Naeem, Huma; Hussain, Mukhtar; Khan, Shoab A
2009-01-01
Surveillance control and reporting (SCR) system for air threats play an important role in the defense of a country. SCR system corresponds to air and ground situation management/processing along with information fusion, communication, coordination, simulation and other critical defense oriented tasks. Threat Evaluation and Weapon Assignment (TEWA) sits at the core of SCR system. In such a system, maximal or near maximal utilization of constrained resources is of extreme importance. Manual TEWA systems cannot provide optimality because of different limitations e.g.surface to air missile (SAM) can fire from a distance of 5Km, but manual TEWA systems are constrained by human vision range and other constraints. Current TEWA systems usually work on target-by-target basis using some type of greedy algorithm thus affecting the optimality of the solution and failing in multi-target scenario. his paper relates to a novel two-staged flexible dynamic decision support based optimal threat evaluation and weapon assignment...
Symplectic algebraic dynamics algorithm
Institute of Scientific and Technical Information of China (English)
2007-01-01
Based on the algebraic dynamics solution of ordinary differential equations andintegration of ,the symplectic algebraic dynamics algorithm sn is designed,which preserves the local symplectic geometric structure of a Hamiltonian systemand possesses the same precision of the na ve algebraic dynamics algorithm n.Computer experiments for the 4th order algorithms are made for five test modelsand the numerical results are compared with the conventional symplectic geometric algorithm,indicating that sn has higher precision,the algorithm-inducedphase shift of the conventional symplectic geometric algorithm can be reduced,and the dynamical fidelity can be improved by one order of magnitude.
Institute of Scientific and Technical Information of China (English)
WANG ShunJin; ZHANG Hua
2007-01-01
Based on the exact analytical solution of ordinary differential equations,a truncation of the Taylor series of the exact solution to the Nth order leads to the Nth order algebraic dynamics algorithm.A detailed numerical comparison is presented with Runge-Kutta algorithm and symplectic geometric algorithm for 12 test models.The results show that the algebraic dynamics algorithm can better preserve both geometrical and dynamical fidelity of a dynamical system at a controllable precision,and it can solve the problem of algorithm-induced dissipation for the Runge-Kutta algorithm and the problem of algorithm-induced phase shift for the symplectic geometric algorithm.
Institute of Scientific and Technical Information of China (English)
2007-01-01
Based on the exact analytical solution of ordinary differential equations, a truncation of the Taylor series of the exact solution to the Nth order leads to the Nth order algebraic dynamics algorithm. A detailed numerical comparison is presented with Runge-Kutta algorithm and symplectic geometric algorithm for 12 test models. The results show that the algebraic dynamics algorithm can better preserve both geometrical and dynamical fidelity of a dynamical system at a controllable precision, and it can solve the problem of algorithm-induced dissipation for the Runge-Kutta algorithm and the problem of algorithm-induced phase shift for the symplectic geometric algorithm.
Control algorithms for dynamic attenuators
Energy Technology Data Exchange (ETDEWEB)
Hsieh, Scott S., E-mail: sshsieh@stanford.edu [Department of Radiology, Stanford University, Stanford, California 94305 and Department of Electrical Engineering, Stanford University, Stanford, California 94305 (United States); Pelc, Norbert J. [Department of Radiology, Stanford University, Stanford California 94305 and Department of Bioengineering, Stanford University, Stanford, California 94305 (United States)
2014-06-15
Purpose: The authors describe algorithms to control dynamic attenuators in CT and compare their performance using simulated scans. Dynamic attenuators are prepatient beam shaping filters that modulate the distribution of x-ray fluence incident on the patient on a view-by-view basis. These attenuators can reduce dose while improving key image quality metrics such as peak or mean variance. In each view, the attenuator presents several degrees of freedom which may be individually adjusted. The total number of degrees of freedom across all views is very large, making many optimization techniques impractical. The authors develop a theory for optimally controlling these attenuators. Special attention is paid to a theoretically perfect attenuator which controls the fluence for each ray individually, but the authors also investigate and compare three other, practical attenuator designs which have been previously proposed: the piecewise-linear attenuator, the translating attenuator, and the double wedge attenuator. Methods: The authors pose and solve the optimization problems of minimizing the mean and peak variance subject to a fixed dose limit. For a perfect attenuator and mean variance minimization, this problem can be solved in simple, closed form. For other attenuator designs, the problem can be decomposed into separate problems for each view to greatly reduce the computational complexity. Peak variance minimization can be approximately solved using iterated, weighted mean variance (WMV) minimization. Also, the authors develop heuristics for the perfect and piecewise-linear attenuators which do not requirea priori knowledge of the patient anatomy. The authors compare these control algorithms on different types of dynamic attenuators using simulated raw data from forward projected DICOM files of a thorax and an abdomen. Results: The translating and double wedge attenuators reduce dose by an average of 30% relative to current techniques (bowtie filter with tube current
Efficient Algorithms for Langevin and DPD Dynamics
Goga, N.; Rzepiela, A. J.; de Vries, A. H.; Marrink, S. J.; Berendsen, H. J. C.
