EEGVIS: A MATLAB Toolbox for Browsing, Exploring, and Viewing Large Datasets.

PubMed

Robbins, Kay A

2012-01-01

Recent advances in data monitoring and sensor technology have accelerated the acquisition of very large data sets. Streaming data sets from instrumentation such as multi-channel EEG recording usually must undergo substantial pre-processing and artifact removal. Even when using automated procedures, most scientists engage in laborious manual examination and processing to assure high quality data and to indentify interesting or problematic data segments. Researchers also do not have a convenient method of method of visually assessing the effects of applying any stage in a processing pipeline. EEGVIS is a MATLAB toolbox that allows users to quickly explore multi-channel EEG and other large array-based data sets using multi-scale drill-down techniques. Customizable summary views reveal potentially interesting sections of data, which users can explore further by clicking to examine using detailed viewing components. The viewer and a companion browser are built on our MoBBED framework, which has a library of modular viewing components that can be mixed and matched to best reveal structure. Users can easily create new viewers for their specific data without any programming during the exploration process. These viewers automatically support pan, zoom, resizing of individual components, and cursor exploration. The toolbox can be used directly in MATLAB at any stage in a processing pipeline, as a plug-in for EEGLAB, or as a standalone precompiled application without MATLAB running. EEGVIS and its supporting packages are freely available under the GNU general public license at http://visual.cs.utsa.edu/eegvis.

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.

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.

GMDPtoolbox: A Matlab library for designing spatial management policies. Application to the long-term collective management of an airborne disease

PubMed Central

Aubertot, Jean-Noël; Peyrard, Nathalie; Sabbadin, Régis

2017-01-01

Designing management policies in ecology and agroecology is complex. Several components must be managed together while they strongly interact spatially. Decision choices must be made under uncertainty on the results of the actions and on the system dynamics. Furthermore, the objectives pursued when managing ecological systems or agroecosystems are usually long term objectives, such as biodiversity conservation or sustainable crop production. The framework of Graph-Based Markov Decision Processes (GMDP) is well adapted to the qualitative modeling of such problems of sequential decision under uncertainty. Spatial interactions are easily modeled and integrated control policies (combining several action levers) can be designed through optimization. The provided policies are adaptive, meaning that management actions are decided at each time step (for instance yearly) and the chosen actions depend on the current system state. This framework has already been successfully applied to forest management and invasive species management. However, up to now, no “easy-to-use” implementation of this framework was available. We present GMDPtoolbox, a Matlab toolbox which can be used both for the design of new management policies and for comparing policies by simulation. We provide an illustration of the use of the toolbox on a realistic crop disease management problem: the design of long term management policy of blackleg of canola using an optimal combination of three possible cultural levers. This example shows how GMDPtoolbox can be used as a tool to support expert thinking. PMID:28982151

GMDPtoolbox: A Matlab library for designing spatial management policies. Application to the long-term collective management of an airborne disease.

PubMed

Cros, Marie-Josée; Aubertot, Jean-Noël; Peyrard, Nathalie; Sabbadin, Régis

2017-01-01

Designing management policies in ecology and agroecology is complex. Several components must be managed together while they strongly interact spatially. Decision choices must be made under uncertainty on the results of the actions and on the system dynamics. Furthermore, the objectives pursued when managing ecological systems or agroecosystems are usually long term objectives, such as biodiversity conservation or sustainable crop production. The framework of Graph-Based Markov Decision Processes (GMDP) is well adapted to the qualitative modeling of such problems of sequential decision under uncertainty. Spatial interactions are easily modeled and integrated control policies (combining several action levers) can be designed through optimization. The provided policies are adaptive, meaning that management actions are decided at each time step (for instance yearly) and the chosen actions depend on the current system state. This framework has already been successfully applied to forest management and invasive species management. However, up to now, no "easy-to-use" implementation of this framework was available. We present GMDPtoolbox, a Matlab toolbox which can be used both for the design of new management policies and for comparing policies by simulation. We provide an illustration of the use of the toolbox on a realistic crop disease management problem: the design of long term management policy of blackleg of canola using an optimal combination of three possible cultural levers. This example shows how GMDPtoolbox can be used as a tool to support expert thinking.

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

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…

A matlab framework for estimation of NLME models using stochastic differential equations: applications for estimation of insulin secretion rates.

PubMed

Mortensen, Stig B; Klim, Søren; Dammann, Bernd; Kristensen, Niels R; Madsen, Henrik; Overgaard, Rune V

2007-10-01

The non-linear mixed-effects model based on stochastic differential equations (SDEs) provides an attractive residual error model, that is able to handle serially correlated residuals typically arising from structural mis-specification of the true underlying model. The use of SDEs also opens up for new tools for model development and easily allows for tracking of unknown inputs and parameters over time. An algorithm for maximum likelihood estimation of the model has earlier been proposed, and the present paper presents the first general implementation of this algorithm. The implementation is done in Matlab and also demonstrates the use of parallel computing for improved estimation times. The use of the implementation is illustrated by two examples of application which focus on the ability of the model to estimate unknown inputs facilitated by the extension to SDEs. The first application is a deconvolution-type estimation of the insulin secretion rate based on a linear two-compartment model for C-peptide measurements. In the second application the model is extended to also give an estimate of the time varying liver extraction based on both C-peptide and insulin measurements.

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.

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.

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

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/.

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

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.

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.

INFFTM: Fast evaluation of 3d Fourier series in MATLAB with an application to quantum vortex reconnections

NASA Astrophysics Data System (ADS)

Caliari, Marco; Zuccher, Simone

2017-04-01

Although Fourier series approximation is ubiquitous in computational physics owing to the Fast Fourier Transform (FFT) algorithm, efficient techniques for the fast evaluation of a three-dimensional truncated Fourier series at a set of arbitrary points are quite rare, especially in MATLAB language. Here we employ the Nonequispaced Fast Fourier Transform (NFFT, by J. Keiner, S. Kunis, and D. Potts), a C library designed for this purpose, and provide a Matlab® and GNU Octave interface that makes NFFT easily available to the Numerical Analysis community. We test the effectiveness of our package in the framework of quantum vortex reconnections, where pseudospectral Fourier methods are commonly used and local high resolution is required in the post-processing stage. We show that the efficient evaluation of a truncated Fourier series at arbitrary points provides excellent results at a computational cost much smaller than carrying out a numerical simulation of the problem on a sufficiently fine regular grid that can reproduce comparable details of the reconnecting vortices.

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.

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…

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.

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

PScan 1.0: flexible software framework for polygon based multiphoton microscopy

NASA Astrophysics Data System (ADS)

Li, Yongxiao; Lee, Woei Ming

2016-12-01

Multiphoton laser scanning microscopes exhibit highly localized nonlinear optical excitation and are powerful instruments for in-vivo deep tissue imaging. Customized multiphoton microscopy has a significantly superior performance for in-vivo imaging because of precise control over the scanning and detection system. To date, there have been several flexible software platforms catered to custom built microscopy systems i.e. ScanImage, HelioScan, MicroManager, that perform at imaging speeds of 30-100fps. In this paper, we describe a flexible software framework for high speed imaging systems capable of operating from 5 fps to 1600 fps. The software is based on the MATLAB image processing toolbox. It has the capability to communicate directly with a high performing imaging card (Matrox Solios eA/XA), thus retaining high speed acquisition. The program is also designed to communicate with LabVIEW and Fiji for instrument control and image processing. Pscan 1.0 can handle high imaging rates and contains sufficient flexibility for users to adapt to their high speed imaging systems.

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

Novel Multiscale Modeling Tool Applied to Pseudomonas aeruginosa Biofilm Formation

PubMed Central

Biggs, Matthew B.; Papin, Jason A.

2013-01-01

Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool. PMID:24147108

Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.

PubMed

Biggs, Matthew B; Papin, Jason A

2013-01-01

Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool.

The Waveform Suite: A robust platform for accessing and manipulating seismic waveforms in MATLAB

NASA Astrophysics Data System (ADS)

Reyes, C. G.; West, M. E.; McNutt, S. R.

2009-12-01

The Waveform Suite, developed at the University of Alaska Geophysical Institute, is an open-source collection of MATLAB classes that provide a means to import, manipulate, display, and share waveform data while ensuring integrity of the data and stability for programs that incorporate them. Data may be imported from a variety of sources, such as Antelope, Winston databases, SAC files, SEISAN, .mat files, or other user-defined file formats. The waveforms being manipulated in MATLAB are isolated from their stored representations, relieving the overlying programs from the responsibility of understanding the specific format in which data is stored or retrieved. The waveform class provides an object oriented framework that simplifies manipulations to waveform data. Playing with data becomes easier because the tedious aspects of data manipulation have been automated. The user is able to change multiple waveforms simultaneously using standard mathematical operators and other syntactically familiar functions. Unlike MATLAB structs or workspace variables, the data stored within waveform class objects are protected from modification, and instead are accessed through standardized functions, such as get and set; these are already familiar to users of MATLAB’s graphical features. This prevents accidental or nonsensical modifications to the data, which in turn simplifies troubleshooting of complex programs. Upgrades to the internal structure of the waveform class are invisible to applications which use it, making maintenance easier. We demonstrate the Waveform Suite’s capabilities on seismic data from Okmok and Redoubt volcanoes. Years of data from Okmok were retrieved from Antelope and Winston databases. Using the Waveform Suite, we built a tremor-location program. Because the program was built on the Waveform Suite, modifying it to operate on real-time data from Redoubt involved only minimal code changes. The utility of the Waveform Suite as a foundation for large developments is demonstrated with the Correlation Toolbox for MATLAB. This mature package contains 50+ codes for carrying out various type of waveform correlation analyses (multiplet analysis, clustering, interferometry, …) This package is greatly strengthened by delegating numerous book-keeping and signal processing tasks to the underlying Waveform Suite. The Waveform Suite’s built-in tools for searching arbitrary directory/file structures is demonstrated with matched video and audio from the recent eruption of Redoubt Volcano. These tools were used to find subsets of photo images corresponding to specific seismic traces. Using Waveform’s audio file routines, matched video and audio were assembled to produce outreach-quality eruption products. The Waveform Suite is not designed as a ready-to-go replacement for more comprehensive packages such as SAC or AH. Rather, it is a suite of classes which provide core time series functionality in a MATLAB environment. It is designed to be a more robust alternative to the numerous ad hoc MATLAB formats that exist. Complex programs may be created upon the Waveform Suite’s framework, while existing programs may be modified to take advantage of the Waveform Suites capabilities.

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/Simulink Framework for Modeling Complex Coolant Flow Configurations of Advanced Automotive Thermal Management Systems: Preprint

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

Titov, Eugene; Lustbader, Jason; Leighton, Daniel

The National Renewable Energy Laboratory's (NREL's) CoolSim MATLAB/Simulink modeling framework was extended by including a newly developed coolant loop solution method aimed at reducing the simulation effort for arbitrarily complex thermal management systems. The new approach does not require the user to identify specific coolant loops and their flow. The user only needs to connect the fluid network elements in a manner consistent with the desired schematic. Using the new solution method, a model of NREL's advanced combined coolant loop system for electric vehicles was created that reflected the test system architecture. This system was built using components provided bymore » the MAHLE Group and included both air conditioning and heat pump modes. Validation with test bench data and verification with the previous solution method were performed for 10 operating points spanning a range of ambient temperatures between -2 degrees C and 43 degrees C. The largest root mean square difference between pressure, temperature, energy and mass flow rate data and simulation results was less than 7%.« less

MATLAB/Simulink Framework for Modeling Complex Coolant Flow Configurations of Advanced Automotive Thermal Management Systems

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

Titov, Gene; Lustbader, Jason; Leighton, Daniel

The National Renewable Energy Laboratory's (NREL's) CoolSim MATLAB/Simulink modeling framework was extended by including a newly developed coolant loop solution method aimed at reducing the simulation effort for arbitrarily complex thermal management systems. The new approach does not require the user to identify specific coolant loops and their flow. The user only needs to connect the fluid network elements in a manner consistent with the desired schematic. Using the new solution method, a model of NREL's advanced combined coolant loop system for electric vehicles was created that reflected the test system architecture. This system was built using components provided bymore » the MAHLE Group and included both air conditioning and heat pump modes. Validation with test bench data and verification with the previous solution method were performed for 10 operating points spanning a range of ambient temperatures between -2 degrees C and 43 degrees C. The largest root mean square difference between pressure, temperature, energy and mass flow rate data and simulation results was less than 7%.« less

Defining Geodetic Reference Frame using Matlab®: PlatEMotion 2.0

NASA Astrophysics Data System (ADS)

Cannavò, Flavio; Palano, Mimmo

2016-03-01

We describe the main features of the developed software tool, namely PlatE-Motion 2.0 (PEM2), which allows inferring the Euler pole parameters by inverting the observed velocities at a set of sites located on a rigid block (inverse problem). PEM2 allows also calculating the expected velocity value for any point located on the Earth providing an Euler pole (direct problem). PEM2 is the updated version of a previous software tool initially developed for easy-to-use file exchange with the GAMIT/GLOBK software package. The software tool is developed in Matlab® framework and, as the previous version, includes a set of MATLAB functions (m-files), GUIs (fig-files), map data files (mat-files) and user's manual as well as some example input files. New changes in PEM2 include (1) some bugs fixed, (2) improvements in the code, (3) improvements in statistical analysis, (4) new input/output file formats. In addition, PEM2 can be now run under the majority of operating systems. The tool is open source and freely available for the scientific community.

An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and Octave.

PubMed

Silva, Ikaro; Moody, George B

The WaveForm DataBase (WFDB) Toolbox for MATLAB/Octave enables integrated access to PhysioNet's software and databases. Using the WFDB Toolbox for MATLAB/Octave, users have access to over 50 physiological databases in PhysioNet. The toolbox provides access over 4 TB of biomedical signals including ECG, EEG, EMG, and PLETH. Additionally, most signals are accompanied by metadata such as medical annotations of clinical events: arrhythmias, sleep stages, seizures, hypotensive episodes, etc. Users of this toolbox should easily be able to reproduce, validate, and compare results published based on PhysioNet's software and databases.

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

MATLAB-Based Program for Teaching Autocorrelation Function and Noise Concepts

ERIC Educational Resources Information Center

Jovanovic Dolecek, G.

2012-01-01

An attractive MATLAB-based tool for teaching the basics of autocorrelation function and noise concepts is presented in this paper. This tool enhances traditional in-classroom lecturing. The demonstrations of the tool described here highlight the description of the autocorrelation function (ACF) in a general case for wide-sense stationary (WSS)…

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.

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.

Multidimensional Recurrence Quantification Analysis (MdRQA) for the Analysis of Multidimensional Time-Series: A Software Implementation in MATLAB and Its Application to Group-Level Data in Joint Action

PubMed Central

Wallot, Sebastian; Roepstorff, Andreas; Mønster, Dan

2016-01-01

We introduce Multidimensional Recurrence Quantification Analysis (MdRQA) as a tool to analyze multidimensional time-series data. We show how MdRQA can be used to capture the dynamics of high-dimensional signals, and how MdRQA can be used to assess coupling between two or more variables. In particular, we describe applications of the method in research on joint and collective action, as it provides a coherent analysis framework to systematically investigate dynamics at different group levels—from individual dynamics, to dyadic dynamics, up to global group-level of arbitrary size. The Appendix in Supplementary Material contains a software implementation in MATLAB to calculate MdRQA measures. PMID:27920748

Multidimensional Recurrence Quantification Analysis (MdRQA) for the Analysis of Multidimensional Time-Series: A Software Implementation in MATLAB and Its Application to Group-Level Data in Joint Action.

PubMed

Wallot, Sebastian; Roepstorff, Andreas; Mønster, Dan

2016-01-01

We introduce Multidimensional Recurrence Quantification Analysis (MdRQA) as a tool to analyze multidimensional time-series data. We show how MdRQA can be used to capture the dynamics of high-dimensional signals, and how MdRQA can be used to assess coupling between two or more variables. In particular, we describe applications of the method in research on joint and collective action, as it provides a coherent analysis framework to systematically investigate dynamics at different group levels-from individual dynamics, to dyadic dynamics, up to global group-level of arbitrary size. The Appendix in Supplementary Material contains a software implementation in MATLAB to calculate MdRQA measures.

Cooperative path following control of multiple nonholonomic mobile robots.

PubMed

Cao, Ke-Cai; Jiang, Bin; Yue, Dong

2017-11-01

Cooperative path following control problem of multiple nonholonomic mobile robots has been considered in this paper. Based on the framework of decomposition, the cooperative path following problem has been transformed into path following problem and cooperative control problem; Then cascaded theory of non-autonomous system has been employed in the design of controllers without resorting to feedback linearization. One time-varying coordinate transformation based on dilation has been introduced to solve the uncontrollable problem of nonholonomic robots when the whole group's reference converges to stationary point. Cooperative path following controllers for nonholonomic robots have been proposed under persistent reference or reference target that converges to stationary point respectively. Simulation results using Matlab have illustrated the effectiveness of the obtained theoretical results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Methodology for creating dedicated machine and algorithm on sunflower counting

NASA Astrophysics Data System (ADS)

Muracciole, Vincent; Plainchault, Patrick; Mannino, Maria-Rosaria; Bertrand, Dominique; Vigouroux, Bertrand

2007-09-01

In order to sell grain lots in European countries, seed industries need a government certification. This certification requests purity testing, seed counting in order to quantify specified seed species and other impurities in lots, and germination testing. These analyses are carried out within the framework of international trade according to the methods of the International Seed Testing Association. Presently these different analyses are still achieved manually by skilled operators. Previous works have already shown that seeds can be characterized by around 110 visual features (morphology, colour, texture), and thus have presented several identification algorithms. Until now, most of the works in this domain are computer based. The approach presented in this article is based on the design of dedicated electronic vision machine aimed to identify and sort seeds. This machine is composed of a FPGA (Field Programmable Gate Array), a DSP (Digital Signal Processor) and a PC bearing the GUI (Human Machine Interface) of the system. Its operation relies on the stroboscopic image acquisition of a seed falling in front of a camera. A first machine was designed according to this approach, in order to simulate all the vision chain (image acquisition, feature extraction, identification) under the Matlab environment. In order to perform this task into dedicated hardware, all these algorithms were developed without the use of the Matlab toolbox. The objective of this article is to present a design methodology for a special purpose identification algorithm based on distance between groups into dedicated hardware machine for seed counting.

Investigation of an alternative generic model for predicting pharmacokinetic changes during physiological stress.

PubMed

Peng, Henry T; Edginton, Andrea N; Cheung, Bob

2013-10-01

Physiologically based pharmacokinetic models were developed using MATLAB Simulink® and PK-Sim®. We compared the capability and usefulness of these two models by simulating pharmacokinetic changes of midazolam under exercise and heat stress to verify the usefulness of MATLAB Simulink® as a generic PBPK modeling software. Although both models show good agreement with experimental data obtained under resting condition, their predictions of pharmacokinetics changes are less accurate in the stressful conditions. However, MATLAB Simulink® may be more flexible to include physiologically based processes such as oral absorption and simulate various stress parameters such as stress intensity, duration and timing of drug administration to improve model performance. Further work will be conducted to modify algorithms in our generic model developed using MATLAB Simulink® and to investigate pharmacokinetics under other physiological stress such as trauma. © The Author(s) 2013.

A Personal Navigation System Based on Inertial and Magnetic Field Measurements

DTIC Science & Technology

2010-09-01

MATLAB IMPLEMENTATION.................................................................74 G. A MODEL FOR PENDULUM MOTION SENSOR DATA...76 1. Pendulum Model for MATLAB Simulation....................................76 2. Sensor Data Generated with the Pendulum Model... PENDULUM ..................................................................................................88 I. FILTER PERFORMANCE WITH REAL PENDULUM DATA

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.

Blueprint XAS: a Matlab-based toolbox for the fitting and analysis of XAS spectra.

PubMed

Delgado-Jaime, Mario Ulises; Mewis, Craig Philip; Kennepohl, Pierre

2010-01-01

Blueprint XAS is a new Matlab-based program developed to fit and analyse X-ray absorption spectroscopy (XAS) data, most specifically in the near-edge region of the spectrum. The program is based on a methodology that introduces a novel background model into the complete fit model and that is capable of generating any number of independent fits with minimal introduction of user bias [Delgado-Jaime & Kennepohl (2010), J. Synchrotron Rad. 17, 119-128]. The functions and settings on the five panels of its graphical user interface are designed to suit the needs of near-edge XAS data analyzers. A batch function allows for the setting of multiple jobs to be run with Matlab in the background. A unique statistics panel allows the user to analyse a family of independent fits, to evaluate fit models and to draw statistically supported conclusions. The version introduced here (v0.2) is currently a toolbox for Matlab. Future stand-alone versions of the program will also incorporate several other new features to create a full package of tools for XAS data processing.

ACCEPT: Introduction of the Adverse Condition and Critical Event Prediction Toolbox

NASA Technical Reports Server (NTRS)

Martin, Rodney A.; Santanu, Das; Janakiraman, Vijay Manikandan; Hosein, Stefan

2015-01-01

The prediction of anomalies or adverse events is a challenging task, and there are a variety of methods which can be used to address the problem. In this paper, we introduce a generic framework developed in MATLAB (sup registered mark) called ACCEPT (Adverse Condition and Critical Event Prediction Toolbox). ACCEPT is an architectural framework designed to compare and contrast the performance of a variety of machine learning and early warning algorithms, and tests the capability of these algorithms to robustly predict the onset of adverse events in any time-series data generating systems or processes.

Simulation of creep effects in framework of a geometrically nonlinear endochronic theory of inelasticity

NASA Astrophysics Data System (ADS)

Zabavnikova, T. A.; Kadashevich, Yu. I.; Pomytkin, S. P.

2018-05-01

A geometric non-linear endochronic theory of inelasticity in tensor parametric form is considered. In the framework of this theory, the creep strains are modelled. The effect of various schemes of applying stresses and changing of material properties on the development of creep strains is studied. The constitutive equations of the model are represented by non-linear systems of ordinary differential equations which are solved in MATLAB environment by implicit difference method. Presented results demonstrate a good qualitative agreement of theoretical data and experimental observations including the description of the tertiary creep and pre-fracture of materials.

A platform for dynamic simulation and control of movement based on OpenSim and MATLAB.

PubMed

Mansouri, Misagh; Reinbolt, Jeffrey A

2012-05-11

Numerical simulations play an important role in solving complex engineering problems and have the potential to revolutionize medical decision making and treatment strategies. In this paper, we combine the rapid model-based design, control systems and powerful numerical method strengths of MATLAB/Simulink with the simulation and human movement dynamics strengths of OpenSim by developing a new interface between the two software tools. OpenSim is integrated with Simulink using the MATLAB S-function mechanism, and the interface is demonstrated using both open-loop and closed-loop control systems. While the open-loop system uses MATLAB/Simulink to separately reproduce the OpenSim Forward Dynamics Tool, the closed-loop system adds the unique feature of feedback control to OpenSim, which is necessary for most human movement simulations. An arm model example was successfully used in both open-loop and closed-loop cases. For the open-loop case, the simulation reproduced results from the OpenSim Forward Dynamics Tool with root mean square (RMS) differences of 0.03° for the shoulder elevation angle and 0.06° for the elbow flexion angle. MATLAB's variable step-size integrator reduced the time required to generate the forward dynamic simulation from 7.1s (OpenSim) to 2.9s (MATLAB). For the closed-loop case, a proportional-integral-derivative controller was used to successfully balance a pole on model's hand despite random force disturbances on the pole. The new interface presented here not only integrates the OpenSim and MATLAB/Simulink software tools, but also will allow neuroscientists, physiologists, biomechanists, and physical therapists to adapt and generate new solutions as treatments for musculoskeletal conditions. Copyright © 2012 Elsevier Ltd. All rights reserved.

Noble-TLBO MPPT Technique and its Comparative Analysis with Conventional methods implemented on Solar Photo Voltaic System

NASA Astrophysics Data System (ADS)

Patsariya, Ajay; Rai, Shiwani; Kumar, Yogendra, Dr.; Kirar, Mukesh, Dr.

2017-08-01

The energy crisis particularly with developing GDPs, has bring up to a new panorama of sustainable power source like solar energy, which has encountered huge development. Progressively high infiltration level of photovoltaic (PV) era emerges in keen matrix. Sunlight based power is irregular and variable, as the sun based source at the ground level is exceedingly subject to overcast cover inconstancy, environmental vaporized levels, and other climate parameters. The inalienable inconstancy of substantial scale sun based era acquaints huge difficulties with keen lattice vitality administration. Exact determining of sun powered power/irradiance is basic to secure financial operation of the shrewd framework. In this paper a noble TLBO-MPPT technique has been proposed to address the vitality of solar energy. A comparative analysis has been presented between conventional PO, IC and the proposed MPPT technique. The research has been done on Matlab Simulink software version 2013.

Rapid-X - An FPGA Development Toolset Using a Custom Simulink Library for MTCA.4 Modules

NASA Astrophysics Data System (ADS)

Prędki, Paweł; Heuer, Michael; Butkowski, Łukasz; Przygoda, Konrad; Schlarb, Holger; Napieralski, Andrzej

2015-06-01

The recent introduction of advanced hardware architectures such as the Micro Telecommunications Computing Architecture (MTCA) caused a change in the approach to implementation of control schemes in many fields. The development has been moving away from traditional programming languages ( C/C++), to hardware description languages (VHDL, Verilog), which are used in FPGA development. With MATLAB/Simulink it is possible to describe complex systems with block diagrams and simulate their behavior. Those diagrams are then used by the HDL experts to implement exactly the required functionality in hardware. Both the porting of existing applications and adaptation of new ones require a lot of development time from them. To solve this, Xilinx System Generator, a toolbox for MATLAB/Simulink, allows rapid prototyping of those block diagrams using hardware modelling. It is still up to the firmware developer to merge this structure with the hardware-dependent HDL project. This prevents the application engineer from quickly verifying the proposed schemes in real hardware. The framework described in this article overcomes these challenges, offering a hardware-independent library of components that can be used in Simulink/System Generator models. The components are subsequently translated into VHDL entities and integrated with a pre-prepared VHDL project template. Furthermore, the entire implementation process is run in the background, giving the user an almost one-click path from control scheme modelling and simulation to bit-file generation. This approach allows the application engineers to quickly develop new schemes and test them in real hardware environment. The applications may range from simple data logging or signal generation ones to very advanced controllers. Taking advantage of the Simulink simulation capabilities and user-friendly hardware implementation routines, the framework significantly decreases the development time of FPGA-based applications.

Tools for Integrating Data Access from the IRIS DMC into Research Workflows

NASA Astrophysics Data System (ADS)

Reyes, C. G.; Suleiman, Y. Y.; Trabant, C.; Karstens, R.; Weertman, B. R.

2012-12-01

Web service interfaces at the IRIS Data Management Center (DMC) provide access to a vast archive of seismological and related geophysical data. These interfaces are designed to easily incorporate data access into data processing workflows. Examples of data that may be accessed include: time series data, related metadata, and earthquake information. The DMC has developed command line scripts, MATLAB® interfaces and a Java library to support a wide variety of data access needs. Users of these interfaces do not need to concern themselves with web service details, networking, or even (in most cases) data conversion. Fetch scripts allow access to the DMC archive and are a comfortable fit for command line users. These scripts are written in Perl and are well suited for automation and integration into existing workflows on most operating systems. For metdata and event information, the Fetch scripts even parse the returned data into simple text summaries. The IRIS Java Web Services Library (IRIS-WS Library) allows Java developers the ability to create programs that access the DMC archives seamlessly. By returning the data and information as native Java objects the Library insulates the developer from data formats, network programming and web service details. The MATLAB interfaces leverage this library to allow users access to the DMC archive directly from within MATLAB (r2009b or newer), returning data into variables for immediate use. Data users and research groups are developing other toolkits that use the DMC's web services. Notably, the ObsPy framework developed at LMU Munich is a Python Toolbox that allows seamless access to data and information via the DMC services. Another example is the MATLAB-based GISMO and Waveform Suite developments that can now access data via web services. In summary, there now exist a host of ways that researchers can bring IRIS DMC data directly into their workflows. MATLAB users can use irisFetch.m, command line users can use the various Fetch scripts, Java users can use the IRIS-WS library, and Python users may request data through ObsPy. To learn more about any of these clients see http://www.iris.edu/ws/wsclients/.

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.

A Bayesian framework based on a Gaussian mixture model and radial-basis-function Fisher discriminant analysis (BayGmmKda V1.1) for spatial prediction of floods

NASA Astrophysics Data System (ADS)

Tien Bui, Dieu; Hoang, Nhat-Duc

2017-09-01

In this study, a probabilistic model, named as BayGmmKda, is proposed for flood susceptibility assessment in a study area in central Vietnam. The new model is a Bayesian framework constructed by a combination of a Gaussian mixture model (GMM), radial-basis-function Fisher discriminant analysis (RBFDA), and a geographic information system (GIS) database. In the Bayesian framework, GMM is used for modeling the data distribution of flood-influencing factors in the GIS database, whereas RBFDA is utilized to construct a latent variable that aims at enhancing the model performance. As a result, the posterior probabilistic output of the BayGmmKda model is used as flood susceptibility index. Experiment results showed that the proposed hybrid framework is superior to other benchmark models, including the adaptive neuro-fuzzy inference system and the support vector machine. To facilitate the model implementation, a software program of BayGmmKda has been developed in MATLAB. The BayGmmKda program can accurately establish a flood susceptibility map for the study region. Accordingly, local authorities can overlay this susceptibility map onto various land-use maps for the purpose of land-use planning or management.

OPTICON: Pro-Matlab software for large order controlled structure design

NASA Technical Reports Server (NTRS)

Peterson, Lee D.

1989-01-01

A software package for large order controlled structure design is described and demonstrated. The primary program, called OPTICAN, uses both Pro-Matlab M-file routines and selected compiled FORTRAN routines linked into the Pro-Matlab structure. The program accepts structural model information in the form of state-space matrices and performs three basic design functions on the model: (1) open loop analyses; (2) closed loop reduced order controller synthesis; and (3) closed loop stability and performance assessment. The current controller synthesis methods which were implemented in this software are based on the Generalized Linear Quadratic Gaussian theory of Bernstein. In particular, a reduced order Optimal Projection synthesis algorithm based on a homotopy solution method was successfully applied to an experimental truss structure using a 58-state dynamic model. These results are presented and discussed. Current plans to expand the practical size of the design model to several hundred states and the intention to interface Pro-Matlab to a supercomputing environment are discussed.

A data-driven dynamics simulation framework for railway vehicles

NASA Astrophysics Data System (ADS)

Nie, Yinyu; Tang, Zhao; Liu, Fengjia; Chang, Jian; Zhang, Jianjun

2018-03-01

The finite element (FE) method is essential for simulating vehicle dynamics with fine details, especially for train crash simulations. However, factors such as the complexity of meshes and the distortion involved in a large deformation would undermine its calculation efficiency. An alternative method, the multi-body (MB) dynamics simulation provides satisfying time efficiency but limited accuracy when highly nonlinear dynamic process is involved. To maintain the advantages of both methods, this paper proposes a data-driven simulation framework for dynamics simulation of railway vehicles. This framework uses machine learning techniques to extract nonlinear features from training data generated by FE simulations so that specific mesh structures can be formulated by a surrogate element (or surrogate elements) to replace the original mechanical elements, and the dynamics simulation can be implemented by co-simulation with the surrogate element(s) embedded into a MB model. This framework consists of a series of techniques including data collection, feature extraction, training data sampling, surrogate element building, and model evaluation and selection. To verify the feasibility of this framework, we present two case studies, a vertical dynamics simulation and a longitudinal dynamics simulation, based on co-simulation with MATLAB/Simulink and Simpack, and a further comparison with a popular data-driven model (the Kriging model) is provided. The simulation result shows that using the legendre polynomial regression model in building surrogate elements can largely cut down the simulation time without sacrifice in accuracy.

Comparing, optimizing, and benchmarking quantum-control algorithms in a unifying programming framework

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

Machnes, S.; Institute for Theoretical Physics, University of Ulm, D-89069 Ulm; Sander, U.

2011-08-15

For paving the way to novel applications in quantum simulation, computation, and technology, increasingly large quantum systems have to be steered with high precision. It is a typical task amenable to numerical optimal control to turn the time course of pulses, i.e., piecewise constant control amplitudes, iteratively into an optimized shape. Here, we present a comparative study of optimal-control algorithms for a wide range of finite-dimensional applications. We focus on the most commonly used algorithms: GRAPE methods which update all controls concurrently, and Krotov-type methods which do so sequentially. Guidelines for their use are given and open research questions aremore » pointed out. Moreover, we introduce a unifying algorithmic framework, DYNAMO (dynamic optimization platform), designed to provide the quantum-technology community with a convenient matlab-based tool set for optimal control. In addition, it gives researchers in optimal-control techniques a framework for benchmarking and comparing newly proposed algorithms with the state of the art. It allows a mix-and-match approach with various types of gradients, update and step-size methods as well as subspace choices. Open-source code including examples is made available at http://qlib.info.« less

The CARMEN software as a service infrastructure.

PubMed

Weeks, Michael; Jessop, Mark; Fletcher, Martyn; Hodge, Victoria; Jackson, Tom; Austin, Jim

2013-01-28

The CARMEN platform allows neuroscientists to share data, metadata, services and workflows, and to execute these services and workflows remotely via a Web portal. This paper describes how we implemented a service-based infrastructure into the CARMEN Virtual Laboratory. A Software as a Service framework was developed to allow generic new and legacy code to be deployed as services on a heterogeneous execution framework. Users can submit analysis code typically written in Matlab, Python, C/C++ and R as non-interactive standalone command-line applications and wrap them as services in a form suitable for deployment on the platform. The CARMEN Service Builder tool enables neuroscientists to quickly wrap their analysis software for deployment to the CARMEN platform, as a service without knowledge of the service framework or the CARMEN system. A metadata schema describes each service in terms of both system and user requirements. The search functionality allows services to be quickly discovered from the many services available. Within the platform, services may be combined into more complicated analyses using the workflow tool. CARMEN and the service infrastructure are targeted towards the neuroscience community; however, it is a generic platform, and can be targeted towards any discipline.

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.

Equilibrium-Staged Separations Using Matlab and Mathematica

ERIC Educational Resources Information Center

Binous, Housam

2008-01-01

We show a new approach, based on the utilization of Matlab and Mathematica, for solving liquid-liquid extraction and binary distillation problems. In addition, the author shares his experience using these two softwares to teach equilibrium staged separations at the National Institute of Applied Sciences and Technology. (Contains 7 figures.)

A web GIS based integrated flood assessment modeling tool for coastal urban watersheds

NASA Astrophysics Data System (ADS)

Kulkarni, A. T.; Mohanty, J.; Eldho, T. I.; Rao, E. P.; Mohan, B. K.

2014-03-01

Urban flooding has become an increasingly important issue in many parts of the world. In this study, an integrated flood assessment model (IFAM) is presented for the coastal urban flood simulation. A web based GIS framework has been adopted to organize the spatial datasets for the study area considered and to run the model within this framework. The integrated flood model consists of a mass balance based 1-D overland flow model, 1-D finite element based channel flow model based on diffusion wave approximation and a quasi 2-D raster flood inundation model based on the continuity equation. The model code is written in MATLAB and the application is integrated within a web GIS server product viz: Web Gram Server™ (WGS), developed at IIT Bombay, using Java, JSP and JQuery technologies. Its user interface is developed using open layers and the attribute data are stored in MySQL open source DBMS. The model is integrated within WGS and is called via Java script. The application has been demonstrated for two coastal urban watersheds of Navi Mumbai, India. Simulated flood extents for extreme rainfall event of 26 July, 2005 in the two urban watersheds of Navi Mumbai city are presented and discussed. The study demonstrates the effectiveness of the flood simulation tool in a web GIS environment to facilitate data access and visualization of GIS datasets and simulation results.

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…

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.

KEGGParser: parsing and editing KEGG pathway maps in Matlab.

PubMed

Arakelyan, Arsen; Nersisyan, Lilit

2013-02-15

KEGG pathway database is a collection of manually drawn pathway maps accompanied with KGML format files intended for use in automatic analysis. KGML files, however, do not contain the required information for complete reproduction of all the events indicated in the static image of a pathway map. Several parsers and editors of KEGG pathways exist for processing KGML files. We introduce KEGGParser-a MATLAB based tool for KEGG pathway parsing, semiautomatic fixing, editing, visualization and analysis in MATLAB environment. It also works with Scilab. The source code is available at http://www.mathworks.com/matlabcentral/fileexchange/37561.

Kinematic simulation and analysis of robot based on MATLAB

NASA Astrophysics Data System (ADS)

Liao, Shuhua; Li, Jiong

2018-03-01

The history of industrial automation is characterized by quick update technology, however, without a doubt, the industrial robot is a kind of special equipment. With the help of MATLAB matrix and drawing capacity in the MATLAB environment each link coordinate system set up by using the d-h parameters method and equation of motion of the structure. Robotics, Toolbox programming Toolbox and GUIDE to the joint application is the analysis of inverse kinematics and path planning and simulation, preliminary solve the problem of college students the car mechanical arm positioning theory, so as to achieve the aim of reservation.

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

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.

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.

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.

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.

A platform for dynamic simulation and control of movement based on OpenSim and MATLAB

PubMed Central

Mansouri, Misagh; Reinbolt, Jeffrey A.

2013-01-01

Numerical simulations play an important role in solving complex engineering problems and have the potential to revolutionize medical decision making and treatment strategies. In this paper, we combine the rapid model-based design, control systems and powerful numerical method strengths of MATLAB/Simulink with the simulation and human movement dynamics strengths of OpenSim by developing a new interface between the two software tools. OpenSim is integrated with Simulink using the MATLAB S-function mechanism, and the interface is demonstrated using both open-loop and closed-loop control systems. While the open-loop system uses MATLAB/Simulink to separately reproduce the OpenSim Forward Dynamics Tool, the closed-loop system adds the unique feature of feedback control to OpenSim, which is necessary for most human movement simulations. An arm model example was successfully used in both open-loop and closed-loop cases. For the open-loop case, the simulation reproduced results from the OpenSim Forward Dynamics Tool with root mean square (RMS) differences of 0.03° for the shoulder elevation angle and 0.06° for the elbow flexion angle. MATLAB’s variable step-size integrator reduced the time required to generate the forward dynamic simulation from 7.1 s (OpenSim) to 2.9 s (MATLAB). For the closed-loop case, a proportional–integral–derivative controller was used to successfully balance a pole on model’s hand despite random force disturbances on the pole. The new interface presented here not only integrates the OpenSim and MATLAB/Simulink software tools, but also will allow neuroscientists, physiologists, biomechanists, and physical therapists to adapt and generate new solutions as treatments for musculoskeletal conditions. PMID:22464351

Pyff - a pythonic framework for feedback applications and stimulus presentation in neuroscience.

PubMed

Venthur, Bastian; Scholler, Simon; Williamson, John; Dähne, Sven; Treder, Matthias S; Kramarek, Maria T; Müller, Klaus-Robert; Blankertz, Benjamin

2010-01-01

This paper introduces Pyff, the Pythonic feedback framework for feedback applications and stimulus presentation. Pyff provides a platform-independent framework that allows users to develop and run neuroscientific experiments in the programming language Python. Existing solutions have mostly been implemented in C++, which makes for a rather tedious programming task for non-computer-scientists, or in Matlab, which is not well suited for more advanced visual or auditory applications. Pyff was designed to make experimental paradigms (i.e., feedback and stimulus applications) easily programmable. It includes base classes for various types of common feedbacks and stimuli as well as useful libraries for external hardware such as eyetrackers. Pyff is also equipped with a steadily growing set of ready-to-use feedbacks and stimuli. It can be used as a standalone application, for instance providing stimulus presentation in psychophysics experiments, or within a closed loop such as in biofeedback or brain-computer interfacing experiments. Pyff communicates with other systems via a standardized communication protocol and is therefore suitable to be used with any system that may be adapted to send its data in the specified format. Having such a general, open-source framework will help foster a fruitful exchange of experimental paradigms between research groups. In particular, it will decrease the need of reprogramming standard paradigms, ease the reproducibility of published results, and naturally entail some standardization of stimulus presentation.

Pyff – A Pythonic Framework for Feedback Applications and Stimulus Presentation in Neuroscience

PubMed Central

Venthur, Bastian; Scholler, Simon; Williamson, John; Dähne, Sven; Treder, Matthias S.; Kramarek, Maria T.; Müller, Klaus-Robert; Blankertz, Benjamin

2010-01-01

This paper introduces Pyff, the Pythonic feedback framework for feedback applications and stimulus presentation. Pyff provides a platform-independent framework that allows users to develop and run neuroscientific experiments in the programming language Python. Existing solutions have mostly been implemented in C++, which makes for a rather tedious programming task for non-computer-scientists, or in Matlab, which is not well suited for more advanced visual or auditory applications. Pyff was designed to make experimental paradigms (i.e., feedback and stimulus applications) easily programmable. It includes base classes for various types of common feedbacks and stimuli as well as useful libraries for external hardware such as eyetrackers. Pyff is also equipped with a steadily growing set of ready-to-use feedbacks and stimuli. It can be used as a standalone application, for instance providing stimulus presentation in psychophysics experiments, or within a closed loop such as in biofeedback or brain–computer interfacing experiments. Pyff communicates with other systems via a standardized communication protocol and is therefore suitable to be used with any system that may be adapted to send its data in the specified format. Having such a general, open-source framework will help foster a fruitful exchange of experimental paradigms between research groups. In particular, it will decrease the need of reprogramming standard paradigms, ease the reproducibility of published results, and naturally entail some standardization of stimulus presentation. PMID:21160550

Teaching Tool for a Control Systems Laboratory Using a Quadrotor as a Plant in MATLAB

ERIC Educational Resources Information Center

Khan, Subhan; Jaffery, Mujtaba Hussain; Hanif, Athar; Asif, Muhammad Rizwan

2017-01-01

This paper presents a MATLAB-based application to teach the guidance, navigation, and control concepts of a quadrotor to undergraduate students, using a graphical user interface (GUI) and 3-D animations. The Simulink quadrotor model is controlled by a proportional integral derivative controller and a linear quadratic regulator controller. The GUI…

MOFA Software for the COBRA Toolbox

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

Griesemer, Marc; Navid, Ali

MOFA-COBRA is a software code for Matlab that performs Multi-Objective Flux Analysis (MOFA), a solving of linear programming problems. Teh leading software package for conducting different types of analyses using constrain-based models is the COBRA Toolbox for Matlab. MOFA-COBRA is an added tool for COBRA that solves multi-objective problems using a novel algorithm.

Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications.

PubMed

Kasabov, Nikola; Scott, Nathan Matthew; Tu, Enmei; Marks, Stefan; Sengupta, Neelava; Capecci, Elisa; Othman, Muhaini; Doborjeh, Maryam Gholami; Murli, Norhanifah; Hartono, Reggio; Espinosa-Ramos, Josafath Israel; Zhou, Lei; Alvi, Fahad Bashir; Wang, Grace; Taylor, Denise; Feigin, Valery; Gulyaev, Sergei; Mahmoud, Mahmoud; Hou, Zeng-Guang; Yang, Jie

2016-06-01

The paper describes a new type of evolving connectionist systems (ECOS) called evolving spatio-temporal data machines based on neuromorphic, brain-like information processing principles (eSTDM). These are multi-modular computer systems designed to deal with large and fast spatio/spectro temporal data using spiking neural networks (SNN) as major processing modules. ECOS and eSTDM in particular can learn incrementally from data streams, can include 'on the fly' new input variables, new output class labels or regression outputs, can continuously adapt their structure and functionality, can be visualised and interpreted for new knowledge discovery and for a better understanding of the data and the processes that generated it. eSTDM can be used for early event prediction due to the ability of the SNN to spike early, before whole input vectors (they were trained on) are presented. A framework for building eSTDM called NeuCube along with a design methodology for building eSTDM using this is presented. The implementation of this framework in MATLAB, Java, and PyNN (Python) is presented. The latter facilitates the use of neuromorphic hardware platforms to run the eSTDM. Selected examples are given of eSTDM for pattern recognition and early event prediction on EEG data, fMRI data, multisensory seismic data, ecological data, climate data, audio-visual data. Future directions are discussed, including extension of the NeuCube framework for building neurogenetic eSTDM and also new applications of eSTDM. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

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.

A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments.

PubMed

Al-Nawashi, Malek; Al-Hazaimeh, Obaida M; Saraee, Mohamad

2017-01-01

Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system that can perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic real-time video-based surveillance system which can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment. To develop our system, we have divided the work into three phases: preprocessing phase, abnormal human activity detection phase, and content-based image retrieval phase. For motion object detection, we used the temporal-differencing algorithm and then located the motions region using the Gaussian function. Furthermore, the shape model based on OMEGA equation was used as a filter for the detected objects (i.e., human and non-human). For object activities analysis, we evaluated and analyzed the human activities of the detected objects. We classified the human activities into two groups: normal activities and abnormal activities based on the support vector machine. The machine then provides an automatic warning in case of abnormal human activities. It also embeds a method to retrieve the detected object from the database for object recognition and identification using content-based image retrieval. Finally, a software-based simulation using MATLAB was performed and the results of the conducted experiments showed an excellent surveillance system that can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment with no human intervention.

Matlab Geochemistry: An open source geochemistry solver based on MRST

NASA Astrophysics Data System (ADS)

McNeece, C. J.; Raynaud, X.; Nilsen, H.; Hesse, M. A.

2017-12-01

The study of geological systems often requires the solution of complex geochemical relations. To address this need we present an open source geochemical solver based on the Matlab Reservoir Simulation Toolbox (MRST) developed by SINTEF. The implementation supports non-isothermal multicomponent aqueous complexation, surface complexation, ion exchange, and dissolution/precipitation reactions. The suite of tools available in MRST allows for rapid model development, in particular the incorporation of geochemical calculations into transport simulations of multiple phases, complex domain geometry and geomechanics. Different numerical schemes and additional physics can be easily incorporated into the existing tools through the object-oriented framework employed by MRST. The solver leverages the automatic differentiation tools available in MRST to solve arbitrarily complex geochemical systems with any choice of species or element concentration as input. Four mathematical approaches enable the solver to be quite robust: 1) the choice of chemical elements as the basis components makes all entries in the composition matrix positive thus preserving convexity, 2) a log variable transformation is used which transfers the nonlinearity to the convex composition matrix, 3) a priori bounds on variables are calculated from the structure of the problem, constraining Netwon's path and 4) an initial guess is calculated implicitly by sequentially adding model complexity. As a benchmark we compare the model to experimental and semi-analytic solutions of the coupled salinity-acidity transport system. Together with the reservoir simulation capabilities of MRST the solver offers a promising tool for geochemical simulations in reservoir domains for applications in a diversity of fields from enhanced oil recovery to radionuclide storage.

A Parallel Framework with Block Matrices of a Discrete Fourier Transform for Vector-Valued Discrete-Time Signals.

PubMed

Soto-Quiros, Pablo

2015-01-01

This paper presents a parallel implementation of a kind of discrete Fourier transform (DFT): the vector-valued DFT. The vector-valued DFT is a novel tool to analyze the spectra of vector-valued discrete-time signals. This parallel implementation is developed in terms of a mathematical framework with a set of block matrix operations. These block matrix operations contribute to analysis, design, and implementation of parallel algorithms in multicore processors. In this work, an implementation and experimental investigation of the mathematical framework are performed using MATLAB with the Parallel Computing Toolbox. We found that there is advantage to use multicore processors and a parallel computing environment to minimize the high execution time. Additionally, speedup increases when the number of logical processors and length of the signal increase.

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…

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…

Automation of PCXMC and ImPACT for NASA Astronaut Medical Imaging Dose and Risk Tracking

NASA Technical Reports Server (NTRS)

Bahadori, Amir; Picco, Charles; Flores-McLaughlin, John; Shavers, Mark; Semones, Edward

2011-01-01

To automate astronaut organ and effective dose calculations from occupational X-ray and computed tomography (CT) examinations incorporating PCXMC and ImPACT tools and to estimate the associated lifetime cancer risk per the National Council on Radiation Protection & Measurements (NCRP) using MATLAB(R). Methods: NASA follows guidance from the NCRP on its operational radiation safety program for astronauts. NCRP Report 142 recommends that astronauts be informed of the cancer risks from reported exposures to ionizing radiation from medical imaging. MATLAB(R) code was written to retrieve exam parameters for medical imaging procedures from a NASA database, calculate associated dose and risk, and return results to the database, using the Microsoft .NET Framework. This code interfaces with the PCXMC executable and emulates the ImPACT Excel spreadsheet to calculate organ doses from X-rays and CTs, respectively, eliminating the need to utilize the PCXMC graphical user interface (except for a few special cases) and the ImPACT spreadsheet. Results: Using MATLAB(R) code to interface with PCXMC and replicate ImPACT dose calculation allowed for rapid evaluation of multiple medical imaging exams. The user inputs the exam parameter data into the database and runs the code. Based on the imaging modality and input parameters, the organ doses are calculated. Output files are created for record, and organ doses, effective dose, and cancer risks associated with each exam are written to the database. Annual and post-flight exposure reports, which are used by the flight surgeon to brief the astronaut, are generated from the database. Conclusions: Automating PCXMC and ImPACT for evaluation of NASA astronaut medical imaging radiation procedures allowed for a traceable and rapid method for tracking projected cancer risks associated with over 12,000 exposures. This code will be used to evaluate future medical radiation exposures, and can easily be modified to accommodate changes to the risk calculation procedure.

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.

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

Science.gov Websites

| 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

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.

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.

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.

System Simulation of Nuclear Power Plant by Coupling RELAP5 and Matlab/Simulink

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

Meng Lin; Dong Hou; Zhihong Xu

2006-07-01

Since RELAP5 code has general and advanced features in thermal-hydraulic computation, it has been widely used in transient and accident safety analysis, experiment planning analysis, and system simulation, etc. So we wish to design, analyze, verify a new Instrumentation And Control (I and C) system of Nuclear Power Plant (NPP) based on the best-estimated code, and even develop our engineering simulator. But because of limited function of simulating control and protection system in RELAP5, it is necessary to expand the function for high efficient, accurate, flexible design and simulation of I and C system. Matlab/Simulink, a scientific computation software, justmore » can compensate the limitation, which is a powerful tool in research and simulation of plant process control. The software is selected as I and C part to be coupled with RELAP5 code to realize system simulation of NPPs. There are two key techniques to be solved. One is the dynamic data exchange, by which Matlab/Simulink receives plant parameters and returns control results. Database is used to communicate the two codes. Accordingly, Dynamic Link Library (DLL) is applied to link database in RELAP5, while DLL and S-Function is applied in Matlab/Simulink. The other problem is synchronization between the two codes for ensuring consistency in global simulation time. Because Matlab/Simulink always computes faster than RELAP5, the simulation time is sent by RELAP5 and received by Matlab/Simulink. A time control subroutine is added into the simulation procedure of Matlab/Simulink to control its simulation advancement. Through these ways, Matlab/Simulink is dynamically coupled with RELAP5. Thus, in Matlab/Simulink, we can freely design control and protection logic of NPPs and test it with best-estimated plant model feedback. A test will be shown to illuminate that results of coupling calculation are nearly the same with one of single RELAP5 with control logic. In practice, a real Pressurized Water Reactor (PWR) is modeled by RELAP5 code, and its main control and protection system is duplicated by Matlab/Simulink. Some steady states and transients are calculated under control of these I and C systems, and the results are compared with the plant test curves. The application showed that it can do exact system simulation of NPPs by coupling RELAP5 and Matlab/Simulink. This paper will mainly focus on the coupling method, plant thermal-hydraulic model, main control logics, test and application results. (authors)« less

Towards a Comprehensive Catalog of Volcanic Seismicity

NASA Astrophysics Data System (ADS)

Thompson, G.

2014-12-01

Catalogs of earthquakes located using differential travel-time techniques are a core product of volcano observatories, and while vital, they represent an incomplete perspective of volcanic seismicity. Many (often most) earthquakes are too small to locate accurately, and are omitted from available catalogs. Low frequency events, tremor and signals related to rockfalls, pyroclastic flows and lahars are not systematically catalogued, and yet from a hazard management perspective are exceedingly important. Because STA/LTA detection schemes break down in the presence of high amplitude tremor, swarms or dome collapses, catalogs may suggest low seismicity when seismicity peaks. We propose to develop a workflow and underlying software toolbox that can be applied to near-real-time and offline waveform data to produce comprehensive catalogs of volcanic seismicity. Existing tools to detect and locate phaseless signals will be adapted to fit within this framework. For this proof of concept the toolbox will be developed in MATLAB, extending the existing GISMO toolbox (an object-oriented MATLAB toolbox for seismic data analysis). Existing database schemas such as the CSS 3.0 will need to be extended to describe this wider range of volcano-seismic signals. WOVOdat may already incorporate many of the additional tables needed. Thus our framework may act as an interface between volcano observatories (or campaign-style research projects) and WOVOdat. We aim to take the further step of reducing volcano-seismic catalogs to sets of continuous metrics that are useful for recognizing data trends, and for feeding alarm systems and forecasting techniques. Previous experience has shown that frequency index, peak frequency, mean frequency, mean event rate, median event rate, and cumulative magnitude (or energy) are potentially useful metrics to generate for all catalogs at a 1-minute sample rate (directly comparable with RSAM and similar metrics derived from continuous data). Our framework includes tools to plot these metrics in a consistent manner. We work with data from unrest at Redoubt volcano and Soufriere Hills volcano to develop our framework.

Intelligent traffic lights based on MATLAB

NASA Astrophysics Data System (ADS)

Nie, Ying

2018-04-01

In this paper, I describes the traffic lights system and it has some. Through analysis, I used MATLAB technology, transformed the camera photographs into digital signals. Than divided the road vehicle is into three methods: very congestion, congestion, a little congestion. Through the MCU programming, solved the different roads have different delay time, and Used this method, saving time and resources, so as to reduce road congestion.

A Game-Theory Based Incentive Framework for an Intelligent Traffic System as Part of a Smart City Initiative.

PubMed

Mei, Haibo; Poslad, Stefan; Du, Shuang

2017-12-11

Intelligent Transportation Systems (ITSs) can be applied to inform and incentivize travellers to help them make cognizant choices concerning their trip routes and transport modality use for their daily travel whilst achieving more sustainable societal and transport authority goals. However, in practice, it is challenging for an ITS to enable incentive generation that is context-driven and personalized, whilst supporting multi-dimensional travel goals. This is because an ITS has to address the situation where different travellers have different travel preferences and constraints for route and modality, in the face of dynamically-varying traffic conditions. Furthermore, personalized incentive generation also needs to dynamically achieve different travel goals from multiple travellers, in the face of their conducts being a mix of both competitive and cooperative behaviours. To address this challenge, a Rule-based Incentive Framework (RIF) is proposed in this paper that utilizes both decision tree and evolutionary game theory to process travel information and intelligently generate personalized incentives for travellers. The travel information processed includes travellers' mobile patterns, travellers' modality preferences and route traffic volume information. A series of MATLAB simulations of RIF was undertaken to validate RIF to show that it is potentially an effective way to incentivize travellers to change travel routes and modalities as an essential smart city service.

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.

Quantitative assessment of computational models for retinotopic map formation

PubMed Central

Sterratt, David C; Cutts, Catherine S; Willshaw, David J; Eglen, Stephen J

2014-01-01

ABSTRACT Molecular and activity‐based cues acting together are thought to guide retinal axons to their terminal sites in vertebrate optic tectum or superior colliculus (SC) to form an ordered map of connections. The details of mechanisms involved, and the degree to which they might interact, are still not well understood. We have developed a framework within which existing computational models can be assessed in an unbiased and quantitative manner against a set of experimental data curated from the mouse retinocollicular system. Our framework facilitates comparison between models, testing new models against known phenotypes and simulating new phenotypes in existing models. We have used this framework to assess four representative models that combine Eph/ephrin gradients and/or activity‐based mechanisms and competition. Two of the models were updated from their original form to fit into our framework. The models were tested against five different phenotypes: wild type, Isl2‐EphA3 ki/ki, Isl2‐EphA3 ki/+, ephrin‐A2,A3,A5 triple knock‐out (TKO), and Math5 −/− (Atoh7). Two models successfully reproduced the extent of the Math5 −/− anteromedial projection, but only one of those could account for the collapse point in Isl2‐EphA3 ki/+. The models needed a weak anteroposterior gradient in the SC to reproduce the residual order in the ephrin‐A2,A3,A5 TKO phenotype, suggesting either an incomplete knock‐out or the presence of another guidance molecule. Our article demonstrates the importance of testing retinotopic models against as full a range of phenotypes as possible, and we have made available MATLAB software, we wrote to facilitate this process. © 2014 Wiley Periodicals, Inc. Develop Neurobiol 75: 641–666, 2015 PMID:25367067

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

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula

PubMed Central

Giordano, Bruno L.; Kayser, Christoph; Rousselet, Guillaume A.; Gross, Joachim; Schyns, Philippe G.

2016-01-01

Abstract We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open‐source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541–1573, 2017. © 2016 Wiley Periodicals, Inc. PMID:27860095

A Multi Agent System for Flow-Based Intrusion Detection

DTIC Science & Technology

2013-03-01

Student t-test, as it is less likely to spuriously indicate significance because of the presence of outliers [128]. We use the MATLAB ranksum function [77...effectiveness of self-organization and “ entangled hierarchies” for accomplishing scenario objectives. One of the interesting features of SOMAS is the ability...cross-validation and automatic model selection. It has interfaces for Java, Python, R, Splus, MATLAB , Perl, Ruby, and LabVIEW. Kernels: linear

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.

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

Improved Modeling in a Matlab-Based Navigation System

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Bar-Itzhack, Itzhack; Harman, Rick; Larimore, Wallace E.

1999-01-01

An innovative approach to autonomous navigation is available for low earth orbit satellites. The system is developed in Matlab and utilizes an Extended Kalman Filter (EKF) to estimate the attitude and trajectory based on spacecraft magnetometer and gyro data. Preliminary tests of the system with real spacecraft data from the Rossi X-Ray Timing Explorer Satellite (RXTE) indicate the existence of unmodeled errors in the magnetometer data. Incorporating into the EKF a statistical model that describes the colored component of the effective measurement of the magnetic field vector could improve the accuracy of the trajectory and attitude estimates and also improve the convergence time. This model is identified as a first order Markov process. With the addition of the model, the EKF attempts to identify the non-white components of the noise allowing for more accurate estimation of the original state vector, i.e. the orbital elements and the attitude. Working in Matlab allows for easy incorporation of new models into the EKF and the resulting navigation system is generic and can easily be applied to future missions resulting in an alternative in onboard or ground-based navigation.

Non-linear modelling and control of semi-active suspensions with variable damping

NASA Astrophysics Data System (ADS)

Chen, Huang; Long, Chen; Yuan, Chao-Chun; Jiang, Hao-Bin

2013-10-01

Electro-hydraulic dampers can provide variable damping force that is modulated by varying the command current; furthermore, they offer advantages such as lower power, rapid response, lower cost, and simple hardware. However, accurate characterisation of non-linear f-v properties in pre-yield and force saturation in post-yield is still required. Meanwhile, traditional linear or quarter vehicle models contain various non-linearities. The development of a multi-body dynamics model is very complex, and therefore, SIMPACK was used with suitable improvements for model development and numerical simulations. A semi-active suspension was built based on a belief-desire-intention (BDI)-agent model framework. Vehicle handling dynamics were analysed, and a co-simulation analysis was conducted in SIMPACK and MATLAB to evaluate the BDI-agent controller. The design effectively improved ride comfort, handling stability, and driving safety. A rapid control prototype was built based on dSPACE to conduct a real vehicle test. The test and simulation results were consistent, which verified the simulation.

ReTrOS: a MATLAB toolbox for reconstructing transcriptional activity from gene and protein expression data.

PubMed

Minas, Giorgos; Momiji, Hiroshi; Jenkins, Dafyd J; Costa, Maria J; Rand, David A; Finkenstädt, Bärbel

2017-06-26

Given the development of high-throughput experimental techniques, an increasing number of whole genome transcription profiling time series data sets, with good temporal resolution, are becoming available to researchers. The ReTrOS toolbox (Reconstructing Transcription Open Software) provides MATLAB-based implementations of two related methods, namely ReTrOS-Smooth and ReTrOS-Switch, for reconstructing the temporal transcriptional activity profile of a gene from given mRNA expression time series or protein reporter time series. The methods are based on fitting a differential equation model incorporating the processes of transcription, translation and degradation. The toolbox provides a framework for model fitting along with statistical analyses of the model with a graphical interface and model visualisation. We highlight several applications of the toolbox, including the reconstruction of the temporal cascade of transcriptional activity inferred from mRNA expression data and protein reporter data in the core circadian clock in Arabidopsis thaliana, and how such reconstructed transcription profiles can be used to study the effects of different cell lines and conditions. The ReTrOS toolbox allows users to analyse gene and/or protein expression time series where, with appropriate formulation of prior information about a minimum of kinetic parameters, in particular rates of degradation, users are able to infer timings of changes in transcriptional activity. Data from any organism and obtained from a range of technologies can be used as input due to the flexible and generic nature of the model and implementation. The output from this software provides a useful analysis of time series data and can be incorporated into further modelling approaches or in hypothesis generation.

MatchGUI: A Graphical MATLAB-Based Tool for Automatic Image Co-Registration

NASA Technical Reports Server (NTRS)

Ansar, Adnan I.

2011-01-01

MatchGUI software, based on MATLAB, automatically matches two images and displays the match result by superimposing one image on the other. A slider bar allows focus to shift between the two images. There are tools for zoom, auto-crop to overlap region, and basic image markup. Given a pair of ortho-rectified images (focused primarily on Mars orbital imagery for now), this software automatically co-registers the imagery so that corresponding image pixels are aligned. MatchGUI requires minimal user input, and performs a registration over scale and inplane rotation fully automatically

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

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.

Orbit Determination Toolbox

NASA Technical Reports Server (NTRS)

Carpenter, James R.; Berry, Kevin; Gregpru. Late; Speckman, Keith; Hur-Diaz, Sun; Surka, Derek; Gaylor, Dave

2010-01-01

The Orbit Determination Toolbox is an orbit determination (OD) analysis tool based on MATLAB and Java that provides a flexible way to do early mission analysis. The toolbox is primarily intended for advanced mission analysis such as might be performed in concept exploration, proposal, early design phase, or rapid design center environments. The emphasis is on flexibility, but it has enough fidelity to produce credible results. Insight into all flight dynamics source code is provided. MATLAB is the primary user interface and is used for piecing together measurement and dynamic models. The Java Astrodynamics Toolbox is used as an engine for things that might be slow or inefficient in MATLAB, such as high-fidelity trajectory propagation, lunar and planetary ephemeris look-ups, precession, nutation, polar motion calculations, ephemeris file parsing, and the like. The primary analysis functions are sequential filter/smoother and batch least-squares commands that incorporate Monte-Carlo data simulation, linear covariance analysis, measurement processing, and plotting capabilities at the generic level. These functions have a user interface that is based on that of the MATLAB ODE suite. To perform a specific analysis, users write MATLAB functions that implement truth and design system models. The user provides his or her models as inputs to the filter commands. The software provides a capability to publish and subscribe to a software bus that is compliant with the NASA Goddard Mission Services Evolution Center (GMSEC) standards, to exchange data with other flight dynamics tools to simplify the flight dynamics design cycle. Using the publish and subscribe approach allows for analysts in a rapid design center environment to seamlessly incorporate changes in spacecraft and mission design into navigation analysis and vice versa.

A Framework for the Comparative Assessment of Neuronal Spike Sorting Algorithms towards More Accurate Off-Line and On-Line Microelectrode Arrays Data Analysis.

PubMed

Regalia, Giulia; Coelli, Stefania; Biffi, Emilia; Ferrigno, Giancarlo; Pedrocchi, Alessandra

2016-01-01

Neuronal spike sorting algorithms are designed to retrieve neuronal network activity on a single-cell level from extracellular multiunit recordings with Microelectrode Arrays (MEAs). In typical analysis of MEA data, one spike sorting algorithm is applied indiscriminately to all electrode signals. However, this approach neglects the dependency of algorithms' performances on the neuronal signals properties at each channel, which require data-centric methods. Moreover, sorting is commonly performed off-line, which is time and memory consuming and prevents researchers from having an immediate glance at ongoing experiments. The aim of this work is to provide a versatile framework to support the evaluation and comparison of different spike classification algorithms suitable for both off-line and on-line analysis. We incorporated different spike sorting "building blocks" into a Matlab-based software, including 4 feature extraction methods, 3 feature clustering methods, and 1 template matching classifier. The framework was validated by applying different algorithms on simulated and real signals from neuronal cultures coupled to MEAs. Moreover, the system has been proven effective in running on-line analysis on a standard desktop computer, after the selection of the most suitable sorting methods. This work provides a useful and versatile instrument for a supported comparison of different options for spike sorting towards more accurate off-line and on-line MEA data analysis.

A Framework for the Comparative Assessment of Neuronal Spike Sorting Algorithms towards More Accurate Off-Line and On-Line Microelectrode Arrays Data Analysis

PubMed Central

Pedrocchi, Alessandra

2016-01-01

Neuronal spike sorting algorithms are designed to retrieve neuronal network activity on a single-cell level from extracellular multiunit recordings with Microelectrode Arrays (MEAs). In typical analysis of MEA data, one spike sorting algorithm is applied indiscriminately to all electrode signals. However, this approach neglects the dependency of algorithms' performances on the neuronal signals properties at each channel, which require data-centric methods. Moreover, sorting is commonly performed off-line, which is time and memory consuming and prevents researchers from having an immediate glance at ongoing experiments. The aim of this work is to provide a versatile framework to support the evaluation and comparison of different spike classification algorithms suitable for both off-line and on-line analysis. We incorporated different spike sorting “building blocks” into a Matlab-based software, including 4 feature extraction methods, 3 feature clustering methods, and 1 template matching classifier. The framework was validated by applying different algorithms on simulated and real signals from neuronal cultures coupled to MEAs. Moreover, the system has been proven effective in running on-line analysis on a standard desktop computer, after the selection of the most suitable sorting methods. This work provides a useful and versatile instrument for a supported comparison of different options for spike sorting towards more accurate off-line and on-line MEA data analysis. PMID:27239191

Stochastic nonlinear mixed effects: a metformin case study.

PubMed

Matzuka, Brett; Chittenden, Jason; Monteleone, Jonathan; Tran, Hien

2016-02-01

In nonlinear mixed effect (NLME) modeling, the intra-individual variability is a collection of errors due to assay sensitivity, dosing, sampling, as well as model misspecification. Utilizing stochastic differential equations (SDE) within the NLME framework allows the decoupling of the measurement errors from the model misspecification. This leads the SDE approach to be a novel tool for model refinement. Using Metformin clinical pharmacokinetic (PK) data, the process of model development through the use of SDEs in population PK modeling was done to study the dynamics of absorption rate. A base model was constructed and then refined by using the system noise terms of the SDEs to track model parameters and model misspecification. This provides the unique advantage of making no underlying assumptions about the structural model for the absorption process while quantifying insufficiencies in the current model. This article focuses on implementing the extended Kalman filter and unscented Kalman filter in an NLME framework for parameter estimation and model development, comparing the methodologies, and illustrating their challenges and utility. The Kalman filter algorithms were successfully implemented in NLME models using MATLAB with run time differences between the ODE and SDE methods comparable to the differences found by Kakhi for their stochastic deconvolution.

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.

The application of MATLAB-based analytic hierarchy process in Hainan residential quarter function factor evaluation

NASA Astrophysics Data System (ADS)

Qiu, Dongdong; Liu, Peiqi

2017-04-01

Since being designated as an international tourist island, Hainan has become an overwhelmingly favored choice of real estate investment. This paper first constructed Hainan residential quarter function factor index system, then evaluated relevant factors, and finally solved the problem of factor importance ranking. In this specific case, the software MATLAB was used to facilitate AHP calculation. The evaluation results have guiding and referential value to both real estate developers and residential consumers.

POST II Trajectory Animation Tool Using MATLAB, V1.0

NASA Technical Reports Server (NTRS)

Raiszadeh, Behzad

2005-01-01

A trajectory animation tool has been developed for accurately depicting position and the attitude of the bodies in flight. The movies generated from This MATLAB based tool serve as an engineering analysis aid to gain further understanding into the dynamic behavior of bodies in flight. This tool has been designed to interface with the output generated from POST II simulations, and is able to animate a single as well as multiple vehicles in flight.

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.

Statechart Analysis with Symbolic PathFinder

NASA Technical Reports Server (NTRS)

Pasareanu, Corina S.

2012-01-01

We report here on our on-going work that addresses the automated analysis and test case generation for software systems modeled using multiple Statechart formalisms. The work is motivated by large programs such as NASA Exploration, that involve multiple systems that interact via safety-critical protocols and are designed with different Statechart variants. To verify these safety-critical systems, we have developed Polyglot, a framework for modeling and analysis of model-based software written using different Statechart formalisms. Polyglot uses a common intermediate representation with customizable Statechart semantics and leverages the analysis and test generation capabilities of the Symbolic PathFinder tool. Polyglot is used as follows: First, the structure of the Statechart model (expressed in Matlab Stateflow or Rational Rhapsody) is translated into a common intermediate representation (IR). The IR is then translated into Java code that represents the structure of the model. The semantics are provided as "pluggable" modules.

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.

Design optimization for active twist rotor blades

NASA Astrophysics Data System (ADS)

Mok, Ji Won

This dissertation introduces the process of optimizing active twist rotor blades in the presence of embedded anisotropic piezo-composite actuators. Optimum design of active twist blades is a complex task, since it involves a rich design space with tightly coupled design variables. The study presents the development of an optimization framework for active helicopter rotor blade cross-sectional design. This optimization framework allows for exploring a rich and highly nonlinear design space in order to optimize the active twist rotor blades. Different analytical components are combined in the framework: cross-sectional analysis (UM/VABS), an automated mesh generator, a beam solver (DYMORE), a three-dimensional local strain recovery module, and a gradient based optimizer within MATLAB. Through the mathematical optimization problem, the static twist actuation performance of a blade is maximized while satisfying a series of blade constraints. These constraints are associated with locations of the center of gravity and elastic axis, blade mass per unit span, fundamental rotating blade frequencies, and the blade strength based on local three-dimensional strain fields under worst loading conditions. Through pre-processing, limitations of the proposed process have been studied. When limitations were detected, resolution strategies were proposed. These include mesh overlapping, element distortion, trailing edge tab modeling, electrode modeling and foam implementation of the mesh generator, and the initial point sensibility of the current optimization scheme. Examples demonstrate the effectiveness of this process. Optimization studies were performed on the NASA/Army/MIT ATR blade case. Even though that design was built and shown significant impact in vibration reduction, the proposed optimization process showed that the design could be improved significantly. The second example, based on a model scale of the AH-64D Apache blade, emphasized the capability of this framework to explore the nonlinear design space of complex planform. Especially for this case, detailed design is carried out to make the actual blade manufacturable. The proposed optimization framework is shown to be an effective tool to design high authority active twist blades to reduce vibration in future helicopter rotor blades.

Automation Framework for Flight Dynamics Products Generation

NASA Technical Reports Server (NTRS)

Wiegand, Robert E.; Esposito, Timothy C.; Watson, John S.; Jun, Linda; Shoan, Wendy; Matusow, Carla

2010-01-01

XFDS provides an easily adaptable automation platform. To date it has been used to support flight dynamics operations. It coordinates the execution of other applications such as Satellite TookKit, FreeFlyer, MATLAB, and Perl code. It provides a mechanism for passing messages among a collection of XFDS processes, and allows sending and receiving of GMSEC messages. A unified and consistent graphical user interface (GUI) is used for the various tools. Its automation configuration is stored in text files, and can be edited either directly or using the GUI.

Finite element based N-Port model for preliminary design of multibody systems

NASA Astrophysics Data System (ADS)

Sanfedino, Francesco; Alazard, Daniel; Pommier-Budinger, Valérie; Falcoz, Alexandre; Boquet, Fabrice

2018-02-01

This article presents and validates a general framework to build a linear dynamic Finite Element-based model of large flexible structures for integrated Control/Structure design. An extension of the Two-Input Two-Output Port (TITOP) approach is here developed. The authors had already proposed such framework for simple beam-like structures: each beam was considered as a TITOP sub-system that could be interconnected to another beam thanks to the ports. The present work studies bodies with multiple attaching points by allowing complex interconnections among several sub-structures in tree-like assembly. The TITOP approach is extended to generate NINOP (N-Input N-Output Port) models. A Matlab toolbox is developed integrating beam and bending plate elements. In particular a NINOP formulation of bending plates is proposed to solve analytic two-dimensional problems. The computation of NINOP models using the outputs of a MSC/Nastran modal analysis is also investigated in order to directly use the results provided by a commercial finite element software. The main advantage of this tool is to provide a model of a multibody system under the form of a block diagram with a minimal number of states. This model is easy to operate for preliminary design and control. An illustrative example highlights the potential of the proposed approach: the synthesis of the dynamical model of a spacecraft with two deployable and flexible solar arrays.

A Game-Theory Based Incentive Framework for an Intelligent Traffic System as Part of a Smart City Initiative

PubMed Central

Mei, Haibo; Poslad, Stefan; Du, Shuang

2017-01-01

Intelligent Transportation Systems (ITSs) can be applied to inform and incentivize travellers to help them make cognizant choices concerning their trip routes and transport modality use for their daily travel whilst achieving more sustainable societal and transport authority goals. However, in practice, it is challenging for an ITS to enable incentive generation that is context-driven and personalized, whilst supporting multi-dimensional travel goals. This is because an ITS has to address the situation where different travellers have different travel preferences and constraints for route and modality, in the face of dynamically-varying traffic conditions. Furthermore, personalized incentive generation also needs to dynamically achieve different travel goals from multiple travellers, in the face of their conducts being a mix of both competitive and cooperative behaviours. To address this challenge, a Rule-based Incentive Framework (RIF) is proposed in this paper that utilizes both decision tree and evolutionary game theory to process travel information and intelligently generate personalized incentives for travellers. The travel information processed includes travellers’ mobile patterns, travellers’ modality preferences and route traffic volume information. A series of MATLAB simulations of RIF was undertaken to validate RIF to show that it is potentially an effective way to incentivize travellers to change travel routes and modalities as an essential smart city service. PMID:29232907

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.

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula.

PubMed

Ince, Robin A A; Giordano, Bruno L; Kayser, Christoph; Rousselet, Guillaume A; Gross, Joachim; Schyns, Philippe G

2017-03-01

We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open-source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541-1573, 2017. © 2016 Wiley Periodicals, Inc. 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Hidden markov model for the prediction of transmembrane proteins using MATLAB.

PubMed

Chaturvedi, Navaneet; Shanker, Sudhanshu; Singh, Vinay Kumar; Sinha, Dhiraj; Pandey, Paras Nath

2011-01-01

Since membranous proteins play a key role in drug targeting therefore transmembrane proteins prediction is active and challenging area of biological sciences. Location based prediction of transmembrane proteins are significant for functional annotation of protein sequences. Hidden markov model based method was widely applied for transmembrane topology prediction. Here we have presented a revised and a better understanding model than an existing one for transmembrane protein prediction. Scripting on MATLAB was built and compiled for parameter estimation of model and applied this model on amino acid sequence to know the transmembrane and its adjacent locations. Estimated model of transmembrane topology was based on TMHMM model architecture. Only 7 super states are defined in the given dataset, which were converted to 96 states on the basis of their length in sequence. Accuracy of the prediction of model was observed about 74 %, is a good enough in the area of transmembrane topology prediction. Therefore we have concluded the hidden markov model plays crucial role in transmembrane helices prediction on MATLAB platform and it could also be useful for drug discovery strategy. The database is available for free at bioinfonavneet@gmail.comvinaysingh@bhu.ac.in.

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.

Moats and Drawbridges: An Isolation Primitive for Reconfigurable Hardware Based Systems

DTIC Science & Technology

2007-05-01

these systems, and after being run through an optimizing CAD tool the resulting circuit is a single entangled mess of gates and wires. To prevent the...translates MATLAB [48] algorithms into HDL, logic synthesis translates this HDL into a netlist, a synthesis tool uses a place-and-route algorithm to...Core Soft Core µ Soft P Core µP Core Hard Soft Algorithms MATLAB gcc ExecutableC Code HDL C Code Bitstream Place and Route NetlistLogic Synthesis EDK µP

Optimal service using Matlab - simulink controlled Queuing system at call centers

NASA Astrophysics Data System (ADS)

Balaji, N.; Siva, E. P.; Chandrasekaran, A. D.; Tamilazhagan, V.

2018-04-01

This paper presents graphical integrated model based academic research on telephone call centres. This paper introduces an important feature of impatient customers and abandonments in the queue system. However the modern call centre is a complex socio-technical system. Queuing theory has now become a suitable application in the telecom industry to provide better online services. Through this Matlab-simulink multi queuing structured models provide better solutions in complex situations at call centres. Service performance measures analyzed at optimal level through Simulink queuing model.

Predicting the performance of local seismic networks using Matlab and Google Earth.

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

Chael, Eric Paul

2009-11-01

We have used Matlab and Google Earth to construct a prototype application for modeling the performance of local seismic networks for monitoring small, contained explosions. Published equations based on refraction experiments provide estimates of peak ground velocities as a function of event distance and charge weight. Matlab routines implement these relations to calculate the amplitudes across a network of stations from sources distributed over a geographic grid. The amplitudes are then compared to ambient noise levels at the stations, and scaled to determine the smallest yield that could be detected at each source location by a specified minimum number ofmore » stations. We use Google Earth as the primary user interface, both for positioning the stations of a hypothetical local network, and for displaying the resulting detection threshold contours.« less

FPGA implemented testbed in 8-by-8 and 2-by-2 OFDM-MIMO channel estimation and design of baseband transceiver.

PubMed

Ramesh, S; Seshasayanan, R

2016-01-01

In this study, a baseband OFDM-MIMO framework with channel timing and estimation synchronization is composed and executed utilizing the FPGA innovation. The framework is prototyped in light of the IEEE 802.11a standard and the signals transmitted and received utilizing a data transmission of 20 MHz. With the assistance of the QPSK tweak, the framework can accomplish a throughput of 24 Mbps. Besides, the LS formula is executed and the estimation of a frequency-specific fading channel is illustrated. For the rough estimation of timing, MNC plan is examined and actualized. Above all else, the whole framework is demonstrated in MATLAB and a drifting point model is set up. At that point, the altered point model is made with the assistance of Simulink and Xilinx's System Generator for DSP. In this way, the framework is incorporated and actualized inside of Xilinx's ISE tools and focused to Xilinx Virtex 5 board. In addition, an equipment co-simulation is contrived to decrease the preparing time while figuring the BER of the fixed point model. The work concentrates on above all else venture for further examination of planning creative channel estimation strategies towards applications in the fourth era (4G) mobile correspondence frameworks.

Hidden attractors in dynamical models of phase-locked loop circuits: Limitations of simulation in MATLAB and SPICE

NASA Astrophysics Data System (ADS)

Kuznetsov, N. V.; Leonov, G. A.; Yuldashev, M. V.; Yuldashev, R. V.

2017-10-01

During recent years it has been shown that hidden oscillations, whose basin of attraction does not overlap with small neighborhoods of equilibria, may significantly complicate simulation of dynamical models, lead to unreliable results and wrong conclusions, and cause serious damage in drilling systems, aircrafts control systems, electromechanical systems, and other applications. This article provides a survey of various phase-locked loop based circuits (used in satellite navigation systems, optical, and digital communication), where such difficulties take place in MATLAB and SPICE. Considered examples can be used for testing other phase-locked loop based circuits and simulation tools, and motivate the development and application of rigorous analytical methods for the global analysis of phase-locked loop based circuits.

MATLAB Simulation of Gradient-Based Neural Network for Online Matrix Inversion

NASA Astrophysics Data System (ADS)

Zhang, Yunong; Chen, Ke; Ma, Weimu; Li, Xiao-Dong

This paper investigates the simulation of a gradient-based recurrent neural network for online solution of the matrix-inverse problem. Several important techniques are employed as follows to simulate such a neural system. 1) Kronecker product of matrices is introduced to transform a matrix-differential-equation (MDE) to a vector-differential-equation (VDE); i.e., finally, a standard ordinary-differential-equation (ODE) is obtained. 2) MATLAB routine "ode45" is introduced to solve the transformed initial-value ODE problem. 3) In addition to various implementation errors, different kinds of activation functions are simulated to show the characteristics of such a neural network. Simulation results substantiate the theoretical analysis and efficacy of the gradient-based neural network for online constant matrix inversion.

Using MATLAB software with Tomcat server and Java platform for remote image analysis in pathology.

PubMed

Markiewicz, Tomasz

2011-03-30

The Matlab software is a one of the most advanced development tool for application in engineering practice. From our point of view the most important is the image processing toolbox, offering many built-in functions, including mathematical morphology, and implementation of a many artificial neural networks as AI. It is very popular platform for creation of the specialized program for image analysis, also in pathology. Based on the latest version of Matlab Builder Java toolbox, it is possible to create the software, serving as a remote system for image analysis in pathology via internet communication. The internet platform can be realized based on Java Servlet Pages with Tomcat server as servlet container. In presented software implementation we propose remote image analysis realized by Matlab algorithms. These algorithms can be compiled to executable jar file with the help of Matlab Builder Java toolbox. The Matlab function must be declared with the set of input data, output structure with numerical results and Matlab web figure. Any function prepared in that manner can be used as a Java function in Java Servlet Pages (JSP). The graphical user interface providing the input data and displaying the results (also in graphical form) must be implemented in JSP. Additionally the data storage to database can be implemented within algorithm written in Matlab with the help of Matlab Database Toolbox directly with the image processing. The complete JSP page can be run by Tomcat server. The proposed tool for remote image analysis was tested on the Computerized Analysis of Medical Images (CAMI) software developed by author. The user provides image and case information (diagnosis, staining, image parameter etc.). When analysis is initialized, input data with image are sent to servlet on Tomcat. When analysis is done, client obtains the graphical results as an image with marked recognized cells and also the quantitative output. Additionally, the results are stored in a server database. The internet platform was tested on PC Intel Core2 Duo T9600 2.8 GHz 4 GB RAM server with 768x576 pixel size, 1.28 Mb tiff format images reffering to meningioma tumour (x400, Ki-67/MIB-1). The time consumption was as following: at analysis by CAMI, locally on a server - 3.5 seconds, at remote analysis - 26 seconds, from which 22 seconds were used for data transfer via internet connection. At jpg format image (102 Kb) the consumption time was reduced to 14 seconds. The results have confirmed that designed remote platform can be useful for pathology image analysis. The time consumption is depended mainly on the image size and speed of the internet connections. The presented implementation can be used for many types of analysis at different staining, tissue, morphometry approaches, etc. The significant problem is the implementation of the JSP page in the multithread form, that can be used parallelly by many users. The presented platform for image analysis in pathology can be especially useful for small laboratory without its own image analysis system.

Using MATLAB software with Tomcat server and Java platform for remote image analysis in pathology

PubMed Central

2011-01-01

Background The Matlab software is a one of the most advanced development tool for application in engineering practice. From our point of view the most important is the image processing toolbox, offering many built-in functions, including mathematical morphology, and implementation of a many artificial neural networks as AI. It is very popular platform for creation of the specialized program for image analysis, also in pathology. Based on the latest version of Matlab Builder Java toolbox, it is possible to create the software, serving as a remote system for image analysis in pathology via internet communication. The internet platform can be realized based on Java Servlet Pages with Tomcat server as servlet container. Methods In presented software implementation we propose remote image analysis realized by Matlab algorithms. These algorithms can be compiled to executable jar file with the help of Matlab Builder Java toolbox. The Matlab function must be declared with the set of input data, output structure with numerical results and Matlab web figure. Any function prepared in that manner can be used as a Java function in Java Servlet Pages (JSP). The graphical user interface providing the input data and displaying the results (also in graphical form) must be implemented in JSP. Additionally the data storage to database can be implemented within algorithm written in Matlab with the help of Matlab Database Toolbox directly with the image processing. The complete JSP page can be run by Tomcat server. Results The proposed tool for remote image analysis was tested on the Computerized Analysis of Medical Images (CAMI) software developed by author. The user provides image and case information (diagnosis, staining, image parameter etc.). When analysis is initialized, input data with image are sent to servlet on Tomcat. When analysis is done, client obtains the graphical results as an image with marked recognized cells and also the quantitative output. Additionally, the results are stored in a server database. The internet platform was tested on PC Intel Core2 Duo T9600 2.8GHz 4GB RAM server with 768x576 pixel size, 1.28Mb tiff format images reffering to meningioma tumour (x400, Ki-67/MIB-1). The time consumption was as following: at analysis by CAMI, locally on a server – 3.5 seconds, at remote analysis – 26 seconds, from which 22 seconds were used for data transfer via internet connection. At jpg format image (102 Kb) the consumption time was reduced to 14 seconds. Conclusions The results have confirmed that designed remote platform can be useful for pathology image analysis. The time consumption is depended mainly on the image size and speed of the internet connections. The presented implementation can be used for many types of analysis at different staining, tissue, morphometry approaches, etc. The significant problem is the implementation of the JSP page in the multithread form, that can be used parallelly by many users. The presented platform for image analysis in pathology can be especially useful for small laboratory without its own image analysis system. PMID:21489188

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.

