Advanced entry guidance algorithm with landing footprint computation
Leavitt, James Aaron
The design and performance evaluation of an entry guidance algorithm for future space transportation vehicles is presented. The algorithm performs two functions: on-board trajectory planning and trajectory tracking. The planned longitudinal path is followed by tracking drag acceleration, as is done by the Space Shuttle entry guidance. Unlike the Shuttle entry guidance, lateral path curvature is also planned and followed. A new trajectory planning function for the guidance algorithm is developed that is suitable for suborbital entry and that significantly enhances the overall performance of the algorithm for both orbital and suborbital entry. In comparison with the previous trajectory planner, the new planner produces trajectories that are easier to track, especially near the upper and lower drag boundaries and for suborbital entry. The new planner accomplishes this by matching the vehicle's initial flight path angle and bank angle, and by enforcing the full three-degree-of-freedom equations of motion with control derivative limits. Insights gained from trajectory optimization results contribute to the design of the new planner, giving it near-optimal downrange and crossrange capabilities. Planned trajectories and guidance simulation results are presented that demonstrate the improved performance. Based on the new planner, a method is developed for approximating the landing footprint for entry vehicles in near real-time, as would be needed for an on-board flight management system. The boundary of the footprint is constructed from the endpoints of extreme downrange and crossrange trajectories generated by the new trajectory planner. The footprint algorithm inherently possesses many of the qualities of the new planner, including quick execution, the ability to accurately approximate the vehicle's glide capabilities, and applicability to a wide range of entry conditions. Footprints can be generated for orbital and suborbital entry conditions using a pre
Advanced computer algebra algorithms for the expansion of Feynman integrals
International Nuclear Information System (INIS)
Ablinger, Jakob; Round, Mark; Schneider, Carsten
2012-10-01
Two-point Feynman parameter integrals, with at most one mass and containing local operator insertions in 4+ε-dimensional Minkowski space, can be transformed to multi-integrals or multi-sums over hyperexponential and/or hypergeometric functions depending on a discrete parameter n. Given such a specific representation, we utilize an enhanced version of the multivariate Almkvist-Zeilberger algorithm (for multi-integrals) and a common summation framework of the holonomic and difference field approach (for multi-sums) to calculate recurrence relations in n. Finally, solving the recurrence we can decide efficiently if the first coefficients of the Laurent series expansion of a given Feynman integral can be expressed in terms of indefinite nested sums and products; if yes, the all n solution is returned in compact representations, i.e., no algebraic relations exist among the occurring sums and products.
Advanced computer algebra algorithms for the expansion of Feynman integrals
Energy Technology Data Exchange (ETDEWEB)
Ablinger, Jakob; Round, Mark; Schneider, Carsten [Johannes Kepler Univ., Linz (Austria). Research Inst. for Symbolic Computation; Bluemlein, Johannes [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany)
2012-10-15
Two-point Feynman parameter integrals, with at most one mass and containing local operator insertions in 4+{epsilon}-dimensional Minkowski space, can be transformed to multi-integrals or multi-sums over hyperexponential and/or hypergeometric functions depending on a discrete parameter n. Given such a specific representation, we utilize an enhanced version of the multivariate Almkvist-Zeilberger algorithm (for multi-integrals) and a common summation framework of the holonomic and difference field approach (for multi-sums) to calculate recurrence relations in n. Finally, solving the recurrence we can decide efficiently if the first coefficients of the Laurent series expansion of a given Feynman integral can be expressed in terms of indefinite nested sums and products; if yes, the all n solution is returned in compact representations, i.e., no algebraic relations exist among the occurring sums and products.
Integrated Graphics Operations and Analysis Lab Development of Advanced Computer Graphics Algorithms
Wheaton, Ira M.
2011-01-01
The focus of this project is to aid the IGOAL in researching and implementing algorithms for advanced computer graphics. First, this project focused on porting the current International Space Station (ISS) Xbox experience to the web. Previously, the ISS interior fly-around education and outreach experience only ran on an Xbox 360. One of the desires was to take this experience and make it into something that can be put on NASA s educational site for anyone to be able to access. The current code works in the Unity game engine which does have cross platform capability but is not 100% compatible. The tasks for an intern to complete this portion consisted of gaining familiarity with Unity and the current ISS Xbox code, porting the Xbox code to the web as is, and modifying the code to work well as a web application. In addition, a procedurally generated cloud algorithm will be developed. Currently, the clouds used in AGEA animations and the Xbox experiences are a texture map. The desire is to create a procedurally generated cloud algorithm to provide dynamically generated clouds for both AGEA animations and the Xbox experiences. This task consists of gaining familiarity with AGEA and the plug-in interface, developing the algorithm, creating an AGEA plug-in to implement the algorithm inside AGEA, and creating a Unity script to implement the algorithm for the Xbox. This portion of the project was unable to be completed in the time frame of the internship; however, the IGOAL will continue to work on it in the future.
Directory of Open Access Journals (Sweden)
Peigang Ning
Full Text Available OBJECTIVE: This work aims to explore the effects of adaptive statistical iterative reconstruction (ASiR and model-based iterative reconstruction (MBIR algorithms in reducing computed tomography (CT radiation dosages in abdominal imaging. METHODS: CT scans on a standard male phantom were performed at different tube currents. Images at the different tube currents were reconstructed with the filtered back-projection (FBP, 50% ASiR and MBIR algorithms and compared. The CT value, image noise and contrast-to-noise ratios (CNRs of the reconstructed abdominal images were measured. Volumetric CT dose indexes (CTDIvol were recorded. RESULTS: At different tube currents, 50% ASiR and MBIR significantly reduced image noise and increased the CNR when compared with FBP. The minimal tube current values required by FBP, 50% ASiR, and MBIR to achieve acceptable image quality using this phantom were 200, 140, and 80 mA, respectively. At the identical image quality, 50% ASiR and MBIR reduced the radiation dose by 35.9% and 59.9% respectively when compared with FBP. CONCLUSIONS: Advanced iterative reconstruction techniques are able to reduce image noise and increase image CNRs. Compared with FBP, 50% ASiR and MBIR reduced radiation doses by 35.9% and 59.9%, respectively.
An advanced computational algorithm for systems analysis of tokamak power plants
International Nuclear Information System (INIS)
Dragojlovic, Zoran; Rene Raffray, A.; Najmabadi, Farrokh; Kessel, Charles; Waganer, Lester; El-Guebaly, Laila; Bromberg, Leslie
2010-01-01
A new computational algorithm for tokamak power plant system analysis is being developed for the ARIES project. The objective of this algorithm is to explore the most influential parameters in the physical, technological and economic trade space related to the developmental transition from experimental facilities to viable commercial power plants. This endeavor is being pursued as a new approach to tokamak systems studies, which examines an expansive, multi-dimensional trade space as opposed to traditional sensitivity analyses about a baseline design point. The new ARIES systems code consists of adaptable modules which are built from a custom-made software toolbox using object-oriented programming. The physics module captures the current tokamak physics knowledge database including modeling of the most-current proposed burning plasma experiment design (FIRE). The engineering model accurately reflects the intent and design detail of the power core elements including accurate and adjustable 3D tokamak geometry and complete modeling of all the power core and ancillary systems. Existing physics and engineering models reflect both near-term as well as advanced technology solutions that have higher performance potential. To fully assess the impact of the range of physics and engineering implementations, the plant cost accounts have been revised to reflect a more functional cost structure, supported by an updated set of costing algorithms for the direct, indirect, and financial cost accounts. All of these features have been validated against the existing ARIES-AT baseline case. The present results demonstrate visualization techniques that provide an insight into trade space assessment of attractive steady-state tokamaks for commercial use.
Algorithmically specialized parallel computers
Snyder, Lawrence; Gannon, Dennis B
1985-01-01
Algorithmically Specialized Parallel Computers focuses on the concept and characteristics of an algorithmically specialized computer.This book discusses the algorithmically specialized computers, algorithmic specialization using VLSI, and innovative architectures. The architectures and algorithms for digital signal, speech, and image processing and specialized architectures for numerical computations are also elaborated. Other topics include the model for analyzing generalized inter-processor, pipelined architecture for search tree maintenance, and specialized computer organization for raster
Carroll, Chester C.; Youngblood, John N.; Saha, Aindam
1987-01-01
Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processing elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed.
Parallel algorithms and cluster computing
Hoffmann, Karl Heinz
2007-01-01
This book presents major advances in high performance computing as well as major advances due to high performance computing. It contains a collection of papers in which results achieved in the collaboration of scientists from computer science, mathematics, physics, and mechanical engineering are presented. From the science problems to the mathematical algorithms and on to the effective implementation of these algorithms on massively parallel and cluster computers we present state-of-the-art methods and technology as well as exemplary results in these fields. This book shows that problems which seem superficially distinct become intimately connected on a computational level.
Diagnosis of autism through EEG processed by advanced computational algorithms: A pilot study.
Grossi, Enzo; Olivieri, Chiara; Buscema, Massimo
2017-04-01
Multi-Scale Ranked Organizing Map coupled with Implicit Function as Squashing Time algorithm(MS-ROM/I-FAST) is a new, complex system based on Artificial Neural networks (ANNs) able to extract features of interest in computerized EEG through the analysis of few minutes of their EEG without any preliminary pre-processing. A proof of concept study previously published showed accuracy values ranging from 94%-98% in discerning subjects with Mild Cognitive Impairment and/or Alzheimer's Disease from healthy elderly people. The presence of deviant patterns in simple resting state EEG recordings in autism, consistent with the atypical organization of the cerebral cortex present, prompted us in applying this potent analytical systems in search of a EEG signature of the disease. The aim of the study is to assess how effectively this methodology distinguishes subjects with autism from typically developing ones. Fifteen definite ASD subjects (13 males; 2 females; age range 7-14; mean value = 10.4) and ten typically developing subjects (4 males; 6 females; age range 7-12; mean value 9.2) were included in the study. Patients received Autism diagnoses according to DSM-V criteria, subsequently confirmed by the ADOS scale. A segment of artefact-free EEG lasting 60 seconds was used to compute input values for subsequent analyses. MS-ROM/I-FAST coupled with a well-documented evolutionary system able to select predictive features (TWIST) created an invariant features vector input of EEG on which supervised machine learning systems acted as blind classifiers. The overall predictive capability of machine learning system in sorting out autistic cases from normal control amounted consistently to 100% with all kind of systems employed using training-testing protocol and to 84% - 92.8% using Leave One Out protocol. The similarities among the ANN weight matrixes measured with apposite algorithms were not affected by the age of the subjects. This suggests that the ANNs do not read age
Algorithms for parallel computers
International Nuclear Information System (INIS)
Churchhouse, R.F.
1985-01-01
Until relatively recently almost all the algorithms for use on computers had been designed on the (usually unstated) assumption that they were to be run on single processor, serial machines. With the introduction of vector processors, array processors and interconnected systems of mainframes, minis and micros, however, various forms of parallelism have become available. The advantage of parallelism is that it offers increased overall processing speed but it also raises some fundamental questions, including: (i) which, if any, of the existing 'serial' algorithms can be adapted for use in the parallel mode. (ii) How close to optimal can such adapted algorithms be and, where relevant, what are the convergence criteria. (iii) How can we design new algorithms specifically for parallel systems. (iv) For multi-processor systems how can we handle the software aspects of the interprocessor communications. Aspects of these questions illustrated by examples are considered in these lectures. (orig.)
Pisano, Aurora; Weichert, Dieter
2015-01-01
Articles in this book examine various materials and how to determine directly the limit state of a structure, in the sense of limit analysis and shakedown analysis. Apart from classical applications in mechanical and civil engineering contexts, the book reports on the emerging field of material design beyond the elastic limit, which has further industrial design and technological applications. Readers will discover that “Direct Methods” and the techniques presented here can in fact be used to numerically estimate the strength of structured materials such as composites or nano-materials, which represent fruitful fields of future applications. Leading researchers outline the latest computational tools and optimization techniques and explore the possibility of obtaining information on the limit state of a structure whose post-elastic loading path and constitutive behavior are not well defined or well known. Readers will discover how Direct Methods allow rapid and direct access to requested information in...
Advanced computers and simulation
International Nuclear Information System (INIS)
Ryne, R.D.
1993-01-01
Accelerator physicists today have access to computers that are far more powerful than those available just 10 years ago. In the early 1980's, desktop workstations performed less one million floating point operations per second (Mflops), and the realized performance of vector supercomputers was at best a few hundred Mflops. Today vector processing is available on the desktop, providing researchers with performance approaching 100 Mflops at a price that is measured in thousands of dollars. Furthermore, advances in Massively Parallel Processors (MPP) have made performance of over 10 gigaflops a reality, and around mid-decade MPPs are expected to be capable of teraflops performance. Along with advances in MPP hardware, researchers have also made significant progress in developing algorithms and software for MPPS. These changes have had, and will continue to have, a significant impact on the work of computational accelerator physicists. Now, instead of running particle simulations with just a few thousand particles, we can perform desktop simulations with tens of thousands of simulation particles, and calculations with well over 1 million particles are being performed on MPPs. In the area of computational electromagnetics, simulations that used to be performed only on vector supercomputers now run in several hours on desktop workstations, and researchers are hoping to perform simulations with over one billion mesh points on future MPPs. In this paper we will discuss the latest advances, and what can be expected in the near future, in hardware, software and applications codes for advanced simulation of particle accelerators
Nour, Abdoulshakour M.
Oil and gas exploration professionals have long recognized the importance of predicting pore pressure before drilling wells. Pre-drill pore pressure estimation not only helps with drilling wells safely but also aids in the determination of formation fluids migration and seal integrity. With respect to the hydrocarbon reservoirs, the appropriate drilling mud weight is directly related to the estimated pore pressure in the formation. If the mud weight is lower than the formation pressure, a blowout may occur, and conversely, if it is higher than the formation pressure, the formation may suffer irreparable damage due to the invasion of drilling fluids into the formation. A simple definition of pore pressure is the pressure of the pore fluids in excess of the hydrostatic pressure. In this thesis, I investigated the utility of advance computer algorithm called Support Vector Machine (SVM) to learn the pattern of high pore pressure regime, using seismic attributes such as Instantaneous phase, t*Attenuation, Cosine of Phase, Vp/Vs ratio, P-Impedance, Reflection Acoustic Impedance, Dominant frequency and one well attribute (Mud-Weigh) as the learning dataset. I applied this technique to the over pressured Qalibah formation of Northwest Saudi Arabia. The results of my research revealed that in the Qalibah formation of Northwest Saudi Arabia, the pore pressure trend can be predicted using SVM with seismic and well attributes as the learning dataset. I was able to show the pore pressure trend at any given point within the geographical extent of the 3D seismic data from which the seismic attributes were derived. In addition, my results surprisingly showed the subtle variation of pressure within the thick succession of shale units of the Qalibah formation.
Quantum Computation and Algorithms
International Nuclear Information System (INIS)
Biham, O.; Biron, D.; Biham, E.; Grassi, M.; Lidar, D.A.
1999-01-01
It is now firmly established that quantum algorithms provide a substantial speedup over classical algorithms for a variety of problems, including the factorization of large numbers and the search for a marked element in an unsorted database. In this talk I will review the principles of quantum algorithms, the basic quantum gates and their operation. The combination of superposition and interference, that makes these algorithms efficient, will be discussed. In particular, Grover's search algorithm will be presented as an example. I will show that the time evolution of the amplitudes in Grover's algorithm can be found exactly using recursion equations, for any initial amplitude distribution
Algorithms for image processing and computer vision
Parker, J R
2010-01-01
A cookbook of algorithms for common image processing applications Thanks to advances in computer hardware and software, algorithms have been developed that support sophisticated image processing without requiring an extensive background in mathematics. This bestselling book has been fully updated with the newest of these, including 2D vision methods in content-based searches and the use of graphics cards as image processing computational aids. It's an ideal reference for software engineers and developers, advanced programmers, graphics programmers, scientists, and other specialists wh
Advances in unconventional computing
2017-01-01
The unconventional computing is a niche for interdisciplinary science, cross-bred of computer science, physics, mathematics, chemistry, electronic engineering, biology, material science and nanotechnology. The aims of this book are to uncover and exploit principles and mechanisms of information processing in and functional properties of physical, chemical and living systems to develop efficient algorithms, design optimal architectures and manufacture working prototypes of future and emergent computing devices. This first volume presents theoretical foundations of the future and emergent computing paradigms and architectures. The topics covered are computability, (non-)universality and complexity of computation; physics of computation, analog and quantum computing; reversible and asynchronous devices; cellular automata and other mathematical machines; P-systems and cellular computing; infinity and spatial computation; chemical and reservoir computing. The book is the encyclopedia, the first ever complete autho...
Advances in Computer Entertainment.
Nijholt, Antinus; Romão, T.; Reidsma, Dennis; Unknown, [Unknown
2012-01-01
These are the proceedings of the 9th International Conference on Advances in Computer Entertainment ACE 2012). ACE has become the leading scientific forum for dissemination of cutting-edge research results in the area of entertainment computing. Interactive entertainment is one of the most vibrant
Quantum Computations: Fundamentals and Algorithms
International Nuclear Information System (INIS)
Duplij, S.A.; Shapoval, I.I.
2007-01-01
Basic concepts of quantum information theory, principles of quantum calculations and the possibility of creation on this basis unique on calculation power and functioning principle device, named quantum computer, are concerned. The main blocks of quantum logic, schemes of quantum calculations implementation, as well as some known today effective quantum algorithms, called to realize advantages of quantum calculations upon classical, are presented here. Among them special place is taken by Shor's algorithm of number factorization and Grover's algorithm of unsorted database search. Phenomena of decoherence, its influence on quantum computer stability and methods of quantum errors correction are described
Computed laminography and reconstruction algorithm
International Nuclear Information System (INIS)
Que Jiemin; Cao Daquan; Zhao Wei; Tang Xiao
2012-01-01
Computed laminography (CL) is an alternative to computed tomography if large objects are to be inspected with high resolution. This is especially true for planar objects. In this paper, we set up a new scanning geometry for CL, and study the algebraic reconstruction technique (ART) for CL imaging. We compare the results of ART with variant weighted functions by computer simulation with a digital phantom. It proves that ART algorithm is a good choice for the CL system. (authors)
Advances in Computer Entertainment.
Nijholt, Antinus; Romão, T.; Reidsma, Dennis; Unknown, [Unknown
2012-01-01
These are the proceedings of the 9th International Conference on Advances in Computer Entertainment ACE 2012). ACE has become the leading scientific forum for dissemination of cutting-edge research results in the area of entertainment computing. Interactive entertainment is one of the most vibrant areas of interest in modern society and is amongst the fastest growing industries in the world. ACE 2012 will bring together leading researchers and practitioners from academia and industry to prese...
Recent advances in computational optimization
2013-01-01
Optimization is part of our everyday life. We try to organize our work in a better way and optimization occurs in minimizing time and cost or the maximization of the profit, quality and efficiency. Also many real world problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization. This book presents recent advances in computational optimization. The volume includes important real world problems like parameter settings for con- trolling processes in bioreactor, robot skin wiring, strip packing, project scheduling, tuning of PID controller and so on. Some of them can be solved by applying traditional numerical methods, but others need a huge amount of computational resources. For them it is shown that is appropriate to develop algorithms based on metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming etc...
Computational geometry algorithms and applications
de Berg, Mark; Overmars, Mark; Schwarzkopf, Otfried
1997-01-01
Computational geometry emerged from the field of algorithms design and anal ysis in the late 1970s. It has grown into a recognized discipline with its own journals, conferences, and a large community of active researchers. The suc cess of the field as a research discipline can on the one hand be explained from the beauty of the problems studied and the solutions obtained, and, on the other hand, by the many application domains--computer graphics, geographic in formation systems (GIS), robotics, and others-in which geometric algorithms play a fundamental role. For many geometric problems the early algorithmic solutions were either slow or difficult to understand and implement. In recent years a number of new algorithmic techniques have been developed that improved and simplified many of the previous approaches. In this textbook we have tried to make these modem algorithmic solutions accessible to a large audience. The book has been written as a textbook for a course in computational geometry, but it can ...
Associative Algorithms for Computational Creativity
Varshney, Lav R.; Wang, Jun; Varshney, Kush R.
2016-01-01
Computational creativity, the generation of new, unimagined ideas or artifacts by a machine that are deemed creative by people, can be applied in the culinary domain to create novel and flavorful dishes. In fact, we have done so successfully using a combinatorial algorithm for recipe generation combined with statistical models for recipe ranking…
Advances in embedded computer vision
Kisacanin, Branislav
2014-01-01
This illuminating collection offers a fresh look at the very latest advances in the field of embedded computer vision. Emerging areas covered by this comprehensive text/reference include the embedded realization of 3D vision technologies for a variety of applications, such as stereo cameras on mobile devices. Recent trends towards the development of small unmanned aerial vehicles (UAVs) with embedded image and video processing algorithms are also examined. The authoritative insights range from historical perspectives to future developments, reviewing embedded implementation, tools, technolog
Advanced algorithms for information science
Energy Technology Data Exchange (ETDEWEB)
Argo, P.; Brislawn, C.; Fitzgerald, T.J.; Kelley, B.; Kim, W.H.; Mazieres, B.; Roeder, H.; Strottman, D.
1998-12-31
This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). In a modern information-controlled society the importance of fast computational algorithms facilitating data compression and image analysis cannot be overemphasized. Feature extraction and pattern recognition are key to many LANL projects and the same types of dimensionality reduction and compression used in source coding are also applicable to image understanding. The authors have begun developing wavelet coding which decomposes data into different length-scale and frequency bands. New transform-based source-coding techniques offer potential for achieving better, combined source-channel coding performance by using joint-optimization techniques. They initiated work on a system that compresses the video stream in real time, and which also takes the additional step of analyzing the video stream concurrently. By using object-based compression schemes (where an object is an identifiable feature of the video signal, repeatable in time or space), they believe that the analysis is directly related to the efficiency of the compression.
Advanced algorithms for information science
International Nuclear Information System (INIS)
Argo, P.; Brislawn, C.; Fitzgerald, T.J.; Kelley, B.; Kim, W.H.; Mazieres, B.; Roeder, H.; Strottman, D.
1998-01-01
This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). In a modern information-controlled society the importance of fast computational algorithms facilitating data compression and image analysis cannot be overemphasized. Feature extraction and pattern recognition are key to many LANL projects and the same types of dimensionality reduction and compression used in source coding are also applicable to image understanding. The authors have begun developing wavelet coding which decomposes data into different length-scale and frequency bands. New transform-based source-coding techniques offer potential for achieving better, combined source-channel coding performance by using joint-optimization techniques. They initiated work on a system that compresses the video stream in real time, and which also takes the additional step of analyzing the video stream concurrently. By using object-based compression schemes (where an object is an identifiable feature of the video signal, repeatable in time or space), they believe that the analysis is directly related to the efficiency of the compression
Computational electromagnetics recent advances and engineering applications
2014-01-01
Emerging Topics in Computational Electromagnetics in Computational Electromagnetics presents advances in Computational Electromagnetics. This book is designed to fill the existing gap in current CEM literature that only cover the conventional numerical techniques for solving traditional EM problems. The book examines new algorithms, and applications of these algorithms for solving problems of current interest that are not readily amenable to efficient treatment by using the existing techniques. The authors discuss solution techniques for problems arising in nanotechnology, bioEM, metamaterials, as well as multiscale problems. They present techniques that utilize recent advances in computer technology, such as parallel architectures, and the increasing need to solve large and complex problems in a time efficient manner by using highly scalable algorithms.
Combinatorial algorithms enabling computational science: tales from the front
International Nuclear Information System (INIS)
Bhowmick, Sanjukta; Boman, Erik G; Devine, Karen; Gebremedhin, Assefaw; Hendrickson, Bruce; Hovland, Paul; Munson, Todd; Pothen, Alex
2006-01-01
Combinatorial algorithms have long played a crucial enabling role in scientific and engineering computations. The importance of discrete algorithms continues to grow with the demands of new applications and advanced architectures. This paper surveys some recent developments in this rapidly changing and highly interdisciplinary field
Combinatorial algorithms enabling computational science: tales from the front
Energy Technology Data Exchange (ETDEWEB)
Bhowmick, Sanjukta [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Boman, Erik G [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Devine, Karen [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Gebremedhin, Assefaw [Computer Science Department, Old Dominion University (United States); Hendrickson, Bruce [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Hovland, Paul [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Munson, Todd [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Pothen, Alex [Computer Science Department, Old Dominion University (United States)
2006-09-15
Combinatorial algorithms have long played a crucial enabling role in scientific and engineering computations. The importance of discrete algorithms continues to grow with the demands of new applications and advanced architectures. This paper surveys some recent developments in this rapidly changing and highly interdisciplinary field.
Essential algorithms a practical approach to computer algorithms
Stephens, Rod
2013-01-01
A friendly and accessible introduction to the most useful algorithms Computer algorithms are the basic recipes for programming. Professional programmers need to know how to use algorithms to solve difficult programming problems. Written in simple, intuitive English, this book describes how and when to use the most practical classic algorithms, and even how to create new algorithms to meet future needs. The book also includes a collection of questions that can help readers prepare for a programming job interview. Reveals methods for manipulating common data structures s
Contact-impact algorithms on parallel computers
International Nuclear Information System (INIS)
Zhong Zhihua; Nilsson, Larsgunnar
1994-01-01
Contact-impact algorithms on parallel computers are discussed within the context of explicit finite element analysis. The algorithms concerned include a contact searching algorithm and an algorithm for contact force calculations. The contact searching algorithm is based on the territory concept of the general HITA algorithm. However, no distinction is made between different contact bodies, or between different contact surfaces. All contact segments from contact boundaries are taken as a single set. Hierarchy territories and contact territories are expanded. A three-dimensional bucket sort algorithm is used to sort contact nodes. The defence node algorithm is used in the calculation of contact forces. Both the contact searching algorithm and the defence node algorithm are implemented on the connection machine CM-200. The performance of the algorithms is examined under different circumstances, and numerical results are presented. ((orig.))
Advances in physiological computing
Fairclough, Stephen H
2014-01-01
This edited collection will provide an overview of the field of physiological computing, i.e. the use of physiological signals as input for computer control. It will cover a breadth of current research, from brain-computer interfaces to telemedicine.
Prospective Algorithms for Quantum Evolutionary Computation
Sofge, Donald A.
2008-01-01
This effort examines the intersection of the emerging field of quantum computing and the more established field of evolutionary computation. The goal is to understand what benefits quantum computing might offer to computational intelligence and how computational intelligence paradigms might be implemented as quantum programs to be run on a future quantum computer. We critically examine proposed algorithms and methods for implementing computational intelligence paradigms, primarily focused on ...
Algorithmic Mechanism Design of Evolutionary Computation.
Pei, Yan
2015-01-01
We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm.
High-order hydrodynamic algorithms for exascale computing
Energy Technology Data Exchange (ETDEWEB)
Morgan, Nathaniel Ray [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-02-05
Hydrodynamic algorithms are at the core of many laboratory missions ranging from simulating ICF implosions to climate modeling. The hydrodynamic algorithms commonly employed at the laboratory and in industry (1) typically lack requisite accuracy for complex multi- material vortical flows and (2) are not well suited for exascale computing due to poor data locality and poor FLOP/memory ratios. Exascale computing requires advances in both computer science and numerical algorithms. We propose to research the second requirement and create a new high-order hydrodynamic algorithm that has superior accuracy, excellent data locality, and excellent FLOP/memory ratios. This proposal will impact a broad range of research areas including numerical theory, discrete mathematics, vorticity evolution, gas dynamics, interface instability evolution, turbulent flows, fluid dynamics and shock driven flows. If successful, the proposed research has the potential to radically transform simulation capabilities and help position the laboratory for computing at the exascale.
Algorithms and file structures for computational geometry
International Nuclear Information System (INIS)
Hinrichs, K.; Nievergelt, J.
1983-01-01
Algorithms for solving geometric problems and file structures for storing large amounts of geometric data are of increasing importance in computer graphics and computer-aided design. As examples of recent progress in computational geometry, we explain plane-sweep algorithms, which solve various topological and geometric problems efficiently; and we present the grid file, an adaptable, symmetric multi-key file structure that provides efficient access to multi-dimensional data along any space dimension. (orig.)
Advances of evolutionary computation methods and operators
Cuevas, Erik; Oliva Navarro, Diego Alberto
2016-01-01
The goal of this book is to present advances that discuss alternative Evolutionary Computation (EC) developments and non-conventional operators which have proved to be eﬀective in the solution of several complex problems. The book has been structured so that each chapter can be read independently from the others. The book contains nine chapters with the following themes: 1) Introduction, 2) the Social Spider Optimization (SSO), 3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB) algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search (LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE) method, 8) the multimodal CAB, 9) the constrained SSO method.
A Faster Algorithm for Computing Straight Skeletons
Cheng, Siu-Wing
2014-09-01
We present a new algorithm for computing the straight skeleton of a polygon. For a polygon with n vertices, among which r are reflex vertices, we give a deterministic algorithm that reduces the straight skeleton computation to a motorcycle graph computation in O(n (logn)logr) time. It improves on the previously best known algorithm for this reduction, which is randomized, and runs in expected O(n√h+1log2n) time for a polygon with h holes. Using known motorcycle graph algorithms, our result yields improved time bounds for computing straight skeletons. In particular, we can compute the straight skeleton of a non-degenerate polygon in O(n (logn) logr + r 4/3 + ε ) time for any ε > 0. On degenerate input, our time bound increases to O(n (logn) logr + r 17/11 + ε ).
A Faster Algorithm for Computing Straight Skeletons
Mencel, Liam A.
2014-05-06
We present a new algorithm for computing the straight skeleton of a polygon. For a polygon with n vertices, among which r are reflex vertices, we give a deterministic algorithm that reduces the straight skeleton computation to a motorcycle graph computation in O(n (log n) log r) time. It improves on the previously best known algorithm for this reduction, which is randomised, and runs in expected O(n √(h+1) log² n) time for a polygon with h holes. Using known motorcycle graph algorithms, our result yields improved time bounds for computing straight skeletons. In particular, we can compute the straight skeleton of a non-degenerate polygon in O(n (log n) log r + r^(4/3 + ε)) time for any ε > 0. On degenerate input, our time bound increases to O(n (log n) log r + r^(17/11 + ε))
A Faster Algorithm for Computing Straight Skeletons
Cheng, Siu-Wing; Mencel, Liam A.; Vigneron, Antoine E.
2014-01-01
We present a new algorithm for computing the straight skeleton of a polygon. For a polygon with n vertices, among which r are reflex vertices, we give a deterministic algorithm that reduces the straight skeleton computation to a motorcycle graph computation in O(n (logn)logr) time. It improves on the previously best known algorithm for this reduction, which is randomized, and runs in expected O(n√h+1log2n) time for a polygon with h holes. Using known motorcycle graph algorithms, our result yields improved time bounds for computing straight skeletons. In particular, we can compute the straight skeleton of a non-degenerate polygon in O(n (logn) logr + r 4/3 + ε ) time for any ε > 0. On degenerate input, our time bound increases to O(n (logn) logr + r 17/11 + ε ).
1981-12-01
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A neural algorithm for a fundamental computing problem.
Dasgupta, Sanjoy; Stevens, Charles F; Navlakha, Saket
2017-11-10
Similarity search-for example, identifying similar images in a database or similar documents on the web-is a fundamental computing problem faced by large-scale information retrieval systems. We discovered that the fruit fly olfactory circuit solves this problem with a variant of a computer science algorithm (called locality-sensitive hashing). The fly circuit assigns similar neural activity patterns to similar odors, so that behaviors learned from one odor can be applied when a similar odor is experienced. The fly algorithm, however, uses three computational strategies that depart from traditional approaches. These strategies can be translated to improve the performance of computational similarity searches. This perspective helps illuminate the logic supporting an important sensory function and provides a conceptually new algorithm for solving a fundamental computational problem. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
CATEGORIES OF COMPUTER SYSTEMS ALGORITHMS
Directory of Open Access Journals (Sweden)
A. V. Poltavskiy
2015-01-01
Full Text Available Philosophy as a frame of reference on world around and as the first science is a fundamental basis, "roots" (R. Descartes for all branches of the scientific knowledge accumulated and applied in all fields of activity of a human being person. The theory of algorithms as one of the fundamental sections of mathematics, is also based on researches of the gnoseology conducting cognition of a true picture of the world of the buman being. From gnoseology and ontology positions as fundamental sections of philosophy modern innovative projects are inconceivable without development of programs,and algorithms.
A Computational Fluid Dynamics Algorithm on a Massively Parallel Computer
Jespersen, Dennis C.; Levit, Creon
1989-01-01
The discipline of computational fluid dynamics is demanding ever-increasing computational power to deal with complex fluid flow problems. We investigate the performance of a finite-difference computational fluid dynamics algorithm on a massively parallel computer, the Connection Machine. Of special interest is an implicit time-stepping algorithm; to obtain maximum performance from the Connection Machine, it is necessary to use a nonstandard algorithm to solve the linear systems that arise in the implicit algorithm. We find that the Connection Machine ran achieve very high computation rates on both explicit and implicit algorithms. The performance of the Connection Machine puts it in the same class as today's most powerful conventional supercomputers.
A Faster Algorithm for Computing Straight Skeletons
Mencel, Liam A.
2014-01-01
computation in O(n (log n) log r) time. It improves on the previously best known algorithm for this reduction, which is randomised, and runs in expected O(n √(h+1) log² n) time for a polygon with h holes. Using known motorcycle graph algorithms, our result
Quantum Genetic Algorithms for Computer Scientists
Lahoz Beltrá, Rafael
2016-01-01
Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural selection. They are popular heuristic optimisation methods based on simulated genetic mechanisms, i.e., mutation, crossover, etc. and population dynamical processes such as reproduction, selection, etc. Over the last decade, the possibility to emulate a quantum computer (a computer using quantum-mechanical phenomena to perform operations on data) has led to a new class of GAs known as “Quantum Geneti...
Advances in randomized parallel computing
Rajasekaran, Sanguthevar
1999-01-01
The technique of randomization has been employed to solve numerous prob lems of computing both sequentially and in parallel. Examples of randomized algorithms that are asymptotically better than their deterministic counterparts in solving various fundamental problems abound. Randomized algorithms have the advantages of simplicity and better performance both in theory and often in practice. This book is a collection of articles written by renowned experts in the area of randomized parallel computing. A brief introduction to randomized algorithms In the aflalysis of algorithms, at least three different measures of performance can be used: the best case, the worst case, and the average case. Often, the average case run time of an algorithm is much smaller than the worst case. 2 For instance, the worst case run time of Hoare's quicksort is O(n ), whereas its average case run time is only O( n log n). The average case analysis is conducted with an assumption on the input space. The assumption made to arrive at t...
A Faster Algorithm for Computing Motorcycle Graphs
Vigneron, Antoine E.; Yan, Lie
2014-01-01
We present a new algorithm for computing motorcycle graphs that runs in (Formula presented.) time for any (Formula presented.), improving on all previously known algorithms. The main application of this result is to computing the straight skeleton of a polygon. It allows us to compute the straight skeleton of a non-degenerate polygon with (Formula presented.) holes in (Formula presented.) expected time. If all input coordinates are (Formula presented.)-bit rational numbers, we can compute the straight skeleton of a (possibly degenerate) polygon with (Formula presented.) holes in (Formula presented.) expected time. In particular, it means that we can compute the straight skeleton of a simple polygon in (Formula presented.) expected time if all input coordinates are (Formula presented.)-bit rationals, while all previously known algorithms have worst-case running time (Formula presented.). © 2014 Springer Science+Business Media New York.
A Faster Algorithm for Computing Motorcycle Graphs
Vigneron, Antoine E.
2014-08-29
We present a new algorithm for computing motorcycle graphs that runs in (Formula presented.) time for any (Formula presented.), improving on all previously known algorithms. The main application of this result is to computing the straight skeleton of a polygon. It allows us to compute the straight skeleton of a non-degenerate polygon with (Formula presented.) holes in (Formula presented.) expected time. If all input coordinates are (Formula presented.)-bit rational numbers, we can compute the straight skeleton of a (possibly degenerate) polygon with (Formula presented.) holes in (Formula presented.) expected time. In particular, it means that we can compute the straight skeleton of a simple polygon in (Formula presented.) expected time if all input coordinates are (Formula presented.)-bit rationals, while all previously known algorithms have worst-case running time (Formula presented.). © 2014 Springer Science+Business Media New York.
Quantum algorithms for computational nuclear physics
Directory of Open Access Journals (Sweden)
Višňák Jakub
2015-01-01
Full Text Available While quantum algorithms have been studied as an efficient tool for the stationary state energy determination in the case of molecular quantum systems, no similar study for analogical problems in computational nuclear physics (computation of energy levels of nuclei from empirical nucleon-nucleon or quark-quark potentials have been realized yet. Although the difference between the above mentioned studies might seem negligible, it will be examined. First steps towards a particular simulation (on classical computer of the Iterative Phase Estimation Algorithm for deuterium and tritium nuclei energy level computation will be carried out with the aim to prove algorithm feasibility (and extensibility to heavier nuclei for its possible practical realization on a real quantum computer.
Computational algorithm for molybdenite concentrate annealing
International Nuclear Information System (INIS)
Alkatseva, V.M.
1995-01-01
Computational algorithm is presented for annealing of molybdenite concentrate with granulated return dust and that of granulated molybdenite concentrate. The algorithm differs from the known analogies for sulphide raw material annealing by including the calculation of return dust mass in stationary annealing; the latter quantity varies form the return dust mass value obtained in the first iteration step. Masses of solid products are determined by distribution of concentrate annealing products, including return dust and benthonite. The algorithm is applied to computations for annealing of other sulphide materials. 3 refs
Grouping genetic algorithms advances and applications
Mutingi, Michael
2017-01-01
This book presents advances and innovations in grouping genetic algorithms, enriched with new and unique heuristic optimization techniques. These algorithms are specially designed for solving industrial grouping problems where system entities are to be partitioned or clustered into efficient groups according to a set of guiding decision criteria. Examples of such problems are: vehicle routing problems, team formation problems, timetabling problems, assembly line balancing, group maintenance planning, modular design, and task assignment. A wide range of industrial grouping problems, drawn from diverse fields such as logistics, supply chain management, project management, manufacturing systems, engineering design and healthcare, are presented. Typical complex industrial grouping problems, with multiple decision criteria and constraints, are clearly described using illustrative diagrams and formulations. The problems are mapped into a common group structure that can conveniently be used as an input scheme to spe...
Computer animation algorithms and techniques
Parent, Rick
2012-01-01
Driven by the demands of research and the entertainment industry, the techniques of animation are pushed to render increasingly complex objects with ever-greater life-like appearance and motion. This rapid progression of knowledge and technique impacts professional developers, as well as students. Developers must maintain their understanding of conceptual foundations, while their animation tools become ever more complex and specialized. The second edition of Rick Parent's Computer Animation is an excellent resource for the designers who must meet this challenge. The first edition establ
Advanced computations in plasma physics
International Nuclear Information System (INIS)
Tang, W.M.
2002-01-01
Scientific simulation in tandem with theory and experiment is an essential tool for understanding complex plasma behavior. In this paper we review recent progress and future directions for advanced simulations in magnetically confined plasmas with illustrative examples chosen from magnetic confinement research areas such as microturbulence, magnetohydrodynamics, magnetic reconnection, and others. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning widely disparate temporal and spatial scales together with access to powerful new computational resources. In particular, the fusion energy science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPP's to produce three-dimensional, general geometry, nonlinear particle simulations which have accelerated progress in understanding the nature of turbulence self-regulation by zonal flows. It should be emphasized that these calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In general, results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. The associated scientific excitement should serve to
FPGA Implementation of Computer Vision Algorithm
Zhou, Zhonghua
2014-01-01
Computer vision algorithms, which play an significant role in vision processing, is widely applied in many aspects such as geology survey, traffic management and medical care, etc.. Most of the situations require the process to be real-timed, in other words, as fast as possible. Field Programmable Gate Arrays (FPGAs) have a advantage of parallelism fabric in programming, comparing to the serial communications of CPUs, which makes FPGA a perfect platform for implementing vision algorithms. The...
Approximate Computing Techniques for Iterative Graph Algorithms
Energy Technology Data Exchange (ETDEWEB)
Panyala, Ajay R.; Subasi, Omer; Halappanavar, Mahantesh; Kalyanaraman, Anantharaman; Chavarria Miranda, Daniel G.; Krishnamoorthy, Sriram
2017-12-18
Approximate computing enables processing of large-scale graphs by trading off quality for performance. Approximate computing techniques have become critical not only due to the emergence of parallel architectures but also the availability of large scale datasets enabling data-driven discovery. Using two prototypical graph algorithms, PageRank and community detection, we present several approximate computing heuristics to scale the performance with minimal loss of accuracy. We present several heuristics including loop perforation, data caching, incomplete graph coloring and synchronization, and evaluate their efficiency. We demonstrate performance improvements of up to 83% for PageRank and up to 450x for community detection, with low impact of accuracy for both the algorithms. We expect the proposed approximate techniques will enable scalable graph analytics on data of importance to several applications in science and their subsequent adoption to scale similar graph algorithms.
Center for Advanced Computational Technology
Noor, Ahmed K.
2000-01-01
The Center for Advanced Computational Technology (ACT) was established to serve as a focal point for diverse research activities pertaining to application of advanced computational technology to future aerospace systems. These activities include the use of numerical simulations, artificial intelligence methods, multimedia and synthetic environments, and computational intelligence, in the modeling, analysis, sensitivity studies, optimization, design and operation of future aerospace systems. The Center is located at NASA Langley and is an integral part of the School of Engineering and Applied Science of the University of Virginia. The Center has four specific objectives: 1) conduct innovative research on applications of advanced computational technology to aerospace systems; 2) act as pathfinder by demonstrating to the research community what can be done (high-potential, high-risk research); 3) help in identifying future directions of research in support of the aeronautical and space missions of the twenty-first century; and 4) help in the rapid transfer of research results to industry and in broadening awareness among researchers and engineers of the state-of-the-art in applications of advanced computational technology to the analysis, design prototyping and operations of aerospace and other high-performance engineering systems. In addition to research, Center activities include helping in the planning and coordination of the activities of a multi-center team of NASA and JPL researchers who are developing an intelligent synthesis environment for future aerospace systems; organizing workshops and national symposia; as well as writing state-of-the-art monographs and NASA special publications on timely topics.
A micro-hydrology computation ordering algorithm
Croley, Thomas E.
1980-11-01
Discrete-distributed-parameter models are essential for watershed modelling where practical consideration of spatial variations in watershed properties and inputs is desired. Such modelling is necessary for analysis of detailed hydrologic impacts from management strategies and land-use effects. Trade-offs between model validity and model complexity exist in resolution of the watershed. Once these are determined, the watershed is then broken into sub-areas which each have essentially spatially-uniform properties. Lumped-parameter (micro-hydrology) models are applied to these sub-areas and their outputs are combined through the use of a computation ordering technique, as illustrated by many discrete-distributed-parameter hydrology models. Manual ordering of these computations requires fore-thought, and is tedious, error prone, sometimes storage intensive and least adaptable to changes in watershed resolution. A programmable algorithm for ordering micro-hydrology computations is presented that enables automatic ordering of computations within the computer via an easily understood and easily implemented "node" definition, numbering and coding scheme. This scheme and the algorithm are detailed in logic flow-charts and an example application is presented. Extensions and modifications of the algorithm are easily made for complex geometries or differing microhydrology models. The algorithm is shown to be superior to manual ordering techniques and has potential use in high-resolution studies.
A micro-hydrology computation ordering algorithm
International Nuclear Information System (INIS)
Croley, T.E. II
1980-01-01
Discrete-distributed-parameter models are essential for watershed modelling where practical consideration of spatial variations in watershed properties and inputs is desired. Such modelling is necessary for analysis of detailed hydrologic impacts from management strategies and land-use effects. Trade-offs between model validity and model complexity exist in resolution of the watershed. Once these are determined, the watershed is then broken into sub-areas which each have essentially spatially-uniform properties. Lumped-parameter (micro-hydrology) models are applied to these sub-areas and their outputs are combined through the use of a computation ordering technique, as illustrated by many discrete-distributed-parameter hydrology models. Manual ordering of these computations requires fore-thought, and is tedious, error prone, sometimes storage intensive and least adaptable to changes in watershed resolution. A programmable algorithm for ordering micro-hydrology computations is presented that enables automatic ordering of computations within the computer via an easily understood and easily implemented node definition, numbering and coding scheme. This scheme and the algorithm are detailed in logic flow-charts and an example application is presented. Extensions and modifications of the algorithm are easily made for complex geometries or differing micro-hydrology models. The algorithm is shown to be superior to manual ordering techniques and has potential use in high-resolution studies. (orig.)
International Conference on Advanced Computing
Patnaik, Srikanta
2014-01-01
This book is composed of the Proceedings of the International Conference on Advanced Computing, Networking, and Informatics (ICACNI 2013), held at Central Institute of Technology, Raipur, Chhattisgarh, India during June 14–16, 2013. The book records current research articles in the domain of computing, networking, and informatics. The book presents original research articles, case-studies, as well as review articles in the said field of study with emphasis on their implementation and practical application. Researchers, academicians, practitioners, and industry policy makers around the globe have contributed towards formation of this book with their valuable research submissions.
Computer and machine vision theory, algorithms, practicalities
Davies, E R
2012-01-01
Computer and Machine Vision: Theory, Algorithms, Practicalities (previously entitled Machine Vision) clearly and systematically presents the basic methodology of computer and machine vision, covering the essential elements of the theory while emphasizing algorithmic and practical design constraints. This fully revised fourth edition has brought in more of the concepts and applications of computer vision, making it a very comprehensive and up-to-date tutorial text suitable for graduate students, researchers and R&D engineers working in this vibrant subject. Key features include: Practical examples and case studies give the 'ins and outs' of developing real-world vision systems, giving engineers the realities of implementing the principles in practice New chapters containing case studies on surveillance and driver assistance systems give practical methods on these cutting-edge applications in computer vision Necessary mathematics and essential theory are made approachable by careful explanations and well-il...
Time-advance algorithms based on Hamilton's principle
International Nuclear Information System (INIS)
Lewis, H.R.; Kostelec, P.J.
1993-01-01
Time-advance algorithms based on Hamilton's variational principle are being developed for application to problems in plasma physics and other areas. Hamilton's principle was applied previously to derive a system of ordinary differential equations in time whose solution provides an approximation to the evolution of a plasma described by the Vlasov-Maxwell equations. However, the variational principle was not used to obtain an algorithm for solving the ordinary differential equations numerically. The present research addresses the numerical solution of systems of ordinary differential equations via Hamilton's principle. The basic idea is first to choose a class of functions for approximating the solution of the ordinary differential equations over a specific time interval. Then the parameters in the approximating function are determined by applying Hamilton's principle exactly within the class of approximating functions. For example, if an approximate solution is desired between time t and time t + Δ t, the class of approximating functions could be polynomials in time up to some degree. The issue of how to choose time-advance algorithms is very important for achieving efficient, physically meaningful computer simulations. The objective is to reliably simulate those characteristics of an evolving system that are scientifically most relevant. Preliminary numerical results are presented, including comparisons with other computational methods
Quantum entanglement and quantum computational algorithms
Indian Academy of Sciences (India)
Abstract. The existence of entangled quantum states gives extra power to quantum computers over their classical counterparts. Quantum entanglement shows up qualitatively at the level of two qubits. We demonstrate that the one- and the two-bit Deutsch-Jozsa algorithm does not require entanglement and can be mapped ...
Conformal geometry computational algorithms and engineering applications
Jin, Miao; He, Ying; Wang, Yalin
2018-01-01
This book offers an essential overview of computational conformal geometry applied to fundamental problems in specific engineering fields. It introduces readers to conformal geometry theory and discusses implementation issues from an engineering perspective. The respective chapters explore fundamental problems in specific fields of application, and detail how computational conformal geometric methods can be used to solve them in a theoretically elegant and computationally efficient way. The fields covered include computer graphics, computer vision, geometric modeling, medical imaging, and wireless sensor networks. Each chapter concludes with a summary of the material covered and suggestions for further reading, and numerous illustrations and computational algorithms complement the text. The book draws on courses given by the authors at the University of Louisiana at Lafayette, the State University of New York at Stony Brook, and Tsinghua University, and will be of interest to senior undergraduates, gradua...
Advanced incomplete factorization algorithms for Stiltijes matrices
Energy Technology Data Exchange (ETDEWEB)
Il`in, V.P. [Siberian Division RAS, Novosibirsk (Russian Federation)
1996-12-31
The modern numerical methods for solving the linear algebraic systems Au = f with high order sparse matrices A, which arise in grid approximations of multidimensional boundary value problems, are based mainly on accelerated iterative processes with easily invertible preconditioning matrices presented in the form of approximate (incomplete) factorization of the original matrix A. We consider some recent algorithmic approaches, theoretical foundations, experimental data and open questions for incomplete factorization of Stiltijes matrices which are {open_quotes}the best{close_quotes} ones in the sense that they have the most advanced results. Special attention is given to solving the elliptic differential equations with strongly variable coefficients, singular perturbated diffusion-convection and parabolic equations.
Bioinspired computation in combinatorial optimization: algorithms and their computational complexity
DEFF Research Database (Denmark)
Neumann, Frank; Witt, Carsten
2012-01-01
Bioinspired computation methods, such as evolutionary algorithms and ant colony optimization, are being applied successfully to complex engineering and combinatorial optimization problems, and it is very important that we understand the computational complexity of these algorithms. This tutorials...... problems. Classical single objective optimization is examined first. They then investigate the computational complexity of bioinspired computation applied to multiobjective variants of the considered combinatorial optimization problems, and in particular they show how multiobjective optimization can help...... to speed up bioinspired computation for single-objective optimization problems. The tutorial is based on a book written by the authors with the same title. Further information about the book can be found at www.bioinspiredcomputation.com....