2012-01-01
In this article, we present several algorithms for stochastic dynamics, including Langevin dynamics and different variants of Dissipative Particle Dynamics (DPD), applicable to systems with or without constraints. The algorithms are based on the impulsive application of friction and noise, thus avoi
Algebraic dynamics solution and algebraic dynamics algorithm of Burgers equations
Institute of Scientific and Technical Information of China (English)
2008-01-01
Algebraic dynamics solution and algebraic dynamics algorithm of nonlinear partial differential evolution equations in the functional space are applied to Burgers equation. The results indicate that the approach is effective for analytical solutions to Burgers equation, and the algorithm for numerical solutions of Burgers equation is more stable, with higher precision than other existing finite difference algo-rithms.
Dynamic Streaming Algorithms for Epsilon-Kernels
Chan, Timothy M.
2016-01-01
Introduced by Agarwal, Har-Peled, and Varadarajan [J. ACM, 2004], an epsilon-kernel of a point set is a coreset that can be used to approximate the width, minimum enclosing cylinder, minimum bounding box, and solve various related geometric optimization problems. Such coresets form one of the most important tools in the design of linear-time approximation algorithms in computational geometry, as well as efficient insertion-only streaming algorithms and dynamic (non-streaming) data structures...
DYNAMIC BANDWIDTH ALLOCATION ALGORITHM UTILIZING FULL BAND
Institute of Scientific and Technical Information of China (English)
Han Guodong; Wen Jianhua; Wu Jiangxing
2006-01-01
A kind of Dynamic Full Bandwidth Utilized (DFBU) allocation algorithm is introduced. This algorithm allows a single link to use bandwidth far beyond its fair share bandwidth in a multi-service packet transporting system. Three important parameters as the bound on maximum and minimum bandwidth, the maximum packet delay and the minimum band width utilization are discussed and analyzed. Results of experiments show that the DFBU-algorithm is capable of making a single link in the system to use all the spare bandwidth (up to full-bandwidth) while the performance of fairness and QoS requirement is still guaranteed.
Dynamic algorithms for the Dyck languages
DEFF Research Database (Denmark)
Frandsen, Gudmund Skovbjerg; Husfeldt, Thore; Miltersen, Peter Bro;
1995-01-01
We study Dynamic Membership problems for the Dyck languages, the class of strings of properly balanced parentheses. We also study the Dynamic Word problem for the free group. We present deterministic algorithms and data structures which maintain a string under replacements of symbols, insertions......, and deletions of symbols, and language membership queries. Updates and queries are handled in polylogarithmic time. We also give both Las Vegas- and Monte Carlo-type randomised algorithms to achieve better running times, and present lower bounds on the complexity for variants of the problems....
Algorithm for dynamic Speckle pattern processing
Cariñe, J.; Guzmán, R.; Torres-Ruiz, F. A.
2016-07-01
In this paper we present a new algorithm for determining surface activity by processing speckle pattern images recorded with a CCD camera. Surface activity can be produced by motility or small displacements among other causes, and is manifested as a change in the pattern recorded in the camera with reference to a static background pattern. This intensity variation is considered to be a small perturbation compared with the mean intensity. Based on a perturbative method we obtain an equation with which we can infer information about the dynamic behavior of the surface that generates the speckle pattern. We define an activity index based on our algorithm that can be easily compared with the outcomes from other algorithms. It is shown experimentally that this index evolves in time in the same way as the Inertia Moment method, however our algorithm is based on direct processing of speckle patterns without the need for other kinds of post-processes (like THSP and co-occurrence matrix), making it a viable real-time method. We also show how this algorithm compares with several other algorithms when applied to calibration experiments. From these results we conclude that our algorithm offer qualitative and quantitative advantages over current methods.