Research and Implementation of Heart Sound Denoising

NASA Astrophysics Data System (ADS)

Liu, Feng; Wang, Yutai; Wang, Yanxiang

Heart sound is one of the most important signals. However, the process of getting heart sound signal can be interfered with many factors outside. Heart sound is weak electric signal and even weak external noise may lead to the misjudgment of pathological and physiological information in this signal, thus causing the misjudgment of disease diagnosis. As a result, it is a key to remove the noise which is mixed with heart sound. In this paper, a more systematic research and analysis which is involved in heart sound denoising based on matlab has been made. The study of heart sound denoising based on matlab firstly use the powerful image processing function of matlab to transform heart sound signals with noise into the wavelet domain through wavelet transform and decomposition these signals in muli-level. Then for the detail coefficient, soft thresholding is made using wavelet transform thresholding to eliminate noise, so that a signal denoising is significantly improved. The reconstructed signals are gained with stepwise coefficient reconstruction for the processed detail coefficient. Lastly, 50HZ power frequency and 35 Hz mechanical and electrical interference signals are eliminated using a notch filter.

nSTAT: Open-Source Neural Spike Train Analysis Toolbox for Matlab

PubMed Central

Cajigas, I.; Malik, W.Q.; Brown, E.N.

2012-01-01

Over the last decade there has been a tremendous advance in the analytical tools available to neuroscientists to understand and model neural function. In particular, the point process - Generalized Linear Model (PPGLM) framework has been applied successfully to problems ranging from neuro-endocrine physiology to neural decoding. However, the lack of freely distributed software implementations of published PP-GLM algorithms together with problem-specific modifications required for their use, limit wide application of these techniques. In an effort to make existing PP-GLM methods more accessible to the neuroscience community, we have developed nSTAT – an open source neural spike train analysis toolbox for Matlab®. By adopting an Object-Oriented Programming (OOP) approach, nSTAT allows users to easily manipulate data by performing operations on objects that have an intuitive connection to the experiment (spike trains, covariates, etc.), rather than by dealing with data in vector/matrix form. The algorithms implemented within nSTAT address a number of common problems including computation of peri-stimulus time histograms, quantification of the temporal response properties of neurons, and characterization of neural plasticity within and across trials. nSTAT provides a starting point for exploratory data analysis, allows for simple and systematic building and testing of point process models, and for decoding of stimulus variables based on point process models of neural function. By providing an open-source toolbox, we hope to establish a platform that can be easily used, modified, and extended by the scientific community to address limitations of current techniques and to extend available techniques to more complex problems. PMID:22981419

Modeling Control Strategies and Range Impacts for Electric Vehicle Integrated Thermal Management Systems with MATLAB/Simulink

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

Titov, Gene; Lustbader, Jason Aaron

The National Renewable Energy Laboratory's (NREL's) CoolSim MATLAB/Simulink modeling framework was used to explore control strategies for an electric vehicle combined loop system. Three system variants of increased complexity and efficiency were explored: a glycol-based positive temperature coefficient heater (PTC), PTC with power electronics and electric motor (PEEM) waste heat recovery, and PTC with PEEM waste heat recovery plus heat pump versions. Additionally, the benefit of electric motor preheating was considered. A two-level control strategy was developed where the mode selection and component control were treated separately. Only the parameters typically available by vehicle sensors were used to control themore » system. The control approach included a mode selection algorithm and controllers for the compressor speed, cabin blower flow rate, coolant flow rate, and the front-end heat exchanger coolant bypass rate. The electric motor was bypassed by the cooling circuit until its temperature exceeded the coolant inlet temperature. The impact of these thermal systems on electric vehicle range during warmup was simulated for the Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Test (HWFET2X) drive cycles weighted 45%/55% respectively. A range of ambient temperatures from -20 degrees C to +20 degrees C was considered. NREL's Future Automotive Systems Technology Simulator (FASTSim) vehicle modeling tool showed up to a 10.9% improvement in range for the full system over the baseline during warmup from cold soak. The full system with preheat showed up to 17% improvement in range.« less

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.

Design of high-performance parallelized gene predictors in MATLAB.

PubMed

Rivard, Sylvain Robert; Mailloux, Jean-Gabriel; Beguenane, Rachid; Bui, Hung Tien

2012-04-10

This paper proposes a method of implementing parallel gene prediction algorithms in MATLAB. The proposed designs are based on either Goertzel's algorithm or on FFTs and have been implemented using varying amounts of parallelism on a central processing unit (CPU) and on a graphics processing unit (GPU). Results show that an implementation using a straightforward approach can require over 4.5 h to process 15 million base pairs (bps) whereas a properly designed one could perform the same task in less than five minutes. In the best case, a GPU implementation can yield these results in 57 s. The present work shows how parallelism can be used in MATLAB for gene prediction in very large DNA sequences to produce results that are over 270 times faster than a conventional approach. This is significant as MATLAB is typically overlooked due to its apparent slow processing time even though it offers a convenient environment for bioinformatics. From a practical standpoint, this work proposes two strategies for accelerating genome data processing which rely on different parallelization mechanisms. Using a CPU, the work shows that direct access to the MEX function increases execution speed and that the PARFOR construct should be used in order to take full advantage of the parallelizable Goertzel implementation. When the target is a GPU, the work shows that data needs to be segmented into manageable sizes within the GFOR construct before processing in order to minimize execution time.

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.

The validity of birth and pregnancy histories in rural Bangladesh.

PubMed

Espeut, Donna; Becker, Stan

2015-08-28

Maternity histories provide a means of estimating fertility and mortality from surveys. The present analysis compares two types of maternity histories-birth histories and pregnancy histories-in three respects: (1) completeness of live birth and infant death reporting; (2) accuracy of the time placement of live births and infant deaths; and (3) the degree to which reported versus actual total fertility measures differ. The analysis covers a 15-year time span and is based on two data sources from Matlab, Bangladesh: the 1994 Matlab Demographic and Health Survey and, as gold standard, the vital events data from Matlab's Demographic Surveillance System. Both histories are near perfect in live-birth completeness; however, pregnancy histories do better in the completeness and time accuracy of deaths during the first year of life. Birth or pregnancy histories can be used for fertility estimation, but pregnancy histories are advised for estimating infant mortality.

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.

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

Dynamic Modeling and Simulation of an Underactuated System

NASA Astrophysics Data System (ADS)

Libardo Duarte Madrid, Juan; Ospina Henao, P. A.; González Querubín, E.

2017-06-01

In this paper, is used the Lagrangian classical mechanics for modeling the dynamics of an underactuated system, specifically a rotary inverted pendulum that will have two equations of motion. A basic design of the system is proposed in SOLIDWORKS 3D CAD software, which based on the material and dimensions of the model provides some physical variables necessary for modeling. In order to verify the results obtained, a comparison the CAD model simulated in the environment SimMechanics of MATLAB software with the mathematical model who was consisting of Euler-Lagrange’s equations implemented in Simulink MATLAB, solved with the ODE23tb method, included in the MATLAB libraries for the solution of systems of equations of the type and order obtained. This article also has a topological analysis of pendulum trajectories through a phase space diagram, which allows the identification of stable and unstable regions of the system.

Early Validation of Failure Detection, Isolation, and Recovery Design Using Heterogeneous Modelling and Simulation

NASA Astrophysics Data System (ADS)

van der Plas, Peter; Guerriero, Suzanne; Cristiano, Leorato; Rugina, Ana

2012-08-01

Modelling and simulation can support a number of use cases across the spacecraft development life-cycle. Given the increasing complexity of space missions, the observed general trend is for a more extensive usage of simulation already in the early phases. A major perceived advantage is that modelling and simulation can enable the validation of critical aspects of the spacecraft design before the actual development is started, as such reducing the risk in later phases.Failure Detection, Isolation, and Recovery (FDIR) is one of the areas with a high potential to benefit from early modelling and simulation. With the increasing level of required spacecraft autonomy, FDIR specifications can grow in such a way that the traditional document-based review process soon becomes inadequate.This paper shows that FDIR modelling and simulation in a system context can provide a powerful tool to support the FDIR verification process. It is highlighted that FDIR modelling at this early stage requires heterogeneous modelling tools and languages, in order to provide an adequate functional description of the different components (i.e. FDIR functions, environment, equipment, etc.) to be modelled.For this reason, an FDIR simulation framework is proposed in this paper. This framework is based on a number of tools already available in the Avionics Systems Laboratory at ESTEC, which are the Avionics Test Bench Functional Engineering Simulator (ATB FES), Matlab/Simulink, TASTE, and Real Time Developer Studio (RTDS).The paper then discusses the application of the proposed simulation framework to a real case-study, i.e. the FDIR modelling of a satellite in support of actual ESA mission. Challenges and benefits of the approach are described. Finally, lessons learned and the generality of the proposed approach are discussed.

Parametric modelling of cardiac system multiple measurement signals: an open-source computer framework for performance evaluation of ECG, PCG and ABP event detectors.

PubMed

Homaeinezhad, M R; Sabetian, P; Feizollahi, A; Ghaffari, A; Rahmani, R

2012-02-01

The major focus of this study is to present a performance accuracy assessment framework based on mathematical modelling of cardiac system multiple measurement signals. Three mathematical algebraic subroutines with simple structural functions for synthetic generation of the synchronously triggered electrocardiogram (ECG), phonocardiogram (PCG) and arterial blood pressure (ABP) signals are described. In the case of ECG signals, normal and abnormal PQRST cycles in complicated conditions such as fascicular ventricular tachycardia, rate dependent conduction block and acute Q-wave infarctions of inferior and anterolateral walls can be simulated. Also, continuous ABP waveform with corresponding individual events such as systolic, diastolic and dicrotic pressures with normal or abnormal morphologies can be generated by another part of the model. In addition, the mathematical synthetic PCG framework is able to generate the S4-S1-S2-S3 cycles in normal and in cardiac disorder conditions such as stenosis, insufficiency, regurgitation and gallop. In the PCG model, the amplitude and frequency content (5-700 Hz) of each sound and variation patterns can be specified. The three proposed models were implemented to generate artificial signals with varies abnormality types and signal-to-noise ratios (SNR), for quantitative detection-delineation performance assessment of several ECG, PCG and ABP individual event detectors designed based on the Hilbert transform, discrete wavelet transform, geometric features such as area curve length (ACLM), the multiple higher order moments (MHOM) metric, and the principal components analysed geometric index (PCAGI). For each method the detection-delineation operating characteristics were obtained automatically in terms of sensitivity, positive predictivity and delineation (segmentation) error rms and checked by the cardiologist. The Matlab m-file script of the synthetic ECG, ABP and PCG signal generators are available in the Appendix.

BCILAB: a platform for brain-computer interface development

NASA Astrophysics Data System (ADS)

Kothe, Christian Andreas; Makeig, Scott

2013-10-01

Objective. The past two decades have seen dramatic progress in our ability to model brain signals recorded by electroencephalography, functional near-infrared spectroscopy, etc., and to derive real-time estimates of user cognitive state, response, or intent for a variety of purposes: to restore communication by the severely disabled, to effect brain-actuated control and, more recently, to augment human-computer interaction. Continuing these advances, largely achieved through increases in computational power and methods, requires software tools to streamline the creation, testing, evaluation and deployment of new data analysis methods. Approach. Here we present BCILAB, an open-source MATLAB-based toolbox built to address the need for the development and testing of brain-computer interface (BCI) methods by providing an organized collection of over 100 pre-implemented methods and method variants, an easily extensible framework for the rapid prototyping of new methods, and a highly automated framework for systematic testing and evaluation of new implementations. Main results. To validate and illustrate the use of the framework, we present two sample analyses of publicly available data sets from recent BCI competitions and from a rapid serial visual presentation task. We demonstrate the straightforward use of BCILAB to obtain results compatible with the current BCI literature. Significance. The aim of the BCILAB toolbox is to provide the BCI community a powerful toolkit for methods research and evaluation, thereby helping to accelerate the pace of innovation in the field, while complementing the existing spectrum of tools for real-time BCI experimentation, deployment and use.

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

GIXSGUI : a MATLAB toolbox for grazing-incidence X-ray scattering data visualization and reduction, and indexing of buried three-dimensional periodic nanostructured films

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

Jiang, Zhang

GIXSGUIis a MATLAB toolbox that offers both a graphical user interface and script-based access to visualize and process grazing-incidence X-ray scattering data from nanostructures on surfaces and in thin films. It provides routine surface scattering data reduction methods such as geometric correction, one-dimensional intensity linecut, two-dimensional intensity reshapingetc. Three-dimensional indexing is also implemented to determine the space group and lattice parameters of buried organized nanoscopic structures in supported thin films.

Perinatal mortality attributable to complications of childbirth in Matlab, Bangladesh.

PubMed Central

Kusiako, T.; Ronsmans, C.; Van der Paal, L.

2000-01-01

Very few population-based studies of perinatal mortality in developing countries have examined the role of intrapartum risk factors. In the present study, the proportion of perinatal deaths that are attributable to complications during childbirth in Matlab, Bangladesh, was assessed using community-based data from a home-based programme led by professional midwives between 1987 and 1993. Complications during labour and delivery--such as prolonged or obstructed labour, abnormal fetal position, and hypertensive diseases of pregnancy--increased the risk of perinatal mortality fivefold and accounted for 30% of perinatal deaths. Premature labour, which occurred in 20% of pregnancies, accounted for 27% of perinatal mortality. Better care by qualified staff during delivery and improved care of newborns should substantially reduce perinatal mortality in this study population. PMID:10859856

PARALLELISATION OF THE MODEL-BASED ITERATIVE RECONSTRUCTION ALGORITHM DIRA.

PubMed

Örtenberg, A; Magnusson, M; Sandborg, M; Alm Carlsson, G; Malusek, A

2016-06-01

New paradigms for parallel programming have been devised to simplify software development on multi-core processors and many-core graphical processing units (GPU). Despite their obvious benefits, the parallelisation of existing computer programs is not an easy task. In this work, the use of the Open Multiprocessing (OpenMP) and Open Computing Language (OpenCL) frameworks is considered for the parallelisation of the model-based iterative reconstruction algorithm DIRA with the aim to significantly shorten the code's execution time. Selected routines were parallelised using OpenMP and OpenCL libraries; some routines were converted from MATLAB to C and optimised. Parallelisation of the code with the OpenMP was easy and resulted in an overall speedup of 15 on a 16-core computer. Parallelisation with OpenCL was more difficult owing to differences between the central processing unit and GPU architectures. The resulting speedup was substantially lower than the theoretical peak performance of the GPU; the cause was explained. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Development of Airport Noise Mapping using Matlab Software (Case Study: Adi Soemarmo Airport - Boyolali, Indonesia)

NASA Astrophysics Data System (ADS)

Andarani, Pertiwi; Setiyo Huboyo, Haryono; Setyanti, Diny; Budiawan, Wiwik

2018-02-01

Noise is considered as one of the main environmental impact of Adi Soemarmo International Airport (ASIA), the second largest airport in Central Java Province, Indonesia. In order to manage the noise of airport, airport noise mapping is necessary. However, a model that requires simple input but still reliable was not available in ASIA. Therefore, the objective of this study are to develop model using Matlab software, to verify its reliability by measuring actual noise exposure, and to analyze the area of noise levels‥ The model was developed based on interpolation or extrapolation of identified Noise-Power-Distance (NPD) data. In accordance with Indonesian Government Ordinance No.40/2012, the noise metric used is WECPNL (Weighted Equivalent Continuous Perceived Noise Level). Based on this model simulation, there are residence area in the region of noise level II (1.912 km2) and III (1.16 km2) and 18 school buildings in the area of noise levels I, II, and III. These land-uses are actually prohibited unless noise insulation is equipped. The model using Matlab in the case of Adi Soemarmo International Airport is valid based on comparison of the field measurement (6 sampling points). However, it is important to validate the model again once the case study (the airport) is changed.

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.

Earth Science Curriculum Enrichment Through Matlab!

NASA Astrophysics Data System (ADS)

Salmun, H.; Buonaiuto, F. S.

2016-12-01

The use of Matlab in Earth Science undergraduate courses in the Department of Geography at Hunter College began as a pilot project in Fall 2008 and has evolved and advanced to being a significant component of an Advanced Oceanography course, the selected tool for data analysis in other courses and the main focus of a graduate course for doctoral students at The city University of New York (CUNY) working on research related to geophysical, oceanic and atmospheric dynamics. The primary objectives of these efforts were to enhance the Earth Science curriculum through course specific applications, to increase undergraduate programming and data analysis skills, and to develop a Matlab users network within the Department and the broader Hunter College and CUNY community. Students have had the opportunity to learn Matlab as a stand-alone course, within an independent study group, or as a laboratory component within related STEM classes. All of these instructional efforts incorporated the use of prepackaged Matlab exercises and a research project. Initial exercises were designed to cover basic scripting and data visualization techniques. Students were provided data and a skeleton script to modify and improve upon based on the laboratory instructions. As student's programming skills increased throughout the semester more advanced scripting, data mining and data analysis were assigned. In order to illustrate the range of applications within the Earth Sciences, laboratory exercises were constructed around topics selected from the disciplines of Geology, Physics, Oceanography, Meteorology and Climatology. In addition the structure of the research component of the courses included both individual and team projects.

Matlab Based LOCO

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

Portmann, Greg; /LBL, Berkeley; Safranek, James

The LOCO algorithm has been used by many accelerators around the world. Although the uses for LOCO vary, the most common use has been to find calibration errors and correct the optics functions. The light source community in particular has made extensive use of the LOCO algorithms to tightly control the beta function and coupling. Maintaining high quality beam parameters requires constant attention so a relatively large effort was put into software development for the LOCO application. The LOCO code was originally written in FORTRAN. This code worked fine but it was somewhat awkward to use. For instance, the FORTRANmore » code itself did not calculate the model response matrix. It required a separate modeling code such as MAD to calculate the model matrix then one manually loads the data into the LOCO code. As the number of people interested in LOCO grew, it required making it easier to use. The decision to port LOCO to Matlab was relatively easy. It's best to use a matrix programming language with good graphics capability; Matlab was also being used for high level machine control; and the accelerator modeling code AT, [5], was already developed for Matlab. Since LOCO requires collecting and processing a relative large amount of data, it is very helpful to have the LOCO code compatible with the high level machine control, [3]. A number of new features were added while porting the code from FORTRAN and new methods continue to evolve, [7][9]. Although Matlab LOCO was written with AT as the underlying tracking code, a mechanism to connect to other modeling codes has been provided.« less

A comparison of sisterhood information on causes of maternal death with the registration causes of maternal death in Matlab, Bangladesh.

PubMed

Shahidullah, M

1995-10-01

To explore whether causes of maternal death can be investigated using the sisterhood method, an indirect method for providing a community-based estimate of the level of maternal mortality, this study compares the sisterhood causes of maternal death with the Matlab Demographic Surveillance System's (DSS) causes of maternal death. Data for this study came from the Matlab DSS, which has been in operation since 1966 as a field site of the International Centre for Diarrhoeal Disease Research, Bangladesh. The maternal deaths that occurred during the 15-year period from 1976 to 1990 in the Matlab DSS area are the basis of this study. A sisterhood survey was conducted in Matlab in November and December 1991 to collect information on conditions, events and symptoms that preceded death. The collected information was evaluated to assign a most likely cause of maternal death. The sisterhood survey cause of maternal death was then compared with the DSS cause of maternal death. Cause of death could not be assigned with reasonable confidence for 34 (11%) of the 305 maternal deaths for which information was collected. For the remaining deaths, the agreement between the two classification systems was generally high for most cause-of-death categories considered. Though cause-of-death information obtained by the sisterhood method will always be subject to some error, it can provide an indication of an overall distribution of causes of maternal deaths. This data can be used for the planning of programmes aimed at reducing maternal mortality and for the evaluation of such programmes over time.

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.

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/.

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.

Dynamic quality of service model for improving performance of multimedia real-time transmission in industrial networks.

PubMed

Gopalakrishnan, Ravichandran C; Karunakaran, Manivannan

2014-01-01

Nowadays, quality of service (QoS) is very popular in various research areas like distributed systems, multimedia real-time applications and networking. The requirements of these systems are to satisfy reliability, uptime, security constraints and throughput as well as application specific requirements. The real-time multimedia applications are commonly distributed over the network and meet various time constraints across networks without creating any intervention over control flows. In particular, video compressors make variable bit-rate streams that mismatch the constant-bit-rate channels typically provided by classical real-time protocols, severely reducing the efficiency of network utilization. Thus, it is necessary to enlarge the communication bandwidth to transfer the compressed multimedia streams using Flexible Time Triggered- Enhanced Switched Ethernet (FTT-ESE) protocol. FTT-ESE provides automation to calculate the compression level and change the bandwidth of the stream. This paper focuses on low-latency multimedia transmission over Ethernet with dynamic quality-of-service (QoS) management. This proposed framework deals with a dynamic QoS for multimedia transmission over Ethernet with FTT-ESE protocol. This paper also presents distinct QoS metrics based both on the image quality and network features. Some experiments with recorded and live video streams show the advantages of the proposed framework. To validate the solution we have designed and implemented a simulator based on the Matlab/Simulink, which is a tool to evaluate different network architecture using Simulink blocks.

WaLA, a versatile model for the life cycle assessment of urban water systems: Formalism and framework for a modular approach.

PubMed

Loubet, Philippe; Roux, Philippe; Bellon-Maurel, Véronique

2016-01-01

The emphasis on the sustainable urban water management has increased over the last decades. In this context decision makers need tools to measure and improve the environmental performance of urban water systems (UWS) and their related scenarios. In this paper, we propose a versatile model, named WaLA (Water system Life cycle Assessment), which reduces the complexity of the UWS while ensuring a good representation of water issues and fulfilling life cycle assessment (LCA) requirements. Indeed, LCAs require building UWS models, which can be tedious if several scenarios are to be compared. The WaLA model is based on a framework that uses a "generic component" representing alternately water technology units and water users, with their associated water flows, and the associated impacts due to water deprivation, emissions, operation and infrastructure. UWS scenarios can be built by inter-operating and connecting the technologies and users components in a modular and integrated way. The model calculates life cycle impacts at a monthly temporal resolution for a set of services provided to users, as defined by the scenario. It also provides the ratio of impacts to amount of services provided and useful information for UWS diagnosis or comparison of different scenarios. The model is implemented in a Matlab/Simulink interface thanks to object-oriented programming. The applicability of the model is demonstrated using a virtual case study based on available life cycle inventory data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparative analysis of existing models for power-grid synchronization

NASA Astrophysics Data System (ADS)

Nishikawa, Takashi; Motter, Adilson E.

2015-01-01

The dynamics of power-grid networks is becoming an increasingly active area of research within the physics and network science communities. The results from such studies are typically insightful and illustrative, but are often based on simplifying assumptions that can be either difficult to assess or not fully justified for realistic applications. Here we perform a comprehensive comparative analysis of three leading models recently used to study synchronization dynamics in power-grid networks—a fundamental problem of practical significance given that frequency synchronization of all power generators in the same interconnection is a necessary condition for a power grid to operate. We show that each of these models can be derived from first principles within a common framework based on the classical model of a generator, thereby clarifying all assumptions involved. This framework allows us to view power grids as complex networks of coupled second-order phase oscillators with both forcing and damping terms. Using simple illustrative examples, test systems, and real power-grid datasets, we study the inherent frequencies of the oscillators as well as their coupling structure, comparing across the different models. We demonstrate, in particular, that if the network structure is not homogeneous, generators with identical parameters need to be modeled as non-identical oscillators in general. We also discuss an approach to estimate the required (dynamical) system parameters that are unavailable in typical power-grid datasets, their use for computing the constants of each of the three models, and an open-source MATLAB toolbox that we provide for these computations.

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.

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.

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

EAGLE: 'EAGLE'Is an' Algorithmic Graph Library for Exploration

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

2015-01-16

The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. Today there is no tools to conduct "graph mining" on RDF standard data sets. We address that need through implementation of popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, degree distribution,more » diversity degree, PageRank, etc.). We implement these algorithms as SPARQL queries, wrapped within Python scripts and call our software tool as EAGLE. In RDF style, EAGLE stands for "EAGLE 'Is an' algorithmic graph library for exploration. EAGLE is like 'MATLAB' for 'Linked Data.'« less

The Kepler Science Operations Center Pipeline Framework Extensions

NASA Technical Reports Server (NTRS)

Klaus, Todd C.; Cote, Miles T.; McCauliff, Sean; Girouard, Forrest R.; Wohler, Bill; Allen, Christopher; Chandrasekaran, Hema; Bryson, Stephen T.; Middour, Christopher; Caldwell, Douglas A.;

Hybrid modeling method for a DEP based particle manipulation.

PubMed

Miled, Mohamed Amine; Gagne, Antoine; Sawan, Mohamad

2013-01-30

In this paper, a new modeling approach for Dielectrophoresis (DEP) based particle manipulation is presented. The proposed method fulfills missing links in finite element modeling between the multiphysic simulation and the biological behavior. This technique is amongst the first steps to develop a more complex platform covering several types of manipulations such as magnetophoresis and optics. The modeling approach is based on a hybrid interface using both ANSYS and MATLAB to link the propagation of the electrical field in the micro-channel to the particle motion. ANSYS is used to simulate the electrical propagation while MATLAB interprets the results to calculate cell displacement and send the new information to ANSYS for another turn. The beta version of the proposed technique takes into account particle shape, weight and its electrical properties. First obtained results are coherent with experimental results.

Hybrid Modeling Method for a DEP Based Particle Manipulation

PubMed Central

Miled, Mohamed Amine; Gagne, Antoine; Sawan, Mohamad

2013-01-01

In this paper, a new modeling approach for Dielectrophoresis (DEP) based particle manipulation is presented. The proposed method fulfills missing links in finite element modeling between the multiphysic simulation and the biological behavior. This technique is amongst the first steps to develop a more complex platform covering several types of manipulations such as magnetophoresis and optics. The modeling approach is based on a hybrid interface using both ANSYS and MATLAB to link the propagation of the electrical field in the micro-channel to the particle motion. ANSYS is used to simulate the electrical propagation while MATLAB interprets the results to calculate cell displacement and send the new information to ANSYS for another turn. The beta version of the proposed technique takes into account particle shape, weight and its electrical properties. First obtained results are coherent with experimental results. PMID:23364197

A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm.

PubMed

Dethier, Julie; Nuyujukian, Paul; Eliasmith, Chris; Stewart, Terry; Elassaad, Shauki A; Shenoy, Krishna V; Boahen, Kwabena

2011-01-01

Motor prostheses aim to restore function to disabled patients. Despite compelling proof of concept systems, barriers to clinical translation remain. One challenge is to develop a low-power, fully-implantable system that dissipates only minimal power so as not to damage tissue. To this end, we implemented a Kalman-filter based decoder via a spiking neural network (SNN) and tested it in brain-machine interface (BMI) experiments with a rhesus monkey. The Kalman filter was trained to predict the arm's velocity and mapped on to the SNN using the Neural Engineering Framework (NEF). A 2,000-neuron embedded Matlab SNN implementation runs in real-time and its closed-loop performance is quite comparable to that of the standard Kalman filter. The success of this closed-loop decoder holds promise for hardware SNN implementations of statistical signal processing algorithms on neuromorphic chips, which may offer power savings necessary to overcome a major obstacle to the successful clinical translation of neural motor prostheses.

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.

Deterministic seismic hazard macrozonation of India

NASA Astrophysics Data System (ADS)

Kolathayar, Sreevalsa; Sitharam, T. G.; Vipin, K. S.

2012-10-01

Earthquakes are known to have occurred in Indian subcontinent from ancient times. This paper presents the results of seismic hazard analysis of India (6°-38°N and 68°-98°E) based on the deterministic approach using latest seismicity data (up to 2010). The hazard analysis was done using two different source models (linear sources and point sources) and 12 well recognized attenuation relations considering varied tectonic provinces in the region. The earthquake data obtained from different sources were homogenized and declustered and a total of 27,146 earthquakes of moment magnitude 4 and above were listed in the study area. The sesismotectonic map of the study area was prepared by considering the faults, lineaments and the shear zones which are associated with earthquakes of magnitude 4 and above. A new program was developed in MATLAB for smoothing of the point sources. For assessing the seismic hazard, the study area was divided into small grids of size 0.1° × 0.1° (approximately 10 × 10 km), and the hazard parameters were calculated at the center of each of these grid cells by considering all the seismic sources within a radius of 300 to 400 km. Rock level peak horizontal acceleration (PHA) and spectral accelerations for periods 0.1 and 1 s have been calculated for all the grid points with a deterministic approach using a code written in MATLAB. Epistemic uncertainty in hazard definition has been tackled within a logic-tree framework considering two types of sources and three attenuation models for each grid point. The hazard evaluation without logic tree approach also has been done for comparison of the results. The contour maps showing the spatial variation of hazard values are presented in the paper.

Tool for Generation of MAC/GMC Representative Unit Cell for CMC/PMC Analysis

NASA Technical Reports Server (NTRS)

Murthy, Pappu L. N.; Pineda, Evan J.

2016-01-01

This document describes a recently developed analysis tool that enhances the resident capabilities of the Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) 4.0. This tool is especially useful in analyzing ceramic matrix composites (CMCs), where higher fidelity with improved accuracy of local response is needed. The tool, however, can be used for analyzing polymer matrix composites (PMCs) as well. MAC/GMC 4.0 is a composite material and laminate analysis software developed at NASA Glenn Research Center. The software package has been built around the concept of the generalized method of cells (GMC). 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 thermomechanical 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 primary focus of the current effort is to provide a graphical user interface (GUI) capability that generates a number of different user-defined repeating unit cells (RUCs). In addition, the code has provisions for generation of a MAC/GMC-compatible input text file that can be merged with any MAC/GMC input file tailored to analyze composite materials. Although the primary intention was to address the three different constituents and phases that are usually present in CMCs-namely, fibers, matrix, and interphase-it can be easily modified to address two-phase polymer matrix composite (PMC) materials where an interphase is absent. Currently, the tool capability includes generation of RUCs for square packing, hexagonal packing, and random fiber packing as well as RUCs based on actual composite micrographs. All these options have the fibers modeled as having a circular cross-sectional area. In addition, a simplified version of RUC is provided where the fibers are treated as having a square cross section and are distributed randomly. This RUC facilitates a speedy analysis using the higher fidelity version of GMC known as HFGMC. The first four mentioned options above support uniform subcell discretization. The last one has variable subcell sizes due to the primary intention of keeping the RUC size to a minimum to gain the speed ups using the higher fidelity version of MAC. The code is implemented within the MATLAB (The Mathworks, Inc., Natick, MA) developmental framework; however, a standalone application that does not need a priori MATLAB installation is also created with the aid of the MATLAB compiler.

A multidimensional approach to measure poverty in rural Bangladesh.

PubMed

Bhuiya, Abbas; Mahmood, Shehrin Shaila; Rana, A K M Masud; Wahed, Tania; Ahmed, Syed Masud; Chowdhury, A Mushtaque R

2007-06-01

Poverty is increasingly being understood as a multidimensional phenomenon. Other than income-consumption, which has been extensively studied in the past, health, education, shelter, and social involvement are among the most important dimensions of poverty. The present study attempts to develop a simple tool to measure poverty in its multidimensionality where it views poverty as an inadequate fulfillment of basic needs, such as food, clothing, shelter, health, education, and social involvement. The scale score ranges between 72 and 24 and is constructed in such a way that the score increases with increasing level of poverty. Using various techniques, the study evaluates the poverty-measurement tool and provides evidence for its reliability and validity by administering it in various areas of rural Bangladesh. The reliability coefficients, such as test-retest coefficient (0.85) and Cronbach's alpha (0.80) of the tool, were satisfactorily high. Based on the socioeconomic status defined by the participatory rural appraisal (PRA) exercise, the level of poverty identified by the scale was 33% in Chakaria, 26% in Matlab, and 32% in other rural areas of the country. The validity of these results was tested against some traditional methods of identifying the poor, and the association of the scores with that of the traditional indicators, such as ownership of land and occupation, asset index (r=0.72), and the wealth ranking obtained from the PRA exercise, was consistent. A statistically significant inverse relationship of the poverty scores with the socioeconomic status was observed in all cases. The scale also allowed the absolute level of poverty to be measured, and in the present study, the highest percentage of absolute poor was found in terms of health (44.2% in Chakaria, 36.4% in Matlab, and 39.1% in other rural areas), followed by social exclusion (35.7% in Chakaria, 28.5% in Matlab, and 22.3% in other rural areas), clothing (6.2% in Chakaria, 8.3% in Matlab, and 20% in other rural areas), education (14.7% in Chakaria, 8% in Matlab, and 16.8% in other rural areas), food (7.8% in Chakaria, 2.9% in Matlab and 3% in other rural areas), and shelter (0.8% in Chakaria, 1.4% in Matlab, and 3.7% in other rural areas). This instrument will also prove itself invaluable in assessing the individual effects of poverty-alleviation programmes or policies on all these different dimensions.

A Multidimensional Approach to Measure Poverty in Rural Bangladesh

PubMed Central

Bhuiya, Abbas; Shaila Mahmood, Shehrin; Rana, A.K.M. Masud; Wahed, Tania; Ahmed, Syed Masud; Chowdhury, A. Mushtaque R.

2007-01-01

Poverty is increasingly being understood as a multidimensional phenomenon. Other than income-consumption, which has been extensively studied in the past, health, education, shelter, and social involvement are among the most important dimensions of poverty. The present study attempts to develop a simple tool to measure poverty in its multidimensionality where it views poverty as an inadequate fulfillment of basic needs, such as food, clothing, shelter, health, education, and social involvement. The scale score ranges between 72 and 24 and is constructed in such a way that the score increases with increasing level of poverty. Using various techniques, the study evaluates the poverty-measurement tool and provides evidence for its reliability and validity by administering it in various areas of rural Bangladesh. The reliability coefficients, such as test-retest coefficient (0.85) and Cronbach's alpha (0.80) of the tool, were satisfactorily high. Based on the socioeconomic status defined by the participatory rural appraisal (PRA) exercise, the level of poverty identified by the scale was 33% in Chakaria, 26% in Matlab, and 32% in other rural areas of the country. The validity of these results was tested against some traditional methods of identifying the poor, and the association of the scores with that of the traditional indicators, such as ownership of land and occupation, asset index (r=0.72), and the wealth ranking obtained from the PRA exercise, was consistent. A statistically significant inverse relationship of the poverty scores with the socioeconomic status was observed in all cases. The scale also allowed the absolute level of poverty to be measured, and in the present study, the highest percentage of absolute poor was found in terms of health (44.2% in Chakaria, 36.4% in Matlab, and 39.1% in other rural areas), followed by social exclusion (35.7% in Chakaria, 28.5% in Matlab, and 22.3% in other rural areas), clothing (6.2% in Chakaria, 8.3% in Matlab, and 20% in other rural areas), education (14.7% in Chakaria, 8% in Matlab, and 16.8% in other rural areas), food (7.8% in Chakaria, 2.9% in Matlab and 3% in other rural areas), and shelter (0.8% in Chakaria, 1.4% in Matlab, and 3.7% in other rural areas). This instrument will also prove itself invaluable in assessing the individual effects of poverty-alleviation programmes or policies on all these different dimensions. PMID:17985815

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.

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

NASA Technical Reports Server (NTRS)

Eichler, Gabriel S.; Huang, Sui; Ingber, Donald E.

2003-01-01

Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/ge/gedihome.html Supplementary information: http://www.chip.org/ge/gedihome.html.

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

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.

Op-Ug TD Optimizer Tool Based on Matlab Code to Find Transition Depth From Open Pit to Block Caving / Narzędzie Optymalizacyjne Oparte O Kod Matlab Wykorzystane Do Określania Głębokości Przejściowej Od Wydobycia Odkrywkowego Do Wybierania Komorami

NASA Astrophysics Data System (ADS)

Bakhtavar, E.

2015-09-01

In this study, transition from open pit to block caving has been considered as a challenging problem. For this purpose, the linear integer programing code of Matlab was initially developed on the basis of the binary integer model proposed by Bakhtavar et al (2012). Then a program based on graphical user interface (GUI) was set up and named "Op-Ug TD Optimizer". It is a beneficial tool for simple application of the model in all situations where open pit is considered together with block caving method for mining an ore deposit. Finally, Op-Ug TD Optimizer has been explained step by step through solving the transition from open pit to block caving problem of a case ore deposit. W pracy tej rozważano skomplikowane zagadnienie przejścia od wybierania odkrywkowego do komorowego. W tym celu opracowano kod programowania liniowego w środowisku MATLAB w oparciu o model liczb binarnych zaproponowany przez Bakhtavara (2012). Następnie opracowano program z wykorzystujący graficzny interfejs użytkownika o nazwie Optymalizator Op-Ug TD. Jest to niezwykle cenne narzędzie umożliwiające stosowanie modelu dla wszystkich warunków w sytuacjach gdy rozważamy prowadzenie wydobycia metodą odkrywkową oraz wydobycie komorowe przy eksploatacji złóż rud żelaza. W końcowej części pracy podano szczegółową instrukcję stosowanie programu Optymalizator na przedstawionym przykładzie przejścia od wydobycia rud żelaza metodami odkrywkowymi poprzez wydobycie komorami.

Using health and demographic surveillance for the early detection of cholera outbreaks: analysis of community- and hospital-based data from Matlab, Bangladesh.

PubMed

Saulnier, Dell D; Persson, Lars-Åke; Streatfield, Peter Kim; Faruque, A S G; Rahman, Anisur

2016-01-01

Cholera outbreaks are a continuing problem in Bangladesh, and the timely detection of an outbreak is important for reducing morbidity and mortality. In Matlab, the ongoing Health and Demographic Surveillance System (HDSS) data records symptoms of diarrhea in children under the age of 5 years at the community level. Cholera surveillance in Matlab currently uses hospital-based data. The objective of this study is to determine whether increases in cholera in Matlab can be detected earlier by using HDSS diarrhea symptom data in a syndromic surveillance analysis, when compared to hospital admissions for cholera. HDSS diarrhea symptom data and hospital admissions for cholera in children under 5 years of age over a 2-year period were analyzed with the syndromic surveillance statistical program EARS (Early Aberration Reporting System). Dates when significant increases in either symptoms or cholera cases occurred were compared to one another. The analysis revealed that there were 43 days over 16 months when the cholera cases or diarrhea symptoms increased significantly. There were 8 months when both data sets detected days with significant increases. In 5 of the 8 months, increases in diarrheal symptoms occurred before increases of cholera cases. The increases in symptoms occurred between 1 and 15 days before the increases in cholera cases. The results suggest that the HDSS survey data may be able to detect an increase in cholera before an increase in hospital admissions is seen. However, there was no direct link between diarrheal symptom increases and cholera cases, and this, as well as other methodological weaknesses, should be taken into consideration.

Simulation, identification and statistical variation in cardiovascular analysis (SISCA) - A software framework for multi-compartment lumped modeling.

PubMed

Huttary, Rudolf; Goubergrits, Leonid; Schütte, Christof; Bernhard, Stefan

2017-08-01

It has not yet been possible to obtain modeling approaches suitable for covering a wide range of real world scenarios in cardiovascular physiology because many of the system parameters are uncertain or even unknown. Natural variability and statistical variation of cardiovascular system parameters in healthy and diseased conditions are characteristic features for understanding cardiovascular diseases in more detail. This paper presents SISCA, a novel software framework for cardiovascular system modeling and its MATLAB implementation. The framework defines a multi-model statistical ensemble approach for dimension reduced, multi-compartment models and focuses on statistical variation, system identification and patient-specific simulation based on clinical data. We also discuss a data-driven modeling scenario as a use case example. The regarded dataset originated from routine clinical examinations and comprised typical pre and post surgery clinical data from a patient diagnosed with coarctation of aorta. We conducted patient and disease specific pre/post surgery modeling by adapting a validated nominal multi-compartment model with respect to structure and parametrization using metadata and MRI geometry. In both models, the simulation reproduced measured pressures and flows fairly well with respect to stenosis and stent treatment and by pre-treatment cross stenosis phase shift of the pulse wave. However, with post-treatment data showing unrealistic phase shifts and other more obvious inconsistencies within the dataset, the methods and results we present suggest that conditioning and uncertainty management of routine clinical data sets needs significantly more attention to obtain reasonable results in patient-specific cardiovascular modeling. Copyright © 2017 Elsevier Ltd. All rights reserved.

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation

PubMed Central

2013-01-01

The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening. PMID:23938087

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation.

PubMed

Hodneland, Erlend; Kögel, Tanja; Frei, Dominik Michael; Gerdes, Hans-Hermann; Lundervold, Arvid

2013-08-09

: The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening.

Evaluation of cardiac signals using discrete wavelet transform with MATLAB graphical user interface.

PubMed

John, Agnes Aruna; Subramanian, Aruna Priyadharshni; Jaganathan, Saravana Kumar; Sethuraman, Balasubramanian

2015-01-01

To process the electrocardiogram (ECG) signals using MATLAB-based graphical user interface (GUI) and to classify the signals based on heart rate. The subject condition was identified using R-peak detection based on discrete wavelet transform followed by a Bayes classifier that classifies the ECG signals. The GUI was designed to display the ECG signal plot. Obtained from MIT database 18 patients had normal heart rate and 9 patients had abnormal heart rate; 14.81% of the patients suffered from tachycardia and 18.52% of the patients have bradycardia. The proposed GUI display was found useful to analyze the digitized ECG signal by a non-technical user and may help in diagnostics. Further improvement can be done by employing field programmable gate array for the real time processing of cardiac signals. Copyright © 2015 Cardiological Society of India. Published by Elsevier B.V. All rights reserved.