Computational algorithms for simulations in atmospheric optics.
Konyaev, P A; Lukin, V P
2016-04-20
A computer simulation technique for atmospheric and adaptive optics based on parallel programing is discussed. A parallel propagation algorithm is designed and a modified spectral-phase method for computer generation of 2D time-variant random fields is developed. Temporal power spectra of Laguerre-Gaussian beam fluctuations are considered as an example to illustrate the applications discussed. Implementation of the proposed algorithms using Intel MKL and IPP libraries and NVIDIA CUDA technology is shown to be very fast and accurate. The hardware system for the computer simulation is an off-the-shelf desktop with an Intel Core i7-4790K CPU operating at a turbo-speed frequency up to 5 GHz and an NVIDIA GeForce GTX-960 graphics accelerator with 1024 1.5 GHz processors.
Quantum Genetic Algorithms for Computer Scientists
Directory of Open Access Journals (Sweden)
Rafael Lahoz-Beltra
2016-10-01
Full Text Available Genetic algorithms (GAs are a class of evolutionary algorithms inspired by Darwinian natural selection. They are popular heuristic optimisation methods based on simulated genetic mechanisms, i.e., mutation, crossover, etc. and population dynamical processes such as reproduction, selection, etc. Over the last decade, the possibility to emulate a quantum computer (a computer using quantum-mechanical phenomena to perform operations on data has led to a new class of GAs known as “Quantum Genetic Algorithms” (QGAs. In this review, we present a discussion, future potential, pros and cons of this new class of GAs. The review will be oriented towards computer scientists interested in QGAs “avoiding” the possible difficulties of quantum-mechanical phenomena.
An introduction to quantum computing algorithms
Pittenger, Arthur O
2000-01-01
In 1994 Peter Shor [65] published a factoring algorithm for a quantum computer that finds the prime factors of a composite integer N more efficiently than is possible with the known algorithms for a classical com puter. Since the difficulty of the factoring problem is crucial for the se curity of a public key encryption system, interest (and funding) in quan tum computing and quantum computation suddenly blossomed. Quan tum computing had arrived. The study of the role of quantum mechanics in the theory of computa tion seems to have begun in the early 1980s with the publications of Paul Benioff [6]' [7] who considered a quantum mechanical model of computers and the computation process. A related question was discussed shortly thereafter by Richard Feynman [35] who began from a different perspec tive by asking what kind of computer should be used to simulate physics. His analysis led him to the belief that with a suitable class of "quantum machines" one could imitate any quantum system.
Advances and applications of optimised algorithms in image processing
Oliva, Diego
2017-01-01
This book presents a study of the use of optimization algorithms in complex image processing problems. The problems selected explore areas ranging from the theory of image segmentation to the detection of complex objects in medical images. Furthermore, the concepts of machine learning and optimization are analyzed to provide an overview of the application of these tools in image processing. The material has been compiled from a teaching perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics, and can be used for courses on Artificial Intelligence, Advanced Image Processing, Computational Intelligence, etc. Likewise, the material can be useful for research from the evolutionary computation, artificial intelligence and image processing co.
Energy Technology Data Exchange (ETDEWEB)
Kraus, Mareen; Weiss, Jakob; Selo, Nadja; Notohamiprodjo, Mike; Bamberg, Fabian; Nikolaou, Konstantin; Othman, Ahmed E. [Eberhard Karls University Tuebingen, Department of Diagnostic and Interventional Radiology, Tuebingen (Germany); Flohr, Thomas [Siemens Healthcare GmbH, Erlangen (Germany)
2016-11-15
The aim of this study was to evaluate the effect of advanced monoenergetic post-processing (MEI+) on the visualisation of spinal growth in contrast-enhanced dual-energy CT (DE-CT). Twenty-six oncologic patients (age, 61 ± 17 years) with spinal tumorous growth were included. Patients underwent contrast-enhanced dual-energy CT on a third-generation dual-source CT scanner. Image acquisition was in dual-energy mode (100/Sn150kV), and scans were initiated 90 s after contrast agent administration. Virtual monoenergetic images (MEI+) were reconstructed at four different kiloelectron volts (keV) levels (40, 60, 80, 100) and compared to the standard blended portal venous computed tomography (CT{sub pv}). Image quality was assessed qualitatively (conspicuity, delineation, sharpness, noise, confidence; two independent readers; 5-point Likert scale; 5 = excellent) and quantitatively by calculating signal-to-noise (SNR) and contrast-to-noise-ratios (CNR). For a subgroup of 10 patients with MR imaging within 4 months of the DE-CT, we compared the monoenergetic images to the MRIs qualitatively. Highest contrast of spinal growth was observed in MEI+ at 40 keV, with significant differences to CT{sub pv} and all other keV reconstructions (60, 80, 100; p < 0.01). Highest conspicuity, delineation and sharpness were observed in MEI+ at 40 keV, with significant differences to CT{sub pv} (p < 0.001). Similarly, MEI+ at 40 keV yielded highest diagnostic confidence (4.6 ± 0.6), also with significant differences to CT{sub pv} (3.45 ± 0.9, p < 0.001) and to high keV reconstructions (80, 100; p ≤ 0.001). Similarly, CNR calculations revealed highest scores for MEI+ at 40 keV followed by 60 keV and CT{sub pv}, with significant differences to high keV MEI+ reconstructions. Qualitative analysis scores peaked for MR images followed by the MEI+ 40-keV reconstructions. MEI+ at low keV levels can significantly improve image quality and delineation of spinal growth in patients with portal
Algorithms for the Computation of Debris Risk
Matney, Mark J.
2017-01-01
Determining the risks from space debris involve a number of statistical calculations. These calculations inevitably involve assumptions about geometry - including the physical geometry of orbits and the geometry of satellites. A number of tools have been developed in NASA’s Orbital Debris Program Office to handle these calculations; many of which have never been published before. These include algorithms that are used in NASA’s Orbital Debris Engineering Model ORDEM 3.0, as well as other tools useful for computing orbital collision rates and ground casualty risks. This paper presents an introduction to these algorithms and the assumptions upon which they are based.
Algorithms for the Computation of Debris Risks
Matney, Mark
2017-01-01
Determining the risks from space debris involve a number of statistical calculations. These calculations inevitably involve assumptions about geometry - including the physical geometry of orbits and the geometry of non-spherical satellites. A number of tools have been developed in NASA's Orbital Debris Program Office to handle these calculations; many of which have never been published before. These include algorithms that are used in NASA's Orbital Debris Engineering Model ORDEM 3.0, as well as other tools useful for computing orbital collision rates and ground casualty risks. This paper will present an introduction to these algorithms and the assumptions upon which they are based.
Parallel Computing Strategies for Irregular Algorithms
Biswas, Rupak; Oliker, Leonid; Shan, Hongzhang; Biegel, Bryan (Technical Monitor)
2002-01-01
Parallel computing promises several orders of magnitude increase in our ability to solve realistic computationally-intensive problems, but relies on their efficient mapping and execution on large-scale multiprocessor architectures. Unfortunately, many important applications are irregular and dynamic in nature, making their effective parallel implementation a daunting task. Moreover, with the proliferation of parallel architectures and programming paradigms, the typical scientist is faced with a plethora of questions that must be answered in order to obtain an acceptable parallel implementation of the solution algorithm. In this paper, we consider three representative irregular applications: unstructured remeshing, sparse matrix computations, and N-body problems, and parallelize them using various popular programming paradigms on a wide spectrum of computer platforms ranging from state-of-the-art supercomputers to PC clusters. We present the underlying problems, the solution algorithms, and the parallel implementation strategies. Smart load-balancing, partitioning, and ordering techniques are used to enhance parallel performance. Overall results demonstrate the complexity of efficiently parallelizing irregular algorithms.
Computational plasticity algorithm for particle dynamics simulations
Krabbenhoft, K.; Lyamin, A. V.; Vignes, C.
2018-01-01
The problem of particle dynamics simulation is interpreted in the framework of computational plasticity leading to an algorithm which is mathematically indistinguishable from the common implicit scheme widely used in the finite element analysis of elastoplastic boundary value problems. This algorithm provides somewhat of a unification of two particle methods, the discrete element method and the contact dynamics method, which usually are thought of as being quite disparate. In particular, it is shown that the former appears as the special case where the time stepping is explicit while the use of implicit time stepping leads to the kind of schemes usually labelled contact dynamics methods. The framing of particle dynamics simulation within computational plasticity paves the way for new approaches similar (or identical) to those frequently employed in nonlinear finite element analysis. These include mixed implicit-explicit time stepping, dynamic relaxation and domain decomposition schemes.
National Aeronautics and Space Administration — The design and qualification of entry systems for planetary exploration largely rely on computational simulations. However, state-of-the-art modeling capabilities...
Advances in medical image computing.
Tolxdorff, T; Deserno, T M; Handels, H; Meinzer, H-P
2009-01-01
Medical image computing has become a key technology in high-tech applications in medicine and an ubiquitous part of modern imaging systems and the related processes of clinical diagnosis and intervention. Over the past years significant progress has been made in the field, both on methodological and on application level. Despite this progress there are still big challenges to meet in order to establish image processing routinely in health care. In this issue, selected contributions of the German Conference on Medical Image Processing (BVM) are assembled to present latest advances in the field of medical image computing. The winners of scientific awards of the German Conference on Medical Image Processing (BVM) 2008 were invited to submit a manuscript on their latest developments and results for possible publication in Methods of Information in Medicine. Finally, seven excellent papers were selected to describe important aspects of recent advances in the field of medical image processing. The selected papers give an impression of the breadth and heterogeneity of new developments. New methods for improved image segmentation, non-linear image registration and modeling of organs are presented together with applications of image analysis methods in different medical disciplines. Furthermore, state-of-the-art tools and techniques to support the development and evaluation of medical image processing systems in practice are described. The selected articles describe different aspects of the intense development in medical image computing. The image processing methods presented enable new insights into the patient's image data and have the future potential to improve medical diagnostics and patient treatment.
Parallel algorithms for mapping pipelined and parallel computations
Nicol, David M.
1988-01-01
Many computational problems in image processing, signal processing, and scientific computing are naturally structured for either pipelined or parallel computation. When mapping such problems onto a parallel architecture it is often necessary to aggregate an obvious problem decomposition. Even in this context the general mapping problem is known to be computationally intractable, but recent advances have been made in identifying classes of problems and architectures for which optimal solutions can be found in polynomial time. Among these, the mapping of pipelined or parallel computations onto linear array, shared memory, and host-satellite systems figures prominently. This paper extends that work first by showing how to improve existing serial mapping algorithms. These improvements have significantly lower time and space complexities: in one case a published O(nm sup 3) time algorithm for mapping m modules onto n processors is reduced to an O(nm log m) time complexity, and its space requirements reduced from O(nm sup 2) to O(m). Run time complexity is further reduced with parallel mapping algorithms based on these improvements, which run on the architecture for which they create the mappings.
Comparison of evolutionary computation algorithms for solving bi ...
Indian Academy of Sciences (India)
failure probability. Multiobjective Evolutionary Computation algorithms (MOEAs) are well-suited for Multiobjective task scheduling on heterogeneous environment. The two Multi-Objective Evolutionary Algorithms such as Multiobjective Genetic. Algorithm (MOGA) and Multiobjective Evolutionary Programming (MOEP) with.
Fast algorithms for computing phylogenetic divergence time.
Crosby, Ralph W; Williams, Tiffani L
2017-12-06
The inference of species divergence time is a key step in most phylogenetic studies. Methods have been available for the last ten years to perform the inference, but the performance of the methods does not yet scale well to studies with hundreds of taxa and thousands of DNA base pairs. For example a study of 349 primate taxa was estimated to require over 9 months of processing time. In this work, we present a new algorithm, AncestralAge, that significantly improves the performance of the divergence time process. As part of AncestralAge, we demonstrate a new method for the computation of phylogenetic likelihood and our experiments show a 90% improvement in likelihood computation time on the aforementioned dataset of 349 primates taxa with over 60,000 DNA base pairs. Additionally, we show that our new method for the computation of the Bayesian prior on node ages reduces the running time for this computation on the 349 taxa dataset by 99%. Through the use of these new algorithms we open up the ability to perform divergence time inference on large phylogenetic studies.
Digital Geometry Algorithms Theoretical Foundations and Applications to Computational Imaging
Barneva, Reneta
2012-01-01
Digital geometry emerged as an independent discipline in the second half of the last century. It deals with geometric properties of digital objects and is developed with the unambiguous goal to provide rigorous theoretical foundations for devising new advanced approaches and algorithms for various problems of visual computing. Different aspects of digital geometry have been addressed in the literature. This book is the first one that explicitly focuses on the presentation of the most important digital geometry algorithms. Each chapter provides a brief survey on a major research area related to the general volume theme, description and analysis of related fundamental algorithms, as well as new original contributions by the authors. Every chapter contains a section in which interesting open problems are addressed.
Advances in algorithms, languages, and complexity
Ko, Ker-I
1997-01-01
This book contains a collection of survey papers in the areas of algorithms, languages and complexity, the three areas in which Professor Ronald V. Book has made significant contributions. As a fonner student and a co-author who have been influenced by him directly, we would like to dedicate this book to Professor Ronald V. Book to honor and celebrate his sixtieth birthday. Professor Book initiated his brilliant academic career in 1958, graduating from Grinnell College with a Bachelor of Arts degree. He obtained a Master of Arts in Teaching degree in 1960 and a Master of Arts degree in 1964 both from Wesleyan University, and a Doctor of Philosophy degree from Harvard University in 1969, under the guidance of Professor Sheila A. Greibach. Professor Book's research in discrete mathematics and theoretical com puter science is reflected in more than 150 scientific publications. These works have made a strong impact on the development of several areas of theoretical computer science. A more detailed summary of h...
Homogeneous Buchberger algorithms and Sullivant's computational commutative algebra challenge
DEFF Research Database (Denmark)
Lauritzen, Niels
2005-01-01
We give a variant of the homogeneous Buchberger algorithm for positively graded lattice ideals. Using this algorithm we solve the Sullivant computational commutative algebra challenge.......We give a variant of the homogeneous Buchberger algorithm for positively graded lattice ideals. Using this algorithm we solve the Sullivant computational commutative algebra challenge....
Recent Advancements in Lightning Jump Algorithm Work
Schultz, Christopher J.; Petersen, Walter A.; Carey, Lawrence D.
2010-01-01
In the past year, the primary objectives were to show the usefulness of total lightning as compared to traditional cloud-to-ground (CG) networks, test the lightning jump algorithm configurations in other regions of the country, increase the number of thunderstorms within our thunderstorm database, and to pinpoint environments that could prove difficult for any lightning jump configuration. A total of 561 thunderstorms have been examined in the past year (409 non-severe, 152 severe) from four regions of the country (North Alabama, Washington D.C., High Plains of CO/KS, and Oklahoma). Results continue to indicate that the 2 lightning jump algorithm configuration holds the most promise in terms of prospective operational lightning jump algorithms, with a probability of detection (POD) at 81%, a false alarm rate (FAR) of 45%, a critical success index (CSI) of 49% and a Heidke Skill Score (HSS) of 0.66. The second best performing algorithm configuration was the Threshold 4 algorithm, which had a POD of 72%, FAR of 51%, a CSI of 41% and an HSS of 0.58. Because a more complex algorithm configuration shows the most promise in terms of prospective operational lightning jump algorithms, accurate thunderstorm cell tracking work must be undertaken to track lightning trends on an individual thunderstorm basis over time. While these numbers for the 2 configuration are impressive, the algorithm does have its weaknesses. Specifically, low-topped and tropical cyclone thunderstorm environments are present issues for the 2 lightning jump algorithm, because of the suppressed vertical depth impact on overall flash counts (i.e., a relative dearth in lightning). For example, in a sample of 120 thunderstorms from northern Alabama that contained 72 missed events by the 2 algorithm 36% of the misses were associated with these two environments (17 storms).
Advanced life support for cardiac arrest beyond the algorithm
DEFF Research Database (Denmark)
Rudolph, Søren Steemann; Isbye, Dan Lou; Pfeiffer, Peter
2018-01-01
In an advanced emergency medical service all parts of the advanced life support (ALS) algorithm can be provided. This evidence-based algorithm outlines resuscitative efforts for the first 10-15 minutes after cardiac arrest, whereafter the algorithm repeats itself. Restoration of spontaneous...... circulation fails in most cases, but in some circumstances the patient may benefit from additional interventional approaches, in which case transport to hospital with ongoing cardiopulmonary resuscitation is indicated. This paper has summarized treatments outside the ALS algorithm, which may be beneficial...
Advances in Computer Science and Engineering
Second International Conference on Advances in Computer Science and Engineering (CES 2012)
2012-01-01
This book includes the proceedings of the second International Conference on Advances in Computer Science and Engineering (CES 2012), which was held during January 13-14, 2012 in Sanya, China. The papers in these proceedings of CES 2012 focus on the researchers’ advanced works in their fields of Computer Science and Engineering mainly organized in four topics, (1) Software Engineering, (2) Intelligent Computing, (3) Computer Networks, and (4) Artificial Intelligence Software.
Nagamalai, Dhinaharan; Chaki, Nabendu
2013-01-01
The international conference on Advances in Computing and Information technology (ACITY 2012) provides an excellent international forum for both academics and professionals for sharing knowledge and results in theory, methodology and applications of Computer Science and Information Technology. The Second International Conference on Advances in Computing and Information technology (ACITY 2012), held in Chennai, India, during July 13-15, 2012, covered a number of topics in all major fields of Computer Science and Information Technology including: networking and communications, network security and applications, web and internet computing, ubiquitous computing, algorithms, bioinformatics, digital image processing and pattern recognition, artificial intelligence, soft computing and applications. Upon a strength review process, a number of high-quality, presenting not only innovative ideas but also a founded evaluation and a strong argumentation of the same, were selected and collected in the present proceedings, ...
A simple algorithm for computing canonical forms
Ford, H.; Hunt, L. R.; Renjeng, S.
1986-01-01
It is well known that all linear time-invariant controllable systems can be transformed to Brunovsky canonical form by a transformation consisting only of coordinate changes and linear feedback. However, the actual procedures for doing this have tended to be overly complex. The technique introduced here is envisioned as an on-line procedure and is inspired by George Meyer's tangent model for nonlinear systems. The process utilizes Meyer's block triangular form as an intermedicate step in going to Brunovsky form. The method also involves orthogonal matrices, thus eliminating the need for the computation of matrix inverses. In addition, the Kronecker indices can be computed as a by-product of this transformation so it is necessary to know them in advance.
Extending the horizons advances in computing, optimization, and decision technologies
Joseph, Anito; Mehrotra, Anuj; Trick, Michael
2007-01-01
Computer Science and Operations Research continue to have a synergistic relationship and this book represents the results of cross-fertilization between OR/MS and CS/AI. It is this interface of OR/CS that makes possible advances that could not have been achieved in isolation. Taken collectively, these articles are indicative of the state-of-the-art in the interface between OR/MS and CS/AI and of the high caliber of research being conducted by members of the INFORMS Computing Society. EXTENDING THE HORIZONS: Advances in Computing, Optimization, and Decision Technologies is a volume that presents the latest, leading research in the design and analysis of algorithms, computational optimization, heuristic search and learning, modeling languages, parallel and distributed computing, simulation, computational logic and visualization. This volume also emphasizes a variety of novel applications in the interface of CS, AI, and OR/MS.
An algorithm of computing inhomogeneous differential equations for definite integrals
Nakayama, Hiromasa; Nishiyama, Kenta
2010-01-01
We give an algorithm to compute inhomogeneous differential equations for definite integrals with parameters. The algorithm is based on the integration algorithm for $D$-modules by Oaku. Main tool in the algorithm is the Gr\\"obner basis method in the ring of differential operators.
Parallel computation of nondeterministic algorithms in VLSI
Energy Technology Data Exchange (ETDEWEB)
Hortensius, P D
1987-01-01
This work examines parallel VLSI implementations of nondeterministic algorithms. It is demonstrated that conventional pseudorandom number generators are unsuitable for highly parallel applications. Efficient parallel pseudorandom sequence generation can be accomplished using certain classes of elementary one-dimensional cellular automata. The pseudorandom numbers appear in parallel on each clock cycle. Extensive study of the properties of these new pseudorandom number generators is made using standard empirical random number tests, cycle length tests, and implementation considerations. Furthermore, it is shown these particular cellular automata can form the basis of efficient VLSI architectures for computations involved in the Monte Carlo simulation of both the percolation and Ising models from statistical mechanics. Finally, a variation on a Built-In Self-Test technique based upon cellular automata is presented. These Cellular Automata-Logic-Block-Observation (CALBO) circuits improve upon conventional design for testability circuitry.
Advanced metaheuristic algorithms for laser optimization
International Nuclear Information System (INIS)
Tomizawa, H.
2010-01-01
A laser is one of the most important experimental tools. In synchrotron radiation field, lasers are widely used for experiments with Pump-Probe techniques. Especially for Xray-FELs, a laser has important roles as a seed light source or photo-cathode-illuminating light source to generate a high brightness electron bunch. The controls of laser pulse characteristics are required for many kinds of experiments. However, the laser should be tuned and customized for each requirement by laser experts. The automatic tuning of laser is required to realize with some sophisticated algorithms. The metaheuristic algorithm is one of the useful candidates to find one of the best solutions as acceptable as possible. The metaheuristic laser tuning system is expected to save our human resources and time for the laser preparations. I have shown successful results on a metaheuristic algorithm based on a genetic algorithm to optimize spatial (transverse) laser profiles and a hill climbing method extended with a fuzzy set theory to choose one of the best laser alignments automatically for each experimental requirement. (author)
Fast algorithm for computing complex number-theoretic transforms
Reed, I. S.; Liu, K. Y.; Truong, T. K.
1977-01-01
A high-radix FFT algorithm for computing transforms over FFT, where q is a Mersenne prime, is developed to implement fast circular convolutions. This new algorithm requires substantially fewer multiplications than the conventional FFT.
Algorithms for computational fluid dynamics n parallel processors
International Nuclear Information System (INIS)
Van de Velde, E.F.
1986-01-01
A study of parallel algorithms for the numerical solution of partial differential equations arising in computational fluid dynamics is presented. The actual implementation on parallel processors of shared and nonshared memory design is discussed. The performance of these algorithms is analyzed in terms of machine efficiency, communication time, bottlenecks and software development costs. For elliptic equations, a parallel preconditioned conjugate gradient method is described, which has been used to solve pressure equations discretized with high order finite elements on irregular grids. A parallel full multigrid method and a parallel fast Poisson solver are also presented. Hyperbolic conservation laws were discretized with parallel versions of finite difference methods like the Lax-Wendroff scheme and with the Random Choice method. Techniques are developed for comparing the behavior of an algorithm on different architectures as a function of problem size and local computational effort. Effective use of these advanced architecture machines requires the use of machine dependent programming. It is shown that the portability problems can be minimized by introducing high level operations on vectors and matrices structured into program libraries
Advancements to the planogram frequency–distance rebinning algorithm
International Nuclear Information System (INIS)
Champley, Kyle M; Kinahan, Paul E; Raylman, Raymond R
2010-01-01
reconstruction) and planogram filtered backprojection image reconstruction algorithms. We show that the PFDRX algorithm produces images that are nearly as accurate as images reconstructed with the planogram filtered backprojection algorithm and more accurate than images reconstructed with the PFDR+FBP algorithm. Both the PFDR+FBP and PFDRX algorithms provide a dramatic improvement in computation time over the planogram filtered backprojection algorithm
Advanced computer-based training
Energy Technology Data Exchange (ETDEWEB)
Fischer, H D; Martin, H D
1987-05-01
The paper presents new techniques of computer-based training for personnel of nuclear power plants. Training on full-scope simulators is further increased by use of dedicated computer-based equipment. An interactive communication system runs on a personal computer linked to a video disc; a part-task simulator runs on 32 bit process computers and shows two versions: as functional trainer or as on-line predictor with an interactive learning system (OPAL), which may be well-tailored to a specific nuclear power plant. The common goal of both develoments is the optimization of the cost-benefit ratio for training and equipment.
Advanced computer-based training
International Nuclear Information System (INIS)
Fischer, H.D.; Martin, H.D.
1987-01-01
The paper presents new techniques of computer-based training for personnel of nuclear power plants. Training on full-scope simulators is further increased by use of dedicated computer-based equipment. An interactive communication system runs on a personal computer linked to a video disc; a part-task simulator runs on 32 bit process computers and shows two versions: as functional trainer or as on-line predictor with an interactive learning system (OPAL), which may be well-tailored to a specific nuclear power plant. The common goal of both develoments is the optimization of the cost-benefit ratio for training and equipment. (orig.) [de
Applying Kitaev's algorithm in an ion trap quantum computer
International Nuclear Information System (INIS)
Travaglione, B.; Milburn, G.J.
2000-01-01
Full text: Kitaev's algorithm is a method of estimating eigenvalues associated with an operator. Shor's factoring algorithm, which enables a quantum computer to crack RSA encryption codes, is a specific example of Kitaev's algorithm. It has been proposed that the algorithm can also be used to generate eigenstates. We extend this proposal for small quantum systems, identifying the conditions under which the algorithm can successfully generate eigenstates. We then propose an implementation scheme based on an ion trap quantum computer. This scheme allows us to illustrate a simple example, in which the algorithm effectively generates eigenstates
Development of computed tomography system and image reconstruction algorithm
International Nuclear Information System (INIS)
Khairiah Yazid; Mohd Ashhar Khalid; Azaman Ahmad; Khairul Anuar Mohd Salleh; Ab Razak Hamzah
2006-01-01
Computed tomography is one of the most advanced and powerful nondestructive inspection techniques, which is currently used in many different industries. In several CT systems, detection has been by combination of an X-ray image intensifier and charge -coupled device (CCD) camera or by using line array detector. The recent development of X-ray flat panel detector has made fast CT imaging feasible and practical. Therefore this paper explained the arrangement of a new detection system which is using the existing high resolution (127 μm pixel size) flat panel detector in MINT and the image reconstruction technique developed. The aim of the project is to develop a prototype flat panel detector based CT imaging system for NDE. The prototype consisted of an X-ray tube, a flat panel detector system, a rotation table and a computer system to control the sample motion and image acquisition. Hence this project is divided to two major tasks, firstly to develop image reconstruction algorithm and secondly to integrate X-ray imaging components into one CT system. The image reconstruction algorithm using filtered back-projection method is developed and compared to other techniques. The MATLAB program is the tools used for the simulations and computations for this project. (Author)
Advances in photonic reservoir computing
Directory of Open Access Journals (Sweden)
Van der Sande Guy
2017-05-01
Full Text Available We review a novel paradigm that has emerged in analogue neuromorphic optical computing. The goal is to implement a reservoir computer in optics, where information is encoded in the intensity and phase of the optical field. Reservoir computing is a bio-inspired approach especially suited for processing time-dependent information. The reservoir’s complex and high-dimensional transient response to the input signal is capable of universal computation. The reservoir does not need to be trained, which makes it very well suited for optics. As such, much of the promise of photonic reservoirs lies in their minimal hardware requirements, a tremendous advantage over other hardware-intensive neural network models. We review the two main approaches to optical reservoir computing: networks implemented with multiple discrete optical nodes and the continuous system of a single nonlinear device coupled to delayed feedback.
Advances in photonic reservoir computing
Van der Sande, Guy; Brunner, Daniel; Soriano, Miguel C.
2017-05-01
We review a novel paradigm that has emerged in analogue neuromorphic optical computing. The goal is to implement a reservoir computer in optics, where information is encoded in the intensity and phase of the optical field. Reservoir computing is a bio-inspired approach especially suited for processing time-dependent information. The reservoir's complex and high-dimensional transient response to the input signal is capable of universal computation. The reservoir does not need to be trained, which makes it very well suited for optics. As such, much of the promise of photonic reservoirs lies in their minimal hardware requirements, a tremendous advantage over other hardware-intensive neural network models. We review the two main approaches to optical reservoir computing: networks implemented with multiple discrete optical nodes and the continuous system of a single nonlinear device coupled to delayed feedback.
A simple algorithm for computing the smallest enclosing circle
DEFF Research Database (Denmark)
Skyum, Sven
1991-01-01
Presented is a simple O(n log n) algorithm for computing the smallest enclosing circle of a convex polygon. It can be easily extended to algorithms that compute the farthest-and the closest-point Voronoi diagram of a convex polygon within the same time bound.......Presented is a simple O(n log n) algorithm for computing the smallest enclosing circle of a convex polygon. It can be easily extended to algorithms that compute the farthest-and the closest-point Voronoi diagram of a convex polygon within the same time bound....
Advances in computational complexity theory
Cai, Jin-Yi
1993-01-01
This collection of recent papers on computational complexity theory grew out of activities during a special year at DIMACS. With contributions by some of the leading experts in the field, this book is of lasting value in this fast-moving field, providing expositions not found elsewhere. Although aimed primarily at researchers in complexity theory and graduate students in mathematics or computer science, the book is accessible to anyone with an undergraduate education in mathematics or computer science. By touching on some of the major topics in complexity theory, this book sheds light on this burgeoning area of research.
Advanced in Computer Science and its Applications
Yen, Neil; Park, James; CSA 2013
2014-01-01
The theme of CSA is focused on the various aspects of computer science and its applications for advances in computer science and its applications and provides an opportunity for academic and industry professionals to discuss the latest issues and progress in the area of computer science and its applications. Therefore this book will be include the various theories and practical applications in computer science and its applications.
Quantum chromodynamics with advanced computing
International Nuclear Information System (INIS)
Kronfeld, A S
2008-01-01
We survey results in lattice quantum chromodynamics from groups in the USQCD Collaboration. The main focus is on physics, but many aspects of the discussion are aimed at an audience of computational physicists
Sorting on STAR. [CDC computer algorithm timing comparison
Stone, H. S.
1978-01-01
Timing comparisons are given for three sorting algorithms written for the CDC STAR computer. One algorithm is Hoare's (1962) Quicksort, which is the fastest or nearly the fastest sorting algorithm for most computers. A second algorithm is a vector version of Quicksort that takes advantage of the STAR's vector operations. The third algorithm is an adaptation of Batcher's (1968) sorting algorithm, which makes especially good use of vector operations but has a complexity of N(log N)-squared as compared with a complexity of N log N for the Quicksort algorithms. In spite of its worse complexity, Batcher's sorting algorithm is competitive with the serial version of Quicksort for vectors up to the largest that can be treated by STAR. Vector Quicksort outperforms the other two algorithms and is generally preferred. These results indicate that unusual instruction sets can introduce biases in program execution time that counter results predicted by worst-case asymptotic complexity analysis.
International Conference on Advanced Computing for Innovation
Angelova, Galia; Agre, Gennady
2016-01-01
This volume is a selected collection of papers presented and discussed at the International Conference “Advanced Computing for Innovation (AComIn 2015)”. The Conference was held at 10th -11th of November, 2015 in Sofia, Bulgaria and was aimed at providing a forum for international scientific exchange between Central/Eastern Europe and the rest of the world on several fundamental topics of computational intelligence. The papers report innovative approaches and solutions in hot topics of computational intelligence – advanced computing, language and semantic technologies, signal and image processing, as well as optimization and intelligent control.
Bringing Advanced Computational Techniques to Energy Research
Energy Technology Data Exchange (ETDEWEB)
Mitchell, Julie C
2012-11-17
Please find attached our final technical report for the BACTER Institute award. BACTER was created as a graduate and postdoctoral training program for the advancement of computational biology applied to questions of relevance to bioenergy research.
Fundamentals of natural computing basic concepts, algorithms, and applications
de Castro, Leandro Nunes
2006-01-01
Introduction A Small Sample of Ideas The Philosophy of Natural Computing The Three Branches: A Brief Overview When to Use Natural Computing Approaches Conceptualization General Concepts PART I - COMPUTING INSPIRED BY NATURE Evolutionary Computing Problem Solving as a Search Task Hill Climbing and Simulated Annealing Evolutionary Biology Evolutionary Computing The Other Main Evolutionary Algorithms From Evolutionary Biology to Computing Scope of Evolutionary Computing Neurocomputing The Nervous System Artif
Advanced topics in computer vision
Farinella, Giovanni Maria; Cipolla, Roberto
2013-01-01
This book presents a broad selection of cutting-edge research, covering both theoretical and practical aspects of reconstruction, registration, and recognition. The text provides an overview of challenging areas and descriptions of novel algorithms. Features: investigates visual features, trajectory features, and stereo matching; reviews the main challenges of semi-supervised object recognition, and a novel method for human action categorization; presents a framework for the visual localization of MAVs, and for the use of moment constraints in convex shape optimization; examines solutions to t
Indian Academy of Sciences (India)
polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.
Soft computing in advanced robotics
Kobayashi, Ichiro; Kim, Euntai
2014-01-01
Intelligent system and robotics are inevitably bound up; intelligent robots makes embodiment of system integration by using the intelligent systems. We can figure out that intelligent systems are to cell units, while intelligent robots are to body components. The two technologies have been synchronized in progress. Making leverage of the robotics and intelligent systems, applications cover boundlessly the range from our daily life to space station; manufacturing, healthcare, environment, energy, education, personal assistance, logistics. This book aims at presenting the research results in relevance with intelligent robotics technology. We propose to researchers and practitioners some methods to advance the intelligent systems and apply them to advanced robotics technology. This book consists of 10 contributions that feature mobile robots, robot emotion, electric power steering, multi-agent, fuzzy visual navigation, adaptive network-based fuzzy inference system, swarm EKF localization and inspection robot. Th...
Koichi, Shungo; Iwata, Satoru; Uno, Takeaki; Koshino, Hiroyuki; Satoh, Hiroko
2007-01-01
We describe a rigorous and fast algorithm for advanced canonical coding of planar chemical structures based on the algorithm of Faulon et al. (J. Chem. Inf. Comput. Sci. 2004, 44, 427-436). Our algorithm works well even for highly symmetric structures; moreover, an advantage of our algorithm includes providing a rigorous canonical numbering of atoms with a consideration of stereochemistry and recognizing symmetric moieties. The planar structural line notation with the canonical numbering is also fit for use with stereochemical line notation. These capabilities are usable for general purposes in chemical structural coding and are particularly essential for detecting equivalent atoms in NMR studies. This algorithm was implemented on a 13C NMR chemical shift prediction system CAST/CNMR. Applications of the algorithm to several organic compounds demonstrate the practical efficiency of the rigorous coding.
Advanced Dynamically Adaptive Algorithms for Stochastic Simulations on Extreme Scales
Energy Technology Data Exchange (ETDEWEB)
Xiu, Dongbin [Univ. of Utah, Salt Lake City, UT (United States)
2017-03-03
The focus of the project is the development of mathematical methods and high-performance computational tools for stochastic simulations, with a particular emphasis on computations on extreme scales. The core of the project revolves around the design of highly efficient and scalable numerical algorithms that can adaptively and accurately, in high dimensional spaces, resolve stochastic problems with limited smoothness, even containing discontinuities.
Computer networks and advanced communications
International Nuclear Information System (INIS)
Koederitz, W.L.; Macon, B.S.
1992-01-01
One of the major methods for getting the most productivity and benefits from computer usage is networking. However, for those who are contemplating a change from stand-alone computers to a network system, the investigation of actual networks in use presents a paradox: network systems can be highly productive and beneficial; at the same time, these networks can create many complex, frustrating problems. The issue becomes a question of whether the benefits of networking are worth the extra effort and cost. In response to this issue, the authors review in this paper the implementation and management of an actual network in the LSU Petroleum Engineering Department. The network, which has been in operation for four years, is large and diverse (50 computers, 2 sites, PC's, UNIX RISC workstations, etc.). The benefits, costs, and method of operation of this network will be described, and an effort will be made to objectively weigh these elements from the point of view of the average computer user
Preface (to: Advances in Computer Entertainment)
Romão, Teresa; Nijholt, Antinus; Romão, Teresa; Reidsma, Dennis
2012-01-01
These are the proceedings of the 9th International Conference on Advances in Computer Entertainment ACE 2012). ACE has become the leading scientific forum for dissemination of cutting-edge research results in the area of entertainment computing. Interactive entertainment is one of the most vibrant
Advance Trends in Soft Computing
Kreinovich, Vladik; Kacprzyk, Janusz; WCSC 2013
2014-01-01
This book is the proceedings of the 3rd World Conference on Soft Computing (WCSC), which was held in San Antonio, TX, USA, on December 16-18, 2013. It presents start-of-the-art theory and applications of soft computing together with an in-depth discussion of current and future challenges in the field, providing readers with a 360 degree view on soft computing. Topics range from fuzzy sets, to fuzzy logic, fuzzy mathematics, neuro-fuzzy systems, fuzzy control, decision making in fuzzy environments, image processing and many more. The book is dedicated to Lotfi A. Zadeh, a renowned specialist in signal analysis and control systems research who proposed the idea of fuzzy sets, in which an element may have a partial membership, in the early 1960s, followed by the idea of fuzzy logic, in which a statement can be true only to a certain degree, with degrees described by numbers in the interval [0,1]. The performance of fuzzy systems can often be improved with the help of optimization techniques, e.g. evolutionary co...
Quantum entanglement and quantum computational algorithms
Indian Academy of Sciences (India)
We demonstrate that the one- and the two-bit Deutsch-Jozsa algorithm does not require entanglement and can be mapped onto a classical optical scheme. It is only for three and more input bits that the DJ algorithm requires the implementation of entangling transformations and in these cases it is impossible to implement ...
Quantum computation and Shor close-quote s factoring algorithm
International Nuclear Information System (INIS)
Ekert, A.; Jozsa, R.
1996-01-01
Current technology is beginning to allow us to manipulate rather than just observe individual quantum phenomena. This opens up the possibility of exploiting quantum effects to perform computations beyond the scope of any classical computer. Recently Peter Shor discovered an efficient algorithm for factoring whole numbers, which uses characteristically quantum effects. The algorithm illustrates the potential power of quantum computation, as there is no known efficient classical method for solving this problem. The authors give an exposition of Shor close-quote s algorithm together with an introduction to quantum computation and complexity theory. They discuss experiments that may contribute to its practical implementation. copyright 1996 The American Physical Society
The ASTRA Toolbox: A platform for advanced algorithm development in electron tomography
Energy Technology Data Exchange (ETDEWEB)
Aarle, Wim van, E-mail: wim.vanaarle@uantwerpen.be [iMinds-Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium); Palenstijn, Willem Jan, E-mail: willemjan.palenstijn@uantwerpen.be [iMinds-Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium); Centrum Wiskunde & Informatica, Science Park 123, NL-1098 XG Amsterdam (Netherlands); De Beenhouwer, Jan, E-mail: jan.debeenhouwer@uantwerpen.be [iMinds-Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium); Altantzis, Thomas, E-mail: thomas.altantzis@uantwerpen.be [Electron Microscopy for Materials Science, University of Antwerp, Groenenborgerlaan 171, B-2020 Wilrijk (Belgium); Bals, Sara, E-mail: sara.bals@uantwerpen.be [Electron Microscopy for Materials Science, University of Antwerp, Groenenborgerlaan 171, B-2020 Wilrijk (Belgium); Batenburg, K. Joost, E-mail: joost.batenburg@cwi.nl [iMinds-Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium); Centrum Wiskunde & Informatica, Science Park 123, NL-1098 XG Amsterdam (Netherlands); Mathematical Institute, Leiden University, P.O. Box 9512, NL-2300 RA Leiden (Netherlands); Sijbers, Jan, E-mail: jan.sijbers@uantwerpen.be [iMinds-Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium)
2015-10-15
We present the ASTRA Toolbox as an open platform for 3D image reconstruction in tomography. Most of the software tools that are currently used in electron tomography offer limited flexibility with respect to the geometrical parameters of the acquisition model and the algorithms used for reconstruction. The ASTRA Toolbox provides an extensive set of fast and flexible building blocks that can be used to develop advanced reconstruction algorithms, effectively removing these limitations. We demonstrate this flexibility, the resulting reconstruction quality, and the computational efficiency of this toolbox by a series of experiments, based on experimental dual-axis tilt series. - Highlights: • The ASTRA Toolbox is an open platform for 3D image reconstruction in tomography. • Advanced reconstruction algorithms can be prototyped using the fast and flexible building blocks. • This flexibility is demonstrated on a common use case: dual-axis tilt series reconstruction with prior knowledge. • The computational efficiency is validated on an experimentally measured tilt series.
The ASTRA Toolbox: A platform for advanced algorithm development in electron tomography
International Nuclear Information System (INIS)
Aarle, Wim van; Palenstijn, Willem Jan; De Beenhouwer, Jan; Altantzis, Thomas; Bals, Sara; Batenburg, K. Joost; Sijbers, Jan
2015-01-01
We present the ASTRA Toolbox as an open platform for 3D image reconstruction in tomography. Most of the software tools that are currently used in electron tomography offer limited flexibility with respect to the geometrical parameters of the acquisition model and the algorithms used for reconstruction. The ASTRA Toolbox provides an extensive set of fast and flexible building blocks that can be used to develop advanced reconstruction algorithms, effectively removing these limitations. We demonstrate this flexibility, the resulting reconstruction quality, and the computational efficiency of this toolbox by a series of experiments, based on experimental dual-axis tilt series. - Highlights: • The ASTRA Toolbox is an open platform for 3D image reconstruction in tomography. • Advanced reconstruction algorithms can be prototyped using the fast and flexible building blocks. • This flexibility is demonstrated on a common use case: dual-axis tilt series reconstruction with prior knowledge. • The computational efficiency is validated on an experimentally measured tilt series
Nakayama, Hiromasa
2006-01-01
We give an algorithm to compute the local $b$ function. In this algorithm, we use the Mora division algorithm in the ring of differential operators and an approximate division algorithm in the ring of differential operators with power series coefficient.
Parallel algorithms and architecture for computation of manipulator forward dynamics
Fijany, Amir; Bejczy, Antal K.
1989-01-01
Parallel computation of manipulator forward dynamics is investigated. Considering three classes of algorithms for the solution of the problem, that is, the O(n), the O(n exp 2), and the O(n exp 3) algorithms, parallelism in the problem is analyzed. It is shown that the problem belongs to the class of NC and that the time and processors bounds are of O(log2/2n) and O(n exp 4), respectively. However, the fastest stable parallel algorithms achieve the computation time of O(n) and can be derived by parallelization of the O(n exp 3) serial algorithms. Parallel computation of the O(n exp 3) algorithms requires the development of parallel algorithms for a set of fundamentally different problems, that is, the Newton-Euler formulation, the computation of the inertia matrix, decomposition of the symmetric, positive definite matrix, and the solution of triangular systems. Parallel algorithms for this set of problems are developed which can be efficiently implemented on a unique architecture, a triangular array of n(n+2)/2 processors with a simple nearest-neighbor interconnection. This architecture is particularly suitable for VLSI and WSI implementations. The developed parallel algorithm, compared to the best serial O(n) algorithm, achieves an asymptotic speedup of more than two orders-of-magnitude in the computation the forward dynamics.
Advances in multi-sensor data fusion: algorithms and applications.
Dong, Jiang; Zhuang, Dafang; Huang, Yaohuan; Fu, Jingying
2009-01-01
With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of "algorithm fusion" methods; (3) Establishment of an automatic quality assessment scheme.
Advances and challenges in computational plasma science
International Nuclear Information System (INIS)
Tang, W M; Chan, V S
2005-01-01
Scientific simulation, which provides a natural bridge between theory and experiment, is an essential tool for understanding complex plasma behaviour. Recent advances in simulations of magnetically confined plasmas are reviewed in this paper, with illustrative examples, chosen from associated research areas such as microturbulence, magnetohydrodynamics and other topics. Progress has been stimulated, in particular, by the exponential growth of computer speed along with significant improvements in computer technology. The advances in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics have produced increasingly good agreement between experimental observations and computational modelling. This was enabled by two key factors: (a) innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning widely disparate temporal and spatial scales and (b) access to powerful new computational resources. Excellent progress has been made in developing codes for which computer run-time and problem-size scale well with the number of processors on massively parallel processors (MPPs). Examples include the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPPs to produce three-dimensional, general geometry, nonlinear particle simulations that have accelerated advances in understanding the nature of turbulence self-regulation by zonal flows. These calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In looking towards the future, the current results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. This
Once upon an algorithm how stories explain computing
Erwig, Martin
2017-01-01
How Hansel and Gretel, Sherlock Holmes, the movie Groundhog Day, Harry Potter, and other familiar stories illustrate the concepts of computing. Picture a computer scientist, staring at a screen and clicking away frantically on a keyboard, hacking into a system, or perhaps developing an app. Now delete that picture. In Once Upon an Algorithm, Martin Erwig explains computation as something that takes place beyond electronic computers, and computer science as the study of systematic problem solving. Erwig points out that many daily activities involve problem solving. Getting up in the morning, for example: You get up, take a shower, get dressed, eat breakfast. This simple daily routine solves a recurring problem through a series of well-defined steps. In computer science, such a routine is called an algorithm. Erwig illustrates a series of concepts in computing with examples from daily life and familiar stories. Hansel and Gretel, for example, execute an algorithm to get home from the forest. The movie Groundho...
B ampersand W PWR advanced control system algorithm development
International Nuclear Information System (INIS)
Winks, R.W.; Wilson, T.L.; Amick, M.
1992-01-01
This paper discusses algorithm development of an Advanced Control System for the B ampersand W Pressurized Water Reactor (PWR) nuclear power plant. The paper summarizes the history of the project, describes the operation of the algorithm, and presents transient results from a simulation of the plant and control system. The history discusses the steps in the development process and the roles played by the utility owners, B ampersand W Nuclear Service Company (BWNS), Oak Ridge National Laboratory (ORNL), and the Foxboro Company. The algorithm description is a brief overview of the features of the control system. The transient results show that operation of the algorithm in a normal power maneuvering mode and in a moderately large upset following a feedwater pump trip
A Visualization Review of Cloud Computing Algorithms in the Last Decade
Directory of Open Access Journals (Sweden)
Junhu Ruan
2016-10-01
Full Text Available Cloud computing has competitive advantages—such as on-demand self-service, rapid computing, cost reduction, and almost unlimited storage—that have attracted extensive attention from both academia and industry in recent years. Some review works have been reported to summarize extant studies related to cloud computing, but few analyze these studies based on the citations. Co-citation analysis can provide scholars a strong support to identify the intellectual bases and leading edges of a specific field. In addition, advanced algorithms, which can directly affect the availability, efficiency, and security of cloud computing, are the key to conducting computing across various clouds. Motivated by these observations, we conduct a specific visualization review of the studies related to cloud computing algorithms using one mainstream co-citation analysis tool—CiteSpace. The visualization results detect the most influential studies, journals, countries, institutions, and authors on cloud computing algorithms and reveal the intellectual bases and focuses of cloud computing algorithms in the literature, providing guidance for interested researchers to make further studies on cloud computing algorithms.
Scientific Discovery through Advanced Computing in Plasma Science
Tang, William
2005-03-01
Advanced computing is generally recognized to be an increasingly vital tool for accelerating progress in scientific research during the 21st Century. For example, the Department of Energy's ``Scientific Discovery through Advanced Computing'' (SciDAC) Program was motivated in large measure by the fact that formidable scientific challenges in its research portfolio could best be addressed by utilizing the combination of the rapid advances in super-computing technology together with the emergence of effective new algorithms and computational methodologies. The imperative is to translate such progress into corresponding increases in the performance of the scientific codes used to model complex physical systems such as those encountered in high temperature plasma research. If properly validated against experimental measurements and analytic benchmarks, these codes can provide reliable predictive capability for the behavior of a broad range of complex natural and engineered systems. This talk reviews recent progress and future directions for advanced simulations with some illustrative examples taken from the plasma science applications area. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by the combination of access to powerful new computational resources together with innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning a huge range in time and space scales. In particular, the plasma science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop (multi-trillion floating point computations
Computation of Asteroid Proper Elements: Recent Advances
Knežević, Z.
2017-12-01
The recent advances in computation of asteroid proper elements are briefly reviewed. Although not representing real breakthroughs in computation and stability assessment of proper elements, these advances can still be considered as important improvements offering solutions to some practical problems encountered in the past. The problem of getting unrealistic values of perihelion frequency for very low eccentricity orbits is solved by computing frequencies using the frequency-modified Fourier transform. The synthetic resonant proper elements adjusted to a given secular resonance helped to prove the existence of Astraea asteroid family. The preliminary assessment of stability with time of proper elements computed by means of the analytical theory provides a good indication of their poorer performance with respect to their synthetic counterparts, and advocates in favor of ceasing their regular maintenance; the final decision should, however, be taken on the basis of more comprehensive and reliable direct estimate of their individual and sample average deviations from constancy.
Advances and Challenges in Computational Plasma Science
International Nuclear Information System (INIS)
Tang, W.M.; Chan, V.S.
2005-01-01
Scientific simulation, which provides a natural bridge between theory and experiment, is an essential tool for understanding complex plasma behavior. Recent advances in simulations of magnetically-confined plasmas are reviewed in this paper with illustrative examples chosen from associated research areas such as microturbulence, magnetohydrodynamics, and other topics. Progress has been stimulated in particular by the exponential growth of computer speed along with significant improvements in computer technology
Preface (to: Advances in Computer Entertainment)
Romão, Teresa; Nijholt, Antinus; Romão, Teresa; Reidsma, Dennis
2012-01-01
These are the proceedings of the 9th International Conference on Advances in Computer Entertainment ACE 2012). ACE has become the leading scientific forum for dissemination of cutting-edge research results in the area of entertainment computing. Interactive entertainment is one of the most vibrant areas of interest in modern society and is amongst the fastest growing industries in the world. ACE 2012 will bring together leading researchers and practitioners from academia and industry to prese...
Advanced computational electromagnetic methods and applications
Li, Wenxing; Elsherbeni, Atef; Rahmat-Samii, Yahya
2015-01-01
This new resource covers the latest developments in computational electromagnetic methods, with emphasis on cutting-edge applications. This book is designed to extend existing literature to the latest development in computational electromagnetic methods, which are of interest to readers in both academic and industrial areas. The topics include advanced techniques in MoM, FEM and FDTD, spectral domain method, GPU and Phi hardware acceleration, metamaterials, frequency and time domain integral equations, and statistics methods in bio-electromagnetics.