An Improved Dynamic Bandwidth Allocation Algorithm for Ethernet PON
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
This paper proposes an improved Dynamic Bandwidth Allocation (DBA) algorithm for EPON, which combines static and traditional dynamic allocation schemes. Simulation result shows that the proposed algorithm may effectively improve the performance of packet delay.
Local minimization algorithms for dynamic programming equations
Kalise, Dante; Kröner, Axel; Kunisch, Karl
2015-01-01
The numerical realization of the dynamic programming principle for continuous-time optimal control leads to nonlinear Hamilton-Jacobi-Bellman equations which require the minimization of a nonlinear mapping over the set of admissible controls. This minimization is often performed by comparison over a finite number of elements of the control set. In this paper we demonstrate the importance of an accurate realization of these minimization problems and propose algorithms by which this can be achi...
Dynamic programming algorithms for biological sequence comparison.
Pearson, W R; Miller, W
1992-01-01
Efficient dynamic programming algorithms are available for a broad class of protein and DNA sequence comparison problems. These algorithms require computer time proportional to the product of the lengths of the two sequences being compared [O(N2)] but require memory space proportional only to the sum of these lengths [O(N)]. Although the requirement for O(N2) time limits use of the algorithms to the largest computers when searching protein and DNA sequence databases, many other applications of these algorithms, such as calculation of distances for evolutionary trees and comparison of a new sequence to a library of sequence profiles, are well within the capabilities of desktop computers. In particular, the results of library searches with rapid searching programs, such as FASTA or BLAST, should be confirmed by performing a rigorous optimal alignment. Whereas rapid methods do not overlook significant sequence similarities, FASTA limits the number of gaps that can be inserted into an alignment, so that a rigorous alignment may extend the alignment substantially in some cases. BLAST does not allow gaps in the local regions that it reports; a calculation that allows gaps is very likely to extend the alignment substantially. Although a Monte Carlo evaluation of the statistical significance of a similarity score with a rigorous algorithm is much slower than the heuristic approach used by the RDF2 program, the dynamic programming approach should take less than 1 hr on a 386-based PC or desktop Unix workstation. For descriptive purposes, we have limited our discussion to methods for calculating similarity scores and distances that use gap penalties of the form g = rk. Nevertheless, programs for the more general case (g = q+rk) are readily available. Versions of these programs that run either on Unix workstations, IBM-PC class computers, or the Macintosh can be obtained from either of the authors.
Enhanced Dynamic Algorithm of Genome Sequence Alignments
Directory of Open Access Journals (Sweden)
Arabi E. keshk
2014-05-01
Full Text Available The merging of biology and computer science has created a new field called computational biology that explore the capacities of computers to gain knowledge from biological data, bioinformatics. Computational biology is rooted in life sciences as well as computers, information sciences, and technologies. The main problem in computational biology is sequence alignment that is a way of arranging the sequences of DNA, RNA or protein to identify the region of similarity and relationship between sequences. This paper introduces an enhancement of dynamic algorithm of genome sequence alignment, which called EDAGSA. It is filling the three main diagonals without filling the entire matrix by the unused data. It gets the optimal solution with decreasing the execution time and therefore the performance is increased. To illustrate the effectiveness of optimizing the performance of the proposed algorithm, it is compared with the traditional methods such as Needleman-Wunsch, Smith-Waterman and longest common subsequence algorithms. Also, database is implemented for using the algorithm in multi-sequence alignments for searching the optimal sequence that matches the given sequence.
An Improved Artificial Immune Algorithm with a Dynamic Threshold
Institute of Scientific and Technical Information of China (English)
Zhang Qiao; Xu Xu; Liang Yan-chun
2006-01-01
An improved artificial immune algorithm with a dynamic threshold is presented. The calculation for the affinity function in the real-valued coding artificial immune algorithm is modified through considering the antibody's fitness and setting the dynamic threshold value. Numerical experiments show that compared with the genetic algorithm and the originally real-valued coding artificial immune algorithm, the improved algorithm possesses high speed of convergence and good performance for preventing premature convergence.
Domain decomposition algorithms and computational fluid dynamics
Chan, Tony F.