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.

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.

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,…

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.

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

Fitting model-based psychometric functions to simultaneity and temporal-order judgment data: MATLAB and R routines.

PubMed

Alcalá-Quintana, Rocío; García-Pérez, Miguel A

2013-12-01

Research on temporal-order perception uses temporal-order judgment (TOJ) tasks or synchrony judgment (SJ) tasks in their binary SJ2 or ternary SJ3 variants. In all cases, two stimuli are presented with some temporal delay, and observers judge the order of presentation. Arbitrary psychometric functions are typically fitted to obtain performance measures such as sensitivity or the point of subjective simultaneity, but the parameters of these functions are uninterpretable. We describe routines in MATLAB and R that fit model-based functions whose parameters are interpretable in terms of the processes underlying temporal-order and simultaneity judgments and responses. These functions arise from an independent-channels model assuming arrival latencies with exponential distributions and a trichotomous decision space. Different routines fit data separately for SJ2, SJ3, and TOJ tasks, jointly for any two tasks, or also jointly for the three tasks (for common cases in which two or even the three tasks were used with the same stimuli and participants). Additional routines provide bootstrap p-values and confidence intervals for estimated parameters. A further routine is included that obtains performance measures from the fitted functions. An R package for Windows and source code of the MATLAB and R routines are available as Supplementary Files.

Analysis of CAD Model-based Visual Tracking for Microassembly using a New Block Set for MATLAB/Simulink

NASA Astrophysics Data System (ADS)

Kudryavtsev, Andrey V.; Laurent, Guillaume J.; Clévy, Cédric; Tamadazte, Brahim; Lutz, Philippe

2015-10-01

Microassembly is an innovative alternative to the microfabrication process of MOEMS, which is quite complex. It usually implies the use of microrobots controlled by an operator. The reliability of this approach has been already confirmed for micro-optical technologies. However, the characterization of assemblies has shown that the operator is the main source of inaccuracies in the teleoperated microassembly. Therefore, there is great interest in automating the microassembly process. One of the constraints of automation in microscale is the lack of high precision sensors capable to provide the full information about the object position. Thus, the usage of visual-based feedback represents a very promising approach allowing to automate the microassembly process. The purpose of this article is to characterize the techniques of object position estimation based on the visual data, i.e., visual tracking techniques from the ViSP library. These algorithms enables a 3-D object pose using a single view of the scene and the CAD model of the object. The performance of three main types of model-based trackers is analyzed and quantified: edge-based, texture-based and hybrid tracker. The problems of visual tracking in microscale are discussed. The control of the micromanipulation station used in the framework of our project is performed using a new Simulink block set. Experimental results are shown and demonstrate the possibility to obtain the repeatability below 1 µm.

GOATS Image Projection Component

NASA Technical Reports Server (NTRS)

Haber, Benjamin M.; Green, Joseph J.

2011-01-01

When doing mission analysis and design of an imaging system in orbit around the Earth, answering the fundamental question of imaging performance requires an understanding of the image products that will be produced by the imaging system. GOATS software represents a series of MATLAB functions to provide for geometric image projections. Unique features of the software include function modularity, a standard MATLAB interface, easy-to-understand first-principles-based analysis, and the ability to perform geometric image projections of framing type imaging systems. The software modules are created for maximum analysis utility, and can all be used independently for many varied analysis tasks, or used in conjunction with other orbit analysis tools.

Modelling and Simulation Based on Matlab/Simulink: A Press Mechanism

NASA Astrophysics Data System (ADS)

Halicioglu, R.; Dulger, L. C.; Bozdana, A. T.

2014-03-01

In this study, design and kinematic analysis of a crank-slider mechanism for a crank press is studied. The crank-slider mechanism is the commonly applied one as direct and indirect drive alternatives in practice. Since inexpensiveness, flexibility and controllability are getting more and more important in many industrial applications especially in automotive industry, a crank press with servo actuator (servo crank press) is taken as an application. Design and kinematic analysis of representative mechanism is presented with geometrical analysis for the inverse kinematic of the mechanism by using desired motion concept of slider. The mechanism is modelled in MATLAB/Simulink platform. The simulation results are presented herein.

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

Energy efficient model based algorithm for control of building HVAC systems.

PubMed

Kirubakaran, V; Sahu, Chinmay; Radhakrishnan, T K; Sivakumaran, N

2015-11-01

Energy efficient designs are receiving increasing attention in various fields of engineering. Heating ventilation and air conditioning (HVAC) control system designs involve improved energy usage with an acceptable relaxation in thermal comfort. In this paper, real time data from a building HVAC system provided by BuildingLAB is considered. A resistor-capacitor (RC) framework for representing thermal dynamics of the building is estimated using particle swarm optimization (PSO) algorithm. With objective costs as thermal comfort (deviation of room temperature from required temperature) and energy measure (Ecm) explicit MPC design for this building model is executed based on its state space representation of the supply water temperature (input)/room temperature (output) dynamics. The controllers are subjected to servo tracking and external disturbance (ambient temperature) is provided from the real time data during closed loop control. The control strategies are ported on a PIC32mx series microcontroller platform. The building model is implemented in MATLAB and hardware in loop (HIL) testing of the strategies is executed over a USB port. Results indicate that compared to traditional proportional integral (PI) controllers, the explicit MPC's improve both energy efficiency and thermal comfort significantly. Copyright © 2015 Elsevier Inc. All rights reserved.

Long-term real-time structural health monitoring using wireless smart sensor

NASA Astrophysics Data System (ADS)

Jang, Shinae; Mensah-Bonsu, Priscilla O.; Li, Jingcheng; Dahal, Sushil

2013-04-01

Improving the safety and security of civil infrastructure has become a critical issue for decades since it plays a central role in the economics and politics of a modern society. Structural health monitoring of civil infrastructure using wireless smart sensor network has emerged as a promising solution recently to increase structural reliability, enhance inspection quality, and reduce maintenance costs. Though hardware and software framework are well prepared for wireless smart sensors, the long-term real-time health monitoring strategy are still not available due to the lack of systematic interface. In this paper, the Imote2 smart sensor platform is employed, and a graphical user interface for the long-term real-time structural health monitoring has been developed based on Matlab for the Imote2 platform. This computer-aided engineering platform enables the control, visualization of measured data as well as safety alarm feature based on modal property fluctuation. A new decision making strategy to check the safety is also developed and integrated in this software. Laboratory validation of the computer aided engineering platform for the Imote2 on a truss bridge and a building structure has shown the potential of the interface for long-term real-time structural health monitoring.

Incorporating the whole-mount prostate histology reconstruction program Histostitcher into the extensible imaging platform (XIP) framework

NASA Astrophysics Data System (ADS)

Toth, Robert; Chappelow, Jonathan; Vetter, Christoph; Kutter, Oliver; Russ, Christoph; Feldman, Michael; Tomaszewski, John; Shih, Natalie; Madabhushi, Anant

2012-03-01

There is a need for identifying quantitative imaging (e.g. MRI) signatures for prostate cancer (CaP), so that computer-aided diagnostic methods can be trained to detect disease extent in vivo. Determining CaP extent on in vivo MRI is difficult to do; however, with the availability of ex vivo surgical whole mount histological sections (WMHS) for CaP patients undergoing radical prostatectomy, co-registration methods can be applied to align and map disease extent onto pre-operative MR imaging from the post-operative histology. Yet obtaining digitized images of WHMS for co-registration with the pre-operative MRI is cumbersome since (a) most digital slide scanners are unable to accommodate the entire section, and (b) significant technical expertise is required for whole mount slide preparation. Consequently, most centers opt to construct quartered sections of each histology slice. Prior to co-registration with MRI, however, these quartered sections need to be digitally stitched together to reconstitute a digital, pseudo WMHS. Histostitcheris an interactive software program that uses semi-automatic registration tools to digitally stitch quartered sections into pseudo WMHS. Histostitcherwas originally developed using the GUI tools provided by the Matlab programming interface, but the clinical use was limited due to the inefficiency of the interface. The limitations of the Matlab based GUI include (a) an inability to edit the fiducials, (b) the rendering being extremely slow, and (c) lack of interactive and rapid visualization tools. In this work, Histostitcherhas been integrated into the eXtensible Imaging Platform (XIP TM ) framework (a set of libraries containing functionalities for analyzing and visualizing medical image data). XIP TM lends the stitching tool much greater flexibility and functionality by (a) allowing interactive and seamless navigation through the full resolution histology images, (b) the ability to easily add, edit, or remove fiducials and annotations in order to register the quadrants and map the disease extent. In this work, we showcase examples of digital stitching of quartered histological sections into pseudo-WHMS using Histostitcher via the new XIP TM interface. This tool will be particularly useful in clinical trials and large cohort studies where a quick, interactive way of digitally reconstructing pseudo WMHS is required.

Trick Simulation Environment 07

NASA Technical Reports Server (NTRS)

Lin, Alexander S.; Penn, John M.

2012-01-01

The Trick Simulation Environment is a generic simulation toolkit used for constructing and running simulations. This release includes a Monte Carlo analysis simulation framework and a data analysis package. It produces all auto documentation in XML. Also, the software is capable of inserting a malfunction at any point during the simulation. Trick 07 adds variable server output options and error messaging and is capable of using and manipulating wide characters for international support. Wide character strings are available as a fundamental type for variables processed by Trick. A Trick Monte Carlo simulation uses a statistically generated, or predetermined, set of inputs to iteratively drive the simulation. Also, there is a framework in place for optimization and solution finding where developers may iteratively modify the inputs per run based on some analysis of the outputs. The data analysis package is capable of reading data from external simulation packages such as MATLAB and Octave, as well as the common comma-separated values (CSV) format used by Excel, without the use of external converters. The file formats for MATLAB and Octave were obtained from their documentation sets, and Trick maintains generic file readers for each format. XML tags store the fields in the Trick header comments. For header files, XML tags for structures and enumerations, and the members within are stored in the auto documentation. For source code files, XML tags for each function and the calling arguments are stored in the auto documentation. When a simulation is built, a top level XML file, which includes all of the header and source code XML auto documentation files, is created in the simulation directory. Trick 07 provides an XML to TeX converter. The converter reads in header and source code XML documentation files and converts the data to TeX labels and tables suitable for inclusion in TeX documents. A malfunction insertion capability allows users to override the value of any simulation variable, or call a malfunction job, at any time during the simulation. Users may specify conditions, use the return value of a malfunction trigger job, or manually activate a malfunction. The malfunction action may consist of executing a block of input file statements in an action block, setting simulation variable values, call a malfunction job, or turn on/off simulation jobs.

A Common Calibration Source Framework for Fully-Polarimetric and Interferometric Radiometers

NASA Technical Reports Server (NTRS)

Kim, Edward J.; Davis, Brynmor; Piepmeier, Jeff; Zukor, Dorothy J. (Technical Monitor)

2000-01-01

Two types of microwave radiometry--synthetic thinned array radiometry (STAR) and fully-polarimetric (FP) radiometry--have received increasing attention during the last several years. STAR radiometers offer a technological solution to achieving high spatial resolution imaging from orbit without requiring a filled aperture or a moving antenna, and FP radiometers measure extra polarization state information upon which entirely new or more robust geophysical retrieval algorithms can be based. Radiometer configurations used for both STAR and FP instruments share one fundamental feature that distinguishes them from more 'standard' radiometers, namely, they measure correlations between pairs of microwave signals. The calibration requirements for correlation radiometers are broader than those for standard radiometers. Quantities of interest include total powers, complex correlation coefficients, various offsets, and possible nonlinearities. A candidate for an ideal calibration source would be one that injects test signals with precisely controllable correlation coefficients and absolute powers simultaneously into a pair of receivers, permitting all of these calibration quantities to be measured. The complex nature of correlation radiometer calibration, coupled with certain inherent similarities between STAR and FP instruments, suggests significant leverage in addressing both problems together. Recognizing this, a project was recently begun at NASA Goddard Space Flight Center to develop a compact low-power subsystem for spaceflight STAR or FP receiver calibration. We present a common theoretical framework for the design of signals for a controlled correlation calibration source. A statistical model is described, along with temporal and spectral constraints on such signals. Finally, a method for realizing these signals is demonstrated using a Matlab-based implementation.

JWST Wavefront Control Toolbox

NASA Technical Reports Server (NTRS)

Shin, Shahram Ron; Aronstein, David L.

2011-01-01

A Matlab-based toolbox has been developed for the wavefront control and optimization of segmented optical surfaces to correct for possible misalignments of James Webb Space Telescope (JWST) using influence functions. The toolbox employs both iterative and non-iterative methods to converge to an optimal solution by minimizing the cost function. The toolbox could be used in either of constrained and unconstrained optimizations. The control process involves 1 to 7 degrees-of-freedom perturbations per segment of primary mirror in addition to the 5 degrees of freedom of secondary mirror. The toolbox consists of a series of Matlab/Simulink functions and modules, developed based on a "wrapper" approach, that handles the interface and data flow between existing commercial optical modeling software packages such as Zemax and Code V. The limitations of the algorithm are dictated by the constraints of the moving parts in the mirrors.

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.

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

Compressed sensing with cyclic-S Hadamard matrix for terahertz imaging applications

NASA Astrophysics Data System (ADS)

Ermeydan, Esra Şengün; ćankaya, Ilyas

2018-01-01

Compressed Sensing (CS) with Cyclic-S Hadamard matrix is proposed for single pixel imaging applications in this study. In single pixel imaging scheme, N = r . c samples should be taken for r×c pixel image where . denotes multiplication. CS is a popular technique claiming that the sparse signals can be reconstructed with samples under Nyquist rate. Therefore to solve the slow data acquisition problem in Terahertz (THz) single pixel imaging, CS is a good candidate. However, changing mask for each measurement is a challenging problem since there is no commercial Spatial Light Modulators (SLM) for THz band yet, therefore circular masks are suggested so that for each measurement one or two column shifting will be enough to change the mask. The CS masks are designed using cyclic-S matrices based on Hadamard transform for 9 × 7 and 15 × 17 pixel images within the framework of this study. The %50 compressed images are reconstructed using total variation based TVAL3 algorithm. Matlab simulations demonstrates that cyclic-S matrices can be used for single pixel imaging based on CS. The circular masks have the advantage to reduce the mechanical SLMs to a single sliding strip, whereas the CS helps to reduce acquisition time and energy since it allows to reconstruct the image from fewer samples.

STOCHSIMGPU: parallel stochastic simulation for the Systems Biology Toolbox 2 for MATLAB.

PubMed

Klingbeil, Guido; Erban, Radek; Giles, Mike; Maini, Philip K

2011-04-15

The importance of stochasticity in biological systems is becoming increasingly recognized and the computational cost of biologically realistic stochastic simulations urgently requires development of efficient software. We present a new software tool STOCHSIMGPU that exploits graphics processing units (GPUs) for parallel stochastic simulations of biological/chemical reaction systems and show that significant gains in efficiency can be made. It is integrated into MATLAB and works with the Systems Biology Toolbox 2 (SBTOOLBOX2) for MATLAB. The GPU-based parallel implementation of the Gillespie stochastic simulation algorithm (SSA), the logarithmic direct method (LDM) and the next reaction method (NRM) is approximately 85 times faster than the sequential implementation of the NRM on a central processing unit (CPU). Using our software does not require any changes to the user's models, since it acts as a direct replacement of the stochastic simulation software of the SBTOOLBOX2. The software is open source under the GPL v3 and available at http://www.maths.ox.ac.uk/cmb/STOCHSIMGPU. The web site also contains supplementary information. klingbeil@maths.ox.ac.uk Supplementary data are available at Bioinformatics online.

Voltage control in Z-source inverter using low cost microcontroller for undergraduate approach

NASA Astrophysics Data System (ADS)

Zulkifli, Shamsul Aizam; Sewang, Mohd Rizal; Salimin, Suriana; Shah, Noor Mazliza Badrul

2017-09-01

This paper is focussing on controlling the output voltage of Z-Source Inverter (ZSI) using a low cost microcontroller with MATLAB-Simulink that has been used for interfacing the voltage control at the output of ZSI. The key advantage of this system is the ability of a low cost microcontroller to process the voltage control blocks based on the mathematical equations created in MATLAB-Simulink. The Proportional Integral (PI) control equations are been applied and then, been downloaded to the microcontroller for observing the changes on the voltage output regarding to the changes on the reference on the PI. The system has been simulated in MATLAB and been verified with the hardware setup. As the results, the Raspberry Pi and Arduino that have been used in this work are able to respond well when there is a change of ZSI output. It proofed that, by applying/introducing this method to student in undergraduate level, it will help the student to understand more on the process of the power converter combine with a control feedback function that can be applied at low cost microcontroller.

Arsenic exposure and adverse health effects: a review of recent findings from arsenic and health studies in Matlab, Bangladesh.

PubMed

Yunus, Mohammad; Sohel, Nazmul; Hore, Samar Kumar; Rahman, Mahfuzar

2011-09-01

The recent discovery of large-scale arsenic (As) contamination of groundwater has raised much concern in Bangladesh. Reliable estimates of the magnitude of As exposure and related health problems have not been comprehensively investigated in Bangladesh. A large population-based study on As and health consequences in Matlab (AsMat) was done in Matlab field site where International Centre for Diarrhoeal Disease Research, Bangladesh has maintained a health and demographic surveillance system registering prospectively all vital events. Taking advantage of the health and demographic surveillance system and collecting data on detailed individual level As exposure using water and urine samples, AsMat investigated the morbidity and mortality associated with As exposure. Reviews of findings to date suggest the adverse effects of As exposure on the risk of skin lesions, high blood pressure, diabetes mellitus, chronic disease, and all-cause infant and adult disease mortality. Future studies of clinical endpoints will enhance our knowledge gaps and will give directions for disease prevention and mitigations. Copyright © 2011. Published by Elsevier B.V.

Control code for laboratory adaptive optics teaching system

NASA Astrophysics Data System (ADS)

Jin, Moonseob; Luder, Ryan; Sanchez, Lucas; Hart, Michael

2017-09-01

By sensing and compensating wavefront aberration, adaptive optics (AO) systems have proven themselves crucial in large astronomical telescopes, retinal imaging, and holographic coherent imaging. Commercial AO systems for laboratory use are now available in the market. One such is the ThorLabs AO kit built around a Boston Micromachines deformable mirror. However, there are limitations in applying these systems to research and pedagogical projects since the software is written with limited flexibility. In this paper, we describe a MATLAB-based software suite to interface with the ThorLabs AO kit by using the MATLAB Engine API and Visual Studio. The software is designed to offer complete access to the wavefront sensor data, through the various levels of processing, to the command signals to the deformable mirror and fast steering mirror. In this way, through a MATLAB GUI, an operator can experiment with every aspect of the AO system's functioning. This is particularly valuable for tests of new control algorithms as well as to support student engagement in an academic environment. We plan to make the code freely available to the community.

Biomechanical ToolKit: Open-source framework to visualize and process biomechanical data.

PubMed

Barre, Arnaud; Armand, Stéphane

2014-04-01

C3D file format is widely used in the biomechanical field by companies and laboratories to store motion capture systems data. However, few software packages can visualize and modify the integrality of the data in the C3D file. Our objective was to develop an open-source and multi-platform framework to read, write, modify and visualize data from any motion analysis systems using standard (C3D) and proprietary file formats (used by many companies producing motion capture systems). The Biomechanical ToolKit (BTK) was developed to provide cost-effective and efficient tools for the biomechanical community to easily deal with motion analysis data. A large panel of operations is available to read, modify and process data through C++ API, bindings for high-level languages (Matlab, Octave, and Python), and standalone application (Mokka). All these tools are open-source and cross-platform and run on all major operating systems (Windows, Linux, MacOS X). Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Some selected quantitative methods of thermal image analysis in Matlab.

PubMed

Koprowski, Robert

2016-05-01

The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

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.

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.

FPGA in-the-loop simulations of cardiac excitation model under voltage clamp conditions

NASA Astrophysics Data System (ADS)

Othman, Norliza; Adon, Nur Atiqah; Mahmud, Farhanahani

2017-01-01

Voltage clamp technique allows the detection of single channel currents in biological membranes in identifying variety of electrophysiological problems in the cellular level. In this paper, a simulation study of the voltage clamp technique has been presented to analyse current-voltage (I-V) characteristics of ion currents based on Luo-Rudy Phase-I (LR-I) cardiac model by using a Field Programmable Gate Array (FPGA). Nowadays, cardiac models are becoming increasingly complex which can cause a vast amount of time to run the simulation. Thus, a real-time hardware implementation using FPGA could be one of the best solutions for high-performance real-time systems as it provides high configurability and performance, and able to executes in parallel mode operation. For shorter time development while retaining high confidence results, FPGA-based rapid prototyping through HDL Coder from MATLAB software has been used to construct the algorithm for the simulation system. Basically, the HDL Coder is capable to convert the designed MATLAB Simulink blocks into hardware description language (HDL) for the FPGA implementation. As a result, the voltage-clamp fixed-point design of LR-I model has been successfully conducted in MATLAB Simulink and the simulation of the I-V characteristics of the ionic currents has been verified on Xilinx FPGA Virtex-6 XC6VLX240T development board through an FPGA-in-the-loop (FIL) simulation.

4D BADA-based Trajectory Generator and 3D Guidance Algorithm

NASA Technical Reports Server (NTRS)

Palacios, Eduardo Sepulveda; Johnson, Marcus A.

2013-01-01

This paper presents a hybrid integration between aerodynamic, airline procedures and other BADA-based (Base of Aircraft Data) coefficients with a classical aircraft dynamic model. This paper also describes a three-dimensional guidance algorithm implemented in order to produce commands for the aircraft to follow a flight plan. The software chosen for this work is MATLAB.

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

An overview on real-time control schemes for wheeled mobile robot

NASA Astrophysics Data System (ADS)

Radzak, M. S. A.; Ali, M. A. H.; Sha’amri, S.; Azwan, A. R.

2018-04-01

The purpose of this paper is to review real-time control motion algorithms for wheeled mobile robot (WMR) when navigating in environment such as road. Its need a good controller to avoid collision with any disturbance and maintain a track error at zero level. The controllers are used with other aiding sensors to measure the WMR’s velocities, posture, and interference to estimate the required torque to be applied on the wheels of mobile robot. Four main categories for wheeled mobile robot control systems have been found in literature which are namely: Kinematic based controller, Dynamic based controllers, artificial intelligence based control system, and Active Force control. A MATLAB/Simulink software is the main software to simulate and implement the control system. The real-time toolbox in MATLAB/SIMULINK are used to receive/send data from sensors/to actuator with presence of disturbances, however others software such C, C++ and visual basic are rare to be used.

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.

Image based book cover recognition and retrieval

NASA Astrophysics Data System (ADS)

Sukhadan, Kalyani; Vijayarajan, V.; Krishnamoorthi, A.; Bessie Amali, D. Geraldine

2017-11-01

In this we are developing a graphical user interface using MATLAB for the users to check the information related to books in real time. We are taking the photos of the book cover using GUI, then by using MSER algorithm it will automatically detect all the features from the input image, after this it will filter bifurcate non-text features which will be based on morphological difference between text and non-text regions. We implemented a text character alignment algorithm which will improve the accuracy of the original text detection. We will also have a look upon the built in MATLAB OCR recognition algorithm and an open source OCR which is commonly used to perform better detection results, post detection algorithm is implemented and natural language processing to perform word correction and false detection inhibition. Finally, the detection result will be linked to internet to perform online matching. More than 86% accuracy can be obtained by this algorithm.

OSCAR a Matlab based optical FFT code

NASA Astrophysics Data System (ADS)

Degallaix, Jérôme

2010-05-01

Optical simulation softwares are essential tools for designing and commissioning laser interferometers. This article aims to introduce OSCAR, a Matlab based FFT code, to the experimentalist community. OSCAR (Optical Simulation Containing Ansys Results) is used to simulate the steady state electric fields in optical cavities with realistic mirrors. The main advantage of OSCAR over other similar packages is the simplicity of its code requiring only a short time to master. As a result, even for a beginner, it is relatively easy to modify OSCAR to suit other specific purposes. OSCAR includes an extensive manual and numerous detailed examples such as simulating thermal aberration, calculating cavity eigen modes and diffraction loss, simulating flat beam cavities and three mirror ring cavities. An example is also provided about how to run OSCAR on the GPU of modern graphic cards instead of the CPU, making the simulation up to 20 times faster.

GRace: a MATLAB-based application for fitting the discrimination-association model.

PubMed

Stefanutti, Luca; Vianello, Michelangelo; Anselmi, Pasquale; Robusto, Egidio

2014-10-28

The Implicit Association Test (IAT) is a computerized two-choice discrimination task in which stimuli have to be categorized as belonging to target categories or attribute categories by pressing, as quickly and accurately as possible, one of two response keys. The discrimination association model has been recently proposed for the analysis of reaction time and accuracy of an individual respondent to the IAT. The model disentangles the influences of three qualitatively different components on the responses to the IAT: stimuli discrimination, automatic association, and termination criterion. The article presents General Race (GRace), a MATLAB-based application for fitting the discrimination association model to IAT data. GRace has been developed for Windows as a standalone application. It is user-friendly and does not require any programming experience. The use of GRace is illustrated on the data of a Coca Cola-Pepsi Cola IAT, and the results of the analysis are interpreted and discussed.

Tool for Analysis and Reduction of Scientific Data

NASA Technical Reports Server (NTRS)

James, Mark

2006-01-01

The Automated Scheduling and Planning Environment (ASPEN) computer program has been updated to version 3.0. ASPEN as a whole (up to version 2.0) has been summarized, and selected aspects of ASPEN have been discussed in several previous NASA Tech Briefs articles. Restated briefly, ASPEN is a modular, reconfigurable, application software framework for solving batch problems that involve reasoning about time, activities, states, and resources. Applications of ASPEN can include planning spacecraft missions, scheduling of personnel, and managing supply chains, inventories, and production lines. ASPEN 3.0 can be customized for a wide range of applications and for a variety of computing environments that include various central processing units and randomaccess memories. Domain-specific reasoning modules (e.g., modules for determining orbits for spacecraft) can easily be plugged into ASPEN 3.0. Improvements over other, similar software that have been incorporated into ASPEN 3.0 include a provision for more expressive time-line values, new parsing capabilities afforded by an ASPEN language based on Extensible Markup Language, improved search capabilities, and improved interfaces to other, utility-type software (notably including MATLAB).

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.

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

A simplified implementation of edge detection in MATLAB is faster and more sensitive than fast fourier transform for actin fiber alignment quantification.

PubMed

Kemeny, Steven Frank; Clyne, Alisa Morss

2011-04-01

Fiber alignment plays a critical role in the structure and function of cells and tissues. While fiber alignment quantification is important to experimental analysis and several different methods for quantifying fiber alignment exist, many studies focus on qualitative rather than quantitative analysis perhaps due to the complexity of current fiber alignment methods. Speed and sensitivity were compared in edge detection and fast Fourier transform (FFT) for measuring actin fiber alignment in cells exposed to shear stress. While edge detection using matrix multiplication was consistently more sensitive than FFT, image processing time was significantly longer. However, when MATLAB functions were used to implement edge detection, MATLAB's efficient element-by-element calculations and fast filtering techniques reduced computation cost 100 times compared to the matrix multiplication edge detection method. The new computation time was comparable to the FFT method, and MATLAB edge detection produced well-distributed fiber angle distributions that statistically distinguished aligned and unaligned fibers in half as many sample images. When the FFT sensitivity was improved by dividing images into smaller subsections, processing time grew larger than the time required for MATLAB edge detection. Implementation of edge detection in MATLAB is simpler, faster, and more sensitive than FFT for fiber alignment quantification.

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.

Motor-Reducer Sizing through a MATLAB-Based Graphical Technique

ERIC Educational Resources Information Center

Giberti, H.; Cinquemani, S.

2012-01-01

The design of the drive system for an automatic machine and its correct sizing is a very important competence for an electrical or mechatronic engineer. This requires knowledge that crosses the fields of electrical engineering, electronics and mechanics, as well as the skill to choose commercial components based upon their technical documentation.…

Remote sensing image segmentation based on Hadoop cloud platform

NASA Astrophysics Data System (ADS)

Li, Jie; Zhu, Lingling; Cao, Fubin

2018-01-01

To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

GCE Data Toolbox for MATLAB - a software framework for automating environmental data processing, quality control and documentation

NASA Astrophysics Data System (ADS)

Sheldon, W.; Chamblee, J.; Cary, R. H.

2013-12-01

Environmental scientists are under increasing pressure from funding agencies and journal publishers to release quality-controlled data in a timely manner, as well as to produce comprehensive metadata for submitting data to long-term archives (e.g. DataONE, Dryad and BCO-DMO). At the same time, the volume of digital data that researchers collect and manage is increasing rapidly due to advances in high frequency electronic data collection from flux towers, instrumented moorings and sensor networks. However, few pre-built software tools are available to meet these data management needs, and those tools that do exist typically focus on part of the data management lifecycle or one class of data. The GCE Data Toolbox has proven to be both a generalized and effective software solution for environmental data management in the Long Term Ecological Research Network (LTER). This open source MATLAB software library, developed by the Georgia Coastal Ecosystems LTER program, integrates metadata capture, creation and management with data processing, quality control and analysis to support the entire data lifecycle. Raw data can be imported directly from common data logger formats (e.g. SeaBird, Campbell Scientific, YSI, Hobo), as well as delimited text files, MATLAB files and relational database queries. Basic metadata are derived from the data source itself (e.g. parsed from file headers) and by value inspection, and then augmented using editable metadata templates containing boilerplate documentation, attribute descriptors, code definitions and quality control rules. Data and metadata content, quality control rules and qualifier flags are then managed together in a robust data structure that supports database functionality and ensures data validity throughout processing. A growing suite of metadata-aware editing, quality control, analysis and synthesis tools are provided with the software to support managing data using graphical forms and command-line functions, as well as developing automated workflows for unattended processing. Finalized data and structured metadata can be exported in a wide variety of text and MATLAB formats or uploaded to a relational database for long-term archiving and distribution. The GCE Data Toolbox can be used as a complete, light-weight solution for environmental data and metadata management, but it can also be used in conjunction with other cyber infrastructure to provide a more comprehensive solution. For example, newly acquired data can be retrieved from a Data Turbine or Campbell LoggerNet Database server for quality control and processing, then transformed to CUAHSI Observations Data Model format and uploaded to a HydroServer for distribution through the CUAHSI Hydrologic Information System. The GCE Data Toolbox can also be leveraged in analytical workflows developed using Kepler or other systems that support MATLAB integration or tool chaining. This software can therefore be leveraged in many ways to help researchers manage, analyze and distribute the data they collect.

Hole size, location optimization in a plate and cylindrical shell for minimum stress points interfacing ANSYS and MATLAB

NASA Astrophysics Data System (ADS)

Thangavel, Soundararaj

Discontinuities in Structures are inevitable. One such discontinuity in a plate and cylindrical shell is presence of a hole / holes. In Plates they are used for mounting bolts where as in Cylinder / Pressure Vessel, they provide provision for mounting Nozzles / Instruments. Location of these holes plays a primary role in minimizing the stress acting with out any external reinforcement. In this Thesis work, Location Parameters are optimized for the presence of one or more holes in a plate and cylindrical shell interfacing ANSYS and MATLAB with boundary constraints based on the geometry. Contour plots are generated for understanding stress distribution and analytical solutions are also discussed for some of the classical problems.

Theory research of seam recognition and welding torch pose control based on machine vision

NASA Astrophysics Data System (ADS)

Long, Qiang; Zhai, Peng; Liu, Miao; He, Kai; Wang, Chunyang

2017-03-01

At present, the automation requirement of the welding become higher, so a method of the welding information extraction by vision sensor is proposed in this paper, and the simulation with the MATLAB has been conducted. Besides, in order to improve the quality of robot automatic welding, an information retrieval method for welding torch pose control by visual sensor is attempted. Considering the demands of welding technology and engineering habits, the relative coordinate systems and variables are strictly defined, and established the mathematical model of the welding pose, and verified its feasibility by using the MATLAB simulation in the paper, these works lay a foundation for the development of welding off-line programming system with high precision and quality.

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.

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.

Analytic reconstruction algorithms for triple-source CT with horizontal data truncation

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

Chen, Ming; Yu, Hengyong, E-mail: hengyong-yu@ieee.org

2015-10-15

Purpose: This paper explores a triple-source imaging method with horizontal data truncation to enlarge the field of view (FOV) for big objects. Methods: The study is conducted by using theoretical analysis, mathematical deduction, and numerical simulations. The proposed algorithms are implemented in c + + and MATLAB. While the basic platform is constructed in MATLAB, the computationally intensive segments are coded in c + +, which are linked via a MEX interface. Results: A triple-source circular scanning configuration with horizontal data truncation is developed, where three pairs of x-ray sources and detectors are unevenly distributed on the same circle tomore » cover the whole imaging object. For this triple-source configuration, a fan-beam filtered backprojection-type algorithm is derived for truncated full-scan projections without data rebinning. The algorithm is also extended for horizontally truncated half-scan projections and cone-beam projections in a Feldkamp-type framework. Using their method, the FOV is enlarged twofold to threefold to scan bigger objects with high speed and quality. The numerical simulation results confirm the correctness and effectiveness of the developed algorithms. Conclusions: The triple-source scanning configuration with horizontal data truncation cannot only keep most of the advantages of a traditional multisource system but also cover a larger FOV for big imaging objects. In addition, because the filtering is shift-invariant, the proposed algorithms are very fast and easily parallelized on graphic processing units.« less

Analytic reconstruction algorithms for triple-source CT with horizontal data truncation.

PubMed

Chen, Ming; Yu, Hengyong

2015-10-01

This paper explores a triple-source imaging method with horizontal data truncation to enlarge the field of view (FOV) for big objects. The study is conducted by using theoretical analysis, mathematical deduction, and numerical simulations. The proposed algorithms are implemented in c + + and matlab. While the basic platform is constructed in matlab, the computationally intensive segments are coded in c + +, which are linked via a mex interface. A triple-source circular scanning configuration with horizontal data truncation is developed, where three pairs of x-ray sources and detectors are unevenly distributed on the same circle to cover the whole imaging object. For this triple-source configuration, a fan-beam filtered backprojection-type algorithm is derived for truncated full-scan projections without data rebinning. The algorithm is also extended for horizontally truncated half-scan projections and cone-beam projections in a Feldkamp-type framework. Using their method, the FOV is enlarged twofold to threefold to scan bigger objects with high speed and quality. The numerical simulation results confirm the correctness and effectiveness of the developed algorithms. The triple-source scanning configuration with horizontal data truncation cannot only keep most of the advantages of a traditional multisource system but also cover a larger FOV for big imaging objects. In addition, because the filtering is shift-invariant, the proposed algorithms are very fast and easily parallelized on graphic processing units.

Neurovascular Network Explorer 1.0: a database of 2-photon single-vessel diameter measurements with MATLAB(®) graphical user interface.

PubMed

Sridhar, Vishnu B; Tian, Peifang; Dale, Anders M; Devor, Anna; Saisan, Payam A

2014-01-01

We present a database client software-Neurovascular Network Explorer 1.0 (NNE 1.0)-that uses MATLAB(®) based Graphical User Interface (GUI) for interaction with a database of 2-photon single-vessel diameter measurements from our previous publication (Tian et al., 2010). These data are of particular interest for modeling the hemodynamic response. NNE 1.0 is downloaded by the user and then runs either as a MATLAB script or as a standalone program on a Windows platform. The GUI allows browsing the database according to parameters specified by the user, simple manipulation and visualization of the retrieved records (such as averaging and peak-normalization), and export of the results. Further, we provide NNE 1.0 source code. With this source code, the user can database their own experimental results, given the appropriate data structure and naming conventions, and thus share their data in a user-friendly format with other investigators. NNE 1.0 provides an example of seamless and low-cost solution for sharing of experimental data by a regular size neuroscience laboratory and may serve as a general template, facilitating dissemination of biological results and accelerating data-driven modeling approaches.

TOPPE: A framework for rapid prototyping of MR pulse sequences.

PubMed

Nielsen, Jon-Fredrik; Noll, Douglas C

2018-06-01

To introduce a framework for rapid prototyping of MR pulse sequences. We propose a simple file format, called "TOPPE", for specifying all details of an MR imaging experiment, such as gradient and radiofrequency waveforms and the complete scan loop. In addition, we provide a TOPPE file "interpreter" for GE scanners, which is a binary executable that loads TOPPE files and executes the sequence on the scanner. We also provide MATLAB scripts for reading and writing TOPPE files and previewing the sequence prior to hardware execution. With this setup, the task of the pulse sequence programmer is reduced to creating TOPPE files, eliminating the need for hardware-specific programming. No sequence-specific compilation is necessary; the interpreter only needs to be compiled once (for every scanner software upgrade). We demonstrate TOPPE in three different applications: k-space mapping, non-Cartesian PRESTO whole-brain dynamic imaging, and myelin mapping in the brain using inhomogeneous magnetization transfer. We successfully implemented and executed the three example sequences. By simply changing the various TOPPE sequence files, a single binary executable (interpreter) was used to execute several different sequences. The TOPPE file format is a complete specification of an MR imaging experiment, based on arbitrary sequences of a (typically small) number of unique modules. Along with the GE interpreter, TOPPE comprises a modular and flexible platform for rapid prototyping of new pulse sequences. Magn Reson Med 79:3128-3134, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

GISMO: A MATLAB toolbox for seismic research, monitoring, & education

NASA Astrophysics Data System (ADS)

Thompson, G.; Reyes, C. G.; Kempler, L. A.

2017-12-01

GISMO is an open-source MATLAB toolbox which provides an object-oriented framework to build workflows and applications that read, process, visualize and write seismic waveform, catalog and instrument response data. GISMO can retrieve data from a variety of sources (e.g. FDSN web services, Earthworm/Winston servers) and data formats (SAC, Seisan, etc.). It can handle waveform data that crosses file boundaries. All this alleviates one of the most time consuming part for scientists developing their own codes. GISMO simplifies seismic data analysis by providing a common interface for your data, regardless of its source. Several common plots are built-in to GISMO, such as record section plots, spectrograms, depth-time sections, event count per unit time, energy release per unit time, etc. Other visualizations include map views and cross-sections of hypocentral data. Several common processing methods are also included, such as an extensive set of tools for correlation analysis. Support is being added to interface GISMO with ObsPy. GISMO encourages community development of an integrated set of codes and accompanying documentation, eliminating the need for seismologists to "reinvent the wheel". By sharing code the consistency and repeatability of results can be enhanced. GISMO is hosted on GitHub with documentation both within the source code and in the project wiki. GISMO has been used at the University of South Florida and University of Alaska Fairbanks in graduate-level courses including Seismic Data Analysis, Time Series Analysis and Computational Seismology. GISMO has also been tailored to interface with the common seismic monitoring software and data formats used by volcano observatories in the US and elsewhere. As an example, toolbox training was delivered to researchers at INETER (Nicaragua). Applications built on GISMO include IceWeb (e.g. web-based spectrograms), which has been used by Alaska Volcano Observatory since 1998 and became the prototype for the USGS Pensive system.

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.

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

Binning in Gaussian Kernel Regularization

DTIC Science & Technology

2005-04-01

OSU-SVM Matlab package, the SVM trained on 966 bins has a comparable test classification rate as the SVM trained on 27,179 samples, but reduces the...71.40%) on 966 randomly sampled data. Using the OSU-SVM Matlab package, the SVM trained on 966 bins has a comparable test classification rate as the...the OSU-SVM Matlab package, the SVM trained on 966 bins has a comparable test classification rate as the SVM trained on 27,179 samples, and reduces

Dust Tsunamis, Blackouts and 50 deg C: Teaching MATLAB in East Africa

NASA Astrophysics Data System (ADS)

Trauth, M. H.

2016-12-01

MATLAB is the tool of choice when analyzing earth and environmental data from East Africa. The software and companion toolboxes helps to process satellite images and digital elevation models, to detect trends, cycles, and recurrent, characteristic types of climate transitions in climate time series, and to model the hydrological balance of ancient lakes. The advantage of MATLAB is that the user can do many different types of analyses with the same software, making the software very attractive for young scientists at African universities. Since 2009 we are organizing summer schools on the subject of data analysis with various tools including MATLAB in Ethiopia, Kenya and Tanzania. Throughout the summerschool, participants are instructed by teams of senior researchers, together with young scientists, some of which were participants of an earlier summerschool. The participants are themselves integrated in teaching, depending on previous knowledge, so that the boundary between teachers and learners constantly shifts or even dissolves. From the extraordinarily positive experience, but also the difficulties in teaching data analysis methods with MATLAB in East Africa is reported.

Development of MATLAB software to control data acquisition from a multichannel systems multi-electrode array.

PubMed

Messier, Erik

2016-08-01

A Multichannel Systems (MCS) microelectrode array data acquisition (DAQ) unit is used to collect multichannel electrograms (EGM) from a Langendorff perfused rabbit heart system to study sudden cardiac death (SCD). MCS provides software through which data being processed by the DAQ unit can be displayed and saved, but this software's combined utility with MATLAB is not very effective. MCSs software stores recorded EGM data in a MathCad (MCD) format, which is then converted to a text file format. These text files are very large, and it is therefore very time consuming to import the EGM data into MATLAB for real-time analysis. Therefore, customized MATLAB software was developed to control the acquisition of data from the MCS DAQ unit, and provide specific laboratory accommodations for this study of SCD. The developed DAQ unit control software will be able to accurately: provide real time display of EGM signals; record and save EGM signals in MATLAB in a desired format; and produce real time analysis of the EGM signals; all through an intuitive GUI.

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.

Numerical inverse method predicting acoustic spinning modes radiated by a ducted fan from free-field test data.

