program across courses and disciplines. However, in courses focused on Geoscience content it can be challenging to get students comfortable with using computational methods to answers Geoscience questions. To help bridge this gap, we have partnered with MathWorks to develop two workshops focused on collecting and developing strategies and resources to help faculty teach students to incorporate data, simulations, and models into the curriculum at the course and program levels. We brought together faculty members from the sciences, including Geoscience and allied fields, who teach computation and quantitative thinking skills using MATLAB to build a resource collection for teaching. These materials, and the outcomes of the workshops are freely available on our website. The workshop outcomes include a collection of teaching activities, essays, and course descriptions that can help faculty incorporate computational skills at the course or program level. The teaching activities include in-class assignments, problem sets, labs, projects, and toolboxes. These activities range from programming assignments to creating and using models. The outcomes also include workshop syntheses that highlights best practices, a set of webpages to support teaching with software such as MATLAB, and an interest group actively discussing aspects these issues in Geoscience and allied fields. Learn more and view the resources at http://serc.carleton.edu/matlab_computation2016/index.html

Fault detection and diagnosis of photovoltaic systems

NASA Astrophysics Data System (ADS)

Wu, Xing

The rapid growth of the solar industry over the past several years has expanded the significance of photovoltaic (PV) systems. One of the primary aims of research in building-integrated PV systems is to improve the performance of the system's efficiency, availability, and reliability. Although much work has been done on technological design to increase a photovoltaic module's efficiency, there is little research so far on fault diagnosis for PV systems. Faults in a PV system, if not detected, may not only reduce power generation, but also threaten the availability and reliability, effectively the "security" of the whole system. In this paper, first a circuit-based simulation baseline model of a PV system with maximum power point tracking (MPPT) is developed using MATLAB software. MATLAB is one of the most popular tools for integrating computation, visualization and programming in an easy-to-use modeling environment. Second, data collection of a PV system at variable surface temperatures and insolation levels under normal operation is acquired. The developed simulation model of PV system is then calibrated and improved by comparing modeled I-V and P-V characteristics with measured I--V and P--V characteristics to make sure the simulated curves are close to those measured values from the experiments. Finally, based on the circuit-based simulation model, a PV model of various types of faults will be developed by changing conditions or inputs in the MATLAB model, and the I--V and P--V characteristic curves, and the time-dependent voltage and current characteristics of the fault modalities will be characterized for each type of fault. These will be developed as benchmark I-V or P-V, or prototype transient curves. If a fault occurs in a PV system, polling and comparing actual measured I--V and P--V characteristic curves with both normal operational curves and these baseline fault curves will aid in fault diagnosis.

Real-Time-Simulation of IEEE-5-Bus Network on OPAL-RT-OP4510 Simulator

NASA Astrophysics Data System (ADS)

Atul Bhandakkar, Anjali; Mathew, Lini, Dr.

2018-03-01

The Real-Time Simulator tools have high computing technologies, improved performance. They are widely used for design and improvement of electrical systems. The advancement of the software tools like MATLAB/SIMULINK with its Real-Time Workshop (RTW) and Real-Time Windows Target (RTWT), real-time simulators are used extensively in many engineering fields, such as industry, education, and research institutions. OPAL-RT-OP4510 is a Real-Time Simulator which is used in both industry and academia. In this paper, the real-time simulation of IEEE-5-Bus network is carried out by means of OPAL-RT-OP4510 with CRO and other hardware. The performance of the network is observed with the introduction of fault at various locations. The waveforms of voltage, current, active and reactive power are observed in the MATLAB simulation environment and on the CRO. Also, Load Flow Analysis (LFA) of IEEE-5-Bus network is computed using MATLAB/Simulink power-gui load flow tool.

Novel Method to Efficiently Create an mHealth App: Implementation of a Real-Time Electrocardiogram R Peak Detector.

PubMed

Gliner, Vadim; Behar, Joachim; Yaniv, Yael

2018-05-22

In parallel to the introduction of mobile communication devices with high computational power and internet connectivity, high-quality and low-cost health sensors have also become available. However, although the technology does exist, no clinical mobile system has been developed to monitor the R peaks from electrocardiogram recordings in real time with low false positive and low false negative detection. Implementation of a robust electrocardiogram R peak detector for various arrhythmogenic events has been hampered by the lack of an efficient design that will conserve battery power without reducing algorithm complexity or ease of implementation. Our goals in this paper are (1) to evaluate the suitability of the MATLAB Mobile platform for mHealth apps and whether it can run on any phone system, and (2) to embed in the MATLAB Mobile platform a real-time electrocardiogram R peak detector with low false positive and low false negative detection in the presence of the most frequent arrhythmia, atrial fibrillation. We implemented an innovative R peak detection algorithm that deals with motion artifacts, electrical drift, breathing oscillations, electrical spikes, and environmental noise by low-pass filtering. It also fixes the signal polarity and deals with premature beats by heuristic filtering. The algorithm was trained on the annotated non-atrial fibrillation MIT-BIH Arrhythmia Database and tested on the atrial fibrillation MIT-BIH Arrhythmia Database. Finally, the algorithm was implemented on mobile phones connected to a mobile electrocardiogram device using the MATLAB Mobile platform. Our algorithm precisely detected the R peaks with a sensitivity of 99.7% and positive prediction of 99.4%. These results are superior to some state-of-the-art algorithms. The algorithm performs similarly on atrial fibrillation and non-atrial fibrillation patient data. Using MATLAB Mobile, we ran our algorithm in less than an hour on both the iOS and Android system. Our app can accurately analyze 1 minute of real-time electrocardiogram signals in less than 1 second on a mobile phone. Accurate real-time identification of heart rate on a beat-to-beat basis in the presence of noise and atrial fibrillation events using a mobile phone is feasible. ©Vadim Gliner, Joachim Behar, Yael Yaniv. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 22.05.2018.

Generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB.

PubMed

Lee, Leng-Feng; Umberger, Brian R

2016-01-01

Computer modeling, simulation and optimization are powerful tools that have seen increased use in biomechanics research. Dynamic optimizations can be categorized as either data-tracking or predictive problems. The data-tracking approach has been used extensively to address human movement problems of clinical relevance. The predictive approach also holds great promise, but has seen limited use in clinical applications. Enhanced software tools would facilitate the application of predictive musculoskeletal simulations to clinically-relevant research. The open-source software OpenSim provides tools for generating tracking simulations but not predictive simulations. However, OpenSim includes an extensive application programming interface that permits extending its capabilities with scripting languages such as MATLAB. In the work presented here, we combine the computational tools provided by MATLAB with the musculoskeletal modeling capabilities of OpenSim to create a framework for generating predictive simulations of musculoskeletal movement based on direct collocation optimal control techniques. In many cases, the direct collocation approach can be used to solve optimal control problems considerably faster than traditional shooting methods. Cyclical and discrete movement problems were solved using a simple 1 degree of freedom musculoskeletal model and a model of the human lower limb, respectively. The problems could be solved in reasonable amounts of time (several seconds to 1-2 hours) using the open-source IPOPT solver. The problems could also be solved using the fmincon solver that is included with MATLAB, but the computation times were excessively long for all but the smallest of problems. The performance advantage for IPOPT was derived primarily by exploiting sparsity in the constraints Jacobian. The framework presented here provides a powerful and flexible approach for generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB. This should allow researchers to more readily use predictive simulation as a tool to address clinical conditions that limit human mobility.

Generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB

PubMed Central

Lee, Leng-Feng

2016-01-01

Computer modeling, simulation and optimization are powerful tools that have seen increased use in biomechanics research. Dynamic optimizations can be categorized as either data-tracking or predictive problems. The data-tracking approach has been used extensively to address human movement problems of clinical relevance. The predictive approach also holds great promise, but has seen limited use in clinical applications. Enhanced software tools would facilitate the application of predictive musculoskeletal simulations to clinically-relevant research. The open-source software OpenSim provides tools for generating tracking simulations but not predictive simulations. However, OpenSim includes an extensive application programming interface that permits extending its capabilities with scripting languages such as MATLAB. In the work presented here, we combine the computational tools provided by MATLAB with the musculoskeletal modeling capabilities of OpenSim to create a framework for generating predictive simulations of musculoskeletal movement based on direct collocation optimal control techniques. In many cases, the direct collocation approach can be used to solve optimal control problems considerably faster than traditional shooting methods. Cyclical and discrete movement problems were solved using a simple 1 degree of freedom musculoskeletal model and a model of the human lower limb, respectively. The problems could be solved in reasonable amounts of time (several seconds to 1–2 hours) using the open-source IPOPT solver. The problems could also be solved using the fmincon solver that is included with MATLAB, but the computation times were excessively long for all but the smallest of problems. The performance advantage for IPOPT was derived primarily by exploiting sparsity in the constraints Jacobian. The framework presented here provides a powerful and flexible approach for generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB. This should allow researchers to more readily use predictive simulation as a tool to address clinical conditions that limit human mobility. PMID:26835184

WinHPC System | High-Performance Computing | NREL

Science.gov Websites

System WinHPC System NREL's WinHPC system is a computing cluster running the Microsoft Windows operating system. It allows users to run jobs requiring a Windows environment such as ANSYS and MATLAB

The pipeline system for Octave and Matlab (PSOM): a lightweight scripting framework and execution engine for scientific workflows.

PubMed

Bellec, Pierre; Lavoie-Courchesne, Sébastien; Dickinson, Phil; Lerch, Jason P; Zijdenbos, Alex P; Evans, Alan C

2012-01-01

The analysis of neuroimaging databases typically involves a large number of inter-connected steps called a pipeline. The pipeline system for Octave and Matlab (PSOM) is a flexible framework for the implementation of pipelines in the form of Octave or Matlab scripts. PSOM does not introduce new language constructs to specify the steps and structure of the workflow. All steps of analysis are instead described by a regular Matlab data structure, documenting their associated command and options, as well as their input, output, and cleaned-up files. The PSOM execution engine provides a number of automated services: (1) it executes jobs in parallel on a local computing facility as long as the dependencies between jobs allow for it and sufficient resources are available; (2) it generates a comprehensive record of the pipeline stages and the history of execution, which is detailed enough to fully reproduce the analysis; (3) if an analysis is started multiple times, it executes only the parts of the pipeline that need to be reprocessed. PSOM is distributed under an open-source MIT license and can be used without restriction for academic or commercial projects. The package has no external dependencies besides Matlab or Octave, is straightforward to install and supports of variety of operating systems (Linux, Windows, Mac). We ran several benchmark experiments on a public database including 200 subjects, using a pipeline for the preprocessing of functional magnetic resonance images (fMRI). The benchmark results showed that PSOM is a powerful solution for the analysis of large databases using local or distributed computing resources.

The pipeline system for Octave and Matlab (PSOM): a lightweight scripting framework and execution engine for scientific workflows

PubMed Central

Bellec, Pierre; Lavoie-Courchesne, Sébastien; Dickinson, Phil; Lerch, Jason P.; Zijdenbos, Alex P.; Evans, Alan C.

2012-01-01

The analysis of neuroimaging databases typically involves a large number of inter-connected steps called a pipeline. The pipeline system for Octave and Matlab (PSOM) is a flexible framework for the implementation of pipelines in the form of Octave or Matlab scripts. PSOM does not introduce new language constructs to specify the steps and structure of the workflow. All steps of analysis are instead described by a regular Matlab data structure, documenting their associated command and options, as well as their input, output, and cleaned-up files. The PSOM execution engine provides a number of automated services: (1) it executes jobs in parallel on a local computing facility as long as the dependencies between jobs allow for it and sufficient resources are available; (2) it generates a comprehensive record of the pipeline stages and the history of execution, which is detailed enough to fully reproduce the analysis; (3) if an analysis is started multiple times, it executes only the parts of the pipeline that need to be reprocessed. PSOM is distributed under an open-source MIT license and can be used without restriction for academic or commercial projects. The package has no external dependencies besides Matlab or Octave, is straightforward to install and supports of variety of operating systems (Linux, Windows, Mac). We ran several benchmark experiments on a public database including 200 subjects, using a pipeline for the preprocessing of functional magnetic resonance images (fMRI). The benchmark results showed that PSOM is a powerful solution for the analysis of large databases using local or distributed computing resources. PMID:22493575

MATLAB algorithm to implement soil water data assimilation with the Ensemble Kalman Filter using HYDRUS.

PubMed

Valdes-Abellan, Javier; Pachepsky, Yakov; Martinez, Gonzalo

2018-01-01

Data assimilation is becoming a promising technique in hydrologic modelling to update not only model states but also to infer model parameters, specifically to infer soil hydraulic properties in Richard-equation-based soil water models. The Ensemble Kalman Filter method is one of the most widely employed method among the different data assimilation alternatives. In this study the complete Matlab© code used to study soil data assimilation efficiency under different soil and climatic conditions is shown. The code shows the method how data assimilation through EnKF was implemented. Richards equation was solved by the used of Hydrus-1D software which was run from Matlab. •MATLAB routines are released to be used/modified without restrictions for other researchers•Data assimilation Ensemble Kalman Filter method code.•Soil water Richard equation flow solved by Hydrus-1D.

Flight Dynamics and Control of a Morphing UAV: Bio inspired by Natural Fliers

DTIC Science & Technology

2017-02-17

Approved for public release: distribution unlimited. IV Modelling and Sizing Tornado Vortex Lattice Method (VLM) was used for aerodynamic prediction... Tornado is a Vortex Lattice Method software programmed in MATLAB; it was selected due to its fast solving time and ability to be controlled through...custom MATLAB scripts. Tornado VLM models the wing as thin sheet of discrete vortices and computes the pressure and force distributions around the

Virtual experiment of optical spatial filtering in Matlab environment

NASA Astrophysics Data System (ADS)

Ji, Yunjing; Wang, Chunyong; Song, Yang; Lai, Jiancheng; Wang, Qinghua; Qi, Jing; Shen, Zhonghua

2017-08-01

The principle of spatial filtering experiment has been introduced, and the computer simulation platform with graphical user interface (GUI) has been made out in Matlab environment. Using it various filtering processes for different input image or different filtering purpose will be completed accurately, and filtering effect can be observed clearly with adjusting experimental parameters. The physical nature of the optical spatial filtering can be showed vividly, and so experimental teaching effect will be promoted.

Improvement of the Performance of an Electrocoagulation Process System Using Fuzzy Control of pH.

PubMed

Demirci, Yavuz; Pekel, Lutfiye Canan; Altinten, Ayla; Alpbaz, Mustafa

2015-12-01

The removal efficiencies of electrocoagulation (EC) systems are highly dependent on the initial value of pH. If an EC system has an acidic influent, the pH of the effluent increases during the treatment process; conversely, if such a system has an alkaline influent, the pH of the effluent decreases during the treatment process. Thus, changes in the pH of the wastewater affect the efficiency of the EC process. In this study, we investigated the dynamic effects of pH. To evaluate approaches for preventing increases in the pH of the system, the MATLAB/Simulink program was used to develop and evaluate an on-line computer-based system for pH control. The aim of this work was to study Proportional-Integral-Derivative (PID) control and fuzzy control of the pH of a real textile wastewater purification process using EC. The performances and dynamic behaviors of these two control systems were evaluated based on determinations of COD, colour, and turbidity removal efficiencies.

Coolant Design System for Liquid Propellant Aerospike Engines

NASA Astrophysics Data System (ADS)

McConnell, Miranda; Branam, Richard

2015-11-01

Liquid propellant rocket engines burn at incredibly high temperatures making it difficult to design an effective coolant system. These particular engines prove to be extremely useful by powering the rocket with a variable thrust that is ideal for space travel. When combined with aerospike engine nozzles, which provide maximum thrust efficiency, this class of rockets offers a promising future for rocketry. In order to troubleshoot the problems that high combustion chamber temperatures pose, this research took a computational approach to heat analysis. Chambers milled into the combustion chamber walls, lined by a copper cover, were tested for their efficiency in cooling the hot copper wall. Various aspect ratios and coolants were explored for the maximum wall temperature by developing our own MATLAB code. The code uses a nodal temperature analysis with conduction and convection equations and assumes no internal heat generation. This heat transfer research will show oxygen is a better coolant than water, and higher aspect ratios are less efficient at cooling. This project funded by NSF REU Grant 1358991.

A Series of Computational Neuroscience Labs Increases Comfort with MATLAB.

PubMed

Nichols, David F

2015-01-01

Computational simulations allow for a low-cost, reliable means to demonstrate complex and often times inaccessible concepts to undergraduates. However, students without prior computer programming training may find working with code-based simulations to be intimidating and distracting. A series of computational neuroscience labs involving the Hodgkin-Huxley equations, an Integrate-and-Fire model, and a Hopfield Memory network were used in an undergraduate neuroscience laboratory component of an introductory level course. Using short focused surveys before and after each lab, student comfort levels were shown to increase drastically from a majority of students being uncomfortable or with neutral feelings about working in the MATLAB environment to a vast majority of students being comfortable working in the environment. Though change was reported within each lab, a series of labs was necessary in order to establish a lasting high level of comfort. Comfort working with code is important as a first step in acquiring computational skills that are required to address many questions within neuroscience.

A Series of Computational Neuroscience Labs Increases Comfort with MATLAB

PubMed Central

Nichols, David F.

2015-01-01

Computational simulations allow for a low-cost, reliable means to demonstrate complex and often times inaccessible concepts to undergraduates. However, students without prior computer programming training may find working with code-based simulations to be intimidating and distracting. A series of computational neuroscience labs involving the Hodgkin-Huxley equations, an Integrate-and-Fire model, and a Hopfield Memory network were used in an undergraduate neuroscience laboratory component of an introductory level course. Using short focused surveys before and after each lab, student comfort levels were shown to increase drastically from a majority of students being uncomfortable or with neutral feelings about working in the MATLAB environment to a vast majority of students being comfortable working in the environment. Though change was reported within each lab, a series of labs was necessary in order to establish a lasting high level of comfort. Comfort working with code is important as a first step in acquiring computational skills that are required to address many questions within neuroscience. PMID:26557798

A vectorized algorithm for 3D dynamics of a tethered satellite

NASA Technical Reports Server (NTRS)

Wilson, Howard B.

1989-01-01

Equations of motion characterizing the three dimensional motion of a tethered satellite during the retrieval phase are studied. The mathematical model involves an arbitrary number of point masses connected by weightless cords. Motion occurs in a gravity gradient field. The formulation presented accounts for general functions describing support point motion, rate of tether retrieval, and arbitrary forces applied to the point masses. The matrix oriented program language MATLAB is used to produce an efficient vectorized formulation for computing natural frequencies and mode shapes for small oscillations about the static equilibrium configuration; and for integrating the nonlinear differential equations governing large amplitude motions. An example of time response pertaining to the skip rope effect is investigated.

An Optimization Framework for Dynamic Hybrid Energy Systems

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

Wenbo Du; Humberto E Garcia; Christiaan J.J. Paredis

A computational framework for the efficient analysis and optimization of dynamic hybrid energy systems (HES) is developed. A microgrid system with multiple inputs and multiple outputs (MIMO) is modeled using the Modelica language in the Dymola environment. The optimization loop is implemented in MATLAB, with the FMI Toolbox serving as the interface between the computational platforms. Two characteristic optimization problems are selected to demonstrate the methodology and gain insight into the system performance. The first is an unconstrained optimization problem that optimizes the dynamic properties of the battery, reactor and generator to minimize variability in the HES. The second problemmore » takes operating and capital costs into consideration by imposing linear and nonlinear constraints on the design variables. The preliminary optimization results obtained in this study provide an essential step towards the development of a comprehensive framework for designing HES.« less

Electro-optic Mach-Zehnder Interferometer based Optical Digital Magnitude Comparator and 1's Complement Calculator

NASA Astrophysics Data System (ADS)

Kumar, Ajay; Raghuwanshi, Sanjeev Kumar

2016-06-01

The optical switching activity is one of the most essential phenomena in the optical domain. The electro-optic effect-based switching phenomena are applicable to generate some effective combinational and sequential logic circuits. The processing of digital computational technique in the optical domain includes some considerable advantages of optical communication technology, e.g. immunity to electro-magnetic interferences, compact size, signal security, parallel computing and larger bandwidth. The paper describes some efficient technique to implement single bit magnitude comparator and 1's complement calculator using the concepts of electro-optic effect. The proposed techniques are simulated on the MATLAB software. However, the suitability of the techniques is verified using the highly reliable Opti-BPM software. It is interesting to analyze the circuits in order to specify some optimized device parameter in order to optimize some performance affecting parameters, e.g. crosstalk, extinction ratio, signal losses through the curved and straight waveguide sections.

Error-Free Text Typing Performance of an Inductive Intra-Oral Tongue Computer Interface for Severely Disabled Individuals.

PubMed

Andreasen Struijk, Lotte N S; Bentsen, Bo; Gaihede, Michael; Lontis, Eugen R

2017-11-01

For severely paralyzed individuals, alternative computer interfaces are becoming increasingly essential for everyday life as social and vocational activities are facilitated by information technology and as the environment becomes more automatic and remotely controllable. Tongue computer interfaces have proven to be desirable by the users partly due to their high degree of aesthetic acceptability, but so far the mature systems have shown a relatively low error-free text typing efficiency. This paper evaluated the intra-oral inductive tongue computer interface (ITCI) in its intended use: Error-free text typing in a generally available text editing system, Word. Individuals with tetraplegia and able bodied individuals used the ITCI for typing using a MATLAB interface and for Word typing for 4 to 5 experimental days, and the results showed an average error-free text typing rate in Word of 11.6 correct characters/min across all participants and of 15.5 correct characters/min for participants familiar with tongue piercings. Improvements in typing rates between the sessions suggest that typing ratescan be improved further through long-term use of the ITCI.

ANSYS-MATLAB co-simulation of mucus flow distribution and clearance effectiveness of a new simulated cough device.

PubMed

Ren, Shuai; Shi, Yan; Cai, Maolin; Zhao, Hongmei; Zhang, Zhaozhi; Zhang, Xiaohua Douglas

2018-06-01

Coughing is an irritable reaction that protects the respiratory system from infection and improves mucus clearance. However, for the patients who cannot cough autonomously, an assisted cough device is essential for mucus clearance. Considering the low efficiency of current assisted cough devices, a new simulated cough device based on the pneumatic system is proposed in this paper. Given the uncertainty of airflow rates necessary to clear mucus from airways, the computational fluid dynamics Eulerian wall film model and cough efficiency (CE) were used in this study to simulate the cough process and evaluate cough effectiveness. The Ansys-Matlab co-simulation model was set up and verified through experimental studies using Newtonian fluids. Next, model simulations were performed using non-Newtonian fluids, and peak cough flow (PCF) and PCF duration time were analyzed to determine their influence on mucus clearance. CE growth rate (λ) was calculated to reflect the CE variation trend. From the numerical simulation results, we find that CE rises as PCF increases while the growth rate trends to slow as PCF increases; when PCF changes from 60 to 360 L/min, CE changes from 3.2% to 51.5% which is approximately 16 times the initial value. Meanwhile, keeping a long PCF duration time could greatly improve CE under the same cough expired volume and PCF. The results indicated that increasing the PCF and PCF duration time can improve the efficiency of mucus clearance. This paper provides a new approach and a research direction for control strategy in simulated cough devices for airway mucus clearance. Copyright © 2018 John Wiley & Sons, Ltd.

Spectral identification of topological domains

PubMed Central

Chen, Jie; Hero, Alfred O.; Rajapakse, Indika

2016-01-01

Motivation: Topological domains have been proposed as the backbone of interphase chromosome structure. They are regions of high local contact frequency separated by sharp boundaries. Genes within a domain often have correlated transcription. In this paper, we present a computational efficient spectral algorithm to identify topological domains from chromosome conformation data (Hi-C data). We consider the genome as a weighted graph with vertices defined by loci on a chromosome and the edge weights given by interaction frequency between two loci. Laplacian-based graph segmentation is then applied iteratively to obtain the domains at the given compactness level. Comparison with algorithms in the literature shows the advantage of the proposed strategy. Results: An efficient algorithm is presented to identify topological domains from the Hi-C matrix. Availability and Implementation: The Matlab source code and illustrative examples are available at http://bionetworks.ccmb.med.umich.edu/ Contact: indikar@med.umich.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153657

UmUTracker: A versatile MATLAB program for automated particle tracking of 2D light microscopy or 3D digital holography data

NASA Astrophysics Data System (ADS)

Zhang, Hanqing; Stangner, Tim; Wiklund, Krister; Rodriguez, Alvaro; Andersson, Magnus

2017-10-01

We present a versatile and fast MATLAB program (UmUTracker) that automatically detects and tracks particles by analyzing video sequences acquired by either light microscopy or digital in-line holographic microscopy. Our program detects the 2D lateral positions of particles with an algorithm based on the isosceles triangle transform, and reconstructs their 3D axial positions by a fast implementation of the Rayleigh-Sommerfeld model using a radial intensity profile. To validate the accuracy and performance of our program, we first track the 2D position of polystyrene particles using bright field and digital holographic microscopy. Second, we determine the 3D particle position by analyzing synthetic and experimentally acquired holograms. Finally, to highlight the full program features, we profile the microfluidic flow in a 100 μm high flow chamber. This result agrees with computational fluid dynamic simulations. On a regular desktop computer UmUTracker can detect, analyze, and track multiple particles at 5 frames per second for a template size of 201 ×201 in a 1024 × 1024 image. To enhance usability and to make it easy to implement new functions we used object-oriented programming. UmUTracker is suitable for studies related to: particle dynamics, cell localization, colloids and microfluidic flow measurement. Program Files doi : http://dx.doi.org/10.17632/fkprs4s6xp.1 Licensing provisions : Creative Commons by 4.0 (CC by 4.0) Programming language : MATLAB Nature of problem: 3D multi-particle tracking is a common technique in physics, chemistry and biology. However, in terms of accuracy, reliable particle tracking is a challenging task since results depend on sample illumination, particle overlap, motion blur and noise from recording sensors. Additionally, the computational performance is also an issue if, for example, a computationally expensive process is executed, such as axial particle position reconstruction from digital holographic microscopy data. Versatile robust tracking programs handling these concerns and providing a powerful post-processing option are significantly limited. Solution method: UmUTracker is a multi-functional tool to extract particle positions from long video sequences acquired with either light microscopy or digital holographic microscopy. The program provides an easy-to-use graphical user interface (GUI) for both tracking and post-processing that does not require any programming skills to analyze data from particle tracking experiments. UmUTracker first conduct automatic 2D particle detection even under noisy conditions using a novel circle detector based on the isosceles triangle sampling technique with a multi-scale strategy. To reduce the computational load for 3D tracking, it uses an efficient implementation of the Rayleigh-Sommerfeld light propagation model. To analyze and visualize the data, an efficient data analysis step, which can for example show 4D flow visualization using 3D trajectories, is included. Additionally, UmUTracker is easy to modify with user-customized modules due to the object-oriented programming style Additional comments: Program obtainable from https://sourceforge.net/projects/umutracker/

MATLAB as an incentive for student learning of skills

NASA Astrophysics Data System (ADS)

Bank, C. G.; Ghent, R. R.

2016-12-01

Our course "Computational Geology" takes a holistic approach to student learning by using MATLAB as a focal point to increase students' computing, quantitative reasoning, data analysis, report writing, and teamwork skills. The course, taught since 2007 with recent enrollments around 35 and aimed at 2nd to 3rd-year students, is required for the Geology and Earth and Environmental Systems major programs, and can be chosen as elective in our other programs, including Geophysics. The course is divided into five projects: Pacific plate velocity from the Hawaiian hotspot track, predicting CO2 concentration in the atmosphere, volume of Earth's oceans and sea-level rise, comparing wind directions for Vancouver and Squamish, and groundwater flow. Each project is based on real data, focusses on a mathematical concept (linear interpolation, gradients, descriptive statistics, differential equations) and highlights a programming task (arrays, functions, text file input/output, curve fitting). Working in teams of three, students need to develop a conceptional model to explain the data, and write MATLAB code to visualize the data and match it to their conceptional model. The programming is guided, and students work individually on different aspects (for example: reading the data, fitting a function, unit conversion) which they need to put together to solve the problem. They then synthesize their thought process in a paper. Anecdotal evidence shows that students continue using MATLAB in other courses.

DataPflex: a MATLAB-based tool for the manipulation and visualization of multidimensional datasets.

PubMed

Hendriks, Bart S; Espelin, Christopher W

2010-02-01

DataPflex is a MATLAB-based application that facilitates the manipulation and visualization of multidimensional datasets. The strength of DataPflex lies in the intuitive graphical user interface for the efficient incorporation, manipulation and visualization of high-dimensional data that can be generated by multiplexed protein measurement platforms including, but not limited to Luminex or Meso-Scale Discovery. Such data can generally be represented in the form of multidimensional datasets [for example (time x stimulation x inhibitor x inhibitor concentration x cell type x measurement)]. For cases where measurements are made in a combinational fashion across multiple dimensions, there is a need for a tool to efficiently manipulate and reorganize such data for visualization. DataPflex accepts data consisting of up to five arbitrary dimensions in addition to a measurement dimension. Data are imported from a simple .xls format and can be exported to MATLAB or .xls. Data dimensions can be reordered, subdivided, merged, normalized and visualized in the form of collections of line graphs, bar graphs, surface plots, heatmaps, IC50's and other custom plots. Open source implementation in MATLAB enables easy extension for custom plotting routines and integration with more sophisticated analysis tools. DataPflex is distributed under the GPL license (http://www.gnu.org/licenses/) together with documentation, source code and sample data files at: http://code.google.com/p/datapflex. Supplementary data available at Bioinformatics online.

Linking Advanced Visualization and MATLAB for the Analysis of 3D Gene Expression Data

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

Ruebel, Oliver; Keranen, Soile V.E.; Biggin, Mark

Three-dimensional gene expression PointCloud data generated by the Berkeley Drosophila Transcription Network Project (BDTNP) provides quantitative information about the spatial and temporal expression of genes in early Drosophila embryos at cellular resolution. The BDTNP team visualizes and analyzes Point-Cloud data using the software application PointCloudXplore (PCX). To maximize the impact of novel, complex data sets, such as PointClouds, the data needs to be accessible to biologists and comprehensible to developers of analysis functions. We address this challenge by linking PCX and Matlab via a dedicated interface, thereby providing biologists seamless access to advanced data analysis functions and giving bioinformatics researchersmore » the opportunity to integrate their analysis directly into the visualization application. To demonstrate the usefulness of this approach, we computationally model parts of the expression pattern of the gene even skipped using a genetic algorithm implemented in Matlab and integrated into PCX via our Matlab interface.« less

DSISoft—a MATLAB VSP data processing package

NASA Astrophysics Data System (ADS)

Beaty, K. S.; Perron, G.; Kay, I.; Adam, E.

2002-05-01

DSISoft is a public domain vertical seismic profile processing software package developed at the Geological Survey of Canada. DSISoft runs under MATLAB version 5.0 and above and hence is portable between computer operating systems supported by MATLAB (i.e. Unix, Windows, Macintosh, Linux). The package includes processing modules for reading and writing various standard seismic data formats, performing data editing, sorting, filtering, and other basic processing modules. The processing sequence can be scripted allowing batch processing and easy documentation. A structured format has been developed to ensure future additions to the package are compatible with existing modules. Interactive modules have been created using MATLAB's graphical user interface builder for displaying seismic data, picking first break times, examining frequency spectra, doing f- k filtering, and plotting the trace header information. DSISoft modular design facilitates the incorporation of new processing algorithms as they are developed. This paper gives an overview of the scope of the software and serves as a guide for the addition of new modules.

A User-Friendly Software Package for HIFU Simulation

NASA Astrophysics Data System (ADS)

Soneson, Joshua E.

2009-04-01

A freely-distributed, MATLAB (The Mathworks, Inc., Natick, MA)-based software package for simulating axisymmetric high-intensity focused ultrasound (HIFU) beams and their heating effects is discussed. The package (HIFU_Simulator) consists of a propagation module which solves the Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation and a heating module which solves Pennes' bioheat transfer (BHT) equation. The pressure, intensity, heating rate, temperature, and thermal dose fields are computed, plotted, the output is released to the MATLAB workspace for further user analysis or postprocessing.

Design of a MATLAB(registered trademark) Image Comparison and Analysis Tool for Augmentation of the Results of the Ann Arbor Distortion Test

DTIC Science & Technology

2016-06-25

The equipment used in this procedure includes: Ann Arbor distortion tester with 50-line grating reticule, IQeye 720 digital video camera with 12...and import them into MATLAB. In order to digitally capture images of the distortion in an optical sample, an IQeye 720 video camera with a 12... video camera and Ann Arbor distortion tester. Figure 8. Computer interface for capturing images seen by IQeye 720 camera. Once an image was

Photogrammetric 3d Reconstruction in Matlab: Development of a Free Tool

NASA Astrophysics Data System (ADS)

Masiero, A.

2017-11-01

This paper presents the current state of development of a free Matlab tool for photogrammetric reconstruction developed at the University of Padova, Italy. The goal of this software is mostly educational, i.e. allowing students to have a close look to the specific steps which lead to the computation of a dense point cloud. As most of recently developed photogrammetric softwares, it is based on a Structure from Motion approach. Despite being mainly motivated by educational purposes, certain implementation details are clearly inspired by recent research works, e.g. limiting the computational burden of the feature matching by determining a suboptimal set of features to be considered, using information provided by external sensors to ease the matching process.

SolCalc: A Suite for the Calculation and the Display of Magnetic Fields Generated by Solenoid Systems

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

Lopes, M. L.

2014-07-01

SolCalc is a software suite that computes and displays magnetic fields generated by a three dimensional (3D) solenoid system. Examples of such systems are the Mu2e magnet system and Helical Solenoids for muon cooling systems. SolCalc was originally coded in Matlab, and later upgraded to a compiled version (called MEX) to improve solving speed. Matlab was chosen because its graphical capabilities represent an attractive feature over other computer languages. Solenoid geometries can be created using any text editor or spread sheets and can be displayed dynamically in 3D. Fields are computed from any given list of coordinates. The field distributionmore » on the surfaces of the coils can be displayed as well. SolCalc was benchmarked against a well-known commercial software for speed and accuracy and the results compared favorably.« less

PLATSIM: A Simulation and Analysis Package for Large-Order Flexible Systems. Version 2.0

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Kenny, Sean P.; Giesy, Daniel P.

1997-01-01

The software package PLATSIM provides efficient time and frequency domain analysis of large-order generic space platforms. PLATSIM can perform open-loop analysis or closed-loop analysis with linear or nonlinear control system models. PLATSIM exploits the particular form of sparsity of the plant matrices for very efficient linear and nonlinear time domain analysis, as well as frequency domain analysis. A new, original algorithm for the efficient computation of open-loop and closed-loop frequency response functions for large-order systems has been developed and is implemented within the package. Furthermore, a novel and efficient jitter analysis routine which determines jitter and stability values from time simulations in a very efficient manner has been developed and is incorporated in the PLATSIM package. In the time domain analysis, PLATSIM simulates the response of the space platform to disturbances and calculates the jitter and stability values from the response time histories. In the frequency domain analysis, PLATSIM calculates frequency response function matrices and provides the corresponding Bode plots. The PLATSIM software package is written in MATLAB script language. A graphical user interface is developed in the package to provide convenient access to its various features.

Computing Across the Physics and Astrophysics Curriculum

NASA Astrophysics Data System (ADS)

DeGioia Eastwood, Kathy; James, M.; Dolle, E.

2012-01-01

Computational skills are essential in today's marketplace. Bachelors entering the STEM workforce report that their undergraduate education does not adequately prepare them to use scientific software and to write programs. Computation can also increase student learning; not only are the students actively engaged, but computational problems allow them to explore physical problems that are more realistic than the few that can be solved analytically. We have received a grant from the NSF CCLI Phase I program to integrate computing into our upper division curriculum. Our language of choice is Matlab; this language had already been chosen for our required sophomore course in Computational Physics because of its prevalence in industry. For two summers we have held faculty workshops to help our professors develop the needed expertise, and we are now in the implementation and evaluation stage. The end product will be a set of learning materials in the form of computational modules that we will make freely available. These modules will include the assignment, pedagogical goals, Matlab code, samples of student work, and instructor comments. At this meeting we present an overview of the project as well as modules written for a course in upper division stellar astrophysics. We acknowledge the support of the NSF through DUE-0837368.

Development of a UNIX network compatible reactivity computer

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

Sanchez, R.F.; Edwards, R.M.

1996-12-31

A state-of-the-art UNIX network compatible controller and UNIX host workstation with MATLAB/SIMULINK software were used to develop, implement, and validate a digital reactivity calculation. An objective of the development was to determine why a Macintosh-based reactivity computer reactivity output drifted intolerably.

Wavelet decomposition based principal component analysis for face recognition using MATLAB

NASA Astrophysics Data System (ADS)

Sharma, Mahesh Kumar; Sharma, Shashikant; Leeprechanon, Nopbhorn; Ranjan, Aashish

2016-03-01

For the realization of face recognition systems in the static as well as in the real time frame, algorithms such as principal component analysis, independent component analysis, linear discriminate analysis, neural networks and genetic algorithms are used for decades. This paper discusses an approach which is a wavelet decomposition based principal component analysis for face recognition. Principal component analysis is chosen over other algorithms due to its relative simplicity, efficiency, and robustness features. The term face recognition stands for identifying a person from his facial gestures and having resemblance with factor analysis in some sense, i.e. extraction of the principal component of an image. Principal component analysis is subjected to some drawbacks, mainly the poor discriminatory power and the large computational load in finding eigenvectors, in particular. These drawbacks can be greatly reduced by combining both wavelet transform decomposition for feature extraction and principal component analysis for pattern representation and classification together, by analyzing the facial gestures into space and time domain, where, frequency and time are used interchangeably. From the experimental results, it is envisaged that this face recognition method has made a significant percentage improvement in recognition rate as well as having a better computational efficiency.

Echo™ User Manual

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

Harvey, Dustin Yewell

Echo™ is a MATLAB-based software package designed for robust and scalable analysis of complex data workflows. An alternative to tedious, error-prone conventional processes, Echo is based on three transformative principles for data analysis: self-describing data, name-based indexing, and dynamic resource allocation. The software takes an object-oriented approach to data analysis, intimately connecting measurement data with associated metadata. Echo operations in an analysis workflow automatically track and merge metadata and computation parameters to provide a complete history of the process used to generate final results, while automated figure and report generation tools eliminate the potential to mislabel those results. History reportingmore » and visualization methods provide straightforward auditability of analysis processes. Furthermore, name-based indexing on metadata greatly improves code readability for analyst collaboration and reduces opportunities for errors to occur. Echo efficiently manages large data sets using a framework that seamlessly allocates resources such that only the necessary computations to produce a given result are executed. Echo provides a versatile and extensible framework, allowing advanced users to add their own tools and data classes tailored to their own specific needs. Applying these transformative principles and powerful features, Echo greatly improves analyst efficiency and quality of results in many application areas.« less

New Automotive Air Conditioning System Simulation Tool Developed in MATLAB/Simulink

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

Kiss, T.; Chaney, L.; Meyer, J.

Further improvements in vehicle fuel efficiency require accurate evaluation of the vehicle's transient total power requirement. When operated, the air conditioning (A/C) system is the largest auxiliary load on a vehicle; therefore, accurate evaluation of the load it places on the vehicle's engine and/or energy storage system is especially important. Vehicle simulation software, such as 'Autonomie,' has been used by OEMs to evaluate vehicles' energy performance. A transient A/C simulation tool incorporated into vehicle simulation models would also provide a tool for developing more efficient A/C systems through a thorough consideration of the transient A/C system performance. The dynamic systemmore » simulation software Matlab/Simulink was used to develop new and more efficient vehicle energy system controls. The various modeling methods used for the new simulation tool are described in detail. Comparison with measured data is provided to demonstrate the validity of the model.« less

Low-rank approximation in the numerical modeling of the Farley-Buneman instability in ionospheric plasma

NASA Astrophysics Data System (ADS)

Dolgov, S. V.; Smirnov, A. P.; Tyrtyshnikov, E. E.

2014-04-01

We consider numerical modeling of the Farley-Buneman instability in the Earth's ionosphere plasma. The ion behavior is governed by the kinetic Vlasov equation with the BGK collisional term in the four-dimensional phase space, and since the finite difference discretization on a tensor product grid is used, this equation becomes the most computationally challenging part of the scheme. To relax the complexity and memory consumption, an adaptive model reduction using the low-rank separation of variables, namely the Tensor Train format, is employed. The approach was verified via a prototype MATLAB implementation. Numerical experiments demonstrate the possibility of efficient separation of space and velocity variables, resulting in the solution storage reduction by a factor of order tens.

A quantum-implementable neural network model

NASA Astrophysics Data System (ADS)

Chen, Jialin; Wang, Lingli; Charbon, Edoardo

2017-10-01

A quantum-implementable neural network, namely quantum probability neural network (QPNN) model, is proposed in this paper. QPNN can use quantum parallelism to trace all possible network states to improve the result. Due to its unique quantum nature, this model is robust to several quantum noises under certain conditions, which can be efficiently implemented by the qubus quantum computer. Another advantage is that QPNN can be used as memory to retrieve the most relevant data and even to generate new data. The MATLAB experimental results of Iris data classification and MNIST handwriting recognition show that much less neuron resources are required in QPNN to obtain a good result than the classical feedforward neural network. The proposed QPNN model indicates that quantum effects are useful for real-life classification tasks.

A Collection of Nonlinear Aircraft Simulations in MATLAB

NASA Technical Reports Server (NTRS)

Garza, Frederico R.; Morelli, Eugene A.

2003-01-01

Nonlinear six degree-of-freedom simulations for a variety of aircraft were created using MATLAB. Data for aircraft geometry, aerodynamic characteristics, mass / inertia properties, and engine characteristics were obtained from open literature publications documenting wind tunnel experiments and flight tests. Each nonlinear simulation was implemented within a common framework in MATLAB, and includes an interface with another commercially-available program to read pilot inputs and produce a three-dimensional (3-D) display of the simulated airplane motion. Aircraft simulations include the General Dynamics F-16 Fighting Falcon, Convair F-106B Delta Dart, Grumman F-14 Tomcat, McDonnell Douglas F-4 Phantom, NASA Langley Free-Flying Aircraft for Sub-scale Experimental Research (FASER), NASA HL-20 Lifting Body, NASA / DARPA X-31 Enhanced Fighter Maneuverability Demonstrator, and the Vought A-7 Corsair II. All nonlinear simulations and 3-D displays run in real time in response to pilot inputs, using contemporary desktop personal computer hardware. The simulations can also be run in batch mode. Each nonlinear simulation includes the full nonlinear dynamics of the bare airframe, with a scaled direct connection from pilot inputs to control surface deflections to provide adequate pilot control. Since all the nonlinear simulations are implemented entirely in MATLAB, user-defined control laws can be added in a straightforward fashion, and the simulations are portable across various computing platforms. Routines for trim, linearization, and numerical integration are included. The general nonlinear simulation framework and the specifics for each particular aircraft are documented.

Sparse distance-based learning for simultaneous multiclass classification and feature selection of metagenomic data.

PubMed

Liu, Zhenqiu; Hsiao, William; Cantarel, Brandi L; Drábek, Elliott Franco; Fraser-Liggett, Claire

2011-12-01

Direct sequencing of microbes in human ecosystems (the human microbiome) has complemented single genome cultivation and sequencing to understand and explore the impact of commensal microbes on human health. As sequencing technologies improve and costs decline, the sophistication of data has outgrown available computational methods. While several existing machine learning methods have been adapted for analyzing microbiome data recently, there is not yet an efficient and dedicated algorithm available for multiclass classification of human microbiota. By combining instance-based and model-based learning, we propose a novel sparse distance-based learning method for simultaneous class prediction and feature (variable or taxa, which is used interchangeably) selection from multiple treatment populations on the basis of 16S rRNA sequence count data. Our proposed method simultaneously minimizes the intraclass distance and maximizes the interclass distance with many fewer estimated parameters than other methods. It is very efficient for problems with small sample sizes and unbalanced classes, which are common in metagenomic studies. We implemented this method in a MATLAB toolbox called MetaDistance. We also propose several approaches for data normalization and variance stabilization transformation in MetaDistance. We validate this method on several real and simulated 16S rRNA datasets to show that it outperforms existing methods for classifying metagenomic data. This article is the first to address simultaneous multifeature selection and class prediction with metagenomic count data. The MATLAB toolbox is freely available online at http://metadistance.igs.umaryland.edu/. zliu@umm.edu Supplementary data are available at Bioinformatics online.

Student's Lab Assignments in PDE Course with MAPLE.

ERIC Educational Resources Information Center

Ponidi, B. Alhadi

Computer-aided software has been used intensively in many mathematics courses, especially in computational subjects, to solve initial value and boundary value problems in Partial Differential Equations (PDE). Many software packages were used in student lab assignments such as FORTRAN, PASCAL, MATLAB, MATHEMATICA, and MAPLE in order to accelerate…

A pedagogical walkthrough of computational modeling and simulation of Wnt signaling pathway using static causal models in MATLAB.

PubMed

Sinha, Shriprakash

2016-12-01

Simulation study in systems biology involving computational experiments dealing with Wnt signaling pathways abound in literature but often lack a pedagogical perspective that might ease the understanding of beginner students and researchers in transition, who intend to work on the modeling of the pathway. This paucity might happen due to restrictive business policies which enforce an unwanted embargo on the sharing of important scientific knowledge. A tutorial introduction to computational modeling of Wnt signaling pathway in a human colorectal cancer dataset using static Bayesian network models is provided. The walkthrough might aid biologists/informaticians in understanding the design of computational experiments that is interleaved with exposition of the Matlab code and causal models from Bayesian network toolbox. The manuscript elucidates the coding contents of the advance article by Sinha (Integr. Biol. 6:1034-1048, 2014) and takes the reader in a step-by-step process of how (a) the collection and the transformation of the available biological information from literature is done, (b) the integration of the heterogeneous data and prior biological knowledge in the network is achieved, (c) the simulation study is designed, (d) the hypothesis regarding a biological phenomena is transformed into computational framework, and (e) results and inferences drawn using d -connectivity/separability are reported. The manuscript finally ends with a programming assignment to help the readers get hands-on experience of a perturbation project. Description of Matlab files is made available under GNU GPL v3 license at the Google code project on https://code.google.com/p/static-bn-for-wnt-signaling-pathway and https: //sites.google.com/site/shriprakashsinha/shriprakashsinha/projects/static-bn-for-wnt-signaling-pathway. Latest updates can be found in the latter website.

Software For Computer-Aided Design Of Control Systems

NASA Technical Reports Server (NTRS)

Wette, Matthew

1994-01-01

Computer Aided Engineering System (CAESY) software developed to provide means to evaluate methods for dealing with users' needs in computer-aided design of control systems. Interpreter program for performing engineering calculations. Incorporates features of both Ada and MATLAB. Designed to be flexible and powerful. Includes internally defined functions, procedures and provides for definition of functions and procedures by user. Written in C language.

Reconstruction for time-domain in vivo EPR 3D multigradient oximetric imaging--a parallel processing perspective.

PubMed

Dharmaraj, Christopher D; Thadikonda, Kishan; Fletcher, Anthony R; Doan, Phuc N; Devasahayam, Nallathamby; Matsumoto, Shingo; Johnson, Calvin A; Cook, John A; Mitchell, James B; Subramanian, Sankaran; Krishna, Murali C

2009-01-01

Three-dimensional Oximetric Electron Paramagnetic Resonance Imaging using the Single Point Imaging modality generates unpaired spin density and oxygen images that can readily distinguish between normal and tumor tissues in small animals. It is also possible with fast imaging to track the changes in tissue oxygenation in response to the oxygen content in the breathing air. However, this involves dealing with gigabytes of data for each 3D oximetric imaging experiment involving digital band pass filtering and background noise subtraction, followed by 3D Fourier reconstruction. This process is rather slow in a conventional uniprocessor system. This paper presents a parallelization framework using OpenMP runtime support and parallel MATLAB to execute such computationally intensive programs. The Intel compiler is used to develop a parallel C++ code based on OpenMP. The code is executed on four Dual-Core AMD Opteron shared memory processors, to reduce the computational burden of the filtration task significantly. The results show that the parallel code for filtration has achieved a speed up factor of 46.66 as against the equivalent serial MATLAB code. In addition, a parallel MATLAB code has been developed to perform 3D Fourier reconstruction. Speedup factors of 4.57 and 4.25 have been achieved during the reconstruction process and oximetry computation, for a data set with 23 x 23 x 23 gradient steps. The execution time has been computed for both the serial and parallel implementations using different dimensions of the data and presented for comparison. The reported system has been designed to be easily accessible even from low-cost personal computers through local internet (NIHnet). The experimental results demonstrate that the parallel computing provides a source of high computational power to obtain biophysical parameters from 3D EPR oximetric imaging, almost in real-time.

HT2DINV: A 2D forward and inverse code for steady-state and transient hydraulic tomography problems

NASA Astrophysics Data System (ADS)

Soueid Ahmed, A.; Jardani, A.; Revil, A.; Dupont, J. P.

2015-12-01

Hydraulic tomography is a technique used to characterize the spatial heterogeneities of storativity and transmissivity fields. The responses of an aquifer to a source of hydraulic stimulations are used to recover the features of the estimated fields using inverse techniques. We developed a 2D free source Matlab package for performing hydraulic tomography analysis in steady state and transient regimes. The package uses the finite elements method to solve the ground water flow equation for simple or complex geometries accounting for the anisotropy of the material properties. The inverse problem is based on implementing the geostatistical quasi-linear approach of Kitanidis combined with the adjoint-state method to compute the required sensitivity matrices. For undetermined inverse problems, the adjoint-state method provides a faster and more accurate approach for the evaluation of sensitivity matrices compared with the finite differences method. Our methodology is organized in a way that permits the end-user to activate parallel computing in order to reduce the computational burden. Three case studies are investigated demonstrating the robustness and efficiency of our approach for inverting hydraulic parameters.

Computational Approaches to Simulation and Optimization of Global Aircraft Trajectories

NASA Technical Reports Server (NTRS)

Ng, Hok Kwan; Sridhar, Banavar

2016-01-01

This study examines three possible approaches to improving the speed in generating wind-optimal routes for air traffic at the national or global level. They are: (a) using the resources of a supercomputer, (b) running the computations on multiple commercially available computers and (c) implementing those same algorithms into NASAs Future ATM Concepts Evaluation Tool (FACET) and compares those to a standard implementation run on a single CPU. Wind-optimal aircraft trajectories are computed using global air traffic schedules. The run time and wait time on the supercomputer for trajectory optimization using various numbers of CPUs ranging from 80 to 10,240 units are compared with the total computational time for running the same computation on a single desktop computer and on multiple commercially available computers for potential computational enhancement through parallel processing on the computer clusters. This study also re-implements the trajectory optimization algorithm for further reduction of computational time through algorithm modifications and integrates that with FACET to facilitate the use of the new features which calculate time-optimal routes between worldwide airport pairs in a wind field for use with existing FACET applications. The implementations of trajectory optimization algorithms use MATLAB, Python, and Java programming languages. The performance evaluations are done by comparing their computational efficiencies and based on the potential application of optimized trajectories. The paper shows that in the absence of special privileges on a supercomputer, a cluster of commercially available computers provides a feasible approach for national and global air traffic system studies.