A Novel Clustering Algorithm Inspired by Membrane Computing
Directory of Open Access Journals (Sweden)
Hong Peng
2015-01-01
Full Text Available P systems are a class of distributed parallel computing models; this paper presents a novel clustering algorithm, which is inspired from mechanism of a tissue-like P system with a loop structure of cells, called membrane clustering algorithm. The objects of the cells express the candidate centers of clusters and are evolved by the evolution rules. Based on the loop membrane structure, the communication rules realize a local neighborhood topology, which helps the coevolution of the objects and improves the diversity of objects in the system. The tissue-like P system can effectively search for the optimal partitioning with the help of its parallel computing advantage. The proposed clustering algorithm is evaluated on four artificial data sets and six real-life data sets. Experimental results show that the proposed clustering algorithm is superior or competitive to k-means algorithm and several evolutionary clustering algorithms recently reported in the literature.
Computationally efficient optimisation algorithms for WECs arrays
DEFF Research Database (Denmark)
Ferri, Francesco
2017-01-01
In this paper two derivative-free global optimization algorithms are applied for the maximisation of the energy absorbed by wave energy converter (WEC) arrays. Wave energy is a large and mostly untapped source of energy that could have a key role in the future energy mix. The collection of this r...
A fast algorithm for sparse matrix computations related to inversion
International Nuclear Information System (INIS)
Li, S.; Wu, W.; Darve, E.
2013-01-01
We have developed a fast algorithm for computing certain entries of the inverse of a sparse matrix. Such computations are critical to many applications, such as the calculation of non-equilibrium Green’s functions G r and G for nano-devices. The FIND (Fast Inverse using Nested Dissection) algorithm is optimal in the big-O sense. However, in practice, FIND suffers from two problems due to the width-2 separators used by its partitioning scheme. One problem is the presence of a large constant factor in the computational cost of FIND. The other problem is that the partitioning scheme used by FIND is incompatible with most existing partitioning methods and libraries for nested dissection, which all use width-1 separators. Our new algorithm resolves these problems by thoroughly decomposing the computation process such that width-1 separators can be used, resulting in a significant speedup over FIND for realistic devices — up to twelve-fold in simulation. The new algorithm also has the added advantage that desired off-diagonal entries can be computed for free. Consequently, our algorithm is faster than the current state-of-the-art recursive methods for meshes of any size. Furthermore, the framework used in the analysis of our algorithm is the first attempt to explicitly apply the widely-used relationship between mesh nodes and matrix computations to the problem of multiple eliminations with reuse of intermediate results. This framework makes our algorithm easier to generalize, and also easier to compare against other methods related to elimination trees. Finally, our accuracy analysis shows that the algorithms that require back-substitution are subject to significant extra round-off errors, which become extremely large even for some well-conditioned matrices or matrices with only moderately large condition numbers. When compared to these back-substitution algorithms, our algorithm is generally a few orders of magnitude more accurate, and our produced round-off errors
Parallel algorithms for computation of the manipulator inertia matrix
Amin-Javaheri, Masoud; Orin, David E.
1989-01-01
The development of an O(log2N) parallel algorithm for the manipulator inertia matrix is presented. It is based on the most efficient serial algorithm which uses the composite rigid body method. Recursive doubling is used to reformulate the linear recurrence equations which are required to compute the diagonal elements of the matrix. It results in O(log2N) levels of computation. Computation of the off-diagonal elements involves N linear recurrences of varying-size and a new method, which avoids redundant computation of position and orientation transforms for the manipulator, is developed. The O(log2N) algorithm is presented in both equation and graphic forms which clearly show the parallelism inherent in the algorithm.
A general algorithm for computing distance transforms in linear time
Meijster, A.; Roerdink, J.B.T.M.; Hesselink, W.H.; Goutsias, J; Vincent, L; Bloomberg, DS
2000-01-01
A new general algorithm fur computing distance transforms of digital images is presented. The algorithm consists of two phases. Both phases consist of two scans, a forward and a backward scan. The first phase scans the image column-wise, while the second phase scans the image row-wise. Since the
A Novel Parallel Algorithm for Edit Distance Computation
Directory of Open Access Journals (Sweden)
Muhammad Murtaza Yousaf
2018-01-01
Full Text Available The edit distance between two sequences is the minimum number of weighted transformation-operations that are required to transform one string into the other. The weighted transformation-operations are insert, remove, and substitute. Dynamic programming solution to find edit distance exists but it becomes computationally intensive when the lengths of strings become very large. This work presents a novel parallel algorithm to solve edit distance problem of string matching. The algorithm is based on resolving dependencies in the dynamic programming solution of the problem and it is able to compute each row of edit distance table in parallel. In this way, it becomes possible to compute the complete table in min(m,n iterations for strings of size m and n whereas state-of-the-art parallel algorithm solves the problem in max(m,n iterations. The proposed algorithm also increases the amount of parallelism in each of its iteration. The algorithm is also capable of exploiting spatial locality while its implementation. Additionally, the algorithm works in a load balanced way that further improves its performance. The algorithm is implemented for multicore systems having shared memory. Implementation of the algorithm in OpenMP shows linear speedup and better execution time as compared to state-of-the-art parallel approach. Efficiency of the algorithm is also proven better in comparison to its competitor.
Computational Intelligence Paradigms in Advanced Pattern Classification
Jain, Lakhmi
2012-01-01
This monograph presents selected areas of application of pattern recognition and classification approaches including handwriting recognition, medical image analysis and interpretation, development of cognitive systems for image computer understanding, moving object detection, advanced image filtration and intelligent multi-object labelling and classification. It is directed to the scientists, application engineers, professors, professors and students will find this book useful.
Enabling high performance computational science through combinatorial algorithms
International Nuclear Information System (INIS)
Boman, Erik G; Bozdag, Doruk; Catalyurek, Umit V; Devine, Karen D; Gebremedhin, Assefaw H; Hovland, Paul D; Pothen, Alex; Strout, Michelle Mills
2007-01-01
The Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute is developing algorithms and software for combinatorial problems that play an enabling role in scientific and engineering computations. Discrete algorithms will be increasingly critical for achieving high performance for irregular problems on petascale architectures. This paper describes recent contributions by researchers at the CSCAPES Institute in the areas of load balancing, parallel graph coloring, performance improvement, and parallel automatic differentiation
Enabling high performance computational science through combinatorial algorithms
Energy Technology Data Exchange (ETDEWEB)
Boman, Erik G [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Bozdag, Doruk [Biomedical Informatics, and Electrical and Computer Engineering, Ohio State University (United States); Catalyurek, Umit V [Biomedical Informatics, and Electrical and Computer Engineering, Ohio State University (United States); Devine, Karen D [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Gebremedhin, Assefaw H [Computer Science and Center for Computational Science, Old Dominion University (United States); Hovland, Paul D [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Pothen, Alex [Computer Science and Center for Computational Science, Old Dominion University (United States); Strout, Michelle Mills [Computer Science, Colorado State University (United States)
2007-07-15
The Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute is developing algorithms and software for combinatorial problems that play an enabling role in scientific and engineering computations. Discrete algorithms will be increasingly critical for achieving high performance for irregular problems on petascale architectures. This paper describes recent contributions by researchers at the CSCAPES Institute in the areas of load balancing, parallel graph coloring, performance improvement, and parallel automatic differentiation.
Industrial Computed Tomography using Proximal Algorithm
Zang, Guangming
2016-04-14
In this thesis, we present ProxiSART, a flexible proximal framework for robust 3D cone beam tomographic reconstruction based on the Simultaneous Algebraic Reconstruction Technique (SART). We derive the proximal operator for the SART algorithm and use it for minimizing the data term in a proximal algorithm. We show the flexibility of the framework by plugging in different powerful regularizers, and show its robustness in achieving better reconstruction results in the presence of noise and using fewer projections. We compare our framework to state-of-the-art methods and existing popular software tomography reconstruction packages, on both synthetic and real datasets, and show superior reconstruction quality, especially from noisy data and a small number of projections.
Computer-aided FTA comprehensive algorithm
International Nuclear Information System (INIS)
Liu Jingcheng; Zhang Yuhua; Tai Yachuan.
1986-01-01
Comprehenive Algorithm uses the method of combining Liao Jionsheng's FTA new way with Fussell's top-down way, coordinates noncoherent FTA with coherent FTA and is fitted with digigital simulation method. It can solve either cohernt FT or noncoherent FT, either stable state problem or dynamic state problem, either MCS (MPS) or PIS. It can calculate either the probability or the distribution of top events and also the probability and the importance of basic events
Accelerating the XGBoost algorithm using GPU computing
Directory of Open Access Journals (Sweden)
Rory Mitchell
2017-07-01
Full Text Available We present a CUDA-based implementation of a decision tree construction algorithm within the gradient boosting library XGBoost. The tree construction algorithm is executed entirely on the graphics processing unit (GPU and shows high performance with a variety of datasets and settings, including sparse input matrices. Individual boosting iterations are parallelised, combining two approaches. An interleaved approach is used for shallow trees, switching to a more conventional radix sort-based approach for larger depths. We show speedups of between 3× and 6× using a Titan X compared to a 4 core i7 CPU, and 1.2× using a Titan X compared to 2× Xeon CPUs (24 cores. We show that it is possible to process the Higgs dataset (10 million instances, 28 features entirely within GPU memory. The algorithm is made available as a plug-in within the XGBoost library and fully supports all XGBoost features including classification, regression and ranking tasks.
NATO Advanced Study Institute on Methods in Computational Molecular Physics
Diercksen, Geerd
1992-01-01
This volume records the lectures given at a NATO Advanced Study Institute on Methods in Computational Molecular Physics held in Bad Windsheim, Germany, from 22nd July until 2nd. August, 1991. This NATO Advanced Study Institute sought to bridge the quite considerable gap which exist between the presentation of molecular electronic structure theory found in contemporary monographs such as, for example, McWeeny's Methods 0/ Molecular Quantum Mechanics (Academic Press, London, 1989) or Wilson's Electron correlation in moleeules (Clarendon Press, Oxford, 1984) and the realization of the sophisticated computational algorithms required for their practical application. It sought to underline the relation between the electronic structure problem and the study of nuc1ear motion. Software for performing molecular electronic structure calculations is now being applied in an increasingly wide range of fields in both the academic and the commercial sectors. Numerous applications are reported in areas as diverse as catalysi...
Advanced soft computing diagnosis method for tumour grading.
Papageorgiou, E I; Spyridonos, P P; Stylios, C D; Ravazoula, P; Groumpos, P P; Nikiforidis, G N
2006-01-01
To develop an advanced diagnostic method for urinary bladder tumour grading. A novel soft computing modelling methodology based on the augmentation of fuzzy cognitive maps (FCMs) with the unsupervised active Hebbian learning (AHL) algorithm is applied. One hundred and twenty-eight cases of urinary bladder cancer were retrieved from the archives of the Department of Histopathology, University Hospital of Patras, Greece. All tumours had been characterized according to the classical World Health Organization (WHO) grading system. To design the FCM model for tumour grading, three experts histopathologists defined the main histopathological features (concepts) and their impact on grade characterization. The resulted FCM model consisted of nine concepts. Eight concepts represented the main histopathological features for tumour grading. The ninth concept represented the tumour grade. To increase the classification ability of the FCM model, the AHL algorithm was applied to adjust the weights of the FCM. The proposed FCM grading model achieved a classification accuracy of 72.5%, 74.42% and 95.55% for tumours of grades I, II and III, respectively. An advanced computerized method to support tumour grade diagnosis decision was proposed and developed. The novelty of the method is based on employing the soft computing method of FCMs to represent specialized knowledge on histopathology and on augmenting FCMs ability using an unsupervised learning algorithm, the AHL. The proposed method performs with reasonably high accuracy compared to other existing methods and at the same time meets the physicians' requirements for transparency and explicability.
Advanced defect detection algorithm using clustering in ultrasonic NDE
Gongzhang, Rui; Gachagan, Anthony
2016-02-01
A range of materials used in industry exhibit scattering properties which limits ultrasonic NDE. Many algorithms have been proposed to enhance defect detection ability, such as the well-known Split Spectrum Processing (SSP) technique. Scattering noise usually cannot be fully removed and the remaining noise can be easily confused with real feature signals, hence becoming artefacts during the image interpretation stage. This paper presents an advanced algorithm to further reduce the influence of artefacts remaining in A-scan data after processing using a conventional defect detection algorithm. The raw A-scan data can be acquired from either traditional single transducer or phased array configurations. The proposed algorithm uses the concept of unsupervised machine learning to cluster segmental defect signals from pre-processed A-scans into different classes. The distinction and similarity between each class and the ensemble of randomly selected noise segments can be observed by applying a classification algorithm. Each class will then be labelled as `legitimate reflector' or `artefacts' based on this observation and the expected probability of defection (PoD) and probability of false alarm (PFA) determined. To facilitate data collection and validate the proposed algorithm, a 5MHz linear array transducer is used to collect A-scans from both austenitic steel and Inconel samples. Each pulse-echo A-scan is pre-processed using SSP and the subsequent application of the proposed clustering algorithm has provided an additional reduction to PFA while maintaining PoD for both samples compared with SSP results alone.
A computational fluid dynamics algorithm on a massively parallel computer
International Nuclear Information System (INIS)
Jespersen, D.C.; Levit, C.
1989-01-01
The implementation and performance of a finite-difference algorithm for the compressible Navier-Stokes equations in two or three dimensions on the Connection Machine are described. This machine is a single-instruction multiple-data machine with up to 65536 physical processors. The implicit portion of the algorithm is of particular interest. Running times and megadrop rates are given for two- and three-dimensional problems. Included are comparisons with the standard codes on a Cray X-MP/48. 15 refs
Fault-tolerant search algorithms reliable computation with unreliable information
Cicalese, Ferdinando
2013-01-01
Why a book on fault-tolerant search algorithms? Searching is one of the fundamental problems in computer science. Time and again algorithmic and combinatorial issues originally studied in the context of search find application in the most diverse areas of computer science and discrete mathematics. On the other hand, fault-tolerance is a necessary ingredient of computing. Due to their inherent complexity, information systems are naturally prone to errors, which may appear at any level - as imprecisions in the data, bugs in the software, or transient or permanent hardware failures. This book pr
Algorithm development for Maxwell's equations for computational electromagnetism
Goorjian, Peter M.
1990-01-01
A new algorithm has been developed for solving Maxwell's equations for the electromagnetic field. It solves the equations in the time domain with central, finite differences. The time advancement is performed implicitly, using an alternating direction implicit procedure. The space discretization is performed with finite volumes, using curvilinear coordinates with electromagnetic components along those directions. Sample calculations are presented of scattering from a metal pin, a square and a circle to demonstrate the capabilities of the new algorithm.
Time reversibility, computer simulation, algorithms, chaos
Hoover, William Graham
2012-01-01
A small army of physicists, chemists, mathematicians, and engineers has joined forces to attack a classic problem, the "reversibility paradox", with modern tools. This book describes their work from the perspective of computer simulation, emphasizing the author's approach to the problem of understanding the compatibility, and even inevitability, of the irreversible second law of thermodynamics with an underlying time-reversible mechanics. Computer simulation has made it possible to probe reversibility from a variety of directions and "chaos theory" or "nonlinear dynamics" has supplied a useful vocabulary and a set of concepts, which allow a fuller explanation of irreversibility than that available to Boltzmann or to Green, Kubo and Onsager. Clear illustration of concepts is emphasized throughout, and reinforced with a glossary of technical terms from the specialized fields which have been combined here to focus on a common theme. The book begins with a discussion, contrasting the idealized reversibility of ba...
Advances in computers improving the web
Zelkowitz, Marvin
2010-01-01
This is volume 78 of Advances in Computers. This series, which began publication in 1960, is the oldest continuously published anthology that chronicles the ever- changing information technology field. In these volumes we publish from 5 to 7 chapters, three times per year, that cover the latest changes to the design, development, use and implications of computer technology on society today.Covers the full breadth of innovations in hardware, software, theory, design, and applications.Many of the in-depth reviews have become standard references that continue to be of significant, lasting value i
Advanced computational approaches to biomedical engineering
Saha, Punam K; Basu, Subhadip
2014-01-01
There has been rapid growth in biomedical engineering in recent decades, given advancements in medical imaging and physiological modelling and sensing systems, coupled with immense growth in computational and network technology, analytic approaches, visualization and virtual-reality, man-machine interaction and automation. Biomedical engineering involves applying engineering principles to the medical and biological sciences and it comprises several topics including biomedicine, medical imaging, physiological modelling and sensing, instrumentation, real-time systems, automation and control, sig
Research Institute for Advanced Computer Science
Gross, Anthony R. (Technical Monitor); Leiner, Barry M.
2000-01-01
The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth; (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking. Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a
Practical algorithms for 3D computer graphics
Ferguson, R Stuart
2013-01-01
""A valuable book to accompany any course that mixes the theory and practice of 3D graphics. The book's web site has many useful programs and code samples.""-Karen Rafferty, Queen's University, Belfast""The topics covered by this book are backed by the OpenFX modeling and animation software. This is a big plus in that it provides a practical perspective and encourages experimentation. … [This] will offer students a more interesting and hands-on learning experience, especially for those wishing to pursue a career in computer game development.""-Naganand Madhavapeddy, GameDeveloper>
Gradient Learning Algorithms for Ontology Computing
Gao, Wei; Zhu, Linli
2014-01-01
The gradient learning model has been raising great attention in view of its promising perspectives for applications in statistics, data dimensionality reducing, and other specific fields. In this paper, we raise a new gradient learning model for ontology similarity measuring and ontology mapping in multidividing setting. The sample error in this setting is given by virtue of the hypothesis space and the trick of ontology dividing operator. Finally, two experiments presented on plant and humanoid robotics field verify the efficiency of the new computation model for ontology similarity measure and ontology mapping applications in multidividing setting. PMID:25530752
Gradient Learning Algorithms for Ontology Computing
Directory of Open Access Journals (Sweden)
Wei Gao
2014-01-01
Full Text Available The gradient learning model has been raising great attention in view of its promising perspectives for applications in statistics, data dimensionality reducing, and other specific fields. In this paper, we raise a new gradient learning model for ontology similarity measuring and ontology mapping in multidividing setting. The sample error in this setting is given by virtue of the hypothesis space and the trick of ontology dividing operator. Finally, two experiments presented on plant and humanoid robotics field verify the efficiency of the new computation model for ontology similarity measure and ontology mapping applications in multidividing setting.
Indian Academy of Sciences (India)
ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...
Computational Tools and Algorithms for Designing Customized Synthetic Genes
Directory of Open Access Journals (Sweden)
Nathan eGould
2014-10-01
Full Text Available Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de-novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.
Computational Tools and Algorithms for Designing Customized Synthetic Genes
Energy Technology Data Exchange (ETDEWEB)
Gould, Nathan [Department of Computer Science, The College of New Jersey, Ewing, NJ (United States); Hendy, Oliver [Department of Biology, The College of New Jersey, Ewing, NJ (United States); Papamichail, Dimitris, E-mail: papamicd@tcnj.edu [Department of Computer Science, The College of New Jersey, Ewing, NJ (United States)
2014-10-06
Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.
Computational Tools and Algorithms for Designing Customized Synthetic Genes
International Nuclear Information System (INIS)
Gould, Nathan; Hendy, Oliver; Papamichail, Dimitris
2014-01-01
Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.
GLOA: A New Job Scheduling Algorithm for Grid Computing
Directory of Open Access Journals (Sweden)
Zahra Pooranian
2013-03-01
Full Text Available The purpose of grid computing is to produce a virtual supercomputer by using free resources available through widespread networks such as the Internet. This resource distribution, changes in resource availability, and an unreliable communication infrastructure pose a major challenge for efficient resource allocation. Because of the geographical spread of resources and their distributed management, grid scheduling is considered to be a NP-complete problem. It has been shown that evolutionary algorithms offer good performance for grid scheduling. This article uses a new evaluation (distributed algorithm inspired by the effect of leaders in social groups, the group leaders' optimization algorithm (GLOA, to solve the problem of scheduling independent tasks in a grid computing system. Simulation results comparing GLOA with several other evaluation algorithms show that GLOA produces shorter makespans.
Advanced Computational Methods in Bio-Mechanics.
Al Qahtani, Waleed M S; El-Anwar, Mohamed I
2018-04-15
A novel partnership between surgeons and machines, made possible by advances in computing and engineering technology, could overcome many of the limitations of traditional surgery. By extending surgeons' ability to plan and carry out surgical interventions more accurately and with fewer traumas, computer-integrated surgery (CIS) systems could help to improve clinical outcomes and the efficiency of healthcare delivery. CIS systems could have a similar impact on surgery to that long since realised in computer-integrated manufacturing. Mathematical modelling and computer simulation have proved tremendously successful in engineering. Computational mechanics has enabled technological developments in virtually every area of our lives. One of the greatest challenges for mechanists is to extend the success of computational mechanics to fields outside traditional engineering, in particular to biology, the biomedical sciences, and medicine. Biomechanics has significant potential for applications in orthopaedic industry, and the performance arts since skills needed for these activities are visibly related to the human musculoskeletal and nervous systems. Although biomechanics is widely used nowadays in the orthopaedic industry to design orthopaedic implants for human joints, dental parts, external fixations and other medical purposes, numerous researches funded by billions of dollars are still running to build a new future for sports and human healthcare in what is called biomechanics era.
An Algorithm for Computing Screened Coulomb Scattering in Geant4
Mendenhall, Marcus H.; Weller, Robert A.
2004-01-01
An algorithm has been developed for the Geant4 Monte-Carlo package for the efficient computation of screened Coulomb interatomic scattering. It explicitly integrates the classical equations of motion for scattering events, resulting in precise tracking of both the projectile and the recoil target nucleus. The algorithm permits the user to plug in an arbitrary screening function, such as Lens-Jensen screening, which is good for backscattering calculations, or Ziegler-Biersack-Littmark screenin...
UNEDF: Advanced Scientific Computing Transforms the Low-Energy Nuclear Many-Body Problem
International Nuclear Information System (INIS)
Stoitsov, Mario; Nam, Hai Ah; Nazarewicz, Witold; Bulgac, Aurel; Hagen, Gaute; Kortelainen, E.M.; Pei, Junchen; Roche, K.J.; Schunck, N.; Thompson, I.; Vary, J.P.; Wild, S.
2011-01-01
The UNEDF SciDAC collaboration of nuclear theorists, applied mathematicians, and computer scientists is developing a comprehensive description of nuclei and their reactions that delivers maximum predictive power with quantified uncertainties. This paper illustrates significant milestones accomplished by UNEDF through integration of the theoretical approaches, advanced numerical algorithms, and leadership class computational resources.
Cloud Computing Task Scheduling Based on Cultural Genetic Algorithm
Directory of Open Access Journals (Sweden)
Li Jian-Wen
2016-01-01
Full Text Available The task scheduling strategy based on cultural genetic algorithm(CGA is proposed in order to improve the efficiency of task scheduling in the cloud computing platform, which targets at minimizing the total time and cost of task scheduling. The improved genetic algorithm is used to construct the main population space and knowledge space under cultural framework which get independent parallel evolution, forming a mechanism of mutual promotion to dispatch the cloud task. Simultaneously, in order to prevent the defects of the genetic algorithm which is easy to fall into local optimum, the non-uniform mutation operator is introduced to improve the search performance of the algorithm. The experimental results show that CGA reduces the total time and lowers the cost of the scheduling, which is an effective algorithm for the cloud task scheduling.
Parallel grid generation algorithm for distributed memory computers
Moitra, Stuti; Moitra, Anutosh
1994-01-01
A parallel grid-generation algorithm and its implementation on the Intel iPSC/860 computer are described. The grid-generation scheme is based on an algebraic formulation of homotopic relations. Methods for utilizing the inherent parallelism of the grid-generation scheme are described, and implementation of multiple levELs of parallelism on multiple instruction multiple data machines are indicated. The algorithm is capable of providing near orthogonality and spacing control at solid boundaries while requiring minimal interprocessor communications. Results obtained on the Intel hypercube for a blended wing-body configuration are used to demonstrate the effectiveness of the algorithm. Fortran implementations bAsed on the native programming model of the iPSC/860 computer and the Express system of software tools are reported. Computational gains in execution time speed-up ratios are given.
Condition Monitoring Through Advanced Sensor and Computational Technology
International Nuclear Information System (INIS)
Kim, Jung Taek; Park, Won Man; Kim, Jung Soo; Seong, Soeng Hwan; Hur, Sub; Cho, Jae Hwan; Jung, Hyung Gue
2005-05-01
The overall goal of this joint research project was to develop and demonstrate advanced sensors and computational technology for continuous monitoring of the condition of components, structures, and systems in advanced and next-generation nuclear power plants (NPPs). This project included investigating and adapting several advanced sensor technologies from Korean and US national laboratory research communities, some of which were developed and applied in non-nuclear industries. The project team investigated and developed sophisticated signal processing, noise reduction, and pattern recognition techniques and algorithms. The researchers installed sensors and conducted condition monitoring tests on two test loops, a check valve (an active component) and a piping elbow (a passive component), to demonstrate the feasibility of using advanced sensors and computational technology to achieve the project goal. Acoustic emission (AE) devices, optical fiber sensors, accelerometers, and ultrasonic transducers (UTs) were used to detect mechanical vibratory response of check valve and piping elbow in normal and degraded configurations. Chemical sensors were also installed to monitor the water chemistry in the piping elbow test loop. Analysis results of processed sensor data indicate that it is feasible to differentiate between the normal and degraded (with selected degradation mechanisms) configurations of these two components from the acquired sensor signals, but it is questionable that these methods can reliably identify the level and type of degradation. Additional research and development efforts are needed to refine the differentiation techniques and to reduce the level of uncertainties
A fast algorithm for sparse matrix computations related to inversion
Energy Technology Data Exchange (ETDEWEB)
Li, S., E-mail: lisong@stanford.edu [Institute for Computational and Mathematical Engineering, Stanford University, 496 Lomita Mall, Durand Building, Stanford, CA 94305 (United States); Wu, W. [Department of Electrical Engineering, Stanford University, 350 Serra Mall, Packard Building, Room 268, Stanford, CA 94305 (United States); Darve, E. [Institute for Computational and Mathematical Engineering, Stanford University, 496 Lomita Mall, Durand Building, Stanford, CA 94305 (United States); Department of Mechanical Engineering, Stanford University, 496 Lomita Mall, Durand Building, Room 209, Stanford, CA 94305 (United States)
2013-06-01
We have developed a fast algorithm for computing certain entries of the inverse of a sparse matrix. Such computations are critical to many applications, such as the calculation of non-equilibrium Green’s functions G{sup r} and G{sup <} for nano-devices. The FIND (Fast Inverse using Nested Dissection) algorithm is optimal in the big-O sense. However, in practice, FIND suffers from two problems due to the width-2 separators used by its partitioning scheme. One problem is the presence of a large constant factor in the computational cost of FIND. The other problem is that the partitioning scheme used by FIND is incompatible with most existing partitioning methods and libraries for nested dissection, which all use width-1 separators. Our new algorithm resolves these problems by thoroughly decomposing the computation process such that width-1 separators can be used, resulting in a significant speedup over FIND for realistic devices — up to twelve-fold in simulation. The new algorithm also has the added advantage that desired off-diagonal entries can be computed for free. Consequently, our algorithm is faster than the current state-of-the-art recursive methods for meshes of any size. Furthermore, the framework used in the analysis of our algorithm is the first attempt to explicitly apply the widely-used relationship between mesh nodes and matrix computations to the problem of multiple eliminations with reuse of intermediate results. This framework makes our algorithm easier to generalize, and also easier to compare against other methods related to elimination trees. Finally, our accuracy analysis shows that the algorithms that require back-substitution are subject to significant extra round-off errors, which become extremely large even for some well-conditioned matrices or matrices with only moderately large condition numbers. When compared to these back-substitution algorithms, our algorithm is generally a few orders of magnitude more accurate, and our produced round
VIRTEX-5 Fpga Implementation of Advanced Encryption Standard Algorithm
Rais, Muhammad H.; Qasim, Syed M.
2010-06-01
In this paper, we present an implementation of Advanced Encryption Standard (AES) cryptographic algorithm using state-of-the-art Virtex-5 Field Programmable Gate Array (FPGA). The design is coded in Very High Speed Integrated Circuit Hardware Description Language (VHDL). Timing simulation is performed to verify the functionality of the designed circuit. Performance evaluation is also done in terms of throughput and area. The design implemented on Virtex-5 (XC5VLX50FFG676-3) FPGA achieves a maximum throughput of 4.34 Gbps utilizing a total of 399 slices.
Quantum computation with classical light: The Deutsch Algorithm
International Nuclear Information System (INIS)
Perez-Garcia, Benjamin; Francis, Jason; McLaren, Melanie; Hernandez-Aranda, Raul I.; Forbes, Andrew; Konrad, Thomas
2015-01-01
We present an implementation of the Deutsch Algorithm using linear optical elements and laser light. We encoded two quantum bits in form of superpositions of electromagnetic fields in two degrees of freedom of the beam: its polarisation and orbital angular momentum. Our approach, based on a Sagnac interferometer, offers outstanding stability and demonstrates that optical quantum computation is possible using classical states of light. - Highlights: • We implement the Deutsh Algorithm using linear optical elements and classical light. • Our qubits are encoded in the polarisation and orbital angular momentum of the beam. • We show that it is possible to achieve quantum computation with two qubits in the classical domain of light
Quantum computation with classical light: The Deutsch Algorithm
Energy Technology Data Exchange (ETDEWEB)
Perez-Garcia, Benjamin [Photonics and Mathematical Optics Group, Tecnológico de Monterrey, Monterrey 64849 (Mexico); University of the Witwatersrand, Private Bag 3, Johannesburg 2050 (South Africa); Francis, Jason [School of Chemistry and Physics, University of KwaZulu-Natal, Private Bag X54001, Durban 4000 (South Africa); McLaren, Melanie [University of the Witwatersrand, Private Bag 3, Johannesburg 2050 (South Africa); Hernandez-Aranda, Raul I. [Photonics and Mathematical Optics Group, Tecnológico de Monterrey, Monterrey 64849 (Mexico); Forbes, Andrew [University of the Witwatersrand, Private Bag 3, Johannesburg 2050 (South Africa); Konrad, Thomas, E-mail: konradt@ukzn.ac.za [School of Chemistry and Physics, University of KwaZulu-Natal, Private Bag X54001, Durban 4000 (South Africa); National Institute of Theoretical Physics, Durban Node, Private Bag X54001, Durban 4000 (South Africa)
2015-08-28
We present an implementation of the Deutsch Algorithm using linear optical elements and laser light. We encoded two quantum bits in form of superpositions of electromagnetic fields in two degrees of freedom of the beam: its polarisation and orbital angular momentum. Our approach, based on a Sagnac interferometer, offers outstanding stability and demonstrates that optical quantum computation is possible using classical states of light. - Highlights: • We implement the Deutsh Algorithm using linear optical elements and classical light. • Our qubits are encoded in the polarisation and orbital angular momentum of the beam. • We show that it is possible to achieve quantum computation with two qubits in the classical domain of light.
Advanced intelligent computational technologies and decision support systems
Kountchev, Roumen
2014-01-01
This book offers a state of the art collection covering themes related to Advanced Intelligent Computational Technologies and Decision Support Systems which can be applied to fields like healthcare assisting the humans in solving problems. The book brings forward a wealth of ideas, algorithms and case studies in themes like: intelligent predictive diagnosis; intelligent analyzing of medical images; new format for coding of single and sequences of medical images; Medical Decision Support Systems; diagnosis of Down’s syndrome; computational perspectives for electronic fetal monitoring; efficient compression of CT Images; adaptive interpolation and halftoning for medical images; applications of artificial neural networks for real-life problems solving; present and perspectives for Electronic Healthcare Record Systems; adaptive approaches for noise reduction in sequences of CT images etc.
Ojalehto, Vesa; Podkopaev, Dmitry; Miettinen, Kaisa
2015-01-01
We generalize the applicability of interactive methods for solving computationally demanding, that is, time-consuming, multiobjective optimization problems. For this purpose we propose a new agent assisted interactive algorithm. It employs a computationally inexpensive surrogate problem and four different agents that intelligently update the surrogate based on the preferences specified by a decision maker. In this way, we decrease the waiting times imposed on the decision maker du...
Computational Design of Advanced Nuclear Fuels
International Nuclear Information System (INIS)
Savrasov, Sergey; Kotliar, Gabriel; Haule, Kristjan
2014-01-01
The objective of the project was to develop a method for theoretical understanding of nuclear fuel materials whose physical and thermophysical properties can be predicted from first principles using a novel dynamical mean field method for electronic structure calculations. We concentrated our study on uranium, plutonium, their oxides, nitrides, carbides, as well as some rare earth materials whose 4f eletrons provide a simplified framework for understanding complex behavior of the f electrons. We addressed the issues connected to the electronic structure, lattice instabilities, phonon and magnon dynamics as well as thermal conductivity. This allowed us to evaluate characteristics of advanced nuclear fuel systems using computer based simulations and avoid costly experiments.
ATCA for Machines-- Advanced Telecommunications Computing Architecture
Energy Technology Data Exchange (ETDEWEB)
Larsen, R.S.; /SLAC
2008-04-22
The Advanced Telecommunications Computing Architecture is a new industry open standard for electronics instrument modules and shelves being evaluated for the International Linear Collider (ILC). It is the first industrial standard designed for High Availability (HA). ILC availability simulations have shown clearly that the capabilities of ATCA are needed in order to achieve acceptable integrated luminosity. The ATCA architecture looks attractive for beam instruments and detector applications as well. This paper provides an overview of ongoing R&D including application of HA principles to power electronics systems.
ATCA for Machines-- Advanced Telecommunications Computing Architecture
International Nuclear Information System (INIS)
Larsen, R
2008-01-01
The Advanced Telecommunications Computing Architecture is a new industry open standard for electronics instrument modules and shelves being evaluated for the International Linear Collider (ILC). It is the first industrial standard designed for High Availability (HA). ILC availability simulations have shown clearly that the capabilities of ATCA are needed in order to achieve acceptable integrated luminosity. The ATCA architecture looks attractive for beam instruments and detector applications as well. This paper provides an overview of ongoing R and D including application of HA principles to power electronics systems
Static Load Balancing Algorithms In Cloud Computing Challenges amp Solutions
Directory of Open Access Journals (Sweden)
Nadeem Shah
2015-08-01
Full Text Available Abstract Cloud computing provides on-demand hosted computing resources and services over the Internet on a pay-per-use basis. It is currently becoming the favored method of communication and computation over scalable networks due to numerous attractive attributes such as high availability scalability fault tolerance simplicity of management and low cost of ownership. Due to the huge demand of cloud computing efficient load balancing becomes critical to ensure that computational tasks are evenly distributed across servers to prevent bottlenecks. The aim of this review paper is to understand the current challenges in cloud computing primarily in cloud load balancing using static algorithms and finding gaps to bridge for more efficient static cloud load balancing in the future. We believe the ideas suggested as new solution will allow researchers to redesign better algorithms for better functionalities and improved user experiences in simple cloud systems. This could assist small businesses that cannot afford infrastructure that supports complex amp dynamic load balancing algorithms.
Fang, Wai-Chi; Alkalai, Leon
1996-01-01
Recent changes within NASA's space exploration program favor the design, implementation, and operation of low cost, lightweight, small and micro spacecraft with multiple launches per year. In order to meet the future needs of these missions with regard to the use of spacecraft microelectronics, NASA's advanced flight computing (AFC) program is currently considering industrial cooperation and advanced packaging architectures. In relation to this, the AFC program is reviewed, considering the design and implementation of NASA's AFC multichip module.
An effective algorithm for computing global sensitivity indices (EASI)
International Nuclear Information System (INIS)
Plischke, Elmar
2010-01-01
We present an algorithm named EASI that estimates first order sensitivity indices from given data using Fast Fourier Transformations. Hence it can be used as a post-processing module for pre-computed model evaluations. Ideas for the estimation of higher order sensitivity indices are also discussed.
Plagiarism Detection Algorithm for Source Code in Computer Science Education
Liu, Xin; Xu, Chan; Ouyang, Boyu
2015-01-01
Nowadays, computer programming is getting more necessary in the course of program design in college education. However, the trick of plagiarizing plus a little modification exists among some students' home works. It's not easy for teachers to judge if there's plagiarizing in source code or not. Traditional detection algorithms cannot fit this…
A simpler and elegant algorithm for computing fractal dimension in ...
Indian Academy of Sciences (India)
Chaotic systems are now frequently encountered in almost all branches of sciences. Dimension of such systems provides an important measure for easy characterization of dynamics of the systems. Conventional algorithms for computing dimension of such systems in higher dimensional state space face an unavoidable ...
International Conference on Computers and Advanced Technology in Education
Advanced Information Technology in Education
2012-01-01
The volume includes a set of selected papers extended and revised from the 2011 International Conference on Computers and Advanced Technology in Education. With the development of computers and advanced technology, the human social activities are changing basically. Education, especially the education reforms in different countries, has been experiencing the great help from the computers and advanced technology. Generally speaking, education is a field which needs more information, while the computers, advanced technology and internet are a good information provider. Also, with the aid of the computer and advanced technology, persons can make the education an effective combination. Therefore, computers and advanced technology should be regarded as an important media in the modern education. Volume Advanced Information Technology in Education is to provide a forum for researchers, educators, engineers, and government officials involved in the general areas of computers and advanced technology in education to d...
Computationally efficient model predictive control algorithms a neural network approach
Ławryńczuk, Maciej
2014-01-01
This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: · A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. · Implementation details of the MPC algorithms for feedforward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. · The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). · The MPC algorithms with neural approximation with no on-line linearization. · The MPC algorithms with guaranteed stability and robustness. · Cooperation between the MPC algorithms and set-point optimization. Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require d...
The advanced computational testing and simulation toolkit (ACTS)
International Nuclear Information System (INIS)
Drummond, L.A.; Marques, O.
2002-01-01
During the past decades there has been a continuous growth in the number of physical and societal problems that have been successfully studied and solved by means of computational modeling and simulation. Distinctively, a number of these are important scientific problems ranging in scale from the atomic to the cosmic. For example, ionization is a phenomenon as ubiquitous in modern society as the glow of fluorescent lights and the etching on silicon computer chips; but it was not until 1999 that researchers finally achieved a complete numerical solution to the simplest example of ionization, the collision of a hydrogen atom with an electron. On the opposite scale, cosmologists have long wondered whether the expansion of the Universe, which began with the Big Bang, would ever reverse itself, ending the Universe in a Big Crunch. In 2000, analysis of new measurements of the cosmic microwave background radiation showed that the geometry of the Universe is flat, and thus the Universe will continue expanding forever. Both of these discoveries depended on high performance computer simulations that utilized computational tools included in the Advanced Computational Testing and Simulation (ACTS) Toolkit. The ACTS Toolkit is an umbrella project that brought together a number of general purpose computational tool development projects funded and supported by the U.S. Department of Energy (DOE). These tools, which have been developed independently, mainly at DOE laboratories, make it easier for scientific code developers to write high performance applications for parallel computers. They tackle a number of computational issues that are common to a large number of scientific applications, mainly implementation of numerical algorithms, and support for code development, execution and optimization. The ACTS Toolkit Project enables the use of these tools by a much wider community of computational scientists, and promotes code portability, reusability, reduction of duplicate efforts
The advanced computational testing and simulation toolkit (ACTS)
Energy Technology Data Exchange (ETDEWEB)
Drummond, L.A.; Marques, O.
2002-05-21
During the past decades there has been a continuous growth in the number of physical and societal problems that have been successfully studied and solved by means of computational modeling and simulation. Distinctively, a number of these are important scientific problems ranging in scale from the atomic to the cosmic. For example, ionization is a phenomenon as ubiquitous in modern society as the glow of fluorescent lights and the etching on silicon computer chips; but it was not until 1999 that researchers finally achieved a complete numerical solution to the simplest example of ionization, the collision of a hydrogen atom with an electron. On the opposite scale, cosmologists have long wondered whether the expansion of the Universe, which began with the Big Bang, would ever reverse itself, ending the Universe in a Big Crunch. In 2000, analysis of new measurements of the cosmic microwave background radiation showed that the geometry of the Universe is flat, and thus the Universe will continue expanding forever. Both of these discoveries depended on high performance computer simulations that utilized computational tools included in the Advanced Computational Testing and Simulation (ACTS) Toolkit. The ACTS Toolkit is an umbrella project that brought together a number of general purpose computational tool development projects funded and supported by the U.S. Department of Energy (DOE). These tools, which have been developed independently, mainly at DOE laboratories, make it easier for scientific code developers to write high performance applications for parallel computers. They tackle a number of computational issues that are common to a large number of scientific applications, mainly implementation of numerical algorithms, and support for code development, execution and optimization. The ACTS Toolkit Project enables the use of these tools by a much wider community of computational scientists, and promotes code portability, reusability, reduction of duplicate efforts
Computational advances in transition phase analysis
International Nuclear Information System (INIS)
Morita, K.; Kondo, S.; Tobita, Y.; Shirakawa, N.; Brear, D.J.; Fischer, E.A.
1994-01-01
In this paper, historical perspective and recent advances are reviewed on computational technologies to evaluate a transition phase of core disruptive accidents in liquid-metal fast reactors. An analysis of the transition phase requires treatment of multi-phase multi-component thermohydraulics coupled with space- and energy-dependent neutron kinetics. Such a comprehensive modeling effort was initiated when the program of SIMMER-series computer code development was initiated in the late 1970s in the USA. Successful application of the latest SIMMER-II in USA, western Europe and Japan have proved its effectiveness, but, at the same time, several areas that require further research have been identified. Based on the experience and lessons learned during the SIMMER-II application through 1980s, a new project of SIMMER-III development is underway at the Power Reactor and Nuclear Fuel Development Corporation (PNC), Japan. The models and methods of SIMMER-III are briefly described with emphasis on recent advances in multi-phase multi-component fluid dynamics technologies and their expected implication on a future reliable transition phase analysis. (author)
Advances in Cross-Cutting Ideas for Computational Climate Science
Energy Technology Data Exchange (ETDEWEB)
Ng, Esmond [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Evans, Katherine J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Caldwell, Peter [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hoffman, Forrest M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Jackson, Charles [Univ. of Texas, Austin, TX (United States); Kerstin, Van Dam [Brookhaven National Lab. (BNL), Upton, NY (United States); Leung, Ruby [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Martin, Daniel F. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ostrouchov, George [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Tuminaro, Raymond [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ullrich, Paul [Univ. of California, Davis, CA (United States); Wild, S. [Argonne National Lab. (ANL), Argonne, IL (United States); Williams, Samuel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2017-01-01
This report presents results from the DOE-sponsored workshop titled, ``Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1) process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for
Advances in Cross-Cutting Ideas for Computational Climate Science
Energy Technology Data Exchange (ETDEWEB)
Ng, E.; Evans, K.; Caldwell, P.; Hoffman, F.; Jackson, C.; Van Dam, K.; Leung, R.; Martin, D.; Ostrouchov, G.; Tuminaro, R.; Ullrich, P.; Wild, S.; Williams, S.
2017-01-01
This report presents results from the DOE-sponsored workshop titled, Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1) process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling
Development of computational algorithms for quantification of pulmonary structures
International Nuclear Information System (INIS)
Oliveira, Marcela de; Alvarez, Matheus; Alves, Allan F.F.; Miranda, Jose R.A.; Pina, Diana R.
2012-01-01
The high-resolution computed tomography has become the imaging diagnostic exam most commonly used for the evaluation of the squeals of Paracoccidioidomycosis. The subjective evaluations the radiological abnormalities found on HRCT images do not provide an accurate quantification. The computer-aided diagnosis systems produce a more objective assessment of the abnormal patterns found in HRCT images. Thus, this research proposes the development of algorithms in MATLAB® computing environment can quantify semi-automatically pathologies such as pulmonary fibrosis and emphysema. The algorithm consists in selecting a region of interest (ROI), and by the use of masks, filter densities and morphological operators, to obtain a quantification of the injured area to the area of a healthy lung. The proposed method was tested on ten HRCT scans of patients with confirmed PCM. The results of semi-automatic measurements were compared with subjective evaluations performed by a specialist in radiology, falling to a coincidence of 80% for emphysema and 58% for fibrosis. (author)
An Alternative Algorithm for Computing Watersheds on Shared Memory Parallel Computers
Meijster, A.; Roerdink, J.B.T.M.
1995-01-01
In this paper a parallel implementation of a watershed algorithm is proposed. The algorithm can easily be implemented on shared memory parallel computers. The watershed transform is generally considered to be inherently sequential since the discrete watershed of an image is defined using recursion.
Localized Ambient Solidity Separation Algorithm Based Computer User Segmentation
Sun, Xiao; Zhang, Tongda; Chai, Yueting; Liu, Yi
2015-01-01
Most of popular clustering methods typically have some strong assumptions of the dataset. For example, the k-means implicitly assumes that all clusters come from spherical Gaussian distributions which have different means but the same covariance. However, when dealing with datasets that have diverse distribution shapes or high dimensionality, these assumptions might not be valid anymore. In order to overcome this weakness, we proposed a new clustering algorithm named localized ambient solidity separation (LASS) algorithm, using a new isolation criterion called centroid distance. Compared with other density based isolation criteria, our proposed centroid distance isolation criterion addresses the problem caused by high dimensionality and varying density. The experiment on a designed two-dimensional benchmark dataset shows that our proposed LASS algorithm not only inherits the advantage of the original dissimilarity increments clustering method to separate naturally isolated clusters but also can identify the clusters which are adjacent, overlapping, and under background noise. Finally, we compared our LASS algorithm with the dissimilarity increments clustering method on a massive computer user dataset with over two million records that contains demographic and behaviors information. The results show that LASS algorithm works extremely well on this computer user dataset and can gain more knowledge from it. PMID:26221133
The algorithmic level is the bridge between computation and brain.
Love, Bradley C
2015-04-01
Every scientist chooses a preferred level of analysis and this choice shapes the research program, even determining what counts as evidence. This contribution revisits Marr's (1982) three levels of analysis (implementation, algorithmic, and computational) and evaluates the prospect of making progress at each individual level. After reviewing limitations of theorizing within a level, two strategies for integration across levels are considered. One is top-down in that it attempts to build a bridge from the computational to algorithmic level. Limitations of this approach include insufficient theoretical constraint at the computation level to provide a foundation for integration, and that people are suboptimal for reasons other than capacity limitations. Instead, an inside-out approach is forwarded in which all three levels of analysis are integrated via the algorithmic level. This approach maximally leverages mutual data constraints at all levels. For example, algorithmic models can be used to interpret brain imaging data, and brain imaging data can be used to select among competing models. Examples of this approach to integration are provided. This merging of levels raises questions about the relevance of Marr's tripartite view. Copyright © 2015 Cognitive Science Society, Inc.
Fibonacci’s Computation Methods vs Modern Algorithms
Directory of Open Access Journals (Sweden)
Ernesto Burattini
2013-12-01
Full Text Available In this paper we discuss some computational procedures given by Leonardo Pisano Fibonacci in his famous Liber Abaci book, and we propose their translation into a modern language for computers (C ++. Among the other we describe the method of “cross” multiplication, we evaluate its computational complexity in algorithmic terms and we show the output of a C ++ code that describes the development of the method applied to the product of two integers. In a similar way we show the operations performed on fractions introduced by Fibonacci. Thanks to the possibility to reproduce on a computer, the Fibonacci’s different computational procedures, it was possible to identify some calculation errors present in the different versions of the original text.
A fast algorithm for computer aided collimation gamma camera (CACAO)
Jeanguillaume, C.; Begot, S.; Quartuccio, M.; Douiri, A.; Franck, D.; Pihet, P.; Ballongue, P.
2000-08-01
The computer aided collimation gamma camera is aimed at breaking down the resolution sensitivity trade-off of the conventional parallel hole collimator. It uses larger and longer holes, having an added linear movement at the acquisition sequence. A dedicated algorithm including shift and sum, deconvolution, parabolic filtering and rotation is described. Examples of reconstruction are given. This work shows that a simple and fast algorithm, based on a diagonal dominant approximation of the problem can be derived. Its gives a practical solution to the CACAO reconstruction problem.
Computational performance of a projection and rescaling algorithm
Pena, Javier; Soheili, Negar
2018-01-01
This paper documents a computational implementation of a {\\em projection and rescaling algorithm} for finding most interior solutions to the pair of feasibility problems \\[ \\text{find} \\; x\\in L\\cap\\mathbb{R}^n_{+} \\;\\;\\;\\; \\text{ and } \\; \\;\\;\\;\\; \\text{find} \\; \\hat x\\in L^\\perp\\cap\\mathbb{R}^n_{+}, \\] where $L$ denotes a linear subspace in $\\mathbb{R}^n$ and $L^\\perp$ denotes its orthogonal complement. The projection and rescaling algorithm is a recently developed method that combines a {\\...
Realization of Deutsch-like algorithm using ensemble computing
International Nuclear Information System (INIS)
Wei Daxiu; Luo Jun; Sun Xianping; Zeng Xizhi
2003-01-01
The Deutsch-like algorithm [Phys. Rev. A. 63 (2001) 034101] distinguishes between even and odd query functions using fewer function calls than its possible classical counterpart in a two-qubit system. But the similar method cannot be applied to a multi-qubit system. We propose a new approach for solving Deutsch-like problem using ensemble computing. The proposed algorithm needs an ancillary qubit and can be easily extended to multi-qubit system with one query. Our ensemble algorithm beginning with a easily-prepared initial state has three main steps. The classifications of the functions can be obtained directly from the spectra of the ancilla qubit. We also demonstrate the new algorithm in a four-qubit molecular system using nuclear magnetic resonance (NMR). One hydrogen and three carbons are selected as the four qubits, and one of carbons is ancilla qubit. We choice two unitary transformations, corresponding to two functions (one odd function and one even function), to validate the ensemble algorithm. The results show that our experiment is successfully and our ensemble algorithm for solving the Deutsch-like problem is virtual
Advanced illumination control algorithm for medical endoscopy applications
Sousa, Ricardo M.; Wäny, Martin; Santos, Pedro; Morgado-Dias, F.