PubMed

Lewy, Serge

2008-07-01

Spinning modes generated by a ducted turbofan at a given frequency determine the acoustic free-field directivity. An inverse method starting from measured directivity patterns is interesting in providing information on the noise sources without requiring tedious spinning-mode experimental analyses. According to a previous article, equations are based on analytical modal splitting inside a cylindrical duct and on a Rayleigh or a Kirchhoff integral on the duct exit cross section to get far-field directivity. Equations are equal in number to free-field measurement locations and the unknowns are the propagating mode amplitudes (there are generally more unknowns than equations). A MATLAB procedure has been implemented by using either the pseudoinverse function or the backslash operator. A constraint comes from the fact that squared modal amplitudes must be positive which involves an iterative least squares fitting. Numerical simulations are discussed along with several examples based on tests performed by Rolls-Royce in the framework of a European project. It is assessed that computation is very fast and it well fits the measured directivities, but the solution depends on the method and is not unique. This means that the initial set of modes should be chosen according to any known physical property of the acoustic sources.

Technical Study of a Standalone Photovoltaic–Wind Energy Based Hybrid Power Supply Systems for Island Electrification in Malaysia

PubMed Central

Samrat, Nahidul Hoque; Ahmad, Norhafizan; Choudhury, Imtiaz Ahmed; Taha, Zahari

2015-01-01

Energy is one of the most important factors in the socioeconomic development of a country. In a developing country like Malaysia, the development of islands is mostly related to the availability of electric power. Power generated by renewable energy sources has recently become one of the most promising solutions for the electrification of islands and remote rural areas. But high dependency on weather conditions and the unpredictable nature of these renewable energy sources are the main drawbacks. To overcome this weakness, different green energy sources and power electronic converters need to be integrated with each other. This study presents a battery storage hybrid standalone photovoltaic-wind energy power supply system. In the proposed standalone hybrid system, a DC-DC buck-boost bidirectional converter controller is used to accumulates the surplus hybrid power in the battery bank and supplies this power to the load during the hybrid power shortage by maintaining the constant dc-link voltage. A three-phase voltage source inverter complex vector control scheme is used to control the load side voltage in terms of the voltage amplitude and frequency. Based on the simulation results obtained from MATLAB/Simulink, it has been found that the overall hybrid framework is capable of working under variable weather and load conditions. PMID:26121032

Technical Study of a Standalone Photovoltaic-Wind Energy Based Hybrid Power Supply Systems for Island Electrification in Malaysia.

PubMed

Samrat, Nahidul Hoque; Ahmad, Norhafizan; Choudhury, Imtiaz Ahmed; Taha, Zahari

2015-01-01

Energy is one of the most important factors in the socioeconomic development of a country. In a developing country like Malaysia, the development of islands is mostly related to the availability of electric power. Power generated by renewable energy sources has recently become one of the most promising solutions for the electrification of islands and remote rural areas. But high dependency on weather conditions and the unpredictable nature of these renewable energy sources are the main drawbacks. To overcome this weakness, different green energy sources and power electronic converters need to be integrated with each other. This study presents a battery storage hybrid standalone photovoltaic-wind energy power supply system. In the proposed standalone hybrid system, a DC-DC buck-boost bidirectional converter controller is used to accumulates the surplus hybrid power in the battery bank and supplies this power to the load during the hybrid power shortage by maintaining the constant dc-link voltage. A three-phase voltage source inverter complex vector control scheme is used to control the load side voltage in terms of the voltage amplitude and frequency. Based on the simulation results obtained from MATLAB/Simulink, it has been found that the overall hybrid framework is capable of working under variable weather and load conditions.

A soft decoding algorithm and hardware implementation for the visual prosthesis based on high order soft demodulation.

PubMed

Yang, Yuan; Quan, Nannan; Bu, Jingjing; Li, Xueping; Yu, Ningmei

2016-09-26

High order modulation and demodulation technology can solve the frequency requirement between the wireless energy transmission and data communication. In order to achieve reliable wireless data communication based on high order modulation technology for visual prosthesis, this work proposed a Reed-Solomon (RS) error correcting code (ECC) circuit on the basis of differential amplitude and phase shift keying (DAPSK) soft demodulation. Firstly, recognizing the weakness of the traditional DAPSK soft demodulation algorithm based on division that is complex for hardware implementation, an improved phase soft demodulation algorithm for visual prosthesis to reduce the hardware complexity is put forward. Based on this new algorithm, an improved RS soft decoding method is hence proposed. In this new decoding method, the combination of Chase algorithm and hard decoding algorithms is used to achieve soft decoding. In order to meet the requirements of implantable visual prosthesis, the method to calculate reliability of symbol-level based on multiplication of bit reliability is derived, which reduces the testing vectors number of Chase algorithm. The proposed algorithms are verified by MATLAB simulation and FPGA experimental results. During MATLAB simulation, the biological channel attenuation property model is added into the ECC circuit. The data rate is 8 Mbps in the MATLAB simulation and FPGA experiments. MATLAB simulation results show that the improved phase soft demodulation algorithm proposed in this paper saves hardware resources without losing bit error rate (BER) performance. Compared with the traditional demodulation circuit, the coding gain of the ECC circuit has been improved by about 3 dB under the same BER of [Formula: see text]. The FPGA experimental results show that under the condition of data demodulation error with wireless coils 3 cm away, the system can correct it. The greater the distance, the higher the BER. Then we use a bit error rate analyzer to measure BER of the demodulation circuit and the RS ECC circuit with different distance of two coils. And the experimental results show that the RS ECC circuit has about an order of magnitude lower BER than the demodulation circuit when under the same coils distance. Therefore, the RS ECC circuit has more higher reliability of the communication in the system. The improved phase soft demodulation algorithm and soft decoding algorithm proposed in this paper enables data communication that is more reliable than other demodulation system, which also provide a significant reference for further study to the visual prosthesis system.

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…

Hyperspectral imaging in medicine: image pre-processing problems and solutions in Matlab.

PubMed

Koprowski, Robert

2015-11-01

The paper presents problems and solutions related to hyperspectral image pre-processing. New methods of preliminary image analysis are proposed. The paper shows problems occurring in Matlab when trying to analyse this type of images. Moreover, new methods are discussed which provide the source code in Matlab that can be used in practice without any licensing restrictions. The proposed application and sample result of hyperspectral image analysis. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Maximum Power Point Tracking Control of Hydrokinetic Turbine and Low-speed High-Thrust Permanent Magnet Generator Design

DTIC Science & Technology

2012-01-01

Schematic of the generator and power converters built in PLECS ............. 26 Figure 3.12. Block diagram of the MPPT control built in Matlab/Simulink...validated by simulation results done in Matlab/Simulink R2010a and PLECS . Figure 3.9 shows the block diagram of the hydrokinetic system built in Matlab...rectifier, boost converter and battery model built in PLECS . The battery bank on the load side is simulated by a constant dc voltage source. 25

A novel framework for the temporal analysis of bone mineral density in metastatic lesions using CT images of the femur

NASA Astrophysics Data System (ADS)

Knoop, Tom H.; Derikx, Loes C.; Verdonschot, Nico; Slump, Cornelis H.

2015-03-01

In the progressive stages of cancer, metastatic lesions in often develop in the femur. The accompanying pain and risk of fracture dramatically affect the quality of life of the patient. Radiotherapy is often administered as palliative treatment to relieve pain and restore the bone around the lesion. It is thought to affect the bone mineralization of the treated region, but the quantitative relation between radiation dose and femur remineralization remains unclear. A new framework for the longitudinal analysis of CT-scans of patients receiving radiotherapy is presented to investigate this relationship. The implemented framework is capable of automatic calibration of Hounsfield Units to calcium equivalent values and the estimation of a prediction interval per scan. Other features of the framework are temporal registration of femurs using elastix, transformation of arbitrary Regions Of Interests (ROI), and extraction of metrics for analysis. Build in Matlab, the modular approach aids easy adaptation to the pertinent questions in the explorative phase of the research. For validation purposes, an in-vitro model consisting of a human cadaver femur with a milled hole in the intertrochanteric region was used, representing a femur with a metastatic lesion. The hole was incrementally stacked with plates of PMMA bone cement with variable radiopaqueness. Using a Kolmogorov-Smirnov (KS) test, changes in density distribution due to an increase of the calcium concentration could be discriminated. In a 21 cm3 ROI, changes in 8% of the volume from 888 ± 57mg • ml-1 to 1000 ± 80mg • ml-1 could be statistically proven using the proposed framework. In conclusion, the newly developed framework proved to be a useful and flexible tool for the analysis of longitudinal CT data.

Automatic short axis orientation of the left ventricle in 3D ultrasound recordings

NASA Astrophysics Data System (ADS)

Pedrosa, João.; Heyde, Brecht; Heeren, Laurens; Engvall, Jan; Zamorano, Jose; Papachristidis, Alexandros; Edvardsen, Thor; Claus, Piet; D'hooge, Jan

2016-04-01

The recent advent of three-dimensional echocardiography has led to an increased interest from the scientific community in left ventricle segmentation frameworks for cardiac volume and function assessment. An automatic orientation of the segmented left ventricular mesh is an important step to obtain a point-to-point correspondence between the mesh and the cardiac anatomy. Furthermore, this would allow for an automatic division of the left ventricle into the standard 17 segments and, thus, fully automatic per-segment analysis, e.g. regional strain assessment. In this work, a method for fully automatic short axis orientation of the segmented left ventricle is presented. The proposed framework aims at detecting the inferior right ventricular insertion point. 211 three-dimensional echocardiographic images were used to validate this framework by comparison to manual annotation of the inferior right ventricular insertion point. A mean unsigned error of 8, 05° +/- 18, 50° was found, whereas the mean signed error was 1, 09°. Large deviations between the manual and automatic annotations (> 30°) only occurred in 3, 79% of cases. The average computation time was 666ms in a non-optimized MATLAB environment, which potentiates real-time application. In conclusion, a successful automatic real-time method for orientation of the segmented left ventricle is proposed.

Mobile Carbon Monoxide Monitoring System Based on Arduino-Matlab for Environmental Monitoring Application

NASA Astrophysics Data System (ADS)

Azieda Mohd Bakri, Nur; Junid, Syed Abdul Mutalib Al; Razak, Abdul Hadi Abdul; Idros, Mohd Faizul Md; Karimi Halim, Abdul

2015-11-01

Nowadays, the increasing level of carbon monoxide globally has become a serious environmental issue which has been highlighted in most of the country globally. The monitoring of carbon monoxide content is one of the approaches to identify the level of carbon monoxide pollution towards providing the solution for control the level of carbon monoxide produced. Thus, this paper proposed a mobile carbon monoxide monitoring system for measuring the carbon monoxide content based on Arduino-Matlab General User Interface (GUI). The objective of this project is to design, develop and implement the real-time mobile carbon monoxide sensor system and interfacing for measuring the level of carbon monoxide contamination in real environment. Four phases or stages of work have been carried out for the accomplishment of the project, which classified as sensor development, controlling and integrating sensor, data collection and data analysis. As a result, a complete design and developed system has been verified with the handheld industrial standard carbon monoxide sensor for calibrating the sensor sensitivity and measurement in the laboratory. Moreover, the system has been tested in real environments by measuring the level of carbon monoxide in three different lands used location; industrial area; residential area and main road (commercial area). In this real environment test, the industrial area recorded the highest reading with 71.23 ppm and 82.59 ppm for sensor 1 and sensor 2 respectively. As a conclusion, the mobile realtime carbon monoxide system based on the Arduino-Matlab is the best approach to measure the carbon monoxide concentration in different land-used since it does not require a manual data collection and reduce the complexity of the existing carbon monoxide level concentration measurement practise at the same time with a complete data analysis facilities.

A Matlab user interface for the statistically assisted fluid registration algorithm and tensor-based morphometry

NASA Astrophysics Data System (ADS)

Yepes-Calderon, Fernando; Brun, Caroline; Sant, Nishita; Thompson, Paul; Lepore, Natasha

2015-01-01

Tensor-Based Morphometry (TBM) is an increasingly popular method for group analysis of brain MRI data. The main steps in the analysis consist of a nonlinear registration to align each individual scan to a common space, and a subsequent statistical analysis to determine morphometric differences, or difference in fiber structure between groups. Recently, we implemented the Statistically-Assisted Fluid Registration Algorithm or SAFIRA,1 which is designed for tracking morphometric differences among populations. To this end, SAFIRA allows the inclusion of statistical priors extracted from the populations being studied as regularizers in the registration. This flexibility and degree of sophistication limit the tool to expert use, even more so considering that SAFIRA was initially implemented in command line mode. Here, we introduce a new, intuitive, easy to use, Matlab-based graphical user interface for SAFIRA's multivariate TBM. The interface also generates different choices for the TBM statistics, including both the traditional univariate statistics on the Jacobian matrix, and comparison of the full deformation tensors.2 This software will be freely disseminated to the neuroimaging research community.

Antropometric parameters problem solving of shoe lasts by deforming membranes with medium weight

NASA Astrophysics Data System (ADS)

Albu, A. V.; Anghel Drugarin, C. V.; Barla, E. M.; Porav, V.

2018-01-01

The paper presents research results into getting a virtual model of shoe last and anthropometric parameters change. The most important change occurs in the fingers region. Alternatives CAD-CAM technology for next generation is based on DELCAM software for the CAM procedure and simulation of MATLAB software. This research has led to the virtual changes of the last, anthropometric parameter - the width of the fingers (ld) and shoe last length - (Lp) and images have been achieved with the representation in section of the shoe last changed from the original shoe lasts by FEM method (Finite element method) in MATLAB environment. The results are applied in the textile industry and in the elaboration of linings consumption or in the development of leather substitutes on fabric, knitted or woven material type.

Spectrum image analysis tool - A flexible MATLAB solution to analyze EEL and CL spectrum images.

PubMed

Schmidt, Franz-Philipp; Hofer, Ferdinand; Krenn, Joachim R

2017-02-01

Spectrum imaging techniques, gaining simultaneously structural (image) and spectroscopic data, require appropriate and careful processing to extract information of the dataset. In this article we introduce a MATLAB based software that uses three dimensional data (EEL/CL spectrum image in dm3 format (Gatan Inc.'s DigitalMicrograph ® )) as input. A graphical user interface enables a fast and easy mapping of spectral dependent images and position dependent spectra. First, data processing such as background subtraction, deconvolution and denoising, second, multiple display options including an EEL/CL moviemaker and, third, the applicability on a large amount of data sets with a small work load makes this program an interesting tool to visualize otherwise hidden details. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

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.

A Series of MATLAB Learning Modules to Enhance Numerical Competency in Applied Marine Sciences

NASA Astrophysics Data System (ADS)

Fischer, A. M.; Lucieer, V.; Burke, C.

2016-12-01

Enhanced numerical competency to navigate the massive data landscapes are critical skills students need to effectively explore, analyse and visualize complex patterns in high-dimensional data for addressing the complexity of many of the world's problems. This is especially the case for interdisciplinary, undergraduate applied marine science programs, where students are required to demonstrate competency in methods and ideas across multiple disciplines. In response to this challenge, we have developed a series of repository-based data exploration, analysis and visualization modules in MATLAB for integration across various attending and online classes within the University of Tasmania. The primary focus of these modules is to teach students to collect, aggregate and interpret data from large on-line marine scientific data repositories to, 1) gain technical skills in discovering, accessing, managing and visualising large, numerous data sources, 2) interpret, analyse and design approaches to visualise these data, and 3) to address, through numerical approaches, complex, real-world problems, that the traditional scientific methods cannot address. All modules, implemented through a MATLAB live script, include a short recorded lecture to introduce the topic, a handout that gives an overview of the activities, an instructor's manual with a detailed methodology and discussion points, a student assessment (quiz and level-specific challenge task), and a survey. The marine science themes addressed through these modules include biodiversity, habitat mapping, algal blooms and sea surface temperature change and utilize a series of marine science and oceanographic data portals. Through these modules students, with minimal experience in MATLAB or numerical methods are introduced to array indexing, concatenation, sorting, and reshaping, principal component analysis, spectral analysis and unsupervised classification within the context of oceanographic processes, marine geology and marine community ecology.

Nanofiber Nerve Guide for Peripheral Nerve Repair and Regeneration

DTIC Science & Technology

2014-01-01

observing cell migration using live - cell imaging microscopy, and analyzing cell migration with our MATLAB-based programs. Our studies...are then pipetted into the chamber and their path of migration is observed using a live - cell imaging microscope (Fig. 6d). Utilizing this migration

Research on the electro-optical assistant landing system based on the dual camera photogrammetry algorithm

NASA Astrophysics Data System (ADS)

Mi, Yuhe; Huang, Yifan; Li, Lin

2015-08-01

Based on the location technique of beacon photogrammetry, Dual Camera Photogrammetry (DCP) algorithm was used to assist helicopters landing on the ship. In this paper, ZEMAX was used to simulate the two Charge Coupled Device (CCD) cameras imaging four beacons on both sides of the helicopter and output the image to MATLAB. Target coordinate systems, image pixel coordinate systems, world coordinate systems and camera coordinate systems were established respectively. According to the ideal pin-hole imaging model, the rotation matrix and translation vector of the target coordinate systems and the camera coordinate systems could be obtained by using MATLAB to process the image information and calculate the linear equations. On the basis mentioned above, ambient temperature and the positions of the beacons and cameras were changed in ZEMAX to test the accuracy of the DCP algorithm in complex sea status. The numerical simulation shows that in complex sea status, the position measurement accuracy can meet the requirements of the project.

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.

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.

An advanced environment for hybrid modeling of biological systems based on modelica.

PubMed

Pross, Sabrina; Bachmann, Bernhard

2011-01-20

Biological systems are often very complex so that an appropriate formalism is needed for modeling their behavior. Hybrid Petri Nets, consisting of time-discrete Petri Net elements as well as continuous ones, have proven to be ideal for this task. Therefore, a new Petri Net library was implemented based on the object-oriented modeling language Modelica which allows the modeling of discrete, stochastic and continuous Petri Net elements by differential, algebraic and discrete equations. An appropriate Modelica-tool performs the hybrid simulation with discrete events and the solution of continuous differential equations. A special sub-library contains so-called wrappers for specific reactions to simplify the modeling process. The Modelica-models can be connected to Simulink-models for parameter optimization, sensitivity analysis and stochastic simulation in Matlab. The present paper illustrates the implementation of the Petri Net component models, their usage within the modeling process and the coupling between the Modelica-tool Dymola and Matlab/Simulink. The application is demonstrated by modeling the metabolism of Chinese Hamster Ovary Cells.

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.

FPGA based hardware optimized implementation of signal processing system for LFM pulsed radar

NASA Astrophysics Data System (ADS)

Azim, Noor ul; Jun, Wang

2016-11-01

Signal processing is one of the main parts of any radar system. Different signal processing algorithms are used to extract information about different parameters like range, speed, direction etc, of a target in the field of radar communication. This paper presents LFM (Linear Frequency Modulation) pulsed radar signal processing algorithms which are used to improve target detection, range resolution and to estimate the speed of a target. Firstly, these algorithms are simulated in MATLAB to verify the concept and theory. After the conceptual verification in MATLAB, the simulation is converted into implementation on hardware using Xilinx FPGA. Chosen FPGA is Xilinx Virtex-6 (XC6LVX75T). For hardware implementation pipeline optimization is adopted and also other factors are considered for resources optimization in the process of implementation. Focusing algorithms in this work for improving target detection, range resolution and speed estimation are hardware optimized fast convolution processing based pulse compression and pulse Doppler processing.

Low cost MATLAB-based pulse oximeter for deployment in research and development applications.

PubMed

Shokouhian, M; Morling, R C S; Kale, I

2013-01-01

Problems such as motion artifact and effects of ambient lights have forced developers to design different signal processing techniques and algorithms to increase the reliability and accuracy of the conventional pulse oximeter device. To evaluate the robustness of these techniques, they are applied either to recorded data or are implemented on chip to be applied to real-time data. Recorded data is the most common method of evaluating however it is not as reliable as real-time measurements. On the other hand, hardware implementation can be both expensive and time consuming. This paper presents a low cost MATLAB-based pulse oximeter that can be used for rapid evaluation of newly developed signal processing techniques and algorithms. Flexibility to apply different signal processing techniques, providing both processed and unprocessed data along with low implementation cost are the important features of this design which makes it ideal for research and development purposes, as well as commercial, hospital and healthcare application.

Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM☆

PubMed Central

López, J.D.; Litvak, V.; Espinosa, J.J.; Friston, K.; Barnes, G.R.

2014-01-01

The MEG/EEG inverse problem is ill-posed, giving different source reconstructions depending on the initial assumption sets. Parametric Empirical Bayes allows one to implement most popular MEG/EEG inversion schemes (Minimum Norm, LORETA, etc.) within the same generic Bayesian framework. It also provides a cost-function in terms of the variational Free energy—an approximation to the marginal likelihood or evidence of the solution. In this manuscript, we revisit the algorithm for MEG/EEG source reconstruction with a view to providing a didactic and practical guide. The aim is to promote and help standardise the development and consolidation of other schemes within the same framework. We describe the implementation in the Statistical Parametric Mapping (SPM) software package, carefully explaining each of its stages with the help of a simple simulated data example. We focus on the Multiple Sparse Priors (MSP) model, which we compare with the well-known Minimum Norm and LORETA models, using the negative variational Free energy for model comparison. The manuscript is accompanied by Matlab scripts to allow the reader to test and explore the underlying algorithm. PMID:24041874

Functional Genomics Assistant (FUGA): a toolbox for the analysis of complex biological networks

PubMed Central

2011-01-01

Background Cellular constituents such as proteins, DNA, and RNA form a complex web of interactions that regulate biochemical homeostasis and determine the dynamic cellular response to external stimuli. It follows that detailed understanding of these patterns is critical for the assessment of fundamental processes in cell biology and pathology. Representation and analysis of cellular constituents through network principles is a promising and popular analytical avenue towards a deeper understanding of molecular mechanisms in a system-wide context. Findings We present Functional Genomics Assistant (FUGA) - an extensible and portable MATLAB toolbox for the inference of biological relationships, graph topology analysis, random network simulation, network clustering, and functional enrichment statistics. In contrast to conventional differential expression analysis of individual genes, FUGA offers a framework for the study of system-wide properties of biological networks and highlights putative molecular targets using concepts of systems biology. Conclusion FUGA offers a simple and customizable framework for network analysis in a variety of systems biology applications. It is freely available for individual or academic use at http://code.google.com/p/fuga. PMID:22035155

Vision-Based Position Estimation Utilizing an Extended Kalman Filter

DTIC Science & Technology

2016-12-01

POSITION ESTIMATION UTILIZING AN EXTENDED KALMAN FILTER by Joseph B. Testa III December 2016 Thesis Advisor: Vladimir Dobrokhodov Co...TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE VISION-BASED POSITION ESTIMATION UTILIZING AN EXTENDED KALMAN FILTER 5. FUNDING...spots” and network relay between the boarding team and ship. 14. SUBJECT TERMS UAV, ROS, extended Kalman filter , Matlab

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.

Web Services Provide Access to SCEC Scientific Research Application Software

NASA Astrophysics Data System (ADS)

Gupta, N.; Gupta, V.; Okaya, D.; Kamb, L.; Maechling, P.

2003-12-01

Web services offer scientific communities a new paradigm for sharing research codes and communicating results. While there are formal technical definitions of what constitutes a web service, for a user community such as the Southern California Earthquake Center (SCEC), we may conceptually consider a web service to be functionality provided on-demand by an application which is run on a remote computer located elsewhere on the Internet. The value of a web service is that it can (1) run a scientific code without the user needing to install and learn the intricacies of running the code; (2) provide the technical framework which allows a user's computer to talk to the remote computer which performs the service; (3) provide the computational resources to run the code; and (4) bundle several analysis steps and provide the end results in digital or (post-processed) graphical form. Within an NSF-sponsored ITR project coordinated by SCEC, we are constructing web services using architectural protocols and programming languages (e.g., Java). However, because the SCEC community has a rich pool of scientific research software (written in traditional languages such as C and FORTRAN), we also emphasize making existing scientific codes available by constructing web service frameworks which wrap around and directly run these codes. In doing so we attempt to broaden community usage of these codes. Web service wrapping of a scientific code can be done using a "web servlet" construction or by using a SOAP/WSDL-based framework. This latter approach is widely adopted in IT circles although it is subject to rapid evolution. Our wrapping framework attempts to "honor" the original codes with as little modification as is possible. For versatility we identify three methods of user access: (A) a web-based GUI (written in HTML and/or Java applets); (B) a Linux/OSX/UNIX command line "initiator" utility (shell-scriptable); and (C) direct access from within any Java application (and with the correct API interface from within C++ and/or C/Fortran). This poster presentation will provide descriptions of the following selected web services and their origin as scientific application codes: 3D community velocity models for Southern California, geocoordinate conversions (latitude/longitude to UTM), execution of GMT graphical scripts, data format conversions (Gocad to Matlab format), and implementation of Seismic Hazard Analysis application programs that calculate hazard curve and hazard map data sets.

GridPV Toolbox

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

Broderick, Robert; Quiroz, Jimmy; Grijalva, Santiago

2014-07-15

Matlab Toolbox for simulating the impact of solar energy on the distribution grid. The majority of the functions are useful for interfacing OpenDSS and MATLAB, and they are of generic use for commanding OpenDSS from MATLAB and retrieving GridPV Toolbox information from simulations. A set of functions is also included for modeling PV plant output and setting up the PV plant in the OpenDSS simulation. The toolbox contains functions for modeling the OpenDSS distribution feeder on satellite images with GPS coordinates. Finally, example simulations functions are included to show potential uses of the toolbox functions.

Estimating aquifer transmissivity from specific capacity using MATLAB.

PubMed

McLin, Stephen G

2005-01-01

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

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.

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.

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.

Piezoelectric Actuator Modeling Using MSC/NASTRAN and MATLAB

NASA Technical Reports Server (NTRS)

Reaves, Mercedes C.; Horta, Lucas G.

2003-01-01

This paper presents a procedure for modeling structures containing piezoelectric actuators using MSCMASTRAN and MATLAB. The paper describes the utility and functionality of one set of validated modeling tools. The tools described herein use MSCMASTRAN to model the structure with piezoelectric actuators and a thermally induced strain to model straining of the actuators due to an applied voltage field. MATLAB scripts are used to assemble the dynamic equations and to generate frequency response functions. The application of these tools is discussed using a cantilever aluminum beam with a surface mounted piezoelectric actuator as a sample problem. Software in the form of MSCINASTRAN DMAP input commands, MATLAB scripts, and a step-by-step procedure to solve the example problem are provided. Analysis results are generated in terms of frequency response functions from deflection and strain data as a function of input voltage to the actuator.

Introduction to multifractal detrended fluctuation analysis in matlab.

PubMed

Ihlen, Espen A F

2012-01-01

Fractal structures are found in biomedical time series from a wide range of physiological phenomena. The multifractal spectrum identifies the deviations in fractal structure within time periods with large and small fluctuations. The present tutorial is an introduction to multifractal detrended fluctuation analysis (MFDFA) that estimates the multifractal spectrum of biomedical time series. The tutorial presents MFDFA step-by-step in an interactive Matlab session. All Matlab tools needed are available in Introduction to MFDFA folder at the website www.ntnu.edu/inm/geri/software. MFDFA are introduced in Matlab code boxes where the reader can employ pieces of, or the entire MFDFA to example time series. After introducing MFDFA, the tutorial discusses the best practice of MFDFA in biomedical signal processing. The main aim of the tutorial is to give the reader a simple self-sustained guide to the implementation of MFDFA and interpretation of the resulting multifractal spectra.

Introduction to Multifractal Detrended Fluctuation Analysis in Matlab

PubMed Central

Ihlen, Espen A. F.

2012-01-01

Fractal structures are found in biomedical time series from a wide range of physiological phenomena. The multifractal spectrum identifies the deviations in fractal structure within time periods with large and small fluctuations. The present tutorial is an introduction to multifractal detrended fluctuation analysis (MFDFA) that estimates the multifractal spectrum of biomedical time series. The tutorial presents MFDFA step-by-step in an interactive Matlab session. All Matlab tools needed are available in Introduction to MFDFA folder at the website www.ntnu.edu/inm/geri/software. MFDFA are introduced in Matlab code boxes where the reader can employ pieces of, or the entire MFDFA to example time series. After introducing MFDFA, the tutorial discusses the best practice of MFDFA in biomedical signal processing. The main aim of the tutorial is to give the reader a simple self-sustained guide to the implementation of MFDFA and interpretation of the resulting multifractal spectra. PMID:22675302

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.

A hardware experimental platform for neural circuits in the auditory cortex

NASA Astrophysics Data System (ADS)

Rodellar-Biarge, Victoria; García-Dominguez, Pablo; Ruiz-Rizaldos, Yago; Gómez-Vilda, Pedro

2011-05-01

Speech processing in the human brain is a very complex process far from being fully understood although much progress has been done recently. Neuromorphic Speech Processing is a new research orientation in bio-inspired systems approach to find solutions to automatic treatment of specific problems (recognition, synthesis, segmentation, diarization, etc) which can not be adequately solved using classical algorithms. In this paper a neuromorphic speech processing architecture is presented. The systematic bottom-up synthesis of layered structures reproduce the dynamic feature detection of speech related to plausible neural circuits which work as interpretation centres located in the Auditory Cortex. The elementary model is based on Hebbian neuron-like units. For the computation of the architecture a flexible framework is proposed in the environment of Matlab®/Simulink®/HDL, which allows building models in different description styles, complexity and implementation levels. It provides a flexible platform for experimenting on the influence of the number of neurons and interconnections, in the precision of the results and in performance evaluation. The experimentation with different architecture configurations may help both in better understanding how neural circuits may work in the brain as well as in how speech processing can benefit from this understanding.

H-Bridge Inverter Loading Analysis for an Energy Management System

DTIC Science & Technology

2013-06-01

In order to accomplish the stated objectives, a physics-based model of the system was developed in MATLAB/Simulink. The system was also implemented ...functional architecture and then compile the high level design down to VHDL in order to program the designed functions to the FPGA. B. INSULATED

MATLAB-Based Teaching Modules in Biochemical Engineering

ERIC Educational Resources Information Center

Lee, Kilho; Comolli, Noelle K.; Kelly, William J.; Huang, Zuyi

2015-01-01

Mathematical models play an important role in biochemical engineering. For example, the models developed in the field of systems biology have been used to identify drug targets to treat pathogens such as Pseudomonas aeruginosa in biofilms. In addition, competitive binding models for chromatography processes have been developed to predict expanded…

Dynamic Modeling and Simulation of a Rotational Inverted Pendulum

NASA Astrophysics Data System (ADS)

Duart, J. L.; Montero, B.; Ospina, P. A.; González, E.

2017-01-01

This paper presents an alternative way to the dynamic modeling of a rotational inverted pendulum using the classic mechanics known as Euler-Lagrange allows to find motion equations that describe our model. It also has a design of the basic model of the system in SolidWorks software, which based on the material and dimensions of the model provides some physical variables necessary for modeling. In order to verify the theoretical results, It was made a contrast between the solutions obtained by simulation SimMechanics-Matlab and the system of equations Euler-Lagrange, solved through ODE23tb method included in Matlab bookstores for solving equations systems of the type and order obtained. This article comprises a pendulum trajectory analysis by a phase space diagram that allows the identification of stable and unstable regions of the system.

Type, Content, and Source of Social Support Perceived by Women during Pregnancy: Evidence from Matlab, Bangladesh

PubMed Central

Paul, Moni; Sibley, Lynn M.

2011-01-01

Specific and contextualized data on social support during distinct health events are needed to improve social support interventions. This study identified the type, content, and source of social support perceived by women during pregnancy. In-depth interviews with 25 women, aged 18-49 years, living in Matlab, Bangladesh, were conducted. The findings demonstrated that women perceived, the receipt of eight distinct types of support. The four most frequently-mentioned types included: practical help with routine activities, information/advice, emotional support and assurance, as well as the provision of resources and material goods. Sources varied by type of support and most frequently included-—mothers, mothers-in-law, sisters-in-law, and husbands. Examples depicting the content of each type of support revealed culturally-specific issues that can inform community-based social support interventions. PMID:21608426

2D to 3D conversion implemented in different hardware

NASA Astrophysics Data System (ADS)

Ramos-Diaz, Eduardo; Gonzalez-Huitron, Victor; Ponomaryov, Volodymyr I.; Hernandez-Fragoso, Araceli

2015-02-01

Conversion of available 2D data for release in 3D content is a hot topic for providers and for success of the 3D applications, in general. It naturally completely relies on virtual view synthesis of a second view given by original 2D video. Disparity map (DM) estimation is a central task in 3D generation but still follows a very difficult problem for rendering novel images precisely. There exist different approaches in DM reconstruction, among them manually and semiautomatic methods that can produce high quality DMs but they demonstrate hard time consuming and are computationally expensive. In this paper, several hardware implementations of designed frameworks for an automatic 3D color video generation based on 2D real video sequence are proposed. The novel framework includes simultaneous processing of stereo pairs using the following blocks: CIE L*a*b* color space conversions, stereo matching via pyramidal scheme, color segmentation by k-means on an a*b* color plane, and adaptive post-filtering, DM estimation using stereo matching between left and right images (or neighboring frames in a video), adaptive post-filtering, and finally, the anaglyph 3D scene generation. Novel technique has been implemented on DSP TMS320DM648, Matlab's Simulink module over a PC with Windows 7, and using graphic card (NVIDIA Quadro K2000) demonstrating that the proposed approach can be applied in real-time processing mode. The time values needed, mean Similarity Structural Index Measure (SSIM) and Bad Matching Pixels (B) values for different hardware implementations (GPU, Single CPU, and DSP) are exposed in this paper.

An approach for quantitative image quality analysis for CT

NASA Astrophysics Data System (ADS)

Rahimi, Amir; Cochran, Joe; Mooney, Doug; Regensburger, Joe

2016-03-01

An objective and standardized approach to assess image quality of Compute Tomography (CT) systems is required in a wide variety of imaging processes to identify CT systems appropriate for a given application. We present an overview of the framework we have developed to help standardize and to objectively assess CT image quality for different models of CT scanners used for security applications. Within this framework, we have developed methods to quantitatively measure metrics that should correlate with feature identification, detection accuracy and precision, and image registration capabilities of CT machines and to identify strengths and weaknesses in different CT imaging technologies in transportation security. To that end we have designed, developed and constructed phantoms that allow for systematic and repeatable measurements of roughly 88 image quality metrics, representing modulation transfer function, noise equivalent quanta, noise power spectra, slice sensitivity profiles, streak artifacts, CT number uniformity, CT number consistency, object length accuracy, CT number path length consistency, and object registration. Furthermore, we have developed a sophisticated MATLAB based image analysis tool kit to analyze CT generated images of phantoms and report these metrics in a format that is standardized across the considered models of CT scanners, allowing for comparative image quality analysis within a CT model or between different CT models. In addition, we have developed a modified sparse principal component analysis (SPCA) method to generate a modified set of PCA components as compared to the standard principal component analysis (PCA) with sparse loadings in conjunction with Hotelling T2 statistical analysis method to compare, qualify, and detect faults in the tested systems.

A Field-Portable, Fiber-Optic Based Near-Infrared Spectrometer and its Applications to Fuels Analysis

DTIC Science & Technology

1991-05-28

R.E., Anal. Chem., 1991, 63, 114. 14. Ozubko, R.S., Clungston, D.M., Furimsky , E., Anal. Chem., 1981, 53, 183. 15. Hayes, P.C., Jr., Anderson, S.D...Adv. Study Inst. Sec. A, 1983, 46, 471. Ozubko, R.S., Clunqston, D.M., Furimsky , E., Anal. Chem., 1981, 53, 183. PC-MATLAB for 80386-based MS-DOS

Visualizing the inner product space ℝm×n in a MATLAB-assisted linear algebra classroom

NASA Astrophysics Data System (ADS)

Caglayan, Günhan

2018-05-01

This linear algebra note offers teaching and learning ideas in the treatment of the inner product space ? in a technology-supported learning environment. Classroom activities proposed in this note demonstrate creative ways of integrating MATLAB technology into various properties of Frobenius inner product as visualization tools that complement the algebraic approach. As implemented in linear algebra lessons in a university in the Unites States, the article also incorporates algebraic and visual work of students who experienced these activities with MATLAB software. The connection between the Frobenius norm and the Euclidean norm is also emphasized.

Characteristics of Multidrug Resistant Shigella and Vibrio cholerae O1 Infections in Patients Treated at an Urban and a Rural Hospital in Bangladesh.

PubMed

Das, Sumon Kumar; Klontz, Erik H; Azmi, Ishrat J; Ud-Din, Abu I M S; Chisti, Mohammod Jobayer; Afrad, Mokibul Hassan; Malek, Mohammad Abdul; Ahmed, Shahnawaz; Das, Jui; Talukder, Kaisar Ali; Salam, Mohammed Abdus; Bardhan, Pradip Kumar; Faruque, Abu Syed Golam; Klontz, Karl C

2013-12-22

We determined the frequency of multidrug resistant (MDR) infections with Shigella spp. and Vibrio cholerae O1 at an urban (Dhaka) and rural (Matlab) hospital in Bangladesh. We also compared sociodemographic and clinical features of patients with MDR infections to those with antibiotic-susceptible infections at both sites. Analyses were conducted using surveillance data from the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), for the years 2000-2012. Compared to patients with antibiotic-susceptible for Shigella infections, those in Dhaka with MDR shigellosis were more likely to experience diarrhea for >24 hours, while, in Matlab, they were more likely to stay inhospital >24 hours. For MDR shigellosis, Dhaka patients were more likely than those in Matlab to have dehydration, stool frequency >10/day, and diarrheal duration >24 hours. Patients with MDR Vibrio cholerae O1 infections in Dhaka were more likely than those in Matlab to experience dehydration and stool frequency >10/day. Thus, patients with MDR shigellosis and Vibrio cholerae O1 infection exhibited features suggesting more severe illness than those with antibiotic-susceptible infections. Moreover, Dhaka patients with MDR shigellosis and Vibrio cholerae O1 infections exhibited features indicating more severe illness than patients in Matlab.

MUTILS - a set of efficient modeling tools for multi-core CPUs implemented in MEX

NASA Astrophysics Data System (ADS)

Krotkiewski, Marcin; Dabrowski, Marcin

2013-04-01

The need for computational performance is common in scientific applications, and in particular in numerical simulations, where high resolution models require efficient processing of large amounts of data. Especially in the context of geological problems the need to increase the model resolution to resolve physical and geometrical complexities seems to have no limits. Alas, the performance of new generations of CPUs does not improve any longer by simply increasing clock speeds. Current industrial trends are to increase the number of computational cores. As a result, parallel implementations are required in order to fully utilize the potential of new processors, and to study more complex models. We target simulations on small to medium scale shared memory computers: laptops and desktop PCs with ~8 CPU cores and up to tens of GB of memory to high-end servers with ~50 CPU cores and hundereds of GB of memory. In this setting MATLAB is often the environment of choice for scientists that want to implement their own models with little effort. It is a useful general purpose mathematical software package, but due to its versatility some of its functionality is not as efficient as it could be. In particular, the challanges of modern multi-core architectures are not fully addressed. We have developed MILAMIN 2 - an efficient FEM modeling environment written in native MATLAB. Amongst others, MILAMIN provides functions to define model geometry, generate and convert structured and unstructured meshes (also through interfaces to external mesh generators), compute element and system matrices, apply boundary conditions, solve the system of linear equations, address non-linear and transient problems, and perform post-processing. MILAMIN strives to combine the ease of code development and the computational efficiency. Where possible, the code is optimized and/or parallelized within the MATLAB framework. Native MATLAB is augmented with the MUTILS library - a set of MEX functions that implement the computationally intensive, performance critical parts of the code, which we have identified to be bottlenecks. Here, we discuss the functionality and performance of the MUTILS library. Currently, it includes: 1. time and memory efficient assembly of sparse matrices for FEM simulations 2. parallel sparse matrix - vector product with optimizations speficic to symmetric matrices and multiple degrees of freedom per node 3. parallel point in triangle location and point in tetrahedron location for unstructured, adaptive 2D and 3D meshes (useful for 'marker in cell' type of methods) 4. parallel FEM interpolation for 2D and 3D meshes of elements of different types and orders, and for different number of degrees of freedom per node 5. a stand-alone, MEX implementation of the Conjugate Gradients iterative solver 6. interface to METIS graph partitioning and a fast implementation of RCM reordering

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.

Pulseq: A rapid and hardware-independent pulse sequence prototyping framework.

PubMed

Layton, Kelvin J; Kroboth, Stefan; Jia, Feng; Littin, Sebastian; Yu, Huijun; Leupold, Jochen; Nielsen, Jon-Fredrik; Stöcker, Tony; Zaitsev, Maxim

2017-04-01

Implementing new magnetic resonance experiments, or sequences, often involves extensive programming on vendor-specific platforms, which can be time consuming and costly. This situation is exacerbated when research sequences need to be implemented on several platforms simultaneously, for example, at different field strengths. This work presents an alternative programming environment that is hardware-independent, open-source, and promotes rapid sequence prototyping. A novel file format is described to efficiently store the hardware events and timing information required for an MR pulse sequence. Platform-dependent interpreter modules convert the file to appropriate instructions to run the sequence on MR hardware. Sequences can be designed in high-level languages, such as MATLAB, or with a graphical interface. Spin physics simulation tools are incorporated into the framework, allowing for comparison between real and virtual experiments. Minimal effort is required to implement relatively advanced sequences using the tools provided. Sequences are executed on three different MR platforms, demonstrating the flexibility of the approach. A high-level, flexible and hardware-independent approach to sequence programming is ideal for the rapid development of new sequences. The framework is currently not suitable for large patient studies or routine scanning although this would be possible with deeper integration into existing workflows. Magn Reson Med 77:1544-1552, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Obstacle Recognition Based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System

PubMed Central

Beruvides, Gerardo

2017-01-01

Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors’ knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions. PMID:28906450

Obstacle Recognition Based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System.

PubMed

Castaño, Fernando; Beruvides, Gerardo; Haber, Rodolfo E; Artuñedo, Antonio

2017-09-14

Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors' knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions.

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.

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

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.

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.

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

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.