Arc_Mat: a Matlab-based spatial data analysis toolbox

NASA Astrophysics Data System (ADS)

Liu, Xingjian; Lesage, James

2010-03-01

This article presents an overview of Arc_Mat, a Matlab-based spatial data analysis software package whose source code has been placed in the public domain. An earlier version of the Arc_Mat toolbox was developed to extract map polygon and database information from ESRI shapefiles and provide high quality mapping in the Matlab software environment. We discuss revisions to the toolbox that: utilize enhanced computing and graphing capabilities of more recent versions of Matlab, restructure the toolbox with object-oriented programming features, and provide more comprehensive functions for spatial data analysis. The Arc_Mat toolbox functionality includes basic choropleth mapping; exploratory spatial data analysis that provides exploratory views of spatial data through various graphs, for example, histogram, Moran scatterplot, three-dimensional scatterplot, density distribution plot, and parallel coordinate plots; and more formal spatial data modeling that draws on the extensive Spatial Econometrics Toolbox functions. A brief review of the design aspects of the revised Arc_Mat is described, and we provide some illustrative examples that highlight representative uses of the toolbox. Finally, we discuss programming with and customizing the Arc_Mat toolbox functionalities.

Validation of Harris Detector and Eigen Features Detector

NASA Astrophysics Data System (ADS)

Kok, K. Y.; Rajendran, P.

2018-05-01

Harris detector is one of the most common features detection for applications such as object recognition, stereo matching and target tracking. In this paper, a similar Harris detector algorithm is written using MATLAB and the performance is compared with MATLAB built in Harris detector for validation. This is to ensure that rewritten version of Harris detector can be used for Unmanned Aerial Vehicle (UAV) application research purpose yet can be further improvised. Another corner detector close to Harris detector, which is Eigen features detector is rewritten and compared as well using same procedures with same purpose. The simulation results have shown that rewritten version for both Harris and Eigen features detectors have the same performance with MATLAB built in detectors with not more than 0.4% coordination deviation, less than 4% & 5% response deviation respectively, and maximum 3% computational cost error.

Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index.

PubMed

Xue, Wufeng; Zhang, Lei; Mou, Xuanqin; Bovik, Alan C

2014-02-01

It is an important task to faithfully evaluate the perceptual quality of output images in many applications, such as image compression, image restoration, and multimedia streaming. A good image quality assessment (IQA) model should not only deliver high quality prediction accuracy, but also be computationally efficient. The efficiency of IQA metrics is becoming particularly important due to the increasing proliferation of high-volume visual data in high-speed networks. We present a new effective and efficient IQA model, called gradient magnitude similarity deviation (GMSD). The image gradients are sensitive to image distortions, while different local structures in a distorted image suffer different degrees of degradations. This motivates us to explore the use of global variation of gradient based local quality map for overall image quality prediction. We find that the pixel-wise gradient magnitude similarity (GMS) between the reference and distorted images combined with a novel pooling strategy-the standard deviation of the GMS map-can predict accurately perceptual image quality. The resulting GMSD algorithm is much faster than most state-of-the-art IQA methods, and delivers highly competitive prediction accuracy. MATLAB source code of GMSD can be downloaded at http://www4.comp.polyu.edu.hk/~cslzhang/IQA/GMSD/GMSD.htm.

siGnum: graphical user interface for EMG signal analysis.

PubMed

Kaur, Manvinder; Mathur, Shilpi; Bhatia, Dinesh; Verma, Suresh

2015-01-01

Electromyography (EMG) signals that represent the electrical activity of muscles can be used for various clinical and biomedical applications. These are complicated and highly varying signals that are dependent on anatomical location and physiological properties of the muscles. EMG signals acquired from the muscles require advanced methods for detection, decomposition and processing. This paper proposes a novel Graphical User Interface (GUI) siGnum developed in MATLAB that will apply efficient and effective techniques on processing of the raw EMG signals and decompose it in a simpler manner. It could be used independent of MATLAB software by employing a deploy tool. This would enable researcher's to gain good understanding of EMG signal and its analysis procedures that can be utilized for more powerful, flexible and efficient applications in near future.

A Survey of Quantum Programming Languages: History, Methods, and Tools

DTIC Science & Technology

2008-01-01

and entanglement , to achieve computational solutions to certain problems in less time (fewer computational cycles) than is possible using classical...superposition of quantum bits, entanglement , destructive measurement, and the no-cloning theorem. These differences must be thoroughly understood and even...computers using well-known languages such as C, C++, Java, and rapid prototyping languages such as Maple, Mathematica, and Matlab . A good on-line

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

PubMed Central

Saa, Pedro A.; Nielsen, Lars K.

2016-01-01

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

TauFactor: An open-source application for calculating tortuosity factors from tomographic data

NASA Astrophysics Data System (ADS)

Cooper, S. J.; Bertei, A.; Shearing, P. R.; Kilner, J. A.; Brandon, N. P.

TauFactor is a MatLab application for efficiently calculating the tortuosity factor, as well as volume fractions, surface areas and triple phase boundary densities, from image based microstructural data. The tortuosity factor quantifies the apparent decrease in diffusive transport resulting from convolutions of the flow paths through porous media. TauFactor was originally developed to improve the understanding of electrode microstructures for batteries and fuel cells; however, the tortuosity factor has been of interest to a wide range of disciplines for over a century, including geoscience, biology and optics. It is still common practice to use correlations, such as that developed by Bruggeman, to approximate the tortuosity factor, but in recent years the increasing availability of 3D imaging techniques has spurred interest in calculating this quantity more directly. This tool provides a fast and accurate computational platform applicable to the big datasets (>108 voxels) typical of modern tomography, without requiring high computational power.

A robust method of computing finite difference coefficients based on Vandermonde matrix

NASA Astrophysics Data System (ADS)

Zhang, Yijie; Gao, Jinghuai; Peng, Jigen; Han, Weimin

2018-05-01

When the finite difference (FD) method is employed to simulate the wave propagation, high-order FD method is preferred in order to achieve better accuracy. However, if the order of FD scheme is high enough, the coefficient matrix of the formula for calculating finite difference coefficients is close to be singular. In this case, when the FD coefficients are computed by matrix inverse operator of MATLAB, inaccuracy can be produced. In order to overcome this problem, we have suggested an algorithm based on Vandermonde matrix in this paper. After specified mathematical transformation, the coefficient matrix is transformed into a Vandermonde matrix. Then the FD coefficients of high-order FD method can be computed by the algorithm of Vandermonde matrix, which prevents the inverse of the singular matrix. The dispersion analysis and numerical results of a homogeneous elastic model and a geophysical model of oil and gas reservoir demonstrate that the algorithm based on Vandermonde matrix has better accuracy compared with matrix inverse operator of MATLAB.

Lowering the Barrier to Reproducible Research by Publishing Provenance from Common Analytical Tools

NASA Astrophysics Data System (ADS)

Jones, M. B.; Slaughter, P.; Walker, L.; Jones, C. S.; Missier, P.; Ludäscher, B.; Cao, Y.; McPhillips, T.; Schildhauer, M.

2015-12-01

Scientific provenance describes the authenticity, origin, and processing history of research products and promotes scientific transparency by detailing the steps in computational workflows that produce derived products. These products include papers, findings, input data, software products to perform computations, and derived data and visualizations. The geosciences community values this type of information, and, at least theoretically, strives to base conclusions on computationally replicable findings. In practice, capturing detailed provenance is laborious and thus has been a low priority; beyond a lab notebook describing methods and results, few researchers capture and preserve detailed records of scientific provenance. We have built tools for capturing and publishing provenance that integrate into analytical environments that are in widespread use by geoscientists (R and Matlab). These tools lower the barrier to provenance generation by automating capture of critical information as researchers prepare data for analysis, develop, test, and execute models, and create visualizations. The 'recordr' library in R and the `matlab-dataone` library in Matlab provide shared functions to capture provenance with minimal changes to normal working procedures. Researchers can capture both scripted and interactive sessions, tag and manage these executions as they iterate over analyses, and then prune and publish provenance metadata and derived products to the DataONE federation of archival repositories. Provenance traces conform to the ProvONE model extension of W3C PROV, enabling interoperability across tools and languages. The capture system supports fine-grained versioning of science products and provenance traces. By assigning global identifiers such as DOIs, reseachers can cite the computational processes used to reach findings. And, finally, DataONE has built a web portal to search, browse, and clearly display provenance relationships between input data, the software used to execute analyses and models, and derived data and products that arise from these computations. This provenance is vital to interpretation and understanding of science, and provides an audit trail that researchers can use to understand and replicate computational workflows in the geosciences.

MATLAB Simulation of Photovoltaic and Photovoltaic/Thermal Systems Performance

NASA Astrophysics Data System (ADS)

Nasir, Farah H. M.; Husaini, Yusnira

2018-03-01

The efficiency of the photovoltaic reduces when the photovoltaic cell temperature increased due to solar irradiance. One solution is come up with the cooling system photovoltaic system. This combination is forming the photovoltaic-thermal (PV/T) system. Not only will it generate electricity also heat at the same time. The aim of this research is to focus on the modeling and simulation of photovoltaic (PV) and photovoltaic-thermal (PV/T) electrical performance by using single-diode equivalent circuit model. Both PV and PV/T models are developed in Matlab/Simulink. By providing the cooling system in PV/T, the efficiency of the system can be increased by decreasing the PV cell temperature. The maximum thermal, electrical and total efficiency values of PV/T in the present research are 35.18%, 15.56% and 50.74% at solar irradiance of 400 W/m2, mass flow rate of 0.05kgs-1 and inlet temperature of 25 °C respectively has been obtained. The photovoltaic-thermal shows that the higher efficiency performance compared to the photovoltaic system.

MNPBEM - A Matlab toolbox for the simulation of plasmonic nanoparticles

NASA Astrophysics Data System (ADS)

Hohenester, Ulrich; Trügler, Andreas

2012-02-01

MNPBEM is a Matlab toolbox for the simulation of metallic nanoparticles (MNP), using a boundary element method (BEM) approach. The main purpose of the toolbox is to solve Maxwell's equations for a dielectric environment where bodies with homogeneous and isotropic dielectric functions are separated by abrupt interfaces. Although the approach is in principle suited for arbitrary body sizes and photon energies, it is tested (and probably works best) for metallic nanoparticles with sizes ranging from a few to a few hundreds of nanometers, and for frequencies in the optical and near-infrared regime. The toolbox has been implemented with Matlab classes. These classes can be easily combined, which has the advantage that one can adapt the simulation programs flexibly for various applications. Program summaryProgram title: MNPBEM Catalogue identifier: AEKJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKJ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License v2 No. of lines in distributed program, including test data, etc.: 15 700 No. of bytes in distributed program, including test data, etc.: 891 417 Distribution format: tar.gz Programming language: Matlab 7.11.0 (R2010b) Computer: Any which supports Matlab 7.11.0 (R2010b) Operating system: Any which supports Matlab 7.11.0 (R2010b) RAM: ⩾1 GByte Classification: 18 Nature of problem: Solve Maxwell's equations for dielectric particles with homogeneous dielectric functions separated by abrupt interfaces. Solution method: Boundary element method using electromagnetic potentials. Running time: Depending on surface discretization between seconds and hours.

Brian: a simulator for spiking neural networks in python.

PubMed

Goodman, Dan; Brette, Romain

2008-01-01

"Brian" is a new simulator for spiking neural networks, written in Python (http://brian. di.ens.fr). It is an intuitive and highly flexible tool for rapidly developing new models, especially networks of single-compartment neurons. In addition to using standard types of neuron models, users can define models by writing arbitrary differential equations in ordinary mathematical notation. Python scientific libraries can also be used for defining models and analysing data. Vectorisation techniques allow efficient simulations despite the overheads of an interpreted language. Brian will be especially valuable for working on non-standard neuron models not easily covered by existing software, and as an alternative to using Matlab or C for simulations. With its easy and intuitive syntax, Brian is also very well suited for teaching computational neuroscience.

SPIDYAN, a MATLAB library for simulating pulse EPR experiments with arbitrary waveform excitation.

PubMed

Pribitzer, Stephan; Doll, Andrin; Jeschke, Gunnar

2016-02-01

Frequency-swept chirp pulses, created with arbitrary waveform generators (AWGs), can achieve inversion over a range of several hundreds of MHz. Such passage pulses provide defined flip angles and increase sensitivity. The fact that spectra are not excited at once, but single transitions are passed one after another, can cause new effects in established pulse EPR sequences. We developed a MATLAB library for simulation of pulse EPR, which is especially suited for modeling spin dynamics in ultra-wideband (UWB) EPR experiments, but can also be used for other experiments and NMR. At present the command line controlled SPin DYnamics ANalysis (SPIDYAN) package supports one-spin and two-spin systems with arbitrary spin quantum numbers. By providing the program with appropriate spin operators and Hamiltonian matrices any spin system is accessible, with limits set only by available memory and computation time. Any pulse sequence using rectangular and linearly or variable-rate frequency-swept chirp pulses, including phase cycling can be quickly created. To keep track of spin evolution the user can choose from a vast variety of detection operators, including transition selective operators. If relaxation effects can be neglected, the program solves the Liouville-von Neumann equation and propagates spin density matrices. In the other cases SPIDYAN uses the quantum mechanical master equation and Liouvillians for propagation. In order to consider the resonator response function, which on the scale of UWB excitation limits bandwidth, the program includes a simple RLC circuit model. Another subroutine can compute waveforms that, for a given resonator, maintain a constant critical adiabaticity factor over the excitation band. Computational efficiency is enhanced by precomputing propagator lookup tables for the whole set of AWG output levels. The features of the software library are discussed and demonstrated with spin-echo and population transfer simulations. Copyright © 2016 Elsevier Inc. All rights reserved.

Optimization design of wind turbine drive train based on Matlab genetic algorithm toolbox

NASA Astrophysics Data System (ADS)

Li, R. N.; Liu, X.; Liu, S. J.

2013-12-01

In order to ensure the high efficiency of the whole flexible drive train of the front-end speed adjusting wind turbine, the working principle of the main part of the drive train is analyzed. As critical parameters, rotating speed ratios of three planetary gear trains are selected as the research subject. The mathematical model of the torque converter speed ratio is established based on these three critical variable quantity, and the effect of key parameters on the efficiency of hydraulic mechanical transmission is analyzed. Based on the torque balance and the energy balance, refer to hydraulic mechanical transmission characteristics, the transmission efficiency expression of the whole drive train is established. The fitness function and constraint functions are established respectively based on the drive train transmission efficiency and the torque converter rotating speed ratio range. And the optimization calculation is carried out by using MATLAB genetic algorithm toolbox. The optimization method and results provide an optimization program for exact match of wind turbine rotor, gearbox, hydraulic mechanical transmission, hydraulic torque converter and synchronous generator, ensure that the drive train work with a high efficiency, and give a reference for the selection of the torque converter and hydraulic mechanical transmission.

RenderToolbox3: MATLAB tools that facilitate physically based stimulus rendering for vision research.

PubMed

Heasly, Benjamin S; Cottaris, Nicolas P; Lichtman, Daniel P; Xiao, Bei; Brainard, David H

2014-02-07

RenderToolbox3 provides MATLAB utilities and prescribes a workflow that should be useful to researchers who want to employ graphics in the study of vision and perhaps in other endeavors as well. In particular, RenderToolbox3 facilitates rendering scene families in which various scene attributes and renderer behaviors are manipulated parametrically, enables spectral specification of object reflectance and illuminant spectra, enables the use of physically based material specifications, helps validate renderer output, and converts renderer output to physical units of radiance. This paper describes the design and functionality of the toolbox and discusses several examples that demonstrate its use. We have designed RenderToolbox3 to be portable across computer hardware and operating systems and to be free and open source (except for MATLAB itself). RenderToolbox3 is available at https://github.com/DavidBrainard/RenderToolbox3.

The Evaluation of Rekeying Protocols Within the Hubenko Architecture as Applied to Wireless Sensor Networks

DTIC Science & Technology

2009-03-01

SENSOR NETWORKS THESIS Presented to the Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and...hierarchical, and Secure Lock within a wireless sensor network (WSN) under the Hubenko architecture. Using a Matlab computer simulation, the impact of the...rekeying protocol should be applied given particular network parameters, such as WSN size. 10 1.3 Experimental Approach A computer simulation in

GPELab, a Matlab toolbox to solve Gross-Pitaevskii equations II: Dynamics and stochastic simulations

NASA Astrophysics Data System (ADS)

Antoine, Xavier; Duboscq, Romain

2015-08-01

GPELab is a free Matlab toolbox for modeling and numerically solving large classes of systems of Gross-Pitaevskii equations that arise in the physics of Bose-Einstein condensates. The aim of this second paper, which follows (Antoine and Duboscq, 2014), is to first present the various pseudospectral schemes available in GPELab for computing the deterministic and stochastic nonlinear dynamics of Gross-Pitaevskii equations (Antoine, et al., 2013). Next, the corresponding GPELab functions are explained in detail. Finally, some numerical examples are provided to show how the code works for the complex dynamics of BEC problems.

Embedded algorithms within an FPGA-based system to process nonlinear time series data

NASA Astrophysics Data System (ADS)

Jones, Jonathan D.; Pei, Jin-Song; Tull, Monte P.

2008-03-01

This paper presents some preliminary results of an ongoing project. A pattern classification algorithm is being developed and embedded into a Field-Programmable Gate Array (FPGA) and microprocessor-based data processing core in this project. The goal is to enable and optimize the functionality of onboard data processing of nonlinear, nonstationary data for smart wireless sensing in structural health monitoring. Compared with traditional microprocessor-based systems, fast growing FPGA technology offers a more powerful, efficient, and flexible hardware platform including on-site (field-programmable) reconfiguration capability of hardware. An existing nonlinear identification algorithm is used as the baseline in this study. The implementation within a hardware-based system is presented in this paper, detailing the design requirements, validation, tradeoffs, optimization, and challenges in embedding this algorithm. An off-the-shelf high-level abstraction tool along with the Matlab/Simulink environment is utilized to program the FPGA, rather than coding the hardware description language (HDL) manually. The implementation is validated by comparing the simulation results with those from Matlab. In particular, the Hilbert Transform is embedded into the FPGA hardware and applied to the baseline algorithm as the centerpiece in processing nonlinear time histories and extracting instantaneous features of nonstationary dynamic data. The selection of proper numerical methods for the hardware execution of the selected identification algorithm and consideration of the fixed-point representation are elaborated. Other challenges include the issues of the timing in the hardware execution cycle of the design, resource consumption, approximation accuracy, and user flexibility of input data types limited by the simplicity of this preliminary design. Future work includes making an FPGA and microprocessor operate together to embed a further developed algorithm that yields better computational and power efficiency.

OXSA: An open-source magnetic resonance spectroscopy analysis toolbox in MATLAB.

PubMed

Purvis, Lucian A B; Clarke, William T; Biasiolli, Luca; Valkovič, Ladislav; Robson, Matthew D; Rodgers, Christopher T

2017-01-01

In vivo magnetic resonance spectroscopy provides insight into metabolism in the human body. New acquisition protocols are often proposed to improve the quality or efficiency of data collection. Processing pipelines must also be developed to use these data optimally. Current fitting software is either targeted at general spectroscopy fitting, or for specific protocols. We therefore introduce the MATLAB-based OXford Spectroscopy Analysis (OXSA) toolbox to allow researchers to rapidly develop their own customised processing pipelines. The toolbox aims to simplify development by: being easy to install and use; seamlessly importing Siemens Digital Imaging and Communications in Medicine (DICOM) standard data; allowing visualisation of spectroscopy data; offering a robust fitting routine; flexibly specifying prior knowledge when fitting; and allowing batch processing of spectra. This article demonstrates how each of these criteria have been fulfilled, and gives technical details about the implementation in MATLAB. The code is freely available to download from https://github.com/oxsatoolbox/oxsa.

Image enhancement using MCNP5 code and MATLAB in neutron radiography.

PubMed

Tharwat, Montaser; Mohamed, Nader; Mongy, T

2014-07-01

This work presents a method that can be used to enhance the neutron radiography (NR) image for objects with high scattering materials like hydrogen, carbon and other light materials. This method used Monte Carlo code, MCNP5, to simulate the NR process and get the flux distribution for each pixel of the image and determines the scattered neutron distribution that caused image blur, and then uses MATLAB to subtract this scattered neutron distribution from the initial image to improve its quality. This work was performed before the commissioning of digital NR system in Jan. 2013. The MATLAB enhancement method is quite a good technique in the case of static based film neutron radiography, while in neutron imaging (NI) technique, image enhancement and quantitative measurement were efficient by using ImageJ software. The enhanced image quality and quantitative measurements were presented in this work. Copyright © 2014 Elsevier Ltd. All rights reserved.

COBRApy: COnstraints-Based Reconstruction and Analysis for Python.

PubMed

Ebrahim, Ali; Lerman, Joshua A; Palsson, Bernhard O; Hyduke, Daniel R

2013-08-08

COnstraint-Based Reconstruction and Analysis (COBRA) methods are widely used for genome-scale modeling of metabolic networks in both prokaryotes and eukaryotes. Due to the successes with metabolism, there is an increasing effort to apply COBRA methods to reconstruct and analyze integrated models of cellular processes. The COBRA Toolbox for MATLAB is a leading software package for genome-scale analysis of metabolism; however, it was not designed to elegantly capture the complexity inherent in integrated biological networks and lacks an integration framework for the multiomics data used in systems biology. The openCOBRA Project is a community effort to promote constraints-based research through the distribution of freely available software. Here, we describe COBRA for Python (COBRApy), a Python package that provides support for basic COBRA methods. COBRApy is designed in an object-oriented fashion that facilitates the representation of the complex biological processes of metabolism and gene expression. COBRApy does not require MATLAB to function; however, it includes an interface to the COBRA Toolbox for MATLAB to facilitate use of legacy codes. For improved performance, COBRApy includes parallel processing support for computationally intensive processes. COBRApy is an object-oriented framework designed to meet the computational challenges associated with the next generation of stoichiometric constraint-based models and high-density omics data sets. http://opencobra.sourceforge.net/

Using the Generic Mapping Tools From Within the MATLAB, Octave and Julia Computing Environments

NASA Astrophysics Data System (ADS)

Luis, J. M. F.; Wessel, P.

2016-12-01

The Generic Mapping Tools (GMT) is a widely used software infrastructure tool set for analyzing and displaying geoscience data. Its power to analyze and process data and produce publication-quality graphics has made it one of several standard processing toolsets used by a large segment of the Earth and Ocean Sciences. GMT's strengths lie in superior publication-quality vector graphics, geodetic-quality map projections, robust data processing algorithms scalable to enormous data sets, and ability to run under all common operating systems. The GMT tool chest offers over 120 modules sharing a common set of command options, file structures, and documentation. GMT modules are command line tools that accept input and write output, and this design allows users to write scripts in which one module's output becomes another module's input, creating highly customized GMT workflows. With the release of GMT 5, these modules are high-level functions with a C API, potentially allowing users access to high-level GMT capabilities from any programmable environment. Many scientists who use GMT also use other computational tools, such as MATLAB® and its clone Octave. We have built a MATLAB/Octave interface on top of the GMT 5 C API. Thus, MATLAB or Octave now has full access to all GMT modules as well as fundamental input/output of GMT data objects via a MEX function. Internally, the GMT/MATLAB C API defines six high-level composite data objects that handle input and output of data via individual GMT modules. These are data tables, grids, text tables (text/data mixed records), color palette tables, raster images (1-4 color bands), and PostScript. The API is responsible for translating between the six GMT objects and the corresponding native MATLAB objects. References to data arrays are passed if transposing of matrices is not required. The GMT and MATLAB/Octave combination is extremely flexible, letting the user harvest the general numerical and graphical capabilities of both systems, and represents a giant step forward in interoperability between GMT and other software package. We will present examples of the symbiotic benefits of combining these platforms. Two other extensions are also in the works: a nearly finished Julia wrapper and an embryonic Python module. Publication supported by FCT- project UID/GEO/50019/2013 - Instituto D. Luiz

Traffic analysis and control using image processing

NASA Astrophysics Data System (ADS)

Senthilkumar, K.; Ellappan, Vijayan; Arun, A. R.

2017-11-01

This paper shows the work on traffic analysis and control till date. It shows an approach to regulate traffic the use of image processing and MATLAB systems. This concept uses computational images that are to be compared with original images of the street taken in order to determine the traffic level percentage and set the timing for the traffic signal accordingly which are used to reduce the traffic stoppage on traffic lights. They concept proposes to solve real life scenarios in the streets, thus enriching the traffic lights by adding image receivers like HD cameras and image processors. The input is then imported into MATLAB to be used. as a method for calculating the traffic on roads. Their results would be computed in order to adjust the traffic light timings on a particular street, and also with respect to other similar proposals but with the added value of solving a real, big instance.

Splitting parameter yield (SPY): A program for semiautomatic analysis of shear-wave splitting

NASA Astrophysics Data System (ADS)

Zaccarelli, Lucia; Bianco, Francesca; Zaccarelli, Riccardo

2012-03-01

SPY is a Matlab algorithm that analyzes seismic waveforms in a semiautomatic way, providing estimates of the two observables of the anisotropy: the shear-wave splitting parameters. We chose to exploit those computational processes that require less intervention by the user, gaining objectivity and reliability as a result. The algorithm joins the covariance matrix and the cross-correlation techniques, and all the computation steps are interspersed by several automatic checks intended to verify the reliability of the yields. The resulting semiautomation generates two new advantages in the field of anisotropy studies: handling a huge amount of data at the same time, and comparing different yields. From this perspective, SPY has been developed in the Matlab environment, which is widespread, versatile, and user-friendly. Our intention is to provide the scientific community with a new monitoring tool for tracking the temporal variations of the crustal stress field.

Introduction to TAFI - A Matlab® toolbox for analysis of flexural isostasy

NASA Astrophysics Data System (ADS)

Jha, S.; Harry, D. L.; Schutt, D.

2016-12-01

The isostatic response of vertical tectonic loads emplaced on thin elastic plates overlying inviscid substrate and the corresponding gravity anomalies are commonly modeled using well established theories and methodologies of flexural analysis. However, such analysis requires some mathematical and coding expertise on part of users. With that in mind, we designed a new interactive Matlab® toolbox called Toolbox for Analysis of Flexural Isostasy (TAFI). TAFI allows users to create forward models (2-D and 3-D) of flexural deformation of the lithosphere and resulting gravity anomaly. TAFI computes Green's Functions for flexure of the elastic plate subjected to point or line loads, and analytical solution for harmonic loads. Flexure due to non-impulsive, distributed 2-D or 3-D loads are computed by convolving the appropriate Green's function with a user-supplied spatially discretized load function. The gravity anomaly associated with each density interface is calculated by using the Fourier Transform of flexural deflection of these interfaces and estimating the gravity in the wavenumber domain. All models created in TAFI are based on Matlab's intrinsic functions and do not require any specialized toolbox, function or library except those distributed with TAFI. Modeling functions within TAFI can be called from Matlab workspace, from within user written programs or from the TAFI's graphical user interface (GUI). The GUI enables the user to model the flexural deflection of lithosphere interactively, enabling real time comparison of model fit with observed data constraining the flexural deformation and gravity, facilitating rapid search for best fitting flexural model. TAFI is a very useful teaching and research tool and have been tested rigorously in graduate level teaching and basic research environment.

A suite of MATLAB-based computational tools for automated analysis of COPAS Biosort data

PubMed Central

Morton, Elizabeth; Lamitina, Todd

2010-01-01

Complex Object Parametric Analyzer and Sorter (COPAS) devices are large-object, fluorescence-capable flow cytometers used for high-throughput analysis of live model organisms, including Drosophila melanogaster, Caenorhabditis elegans, and zebrafish. The COPAS is especially useful in C. elegans high-throughput genome-wide RNA interference (RNAi) screens that utilize fluorescent reporters. However, analysis of data from such screens is relatively labor-intensive and time-consuming. Currently, there are no computational tools available to facilitate high-throughput analysis of COPAS data. We used MATLAB to develop algorithms (COPAquant, COPAmulti, and COPAcompare) to analyze different types of COPAS data. COPAquant reads single-sample files, filters and extracts values and value ratios for each file, and then returns a summary of the data. COPAmulti reads 96-well autosampling files generated with the ReFLX adapter, performs sample filtering, graphs features across both wells and plates, performs some common statistical measures for hit identification, and outputs results in graphical formats. COPAcompare performs a correlation analysis between replicate 96-well plates. For many parameters, thresholds may be defined through a simple graphical user interface (GUI), allowing our algorithms to meet a variety of screening applications. In a screen for regulators of stress-inducible GFP expression, COPAquant dramatically accelerated data analysis and allowed us to rapidly move from raw data to hit identification. Because the COPAS file structure is standardized and our MATLAB code is freely available, our algorithms should be extremely useful for analysis of COPAS data from multiple platforms and organisms. The MATLAB code is freely available at our web site (www.med.upenn.edu/lamitinalab/downloads.shtml). PMID:20569218

Integrating products of Bessel functions with an additional exponential or rational factor

NASA Astrophysics Data System (ADS)

Van Deun, Joris; Cools, Ronald

2008-04-01

We provide two MATLAB programs to compute integrals of the form ex∏i=1kJν_i(ax)dxand 0∞xr+x∏i=1kJν_i(ax)dx with Jν_i(x) the Bessel function of the first kind and (real) order ν. The parameter m is a real number such that ∑ν+m>-1 (to assure integrability near zero), r is real and the numbers c and a are all strictly positive. The program can deliver accurate error estimates. Program summaryProgram title: BESSELINTR, BESSELINTC Catalogue identifier: AEAH_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAH_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 1601 No. of bytes in distributed program, including test data, etc.: 13 161 Distribution format: tar.gz Programming language: Matlab (version ⩾6.5), Octave (version ⩾2.1.69) Computer: All supporting Matlab or Octave Operating system: All supporting Matlab or Octave RAM: For k Bessel functions our program needs approximately ( 500+140k) double precision variables Classification: 4.11 Nature of problem: The problem consists in integrating an arbitrary product of Bessel functions with an additional rational or exponential factor over a semi-infinite interval. Difficulties arise from the irregular oscillatory behaviour and the possible slow decay of the integrand, which prevents truncation at a finite point. Solution method: The interval of integration is split into a finite and infinite part. The integral over the finite part is computed using Gauss-Legendre quadrature. The integrand on the infinite part is approximated using asymptotic expansions and this approximation is integrated exactly with the aid of the upper incomplete gamma function. In the case where a rational factor is present, this factor is first expanded in a Taylor series around infinity. Restrictions: Some (and eventually all) numerical accuracy is lost when one or more of the parameters r,c,a or v grow very large, or when r becomes small. Running time: Less than 0.02 s for a simple problem (two Bessel functions, small parameters), a few seconds for a more complex problem (more than six Bessel functions, large parameters), in Matlab 7.4 (R2007a) on a 2.4 GHz AMD Opteron Processor 250. References:J. Van Deun, R. Cools, Algorithm 858: Computing infinite range integrals of an arbitrary product of Bessel functions, ACM Trans. Math. Software 32 (4) (2006) 580-596.

Simulation tools for two-dimensional experiments in x-ray computed tomography using the FORBILD head phantom

PubMed Central

Yu, Zhicong; Noo, Frédéric; Dennerlein, Frank; Wunderlich, Adam; Lauritsch, Günter; Hornegger, Joachim

2012-01-01

Mathematical phantoms are essential for the development and early-stage evaluation of image reconstruction algorithms in x-ray computed tomography (CT). This note offers tools for computer simulations using a two-dimensional (2D) phantom that models the central axial slice through the FORBILD head phantom. Introduced in 1999, in response to a need for a more robust test, the FORBILD head phantom is now seen by many as the gold standard. However, the simple Shepp-Logan phantom is still heavily used by researchers working on 2D image reconstruction. Universal acceptance of the FORBILD head phantom may have been prevented by its significantly-higher complexity: software that allows computer simulations with the Shepp-Logan phantom is not readily applicable to the FORBILD head phantom. The tools offered here address this problem. They are designed for use with Matlab®, as well as open-source variants, such as FreeMat and Octave, which are all widely used in both academia and industry. To get started, the interested user can simply copy and paste the codes from this PDF document into Matlab® M-files. PMID:22713335

Simulation tools for two-dimensional experiments in x-ray computed tomography using the FORBILD head phantom.

PubMed

Yu, Zhicong; Noo, Frédéric; Dennerlein, Frank; Wunderlich, Adam; Lauritsch, Günter; Hornegger, Joachim

2012-07-07

Mathematical phantoms are essential for the development and early stage evaluation of image reconstruction algorithms in x-ray computed tomography (CT). This note offers tools for computer simulations using a two-dimensional (2D) phantom that models the central axial slice through the FORBILD head phantom. Introduced in 1999, in response to a need for a more robust test, the FORBILD head phantom is now seen by many as the gold standard. However, the simple Shepp-Logan phantom is still heavily used by researchers working on 2D image reconstruction. Universal acceptance of the FORBILD head phantom may have been prevented by its significantly higher complexity: software that allows computer simulations with the Shepp-Logan phantom is not readily applicable to the FORBILD head phantom. The tools offered here address this problem. They are designed for use with Matlab®, as well as open-source variants, such as FreeMat and Octave, which are all widely used in both academia and industry. To get started, the interested user can simply copy and paste the codes from this PDF document into Matlab® M-files.

From design to manufacturing of asymmetric teeth gears using computer application

NASA Astrophysics Data System (ADS)

Suciu, F.; Dascalescu, A.; Ungureanu, M.

2017-05-01

The asymmetric cylindrical gears, with involutes teeth profiles having different base circle diameters, are nonstandard gears, used with the aim to obtain better function parameters for the active profile. We will expect that the manufacturing of these gears became possible only after the design and realization of some specific tools. The paper present how the computer aided design and applications developed in MATLAB, for obtain the geometrical parameters, in the same time for calculation some functional parameters like stress and displacements, transmission error, efficiency of the gears and the 2D models, generated with AUTOLISP applications, are used for computer aided manufacturing of asymmetric gears with standard tools. So the specific tools considered one of the disadvantages of these gears are not necessary and implicitly the expected supplementary costs are reduced. The calculus algorithm established for the asymmetric gear design application use the „direct design“ of the spur gears. This method offers the possibility of determining first the parameters of the gears, followed by the determination of the asymmetric gear rack’s parameters, based on those of the gears. Using original design method and computer applications have been determined the geometrical parameters, the 2D and 3D models of the asymmetric gears and on the base of these models have been manufacturing on CNC machine tool asymmetric gears.

Optimization of CCGT power plant and performance analysis using MATLAB/Simulink with actual operational data.

PubMed

Hasan, Naimul; Rai, Jitendra Nath; Arora, Bharat Bhushan

2014-01-01

In the Modern scenario, the naturally available resources for power generation are being depleted at an alarming rate; firstly due to wastage of power at consumer end, secondly due to inefficiency of various power system components. A Combined Cycle Gas Turbine (CCGT) integrates two cycles- Brayton cycle (Gas Turbine) and Rankine cycle (Steam Turbine) with the objective of increasing overall plant efficiency. This is accomplished by utilising the exhaust of Gas Turbine through a waste-heat recovery boiler to run a Steam Turbine. The efficiency of a gas turbine which ranges from 28% to 33% can hence be raised to about 60% by recovering some of the low grade thermal energy from the exhaust gas for steam turbine process. This paper is a study for the modelling of CCGT and comparing it with actual operational data. The performance model for CCGT plant was developed in MATLAB/Simulink.

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation

PubMed Central

Sherfey, Jason S.; Soplata, Austin E.; Ardid, Salva; Roberts, Erik A.; Stanley, David A.; Pittman-Polletta, Benjamin R.; Kopell, Nancy J.

2018-01-01

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community. PMID:29599715

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation.

PubMed

Sherfey, Jason S; Soplata, Austin E; Ardid, Salva; Roberts, Erik A; Stanley, David A; Pittman-Polletta, Benjamin R; Kopell, Nancy J

2018-01-01

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community.

RARtool: A MATLAB Software Package for Designing Response-Adaptive Randomized Clinical Trials with Time-to-Event Outcomes.

PubMed

Ryeznik, Yevgen; Sverdlov, Oleksandr; Wong, Weng Kee

2015-08-01

Response-adaptive randomization designs are becoming increasingly popular in clinical trial practice. In this paper, we present RARtool , a user interface software developed in MATLAB for designing response-adaptive randomized comparative clinical trials with censored time-to-event outcomes. The RARtool software can compute different types of optimal treatment allocation designs, and it can simulate response-adaptive randomization procedures targeting selected optimal allocations. Through simulations, an investigator can assess design characteristics under a variety of experimental scenarios and select the best procedure for practical implementation. We illustrate the utility of our RARtool software by redesigning a survival trial from the literature.

Advances in Parallel Computing and Databases for Digital Pathology in Cancer Research

DTIC Science & Technology

2016-11-13

these technologies and how we have used them in the past. We are interested in learning more about the needs of clinical pathologists as we continue to...such as image processing and correlation. Further, High Performance Computing (HPC) paradigms such as the Message Passing Interface (MPI) have been...Defense for Research and Engineering. such as pMatlab [4], or bcMPI [5] can significantly reduce the need for deep knowledge of parallel computing. In

E2GPR - Edit your geometry, Execute GprMax2D and Plot the Results!

NASA Astrophysics Data System (ADS)

Pirrone, Daniele; Pajewski, Lara

2015-04-01

In order to predict correctly the Ground Penetrating Radar (GPR) response from a particular scenario, Maxwell's equations have to be solved, subject to the physical and geometrical properties of the considered problem and to its initial conditions. Several techniques have been developed in computational electromagnetics, for the solution of Maxwell's equations. These methods can be classified into two main categories: differential and integral equation solvers, which can be implemented in the time or spectral domain. All of the different methods present compromises between computational efficiency, stability, and the ability to model complex geometries. The Finite-Difference Time-Domain (FDTD) technique has several advantages over alternative approaches: it has inherent simplicity, efficiency and conditional stability; it is suitable to treat impulsive behavior of the electromagnetic field and can provide either ultra-wideband temporal waveforms or the sinusoidal steady-state response at any frequency within the excitation spectrum; it is accurate and highly versatile; and it has become a mature and well-researched technique. Moreover, the FDTD technique is suitable to be executed on parallel-processing CPU-based computers and to exploit the modern computer visualisation capabilities. GprMax [1] is a very well-known and largely validated FDTD software tool, implemented by A. Giannopoulos and available for free public download on www.gprmax.com, together with examples and a detailled user guide. The tool includes two electromagnetic wave simulators, GprMax2D and GprMax3D, for the full-wave simulation of two-dimensional and three-dimensional GPR models. In GprMax, everything can be done with the aid of simple commands that are used to define the model parameters and results to be calculated. These commands need to be entered in a simple ASCII text file. GprMax output files can be stored in ASCII or binary format. The software is provided with MATLAB functions, which can be employed to import synthetic data created by GprMax using the binary-format option into MATLAB, in order to be processed and/or visualized. Further MATLAB procedures for the visualization of GprMax synthetic data have been developed within the COST Action TU1208 [2] and are available for free public download on www.GPRadar.eu. The current version of GprMax3D is compiled with OpenMP, supporting multi-platform shared memory multiprocessing which allows GprMax3D to take advantage of multiple cores/CPUs. GprMax2D, instead, exploits a single core when executed. E2GPR is a new software tool, available free of charge for both academic and commercial use, conceived to: 1) assist in the creation, modification and analysis of GprMax2D models, through a Computer-Aided Design (CAD) system; 2) allow parallel and/or distributed computing with GprMax2D, on a network of computers; 3) automatically plot A-scans and B-scans generated by GprMax2D. The CAD and plotter parts of the tool are implemented in Java and can run on any Java Virtual Machine (JVM) regardless of computer architecture. The part of the tool devoted to supporting parallel and/or distributed computing, instead, requires the set up of a Web-Service (on a server emulator or server); in fact, it is currently configured only for Windows Server and Internet Information Services (IIS). In this work, E2GPR is presented and examples are provided which demonstrate its use. The tool can be currently obtained by contacting the authors. It will soon be possible to download it from www.GPRadar.eu. Acknowledgement This work is a contribution to the COST Action TU1208 'Civil Engineering Applications of Ground Penetrating Radar.' The authors thank COST for funding the Action TU1208. References [1] A. Giannopoulos, 'Modelling ground penetrating radar by GprMax,' Construction and Building Materials, vol. 19, pp. 755-762, 2005. [2] L. Pajewski, A. Benedetto, X. Dérobert, A. Giannopoulos, A. Loizos, G. Manacorda, M. Marciniak, C. Plati, G. Schettini, I. Trinks, "Applications of Ground Penetrating Radar in Civil Engineering - COST Action TU1208," Proc. 7th International Workshop on Advanced Ground Penetrating Radar (IWAGPR), 2-5 July 2013, Nantes, France, pp. 1-6.

NeuroManager: a workflow analysis based simulation management engine for computational neuroscience

PubMed Central

Stockton, David B.; Santamaria, Fidel

2015-01-01

We developed NeuroManager, an object-oriented simulation management software engine for computational neuroscience. NeuroManager automates the workflow of simulation job submissions when using heterogeneous computational resources, simulators, and simulation tasks. The object-oriented approach (1) provides flexibility to adapt to a variety of neuroscience simulators, (2) simplifies the use of heterogeneous computational resources, from desktops to super computer clusters, and (3) improves tracking of simulator/simulation evolution. We implemented NeuroManager in MATLAB, a widely used engineering and scientific language, for its signal and image processing tools, prevalence in electrophysiology analysis, and increasing use in college Biology education. To design and develop NeuroManager we analyzed the workflow of simulation submission for a variety of simulators, operating systems, and computational resources, including the handling of input parameters, data, models, results, and analyses. This resulted in 22 stages of simulation submission workflow. The software incorporates progress notification, automatic organization, labeling, and time-stamping of data and results, and integrated access to MATLAB's analysis and visualization tools. NeuroManager provides users with the tools to automate daily tasks, and assists principal investigators in tracking and recreating the evolution of research projects performed by multiple people. Overall, NeuroManager provides the infrastructure needed to improve workflow, manage multiple simultaneous simulations, and maintain provenance of the potentially large amounts of data produced during the course of a research project. PMID:26528175

NeuroManager: a workflow analysis based simulation management engine for computational neuroscience.

PubMed

Stockton, David B; Santamaria, Fidel

2015-01-01

We developed NeuroManager, an object-oriented simulation management software engine for computational neuroscience. NeuroManager automates the workflow of simulation job submissions when using heterogeneous computational resources, simulators, and simulation tasks. The object-oriented approach (1) provides flexibility to adapt to a variety of neuroscience simulators, (2) simplifies the use of heterogeneous computational resources, from desktops to super computer clusters, and (3) improves tracking of simulator/simulation evolution. We implemented NeuroManager in MATLAB, a widely used engineering and scientific language, for its signal and image processing tools, prevalence in electrophysiology analysis, and increasing use in college Biology education. To design and develop NeuroManager we analyzed the workflow of simulation submission for a variety of simulators, operating systems, and computational resources, including the handling of input parameters, data, models, results, and analyses. This resulted in 22 stages of simulation submission workflow. The software incorporates progress notification, automatic organization, labeling, and time-stamping of data and results, and integrated access to MATLAB's analysis and visualization tools. NeuroManager provides users with the tools to automate daily tasks, and assists principal investigators in tracking and recreating the evolution of research projects performed by multiple people. Overall, NeuroManager provides the infrastructure needed to improve workflow, manage multiple simultaneous simulations, and maintain provenance of the potentially large amounts of data produced during the course of a research project.

Visible in camouflage of military engineering application

NASA Astrophysics Data System (ADS)

Pu, Huan; Kang, Qing; Chen, Shanjing; Wang, Zhenggang

2016-03-01

Our traditional methods of disguise shortcomings, using optical material combined with traditional methods to improve the efficiency of camouflage in disguise. Present lack of effective camouflage effect evaluation system, it refers to Matlab software for optical phase camouflage effect evaluation.

Using the Parallel Computing Toolbox with MATLAB on the Peregrine System |

Science.gov Websites

parallel pool took %g seconds.\\n', toc) % "single program multiple data" spmd fprintf('Worker %d says Hello World!\\n', labindex) end delete(gcp); % close the parallel pool exit To run the script on a compute node, create the file helloWorld.sub: #!/bin/bash #PBS -l walltime=05:00 #PBS -l nodes=1 #PBS -N

MATLAB for laser speckle contrast analysis (LASCA): a practice-based approach

NASA Astrophysics Data System (ADS)

Postnikov, Eugene B.; Tsoy, Maria O.; Postnov, Dmitry E.

2018-04-01

Laser Speckle Contrast Analysis (LASCA) is one of the most powerful modern methods for revealing blood dynamics. The experimental design and theory for this method are well established, and the computational recipie is often regarded to be trivial. However, the achieved performance and spatial resolution may considerable differ for different implementations. We comprise a minireview of known approaches to the spatial laser speckle contrast data processing and their realization in MATLAB code providing an explicit correspondence to the mathematical representation, a discussion of available implementations. We also present the algorithm based on the 2D Haar wavelet transform, also supplied with the program code. This new method provides an opportunity to introduce horizontal, vertical and diagonal speckle contrasts; it may be used for processing highly anisotropic images of vascular trees. We provide the comparative analysis of the accuracy of vascular pattern detection and the processing times with a special attention to details of the used MATLAB procedures.

Design of an ammonia closed-loop storage system in a CSP power plant with a power tower cavity receiver

NASA Astrophysics Data System (ADS)

Abdiwe, Ramadan; Haider, Markus

2017-06-01

In this study the thermochemical system using ammonia as energy storage carrier is investigated and a transient mathematical model using MATLAB software was developed to predict the behavior of the ammonia closed-loop storage system including but not limited to the ammonia solar reactor and the ammonia synthesis reactor. The MATLAB model contains transient mass and energy balances as well as chemical equilibrium model for each relevant system component. For the importance of the dissociation and formation processes in the system, a Computational Fluid Dynamics (CFD) simulation on the ammonia solar and synthesis reactors has been performed. The CFD commercial package FLUENT is used for the simulation study and all the important mechanisms for packed bed reactors are taken into account, such as momentum, heat and mass transfer, and chemical reactions. The FLUENT simulation reveals the profiles inside both reactors and compared them with the profiles from the MATLAB code.

HEART: an automated beat-to-beat cardiovascular analysis package using Matlab.

PubMed

Schroeder, M J Mark J; Perreault, Bill; Ewert, D L Daniel L; Koenig, S C Steven C

2004-07-01

A computer program is described for beat-to-beat analysis of cardiovascular parameters from high-fidelity pressure and flow waveforms. The Hemodynamic Estimation and Analysis Research Tool (HEART) is a post-processing analysis software package developed in Matlab that enables scientists and clinicians to document, load, view, calibrate, and analyze experimental data that have been digitally saved in ascii or binary format. Analysis routines include traditional hemodynamic parameter estimates as well as more sophisticated analyses such as lumped arterial model parameter estimation and vascular impedance frequency spectra. Cardiovascular parameter values of all analyzed beats can be viewed and statistically analyzed. An attractive feature of the HEART program is the ability to analyze data with visual quality assurance throughout the process, thus establishing a framework toward which Good Laboratory Practice (GLP) compliance can be obtained. Additionally, the development of HEART on the Matlab platform provides users with the flexibility to adapt or create study specific analysis files according to their specific needs. Copyright 2003 Elsevier Ltd.

G-Guidance Interface Design for Small Body Mission Simulation

NASA Technical Reports Server (NTRS)

Acikmese, Behcet; Carson, John; Phan, Linh

2008-01-01

The G-Guidance software implements a guidance and control (G and C) algorithm for small-body, autonomous proximity operations, developed under the Small Body GN and C task at JPL. The software is written in Matlab and interfaces with G-OPT, a JPL-developed optimization package written in C that provides G-Guidance with guaranteed convergence to a solution in a finite computation time with a prescribed accuracy. The resulting program is computationally efficient and is a prototype of an onboard, real-time algorithm for autonomous guidance and control. Two thruster firing schemes are available in G-Guidance, allowing tailoring of the software for specific mission maneuvers. For example, descent, landing, or rendezvous benefit from a thruster firing at the maneuver termination to mitigate velocity errors. Conversely, ascent or separation maneuvers benefit from an immediate firing to avoid potential drift toward a second body. The guidance portion of this software explicitly enforces user-defined control constraints and thruster silence times while minimizing total fuel usage. This program is currently specialized to small-body proximity operations, but the underlying method can be generalized to other applications.

An alternative respiratory sounds classification system utilizing artificial neural networks.

PubMed

Oweis, Rami J; Abdulhay, Enas W; Khayal, Amer; Awad, Areen

2015-01-01

Computerized lung sound analysis involves recording lung sound via an electronic device, followed by computer analysis and classification based on specific signal characteristics as non-linearity and nonstationarity caused by air turbulence. An automatic analysis is necessary to avoid dependence on expert skills. This work revolves around exploiting autocorrelation in the feature extraction stage. All process stages were implemented in MATLAB. The classification process was performed comparatively using both artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFIS) toolboxes. The methods have been applied to 10 different respiratory sounds for classification. The ANN was superior to the ANFIS system and returned superior performance parameters. Its accuracy, specificity, and sensitivity were 98.6%, 100%, and 97.8%, respectively. The obtained parameters showed superiority to many recent approaches. The promising proposed method is an efficient fast tool for the intended purpose as manifested in the performance parameters, specifically, accuracy, specificity, and sensitivity. Furthermore, it may be added that utilizing the autocorrelation function in the feature extraction in such applications results in enhanced performance and avoids undesired computation complexities compared to other techniques.

Comparative study of the efficiency of computed univariate and multivariate methods for the estimation of the binary mixture of clotrimazole and dexamethasone using two different spectral regions

NASA Astrophysics Data System (ADS)

Fayez, Yasmin Mohammed; Tawakkol, Shereen Mostafa; Fahmy, Nesma Mahmoud; Lotfy, Hayam Mahmoud; Shehata, Mostafa Abdel-Aty

2018-04-01

Three methods of analysis are conducted that need computational procedures by the Matlab® software. The first is the univariate mean centering method which eliminates the interfering signal of the one component at a selected wave length leaving the amplitude measured to represent the component of interest only. The other two multivariate methods named PLS and PCR depend on a large number of variables that lead to extraction of the maximum amount of information required to determine the component of interest in the presence of the other. Good accurate and precise results are obtained from the three methods for determining clotrimazole in the linearity range 1-12 μg/mL and 75-550 μg/mL with dexamethasone acetate 2-20 μg/mL in synthetic mixtures and pharmaceutical formulation using two different spectral regions 205-240 nm and 233-278 nm. The results obtained are compared statistically to each other and to the official methods.