2015-05-01
CMOS image sensor manufacturer, AWAIBA, is providing the world's smallest digital camera modules to the world market for minimally invasive surgery and one time use endoscopic equipment. Based on the world's smallest digital camera head and the evaluation board provided to it, the aim of this paper is to demonstrate an advanced fast response dynamic control algorithm of the illumination LED source coupled to the camera head, over the LED drivers embedded on the evaluation board. Cost efficient and small size endoscopic camera modules nowadays embed minimal size image sensors capable of not only adjusting gain and exposure time but also LED illumination with adjustable illumination power. The LED illumination power has to be dynamically adjusted while navigating the endoscope over changing illumination conditions of several orders of magnitude within fractions of the second to guarantee a smooth viewing experience. The algorithm is centered on the pixel analysis of selected ROIs enabling it to dynamically adjust the illumination intensity based on the measured pixel saturation level. The control core was developed in VHDL and tested in a laboratory environment over changing light conditions. The obtained results show that it is capable of achieving correction speeds under 1 s while maintaining a static error below 3% relative to the total number of pixels on the image. The result of this work will allow the integration of millimeter sized high brightness LED sources on minimal form factor cameras enabling its use in endoscopic surgical robotic or micro invasive surgery.
Computational Discovery of Materials Using the Firefly Algorithm
Avendaño-Franco, Guillermo; Romero, Aldo
Our current ability to model physical phenomena accurately, the increase computational power and better algorithms are the driving forces behind the computational discovery and design of novel materials, allowing for virtual characterization before their realization in the laboratory. We present the implementation of a novel firefly algorithm, a population-based algorithm for global optimization for searching the structure/composition space. This novel computation-intensive approach naturally take advantage of concurrency, targeted exploration and still keeping enough diversity. We apply the new method in both periodic and non-periodic structures and we present the implementation challenges and solutions to improve efficiency. The implementation makes use of computational materials databases and network analysis to optimize the search and get insights about the geometric structure of local minima on the energy landscape. The method has been implemented in our software PyChemia, an open-source package for materials discovery. We acknowledge the support of DMREF-NSF 1434897 and the Donors of the American Chemical Society Petroleum Research Fund for partial support of this research under Contract 54075-ND10.
Computational biomechanics for medicine from algorithms to models and applications
Joldes, Grand; Nielsen, Poul; Doyle, Barry; Miller, Karol
2017-01-01
This volume comprises the latest developments in both fundamental science and patient-specific applications, discussing topics such as: cellular mechanics; injury biomechanics; biomechanics of heart and vascular system; medical image analysis; and both patient-specific fluid dynamics and solid mechanics simulations. With contributions from researchers world-wide, the Computational Biomechanics for Medicine series of titles provides an opportunity for specialists in computational biomechanics to present their latest methodologies and advancements.
Transport modeling and advanced computer techniques
International Nuclear Information System (INIS)
Wiley, J.C.; Ross, D.W.; Miner, W.H. Jr.
1988-11-01
A workshop was held at the University of Texas in June 1988 to consider the current state of transport codes and whether improved user interfaces would make the codes more usable and accessible to the fusion community. Also considered was the possibility that a software standard could be devised to ease the exchange of routines between groups. It was noted that two of the major obstacles to exchanging routines now are the variety of geometrical representation and choices of units. While the workshop formulated no standards, it was generally agreed that good software engineering would aid in the exchange of routines, and that a continued exchange of ideas between groups would be worthwhile. It seems that before we begin to discuss software standards we should review the current state of computer technology --- both hardware and software to see what influence recent advances might have on our software goals. This is done in this paper
Advanced proton imaging in computed tomography
Mattiazzo, S; Giubilato, P; Pantano, D; Pozzobon, N; Snoeys, W; Wyss, J
2015-01-01
In recent years the use of hadrons for cancer radiation treatment has grown in importance, and many facilities are currently operational or under construction worldwide. To fully exploit the therapeutic advantages offered by hadron therapy, precise body imaging for accurate beam delivery is decisive. Proton computed tomography (pCT) scanners, currently in their R&D phase, provide the ultimate 3D imaging for hadrons treatment guidance. A key component of a pCT scanner is the detector used to track the protons, which has great impact on the scanner performances and ultimately limits its maximum speed. In this article, a novel proton-tracking detector was presented that would have higher scanning speed, better spatial resolution and lower material budget with respect to present state-of-the-art detectors, leading to enhanced performances. This advancement in performances is achieved by employing the very latest development in monolithic active pixel detectors (to build high granularity, low material budget, ...
Computer Algorithms in the Search for Unrelated Stem Cell Donors
Directory of Open Access Journals (Sweden)
David Steiner
2012-01-01
Full Text Available Hematopoietic stem cell transplantation (HSCT is a medical procedure in the field of hematology and oncology, most often performed for patients with certain cancers of the blood or bone marrow. A lot of patients have no suitable HLA-matched donor within their family, so physicians must activate a “donor search process” by interacting with national and international donor registries who will search their databases for adult unrelated donors or cord blood units (CBU. Information and communication technologies play a key role in the donor search process in donor registries both nationally and internationaly. One of the major challenges for donor registry computer systems is the development of a reliable search algorithm. This work discusses the top-down design of such algorithms and current practice. Based on our experience with systems used by several stem cell donor registries, we highlight typical pitfalls in the implementation of an algorithm and underlying data structure.
Advancing analytical algorithms and pipelines for billions of microbial sequences.
Gonzalez, Antonio; Knight, Rob
2012-02-01
The vast number of microbial sequences resulting from sequencing efforts using new technologies require us to re-assess currently available analysis methodologies and tools. Here we describe trends in the development and distribution of software for analyzing microbial sequence data. We then focus on one widely used set of methods, dimensionality reduction techniques, which allow users to summarize and compare these vast datasets. We conclude by emphasizing the utility of formal software engineering methods for the development of computational biology tools, and the need for new algorithms for comparing microbial communities. Such large-scale comparisons will allow us to fulfill the dream of rapid integration and comparison of microbial sequence data sets, in a replicable analytical environment, in order to describe the microbial world we inhabit. Copyright © 2011 Elsevier Ltd. All rights reserved.
Blind source separation advances in theory, algorithms and applications
Wang, Wenwu
2014-01-01
Blind Source Separation intends to report the new results of the efforts on the study of Blind Source Separation (BSS). The book collects novel research ideas and some training in BSS, independent component analysis (ICA), artificial intelligence and signal processing applications. Furthermore, the research results previously scattered in many journals and conferences worldwide are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers, R&D engineers and graduate students in computer science and electronics who wish to learn the core principles, methods, algorithms, and applications of BSS. Dr. Ganesh R. Naik works at University of Technology, Sydney, Australia; Dr. Wenwu Wang works at University of Surrey, UK.
Automated System for Teaching Computational Complexity of Algorithms Course
Directory of Open Access Journals (Sweden)
Vadim S. Roublev
2017-01-01
Full Text Available This article describes problems of designing automated teaching system for “Computational complexity of algorithms” course. This system should provide students with means to familiarize themselves with complex mathematical apparatus and improve their mathematical thinking in the respective area. The article introduces the technique of algorithms symbol scroll table that allows estimating lower and upper bounds of computational complexity. Further, we introduce a set of theorems that facilitate the analysis in cases when the integer rounding of algorithm parameters is involved and when analyzing the complexity of a sum. At the end, the article introduces a normal system of symbol transformations that allows one both to perform any symbol transformations and simplifies the automated validation of such transformations. The article is published in the authors’ wording.
Advances in Integrated Computational Materials Engineering "ICME"
Hirsch, Jürgen
The methods of Integrated Computational Materials Engineering that were developed and successfully applied for Aluminium have been constantly improved. The main aspects and recent advances of integrated material and process modeling are simulations of material properties like strength and forming properties and for the specific microstructure evolution during processing (rolling, extrusion, annealing) under the influence of material constitution and process variations through the production process down to the final application. Examples are discussed for the through-process simulation of microstructures and related properties of Aluminium sheet, including DC ingot casting, pre-heating and homogenization, hot and cold rolling, final annealing. New results are included of simulation solution annealing and age hardening of 6xxx alloys for automotive applications. Physically based quantitative descriptions and computer assisted evaluation methods are new ICME methods of integrating new simulation tools also for customer applications, like heat affected zones in welding of age hardening alloys. The aspects of estimating the effect of specific elements due to growing recycling volumes requested also for high end Aluminium products are also discussed, being of special interest in the Aluminium producing industries.
OPENING REMARKS: Scientific Discovery through Advanced Computing
Strayer, Michael
2006-01-01
Good morning. Welcome to SciDAC 2006 and Denver. I share greetings from the new Undersecretary for Energy, Ray Orbach. Five years ago SciDAC was launched as an experiment in computational science. The goal was to form partnerships among science applications, computer scientists, and applied mathematicians to take advantage of the potential of emerging terascale computers. This experiment has been a resounding success. SciDAC has emerged as a powerful concept for addressing some of the biggest challenges facing our world. As significant as these successes were, I believe there is also significance in the teams that achieved them. In addition to their scientific aims these teams have advanced the overall field of computational science and set the stage for even larger accomplishments as we look ahead to SciDAC-2. I am sure that many of you are expecting to hear about the results of our current solicitation for SciDAC-2. I’m afraid we are not quite ready to make that announcement. Decisions are still being made and we will announce the results later this summer. Nearly 250 unique proposals were received and evaluated, involving literally thousands of researchers, postdocs, and students. These collectively requested more than five times our expected budget. This response is a testament to the success of SciDAC in the community. In SciDAC-2 our budget has been increased to about 70 million for FY 2007 and our partnerships have expanded to include the Environment and National Security missions of the Department. The National Science Foundation has also joined as a partner. These new partnerships are expected to expand the application space of SciDAC, and broaden the impact and visibility of the program. We have, with our recent solicitation, expanded to turbulence, computational biology, and groundwater reactive modeling and simulation. We are currently talking with the Department’s applied energy programs about risk assessment, optimization of complex systems - such
SciDAC advances and applications in computational beam dynamics
International Nuclear Information System (INIS)
Ryne, R; Abell, D; Adelmann, A; Amundson, J; Bohn, C; Cary, J; Colella, P; Dechow, D; Decyk, V; Dragt, A; Gerber, R; Habib, S; Higdon, D; Katsouleas, T; Ma, K-L; McCorquodale, P; Mihalcea, D; Mitchell, C; Mori, W; Mottershead, C T; Neri, F; Pogorelov, I; Qiang, J; Samulyak, R; Serafini, D; Shalf, J; Siegerist, C; Spentzouris, P; Stoltz, P; Terzic, B; Venturini, M; Walstrom, P
2005-01-01
SciDAC has had a major impact on computational beam dynamics and the design of particle accelerators. Particle accelerators-which account for half of the facilities in the DOE Office of Science Facilities for the Future of Science 20 Year Outlook-are crucial for US scientific, industrial, and economic competitiveness. Thanks to SciDAC, accelerator design calculations that were once thought impossible are now carried routinely, and new challenging and important calculations are within reach. SciDAC accelerator modeling codes are being used to get the most science out of existing facilities, to produce optimal designs for future facilities, and to explore advanced accelerator concepts that may hold the key to qualitatively new ways of accelerating charged particle beams. In this paper we present highlights from the SciDAC Accelerator Science and Technology (AST) project Beam Dynamics focus area in regard to algorithm development, software development, and applications
SciDAC Advances and Applications in Computational Beam Dynamics
International Nuclear Information System (INIS)
Ryne, R.; Abell, D.; Adelmann, A.; Amundson, J.; Bohn, C.; Cary, J.; Colella, P.; Dechow, D.; Decyk, V.; Dragt, A.; Gerber, R.; Habib, S.; Higdon, D.; Katsouleas, T.; Ma, K.-L.; McCorquodale, P.; Mihalcea, D.; Mitchell, C.; Mori, W.; Mottershead, C.T.; Neri, F.; Pogorelov, I.; Qiang, J.; Samulyak, R.; Serafini, D.; Shalf, J.; Siegerist, C.; Spentzouris, P.; Stoltz, P.; Terzic, B.; Venturini, M.; Walstrom, P.
2005-01-01
SciDAC has had a major impact on computational beam dynamics and the design of particle accelerators. Particle accelerators--which account for half of the facilities in the DOE Office of Science Facilities for the Future of Science 20 Year Outlook--are crucial for US scientific, industrial, and economic competitiveness. Thanks to SciDAC, accelerator design calculations that were once thought impossible are now carried routinely, and new challenging and important calculations are within reach. SciDAC accelerator modeling codes are being used to get the most science out of existing facilities, to produce optimal designs for future facilities, and to explore advanced accelerator concepts that may hold the key to qualitatively new ways of accelerating charged particle beams. In this poster we present highlights from the SciDAC Accelerator Science and Technology (AST) project Beam Dynamics focus area in regard to algorithm development, software development, and applications
Sort-Mid tasks scheduling algorithm in grid computing
Directory of Open Access Journals (Sweden)
Naglaa M. Reda
2015-11-01
Full Text Available Scheduling tasks on heterogeneous resources distributed over a grid computing system is an NP-complete problem. The main aim for several researchers is to develop variant scheduling algorithms for achieving optimality, and they have shown a good performance for tasks scheduling regarding resources selection. However, using of the full power of resources is still a challenge. In this paper, a new heuristic algorithm called Sort-Mid is proposed. It aims to maximizing the utilization and minimizing the makespan. The new strategy of Sort-Mid algorithm is to find appropriate resources. The base step is to get the average value via sorting list of completion time of each task. Then, the maximum average is obtained. Finally, the task has the maximum average is allocated to the machine that has the minimum completion time. The allocated task is deleted and then, these steps are repeated until all tasks are allocated. Experimental tests show that the proposed algorithm outperforms almost other algorithms in terms of resources utilization and makespan.
Sort-Mid tasks scheduling algorithm in grid computing.
Reda, Naglaa M; Tawfik, A; Marzok, Mohamed A; Khamis, Soheir M
2015-11-01
Scheduling tasks on heterogeneous resources distributed over a grid computing system is an NP-complete problem. The main aim for several researchers is to develop variant scheduling algorithms for achieving optimality, and they have shown a good performance for tasks scheduling regarding resources selection. However, using of the full power of resources is still a challenge. In this paper, a new heuristic algorithm called Sort-Mid is proposed. It aims to maximizing the utilization and minimizing the makespan. The new strategy of Sort-Mid algorithm is to find appropriate resources. The base step is to get the average value via sorting list of completion time of each task. Then, the maximum average is obtained. Finally, the task has the maximum average is allocated to the machine that has the minimum completion time. The allocated task is deleted and then, these steps are repeated until all tasks are allocated. Experimental tests show that the proposed algorithm outperforms almost other algorithms in terms of resources utilization and makespan.
A Novel Cloud Computing Algorithm of Security and Privacy
Directory of Open Access Journals (Sweden)
Chih-Yung Chen
2013-01-01
Full Text Available The emergence of cloud computing has simplified the flow of large-scale deployment distributed system of software suppliers; when issuing respective application programs in a sharing clouds service to different user, the management of material becomes more complex. Therefore, in multitype clouds service of trust environment, when enterprises face cloud computing, what most worries is the issue of security, but individual users are worried whether the privacy material will have an outflow risk. This research has mainly analyzed several different construction patterns of cloud computing, and quite relevant case in the deployment construction security of cloud computing by fit and unfit quality, and proposed finally an optimization safe deployment construction of cloud computing and security mechanism of material protection calculating method, namely, Global Authentication Register System (GARS, to reduce cloud material outflow risk. We implemented a system simulation to test the GARS algorithm of availability, security and performance. By experimental data analysis, the solutions of cloud computing security, and privacy derived from the research can be effective protection in cloud information security. Moreover, we have proposed cloud computing in the information security-related proposals that would provide related units for the development of cloud computing security practice.
Computing return times or return periods with rare event algorithms
Lestang, Thibault; Ragone, Francesco; Bréhier, Charles-Edouard; Herbert, Corentin; Bouchet, Freddy
2018-04-01
The average time between two occurrences of the same event, referred to as its return time (or return period), is a useful statistical concept for practical applications. For instance insurances or public agencies may be interested by the return time of a 10 m flood of the Seine river in Paris. However, due to their scarcity, reliably estimating return times for rare events is very difficult using either observational data or direct numerical simulations. For rare events, an estimator for return times can be built from the extrema of the observable on trajectory blocks. Here, we show that this estimator can be improved to remain accurate for return times of the order of the block size. More importantly, we show that this approach can be generalised to estimate return times from numerical algorithms specifically designed to sample rare events. So far those algorithms often compute probabilities, rather than return times. The approach we propose provides a computationally extremely efficient way to estimate numerically the return times of rare events for a dynamical system, gaining several orders of magnitude of computational costs. We illustrate the method on two kinds of observables, instantaneous and time-averaged, using two different rare event algorithms, for a simple stochastic process, the Ornstein–Uhlenbeck process. As an example of realistic applications to complex systems, we finally discuss extreme values of the drag on an object in a turbulent flow.
Iterative concurrent reconstruction algorithms for emission computed tomography
International Nuclear Information System (INIS)
Brown, J.K.; Hasegawa, B.H.; Lang, T.F.
1994-01-01
Direct reconstruction techniques, such as those based on filtered backprojection, are typically used for emission computed tomography (ECT), even though it has been argued that iterative reconstruction methods may produce better clinical images. The major disadvantage of iterative reconstruction algorithms, and a significant reason for their lack of clinical acceptance, is their computational burden. We outline a new class of ''concurrent'' iterative reconstruction techniques for ECT in which the reconstruction process is reorganized such that a significant fraction of the computational processing occurs concurrently with the acquisition of ECT projection data. These new algorithms use the 10-30 min required for acquisition of a typical SPECT scan to iteratively process the available projection data, significantly reducing the requirements for post-acquisition processing. These algorithms are tested on SPECT projection data from a Hoffman brain phantom acquired with a 2 x 10 5 counts in 64 views each having 64 projections. The SPECT images are reconstructed as 64 x 64 tomograms, starting with six angular views. Other angular views are added to the reconstruction process sequentially, in a manner that reflects their availability for a typical acquisition protocol. The results suggest that if T s of concurrent processing are used, the reconstruction processing time required after completion of the data acquisition can be reduced by at least 1/3 T s. (Author)
DEFF Research Database (Denmark)
Birkegård, Anna Camilla; Dalhoff Andersen, Vibe; Hisham Beshara Halasa, Tariq
2017-01-01
Accurate and detailed data on antimicrobial exposure in pig production are essential when studying the association between antimicrobial exposure and antimicrobial resistance. Due to difficulties in obtaining primary data on antimicrobial exposure in a large number of farms, there is a need...... for a robust and valid method to estimate the exposure using register data. An approach that estimates the antimicrobial exposure in every rearing period during the lifetime of a pig using register data was developed into a computational algorithm. In this approach data from national registers on antimicrobial...... purchases, movements of pigs and farm demographics registered at farm level are used. The algorithm traces batches of pigs retrospectively from slaughter to the farm(s) that housed the pigs during their finisher, weaner, and piglet period. Subsequently, the algorithm estimates the antimicrobial exposure...
Birkegård, Anna Camilla; Andersen, Vibe Dalhoff; Halasa, Tariq; Jensen, Vibeke Frøkjær; Toft, Nils; Vigre, Håkan
2017-10-01
Accurate and detailed data on antimicrobial exposure in pig production are essential when studying the association between antimicrobial exposure and antimicrobial resistance. Due to difficulties in obtaining primary data on antimicrobial exposure in a large number of farms, there is a need for a robust and valid method to estimate the exposure using register data. An approach that estimates the antimicrobial exposure in every rearing period during the lifetime of a pig using register data was developed into a computational algorithm. In this approach data from national registers on antimicrobial purchases, movements of pigs and farm demographics registered at farm level are used. The algorithm traces batches of pigs retrospectively from slaughter to the farm(s) that housed the pigs during their finisher, weaner, and piglet period. Subsequently, the algorithm estimates the antimicrobial exposure as the number of Animal Defined Daily Doses for treatment of one kg pig in each of the rearing periods. Thus, the antimicrobial purchase data at farm level are translated into antimicrobial exposure estimates at batch level. A batch of pigs is defined here as pigs sent to slaughter at the same day from the same farm. In this study we present, validate, and optimise a computational algorithm that calculate the lifetime exposure of antimicrobials for slaughter pigs. The algorithm was evaluated by comparing the computed estimates to data on antimicrobial usage from farm records in 15 farm units. We found a good positive correlation between the two estimates. The algorithm was run for Danish slaughter pigs sent to slaughter in January to March 2015 from farms with more than 200 finishers to estimate the proportion of farms that it was applicable for. In the final process, the algorithm was successfully run for batches of pigs originating from 3026 farms with finisher units (77% of the initial population). This number can be increased if more accurate register data can be
Implementation of PHENIX trigger algorithms on massively parallel computers
International Nuclear Information System (INIS)
Petridis, A.N.; Wohn, F.K.
1995-01-01
The event selection requirements of contemporary high energy and nuclear physics experiments are met by the introduction of on-line trigger algorithms which identify potentially interesting events and reduce the data acquisition rate to levels that are manageable by the electronics. Such algorithms being parallel in nature can be simulated off-line using massively parallel computers. The PHENIX experiment intends to investigate the possible existence of a new phase of matter called the quark gluon plasma which has been theorized to have existed in very early stages of the evolution of the universe by studying collisions of heavy nuclei at ultra-relativistic energies. Such interactions can also reveal important information regarding the structure of the nucleus and mandate a thorough investigation of the simpler proton-nucleus collisions at the same energies. The complexity of PHENIX events and the need to analyze and also simulate them at rates similar to the data collection ones imposes enormous computation demands. This work is a first effort to implement PHENIX trigger algorithms on parallel computers and to study the feasibility of using such machines to run the complex programs necessary for the simulation of the PHENIX detector response. Fine and coarse grain approaches have been studied and evaluated. Depending on the application the performance of a massively parallel computer can be much better or much worse than that of a serial workstation. A comparison between single instruction and multiple instruction computers is also made and possible applications of the single instruction machines to high energy and nuclear physics experiments are outlined. copyright 1995 American Institute of Physics
Recent advances in swarm intelligence and evolutionary computation
2015-01-01
This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference f...
Advances in Computing and Information Technology : Proceedings of the Second International
Nagamalai, Dhinaharan; Chaki, Nabendu
2012-01-01
The international conference on Advances in Computing and Information technology (ACITY 2012) provides an excellent international forum for both academics and professionals for sharing knowledge and results in theory, methodology and applications of Computer Science and Information Technology. The Second International Conference on Advances in Computing and Information technology (ACITY 2012), held in Chennai, India, during July 13-15, 2012, covered a number of topics in all major fields of Computer Science and Information Technology including: networking and communications, network security and applications, web and internet computing, ubiquitous computing, algorithms, bioinformatics, digital image processing and pattern recognition, artificial intelligence, soft computing and applications. Upon a strength review process, a number of high-quality, presenting not only innovative ideas but also a founded evaluation and a strong argumentation of the same, were selected and collected in the present proceedings, ...
Numerical methods design, analysis, and computer implementation of algorithms
Greenbaum, Anne
2012-01-01
Numerical Methods provides a clear and concise exploration of standard numerical analysis topics, as well as nontraditional ones, including mathematical modeling, Monte Carlo methods, Markov chains, and fractals. Filled with appealing examples that will motivate students, the textbook considers modern application areas, such as information retrieval and animation, and classical topics from physics and engineering. Exercises use MATLAB and promote understanding of computational results. The book gives instructors the flexibility to emphasize different aspects--design, analysis, or computer implementation--of numerical algorithms, depending on the background and interests of students. Designed for upper-division undergraduates in mathematics or computer science classes, the textbook assumes that students have prior knowledge of linear algebra and calculus, although these topics are reviewed in the text. Short discussions of the history of numerical methods are interspersed throughout the chapters. The book a...
Application of advanced electronics to a future spacecraft computer design
Carney, P. C.
1980-01-01
Advancements in hardware and software technology are summarized with specific emphasis on spacecraft computer capabilities. Available state of the art technology is reviewed and candidate architectures are defined.
Investigating the Multi-memetic Mind Evolutionary Computation Algorithm Efficiency
Directory of Open Access Journals (Sweden)
M. K. Sakharov
2017-01-01
Full Text Available In solving practically significant problems of global optimization, the objective function is often of high dimensionality and computational complexity and of nontrivial landscape as well. Studies show that often one optimization method is not enough for solving such problems efficiently - hybridization of several optimization methods is necessary.One of the most promising contemporary trends in this field are memetic algorithms (MA, which can be viewed as a combination of the population-based search for a global optimum and the procedures for a local refinement of solutions (memes, provided by a synergy. Since there are relatively few theoretical studies concerning the MA configuration, which is advisable for use to solve the black-box optimization problems, many researchers tend just to adaptive algorithms, which for search select the most efficient methods of local optimization for the certain domains of the search space.The article proposes a multi-memetic modification of a simple SMEC algorithm, using random hyper-heuristics. Presents the software algorithm and memes used (Nelder-Mead method, method of random hyper-sphere surface search, Hooke-Jeeves method. Conducts a comparative study of the efficiency of the proposed algorithm depending on the set and the number of memes. The study has been carried out using Rastrigin, Rosenbrock, and Zakharov multidimensional test functions. Computational experiments have been carried out for all possible combinations of memes and for each meme individually.According to results of study, conducted by the multi-start method, the combinations of memes, comprising the Hooke-Jeeves method, were successful. These results prove a rapid convergence of the method to a local optimum in comparison with other memes, since all methods perform the fixed number of iterations at the most.The analysis of the average number of iterations shows that using the most efficient sets of memes allows us to find the optimal
Advances in computational actinide chemistry in China
Energy Technology Data Exchange (ETDEWEB)
Wang, Dongqi; Wu, Jingyi; Chai, Zhifang [Chinese Academy of Sciences, Beijing (China). Multidisciplinary Initiative Center; Su, Jing [Chinese Academy of Sciences, Shanghai (China). Div. of Nuclear Materials Science and Engineering; Li, Jun [Tsinghua Univ., Beijing (China). Dept. of Chemistry and Laboratory of Organic Optoelectronics and Molecular Engineering
2014-04-01
The advances in computational actinide chemistry made in China are reviewed. Several areas relevant to chemistry of actinides in gas, liquid, and solid phases have been explored. However, we limit the scope to selected contributions in the chemistry of molecular actinide systems in gas and liquid phases. These studies may be classified into two categories: treatment of relativistic effects, which cover the development of two- and four-component Hamiltonians and the optimization of relativistic pseudopotentials, and the applications of theoretical methods in actinide chemistry. The applications include (1) the electronic structures of actinocene, noble gas complexes, An-C multiple bonding compounds, uranyl and its isoelectronic species, fluorides and oxides, molecular systems with metal-metal bonding in their isolated forms (U{sub 2}, Pu{sub 2}) and in fullerene (U{sub 2} rate at C{sub 60}), and the excited states of actinide complexes; (2) chemical reactions, including oxidation, hydrolysis of UF{sub 6}, ligand exchange, reactivities of thorium oxo and sulfido metallocenes, CO{sub 2}/CS{sub 2} functionalization promoted by trivalent uranium complex; and (3) migration of actinides in the environment. A future outlook is discussed. (orig.)
Selection of parameters for advanced machining processes using firefly algorithm
Directory of Open Access Journals (Sweden)
Rajkamal Shukla
2017-02-01
Full Text Available Advanced machining processes (AMPs are widely utilized in industries for machining complex geometries and intricate profiles. In this paper, two significant processes such as electric discharge machining (EDM and abrasive water jet machining (AWJM are considered to get the optimum values of responses for the given range of process parameters. The firefly algorithm (FA is attempted to the considered processes to obtain optimized parameters and the results obtained are compared with the results given by previous researchers. The variation of process parameters with respect to the responses are plotted to confirm the optimum results obtained using FA. In EDM process, the performance parameter “MRR” is increased from 159.70 gm/min to 181.6723 gm/min, while “Ra” and “REWR” are decreased from 6.21 μm to 3.6767 μm and 6.21% to 6.324 × 10−5% respectively. In AWJM process, the value of the “kerf” and “Ra” are decreased from 0.858 mm to 0.3704 mm and 5.41 mm to 4.443 mm respectively. In both the processes, the obtained results show a significant improvement in the responses.
First Responders Guide to Computer Forensics: Advanced Topics
National Research Council Canada - National Science Library
Nolan, Richard; Baker, Marie; Branson, Jake; Hammerstein, Josh; Rush, Kris; Waits, Cal; Schweinsberg, Elizabeth
2005-01-01
First Responders Guide to Computer Forensics: Advanced Topics expands on the technical material presented in SEI handbook CMU/SEI-2005-HB-001, First Responders Guide to Computer Forensics [Nolan 05...
Advances in metaheuristic algorithms for optimal design of structures
Kaveh, A
2017-01-01
This book presents efficient metaheuristic algorithms for optimal design of structures. Many of these algorithms are developed by the author and his colleagues, consisting of Democratic Particle Swarm Optimization, Charged System Search, Magnetic Charged System Search, Field of Forces Optimization, Dolphin Echolocation Optimization, Colliding Bodies Optimization, Ray Optimization. These are presented together with algorithms which were developed by other authors and have been successfully applied to various optimization problems. These consist of Particle Swarm Optimization, Big Bang-Big Crunch Algorithm, Cuckoo Search Optimization, Imperialist Competitive Algorithm, and Chaos Embedded Metaheuristic Algorithms. Finally a multi-objective optimization method is presented to solve large-scale structural problems based on the Charged System Search algorithm. The concepts and algorithms presented in this book are not only applicable to optimization of skeletal structures and finite element models, but can equally ...
Advances in metaheuristic algorithms for optimal design of structures
Kaveh, A
2014-01-01
This book presents efficient metaheuristic algorithms for optimal design of structures. Many of these algorithms are developed by the author and his colleagues, consisting of Democratic Particle Swarm Optimization, Charged System Search, Magnetic Charged System Search, Field of Forces Optimization, Dolphin Echolocation Optimization, Colliding Bodies Optimization, Ray Optimization. These are presented together with algorithms which were developed by other authors and have been successfully applied to various optimization problems. These consist of Particle Swarm Optimization, Big Bang-Big Crunch Algorithm, Cuckoo Search Optimization, Imperialist Competitive Algorithm, and Chaos Embedded Metaheuristic Algorithms. Finally a multi-objective optimization method is presented to solve large-scale structural problems based on the Charged System Search algorithm. The concepts and algorithms presented in this book are not only applicable to optimization of skeletal structures and finite element models, but can equally ...
Jiang, Y.; Xing, H. L.
2016-12-01
Micro-seismic events induced by water injection, mining activity or oil/gas extraction are quite informative, the interpretation of which can be applied for the reconstruction of underground stress and monitoring of hydraulic fracturing progress in oil/gas reservoirs. The source characterises and locations are crucial parameters that required for these purposes, which can be obtained through the waveform matching inversion (WMI) method. Therefore it is imperative to develop a WMI algorithm with high accuracy and convergence speed. Heuristic algorithm, as a category of nonlinear method, possesses a very high convergence speed and good capacity to overcome local minimal values, and has been well applied for many areas (e.g. image processing, artificial intelligence). However, its effectiveness for micro-seismic WMI is still poorly investigated; very few literatures exits that addressing this subject. In this research an advanced heuristic algorithm, gravitational search algorithm (GSA) , is proposed to estimate the focal mechanism (angle of strike, dip and rake) and source locations in three dimension. Unlike traditional inversion methods, the heuristic algorithm inversion does not require the approximation of green function. The method directly interacts with a CPU parallelized finite difference forward modelling engine, and updating the model parameters under GSA criterions. The effectiveness of this method is tested with synthetic data form a multi-layered elastic model; the results indicate GSA can be well applied on WMI and has its unique advantages. Keywords: Micro-seismicity, Waveform matching inversion, gravitational search algorithm, parallel computation
An algorithm for computing screened Coulomb scattering in GEANT4
Energy Technology Data Exchange (ETDEWEB)
Mendenhall, Marcus H. [Vanderbilt University Free Electron Laser Center, P.O. Box 351816 Station B, Nashville, TN 37235-1816 (United States)]. E-mail: marcus.h.mendenhall@vanderbilt.edu; Weller, Robert A. [Department of Electrical Engineering and Computer Science, Vanderbilt University, P.O. Box 351821 Station B, Nashville, TN 37235-1821 (United States)]. E-mail: robert.a.weller@vanderbilt.edu
2005-01-01
An algorithm has been developed for the GEANT4 Monte-Carlo package for the efficient computation of screened Coulomb interatomic scattering. It explicitly integrates the classical equations of motion for scattering events, resulting in precise tracking of both the projectile and the recoil target nucleus. The algorithm permits the user to plug in an arbitrary screening function, such as Lens-Jensen screening, which is good for backscattering calculations, or Ziegler-Biersack-Littmark screening, which is good for nuclear straggling and implantation problems. This will allow many of the applications of the TRIM and SRIM codes to be extended into the much more general GEANT4 framework where nuclear and other effects can be included.
An algorithm for computing screened Coulomb scattering in GEANT4
International Nuclear Information System (INIS)
Mendenhall, Marcus H.; Weller, Robert A.
2005-01-01
An algorithm has been developed for the GEANT4 Monte-Carlo package for the efficient computation of screened Coulomb interatomic scattering. It explicitly integrates the classical equations of motion for scattering events, resulting in precise tracking of both the projectile and the recoil target nucleus. The algorithm permits the user to plug in an arbitrary screening function, such as Lens-Jensen screening, which is good for backscattering calculations, or Ziegler-Biersack-Littmark screening, which is good for nuclear straggling and implantation problems. This will allow many of the applications of the TRIM and SRIM codes to be extended into the much more general GEANT4 framework where nuclear and other effects can be included
Directory of Open Access Journals (Sweden)
S. Selvi
2015-07-01
Full Text Available Grid computing solves high performance and high-throughput computing problems through sharing resources ranging from personal computers to super computers distributed around the world. As the grid environments facilitate distributed computation, the scheduling of grid jobs has become an important issue. In this paper, an investigation on implementing Multiobjective Variable Neighborhood Search (MVNS algorithm for scheduling independent jobs on computational grid is carried out. The performance of the proposed algorithm has been evaluated with Min–Min algorithm, Simulated Annealing (SA and Greedy Randomized Adaptive Search Procedure (GRASP algorithm. Simulation results show that MVNS algorithm generally performs better than other metaheuristics methods.
Fixed-point image orthorectification algorithms for reduced computational cost
French, Joseph Clinton
Imaging systems have been applied to many new applications in recent years. With the advent of low-cost, low-power focal planes and more powerful, lower cost computers, remote sensing applications have become more wide spread. Many of these applications require some form of geolocation, especially when relative distances are desired. However, when greater global positional accuracy is needed, orthorectification becomes necessary. Orthorectification is the process of projecting an image onto a Digital Elevation Map (DEM), which removes terrain distortions and corrects the perspective distortion by changing the viewing angle to be perpendicular to the projection plane. Orthorectification is used in disaster tracking, landscape management, wildlife monitoring and many other applications. However, orthorectification is a computationally expensive process due to floating point operations and divisions in the algorithm. To reduce the computational cost of on-board processing, two novel algorithm modifications are proposed. One modification is projection utilizing fixed-point arithmetic. Fixed point arithmetic removes the floating point operations and reduces the processing time by operating only on integers. The second modification is replacement of the division inherent in projection with a multiplication of the inverse. The inverse must operate iteratively. Therefore, the inverse is replaced with a linear approximation. As a result of these modifications, the processing time of projection is reduced by a factor of 1.3x with an average pixel position error of 0.2% of a pixel size for 128-bit integer processing and over 4x with an average pixel position error of less than 13% of a pixel size for a 64-bit integer processing. A secondary inverse function approximation is also developed that replaces the linear approximation with a quadratic. The quadratic approximation produces a more accurate approximation of the inverse, allowing for an integer multiplication calculation
Noor, Ahmed K. (Editor)
1986-01-01
The papers contained in this volume provide an overview of the advances made in a number of aspects of computational mechanics, identify some of the anticipated industry needs in this area, discuss the opportunities provided by new hardware and parallel algorithms, and outline some of the current government programs in computational mechanics. Papers are included on advances and trends in parallel algorithms, supercomputers for engineering analysis, material modeling in nonlinear finite-element analysis, the Navier-Stokes computer, and future finite-element software systems.
Computer vision algorithm for diabetic foot injury identification and evaluation
Energy Technology Data Exchange (ETDEWEB)
Castaneda M, C. L.; Solis S, L. O.; Martinez B, M. R.; Ortiz R, J. M.; Garza V, I.; Martinez F, M.; Castaneda M, R.; Vega C, H. R., E-mail: lsolis@uaz.edu.mx [Universidad Autonoma de Zacatecas, 98000 Zacatecas, Zac. (Mexico)
2016-10-15
Diabetic foot is one of the most devastating consequences related to diabetes. It is relevant because of its incidence and the elevated percentage of amputations and deaths that the disease implies. Given the fact that the existing tests and laboratories designed to diagnose it are limited and expensive, the most common evaluation is still based on signs and symptoms. This means that the specialist completes a questionnaire based solely on observation and an invasive wound measurement. Using the questionnaire, the physician issues a diagnosis. In the sense, the diagnosis relies only on the criteria and the specialists experience. For some variables such as the lesions area or their location, this dependency is not acceptable. Currently bio-engineering has played a key role on the diagnose of different chronic degenerative diseases. A timely diagnose has proven to be the best tool against diabetic foot. The diabetics foot clinical evaluation, increases the possibility to identify risks and further complications. The main goal of this paper is to present the development of an algorithm based on digital image processing techniques, which enables to optimize the results on the diabetics foot lesion evaluation. Using advanced techniques for object segmentation and adjusting the sensibility parameter, allows the correlation between the algorithms identified wounds and those observed by the physician. Using the developed algorithm it is possible to identify and assess the wounds, their size, and location, in a non-invasive way. (Author)
Computer vision algorithm for diabetic foot injury identification and evaluation
International Nuclear Information System (INIS)
Castaneda M, C. L.; Solis S, L. O.; Martinez B, M. R.; Ortiz R, J. M.; Garza V, I.; Martinez F, M.; Castaneda M, R.; Vega C, H. R.
2016-10-01
Diabetic foot is one of the most devastating consequences related to diabetes. It is relevant because of its incidence and the elevated percentage of amputations and deaths that the disease implies. Given the fact that the existing tests and laboratories designed to diagnose it are limited and expensive, the most common evaluation is still based on signs and symptoms. This means that the specialist completes a questionnaire based solely on observation and an invasive wound measurement. Using the questionnaire, the physician issues a diagnosis. In the sense, the diagnosis relies only on the criteria and the specialists experience. For some variables such as the lesions area or their location, this dependency is not acceptable. Currently bio-engineering has played a key role on the diagnose of different chronic degenerative diseases. A timely diagnose has proven to be the best tool against diabetic foot. The diabetics foot clinical evaluation, increases the possibility to identify risks and further complications. The main goal of this paper is to present the development of an algorithm based on digital image processing techniques, which enables to optimize the results on the diabetics foot lesion evaluation. Using advanced techniques for object segmentation and adjusting the sensibility parameter, allows the correlation between the algorithms identified wounds and those observed by the physician. Using the developed algorithm it is possible to identify and assess the wounds, their size, and location, in a non-invasive way. (Author)
Efficient quantum algorithm for computing n-time correlation functions.
Pedernales, J S; Di Candia, R; Egusquiza, I L; Casanova, J; Solano, E
2014-07-11
We propose a method for computing n-time correlation functions of arbitrary spinorial, fermionic, and bosonic operators, consisting of an efficient quantum algorithm that encodes these correlations in an initially added ancillary qubit for probe and control tasks. For spinorial and fermionic systems, the reconstruction of arbitrary n-time correlation functions requires the measurement of two ancilla observables, while for bosonic variables time derivatives of the same observables are needed. Finally, we provide examples applicable to different quantum platforms in the frame of the linear response theory.
International Nuclear Information System (INIS)
Nam, H; Stoitsov, M; Nazarewicz, W; Hagen, G; Kortelainen, M; Pei, J C; Bulgac, A; Maris, P; Vary, J P; Roche, K J; Schunck, N; Thompson, I; Wild, S M
2012-01-01
The demands of cutting-edge science are driving the need for larger and faster computing resources. With the rapidly growing scale of computing systems and the prospect of technologically disruptive architectures to meet these needs, scientists face the challenge of effectively using complex computational resources to advance scientific discovery. Multi-disciplinary collaborating networks of researchers with diverse scientific backgrounds are needed to address these complex challenges. The UNEDF SciDAC collaboration of nuclear theorists, applied mathematicians, and computer scientists is developing a comprehensive description of nuclei and their reactions that delivers maximum predictive power with quantified uncertainties. This paper describes UNEDF and identifies attributes that classify it as a successful computational collaboration. We illustrate significant milestones accomplished by UNEDF through integrative solutions using the most reliable theoretical approaches, most advanced algorithms, and leadership-class computational resources.
Advanced Fuel Cycle Economic Tools, Algorithms, and Methodologies
Energy Technology Data Exchange (ETDEWEB)
David E. Shropshire
2009-05-01
The Advanced Fuel Cycle Initiative (AFCI) Systems Analysis supports engineering economic analyses and trade-studies, and requires a requisite reference cost basis to support adequate analysis rigor. In this regard, the AFCI program has created a reference set of economic documentation. The documentation consists of the “Advanced Fuel Cycle (AFC) Cost Basis” report (Shropshire, et al. 2007), “AFCI Economic Analysis” report, and the “AFCI Economic Tools, Algorithms, and Methodologies Report.” Together, these documents provide the reference cost basis, cost modeling basis, and methodologies needed to support AFCI economic analysis. The application of the reference cost data in the cost and econometric systems analysis models will be supported by this report. These methodologies include: the energy/environment/economic evaluation of nuclear technology penetration in the energy market—domestic and internationally—and impacts on AFCI facility deployment, uranium resource modeling to inform the front-end fuel cycle costs, facility first-of-a-kind to nth-of-a-kind learning with application to deployment of AFCI facilities, cost tradeoffs to meet nuclear non-proliferation requirements, and international nuclear facility supply/demand analysis. The economic analysis will be performed using two cost models. VISION.ECON will be used to evaluate and compare costs under dynamic conditions, consistent with the cases and analysis performed by the AFCI Systems Analysis team. Generation IV Excel Calculations of Nuclear Systems (G4-ECONS) will provide static (snapshot-in-time) cost analysis and will provide a check on the dynamic results. In future analysis, additional AFCI measures may be developed to show the value of AFCI in closing the fuel cycle. Comparisons can show AFCI in terms of reduced global proliferation (e.g., reduction in enrichment), greater sustainability through preservation of a natural resource (e.g., reduction in uranium ore depletion), value from
Advanced topics in security computer system design
International Nuclear Information System (INIS)
Stachniak, D.E.; Lamb, W.R.
1989-01-01
The capability, performance, and speed of contemporary computer processors, plus the associated performance capability of the operating systems accommodating the processors, have enormously expanded the scope of possibilities for designers of nuclear power plant security computer systems. This paper addresses the choices that could be made by a designer of security computer systems working with contemporary computers and describes the improvement in functionality of contemporary security computer systems based on an optimally chosen design. Primary initial considerations concern the selection of (a) the computer hardware and (b) the operating system. Considerations for hardware selection concern processor and memory word length, memory capacity, and numerous processor features
Mathematical models and algorithms for the computer program 'WOLF'
International Nuclear Information System (INIS)
Halbach, K.
1975-12-01
The computer program FLOW finds the nonrelativistic self- consistent set of two-dimensional ion trajectories and electric fields (including space charges from ions and electrons) for a given set of initial and boundary conditions for the particles and fields. The combination of FLOW with the optimization code PISA gives the program WOLF, which finds the shape of the emitter which is consistent with the plasma forming it, and in addition varies physical characteristics such as electrode position, shapes, and potentials so that some performance characteristics are optimized. The motivation for developing these programs was the desire to design optimum ion source extractor/accelerator systems in a systematic fashion. The purpose of this report is to explain and derive the mathematical models and algorithms which approximate the real physical processes. It serves primarily to document the computer programs. 10 figures
Advanced optimization of permanent magnet wigglers using a genetic algorithm
Energy Technology Data Exchange (ETDEWEB)
Hajima, Ryoichi [Univ. of Tokyo (Japan)
1995-12-31
In permanent magnet wigglers, magnetic imperfection of each magnet piece causes field error. This field error can be reduced or compensated by sorting magnet pieces in proper order. We showed a genetic algorithm has good property for this sorting scheme. In this paper, this optimization scheme is applied to the case of permanent magnets which have errors in the direction of field. The result shows the genetic algorithm is superior to other algorithms.
Advanced optimization of permanent magnet wigglers using a genetic algorithm
International Nuclear Information System (INIS)
Hajima, Ryoichi
1995-01-01
In permanent magnet wigglers, magnetic imperfection of each magnet piece causes field error. This field error can be reduced or compensated by sorting magnet pieces in proper order. We showed a genetic algorithm has good property for this sorting scheme. In this paper, this optimization scheme is applied to the case of permanent magnets which have errors in the direction of field. The result shows the genetic algorithm is superior to other algorithms
Cloud identification using genetic algorithms and massively parallel computation
Buckles, Bill P.; Petry, Frederick E.
1996-01-01
As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMS) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here the results were mixed (60% to 80% accuracy). Given that one is willing to run the experiment several times (say 10), then it is acceptable to claim the higher accuracy rating. This problem has never been successfully automated. Therefore, these results are encouraging even though less impressive than the cloud experiment. Successful conclusion of an automated ocean current detection system would impact coastal fishing, naval tactics, and the study of micro-climates. Finally we contributed to the basic knowledge of GA (genetic algorithm) behavior in parallel environments. We developed better knowledge of the use of subpopulations in the context of shared breeding pools and the migration of individuals. Rigorous experiments were conducted based on quantifiable performance criteria. While much of the work confirmed current wisdom, for the first time we were able to submit conclusive evidence. The software developed under this grant was placed in the public domain. An extensive user
Computational intelligence for big data analysis frontier advances and applications
Dehuri, Satchidananda; Sanyal, Sugata
2015-01-01
The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of big data analysis and cloud computing.
Advanced Technologies, Embedded and Multimedia for Human-Centric Computing
Chao, Han-Chieh; Deng, Der-Jiunn; Park, James; HumanCom and EMC 2013
2014-01-01
The theme of HumanCom and EMC are focused on the various aspects of human-centric computing for advances in computer science and its applications, embedded and multimedia computing and provides an opportunity for academic and industry professionals to discuss the latest issues and progress in the area of human-centric computing. And the theme of EMC (Advanced in Embedded and Multimedia Computing) is focused on the various aspects of embedded system, smart grid, cloud and multimedia computing, and it provides an opportunity for academic, industry professionals to discuss the latest issues and progress in the area of embedded and multimedia computing. Therefore this book will be include the various theories and practical applications in human-centric computing and embedded and multimedia computing.
Indian Academy of Sciences (India)
algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).
Computing homography with RANSAC algorithm: a novel method of registration
Li, Xiaowei; Liu, Yue; Wang, Yongtian; Yan, Dayuan
2005-02-01
An AR (Augmented Reality) system can integrate computer-generated objects with the image sequences of real world scenes in either an off-line or a real-time way. Registration, or camera pose estimation, is one of the key techniques to determine its performance. The registration methods can be classified as model-based and move-matching. The former approach can accomplish relatively accurate registration results, but it requires the precise model of the scene, which is hard to be obtained. The latter approach carries out registration by computing the ego-motion of the camera. Because it does not require the prior-knowledge of the scene, its registration results sometimes turn out to be less accurate. When the model defined is as simple as a plane, a mixed method is introduced to take advantages of the virtues of the two methods mentioned above. Although unexpected objects often occlude this plane in an AR system, one can still try to detect corresponding points with a contract-expand method, while this will import erroneous correspondences. Computing homography with RANSAC algorithm is used to overcome such shortcomings. Using the robustly estimated homography resulted from RANSAC, the camera projective matrix can be recovered and thus registration is accomplished even when the markers are lost in the scene.
Dataflow-Based Mapping of Computer Vision Algorithms onto FPGAs
Directory of Open Access Journals (Sweden)
Ivan Corretjer
2007-01-01
Full Text Available We develop a design methodology for mapping computer vision algorithms onto an FPGA through the use of coarse-grain reconfigurable dataflow graphs as a representation to guide the designer. We first describe a new dataflow modeling technique called homogeneous parameterized dataflow (HPDF, which effectively captures the structure of an important class of computer vision applications. This form of dynamic dataflow takes advantage of the property that in a large number of image processing applications, data production and consumption rates can vary, but are equal across dataflow graph edges for any particular application iteration. After motivating and defining the HPDF model of computation, we develop an HPDF-based design methodology that offers useful properties in terms of verifying correctness and exposing performance-enhancing transformations; we discuss and address various challenges in efficiently mapping an HPDF-based application representation into target-specific HDL code; and we present experimental results pertaining to the mapping of a gesture recognition application onto the Xilinx Virtex II FPGA.