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…

Design Method for Numerical Function Generators Based on Polynomial Approximation for FPGA Implementation

DTIC Science & Technology

2007-08-01

with a Design Specification de- scribed by Scilab [26], a MATLAB-like software applica- tion, and ends up with HDL code. The Design Specifica- tion...Conf. on Field Programmable Logic and Applications (FPL’05), Tampere, Finland, pp. 118–123, Aug. 2005. [26] Scilab 3.0, INRIA-ENPC, France, http

Dynamics Modelling of Transmission Gear Rattle and Analysis on Influence Factors

NASA Astrophysics Data System (ADS)

He, Xiaona; Zhang, Honghui

2018-02-01

Based on the vibration dynamics modeling for the single stage gear of transmission system, this paper is to understand the mechanism of transmission rattle. The dynamic model response using MATLAB and Runge-Kutta algorithm is analyzed, and the ways for reducing the rattle noise of the automotive transmission is summarized.

Simulated Analysis of Linear Reversible Enzyme Inhibition with SCILAB

ERIC Educational Resources Information Center

Antuch, Manuel; Ramos, Yaquelin; Álvarez, Rubén

2014-01-01

SCILAB is a lesser-known program (than MATLAB) for numeric simulations and has the advantage of being free software. A challenging software-based activity to analyze the most common linear reversible inhibition types with SCILAB is described. Students establish typical values for the concentration of enzyme, substrate, and inhibitor to simulate…

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

Interactive Learning Environment for Bio-Inspired Optimization Algorithms for UAV Path Planning

ERIC Educational Resources Information Center

Duan, Haibin; Li, Pei; Shi, Yuhui; Zhang, Xiangyin; Sun, Changhao

2015-01-01

This paper describes the development of BOLE, a MATLAB-based interactive learning environment, that facilitates the process of learning bio-inspired optimization algorithms, and that is dedicated exclusively to unmanned aerial vehicle path planning. As a complement to conventional teaching methods, BOLE is designed to help students consolidate the…

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

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.

A local active noise control system based on a virtual-microphone technique for railway sleeping vehicle applications

NASA Astrophysics Data System (ADS)

Diaz, J.; Egaña, J. M.; Viñolas, J.

2006-11-01

Low-frequency broadband noise generated on a railway vehicle by the wheel-rail interaction could be a big annoyance for passengers in sleeping cars. Low-frequency acoustic radiation is extremely difficult to attenuate by using passive devices. In this article, an active noise control (ANC) technique has been proposed for this purpose. A three-dimensional cabin was built in the laboratory to carry out the experiments. The proposed scheme is based on a Filtered-X Least Mean Square (FXLMS) control algorithm, particularised for a virtual-microphone technique. Control algorithms were designed with the Matlab-Simulink tool, and the Real Time Windows Target toolbox of Matlab was used to run in real time the ANC system. Referring to the results, different simulations and experimental performances were analysed to enlarge the silence zone around the passenger's ear zone and along the bed headboard. Attenuations of up to 20 and 15 dB(A) (re:20 μPa) were achieved at the passenger's ear in simulations and in experimental results, respectively.

Spherical nanoindentation stress-strain analysis, Version 1

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

Weaver, Jordan S.; Turner, David; Miller, Calvin

Nanoindentation is a tool that allows the mechanical response of a variety of materials at the nano to micron length scale to be measured. Recent advances in spherical nanoindentation techniques have allowed for a more reliable and meaningful characterization of the mechanical response from nanoindentation experiments in the form on an indentation stress-strain curve. This code base, Spin, is written in MATLAB (The Mathworks, Inc.) and based on the analysis protocols developed by S.R. Kalidindi and S. Pathak [1, 2]. The inputs include the displacement, load, harmonic contact stiffness, harmonic displacement, and harmonic load from spherical nanoindentation tests in themore » form of an Excel (Microsoft) spreadsheet. The outputs include indentation stress-strain curves and indentation properties as well their variance due to the uncertainty of the zero-point correction in the form of MATLAB data (.mat) and figures (.png). [1] S. Pathak, S.R. Kalidindi. Spherical nanoindentation stress–strain curves, Mater. Sci. Eng R-Rep 91 (2015). [2] S.R. Kalidindi, S. Pathak. Determination of the effective zero-point and the extraction of spherical nanoindentation stress-strain curves, Acta Materialia 56 (2008) 3523-3532.« less

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.

Motor imaginary-based brain-machine interface design using programmable logic controllers for the disabled.

PubMed

Jeyabalan, Vickneswaran; Samraj, Andrews; Loo, Chu Kiong

2010-10-01

Aiming at the implementation of brain-machine interfaces (BMI) for the aid of disabled people, this paper presents a system design for real-time communication between the BMI and programmable logic controllers (PLCs) to control an electrical actuator that could be used in devices to help the disabled. Motor imaginary signals extracted from the brain’s motor cortex using an electroencephalogram (EEG) were used as a control signal. The EEG signals were pre-processed by means of adaptive recursive band-pass filtrations (ARBF) and classified using simplified fuzzy adaptive resonance theory mapping (ARTMAP) in which the classified signals are then translated into control signals used for machine control via the PLC. A real-time test system was designed using MATLAB for signal processing, KEP-Ware V4 OLE for process control (OPC), a wireless local area network router, an Omron Sysmac CPM1 PLC and a 5 V/0.3A motor. This paper explains the signal processing techniques, the PLC's hardware configuration, OPC configuration and real-time data exchange between MATLAB and PLC using the MATLAB OPC toolbox. The test results indicate that the function of exchanging real-time data can be attained between the BMI and PLC through OPC server and proves that it is an effective and feasible method to be applied to devices such as wheelchairs or electronic equipment.

EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis.

PubMed

Delorme, Arnaud; Makeig, Scott

2004-03-15

We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.

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

The relationship between non-communicable disease occurrence and poverty-evidence from demographic surveillance in Matlab, Bangladesh.

PubMed

Mirelman, Andrew J; Rose, Sherri; Khan, Jahangir Am; Ahmed, Sayem; Peters, David H; Niessen, Louis W; Trujillo, Antonio J

2016-07-01

In low-income countries, a growing proportion of the disease burden is attributable to non-communicable diseases (NCDs). There is little knowledge, however, of their impact on wealth, human capital, economic growth or household poverty. This article estimates the risk of being poor after an NCD death in the rural, low-income area of Matlab, Bangladesh. In a matched cohort study, we estimated the 2-year relative risk (RR) of being poor in Matlab households with an NCD death in 2010. Three separate measures of household economic status were used as outcomes: an asset-based index, self-rated household economic condition and total household landholding. Several estimation methods were used including contingency tables, log-binomial regression and regression standardization and machine learning. Households with an NCD death had a large and significant risk of being poor. The unadjusted RR of being poor after death was 1.19, 1.14 and 1.10 for the asset quintile, self-rated condition and landholding outcomes. Adjusting for household and individual level independent variables with log-binomial regression gave RRs of 1.19 [standard error (SE) 0.09], 1.16 (SE 0.07) and 1.14 (SE 0.06), which were found to be exactly the same using regression standardization (SE: 0.09, 0.05, 0.03). Machine learning-based standardization produced slightly smaller RRs though still in the same order of magnitude. The findings show that efforts to address the burden of NCD may also combat household poverty and provide a return beyond improved health. Future work should attempt to disentangle the mechanisms through which economic impacts from an NCD death occur. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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.

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.

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

Development of Matlab Simulink model for dynamics analysis of passive suspension system for lightweight vehicle

NASA Astrophysics Data System (ADS)

Jamali, M. S.; Ismail, K. A.; Taha, Z.; Aiman, M. F.

2017-10-01

In designing suitable isolators to reduce unwanted vibration in vehicles, the response from a mathematical model which characterizes the transmissibility ratio of the input and output of the vehicle is required. In this study, a Matlab Simulink model is developed to study the dynamic behaviour performance of passive suspension system for a lightweight electric vehicle. The Simulink model is based on the two degrees of freedom system quarter car model. The model is compared to the theoretical plots of the transmissibility ratios between the amplitudes of the displacements and accelerations of the sprung and unsprung masses to the amplitudes of the ground, against the frequencies at different damping values. It was found that the frequency responses obtained from the theoretical calculations and from the Simulink simulation is comparable to each other. Hence, the model may be extended to a full vehicle model.

Aurally-adequate time-frequency analysis for scattered sound in auditoria

NASA Astrophysics Data System (ADS)

Norris, Molly K.; Xiang, Ning; Kleiner, Mendel

2005-04-01

The goal of this work was to apply an aurally-adequate time-frequency analysis technique to the analysis of sound scattering effects in auditoria. Time-frequency representations were developed as a motivated effort that takes into account binaural hearing, with a specific implementation of interaural cross-correlation process. A model of the human auditory system was implemented in the MATLAB platform based on two previous models [A. Härmä and K. Palomäki, HUTear, Espoo, Finland; and M. A. Akeroyd, A. Binaural Cross-correlogram Toolbox for MATLAB (2001), University of Sussex, Brighton]. These stages include proper frequency selectivity, the conversion of the mechanical motion of the basilar membrane to neural impulses, and binaural hearing effects. The model was then used in the analysis of room impulse responses with varying scattering characteristics. This paper discusses the analysis results using simulated and measured room impulse responses. [Work supported by the Frank H. and Eva B. Buck Foundation.

Control system of water flow and casting speed in continuous steel casting

NASA Astrophysics Data System (ADS)

Tirian, G. O.; Gheorghiu, C. A.; Hepuţ, T.; Chioncel, C.

2017-05-01

This paper presents the results of research based on real data taken from the installation process at Arcelor Mittal Hunedoara. Using Matlab Simulink an intelligent system is made that takes in data from the process and makes real time adjustments in the rate of flow of the cooling water and the speed of casting that eliminates fissures in the poured material from the secondary cooling of steel. Using Matlab Simulink simulation environment allowed for qualitative analysis for various real world situations. Thus, compared to the old method of approach for the problem of cracks forming in the crust of the steel in the continuous casting, this new method, proposed and developed, brings safety and precision in this complex process, thus removing any doubt on the existence or non-existence of cracks and takes the necessary steps to prevent and correct them.

A MATLAB implementation of the minimum relative entropy method for linear inverse problems

NASA Astrophysics Data System (ADS)

Neupauer, Roseanna M.; Borchers, Brian

2001-08-01

The minimum relative entropy (MRE) method can be used to solve linear inverse problems of the form Gm= d, where m is a vector of unknown model parameters and d is a vector of measured data. The MRE method treats the elements of m as random variables, and obtains a multivariate probability density function for m. The probability density function is constrained by prior information about the upper and lower bounds of m, a prior expected value of m, and the measured data. The solution of the inverse problem is the expected value of m, based on the derived probability density function. We present a MATLAB implementation of the MRE method. Several numerical issues arise in the implementation of the MRE method and are discussed here. We present the source history reconstruction problem from groundwater hydrology as an example of the MRE implementation.

Calculus Demonstrations Using MATLAB

ERIC Educational Resources Information Center

Dunn, Peter K.; Harman, Chris

2002-01-01

The note discusses ways in which technology can be used in the calculus learning process. In particular, five MATLAB programs are detailed for use by instructors or students that demonstrate important concepts in introductory calculus: Newton's method, differentiation and integration. Two of the programs are animated. The programs and the…

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.

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.

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.

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)

The role of socioeconomic status in longitudinal trends of cholera in Matlab, Bangladesh, 1993-2007.

PubMed

Root, Elisabeth Dowling; Rodd, Joshua; Yunus, Mohammad; Emch, Michael

2013-01-01

There has been little evidence of a decline in the global burden of cholera in recent years as the number of cholera cases reported to WHO continues to rise. Cholera remains a global threat to public health and a key indicator of lack of socioeconomic development. Overall socioeconomic development is the ultimate solution for control of cholera as evidenced in developed countries. However, most research has focused on cross-county comparisons so that the role of individual- or small area-level socioeconomic status (SES) in cholera dynamics has not been carefully studied. Reported cases of cholera in Matlab, Bangladesh have fluctuated greatly over time and epidemic outbreaks of cholera continue, most recently with the introduction of a new serotype into the region. The wealth of longitudinal data on the population of Matlab provides a unique opportunity to explore the impact of socioeconomic status and other demographic characteristics on the long-term temporal dynamics of cholera in the region. In this population-based study we examine which factors impact the initial number of cholera cases in a bari at the beginning of the 0139 epidemic and the factors impacting the number of cases over time. Cholera data were derived from the ICDDR,B health records and linked to socioeconomic and geographic data collected as part of the Matlab Health and Demographic Surveillance System. Longitudinal zero-inflated Poisson (ZIP) multilevel regression models are used to examine the impact of environmental and socio-demographic factors on cholera counts across baris. Results indicate that baris with a high socioeconomic status had lower initial rates of cholera at the beginning of the 0139 epidemic (γ(01) = -0.147, p = 0.041) and a higher probability of reporting no cholera cases (α(01) = 0.156, p = 0.061). Populations in baris characterized by low SES are more likely to experience higher cholera morbidity at the beginning of an epidemic than populations in high SES baris.

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…

Washington Play Fairway Analysis - Poly 3D Matlab Fault Modeling Scripts with Input Data to Create Permeability Potential Models

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

Swyer, Michael; Davatzes, Nicholas; Cladouhos, Trenton

Matlab scripts and functions and data used to build Poly3D models and create permeability potential layers for 1) St. Helens Shear Zone, 2) Wind River Valley, and 3) Mount Baker geothermal prospect areas located in Washington state.

SU-F-T-156: Monte Carlo Simulation Using TOPAS for Synchrotron Based Proton Discrete Spot Scanning System

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

Moskvin, V; Pirlepesov, F; Tsiamas, P

Purpose: This study provides an overview of the design and commissioning of the Monte Carlo (MC) model of the spot-scanning proton therapy nozzle and its implementation for the patient plan simulation. Methods: The Hitachi PROBEAT V scanning nozzle was simulated based on vendor specifications using the TOPAS extension of Geant4 code. FLUKA MC simulation was also utilized to provide supporting data for the main simulation. Validation of the MC model was performed using vendor provided data and measurements collected during acceptance/commissioning of the proton therapy machine. Actual patient plans using CT based treatment geometry were simulated and compared to themore » dose distributions produced by the treatment planning system (Varian Eclipse 13.6), and patient quality assurance measurements. In-house MATLAB scripts are used for converting DICOM data into TOPAS input files. Results: Comparison analysis of integrated depth doses (IDDs), therapeutic ranges (R90), and spot shape/sizes at different distances from the isocenter, indicate good agreement between MC and measurements. R90 agreement is within 0.15 mm across all energy tunes. IDDs and spot shapes/sizes differences are within statistical error of simulation (less than 1.5%). The MC simulated data, validated with physical measurements, were used for the commissioning of the treatment planning system. Patient geometry simulations were conducted based on the Eclipse produced DICOM plans. Conclusion: The treatment nozzle and standard option beam model were implemented in the TOPAS framework to simulate a highly conformal discrete spot-scanning proton beam system.« less

Turbofan Volume Dynamics Model for Investigations of Aero-Propulso-Servo-Elastic Effects in a Supersonic Commercial Transport

NASA Technical Reports Server (NTRS)

Connolly, Joseph W.; Kopasakis, George; Lemon, Kimberly A.

2010-01-01

A turbofan simulation has been developed for use in aero-propulso-servo-elastic coupling studies, on supersonic vehicles. A one-dimensional lumped volume approach is used whereby each component (fan, high-pressure compressor, combustor, etc.) is represented as a single volume using characteristic performance maps and conservation equations for continuity, momentum and energy. The simulation is developed in the MATLAB/SIMULINK (The MathWorks, Inc.) environment in order to facilitate controls development, and ease of integration with a future aero-servo-elastic vehicle model being developed at NASA Langley. The complete simulation demonstrated steady state results that closely match a proposed engine suitable for a supersonic business jet at the cruise condition. Preliminary investigation of the transient simulation revealed expected trends for fuel flow disturbances as well as upstream pressure disturbances. A framework for system identification enables development of linear models for controller design. Utilizing this framework, a transfer function modeling an upstream pressure disturbance s impacts on the engine speed is developed as an illustrative case of the system identification. This work will eventually enable an overall vehicle aero-propulso-servo-elastic model

Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM.

PubMed

López, J D; Litvak, V; Espinosa, J J; Friston, K; Barnes, G R

2014-01-01

The MEG/EEG inverse problem is ill-posed, giving different source reconstructions depending on the initial assumption sets. Parametric Empirical Bayes allows one to implement most popular MEG/EEG inversion schemes (Minimum Norm, LORETA, etc.) within the same generic Bayesian framework. It also provides a cost-function in terms of the variational Free energy-an approximation to the marginal likelihood or evidence of the solution. In this manuscript, we revisit the algorithm for MEG/EEG source reconstruction with a view to providing a didactic and practical guide. The aim is to promote and help standardise the development and consolidation of other schemes within the same framework. We describe the implementation in the Statistical Parametric Mapping (SPM) software package, carefully explaining each of its stages with the help of a simple simulated data example. We focus on the Multiple Sparse Priors (MSP) model, which we compare with the well-known Minimum Norm and LORETA models, using the negative variational Free energy for model comparison. The manuscript is accompanied by Matlab scripts to allow the reader to test and explore the underlying algorithm. © 2013. Published by Elsevier Inc. All rights reserved.

Variation of Time Domain Failure Probabilities of Jack-up with Wave Return Periods

NASA Astrophysics Data System (ADS)

Idris, Ahmad; Harahap, Indra S. H.; Ali, Montassir Osman Ahmed

2018-04-01

This study evaluated failure probabilities of jack up units on the framework of time dependent reliability analysis using uncertainty from different sea states representing different return period of the design wave. Surface elevation for each sea state was represented by Karhunen-Loeve expansion method using the eigenfunctions of prolate spheroidal wave functions in order to obtain the wave load. The stochastic wave load was propagated on a simplified jack up model developed in commercial software to obtain the structural response due to the wave loading. Analysis of the stochastic response to determine the failure probability in excessive deck displacement in the framework of time dependent reliability analysis was performed by developing Matlab codes in a personal computer. Results from the study indicated that the failure probability increases with increase in the severity of the sea state representing a longer return period. Although the results obtained are in agreement with the results of a study of similar jack up model using time independent method at higher values of maximum allowable deck displacement, it is in contrast at lower values of the criteria where the study reported that failure probability decreases with increase in the severity of the sea state.

Unified Access Architecture for Large-Scale Scientific Datasets

NASA Astrophysics Data System (ADS)

Karna, Risav

2014-05-01

Data-intensive sciences have to deploy diverse large scale database technologies for data analytics as scientists have now been dealing with much larger volume than ever before. While array databases have bridged many gaps between the needs of data-intensive research fields and DBMS technologies (Zhang 2011), invocation of other big data tools accompanying these databases is still manual and separate the database management's interface. We identify this as an architectural challenge that will increasingly complicate the user's work flow owing to the growing number of useful but isolated and niche database tools. Such use of data analysis tools in effect leaves the burden on the user's end to synchronize the results from other data manipulation analysis tools with the database management system. To this end, we propose a unified access interface for using big data tools within large scale scientific array database using the database queries themselves to embed foreign routines belonging to the big data tools. Such an invocation of foreign data manipulation routines inside a query into a database can be made possible through a user-defined function (UDF). UDFs that allow such levels of freedom as to call modules from another language and interface back and forth between the query body and the side-loaded functions would be needed for this purpose. For the purpose of this research we attempt coupling of four widely used tools Hadoop (hadoop1), Matlab (matlab1), R (r1) and ScaLAPACK (scalapack1) with UDF feature of rasdaman (Baumann 98), an array-based data manager, for investigating this concept. The native array data model used by an array-based data manager provides compact data storage and high performance operations on ordered data such as spatial data, temporal data, and matrix-based data for linear algebra operations (scidbusr1). Performances issues arising due to coupling of tools with different paradigms, niche functionalities, separate processes and output data formats have been anticipated and considered during the design of the unified architecture. The research focuses on the feasibility of the designed coupling mechanism and the evaluation of the efficiency and benefits of our proposed unified access architecture. Zhang 2011: Zhang, Ying and Kersten, Martin and Ivanova, Milena and Nes, Niels, SciQL: Bridging the Gap Between Science and Relational DBMS, Proceedings of the 15th Symposium on International Database Engineering Applications, 2011. Baumann 98: Baumann, P., Dehmel, A., Furtado, P., Ritsch, R., Widmann, N., "The Multidimensional Database System RasDaMan", SIGMOD 1998, Proceedings ACM SIGMOD International Conference on Management of Data, June 2-4, 1998, Seattle, Washington, 1998. hadoop1: hadoop.apache.org, "Hadoop", http://hadoop.apache.org/, [Online; accessed 12-Jan-2014]. scalapack1: netlib.org/scalapack, "ScaLAPACK", http://www.netlib.org/scalapack,[Online; accessed 12-Jan-2014]. r1: r-project.org, "R", http://www.r-project.org/,[Online; accessed 12-Jan-2014]. matlab1: mathworks.com, "Matlab Documentation", http://www.mathworks.de/de/help/matlab/,[Online; accessed 12-Jan-2014]. scidbusr1: scidb.org, "SciDB User's Guide", http://scidb.org/HTMLmanual/13.6/scidb_ug,[Online; accessed 01-Dec-2013].

Managing Data, Provenance and Chaos through Standardization and Automation at the Georgia Coastal Ecosystems LTER Site

NASA Astrophysics Data System (ADS)

Sheldon, W.

2013-12-01

Managing data for a large, multidisciplinary research program such as a Long Term Ecological Research (LTER) site is a significant challenge, but also presents unique opportunities for data stewardship. LTER research is conducted within multiple organizational frameworks (i.e. a specific LTER site as well as the broader LTER network), and addresses both specific goals defined in an NSF proposal as well as broader goals of the network; therefore, every LTER data can be linked to rich contextual information to guide interpretation and comparison. The challenge is how to link the data to this wealth of contextual metadata. At the Georgia Coastal Ecosystems LTER we developed an integrated information management system (GCE-IMS) to manage, archive and distribute data, metadata and other research products as well as manage project logistics, administration and governance (figure 1). This system allows us to store all project information in one place, and provide dynamic links through web applications and services to ensure content is always up to date on the web as well as in data set metadata. The database model supports tracking changes over time in personnel roles, projects and governance decisions, allowing these databases to serve as canonical sources of project history. Storing project information in a central database has also allowed us to standardize both the formatting and content of critical project information, including personnel names, roles, keywords, place names, attribute names, units, and instrumentation, providing consistency and improving data and metadata comparability. Lookup services for these standard terms also simplify data entry in web and database interfaces. We have also coupled the GCE-IMS to our MATLAB- and Python-based data processing tools (i.e. through database connections) to automate metadata generation and packaging of tabular and GIS data products for distribution. Data processing history is automatically tracked throughout the data lifecycle, from initial import through quality control, revision and integration by our data processing system (GCE Data Toolbox for MATLAB), and included in metadata for versioned data products. This high level of automation and system integration has proven very effective in managing the chaos and scalability of our information management program.

A toolbox for the fast information analysis of multiple-site LFP, EEG and spike train recordings

PubMed Central

Magri, Cesare; Whittingstall, Kevin; Singh, Vanessa; Logothetis, Nikos K; Panzeri, Stefano

2009-01-01

Background Information theory is an increasingly popular framework for studying how the brain encodes sensory information. Despite its widespread use for the analysis of spike trains of single neurons and of small neural populations, its application to the analysis of other types of neurophysiological signals (EEGs, LFPs, BOLD) has remained relatively limited so far. This is due to the limited-sampling bias which affects calculation of information, to the complexity of the techniques to eliminate the bias, and to the lack of publicly available fast routines for the information analysis of multi-dimensional responses. Results Here we introduce a new C- and Matlab-based information theoretic toolbox, specifically developed for neuroscience data. This toolbox implements a novel computationally-optimized algorithm for estimating many of the main information theoretic quantities and bias correction techniques used in neuroscience applications. We illustrate and test the toolbox in several ways. First, we verify that these algorithms provide accurate and unbiased estimates of the information carried by analog brain signals (i.e. LFPs, EEGs, or BOLD) even when using limited amounts of experimental data. This test is important since existing algorithms were so far tested primarily on spike trains. Second, we apply the toolbox to the analysis of EEGs recorded from a subject watching natural movies, and we characterize the electrodes locations, frequencies and signal features carrying the most visual information. Third, we explain how the toolbox can be used to break down the information carried by different features of the neural signal into distinct components reflecting different ways in which correlations between parts of the neural signal contribute to coding. We illustrate this breakdown by analyzing LFPs recorded from primary visual cortex during presentation of naturalistic movies. Conclusion The new toolbox presented here implements fast and data-robust computations of the most relevant quantities used in information theoretic analysis of neural data. The toolbox can be easily used within Matlab, the environment used by most neuroscience laboratories for the acquisition, preprocessing and plotting of neural data. It can therefore significantly enlarge the domain of application of information theory to neuroscience, and lead to new discoveries about the neural code. PMID:19607698

A toolbox for the fast information analysis of multiple-site LFP, EEG and spike train recordings.

PubMed

Magri, Cesare; Whittingstall, Kevin; Singh, Vanessa; Logothetis, Nikos K; Panzeri, Stefano

2009-07-16

Information theory is an increasingly popular framework for studying how the brain encodes sensory information. Despite its widespread use for the analysis of spike trains of single neurons and of small neural populations, its application to the analysis of other types of neurophysiological signals (EEGs, LFPs, BOLD) has remained relatively limited so far. This is due to the limited-sampling bias which affects calculation of information, to the complexity of the techniques to eliminate the bias, and to the lack of publicly available fast routines for the information analysis of multi-dimensional responses. Here we introduce a new C- and Matlab-based information theoretic toolbox, specifically developed for neuroscience data. This toolbox implements a novel computationally-optimized algorithm for estimating many of the main information theoretic quantities and bias correction techniques used in neuroscience applications. We illustrate and test the toolbox in several ways. First, we verify that these algorithms provide accurate and unbiased estimates of the information carried by analog brain signals (i.e. LFPs, EEGs, or BOLD) even when using limited amounts of experimental data. This test is important since existing algorithms were so far tested primarily on spike trains. Second, we apply the toolbox to the analysis of EEGs recorded from a subject watching natural movies, and we characterize the electrodes locations, frequencies and signal features carrying the most visual information. Third, we explain how the toolbox can be used to break down the information carried by different features of the neural signal into distinct components reflecting different ways in which correlations between parts of the neural signal contribute to coding. We illustrate this breakdown by analyzing LFPs recorded from primary visual cortex during presentation of naturalistic movies. The new toolbox presented here implements fast and data-robust computations of the most relevant quantities used in information theoretic analysis of neural data. The toolbox can be easily used within Matlab, the environment used by most neuroscience laboratories for the acquisition, preprocessing and plotting of neural data. It can therefore significantly enlarge the domain of application of information theory to neuroscience, and lead to new discoveries about the neural code.

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.

Compact Numerical Function Generators Based on Quadratic Approximation: Architecture and Synthesis Method

DTIC Science & Technology

2006-12-01

Specifi- cation described by Scilab [19], a MATLAB-like software, into HDL code. The Design Specification consists of a func- tion f (x), a domain over x...In- ter. Conf. on Field Programmable Logic and Applications (FPL’05), pp.118–123, Tampere, Finland, Aug. 2005. [19] Scilab 3.0, INRIA-ENPC, France

Programmable Numerical Function Generators Based on Quadratic Approximation: Architecture and Synthesis Method

DTIC Science & Technology

2006-01-01

experts. Fig. 1 shows the synthesis flow for the NFG. It converts the Design Specification described by Scilab [18], a MATLAB-like software, into HDL...Tam- pare, Finland, pp. 118–123, Aug. 2005. [18] Scilab 3.0, INRIA-ENPC, France, http://scilabsoft.inria.fr/ [19] M. J. Schulte and J. E. Stine

Arduino-Based Data Acquisition into Excel, LabVIEW, and MATLAB

ERIC Educational Resources Information Center

Nichols, Daniel

2017-01-01

Data acquisition equipment for physics can be quite expensive. As an alternative, data can be acquired using a low-cost Arduino microcontroller. The Arduino has been used in physics labs where the data are acquired using the Arduino software. The Arduino software, however, does not contain a suite of tools for data fitting and analysis. The data…

Teaching Reform of Course Group Regarding Theory and Design of Mechanisms Based on MATLAB Technology

ERIC Educational Resources Information Center

Shen, Yi; Yuan, Mingxin; Wang, Mingqiang

2013-01-01

Considering that the course group regarding theory and design of mechanisms is characterized by strong engineering application background and the students generally feel very boring and tedious during the learning process, some teaching reforms for the theory and design of mechanisms are carried out to improve the teaching effectiveness in this…

A Simulation Program for Dynamic Infrared (IR) Spectra

ERIC Educational Resources Information Center

Zoerb, Matthew C.; Harris, Charles B.

2013-01-01

A free program for the simulation of dynamic infrared (IR) spectra is presented. The program simulates the spectrum of two exchanging IR peaks based on simple input parameters. Larger systems can be simulated with minor modifications. The program is available as an executable program for PCs or can be run in MATLAB on any operating system. Source…

E-Learning Technologies: Employing Matlab Web Server to Facilitate the Education of Mathematical Programming

ERIC Educational Resources Information Center

Karagiannis, P.; Markelis, I.; Paparrizos, K.; Samaras, N.; Sifaleras, A.

2006-01-01

This paper presents new web-based educational software (webNetPro) for "Linear Network Programming." It includes many algorithms for "Network Optimization" problems, such as shortest path problems, minimum spanning tree problems, maximum flow problems and other search algorithms. Therefore, webNetPro can assist the teaching process of courses such…

Photogrammetry Toolbox Reference Manual

NASA Technical Reports Server (NTRS)

Liu, Tianshu; Burner, Alpheus W.

2014-01-01

Specialized photogrammetric and image processing MATLAB functions useful for wind tunnel and other ground-based testing of aerospace structures are described. These functions include single view and multi-view photogrammetric solutions, basic image processing to determine image coordinates, 2D and 3D coordinate transformations and least squares solutions, spatial and radiometric camera calibration, epipolar relations, and various supporting utility functions.

[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.

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.)

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.

Performance evaluation for volumetric segmentation of multiple sclerosis lesions using MATLAB and computing engine in the graphical processing unit (GPU)

NASA Astrophysics Data System (ADS)

Le, Anh H.; Park, Young W.; Ma, Kevin; Jacobs, Colin; Liu, Brent J.

2010-03-01

Multiple Sclerosis (MS) is a progressive neurological disease affecting myelin pathways in the brain. Multiple lesions in the white matter can cause paralysis and severe motor disabilities of the affected patient. To solve the issue of inconsistency and user-dependency in manual lesion measurement of MRI, we have proposed a 3-D automated lesion quantification algorithm to enable objective and efficient lesion volume tracking. The computer-aided detection (CAD) of MS, written in MATLAB, utilizes K-Nearest Neighbors (KNN) method to compute the probability of lesions on a per-voxel basis. Despite the highly optimized algorithm of imaging processing that is used in CAD development, MS CAD integration and evaluation in clinical workflow is technically challenging due to the requirement of high computation rates and memory bandwidth in the recursive nature of the algorithm. In this paper, we present the development and evaluation of using a computing engine in the graphical processing unit (GPU) with MATLAB for segmentation of MS lesions. The paper investigates the utilization of a high-end GPU for parallel computing of KNN in the MATLAB environment to improve algorithm performance. The integration is accomplished using NVIDIA's CUDA developmental toolkit for MATLAB. The results of this study will validate the practicality and effectiveness of the prototype MS CAD in a clinical setting. The GPU method may allow MS CAD to rapidly integrate in an electronic patient record or any disease-centric health care system.

A Finite Element Model for Mixed Porohyperelasticity with Transport, Swelling, and Growth.

PubMed

Armstrong, Michelle Hine; Buganza Tepole, Adrián; Kuhl, Ellen; Simon, Bruce R; Vande Geest, Jonathan P

2016-01-01

The purpose of this manuscript is to establish a unified theory of porohyperelasticity with transport and growth and to demonstrate the capability of this theory using a finite element model developed in MATLAB. We combine the theories of volumetric growth and mixed porohyperelasticity with transport and swelling (MPHETS) to derive a new method that models growth of biological soft tissues. The conservation equations and constitutive equations are developed for both solid-only growth and solid/fluid growth. An axisymmetric finite element framework is introduced for the new theory of growing MPHETS (GMPHETS). To illustrate the capabilities of this model, several example finite element test problems are considered using model geometry and material parameters based on experimental data from a porcine coronary artery. Multiple growth laws are considered, including time-driven, concentration-driven, and stress-driven growth. Time-driven growth is compared against an exact analytical solution to validate the model. For concentration-dependent growth, changing the diffusivity (representing a change in drug) fundamentally changes growth behavior. We further demonstrate that for stress-dependent, solid-only growth of an artery, growth of an MPHETS model results in a more uniform hoop stress than growth in a hyperelastic model for the same amount of growth time using the same growth law. This may have implications in the context of developing residual stresses in soft tissues under intraluminal pressure. To our knowledge, this manuscript provides the first full description of an MPHETS model with growth. The developed computational framework can be used in concert with novel in-vitro and in-vivo experimental approaches to identify the governing growth laws for various soft tissues.

The What and Where of Adding Channel Noise to the Hodgkin-Huxley Equations

PubMed Central

Goldwyn, Joshua H.; Shea-Brown, Eric

2011-01-01

Conductance-based equations for electrically active cells form one of the most widely studied mathematical frameworks in computational biology. This framework, as expressed through a set of differential equations by Hodgkin and Huxley, synthesizes the impact of ionic currents on a cell's voltage—and the highly nonlinear impact of that voltage back on the currents themselves—into the rapid push and pull of the action potential. Later studies confirmed that these cellular dynamics are orchestrated by individual ion channels, whose conformational changes regulate the conductance of each ionic current. Thus, kinetic equations familiar from physical chemistry are the natural setting for describing conductances; for small-to-moderate numbers of channels, these will predict fluctuations in conductances and stochasticity in the resulting action potentials. At first glance, the kinetic equations provide a far more complex (and higher-dimensional) description than the original Hodgkin-Huxley equations or their counterparts. This has prompted more than a decade of efforts to capture channel fluctuations with noise terms added to the equations of Hodgkin-Huxley type. Many of these approaches, while intuitively appealing, produce quantitative errors when compared to kinetic equations; others, as only very recently demonstrated, are both accurate and relatively simple. We review what works, what doesn't, and why, seeking to build a bridge to well-established results for the deterministic equations of Hodgkin-Huxley type as well as to more modern models of ion channel dynamics. As such, we hope that this review will speed emerging studies of how channel noise modulates electrophysiological dynamics and function. We supply user-friendly MATLAB simulation code of these stochastic versions of the Hodgkin-Huxley equations on the ModelDB website (accession number 138950) and http://www.amath.washington.edu/~etsb/tutorials.html. PMID:22125479

A Finite Element Model for Mixed Porohyperelasticity with Transport, Swelling, and Growth

PubMed Central

Armstrong, Michelle Hine; Buganza Tepole, Adrián; Kuhl, Ellen; Simon, Bruce R.; Vande Geest, Jonathan P.

2016-01-01

The purpose of this manuscript is to establish a unified theory of porohyperelasticity with transport and growth and to demonstrate the capability of this theory using a finite element model developed in MATLAB. We combine the theories of volumetric growth and mixed porohyperelasticity with transport and swelling (MPHETS) to derive a new method that models growth of biological soft tissues. The conservation equations and constitutive equations are developed for both solid-only growth and solid/fluid growth. An axisymmetric finite element framework is introduced for the new theory of growing MPHETS (GMPHETS). To illustrate the capabilities of this model, several example finite element test problems are considered using model geometry and material parameters based on experimental data from a porcine coronary artery. Multiple growth laws are considered, including time-driven, concentration-driven, and stress-driven growth. Time-driven growth is compared against an exact analytical solution to validate the model. For concentration-dependent growth, changing the diffusivity (representing a change in drug) fundamentally changes growth behavior. We further demonstrate that for stress-dependent, solid-only growth of an artery, growth of an MPHETS model results in a more uniform hoop stress than growth in a hyperelastic model for the same amount of growth time using the same growth law. This may have implications in the context of developing residual stresses in soft tissues under intraluminal pressure. To our knowledge, this manuscript provides the first full description of an MPHETS model with growth. The developed computational framework can be used in concert with novel in-vitro and in-vivo experimental approaches to identify the governing growth laws for various soft tissues. PMID:27078495

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.

Changing childhood malnutrition in Bangladesh: trends over the last two decades in urban-rural differentials (1993-2012).

PubMed

Das, Sumon Kumar; Chisti, Mohammod Jobayer; Malek, Mohammad Abdul; Das, Jui; Salam, Mohammed Abdus; Ahmed, Tahmeed; Al Mamun, Abdullah; Faruque, Abu Syed Golam

2015-07-01

The present study determined trends in malnutrition among under-5 children in urban and rural areas of Bangladesh. Surveillance. The study was conducted in the urban Dhaka and the rural Matlab hospitals of the International Centre for Diarrhoeal Disease Research, Bangladesh, where every fiftieth patient and all patients coming from the Health and Demographic Surveillance System were enrolled. A total of 28,816 under-5 children were enrolled at Dhaka from 1993 to 2012 and 11,533 at Matlab between 2000 and 2012. In Dhaka, 46% of the children were underweight, 39% were stunted and 28% were wasted. In Matlab, the corresponding figures were 39%, 31% and 26%, respectively. At Dhaka, 0.5% of the children were overweight and obese when assessed by weight-for-age Z-score >+2.00, 1.4% by BMI-for-age Z-score >+2.00 and 1.4% by weight-for-height Z-score >+2.00; in Matlab the corresponding figures were 0.5%, 1.4% and 1.4%, respectively. In Dhaka, the proportion of underweight, stunting and wasting decreased from 59% to 28% (a 53% reduction), from 54% to 22% (59% reduction) and from 33 % to 21% (36% reduction), respectively, between 1993 and 2012. In Matlab, these indicators decreased from 51% to 27% (a 47% reduction), from 36% to 25% (31% reduction) and from 34% to 14% (59% reduction), respectively, from 2000 to 2012. On the other hand, the proportion of overweight (as assessed by BMI-for-age Z-score) increased significantly over the study period in both Dhaka (from 0.6% to 2.6%) and Matlab (from 0.8% to 2.2%). The proportion of malnourished under-5 children has decreased gradually in both urban and rural Bangladesh; however, the reduction rates are not in line with meeting Millennium Development Goal 1. Trends for increasing childhood obesity have been noted during the study period as well.

Profile of maternal and foetal complications during labour and delivery among women giving birth in hospitals in Matlab and Chandpur, Bangladesh.

PubMed

Huda, Fauzia Akhter; Ahmed, Anisuddin; Dasgupta, Sushil Kanta; Jahan, Musharrat; Ferdous, Jannatul; Koblinsky, Marge; Ronsmans, Carine; Chowdhury, Mahbub Elahi

2012-06-01

Worldwide, for an estimated 358,000 women, pregnancy and childbirth end in death and mourning, and beyond these maternal deaths, 9-10% of pregnant women or about 14 million women per year suffer from acute maternal complications. This paper documents the types and severity of maternal and foetal complications among women who gave birth in hospitals in Matlab and Chandpur, Bangladesh, during 2007-2008. The Community Health Research Workers (CHRWs) of the icddr,b service area in Matlab prospectively collected data for the study from 4,817 women on their places of delivery and pregnancy outcomes. Of them, 3,010 (62.5%) gave birth in different hospitals in Matlab and/or Chandpur and beyond. Review of hospital-records was attempted for 2,102 women who gave birth only in the Matlab Hospital of icddr,b and in other public and private hospitals in the Matlab and Chandpur area. Among those, 1,927 (91.7%) records were found and reviewed by a physician. By reviewing the hospital-records, 7.3% of the women (n=1,927) who gave birth in the local hospitals were diagnosed with a severe maternal complication, and 16.1% with a less-severe maternal complication. Abortion cases--either spontaneous or induced--were excluded from the analysis. Over 12% of all births were delivered by caesarean section (CS). For a substantial proportion (12.5%) of CS, no clear medical indication was recorded in the hospital-register. Twelve maternal deaths occurred during the study period; most (83%) of them had been in contact with a hospital before death. Recommendations include standardization of the hospital record-keeping system, proper monitoring of indications of CS, and introduction of maternal death audit for further improvement of the quality of care in public and private hospitals in rural Bangladesh.

Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.

PubMed

Chatziioannou, Aristotelis; Moulos, Panagiotis; Kolisis, Fragiskos N

2009-10-27

The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. Gene ARMADA provides a highly adaptable, integrative, yet flexible tool which can be used for automated quality control, analysis, annotation and visualization of microarray data, constituting a starting point for further data interpretation and integration with numerous other tools.

Profile of Maternal and Foetal Complications during Labour and Delivery among Women Giving Birth in Hospitals in Matlab and Chandpur, Bangladesh

PubMed Central

Ahmed, Anisuddin; Dasgupta, Sushil Kanta; Jahan, Musharrat; Ferdous, Jannatul; Koblinsky, Marge; Ronsmans, Carine; Chowdhury, Mahbub Elahi

2012-01-01

Worldwide, for an estimated 358,000 women, pregnancy and childbirth end in death and mourning, and beyond these maternal deaths, 9-10% of pregnant women or about 14 million women per year suffer from acute maternal complications. This paper documents the types and severity of maternal and foetal complications among women who gave birth in hospitals in Matlab and Chandpur, Bangladesh, during 2007-2008. The Community Health Research Workers (CHRWs) of the icddr,b service area in Matlab prospectively collected data for the study from 4,817 women on their places of delivery and pregnancy outcomes. Of them, 3,010 (62.5%) gave birth in different hospitals in Matlab and/or Chandpur and beyond. Review of hospital-records was attempted for 2,102 women who gave birth only in the Matlab Hospital of icddr,b and in other public and private hospitals in the Matlab and Chandpur area. Among those, 1,927 (91.7%) records were found and reviewed by a physician. By reviewing the hospital-records, 7.3% of the women (n=1,927) who gave birth in the local hospitals were diagnosed with a severe maternal complication, and 16.1% with a less-severe maternal complication. Abortion cases—either spontaneous or induced—were excluded from the analysis. Over 12% of all births were delivered by caesarean section (CS). For a substantial proportion (12.5%) of CS, no clear medical indication was recorded in the hospital-register. Twelve maternal deaths occurred during the study period; most (83%) of them had been in contact with a hospital before death. Recommendations include standardization of the hospital record-keeping system, proper monitoring of indications of CS, and introduction of maternal death audit for further improvement of the quality of care in public and private hospitals in rural Bangladesh. PMID:22838156

Testing of Haar-Like Feature in Region of Interest Detection for Automated Target Recognition (ATR) System

NASA Technical Reports Server (NTRS)

Zhang, Yuhan; Lu, Dr. Thomas

2010-01-01

The objectives of this project were to develop a ROI (Region of Interest) detector using Haar-like feature similar to the face detection in Intel's OpenCV library, implement it in Matlab code, and test the performance of the new ROI detector against the existing ROI detector that uses Optimal Trade-off Maximum Average Correlation Height filter (OTMACH). The ROI detector included 3 parts: 1, Automated Haar-like feature selection in finding a small set of the most relevant Haar-like features for detecting ROIs that contained a target. 2, Having the small set of Haar-like features from the last step, a neural network needed to be trained to recognize ROIs with targets by taking the Haar-like features as inputs. 3, using the trained neural network from the last step, a filtering method needed to be developed to process the neural network responses into a small set of regions of interests. This needed to be coded in Matlab. All the 3 parts needed to be coded in Matlab. The parameters in the detector needed to be trained by machine learning and tested with specific datasets. Since OpenCV library and Haar-like feature were not available in Matlab, the Haar-like feature calculation needed to be implemented in Matlab. The codes for Adaptive Boosting and max/min filters in Matlab could to be found from the Internet but needed to be integrated to serve the purpose of this project. The performance of the new detector was tested by comparing the accuracy and the speed of the new detector against the existing OTMACH detector. The speed was referred as the average speed to find the regions of interests in an image. The accuracy was measured by the number of false positives (false alarms) at the same detection rate between the two detectors.