TU-AB-BRC-12: Optimized Parallel MonteCarlo Dose Calculations for Secondary MU Checks

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

French, S; Nazareth, D; Bellor, M

Purpose: Secondary MU checks are an important tool used during a physics review of a treatment plan. Commercial software packages offer varying degrees of theoretical dose calculation accuracy, depending on the modality involved. Dose calculations of VMAT plans are especially prone to error due to the large approximations involved. Monte Carlo (MC) methods are not commonly used due to their long run times. We investigated two methods to increase the computational efficiency of MC dose simulations with the BEAMnrc code. Distributed computing resources, along with optimized code compilation, will allow for accurate and efficient VMAT dose calculations. Methods: The BEAMnrcmore » package was installed on a high performance computing cluster accessible to our clinic. MATLAB and PYTHON scripts were developed to convert a clinical VMAT DICOM plan into BEAMnrc input files. The BEAMnrc installation was optimized by running the VMAT simulations through profiling tools which indicated the behavior of the constituent routines in the code, e.g. the bremsstrahlung splitting routine, and the specified random number generator. This information aided in determining the most efficient compiling parallel configuration for the specific CPU’s available on our cluster, resulting in the fastest VMAT simulation times. Our method was evaluated with calculations involving 10{sup 8} – 10{sup 9} particle histories which are sufficient to verify patient dose using VMAT. Results: Parallelization allowed the calculation of patient dose on the order of 10 – 15 hours with 100 parallel jobs. Due to the compiler optimization process, further speed increases of 23% were achieved when compared with the open-source compiler BEAMnrc packages. Conclusion: Analysis of the BEAMnrc code allowed us to optimize the compiler configuration for VMAT dose calculations. In future work, the optimized MC code, in conjunction with the parallel processing capabilities of BEAMnrc, will be applied to provide accurate and efficient secondary MU checks.« less

Diagnostic accuracy of ovarian cyst segmentation in B-mode ultrasound images

NASA Astrophysics Data System (ADS)

Bibicu, Dorin; Moraru, Luminita; Stratulat (Visan), Mirela

2013-11-01

Cystic and polycystic ovary syndrome is an endocrine disorder affecting women in the fertile age. The Moore Neighbor Contour, Watershed Method, Active Contour Models, and a recent method based on Active Contour Model with Selective Binary and Gaussian Filtering Regularized Level Set (ACM&SBGFRLS) techniques were used in this paper to detect the border of the ovarian cyst from echography images. In order to analyze the efficiency of the segmentation an original computer aided software application developed in MATLAB was proposed. The results of the segmentation were compared and evaluated against the reference contour manually delineated by a sonography specialist. Both the accuracy and time complexity of the segmentation tasks are investigated. The Fréchet distance (FD) as a similarity measure between two curves and the area error rate (AER) parameter as the difference between the segmented areas are used as estimators of the segmentation accuracy. In this study, the most efficient methods for the segmentation of the ovarian were analyzed cyst. The research was carried out on a set of 34 ultrasound images of the ovarian cyst.

Using STOQS and stoqstoolbox for in situ Measurement Data Access in Matlab

NASA Astrophysics Data System (ADS)

López-Castejón, F.; Schlining, B.; McCann, M. P.

2012-12-01

This poster presents the stoqstoolbox, an extension to Matlab that simplifies the loading of in situ measurement data directly from STOQS databases. STOQS (Spatial Temporal Oceanographic Query System) is a geospatial database tool designed to provide efficient access to data following the CF-NetCDF Discrete Samples Geometries convention. Data are loaded from CF-NetCDF files into a STOQS database where indexes are created on depth, spatial coordinates and other parameters, e.g. platform type. STOQS provides consistent, simple and efficient methods to query for data. For example, we can request all measurements with a standard_name of sea_water_temperature between two times and from between two depths. Data access is simpler because the data are retrieved by parameter irrespective of platform or mission file names. Access is more efficient because data are retrieved via the index on depth and only the requested data are retrieved from the database and transferred into the Matlab workspace. Applications in the stoqstoolbox query the STOQS database via an HTTP REST application programming interface; they follow the Data Access Object pattern, enabling highly customizable query construction. Data are loaded into Matlab structures that clearly indicate latitude, longitude, depth, measurement data value, and platform name. The stoqstoolbox is designed to be used in concert with other tools, such as nctoolbox, which can load data from any OPeNDAP data source. With these two toolboxes a user can easily work with in situ and other gridded data, such as from numerical models and remote sensing platforms. In order to show the capability of stoqstoolbox we will show an example of model validation using data collected during the May-June 2012 field experiment conducted by the Monterey Bay Aquarium Research Institute (MBARI) in Monterey Bay, California. The data are available from the STOQS server at http://odss.mbari.org/canon/stoqs_may2012/query/. Over 14 million data points of 18 parameters from 6 platforms measured over a 3-week period are available on this server. The model used for comparison is the Regional Ocean Modeling System developed by Jet Propulsion Laboratory for the Monterey Bay. The model output are loaded into Matlab using nctoolbox from the JPL server at http://ourocean.jpl.nasa.gov:8080/thredds/dodsC/MBNowcast. Model validation with in situ measurements can be difficult because of different file formats and because data may be spread across individual data systems for each platform. With stoqstoolbox the researcher must know only the URL of the STOQS server and the OPeNDAP URL of the model output. With selected depth and time constraints a user's Matlab program searches for all in situ measurements available for the same time, depth and variable of the model. STOQS and stoqstoolbox are open source software projects supported by MBARI and the David and Lucile Packard foundation. For more information please see http://code.google.com/p/stoqs.

An Accurate and Efficient Algorithm for Detection of Radio Bursts with an Unknown Dispersion Measure, for Single-dish Telescopes and Interferometers

NASA Astrophysics Data System (ADS)

Zackay, Barak; Ofek, Eran O.

2017-01-01

Astronomical radio signals are subjected to phase dispersion while traveling through the interstellar medium. To optimally detect a short-duration signal within a frequency band, we have to precisely compensate for the unknown pulse dispersion, which is a computationally demanding task. We present the “fast dispersion measure transform” algorithm for optimal detection of such signals. Our algorithm has a low theoretical complexity of 2{N}f{N}t+{N}t{N}{{Δ }}{{log}}2({N}f), where Nf, Nt, and NΔ are the numbers of frequency bins, time bins, and dispersion measure bins, respectively. Unlike previously suggested fast algorithms, our algorithm conserves the sensitivity of brute-force dedispersion. Our tests indicate that this algorithm, running on a standard desktop computer and implemented in a high-level programming language, is already faster than the state-of-the-art dedispersion codes running on graphical processing units (GPUs). We also present a variant of the algorithm that can be efficiently implemented on GPUs. The latter algorithm’s computation and data-transport requirements are similar to those of a two-dimensional fast Fourier transform, indicating that incoherent dedispersion can now be considered a nonissue while planning future surveys. We further present a fast algorithm for sensitive detection of pulses shorter than the dispersive smearing limits of incoherent dedispersion. In typical cases, this algorithm is orders of magnitude faster than enumerating dispersion measures and coherently dedispersing by convolution. We analyze the computational complexity of pulsed signal searches by radio interferometers. We conclude that, using our suggested algorithms, maximally sensitive blind searches for dispersed pulses are feasible using existing facilities. We provide an implementation of these algorithms in Python and MATLAB.

A Matlab-based finite-difference solver for the Poisson problem with mixed Dirichlet-Neumann boundary conditions

NASA Astrophysics Data System (ADS)

Reimer, Ashton S.; Cheviakov, Alexei F.

2013-03-01

A Matlab-based finite-difference numerical solver for the Poisson equation for a rectangle and a disk in two dimensions, and a spherical domain in three dimensions, is presented. The solver is optimized for handling an arbitrary combination of Dirichlet and Neumann boundary conditions, and allows for full user control of mesh refinement. The solver routines utilize effective and parallelized sparse vector and matrix operations. Computations exhibit high speeds, numerical stability with respect to mesh size and mesh refinement, and acceptable error values even on desktop computers. Catalogue identifier: AENQ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENQ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License v3.0 No. of lines in distributed program, including test data, etc.: 102793 No. of bytes in distributed program, including test data, etc.: 369378 Distribution format: tar.gz Programming language: Matlab 2010a. Computer: PC, Macintosh. Operating system: Windows, OSX, Linux. RAM: 8 GB (8, 589, 934, 592 bytes) Classification: 4.3. Nature of problem: To solve the Poisson problem in a standard domain with “patchy surface”-type (strongly heterogeneous) Neumann/Dirichlet boundary conditions. Solution method: Finite difference with mesh refinement. Restrictions: Spherical domain in 3D; rectangular domain or a disk in 2D. Unusual features: Choice between mldivide/iterative solver for the solution of large system of linear algebraic equations that arise. Full user control of Neumann/Dirichlet boundary conditions and mesh refinement. Running time: Depending on the number of points taken and the geometry of the domain, the routine may take from less than a second to several hours to execute.

CERENA: ChEmical REaction Network Analyzer--A Toolbox for the Simulation and Analysis of Stochastic Chemical Kinetics.

PubMed

Kazeroonian, Atefeh; Fröhlich, Fabian; Raue, Andreas; Theis, Fabian J; Hasenauer, Jan

2016-01-01

Gene expression, signal transduction and many other cellular processes are subject to stochastic fluctuations. The analysis of these stochastic chemical kinetics is important for understanding cell-to-cell variability and its functional implications, but it is also challenging. A multitude of exact and approximate descriptions of stochastic chemical kinetics have been developed, however, tools to automatically generate the descriptions and compare their accuracy and computational efficiency are missing. In this manuscript we introduced CERENA, a toolbox for the analysis of stochastic chemical kinetics using Approximations of the Chemical Master Equation solution statistics. CERENA implements stochastic simulation algorithms and the finite state projection for microscopic descriptions of processes, the system size expansion and moment equations for meso- and macroscopic descriptions, as well as the novel conditional moment equations for a hybrid description. This unique collection of descriptions in a single toolbox facilitates the selection of appropriate modeling approaches. Unlike other software packages, the implementation of CERENA is completely general and allows, e.g., for time-dependent propensities and non-mass action kinetics. By providing SBML import, symbolic model generation and simulation using MEX-files, CERENA is user-friendly and computationally efficient. The availability of forward and adjoint sensitivity analyses allows for further studies such as parameter estimation and uncertainty analysis. The MATLAB code implementing CERENA is freely available from http://cerenadevelopers.github.io/CERENA/.

CERENA: ChEmical REaction Network Analyzer—A Toolbox for the Simulation and Analysis of Stochastic Chemical Kinetics

PubMed Central

Kazeroonian, Atefeh; Fröhlich, Fabian; Raue, Andreas; Theis, Fabian J.; Hasenauer, Jan

2016-01-01

Gene expression, signal transduction and many other cellular processes are subject to stochastic fluctuations. The analysis of these stochastic chemical kinetics is important for understanding cell-to-cell variability and its functional implications, but it is also challenging. A multitude of exact and approximate descriptions of stochastic chemical kinetics have been developed, however, tools to automatically generate the descriptions and compare their accuracy and computational efficiency are missing. In this manuscript we introduced CERENA, a toolbox for the analysis of stochastic chemical kinetics using Approximations of the Chemical Master Equation solution statistics. CERENA implements stochastic simulation algorithms and the finite state projection for microscopic descriptions of processes, the system size expansion and moment equations for meso- and macroscopic descriptions, as well as the novel conditional moment equations for a hybrid description. This unique collection of descriptions in a single toolbox facilitates the selection of appropriate modeling approaches. Unlike other software packages, the implementation of CERENA is completely general and allows, e.g., for time-dependent propensities and non-mass action kinetics. By providing SBML import, symbolic model generation and simulation using MEX-files, CERENA is user-friendly and computationally efficient. The availability of forward and adjoint sensitivity analyses allows for further studies such as parameter estimation and uncertainty analysis. The MATLAB code implementing CERENA is freely available from http://cerenadevelopers.github.io/CERENA/. PMID:26807911

Automated processing of thermal infrared images of Osservatorio Vesuviano permanent surveillance network by using Matlab code

NASA Astrophysics Data System (ADS)

Sansivero, Fabio; Vilardo, Giuseppe; Caputo, Teresa

2017-04-01

The permanent thermal infrared surveillance network of Osservatorio Vesuviano (INGV) is composed of 6 stations which acquire IR frames of fumarole fields in the Campi Flegrei caldera and inside the Vesuvius crater (Italy). The IR frames are uploaded to a dedicated server in the Surveillance Center of Osservatorio Vesuviano in order to process the infrared data and to excerpt all the information contained. In a first phase the infrared data are processed by an automated system (A.S.I.R.A. Acq- Automated System of IR Analysis and Acquisition) developed in Matlab environment and with a user-friendly graphic user interface (GUI). ASIRA daily generates time-series of residual temperature values of the maximum temperatures observed in the IR scenes after the removal of seasonal effects. These time-series are displayed in the Surveillance Room of Osservatorio Vesuviano and provide information about the evolution of shallow temperatures field of the observed areas. In particular the features of ASIRA Acq include: a) efficient quality selection of IR scenes, b) IR images co-registration in respect of a reference frame, c) seasonal correction by using a background-removal methodology, a) filing of IR matrices and of the processed data in shared archives accessible to interrogation. The daily archived records can be also processed by ASIRA Plot (Matlab code with GUI) to visualize IR data time-series and to help in evaluating inputs parameters for further data processing and analysis. Additional processing features are accomplished in a second phase by ASIRA Tools which is Matlab code with GUI developed to extract further information from the dataset in automated way. The main functions of ASIRA Tools are: a) the analysis of temperature variations of each pixel of the IR frame in a given time interval, b) the removal of seasonal effects from temperature of every pixel in the IR frames by using an analytic approach (removal of sinusoidal long term seasonal component by using a polynomial fit Matlab function - LTFC_SCOREF), c) the export of data in different raster formats (i.e. Surfer grd). An interesting example of elaborations of the data produced by ASIRA Tools is the map of the temperature changing rate, which provide remarkable information about the potential migration of fumarole activity. The high efficiency of Matlab in processing matrix data from IR scenes and the flexibility of this code-developing tool proved to be very useful to produce applications to use in volcanic surveillance aimed to monitor the evolution of surface temperatures field in diffuse degassing volcanic areas.

A real-time camera calibration system based on OpenCV

NASA Astrophysics Data System (ADS)

Zhang, Hui; Wang, Hua; Guo, Huinan; Ren, Long; Zhou, Zuofeng

2015-07-01

Camera calibration is one of the essential steps in the computer vision research. This paper describes a real-time OpenCV based camera calibration system, and developed and implemented in the VS2008 environment. Experimental results prove that the system to achieve a simple and fast camera calibration, compared with MATLAB, higher precision and does not need manual intervention, and can be widely used in various computer vision system.

Interpretation of the instantaneous frequency of phonocardiogram signals

NASA Astrophysics Data System (ADS)

Rey, Alexis B.

2005-06-01

Short-Time Fourier transforms, Wigner-Ville distribution, and Wavelet Transforms have been commonly used when dealing with non-stationary signals, and they have been known as time-frequency distributions. Also, it is commonly intended to investigate the behaviour of phonocardiogram signals as a means of prediction some oh the pathologies of the human hart. For this, this paper aims to analyze the relationship between the instantaneous frequency of a PCG signal and the so-mentioned time-frequency distributions; three algorithms using Matlab functions have been developed: the first one, the estimation of the IF using the normalized linear moment, the second one, the estimation of the IF using the periodic first moment, and the third one, the computing of the WVD. Meanwhile, the computing of the STFT spectrogram is carried out with a Matlab function. Several simulations of the spectrogram for a set of PCG signals and the estimation of the IF are shown, and its relationship is validated through correlation. Finally, the second algorithm is a better choice because the estimation is not biased, whereas the WVD is very computing-demanding and offers no benefit since the estimation of the IF by using this TFD has an equivalent result when using the derivative of the phase of the analytic signal, which is also less computing-demanding.

Simulating Microbial Community Patterning Using Biocellion

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

Kang, Seung-Hwa; Kahan, Simon H.; Momeni, Babak

2014-04-17

Mathematical modeling and computer simulation are important tools for understanding complex interactions between cells and their biotic and abiotic environment: similarities and differences between modeled and observed behavior provide the basis for hypothesis forma- tion. Momeni et al. [5] investigated pattern formation in communities of yeast strains engaging in different types of ecological interactions, comparing the predictions of mathematical modeling and simulation to actual patterns observed in wet-lab experiments. However, simu- lations of millions of cells in a three-dimensional community are ex- tremely time-consuming. One simulation run in MATLAB may take a week or longer, inhibiting exploration of the vastmore » space of parameter combinations and assumptions. Improving the speed, scale, and accu- racy of such simulations facilitates hypothesis formation and expedites discovery. Biocellion is a high performance software framework for ac- celerating discrete agent-based simulation of biological systems with millions to trillions of cells. Simulations of comparable scale and accu- racy to those taking a week of computer time using MATLAB require just hours using Biocellion on a multicore workstation. Biocellion fur- ther accelerates large scale, high resolution simulations using cluster computers by partitioning the work to run on multiple compute nodes. Biocellion targets computational biologists who have mathematical modeling backgrounds and basic C++ programming skills. This chap- ter describes the necessary steps to adapt the original Momeni et al.'s model to the Biocellion framework as a case study.« less

Mathematical simulation of efficiency of various shapes of solar panels for NASA geostationary satellites

NASA Astrophysics Data System (ADS)

Pandya, Raaghav; Raja, Hammad; Enriquez-Torres, Delfino; Serey-Roman, Maria Ignacia; Hassebo, Yasser; Marciniak, Małgorzata

2018-02-01

The purpose of this research is to analyze mathematically cylindrical shapes of flexible solar panels and compare their efficiency to the flat panels. The efficiency is defined to be the flux density, which is the ratio of the mathematical flux and the surface area. In addition we describe the trajectory of the Sun at specific locations: the North Pole, The Equator and a geostationary satellite above the Equator. The calculations were performed with software: Maple, Mathematica, and MATLAB.

Gravity data inversion to determine 3D topographycal density contrast of Banten area, Indonesia based on fast Fourier transform

NASA Astrophysics Data System (ADS)

Windhari, Ayuty; Handayani, Gunawan

2015-04-01

The 3D inversion gravity anomaly to estimate topographical density using a matlab source code from gridded data provided by Parker Oldenburg algorithm based on fast Fourier transform was computed. We extend and improved the source code of 3DINVERT.M invented by Gomez Ortiz and Agarwal (2005) using the relationship between Fourier transform of the gravity anomaly and the sum of the Fourier transform from the topography density. We gave density contrast between the two media to apply the inversion. FFT routine was implemented to construct amplitude spectrum to the given mean depth. The results were presented as new graphics of inverted topography density, the gravity anomaly due to the inverted topography and the difference between the input gravity data and the computed ones. It terminates when the RMS error is lower than pre-assigned value used as convergence criterion or until maximum of iterations is reached. As an example, we used the matlab program on gravity data of Banten region, Indonesia.

Implementing ADM1 for plant-wide benchmark simulations in Matlab/Simulink.

PubMed

Rosen, C; Vrecko, D; Gernaey, K V; Pons, M N; Jeppsson, U

2006-01-01

The IWA Anaerobic Digestion Model No.1 (ADM1) was presented in 2002 and is expected to represent the state-of-the-art model within this field in the future. Due to its complexity the implementation of the model is not a simple task and several computational aspects need to be considered, in particular if the ADM1 is to be included in dynamic simulations of plant-wide or even integrated systems. In this paper, the experiences gained from a Matlab/Simulink implementation of ADM1 into the extended COST/IWA Benchmark Simulation Model (BSM2) are presented. Aspects related to system stiffness, model interfacing with the ASM family, mass balances, acid-base equilibrium and algebraic solvers for pH and other troublesome state variables, numerical solvers and simulation time are discussed. The main conclusion is that if implemented properly, the ADM1 will also produce high-quality results in dynamic plant-wide simulations including noise, discrete sub-systems, etc. without imposing any major restrictions due to extensive computational efforts.

Mathematical algorithm development and parametric studies with the GEOFRAC three-dimensional stochastic model of natural rock fracture systems

NASA Astrophysics Data System (ADS)

Ivanova, Violeta M.; Sousa, Rita; Murrihy, Brian; Einstein, Herbert H.

2014-06-01

This paper presents results from research conducted at MIT during 2010-2012 on modeling of natural rock fracture systems with the GEOFRAC three-dimensional stochastic model. Following a background summary of discrete fracture network models and a brief introduction of GEOFRAC, the paper provides a thorough description of the newly developed mathematical and computer algorithms for fracture intensity, aperture, and intersection representation, which have been implemented in MATLAB. The new methods optimize, in particular, the representation of fracture intensity in terms of cumulative fracture area per unit volume, P32, via the Poisson-Voronoi Tessellation of planes into polygonal fracture shapes. In addition, fracture apertures now can be represented probabilistically or deterministically whereas the newly implemented intersection algorithms allow for computing discrete pathways of interconnected fractures. In conclusion, results from a statistical parametric study, which was conducted with the enhanced GEOFRAC model and the new MATLAB-based Monte Carlo simulation program FRACSIM, demonstrate how fracture intensity, size, and orientations influence fracture connectivity.

Extracting the Data From the LCM vk4 Formatted Output File

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

Wendelberger, James G.

These are slides about extracting the data from the LCM vk4 formatted output file. The following is covered: vk4 file produced by Keyence VK Software, custom analysis, no off the shelf way to read the file, reading the binary data in a vk4 file, various offsets in decimal lines, finding the height image data, directly in MATLAB, binary output beginning of height image data, color image information, color image binary data, color image decimal and binary data, MATLAB code to read vk4 file (choose a file, read the file, compute offsets, read optical image, laser optical image, read and computemore » laser intensity image, read height image, timing, display height image, display laser intensity image, display RGB laser optical images, display RGB optical images, display beginning data and save images to workspace, gamma correction subroutine), reading intensity form the vk4 file, linear in the low range, linear in the high range, gamma correction for vk4 files, computing the gamma intensity correction, observations.« less

A JavaScript API for the Ice Sheet System Model (ISSM) 4.11: towards an online interactive model for the cryosphere community

NASA Astrophysics Data System (ADS)

Larour, Eric; Cheng, Daniel; Perez, Gilberto; Quinn, Justin; Morlighem, Mathieu; Duong, Bao; Nguyen, Lan; Petrie, Kit; Harounian, Silva; Halkides, Daria; Hayes, Wayne

2017-12-01

Earth system models (ESMs) are becoming increasingly complex, requiring extensive knowledge and experience to deploy and use in an efficient manner. They run on high-performance architectures that are significantly different from the everyday environments that scientists use to pre- and post-process results (i.e., MATLAB, Python). This results in models that are hard to use for non-specialists and are increasingly specific in their application. It also makes them relatively inaccessible to the wider science community, not to mention to the general public. Here, we present a new software/model paradigm that attempts to bridge the gap between the science community and the complexity of ESMs by developing a new JavaScript application program interface (API) for the Ice Sheet System Model (ISSM). The aforementioned API allows cryosphere scientists to run ISSM on the client side of a web page within the JavaScript environment. When combined with a web server running ISSM (using a Python API), it enables the serving of ISSM computations in an easy and straightforward way. The deep integration and similarities between all the APIs in ISSM (MATLAB, Python, and now JavaScript) significantly shortens and simplifies the turnaround of state-of-the-art science runs and their use by the larger community. We demonstrate our approach via a new Virtual Earth System Laboratory (VESL) website (http://vesl.jpl.nasa.gov, VESL(2017)).

OpenNFT: An open-source Python/Matlab framework for real-time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis.

PubMed

Koush, Yury; Ashburner, John; Prilepin, Evgeny; Sladky, Ronald; Zeidman, Peter; Bibikov, Sergei; Scharnowski, Frank; Nikonorov, Artem; De Ville, Dimitri Van

2017-08-01

Neurofeedback based on real-time functional magnetic resonance imaging (rt-fMRI) is a novel and rapidly developing research field. It allows for training of voluntary control over localized brain activity and connectivity and has demonstrated promising clinical applications. Because of the rapid technical developments of MRI techniques and the availability of high-performance computing, new methodological advances in rt-fMRI neurofeedback become possible. Here we outline the core components of a novel open-source neurofeedback framework, termed Open NeuroFeedback Training (OpenNFT), which efficiently integrates these new developments. This framework is implemented using Python and Matlab source code to allow for diverse functionality, high modularity, and rapid extendibility of the software depending on the user's needs. In addition, it provides an easy interface to the functionality of Statistical Parametric Mapping (SPM) that is also open-source and one of the most widely used fMRI data analysis software. We demonstrate the functionality of our new framework by describing case studies that include neurofeedback protocols based on brain activity levels, effective connectivity models, and pattern classification approaches. This open-source initiative provides a suitable framework to actively engage in the development of novel neurofeedback approaches, so that local methodological developments can be easily made accessible to a wider range of users. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Simultaneous Detection of Metalloprotease Activities in Complex Biological Samples Using the PrAMA (Proteolytic Activity Matrix Assay) Method.

PubMed

Conrad, Catharina; Miller, Miles A; Bartsch, Jörg W; Schlomann, Uwe; Lauffenburger, Douglas A

2017-01-01

Proteolytic Activity Matrix Analysis (PrAMA) is a method for simultaneously determining the activities of specific Matrix Metalloproteinases (MMPs) and A Disintegrin and Metalloproteinases (ADAMs) in complex biological samples. In mixtures of unknown proteases, PrAMA infers selective metalloproteinase activities by using a panel of moderately specific FRET-based polypeptide protease substrates in parallel, typically monitored by a plate-reader in a 96-well format. Fluorescence measurements are then quantitatively compared to a standard table of catalytic efficiencies measured from purified mixtures of individual metalloproteinases and FRET substrates. Computational inference of specific activities is performed with an easily used Matlab program, which is provided herein. Thus, we describe PrAMA as a combined experimental and mathematical approach to determine real-time metalloproteinase activities, which has previously been applied to live-cell cultures, cellular lysates, cell culture supernatants, and body fluids from patients.

A Novel Implementation of Efficient Algorithms for Quantum Circuit Synthesis

NASA Astrophysics Data System (ADS)

Zeller, Luke

In this project, we design and develop a computer program to effectively approximate arbitrary quantum gates using the discrete set of Clifford Gates together with the T gate (π/8 gate). Employing recent results from Mosca et. al. and Giles and Selinger, we implement a decomposition scheme that outputs a sequence of Clifford, T, and Tt gates that approximate the input to within a specified error range ɛ. Specifically, the given gate is first rounded to an element of Z[1/2, i] with a precision determined by ɛ, and then exact synthesis is employed to produce the resulting gate. It is known that this procedure is optimal in approximating an arbitrary single qubit gate. Our program, written in Matlab and Python, can complete both approximate and exact synthesis of qubits. It can be used to assist in the experimental implementation of an arbitrary fault-tolerant single qubit gate, for which direct implementation isn't feasible.

Development of a Simple Image Processing Application that Makes Abdominopelvic Tumor Visible on Positron Emission Tomography/Computed Tomography Image.

PubMed

Pandey, Anil Kumar; Saroha, Kartik; Sharma, Param Dev; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

2017-01-01

In this study, we have developed a simple image processing application in MATLAB that uses suprathreshold stochastic resonance (SSR) and helps the user to visualize abdominopelvic tumor on the exported prediuretic positron emission tomography/computed tomography (PET/CT) images. A brainstorming session was conducted for requirement analysis for the program. It was decided that program should load the screen captured PET/CT images and then produces output images in a window with a slider control that should enable the user to view the best image that visualizes the tumor, if present. The program was implemented on personal computer using Microsoft Windows and MATLAB R2013b. The program has option for the user to select the input image. For the selected image, it displays output images generated using SSR in a separate window having a slider control. The slider control enables the user to view images and select one which seems to provide the best visualization of the area(s) of interest. The developed application enables the user to select, process, and view output images in the process of utilizing SSR to detect the presence of abdominopelvic tumor on prediuretic PET/CT image.

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.

Simulation of particle motion in a closed conduit validated against experimental data

NASA Astrophysics Data System (ADS)

Dolanský, Jindřich

2015-05-01

Motion of a number of spherical particles in a closed conduit is examined by means of both simulation and experiment. The bed of the conduit is covered by stationary spherical particles of the size of the moving particles. The flow is driven by experimentally measured velocity profiles which are inputs of the simulation. Altering input velocity profiles generates various trajectory patterns. The lattice Boltzmann method (LBM) based simulation is developed to study mutual interactions of the flow and the particles. The simulation enables to model both the particle motion and the fluid flow. The entropic LBM is employed to deal with the flow characterized by the high Reynolds number. The entropic modification of the LBM along with the enhanced refinement of the lattice grid yield an increase in demands on computational resources. Due to the inherently parallel nature of the LBM it can be handled by employing the Parallel Computing Toolbox (MATLAB) and other transformations enabling usage of the CUDA GPU computing technology. The trajectories of the particles determined within the LBM simulation are validated against data gained from the experiments. The compatibility of the simulation results with the outputs of experimental measurements is evaluated. The accuracy of the applied approach is assessed and stability and efficiency of the simulation is also considered.

Differential network analysis reveals the genome-wide landscape of estrogen receptor modulation in hormonal cancers

PubMed Central

Hsiao, Tzu-Hung; Chiu, Yu-Chiao; Hsu, Pei-Yin; Lu, Tzu-Pin; Lai, Liang-Chuan; Tsai, Mong-Hsun; Huang, Tim H.-M.; Chuang, Eric Y.; Chen, Yidong

2016-01-01

Several mutual information (MI)-based algorithms have been developed to identify dynamic gene-gene and function-function interactions governed by key modulators (genes, proteins, etc.). Due to intensive computation, however, these methods rely heavily on prior knowledge and are limited in genome-wide analysis. We present the modulated gene/gene set interaction (MAGIC) analysis to systematically identify genome-wide modulation of interaction networks. Based on a novel statistical test employing conjugate Fisher transformations of correlation coefficients, MAGIC features fast computation and adaption to variations of clinical cohorts. In simulated datasets MAGIC achieved greatly improved computation efficiency and overall superior performance than the MI-based method. We applied MAGIC to construct the estrogen receptor (ER) modulated gene and gene set (representing biological function) interaction networks in breast cancer. Several novel interaction hubs and functional interactions were discovered. ER+ dependent interaction between TGFβ and NFκB was further shown to be associated with patient survival. The findings were verified in independent datasets. Using MAGIC, we also assessed the essential roles of ER modulation in another hormonal cancer, ovarian cancer. Overall, MAGIC is a systematic framework for comprehensively identifying and constructing the modulated interaction networks in a whole-genome landscape. MATLAB implementation of MAGIC is available for academic uses at https://github.com/chiuyc/MAGIC. PMID:26972162

MATtrack: A MATLAB-Based Quantitative Image Analysis Platform for Investigating Real-Time Photo-Converted Fluorescent Signals in Live Cells.

PubMed

Courtney, Jane; Woods, Elena; Scholz, Dimitri; Hall, William W; Gautier, Virginie W

2015-01-01

We introduce here MATtrack, an open source MATLAB-based computational platform developed to process multi-Tiff files produced by a photo-conversion time lapse protocol for live cell fluorescent microscopy. MATtrack automatically performs a series of steps required for image processing, including extraction and import of numerical values from Multi-Tiff files, red/green image classification using gating parameters, noise filtering, background extraction, contrast stretching and temporal smoothing. MATtrack also integrates a series of algorithms for quantitative image analysis enabling the construction of mean and standard deviation images, clustering and classification of subcellular regions and injection point approximation. In addition, MATtrack features a simple user interface, which enables monitoring of Fluorescent Signal Intensity in multiple Regions of Interest, over time. The latter encapsulates a region growing method to automatically delineate the contours of Regions of Interest selected by the user, and performs background and regional Average Fluorescence Tracking, and automatic plotting. Finally, MATtrack computes convenient visualization and exploration tools including a migration map, which provides an overview of the protein intracellular trajectories and accumulation areas. In conclusion, MATtrack is an open source MATLAB-based software package tailored to facilitate the analysis and visualization of large data files derived from real-time live cell fluorescent microscopy using photoconvertible proteins. It is flexible, user friendly, compatible with Windows, Mac, and Linux, and a wide range of data acquisition software. MATtrack is freely available for download at eleceng.dit.ie/courtney/MATtrack.zip.

MATtrack: A MATLAB-Based Quantitative Image Analysis Platform for Investigating Real-Time Photo-Converted Fluorescent Signals in Live Cells

PubMed Central

Courtney, Jane; Woods, Elena; Scholz, Dimitri; Hall, William W.; Gautier, Virginie W.

2015-01-01

We introduce here MATtrack, an open source MATLAB-based computational platform developed to process multi-Tiff files produced by a photo-conversion time lapse protocol for live cell fluorescent microscopy. MATtrack automatically performs a series of steps required for image processing, including extraction and import of numerical values from Multi-Tiff files, red/green image classification using gating parameters, noise filtering, background extraction, contrast stretching and temporal smoothing. MATtrack also integrates a series of algorithms for quantitative image analysis enabling the construction of mean and standard deviation images, clustering and classification of subcellular regions and injection point approximation. In addition, MATtrack features a simple user interface, which enables monitoring of Fluorescent Signal Intensity in multiple Regions of Interest, over time. The latter encapsulates a region growing method to automatically delineate the contours of Regions of Interest selected by the user, and performs background and regional Average Fluorescence Tracking, and automatic plotting. Finally, MATtrack computes convenient visualization and exploration tools including a migration map, which provides an overview of the protein intracellular trajectories and accumulation areas. In conclusion, MATtrack is an open source MATLAB-based software package tailored to facilitate the analysis and visualization of large data files derived from real-time live cell fluorescent microscopy using photoconvertible proteins. It is flexible, user friendly, compatible with Windows, Mac, and Linux, and a wide range of data acquisition software. MATtrack is freely available for download at eleceng.dit.ie/courtney/MATtrack.zip. PMID:26485569

Construction of multi-functional open modulized Matlab simulation toolbox for imaging ladar system

NASA Astrophysics Data System (ADS)

Wu, Long; Zhao, Yuan; Tang, Meng; He, Jiang; Zhang, Yong

2011-06-01

Ladar system simulation is to simulate the ladar models using computer simulation technology in order to predict the performance of the ladar system. This paper presents the developments of laser imaging radar simulation for domestic and overseas studies and the studies of computer simulation on ladar system with different application requests. The LadarSim and FOI-LadarSIM simulation facilities of Utah State University and Swedish Defence Research Agency are introduced in details. This paper presents the low level of simulation scale, un-unified design and applications of domestic researches in imaging ladar system simulation, which are mostly to achieve simple function simulation based on ranging equations for ladar systems. Design of laser imaging radar simulation with open and modularized structure is proposed to design unified modules for ladar system, laser emitter, atmosphere models, target models, signal receiver, parameters setting and system controller. Unified Matlab toolbox and standard control modules have been built with regulated input and output of the functions, and the communication protocols between hardware modules. A simulation based on ICCD gain-modulated imaging ladar system for a space shuttle is made based on the toolbox. The simulation result shows that the models and parameter settings of the Matlab toolbox are able to simulate the actual detection process precisely. The unified control module and pre-defined parameter settings simplify the simulation of imaging ladar detection. Its open structures enable the toolbox to be modified for specialized requests. The modulization gives simulations flexibility.

3CCD image segmentation and edge detection based on MATLAB

NASA Astrophysics Data System (ADS)

He, Yong; Pan, Jiazhi; Zhang, Yun

2006-09-01

This research aimed to identify weeds from crops in early stage in the field operation by using image-processing technology. As 3CCD images offer greater binary value difference between weed and crop section than ordinary digital images taken by common cameras. It has 3 channels (green, red, ifred) which takes a snap-photo of the same area, and the three images can be composed into one image, which facilitates the segmentation of different areas. By the application of image-processing toolkit on MATLAB, the different areas in the image can be segmented clearly. As edge detection technique is the first and very important step in image processing, The different result of different processing method was compared. Especially, by using the wavelet packet transform toolkit on MATLAB, An image was preprocessed and then the edge was extracted, and getting more clearly cut image of edge. The segmentation methods include operations as erosion, dilation and other algorithms to preprocess the images. It is of great importance to segment different areas in digital images in field real time, so as to be applied in precision farming, to saving energy and herbicide and many other materials. At present time Large scale software as MATLAB on PC was used, but the computation can be reduced and integrated into a small embed system, which means that the application of this technique in agricultural engineering is feasible and of great economical value.

Nearly Interactive Parabolized Navier-Stokes Solver for High Speed Forebody and Inlet Flows

NASA Technical Reports Server (NTRS)

Benson, Thomas J.; Liou, May-Fun; Jones, William H.; Trefny, Charles J.

2009-01-01

A system of computer programs is being developed for the preliminary design of high speed inlets and forebodies. The system comprises four functions: geometry definition, flow grid generation, flow solver, and graphics post-processor. The system runs on a dedicated personal computer using the Windows operating system and is controlled by graphical user interfaces written in MATLAB (The Mathworks, Inc.). The flow solver uses the Parabolized Navier-Stokes equations to compute millions of mesh points in several minutes. Sample two-dimensional and three-dimensional calculations are demonstrated in the paper.

Time series analysis of cholera in Matlab, Bangladesh, during 1988-2001.

PubMed

Ali, Mohammad; Kim, Deok Ryun; Yunus, Mohammad; Emch, Michael

2013-03-01

The study examined the impact of in-situ climatic and marine environmental variability on cholera incidence in an endemic area of Bangladesh and developed a forecasting model for understanding the magnitude of incidence. Diarrhoea surveillance data collected between 1988 and 2001 were obtained from a field research site in Matlab, Bangladesh. Cholera cases were defined as Vibrio cholerae O1 isolated from faecal specimens of patients who sought care at treatment centres serving the Matlab population. Cholera incidence for 168 months was correlated with remotely-sensed sea-surface temperature (SST) and in-situ environmental data, including rainfall and ambient temperature. A seasonal autoregressive integrated moving average (SARIMA) model was used for determining the impact of climatic and environmental variability on cholera incidence and evaluating the ability of the model to forecast the magnitude of cholera. There were 4,157 cholera cases during the study period, with an average of 1.4 cases per 1,000 people. Since monthly cholera cases varied significantly by month, it was necessary to stabilize the variance of cholera incidence by computing the natural logarithm to conduct the analysis. The SARIMA model shows temporal clustering of cholera at one- and 12-month lags. There was a 6% increase in cholera incidence with a minimum temperature increase of one degree celsius in the current month. For increase of SST by one degree celsius, there was a 25% increase in the cholera incidence at currrent month and 18% increase in the cholera incidence at two months. Rainfall did not influenc to cause variation in cholera incidence during the study period. The model forecast the fluctuation of cholera incidence in Matlab reasonably well (Root mean square error, RMSE: 0.108). Thus, the ambient and sea-surface temperature-based model could be used in forecasting cholera outbreaks in Matlab.

Analysis of Gravitational Signals from Core-Collapse Supernovae (CCSNe) using MatLab

NASA Astrophysics Data System (ADS)

Frere, Noah; Mezzacappa, Anthony; Yakunin, Konstantin

2017-01-01

When a massive star runs out of fuel, it collapses under its own weight and rebounds in a powerful supernova explosion, sending, among other things, ripples through space-time, known as gravitational waves (GWs). GWs can be detected by earth-based observatories, such as the Laser Interferometer Gravitational-Wave Observatory (LIGO). Observers must compare the data from GW detectors with theoretical waveforms in order to confirm that the detection of a GW signal from a particular source has occurred. GW predictions for core collapse supernovae (CCSNe) rely on computer simulations. The UTK/ORNL astrophysics group has performed such simulations. Here, I analyze the resulting waveforms, using Matlab, to generate their Fourier transforms, short-time Fourier transforms, energy spectra, evolution of frequencies, and frequency maxima. One product will be a Matlab interface for analyzing and comparing GW predictions based on data from future simulations. This interface will make it easier to analyze waveforms and to share the results with the GW astrophysics community. Funding provided by Department of Physics and Astronomy, University of Tennessee, Knoxville, TN 37996-1200, USA.

Strategies for Sharing Seismic Data Among Multiple Computer Platforms

NASA Astrophysics Data System (ADS)

Baker, L. M.; Fletcher, J. B.

2001-12-01

Seismic waveform data is readily available from a variety of sources, but it often comes in a distinct, instrument-specific data format. For example, data may be from portable seismographs, such as those made by Refraction Technology or Kinemetrics, from permanent seismograph arrays, such as the USGS Parkfield Dense Array, from public data centers, such as the IRIS Data Center, or from personal communication with other researchers through e-mail or ftp. A computer must be selected to import the data - usually whichever is the most suitable for reading the originating format. However, the computer best suited for a specific analysis may not be the same. When copies of the data are then made for analysis, a proliferation of copies of the same data results, in possibly incompatible, computer-specific formats. In addition, if an error is detected and corrected in one copy, or some other change is made, all the other copies must be updated to preserve their validity. Keeping track of what data is available, where it is located, and which copy is authoritative requires an effort that is easy to neglect. We solve this problem by importing waveform data to a shared network file server that is accessible to all our computers on our campus LAN. We use a Network Appliance file server running Sun's Network File System (NFS) software. Using an NFS client software package on each analysis computer, waveform data can then be read by our MatLab or Fortran applications without first copying the data. Since there is a single copy of the waveform data in a single location, the NFS file system hierarchy provides an implicit complete waveform data catalog and the single copy is inherently authoritative. Another part of our solution is to convert the original data into a blocked-binary format (known historically as USGS DR100 or VFBB format) that is interpreted by MatLab or Fortran library routines available on each computer so that the idiosyncrasies of each machine are not visible to the user. Commercial software packages, such as MatLab, also have the ability to share data in their own formats across multiple computer platforms. Our Fortran applications can create plot files in Adobe PostScript, Illustrator, and Portable Document Format (PDF) formats. Vendor support for reading these files is readily available on multiple computer platforms. We will illustrate by example our strategies for sharing seismic data among our multiple computer platforms, and we will discuss our positive and negative experiences. We will include our solutions for handling the different byte ordering, floating-point formats, and text file ``end-of-line'' conventions on the various computer platforms we use (6 different operating systems on 5 processor architectures).

An Elementary Algorithm to Evaluate Trigonometric Functions to High Precision

ERIC Educational Resources Information Center

Johansson, B. Tomas

2018-01-01

Evaluation of the cosine function is done via a simple Cordic-like algorithm, together with a package for handling arbitrary-precision arithmetic in the computer program Matlab. Approximations to the cosine function having hundreds of correct decimals are presented with a discussion around errors and implementation.

Eric Kozubal | NREL

Science.gov Websites

researches new methods and technologies for energy-efficient air conditioning systems. He has tested more -6155 Eric joined NREL in 2002 and is a member of the Commercial Buildings Research Group. Eric recommendations. He uses tools such as CAD, Matlab, Engineer Equation Solver, Excel, and statistical software to

Design optimization for permanent magnet machine with efficient slot per pole ratio

NASA Astrophysics Data System (ADS)

Potnuru, Upendra Kumar; Rao, P. Mallikarjuna

2018-04-01

This paper presents a methodology for the enhancement of a Brush Less Direct Current motor (BLDC) with 6Poles and 8slots. In particular; it is focused on amulti-objective optimization using a Genetic Algorithmand Grey Wolf Optimization developed in MATLAB. The optimization aims to maximize the maximum output power value and minimize the total losses of a motor. This paper presents an application of the MATLAB optimization algorithms to brushless DC (BLDC) motor design, with 7 design parameters chosen to be free. The optimal design parameters of the motor derived by GA are compared with those obtained by Grey Wolf Optimization technique. A comparative report on the specified enhancement approaches appearsthat Grey Wolf Optimization technique has a better convergence.

Image Transmission through OFDM System under the Influence of AWGN Channel

NASA Astrophysics Data System (ADS)

Krishna, Dharavathu; Anuradha, M. S., Dr.

2017-08-01

OFDM system is one among the modern techniques which is most abundantly used in next generation wireless communication networks for transmitting many forms of digital data in efficient manner than compared with other existing traditional techniques. In this paper, one such kind of a digital data corresponding to a two dimensional (2D) gray-scale image is used to evaluate the functionality and overall performance of an OFDM system under the influence of modeled AWGN channel in MATLAB simulation environment. Within the OFDM system, different configurations of notable modulation techniques such as M-PSK and M-QAM are considered for evaluation of the system and necessary valid conclusions are made from the comparison of several observed MATLAB simulation results.

Teaching Computational Thinking: Deciding to Take Small Steps in a Curriculum

NASA Astrophysics Data System (ADS)

Madoff, R. D.; Putkonen, J.

2016-12-01

While computational thinking and reasoning are not necessarily the same as computer programming, programs such as MATLAB can provide the medium through which the logical and computational thinking at the foundation of science can be taught, learned, and experienced. And while math and computer anxiety are often discussed as critical obstacles to students' progress in their geoscience curriculum, it is here suggested that an unfamiliarity with the computational and logical reasoning is what poses a first stumbling block, in addition to the hurdle of expending the effort to learn how to translate a computational problem into the appropriate computer syntax in order to achieve the intended results. Because computational thinking is so vital for all fields, there is a need to initiate many and to build support in the curriculum for it. This presentation focuses on elements to bring into the teaching of computational thinking that are intended as additions to learning MATLAB programming as a basic tool. Such elements include: highlighting a key concept, discussing a basic geoscience problem where the concept would show up, having the student draw or outline a sketch of what they think an operation needs to do in order to perform a desired result, and then finding the relevant syntax to work with. This iterative pedagogy simulates what someone with more experience in programming does, so it discloses the thinking process in the black box of a result. Intended as only a very early stage introduction, advanced applications would need to be developed as students go through an academic program. The objective would be to expose and introduce computational thinking to majors and non-majors and to alleviate some of the math and computer anxiety so that students would choose to advance on with programming or modeling, whether it is built into a 4-year curriculum or not.

Design of a high altitude long endurance flying-wing solar-powered unmanned air vehicle

NASA Astrophysics Data System (ADS)

Alsahlani, A. A.; Johnston, L. J.; Atcliffe, P. A.

2017-06-01

The low-Reynolds number environment of high-altitude §ight places severe demands on the aerodynamic design and stability and control of a high altitude, long endurance (HALE) unmanned air vehicle (UAV). The aerodynamic efficiency of a §ying-wing configuration makes it an attractive design option for such an application and is investigated in the present work. The proposed configuration has a high-aspect ratio, swept-wing planform, the wing sweep being necessary to provide an adequate moment arm for outboard longitudinal and lateral control surfaces. A design optimization framework is developed under a MATLAB environment, combining aerodynamic, structural, and stability analysis. Low-order analysis tools are employed to facilitate efficient computations, which is important when there are multiple optimization loops for the various engineering analyses. In particular, a vortex-lattice method is used to compute the wing planform aerodynamics, coupled to a twodimensional (2D) panel method to derive aerofoil sectional characteristics. Integral boundary-layer methods are coupled to the panel method in order to predict §ow separation boundaries during the design iterations. A quasi-analytical method is adapted for application to flyingwing con¦gurations to predict the wing weight and a linear finite-beam element approach is used for structural analysis of the wing-box. Stability is a particular concern in the low-density environment of high-altitude flight for flying-wing aircraft and so provision of adequate directional stability and control power forms part of the optimization process. At present, a modified Genetic Algorithm is used in all of the optimization loops. Each of the low-order engineering analysis tools is validated using higher-order methods to provide con¦dence in the use of these computationally-efficient tools in the present design-optimization framework. This paper includes the results of employing the present optimization tools in the design of a HALE, flying-wing UAV to indicate that this is a viable design configuration option.

Parameter identification of JONSWAP spectrum acquired by airborne LIDAR

NASA Astrophysics Data System (ADS)

Yu, Yang; Pei, Hailong; Xu, Chengzhong

2017-12-01

In this study, we developed the first linear Joint North Sea Wave Project (JONSWAP) spectrum (JS), which involves a transformation from the JS solution to the natural logarithmic scale. This transformation is convenient for defining the least squares function in terms of the scale and shape parameters. We identified these two wind-dependent parameters to better understand the wind effect on surface waves. Due to its efficiency and high-resolution, we employed the airborne Light Detection and Ranging (LIDAR) system for our measurements. Due to the lack of actual data, we simulated ocean waves in the MATLAB environment, which can be easily translated into industrial programming language. We utilized the Longuet-Higgin (LH) random-phase method to generate the time series of wave records and used the fast Fourier transform (FFT) technique to compute the power spectra density. After validating these procedures, we identified the JS parameters by minimizing the mean-square error of the target spectrum to that of the estimated spectrum obtained by FFT. We determined that the estimation error is relative to the amount of available wave record data. Finally, we found the inverse computation of wind factors (wind speed and wind fetch length) to be robust and sufficiently precise for wave forecasting.

Scalable splitting algorithms for big-data interferometric imaging in the SKA era

NASA Astrophysics Data System (ADS)

Onose, Alexandru; Carrillo, Rafael E.; Repetti, Audrey; McEwen, Jason D.; Thiran, Jean-Philippe; Pesquet, Jean-Christophe; Wiaux, Yves

2016-11-01

In the context of next-generation radio telescopes, like the Square Kilometre Array (SKA), the efficient processing of large-scale data sets is extremely important. Convex optimization tasks under the compressive sensing framework have recently emerged and provide both enhanced image reconstruction quality and scalability to increasingly larger data sets. We focus herein mainly on scalability and propose two new convex optimization algorithmic structures able to solve the convex optimization tasks arising in radio-interferometric imaging. They rely on proximal splitting and forward-backward iterations and can be seen, by analogy, with the CLEAN major-minor cycle, as running sophisticated CLEAN-like iterations in parallel in multiple data, prior, and image spaces. Both methods support any convex regularization function, in particular, the well-studied ℓ1 priors promoting image sparsity in an adequate domain. Tailored for big-data, they employ parallel and distributed computations to achieve scalability, in terms of memory and computational requirements. One of them also exploits randomization, over data blocks at each iteration, offering further flexibility. We present simulation results showing the feasibility of the proposed methods as well as their advantages compared to state-of-the-art algorithmic solvers. Our MATLAB code is available online on GitHub.

Accurate, rapid identification of dislocation lines in coherent diffractive imaging via a min-max optimization formulation

NASA Astrophysics Data System (ADS)

Ulvestad, A.; Menickelly, M.; Wild, S. M.

2018-01-01

Defects such as dislocations impact materials properties and their response during external stimuli. Imaging these defects in their native operating conditions to establish the structure-function relationship and, ultimately, to improve performance via defect engineering has remained a considerable challenge for both electron-based and x-ray-based imaging techniques. While Bragg coherent x-ray diffractive imaging (BCDI) is successful in many cases, nuances in identifying the dislocations has left manual identification as the preferred method. Derivative-based methods are also used, but they can be inaccurate and are computationally inefficient. Here we demonstrate a derivative-free method that is both more accurate and more computationally efficient than either derivative- or human-based methods for identifying 3D dislocation lines in nanocrystal images produced by BCDI. We formulate the problem as a min-max optimization problem and show exceptional accuracy for experimental images. We demonstrate a 227x speedup for a typical experimental dataset with higher accuracy over current methods. We discuss the possibility of using this algorithm as part of a sparsity-based phase retrieval process. We also provide MATLAB code for use by other researchers.

Active model-based balancing strategy for self-reconfigurable batteries

NASA Astrophysics Data System (ADS)

Bouchhima, Nejmeddine; Schnierle, Marc; Schulte, Sascha; Birke, Kai Peter

2016-08-01

This paper describes a novel balancing strategy for self-reconfigurable batteries where the discharge and charge rates of each cell can be controlled. While much effort has been focused on improving the hardware architecture of self-reconfigurable batteries, energy equalization algorithms have not been systematically optimized in terms of maximizing the efficiency of the balancing system. Our approach includes aspects of such optimization theory. We develop a balancing strategy for optimal control of the discharge rate of battery cells. We first formulate the cell balancing as a nonlinear optimal control problem, which is modeled afterward as a network program. Using dynamic programming techniques and MATLAB's vectorization feature, we solve the optimal control problem by generating the optimal battery operation policy for a given drive cycle. The simulation results show that the proposed strategy efficiently balances the cells over the life of the battery, an obvious advantage that is absent in the other conventional approaches. Our algorithm is shown to be robust when tested against different influencing parameters varying over wide spectrum on different drive cycles. Furthermore, due to the little computation time and the proved low sensitivity to the inaccurate power predictions, our strategy can be integrated in a real-time system.