Castagnoli, Giuseppe
2018-03-01
The usual representation of quantum algorithms, limited to the process of solving the problem, is physically incomplete. We complete it in three steps: (i) extending the representation to the process of setting the problem, (ii) relativizing the extended representation to the problem solver to whom the problem setting must be concealed, and (iii) symmetrizing the relativized representation for time reversal to represent the reversibility of the underlying physical process. The third steps projects the input state of the representation, where the problem solver is completely ignorant of the setting and thus the solution of the problem, on one where she knows half solution (half of the information specifying it when the solution is an unstructured bit string). Completing the physical representation shows that the number of computation steps (oracle queries) required to solve any oracle problem in an optimal quantum way should be that of a classical algorithm endowed with the advanced knowledge of half solution.
Genetic algorithm based optimization of advanced solar cell designs modeled in Silvaco AtlasTM
Utsler, James
2006-01-01
A genetic algorithm was used to optimize the power output of multi-junction solar cells. Solar cell operation was modeled using the Silvaco ATLASTM software. The output of the ATLASTM simulation runs served as the input to the genetic algorithm. The genetic algorithm was run as a diffusing computation on a network of eighteen dual processor nodes. Results showed that the genetic algorithm produced better power output optimizations when compared with the results obtained using the hill cli...
Advanced reconstruction algorithms for electron tomography: From comparison to combination
Energy Technology Data Exchange (ETDEWEB)
Goris, B. [EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium); Roelandts, T. [Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium); Batenburg, K.J. [Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium); Centrum Wiskunde and Informatica, Science Park 123, NL-1098XG Amsterdam (Netherlands); Heidari Mezerji, H. [EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium); Bals, S., E-mail: sara.bals@ua.ac.be [EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium)
2013-04-15
In this work, the simultaneous iterative reconstruction technique (SIRT), the total variation minimization (TVM) reconstruction technique and the discrete algebraic reconstruction technique (DART) for electron tomography are compared and the advantages and disadvantages are discussed. Furthermore, we describe how the result of a three dimensional (3D) reconstruction based on TVM can provide objective information that is needed as the input for a DART reconstruction. This approach results in a tomographic reconstruction of which the segmentation is carried out in an objective manner. - Highlights: ► A comparative study between different reconstruction algorithms for tomography is performed. ► Reconstruction algorithms that uses prior knowledge about the specimen have a superior result. ► One reconstruction algorithm can provide the prior knowledge for a second algorithm.
International Nuclear Information System (INIS)
Santi, P.; Favalli, A.; Hauck, D.; Henzl, V.; Henzlova, D.; Ianakiev, K.; Iliev, M.; Swinhoe, M.; Croft, S.; Worrall, L.
2015-01-01
One of the most distinctive and informative signatures of special nuclear materials is the emission of correlated neutrons from either spontaneous or induced fission. Because the emission of correlated neutrons is a unique and unmistakable signature of nuclear materials, the ability to effectively detect, process, and analyze these emissions will continue to play a vital role in the non-proliferation, safeguards, and security missions. While currently deployed neutron measurement techniques based on 3He proportional counter technology, such as neutron coincidence and multiplicity counters currently used by the International Atomic Energy Agency, have proven to be effective over the past several decades for a wide range of measurement needs, a number of technical and practical limitations exist in continuing to apply this technique to future measurement needs. In many cases, those limitations exist within the algorithms that are used to process and analyze the detected signals from these counters that were initially developed approximately 20 years ago based on the technology and computing power that was available at that time. Over the past three years, an effort has been undertaken to address the general shortcomings in these algorithms by developing new algorithms that are based on fundamental physics principles that should lead to the development of more sensitive neutron non-destructive assay instrumentation. Through this effort, a number of advancements have been made in correcting incoming data for electronic dead time, connecting the two main types of analysis techniques used to quantify the data (Shift register analysis and Feynman variance to mean analysis), and in the underlying physical model, known as the point model, that is used to interpret the data in terms of the characteristic properties of the item being measured. The current status of the testing and evaluation of these advancements in correlated neutron analysis techniques will be discussed
Second International Conference on Advanced Computing, Networking and Informatics
Mohapatra, Durga; Konar, Amit; Chakraborty, Aruna
2014-01-01
Advanced Computing, Networking and Informatics are three distinct and mutually exclusive disciplines of knowledge with no apparent sharing/overlap among them. However, their convergence is observed in many real world applications, including cyber-security, internet banking, healthcare, sensor networks, cognitive radio, pervasive computing amidst many others. This two-volume proceedings explore the combined use of Advanced Computing and Informatics in the next generation wireless networks and security, signal and image processing, ontology and human-computer interfaces (HCI). The two volumes together include 148 scholarly papers, which have been accepted for presentation from over 640 submissions in the second International Conference on Advanced Computing, Networking and Informatics, 2014, held in Kolkata, India during June 24-26, 2014. The first volume includes innovative computing techniques and relevant research results in informatics with selective applications in pattern recognition, signal/image process...
Current algorithms for computed electron beam dose planning
International Nuclear Information System (INIS)
Brahme, A.
1985-01-01
Two- and sometimes three-dimensional computer algorithms for electron beam irradiation are capable of taking all irregularities of the body cross-section and the properties of the various tissues into account. This is achieved by dividing the incoming broad beams into a number of narrow pencil beams, the penetration of which can be described by essentially one-dimensional formalisms. The constituent pencil beams are most often described by Gaussian, experimentally or theoretically derived distributions. The accuracy of different dose planning algorithms is discussed in some detail based on their ability to take the different physical interaction processes of high energy electrons into account. It is shown that those programs that take the deviations from the simple Gaussian model into account give the best agreement with experimental results. With such programs a dosimetric relative accuracy of about 5% is generally achieved except in the most complex inhomogeneity configurations. Finally, the present limitations and possible future developments of electron dose planning are discussed. (orig.)
Parallel multiphysics algorithms and software for computational nuclear engineering
International Nuclear Information System (INIS)
Gaston, D; Hansen, G; Kadioglu, S; Knoll, D A; Newman, C; Park, H; Permann, C; Taitano, W
2009-01-01
There is a growing trend in nuclear reactor simulation to consider multiphysics problems. This can be seen in reactor analysis where analysts are interested in coupled flow, heat transfer and neutronics, and in fuel performance simulation where analysts are interested in thermomechanics with contact coupled to species transport and chemistry. These more ambitious simulations usually motivate some level of parallel computing. Many of the coupling efforts to date utilize simple code coupling or first-order operator splitting, often referred to as loose coupling. While these approaches can produce answers, they usually leave questions of accuracy and stability unanswered. Additionally, the different physics often reside on separate grids which are coupled via simple interpolation, again leaving open questions of stability and accuracy. Utilizing state of the art mathematics and software development techniques we are deploying next generation tools for nuclear engineering applications. The Jacobian-free Newton-Krylov (JFNK) method combined with physics-based preconditioning provide the underlying mathematical structure for our tools. JFNK is understood to be a modern multiphysics algorithm, but we are also utilizing its unique properties as a scale bridging algorithm. To facilitate rapid development of multiphysics applications we have developed the Multiphysics Object-Oriented Simulation Environment (MOOSE). Examples from two MOOSE-based applications: PRONGHORN, our multiphysics gas cooled reactor simulation tool and BISON, our multiphysics, multiscale fuel performance simulation tool will be presented.
Scientific Discovery through Advanced Computing (SciDAC-3) Partnership Project Annual Report
Energy Technology Data Exchange (ETDEWEB)
Hoffman, Forest M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Bochev, Pavel B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Cameron-Smith, Philip J.. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Easter, Richard C [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elliott, Scott M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Ghan, Steven J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Liu, Xiaohong [Univ. of Wyoming, Laramie, WY (United States); Lowrie, Robert B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Lucas, Donald D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ma, Po-lun [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Sacks, William J. [National Center for Atmospheric Research (NCAR), Boulder, CO (United States); Shrivastava, Manish [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Singh, Balwinder [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Tautges, Timothy J. [Argonne National Lab. (ANL), Argonne, IL (United States); Taylor, Mark A. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Vertenstein, Mariana [National Center for Atmospheric Research (NCAR), Boulder, CO (United States); Worley, Patrick H. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2014-01-15
The Applying Computationally Efficient Schemes for BioGeochemical Cycles ACES4BGC Project is advancing the predictive capabilities of Earth System Models (ESMs) by reducing two of the largest sources of uncertainty, aerosols and biospheric feedbacks, with a highly efficient computational approach. In particular, this project is implementing and optimizing new computationally efficient tracer advection algorithms for large numbers of tracer species; adding important biogeochemical interactions between the atmosphere, land, and ocean models; and applying uncertainty quanti cation (UQ) techniques to constrain process parameters and evaluate uncertainties in feedbacks between biogeochemical cycles and the climate system.
Advanced computational tools and methods for nuclear analyses of fusion technology systems
International Nuclear Information System (INIS)
Fischer, U.; Chen, Y.; Pereslavtsev, P.; Simakov, S.P.; Tsige-Tamirat, H.; Loughlin, M.; Perel, R.L.; Petrizzi, L.; Tautges, T.J.; Wilson, P.P.H.
2005-01-01
An overview is presented of advanced computational tools and methods developed recently for nuclear analyses of Fusion Technology systems such as the experimental device ITER ('International Thermonuclear Experimental Reactor') and the intense neutron source IFMIF ('International Fusion Material Irradiation Facility'). These include Monte Carlo based computational schemes for the calculation of three-dimensional shut-down dose rate distributions, methods, codes and interfaces for the use of CAD geometry models in Monte Carlo transport calculations, algorithms for Monte Carlo based sensitivity/uncertainty calculations, as well as computational techniques and data for IFMIF neutronics and activation calculations. (author)
Advances in Future Computer and Control Systems v.1
Lin, Sally; 2012 International Conference on Future Computer and Control Systems(FCCS2012)
2012-01-01
FCCS2012 is an integrated conference concentrating its focus on Future Computer and Control Systems. “Advances in Future Computer and Control Systems” presents the proceedings of the 2012 International Conference on Future Computer and Control Systems(FCCS2012) held April 21-22,2012, in Changsha, China including recent research results on Future Computer and Control Systems of researchers from all around the world.
Advances in Future Computer and Control Systems v.2
Lin, Sally; 2012 International Conference on Future Computer and Control Systems(FCCS2012)
2012-01-01
FCCS2012 is an integrated conference concentrating its focus on Future Computer and Control Systems. “Advances in Future Computer and Control Systems” presents the proceedings of the 2012 International Conference on Future Computer and Control Systems(FCCS2012) held April 21-22,2012, in Changsha, China including recent research results on Future Computer and Control Systems of researchers from all around the world.
An Accurate liver segmentation method using parallel computing algorithm
International Nuclear Information System (INIS)
Elbasher, Eiman Mohammed Khalied
2014-12-01
Computed Tomography (CT or CAT scan) is a noninvasive diagnostic imaging procedure that uses a combination of X-rays and computer technology to produce horizontal, or axial, images (often called slices) of the body. A CT scan shows detailed images of any part of the body, including the bones muscles, fat and organs CT scans are more detailed than standard x-rays. CT scans may be done with or without "contrast Contrast refers to a substance taken by mouth and/ or injected into an intravenous (IV) line that causes the particular organ or tissue under study to be seen more clearly. CT scan of the liver and biliary tract are used in the diagnosis of many diseases in the abdomen structures, particularly when another type of examination, such as X-rays, physical examination, and ultra sound is not conclusive. Unfortunately, the presence of noise and artifact in the edges and fine details in the CT images limit the contrast resolution and make diagnostic procedure more difficult. This experimental study was conducted at the College of Medical Radiological Science, Sudan University of Science and Technology and Fidel Specialist Hospital. The sample of study was included 50 patients. The main objective of this research was to study an accurate liver segmentation method using a parallel computing algorithm, and to segment liver and adjacent organs using image processing technique. The main technique of segmentation used in this study was watershed transform. The scope of image processing and analysis applied to medical application is to improve the quality of the acquired image and extract quantitative information from medical image data in an efficient and accurate way. The results of this technique agreed wit the results of Jarritt et al, (2010), Kratchwil et al, (2010), Jover et al, (2011), Yomamoto et al, (1996), Cai et al (1999), Saudha and Jayashree (2010) who used different segmentation filtering based on the methods of enhancing the computed tomography images. Anther
Power-efficient computer architectures recent advances
Själander, Magnus; Kaxiras, Stefanos
2014-01-01
As Moore's Law and Dennard scaling trends have slowed, the challenges of building high-performance computer architectures while maintaining acceptable power efficiency levels have heightened. Over the past ten years, architecture techniques for power efficiency have shifted from primarily focusing on module-level efficiencies, toward more holistic design styles based on parallelism and heterogeneity. This work highlights and synthesizes recent techniques and trends in power-efficient computer architecture.Table of Contents: Introduction / Voltage and Frequency Management / Heterogeneity and Sp
Scale-up of nature’s tissue weaving algorithms to engineer advanced functional materials
Ng, Joanna L.; Knothe, Lillian E.; Whan, Renee M.; Knothe, Ulf; Tate, Melissa L. Knothe
2017-01-01
We are literally the stuff from which our tissue fabrics and their fibers are woven and spun. The arrangement of collagen, elastin and other structural proteins in space and time embodies our tissues and organs with amazing resilience and multifunctional smart properties. For example, the periosteum, a soft tissue sleeve that envelops all nonarticular bony surfaces of the body, comprises an inherently “smart” material that gives hard bones added strength under high impact loads. Yet a paucity of scalable bottom-up approaches stymies the harnessing of smart tissues’ biological, mechanical and organizational detail to create advanced functional materials. Here, a novel approach is established to scale up the multidimensional fiber patterns of natural soft tissue weaves for rapid prototyping of advanced functional materials. First second harmonic generation and two-photon excitation microscopy is used to map the microscopic three-dimensional (3D) alignment, composition and distribution of the collagen and elastin fibers of periosteum, the soft tissue sheath bounding all nonarticular bone surfaces in our bodies. Then, using engineering rendering software to scale up this natural tissue fabric, as well as multidimensional weaving algorithms, macroscopic tissue prototypes are created using a computer-controlled jacquard loom. The capacity to prototype scaled up architectures of natural fabrics provides a new avenue to create advanced functional materials.
TerraFERMA: Harnessing Advanced Computational Libraries in Earth Science
Wilson, C. R.; Spiegelman, M.; van Keken, P.
2012-12-01
Many important problems in Earth sciences can be described by non-linear coupled systems of partial differential equations. These "multi-physics" problems include thermo-chemical convection in Earth and planetary interiors, interactions of fluids and magmas with the Earth's mantle and crust and coupled flow of water and ice. These problems are of interest to a large community of researchers but are complicated to model and understand. Much of this complexity stems from the nature of multi-physics where small changes in the coupling between variables or constitutive relations can lead to radical changes in behavior, which in turn affect critical computational choices such as discretizations, solvers and preconditioners. To make progress in understanding such coupled systems requires a computational framework where multi-physics problems can be described at a high-level while maintaining the flexibility to easily modify the solution algorithm. Fortunately, recent advances in computational science provide a basis for implementing such a framework. Here we present the Transparent Finite Element Rapid Model Assembler (TerraFERMA), which leverages several advanced open-source libraries for core functionality. FEniCS (fenicsproject.org) provides a high level language for describing the weak forms of coupled systems of equations, and an automatic code generator that produces finite element assembly code. PETSc (www.mcs.anl.gov/petsc) provides a wide range of scalable linear and non-linear solvers that can be composed into effective multi-physics preconditioners. SPuD (amcg.ese.ic.ac.uk/Spud) is an application neutral options system that provides both human and machine-readable interfaces based on a single xml schema. Our software integrates these libraries and provides the user with a framework for exploring multi-physics problems. A single options file fully describes the problem, including all equations, coefficients and solver options. Custom compiled applications are
Advanced Computational Methods for Monte Carlo Calculations
Energy Technology Data Exchange (ETDEWEB)
Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2018-01-12
This course is intended for graduate students who already have a basic understanding of Monte Carlo methods. It focuses on advanced topics that may be needed for thesis research, for developing new state-of-the-art methods, or for working with modern production Monte Carlo codes.
In-Place Algorithms for Computing (Layers of) Maxima
DEFF Research Database (Denmark)
Blunck, Henrik; Vahrenhold, Jan
2010-01-01
We describe space-efficient algorithms for solving problems related to finding maxima among points in two and three dimensions. Our algorithms run in optimal time and occupy only constant extra......We describe space-efficient algorithms for solving problems related to finding maxima among points in two and three dimensions. Our algorithms run in optimal time and occupy only constant extra...
Iterative algorithms for large sparse linear systems on parallel computers
Adams, L. M.
1982-01-01
Algorithms for assembling in parallel the sparse system of linear equations that result from finite difference or finite element discretizations of elliptic partial differential equations, such as those that arise in structural engineering are developed. Parallel linear stationary iterative algorithms and parallel preconditioned conjugate gradient algorithms are developed for solving these systems. In addition, a model for comparing parallel algorithms on array architectures is developed and results of this model for the algorithms are given.
Research in Parallel Algorithms and Software for Computational Aerosciences
Domel, Neal D.
1996-01-01
Phase 1 is complete for the development of a computational fluid dynamics CFD) parallel code with automatic grid generation and adaptation for the Euler analysis of flow over complex geometries. SPLITFLOW, an unstructured Cartesian grid code developed at Lockheed Martin Tactical Aircraft Systems, has been modified for a distributed memory/massively parallel computing environment. The parallel code is operational on an SGI network, Cray J90 and C90 vector machines, SGI Power Challenge, and Cray T3D and IBM SP2 massively parallel machines. Parallel Virtual Machine (PVM) is the message passing protocol for portability to various architectures. A domain decomposition technique was developed which enforces dynamic load balancing to improve solution speed and memory requirements. A host/node algorithm distributes the tasks. The solver parallelizes very well, and scales with the number of processors. Partially parallelized and non-parallelized tasks consume most of the wall clock time in a very fine grain environment. Timing comparisons on a Cray C90 demonstrate that Parallel SPLITFLOW runs 2.4 times faster on 8 processors than its non-parallel counterpart autotasked over 8 processors.
Intelligent cloud computing security using genetic algorithm as a computational tools
Razuky AL-Shaikhly, Mazin H.
2018-05-01
An essential change had occurred in the field of Information Technology which represented with cloud computing, cloud giving virtual assets by means of web yet awesome difficulties in the field of information security and security assurance. Currently main problem with cloud computing is how to improve privacy and security for cloud “cloud is critical security”. This paper attempts to solve cloud security by using intelligent system with genetic algorithm as wall to provide cloud data secure, all services provided by cloud must detect who receive and register it to create list of users (trusted or un-trusted) depend on behavior. The execution of present proposal has shown great outcome.
Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring
Energy Technology Data Exchange (ETDEWEB)
Kanemoto, Shigeru; Watanabe, Masaya [The University of Aizu, Aizuwakamatsu (Japan); Yusa, Noritaka [Tohoku University, Sendai (Japan)
2014-08-15
The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology.
Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring
International Nuclear Information System (INIS)
Kanemoto, Shigeru; Watanabe, Masaya; Yusa, Noritaka
2014-01-01
The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology
Advances in Computer, Communication, Control and Automation
011 International Conference on Computer, Communication, Control and Automation
2012-01-01
The volume includes a set of selected papers extended and revised from the 2011 International Conference on Computer, Communication, Control and Automation (3CA 2011). 2011 International Conference on Computer, Communication, Control and Automation (3CA 2011) has been held in Zhuhai, China, November 19-20, 2011. This volume topics covered include signal and Image processing, speech and audio Processing, video processing and analysis, artificial intelligence, computing and intelligent systems, machine learning, sensor and neural networks, knowledge discovery and data mining, fuzzy mathematics and Applications, knowledge-based systems, hybrid systems modeling and design, risk analysis and management, system modeling and simulation. We hope that researchers, graduate students and other interested readers benefit scientifically from the proceedings and also find it stimulating in the process.
CISM-IUTAM School on Advanced Turbulent Flow Computations
Krause, Egon
2000-01-01
This book collects the lecture notes concerning the IUTAM School on Advanced Turbulent Flow Computations held at CISM in Udine September 7–11, 1998. The course was intended for scientists, engineers and post-graduate students interested in the application of advanced numerical techniques for simulating turbulent flows. The topic comprises two closely connected main subjects: modelling and computation, mesh pionts necessary to simulate complex turbulent flow.
Realization of seven-qubit Deutsch-Jozsa algorithm on NMR quantum computer
International Nuclear Information System (INIS)
Wei Daxiu; Yang Xiaodong; Luo Jun; Sun Xianping; Zeng Xizhi; Liu Maili; Ding Shangwu
2002-01-01
Recent years, remarkable progresses in experimental realization of quantum information have been made, especially based on nuclear magnetic resonance (NMR) theory. In all quantum algorithms, Deutsch-Jozsa algorithm has been widely studied. It can be realized on NMR quantum computer and also can be simplified by using the Cirac's scheme. At first the principle of Deutsch-Jozsa quantum algorithm is analyzed, then the authors implement the seven-qubit Deutsch-Jozsa algorithm on NMR quantum computer
3rd International Conference on Advanced Computing, Networking and Informatics
Mohapatra, Durga; Chaki, Nabendu
2016-01-01
Advanced Computing, Networking and Informatics are three distinct and mutually exclusive disciplines of knowledge with no apparent sharing/overlap among them. However, their convergence is observed in many real world applications, including cyber-security, internet banking, healthcare, sensor networks, cognitive radio, pervasive computing amidst many others. This two volume proceedings explore the combined use of Advanced Computing and Informatics in the next generation wireless networks and security, signal and image processing, ontology and human-computer interfaces (HCI). The two volumes together include 132 scholarly articles, which have been accepted for presentation from over 550 submissions in the Third International Conference on Advanced Computing, Networking and Informatics, 2015, held in Bhubaneswar, India during June 23–25, 2015.
Embedded Platforms for Computer Vision-based Advanced Driver Assistance Systems: a Survey
Velez, Gorka; Otaegui, Oihana
2015-01-01
Computer Vision, either alone or combined with other technologies such as radar or Lidar, is one of the key technologies used in Advanced Driver Assistance Systems (ADAS). Its role understanding and analysing the driving scene is of great importance as it can be noted by the number of ADAS applications that use this technology. However, porting a vision algorithm to an embedded automotive system is still very challenging, as there must be a trade-off between several design requisites. Further...
A class of parallel algorithms for computation of the manipulator inertia matrix
Fijany, Amir; Bejczy, Antal K.
1989-01-01
Parallel and parallel/pipeline algorithms for computation of the manipulator inertia matrix are presented. An algorithm based on composite rigid-body spatial inertia method, which provides better features for parallelization, is used for the computation of the inertia matrix. Two parallel algorithms are developed which achieve the time lower bound in computation. Also described is the mapping of these algorithms with topological variation on a two-dimensional processor array, with nearest-neighbor connection, and with cardinality variation on a linear processor array. An efficient parallel/pipeline algorithm for the linear array was also developed, but at significantly higher efficiency.
Efficient conjugate gradient algorithms for computation of the manipulator forward dynamics
Fijany, Amir; Scheid, Robert E.
1989-01-01
The applicability of conjugate gradient algorithms for computation of the manipulator forward dynamics is investigated. The redundancies in the previously proposed conjugate gradient algorithm are analyzed. A new version is developed which, by avoiding these redundancies, achieves a significantly greater efficiency. A preconditioned conjugate gradient algorithm is also presented. A diagonal matrix whose elements are the diagonal elements of the inertia matrix is proposed as the preconditioner. In order to increase the computational efficiency, an algorithm is developed which exploits the synergism between the computation of the diagonal elements of the inertia matrix and that required by the conjugate gradient algorithm.
Advances in Computer Science and Education
Huang, Xiong
2012-01-01
CSE2011 is an integrated conference concentration its focus on computer science and education. In the proceeding, you can learn much more knowledge about computer science and education of researchers from all around the world. The main role of the proceeding is to be used as an exchange pillar for researchers who are working in the mentioned fields. In order to meet the high quality of Springer, AISC series, the organization committee has made their efforts to do the following things. Firstly, poor quality paper has been refused after reviewing course by anonymous referee experts. Secondly, periodically review meetings have been held around the reviewers about five times for exchanging reviewing suggestions. Finally, the conference organizers had several preliminary sessions before the conference. Through efforts of different people and departments, the conference will be successful and fruitful
Defense Science Board Report on Advanced Computing
2009-03-01
computers will require extensive research and development to have a chance of reaching the exascale level. Even if exascale level machines can...generations of petascale and then exascale level computing capability. This includes both the hardware and the complex software that may be...required for the architectures needed for exacscale capability. The challenges are extremely daunting, especially at the exascale
ASDA - Advanced Suit Design Analyzer computer program
Bue, Grant C.; Conger, Bruce C.; Iovine, John V.; Chang, Chi-Min
1992-01-01
An ASDA model developed to evaluate the heat and mass transfer characteristics of advanced pressurized suit design concepts for low pressure or vacuum planetary applications is presented. The model is based on a generalized 3-layer suit that uses the Systems Integrated Numerical Differencing Analyzer '85 in conjunction with a 41-node FORTRAN routine. The latter simulates the transient heat transfer and respiratory processes of a human body in a suited environment. The user options for the suit encompass a liquid cooled garment, a removable jacket, a CO2/H2O permeable layer, and a phase change layer.
Guest editorial preface : Special Issue on Advances in Computer Entertainment
Nijholt, Anton; Romão, Teresa; Cheok, Adrian D.
2013-01-01
This special issue of the International Journal of Creative Interfaces and Computer Graphics contains a selection of papers from ACE 2012, the 9th International Conference on Advances in Computer Entertainment (Nijholt et al., 2012). ACE is the leading scientific forum for dissemination of
Advanced Computing Tools and Models for Accelerator Physics
International Nuclear Information System (INIS)
Ryne, Robert; Ryne, Robert D.
2008-01-01
This paper is based on a transcript of my EPAC'08 presentation on advanced computing tools for accelerator physics. Following an introduction I present several examples, provide a history of the development of beam dynamics capabilities, and conclude with thoughts on the future of large scale computing in accelerator physics
Turing’s algorithmic lens: From computability to complexity theory
Directory of Open Access Journals (Sweden)
Díaz, Josep
2013-12-01
Full Text Available The decidability question, i.e., whether any mathematical statement could be computationally proven true or false, was raised by Hilbert and remained open until Turing answered it in the negative. Then, most efforts in theoretical computer science turned to complexity theory and the need to classify decidable problems according to their difficulty. Among others, the classes P (problems solvable in polynomial time and NP (problems solvable in non-deterministic polynomial time were defined, and one of the most challenging scientific quests of our days arose: whether P = NP. This still open question has implications not only in computer science, mathematics and physics, but also in biology, sociology and economics, and it can be seen as a direct consequence of Turing’s way of looking through the algorithmic lens at different disciplines to discover how pervasive computation is.La cuestión de la decidibilidad, es decir, si es posible demostrar computacionalmente que una expresión matemática es verdadera o falsa, fue planteada por Hilbert y permaneció abierta hasta que Turing la respondió de forma negativa. Establecida la no-decidibilidad de las matemáticas, los esfuerzos en informática teórica se centraron en el estudio de la complejidad computacional de los problemas decidibles. En este artículo presentamos una breve introducción a las clases P (problemas resolubles en tiempo polinómico y NP (problemas resolubles de manera no determinista en tiempo polinómico, al tiempo que exponemos la dificultad de establecer si P = NP y las consecuencias que se derivarían de que ambas clases de problemas fueran iguales. Esta cuestión tiene implicaciones no solo en los campos de la informática, las matemáticas y la física, sino también para la biología, la sociología y la economía. La idea seminal del estudio de la complejidad computacional es consecuencia directa del modo en que Turing abordaba problemas en diferentes ámbitos mediante lo
Wang, Xu; Shi, Fang; Sigrist, Norbert; Seo, Byoung-Joon; Tang, Hong; Bikkannavar, Siddarayappa; Basinger, Scott; Lay, Oliver
2012-01-01
Large aperture telescope commonly features segment mirrors and a coarse phasing step is needed to bring these individual segments into the fine phasing capture range. Dispersed Fringe Sensing (DFS) is a powerful coarse phasing technique and its alteration is currently being used for JWST.An Advanced Dispersed Fringe Sensing (ADFS) algorithm is recently developed to improve the performance and robustness of previous DFS algorithms with better accuracy and unique solution. The first part of the paper introduces the basic ideas and the essential features of the ADFS algorithm and presents the some algorithm sensitivity study results. The second part of the paper describes the full details of algorithm validation process through the advanced wavefront sensing and correction testbed (AWCT): first, the optimization of the DFS hardware of AWCT to ensure the data accuracy and reliability is illustrated. Then, a few carefully designed algorithm validation experiments are implemented, and the corresponding data analysis results are shown. Finally the fiducial calibration using Range-Gate-Metrology technique is carried out and a <10nm or <1% algorithm accuracy is demonstrated.
A block matching-based registration algorithm for localization of locally advanced lung tumors
Energy Technology Data Exchange (ETDEWEB)
Robertson, Scott P.; Weiss, Elisabeth; Hugo, Geoffrey D., E-mail: gdhugo@vcu.edu [Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, 23298 (United States)
2014-04-15
Purpose: To implement and evaluate a block matching-based registration (BMR) algorithm for locally advanced lung tumor localization during image-guided radiotherapy. Methods: Small (1 cm{sup 3}), nonoverlapping image subvolumes (“blocks”) were automatically identified on the planning image to cover the tumor surface using a measure of the local intensity gradient. Blocks were independently and automatically registered to the on-treatment image using a rigid transform. To improve speed and robustness, registrations were performed iteratively from coarse to fine image resolution. At each resolution, all block displacements having a near-maximum similarity score were stored. From this list, a single displacement vector for each block was iteratively selected which maximized the consistency of displacement vectors across immediately neighboring blocks. These selected displacements were regularized using a median filter before proceeding to registrations at finer image resolutions. After evaluating all image resolutions, the global rigid transform of the on-treatment image was computed using a Procrustes analysis, providing the couch shift for patient setup correction. This algorithm was evaluated for 18 locally advanced lung cancer patients, each with 4–7 weekly on-treatment computed tomography scans having physician-delineated gross tumor volumes. Volume overlap (VO) and border displacement errors (BDE) were calculated relative to the nominal physician-identified targets to establish residual error after registration. Results: Implementation of multiresolution registration improved block matching accuracy by 39% compared to registration using only the full resolution images. By also considering multiple potential displacements per block, initial errors were reduced by 65%. Using the final implementation of the BMR algorithm, VO was significantly improved from 77% ± 21% (range: 0%–100%) in the initial bony alignment to 91% ± 8% (range: 56%–100%;p < 0
A block matching-based registration algorithm for localization of locally advanced lung tumors
International Nuclear Information System (INIS)
Robertson, Scott P.; Weiss, Elisabeth; Hugo, Geoffrey D.
2014-01-01
Purpose: To implement and evaluate a block matching-based registration (BMR) algorithm for locally advanced lung tumor localization during image-guided radiotherapy. Methods: Small (1 cm 3 ), nonoverlapping image subvolumes (“blocks”) were automatically identified on the planning image to cover the tumor surface using a measure of the local intensity gradient. Blocks were independently and automatically registered to the on-treatment image using a rigid transform. To improve speed and robustness, registrations were performed iteratively from coarse to fine image resolution. At each resolution, all block displacements having a near-maximum similarity score were stored. From this list, a single displacement vector for each block was iteratively selected which maximized the consistency of displacement vectors across immediately neighboring blocks. These selected displacements were regularized using a median filter before proceeding to registrations at finer image resolutions. After evaluating all image resolutions, the global rigid transform of the on-treatment image was computed using a Procrustes analysis, providing the couch shift for patient setup correction. This algorithm was evaluated for 18 locally advanced lung cancer patients, each with 4–7 weekly on-treatment computed tomography scans having physician-delineated gross tumor volumes. Volume overlap (VO) and border displacement errors (BDE) were calculated relative to the nominal physician-identified targets to establish residual error after registration. Results: Implementation of multiresolution registration improved block matching accuracy by 39% compared to registration using only the full resolution images. By also considering multiple potential displacements per block, initial errors were reduced by 65%. Using the final implementation of the BMR algorithm, VO was significantly improved from 77% ± 21% (range: 0%–100%) in the initial bony alignment to 91% ± 8% (range: 56%–100%;p < 0.001). Left
Advances in Reactor Physics, Mathematics and Computation. Volume 1
Energy Technology Data Exchange (ETDEWEB)
1987-01-01
These proceedings of the international topical meeting on advances in reactor physics, mathematics and computation, volume one, are divided into 6 sessions bearing on: - session 1: Advances in computational methods including utilization of parallel processing and vectorization (7 conferences) - session 2: Fast, epithermal, reactor physics, calculation, versus measurements (9 conferences) - session 3: New fast and thermal reactor designs (9 conferences) - session 4: Thermal radiation and charged particles transport (7 conferences) - session 5: Super computers (7 conferences) - session 6: Thermal reactor design, validation and operating experience (8 conferences).
Special issue on advances in computer entertainment: editorial
Romão, T.; Romão, Teresa; Nijholt, Antinus; Cheok, J.D.; Cheok, Adrian David
2015-01-01
This special issue of the International Journal of Arts and Technology comprises a selection of papers from ACE 2012, the 9th International Conference on Advances in Computer Entertainment (Nijholt et al., 2012). ACE is the leading scientific forum for dissemination of cutting-edge research results in the area of entertainment computing. The main goal of ACE is to stimulate discussion in the development of new and compelling entertainment computing and interactive art concepts and application...
New algorithms for the symmetric tridiagonal eigenvalue computation
Energy Technology Data Exchange (ETDEWEB)
Pan, V. [City Univ. of New York, Bronx, NY (United States)]|[International Computer Sciences Institute, Berkeley, CA (United States)
1994-12-31
The author presents new algorithms that accelerate the bisection method for the symmetric eigenvalue problem. The algorithms rely on some new techniques, which include acceleration of Newton`s iteration and can also be further applied to acceleration of some other iterative processes, in particular, of iterative algorithms for approximating polynomial zeros.
A constrained conjugate gradient algorithm for computed tomography
Energy Technology Data Exchange (ETDEWEB)
Azevedo, S.G.; Goodman, D.M. [Lawrence Livermore National Lab., CA (United States)
1994-11-15
Image reconstruction from projections of x-ray, gamma-ray, protons and other penetrating radiation is a well-known problem in a variety of fields, and is commonly referred to as computed tomography (CT). Various analytical and series expansion methods of reconstruction and been used in the past to provide three-dimensional (3D) views of some interior quantity. The difficulties of these approaches lie in the cases where (a) the number of views attainable is limited, (b) the Poisson (or other) uncertainties are significant, (c) quantifiable knowledge of the object is available, but not implementable, or (d) other limitations of the data exist. We have adapted a novel nonlinear optimization procedure developed at LLNL to address limited-data image reconstruction problems. The technique, known as nonlinear least squares with general constraints or constrained conjugate gradients (CCG), has been successfully applied to a number of signal and image processing problems, and is now of great interest to the image reconstruction community. Previous applications of this algorithm to deconvolution problems and x-ray diffraction images for crystallography have shown the great promise.
The development of computational algorithms for manipulator inverse kinematics
International Nuclear Information System (INIS)
Sasaki, Shinobu
1989-10-01
A solution technique of the inverse kinematics for multi-joint robot manipulators has been considered to be one of the most cumbersome treatment due to non-linearity properties inclusive of trigonometric functions. The most traditional approach is to use the Jacobian matrix on linearization assumptions. This iterative technique, however, is attended with numerical problems having significant influences on the solution characteristics such as initial guess dependence and singularities. Taking these facts into consideration, new approaches have been proposed from different standpoints, which are based on polynomial transformation of kinematic model, the minimization technique in mathematical programming, vector-geometrical concept, and the separation of joint variables associated with the optimization problem. In terms of computer simulations, each approach was identified to be a useful algorithm which leads to theoretically accurate solutions to complicated inverse problems. In this way, the short-term goal of our studies on manipulator inverse problem in the R and D project of remote handling technology was accomplished with success, and consequently the present report sums up the results of basic studies on this matter. (author)
Katsuro-Hopkins, Oksana; Sabbagh, S. A.; Bialek, J. M.; Park, H. K.; Kim, J. Y.; You, K.-I.; Glasser, A. H.; Lao, L. L.
2007-11-01
Stability to ideal MHD kink/ballooning modes and the resistive wall mode (RWM) is investigated for the KSTAR tokamak. Free-boundary equilibria that comply with magnetic field coil current constraints are computed for monotonic and reversed shear safety factor profiles and H-mode tokamak pressure profiles. Advanced tokamak operation at moderate to low plasma internal inductance shows that a factor of two improvement in the plasma beta limit over the no-wall beta limit is possible for toroidal mode number of unity. The KSTAR conducting structure, passive stabilizers, and in-vessel control coils are modeled by the VALEN-3D code and the active RWM stabilization performance of the device is evaluated using both standard and advanced feedback algorithms. Steady-state power and voltage requirements for the system are estimated based on the expected noise on the RWM sensor signals. Using NSTX experimental RWM sensors noise data as input, a reduced VALEN state-space LQG controller is designed to realistically assess KSTAR stabilization system performance.
Gerjuoy, Edward
2005-06-01
The security of messages encoded via the widely used RSA public key encryption system rests on the enormous computational effort required to find the prime factors of a large number N using classical (conventional) computers. In 1994 Peter Shor showed that for sufficiently large N, a quantum computer could perform the factoring with much less computational effort. This paper endeavors to explain, in a fashion comprehensible to the nonexpert, the RSA encryption protocol; the various quantum computer manipulations constituting the Shor algorithm; how the Shor algorithm performs the factoring; and the precise sense in which a quantum computer employing Shor's algorithm can be said to accomplish the factoring of very large numbers with less computational effort than a classical computer. It is made apparent that factoring N generally requires many successive runs of the algorithm. Our analysis reveals that the probability of achieving a successful factorization on a single run is about twice as large as commonly quoted in the literature.
Davidson, Natalie R; Godfrey, Keith R; Alquaddoomi, Faisal; Nola, David; DiStefano, Joseph J
2017-05-01
We describe and illustrate use of DISTING, a novel web application for computing alternative structurally identifiable linear compartmental models that are input-output indistinguishable from a postulated linear compartmental model. Several computer packages are available for analysing the structural identifiability of such models, but DISTING is the first to be made available for assessing indistinguishability. The computational algorithms embedded in DISTING are based on advanced versions of established geometric and algebraic properties of linear compartmental models, embedded in a user-friendly graphic model user interface. Novel computational tools greatly speed up the overall procedure. These include algorithms for Jacobian matrix reduction, submatrix rank reduction, and parallelization of candidate rank computations in symbolic matrix analysis. The application of DISTING to three postulated models with respectively two, three and four compartments is given. The 2-compartment example is used to illustrate the indistinguishability problem; the original (unidentifiable) model is found to have two structurally identifiable models that are indistinguishable from it. The 3-compartment example has three structurally identifiable indistinguishable models. It is found from DISTING that the four-compartment example has five structurally identifiable models indistinguishable from the original postulated model. This example shows that care is needed when dealing with models that have two or more compartments which are neither perturbed nor observed, because the numbering of these compartments may be arbitrary. DISTING is universally and freely available via the Internet. It is easy to use and circumvents tedious and complicated algebraic analysis previously done by hand. Copyright © 2017 Elsevier B.V. All rights reserved.
Quantum computation: algorithms and implementation in quantum dot devices
Gamble, John King
In this thesis, we explore several aspects of both the software and hardware of quantum computation. First, we examine the computational power of multi-particle quantum random walks in terms of distinguishing mathematical graphs. We study both interacting and non-interacting multi-particle walks on strongly regular graphs, proving some limitations on distinguishing powers and presenting extensive numerical evidence indicative of interactions providing more distinguishing power. We then study the recently proposed adiabatic quantum algorithm for Google PageRank, and show that it exhibits power-law scaling for realistic WWW-like graphs. Turning to hardware, we next analyze the thermal physics of two nearby 2D electron gas (2DEG), and show that an analogue of the Coulomb drag effect exists for heat transfer. In some distance and temperature, this heat transfer is more significant than phonon dissipation channels. After that, we study the dephasing of two-electron states in a single silicon quantum dot. Specifically, we consider dephasing due to the electron-phonon coupling and charge noise, separately treating orbital and valley excitations. In an ideal system, dephasing due to charge noise is strongly suppressed due to a vanishing dipole moment. However, introduction of disorder or anharmonicity leads to large effective dipole moments, and hence possibly strong dephasing. Building on this work, we next consider more realistic systems, including structural disorder systems. We present experiment and theory, which demonstrate energy levels that vary with quantum dot translation, implying a structurally disordered system. Finally, we turn to the issues of valley mixing and valley-orbit hybridization, which occurs due to atomic-scale disorder at quantum well interfaces. We develop a new theoretical approach to study these effects, which we name the disorder-expansion technique. We demonstrate that this method successfully reproduces atomistic tight-binding techniques
Griffiths, Thomas L; Lieder, Falk; Goodman, Noah D
2015-04-01
Marr's levels of analysis-computational, algorithmic, and implementation-have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea is to push the notion of rationality, often used in defining computational-level models, deeper toward the algorithmic level. We offer a simple recipe for reverse-engineering the mind's cognitive strategies by deriving optimal algorithms for a series of increasingly more realistic abstract computational architectures, which we call "resource-rational analysis." Copyright © 2015 Cognitive Science Society, Inc.
Yu, Nengjie; Li Qing Feng; Tang, Chuan-Xiang; Zheng, Shuxin
2005-01-01
A new method for low energy electron beam profile measurement is advanced, which presents a full 2-D beam profile distribution other than the traditional 2-D beam profile distribution given by 1-D vertical and horizontal beam profiles. The method is based on the CT (Computer Tomography) algorithm. Multi-sets of data about the 1-D beam profile projections are attained by rotating the multi-wire scanner. Then a 2-D beam profile is reconstructed from these projections with CT algorithm. The principle of this method is presented. The simulation and the experiment results are compared and analyzed in detail.
Optimum design for rotor-bearing system using advanced generic algorithm
International Nuclear Information System (INIS)
Kim, Young Chan; Choi, Seong Pil; Yang, Bo Suk
2001-01-01
This paper describes a combinational method to compute the global and local solutions of optimization problems. The present hybrid algorithm uses both a generic algorithm and a local concentrate search algorithm (e.g simplex method). The hybrid algorithm is not only faster than the standard genetic algorithm but also supplies a more accurate solution. In addition, this algorithm can find the global and local optimum solutions. The present algorithm can be supplied to minimize the resonance response (Q factor) and to yield the critical speeds as far from the operating speed as possible. These factors play very important roles in designing a rotor-bearing system under the dynamic behavior constraint. In the present work, the shaft diameter, the bearing length, and clearance are used as the design variables
Computational neuroscience for advancing artificial intelligence
Directory of Open Access Journals (Sweden)
Fernando P. Ponce
2011-07-01
Full Text Available resumen del libro de Alonso, E. y Mondragón, E. (2011. Hershey, NY: Medical Information Science Reference. La neurociencia como disciplinapersigue el entendimiento del cerebro y su relación con el funcionamiento de la mente a través del análisis de la comprensión de la interacción de diversos procesos físicos, químicos y biológicos (Bassett & Gazzaniga, 2011. Por otra parte, numerosas disciplinasprogresivamente han realizado significativas contribuciones en esta empresa tales como la matemática, la psicología o la filosofía, entre otras. Producto de este esfuerzo, es que junto con la neurociencia tradicional han aparecido disciplinas complementarias como la neurociencia cognitiva, la neuropsicología o la neurocienciacomputacional (Bengio, 2007; Dayan & Abbott, 2005. En el contexto de la neurociencia computacional como disciplina complementaria a laneurociencia tradicional. Alonso y Mondragón (2011 editan el libroComputacional Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications.
Ziatdinov, Rushan; Musa, Sajid
2013-01-01
In this paper, we describe the possibilities of using a rapid mental computation system in elementary education. The system consists of a number of readily memorized operations that allow one to perform arithmetic computations very quickly. These operations are actually simple algorithms which can develop or improve the algorithmic thinking of pupils. Using a rapid mental computation system allows forming the basis for the study of computer science in secondary school.
Advanced algorithms for radiographic material discrimination and inspection system design
Energy Technology Data Exchange (ETDEWEB)
Gilbert, Andrew J. [Pacific Northwest National Laboratory, Richland, WA 99354 (United States); McDonald, Benjamin S., E-mail: benjamin.mcdonald@pnnl.gov [Pacific Northwest National Laboratory, Richland, WA 99354 (United States); Deinert, Mark R., E-mail: mdeinert@mines.edu [Colorado School of Mines, Golden, CO 80401 (United States)
2016-10-15
X-ray and neutron radiography are powerful tools for non-invasively inspecting the interior of objects. However, current methods are limited in their ability to differentiate materials when multiple materials are present, especially within large and complex objects. Past work has demonstrated that the spectral shift that X-ray beams undergo in traversing an object can be used to detect and quantify nuclear materials. The technique uses a spectrally sensitive detector and an inverse algorithm that varies the composition of the object until the X-ray spectrum predicted by X-ray transport matches the one measured. Here we show that this approach can be adapted to multi-mode radiography, with energy integrating detectors, and that the Cramér–Rao lower bound can be used to choose an optimal set of inspection modes a priori. We consider multi-endpoint X-ray radiography alone, or in combination with neutron radiography using deuterium–deuterium (DD) or deuterium–tritium (DT) sources. We show that for an optimal mode choice, the algorithm can improve discrimination between high-Z materials, specifically between tungsten and plutonium, and estimate plutonium mass within a simulated nuclear material storage system to within 1%.
A Flexible Reservation Algorithm for Advance Network Provisioning
Energy Technology Data Exchange (ETDEWEB)
Balman, Mehmet; Chaniotakis, Evangelos; Shoshani, Arie; Sim, Alex
2010-04-12
Many scientific applications need support from a communication infrastructure that provides predictable performance, which requires effective algorithms for bandwidth reservations. Network reservation systems such as ESnet's OSCARS, establish guaranteed bandwidth of secure virtual circuits for a certain bandwidth and length of time. However, users currently cannot inquire about bandwidth availability, nor have alternative suggestions when reservation requests fail. In general, the number of reservation options is exponential with the number of nodes n, and current reservation commitments. We present a novel approach for path finding in time-dependent networks taking advantage of user-provided parameters of total volume and time constraints, which produces options for earliest completion and shortest duration. The theoretical complexity is only O(n2r2) in the worst-case, where r is the number of reservations in the desired time interval. We have implemented our algorithm and developed efficient methodologies for incorporation into network reservation frameworks. Performance measurements confirm the theoretical predictions.
An efficient algorithm to compute subsets of points in ℤ n
Pacheco Martínez, Ana María; Real Jurado, Pedro
2012-01-01
In this paper we show a more efficient algorithm than that in [8] to compute subsets of points non-congruent by isometries. This algorithm can be used to reconstruct the object from the digital image. Both algorithms are compared, highlighting the improvements obtained in terms of CPU time.
The Support Reduction Algorithm for Computing Non-Parametric Function Estimates in Mixture Models
GROENEBOOM, PIET; JONGBLOED, GEURT; WELLNER, JON A.
2008-01-01
In this paper, we study an algorithm (which we call the support reduction algorithm) that can be used to compute non-parametric M-estimators in mixture models. The algorithm is compared with natural competitors in the context of convex regression and the ‘Aspect problem’ in quantum physics.
Arkin, Ethem; Tekinerdogan, Bedir
2016-01-01
Mapping parallel algorithms to parallel computing platforms requires several activities such as the analysis of the parallel algorithm, the definition of the logical configuration of the platform, the mapping of the algorithm to the logical configuration platform and the implementation of the
An extended Intelligent Water Drops algorithm for workflow scheduling in cloud computing environment
Directory of Open Access Journals (Sweden)
Shaymaa Elsherbiny
2018-03-01
Full Text Available Cloud computing is emerging as a high performance computing environment with a large scale, heterogeneous collection of autonomous systems and flexible computational architecture. Many resource management methods may enhance the efficiency of the whole cloud computing system. The key part of cloud computing resource management is resource scheduling. Optimized scheduling of tasks on the cloud virtual machines is an NP-hard problem and many algorithms have been presented to solve it. The variations among these schedulers are due to the fact that the scheduling strategies of the schedulers are adapted to the changing environment and the types of tasks. The focus of this paper is on workflows scheduling in cloud computing, which is gaining a lot of attention recently because workflows have emerged as a paradigm to represent complex computing problems. We proposed a novel algorithm extending the natural-based Intelligent Water Drops (IWD algorithm that optimizes the scheduling of workflows on the cloud. The proposed algorithm is implemented and embedded within the workflows simulation toolkit and tested in different simulated cloud environments with different cost models. Our algorithm showed noticeable enhancements over the classical workflow scheduling algorithms. We made a comparison between the proposed IWD-based algorithm with other well-known scheduling algorithms, including MIN-MIN, MAX-MIN, Round Robin, FCFS, and MCT, PSO and C-PSO, where the proposed algorithm presented noticeable enhancements in the performance and cost in most situations.
In-Place Algorithms for Computing (Layers of) Maxima
DEFF Research Database (Denmark)
Blunck, Henrik; Vahrenhold, Jan
2006-01-01
We describe space-efficient algorithms for solving problems related to finding maxima among points in two and three dimensions. Our algorithms run in optimal O(n log2 n) time and require O(1) space in addition to the representation of the input.......We describe space-efficient algorithms for solving problems related to finding maxima among points in two and three dimensions. Our algorithms run in optimal O(n log2 n) time and require O(1) space in addition to the representation of the input....
Mental Computation or Standard Algorithm? Children's Strategy Choices on Multi-Digit Subtractions
Torbeyns, Joke; Verschaffel, Lieven
2016-01-01
This study analyzed children's use of mental computation strategies and the standard algorithm on multi-digit subtractions. Fifty-eight Flemish 4th graders of varying mathematical achievement level were individually offered subtractions that either stimulated the use of mental computation strategies or the standard algorithm in one choice and two…
A heuristic algorithm for computing the Poincar\\'e series of the invariants of binary forms
Djoković, Dragomir Ž.