1988-01-01
Some of the new domain decomposition algorithms are applied to two model problems in computational fluid dynamics: the two-dimensional convection-diffusion problem and the incompressible driven cavity flow problem. First, a brief introduction to the various approaches of domain decomposition is given, and a survey of domain decomposition preconditioners for the operator on the interface separating the subdomains is then presented. For the convection-diffusion problem, the effect of the convection term and its discretization on the performance of some of the preconditioners is discussed. For the driven cavity problem, the effectiveness of a class of boundary probe preconditioners is examined.
A LEAP-FROG ALGORITHM FOR STOCHASTIC DYNAMICS
Van Gunsteren, W. F.; Berendsen, H. J. C.
1988-01-01
A third-order algorithm for stochastic dynamics (SD) simulations is proposed, identical to the powerful molecular dynamics leapfrog algorithm in the limit of infinitely small friction coefficient gamma. It belongs to the class of SD algorithms, in which the integration time step Delta t is not limit
Dynamic Data Updating Algorithm for Image Superresolution Reconstruction
Institute of Scientific and Technical Information of China (English)
TAN Bing; XU Qing; ZHANG Yan; XING Shuai
2006-01-01
A dynamic data updating algorithm for image superesolution is proposed. On the basis of Delaunay triangulation and its local updating property, this algorithm can update the changed region directly under the circumstances that only a part of the source images has been changed. For its high efficiency and adaptability, this algorithm can serve as a fast algorithm for image superesolution reconstruction.
Domain decomposition algorithms and computation fluid dynamics
Chan, Tony F.
1988-01-01
In the past several years, domain decomposition was a very popular topic, partly motivated by the potential of parallelization. While a large body of theory and algorithms were developed for model elliptic problems, they are only recently starting to be tested on realistic applications. The application of some of these methods to two model problems in computational fluid dynamics are investigated. Some examples are two dimensional convection-diffusion problems and the incompressible driven cavity flow problem. The construction and analysis of efficient preconditioners for the interface operator to be used in the iterative solution of the interface solution is described. For the convection-diffusion problems, the effect of the convection term and its discretization on the performance of some of the preconditioners is discussed. For the driven cavity problem, the effectiveness of a class of boundary probe preconditioners is discussed.
Optimized Dynamical Decoupling via Genetic Algorithms
Quiroz, Gregory
2013-01-01
We utilize genetic algorithms to find optimal dynamical decoupling (DD) sequences for a single-qubit system subjected to a general decoherence model under a variety of control pulse conditions. We focus on the case of sequences with equal pulse-intervals and perform the optimization with respect to pulse type and order. In this manner we obtain robust DD sequences, first in the limit of ideal pulses, then when including pulse imperfections such as finite pulse duration and qubit rotation (flip-angle) errors. Although our optimization is numerical, we identify a deterministic structure underlies the top-performing sequences. We use this structure to devise DD sequences which outperform previously designed concatenated DD (CDD) and quadratic DD (QDD) sequences in the presence of pulse errors. We explain our findings using time-dependent perturbation theory and provide a detailed scaling analysis of the optimal sequences.
Asset-Based Assessment in Educational Psychology: Capturing Perceptions during a Paradigm Shift
Lubbe, Carien; Eloff, Irma
2004-01-01
Several trends are compelling educational psychologists towards a philosophy of assessment that is asset-based and strength focused. This article shares the results from a study that explored perceptions about asset-based assessment in Educational Psychology in South Africa. Three focus groups were held and four main themes emerged from the…
Directory of Open Access Journals (Sweden)
Tanti Octavia
2003-01-01
Full Text Available A Modified Giffler and Thompson algorithm combined with dynamic slack time is used to allocate machines resources in dynamic nature. It was compared with a Real Time Order Promising (RTP algorithm. The performance of modified Giffler and Thompson and RTP algorithms are measured by mean tardiness. The result shows that modified Giffler and Thompson algorithm combined with dynamic slack time provides significantly better result compared with RTP algorithm in terms of mean tardiness.
Parallel-Processing Algorithms For Dynamics Of Manipulators
Fijany, Amir; Bejczy, Antal K.
1991-01-01
Class of parallel and parallel/pipeline algorithms presented for more efficient computation of manipulator inertia matrix. Essential for implementing advanced dynamic control schemes as well as dynamic simulation of manipulator motion.
On an algorithm for dynamic reconstruction of the input
Blizorukova, M. S.; V.I. Maksimov
2013-01-01
We consider the problem of dynamic reconstruction of the input in a system described by a vector differential equation and nonlinear in the state variable. We indicate an algorithm that is stable under information noises and computational errors and is aimed at infinite system operation time. The algorithm is based on the dynamic regularization method. © 2013 Pleiades Publishing, Ltd.