Indirect adaptive soft computing based wavelet-embedded control paradigms for WT/PV/SOFC in a grid/charging station connected hybrid power system.

PubMed

Mumtaz, Sidra; Khan, Laiq; Ahmed, Saghir; Bader, Rabiah

2017-01-01

This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG). A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV) system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC) is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms.

Indirect adaptive soft computing based wavelet-embedded control paradigms for WT/PV/SOFC in a grid/charging station connected hybrid power system

PubMed Central

Khan, Laiq; Ahmed, Saghir; Bader, Rabiah

2017-01-01

This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG). A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV) system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC) is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms. PMID:28877191

Can I Trust This Software Package? An Exercise in Validation of Computational Results

ERIC Educational Resources Information Center

Shacham, Mordechai; Brauner, Neima; Ashurst, W. Robert; Cutlip, Michael B.

2008-01-01

Mathematical software packages such as Polymath, MATLAB, and Mathcad are currently widely used for engineering problem solving. Applications of several of these packages to typical chemical engineering problems have been demonstrated by Cutlip, et al. The main characteristic of these packages is that they provide a "problem-solving environment…

GLS-Finder: An Automated Data-Mining System for Fast Profiling Glucosinolates and its Application in Brassica Vegetables

USDA-ARS?s Scientific Manuscript database

A rapid computer-aided program for profiling glucosinolates, “GLS-Finder", was developed. GLS-Finder is a Matlab script based expert system that is capable for qualitative and semi-quantitative analysis of glucosinolates in samples using data generated by ultra-high performance liquid chromatograph...

Short Project-Based Learning with MATLAB Applications to Support the Learning of Video-Image Processing

ERIC Educational Resources Information Center

Gil, Pablo

2017-01-01

University courses concerning Computer Vision and Image Processing are generally taught using a traditional methodology that is focused on the teacher rather than on the students. This approach is consequently not effective when teachers seek to attain cognitive objectives involving their students' critical thinking. This manuscript covers the…

Solutions of the epidemic of EIAV infection by HPM

NASA Astrophysics Data System (ADS)

Balamuralitharan, S.; Geethamalini, S.

2018-04-01

In this article, Homotopy Perturbation Method (HPM) is to process of estimate to the arrangements to a model for Equine Infectious Anemia Virus (EIAV) disease. This technique allows a direct scheme for solving the problem. MATLAB is operated to complete the computations. Graphical results are displayed and discussed quantitatively and simplicity of the method.

Enabling On-Demand Database Computing with MIT SuperCloud Database Management System

DTIC Science & Technology

2015-09-15

arc.liv.ac.uk/trac/SGE) provides these services and is independent of programming language (C, Fortran, Java , Matlab, etc) or parallel programming...a MySQL database to store DNS records. The DNS records are controlled via a simple web service interface that allows records to be created

Image Based Synthesis for Airborne Minefield Data

DTIC Science & Technology

2005-12-01

Jia, and C-K. Tang, "Image repairing: robust image synthesis by adaptive ND tensor voting ", Proceedings of the IEEE, Computer Society Conference on...utility is capable to synthesize a single frame data as well as list of frames along a flight path. The application is developed in MATLAB -6.5 using the

Introducing the Boundary Element Method with MATLAB

ERIC Educational Resources Information Center

Ang, Keng-Cheng

2008-01-01

The boundary element method provides an excellent platform for learning and teaching a computational method for solving problems in physical and engineering science. However, it is often left out in many undergraduate courses as its implementation is deemed to be difficult. This is partly due to the perception that coding the method requires…

Writing Parallel Parameter Sweep Applications with pMatlab

DTIC Science & Technology

2011-01-01

formulate this type of problem in a leader-worker paradigm. The SETI @Home project is a well- known leader-worker parallel application [1]. The SETI ...their results back to the SETI @Home servers when they are done computing the job. Because each job is independent, it does not matter if the 415th job

Efficient experimental design for uncertainty reduction in gene regulatory networks.

PubMed

Dehghannasiri, Roozbeh; Yoon, Byung-Jun; Dougherty, Edward R

2015-01-01

An accurate understanding of interactions among genes plays a major role in developing therapeutic intervention methods. Gene regulatory networks often contain a significant amount of uncertainty. The process of prioritizing biological experiments to reduce the uncertainty of gene regulatory networks is called experimental design. Under such a strategy, the experiments with high priority are suggested to be conducted first. The authors have already proposed an optimal experimental design method based upon the objective for modeling gene regulatory networks, such as deriving therapeutic interventions. The experimental design method utilizes the concept of mean objective cost of uncertainty (MOCU). MOCU quantifies the expected increase of cost resulting from uncertainty. The optimal experiment to be conducted first is the one which leads to the minimum expected remaining MOCU subsequent to the experiment. In the process, one must find the optimal intervention for every gene regulatory network compatible with the prior knowledge, which can be prohibitively expensive when the size of the network is large. In this paper, we propose a computationally efficient experimental design method. This method incorporates a network reduction scheme by introducing a novel cost function that takes into account the disruption in the ranking of potential experiments. We then estimate the approximate expected remaining MOCU at a lower computational cost using the reduced networks. Simulation results based on synthetic and real gene regulatory networks show that the proposed approximate method has close performance to that of the optimal method but at lower computational cost. The proposed approximate method also outperforms the random selection policy significantly. A MATLAB software implementing the proposed experimental design method is available at http://gsp.tamu.edu/Publications/supplementary/roozbeh15a/.

Efficient experimental design for uncertainty reduction in gene regulatory networks

PubMed Central

2015-01-01

Background An accurate understanding of interactions among genes plays a major role in developing therapeutic intervention methods. Gene regulatory networks often contain a significant amount of uncertainty. The process of prioritizing biological experiments to reduce the uncertainty of gene regulatory networks is called experimental design. Under such a strategy, the experiments with high priority are suggested to be conducted first. Results The authors have already proposed an optimal experimental design method based upon the objective for modeling gene regulatory networks, such as deriving therapeutic interventions. The experimental design method utilizes the concept of mean objective cost of uncertainty (MOCU). MOCU quantifies the expected increase of cost resulting from uncertainty. The optimal experiment to be conducted first is the one which leads to the minimum expected remaining MOCU subsequent to the experiment. In the process, one must find the optimal intervention for every gene regulatory network compatible with the prior knowledge, which can be prohibitively expensive when the size of the network is large. In this paper, we propose a computationally efficient experimental design method. This method incorporates a network reduction scheme by introducing a novel cost function that takes into account the disruption in the ranking of potential experiments. We then estimate the approximate expected remaining MOCU at a lower computational cost using the reduced networks. Conclusions Simulation results based on synthetic and real gene regulatory networks show that the proposed approximate method has close performance to that of the optimal method but at lower computational cost. The proposed approximate method also outperforms the random selection policy significantly. A MATLAB software implementing the proposed experimental design method is available at http://gsp.tamu.edu/Publications/supplementary/roozbeh15a/. PMID:26423515

On computing special functions in marine engineering

NASA Astrophysics Data System (ADS)

Constantinescu, E.; Bogdan, M.

2015-11-01

Important modeling applications in marine engineering conduct us to a special class of solutions for difficult differential equations with variable coefficients. In order to be able to solve and implement such models (in wave theory, in acoustics, in hydrodynamics, in electromagnetic waves, but also in many other engineering fields), it is necessary to compute so called special functions: Bessel functions, modified Bessel functions, spherical Bessel functions, Hankel functions. The aim of this paper is to develop numerical solutions in Matlab for the above mentioned special functions. Taking into account the main properties for Bessel and modified Bessel functions, we shortly present analytically solutions (where possible) in the form of series. Especially it is studied the behavior of these special functions using Matlab facilities: numerical solutions and plotting. Finally, it will be compared the behavior of the special functions and point out other directions for investigating properties of Bessel and spherical Bessel functions. The asymptotic forms of Bessel functions and modified Bessel functions allow determination of important properties of these functions. The modified Bessel functions tend to look more like decaying and growing exponentials.

Review of Real-Time Simulator and the Steps Involved for Implementation of a Model from MATLAB/SIMULINK to Real-Time

NASA Astrophysics Data System (ADS)

Mikkili, Suresh; Panda, Anup Kumar; Prattipati, Jayanthi

2015-06-01

Nowadays the researchers want to develop their model in real-time environment. Simulation tools have been widely used for the design and improvement of electrical systems since the mid twentieth century. The evolution of simulation tools has progressed in step with the evolution of computing technologies. In recent years, computing technologies have improved dramatically in performance and become widely available at a steadily decreasing cost. Consequently, simulation tools have also seen dramatic performance gains and steady cost decreases. Researchers and engineers now have the access to affordable, high performance simulation tools that were previously too cost prohibitive, except for the largest manufacturers. This work has introduced a specific class of digital simulator known as a real-time simulator by answering the questions "what is real-time simulation", "why is it needed" and "how it works". The latest trend in real-time simulation consists of exporting simulation models to FPGA. In this article, the Steps involved for implementation of a model from MATLAB to REAL-TIME are provided in detail.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-11-01

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

Tool for Statistical Analysis and Display of Landing Sites

NASA Technical Reports Server (NTRS)

Wawrzyniak, Geoffrey; Kennedy, Brian; Knocke, Philip; Michel, John

2006-01-01

MarsLS is a software tool for analyzing statistical dispersion of spacecraft-landing sites and displaying the results of its analyses. Originally intended for the Mars Explorer Rover (MER) mission, MarsLS is also applicable to landing sites on Earth and non-MER sites on Mars. MarsLS is a collection of interdependent MATLAB scripts that utilize the MATLAB graphical-user-interface software environment to display landing-site data (see figure) on calibrated image-maps of the Martian or other terrain. The landing-site data comprise latitude/longitude pairs generated by Monte Carlo runs of other computer programs that simulate entry, descent, and landing. Using these data, MarsLS can compute a landing-site ellipse a standard means of depicting the area within which the spacecraft can be expected to land with a given probability. MarsLS incorporates several features for the user s convenience, including capabilities for drawing lines and ellipses, overlaying kilometer or latitude/longitude grids, drawing and/or specifying lines and/or points, entering notes, defining and/or displaying polygons to indicate hazards or areas of interest, and evaluating hazardous and/or scientifically interesting areas. As part of such an evaluation, MarsLS can compute the probability of landing in a specified polygonal area.

Design and Testing of a Liquid Nitrous Oxide and Ethanol Fueled Rocket Engine

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

Youngblood, Stewart

A small-scale, bi-propellant, liquid fueled rocket engine and supporting test infrastructure were designed and constructed at the Energetic Materials Research and Testing Center (EMRTC). This facility was used to evaluate liquid nitrous oxide and ethanol as potential rocket propellants. Thrust and pressure measurements along with high-speed digital imaging of the rocket exhaust plume were made. This experimental data was used for validation of a computational model developed of the rocket engine tested. The developed computational model was utilized to analyze rocket engine performance across a range of operating pressures, fuel-oxidizer mixture ratios, and outlet nozzle configurations. A comparative study ofmore » the modeling of a liquid rocket engine was performed using NASA CEA and Cantera, an opensource equilibrium code capable of being interfaced with MATLAB. One goal of this modeling was to demonstrate the ability of Cantera to accurately model the basic chemical equilibrium, thermodynamics, and transport properties for varied fuel and oxidizer operating conditions. Once validated for basic equilibrium, an expanded MATLAB code, referencing Cantera, was advanced beyond CEAs capabilities to predict rocket engine performance as a function of supplied propellant flow rate and rocket engine nozzle dimensions. Cantera was found to comparable favorably to CEA for making equilibrium calculations, supporting its use as an alternative to CEA. The developed rocket engine performs as predicted, demonstrating the developedMATLAB rocket engine model was successful in predicting real world rocket engine performance. Finally, nitrous oxide and ethanol were shown to perform well as rocket propellants, with specific impulses experimentally recorded in the range of 250 to 260 seconds.« less

Computer aided design environment for the analysis and design of multi-body flexible structures

NASA Technical Reports Server (NTRS)

Ramakrishnan, Jayant V.; Singh, Ramen P.

1989-01-01

A computer aided design environment consisting of the programs NASTRAN, TREETOPS and MATLAB is presented in this paper. With links for data transfer between these programs, the integrated design of multi-body flexible structures is significantly enhanced. The CAD environment is used to model the Space Shuttle/Pinhole Occulater Facility. Then a controller is designed and evaluated in the nonlinear time history sense. Recent enhancements and ongoing research to add more capabilities are also described.

A Compilation of MATLAB Scripts and Functions for MACGMC Analyses

NASA Technical Reports Server (NTRS)

Murthy, Pappu L. N.; Bednarcyk, Brett A.; Mital, Subodh K.

2017-01-01

The primary aim of the current effort is to provide scripts that automate many of the repetitive pre- and post-processing tasks associated with composite materials analyses using the Micromechanics Analysis Code with the Generalized Method of Cells. This document consists of a compilation of hundreds of scripts that were developed in MATLAB (The Mathworks, Inc., Natick, MA) programming language and consolidated into 16 MATLAB functions. (MACGMC). MACGMC is a composite material and laminate analysis software code developed at NASA Glenn Research Center. The software package has been built around the generalized method of cells (GMC) family of micromechanics theories. The computer code is developed with a user-friendly framework, along with a library of local inelastic, damage, and failure models. Further, application of simulated thermo-mechanical loading, generation of output results, and selection of architectures to represent the composite material have been automated to increase the user friendliness, as well as to make it more robust in terms of input preparation and code execution. Finally, classical lamination theory has been implemented within the software, wherein GMC is used to model the composite material response of each ply. Thus, the full range of GMC composite material capabilities is available for analysis of arbitrary laminate configurations as well. The pre-processing tasks include generation of a multitude of different repeating unit cells (RUCs) for CMCs and PMCs, visualization of RUCs from MACGMC input and output files and generation of the RUC section of a MACGMC input file. The post-processing tasks include visualization of the predicted composite response, such as local stress and strain contours, damage initiation and progression, stress-strain behavior, and fatigue response. In addition to the above, several miscellaneous scripts have been developed that can be used to perform repeated Monte-Carlo simulations to enable probabilistic simulations with minimal manual intervention. This document is formatted to provide MATLAB source files and descriptions of how to utilize them. It is assumed that the user has a basic understanding of how MATLAB scripts work and some MATLAB programming experience.

Multi-GPU three dimensional Stokes solver for simulating glacier flow

NASA Astrophysics Data System (ADS)

Licul, Aleksandar; Herman, Frédéric; Podladchikov, Yuri; Räss, Ludovic; Omlin, Samuel

2016-04-01

Here we present how we have recently developed a three-dimensional Stokes solver on the GPUs and apply it to a glacier flow. We numerically solve the Stokes momentum balance equations together with the incompressibility equation, while also taking into account strong nonlinearities for ice rheology. We have developed a fully three-dimensional numerical MATLAB application based on an iterative finite difference scheme with preconditioning of residuals. Differential equations are discretized on a regular staggered grid. We have ported it to C-CUDA to run it on GPU's in parallel, using MPI. We demonstrate the accuracy and efficiency of our developed model by manufactured analytical solution test for three-dimensional Stokes ice sheet models (Leng et al.,2013) and by comparison with other well-established ice sheet models on diagnostic ISMIP-HOM benchmark experiments (Pattyn et al., 2008). The results show that our developed model is capable to accurately and efficiently solve Stokes system of equations in a variety of different test scenarios, while preserving good parallel efficiency on up to 80 GPU's. For example, in 3D test scenarios with 250000 grid points our solver converges in around 3 minutes for single precision computations and around 10 minutes for double precision computations. We have also optimized the developed code to efficiently run on our newly acquired state-of-the-art GPU cluster octopus. This allows us to solve our problem on more than 20 million grid points, by just increasing the number of GPU used, while keeping the computation time the same. In future work we will apply our solver to real world applications and implement the free surface evolution capabilities. REFERENCES Leng,W.,Ju,L.,Gunzburger,M. & Price,S., 2013. Manufactured solutions and the verification of three-dimensional stokes ice-sheet models. Cryosphere 7,19-29. Pattyn, F., Perichon, L., Aschwanden, A., Breuer, B., de Smedt, B., Gagliardini, O., Gudmundsson,G.H., Hindmarsh, R.C.A., Hubbard, A., Johnson, J.V., Kleiner, T., Konovalov,Y., Martin, C., Payne, A.J., Pollard, D., Price, S., Rckamp, M., Saito, F., Souk, O.,Sugiyama, S. & Zwinger, T., 2008. Benchmark experiments for higher-order and full-stokes ice sheet models (ismiphom). The Cryosphere 2, 95-108.

MOBBED: a computational data infrastructure for handling large collections of event-rich time series datasets in MATLAB

PubMed Central

Cockfield, Jeremy; Su, Kyungmin; Robbins, Kay A.

2013-01-01

Experiments to monitor human brain activity during active behavior record a variety of modalities (e.g., EEG, eye tracking, motion capture, respiration monitoring) and capture a complex environmental context leading to large, event-rich time series datasets. The considerable variability of responses within and among subjects in more realistic behavioral scenarios requires experiments to assess many more subjects over longer periods of time. This explosion of data requires better computational infrastructure to more systematically explore and process these collections. MOBBED is a lightweight, easy-to-use, extensible toolkit that allows users to incorporate a computational database into their normal MATLAB workflow. Although capable of storing quite general types of annotated data, MOBBED is particularly oriented to multichannel time series such as EEG that have event streams overlaid with sensor data. MOBBED directly supports access to individual events, data frames, and time-stamped feature vectors, allowing users to ask questions such as what types of events or features co-occur under various experimental conditions. A database provides several advantages not available to users who process one dataset at a time from the local file system. In addition to archiving primary data in a central place to save space and avoid inconsistencies, such a database allows users to manage, search, and retrieve events across multiple datasets without reading the entire dataset. The database also provides infrastructure for handling more complex event patterns that include environmental and contextual conditions. The database can also be used as a cache for expensive intermediate results that are reused in such activities as cross-validation of machine learning algorithms. MOBBED is implemented over PostgreSQL, a widely used open source database, and is freely available under the GNU general public license at http://visual.cs.utsa.edu/mobbed. Source and issue reports for MOBBED are maintained at http://vislab.github.com/MobbedMatlab/ PMID:24124417

MOBBED: a computational data infrastructure for handling large collections of event-rich time series datasets in MATLAB.

PubMed

Cockfield, Jeremy; Su, Kyungmin; Robbins, Kay A

2013-01-01

Experiments to monitor human brain activity during active behavior record a variety of modalities (e.g., EEG, eye tracking, motion capture, respiration monitoring) and capture a complex environmental context leading to large, event-rich time series datasets. The considerable variability of responses within and among subjects in more realistic behavioral scenarios requires experiments to assess many more subjects over longer periods of time. This explosion of data requires better computational infrastructure to more systematically explore and process these collections. MOBBED is a lightweight, easy-to-use, extensible toolkit that allows users to incorporate a computational database into their normal MATLAB workflow. Although capable of storing quite general types of annotated data, MOBBED is particularly oriented to multichannel time series such as EEG that have event streams overlaid with sensor data. MOBBED directly supports access to individual events, data frames, and time-stamped feature vectors, allowing users to ask questions such as what types of events or features co-occur under various experimental conditions. A database provides several advantages not available to users who process one dataset at a time from the local file system. In addition to archiving primary data in a central place to save space and avoid inconsistencies, such a database allows users to manage, search, and retrieve events across multiple datasets without reading the entire dataset. The database also provides infrastructure for handling more complex event patterns that include environmental and contextual conditions. The database can also be used as a cache for expensive intermediate results that are reused in such activities as cross-validation of machine learning algorithms. MOBBED is implemented over PostgreSQL, a widely used open source database, and is freely available under the GNU general public license at http://visual.cs.utsa.edu/mobbed. Source and issue reports for MOBBED are maintained at http://vislab.github.com/MobbedMatlab/

Optical cell tracking analysis using a straight-forward approach to minimize processing time for high frame rate data

NASA Astrophysics Data System (ADS)

Seeto, Wen Jun; Lipke, Elizabeth Ann

2016-03-01

Tracking of rolling cells via in vitro experiment is now commonly performed using customized computer programs. In most cases, two critical challenges continue to limit analysis of cell rolling data: long computation times due to the complexity of tracking algorithms and difficulty in accurately correlating a given cell with itself from one frame to the next, which is typically due to errors caused by cells that either come close in proximity to each other or come in contact with each other. In this paper, we have developed a sophisticated, yet simple and highly effective, rolling cell tracking system to address these two critical problems. This optical cell tracking analysis (OCTA) system first employs ImageJ for cell identification in each frame of a cell rolling video. A custom MATLAB code was written to use the geometric and positional information of all cells as the primary parameters for matching each individual cell with itself between consecutive frames and to avoid errors when tracking cells that come within close proximity to one another. Once the cells are matched, rolling velocity can be obtained for further analysis. The use of ImageJ for cell identification eliminates the need for high level MATLAB image processing knowledge. As a result, only fundamental MATLAB syntax is necessary for cell matching. OCTA has been implemented in the tracking of endothelial colony forming cell (ECFC) rolling under shear. The processing time needed to obtain tracked cell data from a 2 min ECFC rolling video recorded at 70 frames per second with a total of over 8000 frames is less than 6 min using a computer with an Intel® Core™ i7 CPU 2.80 GHz (8 CPUs). This cell tracking system benefits cell rolling analysis by substantially reducing the time required for post-acquisition data processing of high frame rate video recordings and preventing tracking errors when individual cells come in close proximity to one another.

Theoretical analysis of a novel ultrasound generator on an optical fiber tip

NASA Astrophysics Data System (ADS)

Wu, Nan; Wang, Wenhui; Tian, Ye; Guthy, Charles; Wang, Xingwei

2010-04-01

A novel ultrasound generator consisting of a single mode optical fiber with a layer of gold nanoparticles on its tip has been designed. The generator utilizes the optical and photo-acoustic properties of gold nanoparticles. When heated by laser pulses, a thin absorption layer made up of these nanoparticles at the cleaved surface of a single mode fiber generates a mechanical shock wave caused by thermal expansion. Mie's theory was applied in a MATLAB simulation to determine the relationship between the absorption efficiency and the optical resonance wavelengths of a layer of gold nanospheres. Results showed that the absorption efficiency and related resonance wavelengths of gold nanospheres varied based on the size of the gold nanosphere particles. In order to obtain the bandwidths associated with ultrasound, another MATLAB simulation was run to study the relationship between the power of the laser being used, the size of the gold nanosphere, and the energy decay time. The results of this and the previous simulation showed that the energy decay time is picoseconds in length.

An efficient Matlab script to calculate heterogeneous anisotropically elastic wave propagation in three dimensions

USGS Publications Warehouse

Boyd, O.S.

2006-01-01

We have created a second-order finite-difference solution to the anisotropic elastic wave equation in three dimensions and implemented the solution as an efficient Matlab script. This program allows the user to generate synthetic seismograms for three-dimensional anisotropic earth structure. The code was written for teleseismic wave propagation in the 1-0.1 Hz frequency range but is of general utility and can be used at all scales of space and time. This program was created to help distinguish among various types of lithospheric structure given the uneven distribution of sources and receivers commonly utilized in passive source seismology. Several successful implementations have resulted in a better appreciation for subduction zone structure, the fate of a transform fault with depth, lithospheric delamination, and the effects of wavefield focusing and defocusing on attenuation. Companion scripts are provided which help the user prepare input to the finite-difference solution. Boundary conditions including specification of the initial wavefield, absorption and two types of reflection are available. ?? 2005 Elsevier Ltd. All rights reserved.

Developing Matlab scripts for image analysis and quality assessment

NASA Astrophysics Data System (ADS)

Vaiopoulos, A. D.

2011-11-01

Image processing is a very helpful tool in many fields of modern sciences that involve digital imaging examination and interpretation. Processed images however, often need to be correlated with the original image, in order to ensure that the resulting image fulfills its purpose. Aside from the visual examination, which is mandatory, image quality indices (such as correlation coefficient, entropy and others) are very useful, when deciding which processed image is the most satisfactory. For this reason, a single program (script) was written in Matlab language, which automatically calculates eight indices by utilizing eight respective functions (independent function scripts). The program was tested in both fused hyperspectral (Hyperion-ALI) and multispectral (ALI, Landsat) imagery and proved to be efficient. Indices were found to be in agreement with visual examination and statistical observations.

An Improved Perturb and Observe Algorithm for Photovoltaic Motion Carriers

NASA Astrophysics Data System (ADS)

Peng, Lele; Xu, Wei; Li, Liming; Zheng, Shubin

2018-03-01

An improved perturbation and observation algorithm for photovoltaic motion carriers is proposed in this paper. The model of the proposed algorithm is given by using Lambert W function and tangent error method. Moreover, by using matlab and experiment of photovoltaic system, the tracking performance of the proposed algorithm is tested. And the results demonstrate that the improved algorithm has fast tracking speed and high efficiency. Furthermore, the energy conversion efficiency by the improved method has increased by nearly 8.2%.

Design of Ablation Test Device for Brick Coating of Gun

NASA Astrophysics Data System (ADS)

shirui, YAO; yongcai, CHEN; fei, WANG; jianxin, ZHAO

2018-03-01

As a result of the live ammunition test conditions, the barrel resistance of the barrel coating has high cost, time consuming, low efficiency and high test site requirements. This article designed a simple, convenient and efficient test device. Through the internal trajectory calculation by Matlab, the ablation environment produced by the ablation test device has achieved the expected effect, which is consistent with the working condition of the tube in the launching state, which can better reflect the ablation of the coating.

Lightweight robotic mobility: template-based modeling for dynamics and controls using ADAMS/car and MATLAB

NASA Astrophysics Data System (ADS)

Adamczyk, Peter G.; Gorsich, David J.; Hudas, Greg R.; Overholt, James

2003-09-01

The U.S. Army is seeking to develop autonomous off-road mobile robots to perform tasks in the field such as supply delivery and reconnaissance in dangerous territory. A key problem to be solved with these robots is off-road mobility, to ensure that the robots can accomplish their tasks without loss or damage. We have developed a computer model of one such concept robot, the small-scale "T-1" omnidirectional vehicle (ODV), to study the effects of different control strategies on the robot's mobility in off-road settings. We built the dynamic model in ADAMS/Car and the control system in Matlab/Simulink. This paper presents the template-based method used to construct the ADAMS model of the T-1 ODV. It discusses the strengths and weaknesses of ADAMS/Car software in such an application, and describes the benefits and challenges of the approach as a whole. The paper also addresses effective linking of ADAMS/Car and Matlab for complete control system development. Finally, this paper includes a section describing the extension of the T-1 templates to other similar ODV concepts for rapid development.

A MATLAB-based graphical user interface program for computing functionals of the geopotential up to ultra-high degrees and orders

NASA Astrophysics Data System (ADS)

Bucha, Blažej; Janák, Juraj

2013-07-01

We present a novel graphical user interface program GrafLab (GRAvity Field LABoratory) for spherical harmonic synthesis (SHS) created in MATLAB®. This program allows to comfortably compute 38 various functionals of the geopotential up to ultra-high degrees and orders of spherical harmonic expansion. For the most difficult part of the SHS, namely the evaluation of the fully normalized associated Legendre functions (fnALFs), we used three different approaches according to required maximum degree: (i) the standard forward column method (up to maximum degree 1800, in some cases up to degree 2190); (ii) the modified forward column method combined with Horner's scheme (up to maximum degree 2700); (iii) the extended-range arithmetic (up to an arbitrary maximum degree). For the maximum degree 2190, the SHS with fnALFs evaluated using the extended-range arithmetic approach takes only approximately 2-3 times longer than its standard arithmetic counterpart, i.e. the standard forward column method. In the GrafLab, the functionals of the geopotential can be evaluated on a regular grid or point-wise, while the input coordinates can either be read from a data file or entered manually. For the computation on a regular grid we decided to apply the lumped coefficients approach due to significant time-efficiency of this method. Furthermore, if a full variance-covariances matrix of spherical harmonic coefficients is available, it is possible to compute the commission errors of the functionals. When computing on a regular grid, the output functionals or their commission errors may be depicted on a map using automatically selected cartographic projection.

A general formula for computing maximum proportion correct scores in various psychophysical paradigms with arbitrary probability distributions of stimulus observations.

PubMed

Dai, Huanping; Micheyl, Christophe

2015-05-01

Proportion correct (Pc) is a fundamental measure of task performance in psychophysics. The maximum Pc score that can be achieved by an optimal (maximum-likelihood) observer in a given task is of both theoretical and practical importance, because it sets an upper limit on human performance. Within the framework of signal detection theory, analytical solutions for computing the maximum Pc score have been established for several common experimental paradigms under the assumption of Gaussian additive internal noise. However, as the scope of applications of psychophysical signal detection theory expands, the need is growing for psychophysicists to compute maximum Pc scores for situations involving non-Gaussian (internal or stimulus-induced) noise. In this article, we provide a general formula for computing the maximum Pc in various psychophysical experimental paradigms for arbitrary probability distributions of sensory activity. Moreover, easy-to-use MATLAB code implementing the formula is provided. Practical applications of the formula are illustrated, and its accuracy is evaluated, for two paradigms and two types of probability distributions (uniform and Gaussian). The results demonstrate that Pc scores computed using the formula remain accurate even for continuous probability distributions, as long as the conversion from continuous probability density functions to discrete probability mass functions is supported by a sufficiently high sampling resolution. We hope that the exposition in this article, and the freely available MATLAB code, facilitates calculations of maximum performance for a wider range of experimental situations, as well as explorations of the impact of different assumptions concerning internal-noise distributions on maximum performance in psychophysical experiments.

MultiElec: A MATLAB Based Application for MEA Data Analysis.

PubMed

Georgiadis, Vassilis; Stephanou, Anastasis; Townsend, Paul A; Jackson, Thomas R

2015-01-01

We present MultiElec, an open source MATLAB based application for data analysis of microelectrode array (MEA) recordings. MultiElec displays an extremely user-friendly graphic user interface (GUI) that allows the simultaneous display and analysis of voltage traces for 60 electrodes and includes functions for activation-time determination, the production of activation-time heat maps with activation time and isoline display. Furthermore, local conduction velocities are semi-automatically calculated along with their corresponding vector plots. MultiElec allows ad hoc signal suppression, enabling the user to easily and efficiently handle signal artefacts and for incomplete data sets to be analysed. Voltage traces and heat maps can be simply exported for figure production and presentation. In addition, our platform is able to produce 3D videos of signal progression over all 60 electrodes. Functions are controlled entirely by a single GUI with no need for command line input or any understanding of MATLAB code. MultiElec is open source under the terms of the GNU General Public License as published by the Free Software Foundation, version 3. Both the program and source code are available to download from http://www.cancer.manchester.ac.uk/MultiElec/.

On algorithmic optimization of histogramming functions for GEM systems

NASA Astrophysics Data System (ADS)

Krawczyk, Rafał D.; Czarski, Tomasz; Kolasinski, Piotr; Poźniak, Krzysztof T.; Linczuk, Maciej; Byszuk, Adrian; Chernyshova, Maryna; Juszczyk, Bartlomiej; Kasprowicz, Grzegorz; Wojenski, Andrzej; Zabolotny, Wojciech

2015-09-01

This article concerns optimization methods for data analysis for the X-ray GEM detector system. The offline analysis of collected samples was optimized for MATLAB computations. Compiled functions in C language were used with MEX library. Significant speedup was received for both ordering-preprocessing and for histogramming of samples. Utilized techniques with obtained results are presented.

Airborne Wireless Communication Modeling and Analysis with MATLAB

DTIC Science & Technology

2014-03-27

research develops a physical layer model that combines antenna modeling using computational electromagnetics and the two-ray propagation model to...predict the received signal strength. The antenna is modeled with triangular patches and analyzed by extending the antenna modeling algorithm by Sergey...7  2.7. Propagation Modeling : Statistical Models ............................................................8  2.8. Antenna Modeling

Numerical Problems and Agent-Based Models for a Mass Transfer Course

ERIC Educational Resources Information Center

Murthi, Manohar; Shea, Lonnie D.; Snurr, Randall Q.

2009-01-01

Problems requiring numerical solutions of differential equations or the use of agent-based modeling are presented for use in a course on mass transfer. These problems were solved using the popular technical computing language MATLABTM. Students were introduced to MATLAB via a problem with an analytical solution. A more complex problem to which no…

Applications of the Peng-Robinson Equation of State Using MATLAB[R

ERIC Educational Resources Information Center

Nasri, Zakia; Binous, Housam

2009-01-01

A single equation of state (EOS) such as the Peng-Robinson (PR) EOS can accurately describe both the liquid and vapor phase. We present several applications of this equation of state, including estimation of pure component properties and computation of the vapor-liquid equilibrium (VLE) diagram for binary mixtures. We perform high-pressure…

The Relationship between Gender and Students' Attitude and Experience of Using a Computer Algebra System

ERIC Educational Resources Information Center

Ocak, Mehmet

2008-01-01

This correlational study examined the relationship between gender and the students' attitude and prior knowledge of using one of the mathematical software programs (MATLAB). Participants were selected from one community college, one state university and one private college. Students were volunteers from three Calculus I classrooms (one class from…

A security mechanism based on evolutionary game in fog computing.

PubMed

Sun, Yan; Lin, Fuhong; Zhang, Nan

2018-02-01

Fog computing is a distributed computing paradigm at the edge of the network and requires cooperation of users and sharing of resources. When users in fog computing open their resources, their devices are easily intercepted and attacked because they are accessed through wireless network and present an extensive geographical distribution. In this study, a credible third party was introduced to supervise the behavior of users and protect the security of user cooperation. A fog computing security mechanism based on human nervous system is proposed, and the strategy for a stable system evolution is calculated. The MATLAB simulation results show that the proposed mechanism can reduce the number of attack behaviors effectively and stimulate users to cooperate in application tasks positively.

MO-FG-CAMPUS-TeP2-01: A Graph Form ADMM Algorithm for Constrained Quadratic Radiation Treatment Planning

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

Liu, X; Belcher, AH; Wiersma, R

Purpose: In radiation therapy optimization the constraints can be either hard constraints which must be satisfied or soft constraints which are included but do not need to be satisfied exactly. Currently the voxel dose constraints are viewed as soft constraints and included as a part of the objective function and approximated as an unconstrained problem. However in some treatment planning cases the constraints should be specified as hard constraints and solved by constrained optimization. The goal of this work is to present a computation efficiency graph form alternating direction method of multipliers (ADMM) algorithm for constrained quadratic treatment planning optimizationmore » and compare it with several commonly used algorithms/toolbox. Method: ADMM can be viewed as an attempt to blend the benefits of dual decomposition and augmented Lagrangian methods for constrained optimization. Various proximal operators were first constructed as applicable to quadratic IMRT constrained optimization and the problem was formulated in a graph form of ADMM. A pre-iteration operation for the projection of a point to a graph was also proposed to further accelerate the computation. Result: The graph form ADMM algorithm was tested by the Common Optimization for Radiation Therapy (CORT) dataset including TG119, prostate, liver, and head & neck cases. Both unconstrained and constrained optimization problems were formulated for comparison purposes. All optimizations were solved by LBFGS, IPOPT, Matlab built-in toolbox, CVX (implementing SeDuMi) and Mosek solvers. For unconstrained optimization, it was found that LBFGS performs the best, and it was 3–5 times faster than graph form ADMM. However, for constrained optimization, graph form ADMM was 8 – 100 times faster than the other solvers. Conclusion: A graph form ADMM can be applied to constrained quadratic IMRT optimization. It is more computationally efficient than several other commercial and noncommercial optimizers and it also used significantly less computer memory.« less

SU-F-J-174: A Series of Computational Human Phantoms in DICOM-RT Format for Normal Tissue Dose Reconstruction in Epidemiological Studies

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

Pyakuryal, A; Moroz, B; Lee, C

2016-06-15

Purpose: Epidemiological studies of second cancer risk in radiotherapy patients often require individualized dose estimates of normal tissues. Prior to 3D conformal radiation therapy planning, patient anatomy information was mostly limited to 2D radiological images or not even available. Generic patient CT images are often used in commercial radiotherapy treatment planning system (TPS) to reconstruct normal tissue doses. The objective of the current work was to develop a series of reference size computational human phantoms in DICOM-RT format for direct use in dose reconstruction in TPS. Methods: Contours of 93 organs and tissues were extracted from a series of pediatricmore » and adult hybrid computational human phantoms (newborn, 1-, 5-, 10-, 15-year-old, and adult males and females) using Rhinoceros software. A MATLAB script was created to convert the contours into the DICOM-RT structure format. The simulated CT images with the resolution of 1×1×3 mm3 were also generated from the binary phantom format and coupled with the DICOM-structure files. Accurate volumes of the organs were drawn in the format using precise delineation of the contours in converted format. Due to complex geometry of organs, higher resolution (1×1×1 mm3) was found to be more efficient in the conversion of newborn and 1-year-old phantoms. Results: Contour sets were efficiently converted into DICOM-RT structures in relatively short time (about 30 minutes for each phantom). A good agreement was observed in the volumes between the original phantoms and the converted contours for large organs (NRMSD<1.0%) and small organs (NRMSD<7.7%). Conclusion: A comprehensive series of computational human phantoms in DICOM-RT format was created to support epidemiological studies of second cancer risks in radiotherapy patients. We confirmed the DICOM-RT phantoms were successfully imported into the TPS programs of major vendors.« less

Selection of regularization parameter in total variation image restoration.

PubMed

Liao, Haiyong; Li, Fang; Ng, Michael K

2009-11-01

We consider and study total variation (TV) image restoration. In the literature there are several regularization parameter selection methods for Tikhonov regularization problems (e.g., the discrepancy principle and the generalized cross-validation method). However, to our knowledge, these selection methods have not been applied to TV regularization problems. The main aim of this paper is to develop a fast TV image restoration method with an automatic selection of the regularization parameter scheme to restore blurred and noisy images. The method exploits the generalized cross-validation (GCV) technique to determine inexpensively how much regularization to use in each restoration step. By updating the regularization parameter in each iteration, the restored image can be obtained. Our experimental results for testing different kinds of noise show that the visual quality and SNRs of images restored by the proposed method is promising. We also demonstrate that the method is efficient, as it can restore images of size 256 x 256 in approximately 20 s in the MATLAB computing environment.

Time Series Analysis of Cholera in Matlab, Bangladesh, during 1988-2001

PubMed Central

Kim, Deok Ryun; Yunus, Mohammad; Emch, Michael

2013-01-01

The study examined the impact of in-situ climatic and marine environmental variability on cholera incidence in an endemic area of Bangladesh and developed a forecasting model for understanding the magnitude of incidence. Diarrhoea surveillance data collected between 1988 and 2001were obtained from a field research site in Matlab, Bangladesh. Cholera cases were defined as Vibrio cholerae O1 isolated from faecal specimens of patients who sought care at treatment centres serving the Matlab population. Cholera incidence for 168 months was correlated with remotely-sensed sea-surface temperature (SST) and in-situ environmental data, including rainfall and ambient temperature. A seasonal autoregressive integrated moving average (SARIMA) model was used for determining the impact of climatic and environmental variability on cholera incidence and evaluating the ability of the model to forecast the magnitude of cholera. There were 4,157 cholera cases during the study period, with an average of 1.4 cases per 1,000 people. Since monthly cholera cases varied significantly by month, it was necessary to stabilize the variance of cholera incidence by computing the natural logarithm to conduct the analysis. The SARIMA model shows temporal clustering of cholera at one- and 12-month lags. There was a 6% increase in cholera incidence with a minimum temperature increase of one degree celsius in the current month. For increase of SST by one degree celsius, there was a 25% increase in the cholera incidence at currrent month and 18% increase in the cholera incidence at two months. Rainfall did not influenc to cause variation in cholera incidence during the study period. The model forecast the fluctuation of cholera incidence in Matlab reasonably well (Root mean square error, RMSE: 0.108). Thus, the ambient and sea-surface temperature-based model could be used in forecasting cholera outbreaks in Matlab. PMID:23617200

Sodium 3D COncentration MApping (COMA 3D) using 23Na and proton MRI

NASA Astrophysics Data System (ADS)

Truong, Milton L.; Harrington, Michael G.; Schepkin, Victor D.; Chekmenev, Eduard Y.

2014-10-01

Functional changes of sodium 3D MRI signals were converted into millimolar concentration changes using an open-source fully automated MATLAB toolbox. These concentration changes are visualized via 3D sodium concentration maps, and they are overlaid over conventional 3D proton images to provide high-resolution co-registration for easy correlation of functional changes to anatomical regions. Nearly 5000/h concentration maps were generated on a personal computer (ca. 2012) using 21.1 T 3D sodium MRI brain images of live rats with spatial resolution of 0.8 × 0.8 × 0.8 mm3 and imaging matrices of 60 × 60 × 60. The produced concentration maps allowed for non-invasive quantitative measurement of in vivo sodium concentration in the normal rat brain as a functional response to migraine-like conditions. The presented work can also be applied to sodium-associated changes in migraine, cancer, and other metabolic abnormalities that can be sensed by molecular imaging. The MATLAB toolbox allows for automated image analysis of the 3D images acquired on the Bruker platform and can be extended to other imaging platforms. The resulting images are presented in a form of series of 2D slices in all three dimensions in native MATLAB and PDF formats. The following is provided: (a) MATLAB source code for image processing, (b) the detailed processing procedures, (c) description of the code and all sub-routines, (d) example data sets of initial and processed data. The toolbox can be downloaded at: http://www.vuiis.vanderbilt.edu/ truongm/COMA3D/.

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

NASA Technical Reports Server (NTRS)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

Interactive Supercomputing’s Star-P Platform

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

Edelman, Alan; Husbands, Parry; Leibman, Steve

2006-09-19

The thesis of this extended abstract is simple. High productivity comes from high level infrastructures. To measure this, we introduce a methodology that goes beyond the tradition of timing software in serial and tuned parallel modes. We perform a classroom productivity study involving 29 students who have written a homework exercise in a low level language (MPI message passing) and a high level language (Star-P with MATLAB client). Our conclusions indicate what perhaps should be of little surprise: (1) the high level language is always far easier on the students than the low level language. (2) The early versions ofmore » the high level language perform inadequately compared to the tuned low level language, but later versions substantially catch up. Asymptotically, the analogy must hold that message passing is to high level language parallel programming as assembler is to high level environments such as MATLAB, Mathematica, Maple, or even Python. We follow the Kepner method that correctly realizes that traditional speedup numbers without some discussion of the human cost of reaching these numbers can fail to reflect the true human productivity cost of high performance computing. Traditional data compares low level message passing with serial computation. With the benefit of a high level language system in place, in our case Star-P running with MATLAB client, and with the benefit of a large data pool: 29 students, each running the same code ten times on three evolutions of the same platform, we can methodically demonstrate the productivity gains. To date we are not aware of any high level system as extensive and interoperable as Star-P, nor are we aware of an experiment of this kind performed with this volume of data.« less

SIGNUM: A Matlab, TIN-based landscape evolution model

NASA Astrophysics Data System (ADS)

Refice, A.; Giachetta, E.; Capolongo, D.

2012-08-01

Several numerical landscape evolution models (LEMs) have been developed to date, and many are available as open source codes. Most are written in efficient programming languages such as Fortran or C, but often require additional code efforts to plug in to more user-friendly data analysis and/or visualization tools to ease interpretation and scientific insight. In this paper, we present an effort to port a common core of accepted physical principles governing landscape evolution directly into a high-level language and data analysis environment such as Matlab. SIGNUM (acronym for Simple Integrated Geomorphological Numerical Model) is an independent and self-contained Matlab, TIN-based landscape evolution model, built to simulate topography development at various space and time scales. SIGNUM is presently capable of simulating hillslope processes such as linear and nonlinear diffusion, fluvial incision into bedrock, spatially varying surface uplift which can be used to simulate changes in base level, thrust and faulting, as well as effects of climate changes. Although based on accepted and well-known processes and algorithms in its present version, it is built with a modular structure, which allows to easily modify and upgrade the simulated physical processes to suite virtually any user needs. The code is conceived as an open-source project, and is thus an ideal tool for both research and didactic purposes, thanks to the high-level nature of the Matlab environment and its popularity among the scientific community. In this paper the simulation code is presented together with some simple examples of surface evolution, and guidelines for development of new modules and algorithms are proposed.

Application of Microsoft's ActiveX and DirectX technologies to the visulization of physical system dynamics

NASA Astrophysics Data System (ADS)

Mann, Christopher; Narasimhamurthi, Natarajan

1998-08-01

This paper discusses a specific implementation of a web and complement based simulation systems. The overall simulation container is implemented within a web page viewed with Microsoft's Internet Explorer 4.0 web browser. Microsoft's ActiveX/Distributed Component Object Model object interfaces are used in conjunction with the Microsoft DirectX graphics APIs to provide visualization functionality for the simulation. The MathWorks' Matlab computer aided control system design program is used as an ActiveX automation server to provide the compute engine for the simulations.

Advanced information processing system: Hosting of advanced guidance, navigation and control algorithms on AIPS using ASTER

NASA Technical Reports Server (NTRS)

Brenner, Richard; Lala, Jaynarayan H.; Nagle, Gail A.; Schor, Andrei; Turkovich, John

1994-01-01

This program demonstrated the integration of a number of technologies that can increase the availability and reliability of launch vehicles while lowering costs. Availability is increased with an advanced guidance algorithm that adapts trajectories in real-time. Reliability is increased with fault-tolerant computers and communication protocols. Costs are reduced by automatically generating code and documentation. This program was realized through the cooperative efforts of academia, industry, and government. The NASA-LaRC coordinated the effort, while Draper performed the integration. Georgia Institute of Technology supplied a weak Hamiltonian finite element method for optimal control problems. Martin Marietta used MATLAB to apply this method to a launch vehicle (FENOC). Draper supplied the fault-tolerant computing and software automation technology. The fault-tolerant technology includes sequential and parallel fault-tolerant processors (FTP & FTPP) and authentication protocols (AP) for communication. Fault-tolerant technology was incrementally incorporated. Development culminated with a heterogeneous network of workstations and fault-tolerant computers using AP. Draper's software automation system, ASTER, was used to specify a static guidance system based on FENOC, navigation, flight control (GN&C), models, and the interface to a user interface for mission control. ASTER generated Ada code for GN&C and C code for models. An algebraic transform engine (ATE) was developed to automatically translate MATLAB scripts into ASTER.

Wide-Angle Multistatic Synthetic Aperture Radar: Focused Image Formation and Aliasing Artifact Mitigation

DTIC Science & Technology

2005-07-01

Progress in Applied Computational Electro- magnetics. ACES, Syracuse, NY, 2004. 91. Mahafza, Bassem R. Radar Systems Analysis and Design Using MATLAB...Figure Page 4.5. RCS chamber coordinate system . . . . . . . . . . . . . . . . . 88 4.6. AFIT’s RCS Chamber...4.11. Frequency domain schematic of RCS data collection . . . . . . 98 4.12. Spherical coordinate system for RCS data calibration . . . . . . 102 4.13

A Switching-Mode Power Supply Design Tool to Improve Learning in a Power Electronics Course

ERIC Educational Resources Information Center

Miaja, P. F.; Lamar, D. G.; de Azpeitia, M.; Rodriguez, A.; Rodriguez, M.; Hernando, M. M.

2011-01-01

The static design of ac/dc and dc/dc switching-mode power supplies (SMPS) relies on a simple but repetitive process. Although specific spreadsheets, available in various computer-aided design (CAD) programs, are widely used, they are difficult to use in educational applications. In this paper, a graphic tool programmed in MATLAB is presented,…

Analysis of Power Laws, Shape Collapses, and Neural Complexity: New Techniques and MATLAB Support via the NCC Toolbox

PubMed Central

Marshall, Najja; Timme, Nicholas M.; Bennett, Nicholas; Ripp, Monica; Lautzenhiser, Edward; Beggs, John M.

2016-01-01

Neural systems include interactions that occur across many scales. Two divergent methods for characterizing such interactions have drawn on the physical analysis of critical phenomena and the mathematical study of information. Inferring criticality in neural systems has traditionally rested on fitting power laws to the property distributions of “neural avalanches” (contiguous bursts of activity), but the fractal nature of avalanche shapes has recently emerged as another signature of criticality. On the other hand, neural complexity, an information theoretic measure, has been used to capture the interplay between the functional localization of brain regions and their integration for higher cognitive functions. Unfortunately, treatments of all three methods—power-law fitting, avalanche shape collapse, and neural complexity—have suffered from shortcomings. Empirical data often contain biases that introduce deviations from true power law in the tail and head of the distribution, but deviations in the tail have often been unconsidered; avalanche shape collapse has required manual parameter tuning; and the estimation of neural complexity has relied on small data sets or statistical assumptions for the sake of computational efficiency. In this paper we present technical advancements in the analysis of criticality and complexity in neural systems. We use maximum-likelihood estimation to automatically fit power laws with left and right cutoffs, present the first automated shape collapse algorithm, and describe new techniques to account for large numbers of neural variables and small data sets in the calculation of neural complexity. In order to facilitate future research in criticality and complexity, we have made the software utilized in this analysis freely available online in the MATLAB NCC (Neural Complexity and Criticality) Toolbox. PMID:27445842

Analysis of Power Laws, Shape Collapses, and Neural Complexity: New Techniques and MATLAB Support via the NCC Toolbox.

PubMed

Marshall, Najja; Timme, Nicholas M; Bennett, Nicholas; Ripp, Monica; Lautzenhiser, Edward; Beggs, John M

2016-01-01

Neural systems include interactions that occur across many scales. Two divergent methods for characterizing such interactions have drawn on the physical analysis of critical phenomena and the mathematical study of information. Inferring criticality in neural systems has traditionally rested on fitting power laws to the property distributions of "neural avalanches" (contiguous bursts of activity), but the fractal nature of avalanche shapes has recently emerged as another signature of criticality. On the other hand, neural complexity, an information theoretic measure, has been used to capture the interplay between the functional localization of brain regions and their integration for higher cognitive functions. Unfortunately, treatments of all three methods-power-law fitting, avalanche shape collapse, and neural complexity-have suffered from shortcomings. Empirical data often contain biases that introduce deviations from true power law in the tail and head of the distribution, but deviations in the tail have often been unconsidered; avalanche shape collapse has required manual parameter tuning; and the estimation of neural complexity has relied on small data sets or statistical assumptions for the sake of computational efficiency. In this paper we present technical advancements in the analysis of criticality and complexity in neural systems. We use maximum-likelihood estimation to automatically fit power laws with left and right cutoffs, present the first automated shape collapse algorithm, and describe new techniques to account for large numbers of neural variables and small data sets in the calculation of neural complexity. In order to facilitate future research in criticality and complexity, we have made the software utilized in this analysis freely available online in the MATLAB NCC (Neural Complexity and Criticality) Toolbox.

An Algebra-Based Introductory Computational Neuroscience Course with Lab.