2006-01-01
We propose a heuristic algorithm for fast computation of the Poincar\\'{e} series $P_n(t)$ of the invariants of binary forms of degree $n$, viewed as rational functions. The algorithm is based on certain polynomial identities which remain to be proved rigorously. By using it, we have computed the $P_n(t)$ for $n\\le30$.
Advanced signal separation and recovery algorithms for digital x-ray spectroscopy
International Nuclear Information System (INIS)
Mahmoud, Imbaby I.; El-Tokhy, Mohamed S.
2015-01-01
X-ray spectroscopy is widely used for in-situ applications for samples analysis. Therefore, spectrum drawing and assessment of x-ray spectroscopy with high accuracy is the main scope of this paper. A Silicon Lithium Si(Li) detector that cooled with a nitrogen is used for signal extraction. The resolution of the ADC is 12 bits. Also, the sampling rate of ADC is 5 MHz. Hence, different algorithms are implemented. These algorithms were run on a personal computer with Intel core TM i5-3470 CPU and 3.20 GHz. These algorithms are signal preprocessing, signal separation and recovery algorithms, and spectrum drawing algorithm. Moreover, statistical measurements are used for evaluation of these algorithms. Signal preprocessing based on DC-offset correction and signal de-noising is performed. DC-offset correction was done by using minimum value of radiation signal. However, signal de-noising was implemented using fourth order finite impulse response (FIR) filter, linear phase least-square FIR filter, complex wavelet transforms (CWT) and Kalman filter methods. We noticed that Kalman filter achieves large peak signal to noise ratio (PSNR) and lower error than other methods. However, CWT takes much longer execution time. Moreover, three different algorithms that allow correction of x-ray signal overlapping are presented. These algorithms are 1D non-derivative peak search algorithm, second derivative peak search algorithm and extrema algorithm. Additionally, the effect of signal separation and recovery algorithms on spectrum drawing is measured. Comparison between these algorithms is introduced. The obtained results confirm that second derivative peak search algorithm as well as extrema algorithm have very small error in comparison with 1D non-derivative peak search algorithm. However, the second derivative peak search algorithm takes much longer execution time. Therefore, extrema algorithm introduces better results over other algorithms. It has the advantage of recovering and
Tools for Analyzing Computing Resource Management Strategies and Algorithms for SDR Clouds
Marojevic, Vuk; Gomez-Miguelez, Ismael; Gelonch, Antoni
2012-09-01
Software defined radio (SDR) clouds centralize the computing resources of base stations. The computing resource pool is shared between radio operators and dynamically loads and unloads digital signal processing chains for providing wireless communications services on demand. Each new user session request particularly requires the allocation of computing resources for executing the corresponding SDR transceivers. The huge amount of computing resources of SDR cloud data centers and the numerous session requests at certain hours of a day require an efficient computing resource management. We propose a hierarchical approach, where the data center is divided in clusters that are managed in a distributed way. This paper presents a set of computing resource management tools for analyzing computing resource management strategies and algorithms for SDR clouds. We use the tools for evaluating a different strategies and algorithms. The results show that more sophisticated algorithms can achieve higher resource occupations and that a tradeoff exists between cluster size and algorithm complexity.
Advances in FDTD computational electrodynamics photonics and nanotechnology
Oskooi, Ardavan; Johnson, Steven G
2013-01-01
Advances in photonics and nanotechnology have the potential to revolutionize humanity s ability to communicate and compute. To pursue these advances, it is mandatory to understand and properly model interactions of light with materials such as silicon and gold at the nanoscale, i.e., the span of a few tens of atoms laid side by side. These interactions are governed by the fundamental Maxwell s equations of classical electrodynamics, supplemented by quantum electrodynamics. This book presents the current state-of-the-art in formulating and implementing computational models of these interactions. Maxwell s equations are solved using the finite-difference time-domain (FDTD) technique, pioneered by the senior editor, whose prior Artech books in this area are among the top ten most-cited in the history of engineering. You discover the most important advances in all areas of FDTD and PSTD computational modeling of electromagnetic wave interactions. This cutting-edge resource helps you understand the latest develo...
Glushkov, A. V.; Gurskaya, M. Yu; Ignatenko, A. V.; Smirnov, A. V.; Serga, I. N.; Svinarenko, A. A.; Ternovsky, E. V.
2017-10-01
The consistent relativistic energy approach to the finite Fermi-systems (atoms and nuclei) in a strong realistic laser field is presented and applied to computing the multiphoton resonances parameters in some atoms and nuclei. The approach is based on the Gell-Mann and Low S-matrix formalism, multiphoton resonance lines moments technique and advanced Ivanov-Ivanova algorithm of calculating the Green’s function of the Dirac equation. The data for multiphoton resonance width and shift for the Cs atom and the 57Fe nucleus in dependence upon the laser intensity are listed.
Parameterized algorithmics for computational social choice : nine research challenges
Bredereck, R.; Chen, J.; Faliszewski, P.; Guo, J.; Niedermeier, R.; Woeginger, G.J.
2014-01-01
Computational Social Choice is an interdisciplinary research area involving Economics, Political Science, and Social Science on the one side, and Mathematics and Computer Science (including Artificial Intelligence and Multiagent Systems) on the other side. Typical computational problems studied in
Arkin, Ethem; Tekinerdogan, Bedir; Imre, Kayhan M.
2017-01-01
The need for high-performance computing together with the increasing trend from single processor to parallel computer architectures has leveraged the adoption of parallel computing. To benefit from parallel computing power, usually parallel algorithms are defined that can be mapped and executed
Projected role of advanced computational aerodynamic methods at the Lockheed-Georgia company
Lores, M. E.
1978-01-01
Experience with advanced computational methods being used at the Lockheed-Georgia Company to aid in the evaluation and design of new and modified aircraft indicates that large and specialized computers will be needed to make advanced three-dimensional viscous aerodynamic computations practical. The Numerical Aerodynamic Simulation Facility should be used to provide a tool for designing better aerospace vehicles while at the same time reducing development costs by performing computations using Navier-Stokes equations solution algorithms and permitting less sophisticated but nevertheless complex calculations to be made efficiently. Configuration definition procedures and data output formats can probably best be defined in cooperation with industry, therefore, the computer should handle many remote terminals efficiently. The capability of transferring data to and from other computers needs to be provided. Because of the significant amount of input and output associated with 3-D viscous flow calculations and because of the exceedingly fast computation speed envisioned for the computer, special attention should be paid to providing rapid, diversified, and efficient input and output.
Abdullahi, Mohammed; Ngadi, Md Asri
2016-01-01
Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS) has been shown to perform competitively with Particle Swarm Optimization (PSO). The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA) based SOS (SASOS) in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs) which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.
Directory of Open Access Journals (Sweden)
Mohammed Abdullahi
Full Text Available Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS has been shown to perform competitively with Particle Swarm Optimization (PSO. The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA based SOS (SASOS in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.
9th International Conference on Advanced Computing & Communication Technologies
Mandal, Jyotsna; Auluck, Nitin; Nagarajaram, H
2016-01-01
This book highlights a collection of high-quality peer-reviewed research papers presented at the Ninth International Conference on Advanced Computing & Communication Technologies (ICACCT-2015) held at Asia Pacific Institute of Information Technology, Panipat, India during 27–29 November 2015. The book discusses a wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academia and industry present their original work and exchange ideas, information, techniques and applications in the field of Advanced Computing and Communication Technology.
Computation of watersheds based on parallel graph algorithms
Meijster, A.; Roerdink, J.B.T.M.; Maragos, P; Schafer, RW; Butt, MA
1996-01-01
In this paper the implementation of a parallel watershed algorithm is described. The algorithm has been implemented on a Cray J932, which is a shared memory architecture with 32 processors. The watershed transform has generally been considered to be inherently sequential, but recently a few research
Teaching Computation in Primary School without Traditional Written Algorithms
Hartnett, Judy
2015-01-01
Concerns regarding the dominance of the traditional written algorithms in schools have been raised by many mathematics educators, yet the teaching of these procedures remains a dominant focus in in primary schools. This paper reports on a project in one school where the staff agreed to put the teaching of the traditional written algorithm aside,…
Faster Algorithms for Computing Longest Common Increasing Subsequences
DEFF Research Database (Denmark)
Kutz, Martin; Brodal, Gerth Stølting; Kaligosi, Kanela
2011-01-01
of the alphabet, and Sort is the time to sort each input sequence. For k⩾3 length-n sequences we present an algorithm which improves the previous best bound by more than a factor k for many inputs. In both cases, our algorithms are conceptually quite simple but rely on existing sophisticated data structures......We present algorithms for finding a longest common increasing subsequence of two or more input sequences. For two sequences of lengths n and m, where m⩾n, we present an algorithm with an output-dependent expected running time of and O(m) space, where ℓ is the length of an LCIS, σ is the size....... Finally, we introduce the problem of longest common weakly-increasing (or non-decreasing) subsequences (LCWIS), for which we present an -time algorithm for the 3-letter alphabet case. For the extensively studied longest common subsequence problem, comparable speedups have not been achieved for small...
Recovery Act: Advanced Direct Methanol Fuel Cell for Mobile Computing
Energy Technology Data Exchange (ETDEWEB)
Fletcher, James H. [University of North Florida; Cox, Philip [University of North Florida; Harrington, William J [University of North Florida; Campbell, Joseph L [University of North Florida
2013-09-03
ABSTRACT Project Title: Recovery Act: Advanced Direct Methanol Fuel Cell for Mobile Computing PROJECT OBJECTIVE The objective of the project was to advance portable fuel cell system technology towards the commercial targets of power density, energy density and lifetime. These targets were laid out in the DOE’s R&D roadmap to develop an advanced direct methanol fuel cell power supply that meets commercial entry requirements. Such a power supply will enable mobile computers to operate non-stop, unplugged from the wall power outlet, by using the high energy density of methanol fuel contained in a replaceable fuel cartridge. Specifically this project focused on balance-of-plant component integration and miniaturization, as well as extensive component, subassembly and integrated system durability and validation testing. This design has resulted in a pre-production power supply design and a prototype that meet the rigorous demands of consumer electronic applications. PROJECT TASKS The proposed work plan was designed to meet the project objectives, which corresponded directly with the objectives outlined in the Funding Opportunity Announcement: To engineer the fuel cell balance-of-plant and packaging to meet the needs of consumer electronic systems, specifically at power levels required for mobile computing. UNF used existing balance-of-plant component technologies developed under its current US Army CERDEC project, as well as a previous DOE project completed by PolyFuel, to further refine them to both miniaturize and integrate their functionality to increase the system power density and energy density. Benefits of UNF’s novel passive water recycling MEA (membrane electrode assembly) and the simplified system architecture it enabled formed the foundation of the design approach. The package design was hardened to address orientation independence, shock, vibration, and environmental requirements. Fuel cartridge and fuel subsystems were improved to ensure effective fuel
New or improved computational methods and advanced reactor design
International Nuclear Information System (INIS)
Nakagawa, Masayuki; Takeda, Toshikazu; Ushio, Tadashi
1997-01-01
Nuclear computational method has been studied continuously up to date, as a fundamental technology supporting the nuclear development. At present, research on computational method according to new theory and the calculating method thought to be difficult to practise are also continued actively to find new development due to splendid improvement of features of computer. In Japan, many light water type reactors are now in operations, new computational methods are induced for nuclear design, and a lot of efforts are concentrated for intending to more improvement of economics and safety. In this paper, some new research results on the nuclear computational methods and their application to nuclear design of the reactor were described for introducing recent trend of the nuclear design of the reactor. 1) Advancement of the computational method, 2) Reactor core design and management of the light water reactor, and 3) Nuclear design of the fast reactor. (G.K.)
Advances in equine computed tomography and use of contrast media.
Puchalski, Sarah M
2012-12-01
Advances in equine computed tomography have been made as a result of improvements in software and hardware and an increasing body of knowledge. Contrast media can be administered intravascularly or intrathecally. Contrast media is useful to differentiate between tissues of similar density. Equine computed tomography can be used for many different clinical conditions, including lameness diagnosis, fracture identification and characterization, preoperative planning, and characterization of skull diseases. Copyright © 2012 Elsevier Inc. All rights reserved.
Fast Algorithm for Computing the Discrete Hartley Transform of Type-II
Directory of Open Access Journals (Sweden)
Mounir Taha Hamood
2016-06-01
Full Text Available The generalized discrete Hartley transforms (GDHTs have proved to be an efficient alternative to the generalized discrete Fourier transforms (GDFTs for real-valued data applications. In this paper, the development of direct computation of radix-2 decimation-in-time (DIT algorithm for the fast calculation of the GDHT of type-II (DHT-II is presented. The mathematical analysis and the implementation of the developed algorithm are derived, showing that this algorithm possesses a regular structure and can be implemented in-place for efficient memory utilization.The performance of the proposed algorithm is analyzed and the computational complexity is calculated for different transform lengths. A comparison between this algorithm and existing DHT-II algorithms shows that it can be considered as a good compromise between the structural and computational complexities.
Innovations and Advances in Computer, Information, Systems Sciences, and Engineering
Sobh, Tarek
2013-01-01
Innovations and Advances in Computer, Information, Systems Sciences, and Engineering includes the proceedings of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CISSE 2011). The contents of this book are a set of rigorously reviewed, world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of Industrial Electronics, Technology and Automation, Telecommunications and Networking, Systems, Computing Sciences and Software Engineering, Engineering Education, Instructional Technology, Assessment, and E-learning.
Advances in computers dependable and secure systems engineering
Hurson, Ali
2012-01-01
Since its first volume in 1960, Advances in Computers has presented detailed coverage of innovations in computer hardware, software, theory, design, and applications. It has also provided contributors with a medium in which they can explore their subjects in greater depth and breadth than journal articles usually allow. As a result, many articles have become standard references that continue to be of sugnificant, lasting value in this rapidly expanding field. In-depth surveys and tutorials on new computer technologyWell-known authors and researchers in the fieldExtensive bibliographies with m
DNA algorithms of implementing biomolecular databases on a biological computer.
Chang, Weng-Long; Vasilakos, Athanasios V
2015-01-01
In this paper, DNA algorithms are proposed to perform eight operations of relational algebra (calculus), which include Cartesian product, union, set difference, selection, projection, intersection, join, and division, on biomolecular relational databases.
Advances in Reactor physics, mathematics and computation. Volume 3
Energy Technology Data Exchange (ETDEWEB)
1987-01-01
These proceedings of the international topical meeting on advances in reactor physics, mathematics and computation, volume 3, are divided into sessions bearing on: - poster sessions on benchmark and codes: 35 conferences - review of status of assembly spectrum codes: 9 conferences - Numerical methods in fluid mechanics and thermal hydraulics: 16 conferences - stochastic transport and methods: 7 conferences.
Editorial : Special Issue on Advances in Computer Entertainment
Romão, Teresa; Nijholt, Anton; Cheok, Adrian David
2015-01-01
This special issue of the International Journal of Arts and Technology comprises a selection of papers from ACE 2012, the 9th International Conference on Advances in Computer Entertainment (Nijholt et al., 2012). ACE is the leading scientific forum for the dissemination of cutting-edge research
Advances in Computer Entertainment. 10th International Conference, ACE 2013
Reidsma, Dennis; Katayose, H.; Nijholt, Antinus; Unknown, [Unknown
2013-01-01
These are the proceedings of the 10th International Conference on Advances in Computer Entertainment (ACE 2013), hosted by the Human Media Interaction research group of the Centre for Telematics and Information Technology at the University of Twente, The Netherlands. The ACE series of conferences,
Attitudes toward Advanced and Multivariate Statistics When Using Computers.
Kennedy, Robert L.; McCallister, Corliss Jean
This study investigated the attitudes toward statistics of graduate students who studied advanced statistics in a course in which the focus of instruction was the use of a computer program in class. The use of the program made it possible to provide an individualized, self-paced, student-centered, and activity-based course. The three sections…
Computer-Assisted Foreign Language Teaching and Learning: Technological Advances
Zou, Bin; Xing, Minjie; Wang, Yuping; Sun, Mingyu; Xiang, Catherine H.
2013-01-01
Computer-Assisted Foreign Language Teaching and Learning: Technological Advances highlights new research and an original framework that brings together foreign language teaching, experiments and testing practices that utilize the most recent and widely used e-learning resources. This comprehensive collection of research will offer linguistic…
[Advancements of computer chemistry in separation of Chinese medicine].
Li, Lingjuan; Hong, Hong; Xu, Xuesong; Guo, Liwei
2011-12-01
Separating technique of Chinese medicine is not only a key technique in the field of Chinese medicine' s research and development, but also a significant step in the modernization of Chinese medicinal preparation. Computer chemistry can build model and look for the regulations from Chinese medicine system which is full of complicated data. This paper analyzed the applicability, key technology, basic mode and common algorithm of computer chemistry applied in the separation of Chinese medicine, introduced the mathematic mode and the setting methods of Extraction kinetics, investigated several problems which based on traditional Chinese medicine membrane procession, and forecasted the application prospect.
Fiala, L.; Lokajicek, M.; Tumova, N.
2015-05-01
This volume of the IOP Conference Series is dedicated to scientific contributions presented at the 16th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2014), this year the motto was ''bridging disciplines''. The conference took place on September 1-5, 2014, at the Faculty of Civil Engineering, Czech Technical University in Prague, Czech Republic. The 16th edition of ACAT explored the boundaries of computing system architectures, data analysis algorithmics, automatic calculations, and theoretical calculation technologies. It provided a forum for confronting and exchanging ideas among these fields, where new approaches in computing technologies for scientific research were explored and promoted. This year's edition of the workshop brought together over 140 participants from all over the world. The workshop's 16 invited speakers presented key topics on advanced computing and analysis techniques in physics. During the workshop, 60 talks and 40 posters were presented in three tracks: Computing Technology for Physics Research, Data Analysis - Algorithms and Tools, and Computations in Theoretical Physics: Techniques and Methods. The round table enabled discussions on expanding software, knowledge sharing and scientific collaboration in the respective areas. ACAT 2014 was generously sponsored by Western Digital, Brookhaven National Laboratory, Hewlett Packard, DataDirect Networks, M Computers, Bright Computing, Huawei and PDV-Systemhaus. Special appreciations go to the track liaisons Lorenzo Moneta, Axel Naumann and Grigory Rubtsov for their work on the scientific program and the publication preparation. ACAT's IACC would also like to express its gratitude to all referees for their work on making sure the contributions are published in the proceedings. Our thanks extend to the conference liaisons Andrei Kataev and Jerome Lauret who worked with the local contacts and made this conference possible as well as to the program
Fast algorithm for automatically computing Strahler stream order
Lanfear, Kenneth J.
1990-01-01
An efficient algorithm was developed to determine Strahler stream order for segments of stream networks represented in a Geographic Information System (GIS). The algorithm correctly assigns Strahler stream order in topologically complex situations such as braided streams and multiple drainage outlets. Execution time varies nearly linearly with the number of stream segments in the network. This technique is expected to be particularly useful for studying the topology of dense stream networks derived from digital elevation model data.
[Activities of Research Institute for Advanced Computer Science
Gross, Anthony R. (Technical Monitor); Leiner, Barry M.
2001-01-01
The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administrations missions. RIACS is located at the NASA Ames Research Center, Moffett Field, California. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1. Automated Reasoning for Autonomous Systems Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. 2. Human-Centered Computing Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities. 3. High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to analysis of large scientific datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.
Parallel algorithms and archtectures for computational structural mechanics
Patrick, Merrell; Ma, Shing; Mahajan, Umesh
1989-01-01
The determination of the fundamental (lowest) natural vibration frequencies and associated mode shapes is a key step used to uncover and correct potential failures or problem areas in most complex structures. However, the computation time taken by finite element codes to evaluate these natural frequencies is significant, often the most computationally intensive part of structural analysis calculations. There is continuing need to reduce this computation time. This study addresses this need by developing methods for parallel computation.
Emerging Nanophotonic Applications Explored with Advanced Scientific Parallel Computing
Meng, Xiang
The domain of nanoscale optical science and technology is a combination of the classical world of electromagnetics and the quantum mechanical regime of atoms and molecules. Recent advancements in fabrication technology allows the optical structures to be scaled down to nanoscale size or even to the atomic level, which are far smaller than the wavelength they are designed for. These nanostructures can have unique, controllable, and tunable optical properties and their interactions with quantum materials can have important near-field and far-field optical response. Undoubtedly, these optical properties can have many important applications, ranging from the efficient and tunable light sources, detectors, filters, modulators, high-speed all-optical switches; to the next-generation classical and quantum computation, and biophotonic medical sensors. This emerging research of nanoscience, known as nanophotonics, is a highly interdisciplinary field requiring expertise in materials science, physics, electrical engineering, and scientific computing, modeling and simulation. It has also become an important research field for investigating the science and engineering of light-matter interactions that take place on wavelength and subwavelength scales where the nature of the nanostructured matter controls the interactions. In addition, the fast advancements in the computing capabilities, such as parallel computing, also become as a critical element for investigating advanced nanophotonic devices. This role has taken on even greater urgency with the scale-down of device dimensions, and the design for these devices require extensive memory and extremely long core hours. Thus distributed computing platforms associated with parallel computing are required for faster designs processes. Scientific parallel computing constructs mathematical models and quantitative analysis techniques, and uses the computing machines to analyze and solve otherwise intractable scientific challenges. In
2014 National Workshop on Advances in Communication and Computing
Prasanna, S; Sarma, Kandarpa; Saikia, Navajit
2015-01-01
The present volume is a compilation of research work in computation, communication, vision sciences, device design, fabrication, upcoming materials and related process design, etc. It is derived out of selected manuscripts submitted to the 2014 National Workshop on Advances in Communication and Computing (WACC 2014), Assam Engineering College, Guwahati, Assam, India which is emerging out to be a premier platform for discussion and dissemination of knowhow in this part of the world. The papers included in the volume are indicative of the recent thrust in computation, communications and emerging technologies. Certain recent advances in ZnO nanostructures for alternate energy generation provide emerging insights into an area that has promises for the energy sector including conservation and green technology. Similarly, scholarly contributions have focused on malware detection and related issues. Several contributions have focused on biomedical aspects including contributions related to cancer detection using act...
Zhang, Leihong; Liang, Dong; Li, Bei; Kang, Yi; Pan, Zilan; Zhang, Dawei; Gao, Xiumin; Ma, Xiuhua
2016-07-01
On the basis of analyzing the cosine light field with determined analytic expression and the pseudo-inverse method, the object is illuminated by a presetting light field with a determined discrete Fourier transform measurement matrix, and the object image is reconstructed by the pseudo-inverse method. The analytic expression of the algorithm of computational ghost imaging based on discrete Fourier transform measurement matrix is deduced theoretically, and compared with the algorithm of compressive computational ghost imaging based on random measurement matrix. The reconstruction process and the reconstruction error are analyzed. On this basis, the simulation is done to verify the theoretical analysis. When the sampling measurement number is similar to the number of object pixel, the rank of discrete Fourier transform matrix is the same as the one of the random measurement matrix, the PSNR of the reconstruction image of FGI algorithm and PGI algorithm are similar, the reconstruction error of the traditional CGI algorithm is lower than that of reconstruction image based on FGI algorithm and PGI algorithm. As the decreasing of the number of sampling measurement, the PSNR of reconstruction image based on FGI algorithm decreases slowly, and the PSNR of reconstruction image based on PGI algorithm and CGI algorithm decreases sharply. The reconstruction time of FGI algorithm is lower than that of other algorithms and is not affected by the number of sampling measurement. The FGI algorithm can effectively filter out the random white noise through a low-pass filter and realize the reconstruction denoising which has a higher denoising capability than that of the CGI algorithm. The FGI algorithm can improve the reconstruction accuracy and the reconstruction speed of computational ghost imaging.
Hard Real-Time Task Scheduling in Cloud Computing Using an Adaptive Genetic Algorithm
Directory of Open Access Journals (Sweden)
Amjad Mahmood
2017-04-01
Full Text Available In the Infrastructure-as-a-Service cloud computing model, virtualized computing resources in the form of virtual machines are provided over the Internet. A user can rent an arbitrary number of computing resources to meet their requirements, making cloud computing an attractive choice for executing real-time tasks. Economical task allocation and scheduling on a set of leased virtual machines is an important problem in the cloud computing environment. This paper proposes a greedy and a genetic algorithm with an adaptive selection of suitable crossover and mutation operations (named as AGA to allocate and schedule real-time tasks with precedence constraint on heterogamous virtual machines. A comprehensive simulation study has been done to evaluate the performance of the proposed algorithms in terms of their solution quality and efficiency. The simulation results show that AGA outperforms the greedy algorithm and non-adaptive genetic algorithm in terms of solution quality.
DEFF Research Database (Denmark)
Sidky, Emil Y.; Jørgensen, Jakob Heide; Pan, Xiaochuan
2012-01-01
The primal–dual optimization algorithm developed in Chambolle and Pock (CP) (2011 J. Math. Imag. Vis. 40 1–26) is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems...... for the purpose of designing iterative image reconstruction algorithms for CT. The primal–dual algorithm is briefly summarized in this paper, and its potential for prototyping is demonstrated by explicitly deriving CP algorithm instances for many optimization problems relevant to CT. An example application...
Feng, T.; Timmermans, H.J.P.
2016-01-01
Global Positioning System (GPS) technologies have been increasingly considered as an alternative to traditional travel survey methods to collect activity-travel data. Algorithms applied to extract activity-travel patterns vary from informal ad-hoc decision rules to advanced machine learning methods
Improved FHT Algorithms for Fast Computation of the Discrete Hartley Transform
Directory of Open Access Journals (Sweden)
M. T. Hamood
2013-05-01
Full Text Available In this paper, by using the symmetrical properties of the discrete Hartley transform (DHT, an improved radix-2 fast Hartley transform (FHT algorithm with arithmetic complexity comparable to that of the real-valued fast Fourier transform (RFFT is developed. It has a simple and regular butterfly structure and possesses the in-place computation property. Furthermore, using the same principles, the development can be extended to more efficient radix-based FHT algorithms. An example for the improved radix-4 FHT algorithm is given to show the validity of the presented method. The arithmetic complexity for the new algorithms are computed and then compared with the existing FHT algorithms. The results of these comparisons have shown that the developed algorithms reduce the number of multiplications and additions considerably.
A sub-cubic time algorithm for computing the quartet distance between two general trees
DEFF Research Database (Denmark)
Nielsen, Jesper; Kristensen, Anders Kabell; Mailund, Thomas
2011-01-01
Background When inferring phylogenetic trees different algorithms may give different trees. To study such effects a measure for the distance between two trees is useful. Quartet distance is one such measure, and is the number of quartet topologies that differ between two trees. Results We have...... derived a new algorithm for computing the quartet distance between a pair of general trees, i.e. trees where inner nodes can have any degree ≥ 3. The time and space complexity of our algorithm is sub-cubic in the number of leaves and does not depend on the degree of the inner nodes. This makes...... it the fastest algorithm so far for computing the quartet distance between general trees independent of the degree of the inner nodes. Conclusions We have implemented our algorithm and two of the best competitors. Our new algorithm is significantly faster than the competition and seems to run in close...
International Nuclear Information System (INIS)
Vecharynski, Eugene; Yang, Chao; Pask, John E.
2015-01-01
We present an iterative algorithm for computing an invariant subspace associated with the algebraically smallest eigenvalues of a large sparse or structured Hermitian matrix A. We are interested in the case in which the dimension of the invariant subspace is large (e.g., over several hundreds or thousands) even though it may still be small relative to the dimension of A. These problems arise from, for example, density functional theory (DFT) based electronic structure calculations for complex materials. The key feature of our algorithm is that it performs fewer Rayleigh–Ritz calculations compared to existing algorithms such as the locally optimal block preconditioned conjugate gradient or the Davidson algorithm. It is a block algorithm, and hence can take advantage of efficient BLAS3 operations and be implemented with multiple levels of concurrency. We discuss a number of practical issues that must be addressed in order to implement the algorithm efficiently on a high performance computer
Back propagation and Monte Carlo algorithms for neural network computations
International Nuclear Information System (INIS)
Junczys, R.; Wit, R.
1996-01-01
Results of teaching procedures for neural network for two different algorithms are presented. The first one is based on the well known back-propagation technique, the second is an adopted version of the Monte Carlo global minimum seeking method. Combination of these two, different in nature, approaches provides promising results. (author) nature, approaches provides promising results. (author)
Computationally efficient algorithms for statistical image processing : implementation in R
Langovoy, M.; Wittich, O.
2010-01-01
In the series of our earlier papers on the subject, we proposed a novel statistical hypothesis testing method for detection of objects in noisy images. The method uses results from percolation theory and random graph theory. We developed algorithms that allowed to detect objects of unknown shapes in
Advances in bio-inspired computing for combinatorial optimization problems
Pintea, Camelia-Mihaela
2013-01-01
Advances in Bio-inspired Combinatorial Optimization Problems' illustrates several recent bio-inspired efficient algorithms for solving NP-hard problems.Theoretical bio-inspired concepts and models, in particular for agents, ants and virtual robots are described. Large-scale optimization problems, for example: the Generalized Traveling Salesman Problem and the Railway Traveling Salesman Problem, are solved and their results are discussed.Some of the main concepts and models described in this book are: inner rule to guide ant search - a recent model in ant optimization, heterogeneous sensitive a
International Nuclear Information System (INIS)
Miller, I.; Roman, K.
1979-12-01
In order to perform studies of the influence of regional groundwater flow systems on the long-term performance of potential high-level nuclear waste repositories, it was determined that an adequate computer model would have to consider the full three-dimensional flow system. Golder Associates' SOLTR code, while three-dimensional, has an overly simple algorithm for simulating the passage of radionuclides from one aquifier to another above or below it. Part 1 of this report describes the algorithm developed to provide SOLTR with an improved capability for simulating interaquifer transport
Computer code qualification program for the Advanced CANDU Reactor
International Nuclear Information System (INIS)
Popov, N.K.; Wren, D.J.; Snell, V.G.; White, A.J.; Boczar, P.G.
2003-01-01
Atomic Energy of Canada Ltd (AECL) has developed and implemented a Software Quality Assurance program (SQA) to ensure that its analytical, scientific and design computer codes meet the required standards for software used in safety analyses. This paper provides an overview of the computer programs used in Advanced CANDU Reactor (ACR) safety analysis, and assessment of their applicability in the safety analyses of the ACR design. An outline of the incremental validation program, and an overview of the experimental program in support of the code validation are also presented. An outline of the SQA program used to qualify these computer codes is also briefly presented. To provide context to the differences in the SQA with respect to current CANDUs, the paper also provides an overview of the ACR design features that have an impact on the computer code qualification. (author)
Advanced computer graphics techniques as applied to the nuclear industry
International Nuclear Information System (INIS)
Thomas, J.J.; Koontz, A.S.
1985-08-01
Computer graphics is a rapidly advancing technological area in computer science. This is being motivated by increased hardware capability coupled with reduced hardware costs. This paper will cover six topics in computer graphics, with examples forecasting how each of these capabilities could be used in the nuclear industry. These topics are: (1) Image Realism with Surfaces and Transparency; (2) Computer Graphics Motion; (3) Graphics Resolution Issues and Examples; (4) Iconic Interaction; (5) Graphic Workstations; and (6) Data Fusion - illustrating data coming from numerous sources, for display through high dimensional, greater than 3-D, graphics. All topics will be discussed using extensive examples with slides, video tapes, and movies. Illustrations have been omitted from the paper due to the complexity of color reproduction. 11 refs., 2 figs., 3 tabs
Advanced Simulation and Computing FY17 Implementation Plan, Version 0
Energy Technology Data Exchange (ETDEWEB)
McCoy, Michel [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Archer, Bill [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hendrickson, Bruce [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wade, Doug [National Nuclear Security Administration (NNSA), Washington, DC (United States). Office of Advanced Simulation and Computing and Institutional Research and Development; Hoang, Thuc [National Nuclear Security Administration (NNSA), Washington, DC (United States). Computational Systems and Software Environment
2016-08-29
The Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, surety, and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational capabilities to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balance of resource, including technical staff, hardware, simulation software, and computer science solutions. ASC is now focused on increasing predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), and quantifying critical margins and uncertainties. Resolving each issue requires increasingly difficult analyses because the aging process has progressively moved the stockpile further away from the original test base. Where possible, the program also enables the use of high performance computing (HPC) and simulation tools to address broader national security needs, such as foreign nuclear weapon assessments and counter nuclear terrorism.
Advanced computer techniques for inverse modeling of electric current in cardiac tissue
Energy Technology Data Exchange (ETDEWEB)
Hutchinson, S.A.; Romero, L.A.; Diegert, C.F.
1996-08-01
For many years, ECG`s and vector cardiograms have been the tools of choice for non-invasive diagnosis of cardiac conduction problems, such as found in reentrant tachycardia or Wolff-Parkinson-White (WPW) syndrome. Through skillful analysis of these skin-surface measurements of cardiac generated electric currents, a physician can deduce the general location of heart conduction irregularities. Using a combination of high-fidelity geometry modeling, advanced mathematical algorithms and massively parallel computing, Sandia`s approach would provide much more accurate information and thus allow the physician to pinpoint the source of an arrhythmia or abnormal conduction pathway.
Simple and Effective Algorithms: Computer-Adaptive Testing.
Linacre, John Michael
Computer-adaptive testing (CAT) allows improved security, greater scoring accuracy, shorter testing periods, quicker availability of results, and reduced guessing and other undesirable test behavior. Simple approaches can be applied by the classroom teacher, or other content specialist, who possesses simple computer equipment and elementary…
A Tabu Search Algorithm for application placement in computer clustering
van der Gaast, Jelmer; Rietveld, Cornelieus A.; Gabor, Adriana; Zhang, Yingqian
2014-01-01
This paper presents and analyzes a model for the problem of placing applications on computer clusters (APP). In this problem, organizations requesting a set of software applications have to be assigned to computer clusters such that the costs of opening clusters and installing the necessary
A coordinate descent MM algorithm for fast computation of sparse logistic PCA
Lee, Seokho; Huang, Jianhua Z.
2013-01-01
Sparse logistic principal component analysis was proposed in Lee et al. (2010) for exploratory analysis of binary data. Relying on the joint estimation of multiple principal components, the algorithm therein is computationally too demanding
Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Usman, Mohammed Joda
2017-01-01
Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing. PMID:28467505
Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Abdulhamid, Shafi'i Muhammad; Usman, Mohammed Joda
2017-01-01
Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing.
Activities of the Research Institute for Advanced Computer Science
Oliger, Joseph
1994-01-01
The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under contract with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. Research at RIACS is currently being done in the following areas: (1) parallel computing; (2) advanced methods for scientific computing; (3) high performance networks; and (4) learning systems. RIACS technical reports are usually preprints of manuscripts that have been submitted to research journals or conference proceedings. A list of these reports for the period January 1, 1994 through December 31, 1994 is in the Reports and Abstracts section of this report.
Performance evaluation of scientific programs on advanced architecture computers
International Nuclear Information System (INIS)
Walker, D.W.; Messina, P.; Baille, C.F.
1988-01-01
Recently a number of advanced architecture machines have become commercially available. These new machines promise better cost-performance then traditional computers, and some of them have the potential of competing with current supercomputers, such as the Cray X/MP, in terms of maximum performance. This paper describes an on-going project to evaluate a broad range of advanced architecture computers using a number of complete scientific application programs. The computers to be evaluated include distributed- memory machines such as the NCUBE, INTEL and Caltech/JPL hypercubes, and the MEIKO computing surface, shared-memory, bus architecture machines such as the Sequent Balance and the Alliant, very long instruction word machines such as the Multiflow Trace 7/200 computer, traditional supercomputers such as the Cray X.MP and Cray-2, and SIMD machines such as the Connection Machine. Currently 11 application codes from a number of scientific disciplines have been selected, although it is not intended to run all codes on all machines. Results are presented for two of the codes (QCD and missile tracking), and future work is proposed
An algorithm to compute the canonical basis of an irreducible Uq(g)-module
de Graaf, W. A.
2002-01-01
An algorithm is described to compute the canonical basis of an irreducible module over a quantized enveloping algebra of a finite-dimensional semisimple Lie algebra. The algorithm works for modules that are constructed as a submodule of a tensor product of modules with known canonical bases.
A new fast algorithm for computing a complex number: Theoretic transforms
Reed, I. S.; Liu, K. Y.; Truong, T. K.
1977-01-01
A high-radix fast Fourier transformation (FFT) algorithm for computing transforms over GF(sq q), where q is a Mersenne prime, is developed to implement fast circular convolutions. This new algorithm requires substantially fewer multiplications than the conventional FFT.
A simple algorithm for computing positively weighted straight skeletons of monotone polygons☆
Biedl, Therese; Held, Martin; Huber, Stefan; Kaaser, Dominik; Palfrader, Peter
2015-01-01
We study the characteristics of straight skeletons of monotone polygonal chains and use them to devise an algorithm for computing positively weighted straight skeletons of monotone polygons. Our algorithm runs in O(nlogn) time and O(n) space, where n denotes the number of vertices of the polygon. PMID:25648376
A simple algorithm for computing positively weighted straight skeletons of monotone polygons.
Biedl, Therese; Held, Martin; Huber, Stefan; Kaaser, Dominik; Palfrader, Peter
2015-02-01
We study the characteristics of straight skeletons of monotone polygonal chains and use them to devise an algorithm for computing positively weighted straight skeletons of monotone polygons. Our algorithm runs in [Formula: see text] time and [Formula: see text] space, where n denotes the number of vertices of the polygon.
Advances in Reactor Physics, Mathematics and Computation. Volume 2
Energy Technology Data Exchange (ETDEWEB)
1987-01-01
These proceedings of the international topical meeting on advances in reactor physics, mathematics and computation, Volume 2, are divided into 7 sessions bearing on: - session 7: Deterministic transport methods 1 (7 conferences), - session 8: Interpretation and analysis of reactor instrumentation (6 conferences), - session 9: High speed computing applied to reactor operations (5 conferences), - session 10: Diffusion theory and kinetics (7 conferences), - session 11: Fast reactor design, validation and operating experience (8 conferences), - session 12: Deterministic transport methods 2 (7 conferences), - session 13: Application of expert systems to physical aspects of reactor design and operation.
A comparison between physicians and computer algorithms for form CMS-2728 data reporting.
Malas, Mohammed Said; Wish, Jay; Moorthi, Ranjani; Grannis, Shaun; Dexter, Paul; Duke, Jon; Moe, Sharon
2017-01-01
CMS-2728 form (Medical Evidence Report) assesses 23 comorbidities chosen to reflect poor outcomes and increased mortality risk. Previous studies questioned the validity of physician reporting on forms CMS-2728. We hypothesize that reporting of comorbidities by computer algorithms identifies more comorbidities than physician completion, and, therefore, is more reflective of underlying disease burden. We collected data from CMS-2728 forms for all 296 patients who had incident ESRD diagnosis and received chronic dialysis from 2005 through 2014 at Indiana University outpatient dialysis centers. We analyzed patients' data from electronic medical records systems that collated information from multiple health care sources. Previously utilized algorithms or natural language processing was used to extract data on 10 comorbidities for a period of up to 10 years prior to ESRD incidence. These algorithms incorporate billing codes, prescriptions, and other relevant elements. We compared the presence or unchecked status of these comorbidities on the forms to the presence or absence according to the algorithms. Computer algorithms had higher reporting of comorbidities compared to forms completion by physicians. This remained true when decreasing data span to one year and using only a single health center source. The algorithms determination was well accepted by a physician panel. Importantly, algorithms use significantly increased the expected deaths and lowered the standardized mortality ratios. Using computer algorithms showed superior identification of comorbidities for form CMS-2728 and altered standardized mortality ratios. Adapting similar algorithms in available EMR systems may offer more thorough evaluation of comorbidities and improve quality reporting. © 2016 International Society for Hemodialysis.
Medical image computing for computer-supported diagnostics and therapy. Advances and perspectives.
Handels, H; Ehrhardt, J
2009-01-01
Medical image computing has become one of the most challenging fields in medical informatics. In image-based diagnostics of the future software assistance will become more and more important, and image analysis systems integrating advanced image computing methods are needed to extract quantitative image parameters to characterize the state and changes of image structures of interest (e.g. tumors, organs, vessels, bones etc.) in a reproducible and objective way. Furthermore, in the field of software-assisted and navigated surgery medical image computing methods play a key role and have opened up new perspectives for patient treatment. However, further developments are needed to increase the grade of automation, accuracy, reproducibility and robustness. Moreover, the systems developed have to be integrated into the clinical workflow. For the development of advanced image computing systems methods of different scientific fields have to be adapted and used in combination. The principal methodologies in medical image computing are the following: image segmentation, image registration, image analysis for quantification and computer assisted image interpretation, modeling and simulation as well as visualization and virtual reality. Especially, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients and will gain importance in diagnostic and therapy of the future. From a methodical point of view the authors identify the following future trends and perspectives in medical image computing: development of optimized application-specific systems and integration into the clinical workflow, enhanced computational models for image analysis and virtual reality training systems, integration of different image computing methods, further integration of multimodal image data and biosignals and advanced methods for 4D medical image computing. The development of image analysis systems for diagnostic support or
Uhr, Leonard
1984-01-01
Computer Science and Applied Mathematics: Algorithm-Structured Computer Arrays and Networks: Architectures and Processes for Images, Percepts, Models, Information examines the parallel-array, pipeline, and other network multi-computers.This book describes and explores arrays and networks, those built, being designed, or proposed. The problems of developing higher-level languages for systems and designing algorithm, program, data flow, and computer structure are also discussed. This text likewise describes several sequences of successively more general attempts to combine the power of arrays wi
An Algorithm for Fast Computation of 3D Zernike Moments for Volumetric Images
Hosny, Khalid M.; Hafez, Mohamed A.
2012-01-01
An algorithm was proposed for very fast and low-complexity computation of three-dimensional Zernike moments. The 3D Zernike moments were expressed in terms of exact 3D geometric moments where the later are computed exactly through the mathematical integration of the monomial terms over the digital image/object voxels. A new symmetry-based method was proposed to compute 3D Zernike moments with 87% reduction in the computational complexity. A fast 1D cascade algorithm was also employed to add m...
Lee, Wei-Po; Hsiao, Yu-Ting; Hwang, Wei-Che
2014-01-16
To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high
Ergul, Ozgur
2014-01-01
The Multilevel Fast Multipole Algorithm (MLFMA) for Solving Large-Scale Computational Electromagnetic Problems provides a detailed and instructional overview of implementing MLFMA. The book: Presents a comprehensive treatment of the MLFMA algorithm, including basic linear algebra concepts, recent developments on the parallel computation, and a number of application examplesCovers solutions of electromagnetic problems involving dielectric objects and perfectly-conducting objectsDiscusses applications including scattering from airborne targets, scattering from red
Soft computing in design and manufacturing of advanced materials
Cios, Krzysztof J.; Baaklini, George Y; Vary, Alex
1993-01-01
The potential of fuzzy sets and neural networks, often referred to as soft computing, for aiding in all aspects of manufacturing of advanced materials like ceramics is addressed. In design and manufacturing of advanced materials, it is desirable to find which of the many processing variables contribute most to the desired properties of the material. There is also interest in real time quality control of parameters that govern material properties during processing stages. The concepts of fuzzy sets and neural networks are briefly introduced and it is shown how they can be used in the design and manufacturing processes. These two computational methods are alternatives to other methods such as the Taguchi method. The two methods are demonstrated by using data collected at NASA Lewis Research Center. Future research directions are also discussed.
An optimal algorithm for computing all subtree repeats in trees.
Flouri, T; Kobert, K; Pissis, S P; Stamatakis, A
2014-05-28
Given a labelled tree T, our goal is to group repeating subtrees of T into equivalence classes with respect to their topologies and the node labels. We present an explicit, simple and time-optimal algorithm for solving this problem for unrooted unordered labelled trees and show that the running time of our method is linear with respect to the size of T. By unordered, we mean that the order of the adjacent nodes (children/neighbours) of any node of T is irrelevant. An unrooted tree T does not have a node that is designated as root and can also be referred to as an undirected tree. We show how the presented algorithm can easily be modified to operate on trees that do not satisfy some or any of the aforementioned assumptions on the tree structure; for instance, how it can be applied to rooted, ordered or unlabelled trees.
Advanced Computing for 21st Century Accelerator Science and Technology
International Nuclear Information System (INIS)
Dragt, Alex J.
2004-01-01
Dr. Dragt of the University of Maryland is one of the Institutional Principal Investigators for the SciDAC Accelerator Modeling Project Advanced Computing for 21st Century Accelerator Science and Technology whose principal investigators are Dr. Kwok Ko (Stanford Linear Accelerator Center) and Dr. Robert Ryne (Lawrence Berkeley National Laboratory). This report covers the activities of Dr. Dragt while at Berkeley during spring 2002 and at Maryland during fall 2003
Parallel-Computing Architecture for JWST Wavefront-Sensing Algorithms
2011-09-01
results due to the increasing cost and complexity of each test. 2. ALGORITHM OVERVIEW Phase retrieval is an image-based wavefront-sensing...broadband illumination problems we have found that hand-tuning the right matrix sizes can account for a speedup of 86x faster. This comes from hand-picking...Wavefront Sensing and Control”. Proceedings of SPIE (2007) vol. 6687 (08). [5] Greenhouse, M. A., Drury , M. P., Dunn, J. L., Glazer, S. D., Greville, E
Study on Cloud Computing Resource Scheduling Strategy Based on the Ant Colony Optimization Algorithm
Lingna He; Qingshui Li; Linan Zhu
2012-01-01
In order to replace the traditional Internet software usage patterns and enterprise management mode, this paper proposes a new business calculation mode- cloud computing, resources scheduling strategy is the key technology in cloud computing, Based on the study of cloud computing system structure and the mode of operation, The key research for cloud computing the process of the work scheduling and resource allocation problems based on ant colony algorithm , Detailed analysis and design of the...
GTV-based prescription in SBRT for lung lesions using advanced dose calculation algorithms
International Nuclear Information System (INIS)
Lacornerie, Thomas; Lisbona, Albert; Mirabel, Xavier; Lartigau, Eric; Reynaert, Nick
2014-01-01
The aim of current study was to investigate the way dose is prescribed to lung lesions during SBRT using advanced dose calculation algorithms that take into account electron transport (type B algorithms). As type A algorithms do not take into account secondary electron transport, they overestimate the dose to lung lesions. Type B algorithms are more accurate but still no consensus is reached regarding dose prescription. The positive clinical results obtained using type A algorithms should be used as a starting point. In current work a dose-calculation experiment is performed, presenting different prescription methods. Three cases with three different sizes of peripheral lung lesions were planned using three different treatment platforms. For each individual case 60 Gy to the PTV was prescribed using a type A algorithm and the dose distribution was recalculated using a type B algorithm in order to evaluate the impact of the secondary electron transport. Secondly, for each case a type B algorithm was used to prescribe 48 Gy to the PTV, and the resulting doses to the GTV were analyzed. Finally, prescriptions based on specific GTV dose volumes were evaluated. When using a type A algorithm to prescribe the same dose to the PTV, the differences regarding median GTV doses among platforms and cases were always less than 10% of the prescription dose. The prescription to the PTV based on type B algorithms, leads to a more important variability of the median GTV dose among cases and among platforms, (respectively 24%, and 28%). However, when 54 Gy was prescribed as median GTV dose, using a type B algorithm, the variability observed was minimal. Normalizing the prescription dose to the median GTV dose for lung lesions avoids variability among different cases and treatment platforms of SBRT when type B algorithms are used to calculate the dose. The combination of using a type A algorithm to optimize a homogeneous dose in the PTV and using a type B algorithm to prescribe the
Computing gap free Pareto front approximations with stochastic search algorithms.
Schütze, Oliver; Laumanns, Marco; Tantar, Emilia; Coello, Carlos A Coello; Talbi, El-Ghazali
2010-01-01
Recently, a convergence proof of stochastic search algorithms toward finite size Pareto set approximations of continuous multi-objective optimization problems has been given. The focus was on obtaining a finite approximation that captures the entire solution set in some suitable sense, which was defined by the concept of epsilon-dominance. Though bounds on the quality of the limit approximation-which are entirely determined by the archiving strategy and the value of epsilon-have been obtained, the strategies do not guarantee to obtain a gap free approximation of the Pareto front. That is, such approximations A can reveal gaps in the sense that points f in the Pareto front can exist such that the distance of f to any image point F(a), a epsilon A, is "large." Since such gap free approximations are desirable in certain applications, and the related archiving strategies can be advantageous when memetic strategies are included in the search process, we are aiming in this work for such methods. We present two novel strategies that accomplish this task in the probabilistic sense and under mild assumptions on the stochastic search algorithm. In addition to the convergence proofs, we give some numerical results to visualize the behavior of the different archiving strategies. Finally, we demonstrate the potential for a possible hybridization of a given stochastic search algorithm with a particular local search strategy-multi-objective continuation methods-by showing that the concept of epsilon-dominance can be integrated into this approach in a suitable way.
Creating Very True Quantum Algorithms for Quantum Energy Based Computing
Nagata, Koji; Nakamura, Tadao; Geurdes, Han; Batle, Josep; Abdalla, Soliman; Farouk, Ahmed; Diep, Do Ngoc
2018-04-01
An interpretation of quantum mechanics is discussed. It is assumed that quantum is energy. An algorithm by means of the energy interpretation is discussed. An algorithm, based on the energy interpretation, for fast determining a homogeneous linear function f( x) := s. x = s 1 x 1 + s 2 x 2 + ⋯ + s N x N is proposed. Here x = ( x 1, … , x N ), x j ∈ R and the coefficients s = ( s 1, … , s N ), s j ∈ N. Given the interpolation values (f(1), f(2),...,f(N))=ěc {y}, the unknown coefficients s = (s1(ěc {y}),\\dots , sN(ěc {y})) of the linear function shall be determined, simultaneously. The speed of determining the values is shown to outperform the classical case by a factor of N. Our method is based on the generalized Bernstein-Vazirani algorithm to qudit systems. Next, by using M parallel quantum systems, M homogeneous linear functions are determined, simultaneously. The speed of obtaining the set of M homogeneous linear functions is shown to outperform the classical case by a factor of N × M.