PFMCal : Photonic force microscopy calibration extended for its application in high-frequency microrheology

NASA Astrophysics Data System (ADS)

Butykai, A.; Domínguez-García, P.; Mor, F. M.; Gaál, R.; Forró, L.; Jeney, S.

2017-11-01

The present document is an update of the previously published MatLab code for the calibration of optical tweezers in the high-resolution detection of the Brownian motion of non-spherical probes [1]. In this instance, an alternative version of the original code, based on the same physical theory [2], but focused on the automation of the calibration of measurements using spherical probes, is outlined. The new added code is useful for high-frequency microrheology studies, where the probe radius is known but the viscosity of the surrounding fluid maybe not. This extended calibration methodology is automatic, without the need of a user's interface. A code for calibration by means of thermal noise analysis [3] is also included; this is a method that can be applied when using viscoelastic fluids if the trap stiffness is previously estimated [4]. The new code can be executed in MatLab and using GNU Octave. Program Files doi:http://dx.doi.org/10.17632/s59f3gz729.1 Licensing provisions: GPLv3 Programming language: MatLab 2016a (MathWorks Inc.) and GNU Octave 4.0 Operating system: Linux and Windows. Supplementary material: A new document README.pdf includes basic running instructions for the new code. Journal reference of previous version: Computer Physics Communications, 196 (2015) 599 Does the new version supersede the previous version?: No. It adds alternative but compatible code while providing similar calibration factors. Nature of problem (approx. 50-250 words): The original code uses a MatLab-provided user's interface, which is not available in GNU Octave, and cannot be used outside of a proprietary software as MatLab. Besides, the process of calibration when using spherical probes needs an automatic method when calibrating big amounts of different data focused to microrheology. Solution method (approx. 50-250 words): The new code can be executed in the latest version of MatLab and using GNU Octave, a free and open-source alternative to MatLab. This code generates an automatic calibration process which requires only to write the input data in the main script. Additionally, we include a calibration method based on thermal noise statistics, which can be used with viscoelastic fluids if the trap stiffness is previously estimated. Reasons for the new version: This version extends the functionality of PFMCal for the particular case of spherical probes and unknown fluid viscosities. The extended code is automatic, works in different operating systems and it is compatible with GNU Octave. Summary of revisions: The original MatLab program in the previous version, which is executed by PFMCal.m, is not changed. Here, we have added two additional main archives named PFMCal_auto.m and PFMCal_histo.m, which implement automatic calculations of the calibration process and calibration through Boltzmann statistics, respectively. The process of calibration using this code for spherical beads is described in the README.pdf file provided in the new code submission. Here, we obtain different calibration factors, β (given in μm/V), according to [2], related to two statistical quantities: the mean-squared displacement (MSD), βMSD, and the velocity autocorrelation function (VAF), βVAF. Using that methodology, the trap stiffness, k, and the zero-shear viscosity of the fluid, η, can be calculated if the value of the particle's radius, a, is previously known. For comparison, we include in the extended code the method of calibration using the corner frequency of the power-spectral density (PSD) [5], providing a calibration factor βPSD. Besides, with the prior estimation of the trap stiffness, along with the known value of the particle's radius, we can use thermal noise statistics to obtain calibration factors, β, according to the quadratic form of the optical potential, βE, and related to the Gaussian distribution of the bead's positions, βσ2. This method has been demonstrated to be applicable to the calibration of optical tweezers when using non-Newtonian viscoelastic polymeric liquids [4]. An example of the results using this calibration process is summarized in Table 1. Using the data provided in the new code submission, for water and acetone fluids, we calculate all the calibration factors by using the original PFMCal.m and by the new non-GUI code PFMCal_auto.m and PFMCal_histo.m. Regarding the new code, PFMCal_auto.m returns η, k, βMSD, βVAF and βPSD, while PFMCal_histo.m provides βσ2 and βE. Table 1 shows how we obtain the expected viscosity of the two fluids at this temperature and how the different methods provide good agreement between trap stiffnesses and calibration factors. Additional comments including Restrictions and Unusual features (approx. 50-250 words): The original code, PFMCal.m, runs under MatLab using the Statistics Toolbox. The extended code, PFMCal_auto.m and PFMCal_histo.m, can be executed without modification using MatLab or GNU Octave. The code has been tested in Linux and Windows operating systems.

g-PRIME: A Free, Windows Based Data Acquisition and Event Analysis Software Package for Physiology in Classrooms and Research Labs.

PubMed

Lott, Gus K; Johnson, Bruce R; Bonow, Robert H; Land, Bruce R; Hoy, Ronald R

2009-01-01

We present g-PRIME, a software based tool for physiology data acquisition, analysis, and stimulus generation in education and research. This software was developed in an undergraduate neurophysiology course and strongly influenced by instructor and student feedback. g-PRIME is a free, stand-alone, windows application coded and "compiled" in Matlab (does not require a Matlab license). g-PRIME supports many data acquisition interfaces from the PC sound card to expensive high throughput calibrated equipment. The program is designed as a software oscilloscope with standard trigger modes, multi-channel visualization controls, and data logging features. Extensive analysis options allow real time and offline filtering of signals, multi-parameter threshold-and-window based event detection, and two-dimensional display of a variety of parameters including event time, energy density, maximum FFT frequency component, max/min amplitudes, and inter-event rate and intervals. The software also correlates detected events with another simultaneously acquired source (event triggered average) in real time or offline. g-PRIME supports parameter histogram production and a variety of elegant publication quality graphics outputs. A major goal of this software is to merge powerful engineering acquisition and analysis tools with a biological approach to studies of nervous system function.

Modeling, control, and simulation of battery storage photovoltaic-wave energy hybrid renewable power generation systems for island electrification in Malaysia.

PubMed

Samrat, Nahidul Hoque; Bin Ahmad, Norhafizan; Choudhury, Imtiaz Ahmed; Bin Taha, Zahari

2014-01-01

Today, the whole world faces a great challenge to overcome the environmental problems related to global energy production. Most of the islands throughout the world depend on fossil fuel importation with respect to energy production. Recent development and research on green energy sources can assure sustainable power supply for the islands. But unpredictable nature and high dependency on weather conditions are the main limitations of renewable energy sources. To overcome this drawback, different renewable sources and converters need to be integrated with each other. This paper proposes a standalone hybrid photovoltaic- (PV-) wave energy conversion system with energy storage. In the proposed hybrid system, control of the bidirectional buck-boost DC-DC converter (BBDC) is used to maintain the constant dc-link voltage. It also accumulates the excess hybrid power in the battery bank and supplies this power to the system load during the shortage of hybrid power. A three-phase complex vector control scheme voltage source inverter (VSI) is used to control the load side voltage in terms of the frequency and voltage amplitude. Based on the simulation results obtained from Matlab/Simulink, it has been found that the overall hybrid framework is capable of working under the variable weather and load conditions.

Modeling, Control, and Simulation of Battery Storage Photovoltaic-Wave Energy Hybrid Renewable Power Generation Systems for Island Electrification in Malaysia

PubMed Central

Samrat, Nahidul Hoque; Ahmad, Norhafizan Bin; Choudhury, Imtiaz Ahmed; Taha, Zahari Bin

2014-01-01

Today, the whole world faces a great challenge to overcome the environmental problems related to global energy production. Most of the islands throughout the world depend on fossil fuel importation with respect to energy production. Recent development and research on green energy sources can assure sustainable power supply for the islands. But unpredictable nature and high dependency on weather conditions are the main limitations of renewable energy sources. To overcome this drawback, different renewable sources and converters need to be integrated with each other. This paper proposes a standalone hybrid photovoltaic- (PV-) wave energy conversion system with energy storage. In the proposed hybrid system, control of the bidirectional buck-boost DC-DC converter (BBDC) is used to maintain the constant dc-link voltage. It also accumulates the excess hybrid power in the battery bank and supplies this power to the system load during the shortage of hybrid power. A three-phase complex vector control scheme voltage source inverter (VSI) is used to control the load side voltage in terms of the frequency and voltage amplitude. Based on the simulation results obtained from Matlab/Simulink, it has been found that the overall hybrid framework is capable of working under the variable weather and load conditions. PMID:24892049

NeuroCa: integrated framework for systematic analysis of spatiotemporal neuronal activity patterns from large-scale optical recording data

PubMed Central

Jang, Min Jee; Nam, Yoonkey

2015-01-01

Abstract. Optical recording facilitates monitoring the activity of a large neural network at the cellular scale, but the analysis and interpretation of the collected data remain challenging. Here, we present a MATLAB-based toolbox, named NeuroCa, for the automated processing and quantitative analysis of large-scale calcium imaging data. Our tool includes several computational algorithms to extract the calcium spike trains of individual neurons from the calcium imaging data in an automatic fashion. Two algorithms were developed to decompose the imaging data into the activity of individual cells and subsequently detect calcium spikes from each neuronal signal. Applying our method to dense networks in dissociated cultures, we were able to obtain the calcium spike trains of ∼1000 neurons in a few minutes. Further analyses using these data permitted the quantification of neuronal responses to chemical stimuli as well as functional mapping of spatiotemporal patterns in neuronal firing within the spontaneous, synchronous activity of a large network. These results demonstrate that our method not only automates time-consuming, labor-intensive tasks in the analysis of neural data obtained using optical recording techniques but also provides a systematic way to visualize and quantify the collective dynamics of a network in terms of its cellular elements. PMID:26229973

Haptic-Based Neurorehabilitation in Poststroke Patients: A Feasibility Prospective Multicentre Trial for Robotics Hand Rehabilitation

PubMed Central

Daud Albasini, Omar A.; Oboe, Roberto; Tonin, Paolo; Paolucci, Stefano; Sandrini, Giorgio; Piron, Lamberto

2013-01-01

Background. Haptic robots allow the exploitation of known motor learning mechanisms, representing a valuable option for motor treatment after stroke. The aim of this feasibility multicentre study was to test the clinical efficacy of a haptic prototype, for the recovery of hand function after stroke. Methods. A prospective pilot clinical trial was planned on 15 consecutive patients enrolled in 3 rehabilitation centre in Italy. All the framework features of the haptic robot (e.g., control loop, external communication, and graphic rendering for virtual reality) were implemented into a real-time MATLAB/Simulink environment, controlling a five-bar linkage able to provide forces up to 20 [N] at the end effector, used for finger and hand rehabilitation therapies. Clinical (i.e., Fugl-Meyer upper extremity scale; nine hold pegboard test) and kinematics (i.e., time; velocity; jerk metric; normalized jerk of standard movements) outcomes were assessed before and after treatment to detect changes in patients' motor performance. Reorganization of cortical activation was detected in one patient by fMRI. Results and Conclusions. All patients showed significant improvements in both clinical and kinematic outcomes. Additionally, fMRI results suggest that the proposed approach may promote a better cortical activation in the brain. PMID:24319496

Haptic-based neurorehabilitation in poststroke patients: a feasibility prospective multicentre trial for robotics hand rehabilitation.

PubMed

Turolla, Andrea; Daud Albasini, Omar A; Oboe, Roberto; Agostini, Michela; Tonin, Paolo; Paolucci, Stefano; Sandrini, Giorgio; Venneri, Annalena; Piron, Lamberto

2013-01-01

Background. Haptic robots allow the exploitation of known motor learning mechanisms, representing a valuable option for motor treatment after stroke. The aim of this feasibility multicentre study was to test the clinical efficacy of a haptic prototype, for the recovery of hand function after stroke. Methods. A prospective pilot clinical trial was planned on 15 consecutive patients enrolled in 3 rehabilitation centre in Italy. All the framework features of the haptic robot (e.g., control loop, external communication, and graphic rendering for virtual reality) were implemented into a real-time MATLAB/Simulink environment, controlling a five-bar linkage able to provide forces up to 20 [N] at the end effector, used for finger and hand rehabilitation therapies. Clinical (i.e., Fugl-Meyer upper extremity scale; nine hold pegboard test) and kinematics (i.e., time; velocity; jerk metric; normalized jerk of standard movements) outcomes were assessed before and after treatment to detect changes in patients' motor performance. Reorganization of cortical activation was detected in one patient by fMRI. Results and Conclusions. All patients showed significant improvements in both clinical and kinematic outcomes. Additionally, fMRI results suggest that the proposed approach may promote a better cortical activation in the brain.

Enhancing Teaching using MATLAB Add-Ins for Excel

ERIC Educational Resources Information Center

Hamilton, Paul V.

2004-01-01

In this paper I will illustrate how to extend the capabilities of Microsoft Excel spreadsheets with add-ins created by MATLAB. Excel provides a broad array of fundamental tools but often comes up short when more sophisticated scenarios are involved. To overcome this short-coming of Excel while retaining its ease of use, I will describe how…

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.

The Relationship between Gender and Students' Attitude and Experience of Using a Mathematical Software Program (MATLAB)

ERIC Educational Resources Information Center

Ocak, Mehmet A.

2006-01-01

This correlation 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…

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…

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

Cross-species 3D virtual reality toolbox for visual and cognitive experiments.

PubMed

Doucet, Guillaume; Gulli, Roberto A; Martinez-Trujillo, Julio C

2016-06-15

Although simplified visual stimuli, such as dots or gratings presented on homogeneous backgrounds, provide strict control over the stimulus parameters during visual experiments, they fail to approximate visual stimulation in natural conditions. Adoption of virtual reality (VR) in neuroscience research has been proposed to circumvent this problem, by combining strict control of experimental variables and behavioral monitoring within complex and realistic environments. We have created a VR toolbox that maximizes experimental flexibility while minimizing implementation costs. A free VR engine (Unreal 3) has been customized to interface with any control software via text commands, allowing seamless introduction into pre-existing laboratory data acquisition frameworks. Furthermore, control functions are provided for the two most common programming languages used in visual neuroscience: Matlab and Python. The toolbox offers milliseconds time resolution necessary for electrophysiological recordings and is flexible enough to support cross-species usage across a wide range of paradigms. Unlike previously proposed VR solutions whose implementation is complex and time-consuming, our toolbox requires minimal customization or technical expertise to interface with pre-existing data acquisition frameworks as it relies on already familiar programming environments. Moreover, as it is compatible with a variety of display and input devices, identical VR testing paradigms can be used across species, from rodents to humans. This toolbox facilitates the addition of VR capabilities to any laboratory without perturbing pre-existing data acquisition frameworks, or requiring any major hardware changes. Copyright © 2016 Z. All rights reserved.

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

A Comprehensive Application to Assist in Acid-Base Titration Self-Learning: An Approach for High School and Undergraduate Students

ERIC Educational Resources Information Center

Gonza´lez-Go´mez, David; Rodríguez, Diego Airado; Can~ada-Can~ada, Florentina; Jeong, Jin Su

2015-01-01

Currently, there are a number of educational applications that allow students to reinforce theoretical or numerical concepts through an interactive way. More precisely, in the field of the analytical chemistry, MATLAB has been widely used to write easy-to-implement code, facilitating complex performances and/or tedious calculations. The main…

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

Fission gas bubble identification using MATLAB's image processing toolbox

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

Collette, R.; King, J.; Keiser, Jr., D.

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

Effect of separate sampling on classification accuracy.

PubMed

Shahrokh Esfahani, Mohammad; Dougherty, Edward R

2014-01-15

Measurements are commonly taken from two phenotypes to build a classifier, where the number of data points from each class is predetermined, not random. In this 'separate sampling' scenario, the data cannot be used to estimate the class prior probabilities. Moreover, predetermined class sizes can severely degrade classifier performance, even for large samples. We employ simulations using both synthetic and real data to show the detrimental effect of separate sampling on a variety of classification rules. We establish propositions related to the effect on the expected classifier error owing to a sampling ratio different from the population class ratio. From these we derive a sample-based minimax sampling ratio and provide an algorithm for approximating it from the data. We also extend to arbitrary distributions the classical population-based Anderson linear discriminant analysis minimax sampling ratio derived from the discriminant form of the Bayes classifier. All the codes for synthetic data and real data examples are written in MATLAB. A function called mmratio, whose output is an approximation of the minimax sampling ratio of a given dataset, is also written in MATLAB. All the codes are available at: http://gsp.tamu.edu/Publications/supplementary/shahrokh13b.

MATLAB Simulation of UPQC for Power Quality Mitigation Using an Ant Colony Based Fuzzy Control Technique

PubMed Central

Kumarasabapathy, N.; Manoharan, P. S.

2015-01-01

This paper proposes a fuzzy logic based new control scheme for the Unified Power Quality Conditioner (UPQC) for minimizing the voltage sag and total harmonic distortion in the distribution system consequently to improve the power quality. UPQC is a recent power electronic module which guarantees better power quality mitigation as it has both series-active and shunt-active power filters (APFs). The fuzzy logic controller has recently attracted a great deal of attention and possesses conceptually the quality of the simplicity by tackling complex systems with vagueness and ambiguity. In this research, the fuzzy logic controller is utilized for the generation of reference signal controlling the UPQC. To enable this, a systematic approach for creating the fuzzy membership functions is carried out by using an ant colony optimization technique for optimal fuzzy logic control. An exhaustive simulation study using the MATLAB/Simulink is carried out to investigate and demonstrate the performance of the proposed fuzzy logic controller and the simulation results are compared with the PI controller in terms of its performance in improving the power quality by minimizing the voltage sag and total harmonic distortion. PMID:26504895

A low-cost real color picker based on Arduino.

PubMed

Agudo, Juan Enrique; Pardo, Pedro J; Sánchez, Héctor; Pérez, Ángel Luis; Suero, María Isabel

2014-07-07

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.

Fission gas bubble identification using MATLAB's image processing toolbox

DOE PAGES

Collette, R.; King, J.; Keiser, Jr., D.; ...

2016-06-08

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

Optimization by means of an analytical heat transfer model of a thermal insulation for CSP applications based on radiative shields

NASA Astrophysics Data System (ADS)

Gaetano, A.; Roncolato, J.; Montorfano, D.; Barbato, M. C.; Ambrosetti, G.; Pedretti, A.

2016-05-01

The employment of new gaseous heat transfer fluids as air or CO2, which are cheaper and environmentally friendly, is drawing more and more attention within the field of Concentrated Solar Power applications. However, despite the advantages, their use requires receivers with a larger heat transfer area and flow cross section with a consequent greater volume of thermal insulation. Solid thermal insulations currently used present high thermal inertia which is energetically penalizing during the daily transient phases faced by the main plant components (e.g. receivers). With the aim of overcoming this drawback a thermal insulation based on radiative shields is presented in this study. Starting from an initial layout comprising a solid thermal insulation layer, the geometry was optimized avoiding the use of the solid insulation keeping performance and fulfilling the geometrical constraints. An analytical Matlab model was implemented to assess the system thermal behavior in terms of heat loss taking into account conductive, convective and radiative contributions. Accurate 2D Computational Fluid Dynamics (CFD) simulations were run to validate the Matlab model which was then used to select the most promising among three new different designs.

Intelligence system based classification approach for medical disease diagnosis

NASA Astrophysics Data System (ADS)

Sagir, Abdu Masanawa; Sathasivam, Saratha

2017-08-01

The prediction of breast cancer in women who have no signs or symptoms of the disease as well as survivability after undergone certain surgery has been a challenging problem for medical researchers. The decision about presence or absence of diseases depends on the physician's intuition, experience and skill for comparing current indicators with previous one than on knowledge rich data hidden in a database. This measure is a very crucial and challenging task. The goal is to predict patient condition by using an adaptive neuro fuzzy inference system (ANFIS) pre-processed by grid partitioning. To achieve an accurate diagnosis at this complex stage of symptom analysis, the physician may need efficient diagnosis system. A framework describes methodology for designing and evaluation of classification performances of two discrete ANFIS systems of hybrid learning algorithms least square estimates with Modified Levenberg-Marquardt and Gradient descent algorithms that can be used by physicians to accelerate diagnosis process. The proposed method's performance was evaluated based on training and test datasets with mammographic mass and Haberman's survival Datasets obtained from benchmarked datasets of University of California at Irvine's (UCI) machine learning repository. The robustness of the performance measuring total accuracy, sensitivity and specificity is examined. In comparison, the proposed method achieves superior performance when compared to conventional ANFIS based gradient descent algorithm and some related existing methods. The software used for the implementation is MATLAB R2014a (version 8.3) and executed in PC Intel Pentium IV E7400 processor with 2.80 GHz speed and 2.0 GB of RAM.

An OpenMI Implementation of a Water Resources System using Simple Script Wrappers

NASA Astrophysics Data System (ADS)

Steward, D. R.; Aistrup, J. A.; Kulcsar, L.; Peterson, J. M.; Welch, S. M.; Andresen, D.; Bernard, E. A.; Staggenborg, S. A.; Bulatewicz, T.

2013-12-01

This team has developed an adaption of the Open Modelling Interface (OpenMI) that utilizes Simple Script Wrappers. Code is made OpenMI compliant through organization within three modules that initialize, perform time steps, and finalize results. A configuration file is prepared that specifies variables a model expects to receive as input and those it will make available as output. An example is presented for groundwater, economic, and agricultural production models in the High Plains Aquifer region of Kansas. Our models use the programming environments in Scilab and Matlab, along with legacy Fortran code, and our Simple Script Wrappers can also use Python. These models are collectively run within this interdisciplinary framework from initial conditions into the future. It will be shown that by applying model constraints to one model, the impact may be accessed on changes to the water resources system.

Development of user-friendly and interactive data collection system for cerebral palsy.

PubMed

Raharjo, I; Burns, T G; Venugopalan, J; Wang, M D

2016-02-01

Cerebral palsy (CP) is a permanent motor disorder that appears in early age and it requires multiple tests to assess the physical and mental capabilities of the patients. Current medical record data collection systems, e.g., EPIC, employed for CP are very general, difficult to navigate, and prone to errors. The data cannot easily be extracted which limits data analysis on this rich source of information. To overcome these limitations, we designed and prototyped a database with a graphical user interface geared towards clinical research specifically in CP. The platform with MySQL and Java framework is reliable, secure, and can be easily integrated with other programming languages for data analysis such as MATLAB. This database with GUI design is a promising tool for data collection and can be applied in many different fields aside from CP to infer useful information out of the vast amount of data being collected.

Development of user-friendly and interactive data collection system for cerebral palsy

PubMed Central

Raharjo, I.; Burns, T. G.; Venugopalan, J.; Wang., M. D.

2016-01-01

Cerebral palsy (CP) is a permanent motor disorder that appears in early age and it requires multiple tests to assess the physical and mental capabilities of the patients. Current medical record data collection systems, e.g., EPIC, employed for CP are very general, difficult to navigate, and prone to errors. The data cannot easily be extracted which limits data analysis on this rich source of information. To overcome these limitations, we designed and prototyped a database with a graphical user interface geared towards clinical research specifically in CP. The platform with MySQL and Java framework is reliable, secure, and can be easily integrated with other programming languages for data analysis such as MATLAB. This database with GUI design is a promising tool for data collection and can be applied in many different fields aside from CP to infer useful information out of the vast amount of data being collected. PMID:28133638

Fault-tolerant Control of a Cyber-physical System

NASA Astrophysics Data System (ADS)

Roxana, Rusu-Both; Eva-Henrietta, Dulf

2017-10-01

Cyber-physical systems represent a new emerging field in automatic control. The fault system is a key component, because modern, large scale processes must meet high standards of performance, reliability and safety. Fault propagation in large scale chemical processes can lead to loss of production, energy, raw materials and even environmental hazard. The present paper develops a multi-agent fault-tolerant control architecture using robust fractional order controllers for a (13C) cryogenic separation column cascade. The JADE (Java Agent DEvelopment Framework) platform was used to implement the multi-agent fault tolerant control system while the operational model of the process was implemented in Matlab/SIMULINK environment. MACSimJX (Multiagent Control Using Simulink with Jade Extension) toolbox was used to link the control system and the process model. In order to verify the performance and to prove the feasibility of the proposed control architecture several fault simulation scenarios were performed.

Utilizing feedback in adaptive SAR ATR systems

NASA Astrophysics Data System (ADS)

Horsfield, Owen; Blacknell, David

2009-05-01

Existing SAR ATR systems are usually trained off-line with samples of target imagery or CAD models, prior to conducting a mission. If the training data is not representative of mission conditions, then poor performance may result. In addition, it is difficult to acquire suitable training data for the many target types of interest. The Adaptive SAR ATR Problem Set (AdaptSAPS) program provides a MATLAB framework and image database for developing systems that adapt to mission conditions, meaning less reliance on accurate training data. A key function of an adaptive system is the ability to utilise truth feedback to improve performance, and it is this feature which AdaptSAPS is intended to exploit. This paper presents a new method for SAR ATR that does not use training data, based on supervised learning. This is achieved by using feature-based classification, and several new shadow features have been developed for this purpose. These features allow discrimination of vehicles from clutter, and classification of vehicles into two classes: targets, comprising military combat types, and non-targets, comprising bulldozers and trucks. The performance of the system is assessed using three baseline missions provided with AdaptSAPS, as well as three additional missions. All performance metrics indicate a distinct learning trend over the course of a mission, with most third and fourth quartile performance levels exceeding 85% correct classification. It has been demonstrated that these performance levels can be maintained even when truth feedback rates are reduced by up to 55% over the course of a mission.

Surface mesh to voxel data registration for patient-specific anatomical modeling

NASA Astrophysics Data System (ADS)

de Oliveira, Júlia E. E.; Giessler, Paul; Keszei, András.; Herrler, Andreas; Deserno, Thomas M.

2016-03-01

Virtual Physiological Human (VPH) models are frequently used for training, planning, and performing medical procedures. The Regional Anaesthesia Simulator and Assistant (RASimAs) project has the goal of increasing the application and effectiveness of regional anesthesia (RA) by combining a simulator of ultrasound-guided and electrical nerve-stimulated RA procedures and a subject-specific assistance system through an integration of image processing, physiological models, subject-specific data, and virtual reality. Individualized models enrich the virtual training tools for learning and improving regional anaesthesia (RA) skills. Therefore, we suggest patient-specific VPH models that are composed by registering the general mesh-based models with patient voxel data-based recordings. Specifically, the pelvis region has been focused for the support of the femoral nerve block. The processing pipeline is composed of different freely available toolboxes such as MatLab, the open Simulation framework (SOFA), and MeshLab. The approach of Gilles is applied for mesh-to-voxel registration. Personalized VPH models include anatomical as well as mechanical properties of the tissues. Two commercial VPH models (Zygote and Anatomium) were used together with 34 MRI data sets. Results are presented for the skin surface and pelvic bones. Future work will extend the registration procedure to cope with all model tissue (i.e., skin, muscle, bone, vessel, nerve, fascia) in a one-step procedure and extrapolating the personalized models to body regions actually being out of the captured field of view.

A Low Cost Rokkaku Kite Setup for Aerial Photogrammetric System

NASA Astrophysics Data System (ADS)

Khan, A. F.; Khurshid, K.; Saleh, N.; Yousuf, A. A.

2015-03-01

Orthogonally Projected Area (OPA) of a geographical feature has primarily been studied utilizing rather time consuming field based sampling techniques. Remote sensing on the contrary provides the ability to acquire large scale data at a snapshot of time and lets the OPA to be calculated conveniently and with reasonable accuracy. Unfortunately satellite based remote sensing provides data at high cost and limited spatial resolution for scientific studies focused at small areas such as micro lakes micro ecosystems, etc. More importantly, recent satellite data may not be readily available for a particular location. This paper describes a low cost photogrammetric system to measure the OPA of a small scale geographic feature such as a plot of land, micro lake or an archaeological site, etc. Fitted with a consumer grade digital imaging system, a Rokkaku kite aerial platform with stable flight characteristics is designed and fabricated for image acquisition. The data processing procedure involves automatic Ground Control Point (GCP) detection, intelligent target area shape determination with minimal human input. A Graphical User Interface (GUI) is built from scratch in MATLAB to allow the user to conveniently process the acquired data, archive and retrieve the results. Extensive on-field experimentation consists of multiple geographic features including flat land surfaces, buildings, undulating rural areas, and an irregular shaped micro lake, etc. Our results show that the proposed system is not only low cost, but provides a framework that is easy and fast to setup while maintaining the required constraints on the accuracy.

Optimal integration strategies for a syngas fuelled SOFC and gas turbine hybrid

NASA Astrophysics Data System (ADS)

Zhao, Yingru; Sadhukhan, Jhuma; Lanzini, Andrea; Brandon, Nigel; Shah, Nilay

This article aims to develop a thermodynamic modelling and optimization framework for a thorough understanding of the optimal integration of fuel cell, gas turbine and other components in an ambient pressure SOFC-GT hybrid power plant. This method is based on the coupling of a syngas-fed SOFC model and an associated irreversible GT model, with an optimization algorithm developed using MATLAB to efficiently explore the range of possible operating conditions. Energy and entropy balance analysis has been carried out for the entire system to observe the irreversibility distribution within the plant and the contribution of different components. Based on the methodology developed, a comprehensive parametric analysis has been performed to explore the optimum system behavior, and predict the sensitivity of system performance to the variations in major design and operating parameters. The current density, operating temperature, fuel utilization and temperature gradient of the fuel cell, as well as the isentropic efficiencies and temperature ratio of the gas turbine cycle, together with three parameters related to the heat transfer between subsystems are all set to be controllable variables. Other factors affecting the hybrid efficiency have been further simulated and analysed. The model developed is able to predict the performance characteristics of a wide range of hybrid systems potentially sizing from 2000 to 2500 W m -2 with efficiencies varying between 50% and 60%. The analysis enables us to identify the system design tradeoffs, and therefore to determine better integration strategies for advanced SOFC-GT systems.

Web-based health services and clinical decision support.

PubMed

Jegelevicius, Darius; Marozas, Vaidotas; Lukosevicius, Arunas; Patasius, Martynas

2004-01-01

The purpose of this study was the development of a Web-based e-health service for comprehensive assistance and clinical decision support. The service structure consists of a Web server, a PHP-based Web interface linked to a clinical SQL database, Java applets for interactive manipulation and visualization of signals and a Matlab server linked with signal and data processing algorithms implemented by Matlab programs. The service ensures diagnostic signal- and image analysis-sbased clinical decision support. By using the discussed methodology, a pilot service for pathology specialists for automatic calculation of the proliferation index has been developed. Physicians use a simple Web interface for uploading the pictures under investigation to the server; subsequently a Java applet interface is used for outlining the region of interest and, after processing on the server, the requested proliferation index value is calculated. There is also an "expert corner", where experts can submit their index estimates and comments on particular images, which is especially important for system developers. These expert evaluations are used for optimization and verification of automatic analysis algorithms. Decision support trials have been conducted for ECG and ophthalmology ultrasonic investigations of intraocular tumor differentiation. Data mining algorithms have been applied and decision support trees constructed. These services are under implementation by a Web-based system too. The study has shown that the Web-based structure ensures more effective, flexible and accessible services compared with standalone programs and is very convenient for biomedical engineers and physicians, especially in the development phase.

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.…

Generation of Quality Pulses for Control of Qubit/Quantum Memory Spin States: Experimental and Simulation

DTIC Science & Technology

2016-09-01

magnetic and nuclear spins of an entangled ensemble or of single spins or photons . These quantum states can be controlled by resonant microwave...3 3.1 SIMULATION MODEL USING MATLAB /SIMULINK...4 3.1 SIMULATION MODEL USING MATLAB ®/SIMULINK Figure 7 presents the Simulink simulation example of I/Q modulation followed by a switch

Visualizing the Inner Product Space R[superscript m x n] in a MATLAB-Assisted Linear Algebra Classroom

ERIC Educational Resources Information Center

Caglayan, Günhan

2018-01-01

This linear algebra note offers teaching and learning ideas in the treatment of the inner product space R[superscript m x n] in a technology-supported learning environment. Classroom activities proposed in this note demonstrate creative ways of integrating MATLAB technology into various properties of Frobenius inner product as visualization tools…

MATLAB/Simulink Pulse-Echo Ultrasound System Simulator Based on Experimentally Validated Models.

PubMed

Kim, Taehoon; Shin, Sangmin; Lee, Hyongmin; Lee, Hyunsook; Kim, Heewon; Shin, Eunhee; Kim, Suhwan

2016-02-01

A flexible clinical ultrasound system must operate with different transducers, which have characteristic impulse responses and widely varying impedances. The impulse response determines the shape of the high-voltage pulse that is transmitted and the specifications of the front-end electronics that receive the echo; the impedance determines the specification of the matching network through which the transducer is connected. System-level optimization of these subsystems requires accurate modeling of pulse-echo (two-way) response, which in turn demands a unified simulation of the ultrasonics and electronics. In this paper, this is realized by combining MATLAB/Simulink models of the high-voltage transmitter, the transmission interface, the acoustic subsystem which includes wave propagation and reflection, the receiving interface, and the front-end receiver. To demonstrate the effectiveness of our simulator, the models are experimentally validated by comparing the simulation results with the measured data from a commercial ultrasound system. This simulator could be used to quickly provide system-level feedback for an optimized tuning of electronic design parameters.

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.

A MATLAB-based finite-element visualization of quantum reactive scattering. I. Collinear atom-diatom reactions

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

Warehime, Mick; Alexander, Millard H., E-mail: mha@umd.edu

We restate the application of the finite element method to collinear triatomic reactive scattering dynamics with a novel treatment of the scattering boundary conditions. The method provides directly the reactive scattering wave function and, subsequently, the probability current density field. Visualizing these quantities provides additional insight into the quantum dynamics of simple chemical reactions beyond simplistic one-dimensional models. Application is made here to a symmetric reaction (H+H{sub 2}), a heavy-light-light reaction (F+H{sub 2}), and a heavy-light-heavy reaction (F+HCl). To accompany this article, we have written a MATLAB code which is fast, simple enough to be accessible to a wide audience,more » as well as generally applicable to any problem that can be mapped onto a collinear atom-diatom reaction. The code and user's manual are available for download from http://www2.chem.umd.edu/groups/alexander/FEM.« less

Ensemble: a web-based system for psychology survey and experiment management.

PubMed

Tomic, Stefan T; Janata, Petr

2007-08-01

We provide a description of Ensemble, a suite of Web-integrated modules for managing and analyzing data associated with psychology experiments in a small research lab. The system delivers interfaces via a Web browser for creating and presenting simple surveys without the need to author Web pages and with little or no programming effort. The surveys may be extended by selecting and presenting auditory and/or visual stimuli with MATLAB and Flash to enable a wide range of psychophysical and cognitive experiments which do not require the recording of precise reaction times. Additionally, one is provided with the ability to administer and present experiments remotely. The software technologies employed by the various modules of Ensemble are MySQL, PHP, MATLAB, and Flash. The code for Ensemble is open source and available to the public, so that its functions can be readily extended by users. We describe the architecture of the system, the functionality of each module, and provide basic examples of the interfaces.

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

BioSigPlot: an opensource tool for the visualization of multi-channel biomedical signals with Matlab.

PubMed

Boudet, Samuel; Peyrodie, Laurent; Gallois, Philippe; de l'Aulnoit, Denis Houzé; Cao, Hua; Forzy, Gérard

2013-01-01

This paper presents a Matlab-based software (MathWorks inc.) called BioSigPlot for the visualization of multi-channel biomedical signals, particularly for the EEG. This tool is designed for researchers on both engineering and medicine who have to collaborate to visualize and analyze signals. It aims to provide a highly customizable interface for signal processing experimentation in order to plot several kinds of signals while integrating the common tools for physician. The main advantages compared to other existing programs are the multi-dataset displaying, the synchronization with video and the online processing. On top of that, this program uses object oriented programming, so that the interface can be controlled by both graphic controls and command lines. It can be used as EEGlab plug-in but, since it is not limited to EEG, it would be distributed separately. BioSigPlot is distributed free of charge (http://biosigplot.sourceforge.net), under the terms of GNU Public License for non-commercial use and open source development.

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.

Intimate partner violence against women: experiences from a woman-focused development programme in Matlab, Bangladesh.

PubMed

Ahmed, Syed Masud

2005-03-01

This paper explores the association between microcredit-based development programmes and domestic violence against women perpetrated by their husbands. A sub-set of cross-sectional data collected in 1999 from 60 BRAC-ICDDR,B study villages in Matlab, Bangladesh, was used. Data were analyzed to characterize group-level differences among study women regarding the reported occurrence of violence (physical and/or mental) and to identify its predictors. About 17.5% of women had experienced violence from their husbands in the past four months, the proportion being greater among BRAC households (p = 0.05). Results of logistic regression identified age, schooling, age of household head, and self-rated poverty status of household as important predictors of violence, but not level of BRAC membership. The study concludes that the greater level of domestic violence reported during the initial stages of BRAC membership subsided with the introduction of skill-development training among participant women over time.

Numerical simulation of water hammer in low pressurized pipe: comparison of SimHydraulics and Lax-Wendroff method with experiment

NASA Astrophysics Data System (ADS)

Himr, D.

2013-04-01

Article describes simulation of unsteady flow during water hammer with two programs, which use different numerical approaches to solve ordinary one dimensional differential equations describing the dynamics of hydraulic elements and pipes. First one is Matlab-Simulink-SimHydraulics, which is a commercial software developed to solve the dynamics of general hydraulic systems. It defines them with block elements. The other software is called HYDRA and it is based on the Lax-Wendrff numerical method, which serves as a tool to solve the momentum and continuity equations. This program was developed in Matlab by Brno University of Technology. Experimental measurements were performed on a simple test rig, which consists of an elastic pipe with strong damping connecting two reservoirs. Water hammer is induced with fast closing the valve. Physical properties of liquid and pipe elasticity parameters were considered in both simulations, which are in very good agreement and differences in comparison with experimental data are minimal.

Evaluation of interaction dynamics of concurrent processes

NASA Astrophysics Data System (ADS)

Sobecki, Piotr; Białasiewicz, Jan T.; Gross, Nicholas

2017-03-01

The purpose of this paper is to present the wavelet tools that enable the detection of temporal interactions of concurrent processes. In particular, the determination of interaction coherence of time-varying signals is achieved using a complex continuous wavelet transform. This paper has used electrocardiogram (ECG) and seismocardiogram (SCG) data set to show multiple continuous wavelet analysis techniques based on Morlet wavelet transform. MATLAB Graphical User Interface (GUI), developed in the reported research to assist in quick and simple data analysis, is presented. These software tools can discover the interaction dynamics of time-varying signals, hence they can reveal their correlation in phase and amplitude, as well as their non-linear interconnections. The user-friendly MATLAB GUI enables effective use of the developed software what enables to load two processes under investigation, make choice of the required processing parameters, and then perform the analysis. The software developed is a useful tool for researchers who have a need for investigation of interaction dynamics of concurrent processes.

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.

Mathematical model of compact type evaporator

NASA Astrophysics Data System (ADS)

Borovička, Martin; Hyhlík, Tomáš

2018-06-01

In this paper, development of the mathematical model for evaporator used in heat pump circuits is covered, with focus on air dehumidification application. Main target of this ad-hoc numerical model is to simulate heat and mass transfer in evaporator for prescribed inlet conditions and different geometrical parameters. Simplified 2D mathematical model is developed in MATLAB SW. Solvers for multiple heat and mass transfer problems - plate surface temperature, condensate film temperature, local heat and mass transfer coefficients, refrigerant temperature distribution, humid air enthalpy change are included as subprocedures of this model. An automatic procedure of data transfer is developed in order to use results of MATLAB model in more complex simulation within commercial CFD code. In the end, Proper Orthogonal Decomposition (POD) method is introduced and implemented into MATLAB model.

PMU Data Event Detection: A User Guide for Power Engineers

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

Allen, A.; Singh, M.; Muljadi, E.

2014-10-01

This user guide is intended to accompany a software package containing a Matrix Laboratory (MATLAB) script and related functions for processing phasor measurement unit (PMU) data. This package and guide have been developed by the National Renewable Energy Laboratory and the University of Texas at Austin. The objective of this data processing exercise is to discover events in the vast quantities of data collected by PMUs. This document attempts to cover some of the theory behind processing the data to isolate events as well as the functioning of the MATLAB scripts. The report describes (1) the algorithms and mathematical backgroundmore » that the accompanying MATLAB codes use to detect events in PMU data and (2) the inputs required from the user and the outputs generated by the scripts.« less

Fault Diagnosis System of Wind Turbine Generator Based on Petri Net

NASA Astrophysics Data System (ADS)

Zhang, Han

Petri net is an important tool for discrete event dynamic systems modeling and analysis. And it has great ability to handle concurrent phenomena and non-deterministic phenomena. Currently Petri nets used in wind turbine fault diagnosis have not participated in the actual system. This article will combine the existing fuzzy Petri net algorithms; build wind turbine control system simulation based on Siemens S7-1200 PLC, while making matlab gui interface for migration of the system to different platforms.