PubMed

Fink, Christian G

2017-01-01

A course in computational neuroscience has been developed at Ohio Wesleyan University which requires no previous experience with calculus or computer programming, and which exposes students to theoretical models of neural information processing and techniques for analyzing neural data. The exploration of theoretical models of neural processes is conducted in the classroom portion of the course, while data analysis techniques are covered in lab. Students learn to program in MATLAB and are offered the opportunity to conclude the course with a final project in which they explore a topic of their choice within computational neuroscience. Results from a questionnaire administered at the beginning and end of the course indicate significant gains in student facility with core concepts in computational neuroscience, as well as with analysis techniques applied to neural data.

Ant Lion Optimization algorithm for kidney exchanges.

PubMed

Hamouda, Eslam; El-Metwally, Sara; Tarek, Mayada

2018-01-01

The kidney exchange programs bring new insights in the field of organ transplantation. They make the previously not allowed surgery of incompatible patient-donor pairs easier to be performed on a large scale. Mathematically, the kidney exchange is an optimization problem for the number of possible exchanges among the incompatible pairs in a given pool. Also, the optimization modeling should consider the expected quality-adjusted life of transplant candidates and the shortage of computational and operational hospital resources. In this article, we introduce a bio-inspired stochastic-based Ant Lion Optimization, ALO, algorithm to the kidney exchange space to maximize the number of feasible cycles and chains among the pool pairs. Ant Lion Optimizer-based program achieves comparable kidney exchange results to the deterministic-based approaches like integer programming. Also, ALO outperforms other stochastic-based methods such as Genetic Algorithm in terms of the efficient usage of computational resources and the quantity of resulting exchanges. Ant Lion Optimization algorithm can be adopted easily for on-line exchanges and the integration of weights for hard-to-match patients, which will improve the future decisions of kidney exchange programs. A reference implementation for ALO algorithm for kidney exchanges is written in MATLAB and is GPL licensed. It is available as free open-source software from: https://github.com/SaraEl-Metwally/ALO_algorithm_for_Kidney_Exchanges.

Mid-frequency Band Dynamics of Large Space Structures

NASA Technical Reports Server (NTRS)

Coppolino, Robert N.; Adams, Douglas S.

2004-01-01

High and low intensity dynamic environments experienced by a spacecraft during launch and on-orbit operations, respectively, induce structural loads and motions, which are difficult to reliably predict. Structural dynamics in low- and mid-frequency bands are sensitive to component interface uncertainty and non-linearity as evidenced in laboratory testing and flight operations. Analytical tools for prediction of linear system response are not necessarily adequate for reliable prediction of mid-frequency band dynamics and analysis of measured laboratory and flight data. A new MATLAB toolbox, designed to address the key challenges of mid-frequency band dynamics, is introduced in this paper. Finite-element models of major subassemblies are defined following rational frequency-wavelength guidelines. For computational efficiency, these subassemblies are described as linear, component mode models. The complete structural system model is composed of component mode subassemblies and linear or non-linear joint descriptions. Computation and display of structural dynamic responses are accomplished employing well-established, stable numerical methods, modern signal processing procedures and descriptive graphical tools. Parametric sensitivity and Monte-Carlo based system identification tools are used to reconcile models with experimental data and investigate the effects of uncertainties. Models and dynamic responses are exported for employment in applications, such as detailed structural integrity and mechanical-optical-control performance analyses.

Computing Fourier integral operators with caustics

NASA Astrophysics Data System (ADS)

Caday, Peter

2016-12-01

Fourier integral operators (FIOs) have widespread applications in imaging, inverse problems, and PDEs. An implementation of a generic algorithm for computing FIOs associated with canonical graphs is presented, based on a recent paper of de Hoop et al. Given the canonical transformation and principal symbol of the operator, a preprocessing step reduces application of an FIO approximately to multiplications, pushforwards and forward and inverse discrete Fourier transforms, which can be computed in O({N}n+(n-1)/2{log}N) time for an n-dimensional FIO. The same preprocessed data also allows computation of the inverse and transpose of the FIO, with identical runtime. Examples demonstrate the algorithm’s output, and easily extendible MATLAB/C++ source code is available from the author.

Analyzation of photopolymer materials shrunken influence for thick hologram gratings

NASA Astrophysics Data System (ADS)

Li, Zhenzhen; Xiao, Xue; Chen, Wei; Kang, Guoguo; Huang, Yong; Tan, Xiaodi

2016-09-01

The photopolymer materials are good media to record thick hologram gratings, because photopolymer materials have high resolution, low cost, simple process technology and so on. According to coupled wave theory for thick hologram gratings, we know that the same object beam can be reconstructed if the same reference beam is used to retrieve a thick hologram grating. However, the shrinkage always occurs in the photopolymer materials because of environment temperature, humidity, vibration etc. For instance, the same object beam cannot be reconstructed even the same reference beam to be used. In this paper, we will analysis the shrinkage influence of photopolymer materials for thick hologram gratings. We divide the photopolymer materials into several geometry layers, and analysis the reconstructed characteristics separately basing on coupled wave theory of Kogelnik. Through gradually continuous changing the angle between gratings and the border (we call it slant angle), we can build the geometry model of gratings bending caused by shrinkage of materials. We calculate wave complex amplitude diffracted from every layer, and superpose them to compute the total diffraction efficiency. We simulate above methods to obtain the curve of diffraction efficiency with reconstruction wavelength by using Matlab software. Comparing the simulated results with the experiments results, we can deduce the probable situation of thick hologram gratings bending after photopolymer materials shrink.

Algorithm of composing the schedule of construction and installation works

NASA Astrophysics Data System (ADS)

Nehaj, Rustam; Molotkov, Georgij; Rudchenko, Ivan; Grinev, Anatolij; Sekisov, Aleksandr

2017-10-01

An algorithm for scheduling works is developed, in which the priority of the work corresponds to the total weight of the subordinate works, the vertices of the graph, and it is proved that for graphs of the tree type the algorithm is optimal. An algorithm is synthesized to reduce the search for solutions when drawing up schedules of construction and installation works, allocating a subset with the optimal solution of the problem of the minimum power, which is determined by the structure of its initial data and numerical values. An algorithm for scheduling construction and installation work is developed, taking into account the schedule for the movement of brigades, which is characterized by the possibility to efficiently calculate the values of minimizing the time of work performance by the parameters of organizational and technological reliability through the use of the branch and boundary method. The program of the computational algorithm was compiled in the MatLAB-2008 program. For the initial data of the matrix, random numbers were taken, uniformly distributed in the range from 1 to 100. It takes 0.5; 2.5; 7.5; 27 minutes to solve the problem. Thus, the proposed method for estimating the lower boundary of the solution is sufficiently accurate and allows efficient solution of the minimax task of scheduling construction and installation works.

Design and simulation of permanent magnet synchronous motor control system

NASA Astrophysics Data System (ADS)

Li, Li; Liu, Yongqiu

2018-06-01

In recent years, with the development of power electronics, microelectronics, new motor control theory and rare earth permanent magnet materials, permanent magnet synchronous motors have been rapidly applied. Permanent magnet synchronous motors have the advantages of small size, low loss and high efficiency. Today, energy conservation and environmental protection are increasingly valued. It is very necessary to study them. Permanent magnet synchronous motor control system has a wide range of application prospects in the fields of electric vehicles, ships and other transportation. Using the simulation function of MATLAB/SIMULINK, a modular design structure was used to simulate the whole system model of speed loop adjustment, current PI modulation, SVPWM (Space Vector Pulse Width Module) wave generation and double closed loop. The results show that this control method has good robustness, and this method can improve the design efficiency and shorten the system design time. In this article, the analysis of the control principle of modern permanent magnet synchronous motor and the various processes of MATLAB simulation application will be analyzed in detail. The basic theory, basic method and application technology of the permanent magnet synchronous motor control system are systematically introduced.

Updates to FuncLab, a Matlab based GUI for handling receiver functions

NASA Astrophysics Data System (ADS)

Porritt, Robert W.; Miller, Meghan S.

2018-02-01

Receiver functions are a versatile tool commonly used in seismic imaging. Depending on how they are processed, they can be used to image discontinuity structure within the crust or mantle or they can be inverted for seismic velocity either directly or jointly with complementary datasets. However, modern studies generally require large datasets which can be challenging to handle; therefore, FuncLab was originally written as an interactive Matlab GUI to assist in handling these large datasets. This software uses a project database to allow interactive trace editing, data visualization, H-κ stacking for crustal thickness and Vp/Vs ratio, and common conversion point stacking while minimizing computational costs. Since its initial release, significant advances have been made in the implementation of web services and changes in the underlying Matlab platform have necessitated a significant revision to the software. Here, we present revisions to the software, including new features such as data downloading via irisFetch.m, receiver function calculations via processRFmatlab, on-the-fly cross-section tools, interface picking, and more. In the descriptions of the tools, we present its application to a test dataset in Michigan, Wisconsin, and neighboring areas following the passage of USArray Transportable Array. The software is made available online at https://robporritt.wordpress.com/software.

MATLAB tools for improved characterization and quantification of volcanic incandescence in Webcam imagery; applications at Kilauea Volcano, Hawai'i

USGS Publications Warehouse

Patrick, Matthew R.; Kauahikaua, James P.; Antolik, Loren

2010-01-01

Webcams are now standard tools for volcano monitoring and are used at observatories in Alaska, the Cascades, Kamchatka, Hawai'i, Italy, and Japan, among other locations. Webcam images allow invaluable documentation of activity and provide a powerful comparative tool for interpreting other monitoring datastreams, such as seismicity and deformation. Automated image processing can improve the time efficiency and rigor of Webcam image interpretation, and potentially extract more information on eruptive activity. For instance, Lovick and others (2008) provided a suite of processing tools that performed such tasks as noise reduction, eliminating uninteresting images from an image collection, and detecting incandescence, with an application to dome activity at Mount St. Helens during 2007. In this paper, we present two very simple automated approaches for improved characterization and quantification of volcanic incandescence in Webcam images at Kilauea Volcano, Hawai`i. The techniques are implemented in MATLAB (version 2009b, Copyright: The Mathworks, Inc.) to take advantage of the ease of matrix operations. Incandescence is a useful indictor of the location and extent of active lava flows and also a potentially powerful proxy for activity levels at open vents. We apply our techniques to a period covering both summit and east rift zone activity at Kilauea during 2008?2009 and compare the results to complementary datasets (seismicity, tilt) to demonstrate their integrative potential. A great strength of this study is the demonstrated success of these tools in an operational setting at the Hawaiian Volcano Observatory (HVO) over the course of more than a year. Although applied only to Webcam images here, the techniques could be applied to any type of sequential images, such as time-lapse photography. We expect that these tools are applicable to many other volcano monitoring scenarios, and the two MATLAB scripts, as they are implemented at HVO, are included in the appendixes. These scripts would require minor to moderate modifications for use elsewhere, primarily to customize directory navigation. If the user has some familiarity with MATLAB, or programming in general, these modifications should be easy. Although we originally anticipated needing the Image Processing Toolbox, the scripts in the appendixes do not require it. Thus, only the base installation of MATLAB is needed. Because fairly basic MATLAB functions are used, we expect that the script can be run successfully by versions earlier than 2009b.

Quantitative Image Feature Engine (QIFE): an Open-Source, Modular Engine for 3D Quantitative Feature Extraction from Volumetric Medical Images.

PubMed

Echegaray, Sebastian; Bakr, Shaimaa; Rubin, Daniel L; Napel, Sandy

2017-10-06

The aim of this study was to develop an open-source, modular, locally run or server-based system for 3D radiomics feature computation that can be used on any computer system and included in existing workflows for understanding associations and building predictive models between image features and clinical data, such as survival. The QIFE exploits various levels of parallelization for use on multiprocessor systems. It consists of a managing framework and four stages: input, pre-processing, feature computation, and output. Each stage contains one or more swappable components, allowing run-time customization. We benchmarked the engine using various levels of parallelization on a cohort of CT scans presenting 108 lung tumors. Two versions of the QIFE have been released: (1) the open-source MATLAB code posted to Github, (2) a compiled version loaded in a Docker container, posted to DockerHub, which can be easily deployed on any computer. The QIFE processed 108 objects (tumors) in 2:12 (h/mm) using 1 core, and 1:04 (h/mm) hours using four cores with object-level parallelization. We developed the Quantitative Image Feature Engine (QIFE), an open-source feature-extraction framework that focuses on modularity, standards, parallelism, provenance, and integration. Researchers can easily integrate it with their existing segmentation and imaging workflows by creating input and output components that implement their existing interfaces. Computational efficiency can be improved by parallelizing execution at the cost of memory usage. Different parallelization levels provide different trade-offs, and the optimal setting will depend on the size and composition of the dataset to be processed.

MATLAB Toolboxes for Reference Electrode Standardization Technique (REST) of Scalp EEG

PubMed Central

Dong, Li; Li, Fali; Liu, Qiang; Wen, Xin; Lai, Yongxiu; Xu, Peng; Yao, Dezhong

2017-01-01

Reference electrode standardization technique (REST) has been increasingly acknowledged and applied as a re-reference technique to transform an actual multi-channels recordings to approximately zero reference ones in electroencephalography/event-related potentials (EEG/ERPs) community around the world in recent years. However, a more easy-to-use toolbox for re-referencing scalp EEG data to zero reference is still lacking. Here, we have therefore developed two open-source MATLAB toolboxes for REST of scalp EEG. One version of REST is closely integrated into EEGLAB, which is a popular MATLAB toolbox for processing the EEG data; and another is a batch version to make it more convenient and efficient for experienced users. Both of them are designed to provide an easy-to-use for novice researchers and flexibility for experienced researchers. All versions of the REST toolboxes can be freely downloaded at http://www.neuro.uestc.edu.cn/rest/Down.html, and the detailed information including publications, comments and documents on REST can also be found from this website. An example of usage is given with comparative results of REST and average reference. We hope these user-friendly REST toolboxes could make the relatively novel technique of REST easier to study, especially for applications in various EEG studies. PMID:29163006

MATLAB Toolboxes for Reference Electrode Standardization Technique (REST) of Scalp EEG.

PubMed

Dong, Li; Li, Fali; Liu, Qiang; Wen, Xin; Lai, Yongxiu; Xu, Peng; Yao, Dezhong

2017-01-01

Reference electrode standardization technique (REST) has been increasingly acknowledged and applied as a re-reference technique to transform an actual multi-channels recordings to approximately zero reference ones in electroencephalography/event-related potentials (EEG/ERPs) community around the world in recent years. However, a more easy-to-use toolbox for re-referencing scalp EEG data to zero reference is still lacking. Here, we have therefore developed two open-source MATLAB toolboxes for REST of scalp EEG. One version of REST is closely integrated into EEGLAB, which is a popular MATLAB toolbox for processing the EEG data; and another is a batch version to make it more convenient and efficient for experienced users. Both of them are designed to provide an easy-to-use for novice researchers and flexibility for experienced researchers. All versions of the REST toolboxes can be freely downloaded at http://www.neuro.uestc.edu.cn/rest/Down.html, and the detailed information including publications, comments and documents on REST can also be found from this website. An example of usage is given with comparative results of REST and average reference. We hope these user-friendly REST toolboxes could make the relatively novel technique of REST easier to study, especially for applications in various EEG studies.

Creating an EPICS Based Test Stand Development System for a BPM Digitizer of the Linac Coherent Light Source

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

Not Available

2011-06-22

The Linac Coherent Light Source (LCLS) is required to deliver a high quality electron beam for producing coherent X-rays. As a result, high resolution beam position monitoring is required. The Beam Position Monitor (BPM) digitizer acquires analog signals from the beam line and digitizes them to obtain beam position data. Although Matlab is currently being used to test the BPM digitizer?s functions and capability, the Controls Department at SLAC prefers to use Experimental Physics and Industrial Control Systems (EPICS). This paper discusses the transition of providing similar as well as enhanced functionalities, than those offered by Matlab, to test themore » digitizer. Altogether, the improved test stand development system can perform mathematical and statistical calculations with the waveform signals acquired from the digitizer and compute the fast Fourier transform (FFT) of the signals. Finally, logging of meaningful data into files has been added.« less

Dynamical modeling and multi-experiment fitting with PottersWheel

PubMed Central

Maiwald, Thomas; Timmer, Jens

2008-01-01

Motivation: Modelers in Systems Biology need a flexible framework that allows them to easily create new dynamic models, investigate their properties and fit several experimental datasets simultaneously. Multi-experiment-fitting is a powerful approach to estimate parameter values, to check the validity of a given model, and to discriminate competing model hypotheses. It requires high-performance integration of ordinary differential equations and robust optimization. Results: We here present the comprehensive modeling framework Potters-Wheel (PW) including novel functionalities to satisfy these requirements with strong emphasis on the inverse problem, i.e. data-based modeling of partially observed and noisy systems like signal transduction pathways and metabolic networks. PW is designed as a MATLAB toolbox and includes numerous user interfaces. Deterministic and stochastic optimization routines are combined by fitting in logarithmic parameter space allowing for robust parameter calibration. Model investigation includes statistical tests for model-data-compliance, model discrimination, identifiability analysis and calculation of Hessian- and Monte-Carlo-based parameter confidence limits. A rich application programming interface is available for customization within own MATLAB code. Within an extensive performance analysis, we identified and significantly improved an integrator–optimizer pair which decreases the fitting duration for a realistic benchmark model by a factor over 3000 compared to MATLAB with optimization toolbox. Availability: PottersWheel is freely available for academic usage at http://www.PottersWheel.de/. The website contains a detailed documentation and introductory videos. The program has been intensively used since 2005 on Windows, Linux and Macintosh computers and does not require special MATLAB toolboxes. Contact: maiwald@fdm.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:18614583

Numerical study of fluid motion in bioreactor with two mixers

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

Zheleva, I., E-mail: izheleva@uni-ruse.bg; Lecheva, A., E-mail: alecheva@uni-ruse.bg

2015-10-28

Numerical study of hydrodynamic laminar behavior of a viscous fluid in bioreactor with multiple mixers is provided in the present paper. The reactor is equipped with two disk impellers. The fluid motion is studied in stream function-vorticity formulation. The calculations are made by a computer program, written in MATLAB. The fluid structure is described and numerical results are graphically presented and commented.

tweezercalib 2.0: Faster version of MatLab package for precise calibration of optical tweezers

NASA Astrophysics Data System (ADS)

Hansen, Poul Martin; Tolić-Nørrelykke, Iva Marija; Flyvbjerg, Henrik; Berg-Sørensen, Kirstine

2006-03-01

We present a vectorized version of the MatLab (MathWorks Inc.) package tweezercalib for calibration of optical tweezers with precision. The calibration is based on the power spectrum of the Brownian motion of a dielectric bead trapped in the tweezers. Precision is achieved by accounting for a number of factors that affect this power spectrum, as described in vs. 1 of the package [I.M. Tolić-Nørrelykke, K. Berg-Sørensen, H. Flyvbjerg, Matlab program for precision calibration of optical tweezers, Comput. Phys. Comm. 159 (2004) 225-240]. The graphical user interface allows the user to include or leave out each of these factors. Several "health tests" are applied to the experimental data during calibration, and test results are displayed graphically. Thus, the user can easily see whether the data comply with the theory used for their interpretation. Final calibration results are given with statistical errors and covariance matrix. New version program summaryTitle of program: tweezercalib Catalogue identifier: ADTV_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADTV_v2_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Reference in CPC to previous version: I.M. Tolić-Nørrelykke, K. Berg-Sørensen, H. Flyvbjerg, Comput. Phys. Comm. 159 (2004) 225 Catalogue identifier of previous version: ADTV Does the new version supersede the original program: Yes Computer for which the program is designed and others on which it has been tested: General computer running MatLab (Mathworks Inc.) Operating systems under with the program has been tested: Windows2000, Windows-XP, Linux Programming language used: MatLab (Mathworks Inc.), standard license Memory required to execute with typical data: Of order four times the size of the data file High speed storage required: none No. of lines in distributed program, including test data, etc.: 135 989 No. of bytes in distributed program, including test data, etc.: 1 527 611 Distribution format: tar. gz Nature of physical problem: Calibrate optical tweezers with precision by fitting theory to experimental power spectrum of position of bead doing Brownian motion in incompressible fluid, possibly near microscope cover slip, while trapped in optical tweezers. Thereby determine spring constant of optical trap and conversion factor for arbitrary-units-to-nanometers for detection system. Method of solution: Elimination of cross-talk between quadrant photo-diode's output channels for positions (optional). Check that distribution of recorded positions agrees with Boltzmann distribution of bead in harmonic trap. Data compression and noise reduction by blocking method applied to power spectrum. Full accounting for hydrodynamic effects: Frequency-dependent drag force and interaction with nearby cover slip (optional). Full accounting for electronic filters (optional), for "virtual filtering" caused by detection system (optional). Full accounting for aliasing caused by finite sampling rate (optional). Standard non-linear least-squares fitting. Statistical support for fit is given, with several plots facilitating inspection of consistency and quality of data and fit. Summary of revisions: A faster fitting routine, adapted from [J. Nocedal, Y.x. Yuan, Combining trust region and line search techniques, Technical Report OTC 98/04, Optimization Technology Center, 1998; W.H. Press, B.P. Flannery, S.A. Teukolsky, W.T. Vetterling, Numerical Recipes. The Art of Scientific Computing, Cambridge University Press, Cambridge, 1986], is applied. It uses fewer function evaluations, and the remaining function evaluations have been vectorized. Calls to routines in Toolboxes not included with a standard MatLab license have been replaced by calls to routines that are included in the present package. Fitting parameters are rescaled to ensure that they are all of roughly the same size (of order 1) while being fitted. Generally, the program package has been updated to comply with MatLab, vs. 7.0, and optimized for speed. Restrictions on the complexity of the problem: Data should be positions of bead doing Brownian motion while held by optical tweezers. For high precision in final results, data should be time series measured over a long time, with sufficiently high experimental sampling rate: The sampling rate should be well above the characteristic frequency of the trap, the so-called corner frequency. Thus, the sampling frequency should typically be larger than 10 kHz. The Fast Fourier Transform used works optimally when the time series contain 2 data points, and long measurement time is obtained with n>12-15. Finally, the optics should be set to ensure a harmonic trapping potential in the range of positions visited by the bead. The fitting procedure checks for harmonic potential. Typical running time: Seconds Unusual features of the program: None References: The theoretical underpinnings for the procedure are found in [K. Berg-Sørensen, H. Flyvbjerg, Power spectrum analysis for optical tweezers, Rev. Sci. Ins. 75 (2004) 594-612].

Experiences in teaching of modeling and simulation with emphasize on equation-based and acausal modeling techniques.

PubMed

Kulhánek, Tomáš; Ježek, Filip; Mateják, Marek; Šilar, Jan; Kofránek, Jří

2015-08-01

This work introduces experiences of teaching modeling and simulation for graduate students in the field of biomedical engineering. We emphasize the acausal and object-oriented modeling technique and we have moved from teaching block-oriented tool MATLAB Simulink to acausal and object oriented Modelica language, which can express the structure of the system rather than a process of computation. However, block-oriented approach is allowed in Modelica language too and students have tendency to express the process of computation. Usage of the exemplar acausal domains and approach allows students to understand the modeled problems much deeper. The causality of the computation is derived automatically by the simulation tool.

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

Lai, Jih-Sheng

This paper introduces control system design based softwares, SIMNON and MATLAB/SIMULINK, for power electronics system simulation. A complete power electronics system typically consists of a rectifier bridge along with its smoothing capacitor, an inverter, and a motor. The system components, featuring discrete or continuous, linear or nonlinear, are modeled in mathematical equations. Inverter control methods,such as pulse-width-modulation and hysteresis current control, are expressed in either computer algorithms or digital circuits. After describing component models and control methods, computer programs are then developed for complete systems simulation. Simulation results are mainly used for studying system performances, such as input and outputmore » current harmonics, torque ripples, and speed responses. Key computer programs and simulation results are demonstrated for educational purposes.« less

Human-computer interfaces applied to numerical solution of the Plateau problem

NASA Astrophysics Data System (ADS)

Elias Fabris, Antonio; Soares Bandeira, Ivana; Ramos Batista, Valério

2015-09-01

In this work we present a code in Matlab to solve the Problem of Plateau numerically, and the code will include human-computer interface. The Problem of Plateau has applications in areas of knowledge like, for instance, Computer Graphics. The solution method will be the same one of the Surface Evolver, but the difference will be a complete graphical interface with the user. This will enable us to implement other kinds of interface like ocular mouse, voice, touch, etc. To date, Evolver does not include any graphical interface, which restricts its use by the scientific community. Specially, its use is practically impossible for most of the Physically Challenged People.

Read margin analysis of crossbar arrays using the cell-variability-aware simulation method

NASA Astrophysics Data System (ADS)

Sun, Wookyung; Choi, Sujin; Shin, Hyungsoon

2018-02-01

This paper proposes a new concept of read margin analysis of crossbar arrays using cell-variability-aware simulation. The size of the crossbar array should be considered to predict the read margin characteristic of the crossbar array because the read margin depends on the number of word lines and bit lines. However, an excessively high-CPU time is required to simulate large arrays using a commercial circuit simulator. A variability-aware MATLAB simulator that considers independent variability sources is developed to analyze the characteristics of the read margin according to the array size. The developed MATLAB simulator provides an effective method for reducing the simulation time while maintaining the accuracy of the read margin estimation in the crossbar array. The simulation is also highly efficient in analyzing the characteristic of the crossbar memory array considering the statistical variations in the cell characteristics.

SU-F-T-584: Investigating Correction Methods for Ion Recombination Effects in OCTAVIUS 1000 SRS Measurements

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

Knill, C; Wayne State University School of Medicine, Detroit, MI; Snyder, M

Purpose: PTW’s Octavius 1000 SRS array performs IMRT QA measurements with liquid filled ionization chambers (LICs). Collection efficiencies of LICs have been shown to change during IMRT delivery as a function of LINAC pulse frequency and pulse dose, which affects QA results. In this study, two methods were developed to correct changes in collection efficiencies during IMRT QA measurements, and the effects of these corrections on QA pass rates were compared. Methods: For the first correction, Matlab software was developed that calculates pulse frequency and pulse dose for each detector, using measurement and DICOM RT Plan files. Pulse information ismore » converted to collection efficiency and measurements are corrected by multiplying detector dose by ratios of calibration to measured collection efficiencies. For the second correction, MU/min in daily 1000 SRS calibration was chosen to match average MU/min of the VMAT plan. Usefulness of derived corrections were evaluated using 6MV and 10FFF SBRT RapidArc plans delivered to the OCTAVIUS 4D system using a TrueBeam equipped with an HD- MLC. Effects of the two corrections on QA results were examined by performing 3D gamma analysis comparing predicted to measured dose, with and without corrections. Results: After complex Matlab corrections, average 3D gamma pass rates improved by [0.07%,0.40%,1.17%] for 6MV and [0.29%,1.40%,4.57%] for 10FFF using [3%/3mm,2%/2mm,1%/1mm] criteria. Maximum changes in gamma pass rates were [0.43%,1.63%,3.05%] for 6MV and [1.00%,4.80%,11.2%] for 10FFF using [3%/3mm,2%/2mm,1%/1mm] criteria. On average, pass rates of simple daily calibration corrections were within 1% of complex Matlab corrections. Conclusion: Ion recombination effects can potentially be clinically significant for OCTAVIUS 1000 SRS measurements, especially for higher pulse dose unflattened beams when using tighter gamma tolerances. Matching daily 1000 SRS calibration MU/min to average planned MU/min is a simple correction that greatly reduces ion recombination effects, improving measurements accuracy and gamma pass rates. This work was supported by PTW.« less

Edge detection and mathematic fitting for corneal surface with Matlab software.

PubMed

Di, Yue; Li, Mei-Yan; Qiao, Tong; Lu, Na

2017-01-01

To select the optimal edge detection methods to identify the corneal surface, and compare three fitting curve equations with Matlab software. Fifteen subjects were recruited. The corneal images from optical coherence tomography (OCT) were imported into Matlab software. Five edge detection methods (Canny, Log, Prewitt, Roberts, Sobel) were used to identify the corneal surface. Then two manual identifying methods (ginput and getpts) were applied to identify the edge coordinates respectively. The differences among these methods were compared. Binomial curve (y=Ax 2 +Bx+C), Polynomial curve [p(x)=p1x n +p2x n-1 +....+pnx+pn+1] and Conic section (Ax 2 +Bxy+Cy 2 +Dx+Ey+F=0) were used for curve fitting the corneal surface respectively. The relative merits among three fitting curves were analyzed. Finally, the eccentricity (e) obtained by corneal topography and conic section were compared with paired t -test. Five edge detection algorithms all had continuous coordinates which indicated the edge of the corneal surface. The ordinates of manual identifying were close to the inside of the actual edges. Binomial curve was greatly affected by tilt angle. Polynomial curve was lack of geometrical properties and unstable. Conic section could calculate the tilted symmetry axis, eccentricity, circle center, etc . There were no significant differences between 'e' values by corneal topography and conic section ( t =0.9143, P =0.3760 >0.05). It is feasible to simulate the corneal surface with mathematical curve with Matlab software. Edge detection has better repeatability and higher efficiency. The manual identifying approach is an indispensable complement for detection. Polynomial and conic section are both the alternative methods for corneal curve fitting. Conic curve was the optimal choice based on the specific geometrical properties.

Event-driven processing for hardware-efficient neural spike sorting

NASA Astrophysics Data System (ADS)

Liu, Yan; Pereira, João L.; Constandinou, Timothy G.

2018-02-01

Objective. The prospect of real-time and on-node spike sorting provides a genuine opportunity to push the envelope of large-scale integrated neural recording systems. In such systems the hardware resources, power requirements and data bandwidth increase linearly with channel count. Event-based (or data-driven) processing can provide here a new efficient means for hardware implementation that is completely activity dependant. In this work, we investigate using continuous-time level-crossing sampling for efficient data representation and subsequent spike processing. Approach. (1) We first compare signals (synthetic neural datasets) encoded with this technique against conventional sampling. (2) We then show how such a representation can be directly exploited by extracting simple time domain features from the bitstream to perform neural spike sorting. (3) The proposed method is implemented in a low power FPGA platform to demonstrate its hardware viability. Main results. It is observed that considerably lower data rates are achievable when using 7 bits or less to represent the signals, whilst maintaining the signal fidelity. Results obtained using both MATLAB and reconfigurable logic hardware (FPGA) indicate that feature extraction and spike sorting accuracies can be achieved with comparable or better accuracy than reference methods whilst also requiring relatively low hardware resources. Significance. By effectively exploiting continuous-time data representation, neural signal processing can be achieved in a completely event-driven manner, reducing both the required resources (memory, complexity) and computations (operations). This will see future large-scale neural systems integrating on-node processing in real-time hardware.

Seaworthy Quantum Key Distribution Design and Validation (SEAKEY)

DTIC Science & Technology

2014-10-30

to single photon detection, at comparable detection efficiencies. On the other hand, error-correction codes are better developed for small-alphabet...protocol is several orders of magnitude better than the Shapiro protocol, which needs entangled states. The bits/mode performance achieved by our...putting together a software tool implemented in MATLAB , which talks to the MODTRAN database via an intermediate numerical dump of transmission data

Mathematical model of ambulance resources in Saint-Petersburg

NASA Astrophysics Data System (ADS)

Shavidze, G. G.; Balykina, Y. E.; Lejnina, E. A.; Svirkin, M. V.

2016-06-01

Emergency medical system is one of the main elements in city infrastructure. The article contains analysis of existing system of ambulance resource distribution. Paper considers the idea of using multiperiodicity as a tool to increase the efficiency of the Emergency Medical Services. The program developed in programming environment Matlab helps to evaluate the changes in the functioning of the system of emergency medical service.

A comparison of approaches for finding minimum identifying codes on graphs

NASA Astrophysics Data System (ADS)

Horan, Victoria; Adachi, Steve; Bak, Stanley

2016-05-01

In order to formulate mathematical conjectures likely to be true, a number of base cases must be determined. However, many combinatorial problems are NP-hard and the computational complexity makes this research approach difficult using a standard brute force approach on a typical computer. One sample problem explored is that of finding a minimum identifying code. To work around the computational issues, a variety of methods are explored and consist of a parallel computing approach using MATLAB, an adiabatic quantum optimization approach using a D-Wave quantum annealing processor, and lastly using satisfiability modulo theory (SMT) and corresponding SMT solvers. Each of these methods requires the problem to be formulated in a unique manner. In this paper, we address the challenges of computing solutions to this NP-hard problem with respect to each of these methods.

Nonlinear Boltzmann equation for the homogeneous isotropic case: Minimal deterministic Matlab program

NASA Astrophysics Data System (ADS)

Asinari, Pietro

2010-10-01

The homogeneous isotropic Boltzmann equation (HIBE) is a fundamental dynamic model for many applications in thermodynamics, econophysics and sociodynamics. Despite recent hardware improvements, the solution of the Boltzmann equation remains extremely challenging from the computational point of view, in particular by deterministic methods (free of stochastic noise). This work aims to improve a deterministic direct method recently proposed [V.V. Aristov, Kluwer Academic Publishers, 2001] for solving the HIBE with a generic collisional kernel and, in particular, for taking care of the late dynamics of the relaxation towards the equilibrium. Essentially (a) the original problem is reformulated in terms of particle kinetic energy (exact particle number and energy conservation during microscopic collisions) and (b) the computation of the relaxation rates is improved by the DVM-like correction, where DVM stands for Discrete Velocity Model (ensuring that the macroscopic conservation laws are exactly satisfied). Both these corrections make possible to derive very accurate reference solutions for this test case. Moreover this work aims to distribute an open-source program (called HOMISBOLTZ), which can be redistributed and/or modified for dealing with different applications, under the terms of the GNU General Public License. The program has been purposely designed in order to be minimal, not only with regards to the reduced number of lines (less than 1000), but also with regards to the coding style (as simple as possible). Program summaryProgram title: HOMISBOLTZ Catalogue identifier: AEGN_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGN_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License No. of lines in distributed program, including test data, etc.: 23 340 No. of bytes in distributed program, including test data, etc.: 7 635 236 Distribution format: tar.gz Programming language: Tested with Matlab version ⩽6.5. However, in principle, any recent version of Matlab or Octave should work Computer: All supporting Matlab or Octave Operating system: All supporting Matlab or Octave RAM: 300 MBytes Classification: 23 Nature of problem: The problem consists in integrating the homogeneous Boltzmann equation for a generic collisional kernel in case of isotropic symmetry, by a deterministic direct method. Difficulties arise from the multi-dimensionality of the collisional operator and from satisfying the conservation of particle number and energy (momentum is trivial for this test case) as accurately as possible, in order to preserve the late dynamics. Solution method: The solution is based on the method proposed by Aristov (2001) [1], but with two substantial improvements: (a) the original problem is reformulated in terms of particle kinetic energy (this allows one to ensure exact particle number and energy conservation during microscopic collisions) and (b) a DVM-like correction (where DVM stands for Discrete Velocity Model) is adopted for improving the relaxation rates (this allows one to satisfy exactly the conservation laws at macroscopic level, which is particularly important for describing the late dynamics in the relaxation towards the equilibrium). Both these corrections make possible to derive very accurate reference solutions for this test case. Restrictions: The nonlinear Boltzmann equation is extremely challenging from the computational point of view, in particular for deterministic methods, despite the increased computational power of recent hardware. In this work, only the homogeneous isotropic case is considered, for making possible the development of a minimal program (by a simple scripting language) and allowing the user to check the advantages of the proposed improvements beyond Aristov's (2001) method [1]. The initial conditions are supposed parameterized according to a fixed analytical expression, but this can be easily modified. Running time: From minutes to hours (depending on the adopted discretization of the kinetic energy space). For example, on a 64 bit workstation with Intel CoreTM i7-820Q Quad Core CPU at 1.73 GHz and 8 MBytes of RAM, the provided test run (with the corresponding binary data file storing the pre-computed relaxation rates) requires 154 seconds. References:V.V. Aristov, Direct Methods for Solving the Boltzmann Equation and Study of Nonequilibrium Flows, Kluwer Academic Publishers, 2001.

A conjugate gradient method with descent properties under strong Wolfe line search

NASA Astrophysics Data System (ADS)

Zull, N.; ‘Aini, N.; Shoid, S.; Ghani, N. H. A.; Mohamed, N. S.; Rivaie, M.; Mamat, M.

2017-09-01

The conjugate gradient (CG) method is one of the optimization methods that are often used in practical applications. The continuous and numerous studies conducted on the CG method have led to vast improvements in its convergence properties and efficiency. In this paper, a new CG method possessing the sufficient descent and global convergence properties is proposed. The efficiency of the new CG algorithm relative to the existing CG methods is evaluated by testing them all on a set of test functions using MATLAB. The tests are measured in terms of iteration numbers and CPU time under strong Wolfe line search. Overall, this new method performs efficiently and comparable to the other famous methods.

A native Bayesian classifier based routing protocol for VANETS

NASA Astrophysics Data System (ADS)

Bao, Zhenshan; Zhou, Keqin; Zhang, Wenbo; Gong, Xiaolei

2016-12-01

Geographic routing protocols are one of the most hot research areas in VANET (Vehicular Ad-hoc Network). However, there are few routing protocols can take both the transmission efficient and the usage of ratio into account. As we have noticed, different messages in VANET may ask different quality of service. So we raised a Native Bayesian Classifier based routing protocol (Naive Bayesian Classifier-Greedy, NBC-Greedy), which can classify and transmit different messages by its emergency degree. As a result, we can balance the transmission efficient and the usage of ratio with this protocol. Based on Matlab simulation, we can draw a conclusion that NBC-Greedy is more efficient and stable than LR-Greedy and GPSR.

DGSA: A Matlab toolbox for distance-based generalized sensitivity analysis of geoscientific computer experiments

NASA Astrophysics Data System (ADS)

Park, Jihoon; Yang, Guang; Satija, Addy; Scheidt, Céline; Caers, Jef

2016-12-01

Sensitivity analysis plays an important role in geoscientific computer experiments, whether for forecasting, data assimilation or model calibration. In this paper we focus on an extension of a method of regionalized sensitivity analysis (RSA) to applications typical in the Earth Sciences. Such applications involve the building of large complex spatial models, the application of computationally extensive forward modeling codes and the integration of heterogeneous sources of model uncertainty. The aim of this paper is to be practical: 1) provide a Matlab code, 2) provide novel visualization methods to aid users in getting a better understanding in the sensitivity 3) provide a method based on kernel principal component analysis (KPCA) and self-organizing maps (SOM) to account for spatial uncertainty typical in Earth Science applications and 4) provide an illustration on a real field case where the above mentioned complexities present themselves. We present methods that extend the original RSA method in several ways. First we present the calculation of conditional effects, defined as the sensitivity of a parameter given a level of another parameters. Second, we show how this conditional effect can be used to choose nominal values or ranges to fix insensitive parameters aiming to minimally affect uncertainty in the response. Third, we develop a method based on KPCA and SOM to assign a rank to spatial models in order to calculate the sensitivity on spatial variability in the models. A large oil/gas reservoir case is used as illustration of these ideas.

MATLAB-based algorithm to estimate depths of isolated thin dike-like sources using higher-order horizontal derivatives of magnetic anomalies.

PubMed

Ekinci, Yunus Levent

2016-01-01

This paper presents an easy-to-use open source computer algorithm (code) for estimating the depths of isolated single thin dike-like source bodies by using numerical second-, third-, and fourth-order horizontal derivatives computed from observed magnetic anomalies. The approach does not require a priori information and uses some filters of successive graticule spacings. The computed higher-order horizontal derivative datasets are used to solve nonlinear equations for depth determination. The solutions are independent from the magnetization and ambient field directions. The practical usability of the developed code, designed in MATLAB R2012b (MathWorks Inc.), was successfully examined using some synthetic simulations with and without noise. The algorithm was then used to estimate the depths of some ore bodies buried in different regions (USA, Sweden, and Canada). Real data tests clearly indicated that the obtained depths are in good agreement with those of previous studies and drilling information. Additionally, a state-of-the-art inversion scheme based on particle swarm optimization produced comparable results to those of the higher-order horizontal derivative analyses in both synthetic and real anomaly cases. Accordingly, the proposed code is verified to be useful in interpreting isolated single thin dike-like magnetized bodies and may be an alternative processing technique. The open source code can be easily modified and adapted to suit the benefits of other researchers.

Parallel and Preemptable Dynamically Dimensioned Search Algorithms for Single and Multi-objective Optimization in Water Resources

NASA Astrophysics Data System (ADS)

Tolson, B.; Matott, L. S.; Gaffoor, T. A.; Asadzadeh, M.; Shafii, M.; Pomorski, P.; Xu, X.; Jahanpour, M.; Razavi, S.; Haghnegahdar, A.; Craig, J. R.

2015-12-01

We introduce asynchronous parallel implementations of the Dynamically Dimensioned Search (DDS) family of algorithms including DDS, discrete DDS, PA-DDS and DDS-AU. These parallel algorithms are unique from most existing parallel optimization algorithms in the water resources field in that parallel DDS is asynchronous and does not require an entire population (set of candidate solutions) to be evaluated before generating and then sending a new candidate solution for evaluation. One key advance in this study is developing the first parallel PA-DDS multi-objective optimization algorithm. The other key advance is enhancing the computational efficiency of solving optimization problems (such as model calibration) by combining a parallel optimization algorithm with the deterministic model pre-emption concept. These two efficiency techniques can only be combined because of the asynchronous nature of parallel DDS. Model pre-emption functions to terminate simulation model runs early, prior to completely simulating the model calibration period for example, when intermediate results indicate the candidate solution is so poor that it will definitely have no influence on the generation of further candidate solutions. The computational savings of deterministic model preemption available in serial implementations of population-based algorithms (e.g., PSO) disappear in synchronous parallel implementations as these algorithms. In addition to the key advances above, we implement the algorithms across a range of computation platforms (Windows and Unix-based operating systems from multi-core desktops to a supercomputer system) and package these for future modellers within a model-independent calibration software package called Ostrich as well as MATLAB versions. Results across multiple platforms and multiple case studies (from 4 to 64 processors) demonstrate the vast improvement over serial DDS-based algorithms and highlight the important role model pre-emption plays in the performance of parallel, pre-emptable DDS algorithms. Case studies include single- and multiple-objective optimization problems in water resources model calibration and in many cases linear or near linear speedups are observed.

Embracing equifinality with efficiency: Limits of Acceptability sampling using the DREAM(LOA) algorithm

NASA Astrophysics Data System (ADS)

Vrugt, Jasper A.; Beven, Keith J.

2018-04-01

This essay illustrates some recent developments to the DiffeRential Evolution Adaptive Metropolis (DREAM) MATLAB toolbox of Vrugt (2016) to delineate and sample the behavioural solution space of set-theoretic likelihood functions used within the GLUE (Limits of Acceptability) framework (Beven and Binley, 1992, 2014; Beven and Freer, 2001; Beven, 2006). This work builds on the DREAM(ABC) algorithm of Sadegh and Vrugt (2014) and enhances significantly the accuracy and CPU-efficiency of Bayesian inference with GLUE. In particular it is shown how lack of adequate sampling in the model space might lead to unjustified model rejection.

Design and implementation of digital controllers for smart structures using field-programmable gate arrays

NASA Astrophysics Data System (ADS)

Kelly, Jamie S.; Bowman, Hiroshi C.; Rao, Vittal S.; Pottinger, Hardy J.

1997-06-01

Implementation issues represent an unfamiliar challenge to most control engineers, and many techniques for controller design ignore these issues outright. Consequently, the design of controllers for smart structural systems usually proceeds without regard for their eventual implementation, thus resulting either in serious performance degradation or in hardware requirements that squander power, complicate integration, and drive up cost. The level of integration assumed by the Smart Patch further exacerbates these difficulties, and any design inefficiency may render the realization of a single-package sensor-controller-actuator system infeasible. The goal of this research is to automate the controller implementation process and to relieve the design engineer of implementation concerns like quantization, computational efficiency, and device selection. We specifically target Field Programmable Gate Arrays (FPGAs) as our hardware platform because these devices are highly flexible, power efficient, and reprogrammable. The current study develops an automated implementation sequence that minimizes hardware requirements while maintaining controller performance. Beginning with a state space representation of the controller, the sequence automatically generates a configuration bitstream for a suitable FPGA implementation. MATLAB functions optimize and simulate the control algorithm before translating it into the VHSIC hardware description language. These functions improve power efficiency and simplify integration in the final implementation by performing a linear transformation that renders the controller computationally friendly. The transformation favors sparse matrices in order to reduce multiply operations and the hardware necessary to support them; simultaneously, the remaining matrix elements take on values that minimize limit cycles and parameter sensitivity. The proposed controller design methodology is implemented on a simple cantilever beam test structure using FPGA hardware. The experimental closed loop response is compared with that of an automated FPGA controller implementation. Finally, we explore the integration of FPGA based controllers into a multi-chip module, which we believe represents the next step towards the realization of the Smart Patch.

Improved Load Alleviation Capability for the KC-135

DTIC Science & Technology

1997-09-01

software, such as Matlab, Mathematica, Simulink, and Robotica Front End for Mathematica available in the simulation laboratory Overview This thesis report is...outlined in Spong’s text in order to utilize the Robotica system development software which automates the process of calculating the kinematic and...kinematic and dynamic equations can be accomplished using a computer tool called Robotica Front End (RFE) [ 15], developed by Doctor Spong. Boom Root d3

The reduction in treatment efficiency at high acoustic powers during MR-guided transcranial focused ultrasound thalamotomy for Essential Tremor.

PubMed

Hughes, Alec; Huang, Yuexi; Schwartz, Michael L; Hynynen, Kullervo

2018-05-14

To analyze clinical data indicating a reduction in the induced energy-temperature efficiency relationship during transcranial focused ultrasound (FUS) Essential Tremor (ET) thalamotomy treatments at higher acoustic powers, establish its relationship with the spatial distribution of the focal temperature elevation, and explore its cause. A retrospective observational study of patients (n = 19) treated between July 2015 and August 2016 for (ET) by FUS thalamotomy was performed. These data were analyzed to compare the relationships between the applied power, the applied energy, the resultant peak temperature achieved in the brain, and the dispersion of the focal volume. Full ethics approval was received and all patients provided signed informed consent forms before the initiation of the study. Computer simulations, animal experiments, and clinical system tests were performed to determine the effects of skull heating, changes in brain properties and transducer acoustic output, respectively. All animal procedures were approved by the Animal Care and Use Committee and conformed to the guidelines set out by the Canadian Council on Animal Care. MATLAB was used to perform statistical analysis. The reduction in the energy efficiency relationship during treatment correlates with the increase in size of the focal volume at higher sonication powers. A linear relationship exists showing that a decrease in treatment efficiency correlates positively with an increase in the focal size over the course of treatment (P < 0.01), supporting the hypothesis of transient skull and tissue heating causing acoustic aberrations leading to a decrease in efficiency. Changes in thermal conductivity, perfusion, absorption rates in the brain, as well as ultrasound transducer acoustic output levels were found to have minimal effects on the observed reduction in efficiency. The reduction in energy-temperature efficiency during high-power FUS treatments correlated with observed increases in the size of the focal volume and is likely caused by transient changes in the tissue and skull during heating. © 2018 American Association of Physicists in Medicine.

Monostatic Radar Cross Section Estimation of Missile Shaped Object Using Physical Optics Method

NASA Astrophysics Data System (ADS)

Sasi Bhushana Rao, G.; Nambari, Swathi; Kota, Srikanth; Ranga Rao, K. S.

2017-08-01

Stealth Technology manages many signatures for a target in which most radar systems use radar cross section (RCS) for discriminating targets and classifying them with regard to Stealth. During a war target’s RCS has to be very small to make target invisible to enemy radar. In this study, Radar Cross Section of perfectly conducting objects like cylinder, truncated cone (frustum) and circular flat plate is estimated with respect to parameters like size, frequency and aspect angle. Due to the difficulties in exactly predicting the RCS, approximate methods become the alternative. Majority of approximate methods are valid in optical region and where optical region has its own strengths and weaknesses. Therefore, the analysis given in this study is purely based on far field monostatic RCS measurements in the optical region. Computation is done using Physical Optics (PO) method for determining RCS of simple models. In this study not only the RCS of simple models but also missile shaped and rocket shaped models obtained from the cascaded objects with backscatter has been computed using Matlab simulation. Rectangular plots are obtained for RCS in dbsm versus aspect angle for simple and missile shaped objects using Matlab simulation. Treatment of RCS, in this study is based on Narrow Band.

Distributed Acoustic Sensing (DAS) Data for Periodic Hydraulic Tests: Hydraulic Data

DOE Data Explorer

Cole, Matthew

2015-07-31

Hydraulic responses from periodic hydraulic tests conducted at the Mirror Lake Fractured Rock Research Site, during the summer of 2015. These hydraulic responses were measured also using distributed acoustic sensing (DAS) which is cataloged in a different submission under this grant number. The tests are explained in detail in Matthew Cole's MS Thesis which is cataloged here. The injection and drawdown data and the codes used to analyze the data. Sinusoidal Data is a Matlab data file containing a data table for each period-length test. Within each table is a column labeled: time (seconds since beginning of pumping), Inj_m3pm (formation injection in cubic meters per minute), and head for each observation well (meters). The three Matlab script files (*.m) were used to analyze hydraulic responses from the data file above. High-Pass Sinusoid is a routine for filtering the data, computing the FFT, and extracting phase and amplitude values. Borestore is a routine which contains the borehole storage analytic solution and compares modeled amplitude and phase from this solution to computed amplitude and phase from the data. Patsearch Borestore is a routine containing the built-in pattern search optimization method. This minimizes the total error between modeled and actual amplitude and phase in Borestore. Comments within the script files contain more specific instructions for their use.

System analysis tools for an ELT at ESO

NASA Astrophysics Data System (ADS)

Mueller, Michael; Koch, Franz

2006-06-01

Engineering of complex, large scale systems like the ELT designs currently investigated and developed in Europe and Northern America require powerful and sophisticated tools within specific technical disciplines such as mechanics, optics and control engineering. However, even analyzing a certain component of the telescope like the telescope structure necessitates a system approach to evaluate the structural effects onto the optical performance. This paper shows several software tools developed by the European Southern Observatory (ESO) which focus onto the system approach in the analyses: Using modal results of a finite element analysis the SMI-toolbox allows an easy generation of structural models with different sizes and levels of accuracy for the control design and closed-loop simulations. The optical modeling code BeamWarrior was developed by ESO and Astrium GmbH, Germany) especially for integrated modeling and interfering with a structural model. Within BeamWarrior displacements and deformations can be applied in an arbitrary coordinate system, and hence also in the global coordinates of the FE model avoiding error prone transformations. In addition to this, a sparse state space model object was developed for Matlab to gain in computational efficiency and reduced memory requirements due to the sparsity pattern of both the structural models and the control architecture. As one result these tools allow building an integrated model in order to reliably simulate interactions, cross-coupling effects, system responses, and to evaluate global performance. In order to evaluate disturbance effects on the optical performance in openloop more efficiently, an optical evaluation toolbox was built in the FE software ANSYS which performs Zernike decomposition and best-fit computation of the deformations directly in the FE analysis.

Integrating mitosis, toxicity, and transgene expression in a telecommunications packet-switched network model of lipoplex-mediated gene delivery.