Image analysis and modeling in medical image computing. Recent developments and advances.
Handels, H; Deserno, T M; Meinzer, H-P; Tolxdorff, T
2012-01-01
Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body
Why advanced computing? The key to space-based operations
Phister, Paul W., Jr.; Plonisch, Igor; Mineo, Jack
2000-11-01
The 'what is the requirement?' aspect of advanced computing and how it relates to and supports Air Force space-based operations is a key issue. In support of the Air Force Space Command's five major mission areas (space control, force enhancement, force applications, space support and mission support), two-fifths of the requirements have associated stringent computing/size implications. The Air Force Research Laboratory's 'migration to space' concept will eventually shift Science and Technology (S&T) dollars from predominantly airborne systems to airborne-and-space related S&T areas. One challenging 'space' area is in the development of sophisticated on-board computing processes for the next generation smaller, cheaper satellite systems. These new space systems (called microsats or nanosats) could be as small as a softball, yet perform functions that are currently being done by large, vulnerable ground-based assets. The Joint Battlespace Infosphere (JBI) concept will be used to manage the overall process of space applications coupled with advancements in computing. The JBI can be defined as a globally interoperable information 'space' which aggregates, integrates, fuses, and intelligently disseminates all relevant battlespace knowledge to support effective decision-making at all echelons of a Joint Task Force (JTF). This paper explores a single theme -- on-board processing is the best avenue to take advantage of advancements in high-performance computing, high-density memories, communications, and re-programmable architecture technologies. The goal is to break away from 'no changes after launch' design to a more flexible design environment that can take advantage of changing space requirements and needs while the space vehicle is 'on orbit.'
Cloud computing task scheduling strategy based on improved differential evolution algorithm
Ge, Junwei; He, Qian; Fang, Yiqiu
2017-04-01
In order to optimize the cloud computing task scheduling scheme, an improved differential evolution algorithm for cloud computing task scheduling is proposed. Firstly, the cloud computing task scheduling model, according to the model of the fitness function, and then used improved optimization calculation of the fitness function of the evolutionary algorithm, according to the evolution of generation of dynamic selection strategy through dynamic mutation strategy to ensure the global and local search ability. The performance test experiment was carried out in the CloudSim simulation platform, the experimental results show that the improved differential evolution algorithm can reduce the cloud computing task execution time and user cost saving, good implementation of the optimal scheduling of cloud computing tasks.
International Nuclear Information System (INIS)
Fischler, M.
1992-10-01
The Fermilab Computer R ampersand D and Theory departments have for several years collaborated on a multi-GFLOP (recently upgraded to 50 GFLOP) system for lattice gauge calculations. The primary emphasis is on flexibility and ease of algorithm development. This system (ACPMAPS) has been in use for some time, allowing theorists to produce QCD results with relevance for the analysis of experimental data. We present general observations about benefits of such a scientist-oriented system, and summarize some of the advances recently made. We also discuss what was discovered about features needed in a useful algorithm exploration platform. These lessons can be applied to the design and evaluation of future massively parallel systems (commercial or otherwise)
A New Method of Histogram Computation for Efficient Implementation of the HOG Algorithm
Directory of Open Access Journals (Sweden)
Mariana-Eugenia Ilas
2018-03-01
Full Text Available In this paper we introduce a new histogram computation method to be used within the histogram of oriented gradients (HOG algorithm. The new method replaces the arctangent with the slope computation and the classical magnitude allocation based on interpolation with a simpler algorithm. The new method allows a more efficient implementation of HOG in general, and particularly in field-programmable gate arrays (FPGAs, by considerably reducing the area (thus increasing the level of parallelism, while maintaining very close classification accuracy compared to the original algorithm. Thus, the new method is attractive for many applications, including car detection and classification.
A Line Search Multilevel Truncated Newton Algorithm for Computing the Optical Flow
Directory of Open Access Journals (Sweden)
Lluís Garrido
2015-06-01
Full Text Available We describe the implementation details and give the experimental results of three optimization algorithms for dense optical flow computation. In particular, using a line search strategy, we evaluate the performance of the unilevel truncated Newton method (LSTN, a multiresolution truncated Newton (MR/LSTN and a full multigrid truncated Newton (FMG/LSTN. We use three image sequences and four models of optical flow for performance evaluation. The FMG/LSTN algorithm is shown to lead to better optical flow estimation with less computational work than both the LSTN and MR/LSTN algorithms.
International Nuclear Information System (INIS)
Vignes, J.
1986-01-01
Any result of algorithms provided by a computer always contains an error resulting from floating-point arithmetic round-off error propagation. Furthermore signal processing algorithms are also generally performed with data containing errors. The permutation-perturbation method, also known under the name CESTAC (controle et estimation stochastique d'arrondi de calcul) is a very efficient practical method for evaluating these errors and consequently for estimating the exact significant decimal figures of any result of algorithms performed on a computer. The stochastic approach of this method, its probabilistic proof, and the perfect agreement between the theoretical and practical aspects are described in this paper [fr
Fast GPU-based computation of the sensitivity matrix for a PET list-mode OSEM algorithm
Energy Technology Data Exchange (ETDEWEB)
Nassiri, Moulay Ali; Carrier, Jean-Francois [Montreal Univ., QC (Canada). Dept. de Radio-Oncologie; Hissoiny, Sami [Ecole Polytechnique de Montreal, QC (Canada). Dept. de Genie Informatique et Genie Logiciel; Despres, Philippe [Quebec Univ. (Canada). Dept. de Radio-Oncologie
2011-07-01
One of the obstacle in introducing a list-mode PET reconstruction algorithm for routine clinical use is the long computation time required for the sensitivity matrix calculation. This matrix must be computed for each study because it depends on the object attenuation map. During the last decade, studies have shown that 3D list-mode OSEM reconstruction algorithms could be effectively performed and considerably accelerated by GPU devices. However, most of that preliminary work (1) was done for pre-clinical PET systems in which the number of LORs is small compared to modern human PET systems and (2) supposed that the sensitivity matrix is pre-calculated. The time required to compute this matrix can however be longer than the reconstruction time itself. The objective of this work is to investigate the performance of sensitivity matrix calculations in terms of computation time with modern GPUs, for clinical fully 3D LM-OSEM for modern PET scanners. For this purpose, sensitivity matrix calculations and full list-mode OSEM reconstruction for human PET systems were implemented on GPUs using the CUDA framework. The system matrices were built on-the-fly by using the multi-ray Siddon algorithm. The time to compute the sensitivity matrix for 288 x 288 x 57 arrays using 3 tangential LORs was 29 seconds. The 3D LM-OSEM algorithm, including the sensitivity matrix calculation, was performed for the same LORs in 71 seconds for 62 millions events, 6 frames and 1 iterations. This work let envision fast reconstructions for advanced PET application such as dynamic studies and parametric image reconstruction. (orig.)
Magnet sorting algorithms for insertion devices for the Advanced Light Source
International Nuclear Information System (INIS)
Humphries, D.; Hoyer, E.; Kincaid, B.; Marks, S.; Schlueter, R.
1994-01-01
Insertion devices for the Advanced Light Source (ALS) incorporate up to 3,000 magnet blocks each for pole energization. In order to minimize field errors, these magnets must be measured, sorted and assigned appropriate locations and orientation in the magnetic structures. Sorting must address multiple objectives, including pole excitation and minimization of integrated multipole fields from minor field components in the magnets. This is equivalent to a combinatorial minimization problem with a large configuration space. Multi-stage sorting algorithms use ordering and pairing schemes in conjunction with other combinatorial methods to solve the minimization problem. This paper discusses objective functions, solution algorithms and results of application to magnet block measurement data
DEFF Research Database (Denmark)
Wøhlk, Sanne; Laporte, Gilbert
2017-01-01
The aim of this paper is to computationally compare several algorithms for the Minimum Cost Perfect Matching Problem on an undirected complete graph. Our work is motivated by the need to solve large instances of the Capacitated Arc Routing Problem (CARP) arising in the optimization of garbage...... collection in Denmark. Common heuristics for the CARP involve the optimal matching of the odd-degree nodes of a graph. The algorithms used in the comparison include the CPLEX solution of an exact formulation, the LEDA matching algorithm, a recent implementation of the Blossom algorithm, as well as six...
Computational experiment approach to advanced secondary mathematics curriculum
Abramovich, Sergei
2014-01-01
This book promotes the experimental mathematics approach in the context of secondary mathematics curriculum by exploring mathematical models depending on parameters that were typically considered advanced in the pre-digital education era. This approach, by drawing on the power of computers to perform numerical computations and graphical constructions, stimulates formal learning of mathematics through making sense of a computational experiment. It allows one (in the spirit of Freudenthal) to bridge serious mathematical content and contemporary teaching practice. In other words, the notion of teaching experiment can be extended to include a true mathematical experiment. When used appropriately, the approach creates conditions for collateral learning (in the spirit of Dewey) to occur including the development of skills important for engineering applications of mathematics. In the context of a mathematics teacher education program, this book addresses a call for the preparation of teachers capable of utilizing mo...
Advances in neural networks computational intelligence for ICT
Esposito, Anna; Morabito, Francesco; Pasero, Eros
2016-01-01
This carefully edited book is putting emphasis on computational and artificial intelligent methods for learning and their relative applications in robotics, embedded systems, and ICT interfaces for psychological and neurological diseases. The book is a follow-up of the scientific workshop on Neural Networks (WIRN 2015) held in Vietri sul Mare, Italy, from the 20th to the 22nd of May 2015. The workshop, at its 27th edition became a traditional scientific event that brought together scientists from many countries, and several scientific disciplines. Each chapter is an extended version of the original contribution presented at the workshop, and together with the reviewers’ peer revisions it also benefits from the live discussion during the presentation. The content of book is organized in the following sections. 1. Introduction, 2. Machine Learning, 3. Artificial Neural Networks: Algorithms and models, 4. Intelligent Cyberphysical and Embedded System, 5. Computational Intelligence Methods for Biomedical ICT in...
Efficient Geo-Computational Algorithms for Constructing Space-Time Prisms in Road Networks
Directory of Open Access Journals (Sweden)
Hui-Ping Chen
2016-11-01
Full Text Available The Space-time prism (STP is a key concept in time geography for analyzing human activity-travel behavior under various Space-time constraints. Most existing time-geographic studies use a straightforward algorithm to construct STPs in road networks by using two one-to-all shortest path searches. However, this straightforward algorithm can introduce considerable computational overhead, given the fact that accessible links in a STP are generally a small portion of the whole network. To address this issue, an efficient geo-computational algorithm, called NTP-A*, is proposed. The proposed NTP-A* algorithm employs the A* and branch-and-bound techniques to discard inaccessible links during two shortest path searches, and thereby improves the STP construction performance. Comprehensive computational experiments are carried out to demonstrate the computational advantage of the proposed algorithm. Several implementation techniques, including the label-correcting technique and the hybrid link-node labeling technique, are discussed and analyzed. Experimental results show that the proposed NTP-A* algorithm can significantly improve STP construction performance in large-scale road networks by a factor of 100, compared with existing algorithms.
Dynamic Programming and Graph Algorithms in Computer Vision*
Felzenszwalb, Pedro F.; Zabih, Ramin
2013-01-01
Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting, since by carefully exploiting problem structure they often provide non-trivial guarantees concerning solution quality. In this paper we briefly review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo; the mid-level problem of interactive object segmentation; and the high-level problem of model-based recognition. PMID:20660950
Noise filtering algorithm for the MFTF-B computer based control system
International Nuclear Information System (INIS)
Minor, E.G.
1983-01-01
An algorithm to reduce the message traffic in the MFTF-B computer based control system is described. The algorithm filters analog inputs to the control system. Its purpose is to distinguish between changes in the inputs due to noise and changes due to significant variations in the quantity being monitored. Noise is rejected while significant changes are reported to the control system data base, thus keeping the data base updated with a minimum number of messages. The algorithm is memory efficient, requiring only four bytes of storage per analog channel, and computationally simple, requiring only subtraction and comparison. Quantitative analysis of the algorithm is presented for the case of additive Gaussian noise. It is shown that the algorithm is stable and tends toward the mean value of the monitored variable over a wide variety of additive noise distributions
Algorithmic mechanisms for reliable crowdsourcing computation under collusion.
Fernández Anta, Antonio; Georgiou, Chryssis; Mosteiro, Miguel A; Pareja, Daniel
2015-01-01
We consider a computing system where a master processor assigns a task for execution to worker processors that may collude. We model the workers' decision of whether to comply (compute the task) or not (return a bogus result to save the computation cost) as a game among workers. That is, we assume that workers are rational in a game-theoretic sense. We identify analytically the parameter conditions for a unique Nash Equilibrium where the master obtains the correct result. We also evaluate experimentally mixed equilibria aiming to attain better reliability-profit trade-offs. For a wide range of parameter values that may be used in practice, our simulations show that, in fact, both master and workers are better off using a pure equilibrium where no worker cheats, even under collusion, and even for colluding behaviors that involve deviating from the game.
A recursive algorithm for computing the inverse of the Vandermonde matrix
Directory of Open Access Journals (Sweden)
Youness Aliyari Ghassabeh
2016-12-01
Full Text Available The inverse of a Vandermonde matrix has been used for signal processing, polynomial interpolation, curve fitting, wireless communication, and system identification. In this paper, we propose a novel fast recursive algorithm to compute the inverse of a Vandermonde matrix. The algorithm computes the inverse of a higher order Vandermonde matrix using the available lower order inverse matrix with a computational cost of $ O(n^2 $. The proposed algorithm is given in a matrix form, which makes it appropriate for hardware implementation. The running time of the proposed algorithm to find the inverse of a Vandermonde matrix using a lower order Vandermonde matrix is compared with the running time of the matrix inversion function implemented in MATLAB.
International Nuclear Information System (INIS)
Murase, Kenya; Itoh, Hisao; Mogami, Hiroshi; Ishine, Masashiro; Kawamura, Masashi; Iio, Atsushi; Hamamoto, Ken
1987-01-01
A computer based simulation method was developed to assess the relative effectiveness and availability of various attenuation compensation algorithms in single photon emission computed tomography (SPECT). The effect of the nonuniformity of attenuation coefficient distribution in the body, the errors in determining a body contour and the statistical noise on reconstruction accuracy and the computation time in using the algorithms were studied. The algorithms were classified into three groups: precorrection, post correction and iterative correction methods. Furthermore, a hybrid method was devised by combining several methods. This study will be useful for understanding the characteristics limitations and strengths of the algorithms and searching for a practical correction method for photon attenuation in SPECT. (orig.)
A subspace preconditioning algorithm for eigenvector/eigenvalue computation
Energy Technology Data Exchange (ETDEWEB)
Bramble, J.H.; Knyazev, A.V.; Pasciak, J.E.
1996-12-31
We consider the problem of computing a modest number of the smallest eigenvalues along with orthogonal bases for the corresponding eigen-spaces of a symmetric positive definite matrix. In our applications, the dimension of a matrix is large and the cost of its inverting is prohibitive. In this paper, we shall develop an effective parallelizable technique for computing these eigenvalues and eigenvectors utilizing subspace iteration and preconditioning. Estimates will be provided which show that the preconditioned method converges linearly and uniformly in the matrix dimension when used with a uniform preconditioner under the assumption that the approximating subspace is close enough to the span of desired eigenvectors.
Energy Technology Data Exchange (ETDEWEB)
Kim, Jung-Taek (Korea Atomic Energy Research Institute, Daejon, Korea); Luk, Vincent K.
2005-05-01
The overall goal of this joint research project was to develop and demonstrate advanced sensors and computational technology for continuous monitoring of the condition of components, structures, and systems in advanced and next-generation nuclear power plants (NPPs). This project included investigating and adapting several advanced sensor technologies from Korean and US national laboratory research communities, some of which were developed and applied in non-nuclear industries. The project team investigated and developed sophisticated signal processing, noise reduction, and pattern recognition techniques and algorithms. The researchers installed sensors and conducted condition monitoring tests on two test loops, a check valve (an active component) and a piping elbow (a passive component), to demonstrate the feasibility of using advanced sensors and computational technology to achieve the project goal. Acoustic emission (AE) devices, optical fiber sensors, accelerometers, and ultrasonic transducers (UTs) were used to detect mechanical vibratory response of check valve and piping elbow in normal and degraded configurations. Chemical sensors were also installed to monitor the water chemistry in the piping elbow test loop. Analysis results of processed sensor data indicate that it is feasible to differentiate between the normal and degraded (with selected degradation mechanisms) configurations of these two components from the acquired sensor signals, but it is questionable that these methods can reliably identify the level and type of degradation. Additional research and development efforts are needed to refine the differentiation techniques and to reduce the level of uncertainties.
Milde, Anja; Volkwein, Stefan
2018-01-01
This edited monograph collects research contributions and addresses the advancement of efficient numerical procedures in the area of model order reduction (MOR) for simulation, optimization and control. The topical scope includes, but is not limited to, new out-of-the-box algorithmic solutions for scientific computing, e.g. reduced basis methods for industrial problems and MOR approaches for electrochemical processes. The target audience comprises research experts and practitioners in the field of simulation, optimization and control, but the book may also be beneficial for graduate students alike. .
An algorithm of discovering signatures from DNA databases on a computer cluster.
Lee, Hsiao Ping; Sheu, Tzu-Fang
2014-10-05
Signatures are short sequences that are unique and not similar to any other sequence in a database that can be used as the basis to identify different species. Even though several signature discovery algorithms have been proposed in the past, these algorithms require the entirety of databases to be loaded in the memory, thus restricting the amount of data that they can process. It makes those algorithms unable to process databases with large amounts of data. Also, those algorithms use sequential models and have slower discovery speeds, meaning that the efficiency can be improved. In this research, we are debuting the utilization of a divide-and-conquer strategy in signature discovery and have proposed a parallel signature discovery algorithm on a computer cluster. The algorithm applies the divide-and-conquer strategy to solve the problem posed to the existing algorithms where they are unable to process large databases and uses a parallel computing mechanism to effectively improve the efficiency of signature discovery. Even when run with just the memory of regular personal computers, the algorithm can still process large databases such as the human whole-genome EST database which were previously unable to be processed by the existing algorithms. The algorithm proposed in this research is not limited by the amount of usable memory and can rapidly find signatures in large databases, making it useful in applications such as Next Generation Sequencing and other large database analysis and processing. The implementation of the proposed algorithm is available at http://www.cs.pu.edu.tw/~fang/DDCSDPrograms/DDCSD.htm.
Computer Adaptive Testing, Big Data and Algorithmic Approaches to Education
Thompson, Greg
2017-01-01
This article critically considers the promise of computer adaptive testing (CAT) and digital data to provide better and quicker data that will improve the quality, efficiency and effectiveness of schooling. In particular, it uses the case of the Australian NAPLAN test that will become an online, adaptive test from 2016. The article argues that…
Iterative algorithms to approximate canonieal Gabor windows: Computational aspects
DEFF Research Database (Denmark)
Janssen, A. J. E. M.; Søndergaard, Peter Lempel
2007-01-01
In this article we investigate the computational aspects of some recently proposed iterative methods for approximating the canonical tight and canonical dual window of a Gabor frame (g, a, b). The iterations start with the window g while the iteration steps comprise the window g, the k(th) iteran...
Effective computing algorithm for maintenance optimization of highly reliable systems
Czech Academy of Sciences Publication Activity Database
Briš, R.; Byczanski, Petr
2013-01-01
Roč. 109, č. 1 (2013), s. 77-85 ISSN 0951-8320 R&D Projects: GA MŠk(CZ) ED1.1.00/02.0070 Institutional support: RVO:68145535 Keywords : exact computing * maintenance * optimization * unavailability Subject RIV: BA - General Mathematics Impact factor: 2.048, year: 2013 http://www.sciencedirect.com/science/article/pii/S0951832012001639
A computational algorithm addressing how vessel length might depend on vessel diameter
Jing Cai; Shuoxin Zhang; Melvin T. Tyree
2010-01-01
The objective of this method paper was to examine a computational algorithm that may reveal how vessel length might depend on vessel diameter within any given stem or species. The computational method requires the assumption that vessels remain approximately constant in diameter over their entire length. When this method is applied to three species or hybrids in the...
Cognitive Correlates of Performance in Algorithms in a Computer Science Course for High School
Avancena, Aimee Theresa; Nishihara, Akinori
2014-01-01
Computer science for high school faces many challenging issues. One of these is whether the students possess the appropriate cognitive ability for learning the fundamentals of computer science. Online tests were created based on known cognitive factors and fundamental algorithms and were implemented among the second grade students in the…
Microscope self-calibration based on micro laser line imaging and soft computing algorithms
Apolinar Muñoz Rodríguez, J.
2018-06-01
A technique to perform microscope self-calibration via micro laser line and soft computing algorithms is presented. In this technique, the microscope vision parameters are computed by means of soft computing algorithms based on laser line projection. To implement the self-calibration, a microscope vision system is constructed by means of a CCD camera and a 38 μm laser line. From this arrangement, the microscope vision parameters are represented via Bezier approximation networks, which are accomplished through the laser line position. In this procedure, a genetic algorithm determines the microscope vision parameters by means of laser line imaging. Also, the approximation networks compute the three-dimensional vision by means of the laser line position. Additionally, the soft computing algorithms re-calibrate the vision parameters when the microscope vision system is modified during the vision task. The proposed self-calibration improves accuracy of the traditional microscope calibration, which is accomplished via external references to the microscope system. The capability of the self-calibration based on soft computing algorithms is determined by means of the calibration accuracy and the micro-scale measurement error. This contribution is corroborated by an evaluation based on the accuracy of the traditional microscope calibration.
An advanced course in computational nuclear physics bridging the scales from quarks to neutron stars
Lombardo, Maria; Kolck, Ubirajara
2017-01-01
This graduate-level text collects and synthesizes a series of ten lectures on the nuclear quantum many-body problem. Starting from our current understanding of the underlying forces, it presents recent advances within the field of lattice quantum chromodynamics before going on to discuss effective field theories, central many-body methods like Monte Carlo methods, coupled cluster theories, the similarity renormalization group approach, Green’s function methods and large-scale diagonalization approaches. Algorithmic and computational advances show particular promise for breakthroughs in predictive power, including proper error estimates, a better understanding of the underlying effective degrees of freedom and of the respective forces at play. Enabled by recent improvements in theoretical, experimental and numerical techniques, the state-of-the art applications considered in this volume span the entire range, from our smallest components – quarks and gluons as the mediators of the strong force – to the c...
Design and installation of advanced computer safety related instrumentation
International Nuclear Information System (INIS)
Koch, S.; Andolina, K.; Ruether, J.
1993-01-01
The rapidly developing area of computer systems creates new opportunities for commercial utilities operating nuclear reactors to improve plant operation and efficiency. Two of the main obstacles to utilizing the new technology in safety-related applications is the current policy of the licensing agencies and the fear of decision making managers to introduce new technologies. Once these obstacles are overcome, advanced diagnostic systems, CRT-based displays, and advanced communication channels can improve plant operation considerably. The article discusses outstanding issues in the area of designing, qualifying, and licensing of computer-based instrumentation and control systems. The authors describe the experience gained in designing three safety-related systems, that include a Programmable Logic Controller (PLC) based Safeguard Load Sequencer for NSP Prairie Island, a digital Containment Isolation monitoring system for TVA Browns Ferry, and a study that was conducted for EPRI/NSP regarding a PLC-based Reactor Protection system. This article presents the benefits to be gained in replacing existing, outdated equipment with new advanced instrumentation
Cabaret, S; Coppier, H; Rachid, A; Barillère, R; CERN. Geneva. IT Department
2007-01-01
The GCS (Gas Control System) project team at CERN uses a Model Driven Approach with a Framework - UNICOS (UNified Industrial COntrol System) - based on PLC (Programming Language Controller) and SCADA (Supervisory Control And Data Acquisition) technologies. The first' UNICOS versions were able to provide a PID (Proportional Integrative Derivative) controller whereas the Gas Systems required more advanced control strategies. The MultiController is a new UNICOS object which provides the following advanced control algorithms: Smith Predictor, PFC (Predictive Function Control), RST* and GPC (Global Predictive Control). Its design is based on a monolithic entity with a global structure definition which is able to capture the desired set of parameters of any specific control algorithm supported by the object. The SCADA system -- PVSS - supervises the MultiController operation. The PVSS interface provides users with supervision faceplate, in particular it links any MultiController with recipes: the GCS experts are ab...
Arbitrated Quantum Signature with Hamiltonian Algorithm Based on Blind Quantum Computation
Shi, Ronghua; Ding, Wanting; Shi, Jinjing
2018-03-01
A novel arbitrated quantum signature (AQS) scheme is proposed motivated by the Hamiltonian algorithm (HA) and blind quantum computation (BQC). The generation and verification of signature algorithm is designed based on HA, which enables the scheme to rely less on computational complexity. It is unnecessary to recover original messages when verifying signatures since the blind quantum computation is applied, which can improve the simplicity and operability of our scheme. It is proved that the scheme can be deployed securely, and the extended AQS has some extensive applications in E-payment system, E-government, E-business, etc.
Fast parallel algorithms that compute transitive closure of a fuzzy relation
Kreinovich, Vladik YA.
1993-01-01
The notion of a transitive closure of a fuzzy relation is very useful for clustering in pattern recognition, for fuzzy databases, etc. The original algorithm proposed by L. Zadeh (1971) requires the computation time O(n(sup 4)), where n is the number of elements in the relation. In 1974, J. C. Dunn proposed a O(n(sup 2)) algorithm. Since we must compute n(n-1)/2 different values s(a, b) (a not equal to b) that represent the fuzzy relation, and we need at least one computational step to compute each of these values, we cannot compute all of them in less than O(n(sup 2)) steps. So, Dunn's algorithm is in this sense optimal. For small n, it is ok. However, for big n (e.g., for big databases), it is still a lot, so it would be desirable to decrease the computation time (this problem was formulated by J. Bezdek). Since this decrease cannot be done on a sequential computer, the only way to do it is to use a computer with several processors working in parallel. We show that on a parallel computer, transitive closure can be computed in time O((log(sub 2)(n))2).
Computational Analysis of 3D Ising Model Using Metropolis Algorithms
International Nuclear Information System (INIS)
Sonsin, A F; Cortes, M R; Nunes, D R; Gomes, J V; Costa, R S
2015-01-01
We simulate the Ising Model with the Monte Carlo method and use the algorithms of Metropolis to update the distribution of spins. We found that, in the specific case of the three-dimensional Ising Model, methods of Metropolis are efficient. Studying the system near the point of phase transition, we observe that the magnetization goes to zero. In our simulations we analyzed the behavior of the magnetization and magnetic susceptibility to verify the phase transition in a paramagnetic to ferromagnetic material. The behavior of the magnetization and of the magnetic susceptibility as a function of the temperature suggest a phase transition around KT/J ≈ 4.5 and was evidenced the problem of finite size of the lattice to work with large lattice. (paper)
Algorithms: economical computation of functions of real matrices
International Nuclear Information System (INIS)
Weiss, Z.
1991-01-01
An algorithm is presented which economizes on the calculation of F(a), where A is a real matrix and F(x) a real valued function of x, using spectral analysis. Assuming the availability of the software for the calculation of the complete set of eigenvalues and eigen vectors of A, it is shown that the complex matrix arithmetics involved in subsequent operations leading from A to F(A) can be reduced to the size comparable with the analogous problem in real matrix arithmetics. Saving in CPU time and storage has been achieved by utilizing explicitly the property that complex eigenvalues of a real matrix appear in pairs of complex conjugated numbers. (author)
Schüller, Anton; Schweitzer, Marc
2017-01-01
The contributions gathered here provide an overview of current research projects and selected software products of the Fraunhofer Institute for Algorithms and Scientific Computing SCAI. They show the wide range of challenges that scientific computing currently faces, the solutions it offers, and its important role in developing applications for industry. Given the exciting field of applied collaborative research and development it discusses, the book will appeal to scientists, practitioners, and students alike. The Fraunhofer Institute for Algorithms and Scientific Computing SCAI combines excellent research and application-oriented development to provide added value for our partners. SCAI develops numerical techniques, parallel algorithms and specialized software tools to support and optimize industrial simulations. Moreover, it implements custom software solutions for production and logistics, and offers calculations on high-performance computers. Its services and products are based on state-of-the-art metho...
Advanced Suspension and Control Algorithm for U.S. Army Ground Vehicles
2013-04-01
magnetorheological fluid damper . This report provides a record of the research findings from this research project on advanced suspension and control...nonlinear control algorithm that can effectively work with semi-active dampers , such as the magnetorheological (MR) fluid damper . This research...rheological fluid effects). This is because the viscous damping force for high shaft speed becomes excessive and will transmit the terrain-induced
The history of cosmic baryons: discoveries using advanced computing
International Nuclear Information System (INIS)
Norman, Michael L
2005-01-01
We live in the era of the cosmological concordance model. This refers to the precise set of cosmological parameters which describe the average composition, geometry, and expansion rate of the universe we inhabit. Due to recent observational, theoretical, and computational advances, these parameters are now known to approximately 10% accuracy, and new efforts are underway to increase precision tenfold. It is found that we live in a spatially flat, dark matter-dominated universe whose rate of expansion is accelerating due to an unseen, unknown dark energy field. Baryons-the stuff of stars, galaxies, and us-account for only 4% of the total mass-energy inventory. And yet, it is through the astronomical study of baryons that we infer the rest. In this talk I will highlight the important role advanced scientific computing has played in getting us to the concordance model, and also the computational discoveries that have been made about the history of cosmic baryons using hydrodynamical cosmological simulations. I will conclude by discussing the central role that very large scale simulations of cosmological structure formation will play in deciphering the results of upcoming dark energy surveys
Secure Computation, I/O-Efficient Algorithms and Distributed Signatures
DEFF Research Database (Denmark)
Damgård, Ivan Bjerre; Kölker, Jonas; Toft, Tomas
2012-01-01
values of form r, gr for random secret-shared r ∈ ℤq and gr in a group of order q. This costs a constant number of exponentiation per player per value generated, even if less than n/3 players are malicious. This can be used for efficient distributed computing of Schnorr signatures. We further develop...... the technique so we can sign secret data in a distributed fashion at essentially the same cost....
International Nuclear Information System (INIS)
2016-01-01
Preface The 2016 version of the International Workshop on Advanced Computing and Analysis Techniques in Physics Research took place on January 18-22, 2016, at the Universidad Técnica Federico Santa Maria -UTFSM- in Valparaiso, Chile. The present volume of IOP Conference Series is devoted to the selected scientific contributions presented at the workshop. In order to guarantee the scientific quality of the Proceedings all papers were thoroughly peer-reviewed by an ad-hoc Editorial Committee with the help of many careful reviewers. The ACAT Workshop series has a long tradition starting in 1990 (Lyon, France), and takes place in intervals of a year and a half. Formerly these workshops were known under the name AIHENP (Artificial Intelligence for High Energy and Nuclear Physics). Each edition brings together experimental and theoretical physicists and computer scientists/experts, from particle and nuclear physics, astronomy and astrophysics in order to exchange knowledge and experience in computing and data analysis in physics. Three tracks cover the main topics: Computing technology: languages and system architectures. Data analysis: algorithms and tools. Theoretical Physics: techniques and methods. Although most contributions and discussions are related to particle physics and computing, other fields like condensed matter physics, earth physics, biophysics are often addressed in the hope to share our approaches and visions. It created a forum for exchanging ideas among fields, exploring and promoting cutting-edge computing technologies and debating hot topics. (paper)
Computer Hardware, Advanced Mathematics and Model Physics pilot project final report
International Nuclear Information System (INIS)
1992-05-01
The Computer Hardware, Advanced Mathematics and Model Physics (CHAMMP) Program was launched in January, 1990. A principal objective of the program has been to utilize the emerging capabilities of massively parallel scientific computers in the challenge of regional scale predictions of decade-to-century climate change. CHAMMP has already demonstrated the feasibility of achieving a 10,000 fold increase in computational throughput for climate modeling in this decade. What we have also recognized, however, is the need for new algorithms and computer software to capitalize on the radically new computing architectures. This report describes the pilot CHAMMP projects at the DOE National Laboratories and the National Center for Atmospheric Research (NCAR). The pilot projects were selected to identify the principal challenges to CHAMMP and to entrain new scientific computing expertise. The success of some of these projects has aided in the definition of the CHAMMP scientific plan. Many of the papers in this report have been or will be submitted for publication in the open literature. Readers are urged to consult with the authors directly for questions or comments about their papers
High-speed computation of the EM algorithm for PET image reconstruction
International Nuclear Information System (INIS)
Rajan, K.; Patnaik, L.M.; Ramakrishna, J.
1994-01-01
The PET image reconstruction based on the EM algorithm has several attractive advantages over the conventional convolution backprojection algorithms. However, two major drawbacks have impeded the routine use of the EM algorithm, namely, the long computational time due to slow convergence and the large memory required for the storage of the image, projection data and the probability matrix. In this study, the authors attempts to solve these two problems by parallelizing the EM algorithm on a multiprocessor system. The authors have implemented an extended hypercube (EH) architecture for the high-speed computation of the EM algorithm using the commercially available fast floating point digital signal processor (DSP) chips as the processing elements (PEs). The authors discuss and compare the performance of the EM algorithm on a 386/387 machine, CD 4360 mainframe, and on the EH system. The results show that the computational speed performance of an EH using DSP chips as PEs executing the EM image reconstruction algorithm is about 130 times better than that of the CD 4360 mainframe. The EH topology is expandable with more number of PEs
Energy Technology Data Exchange (ETDEWEB)
Santi, Peter Angelo [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Cutler, Theresa Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Favalli, Andrea [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Koehler, Katrina Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Henzl, Vladimir [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Henzlova, Daniela [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Parker, Robert Francis [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Croft, Stephen [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2015-12-01
In order to improve the accuracy and capabilities of neutron multiplicity counting, additional quantifiable information is needed in order to address the assumptions that are present in the point model. Extracting and utilizing higher order moments (Quads and Pents) from the neutron pulse train represents the most direct way of extracting additional information from the measurement data to allow for an improved determination of the physical properties of the item of interest. The extraction of higher order moments from a neutron pulse train required the development of advanced dead time correction algorithms which could correct for dead time effects in all of the measurement moments in a self-consistent manner. In addition, advanced analysis algorithms have been developed to address specific assumptions that are made within the current analysis model, namely that all neutrons are created at a single point within the item of interest, and that all neutrons that are produced within an item are created with the same energy distribution. This report will discuss the current status of implementation and initial testing of the advanced dead time correction and analysis algorithms that have been developed in an attempt to utilize higher order moments to improve the capabilities of correlated neutron measurement techniques.
Indian Academy of Sciences (India)
to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...
Automated Development of Accurate Algorithms and Efficient Codes for Computational Aeroacoustics
Goodrich, John W.; Dyson, Rodger W.
1999-01-01
The simulation of sound generation and propagation in three space dimensions with realistic aircraft components is a very large time dependent computation with fine details. Simulations in open domains with embedded objects require accurate and robust algorithms for propagation, for artificial inflow and outflow boundaries, and for the definition of geometrically complex objects. The development, implementation, and validation of methods for solving these demanding problems is being done to support the NASA pillar goals for reducing aircraft noise levels. Our goal is to provide algorithms which are sufficiently accurate and efficient to produce usable results rapidly enough to allow design engineers to study the effects on sound levels of design changes in propulsion systems, and in the integration of propulsion systems with airframes. There is a lack of design tools for these purposes at this time. Our technical approach to this problem combines the development of new, algorithms with the use of Mathematica and Unix utilities to automate the algorithm development, code implementation, and validation. We use explicit methods to ensure effective implementation by domain decomposition for SPMD parallel computing. There are several orders of magnitude difference in the computational efficiencies of the algorithms which we have considered. We currently have new artificial inflow and outflow boundary conditions that are stable, accurate, and unobtrusive, with implementations that match the accuracy and efficiency of the propagation methods. The artificial numerical boundary treatments have been proven to have solutions which converge to the full open domain problems, so that the error from the boundary treatments can be driven as low as is required. The purpose of this paper is to briefly present a method for developing highly accurate algorithms for computational aeroacoustics, the use of computer automation in this process, and a brief survey of the algorithms that
Advances in Computational Stability Analysis of Composite Aerospace Structures
International Nuclear Information System (INIS)
Degenhardt, R.; Araujo, F. C. de
2010-01-01
European aircraft industry demands for reduced development and operating costs. Structural weight reduction by exploitation of structural reserves in composite aerospace structures contributes to this aim, however, it requires accurate and experimentally validated stability analysis of real structures under realistic loading conditions. This paper presents different advances from the area of computational stability analysis of composite aerospace structures which contribute to that field. For stringer stiffened panels main results of the finished EU project COCOMAT are given. It investigated the exploitation of reserves in primary fibre composite fuselage structures through an accurate and reliable simulation of postbuckling and collapse. For unstiffened cylindrical composite shells a proposal for a new design method is presented.
3D data processing with advanced computer graphics tools
Zhang, Song; Ekstrand, Laura; Grieve, Taylor; Eisenmann, David J.; Chumbley, L. Scott
2012-09-01
Often, the 3-D raw data coming from an optical profilometer contains spiky noises and irregular grid, which make it difficult to analyze and difficult to store because of the enormously large size. This paper is to address these two issues for an optical profilometer by substantially reducing the spiky noise of the 3-D raw data from an optical profilometer, and by rapidly re-sampling the raw data into regular grids at any pixel size and any orientation with advanced computer graphics tools. Experimental results will be presented to demonstrate the effectiveness of the proposed approach.
Advanced computational modelling for drying processes – A review
International Nuclear Information System (INIS)
Defraeye, Thijs
2014-01-01
Highlights: • Understanding the product dehydration process is a key aspect in drying technology. • Advanced modelling thereof plays an increasingly important role for developing next-generation drying technology. • Dehydration modelling should be more energy-oriented. • An integrated “nexus” modelling approach is needed to produce more energy-smart products. • Multi-objective process optimisation requires development of more complete multiphysics models. - Abstract: Drying is one of the most complex and energy-consuming chemical unit operations. R and D efforts in drying technology have skyrocketed in the past decades, as new drivers emerged in this industry next to procuring prime product quality and high throughput, namely reduction of energy consumption and carbon footprint as well as improving food safety and security. Solutions are sought in optimising existing technologies or developing new ones which increase energy and resource efficiency, use renewable energy, recuperate waste heat and reduce product loss, thus also the embodied energy therein. Novel tools are required to push such technological innovations and their subsequent implementation. Particularly computer-aided drying process engineering has a large potential to develop next-generation drying technology, including more energy-smart and environmentally-friendly products and dryers systems. This review paper deals with rapidly emerging advanced computational methods for modelling dehydration of porous materials, particularly for foods. Drying is approached as a combined multiphysics, multiscale and multiphase problem. These advanced methods include computational fluid dynamics, several multiphysics modelling methods (e.g. conjugate modelling), multiscale modelling and modelling of material properties and the associated propagation of material property variability. Apart from the current challenges for each of these, future perspectives should be directed towards material property
Software for the ACP [Advanced Computer Program] multiprocessor system
International Nuclear Information System (INIS)
Biel, J.; Areti, H.; Atac, R.
1987-01-01
Software has been developed for use with the Fermilab Advanced Computer Program (ACP) multiprocessor system. The software was designed to make a system of a hundred independent node processors as easy to use as a single, powerful CPU. Subroutines have been developed by which a user's host program can send data to and get results from the program running in each of his ACP node processors. Utility programs make it easy to compile and link host and node programs, to debug a node program on an ACP development system, and to submit a debugged program to an ACP production system
Fermilab advanced computer program multi-microprocessor project
International Nuclear Information System (INIS)
Nash, T.; Areti, H.; Biel, J.
1985-06-01
Fermilab's Advanced Computer Program is constructing a powerful 128 node multi-microprocessor system for data analysis in high-energy physics. The system will use commercial 32-bit microprocessors programmed in Fortran-77. Extensive software supports easy migration of user applications from a uniprocessor environment to the multiprocessor and provides sophisticated program development, debugging, and error handling and recovery tools. This system is designed to be readily copied, providing computing cost effectiveness of below $2200 per VAX 11/780 equivalent. The low cost, commercial availability, compatibility with off-line analysis programs, and high data bandwidths (up to 160 MByte/sec) make the system an ideal choice for applications to on-line triggers as well as an offline data processor
Review of research on advanced computational science in FY2016
International Nuclear Information System (INIS)
2017-12-01
Research on advanced computational science for nuclear applications, based on “Plan to Achieve Medium- to Long-term Objectives of the Japan Atomic Energy Agency (Medium- to Long-term Plan)”, has been performed at Center for Computational Science and e-Systems (CCSE), Japan Atomic Energy Agency. CCSE established the committee consisting of outside experts and authorities which does research evaluation and advices for the assistance of the research and development. This report summarizes the followings. (1) Results of the R and D performed at CCSE in FY 2016 (April 1st, 2016 - March 31st, 2017), (2) Results of the evaluation on the R and D by the committee in FY 2016. (author)
Advanced data analysis in neuroscience integrating statistical and computational models
Durstewitz, Daniel
2017-01-01
This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanat ory frameworks, but become powerfu...
Review of research on advanced computational science in FY2015
International Nuclear Information System (INIS)
2017-01-01
Research on advanced computational science for nuclear applications, based on 'Plan to Achieve Medium- to Long-term Objectives of the Japan Atomic Energy Agency (Medium- to Long-term Plan)', has been performed at Center for Computational Science and e-Systems (CCSE), Japan Atomic Energy Agency. CCSE established the committee consisting of outside experts and authorities which does research evaluation and advices for the assistance of the research and development. This report summarizes the followings. (1) Results of the R and D performed at CCSE in FY 2015 (April 1st, 2015 - March 31st, 2016), (2) Results of the evaluation on the R and D by the committee in FY 2015 (April 1st, 2015 - March 31st, 2016). (author)
An Advanced Coupled Genetic Algorithm for Identifying Unknown Moving Loads on Bridge Decks
Directory of Open Access Journals (Sweden)
Sang-Youl Lee
2014-01-01
Full Text Available This study deals with an inverse method to identify moving loads on bridge decks using the finite element method (FEM and a coupled genetic algorithm (c-GA. We developed the inverse technique using a coupled genetic algorithm that can make global solution searches possible as opposed to classical gradient-based optimization techniques. The technique described in this paper allows us to not only detect the weight of moving vehicles but also find their moving velocities. To demonstrate the feasibility of the method, the algorithm is applied to a bridge deck model with beam elements. In addition, 1D and 3D finite element models are simulated to study the influence of measurement errors and model uncertainty between numerical and real structures. The results demonstrate the excellence of the method from the standpoints of computation efficiency and avoidance of premature convergence.
Computational Modeling of Teaching and Learning through Application of Evolutionary Algorithms
Directory of Open Access Journals (Sweden)
Richard Lamb
2015-09-01
Full Text Available Within the mind, there are a myriad of ideas that make sense within the bounds of everyday experience, but are not reflective of how the world actually exists; this is particularly true in the domain of science. Classroom learning with teacher explanation are a bridge through which these naive understandings can be brought in line with scientific reality. The purpose of this paper is to examine how the application of a Multiobjective Evolutionary Algorithm (MOEA can work in concert with an existing computational-model to effectively model critical-thinking in the science classroom. An evolutionary algorithm is an algorithm that iteratively optimizes machine learning based computational models. The research question is, does the application of an evolutionary algorithm provide a means to optimize the Student Task and Cognition Model (STAC-M and does the optimized model sufficiently represent and predict teaching and learning outcomes in the science classroom? Within this computational study, the authors outline and simulate the effect of teaching on the ability of a “virtual” student to solve a Piagetian task. Using the Student Task and Cognition Model (STAC-M a computational model of student cognitive processing in science class developed in 2013, the authors complete a computational experiment which examines the role of cognitive retraining on student learning. Comparison of the STAC-M and the STAC-M with inclusion of the Multiobjective Evolutionary Algorithm shows greater success in solving the Piagetian science-tasks post cognitive retraining with the Multiobjective Evolutionary Algorithm. This illustrates the potential uses of cognitive and neuropsychological computational modeling in educational research. The authors also outline the limitations and assumptions of computational modeling.
A coordinate descent MM algorithm for fast computation of sparse logistic PCA
Lee, Seokho
2013-06-01
Sparse logistic principal component analysis was proposed in Lee et al. (2010) for exploratory analysis of binary data. Relying on the joint estimation of multiple principal components, the algorithm therein is computationally too demanding to be useful when the data dimension is high. We develop a computationally fast algorithm using a combination of coordinate descent and majorization-minimization (MM) auxiliary optimization. Our new algorithm decouples the joint estimation of multiple components into separate estimations and consists of closed-form elementwise updating formulas for each sparse principal component. The performance of the proposed algorithm is tested using simulation and high-dimensional real-world datasets. © 2013 Elsevier B.V. All rights reserved.
ESHOPPS: A COMPUTATIONAL TOOL TO AID THE TEACHING OF SHORTEST PATH ALGORITHMS
Directory of Open Access Journals (Sweden)
S. J. de A. LIMA
2015-07-01
Full Text Available The development of a computational tool called EShoPPS – Environment for Shortest Path Problem Solving, which is used to assist students in understanding the working of Dijkstra, Greedy search and A*(star algorithms is presented in this paper. Such algorithms are commonly taught in graduate and undergraduate courses of Engineering and Informatics and are used for solving many optimization problems that can be characterized as Shortest Path Problem. The EShoPPS is an interactive tool that allows students to create a graph representing the problem and also helps in developing their knowledge of each specific algorithm. Experiments performed with 155 students of undergraduate and graduate courses such as Industrial Engineering, Computer Science and Information Systems have shown that by using the EShoPPS tool students were able to improve their interpretation of investigated algorithms.
The ACP (Advanced Computer Program) multiprocessor system at Fermilab
Energy Technology Data Exchange (ETDEWEB)
Nash, T.; Areti, H.; Atac, R.; Biel, J.; Case, G.; Cook, A.; Fischler, M.; Gaines, I.; Hance, R.; Husby, D.
1986-09-01
The Advanced Computer Program at Fermilab has developed a multiprocessor system which is easy to use and uniquely cost effective for many high energy physics problems. The system is based on single board computers which cost under $2000 each to build including 2 Mbytes of on board memory. These standard VME modules each run experiment reconstruction code in Fortran at speeds approaching that of a VAX 11/780. Two versions have been developed: one uses Motorola's 68020 32 bit microprocessor, the other runs with AT and T's 32100. both include the corresponding floating point coprocessor chip. The first system, when fully configured, uses 70 each of the two types of processors. A 53 processor system has been operated for several months with essentially no down time by computer operators in the Fermilab Computer Center, performing at nearly the capacity of 6 CDC Cyber 175 mainframe computers. The VME crates in which the processing ''nodes'' sit are connected via a high speed ''Branch Bus'' to one or more MicroVAX computers which act as hosts handling system resource management and all I/O in offline applications. An interface from Fastbus to the Branch Bus has been developed for online use which has been tested error free at 20 Mbytes/sec for 48 hours. ACP hardware modules are now available commercially. A major package of software, including a simulator that runs on any VAX, has been developed. It allows easy migration of existing programs to this multiprocessor environment. This paper describes the ACP Multiprocessor System and early experience with it at Fermilab and elsewhere.
The ACP [Advanced Computer Program] multiprocessor system at Fermilab
International Nuclear Information System (INIS)
Nash, T.; Areti, H.; Atac, R.
1986-09-01
The Advanced Computer Program at Fermilab has developed a multiprocessor system which is easy to use and uniquely cost effective for many high energy physics problems. The system is based on single board computers which cost under $2000 each to build including 2 Mbytes of on board memory. These standard VME modules each run experiment reconstruction code in Fortran at speeds approaching that of a VAX 11/780. Two versions have been developed: one uses Motorola's 68020 32 bit microprocessor, the other runs with AT and T's 32100. both include the corresponding floating point coprocessor chip. The first system, when fully configured, uses 70 each of the two types of processors. A 53 processor system has been operated for several months with essentially no down time by computer operators in the Fermilab Computer Center, performing at nearly the capacity of 6 CDC Cyber 175 mainframe computers. The VME crates in which the processing ''nodes'' sit are connected via a high speed ''Branch Bus'' to one or more MicroVAX computers which act as hosts handling system resource management and all I/O in offline applications. An interface from Fastbus to the Branch Bus has been developed for online use which has been tested error free at 20 Mbytes/sec for 48 hours. ACP hardware modules are now available commercially. A major package of software, including a simulator that runs on any VAX, has been developed. It allows easy migration of existing programs to this multiprocessor environment. This paper describes the ACP Multiprocessor System and early experience with it at Fermilab and elsewhere
Computer algorithm for analyzing and processing borehole strainmeter data
Langbein, John O.
2010-01-01
The newly installed Plate Boundary Observatory (PBO) strainmeters record signals from tectonic activity, Earth tides, and atmospheric pressure. Important information about tectonic processes may occur at amplitudes at and below tidal strains and pressure loading. If incorrect assumptions are made regarding the background noise in the strain data, then the estimates of tectonic signal amplitudes may be incorrect. Furthermore, the use of simplifying assumptions that data are uncorrelated can lead to incorrect results and pressure loading and tides may not be completely removed from the raw data. Instead, any algorithm used to process strainmeter data must incorporate the strong temporal correlations that are inherent with these data. The technique described here uses least squares but employs data covariance that describes the temporal correlation of strainmeter data. There are several advantages to this method since many parameters are estimated simultaneously. These parameters include: (1) functional terms that describe the underlying error model, (2) the tidal terms, (3) the pressure loading term(s), (4) amplitudes of offsets, either those from earthquakes or from the instrument, (5) rate and changes in rate, and (6) the amplitudes and time constants of either logarithmic or exponential curves that can characterize postseismic deformation or diffusion of fluids near the strainmeter. With the proper error model, realistic estimates of the standard errors of the various parameters are obtained; this is especially critical in determining the statistical significance of a suspected, tectonic strain signal. The program also provides a method of tracking the various adjustments required to process strainmeter data. In addition, the program provides several plots to assist with identifying either tectonic signals or other signals that may need to be removed before any geophysical signal can be identified.