Successful Community Midwives in Pakistan: An Asset-Based Approach.
Mumtaz, Zubia; Levay, Adrienne V; Bhatti, Afshan
2015-01-01
In response to the low levels of skilled birth attendance in rural Pakistan, the government introduced a new cadre of community midwives (CMWs) in 2006. Assessments to-date have found that these CMWs have yet to emerge as significant providers for a number of sociocultural, geographic and financial reasons. However, a small number of CMWs have managed to establish functional practices in the private sector in conservative, infrastructure-challenged rural contexts. With an objective to highlight "what are the successful CMWs doing right given their context?" this paper adopts an asset-based approach to explore the experiences of the Pakistani CMWs who have managed to overcome the barriers and practice. We drew upon ethnographic data that was collected as part of a larger mixed methods study conducted in 2011-2012 in districts Jhelum and Layyah, Pakistan. Thirty eight CMWs, 45 other health care providers, 20 policymakers, 78 women, 35 husbands and 23 older women were interviewed. CMW clinics and practices were observed. Our data showed that only eight 8 out of 38 CMWs sampled were active providers. Poverty as a push factor to work and intrinsic individual-level characteristics that enabled the CMWs to respond successfully to the demands of the midwifery profession in the private sector emerged as the two key themes. Household poverty pushed the CMWs to work in this perceived low-status occupation. Their families supported them since they became the breadwinners. The successful CMWs also had an intrinsic sense of what was required to establish a private practice; they exhibited professionalism, had strong business sense and provided respectful maternity care. The study provides insight into how the program might improve its functioning by adapting its recruitment criteria to ensure selection of right candidates.
Successful Community Midwives in Pakistan: An Asset-Based Approach.
Directory of Open Access Journals (Sweden)
Zubia Mumtaz
Full Text Available In response to the low levels of skilled birth attendance in rural Pakistan, the government introduced a new cadre of community midwives (CMWs in 2006. Assessments to-date have found that these CMWs have yet to emerge as significant providers for a number of sociocultural, geographic and financial reasons. However, a small number of CMWs have managed to establish functional practices in the private sector in conservative, infrastructure-challenged rural contexts. With an objective to highlight "what are the successful CMWs doing right given their context?" this paper adopts an asset-based approach to explore the experiences of the Pakistani CMWs who have managed to overcome the barriers and practice. We drew upon ethnographic data that was collected as part of a larger mixed methods study conducted in 2011-2012 in districts Jhelum and Layyah, Pakistan. Thirty eight CMWs, 45 other health care providers, 20 policymakers, 78 women, 35 husbands and 23 older women were interviewed. CMW clinics and practices were observed. Our data showed that only eight 8 out of 38 CMWs sampled were active providers. Poverty as a push factor to work and intrinsic individual-level characteristics that enabled the CMWs to respond successfully to the demands of the midwifery profession in the private sector emerged as the two key themes. Household poverty pushed the CMWs to work in this perceived low-status occupation. Their families supported them since they became the breadwinners. The successful CMWs also had an intrinsic sense of what was required to establish a private practice; they exhibited professionalism, had strong business sense and provided respectful maternity care. The study provides insight into how the program might improve its functioning by adapting its recruitment criteria to ensure selection of right candidates.
Recursive dynamics algorithm for multibody systems with prescribed motion
Jain, Abhinandan; Rodriguez, Guillermo
1993-10-01
This paper uses spatial operator techniques to develop a new algorithm for the dynamics of multibody systems with hinges undergoing prescribed motion. This algorithm is spatially recursive, and its computational complexity grows only linearly with the number of degrees of freedom in the system. Its structure is a hybrid of known recursive forward and inverse dynamics algorithms for regular multibody systems. Changes to the prescribed/nonprescribed nature of hinges can be implemented during run time since they are handled with very low overhead in the algorithm.