PubMed

Martin, Timothy M; Wysocki, Beata J; Beyersdorf, Jared P; Wysocki, Tadeusz A; Pannier, Angela K

2014-08-01

Gene delivery systems transport exogenous genetic information to cells or biological systems with the potential to directly alter endogenous gene expression and behavior with applications in functional genomics, tissue engineering, medical devices, and gene therapy. Nonviral systems offer advantages over viral systems because of their low immunogenicity, inexpensive synthesis, and easy modification but suffer from lower transfection levels. The representation of gene transfer using models offers perspective and interpretation of complex cellular mechanisms,including nonviral gene delivery where exact mechanisms are unknown. Here, we introduce a novel telecommunications model of the nonviral gene delivery process in which the delivery of the gene to a cell is synonymous with delivery of a packet of information to a destination computer within a packet-switched computer network. Such a model uses nodes and layers to simplify the complexity of modeling the transfection process and to overcome several challenges of existing models. These challenges include a limited scope and limited time frame, which often does not incorporate biological effects known to affect transfection. The telecommunication model was constructed in MATLAB to model lipoplex delivery of the gene encoding the green fluorescent protein to HeLa cells. Mitosis and toxicity events were included in the model resulting in simulation outputs of nuclear internalization and transfection efficiency that correlated with experimental data. A priori predictions based on model sensitivity analysis suggest that increasing endosomal escape and decreasing lysosomal degradation, protein degradation, and GFP-induced toxicity can improve transfection efficiency by three-fold. Application of the telecommunications model to nonviral gene delivery offers insight into the development of new gene delivery systems with therapeutically relevant transfection levels.

Multiobjective optimisation of bogie suspension to boost speed on curves

NASA Astrophysics Data System (ADS)

Milad Mousavi-Bideleh, Seyed; Berbyuk, Viktor

2016-01-01

To improve safety and maximum admissible speed on different operational scenarios, multiobjective optimisation of bogie suspension components of a one-car railway vehicle model is considered. The vehicle model has 50 degrees of freedom and is developed in multibody dynamics software SIMPACK. Track shift force, running stability, and risk of derailment are selected as safety objective functions. The improved maximum admissible speeds of the vehicle on curves are determined based on the track plane accelerations up to 1.5 m/s2. To attenuate the number of design parameters for optimisation and improve the computational efficiency, a global sensitivity analysis is accomplished using the multiplicative dimensional reduction method (M-DRM). A multistep optimisation routine based on genetic algorithm (GA) and MATLAB/SIMPACK co-simulation is executed at three levels. The bogie conventional secondary and primary suspension components are chosen as the design parameters in the first two steps, respectively. In the last step semi-active suspension is in focus. The input electrical current to magnetorheological yaw dampers is optimised to guarantee an appropriate safety level. Semi-active controllers are also applied and the respective effects on bogie dynamics are explored. The safety Pareto optimised results are compared with those associated with in-service values. The global sensitivity analysis and multistep approach significantly reduced the number of design parameters and improved the computational efficiency of the optimisation. Furthermore, using the optimised values of design parameters give the possibility to run the vehicle up to 13% faster on curves while a satisfactory safety level is guaranteed. The results obtained can be used in Pareto optimisation and active bogie suspension design problems.

Histostitcher™: An informatics software platform for reconstructing whole-mount prostate histology using the extensible imaging platform framework

PubMed Central

Toth, Robert J.; Shih, Natalie; Tomaszewski, John E.; Feldman, Michael D.; Kutter, Oliver; Yu, Daphne N.; Paulus, John C.; Paladini, Ginaluca; Madabhushi, Anant

2014-01-01

Context: Co-registration of ex-vivo histologic images with pre-operative imaging (e.g., magnetic resonance imaging [MRI]) can be used to align and map disease extent, and to identify quantitative imaging signatures. However, ex-vivo histology images are frequently sectioned into quarters prior to imaging. Aims: This work presents Histostitcher™, a software system designed to create a pseudo whole mount histology section (WMHS) from a stitching of four individual histology quadrant images. Materials and Methods: Histostitcher™ uses user-identified fiducials on the boundary of two quadrants to stitch such quadrants. An original prototype of Histostitcher™ was designed using the Matlab programming languages. However, clinical use was limited due to slow performance, computer memory constraints and an inefficient workflow. The latest version was created using the extensible imaging platform (XIP™) architecture in the C++ programming language. A fast, graphics processor unit renderer was designed to intelligently cache the visible parts of the histology quadrants and the workflow was significantly improved to allow modifying existing fiducials, fast transformations of the quadrants and saving/loading sessions. Results: The new stitching platform yielded significantly more efficient workflow and reconstruction than the previous prototype. It was tested on a traditional desktop computer, a Windows 8 Surface Pro table device and a 27 inch multi-touch display, with little performance difference between the different devices. Conclusions: Histostitcher™ is a fast, efficient framework for reconstructing pseudo WMHS from individually imaged quadrants. The highly modular XIP™ framework was used to develop an intuitive interface and future work will entail mapping the disease extent from the pseudo WMHS onto pre-operative MRI. PMID:24843820

Teaching Computational Geophysics Classes using Active Learning Techniques

NASA Astrophysics Data System (ADS)

Keers, H.; Rondenay, S.; Harlap, Y.; Nordmo, I.

2016-12-01

We give an overview of our experience in teaching two computational geophysics classes at the undergraduate level. In particular we describe The first class is for most students the first programming class and assumes that the students have had an introductory course in geophysics. In this class the students are introduced to basic Matlab skills: use of variables, basic array and matrix definition and manipulation, basic statistics, 1D integration, plotting of lines and surfaces, making of .m files and basic debugging techniques. All of these concepts are applied to elementary but important concepts in earthquake and exploration geophysics (including epicentre location, computation of travel time curves for simple layered media plotting of 1D and 2D velocity models etc.). It is important to integrate the geophysics with the programming concepts: we found that this enhances students' understanding. Moreover, as this is a 3 year Bachelor program, and this class is taught in the 2nd semester, there is little time for a class that focusses on only programming. In the second class, which is optional and can be taken in the 4th or 6th semester, but often is also taken by Master students we extend the Matlab programming to include signal processing and ordinary and partial differential equations, again with emphasis on geophysics (such as ray tracing and solving the acoustic wave equation). This class also contains a project in which the students have to write a brief paper on a topic in computational geophysics, preferably with programming examples. When teaching these classes it was found that active learning techniques, in which the students actively participate in the class, either individually, in pairs or in groups, are indispensable. We give a brief overview of the various activities that we have developed when teaching theses classes.

Application of PSAT to Load Flow Analysis with STATCOM under Load Increase Scenario and Line Contingencies

NASA Astrophysics Data System (ADS)

Telang, Aparna S.; Bedekar, P. P.

2017-09-01

Load flow analysis is the initial and essential step for any power system computation. It is required for choosing better options for power system expansion to meet with ever increasing load demand. Implementation of Flexible AC Transmission System (FACTS) device like STATCOM, in the load flow, which is having fast and very flexible control, is one of the important tasks for power system researchers. This paper presents a simple and systematic approach for steady state power flow calculations with FACTS controller, static synchronous compensator (STATCOM) using command line usage of MATLAB tool-power system analysis toolbox (PSAT). The complexity of MATLAB language programming increases due to incorporation of STATCOM in an existing Newton-Raphson load flow algorithm. Thus, the main contribution of this paper is to show how command line usage of user friendly MATLAB tool, PSAT, can extensively be used for quicker and wider interpretation of the results of load flow with STATCOM. The novelty of this paper lies in the method of applying the load increase pattern, where the active and reactive loads have been changed simultaneously at all the load buses under consideration for creating stressed conditions for load flow analysis with STATCOM. The performance have been evaluated on many standard IEEE test systems and the results for standard IEEE-30 bus system, IEEE-57 bus system, and IEEE-118 bus system are presented.

Pulseq-Graphical Programming Interface: Open source visual environment for prototyping pulse sequences and integrated magnetic resonance imaging algorithm development.

PubMed

Ravi, Keerthi Sravan; Potdar, Sneha; Poojar, Pavan; Reddy, Ashok Kumar; Kroboth, Stefan; Nielsen, Jon-Fredrik; Zaitsev, Maxim; Venkatesan, Ramesh; Geethanath, Sairam

2018-03-11

To provide a single open-source platform for comprehensive MR algorithm development inclusive of simulations, pulse sequence design and deployment, reconstruction, and image analysis. We integrated the "Pulseq" platform for vendor-independent pulse programming with Graphical Programming Interface (GPI), a scientific development environment based on Python. Our integrated platform, Pulseq-GPI, permits sequences to be defined visually and exported to the Pulseq file format for execution on an MR scanner. For comparison, Pulseq files using either MATLAB only ("MATLAB-Pulseq") or Python only ("Python-Pulseq") were generated. We demonstrated three fundamental sequences on a 1.5 T scanner. Execution times of the three variants of implementation were compared on two operating systems. In vitro phantom images indicate equivalence with the vendor supplied implementations and MATLAB-Pulseq. The examples demonstrated in this work illustrate the unifying capability of Pulseq-GPI. The execution times of all the three implementations were fast (a few seconds). The software is capable of user-interface based development and/or command line programming. The tool demonstrated here, Pulseq-GPI, integrates the open-source simulation, reconstruction and analysis capabilities of GPI Lab with the pulse sequence design and deployment features of Pulseq. Current and future work includes providing an ISMRMRD interface and incorporating Specific Absorption Ratio and Peripheral Nerve Stimulation computations. Copyright © 2018 Elsevier Inc. All rights reserved.

[The endpoint detection of cough signal in continuous speech].

PubMed

Yang, Guoqing; Mo, Hongqiang; Li, Wen; Lian, Lianfang; Zheng, Zeguang

2010-06-01

The endpoint detection of cough signal in continuous speech has been researched in order to improve the efficiency and veracity of manual recognition or computer-based automatic recognition. First, using the short time zero crossing ratio(ZCR) for identifying the suspicious coughs and getting the threshold of short time energy based on acoustic characteristics of cough. Then, the short time energy is combined with short time ZCR in order to implement the endpoint detection of cough in continuous speech. To evaluate the effect of the method, first, the virtual number of coughs in each recording was identified by two experienced doctors using the graphical user interface (GUI). Second, the recordings were analyzed by automatic endpoint detection program under Matlab7.0. Finally, the comparison between these two results showed: The error rate of undetected cough is 2.18%, and 98.13% of noise, silence and speech were removed. The way of setting short time energy threshold is robust. The endpoint detection program can remove most speech and noise, thus maintaining a lower rate of error.

Nonlocal Electrostatics in Spherical Geometries Using Eigenfunction Expansions of Boundary-Integral Operators.

PubMed

Bardhan, Jaydeep P; Knepley, Matthew G; Brune, Peter

2015-01-01

In this paper, we present an exact, infinite-series solution to Lorentz nonlocal continuum electrostatics for an arbitrary charge distribution in a spherical solute. Our approach relies on two key steps: (1) re-formulating the PDE problem using boundary-integral equations, and (2) diagonalizing the boundary-integral operators using the fact that their eigenfunctions are the surface spherical harmonics. To introduce this uncommon approach for calculations in separable geometries, we first re-derive Kirkwood's classic results for a protein surrounded concentrically by a pure-water ion-exclusion (Stern) layer and then a dilute electrolyte, which is modeled with the linearized Poisson-Boltzmann equation. The eigenfunction-expansion approach provides a computationally efficient way to test some implications of nonlocal models, including estimating the reasonable range of the nonlocal length-scale parameter λ. Our results suggest that nonlocal solvent response may help to reduce the need for very high dielectric constants in calculating pH-dependent protein behavior, though more sophisticated nonlocal models are needed to resolve this question in full. An open-source MATLAB implementation of our approach is freely available online.

Nonlocal Electrostatics in Spherical Geometries Using Eigenfunction Expansions of Boundary-Integral Operators

PubMed Central

Bardhan, Jaydeep P.; Knepley, Matthew G.; Brune, Peter

2015-01-01

In this paper, we present an exact, infinite-series solution to Lorentz nonlocal continuum electrostatics for an arbitrary charge distribution in a spherical solute. Our approach relies on two key steps: (1) re-formulating the PDE problem using boundary-integral equations, and (2) diagonalizing the boundary-integral operators using the fact that their eigenfunctions are the surface spherical harmonics. To introduce this uncommon approach for calculations in separable geometries, we first re-derive Kirkwood’s classic results for a protein surrounded concentrically by a pure-water ion-exclusion (Stern) layer and then a dilute electrolyte, which is modeled with the linearized Poisson–Boltzmann equation. The eigenfunction-expansion approach provides a computationally efficient way to test some implications of nonlocal models, including estimating the reasonable range of the nonlocal length-scale parameter λ. Our results suggest that nonlocal solvent response may help to reduce the need for very high dielectric constants in calculating pH-dependent protein behavior, though more sophisticated nonlocal models are needed to resolve this question in full. An open-source MATLAB implementation of our approach is freely available online. PMID:26273581

New approach to calculate the true-coincidence effect of HpGe detector

NASA Astrophysics Data System (ADS)

Alnour, I. A.; Wagiran, H.; Ibrahim, N.; Hamzah, S.; Siong, W. B.; Elias, M. S.

2016-01-01

The corrections for true-coincidence effects in HpGe detector are important, especially at low source-to-detector distances. This work established an approach to calculate the true-coincidence effects experimentally for HpGe detectors of type Canberra GC3018 and Ortec GEM25-76-XLB-C, which are in operation at neutron activation analysis lab in Malaysian Nuclear Agency (NM). The correction for true-coincidence effects was performed close to detector at distances 2 and 5 cm using 57Co, 60Co, 133Ba and 137Cs as standard point sources. The correction factors were ranged between 0.93-1.10 at 2 cm and 0.97-1.00 at 5 cm for Canberra HpGe detector; whereas for Ortec HpGe detector ranged between 0.92-1.13 and 0.95-100 at 2 and 5 cm respectively. The change in efficiency calibration curve of the detector at 2 and 5 cm after correction was found to be less than 1%. Moreover, the polynomial parameters functions were simulated through a computer program, MATLAB in order to find an accurate fit to the experimental data points.

A highly detailed FEM volume conductor model based on the ICBM152 average head template for EEG source imaging and TCS targeting.

PubMed

Haufe, Stefan; Huang, Yu; Parra, Lucas C

2015-08-01

In electroencephalographic (EEG) source imaging as well as in transcranial current stimulation (TCS), it is common to model the head using either three-shell boundary element (BEM) or more accurate finite element (FEM) volume conductor models. Since building FEMs is computationally demanding and labor intensive, they are often extensively reused as templates even for subjects with mismatching anatomies. BEMs can in principle be used to efficiently build individual volume conductor models; however, the limiting factor for such individualization are the high acquisition costs of structural magnetic resonance images. Here, we build a highly detailed (0.5mm(3) resolution, 6 tissue type segmentation, 231 electrodes) FEM based on the ICBM152 template, a nonlinear average of 152 adult human heads, which we call ICBM-NY. We show that, through more realistic electrical modeling, our model is similarly accurate as individual BEMs. Moreover, through using an unbiased population average, our model is also more accurate than FEMs built from mismatching individual anatomies. Our model is made available in Matlab format.

Experimental and analytical investigation of inertial propulsion mechanisms and motion simulation of rigid multi-body mechanical systems

NASA Astrophysics Data System (ADS)

Almesallmy, Mohammed

Methodologies are developed for dynamic analysis of mechanical systems with emphasis on inertial propulsion systems. This work adopted the Lagrangian methodology. Lagrangian methodology is the most efficient classical computational technique, which we call Equations of Motion Code (EOMC). The EOMC is applied to several simple dynamic mechanical systems for easier understanding of the method and to aid other investigators in developing equations of motion of any dynamic system. In addition, it is applied to a rigid multibody system, such as Thomson IPS [Thomson 1986]. Furthermore, a simple symbolic algorithm is developed using Maple software, which can be used to convert any nonlinear n-order ordinary differential equation (ODE) systems into 1st-order ODE system in ready format to be used in Matlab software. A side issue, but equally important, we have started corresponding with the U.S. Patent office to persuade them that patent applications, claiming gross linear motion based on inertial propulsion systems should be automatically rejected. The precedent is rejection of patent applications involving perpetual motion machines.

Action change detection in video using a bilateral spatial-temporal constraint

NASA Astrophysics Data System (ADS)

Tian, Jing; Chen, Li

2016-08-01

Action change detection in video aims to detect action discontinuity in video. The silhouettes-based features are desirable for action change detection. This paper studies the problem of silhouette-quality assessment. For that, a non-reference approach without the need for ground truth is proposed in this paper to evaluate the quality of silhouettes, by exploiting both the boundary contrast of the silhouettes in the spatial domain and the consistency of the silhouettes in the temporal domain. This is in contrast to that either only spatial information or only temporal information of silhouettes is exploited in conventional approaches. Experiments are conducted using artificially generated degraded silhouettes to show that the proposed approach outperforms conventional approaches to achieve more accurate quality assessment. Furthermore, experiments are performed to show that the proposed approach is able to improve the accuracy performance of conventional action change approaches in two human action video data-sets. The average runtime of the proposed approach for Weizmann action video data-set is 0.08 second for one frame using Matlab programming language. It is computationally efficient and potential to real-time implementations.

High Power Orbit Transfer Vehicle

DTIC Science & Technology

2003-07-01

multijunction device is a stack of individual single-junction cells in descending order of band gap. The top cell captures the high-energy photons and passes...the rest of the photons on to be absorbed by lower-band-gap cells. Multijunction devices achieve a higher total conversion efficiency because they...minimum temperatures on the thruster modules and main bus. In the MATLAB code for these calculations, maximum and minimum temperatures are plotted

Unconditionally energy stable time stepping scheme for Cahn–Morral equation: Application to multi-component spinodal decomposition and optimal space tiling

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

Tavakoli, Rouhollah, E-mail: rtavakoli@sharif.ir

An unconditionally energy stable time stepping scheme is introduced to solve Cahn–Morral-like equations in the present study. It is constructed based on the combination of David Eyre's time stepping scheme and Schur complement approach. Although the presented method is general and independent of the choice of homogeneous free energy density function term, logarithmic and polynomial energy functions are specifically considered in this paper. The method is applied to study the spinodal decomposition in multi-component systems and optimal space tiling problems. A penalization strategy is developed, in the case of later problem, to avoid trivial solutions. Extensive numerical experiments demonstrate themore » success and performance of the presented method. According to the numerical results, the method is convergent and energy stable, independent of the choice of time stepsize. Its MATLAB implementation is included in the appendix for the numerical evaluation of algorithm and reproduction of the presented results. -- Highlights: •Extension of Eyre's convex–concave splitting scheme to multiphase systems. •Efficient solution of spinodal decomposition in multi-component systems. •Efficient solution of least perimeter periodic space partitioning problem. •Developing a penalization strategy to avoid trivial solutions. •Presentation of MATLAB implementation of the introduced algorithm.« less

General MACOS Interface for Modeling and Analysis for Controlled Optical Systems

NASA Technical Reports Server (NTRS)

Sigrist, Norbert; Basinger, Scott A.; Redding, David C.

2012-01-01

The General MACOS Interface (GMI) for Modeling and Analysis for Controlled Optical Systems (MACOS) enables the use of MATLAB as a front-end for JPL s critical optical modeling package, MACOS. MACOS is JPL s in-house optical modeling software, which has proven to be a superb tool for advanced systems engineering of optical systems. GMI, coupled with MACOS, allows for seamless interfacing with modeling tools from other disciplines to make possible integration of dynamics, structures, and thermal models with the addition of control systems for deformable optics and other actuated optics. This software package is designed as a tool for analysts to quickly and easily use MACOS without needing to be an expert at programming MACOS. The strength of MACOS is its ability to interface with various modeling/development platforms, allowing evaluation of system performance with thermal, mechanical, and optical modeling parameter variations. GMI provides an improved means for accessing selected key MACOS functionalities. The main objective of GMI is to marry the vast mathematical and graphical capabilities of MATLAB with the powerful optical analysis engine of MACOS, thereby providing a useful tool to anyone who can program in MATLAB. GMI also improves modeling efficiency by eliminating the need to write an interface function for each task/project, reducing error sources, speeding up user/modeling tasks, and making MACOS well suited for fast prototyping.

Tutorial: Parallel Computing of Simulation Models for Risk Analysis.

PubMed

Reilly, Allison C; Staid, Andrea; Gao, Michael; Guikema, Seth D

2016-10-01

Simulation models are widely used in risk analysis to study the effects of uncertainties on outcomes of interest in complex problems. Often, these models are computationally complex and time consuming to run. This latter point may be at odds with time-sensitive evaluations or may limit the number of parameters that are considered. In this article, we give an introductory tutorial focused on parallelizing simulation code to better leverage modern computing hardware, enabling risk analysts to better utilize simulation-based methods for quantifying uncertainty in practice. This article is aimed primarily at risk analysts who use simulation methods but do not yet utilize parallelization to decrease the computational burden of these models. The discussion is focused on conceptual aspects of embarrassingly parallel computer code and software considerations. Two complementary examples are shown using the languages MATLAB and R. A brief discussion of hardware considerations is located in the Appendix. © 2016 Society for Risk Analysis.

Overhead Crane Computer Model

NASA Astrophysics Data System (ADS)

Enin, S. S.; Omelchenko, E. Y.; Fomin, N. V.; Beliy, A. V.

2018-03-01

The paper has a description of a computer model of an overhead crane system. The designed overhead crane system consists of hoisting, trolley and crane mechanisms as well as a payload two-axis system. With the help of the differential equation of specified mechanisms movement derived through Lagrange equation of the II kind, it is possible to build an overhead crane computer model. The computer model was obtained using Matlab software. Transients of coordinate, linear speed and motor torque of trolley and crane mechanism systems were simulated. In addition, transients of payload swaying were obtained with respect to the vertical axis. A trajectory of the trolley mechanism with simultaneous operation with the crane mechanism is represented in the paper as well as a two-axis trajectory of payload. The designed computer model of an overhead crane is a great means for studying positioning control and anti-sway control systems.

SU-E-T-37: A GPU-Based Pencil Beam Algorithm for Dose Calculations in Proton Radiation Therapy

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

Kalantzis, G; Leventouri, T; Tachibana, H

Purpose: Recent developments in radiation therapy have been focused on applications of charged particles, especially protons. Over the years several dose calculation methods have been proposed in proton therapy. A common characteristic of all these methods is their extensive computational burden. In the current study we present for the first time, to our best knowledge, a GPU-based PBA for proton dose calculations in Matlab. Methods: In the current study we employed an analytical expression for the protons depth dose distribution. The central-axis term is taken from the broad-beam central-axis depth dose in water modified by an inverse square correction whilemore » the distribution of the off-axis term was considered Gaussian. The serial code was implemented in MATLAB and was launched on a desktop with a quad core Intel Xeon X5550 at 2.67GHz with 8 GB of RAM. For the parallelization on the GPU, the parallel computing toolbox was employed and the code was launched on a GTX 770 with Kepler architecture. The performance comparison was established on the speedup factors. Results: The performance of the GPU code was evaluated for three different energies: low (50 MeV), medium (100 MeV) and high (150 MeV). Four square fields were selected for each energy, and the dose calculations were performed with both the serial and parallel codes for a homogeneous water phantom with size 300×300×300 mm3. The resolution of the PBs was set to 1.0 mm. The maximum speedup of ∼127 was achieved for the highest energy and the largest field size. Conclusion: A GPU-based PB algorithm for proton dose calculations in Matlab was presented. A maximum speedup of ∼127 was achieved. Future directions of the current work include extension of our method for dose calculation in heterogeneous phantoms.« less

Short Project-Based Learning with MATLAB Applications to Support the Learning of Video-Image Processing

NASA Astrophysics Data System (ADS)

Gil, Pablo

2017-10-01

University courses concerning Computer Vision and Image Processing are generally taught using a traditional methodology that is focused on the teacher rather than on the students. This approach is consequently not effective when teachers seek to attain cognitive objectives involving their students' critical thinking. This manuscript covers the development, implementation and assessment of a short project-based engineering course with MATLAB applications Multimedia Engineering being taken by Bachelor's degree students. The principal goal of all course lectures and hands-on laboratory activities was for the students to not only acquire image-specific technical skills but also a general knowledge of data analysis so as to locate phenomena in pixel regions of images and video frames. This would hopefully enable the students to develop skills regarding the implementation of the filters, operators, methods and techniques used for image processing and computer vision software libraries. Our teaching-learning process thus permits the accomplishment of knowledge assimilation, student motivation and skill development through the use of a continuous evaluation strategy to solve practical and real problems by means of short projects designed using MATLAB applications. Project-based learning is not new. This approach has been used in STEM learning in recent decades. But there are many types of projects. The aim of the current study is to analyse the efficacy of short projects as a learning tool when compared to long projects during which the students work with more independence. This work additionally presents the impact of different types of activities, and not only short projects, on students' overall results in this subject. Moreover, a statistical study has allowed the author to suggest a link between the students' success ratio and the type of content covered and activities completed on the course. The results described in this paper show that those students who took part in short projects made a significant improvement when compared to those who participated in long projects.

Automatic analysis (aa): efficient neuroimaging workflows and parallel processing using Matlab and XML.

PubMed

Cusack, Rhodri; Vicente-Grabovetsky, Alejandro; Mitchell, Daniel J; Wild, Conor J; Auer, Tibor; Linke, Annika C; Peelle, Jonathan E

2014-01-01

Recent years have seen neuroimaging data sets becoming richer, with larger cohorts of participants, a greater variety of acquisition techniques, and increasingly complex analyses. These advances have made data analysis pipelines complicated to set up and run (increasing the risk of human error) and time consuming to execute (restricting what analyses are attempted). Here we present an open-source framework, automatic analysis (aa), to address these concerns. Human efficiency is increased by making code modular and reusable, and managing its execution with a processing engine that tracks what has been completed and what needs to be (re)done. Analysis is accelerated by optional parallel processing of independent tasks on cluster or cloud computing resources. A pipeline comprises a series of modules that each perform a specific task. The processing engine keeps track of the data, calculating a map of upstream and downstream dependencies for each module. Existing modules are available for many analysis tasks, such as SPM-based fMRI preprocessing, individual and group level statistics, voxel-based morphometry, tractography, and multi-voxel pattern analyses (MVPA). However, aa also allows for full customization, and encourages efficient management of code: new modules may be written with only a small code overhead. aa has been used by more than 50 researchers in hundreds of neuroimaging studies comprising thousands of subjects. It has been found to be robust, fast, and efficient, for simple-single subject studies up to multimodal pipelines on hundreds of subjects. It is attractive to both novice and experienced users. aa can reduce the amount of time neuroimaging laboratories spend performing analyses and reduce errors, expanding the range of scientific questions it is practical to address.

Binomial tau-leap spatial stochastic simulation algorithm for applications in chemical kinetics.

PubMed

Marquez-Lago, Tatiana T; Burrage, Kevin

2007-09-14

In cell biology, cell signaling pathway problems are often tackled with deterministic temporal models, well mixed stochastic simulators, and/or hybrid methods. But, in fact, three dimensional stochastic spatial modeling of reactions happening inside the cell is needed in order to fully understand these cell signaling pathways. This is because noise effects, low molecular concentrations, and spatial heterogeneity can all affect the cellular dynamics. However, there are ways in which important effects can be accounted without going to the extent of using highly resolved spatial simulators (such as single-particle software), hence reducing the overall computation time significantly. We present a new coarse grained modified version of the next subvolume method that allows the user to consider both diffusion and reaction events in relatively long simulation time spans as compared with the original method and other commonly used fully stochastic computational methods. Benchmarking of the simulation algorithm was performed through comparison with the next subvolume method and well mixed models (MATLAB), as well as stochastic particle reaction and transport simulations (CHEMCELL, Sandia National Laboratories). Additionally, we construct a model based on a set of chemical reactions in the epidermal growth factor receptor pathway. For this particular application and a bistable chemical system example, we analyze and outline the advantages of our presented binomial tau-leap spatial stochastic simulation algorithm, in terms of efficiency and accuracy, in scenarios of both molecular homogeneity and heterogeneity.

Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods

NASA Astrophysics Data System (ADS)

Maximov, Ivan I.; Vinding, Mads S.; Tse, Desmond H. Y.; Nielsen, Niels Chr.; Shah, N. Jon

2015-05-01

There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy. The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community.

Optimal digital filtering for tremor suppression.

PubMed

Gonzalez, J G; Heredia, E A; Rahman, T; Barner, K E; Arce, G R

2000-05-01

Remote manually operated tasks such as those found in teleoperation, virtual reality, or joystick-based computer access, require the generation of an intermediate electrical signal which is transmitted to the controlled subsystem (robot arm, virtual environment, or a cursor in a computer screen). When human movements are distorted, for instance, by tremor, performance can be improved by digitally filtering the intermediate signal before it reaches the controlled device. This paper introduces a novel tremor filtering framework in which digital equalizers are optimally designed through pursuit tracking task experiments. Due to inherent properties of the man-machine system, the design of tremor suppression equalizers presents two serious problems: 1) performance criteria leading to optimizations that minimize mean-squared error are not efficient for tremor elimination and 2) movement signals show ill-conditioned autocorrelation matrices, which often result in useless or unstable solutions. To address these problems, a new performance indicator in the context of tremor is introduced, and the optimal equalizer according to this new criterion is developed. Ill-conditioning of the autocorrelation matrix is overcome using a novel method which we call pulled-optimization. Experiments performed with artificially induced vibrations and a subject with Parkinson's disease show significant improvement in performance. Additional results, along with MATLAB source code of the algorithms, and a customizable demo for PC joysticks, are available on the Internet at http:¿tremor-suppression.com.

Computation of neutron fluxes in clusters of fuel pins arranged in hexagonal assemblies (2D and 3D)

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

Prabha, H.; Marleau, G.

2012-07-01

For computations of fluxes, we have used Carvik's method of collision probabilities. This method requires tracking algorithms. An algorithm to compute tracks (in 2D and 3D) has been developed for seven hexagonal geometries with cluster of fuel pins. This has been implemented in the NXT module of the code DRAGON. The flux distribution in cluster of pins has been computed by using this code. For testing the results, they are compared when possible with the EXCELT module of the code DRAGON. Tracks are plotted in the NXT module by using MATLAB, these plots are also presented here. Results are presentedmore » with increasing number of lines to show the convergence of these results. We have numerically computed volumes, surface areas and the percentage errors in these computations. These results show that 2D results converge faster than 3D results. The accuracy on the computation of fluxes up to second decimal is achieved with fewer lines. (authors)« less

Distributed electromechanical actuation system design for a morphing trailing edge wing

NASA Astrophysics Data System (ADS)

Dimino, I.; Diodati, G.; Concilio, A.; Volovick, A.; Zivan, L.

2016-04-01

Next-generation flight control actuation technology will be based on "more electric" concepts to ensure benefits in terms of efficiency, weight and maintenance. This paper is concerned with the design of an un-shafted distributed servo-electromechanical actuation system, suited for morphing trailing edge wings of large commercial aircraft. It aims at producing small wing camber variations in the range between -5° and +5° in cruise, to enable aerodynamic efficiency improvements. The deployment kinematics is based on multiple "direct-drive" actuation, each made of light-weight compact lever mechanisms, rigidly connected to compliant ribs and sustained by load-bearing motors. Navier-Stokes computations are performed to estimate the pressure distribution over the interested wing region and the resulting hinge moments. These transfer to the primary structure via the driving mechanism. An electro-mechanical Matlab/Simulink model of the distributed actuation architecture is developed and used as a design tool, to preliminary evaluate the complete system performance. Implementing a multi-shaft strategy, each actuator is sized for the torque acting on the respective adaptive rib, following the effect of both the aerodynamic pressure and the morphing skin stiffness. Elastic trailing edge rotations and power needs are evaluated in operative conditions. Focus is finally given to the key challenges of the proposed concept: targeting quantifiable performance improvements while being compliant to the demanding requirements in terms of reliability and safety.

Integrated platform and API for electrophysiological data

PubMed Central

Sobolev, Andrey; Stoewer, Adrian; Leonhardt, Aljoscha; Rautenberg, Philipp L.; Kellner, Christian J.; Garbers, Christian; Wachtler, Thomas

2014-01-01

Recent advancements in technology and methodology have led to growing amounts of increasingly complex neuroscience data recorded from various species, modalities, and levels of study. The rapid data growth has made efficient data access and flexible, machine-readable data annotation a crucial requisite for neuroscientists. Clear and consistent annotation and organization of data is not only an important ingredient for reproducibility of results and re-use of data, but also essential for collaborative research and data sharing. In particular, efficient data management and interoperability requires a unified approach that integrates data and metadata and provides a common way of accessing this information. In this paper we describe GNData, a data management platform for neurophysiological data. GNData provides a storage system based on a data representation that is suitable to organize data and metadata from any electrophysiological experiment, with a functionality exposed via a common application programming interface (API). Data representation and API structure are compatible with existing approaches for data and metadata representation in neurophysiology. The API implementation is based on the Representational State Transfer (REST) pattern, which enables data access integration in software applications and facilitates the development of tools that communicate with the service. Client libraries that interact with the API provide direct data access from computing environments like Matlab or Python, enabling integration of data management into the scientist's experimental or analysis routines. PMID:24795616

AnyWave: a cross-platform and modular software for visualizing and processing electrophysiological signals.

PubMed

Colombet, B; Woodman, M; Badier, J M; Bénar, C G

2015-03-15

The importance of digital signal processing in clinical neurophysiology is growing steadily, involving clinical researchers and methodologists. There is a need for crossing the gap between these communities by providing efficient delivery of newly designed algorithms to end users. We have developed such a tool which both visualizes and processes data and, additionally, acts as a software development platform. AnyWave was designed to run on all common operating systems. It provides access to a variety of data formats and it employs high fidelity visualization techniques. It also allows using external tools as plug-ins, which can be developed in languages including C++, MATLAB and Python. In the current version, plug-ins allow computation of connectivity graphs (non-linear correlation h2) and time-frequency representation (Morlet wavelets). The software is freely available under the LGPL3 license. AnyWave is designed as an open, highly extensible solution, with an architecture that permits rapid delivery of new techniques to end users. We have developed AnyWave software as an efficient neurophysiological data visualizer able to integrate state of the art techniques. AnyWave offers an interface well suited to the needs of clinical research and an architecture designed for integrating new tools. We expect this software to strengthen the collaboration between clinical neurophysiologists and researchers in biomedical engineering and signal processing. Copyright © 2015 Elsevier B.V. All rights reserved.

Integrated platform and API for electrophysiological data.

PubMed

Sobolev, Andrey; Stoewer, Adrian; Leonhardt, Aljoscha; Rautenberg, Philipp L; Kellner, Christian J; Garbers, Christian; Wachtler, Thomas

2014-01-01

Recent advancements in technology and methodology have led to growing amounts of increasingly complex neuroscience data recorded from various species, modalities, and levels of study. The rapid data growth has made efficient data access and flexible, machine-readable data annotation a crucial requisite for neuroscientists. Clear and consistent annotation and organization of data is not only an important ingredient for reproducibility of results and re-use of data, but also essential for collaborative research and data sharing. In particular, efficient data management and interoperability requires a unified approach that integrates data and metadata and provides a common way of accessing this information. In this paper we describe GNData, a data management platform for neurophysiological data. GNData provides a storage system based on a data representation that is suitable to organize data and metadata from any electrophysiological experiment, with a functionality exposed via a common application programming interface (API). Data representation and API structure are compatible with existing approaches for data and metadata representation in neurophysiology. The API implementation is based on the Representational State Transfer (REST) pattern, which enables data access integration in software applications and facilitates the development of tools that communicate with the service. Client libraries that interact with the API provide direct data access from computing environments like Matlab or Python, enabling integration of data management into the scientist's experimental or analysis routines.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Fast Boundary Element Method for acoustics with the Sparse Cardinal Sine Decomposition

NASA Astrophysics Data System (ADS)

Alouges, François; Aussal, Matthieu; Parolin, Emile

2017-07-01

This paper presents the newly proposed method Sparse Cardinal Sine Decomposition that allows fast convolution on unstructured grids. We focus on its use when coupled with finite element techniques to solve acoustic problems with the (compressed) Boundary Element Method. In addition, we also compare the computational performances of two equivalent Matlab® and Python implementations of the method. We show validation test cases in order to assess the precision of the approach. Eventually, the performance of the method is illustrated by the computation of the acoustic target strength of a realistic submarine from the Benchmark Target Strength Simulation international workshop.

Genetic Interaction Score (S-Score) Calculation, Clustering, and Visualization of Genetic Interaction Profiles for Yeast.

PubMed

Roguev, Assen; Ryan, Colm J; Xu, Jiewei; Colson, Isabelle; Hartsuiker, Edgar; Krogan, Nevan

2018-02-01

This protocol describes computational analysis of genetic interaction screens, ranging from data capture (plate imaging) to downstream analyses. Plate imaging approaches using both digital camera and office flatbed scanners are included, along with a protocol for the extraction of colony size measurements from the resulting images. A commonly used genetic interaction scoring method, calculation of the S-score, is discussed. These methods require minimal computer skills, but some familiarity with MATLAB and Linux/Unix is a plus. Finally, an outline for using clustering and visualization software for analysis of resulting data sets is provided. © 2018 Cold Spring Harbor Laboratory Press.

Digital Model of Railway Electric Traction Lines

NASA Astrophysics Data System (ADS)

Garg, Rachana; Mahajan, Priya; Kumar, Parmod

2017-08-01

The characteristic impedance and propagation constant define the behavior of signal propagation over the transmission lines. The digital model for railway traction lines which includes railway tracks is developed, using curve fitting technique in MATLAB. The sensitivity of this model has been computed with respect to frequency. The digital sensitivity values are compared with the values of analog sensitivity. The developed model is useful for digital protection, integrated operation, control and planning of the system.

Light-Field Imaging Toolkit

NASA Astrophysics Data System (ADS)

Bolan, Jeffrey; Hall, Elise; Clifford, Chris; Thurow, Brian

The Light-Field Imaging Toolkit (LFIT) is a collection of MATLAB functions designed to facilitate the rapid processing of raw light field images captured by a plenoptic camera. An included graphical user interface streamlines the necessary post-processing steps associated with plenoptic images. The generation of perspective shifted views and computationally refocused images is supported, in both single image and animated formats. LFIT performs necessary calibration, interpolation, and structuring steps to enable future applications of this technology.

Wide-field Imaging System and Rapid Direction of Optical Zoom (WOZ)

DTIC Science & Technology

2010-09-25

commercial software packages: SolidWorks, COMSOL Multiphysics, and ZEMAX optical design. SolidWorks is a computer aided design package, which as a live...interface to COMSOL. COMSOL is a finite element analysis/partial differential equation solver. ZEMAX is an optical design package. Both COMSOL and... ZEMAX have live interfaces to MatLab. Our initial investigations have enabled a model in SolidWorks to be updated in COMSOL, an FEA calculation

Control Demonstration of a Thin Deformable In-Plane Actuated Mirror

DTIC Science & Technology

2006-03-01

where a four-quadrant electrode grid sitting behind a pre-shaped membrane mirror uses electrostatic forces to deform the surface. Any manufacturing...to receive the Wavescope data due to its MATLAB and Simulink capa- bilities. The dSPACE computer system is stocked with a UART (Universal Asynchronous...cations,” SPIE Smart Structures and Materials Symposium, EAPAD Conference, Vol. 5051-45 (2003). 6. Bennet, H. E. and others, . “Development of

Fluidica CFD software for fluids instruction

NASA Astrophysics Data System (ADS)

Colonius, Tim

2008-11-01

Fluidica is an open-source freely available Matlab graphical user interface (GUI) to to an immersed-boundary Navier- Stokes solver. The algorithm is programmed in Fortran and compiled into Matlab as mex-function. The user can create external flows about arbitrarily complex bodies and collections of free vortices. The code runs fast enough for complex 2D flows to be computed and visualized in real-time on the screen. This facilitates its use in homework and in the classroom for demonstrations of various potential-flow and viscous flow phenomena. The GUI has been written with the goal of allowing the student to learn how to use the software as she goes along. The user can select which quantities are viewed on the screen, including contours of various scalars, velocity vectors, streamlines, particle trajectories, streaklines, and finite-time Lyapunov exponents. In this talk, we demonstrate the software in the context of worked classroom examples demonstrating lift and drag, starting vortices, separation, and vortex dynamics.

ELRIS2D: A MATLAB Package for the 2D Inversion of DC Resistivity/IP Data

NASA Astrophysics Data System (ADS)

Akca, Irfan

2016-04-01

ELRIS2D is an open source code written in MATLAB for the two-dimensional inversion of direct current resistivity (DCR) and time domain induced polarization (IP) data. The user interface of the program is designed for functionality and ease of use. All available settings of the program can be reached from the main window. The subsurface is discre-tized using a hybrid mesh generated by the combination of structured and unstructured meshes, which reduces the computational cost of the whole inversion procedure. The inversion routine is based on the smoothness constrained least squares method. In order to verify the program, responses of two test models and field data sets were inverted. The models inverted from the synthetic data sets are consistent with the original test models in both DC resistivity and IP cases. A field data set acquired in an archaeological site is also used for the verification of outcomes of the program in comparison with the excavation results.

The software-defined fast post-processing for GEM soft x-ray diagnostics in the Tungsten Environment in Steady-state Tokamak thermal fusion reactor

NASA Astrophysics Data System (ADS)

Krawczyk, Rafał Dominik; Czarski, Tomasz; Linczuk, Paweł; Wojeński, Andrzej; Kolasiński, Piotr; GÄ ska, Michał; Chernyshova, Maryna; Mazon, Didier; Jardin, Axel; Malard, Philippe; Poźniak, Krzysztof; Kasprowicz, Grzegorz; Zabołotny, Wojciech; Kowalska-Strzeciwilk, Ewa; Malinowski, Karol

2018-06-01

This article presents a novel software-defined server-based solutions that were introduced in the fast, real-time computation systems for soft X-ray diagnostics for the WEST (Tungsten Environment in Steady-state Tokamak) reactor in Cadarache, France. The objective of the research was to provide a fast processing of data at high throughput and with low latencies for investigating the interplay between the particle transport and magnetohydrodynamic activity. The long-term objective is to implement in the future a fast feedback signal in the reactor control mechanisms to sustain the fusion reaction. The implemented electronic measurement device is anticipated to be deployed in the WEST. A standalone software-defined computation engine was designed to handle data collected at high rates in the server back-end of the system. Signals are obtained from the front-end field-programmable gate array mezzanine cards that acquire and perform a selection from the gas electron multiplier detector. A fast, authorial library for plasma diagnostics was written in C++. It originated from reference offline MATLAB implementations. They were redesigned for runtime analysis during the experiment in the novel online modes of operation. The implementation allowed the benchmarking, evaluation, and optimization of plasma processing algorithms with the possibility to check the consistency with reference computations written in MATLAB. The back-end software and hardware architecture are presented with data evaluation mechanisms. The online modes of operation for the WEST are discussed. The results concerning the performance of the processing and the introduced functionality are presented.

An open architecture for hybrid force-visual servo control of robotic manipulators in unstructured environments

NASA Astrophysics Data System (ADS)

Hassanzadeh, Iraj; Janabi-Sharifi, Farrokh

2005-12-01

In this paper, a new open architecture for visual servo control tasks is illustrated. A Puma-560 robotic manipulator is used to prove the concept. This design enables doing hybrid forcehisual servo control in an unstructured environment in different modes. Also, it can be controlled through Internet in teleoperation mode using a haptic device. Our proposed structure includes two major parts, hardware and software. In terms of hardware, it consists of a master (host) computer, a slave (target) computer, a Puma 560 manipulator, a CCD camera, a force sensor and a haptic device. There are five DAQ cards, interfacing Puma 560 and a slave computer. An open architecture package is developed using Matlab (R), Simulink (R) and XPC target toolbox. This package has the Hardware-In-the-Loop (HIL) property, i.e., enables one to readily implement different configurations of force, visual or hybrid control in real time. The implementation includes the following stages. First of all, retrofitting of puma was carried out. Then a modular joint controller for Puma 560 was realized using Simulink (R). Force sensor driver and force control implementation were written, using sjknction blocks of Simulink (R). Visual images were captured through Image Acquisition Toolbox of Matlab (R), and processed using Image Processing Toolbox. A haptic device interface was also written in Simulink (R). Thus, this setup could be readily reconfigured and accommodate any other robotic manipulator and/or other sensors without the trouble of the external issues relevant to the control, interface and software, while providing flexibility in components modification.

Computer program for analysis of hemodynamic response to head-up tilt test

NASA Astrophysics Data System (ADS)

ŚwiÄ tek, Eliza; Cybulski, Gerard; Koźluk, Edward; PiÄ tkowska, Agnieszka; Niewiadomski, Wiktor

2014-11-01

The aim of this work was to create a computer program, written in the MATLAB environment, which enables the visualization and analysis of hemodynamic parameters recorded during a passive tilt test using the CNS Task Force Monitor System. The application was created to help in the assessment of the relationship between the values and dynamics of changes of the selected parameters and the risk of orthostatic syncope. The signal analysis included: R-R intervals (RRI), heart rate (HR), systolic blood pressure (sBP), diastolic blood pressure (dBP), mean blood pressure (mBP), stroke volume (SV), stroke index (SI), cardiac output (CO), cardiac index (CI), total peripheral resistance (TPR), total peripheral resistance index (TPRI), ventricular ejection time (LVET) and thoracic fluid content (TFC). The program enables the user to visualize waveforms for a selected parameter and to perform smoothing with selected moving average parameters. It allows one to construct the graph of means for any range, and the Poincare plot for a selected time range. The program automatically determines the average value of the parameter before tilt, its minimum and maximum value immediately after changing positions and the times of their occurrence. It is possible to correct the automatically detected points manually. For the RR interval, it determines the acceleration index (AI) and the brake index (BI). It is possible to save calculated values to an XLS with a name specified by user. The application has a user-friendly graphical interface and can run on a computer that has no MATLAB software.

Development of a Mammographic Image Processing Environment Using MATLAB.

DTIC Science & Technology

1994-12-01

S. .° : i. .... ...... Correctness Reliability Efficiency Integrity Usability Figure 1.2 - McCall’s software quality factors [ Pressman , 1987] 1.4...quality factors [ Pressman , 1987] 3-13 Each quality factor itself is related to independent attributes called criteria [Cooper and Fisher, 1979], or...metrics by [ Pressman , 1987], that can be used to judge, define, and measure quality [Cooper and Fisher, 1979]. Figure 3.9 shows the criteria that are used

An Efficient Augmented Lagrangian Method with Applications to Total Variation Minimization

DTIC Science & Technology

2012-08-17

the classic augmented Lagrangian multiplier method, we propose, analyze and test an algorithm for solving a class of equality-constrained non-smooth...method, we propose, analyze and test an algorithm for solving a class of equality-constrained non-smooth optimization problems (chie y but not...significantly outperforming several state-of-the-art solvers on most tested problems. The resulting MATLAB solver, called TVAL3, has been posted online [23]. 2

Application of Analytic Hierarchy Process (AHP) in the analysis of the fuel efficiency in the automobile industry with the utilization of Natural Fiber Polymer Composites (NFPC)

NASA Astrophysics Data System (ADS)

Jayamani, E.; Perera, D. S.; Soon, K. H.; Bakri, M. K. B.

2017-04-01

A systematic method of material analysis aiming for fuel efficiency improvement with the utilization of natural fiber reinforced polymer matrix composites in the automobile industry is proposed. A multi-factor based decision criteria with Analytical Hierarchy Process (AHP) was used and executed through MATLAB to achieve improved fuel efficiency through the weight reduction of vehicular components by effective comparison between two engine hood designs. The reduction was simulated by utilizing natural fiber polymer composites with thermoplastic polypropylene (PP) as the matrix polymer and benchmarked against a synthetic based composite component. Results showed that PP with 35% of flax fiber loading achieved a 0.4% improvement in fuel efficiency, and it was the highest among the 27 candidate fibers.

Optimization of single photon detection model based on GM-APD

NASA Astrophysics Data System (ADS)

Chen, Yu; Yang, Yi; Hao, Peiyu

2017-11-01

One hundred kilometers high precision laser ranging hopes the detector has very strong detection ability for very weak light. At present, Geiger-Mode of Avalanche Photodiode has more use. It has high sensitivity and high photoelectric conversion efficiency. Selecting and designing the detector parameters according to the system index is of great importance to the improvement of photon detection efficiency. Design optimization requires a good model. In this paper, we research the existing Poisson distribution model, and consider the important detector parameters of dark count rate, dead time, quantum efficiency and so on. We improve the optimization of detection model, select the appropriate parameters to achieve optimal photon detection efficiency. The simulation is carried out by using Matlab and compared with the actual test results. The rationality of the model is verified. It has certain reference value in engineering applications.

Design of Excess 3 to BCD code converter using electro-optic effect of Mach-Zehnder Interferometers for efficient data transmission

NASA Astrophysics Data System (ADS)

Kumar, Santosh; Chanderkanta; Amphawan, Angela

2016-04-01

Excess 3 code is one of the most important codes used for efficient data storage and transmission. It is a non-weighted code and also known as self complimenting code. In this paper, a four bit optical Excess 3 to BCD code converter is proposed using electro-optic effect inside lithium-niobate based Mach-Zehnder interferometers (MZIs). The MZI structures have powerful capability to switching an optical input signal to a desired output port. The paper constitutes a mathematical description of the proposed device and thereafter simulation using MATLAB. The study is verified using beam propagation method (BPM).

Real-time visual simulation of APT system based on RTW and Vega

NASA Astrophysics Data System (ADS)

Xiong, Shuai; Fu, Chengyu; Tang, Tao

2012-10-01

The Matlab/Simulink simulation model of APT (acquisition, pointing and tracking) system is analyzed and established. Then the model's C code which can be used for real-time simulation is generated by RTW (Real-Time Workshop). Practical experiments show, the simulation result of running the C code is the same as running the Simulink model directly in the Matlab environment. MultiGen-Vega is a real-time 3D scene simulation software system. With it and OpenGL, the APT scene simulation platform is developed and used to render and display the virtual scenes of the APT system. To add some necessary graphics effects to the virtual scenes real-time, GLSL (OpenGL Shading Language) shaders are used based on programmable GPU. By calling the C code, the scene simulation platform can adjust the system parameters on-line and get APT system's real-time simulation data to drive the scenes. Practical application shows that this visual simulation platform has high efficiency, low charge and good simulation effect.

BOLDSync: a MATLAB-based toolbox for synchronized stimulus presentation in functional MRI.

PubMed

Joshi, Jitesh; Saharan, Sumiti; Mandal, Pravat K

2014-02-15

Precise and synchronized presentation of paradigm stimuli in functional magnetic resonance imaging (fMRI) is central to obtaining accurate information about brain regions involved in a specific task. In this manuscript, we present a new MATLAB-based toolbox, BOLDSync, for synchronized stimulus presentation in fMRI. BOLDSync provides a user friendly platform for design and presentation of visual, audio, as well as multimodal audio-visual (AV) stimuli in functional imaging experiments. We present simulation experiments that demonstrate the millisecond synchronization accuracy of BOLDSync, and also illustrate the functionalities of BOLDSync through application to an AV fMRI study. BOLDSync gains an advantage over other available proprietary and open-source toolboxes by offering a user friendly and accessible interface that affords both precision in stimulus presentation and versatility across various types of stimulus designs and system setups. BOLDSync is a reliable, efficient, and versatile solution for synchronized stimulus presentation in fMRI study. Copyright © 2013 Elsevier B.V. All rights reserved.