Theoretical and algorithmic advances in multi-parametric programming and control
Pistikopoulos, Efstratios N.; Dominguez, Luis; Panos, Christos; Kouramas, Konstantinos; Chinchuluun, Altannar
2012-01-01
This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.
Theoretical and algorithmic advances in multi-parametric programming and control
Pistikopoulos, Efstratios N.
2012-04-21
This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.
Nuclear power reactor analysis, methods, algorithms and computer programs
International Nuclear Information System (INIS)
Matausek, M.V
1981-01-01
Full text: For a developing country buying its first nuclear power plants from a foreign supplier, disregarding the type and scope of the contract, there is a certain number of activities which have to be performed by local stuff and domestic organizations. This particularly applies to the choice of the nuclear fuel cycle strategy and the choice of the type and size of the reactors, to bid parameters specification, bid evaluation and final safety analysis report evaluation, as well as to in-core fuel management activities. In the Nuclear Engineering Department of the Boris Kidric Institute of Nuclear Sciences (NET IBK) the continual work is going on, related to the following topics: cross section and resonance integral calculations, spectrum calculations, generation of group constants, lattice and cell problems, criticality and global power distribution search, fuel burnup analysis, in-core fuel management procedures, cost analysis and power plant economics, safety and accident analysis, shielding problems and environmental impact studies, etc. The present paper gives the details of the methods developed and the results achieved, with the particular emphasis on the NET IBK computer program package for the needs of planning, construction and operation of nuclear power plants. The main problems encountered so far were related to small working team, lack of large and powerful computers, absence of reliable basic nuclear data and shortage of experimental and empirical results for testing theoretical models. Some of these difficulties have been overcome thanks to bilateral and multilateral cooperation with developed countries, mostly through IAEA. It is the authors opinion, however, that mutual cooperation of developing countries, having similar problems and similar goals, could lead to significant results. Some activities of this kind are suggested and discussed. (author)
Teodorescu, Liliana; Britton, David; Glover, Nigel; Heinrich, Gudrun; Lauret, Jérôme; Naumann, Axel; Speer, Thomas; Teixeira-Dias, Pedro
2012-06-01
ACAT2011 This volume of Journal of Physics: Conference Series is dedicated to scientific contributions presented at the 14th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2011) which took place on 5-7 September 2011 at Brunel University, UK. The workshop series, which began in 1990 in Lyon, France, brings together computer science researchers and practitioners, and researchers from particle physics and related fields in order to explore and confront the boundaries of computing and of automatic data analysis and theoretical calculation techniques. It is a forum for the exchange of ideas among the fields, exploring and promoting cutting-edge computing, data analysis and theoretical calculation techniques in fundamental physics research. This year's edition of the workshop brought together over 100 participants from all over the world. 14 invited speakers presented key topics on computing ecosystems, cloud computing, multivariate data analysis, symbolic and automatic theoretical calculations as well as computing and data analysis challenges in astrophysics, bioinformatics and musicology. Over 80 other talks and posters presented state-of-the art developments in the areas of the workshop's three tracks: Computing Technologies, Data Analysis Algorithms and Tools, and Computational Techniques in Theoretical Physics. Panel and round table discussions on data management and multivariate data analysis uncovered new ideas and collaboration opportunities in the respective areas. This edition of ACAT was generously sponsored by the Science and Technology Facility Council (STFC), the Institute for Particle Physics Phenomenology (IPPP) at Durham University, Brookhaven National Laboratory in the USA and Dell. We would like to thank all the participants of the workshop for the high level of their scientific contributions and for the enthusiastic participation in all its activities which were, ultimately, the key factors in the
Wang, Jianxiong
2014-06-01
This volume of Journal of Physics: Conference Series is dedicated to scientific contributions presented at the 15th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2013) which took place on 16-21 May 2013 at the Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China. The workshop series brings together computer science researchers and practitioners, and researchers from particle physics and related fields to explore and confront the boundaries of computing and of automatic data analysis and theoretical calculation techniques. This year's edition of the workshop brought together over 120 participants from all over the world. 18 invited speakers presented key topics on the universe in computer, Computing in Earth Sciences, multivariate data analysis, automated computation in Quantum Field Theory as well as computing and data analysis challenges in many fields. Over 70 other talks and posters presented state-of-the-art developments in the areas of the workshop's three tracks: Computing Technologies, Data Analysis Algorithms and Tools, and Computational Techniques in Theoretical Physics. The round table discussions on open-source, knowledge sharing and scientific collaboration stimulate us to think over the issue in the respective areas. ACAT 2013 was generously sponsored by the Chinese Academy of Sciences (CAS), National Natural Science Foundation of China (NFSC), Brookhaven National Laboratory in the USA (BNL), Peking University (PKU), Theoretical Physics Cernter for Science facilities of CAS (TPCSF-CAS) and Sugon. We would like to thank all the participants for their scientific contributions and for the en- thusiastic participation in all its activities of the workshop. Further information on ACAT 2013 can be found at http://acat2013.ihep.ac.cn. Professor Jianxiong Wang Institute of High Energy Physics Chinese Academy of Science Details of committees and sponsors are available in the PDF
International Nuclear Information System (INIS)
Montero Gonzalez, Allan
2012-01-01
A literature review has been carried out in the diagnostic and monitoring algorithms for image of incidentalomas of solid abdominal organs (liver, kidney and adrenal glands) detected by computed tomography (CT). The criteria have been unified and updated for a effective diagnosis. Posed algorithms have been made in simplified form. The imaging techniques have been specified for each pathology, showing the advantages and disadvantages of using it and justifying the application in daily practice [es
Fast algorithms for computing defects and their derivatives in the Regge calculus
International Nuclear Information System (INIS)
Brewin, Leo
2011-01-01
Any practical attempt to solve the Regge equations, these being a large system of non-linear algebraic equations, will almost certainly employ a Newton-Raphson-like scheme. In such cases, it is essential that efficient algorithms be used when computing the defect angles and their derivatives with respect to the leg lengths. The purpose of this paper is to present details of such an algorithm.
Energy Technology Data Exchange (ETDEWEB)
Jimenez, Edward S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Orr, Laurel J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Thompson, Kyle R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2013-09-01
The goal of this work is to develop a fast computed tomography (CT) reconstruction algorithm based on graphics processing units (GPU) that achieves significant improvement over traditional central processing unit (CPU) based implementations. The main challenge in developing a CT algorithm that is capable of handling very large datasets is parallelizing the algorithm in such a way that data transfer does not hinder performance of the reconstruction algorithm. General Purpose Graphics Processing (GPGPU) is a new technology that the Science and Technology (S&T) community is starting to adopt in many fields where CPU-based computing is the norm. GPGPU programming requires a new approach to algorithm development that utilizes massively multi-threaded environments. Multi-threaded algorithms in general are difficult to optimize since performance bottlenecks occur that are non-existent in single-threaded algorithms such as memory latencies. If an efficient GPU-based CT reconstruction algorithm can be developed; computational times could be improved by a factor of 20. Additionally, cost benefits will be realized as commodity graphics hardware could potentially replace expensive supercomputers and high-end workstations. This project will take advantage of the CUDA programming environment and attempt to parallelize the task in such a way that multiple slices of the reconstruction volume are computed simultaneously. This work will also take advantage of the GPU memory by utilizing asynchronous memory transfers, GPU texture memory, and (when possible) pinned host memory so that the memory transfer bottleneck inherent to GPGPU is amortized. Additionally, this work will take advantage of GPU-specific hardware (i.e. fast texture memory, pixel-pipelines, hardware interpolators, and varying memory hierarchy) that will allow for additional performance improvements.
Desiderata for computable representations of electronic health records-driven phenotype algorithms.
Mo, Huan; Thompson, William K; Rasmussen, Luke V; Pacheco, Jennifer A; Jiang, Guoqian; Kiefer, Richard; Zhu, Qian; Xu, Jie; Montague, Enid; Carrell, David S; Lingren, Todd; Mentch, Frank D; Ni, Yizhao; Wehbe, Firas H; Peissig, Peggy L; Tromp, Gerard; Larson, Eric B; Chute, Christopher G; Pathak, Jyotishman; Denny, Joshua C; Speltz, Peter; Kho, Abel N; Jarvik, Gail P; Bejan, Cosmin A; Williams, Marc S; Borthwick, Kenneth; Kitchner, Terrie E; Roden, Dan M; Harris, Paul A
2015-11-01
Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM). A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms. We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility. A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages. © The Author 2015. Published by Oxford University Press on behalf of the American Medical
Advances in x-ray computed microtomography at the NSLS
International Nuclear Information System (INIS)
Dowd, B.A.; Andrews, A.B.; Marr, R.B.; Siddons, D.P.; Jones, K.W.; Peskin, A.M.
1998-08-01
The X-Ray Computed Microtomography workstation at beamline X27A at the NSLS has been utilized by scientists from a broad range of disciplines from industrial materials processing to environmental science. The most recent applications are presented here as well as a description of the facility that has evolved to accommodate a wide variety of materials and sample sizes. One of the most exciting new developments reported here resulted from a pursuit of faster reconstruction techniques. A Fast Filtered Back Transform (FFBT) reconstruction program has been developed and implemented, that is based on a refinement of the gridding algorithm first developed for use with radio astronomical data. This program has reduced the reconstruction time to 8.5 sec for a 929 x 929 pixel 2 slice on an R10,000 CPU, more than 8x reduction compared with the Filtered Back-Projection method
DEFF Research Database (Denmark)
Bron, Esther E.; Smits, Marion; van der Flier, Wiesje M.
2015-01-01
algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease...... of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume......Abstract Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform...
A novel computer algorithm for modeling and treating mandibular fractures: A pilot study.
Rizzi, Christopher J; Ortlip, Timothy; Greywoode, Jewel D; Vakharia, Kavita T; Vakharia, Kalpesh T
2017-02-01
To describe a novel computer algorithm that can model mandibular fracture repair. To evaluate the algorithm as a tool to model mandibular fracture reduction and hardware selection. Retrospective pilot study combined with cross-sectional survey. A computer algorithm utilizing Aquarius Net (TeraRecon, Inc, Foster City, CA) and Adobe Photoshop CS6 (Adobe Systems, Inc, San Jose, CA) was developed to model mandibular fracture repair. Ten different fracture patterns were selected from nine patients who had already undergone mandibular fracture repair. The preoperative computed tomography (CT) images were processed with the computer algorithm to create virtual images that matched the actual postoperative three-dimensional CT images. A survey comparing the true postoperative image with the virtual postoperative images was created and administered to otolaryngology resident and attending physicians. They were asked to rate on a scale from 0 to 10 (0 = completely different; 10 = identical) the similarity between the two images in terms of the fracture reduction and fixation hardware. Ten mandible fracture cases were analyzed and processed. There were 15 survey respondents. The mean score for overall similarity between the images was 8.41 ± 0.91; the mean score for similarity of fracture reduction was 8.61 ± 0.98; and the mean score for hardware appearance was 8.27 ± 0.97. There were no significant differences between attending and resident responses. There were no significant differences based on fracture location. This computer algorithm can accurately model mandibular fracture repair. Images created by the algorithm are highly similar to true postoperative images. The algorithm can potentially assist a surgeon planning mandibular fracture repair. 4. Laryngoscope, 2016 127:331-336, 2017. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.
Canadell, Marta; Haro, Àlex
2017-12-01
We present several algorithms for computing normally hyperbolic invariant tori carrying quasi-periodic motion of a fixed frequency in families of dynamical systems. The algorithms are based on a KAM scheme presented in Canadell and Haro (J Nonlinear Sci, 2016. doi: 10.1007/s00332-017-9389-y), to find the parameterization of the torus with prescribed dynamics by detuning parameters of the model. The algorithms use different hyperbolicity and reducibility properties and, in particular, compute also the invariant bundles and Floquet transformations. We implement these methods in several 2-parameter families of dynamical systems, to compute quasi-periodic arcs, that is, the parameters for which 1D normally hyperbolic invariant tori with a given fixed frequency do exist. The implementation lets us to perform the continuations up to the tip of the quasi-periodic arcs, for which the invariant curves break down. Three different mechanisms of breakdown are analyzed, using several observables, leading to several conjectures.
Introduction: a brief overview of iterative algorithms in X-ray computed tomography.
Soleimani, M; Pengpen, T
2015-06-13
This paper presents a brief overview of some basic iterative algorithms, and more sophisticated methods are presented in the research papers in this issue. A range of algebraic iterative algorithms are covered here including ART, SART and OS-SART. A major limitation of the traditional iterative methods is their computational time. The Krylov subspace based methods such as the conjugate gradients (CG) algorithm and its variants can be used to solve linear systems of equations arising from large-scale CT with possible implementation using modern high-performance computing tools. The overall aim of this theme issue is to stimulate international efforts to develop the next generation of X-ray computed tomography (CT) image reconstruction software. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Automatic computer aided analysis algorithms and system for adrenal tumors on CT images.
Chai, Hanchao; Guo, Yi; Wang, Yuanyuan; Zhou, Guohui
2017-12-04
The adrenal tumor will disturb the secreting function of adrenocortical cells, leading to many diseases. Different kinds of adrenal tumors require different therapeutic schedules. In the practical diagnosis, it highly relies on the doctor's experience to judge the tumor type by reading the hundreds of CT images. This paper proposed an automatic computer aided analysis method for adrenal tumors detection and classification. It consisted of the automatic segmentation algorithms, the feature extraction and the classification algorithms. These algorithms were then integrated into a system and conducted on the graphic interface by using MATLAB Graphic user interface (GUI). The accuracy of the automatic computer aided segmentation and classification reached 90% on 436 CT images. The experiments proved the stability and reliability of this automatic computer aided analytic system.
New approach for measuring 3D space by using Advanced SURF Algorithm
Energy Technology Data Exchange (ETDEWEB)
Youm, Minkyo; Min, Byungil; Suh, Kyungsuk [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Lee, Backgeun [Sungkyunkwan Univ., Suwon (Korea, Republic of)
2013-05-15
The nuclear disasters compared to natural disaster create a more extreme condition for analyzing and evaluating. In this paper, measuring 3D space and modeling was studied by simple pictures in case of small sand dune. The suggested method can be used for the acquisition of spatial information by robot at the disaster area. As a result, these data are helpful for identify the damaged part, degree of damage and determination of recovery sequences. In this study we are improving computer vision algorithm for 3-D geo spatial information measurement. And confirm by test. First, we can get noticeable improvement of 3-D geo spatial information result by SURF algorithm and photogrammetry surveying. Second, we can confirm not only decrease algorithm running time, but also increase matching points through epi polar line filtering. From the study, we are extracting 3-D model by open source algorithm and delete miss match point by filtering method. However on characteristic of SURF algorithm, it can't find match point if structure don't have strong feature. So we will need more study about find feature point if structure don't have strong feature.
Energy Technology Data Exchange (ETDEWEB)
Carey, G.F.; Young, D.M.
1993-12-31
The program outlined here is directed to research on methods, algorithms, and software for distributed parallel supercomputers. Of particular interest are finite element methods and finite difference methods together with sparse iterative solution schemes for scientific and engineering computations of very large-scale systems. Both linear and nonlinear problems will be investigated. In the nonlinear case, applications with bifurcation to multiple solutions will be considered using continuation strategies. The parallelizable numerical methods of particular interest are a family of partitioning schemes embracing domain decomposition, element-by-element strategies, and multi-level techniques. The methods will be further developed incorporating parallel iterative solution algorithms with associated preconditioners in parallel computer software. The schemes will be implemented on distributed memory parallel architectures such as the CRAY MPP, Intel Paragon, the NCUBE3, and the Connection Machine. We will also consider other new architectures such as the Kendall-Square (KSQ) and proposed machines such as the TERA. The applications will focus on large-scale three-dimensional nonlinear flow and reservoir problems with strong convective transport contributions. These are legitimate grand challenge class computational fluid dynamics (CFD) problems of significant practical interest to DOE. The methods developed and algorithms will, however, be of wider interest.
Iterative schemes for parallel Sn algorithms in a shared-memory computing environment
International Nuclear Information System (INIS)
Haghighat, A.; Hunter, M.A.; Mattis, R.E.
1995-01-01
Several two-dimensional spatial domain partitioning S n transport theory algorithms are developed on the basis of different iterative schemes. These algorithms are incorporated into TWOTRAN-II and tested on the shared-memory CRAY Y-MP C90 computer. For a series of fixed-source r-z geometry homogeneous problems, it is demonstrated that the concurrent red-black algorithms may result in large parallel efficiencies (>60%) on C90. It is also demonstrated that for a realistic shielding problem, the use of the negative flux fixup causes high load imbalance, which results in a significant loss of parallel efficiency
Li, Tiejun; Min, Bin; Wang, Zhiming
2013-03-14
The stochastic integral ensuring the Newton-Leibnitz chain rule is essential in stochastic energetics. Marcus canonical integral has this property and can be understood as the Wong-Zakai type smoothing limit when the driving process is non-Gaussian. However, this important concept seems not well-known for physicists. In this paper, we discuss Marcus integral for non-Gaussian processes and its computation in the context of stochastic energetics. We give a comprehensive introduction to Marcus integral and compare three equivalent definitions in the literature. We introduce the exact pathwise simulation algorithm and give the error analysis. We show how to compute the thermodynamic quantities based on the pathwise simulation algorithm. We highlight the information hidden in the Marcus mapping, which plays the key role in determining thermodynamic quantities. We further propose the tau-leaping algorithm, which advance the process with deterministic time steps when tau-leaping condition is satisfied. The numerical experiments and its efficiency analysis show that it is very promising.
Signal and image processing algorithm performance in a virtual and elastic computing environment
Bennett, Kelly W.; Robertson, James
2013-05-01
The U.S. Army Research Laboratory (ARL) supports the development of classification, detection, tracking, and localization algorithms using multiple sensing modalities including acoustic, seismic, E-field, magnetic field, PIR, and visual and IR imaging. Multimodal sensors collect large amounts of data in support of algorithm development. The resulting large amount of data, and their associated high-performance computing needs, increases and challenges existing computing infrastructures. Purchasing computer power as a commodity using a Cloud service offers low-cost, pay-as-you-go pricing models, scalability, and elasticity that may provide solutions to develop and optimize algorithms without having to procure additional hardware and resources. This paper provides a detailed look at using a commercial cloud service provider, such as Amazon Web Services (AWS), to develop and deploy simple signal and image processing algorithms in a cloud and run the algorithms on a large set of data archived in the ARL Multimodal Signatures Database (MMSDB). Analytical results will provide performance comparisons with existing infrastructure. A discussion on using cloud computing with government data will discuss best security practices that exist within cloud services, such as AWS.
International Nuclear Information System (INIS)
Woodruff, S.B.
1992-01-01
The Transient Reactor Analysis Code (TRAC), which features a two- fluid treatment of thermal-hydraulics, is designed to model transients in water reactors and related facilities. One of the major computational costs associated with TRAC and similar codes is calculating constitutive coefficients. Although the formulations for these coefficients are local the costs are flow-regime- or data-dependent; i.e., the computations needed for a given spatial node often vary widely as a function of time. Consequently, poor load balancing will degrade efficiency on either vector or data parallel architectures when the data are organized according to spatial location. Unfortunately, a general automatic solution to the load-balancing problem associated with data-dependent computations is not yet available for massively parallel architectures. This document discusses why developers algorithms, such as a neural net representation, that do not exhibit algorithms, such as a neural net representation, that do not exhibit load-balancing problems
OPENING REMARKS: SciDAC: Scientific Discovery through Advanced Computing
Strayer, Michael
2005-01-01
with industry and virtual prototyping. New instruments of collaboration will include institutes and centers while summer schools, workshops and outreach will invite new talent and expertise. Computational science adds new dimensions to science and its practice. Disciplines of fusion, accelerator science, and combustion are poised to blur the boundaries between pure and applied science. As we open the door into FY2006 we shall see a landscape of new scientific challenges: in biology, chemistry, materials, and astrophysics to name a few. The enabling technologies of SciDAC have been transformational as drivers of change. Planning for major new software systems assumes a base line employing Common Component Architectures and this has become a household word for new software projects. While grid algorithms and mesh refinement software have transformed applications software, data management and visualization have transformed our understanding of science from data. The Gordon Bell prize now seems to be dominated by computational science and solvers developed by TOPS ISIC. The priorities of the Office of Science in the Department of Energy are clear. The 20 year facilities plan is driven by new science. High performance computing is placed amongst the two highest priorities. Moore's law says that by the end of the next cycle of SciDAC we shall have peta-flop computers. The challenges of petascale computing are enormous. These and the associated computational science are the highest priorities for computing within the Office of Science. Our effort in Leadership Class computing is just a first step towards this goal. Clearly, computational science at this scale will face enormous challenges and possibilities. Performance evaluation and prediction will be critical to unraveling the needed software technologies. We must not lose sight of our overarching goal—that of scientific discovery. Science does not stand still and the landscape of science discovery and computing holds
Recent Advances in Computational Mechanics of the Human Knee Joint
Kazemi, M.; Dabiri, Y.; Li, L. P.
2013-01-01
Computational mechanics has been advanced in every area of orthopedic biomechanics. The objective of this paper is to provide a general review of the computational models used in the analysis of the mechanical function of the knee joint in different loading and pathological conditions. Major review articles published in related areas are summarized first. The constitutive models for soft tissues of the knee are briefly discussed to facilitate understanding the joint modeling. A detailed review of the tibiofemoral joint models is presented thereafter. The geometry reconstruction procedures as well as some critical issues in finite element modeling are also discussed. Computational modeling can be a reliable and effective method for the study of mechanical behavior of the knee joint, if the model is constructed correctly. Single-phase material models have been used to predict the instantaneous load response for the healthy knees and repaired joints, such as total and partial meniscectomies, ACL and PCL reconstructions, and joint replacements. Recently, poromechanical models accounting for fluid pressurization in soft tissues have been proposed to study the viscoelastic response of the healthy and impaired knee joints. While the constitutive modeling has been considerably advanced at the tissue level, many challenges still exist in applying a good material model to three-dimensional joint simulations. A complete model validation at the joint level seems impossible presently, because only simple data can be obtained experimentally. Therefore, model validation may be concentrated on the constitutive laws using multiple mechanical tests of the tissues. Extensive model verifications at the joint level are still crucial for the accuracy of the modeling. PMID:23509602
Förster, Michael
2014-01-01
Numerical programs often use parallel programming techniques such as OpenMP to compute the program's output values as efficient as possible. In addition, derivative values of these output values with respect to certain input values play a crucial role. To achieve code that computes not only the output values simultaneously but also the derivative values, this work introduces several source-to-source transformation rules. These rules are based on a technique called algorithmic differentiation. The main focus of this work lies on the important reverse mode of algorithmic differentiation. The inh
Unified algorithm for partial differential equations and examples of numerical computation
International Nuclear Information System (INIS)
Watanabe, Tsuguhiro
1999-01-01
A new unified algorithm is proposed to solve partial differential equations which describe nonlinear boundary value problems, eigenvalue problems and time developing boundary value problems. The algorithm is composed of implicit difference scheme and multiple shooting scheme and is named as HIDM (Higher order Implicit Difference Method). A new prototype computer programs for 2-dimensional partial differential equations is constructed and tested successfully to several problems. Extension of the computer programs to 3 or more higher order dimension problems will be easy due to the direct product type difference scheme. (author)
Energy Technology Data Exchange (ETDEWEB)
Reed, Daniel [University of Iowa; Berzins, Martin [University of Utah; Pennington, Robert; Sarkar, Vivek [Rice University; Taylor, Valerie [Texas A& M University
2015-08-01
On November 19, 2014, the Advanced Scientific Computing Advisory Committee (ASCAC) was charged with reviewing the Department of Energy’s conceptual design for the Exascale Computing Initiative (ECI). In particular, this included assessing whether there are significant gaps in the ECI plan or areas that need to be given priority or extra management attention. Given the breadth and depth of previous reviews of the technical challenges inherent in exascale system design and deployment, the subcommittee focused its assessment on organizational and management issues, considering technical issues only as they informed organizational or management priorities and structures. This report presents the observations and recommendations of the subcommittee.
A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update
Lotte, F.; Bougrain, L.; Cichocki, A.; Clerc, M.; Congedo, M.; Rakotomamonjy, A.; Yger, F.
2018-06-01
Objective. Most current electroencephalography (EEG)-based brain–computer interfaces (BCIs) are based on machine learning algorithms. There is a large diversity of classifier types that are used in this field, as described in our 2007 review paper. Now, approximately ten years after this review publication, many new algorithms have been developed and tested to classify EEG signals in BCIs. The time is therefore ripe for an updated review of EEG classification algorithms for BCIs. Approach. We surveyed the BCI and machine learning literature from 2007 to 2017 to identify the new classification approaches that have been investigated to design BCIs. We synthesize these studies in order to present such algorithms, to report how they were used for BCIs, what were the outcomes, and to identify their pros and cons. Main results. We found that the recently designed classification algorithms for EEG-based BCIs can be divided into four main categories: adaptive classifiers, matrix and tensor classifiers, transfer learning and deep learning, plus a few other miscellaneous classifiers. Among these, adaptive classifiers were demonstrated to be generally superior to static ones, even with unsupervised adaptation. Transfer learning can also prove useful although the benefits of transfer learning remain unpredictable. Riemannian geometry-based methods have reached state-of-the-art performances on multiple BCI problems and deserve to be explored more thoroughly, along with tensor-based methods. Shrinkage linear discriminant analysis and random forests also appear particularly useful for small training samples settings. On the other hand, deep learning methods have not yet shown convincing improvement over state-of-the-art BCI methods. Significance. This paper provides a comprehensive overview of the modern classification algorithms used in EEG-based BCIs, presents the principles of these methods and guidelines on when and how to use them. It also identifies a number of challenges
A review of classification algorithms for EEG-based brain-computer interfaces: a 10 year update.
Lotte, F; Bougrain, L; Cichocki, A; Clerc, M; Congedo, M; Rakotomamonjy, A; Yger, F
2018-06-01
Most current electroencephalography (EEG)-based brain-computer interfaces (BCIs) are based on machine learning algorithms. There is a large diversity of classifier types that are used in this field, as described in our 2007 review paper. Now, approximately ten years after this review publication, many new algorithms have been developed and tested to classify EEG signals in BCIs. The time is therefore ripe for an updated review of EEG classification algorithms for BCIs. We surveyed the BCI and machine learning literature from 2007 to 2017 to identify the new classification approaches that have been investigated to design BCIs. We synthesize these studies in order to present such algorithms, to report how they were used for BCIs, what were the outcomes, and to identify their pros and cons. We found that the recently designed classification algorithms for EEG-based BCIs can be divided into four main categories: adaptive classifiers, matrix and tensor classifiers, transfer learning and deep learning, plus a few other miscellaneous classifiers. Among these, adaptive classifiers were demonstrated to be generally superior to static ones, even with unsupervised adaptation. Transfer learning can also prove useful although the benefits of transfer learning remain unpredictable. Riemannian geometry-based methods have reached state-of-the-art performances on multiple BCI problems and deserve to be explored more thoroughly, along with tensor-based methods. Shrinkage linear discriminant analysis and random forests also appear particularly useful for small training samples settings. On the other hand, deep learning methods have not yet shown convincing improvement over state-of-the-art BCI methods. This paper provides a comprehensive overview of the modern classification algorithms used in EEG-based BCIs, presents the principles of these methods and guidelines on when and how to use them. It also identifies a number of challenges to further advance EEG classification in BCI.
International conference on Advances in Intelligent Control and Innovative Computing
Castillo, Oscar; Huang, Xu; Intelligent Control and Innovative Computing
2012-01-01
In the lightning-fast world of intelligent control and cutting-edge computing, it is vitally important to stay abreast of developments that seem to follow each other without pause. This publication features the very latest and some of the very best current research in the field, with 32 revised and extended research articles written by prominent researchers in the field. Culled from contributions to the key 2011 conference Advances in Intelligent Control and Innovative Computing, held in Hong Kong, the articles deal with a wealth of relevant topics, from the most recent work in artificial intelligence and decision-supporting systems, to automated planning, modelling and simulation, signal processing, and industrial applications. Not only does this work communicate the current state of the art in intelligent control and innovative computing, it is also an illuminating guide to up-to-date topics for researchers and graduate students in the field. The quality of the contents is absolutely assured by the high pro...
Computational brain models: Advances from system biology and future challenges
Directory of Open Access Journals (Sweden)
George E. Barreto
2015-02-01
Full Text Available Computational brain models focused on the interactions between neurons and astrocytes, modeled via metabolic reconstructions, are reviewed. The large source of experimental data provided by the -omics techniques and the advance/application of computational and data-management tools are being fundamental. For instance, in the understanding of the crosstalk between these cells, the key neuroprotective mechanisms mediated by astrocytes in specific metabolic scenarios (1 and the identification of biomarkers for neurodegenerative diseases (2,3. However, the modeling of these interactions demands a clear view of the metabolic and signaling pathways implicated, but most of them are controversial and are still under evaluation (4. Hence, to gain insight into the complexity of these interactions a current view of the main pathways implicated in the neuron-astrocyte communication processes have been made from recent experimental reports and reviews. Furthermore, target problems, limitations and main conclusions have been identified from metabolic models of the brain reported from 2010. Finally, key aspects to take into account into the development of a computational model of the brain and topics that could be approached from a systems biology perspective in future research are highlighted.
Computationally Efficient DOA Tracking Algorithm in Monostatic MIMO Radar with Automatic Association
Directory of Open Access Journals (Sweden)
Huaxin Yu
2014-01-01
Full Text Available We consider the problem of tracking the direction of arrivals (DOA of multiple moving targets in monostatic multiple-input multiple-output (MIMO radar. A low-complexity DOA tracking algorithm in monostatic MIMO radar is proposed. The proposed algorithm obtains DOA estimation via the difference between previous and current covariance matrix of the reduced-dimension transformation signal, and it reduces the computational complexity and realizes automatic association in DOA tracking. Error analysis and Cramér-Rao lower bound (CRLB of DOA tracking are derived in the paper. The proposed algorithm not only can be regarded as an extension of array-signal-processing DOA tracking algorithm in (Zhang et al. (2008, but also is an improved version of the DOA tracking algorithm in (Zhang et al. (2008. Furthermore, the proposed algorithm has better DOA tracking performance than the DOA tracking algorithm in (Zhang et al. (2008. The simulation results demonstrate effectiveness of the proposed algorithm. Our work provides the technical support for the practical application of MIMO radar.
Directory of Open Access Journals (Sweden)
Jorge Patiño
2016-01-01
Full Text Available This paper presents an evaluation performance of computational intelligence algorithms based on the multiobjective theory for the solution of the Routing and Wavelength Assignment problem (RWA in optical networks. The study evaluates the Firefly Algorithm, the Differential Evolutionary Algorithm, the Simulated Annealing Algorithm and two versions of the Particle Swarm Optimization algorithm. The paper provides a description of the multiobjective algorithms; then, an evaluation based on the performance provided by the multiobjective algorithms versus mono-objective approaches when dealing with different traffic loads, different numberof wavelengths and wavelength conversion process over the NSFNet topology is presented. Simulation results show that monoobjective algorithms properly solve the RWA problem for low values of data traffic and low number of wavelengths. However, the multiobjective approaches adapt better to online traffic when the number of wavelengths available in the network increases as well as when wavelength conversion is implemented in the nodes.
Dongarra, Jack; Ltaief, Hatem; Luszczek, Piotr R.; Weaver, Vincent M.
2012-01-01
We propose to study the impact on the energy footprint of two advanced algorithmic strategies in the context of high performance dense linear algebra libraries: (1) mixed precision algorithms with iterative refinement allow to run at the peak performance of single precision floating-point arithmetic while achieving double precision accuracy and (2) tree reduction technique exposes more parallelism when factorizing tall and skinny matrices for solving over determined systems of linear equations or calculating the singular value decomposition. Integrated within the PLASMA library using tile algorithms, which will eventually supersede the block algorithms from LAPACK, both strategies further excel in performance in the presence of a dynamic task scheduler while targeting multicore architecture. Energy consumption measurements are reported along with parallel performance numbers on a dual-socket quad-core Intel Xeon as well as a quad-socket quad-core Intel Sandy Bridge chip, both providing component-based energy monitoring at all levels of the system, through the Power Pack framework and the Running Average Power Limit model, respectively. © 2012 IEEE.
Dongarra, Jack
2012-11-01
We propose to study the impact on the energy footprint of two advanced algorithmic strategies in the context of high performance dense linear algebra libraries: (1) mixed precision algorithms with iterative refinement allow to run at the peak performance of single precision floating-point arithmetic while achieving double precision accuracy and (2) tree reduction technique exposes more parallelism when factorizing tall and skinny matrices for solving over determined systems of linear equations or calculating the singular value decomposition. Integrated within the PLASMA library using tile algorithms, which will eventually supersede the block algorithms from LAPACK, both strategies further excel in performance in the presence of a dynamic task scheduler while targeting multicore architecture. Energy consumption measurements are reported along with parallel performance numbers on a dual-socket quad-core Intel Xeon as well as a quad-socket quad-core Intel Sandy Bridge chip, both providing component-based energy monitoring at all levels of the system, through the Power Pack framework and the Running Average Power Limit model, respectively. © 2012 IEEE.
Directory of Open Access Journals (Sweden)
Jianning Wu
2015-01-01
Full Text Available The accurate identification of gait asymmetry is very beneficial to the assessment of at-risk gait in the clinical applications. This paper investigated the application of classification method based on statistical learning algorithm to quantify gait symmetry based on the assumption that the degree of intrinsic change in dynamical system of gait is associated with the different statistical distributions between gait variables from left-right side of lower limbs; that is, the discrimination of small difference of similarity between lower limbs is considered the reorganization of their different probability distribution. The kinetic gait data of 60 participants were recorded using a strain gauge force platform during normal walking. The classification method is designed based on advanced statistical learning algorithm such as support vector machine algorithm for binary classification and is adopted to quantitatively evaluate gait symmetry. The experiment results showed that the proposed method could capture more intrinsic dynamic information hidden in gait variables and recognize the right-left gait patterns with superior generalization performance. Moreover, our proposed techniques could identify the small significant difference between lower limbs when compared to the traditional symmetry index method for gait. The proposed algorithm would become an effective tool for early identification of the elderly gait asymmetry in the clinical diagnosis.
Wu, Jianning; Wu, Bin
2015-01-01
The accurate identification of gait asymmetry is very beneficial to the assessment of at-risk gait in the clinical applications. This paper investigated the application of classification method based on statistical learning algorithm to quantify gait symmetry based on the assumption that the degree of intrinsic change in dynamical system of gait is associated with the different statistical distributions between gait variables from left-right side of lower limbs; that is, the discrimination of small difference of similarity between lower limbs is considered the reorganization of their different probability distribution. The kinetic gait data of 60 participants were recorded using a strain gauge force platform during normal walking. The classification method is designed based on advanced statistical learning algorithm such as support vector machine algorithm for binary classification and is adopted to quantitatively evaluate gait symmetry. The experiment results showed that the proposed method could capture more intrinsic dynamic information hidden in gait variables and recognize the right-left gait patterns with superior generalization performance. Moreover, our proposed techniques could identify the small significant difference between lower limbs when compared to the traditional symmetry index method for gait. The proposed algorithm would become an effective tool for early identification of the elderly gait asymmetry in the clinical diagnosis.
DEFF Research Database (Denmark)
Boiroux, Dimitri; Juhl, Rune; Madsen, Henrik
2016-01-01
This paper addresses maximum likelihood parameter estimation of continuous-time nonlinear systems with discrete-time measurements. We derive an efficient algorithm for the computation of the log-likelihood function and its gradient, which can be used in gradient-based optimization algorithms....... This algorithm uses UD decomposition of symmetric matrices and the array algorithm for covariance update and gradient computation. We test our algorithm on the Lotka-Volterra equations. Compared to the maximum likelihood estimation based on finite difference gradient computation, we get a significant speedup...
National Aeronautics and Space Administration — SSCI proposes to develop and test a framework referred to as the ADVANCE (Algorithm Design and Validation for Adaptive Nonlinear Control Enhancement), within which...
A multiresolution approach to iterative reconstruction algorithms in X-ray computed tomography.
De Witte, Yoni; Vlassenbroeck, Jelle; Van Hoorebeke, Luc
2010-09-01
In computed tomography, the application of iterative reconstruction methods in practical situations is impeded by their high computational demands. Especially in high resolution X-ray computed tomography, where reconstruction volumes contain a high number of volume elements (several giga voxels), this computational burden prevents their actual breakthrough. Besides the large amount of calculations, iterative algorithms require the entire volume to be kept in memory during reconstruction, which quickly becomes cumbersome for large data sets. To overcome this obstacle, we present a novel multiresolution reconstruction, which greatly reduces the required amount of memory without significantly affecting the reconstructed image quality. It is shown that, combined with an efficient implementation on a graphical processing unit, the multiresolution approach enables the application of iterative algorithms in the reconstruction of large volumes at an acceptable speed using only limited resources.
An Algorithm for Fast Computation of 3D Zernike Moments for Volumetric Images
Directory of Open Access Journals (Sweden)
Khalid M. Hosny
2012-01-01
Full Text Available An algorithm was proposed for very fast and low-complexity computation of three-dimensional Zernike moments. The 3D Zernike moments were expressed in terms of exact 3D geometric moments where the later are computed exactly through the mathematical integration of the monomial terms over the digital image/object voxels. A new symmetry-based method was proposed to compute 3D Zernike moments with 87% reduction in the computational complexity. A fast 1D cascade algorithm was also employed to add more complexity reduction. The comparison with existing methods was performed, where the numerical experiments and the complexity analysis ensured the efficiency of the proposed method especially with image and objects of large sizes.
5G Network Communication, Caching, and Computing Algorithms Based on the Two‐Tier Game Model
Directory of Open Access Journals (Sweden)
Sungwook Kim
2018-02-01
Full Text Available In this study, we developed hybrid control algorithms in smart base stations (SBSs along with devised communication, caching, and computing techniques. In the proposed scheme, SBSs are equipped with computing power and data storage to collectively offload the computation from mobile user equipment and to cache the data from clouds. To combine in a refined manner the communication, caching, and computing algorithms, game theory is adopted to characterize competitive and cooperative interactions. The main contribution of our proposed scheme is to illuminate the ultimate synergy behind a fully integrated approach, while providing excellent adaptability and flexibility to satisfy the different performance requirements. Simulation results demonstrate that the proposed approach can outperform existing schemes by approximately 5% to 15% in terms of bandwidth utilization, access delay, and system throughput.
Identification of Enhancers In Human: Advances In Computational Studies
Kleftogiannis, Dimitrios A.
2016-03-24
framework for identifying enhancers. The proposed system called Dragon Ensemble Enhancer Predictor (DEEP) is based on the novel deep learning two-layer ensemble algorithm capable of identifying enhancers characterized by different cellular conditions. Experimental results using data from ENCODE and FANTOM5, demonstrate that DEEP surpasses in terms of recognition performance the major systems for enhancer prediction and shows very good generalization capabilities in unknown cell-lines and tissues. Finally, we take a step further by developing a novel feature selection method suitable for defining a computational framework capable of analyzing the genomic content of enhancers and reporting cell-line specific predictive signatures.
Workflow Scheduling Using Hybrid GA-PSO Algorithm in Cloud Computing
Directory of Open Access Journals (Sweden)
Ahmad M. Manasrah
2018-01-01
Full Text Available Cloud computing environment provides several on-demand services and resource sharing for clients. Business processes are managed using the workflow technology over the cloud, which represents one of the challenges in using the resources in an efficient manner due to the dependencies between the tasks. In this paper, a Hybrid GA-PSO algorithm is proposed to allocate tasks to the resources efficiently. The Hybrid GA-PSO algorithm aims to reduce the makespan and the cost and balance the load of the dependent tasks over the heterogonous resources in cloud computing environments. The experiment results show that the GA-PSO algorithm decreases the total execution time of the workflow tasks, in comparison with GA, PSO, HSGA, WSGA, and MTCT algorithms. Furthermore, it reduces the execution cost. In addition, it improves the load balancing of the workflow application over the available resources. Finally, the obtained results also proved that the proposed algorithm converges to optimal solutions faster and with higher quality compared to other algorithms.
A parallel simulated annealing algorithm for standard cell placement on a hypercube computer
Jones, Mark Howard
1987-01-01
A parallel version of a simulated annealing algorithm is presented which is targeted to run on a hypercube computer. A strategy for mapping the cells in a two dimensional area of a chip onto processors in an n-dimensional hypercube is proposed such that both small and large distance moves can be applied. Two types of moves are allowed: cell exchanges and cell displacements. The computation of the cost function in parallel among all the processors in the hypercube is described along with a distributed data structure that needs to be stored in the hypercube to support parallel cost evaluation. A novel tree broadcasting strategy is used extensively in the algorithm for updating cell locations in the parallel environment. Studies on the performance of the algorithm on example industrial circuits show that it is faster and gives better final placement results than the uniprocessor simulated annealing algorithms. An improved uniprocessor algorithm is proposed which is based on the improved results obtained from parallelization of the simulated annealing algorithm.
Radev, Dimitar; Lokshina, Izabella
2010-11-01
The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.
Gyrokinetic particle-in-cell simulations of plasma microturbulence on advanced computing platforms
International Nuclear Information System (INIS)
Ethier, S; Tang, W M; Lin, Z
2005-01-01
Since its introduction in the early 1980s, the gyrokinetic particle-in-cell (PIC) method has been very successfully applied to the exploration of many important kinetic stability issues in magnetically confined plasmas. Its self-consistent treatment of charged particles and the associated electromagnetic fluctuations makes this method appropriate for studying enhanced transport driven by plasma turbulence. Advances in algorithms and computer hardware have led to the development of a parallel, global, gyrokinetic code in full toroidal geometry, the gyrokinetic toroidal code (GTC), developed at the Princeton Plasma Physics Laboratory. It has proven to be an invaluable tool to study key effects of low-frequency microturbulence in fusion plasmas. As a high-performance computing applications code, its flexible mixed-model parallel algorithm has allowed GTC to scale to over a thousand processors, which is routinely used for simulations. Improvements are continuously being made. As the US ramps up its support for the International Tokamak Experimental Reactor (ITER), the need for understanding the impact of turbulent transport in burning plasma fusion devices is of utmost importance. Accordingly, the GTC code is at the forefront of the set of numerical tools being used to assess and predict the performance of ITER on critical issues such as the efficiency of energy confinement in reactors
Advanced information processing system: Inter-computer communication services
Burkhardt, Laura; Masotto, Tom; Sims, J. Terry; Whittredge, Roy; Alger, Linda S.
1991-01-01
The purpose is to document the functional requirements and detailed specifications for the Inter-Computer Communications Services (ICCS) of the Advanced Information Processing System (AIPS). An introductory section is provided to outline the overall architecture and functional requirements of the AIPS and to present an overview of the ICCS. An overview of the AIPS architecture as well as a brief description of the AIPS software is given. The guarantees of the ICCS are provided, and the ICCS is described as a seven-layered International Standards Organization (ISO) Model. The ICCS functional requirements, functional design, and detailed specifications as well as each layer of the ICCS are also described. A summary of results and suggestions for future work are presented.
Computational modeling, optimization and manufacturing simulation of advanced engineering materials
2016-01-01
This volume presents recent research work focused in the development of adequate theoretical and numerical formulations to describe the behavior of advanced engineering materials. Particular emphasis is devoted to applications in the fields of biological tissues, phase changing and porous materials, polymers and to micro/nano scale modeling. Sensitivity analysis, gradient and non-gradient based optimization procedures are involved in many of the chapters, aiming at the solution of constitutive inverse problems and parameter identification. All these relevant topics are exposed by experienced international and inter institutional research teams resulting in a high level compilation. The book is a valuable research reference for scientists, senior undergraduate and graduate students, as well as for engineers acting in the area of computational material modeling.
International Nuclear Information System (INIS)
Nash, T.; Areti, H.; Atac, R.
1988-08-01
Fermilab's Advanced Computer Program (ACP) has been developing highly cost effective, yet practical, parallel computers for high energy physics since 1984. The ACP's latest developments are proceeding in two directions. A Second Generation ACP Multiprocessor System for experiments will include $3500 RISC processors each with performance over 15 VAX MIPS. To support such high performance, the new system allows parallel I/O, parallel interprocess communication, and parallel host processes. The ACP Multi-Array Processor, has been developed for theoretical physics. Each $4000 node is a FORTRAN or C programmable pipelined 20 MFlops (peak), 10 MByte single board computer. These are plugged into a 16 port crossbar switch crate which handles both inter and intra crate communication. The crates are connected in a hypercube. Site oriented applications like lattice gauge theory are supported by system software called CANOPY, which makes the hardware virtually transparent to users. A 256 node, 5 GFlop, system is under construction. 10 refs., 7 figs
Smolyak's algorithm: A powerful black box for the acceleration of scientific computations
Tempone, Raul
2017-03-26
We provide a general discussion of Smolyak\\'s algorithm for the acceleration of scientific computations. The algorithm first appeared in Smolyak\\'s work on multidimensional integration and interpolation. Since then, it has been generalized in multiple directions and has been associated with the keywords: sparse grids, hyperbolic cross approximation, combination technique, and multilevel methods. Variants of Smolyak\\'s algorithm have been employed in the computation of high-dimensional integrals in finance, chemistry, and physics, in the numerical solution of partial and stochastic differential equations, and in uncertainty quantification. Motivated by this broad and ever-increasing range of applications, we describe a general framework that summarizes fundamental results and assumptions in a concise application-independent manner.
A Randomized Exchange Algorithm for Computing Optimal Approximate Designs of Experiments
Harman, Radoslav
2018-01-17
We propose a class of subspace ascent methods for computing optimal approximate designs that covers both existing as well as new and more efficient algorithms. Within this class of methods, we construct a simple, randomized exchange algorithm (REX). Numerical comparisons suggest that the performance of REX is comparable or superior to the performance of state-of-the-art methods across a broad range of problem structures and sizes. We focus on the most commonly used criterion of D-optimality that also has applications beyond experimental design, such as the construction of the minimum volume ellipsoid containing a given set of data-points. For D-optimality, we prove that the proposed algorithm converges to the optimum. We also provide formulas for the optimal exchange of weights in the case of the criterion of A-optimality. These formulas enable one to use REX for computing A-optimal and I-optimal designs.
Smolyak's algorithm: A powerful black box for the acceleration of scientific computations
Tempone, Raul; Wolfers, Soeren
2017-01-01
We provide a general discussion of Smolyak's algorithm for the acceleration of scientific computations. The algorithm first appeared in Smolyak's work on multidimensional integration and interpolation. Since then, it has been generalized in multiple directions and has been associated with the keywords: sparse grids, hyperbolic cross approximation, combination technique, and multilevel methods. Variants of Smolyak's algorithm have been employed in the computation of high-dimensional integrals in finance, chemistry, and physics, in the numerical solution of partial and stochastic differential equations, and in uncertainty quantification. Motivated by this broad and ever-increasing range of applications, we describe a general framework that summarizes fundamental results and assumptions in a concise application-independent manner.
A Randomized Exchange Algorithm for Computing Optimal Approximate Designs of Experiments
Harman, Radoslav; Filová , Lenka; Richtarik, Peter
2018-01-01
We propose a class of subspace ascent methods for computing optimal approximate designs that covers both existing as well as new and more efficient algorithms. Within this class of methods, we construct a simple, randomized exchange algorithm (REX). Numerical comparisons suggest that the performance of REX is comparable or superior to the performance of state-of-the-art methods across a broad range of problem structures and sizes. We focus on the most commonly used criterion of D-optimality that also has applications beyond experimental design, such as the construction of the minimum volume ellipsoid containing a given set of data-points. For D-optimality, we prove that the proposed algorithm converges to the optimum. We also provide formulas for the optimal exchange of weights in the case of the criterion of A-optimality. These formulas enable one to use REX for computing A-optimal and I-optimal designs.
THE USE OF COMPUTER VISION ALGORITHMS FOR AUTOMATIC ORIENTATION OF TERRESTRIAL LASER SCANNING DATA
Directory of Open Access Journals (Sweden)
J. S. Markiewicz
2016-06-01
Full Text Available The paper presents analysis of the orientation of terrestrial laser scanning (TLS data. In the proposed data processing methodology, point clouds are considered as panoramic images enriched by the depth map. Computer vision (CV algorithms are used for orientation, which are applied for testing the correctness of the detection of tie points and time of computations, and for assessing difficulties in their implementation. The BRISK, FASRT, MSER, SIFT, SURF, ASIFT and CenSurE algorithms are used to search for key-points. The source data are point clouds acquired using a Z+F 5006h terrestrial laser scanner on the ruins of Iłża Castle, Poland. Algorithms allowing combination of the photogrammetric and CV approaches are also presented.
The Use of Computer Vision Algorithms for Automatic Orientation of Terrestrial Laser Scanning Data
Markiewicz, Jakub Stefan
2016-06-01
The paper presents analysis of the orientation of terrestrial laser scanning (TLS) data. In the proposed data processing methodology, point clouds are considered as panoramic images enriched by the depth map. Computer vision (CV) algorithms are used for orientation, which are applied for testing the correctness of the detection of tie points and time of computations, and for assessing difficulties in their implementation. The BRISK, FASRT, MSER, SIFT, SURF, ASIFT and CenSurE algorithms are used to search for key-points. The source data are point clouds acquired using a Z+F 5006h terrestrial laser scanner on the ruins of Iłża Castle, Poland. Algorithms allowing combination of the photogrammetric and CV approaches are also presented.