A New Dynamical Evolutionary Algorithm Based on Statistical Mechanics
Institute of Scientific and Technical Information of China (English)
LI YuanXiang(李元香); ZOU XiuFen(邹秀芬); KANG LiShan(康立山); Zbigniew Michalewicz
2003-01-01
In this paper, a new dynamical evolutionary algorithm (DEA) is presented basedon the theory of statistical mechanics. The novelty of this kind of dynamical evolutionary algorithmis that all individuals in a population (called particles in a dynamical system) are running andsearching with their population evolving driven by a nev selecting mechanism. This mechanismsimulates the principle of molecular dynamics, which is easy to design and implement. A basictheoretical analysis for the dynamical evolutionary algorithm is given and as a consequence twostopping criteria of the algorithm are derived from the principle of energy minimization and the lawof entropy increasing. In order to verify the effectiveness of the scheme, DEA is applied to solvingsome typical numerical function minimization problems which are poorly solved by traditionalevolutionary algorithms. The experimental results show that DEA is fast and reliable.
Algebraic dynamics solution to and algebraic dynamics algorithm for nonlinear advection equation
Institute of Scientific and Technical Information of China (English)
2008-01-01
Algebraic dynamics approach and algebraic dynamics algorithm for the solution of nonlinear partial differential equations are applied to the nonlinear advection equa-tion. The results show that the approach is effective for the exact analytical solu-tion and the algorithm has higher precision than other existing algorithms in nu-merical computation for the nonlinear advection equation.
Intersecting Asset-Based Service, Strengths, and Mentoring for Socially Responsible Leadership.
Hastings, Lindsay
2016-06-01
Grounded in a youth leadership and mentoring program, this chapter discusses the value of asset-based community development from the service-learning literature and the concept of generativity from the leadership development literature. PMID:27150907
Dynamic Uniform Scaling for Multiobjective Genetic Algorithms
DEFF Research Database (Denmark)
Pedersen, Gerulf; Goldberg, D.E.
2004-01-01
Before Multiobjective Evolutionary Algorithms (MOEAs) can be used as a widespread tool for solving arbitrary real world problems there are some salient issues which require further investigation. One of these issues is how a uniform distribution of solutions along the Pareto non-dominated front can......, the issue of obtaining a diverse set of solutions for badly scaled objective functions will be investigated and proposed solutions will be implemented using the NSGA-II algorithm....
Research of Steward Dynamic Platform Simulation Numerical Algorithm
Institute of Scientific and Technical Information of China (English)
Wang Mingwei; Hu Deji
2015-01-01
In order to achieve attitude control of the six degrees of freedom Steward dynamic platform, as well as the real time simulation cockpit attitude, Washout Filtering method was adopted in this paper as the simulation algorithm to derive Washout Filter high-pass, low-pass filter transfer function into a differential equation algorithm and longitudinal acceleration tilt strategy, pitching strategies etc. Experimental examples are used to verify correctness of the algorithm.
Finding Global Minima with a New Dynamical Evolutionary Algorithm
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
A new dynamical evolutionary algorithm (DEA) based on the theory of statistical mechanics is presented. This algorithm is very different from the traditional evolutionary algorithm and the two novel fe-atures are the unique of selecting strategy and the determination of individuals that are selected to crossover and mutate. We use DEA to solve a lot of global optimization problems that are nonlinear, multimodal and multidimensional and obtain satisfactory results.
Institute of Scientific and Technical Information of China (English)
WANG Shundin; ZHANG Hua
2008-01-01
Using functional derivative technique In quantum field theory,the algebraic dy-namics approach for solution of ordinary differential evolution equations was gen-eralized to treat partial differential evolution equations.The partial differential evo-lution equations were lifted to the corresponding functional partial differential equations in functional space by Introducing the time translation operator.The functional partial differential evolution equations were solved by algebraic dynam-ics.The algebraic dynamics solutions are analytical In Taylor series In terms of both initial functions and time.Based on the exact analytical solutions,a new nu-merical algorithm-algebraic dynamics algorithm was proposed for partial differ-ential evolution equations.The difficulty of and the way out for the algorithm were discussed.The application of the approach to and computer numerical experi-ments on the nonlinear Burgers equation and meteorological advection equation indicate that the algebraic dynamics approach and algebraic dynamics algorithm are effective to the solution of nonlinear partial differential evolution equations both analytically and numerically.