Evolved Design, Integration, and Test of a Modular, Multi-Link, Spacecraft-Based Robotic Manipulator

DTIC Science & Technology

2016-06-01

of the MATLAB code, the SPART model [24]. The portions of the SPART model relevant to this thesis are contained in (Appendices E –P). While the SPART...the kinematics and the dynamics of the system must be modeled and simulated numerically to understand how the system will behave for a given number... simulators with multiple-link robotic arms has been ongoing. B . STATE OF THE ART 1. An Overarching Context Space-based manipulators and the experimental

Extraction of CT dose information from DICOM metadata: automated Matlab-based approach.

PubMed

Dave, Jaydev K; Gingold, Eric L

2013-01-01

The purpose of this study was to extract exposure parameters and dose-relevant indexes of CT examinations from information embedded in DICOM metadata. DICOM dose report files were identified and retrieved from a PACS. An automated software program was used to extract from these files information from the structured elements in the DICOM metadata relevant to exposure. Extracting information from DICOM metadata eliminated potential errors inherent in techniques based on optical character recognition, yielding 100% accuracy.

Research on cloud background infrared radiation simulation based on fractal and statistical data

NASA Astrophysics Data System (ADS)

Liu, Xingrun; Xu, Qingshan; Li, Xia; Wu, Kaifeng; Dong, Yanbing

2018-02-01

Cloud is an important natural phenomenon, and its radiation causes serious interference to infrared detector. Based on fractal and statistical data, a method is proposed to realize cloud background simulation, and cloud infrared radiation data field is assigned using satellite radiation data of cloud. A cloud infrared radiation simulation model is established using matlab, and it can generate cloud background infrared images for different cloud types (low cloud, middle cloud, and high cloud) in different months, bands and sensor zenith angles.

Optimal Control of Micro Grid Operation Mode Seamless Switching Based on Radau Allocation Method

NASA Astrophysics Data System (ADS)

Chen, Xiaomin; Wang, Gang

2017-05-01

The seamless switching process of micro grid operation mode directly affects the safety and stability of its operation. According to the switching process from island mode to grid-connected mode of micro grid, we establish a dynamic optimization model based on two grid-connected inverters. We use Radau allocation method to discretize the model, and use Newton iteration method to obtain the optimal solution. Finally, we implement the optimization mode in MATLAB and get the optimal control trajectory of the inverters.

Analyzing gene expression time-courses based on multi-resolution shape mixture model.

PubMed

Li, Ying; He, Ye; Zhang, Yu

2016-11-01

Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.

VARS-TOOL: A Comprehensive, Efficient, and Robust Sensitivity Analysis Toolbox

NASA Astrophysics Data System (ADS)

Razavi, S.; Sheikholeslami, R.; Haghnegahdar, A.; Esfahbod, B.

2016-12-01

VARS-TOOL is an advanced sensitivity and uncertainty analysis toolbox, applicable to the full range of computer simulation models, including Earth and Environmental Systems Models (EESMs). The toolbox was developed originally around VARS (Variogram Analysis of Response Surfaces), which is a general framework for Global Sensitivity Analysis (GSA) that utilizes the variogram/covariogram concept to characterize the full spectrum of sensitivity-related information, thereby providing a comprehensive set of "global" sensitivity metrics with minimal computational cost. VARS-TOOL is unique in that, with a single sample set (set of simulation model runs), it generates simultaneously three philosophically different families of global sensitivity metrics, including (1) variogram-based metrics called IVARS (Integrated Variogram Across a Range of Scales - VARS approach), (2) variance-based total-order effects (Sobol approach), and (3) derivative-based elementary effects (Morris approach). VARS-TOOL is also enabled with two novel features; the first one being a sequential sampling algorithm, called Progressive Latin Hypercube Sampling (PLHS), which allows progressively increasing the sample size for GSA while maintaining the required sample distributional properties. The second feature is a "grouping strategy" that adaptively groups the model parameters based on their sensitivity or functioning to maximize the reliability of GSA results. These features in conjunction with bootstrapping enable the user to monitor the stability, robustness, and convergence of GSA with the increase in sample size for any given case study. VARS-TOOL has been shown to achieve robust and stable results within 1-2 orders of magnitude smaller sample sizes (fewer model runs) than alternative tools. VARS-TOOL, available in MATLAB and Python, is under continuous development and new capabilities and features are forthcoming.

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.

The Role of Socioeconomic Status in Longitudinal Trends of Cholera in Matlab, Bangladesh, 1993–2007

PubMed Central

Root, Elisabeth Dowling; Rodd, Joshua; Yunus, Mohammad; Emch, Michael

2013-01-01

There has been little evidence of a decline in the global burden of cholera in recent years as the number of cholera cases reported to WHO continues to rise. Cholera remains a global threat to public health and a key indicator of lack of socioeconomic development. Overall socioeconomic development is the ultimate solution for control of cholera as evidenced in developed countries. However, most research has focused on cross-county comparisons so that the role of individual- or small area-level socioeconomic status (SES) in cholera dynamics has not been carefully studied. Reported cases of cholera in Matlab, Bangladesh have fluctuated greatly over time and epidemic outbreaks of cholera continue, most recently with the introduction of a new serotype into the region. The wealth of longitudinal data on the population of Matlab provides a unique opportunity to explore the impact of socioeconomic status and other demographic characteristics on the long-term temporal dynamics of cholera in the region. In this population-based study we examine which factors impact the initial number of cholera cases in a bari at the beginning of the 0139 epidemic and the factors impacting the number of cases over time. Cholera data were derived from the ICDDR,B health records and linked to socioeconomic and geographic data collected as part of the Matlab Health and Demographic Surveillance System. Longitudinal zero-inflated Poisson (ZIP) multilevel regression models are used to examine the impact of environmental and socio-demographic factors on cholera counts across baris. Results indicate that baris with a high socioeconomic status had lower initial rates of cholera at the beginning of the 0139 epidemic (γ01 = −0.147, p = 0.041) and a higher probability of reporting no cholera cases (α01 = 0.156, p = 0.061). Populations in baris characterized by low SES are more likely to experience higher cholera morbidity at the beginning of an epidemic than populations in high SES baris. PMID:23326618

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

A Constant Envelope OFDM Implementation on GNU Radio

DTIC Science & Technology

2015-02-02

more advanced schemes like Decision Feedback Equalization or Turbo Equalization must be implemented to avoid the noise enhancement that all linear...block is coded in C++, and uses the phase unwrapping algorithm similar to MATLABs unwrap() function. To avoid false wraps propagating throughout the...outperform the real-time GNU radio implementation at higher SNR’s. While the unequalized experiment with the Matlab processor usually stayed within 5

Preventing Pirates from Boarding Commercial Vessels - A Systems Approach

DTIC Science & Technology

2014-09-01

was developed in MATLAB to run simulations designed to estimate the relative effectiveness of each assessed countermeasure. A cost analysis was...project indicated that the P-Trap countermeasure, designed to entangle the pirate’s propellers with thin lines, is both effective and economically viable...vessels. A model of the operational environment was developed in MATLAB to run simulations designed to estimate the relative effectiveness of each

Exploiting Non-sequence Data in Dynamic Model Learning

DTIC Science & Technology

2013-10-01

For our experiments here and in Section 3.5, we implement the proposed algorithms in MATLAB and use the maximum directed spanning tree solver...embarrassingly parallelizable, whereas PM’s maximum directed spanning tree procedure is harder to parallelize. In this experiment, our MATLAB ...some estimation problems, this approach is able to give unique and consistent estimates while the maximum- likelihood method gets entangled in

GRAFLAB 2.3 for UNIX - A MATLAB database, plotting, and analysis tool: User`s guide

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

Dunn, W.N.

1998-03-01

This report is a user`s manual for GRAFLAB, which is a new database, analysis, and plotting package that has been written entirely in the MATLAB programming language. GRAFLAB is currently used for data reduction, analysis, and archival. GRAFLAB was written to replace GRAFAID, which is a FORTRAN database, analysis, and plotting package that runs on VAX/VMS.

Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data

PubMed Central

McFarquhar, Martyn; McKie, Shane; Emsley, Richard; Suckling, John; Elliott, Rebecca; Williams, Stephen

2016-01-01

Repeated measurements and multimodal data are common in neuroimaging research. Despite this, conventional approaches to group level analysis ignore these repeated measurements in favour of multiple between-subject models using contrasts of interest. This approach has a number of drawbacks as certain designs and comparisons of interest are either not possible or complex to implement. Unfortunately, even when attempting to analyse group level data within a repeated-measures framework, the methods implemented in popular software packages make potentially unrealistic assumptions about the covariance structure across the brain. In this paper, we describe how this issue can be addressed in a simple and efficient manner using the multivariate form of the familiar general linear model (GLM), as implemented in a new MATLAB toolbox. This multivariate framework is discussed, paying particular attention to methods of inference by permutation. Comparisons with existing approaches and software packages for dependent group-level neuroimaging data are made. We also demonstrate how this method is easily adapted for dependency at the group level when multiple modalities of imaging are collected from the same individuals. Follow-up of these multimodal models using linear discriminant functions (LDA) is also discussed, with applications to future studies wishing to integrate multiple scanning techniques into investigating populations of interest. PMID:26921716

Performance Assessment and Translation of Physiologically Based Pharmacokinetic Models From acslX to Berkeley Madonna, MATLAB, and R Language: Oxytetracycline and Gold Nanoparticles As Case Examples.

PubMed

Lin, Zhoumeng; Jaberi-Douraki, Majid; He, Chunla; Jin, Shiqiang; Yang, Raymond S H; Fisher, Jeffrey W; Riviere, Jim E

2017-07-01

Many physiologically based pharmacokinetic (PBPK) models for environmental chemicals, drugs, and nanomaterials have been developed to aid risk and safety assessments using acslX. However, acslX has been rendered sunset since November 2015. Alternative modeling tools and tutorials are needed for future PBPK applications. This forum article aimed to: (1) demonstrate the performance of 4 PBPK modeling software packages (acslX, Berkeley Madonna, MATLAB, and R language) tested using 2 existing models (oxytetracycline and gold nanoparticles); (2) provide a tutorial of PBPK model code conversion from acslX to Berkeley Madonna, MATLAB, and R language; (3) discuss the advantages and disadvantages of each software package in the implementation of PBPK models in toxicology, and (4) share our perspective about future direction in this field. Simulation results of plasma/tissue concentrations/amounts of oxytetracycline and gold from different models were compared visually and statistically with linear regression analyses. Simulation results from the original models were correlated well with results from the recoded models, with time-concentration/amount curves nearly superimposable and determination coefficients of 0.86-1.00. Step-by-step explanations of the recoding of the models in different software programs are provided in the Supplementary Data. In summary, this article presents a tutorial of PBPK model code conversion for a small molecule and a nanoparticle among 4 software packages, and a performance comparison of these software packages in PBPK model implementation. This tutorial helps beginners learn PBPK modeling, provides suggestions for selecting a suitable tool for future projects, and may lead to the transition from acslX to alternative modeling tools. © The Author 2017. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Simulations of pattern dynamics for reaction-diffusion systems via SIMULINK.

PubMed

Wang, Kaier; Steyn-Ross, Moira L; Steyn-Ross, D Alistair; Wilson, Marcus T; Sleigh, Jamie W; Shiraishi, Yoichi

2014-04-11

Investigation of the nonlinear pattern dynamics of a reaction-diffusion system almost always requires numerical solution of the system's set of defining differential equations. Traditionally, this would be done by selecting an appropriate differential equation solver from a library of such solvers, then writing computer codes (in a programming language such as C or Matlab) to access the selected solver and display the integrated results as a function of space and time. This "code-based" approach is flexible and powerful, but requires a certain level of programming sophistication. A modern alternative is to use a graphical programming interface such as Simulink to construct a data-flow diagram by assembling and linking appropriate code blocks drawn from a library. The result is a visual representation of the inter-relationships between the state variables whose output can be made completely equivalent to the code-based solution. As a tutorial introduction, we first demonstrate application of the Simulink data-flow technique to the classical van der Pol nonlinear oscillator, and compare Matlab and Simulink coding approaches to solving the van der Pol ordinary differential equations. We then show how to introduce space (in one and two dimensions) by solving numerically the partial differential equations for two different reaction-diffusion systems: the well-known Brusselator chemical reactor, and a continuum model for a two-dimensional sheet of human cortex whose neurons are linked by both chemical and electrical (diffusive) synapses. We compare the relative performances of the Matlab and Simulink implementations. The pattern simulations by Simulink are in good agreement with theoretical predictions. Compared with traditional coding approaches, the Simulink block-diagram paradigm reduces the time and programming burden required to implement a solution for reaction-diffusion systems of equations. Construction of the block-diagram does not require high-level programming skills, and the graphical interface lends itself to easy modification and use by non-experts.

Advanced Digital Signal Processing for Hybrid Lidar

DTIC Science & Technology

2014-10-30

obtain range measurements . A MATLAB- based system developed at Clarkson University in FY14 has been used to perform real-time FDR ranging... measurement accuracy. There have been various methods that attempt to reduce the backscatter. One method is to increase the modulation frequency beyond...an unambiguous range measurement . In general, it is desired to determine which combination of Radio Frequency (RF) modulation frequencies, modulation

Advanced Digital Signal Processing for Hybrid Lidar

DTIC Science & Technology

2014-09-30

with a PC running LabVIEW performing the final calculations to obtain range measurements . A MATLAB- based system developed at Clarkson University in...the image contrast and resolution as well as the object ranging measurement accuracy. There have been various methods that attempt to reduce the...high speed modulation to help suppress backscatter while also providing an unambiguous range measurement . In general, it is desired to determine which

An enhanced DWBA algorithm in hybrid WDM/TDM EPON networks with heterogeneous propagation delays

NASA Astrophysics Data System (ADS)

Li, Chengjun; Guo, Wei; Jin, Yaohui; Sun, Weiqiang; Hu, Weisheng

2011-12-01

An enhanced dynamic wavelength and bandwidth allocation (DWBA) algorithm in hybrid WDM/TDM PON is proposed and experimentally demonstrated. In addition to the fairness of bandwidth allocation, this algorithm also considers the varying propagation delays between ONUs and OLT. The simulation based on MATLAB indicates that the improved algorithm has a better performance compared with some other algorithms.

Modeling of Habitat and Foraging Behavior of Beaked Whales in the Southern California Bight

DTIC Science & Technology

2014-09-30

preference. APPROACH High-Frequency Acoustic Recording Packages ( HARPs , Wiggins & Hildebrand 2007) have collected acoustic data at 17 sites...signal processing for HARP data is performed using the MATLAB (Mathworks, Natick, MA) based custom program Triton (Wiggins & Hildebrand 2007) and... HARP data are stored with the remainder of metadata (e.g. project name, instrument location, detection settings, detection effort) in the database

General Tool for Evaluating High-Contrast Coronagraphic Telescope Performance Error Budgets

NASA Technical Reports Server (NTRS)

Marchen, Luis F.

2011-01-01

The Coronagraph Performance Error Budget (CPEB) tool automates many of the key steps required to evaluate the scattered starlight contrast in the dark hole of a space-based coronagraph. The tool uses a Code V prescription of the optical train, and uses MATLAB programs to call ray-trace code that generates linear beam-walk and aberration sensitivity matrices for motions of the optical elements and line-of-sight pointing, with and without controlled fine-steering mirrors (FSMs). The sensitivity matrices are imported by macros into Excel 2007, where the error budget is evaluated. The user specifies the particular optics of interest, and chooses the quality of each optic from a predefined set of PSDs. The spreadsheet creates a nominal set of thermal and jitter motions, and combines that with the sensitivity matrices to generate an error budget for the system. CPEB also contains a combination of form and ActiveX controls with Visual Basic for Applications code to allow for user interaction in which the user can perform trade studies such as changing engineering requirements, and identifying and isolating stringent requirements. It contains summary tables and graphics that can be instantly used for reporting results in view graphs. The entire process to obtain a coronagraphic telescope performance error budget has been automated into three stages: conversion of optical prescription from Zemax or Code V to MACOS (in-house optical modeling and analysis tool), a linear models process, and an error budget tool process. The first process was improved by developing a MATLAB package based on the Class Constructor Method with a number of user-defined functions that allow the user to modify the MACOS optical prescription. The second process was modified by creating a MATLAB package that contains user-defined functions that automate the process. The user interfaces with the process by utilizing an initialization file where the user defines the parameters of the linear model computations. Other than this, the process is fully automated. The third process was developed based on the Terrestrial Planet Finder coronagraph Error Budget Tool, but was fully automated by using VBA code, form, and ActiveX controls.

Poster - 09: A MATLAB-based Program for Automated Quality Assurance of a Prostate Brachytherapy Ultrasound System

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

Poon, Justin; Sabondjian, Eric; Sankreacha, Raxa

Purpose: A robust Quality Assurance (QA) program is essential for prostate brachytherapy ultrasound systems due to the importance of imaging accuracy during treatment and planning. Task Group 128 of the American Association of Physicists in Medicine has recommended a set of QA tests covering grayscale visibility, depth of penetration, axial and lateral resolution, distance measurement, area measurement, volume measurement, and template/electronic grid alignment. Making manual measurements on the ultrasound system can be slow and inaccurate, so a MATLAB program was developed for automation of the described tests. Methods: Test images were acquired using a BK Medical Flex Focus 400 ultrasoundmore » scanner and 8848 transducer with the CIRS Brachytherapy QA Phantom – Model 045A. For each test, the program automatically segments the inputted image(s), makes the appropriate measurements, and indicates if the test passed or failed. The program was tested by analyzing two sets of images, where the measurements from the first set were used as baseline values. Results: The program successfully analyzed the images for each test and determined if any action limits were exceeded. All tests passed – the measurements made by the program were consistent and met the requirements outlined by Task Group 128. Conclusions: The MATLAB program we have developed can be used for automated QA of an ultrasound system for prostate brachytherapy. The GUI provides a user-friendly way to analyze images without the need for any manual measurement, potentially removing intra- and inter-user variability for more consistent results.« less

Widely applicable MATLAB routines for automated analysis of saccadic reaction times.

PubMed

Leppänen, Jukka M; Forssman, Linda; Kaatiala, Jussi; Yrttiaho, Santeri; Wass, Sam

2015-06-01

Saccadic reaction time (SRT) is a widely used dependent variable in eye-tracking studies of human cognition and its disorders. SRTs are also frequently measured in studies with special populations, such as infants and young children, who are limited in their ability to follow verbal instructions and remain in a stable position over time. In this article, we describe a library of MATLAB routines (Mathworks, Natick, MA) that are designed to (1) enable completely automated implementation of SRT analysis for multiple data sets and (2) cope with the unique challenges of analyzing SRTs from eye-tracking data collected from poorly cooperating participants. The library includes preprocessing and SRT analysis routines. The preprocessing routines (i.e., moving median filter and interpolation) are designed to remove technical artifacts and missing samples from raw eye-tracking data. The SRTs are detected by a simple algorithm that identifies the last point of gaze in the area of interest, but, critically, the extracted SRTs are further subjected to a number of postanalysis verification checks to exclude values contaminated by artifacts. Example analyses of data from 5- to 11-month-old infants demonstrated that SRTs extracted with the proposed routines were in high agreement with SRTs obtained manually from video records, robust against potential sources of artifact, and exhibited moderate to high test-retest stability. We propose that the present library has wide utility in standardizing and automating SRT-based cognitive testing in various populations. The MATLAB routines are open source and can be downloaded from http://www.uta.fi/med/icl/methods.html .

COMETS2: An advanced MATLAB toolbox for the numerical analysis of electric fields generated by transcranial direct current stimulation.

PubMed

Lee, Chany; Jung, Young-Jin; Lee, Sang Jun; Im, Chang-Hwan

2017-02-01

Since there is no way to measure electric current generated by transcranial direct current stimulation (tDCS) inside the human head through in vivo experiments, numerical analysis based on the finite element method has been widely used to estimate the electric field inside the head. In 2013, we released a MATLAB toolbox named COMETS, which has been used by a number of groups and has helped researchers to gain insight into the electric field distribution during stimulation. The aim of this study was to develop an advanced MATLAB toolbox, named COMETS2, for the numerical analysis of the electric field generated by tDCS. COMETS2 can generate any sizes of rectangular pad electrodes on any positions on the scalp surface. To reduce the large computational burden when repeatedly testing multiple electrode locations and sizes, a new technique to decompose the global stiffness matrix was proposed. As examples of potential applications, we observed the effects of sizes and displacements of electrodes on the results of electric field analysis. The proposed mesh decomposition method significantly enhanced the overall computational efficiency. We implemented an automatic electrode modeler for the first time, and proposed a new technique to enhance the computational efficiency. In this paper, an efficient toolbox for tDCS analysis is introduced (freely available at http://www.cometstool.com). It is expected that COMETS2 will be a useful toolbox for researchers who want to benefit from the numerical analysis of electric fields generated by tDCS. Copyright © 2016. Published by Elsevier B.V.

Simulation analysis of space remote sensing image quality degradation induced by satellite platform vibration

NASA Astrophysics Data System (ADS)

Yang, Feng; Zhang, Xiaofang; Huang, Yu; Hao, Weiwei; Guo, Baiwei

2012-11-01

Satellite platform vibration causes the image quality to be degraded, it is necessary to study its influence on image quality. The forms of Satellite platform vibration consist of linear vibration, sinusoidal vibration and random vibration. Based on Matlab & Zemax, the simulation system has been developed for simulating impact caused by satellite platform vibration on image quality. Dynamic Data Exchange is used for the communication between Matlab and Zemax. The data of sinusoidal vibration are produced by sinusoidal curve with specific amplitude and frequency. The data of random vibration are obtained by combining sinusoidal signals with 10Hz, 100Hz and 200Hz's frequency, 100, 12, 1.9's amplitude and white noise with zero mean value. Satellite platform vibration data which produced by Matlab are added to the optical system, and its point spread function can be obtained by Zemax. Blurred image can be gained by making the convolution of PSF and the original image. The definition of the original image and the blurred image are evaluated by using average gradient values of image gray. The impact caused by the sine and random vibration of six DOFs on the image quality are respectively simulated. The simulation result reveal that the decenter of X-, Y-, Z- direction and the tilt of Z-direction have a little effect on image quality, while the tilt of X-, Y- direction make image quality seriously degraded. Thus, it can be concluded that correcting the error of satellite platform vibration by FSM is a viable and effective way.

Grid Integrated Distributed PV (GridPV) Version 2.

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

Reno, Matthew J.; Coogan, Kyle

2014-12-01

This manual provides the documentation of the MATLAB toolbox of functions for using OpenDSS to simulate the impact of solar energy on the distribution system. The majority of the functio ns are useful for interfacing OpenDSS and MATLAB, and they are of generic use for commanding OpenDSS from MATLAB and retrieving information from simulations. A set of functions is also included for modeling PV plant output and setting up the PV plant in th e OpenDSS simulation. The toolbox contains functions for modeling the OpenDSS distribution feeder on satellite images with GPS coordinates. Finally, example simulations functions are included tomore » show potential uses of the toolbox functions. Each function i n the toolbox is documented with the function use syntax, full description, function input list, function output list, example use, and example output.« less

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.

VQone MATLAB toolbox: A graphical experiment builder for image and video quality evaluations: VQone MATLAB toolbox.

PubMed

Nuutinen, Mikko; Virtanen, Toni; Rummukainen, Olli; Häkkinen, Jukka

2016-03-01

This article presents VQone, a graphical experiment builder, written as a MATLAB toolbox, developed for image and video quality ratings. VQone contains the main elements needed for the subjective image and video quality rating process. This includes building and conducting experiments and data analysis. All functions can be controlled through graphical user interfaces. The experiment builder includes many standardized image and video quality rating methods. Moreover, it enables the creation of new methods or modified versions from standard methods. VQone is distributed free of charge under the terms of the GNU general public license and allows code modifications to be made so that the program's functions can be adjusted according to a user's requirements. VQone is available for download from the project page (http://www.helsinki.fi/psychology/groups/visualcognition/).

Gro2mat: a package to efficiently read gromacs output in MATLAB.

PubMed

Dien, Hung; Deane, Charlotte M; Knapp, Bernhard

2014-07-30

Molecular dynamics (MD) simulations are a state-of-the-art computational method used to investigate molecular interactions at atomic scale. Interaction processes out of experimental reach can be monitored using MD software, such as Gromacs. Here, we present the gro2mat package that allows fast and easy access to Gromacs output files from Matlab. Gro2mat enables direct parsing of the most common Gromacs output formats including the binary xtc-format. No openly available Matlab parser currently exists for this format. The xtc reader is orders of magnitudes faster than other available pdb/ascii workarounds. Gro2mat is especially useful for scientists with an interest in quick prototyping of new mathematical and statistical approaches for Gromacs trajectory analyses. © 2014 Wiley Periodicals, Inc. Copyright © 2014 Wiley Periodicals, Inc.

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

Deterministic Intracellular Modeling

DTIC Science & Technology

2003-03-01

eukaryotes encompass all plants, animal, fungi and protists [6:71]. Structures in this class are more defined. For example, cells in this class possess a...affect cells. 5.3 Recommendations Further research into the construction and evaluation of intracellular models would benefit Air Force toxicology studies...manual220/indexE.html. 16. MathWorks, “The Benefits of MATLAB.” Internet, 2003. http://www.mathworks.com/products/matlab/description1.jsp. 17. Mendes

Matlab as a robust control design tool

NASA Technical Reports Server (NTRS)

Gregory, Irene M.

1994-01-01

This presentation introduces Matlab as a tool used in flight control research. The example used to illustrate some of the capabilities of this software is a robust controller designed for a single stage to orbit air breathing vehicles's ascent to orbit. The global requirements of the controller are to stabilize the vehicle and follow a trajectory in the presence of atmospheric disturbances and strong dynamic coupling between airframe and propulsion.

MSiReader: an open-source interface to view and analyze high resolving power MS imaging files on Matlab platform.

PubMed

Robichaud, Guillaume; Garrard, Kenneth P; Barry, Jeremy A; Muddiman, David C

2013-05-01

During the past decade, the field of mass spectrometry imaging (MSI) has greatly evolved, to a point where it has now been fully integrated by most vendors as an optional or dedicated platform that can be purchased with their instruments. However, the technology is not mature and multiple research groups in both academia and industry are still very actively studying the fundamentals of imaging techniques, adapting the technology to new ionization sources, and developing new applications. As a result, there important varieties of data file formats used to store mass spectrometry imaging data and, concurrent to the development of MSi, collaborative efforts have been undertaken to introduce common imaging data file formats. However, few free software packages to read and analyze files of these different formats are readily available. We introduce here MSiReader, a free open source application to read and analyze high resolution MSI data from the most common MSi data formats. The application is built on the Matlab platform (Mathworks, Natick, MA, USA) and includes a large selection of data analysis tools and features. People who are unfamiliar with the Matlab language will have little difficult navigating the user-friendly interface, and users with Matlab programming experience can adapt and customize MSiReader for their own needs.

MSiReader: An Open-Source Interface to View and Analyze High Resolving Power MS Imaging Files on Matlab Platform

NASA Astrophysics Data System (ADS)

Robichaud, Guillaume; Garrard, Kenneth P.; Barry, Jeremy A.; Muddiman, David C.

2013-05-01

During the past decade, the field of mass spectrometry imaging (MSI) has greatly evolved, to a point where it has now been fully integrated by most vendors as an optional or dedicated platform that can be purchased with their instruments. However, the technology is not mature and multiple research groups in both academia and industry are still very actively studying the fundamentals of imaging techniques, adapting the technology to new ionization sources, and developing new applications. As a result, there important varieties of data file formats used to store mass spectrometry imaging data and, concurrent to the development of MSi, collaborative efforts have been undertaken to introduce common imaging data file formats. However, few free software packages to read and analyze files of these different formats are readily available. We introduce here MSiReader, a free open source application to read and analyze high resolution MSI data from the most common MSi data formats. The application is built on the Matlab platform (Mathworks, Natick, MA, USA) and includes a large selection of data analysis tools and features. People who are unfamiliar with the Matlab language will have little difficult navigating the user-friendly interface, and users with Matlab programming experience can adapt and customize MSiReader for their own needs.

NLSEmagic: Nonlinear Schrödinger equation multi-dimensional Matlab-based GPU-accelerated integrators using compact high-order schemes

NASA Astrophysics Data System (ADS)

Caplan, R. M.

2013-04-01

We present a simple to use, yet powerful code package called NLSEmagic to numerically integrate the nonlinear Schrödinger equation in one, two, and three dimensions. NLSEmagic is a high-order finite-difference code package which utilizes graphic processing unit (GPU) parallel architectures. The codes running on the GPU are many times faster than their serial counterparts, and are much cheaper to run than on standard parallel clusters. The codes are developed with usability and portability in mind, and therefore are written to interface with MATLAB utilizing custom GPU-enabled C codes with the MEX-compiler interface. The packages are freely distributed, including user manuals and set-up files. Catalogue identifier: AEOJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEOJ_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.: 124453 No. of bytes in distributed program, including test data, etc.: 4728604 Distribution format: tar.gz Programming language: C, CUDA, MATLAB. Computer: PC, MAC. Operating system: Windows, MacOS, Linux. Has the code been vectorized or parallelized?: Yes. Number of processors used: Single CPU, number of GPU processors dependent on chosen GPU card (max is currently 3072 cores on GeForce GTX 690). Supplementary material: Setup guide, Installation guide. RAM: Highly dependent on dimensionality and grid size. For typical medium-large problem size in three dimensions, 4GB is sufficient. Keywords: Nonlinear Schröodinger Equation, GPU, high-order finite difference, Bose-Einstien condensates. Classification: 4.3, 7.7. Nature of problem: Integrate solutions of the time-dependent one-, two-, and three-dimensional cubic nonlinear Schrödinger equation. Solution method: The integrators utilize a fully-explicit fourth-order Runge-Kutta scheme in time and both second- and fourth-order differencing in space. The integrators are written to run on NVIDIA GPUs and are interfaced with MATLAB including built-in visualization and analysis tools. Restrictions: The main restriction for the GPU integrators is the amount of RAM on the GPU as the code is currently only designed for running on a single GPU. Unusual features: Ability to visualize real-time simulations through the interaction of MATLAB and the compiled GPU integrators. Additional comments: Setup guide and Installation guide provided. Program has a dedicated web site at www.nlsemagic.com. Running time: A three-dimensional run with a grid dimension of 87×87×203 for 3360 time steps (100 non-dimensional time units) takes about one and a half minutes on a GeForce GTX 580 GPU card.

Study on the variable cycle engine modeling techniques based on the component method

NASA Astrophysics Data System (ADS)

Zhang, Lihua; Xue, Hui; Bao, Yuhai; Li, Jijun; Yan, Lan

2016-01-01

Based on the structure platform of the gas turbine engine, the components of variable cycle engine were simulated by using the component method. The mathematical model of nonlinear equations correspondeing to each component of the gas turbine engine was established. Based on Matlab programming, the nonlinear equations were solved by using Newton-Raphson steady-state algorithm, and the performance of the components for engine was calculated. The numerical simulation results showed that the model bulit can describe the basic performance of the gas turbine engine, which verified the validity of the model.

Advanced Digital Signal Processing for Hybrid Lidar FY 2014

DTIC Science & Technology

2014-10-30

processing steps on raw data, with a PC miming Lab VIEW performing the fmal calculations to obtain range measurements . A MATLAB- based system...regarding the object and it reduces the image contrast and resolution as well as the object ranging measurement accuracy. There have been various...frequency (>100MHz) approach that uses high speed modulation to help suppress backscatter while also providing an unambiguous range measurement . In general

PI and repetitive control for single phase inverter based on virtual rotating coordinate system

NASA Astrophysics Data System (ADS)

Li, Mengqi; Tong, Yibin; Jiang, Jiuchun; Liang, Jiangang

2018-03-01

Microgrid technology developed rapidly and nonlinear loads were connected increasingly. A new control strategy was proposed for single phase inverter when connected nonlinear loads under island condition. PI and repetitive compound controller was realized under synchronous rotating coordinate system and acquired high quality sinusoidal voltage output without voltage spike when loads step changed. Validity and correctness were verified by simulation using MATLAB/Simulink.

An Empirical Model-based MOE for Friction Reduction by Slot-Ejected Polymer Solutions in an Aqueous Environment

DTIC Science & Technology

2007-12-21

of hydrodynamics and the physical characteristics of the polymers. The physics models include both analytical models and numerical simulations ...the experimental observations. The numerical simulations also succeed in replicating some experimental measurements. However, there is still no...become quite significant. 4.5 Documentation The complete model is coded in MatLab . In the model, all units are cgs, so distances are in

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

DTIC Science & Technology

2010-12-24

The modeling tools are based on interaction between three commercial software packages: SolidWorks, COMSOL Multiphysics, and ZEMAX optical design...deformation resulting from the applied voltages. Finally, the deformed surface can be exported to ZEMAX via MatLab. From ZEMAX , various analyses can...results to extract from ZEMAX to support the optimization remains to be determined. Figure 1 shows the deformation calculated using a model of an

Numerical estimation of the relative entropy of entanglement

NASA Astrophysics Data System (ADS)

Zinchenko, Yuriy; Friedland, Shmuel; Gour, Gilad

2010-11-01

We propose a practical algorithm for the calculation of the relative entropy of entanglement (REE), defined as the minimum relative entropy between a state and the set of states with positive partial transpose. Our algorithm is based on a practical semidefinite cutting plane approach. In low dimensions the implementation of the algorithm in matlab provides an estimation for the REE with an absolute error smaller than 10-3.

Educational Software for Interference and Optical Diffraction Analysis in Fresnel and Fraunhofer Regions Based on MATLAB GUIs and the FDTD Method

ERIC Educational Resources Information Center

Frances, J.; Perez-Molina, M.; Bleda, S.; Fernandez, E.; Neipp, C.; Belendez, A.

2012-01-01

Interference and diffraction of light are elementary topics in optics. The aim of the work presented here is to develop an accurate and cheap optical-system simulation software that provides a virtual laboratory for studying the effects of propagation in both time and space for the near- and far-field regions. In laboratory sessions, this software…

Characterization of a Hyperspectral Chromotomographic Imaging Ground System

DTIC Science & Technology

2012-03-22

developed by the Air Force Institute of Technology (AFIT). The optical model is constructed using Zemax and MATLAB. The model provides the mechanism required...can also be used to incorporate interferometric measurements of optical components and model them in Zemax. The model uses a Zernike Phase Surface to...THE AIR FORCE AIR UNIVERSITY AIR FORCE INSTITUTE OF TECHNOLOGY Wright-Patterson Air Force Base, Ohio DISTRIBUTION STATEMENT A APPROVED FOR PUBLIC

TTLEM: Open access tool for building numerically accurate landscape evolution models in MATLAB

NASA Astrophysics Data System (ADS)

Campforts, Benjamin; Schwanghart, Wolfgang; Govers, Gerard

2017-04-01

Despite a growing interest in LEMs, accuracy assessment of the numerical methods they are based on has received little attention. Here, we present TTLEM which is an open access landscape evolution package designed to develop and test your own scenarios and hypothesises. TTLEM uses a higher order flux-limiting finite-volume method to simulate river incision and tectonic displacement. We show that this scheme significantly influences the evolution of simulated landscapes and the spatial and temporal variability of erosion rates. Moreover, it allows the simulation of lateral tectonic displacement on a fixed grid. Through the use of a simple GUI the software produces visible output of evolving landscapes through model run time. In this contribution, we illustrate numerical landscape evolution through a set of movies spanning different spatial and temporal scales. We focus on the erosional domain and use both spatially constant and variable input values for uplift, lateral tectonic shortening, erodibility and precipitation. Moreover, we illustrate the relevance of a stochastic approach for realistic hillslope response modelling. TTLEM is a fully open source software package, written in MATLAB and based on the TopoToolbox platform (topotoolbox.wordpress.com). Installation instructions can be found on this website and the therefore designed GitHub repository.

A High-Fidelity Simulation of a Generic Commercial Aircraft Engine and Controller

NASA Technical Reports Server (NTRS)

May, Ryan D.; Csank, Jeffrey; Lavelle, Thomas M.; Litt, Jonathan S.; Guo, Ten-Huei

2010-01-01

A new high-fidelity simulation of a generic 40,000 lb thrust class commercial turbofan engine with a representative controller, known as CMAPSS40k, has been developed. Based on dynamic flight test data of a highly instrumented engine and previous engine simulations developed at NASA Glenn Research Center, this non-proprietary simulation was created especially for use in the development of new engine control strategies. C-MAPSS40k is a highly detailed, component-level engine model written in MATLAB/Simulink (The MathWorks, Inc.). Because the model is built in Simulink, users have the ability to use any of the MATLAB tools for analysis and control system design. The engine components are modeled in C-code, which is then compiled to allow faster-than-real-time execution. The engine controller is based on common industry architecture and techniques to produce realistic closed-loop transient responses while ensuring that no safety or operability limits are violated. A significant feature not found in other non-proprietary models is the inclusion of transient stall margin debits. These debits provide an accurate accounting of the compressor surge margin, which is critical in the design of an engine controller. This paper discusses the development, characteristics, and capabilities of the C-MAPSS40k simulation

The pointillism method for creating stimuli suitable for use in computer-based visual contrast sensitivity testing.

PubMed

Turner, Travis H

2005-03-30

An increasingly large corpus of clinical and experimental neuropsychological research has demonstrated the utility of measuring visual contrast sensitivity. Unfortunately, existing means of measuring contrast sensitivity can be prohibitively expensive, difficult to standardize, or lack reliability. Additionally, most existing tests do not allow full control over important characteristics, such as off-angle rotations, waveform, contrast, and spatial frequency. Ideally, researchers could manipulate characteristics and display stimuli in a computerized task designed to meet experimental needs. Thus far, 256-bit color limitation in standard cathode ray tube (CRT) monitors has been preclusive. To this end, the pointillism method (PM) was developed. Using MATLAB software, stimuli are created based on both mathematical and stochastic components, such that differences in regional luminance values of the gradient field closely approximate the desired contrast. This paper describes the method and examines its performance in sine and square-wave image sets from a range of contrast values. Results suggest the utility of the method for most experimental applications. Weaknesses in the current version, the need for validation and reliability studies, and considerations regarding applications are discussed. Syntax for the program is provided in an appendix, and a version of the program independent of MATLAB is available from the author.

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.

iMatTOUGH: An open-source Matlab-based graphical user interface for pre- and post-processing of TOUGH2 and iTOUGH2 models

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

Tran, Anh Phuong; Dafflon, Baptiste; Hubbard, Susan

TOUGH2 and iTOUGH2 are powerful models that simulate the heat and fluid flows in porous and fracture media, and perform parameter estimation, sensitivity analysis and uncertainty propagation analysis. However, setting up the input files is not only tedious, but error prone, and processing output files is time consuming. Here, we present an open source Matlab-based tool (iMatTOUGH) that supports the generation of all necessary inputs for both TOUGH2 and iTOUGH2 and visualize their outputs. The tool links the inputs of TOUGH2 and iTOUGH2, making sure the two input files are consistent. It supports the generation of rectangular computational mesh, i.e.,more » it automatically generates the elements and connections as well as their properties as required by TOUGH2. The tool also allows the specification of initial and time-dependent boundary conditions for better subsurface heat and water flow simulations. The effectiveness of the tool is illustrated by an example that uses TOUGH2 and iTOUGH2 to estimate soil hydrological and thermal properties from soil temperature data and simulate the heat and water flows at the Rifle site in Colorado.« less

A Matlab toolkit for three-dimensional electrical impedance tomography: a contribution to the Electrical Impedance and Diffuse Optical Reconstruction Software project

NASA Astrophysics Data System (ADS)

Polydorides, Nick; Lionheart, William R. B.

2002-12-01

The objective of the Electrical Impedance and Diffuse Optical Reconstruction Software project is to develop freely available software that can be used to reconstruct electrical or optical material properties from boundary measurements. Nonlinear and ill posed problems such as electrical impedance and optical tomography are typically approached using a finite element model for the forward calculations and a regularized nonlinear solver for obtaining a unique and stable inverse solution. Most of the commercially available finite element programs are unsuitable for solving these problems because of their conventional inefficient way of calculating the Jacobian, and their lack of accurate electrode modelling. A complete package for the two-dimensional EIT problem was officially released by Vauhkonen et al at the second half of 2000. However most industrial and medical electrical imaging problems are fundamentally three-dimensional. To assist the development we have developed and released a free toolkit of Matlab routines which can be employed to solve the forward and inverse EIT problems in three dimensions based on the complete electrode model along with some basic visualization utilities, in the hope that it will stimulate further development. We also include a derivation of the formula for the Jacobian (or sensitivity) matrix based on the complete electrode model.

iMatTOUGH: An open-source Matlab-based graphical user interface for pre- and post-processing of TOUGH2 and iTOUGH2 models

DOE PAGES

Tran, Anh Phuong; Dafflon, Baptiste; Hubbard, Susan

2016-04-01

TOUGH2 and iTOUGH2 are powerful models that simulate the heat and fluid flows in porous and fracture media, and perform parameter estimation, sensitivity analysis and uncertainty propagation analysis. However, setting up the input files is not only tedious, but error prone, and processing output files is time consuming. Here, we present an open source Matlab-based tool (iMatTOUGH) that supports the generation of all necessary inputs for both TOUGH2 and iTOUGH2 and visualize their outputs. The tool links the inputs of TOUGH2 and iTOUGH2, making sure the two input files are consistent. It supports the generation of rectangular computational mesh, i.e.,more » it automatically generates the elements and connections as well as their properties as required by TOUGH2. The tool also allows the specification of initial and time-dependent boundary conditions for better subsurface heat and water flow simulations. The effectiveness of the tool is illustrated by an example that uses TOUGH2 and iTOUGH2 to estimate soil hydrological and thermal properties from soil temperature data and simulate the heat and water flows at the Rifle site in Colorado.« less

Performance Improvements to the Naval Postgraduate School Turbopropulsion Labs Transonic Axially Splittered Rotor

DTIC Science & Technology

2013-12-01

Implementation of current NPS TPL design procedure that uses COTS software (MATLAB, SolidWorks, and ANSYS - CFX ) for the geometric rendering and...procedure that uses commercial-off-the-shelf software (MATLAB, SolidWorks, and ANSYS - CFX ) for the geometric rendering and analysis was modified and... CFX The CFD simulation program in ANSYS Workbench. CFX -Pre CFX boundary conditions and solver settings module. CFX -Solver CFX solver program. CFX

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