A high throughput MATLAB program for automated force-curve processing using the AdG polymer model.

PubMed

O'Connor, Samantha; Gaddis, Rebecca; Anderson, Evan; Camesano, Terri A; Burnham, Nancy A

2015-02-01

Research in understanding biofilm formation is dependent on accurate and representative measurements of the steric forces related to brush on bacterial surfaces. A MATLAB program to analyze force curves from an AFM efficiently, accurately, and with minimal user bias has been developed. The analysis is based on a modified version of the Alexander and de Gennes (AdG) polymer model, which is a function of equilibrium polymer brush length, probe radius, temperature, separation distance, and a density variable. Automating the analysis reduces the amount of time required to process 100 force curves from several days to less than 2min. The use of this program to crop and fit force curves to the AdG model will allow researchers to ensure proper processing of large amounts of experimental data and reduce the time required for analysis and comparison of data, thereby enabling higher quality results in a shorter period of time. Copyright © 2014 Elsevier B.V. All rights reserved.

Fully Automated Sunspot Detection and Classification Using SDO HMI Imagery in MATLAB

DTIC Science & Technology

2014-03-27

FULLY AUTOMATED SUNSPOT DETECTION AND CLASSIFICATION USING SDO HMI IMAGERY IN MATLAB THESIS Gordon M. Spahr, Second Lieutenant, USAF AFIT-ENP-14-M-34...CLASSIFICATION USING SDO HMI IMAGERY IN MATLAB THESIS Presented to the Faculty Department of Engineering Physics Graduate School of Engineering and Management Air...DISTRIUBUTION UNLIMITED. AFIT-ENP-14-M-34 FULLY AUTOMATED SUNSPOT DETECTION AND CLASSIFICATION USING SDO HMI IMAGERY IN MATLAB Gordon M. Spahr, BS Second

Echolocation-Based Foraging by Harbor Porpoises and Sperm Whales, Including Effects on Noise and Acoustic Propagation

DTIC Science & Technology

2008-09-01

Behavioural Point Process Data 234 Appendix B: Matlab Code 258 Matlab Code Used in Chapter 2 (Porpoise Prey Capture Analysis) 258 Click Extraction and...Measurement of Click Properties 258 Envelope-based Click Detector 262 Matlab Code Used in Chapter 3 (Transmission Loss in Porpoise Habitats) ..267...Click Extraction from Data Wavefiles 267 Click Level Determination (Grand Manan Datasets) 270 Click Level Determination (Danish Datasets) 287 Matlab

Flexible missile autopilot design studies with PC-MATLAB/386

NASA Technical Reports Server (NTRS)

Ruth, Michael J.

1989-01-01

Development of a responsive, high-bandwidth missile autopilot for airframes which have structural modes of unusually low frequency presents a challenging design task. Such systems are viable candidates for modern, state-space control design methods. The PC-MATLAB interactive software package provides an environment well-suited to the development of candidate linear control laws for flexible missile autopilots. The strengths of MATLAB include: (1) exceptionally high speed (MATLAB's version for 80386-based PC's offers benchmarks approaching minicomputer and mainframe performance); (2) ability to handle large design models of several hundred degrees of freedom, if necessary; and (3) broad extensibility through user-defined functions. To characterize MATLAB capabilities, a simplified design example is presented. This involves interactive definition of an observer-based state-space compensator for a flexible missile autopilot design task. MATLAB capabilities and limitations, in the context of this design task, are then summarized.

Massively parallel data processing for quantitative total flow imaging with optical coherence microscopy and tomography

NASA Astrophysics Data System (ADS)

Sylwestrzak, Marcin; Szlag, Daniel; Marchand, Paul J.; Kumar, Ashwin S.; Lasser, Theo

2017-08-01

We present an application of massively parallel processing of quantitative flow measurements data acquired using spectral optical coherence microscopy (SOCM). The need for massive signal processing of these particular datasets has been a major hurdle for many applications based on SOCM. In view of this difficulty, we implemented and adapted quantitative total flow estimation algorithms on graphics processing units (GPU) and achieved a 150 fold reduction in processing time when compared to a former CPU implementation. As SOCM constitutes the microscopy counterpart to spectral optical coherence tomography (SOCT), the developed processing procedure can be applied to both imaging modalities. We present the developed DLL library integrated in MATLAB (with an example) and have included the source code for adaptations and future improvements. Catalogue identifier: AFBT_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AFBT_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU GPLv3 No. of lines in distributed program, including test data, etc.: 913552 No. of bytes in distributed program, including test data, etc.: 270876249 Distribution format: tar.gz Programming language: CUDA/C, MATLAB. Computer: Intel x64 CPU, GPU supporting CUDA technology. Operating system: 64-bit Windows 7 Professional. Has the code been vectorized or parallelized?: Yes, CPU code has been vectorized in MATLAB, CUDA code has been parallelized. RAM: Dependent on users parameters, typically between several gigabytes and several tens of gigabytes Classification: 6.5, 18. Nature of problem: Speed up of data processing in optical coherence microscopy Solution method: Utilization of GPU for massively parallel data processing Additional comments: Compiled DLL library with source code and documentation, example of utilization (MATLAB script with raw data) Running time: 1,8 s for one B-scan (150 × faster in comparison to the CPU data processing time)

ImageJ-MATLAB: a bidirectional framework for scientific image analysis interoperability.

PubMed

Hiner, Mark C; Rueden, Curtis T; Eliceiri, Kevin W

2017-02-15

ImageJ-MATLAB is a lightweight Java library facilitating bi-directional interoperability between MATLAB and ImageJ. By defining a standard for translation between matrix and image data structures, researchers are empowered to select the best tool for their image-analysis tasks. Freely available extension to ImageJ2 ( http://imagej.net/Downloads ). Installation and use instructions available at http://imagej.net/MATLAB_Scripting. Tested with ImageJ 2.0.0-rc-54 , Java 1.8.0_66 and MATLAB R2015b. eliceiri@wisc.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

EEGgui: a program used to detect electroencephalogram anomalies after traumatic brain injury.

PubMed

Sick, Justin; Bray, Eric; Bregy, Amade; Dietrich, W Dalton; Bramlett, Helen M; Sick, Thomas

2013-05-21

Identifying and quantifying pathological changes in brain electrical activity is important for investigations of brain injury and neurological disease. An example is the development of epilepsy, a secondary consequence of traumatic brain injury. While certain epileptiform events can be identified visually from electroencephalographic (EEG) or electrocorticographic (ECoG) records, quantification of these pathological events has proved to be more difficult. In this study we developed MATLAB-based software that would assist detection of pathological brain electrical activity following traumatic brain injury (TBI) and present our MATLAB code used for the analysis of the ECoG. Software was developed using MATLAB(™) and features of the open access EEGLAB. EEGgui is a graphical user interface in the MATLAB programming platform that allows scientists who are not proficient in computer programming to perform a number of elaborate analyses on ECoG signals. The different analyses include Power Spectral Density (PSD), Short Time Fourier analysis and Spectral Entropy (SE). ECoG records used for demonstration of this software were derived from rats that had undergone traumatic brain injury one year earlier. The software provided in this report provides a graphical user interface for displaying ECoG activity and calculating normalized power density using fast fourier transform of the major brain wave frequencies (Delta, Theta, Alpha, Beta1, Beta2 and Gamma). The software further detects events in which power density for these frequency bands exceeds normal ECoG by more than 4 standard deviations. We found that epileptic events could be identified and distinguished from a variety of ECoG phenomena associated with normal changes in behavior. We further found that analysis of spectral entropy was less effective in distinguishing epileptic from normal changes in ECoG activity. The software presented here was a successful modification of EEGLAB in the Matlab environment that allows detection of epileptiform ECoG signals in animals after TBI. The code allows import of large EEG or ECoG data records as standard text files and uses fast fourier transform as a basis for detection of abnormal events. The software can also be used to monitor injury-induced changes in spectral entropy if required. We hope that the software will be useful for other investigators in the field of traumatic brain injury and will stimulate future advances of quantitative analysis of brain electrical activity after neurological injury or disease.

Quantifying Similarity and Distance Measures for Vector-Based Datasets: Histograms, Signals, and Probability Distribution Functions

DTIC Science & Technology

2017-02-01

note, a number of different measures implemented in both MATLAB and Python as functions are used to quantify similarity/distance between 2 vector-based...this technical note are widely used and may have an important role when computing the distance and similarity of large datasets and when considering high...throughput processes. In this technical note, a number of different measures implemented in both MAT- LAB and Python as functions are used to

Practical Implementation of Multiple Model Adaptive Estimation Using Neyman-Pearson Based Hypothesis Testing and Spectral Estimation Tools

DTIC Science & Technology

1996-09-01

Generalized Likelihood Ratio (GLR) and voting techniques. The third class consisted of multiple hypothesis filter detectors, specifically the MMAE. The...vector version, versus a tensor if we use the matrix version of the power spectral density estimate. Using this notation, we will derive an...as MATLAB , have an intrinsic sample covariance computation available, which makes this method quite easy to implement. In practice, the mean for the

Pervasive access to MRI bias artifact suppression service on a grid.

PubMed

Ardizzone, Edoardo; Gambino, Orazio; Genco, Alessandro; Pirrone, Roberto; Sorce, Salvatore

2009-01-01

Bias artifact corrupts MRIs in such a way that the image is afflicted by illumination variations. Some of the authors proposed the exponential entropy-driven homomorphic unsharp masking ( E(2)D-HUM) algorithm that corrects this artifact without any a priori hypothesis about the tissues or the MRI modality. Moreover, E(2)D-HUM does not care about the body part under examination and does not require any particular training task. People who want to use this algorithm, which is Matlab-based, have to set their own computers in order to execute it. Furthermore, they have to be Matlab-skilled to exploit all the features of the algorithm. In this paper, we propose to make such algorithm available as a service on a grid infrastructure, so that people can use it almost from everywhere, in a pervasive fashion, by means of a suitable user interface running on smartphones. The proposed solution allows physicians to use the E(2)D-HUM algorithm (or any other kind of algorithm, given that it is available as a service on the grid), being it remotely executed somewhere in the grid, and the results are sent back to the user's device. This way, physicians do not need to be aware of how to use Matlab to process their images. The pervasive service provision for medical image enhancement is presented, along with some experimental results obtained using smartphones connected to an existing Globus-based grid infrastructure.

Fundamentals of Structural Geology

NASA Astrophysics Data System (ADS)

Pollard, David D.; Fletcher, Raymond C.

2005-09-01

Fundamentals of Structural Geology provides a new framework for the investigation of geological structures by integrating field mapping and mechanical analysis. Assuming a basic knowledge of physical geology, introductory calculus and physics, it emphasizes the observational data, modern mapping technology, principles of continuum mechanics, and the mathematical and computational skills, necessary to quantitatively map, describe, model, and explain deformation in Earth's lithosphere. By starting from the fundamental conservation laws of mass and momentum, the constitutive laws of material behavior, and the kinematic relationships for strain and rate of deformation, the authors demonstrate the relevance of solid and fluid mechanics to structural geology. This book offers a modern quantitative approach to structural geology for advanced students and researchers in structural geology and tectonics. It is supported by a website hosting images from the book, additional colour images, student exercises and MATLAB scripts. Solutions to the exercises are available to instructors. The book integrates field mapping using modern technology with the analysis of structures based on a complete mechanics MATLAB is used to visualize physical fields and analytical results and MATLAB scripts can be downloaded from the website to recreate textbook graphics and enable students to explore their choice of parameters and boundary conditions The supplementary website hosts color images of outcrop photographs used in the text, supplementary color images, and images of textbook figures for classroom presentations The textbook website also includes student exercises designed to instill the fundamental relationships, and to encourage the visualization of the evolution of geological structures; solutions are available to instructors

BasinVis 1.0: A MATLAB®-based program for sedimentary basin subsidence analysis and visualization

NASA Astrophysics Data System (ADS)

Lee, Eun Young; Novotny, Johannes; Wagreich, Michael

2016-06-01

Stratigraphic and structural mapping is important to understand the internal structure of sedimentary basins. Subsidence analysis provides significant insights for basin evolution. We designed a new software package to process and visualize stratigraphic setting and subsidence evolution of sedimentary basins from well data. BasinVis 1.0 is implemented in MATLAB®, a multi-paradigm numerical computing environment, and employs two numerical methods: interpolation and subsidence analysis. Five different interpolation methods (linear, natural, cubic spline, Kriging, and thin-plate spline) are provided in this program for surface modeling. The subsidence analysis consists of decompaction and backstripping techniques. BasinVis 1.0 incorporates five main processing steps; (1) setup (study area and stratigraphic units), (2) loading well data, (3) stratigraphic setting visualization, (4) subsidence parameter input, and (5) subsidence analysis and visualization. For in-depth analysis, our software provides cross-section and dip-slip fault backstripping tools. The graphical user interface guides users through the workflow and provides tools to analyze and export the results. Interpolation and subsidence results are cached to minimize redundant computations and improve the interactivity of the program. All 2D and 3D visualizations are created by using MATLAB plotting functions, which enables users to fine-tune the results using the full range of available plot options in MATLAB. We demonstrate all functions in a case study of Miocene sediment in the central Vienna Basin.

A Computational Intelligence (CI) Approach to the Precision Mars Lander Problem

NASA Technical Reports Server (NTRS)

Birge, Brian; Walberg, Gerald

2002-01-01

A Mars precision landing requires a landed footprint of no more than 100 meters. Obstacles to reducing the landed footprint include trajectory dispersions due to initial atmospheric entry conditions such as entry angle, parachute deployment height, environment parameters such as wind, atmospheric density, parachute deployment dynamics, unavoidable injection error or propagated error from launch, etc. Computational Intelligence (CI) techniques such as Artificial Neural Nets and Particle Swarm Optimization have been shown to have great success with other control problems. The research period extended previous work on investigating applicability of the computational intelligent approaches. The focus of this investigation was on Particle Swarm Optimization and basic Neural Net architectures. The research investigating these issues was performed for the grant cycle from 5/15/01 to 5/15/02. Matlab 5.1 and 6.0 along with NASA's POST were the primary computational tools.

Likelihood Ratio Test Polarimetric SAR Ship Detection Application

DTIC Science & Technology

2005-12-01

menu. Under the Matlab menu, the user can export an area of an image to the MatlabTM MAT file format, as well as call RGB image and Pauli...must specify various parameters such as the area of the image to analyze. Export Image Area to MatlabTM (PoIGASP & COASP) Generates a MatlabTM file...represented by the Minister of National Defence, 2005 (0 Sa majest6 la reine, repr(sent(e par le ministre de la Defense nationale, 2005 Abstract This

ANNIT - An Efficient Inversion Algorithm based on Prediction Principles

NASA Astrophysics Data System (ADS)

Růžek, B.; Kolář, P.

2009-04-01

Solution of inverse problems represents meaningful job in geophysics. The amount of data is continuously increasing, methods of modeling are being improved and the computer facilities are also advancing great technical progress. Therefore the development of new and efficient algorithms and computer codes for both forward and inverse modeling is still up to date. ANNIT is contributing to this stream since it is a tool for efficient solution of a set of non-linear equations. Typical geophysical problems are based on parametric approach. The system is characterized by a vector of parameters p, the response of the system is characterized by a vector of data d. The forward problem is usually represented by unique mapping F(p)=d. The inverse problem is much more complex and the inverse mapping p=G(d) is available in an analytical or closed form only exceptionally and generally it may not exist at all. Technically, both forward and inverse mapping F and G are sets of non-linear equations. ANNIT solves such situation as follows: (i) joint subspaces {pD, pM} of original data and model spaces D, M, resp. are searched for, within which the forward mapping F is sufficiently smooth that the inverse mapping G does exist, (ii) numerical approximation of G in subspaces {pD, pM} is found, (iii) candidate solution is predicted by using this numerical approximation. ANNIT is working in an iterative way in cycles. The subspaces {pD, pM} are searched for by generating suitable populations of individuals (models) covering data and model spaces. The approximation of the inverse mapping is made by using three methods: (a) linear regression, (b) Radial Basis Function Network technique, (c) linear prediction (also known as "Kriging"). The ANNIT algorithm has built in also an archive of already evaluated models. Archive models are re-used in a suitable way and thus the number of forward evaluations is minimized. ANNIT is now implemented both in MATLAB and SCILAB. Numerical tests show good performance of the algorithm. Both versions and documentation are available on Internet and anybody can download them. The goal of this presentation is to offer the algorithm and computer codes for anybody interested in the solution to inverse problems.

A MacCormack-TVD finite difference method to simulate the mass flow in mountainous terrain with variable computational domain

NASA Astrophysics Data System (ADS)

Ouyang, Chaojun; He, Siming; Xu, Qiang; Luo, Yu; Zhang, Wencheng

2013-03-01

A two-dimensional mountainous mass flow dynamic procedure solver (Massflow-2D) using the MacCormack-TVD finite difference scheme is proposed. The solver is implemented in Matlab on structured meshes with variable computational domain. To verify the model, a variety of numerical test scenarios, namely, the classical one-dimensional and two-dimensional dam break, the landslide in Hong Kong in 1993 and the Nora debris flow in the Italian Alps in 2000, are executed, and the model outputs are compared with published results. It is established that the model predictions agree well with both the analytical solution as well as the field observations.

COSMIC monthly progress report

NASA Technical Reports Server (NTRS)

1994-01-01

Activities of the Computer Software Management and Information Center (COSMIC) are summarized for the month of April 1994. Tables showing the current inventory of programs available from COSMIC are presented and program processing and evaluation activities are summarized. Five articles were prepared for publication in the NASA Tech Brief Journal. These articles (included in this report) describe the following software items: GAP 1.0 - Groove Analysis Program, Version 1.0; SUBTRANS - Subband/Transform MATLAB Functions for Image Processing; CSDM - COLD-SAT Dynamic Model; CASRE - Computer Aided Software Reliability Estimation; and XOPPS - OEL Project Planner/Scheduler Tool. Activities in the areas of marketing, customer service, benefits identification, maintenance and support, and disseminations are also described along with a budget summary.

An Efficient, Noniterative Method of Identifying the Cost-Effectiveness Frontier.

PubMed

Suen, Sze-chuan; Goldhaber-Fiebert, Jeremy D

2016-01-01

Cost-effectiveness analysis aims to identify treatments and policies that maximize benefits subject to resource constraints. However, the conventional process of identifying the efficient frontier (i.e., the set of potentially cost-effective options) can be algorithmically inefficient, especially when considering a policy problem with many alternative options or when performing an extensive suite of sensitivity analyses for which the efficient frontier must be found for each. Here, we describe an alternative one-pass algorithm that is conceptually simple, easier to implement, and potentially faster for situations that challenge the conventional approach. Our algorithm accomplishes this by exploiting the relationship between the net monetary benefit and the cost-effectiveness plane. To facilitate further evaluation and use of this approach, we also provide scripts in R and Matlab that implement our method and can be used to identify efficient frontiers for any decision problem. © The Author(s) 2015.

An Efficient, Non-iterative Method of Identifying the Cost-Effectiveness Frontier

PubMed Central

Suen, Sze-chuan; Goldhaber-Fiebert, Jeremy D.

2015-01-01

Cost-effectiveness analysis aims to identify treatments and policies that maximize benefits subject to resource constraints. However, the conventional process of identifying the efficient frontier (i.e., the set of potentially cost-effective options) can be algorithmically inefficient, especially when considering a policy problem with many alternative options or when performing an extensive suite of sensitivity analyses for which the efficient frontier must be found for each. Here, we describe an alternative one-pass algorithm that is conceptually simple, easier to implement, and potentially faster for situations that challenge the conventional approach. Our algorithm accomplishes this by exploiting the relationship between the net monetary benefit and the cost-effectiveness plane. To facilitate further evaluation and use of this approach, we additionally provide scripts in R and Matlab that implement our method and can be used to identify efficient frontiers for any decision problem. PMID:25926282

Computation of thermodynamic equilibrium in systems under stress

NASA Astrophysics Data System (ADS)

Vrijmoed, Johannes C.; Podladchikov, Yuri Y.

2016-04-01

Metamorphic reactions may be partly controlled by the local stress distribution as suggested by observations of phase assemblages around garnet inclusions related to an amphibolite shear zone in granulite of the Bergen Arcs in Norway. A particular example presented in fig. 14 of Mukai et al. [1] is discussed here. A garnet crystal embedded in a plagioclase matrix is replaced on the left side by a high pressure intergrowth of kyanite and quartz and on the right side by chlorite-amphibole. This texture apparently represents disequilibrium. In this case, the minerals adapt to the low pressure ambient conditions only where fluids were present. Alternatively, here we compute that this particular low pressure and high pressure assemblage around a stressed rigid inclusion such as garnet can coexist in equilibrium. To do the computations we developed the Thermolab software package. The core of the software package consists of Matlab functions that generate Gibbs energy of minerals and melts from the Holland and Powell database [2] and aqueous species from the SUPCRT92 database [3]. Most up to date solid solutions are included in a general formulation. The user provides a Matlab script to do the desired calculations using the core functions. Gibbs energy of all minerals, solutions and species are benchmarked versus THERMOCALC, PerpleX [4] and SUPCRT92 and are reproduced within round off computer error. Multi-component phase diagrams have been calculated using Gibbs minimization to benchmark with THERMOCALC and Perple_X. The Matlab script to compute equilibrium in a stressed system needs only two modifications of the standard phase diagram script. Firstly, Gibbs energy of phases considered in the calculation is generated for multiple values of thermodynamic pressure. Secondly, for the Gibbs minimization the proportion of the system at each particular thermodynamic pressure needs to be constrained. The user decides which part of the stress tensor is input as thermodynamic pressure. To compute a case of high and low pressure around a stressed inclusion we first did a Finite Element Method calculation of a rigid inclusion in a viscous matrix under simple shear. From the computed stress distribution we took the local pressure (mean stress) in each grid point of the FEM calculation. This was used as input thermodynamic pressure in the Gibbs minimization and the result showed it is possible to have an equilibrium situation in which chlorite-amphibole is stable in the low pressure domain and kyanite in the high pressure domain of the stress field around the inclusion. Interestingly, the calculation predicts the redistribution of fluid from an average content of fluid in the system. The fluid in equilibrium tends to accumulate in the low pressure areas whereas it leaves the high pressure areas dry. Transport of fluid components occurs not necessarily by fluid flow, but may happen for example by diffusion. We conclude that an apparent disequilibrium texture may be explained by equilibrium under pressure variations, and apparent fluid addition by redistribution of fluid controlled by the local stress distribution. [1] Mukai et al. (2014), Journal of Petrology, 55 (8), p. 1457-1477. [2] Holland and Powell (1998), Journal of Metamorphic Geology, 16, p. 309-343 [3] Johnson et al. (1992), Computers & Geosciences, 18 (7), p. 899-947 [4] Connolly (2005), Earth and Planetary Science Letters, 236, p. 524-541

Generalized Preconditioned Locally Harmonic Residual Eigensolver (GPLHR) v0.1

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

VECHARYNSKI, EUGENE; YANG, CHAO

The software contains a MATLAB implementation of the Generalized Preconditioned Locally Harmonic Residual (GPLHR) method for solving standard and generalized non-Hermitian eigenproblems. The method is particularly useful for computing a subset of eigenvalues, and their eigen- or Schur vectors, closest to a given shift. The proposed method is based on block iterations and can take advantage of a preconditioner if it is available. It does not need to perform exact shift-and-invert transformation. Standard and generalized eigenproblems are handled in a unified framework.

Understanding and Mitigating Vortex-Dominated, Tip-Leakage and End-Wall Losses in a Transonic Splittered Rotor Stage

DTIC Science & Technology

2015-04-23

blade geometry parameters the TPL design 9   tool was initiated by running the MATLAB script (*.m) Main_SpeedLine_Auto. Main_SpeedLine_Auto...SolidWorks for solid model generation of the blade shapes. Computational Analysis With solid models generated of the gas -path air wedge, automated...287 mm (11.3 in) Constrained by existing TCR geometry Number of Passages 12 None A blade tip-down design approach was used. The outputs of the

Bayesian Estimation of Reliability Burr Type XII Under Al-Bayyatis’ Suggest Loss Function with Numerical Solution

NASA Astrophysics Data System (ADS)

Mohammed, Amal A.; Abraheem, Sudad K.; Fezaa Al-Obedy, Nadia J.

2018-05-01

In this paper is considered with Burr type XII distribution. The maximum likelihood, Bayes methods of estimation are used for estimating the unknown scale parameter (α). Al-Bayyatis’ loss function and suggest loss function are used to find the reliability with the least loss. So the reliability function is expanded in terms of a set of power function. For this performance, the Matlab (ver.9) is used in computations and some examples are given.

Classifying Infrastructure in an Urban Battlespace Using Thermal IR Signatures

DTIC Science & Technology

2006-11-01

Huntsville, Alabama for sharing their ATLAS data for Atlanta. REFERENCES Bentz , D . P . (2000). A Computer Model to Predict the Surface Temperature...10: 2 2 xt α Δ Δ ≤ (10) 2.2 Implementing the Model Bentz uses a 1- D finite difference grid with a varying number of nodes. The nodes are equally...and rooftops were modeled as a function of time and environmental conditions using 1- D heat transfer theory. The model was implemented in MATLAB

Mathematical Formulation used by MATLAB Code to Convert FTIR Interferograms to Calibrated Spectra

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

Armstrong, Derek Elswick

This report discusses the mathematical procedures used to convert raw interferograms from Fourier transform infrared (FTIR) sensors to calibrated spectra. The work discussed in this report was completed as part of the Helios project at Los Alamos National Laboratory. MATLAB code was developed to convert the raw interferograms to calibrated spectra. The report summarizes the developed MATLAB scripts and functions, along with a description of the mathematical methods used by the code. The first step in working with raw interferograms is to convert them to uncalibrated spectra by applying an apodization function to the raw data and then by performingmore » a Fourier transform. The developed MATLAB code also addresses phase error correction by applying the Mertz method. This report provides documentation for the MATLAB scripts.« less

A Comparison of LBG and ADPCM Speech Compression Techniques

NASA Astrophysics Data System (ADS)

Bachu, Rajesh G.; Patel, Jignasa; Barkana, Buket D.

Speech compression is the technology of converting human speech into an efficiently encoded representation that can later be decoded to produce a close approximation of the original signal. In all speech there is a degree of predictability and speech coding techniques exploit this to reduce bit rates yet still maintain a suitable level of quality. This paper is a study and implementation of Linde-Buzo-Gray Algorithm (LBG) and Adaptive Differential Pulse Code Modulation (ADPCM) algorithms to compress speech signals. In here we implemented the methods using MATLAB 7.0. The methods we used in this study gave good results and performance in compressing the speech and listening tests showed that efficient and high quality coding is achieved.

VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

PubMed

Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

2016-01-01

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level.

QPSO-Based Adaptive DNA Computing Algorithm

PubMed Central

Karakose, Mehmet; Cigdem, Ugur

2013-01-01

DNA (deoxyribonucleic acid) computing that is a new computation model based on DNA molecules for information storage has been increasingly used for optimization and data analysis in recent years. However, DNA computing algorithm has some limitations in terms of convergence speed, adaptability, and effectiveness. In this paper, a new approach for improvement of DNA computing is proposed. This new approach aims to perform DNA computing algorithm with adaptive parameters towards the desired goal using quantum-behaved particle swarm optimization (QPSO). Some contributions provided by the proposed QPSO based on adaptive DNA computing algorithm are as follows: (1) parameters of population size, crossover rate, maximum number of operations, enzyme and virus mutation rate, and fitness function of DNA computing algorithm are simultaneously tuned for adaptive process, (2) adaptive algorithm is performed using QPSO algorithm for goal-driven progress, faster operation, and flexibility in data, and (3) numerical realization of DNA computing algorithm with proposed approach is implemented in system identification. Two experiments with different systems were carried out to evaluate the performance of the proposed approach with comparative results. Experimental results obtained with Matlab and FPGA demonstrate ability to provide effective optimization, considerable convergence speed, and high accuracy according to DNA computing algorithm. PMID:23935409

Fast semivariogram computation using FPGA architectures

NASA Astrophysics Data System (ADS)

Lagadapati, Yamuna; Shirvaikar, Mukul; Dong, Xuanliang

2015-02-01

The semivariogram is a statistical measure of the spatial distribution of data and is based on Markov Random Fields (MRFs). Semivariogram analysis is a computationally intensive algorithm that has typically seen applications in the geosciences and remote sensing areas. Recently, applications in the area of medical imaging have been investigated, resulting in the need for efficient real time implementation of the algorithm. The semivariogram is a plot of semivariances for different lag distances between pixels. A semi-variance, γ(h), is defined as the half of the expected squared differences of pixel values between any two data locations with a lag distance of h. Due to the need to examine each pair of pixels in the image or sub-image being processed, the base algorithm complexity for an image window with n pixels is O(n2). Field Programmable Gate Arrays (FPGAs) are an attractive solution for such demanding applications due to their parallel processing capability. FPGAs also tend to operate at relatively modest clock rates measured in a few hundreds of megahertz, but they can perform tens of thousands of calculations per clock cycle while operating in the low range of power. This paper presents a technique for the fast computation of the semivariogram using two custom FPGA architectures. The design consists of several modules dedicated to the constituent computational tasks. A modular architecture approach is chosen to allow for replication of processing units. This allows for high throughput due to concurrent processing of pixel pairs. The current implementation is focused on isotropic semivariogram computations only. Anisotropic semivariogram implementation is anticipated to be an extension of the current architecture, ostensibly based on refinements to the current modules. The algorithm is benchmarked using VHDL on a Xilinx XUPV5-LX110T development Kit, which utilizes the Virtex5 FPGA. Medical image data from MRI scans are utilized for the experiments. Computational speedup is measured with respect to Matlab implementation on a personal computer with an Intel i7 multi-core processor. Preliminary simulation results indicate that a significant advantage in speed can be attained by the architectures, making the algorithm viable for implementation in medical devices

Comparative Analysis of Reduced-Rule Compressed Fuzzy Logic Control and Incremental Conductance MPPT Methods

NASA Astrophysics Data System (ADS)

Kandemir, Ekrem; Borekci, Selim; Cetin, Numan S.

2018-04-01

Photovoltaic (PV) power generation has been widely used in recent years, with techniques for increasing the power efficiency representing one of the most important issues. The available maximum power of a PV panel is dependent on environmental conditions such as solar irradiance and temperature. To extract the maximum available power from a PV panel, various maximum-power-point tracking (MPPT) methods are used. In this work, two different MPPT methods were implemented for a 150-W PV panel. The first method, known as incremental conductance (Inc. Cond.) MPPT, determines the maximum power by measuring the derivative of the PV voltage and current. The other method is based on reduced-rule compressed fuzzy logic control (RR-FLC), using which it is relatively easier to determine the maximum power because a single input variable is used to reduce computing loads. In this study, a 150-W PV panel system model was realized using these MPPT methods in MATLAB and the results compared. According to the simulation results, the proposed RR-FLC-based MPPT could increase the response rate and tracking accuracy by 4.66% under standard test conditions.

A Locally Modal B-Spline Based Full-Vector Finite-Element Method with PML for Nonlinear and Lossy Plasmonic Waveguide

NASA Astrophysics Data System (ADS)

Karimi, Hossein; Nikmehr, Saeid; Khodapanah, Ehsan

2016-09-01

In this paper, we develop a B-spline finite-element method (FEM) based on a locally modal wave propagation with anisotropic perfectly matched layers (PMLs), for the first time, to simulate nonlinear and lossy plasmonic waveguides. Conventional approaches like beam propagation method, inherently omit the wave spectrum and do not provide physical insight into nonlinear modes especially in the plasmonic applications, where nonlinear modes are constructed by linear modes with very close propagation constant quantities. Our locally modal B-spline finite element method (LMBS-FEM) does not suffer from the weakness of the conventional approaches. To validate our method, first, propagation of wave for various kinds of linear, nonlinear, lossless and lossy materials of metal-insulator plasmonic structures are simulated using LMBS-FEM in MATLAB and the comparisons are made with FEM-BPM module of COMSOL Multiphysics simulator and B-spline finite-element finite-difference wide angle beam propagation method (BSFEFD-WABPM). The comparisons show that not only our developed numerical approach is computationally more accurate and efficient than conventional approaches but also it provides physical insight into the nonlinear nature of the propagation modes.

Reliable fuzzy H∞ control for active suspension of in-wheel motor driven electric vehicles with dynamic damping

NASA Astrophysics Data System (ADS)

Shao, Xinxin; Naghdy, Fazel; Du, Haiping

2017-03-01

A fault-tolerant fuzzy H∞ control design approach for active suspension of in-wheel motor driven electric vehicles in the presence of sprung mass variation, actuator faults and control input constraints is proposed. The controller is designed based on the quarter-car active suspension model with a dynamic-damping-in-wheel-motor-driven-system, in which the suspended motor is operated as a dynamic absorber. The Takagi-Sugeno (T-S) fuzzy model is used to model this suspension with possible sprung mass variation. The parallel-distributed compensation (PDC) scheme is deployed to derive a fault-tolerant fuzzy controller for the T-S fuzzy suspension model. In order to reduce the motor wear caused by the dynamic force transmitted to the in-wheel motor, the dynamic force is taken as an additional controlled output besides the traditional optimization objectives such as sprung mass acceleration, suspension deflection and actuator saturation. The H∞ performance of the proposed controller is derived as linear matrix inequalities (LMIs) comprising three equality constraints which are solved efficiently by means of MATLAB LMI Toolbox. The proposed controller is applied to an electric vehicle suspension and its effectiveness is demonstrated through computer simulation.

New approach to calculate the true-coincidence effect of HpGe detector

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

Alnour, I. A., E-mail: aaibrahim3@live.utm.my, E-mail: ibrahim.elnour@yahoo.com; Wagiran, H.; Ibrahim, N.

The corrections for true-coincidence effects in HpGe detector are important, especially at low source-to-detector distances. This work established an approach to calculate the true-coincidence effects experimentally for HpGe detectors of type Canberra GC3018 and Ortec GEM25-76-XLB-C, which are in operation at neutron activation analysis lab in Malaysian Nuclear Agency (NM). The correction for true-coincidence effects was performed close to detector at distances 2 and 5 cm using {sup 57}Co, {sup 60}Co, {sup 133}Ba and {sup 137}Cs as standard point sources. The correction factors were ranged between 0.93-1.10 at 2 cm and 0.97-1.00 at 5 cm for Canberra HpGe detector; whereas for Ortec HpGemore » detector ranged between 0.92-1.13 and 0.95-100 at 2 and 5 cm respectively. The change in efficiency calibration curve of the detector at 2 and 5 cm after correction was found to be less than 1%. Moreover, the polynomial parameters functions were simulated through a computer program, MATLAB in order to find an accurate fit to the experimental data points.« less

SIRF: Simultaneous Satellite Image Registration and Fusion in a Unified Framework.

PubMed

Chen, Chen; Li, Yeqing; Liu, Wei; Huang, Junzhou

2015-11-01

In this paper, we propose a novel method for image fusion with a high-resolution panchromatic image and a low-resolution multispectral (Ms) image at the same geographical location. The fusion is formulated as a convex optimization problem which minimizes a linear combination of a least-squares fitting term and a dynamic gradient sparsity regularizer. The former is to preserve accurate spectral information of the Ms image, while the latter is to keep sharp edges of the high-resolution panchromatic image. We further propose to simultaneously register the two images during the fusing process, which is naturally achieved by virtue of the dynamic gradient sparsity property. An efficient algorithm is then devised to solve the optimization problem, accomplishing a linear computational complexity in the size of the output image in each iteration. We compare our method against six state-of-the-art image fusion methods on Ms image data sets from four satellites. Extensive experimental results demonstrate that the proposed method substantially outperforms the others in terms of both spatial and spectral qualities. We also show that our method can provide high-quality products from coarsely registered real-world IKONOS data sets. Finally, a MATLAB implementation is provided to facilitate future research.

SAD-Based Stereo Vision Machine on a System-on-Programmable-Chip (SoPC)

PubMed Central

Zhang, Xiang; Chen, Zhangwei

2013-01-01

This paper, proposes a novel solution for a stereo vision machine based on the System-on-Programmable-Chip (SoPC) architecture. The SOPC technology provides great convenience for accessing many hardware devices such as DDRII, SSRAM, Flash, etc., by IP reuse. The system hardware is implemented in a single FPGA chip involving a 32-bit Nios II microprocessor, which is a configurable soft IP core in charge of managing the image buffer and users' configuration data. The Sum of Absolute Differences (SAD) algorithm is used for dense disparity map computation. The circuits of the algorithmic module are modeled by the Matlab-based DSP Builder. With a set of configuration interfaces, the machine can process many different sizes of stereo pair images. The maximum image size is up to 512 K pixels. This machine is designed to focus on real time stereo vision applications. The stereo vision machine offers good performance and high efficiency in real time. Considering a hardware FPGA clock of 90 MHz, 23 frames of 640 × 480 disparity maps can be obtained in one second with 5 × 5 matching window and maximum 64 disparity pixels. PMID:23459385

Use of CellNetAnalyzer in biotechnology and metabolic engineering.

PubMed

von Kamp, Axel; Thiele, Sven; Hädicke, Oliver; Klamt, Steffen

2017-11-10

Mathematical models of the cellular metabolism have become an essential tool for the optimization of biotechnological processes. They help to obtain a systemic understanding of the metabolic processes in the used microorganisms and to find suitable genetic modifications maximizing the production performance. In particular, methods of stoichiometric and constraint-based modeling are frequently used in the context of metabolic and bioprocess engineering. Since metabolic networks can be complex and comprise hundreds or even thousands of metabolites and reactions, dedicated software tools are required for an efficient analysis. One such software suite is CellNetAnalyzer, a MATLAB package providing, among others, various methods for analyzing stoichiometric and constraint-based metabolic models. CellNetAnalyzer can be used via command-line based operations or via a graphical user interface with embedded network visualizations. Herein we will present key functionalities of CellNetAnalyzer for applications in biotechnology and metabolic engineering and thereby review constraint-based modeling techniques such as metabolic flux analysis, flux balance analysis, flux variability analysis, metabolic pathway analysis (elementary flux modes) and methods for computational strain design. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Conceptual design of a high-speed electromagnetic switch for a modified flux-coupling-type SFCL and its application in renewable energy system.

PubMed

Chen, Lei; Chen, Hongkun; Yang, Jun; Shu, Zhengyu; He, Huiwen; Shu, Xin

2016-01-01

The modified flux-coupling-type superconducting fault current (SFCL) is a high-efficient electrical auxiliary device, whose basic function is to suppress the short-circuit current by controlling the magnetic path through a high-speed switch. In this paper, the high-speed switch is based on electromagnetic repulsion mechanism, and its conceptual design is carried out to promote the application of the modified SFCL. Regarding that the switch which is consisting of a mobile copper disc, two fixed opening and closing coils, the computational method for the electromagnetic force is discussed, and also the dynamic mathematical model including circuit equation, magnetic field equation as well as mechanical motion equation is theoretically deduced. According to the mathematical modeling and calculation of characteristic parameters, a feasible design scheme is presented, and the high-speed switch's response time can be less than 0.5 ms. For that the modified SFCL is equipped with this high-speed switch, the SFCL's application in a 10 kV micro-grid system with multiple renewable energy sources are assessed in the MATLAB software. The simulations are well able to affirm the SFCL's performance behaviors.

Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods.

PubMed

Maximov, Ivan I; Vinding, Mads S; Tse, Desmond H Y; Nielsen, Niels Chr; Shah, N Jon

2015-05-01

There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy. The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community. Copyright © 2015 Elsevier Inc. All rights reserved.

A method for discrimination of noise and EMG signal regions recorded during rhythmic behaviors.

PubMed

Ying, Rex; Wall, Christine E

2016-12-08

Analyses of muscular activity during rhythmic behaviors provide critical data for biomechanical studies. Electrical potentials measured from muscles using electromyography (EMG) require discrimination of noise regions as the first step in analysis. An experienced analyst can accurately identify the onset and offset of EMG but this process takes hours to analyze a short (10-15s) record of rhythmic EMG bursts. Existing computational techniques reduce this time but have limitations. These include a universal threshold for delimiting noise regions (i.e., a single signal value for identifying the EMG signal onset and offset), pre-processing using wide time intervals that dampen sensitivity for EMG signal characteristics, poor performance when a low frequency component (e.g., DC offset) is present, and high computational complexity leading to lack of time efficiency. We present a new statistical method and MATLAB script (EMG-Extractor) that includes an adaptive algorithm to discriminate noise regions from EMG that avoids these limitations and allows for multi-channel datasets to be processed. We evaluate the EMG-Extractor with EMG data on mammalian jaw-adductor muscles during mastication, a rhythmic behavior typified by low amplitude onsets/offsets and complex signal pattern. The EMG-Extractor consistently and accurately distinguishes noise from EMG in a manner similar to that of an experienced analyst. It outputs the raw EMG signal region in a form ready for further analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Investigating ion recombination effects in a liquid-filled ionization chamber array used for IMRT QA measurements

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

Knill, Cory, E-mail: knillcor@gmail.com; Snyder, Michael; Rakowski, Joseph T.

Purpose: PTW’s Octavius 1000 SRS array performs IMRT quality assurance (QA) measurements with liquid-filled ionization chambers (LICs) to allow closer detector spacing and higher resolution, compared to air-filled QA devices. However, reduced ion mobility in LICs relative to air leads to increased ion recombination effects and reduced collection efficiencies that are dependent on Linac pulse frequency and pulse dose. These pulse parameters are variable during an IMRT delivery, which affects QA results. In this study, (1) 1000 SRS collection efficiencies were measured as a function of pulse frequency and pulse dose, (2) two methods were developed to correct changes inmore » collection efficiencies during IMRT QA measurements, and the effects of these corrections on QA pass rates were compared. Methods: To obtain collection efficiencies, the OCTAVIUS 1000 SRS was used to measure open fields of varying pulse frequency, pulse dose, and beam energy with results normalized to air-filled chamber measurements. Changes in ratios of 1000 SRS to chamber measured dose were attributed to changing collection efficiencies, which were then correlated to pulse parameters using regression analysis. The usefulness of the derived corrections was then evaluated using 6 MV and 10FFF SBRT RapidArc plans delivered to the OCTAVIUS 4D system using a TrueBeam (Varian Medical Systems) linear accelerator equipped with a high definition multileaf collimator. For the first correction, MATLAB software was developed that calculates pulse frequency and pulse dose for each detector, using measurement and DICOM RT Plan files. Pulse information is converted to collection efficiency, and measurements are corrected by multiplying detector dose by ratios of calibration to measured collection efficiencies. For the second correction the MU/min in the daily 1000 SRS calibration was chosen to match the average MU/min of the volumetric modulated arc therapy plan. Effects of the two corrections on QA results were examined by performing 3D gamma analysis comparing predicted to measured dose, with and without corrections. Results: Collection efficiencies correlated linearly to pulse dose, while correlations with pulse frequency were less defined, generally increasing as pulse frequency decreased. After complex MATLAB corrections, average 3D gamma pass rates improved by [0.07%,0.40%,1.17%] for 6 MV and [0.29%,1.40%,4.57%] for 10FFF using [3%/3 mm,2%/2 mm,1%/1 mm] criteria. Maximum changes in gamma pass rates were [0.43%,1.63%,3.05%] for 6 MV and [1.00%,4.80%,11.2%] for 10FFF using [3%/3 mm,2%/2 mm,1%/1 mm] criteria. On average, pass rates of simple daily calibration corrections were within 1% of complex MATLAB corrections. Conclusions: OCTAVIUS 1000 SRS ion recombination effects have little effect on 6 MV measurements. However, the effect could potentially be clinically significant for higher pulse dose unflattened beams when using tighter gamma tolerances, especially when small aperture sizes are used, as is common for SRS/SBRT. In addition, ion recombination effects are strongly correlated to changing MU/min, therefore MU/min used in daily 1000 SRS calibrations should be matched to the expected average MU/min of the IMRT plan.« less

SU-F-R-18: Updates to the Computational Environment for Radiological Research for Image Analysis

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

Apte, Aditya P.; Deasy, Joseph O.

2016-06-15

Purpose: To present new tools in CERR for Texture Analysis and Visualization. Method: (1) Quantitative Image Analysis: We added the ability to compute Haralick texture features based on local neighbourhood. The Texture features depend on many parameters used in their derivation. For example: (a) directionality, (b) quantization of image, (c) patch-size for the neighborhood, (d) handling of the edge voxels within the region of interest, (e) Averaging co-occurance matrix vs texture features for different directions etc. A graphical user interface was built to set these parameters and then visualize their impact on the resulting texture maps. The entire functionality wasmore » written in Matlab. Array indexing was used to speed up the texture calculation. The computation speed is very competitive with the ITK library. Moreover, our implementation works with multiple CPUs and the computation time can be further reduced by using multiple processor threads. In order to reduce the Haralick texture maps into scalar features, we propose the use of Texture Volume Histograms. This lets users make use of the entire distribution of texture values within the region of interest rather than using just the mean and the standard deviations. (2) Qualitative/Visualization tools: The derived texture maps are stored as a new scan (derived) within CERR’s planC data structure. A display that compares various scans was built to show the raw image and the derived texture maps side-by-side. These images are positionally linked and can be navigated together. CERR’s graphics handling was updated and sped-up to be compatible with the newer Matlab versions. As a result, the users can use (a) different window levels and colormaps for different viewports, (b) click-and-drag or use mouse scroll-wheel to navigate slices. Results: The new features and updates are available via https://www.github.com/adityaapte/cerr . Conclusion: Features added to CERR increase its utility in Radiomics and Outcomes modeling.« less

Theoretical Efficiency of 3rd Generation Solar Cells: Comparison between Carrier Multiplication and Down-Conversion

DTIC Science & Technology

2012-01-01

rewrite this equation using a generalization of Eq. (6), for a given multiplicity mrM : ym Z 1 mEg E2dE eE=kTS1 Z 1 Eg E2dE eE=kTS1 ð13Þ Note that...vectorized quadrature algorithms . We used the quadgk function in Matlab to evaluate all function, since it is best at handling the pole at EqV¼0 in the

Rapid Generation of Large Dimension Photon Sieve Designs

NASA Technical Reports Server (NTRS)

Hariharan, Shravan; Fitzpatrick, Sean; Kim, Hyun Jung; Julian, Matthew; Sun, Wenbo; Tedjojuwono, Ken; MacDonnell, David

2017-01-01

A photon sieve is a revolutionary optical instrument that provides high resolution imaging at a fraction of the weight of typical telescopes (areal density of 0.3 kg/m2 compared to 25 kg/m2 for the James Webb Space Telescope). The photon sieve is a variation of a Fresnel Zone Plate consisting of many small holes spread out in a ring-like pattern, which focuses light of a specific wavelength by diffraction. The team at NASA Langley Research Center has produced a variety of small photon sieves for testing. However, it is necessary to increase both the scale and rate of production, as a single sieve previously took multiple weeks to design and fabricate. This report details the different methods used in producing photon sieve designs in two file formats: CIF and DXF. The difference between these methods, and the two file formats were compared, to determine the most efficient design process. Finally, a step-by-step sieve design and fabrication process was described. The design files can be generated in both formats using an editing tool such as Microsoft Excel. However, an approach using a MATLAB program reduced the computing time of the designs and increased the ability of the user to generate large photon sieve designs. Although the CIF generation process was deemed the most efficient, the design techniques for both file types have been proven to generate complete photon sieves that can be used for scientific applications

Multi-Scale Peak and Trough Detection Optimised for Periodic and Quasi-Periodic Neuroscience Data.

PubMed

Bishop, Steven M; Ercole, Ari

2018-01-01

The reliable detection of peaks and troughs in physiological signals is essential to many investigative techniques in medicine and computational biology. Analysis of the intracranial pressure (ICP) waveform is a particular challenge due to multi-scale features, a changing morphology over time and signal-to-noise limitations. Here we present an efficient peak and trough detection algorithm that extends the scalogram approach of Scholkmann et al., and results in greatly improved algorithm runtime performance. Our improved algorithm (modified Scholkmann) was developed and analysed in MATLAB R2015b. Synthesised waveforms (periodic, quasi-periodic and chirp sinusoids) were degraded with white Gaussian noise to achieve signal-to-noise ratios down to 5 dB and were used to compare the performance of the original Scholkmann and modified Scholkmann algorithms. The modified Scholkmann algorithm has false-positive (0%) and false-negative (0%) detection rates identical to the original Scholkmann when applied to our test suite. Actual compute time for a 200-run Monte Carlo simulation over a multicomponent noisy test signal was 40.96 ± 0.020 s (mean ± 95%CI) for the original Scholkmann and 1.81 ± 0.003 s (mean ± 95%CI) for the modified Scholkmann, demonstrating the expected improvement in runtime complexity from [Formula: see text] to [Formula: see text]. The accurate interpretation of waveform data to identify peaks and troughs is crucial in signal parameterisation, feature extraction and waveform identification tasks. Modification of a standard scalogram technique has produced a robust algorithm with linear computational complexity that is particularly suited to the challenges presented by large, noisy physiological datasets. The algorithm is optimised through a single parameter and can identify sub-waveform features with minimal additional overhead, and is easily adapted to run in real time on commodity hardware.

A preliminary study of in-house Monte Carlo simulations: an integrated Monte Carlo verification system.

PubMed

Mukumoto, Nobutaka; Tsujii, Katsutomo; Saito, Susumu; Yasunaga, Masayoshi; Takegawa, Hideki; Yamamoto, Tokihiro; Numasaki, Hodaka; Teshima, Teruki

2009-10-01

To develop an infrastructure for the integrated Monte Carlo verification system (MCVS) to verify the accuracy of conventional dose calculations, which often fail to accurately predict dose distributions, mainly due to inhomogeneities in the patient's anatomy, for example, in lung and bone. The MCVS consists of the graphical user interface (GUI) based on a computational environment for radiotherapy research (CERR) with MATLAB language. The MCVS GUI acts as an interface between the MCVS and a commercial treatment planning system to import the treatment plan, create MC input files, and analyze MC output dose files. The MCVS consists of the EGSnrc MC codes, which include EGSnrc/BEAMnrc to simulate the treatment head and EGSnrc/DOSXYZnrc to calculate the dose distributions in the patient/phantom. In order to improve computation time without approximations, an in-house cluster system was constructed. The phase-space data of a 6-MV photon beam from a Varian Clinac unit was developed and used to establish several benchmarks under homogeneous conditions. The MC results agreed with the ionization chamber measurements to within 1%. The MCVS GUI could import and display the radiotherapy treatment plan created by the MC method and various treatment planning systems, such as RTOG and DICOM-RT formats. Dose distributions could be analyzed by using dose profiles and dose volume histograms and compared on the same platform. With the cluster system, calculation time was improved in line with the increase in the number of central processing units (CPUs) at a computation efficiency of more than 98%. Development of the MCVS was successful for performing MC simulations and analyzing dose distributions.