Dynamic Obfuscation Algorithm based on Demand-Driven Symbolic Execution
Directory of Open Access Journals (Sweden)
Yubo Yang
2014-06-01
Full Text Available Dynamic code obfuscation technique increases the difficulty of dynamically reverse by the runtime confusion. Path explosion directly affects the efficiency and accuracy of dynamic symbolic analysis. Because of the defect, this paper presents a novel algorithm DDD (Demand-Driven Dynamic Obfuscation Algorithm by using the demand-driven theory of symbolic analysis. First, create a large number of invalid paths to mislead the result of symbolic analysis. Second, according to the demand-driven theory, create a specific execution path to protect the security of software. The design and implementation of the algorithm is based on the current popular and mature SMT (satisfiability model theory, and the experimental effects are tested by Z3 - the SMT solver and Pex - the symbolic execution test tools. The experimental results prove that the algorithm enhance the security of the program.
New MPPT algorithm based on hybrid dynamical theory
Elmetennani, Shahrazed
2014-11-01
This paper presents a new maximum power point tracking algorithm based on the hybrid dynamical theory. A multiceli converter has been considered as an adaptation stage for the photovoltaic chain. The proposed algorithm is a hybrid automata switching between eight different operating modes, which has been validated by simulation tests under different working conditions. © 2014 IEEE.
Multi-Particle Collision Dynamics Algorithm for Nematic Fluids
Shendruk, Tyler N.; Yeomans, Julia M.
2015-01-01
Research on transport, self-assembly and defect dynamics within confined, flowing liquid crystals requires versatile and computationally efficient mesoscopic algorithms to account for fluctuating nematohydrodynamic interactions. We present a multi-particle collision dynamics (MPCD) based algorithm to simulate liquid-crystal hydrodynamic and director fields in two and three dimensions. The nematic-MPCD method is shown to successfully reproduce the features of a nematic liquid crystal, includin...
Partially dynamic vehicle routing - models and algorithms
DEFF Research Database (Denmark)
Larsen, Allan; Madsen, Oli B.G.; Solomon, M.
2002-01-01
In this paper we propose a framework for dynamic routing systems based on their degree of dynamism. Next, we consider its impact on solution methodology and quality. Specifically, we introduce the Partially Dynamic Travelling Repairman Problem and describe several dynamic policies to minimize...... routing costs. The results of our computational study indicate that increasing the dynamic level results in a linear increase in route length for all policies studied. Furthermore, a Nearest Neighbour policy performed, on the average, uniformly better than the other dispatching rules studied. Among these...
A New Parallel Algorithm in Power Flow Calculation: Dynamic Asynchronous Parallel Algorithm
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Based on the general methods in power flow calculation of power system and onconceptions and classifications of parallel algorithm, a new approach named DynamicAsynchronous Parallel Algorithm that applies to the online analysis and real-time dispatching and controlling of large-scale power network was put forward in this paper. Its performances of high speed and dynamic following have been verified on IEEE-14 bus system.
Institute of Scientific and Technical Information of China (English)
2008-01-01
Using functional derivative technique in quantum field theory, the algebraic dy-namics approach for solution of ordinary differential evolution equations was gen-eralized to treat partial differential evolution equations. The partial differential evo-lution equations were lifted to the corresponding functional partial differential equations in functional space by introducing the time translation operator. The functional partial differential evolution equations were solved by algebraic dynam-ics. The algebraic dynamics solutions are analytical in Taylor series in terms of both initial functions and time. Based on the exact analytical solutions, a new nu-merical algorithm—algebraic dynamics algorithm was proposed for partial differ-ential evolution equations. The difficulty of and the way out for the algorithm were discussed. The application of the approach to and computer numerical experi-ments on the nonlinear Burgers equation and meteorological advection equation indicate that the algebraic dynamics approach and algebraic dynamics algorithm are effective to the solution of nonlinear partial differential evolution equations both analytically and numerically.
Computational Granular Dynamics Models and Algorithms
Pöschel, Thorsten
2005-01-01
Computer simulations not only belong to the most important methods for the theoretical investigation of granular materials, but also provide the tools that have enabled much of the expanding research by physicists and engineers. The present book is intended to serve as an introduction to the application of numerical methods to systems of granular particles. Accordingly, emphasis is placed on a general understanding of the subject rather than on the presentation of the latest advances in numerical algorithms. Although a basic knowledge of C++ is needed for the understanding of the numerical methods and algorithms in the book, it avoids usage of elegant but complicated algorithms to remain accessible for those who prefer to use a different programming language. While the book focuses more on models than on the physics of granular material, many applications to real systems are presented.