High-Fidelity Real-Time Trajectory Optimization for Reusable Launch Vehicles

DTIC Science & Technology

2006-12-01

6.20 Max DR Yawing Moment History. ...............................................................270 Figure 6.21 Snapshot from MATLAB “Profile...Propagation using “ode45” (Euler Angles)...........................................330 Figure 6.114 Interpolated Elevon Controls using Various MATLAB ...Schemes.................332 Figure 6.115 Interpolated Flap Controls using Various MATLAB Schemes.....................333 Figure 6.116 Interpolated

A Matlab/Simulink-Based Interactive Module for Servo Systems Learning

ERIC Educational Resources Information Center

Aliane, N.

2010-01-01

This paper presents an interactive module for learning both the fundamental and practical issues of servo systems. This module, developed using Simulink in conjunction with the Matlab graphical user interface (Matlab-GUI) tool, is used to supplement conventional lectures in control engineering and robotics subjects. First, the paper introduces the…

Study of Lead as a Source X-ray Radiation Protection with an Analysis Grey Level Image

NASA Astrophysics Data System (ADS)

Susilo; Rahma, I. N.; Mosik; Masturi

2017-04-01

X-ray utilization in the medical field still has a potential danger for the human. This occurs when exposure to x-ray radiation received exceeds the dose limit value. It required a radiation shielding to prevent the hazard, and lead is one of the metals usually used as x-ray radiation shield. This work aims to determine the metallic lead properties to find out of the step wedge lead radiograph image. The instruments used are the plane x-ray, digital radiography system and personal computer installed by MATLAB, while the material is step wedge lead. The image of radiograph was analysed using GUI applications on MATLAB software to determine the values of grey level from the image and the optical density of the radiograph image. The results showed the greater optical density, the higher the image contrast, and the value of optical density in the image is inversely proportional to the voltage x-ray since the value of grey level at high voltage is smaller than that of at low voltage.

Robust Correlation Analyses: False Positive and Power Validation Using a New Open Source Matlab Toolbox

PubMed Central

Pernet, Cyril R.; Wilcox, Rand; Rousselet, Guillaume A.

2012-01-01

Pearson’s correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab(R) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand. PMID:23335907

Robust correlation analyses: false positive and power validation using a new open source matlab toolbox.

PubMed

Pernet, Cyril R; Wilcox, Rand; Rousselet, Guillaume A

2012-01-01

Pearson's correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab((R)) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand.

Diagnosis of Lung Cancer by Fractal Analysis of Damaged DNA

PubMed Central

Namazi, Hamidreza; Kiminezhadmalaie, Mona

2015-01-01

Cancer starts when cells in a part of the body start to grow out of control. In fact cells become cancer cells because of DNA damage. A DNA walk of a genome represents how the frequency of each nucleotide of a pairing nucleotide couple changes locally. In this research in order to study the cancer genes, DNA walk plots of genomes of patients with lung cancer were generated using a program written in MATLAB language. The data so obtained was checked for fractal property by computing the fractal dimension using a program written in MATLAB. Also, the correlation of damaged DNA was studied using the Hurst exponent measure. We have found that the damaged DNA sequences are exhibiting higher degree of fractality and less correlation compared with normal DNA sequences. So we confirmed this method can be used for early detection of lung cancer. The method introduced in this research not only is useful for diagnosis of lung cancer but also can be applied for detection and growth analysis of different types of cancers. PMID:26539245

How to get students to love (or not hate) MATLAB and programming

NASA Astrophysics Data System (ADS)

Reckinger, Shanon; Reckinger, Scott

2014-11-01

An effective programming course geared toward engineering students requires the utilization of modern teaching philosophies. A newly designed course that focuses on programming in MATLAB involves flipping the classroom and integrating various active teaching techniques. Vital aspects of the new course design include: lengthening in-class contact hours, Process-Oriented Guided Inquiry Learning (POGIL) method worksheets (self-guided instruction), student created video content posted on YouTube, clicker questions (used in class to practice reading and debugging code), programming exams that don't require computers, integrating oral exams into the classroom, fostering an environment for formal and informal peer learning, and designing in a broader theme to tie together assignments. However, possibly the most important piece to this programming course puzzle: the instructor needs to be able to find programming mistakes very fast and then lead individuals and groups through the steps to find their mistakes themselves. The effectiveness of the new course design is demonstrated through pre- and post- concept exam results and student evaluation feedback. Students reported that the course was challenging and required a lot of effort, but left largely positive feedback.

Pareto Design of State Feedback Tracking Control of a Biped Robot via Multiobjective PSO in Comparison with Sigma Method and Genetic Algorithms: Modified NSGAII and MATLAB's Toolbox

PubMed Central

Mahmoodabadi, M. J.; Taherkhorsandi, M.; Bagheri, A.

2014-01-01

An optimal robust state feedback tracking controller is introduced to control a biped robot. In the literature, the parameters of the controller are usually determined by a tedious trial and error process. To eliminate this process and design the parameters of the proposed controller, the multiobjective evolutionary algorithms, that is, the proposed method, modified NSGAII, Sigma method, and MATLAB's Toolbox MOGA, are employed in this study. Among the used evolutionary optimization algorithms to design the controller for biped robots, the proposed method operates better in the aspect of designing the controller since it provides ample opportunities for designers to choose the most appropriate point based upon the design criteria. Three points are chosen from the nondominated solutions of the obtained Pareto front based on two conflicting objective functions, that is, the normalized summation of angle errors and normalized summation of control effort. Obtained results elucidate the efficiency of the proposed controller in order to control a biped robot. PMID:24616619

Weight optimization of plane truss using genetic algorithm

NASA Astrophysics Data System (ADS)

Neeraja, D.; Kamireddy, Thejesh; Santosh Kumar, Potnuru; Simha Reddy, Vijay

2017-11-01

Optimization of structure on basis of weight has many practical benefits in every engineering field. The efficiency is proportionally related to its weight and hence weight optimization gains prime importance. Considering the field of civil engineering, weight optimized structural elements are economical and easier to transport to the site. In this study, genetic optimization algorithm for weight optimization of steel truss considering its shape, size and topology aspects has been developed in MATLAB. Material strength and Buckling stability have been adopted from IS 800-2007 code of construction steel. The constraints considered in the present study are fabrication, basic nodes, displacements, and compatibility. Genetic programming is a natural selection search technique intended to combine good solutions to a problem from many generations to improve the results. All solutions are generated randomly and represented individually by a binary string with similarities of natural chromosomes, and hence it is termed as genetic programming. The outcome of the study is a MATLAB program, which can optimise a steel truss and display the optimised topology along with element shapes, deflections, and stress results.

An Effective Construction Method of Modular Manipulator 3D Virtual Simulation Platform

NASA Astrophysics Data System (ADS)

Li, Xianhua; Lv, Lei; Sheng, Rui; Sun, Qing; Zhang, Leigang

2018-06-01

This work discusses about a fast and efficient method of constructing an open 3D manipulator virtual simulation platform which make it easier for teachers and students to learn about positive and inverse kinematics of a robot manipulator. The method was carried out using MATLAB. In which, the Robotics Toolbox, MATLAB GUI and 3D animation with the help of modelling using SolidWorks, were fully applied to produce a good visualization of the system. The advantages of using quickly build is its powerful function of the input and output and its ability to simulate a 3D manipulator realistically. In this article, a Schunk six DOF modular manipulator was constructed by the author's research group to be used as example. The implementation steps of this method was detailed described, and thereafter, a high-level open and realistic visualization manipulator 3D virtual simulation platform was achieved. With the graphs obtained from simulation, the test results show that the manipulator 3D virtual simulation platform can be constructed quickly with good usability and high maneuverability, and it can meet the needs of scientific research and teaching.

DAFNE: A Matlab toolbox for Bayesian multi-source remote sensing and ancillary data fusion, with application to flood mapping

NASA Astrophysics Data System (ADS)

D'Addabbo, Annarita; Refice, Alberto; Lovergine, Francesco P.; Pasquariello, Guido

2018-03-01

High-resolution, remotely sensed images of the Earth surface have been proven to be of help in producing detailed flood maps, thanks to their synoptic overview of the flooded area and frequent revisits. However, flood scenarios can be complex situations, requiring the integration of different data in order to provide accurate and robust flood information. Several processing approaches have been recently proposed to efficiently combine and integrate heterogeneous information sources. In this paper, we introduce DAFNE, a Matlab®-based, open source toolbox, conceived to produce flood maps from remotely sensed and other ancillary information, through a data fusion approach. DAFNE is based on Bayesian Networks, and is composed of several independent modules, each one performing a different task. Multi-temporal and multi-sensor data can be easily handled, with the possibility of following the evolution of an event through multi-temporal output flood maps. Each DAFNE module can be easily modified or upgraded to meet different user needs. The DAFNE suite is presented together with an example of its application.

MATLAB implementation of a dynamic clamp with bandwidth >125 KHz capable of generating INa at 37°C

PubMed Central

Clausen, Chris; Valiunas, Virginijus; Brink, Peter R.; Cohen, Ira S.

2012-01-01

We describe the construction of a dynamic clamp with bandwidth >125 KHz that utilizes a high performance, yet low cost, standard home/office PC interfaced with a high-speed (16 bit) data acquisition module. High bandwidth is achieved by exploiting recently available software advances (code-generation technology, optimized real-time kernel). Dynamic-clamp programs are constructed using Simulink, a visual programming language. Blocks for computation of membrane currents are written in the high-level matlab language; no programming in C is required. The instrument can be used in single- or dual-cell configurations, with the capability to modify programs while experiments are in progress. We describe an algorithm for computing the fast transient Na+ current (INa) in real time, and test its accuracy and stability using rate constants appropriate for 37°C. We then construct a program capable of supplying three currents to a cell preparation: INa, the hyperpolarizing-activated inward pacemaker current (If), and an inward-rectifier K+ current (IK1). The program corrects for the IR drop due to electrode current flow, and also records all voltages and currents. We tested this program on dual patch-clamped HEK293 cells where the dynamic clamp controls a current-clamp amplifier and a voltage-clamp amplifier controls membrane potential, and current-clamped HEK293 cells where the dynamic clamp produces spontaneous pacing behavior exhibiting Na+ spikes in otherwise passive cells. PMID:23224681

gPKPDSim: a SimBiology®-based GUI application for PKPD modeling in drug development.

PubMed

Hosseini, Iraj; Gajjala, Anita; Bumbaca Yadav, Daniela; Sukumaran, Siddharth; Ramanujan, Saroja; Paxson, Ricardo; Gadkar, Kapil

2018-04-01

Modeling and simulation (M&S) is increasingly used in drug development to characterize pharmacokinetic-pharmacodynamic (PKPD) relationships and support various efforts such as target feasibility assessment, molecule selection, human PK projection, and preclinical and clinical dose and schedule determination. While model development typically require mathematical modeling expertise, model exploration and simulations could in many cases be performed by scientists in various disciplines to support the design, analysis and interpretation of experimental studies. To this end, we have developed a versatile graphical user interface (GUI) application to enable easy use of any model constructed in SimBiology ® to execute various common PKPD analyses. The MATLAB ® -based GUI application, called gPKPDSim, has a single screen interface and provides functionalities including simulation, data fitting (parameter estimation), population simulation (exploring the impact of parameter variability on the outputs of interest), and non-compartmental PK analysis. Further, gPKPDSim is a user-friendly tool with capabilities including interactive visualization, exporting of results and generation of presentation-ready figures. gPKPDSim was designed primarily for use in preclinical and translational drug development, although broader applications exist. gPKPDSim is a MATLAB ® -based open-source application and is publicly available to download from MATLAB ® Central™. We illustrate the use and features of gPKPDSim using multiple PKPD models to demonstrate the wide applications of this tool in pharmaceutical sciences. Overall, gPKPDSim provides an integrated, multi-purpose user-friendly GUI application to enable efficient use of PKPD models by scientists from various disciplines, regardless of their modeling expertise.

Comparison of cyclic correlation algorithm implemented in matlab and python

NASA Astrophysics Data System (ADS)

Carr, Richard; Whitney, James

Simulation is a necessary step for all engineering projects. Simulation gives the engineers an approximation of how their devices will perform under different circumstances, without hav-ing to build, or before building a physical prototype. This is especially true for space bound devices, i.e., space communication systems, where the impact of system malfunction or failure is several orders of magnitude over that of terrestrial applications. Therefore having a reliable simulation tool is key in developing these devices and systems. Math Works Matrix Laboratory (MATLAB) is a matrix based software used by scientists and engineers to solve problems and perform complex simulations. MATLAB has a number of applications in a wide variety of fields which include communications, signal processing, image processing, mathematics, eco-nomics and physics. Because of its many uses MATLAB has become the preferred software for many engineers; it is also very expensive, especially for students and startups. One alternative to MATLAB is Python. The Python is a powerful, easy to use, open source programming environment that can be used to perform many of the same functions as MATLAB. Python programming environment has been steadily gaining popularity in niche programming circles. While there are not as many function included in the software as MATLAB, there are many open source functions that have been developed that are available to be downloaded for free. This paper illustrates how Python can implement the cyclic correlation algorithm and com-pares the results to the cyclic correlation algorithm implemented in the MATLAB environment. Some of the characteristics to be compared are the accuracy and precision of the results, and the length of the programs. The paper will demonstrate that Python is capable of performing simulations of complex algorithms such cyclic correlation.

On computing the geoelastic response to a disk load

NASA Astrophysics Data System (ADS)

Bevis, M.; Melini, D.; Spada, G.

2016-06-01

We review the theory of the Earth's elastic and gravitational response to a surface disk load. The solutions for displacement of the surface and the geoid are developed using expansions of Legendre polynomials, their derivatives and the load Love numbers. We provide a MATLAB function called diskload that computes the solutions for both uncompensated and compensated disk loads. In order to numerically implement the Legendre expansions, it is necessary to choose a harmonic degree, nmax, at which to truncate the series used to construct the solutions. We present a rule of thumb (ROT) for choosing an appropriate value of nmax, describe the consequences of truncating the expansions prematurely and provide a means to judiciously violate the ROT when that becomes a practical necessity.

Modeling and minimizing interference from corneal birefringence in retinal birefringence scanning for foveal fixation detection

PubMed Central

Irsch, Kristina; Gramatikov, Boris; Wu, Yi-Kai; Guyton, David

2011-01-01

Utilizing the measured corneal birefringence from a data set of 150 eyes of 75 human subjects, an algorithm and related computer program, based on Müller-Stokes matrix calculus, were developed in MATLAB for assessing the influence of corneal birefringence on retinal birefringence scanning (RBS) and for converging upon an optical/mechanical design using wave plates (“wave-plate-enhanced RBS”) that allows foveal fixation detection essentially independently of corneal birefringence. The RBS computer model, and in particular the optimization algorithm, were verified with experimental human data using an available monocular RBS-based eye fixation monitor. Fixation detection using wave-plate-enhanced RBS is adaptable to less cooperative subjects, including young children at risk for developing amblyopia. PMID:21750772

Effect of intra-aortic balloon pump on coronary blood flow during different balloon cycles support: A computer study.

PubMed

Aye, Thin Pa Pa; Htet, Zwe Lin; Singhavilai, Thamvarit; Naiyanetr, Phornphop

2015-01-01

Intra-aortic balloon pump (IABP) has been used in clinical treatment as a mechanical circulatory support device for patients with heart failure. A computer model is used to study the effect on coronary blood flow (CBF) with different balloon cycles under both normal and pathological conditions. The model of cardiovascular and IABP is developed by using MATLAB SIMULINK. The effect on coronary blood flow has been studied under both normal and pathological conditions using different balloon cycles (balloon off; 1:4; 1:2; 1:1). A pathological heart is implemented by reducing the left ventricular contractility. The result of this study shows that the rate of balloon cycles is related to the level of coronary blood flow.

MOCCASIN: converting MATLAB ODE models to SBML.

PubMed

Gómez, Harold F; Hucka, Michael; Keating, Sarah M; Nudelman, German; Iber, Dagmar; Sealfon, Stuart C

2016-06-15

MATLAB is popular in biological research for creating and simulating models that use ordinary differential equations (ODEs). However, sharing or using these models outside of MATLAB is often problematic. A community standard such as Systems Biology Markup Language (SBML) can serve as a neutral exchange format, but translating models from MATLAB to SBML can be challenging-especially for legacy models not written with translation in mind. We developed MOCCASIN (Model ODE Converter for Creating Automated SBML INteroperability) to help. MOCCASIN can convert ODE-based MATLAB models of biochemical reaction networks into the SBML format. MOCCASIN is available under the terms of the LGPL 2.1 license (http://www.gnu.org/licenses/lgpl-2.1.html). Source code, binaries and test cases can be freely obtained from https://github.com/sbmlteam/moccasin : mhucka@caltech.edu More information is available at https://github.com/sbmlteam/moccasin. © The Author 2016. Published by Oxford University Press.

Role of Gist and PHOG Features in Computer-Aided Diagnosis of Tuberculosis without Segmentation

PubMed Central

Chauhan, Arun; Chauhan, Devesh; Rout, Chittaranjan

2014-01-01

Purpose Effective diagnosis of tuberculosis (TB) relies on accurate interpretation of radiological patterns found in a chest radiograph (CXR). Lack of skilled radiologists and other resources, especially in developing countries, hinders its efficient diagnosis. Computer-aided diagnosis (CAD) methods provide second opinion to the radiologists for their findings and thereby assist in better diagnosis of cancer and other diseases including TB. However, existing CAD methods for TB are based on the extraction of textural features from manually or semi-automatically segmented CXRs. These methods are prone to errors and cannot be implemented in X-ray machines for automated classification. Methods Gabor, Gist, histogram of oriented gradients (HOG), and pyramid histogram of oriented gradients (PHOG) features extracted from the whole image can be implemented into existing X-ray machines to discriminate between TB and non-TB CXRs in an automated manner. Localized features were extracted for the above methods using various parameters, such as frequency range, blocks and region of interest. The performance of these features was evaluated against textural features. Two digital CXR image datasets (8-bit DA and 14-bit DB) were used for evaluating the performance of these features. Results Gist (accuracy 94.2% for DA, 86.0% for DB) and PHOG (accuracy 92.3% for DA, 92.0% for DB) features provided better results for both the datasets. These features were implemented to develop a MATLAB toolbox, TB-Xpredict, which is freely available for academic use at http://sourceforge.net/projects/tbxpredict/. This toolbox provides both automated training and prediction modules and does not require expertise in image processing for operation. Conclusion Since the features used in TB-Xpredict do not require segmentation, the toolbox can easily be implemented in X-ray machines. This toolbox can effectively be used for the mass screening of TB in high-burden areas with improved efficiency. PMID:25390291

Kinematic analysis of the finger exoskeleton using MATLAB/Simulink.

PubMed

Nasiłowski, Krzysztof; Awrejcewicz, Jan; Lewandowski, Donat

2014-01-01

A paralyzed and not fully functional part of human body can be supported by the properly designed exoskeleton system with motoric abilities. It can help in rehabilitation, or movement of a disabled/paralyzed limb. Both suitably selected geometry and specialized software are studied applying the MATLAB environment. A finger exoskeleton was the base for MATLAB/Simulink model. Specialized software, such as MATLAB/Simulink give us an opportunity to optimize calculation reaching precise results, which help in next steps of design process. The calculations carried out yield information regarding movement relation between three functionally connected actuators and showed distance and velocity changes during the whole simulation time.

The Realization of Drilling Fault Diagnosis Based on Hybrid Programming with Matlab and VB

NASA Astrophysics Data System (ADS)

Wang, Jiangping; Hu, Yingcai

This paper presents a method using hybrid programming with Matlab and VB based on ActiveX to design the system of drilling accident prediction and diagnosis. So that the powerful calculating function and graphical display function of Matlab and visual development interface of VB are combined fully. The main interface of the diagnosis system is compiled in VB,and the analysis and fault diagnosis are implemented by neural network tool boxes in Matlab.The system has favorable interactive interface,and the fault example validation shows that the diagnosis result is feasible and can meet the demands of drilling accident prediction and diagnosis.

Deterministic modelling and stochastic simulation of biochemical pathways using MATLAB.

PubMed

Ullah, M; Schmidt, H; Cho, K H; Wolkenhauer, O

2006-03-01

The analysis of complex biochemical networks is conducted in two popular conceptual frameworks for modelling. The deterministic approach requires the solution of ordinary differential equations (ODEs, reaction rate equations) with concentrations as continuous state variables. The stochastic approach involves the simulation of differential-difference equations (chemical master equations, CMEs) with probabilities as variables. This is to generate counts of molecules for chemical species as realisations of random variables drawn from the probability distribution described by the CMEs. Although there are numerous tools available, many of them free, the modelling and simulation environment MATLAB is widely used in the physical and engineering sciences. We describe a collection of MATLAB functions to construct and solve ODEs for deterministic simulation and to implement realisations of CMEs for stochastic simulation using advanced MATLAB coding (Release 14). The program was successfully applied to pathway models from the literature for both cases. The results were compared to implementations using alternative tools for dynamic modelling and simulation of biochemical networks. The aim is to provide a concise set of MATLAB functions that encourage the experimentation with systems biology models. All the script files are available from www.sbi.uni-rostock.de/ publications_matlab-paper.html.

NASA One-Dimensional Combustor Simulation--User Manual for S1D_ML

NASA Technical Reports Server (NTRS)

Stueber, Thomas J.; Paxson, Daniel E.

2014-01-01

The work presented in this paper is to promote research leading to a closed-loop control system to actively suppress thermo-acoustic instabilities. To serve as a model for such a closed-loop control system, a one-dimensional combustor simulation composed using MATLAB software tools has been written. This MATLAB based process is similar to a precursor one-dimensional combustor simulation that was formatted as FORTRAN 77 source code. The previous simulation process requires modification to the FORTRAN 77 source code, compiling, and linking when creating a new combustor simulation executable file. The MATLAB based simulation does not require making changes to the source code, recompiling, or linking. Furthermore, the MATLAB based simulation can be run from script files within the MATLAB environment or with a compiled copy of the executable file running in the Command Prompt window without requiring a licensed copy of MATLAB. This report presents a general simulation overview. Details regarding how to setup and initiate a simulation are also presented. Finally, the post-processing section describes the two types of files created while running the simulation and it also includes simulation results for a default simulation included with the source code.

Computational models of an inductive power transfer system for electric vehicle battery charge

NASA Astrophysics Data System (ADS)

Anele, A. O.; Hamam, Y.; Chassagne, L.; Linares, J.; Alayli, Y.; Djouani, K.

2015-09-01

One of the issues to be solved for electric vehicles (EVs) to become a success is the technical solution of its charging system. In this paper, computational models of an inductive power transfer (IPT) system for EV battery charge are presented. Based on the fundamental principles behind IPT systems, 3 kW single phase and 22 kW three phase IPT systems for Renault ZOE are designed in MATLAB/Simulink. The results obtained based on the technical specifications of the lithium-ion battery and charger type of Renault ZOE show that the models are able to provide the total voltage required by the battery. Also, considering the charging time for each IPT model, they are capable of delivering the electricity needed to power the ZOE. In conclusion, this study shows that the designed computational IPT models may be employed as a support structure needed to effectively power any viable EV.

Modeling and Parameter Estimation of Spacecraft Fuel Slosh with Diaphragms Using Pendulum Analogs

NASA Technical Reports Server (NTRS)

Chatman, Yadira; Gangadharan, Sathya; Schlee, Keith; Ristow, James; Suderman, James; Walker, Charles; Hubert, Carl

2007-01-01

Prediction and control of liquid slosh in moving containers is an important consideration in the design of spacecraft and launch vehicle control systems. Even with modern computing systems, CFD type simulations are not fast enough to allow for large scale Monte Carlo analyses of spacecraft and launch vehicle dynamic behavior with slosh included. It is still desirable to use some type of simplified mechanical analog for the slosh to shorten computation time. Analytic determination of the slosh analog parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices such as elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks, these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the hand-derived equations of motion for the mechanical analog are evaluated and their results compared with the experimental results. This paper will describe efforts by the university component of a team comprised of NASA's Launch Services Program, Embry Riddle Aeronautical University, Southwest Research Institute and Hubert Astronautics to improve the accuracy and efficiency of modeling techniques used to predict these types of motions. Of particular interest is the effect of diaphragms and bladders on the slosh dynamics and how best to model these devices. The previous research was an effort to automate the process of slosh model parameter identification using a MATLAB/SimMechanics-based computer simulation. These results are the first step in applying the same computer estimation to a full-size tank and vehicle propulsion system. The introduction of diaphragms to this experimental set-up will aid in a better and more complete prediction of fuel slosh characteristics and behavior. Automating the parameter identification process will save time and thus allow earlier identification of potential vehicle performance problems.

Computation of the phase response curve: a direct numerical approach.

PubMed

Govaerts, W; Sautois, B

2006-04-01

Neurons are often modeled by dynamical systems--parameterized systems of differential equations. A typical behavioral pattern of neurons is periodic spiking; this corresponds to the presence of stable limit cycles in the dynamical systems model. The phase resetting and phase response curves (PRCs) describe the reaction of the spiking neuron to an input pulse at each point of the cycle. We develop a new method for computing these curves as a by-product of the solution of the boundary value problem for the stable limit cycle. The method is mathematically equivalent to the adjoint method, but our implementation is computationally much faster and more robust than any existing method. In fact, it can compute PRCs even where the limit cycle can hardly be found by time integration, for example, because it is close to another stable limit cycle. In addition, we obtain the discretized phase response curve in a form that is ideally suited for most applications. We present several examples and provide the implementation in a freely available Matlab code.

Performance Evaluation of Counter-Based Dynamic Load Balancing Schemes for Massive Contingency Analysis with Different Computing Environments

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

Chen, Yousu; Huang, Zhenyu; Chavarría-Miranda, Daniel

Contingency analysis is a key function in the Energy Management System (EMS) to assess the impact of various combinations of power system component failures based on state estimation. Contingency analysis is also extensively used in power market operation for feasibility test of market solutions. High performance computing holds the promise of faster analysis of more contingency cases for the purpose of safe and reliable operation of today’s power grids with less operating margin and more intermittent renewable energy sources. This paper evaluates the performance of counter-based dynamic load balancing schemes for massive contingency analysis under different computing environments. Insights frommore » the performance evaluation can be used as guidance for users to select suitable schemes in the application of massive contingency analysis. Case studies, as well as MATLAB simulations, of massive contingency cases using the Western Electricity Coordinating Council power grid model are presented to illustrate the application of high performance computing with counter-based dynamic load balancing schemes.« less

Neural networks as a control methodology

NASA Technical Reports Server (NTRS)

Mccullough, Claire L.

1990-01-01

While conventional computers must be programmed in a logical fashion by a person who thoroughly understands the task to be performed, the motivation behind neural networks is to develop machines which can train themselves to perform tasks, using available information about desired system behavior and learning from experience. There are three goals of this fellowship program: (1) to evaluate various neural net methods and generate computer software to implement those deemed most promising on a personal computer equipped with Matlab; (2) to evaluate methods currently in the professional literature for system control using neural nets to choose those most applicable to control of flexible structures; and (3) to apply the control strategies chosen in (2) to a computer simulation of a test article, the Control Structures Interaction Suitcase Demonstrator, which is a portable system consisting of a small flexible beam driven by a torque motor and mounted on springs tuned to the first flexible mode of the beam. Results of each are discussed.

Maximum power point tracking algorithm based on sliding mode and fuzzy logic for photovoltaic sources under variable environmental conditions

NASA Astrophysics Data System (ADS)

Atik, L.; Petit, P.; Sawicki, J. P.; Ternifi, Z. T.; Bachir, G.; Della, M.; Aillerie, M.

2017-02-01

Solar panels have a nonlinear voltage-current characteristic, with a distinct maximum power point (MPP), which depends on the environmental factors, such as temperature and irradiation. In order to continuously harvest maximum power from the solar panels, they have to operate at their MPP despite the inevitable changes in the environment. Various methods for maximum power point tracking (MPPT) were developed and finally implemented in solar power electronic controllers to increase the efficiency in the electricity production originate from renewables. In this paper we compare using Matlab tools Simulink, two different MPP tracking methods, which are, fuzzy logic control (FL) and sliding mode control (SMC), considering their efficiency in solar energy production.

PV_LIB Toolbox v. 1.3

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

2015-12-09

PV_LIB comprises a library of Matlab? code for modeling photovoltaic (PV) systems. Included are functions to compute solar position and to estimate irradiance in the PV system's plane of array, cell temperature, PV module electrical output, and conversion from DC to AC power. Also included are functions that aid in determining parameters for module performance models from module characterization testing. PV_LIB is open source code primarily intended for research and academic purposes. All algorithms are documented in openly available literature with the appropriate references included in comments within the code.

High performance data acquisition, identification, and monitoring for active magnetic bearings

NASA Technical Reports Server (NTRS)

Herzog, Raoul; Siegwart, Roland

1994-01-01

Future active magnetic bearing systems (AMB) must feature easier on-site tuning, higher stiffness and damping, better robustness with respect to undesirable vibrations in housing and foundation, and enhanced monitoring and identification abilities. To get closer to these goals we developed a fast parallel link from the digitally controlled AMB to Matlab, which is used on a host computer for data processing, identification, and controller layout. This enables the magnetic bearing to take its frequency responses without using any additional measurement equipment. These measurements can be used for AMB identification.

More-Realistic Digital Modeling of a Human Body

NASA Technical Reports Server (NTRS)

Rogge, Renee

2010-01-01

A MATLAB computer program has been written to enable improved (relative to an older program) modeling of a human body for purposes of designing space suits and other hardware with which an astronaut must interact. The older program implements a kinematic model based on traditional anthropometric measurements that do provide important volume and surface information. The present program generates a three-dimensional (3D) whole-body model from 3D body-scan data. The program utilizes thin-plate spline theory to reposition the model without need for additional scans.

Model implementation for dynamic computation of system cost

NASA Astrophysics Data System (ADS)

Levri, J.; Vaccari, D.

The Advanced Life Support (ALS) Program metric is the ratio of the equivalent system mass (ESM) of a mission based on International Space Station (ISS) technology to the ESM of that same mission based on ALS technology. ESM is a mission cost analog that converts the volume, power, cooling and crewtime requirements of a mission into mass units to compute an estimate of the life support system emplacement cost. Traditionally, ESM has been computed statically, using nominal values for system sizing. However, computation of ESM with static, nominal sizing estimates cannot capture the peak sizing requirements driven by system dynamics. In this paper, a dynamic model for a near-term Mars mission is described. The model is implemented in Matlab/Simulink' for the purpose of dynamically computing ESM. This paper provides a general overview of the crew, food, biomass, waste, water and air blocks in the Simulink' model. Dynamic simulations of the life support system track mass flow, volume and crewtime needs, as well as power and cooling requirement profiles. The mission's ESM is computed, based upon simulation responses. Ultimately, computed ESM values for various system architectures will feed into an optimization search (non-derivative) algorithm to predict parameter combinations that result in reduced objective function values.

High Step-Up DC—DC Converter for AC Photovoltaic Module with MPPT Control

NASA Astrophysics Data System (ADS)

Sundar, Govindasamy; Karthick, Narashiman; Rama Reddy, Sasi

2014-08-01

This paper presents the high gain step-up BOOST converter which is essential to step up the low output voltage from PV panel to the high voltage according to the requirement of the application. In this paper a high gain BOOST converter with coupled inductor technique is proposed with the MPPT control. Without extreme duty ratios and the numerous turns-ratios of a coupled inductor this converter achieves a high step-up voltage-conversion ratio and the leakage energy of the coupled inductor is efficiently recycled to the load. MPPT control used to extract the maximum power from PV panel by controlling the Duty ratio of the converter. The PV panel, BOOST converter and the MPPT are modeled using Sim Power System blocks in MATLAB/SIMULINK environment. The prototype model of the proposed converter has been implemented with the maximum measured efficiency is up to 95.4% and full-load efficiency is 93.1%.

Definition of Static Voltage Characteristics of the Motor Load for the Purpose of Increase in Energy Efficiency of Coal Mines of Kuzbass

NASA Astrophysics Data System (ADS)

Nepsha, Fedor; Efremenko, Vladimir

2017-11-01

The task of determining the static load characteristics is one of the most important tasks, the solution of which is necessary for the correct development of measures to increase the energy efficiency of the Kuzbass coal mines. At present, the influence of electric receivers on the level of consumption of active and reactive power is not taken into account, therefore, the proposed measures to increase the energy efficiency are not optimal. The article analyzes the L-shaped and T-shaped circuit for the replacement of an asynchronous motor (AM), according to the results of which it is determined that the T-shaped replacement scheme is the most accurate for determination of static load characteristics. The authors proposed and implemented in the MATLAB Simulink environment an algorithm for determining the static voltage characteristics of the motor load.

High convergence efficiency design of flat Fresnel lens with large aperture

NASA Astrophysics Data System (ADS)

Ke, Jieyao; Zhao, Changming; Guan, Zhe

2018-01-01

This paper designed a circle-shaped Fresnel lens with large aperture as part of the solar pumped laser design project. The Fresnel lens designed in this paper simulate in size 1000mm×1000mm, focus length 1200mm and polymethyl methacrylate (PMMA) material in order to conduct high convergence efficiency. In the light of design requirement of concentric ring with same width of 0.3mm, this paper proposed an optimized Fresnel lens design based on previous sphere design and conduct light tracing simulation in Matlab. This paper also analyzed the effect of light spot size, light intensity distribution, optical efficiency under four conditions, monochromatic parallel light, parallel spectrum light, divergent monochromatic light and sunlight. Design by 550nm wavelength and under the condition of Fresnel reflection, the results indicated that the designed lens could convergent sunlight in diffraction limit of 11.8mm with a 78.7% optical efficiency, better than the sphere cutting design results of 30.4%.

Computer programming in the UK undergraduate mathematics curriculum

NASA Astrophysics Data System (ADS)

Sangwin, Christopher J.; O'Toole, Claire

2017-11-01

This paper reports a study which investigated the extent to which undergraduate mathematics students in the United Kingdom are currently taught to programme a computer as a core part of their mathematics degree programme. We undertook an online survey, with significant follow-up correspondence, to gather data on current curricula and received replies from 46 (63%) of the departments who teach a BSc mathematics degree. We found that 78% of BSc degree courses in mathematics included computer programming in a compulsory module but 11% of mathematics degree programmes do not teach programming to all their undergraduate mathematics students. In 2016, programming is most commonly taught to undergraduate mathematics students through imperative languages, notably MATLAB, using numerical analysis as the underlying (or parallel) mathematical subject matter. Statistics is a very popular choice in optional courses, using the package R. Computer algebra systems appear to be significantly less popular for compulsory first-year courses than a decade ago, and there was no mention of logic programming, functional programming or automatic theorem proving software. The modal form of assessment of computing modules is entirely by coursework (i.e. no examination).

Teaching ocean wave forecasting using computer-generated visualization and animation—Part 2: swell forecasting

NASA Astrophysics Data System (ADS)

Whitford, Dennis J.

2002-05-01

This paper, the second of a two-part series, introduces undergraduate students to ocean wave forecasting using interactive computer-generated visualization and animation. Verbal descriptions and two-dimensional illustrations are often insufficient for student comprehension. Fortunately, the introduction of computers in the geosciences provides a tool for addressing this problem. Computer-generated visualization and animation, accompanied by oral explanation, have been shown to be a pedagogical improvement to more traditional methods of instruction. Cartographic science and other disciplines using geographical information systems have been especially aggressive in pioneering the use of visualization and animation, whereas oceanography has not. This paper will focus on the teaching of ocean swell wave forecasting, often considered a difficult oceanographic topic due to the mathematics and physics required, as well as its interdependence on time and space. Several MATLAB ® software programs are described and offered to visualize and animate group speed, frequency dispersion, angular dispersion, propagation, and wave height forecasting of deep water ocean swell waves. Teachers may use these interactive visualizations and animations without requiring an extensive background in computer programming.

A fast object-oriented Matlab implementation of the Reproducing Kernel Particle Method

NASA Astrophysics Data System (ADS)

Barbieri, Ettore; Meo, Michele

2012-05-01

Novel numerical methods, known as Meshless Methods or Meshfree Methods and, in a wider perspective, Partition of Unity Methods, promise to overcome most of disadvantages of the traditional finite element techniques. The absence of a mesh makes meshfree methods very attractive for those problems involving large deformations, moving boundaries and crack propagation. However, meshfree methods still have significant limitations that prevent their acceptance among researchers and engineers, namely the computational costs. This paper presents an in-depth analysis of computational techniques to speed-up the computation of the shape functions in the Reproducing Kernel Particle Method and Moving Least Squares, with particular focus on their bottlenecks, like the neighbour search, the inversion of the moment matrix and the assembly of the stiffness matrix. The paper presents numerous computational solutions aimed at a considerable reduction of the computational times: the use of kd-trees for the neighbour search, sparse indexing of the nodes-points connectivity and, most importantly, the explicit and vectorized inversion of the moment matrix without using loops and numerical routines.

The Alba ray tracing code: ART

NASA Astrophysics Data System (ADS)

Nicolas, Josep; Barla, Alessandro; Juanhuix, Jordi

2013-09-01

The Alba ray tracing code (ART) is a suite of Matlab functions and tools for the ray tracing simulation of x-ray beamlines. The code is structured in different layers, which allow its usage as part of optimization routines as well as an easy control from a graphical user interface. Additional tools for slope error handling and for grating efficiency calculations are also included. Generic characteristics of ART include the accumulation of rays to improve statistics without memory limitations, and still providing normalized values of flux and resolution in physically meaningful units.

Standardizing Methods for Weapons Accuracy and Effectiveness Evaluation

DTIC Science & Technology

2014-06-01

37  B.  MONTE CARLO APPROACH............................37  C.  EXPECTED VALUE THEOREM..........................38  D.  PHIT /PNM METHODOLOGY...MATLAB CODE – SR_CDF_DATA.......................96  F.  MATLAB CODE – GE_EXTRACT........................98  G.  MATLAB CODE - PHIT /PNM...Normal fit to test data.........................18  Figure 11.  Double Normal fit to test data..................19  Figure 12.  PHIT /PNM Methodology (from

Subband/Transform MATLAB Functions For Processing Images

NASA Technical Reports Server (NTRS)

Glover, D.

1995-01-01

SUBTRANS software is package of routines implementing image-data-processing functions for use with MATLAB*(TM) software. Provides capability to transform image data with block transforms and to produce spatial-frequency subbands of transformed data. Functions cascaded to provide further decomposition into more subbands. Also used in image-data-compression systems. For example, transforms used to prepare data for lossy compression. Written for use in MATLAB mathematical-analysis environment.

Detection and Classification of Objects in Synthetic Aperture Radar Imagery

DTIC Science & Technology

2006-02-01

a higher False Alarm Rate (FAR). Currently, a standard edge detector is the Canny algorithm, which is available with the mathematics package MATLAB ...the algorithm used to calculate the Radon transform. The MATLAB implementation uses the built in Radon transform procedure, which is extremely... MATLAB code for a faster forward-backwards selection process has also been provided. In both cases, the feature selection was accomplished by using

Forward Field Computation with OpenMEEG

PubMed Central

Gramfort, Alexandre; Papadopoulo, Théodore; Olivi, Emmanuel; Clerc, Maureen

2011-01-01

To recover the sources giving rise to electro- and magnetoencephalography in individual measurements, realistic physiological modeling is required, and accurate numerical solutions must be computed. We present OpenMEEG, which solves the electromagnetic forward problem in the quasistatic regime, for head models with piecewise constant conductivity. The core of OpenMEEG consists of the symmetric Boundary Element Method, which is based on an extended Green Representation theorem. OpenMEEG is able to provide lead fields for four different electromagnetic forward problems: Electroencephalography (EEG), Magnetoencephalography (MEG), Electrical Impedance Tomography (EIT), and intracranial electric potentials (IPs). OpenMEEG is open source and multiplatform. It can be used from Python and Matlab in conjunction with toolboxes that solve the inverse problem; its integration within FieldTrip is operational since release 2.0. PMID:21437231

Modeling the small-scale dish-mounted solar thermal Brayton cycle

NASA Astrophysics Data System (ADS)

Le Roux, Willem G.; Meyer, Josua P.

2016-05-01

The small-scale dish-mounted solar thermal Brayton cycle (STBC) makes use of a sun-tracking dish reflector, solar receiver, recuperator and micro-turbine to generate power in the range of 1-20 kW. The modeling of such a system, using a turbocharger as micro-turbine, is required so that optimisation and further development of an experimental setup can be done. As a validation, an analytical model of the small-scale STBC in Matlab, where the net power output is determined from an exergy analysis, is compared with Flownex, an integrated systems CFD code. A 4.8 m diameter parabolic dish with open-cavity tubular receiver and plate-type counterflow recuperator is considered, based on previous work. A dish optical error of 10 mrad, a tracking error of 1° and a receiver aperture area of 0.25 m × 0.25 m are considered. Since the recuperator operates at a very high average temperature, the recuperator is modeled using an updated ɛ-NTU method which takes heat loss to the environment into consideration. Compressor and turbine maps from standard off-the-shelf Garrett turbochargers are used. The results show that for the calculation of the steady-state temperatures and pressures, there is good comparison between the Matlab and Flownex results (within 8%) except for the recuperator outlet temperature, which is due to the use of different ɛ-NTU methods. With the use of Matlab and Flownex, it is shown that the small-scale open STBC with an existing off-the-shelf turbocharger could generate a positive net power output with solar-to-mechanical efficiency of up to 12%, with much room for improvement.

Metallic Junction Thermoelectric Device Simulations

NASA Technical Reports Server (NTRS)

Duzik, Adam J.; Choi, Sang H.

2017-01-01

Thermoelectric junctions made of semiconductors have existed in radioisotope thermoelectric generators (RTG) for deep space missions, but are currently being adapted for terrestrial energy harvesting. Unfortunately, these devices are inefficient, operating at only 7% efficiency. This low efficiency has driven efforts to make high-figure-of-merit thermoelectric devices, which require a high electrical conductivity but a low thermal conductivity, a combination that is difficult to achieve. Lowered thermal conductivity has increased efficiency, but at the cost of power output. An alternative setup is to use metallic junctions rather than semiconductors as thermoelectric devices. Metals have orders of magnitude more electrons and electronic conductivities higher than semiconductors, but thermal conductivity is higher as well. To evaluate the viability of metallic junction thermoelectrics, a two dimensional heat transfer MATLAB simulation was constructed to calculate efficiency and power output. High Seebeck coefficient alloys, Chromel (90%Ni-10%Cr) and Constantan (55%Cu-45%Ni), produced efficiencies of around 20-30%. Parameters such as the number of layers of junctions, lateral junction density, and junction sizes for both series- and parallel-connected junctions were explored.

Analysis of forward scattering of an acoustical zeroth-order Bessel beam from rigid complicated (aspherical) structures

NASA Astrophysics Data System (ADS)

Li, Wei; Chai, Yingbin; Gong, Zhixiong; Marston, Philip L.

2017-10-01

The forward scattering from rigid spheroids and endcapped cylinders with finite length (even with a large aspect ratio) immersed in a non-viscous fluid under the illumination of an idealized zeroth-order acoustical Bessel beam (ABB) with arbitrary angles of incidence is calculated and analyzed in the implementation of the T-matrix method (TTM). Based on the present method, the incident coefficients of expansion for the incident ABB are derived and simplifying methods are proposed for the numerical accuracy and computational efficiency according to the geometrical symmetries. A home-made MATLAB software package is constructed accordingly, and then verified and validated for the ABB scattering from rigid aspherical obstacles. Several numerical examples are computed for the forward scattering from both rigid spheroids and finite cylinder, with particular emphasis on the aspect ratios, the half-cone angles of ABBs, the incident angles and the dimensionless frequencies. The rectangular patterns of target strength in the (β, θs) domain (where β is the half-cone angle of the ABB and θs is the scattered polar angle) and local/total forward scattering versus dimensionless frequency are exhibited, which could provide new insights into the physical mechanisms of Bessel beam scattering by rigid spheroids and finite cylinders. The ray diagrams in geometrical models for the scattering in the forward half-space and the optical cross-section theorem help to interpret the scattering mechanisms of ABBs. This research work may provide an alternative for the partial wave series solution under certain circumstances interacting with ABBs for complicated obstacles and benefit some related works in optics and electromagnetics.

Matlab-Excel Interface for OpenDSS

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

The software allows users of the OpenDSS grid modeling software to access their load flow models using a GUI interface developed in MATLAB. The circuit definitions are entered into a Microsoft Excel spreadsheet which makes circuit creation and editing a much simpler process than the basic text-based editors used in the native OpenDSS interface. Plot tools have been developed which can be accessed through a MATLAB GUI once the desired parameters have been simulated.

Matlab based Toolkits used to Interface with Optical Design Software for NASA's James Webb Space Telescope

NASA Technical Reports Server (NTRS)

Howard, Joseph

2007-01-01

The viewgraph presentation provides an introduction to the James Webb Space Telescope (JWST). The first part provides a brief overview of Matlab toolkits including CodeV, OSLO, and Zemax Toolkits. The toolkit overview examines purpose, layout, how Matlab gets data from CodeV, function layout, and using cvHELP. The second part provides examples of use with JWST, including wavefront sensitivities and alignment simulations.

Test Generator for MATLAB Simulations

NASA Technical Reports Server (NTRS)

Henry, Joel

2011-01-01

MATLAB Automated Test Tool, version 3.0 (MATT 3.0) is a software package that provides automated tools that reduce the time needed for extensive testing of simulation models that have been constructed in the MATLAB programming language by use of the Simulink and Real-Time Workshop programs. MATT 3.0 runs on top of the MATLAB engine application-program interface to communicate with the Simulink engine. MATT 3.0 automatically generates source code from the models, generates custom input data for testing both the models and the source code, and generates graphs and other presentations that facilitate comparison of the outputs of the models and the source code for the same input data. Context-sensitive and fully searchable help is provided in HyperText Markup Language (HTML) format.

Integration of MATLAB Simulink(Registered Trademark) Models with the Vertical Motion Simulator

NASA Technical Reports Server (NTRS)

Lewis, Emily K.; Vuong, Nghia D.

2012-01-01

This paper describes the integration of MATLAB Simulink(Registered TradeMark) models into the Vertical Motion Simulator (VMS) at NASA Ames Research Center. The VMS is a high-fidelity, large motion flight simulator that is capable of simulating a variety of aerospace vehicles. Integrating MATLAB Simulink models into the VMS needed to retain the development flexibility of the MATLAB environment and allow rapid deployment of model changes. The process developed at the VMS was used successfully in a number of recent simulation experiments. This accomplishment demonstrated that the model integrity was preserved, while working within the hard real-time run environment of the VMS architecture, and maintaining the unique flexibility of the VMS to meet diverse research requirements.

Changing patient population in Dhaka Hospital and Matlab Hospital of icddr,b.

PubMed

Das, S K; Rahman, A; Chisti, M J; Ahmed, S; Malek, M A; Salam, M A; Bardhan, P K; Faruque, A S G

2014-02-01

The Diarrhoeal Disease Surveillance System of icddr,b noted increasing number of patients ≥60 years at urban Dhaka and rural Matlab from 2001 to 2012. Shigella and Vibrio cholerae were more frequently isolated from elderly people than children under 5 years and adults aged 5-59 in both areas. The resistance observed to various drugs of Shigella in Dhaka and Matlab was trimethoprim-sulphamethoxazole (72-63%), ampicillin (43-55%), nalidixic acid (58-61%), mecillinam (12-9%), azithromycin (13-0%), ciprofloxacin (11-13%) and ceftriaxone (11-0%). Vibrio cholerae isolated in Dhaka and Matlab was resistant to trimethoprim-sulphamethoxazole (98-94%), furazolidone (100%), erythromycin (71-53%), tetracycline (46-44%), ciprofloxacin (3-10%) and azithromycin (3-0%). © 2013 John Wiley & Sons Ltd.

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms

PubMed Central

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts’ Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2–100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms. PMID:28487831

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

Tumuluru, Jaya Shankar; McCulloch, Richard Chet James

In this work a new hybrid genetic algorithm was developed which combines a rudimentary adaptive steepest ascent hill climbing algorithm with a sophisticated evolutionary algorithm in order to optimize complex multivariate design problems. By combining a highly stochastic algorithm (evolutionary) with a simple deterministic optimization algorithm (adaptive steepest ascent) computational resources are conserved and the solution converges rapidly when compared to either algorithm alone. In genetic algorithms natural selection is mimicked by random events such as breeding and mutation. In the adaptive steepest ascent algorithm each variable is perturbed by a small amount and the variable that caused the mostmore » improvement is incremented by a small step. If the direction of most benefit is exactly opposite of the previous direction with the most benefit then the step size is reduced by a factor of 2, thus the step size adapts to the terrain. A graphical user interface was created in MATLAB to provide an interface between the hybrid genetic algorithm and the user. Additional features such as bounding the solution space and weighting the objective functions individually are also built into the interface. The algorithm developed was tested to optimize the functions developed for a wood pelleting process. Using process variables (such as feedstock moisture content, die speed, and preheating temperature) pellet properties were appropriately optimized. Specifically, variables were found which maximized unit density, bulk density, tapped density, and durability while minimizing pellet moisture content and specific energy consumption. The time and computational resources required for the optimization were dramatically decreased using the hybrid genetic algorithm when compared to MATLAB's native evolutionary optimization tool.« less

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms.

PubMed

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts' Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2-100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms.

A Low-Cost Real Color Picker Based on Arduino

PubMed Central

Agudo, Juan Enrique; Pardo, Pedro J.; Sánchez, Héctor; Pérez, Ángel Luis; Suero, María Isabel

2014-01-01

Color measurements have traditionally been linked to expensive and difficult to handle equipment. The set of mathematical transformations that are needed to transfer a color that we observe in any object that doesn't emit its own light (which is usually called a color-object) so that it can be displayed on a computer screen or printed on paper is not at all trivial. This usually requires a thorough knowledge of color spaces, colorimetric transformations and color management systems. The TCS3414CS color sensor (I2C Sensor Color Grove), a system for capturing, processing and color management that allows the colors of any non-self-luminous object using a low-cost hardware based on Arduino, is presented in this paper. Specific software has been developed in Matlab and a study of the linearity of chromatic channels and accuracy of color measurements for this device has been undertaken. All used scripts (Arduino and Matlab) are attached as supplementary material. The results show acceptable accuracy values that, although obviously do not reach the levels obtained with the other scientific instruments, for the price difference they present a good low cost option. PMID:25004152

The TimeStudio Project: An open source scientific workflow system for the behavioral and brain sciences.

PubMed

Nyström, Pär; Falck-Ytter, Terje; Gredebäck, Gustaf

2016-06-01

This article describes a new open source scientific workflow system, the TimeStudio Project, dedicated to the behavioral and brain sciences. The program is written in MATLAB and features a graphical user interface for the dynamic pipelining of computer algorithms developed as TimeStudio plugins. TimeStudio includes both a set of general plugins (for reading data files, modifying data structures, visualizing data structures, etc.) and a set of plugins specifically developed for the analysis of event-related eyetracking data as a proof of concept. It is possible to create custom plugins to integrate new or existing MATLAB code anywhere in a workflow, making TimeStudio a flexible workbench for organizing and performing a wide range of analyses. The system also features an integrated sharing and archiving tool for TimeStudio workflows, which can be used to share workflows both during the data analysis phase and after scientific publication. TimeStudio thus facilitates the reproduction and replication of scientific studies, increases the transparency of analyses, and reduces individual researchers' analysis workload. The project website ( http://timestudioproject.com ) contains the latest releases of TimeStudio, together with documentation and user forums.