Using Genetic Algorithms for Navigation Planning in Dynamic Environments
Directory of Open Access Journals (Sweden)
Ferhat Uçan
2012-01-01
Full Text Available Navigation planning can be considered as a combination of searching and executing the most convenient flight path from an initial waypoint to a destination waypoint. Generally the aim is to follow the flight path, which provides minimum fuel consumption for the air vehicle. For dynamic environments, constraints change dynamically during flight. This is a special case of dynamic path planning. As the main concern of this paper is flight planning, the conditions and objectives that are most probable to be used in navigation problem are considered. In this paper, the genetic algorithm solution of the dynamic flight planning problem is explained. The evolutionary dynamic navigation planning algorithm is developed for compensating the existing deficiencies of the other approaches. The existing fully dynamic algorithms process unit changes to topology one modification at a time, but when there are several such operations occurring in the environment simultaneously, the algorithms are quite inefficient. The proposed algorithm may respond to the concurrent constraint updates in a shorter time for dynamic environment. The most secure navigation of the air vehicle is planned and executed so that the fuel consumption is minimum.
A multicast dynamic wavelength assignment algorithm based on matching degree
Institute of Scientific and Technical Information of China (English)
WU Qi-wu; ZHOU Xian-wei; WANG Jian-ping; YIN Zhi-hong; ZHANG Long
2009-01-01
The wavelength assignment with multiple multicast requests in fixed routing WDM network is studied. A new multicast dynamic wavelength assignment algorithm is presented based on matching degree. First, the wavelength matching degree between available wavelengths and multicast routing trees is introduced into the algorithm. Then, the wavelength assign-ment is translated into the maximum weight matching in bipartite graph, and this matching problem is solved by using an extended Kuhn-Munkres algorithm. The simulation results prove that the overall optimal wavelength assignment scheme is obtained in polynomial time. At the same time, the proposed algorithm can reduce the connecting blocking probability and improve the system resource utilization.
Dynamic gate algorithm for multimode fiber Bragg grating sensor systems.
Ganziy, D; Jespersen, O; Woyessa, G; Rose, B; Bang, O
2015-06-20
We propose a novel dynamic gate algorithm (DGA) for precise and accurate peak detection. The algorithm uses a threshold-determined detection window and center of gravity algorithm with bias compensation. We analyze the wavelength fit resolution of the DGA for different values of the signal-to-noise ratio and different peak shapes. Our simulations and experiments demonstrate that the DGA method is fast and robust with better stability and accuracy than conventional algorithms. This makes it very attractive for future implementation in sensing systems, especially based on multimode fiber Bragg gratings. PMID:26193010
Performance Comparision of Dynamic Load Balancing Algorithm in Cloud Computing
Directory of Open Access Journals (Sweden)
Yogita kaushik
2016-08-01
Full Text Available Cloud computing as a distributed paradigm, it has the latent to make over a large part of the Cooperative industry. In cloud computing it’s automatically describe more technologies like distributed computing, virtualization, software, web services and networking. We review the new cloud computing technologies, and indicate the main challenges for their development in future, among which load balancing problem stands out and attracts our attention Concept of load balancing in networking and in cloud environment both are widely different. Load balancing in networking its complete concern to avoid the problem of overloading and under loading in any sever networking cloud computing its complete different its involves different elements metrics such as security, reliability, throughput, tolerance, on demand services, cost etc. Through these elements we avoiding various node problem of distributing system where many services waiting for request and others are heavily loaded and through these its increase response time and degraded performance optimization. In this paper first we classify algorithms in static and dynamic. Then we analyzed the dynamic algorithms applied in dynamics environments in cloud. Through this paper we have been show compression of various dynamics algorithm in which we include honey bee algorithm, throttled algorithm, Biased random algorithm with different elements and describe how and which is best in cloud environment with different metrics mainly used elements are performance, resource utilization and minimum cost. Our main focus of paper is in the analyze various load balancing algorithms and their applicability in cloud environment.
Effective multicasting algorithm for dynamic membership with delay constraint
Institute of Scientific and Technical Information of China (English)
CHEN Lin; XU Zheng-quan
2006-01-01
This paper proposes an effective heuristic algorithm for dynamic multicast routing with delay-constrained DDMR.The tree constructed by DDMR has the following characteristics: (1) multicast tree changes with the dynamic memberships; (2)the cost of the tree is as small as possible at each node addition/removal event; (3) all of the path delay meet a fixed delay constraint;(4) minimal perturbation to an existing tree. The proposed algorithm is based on "damage" and "usefulness" concepts proposed in previous work, and has a new parameter bf(Balancing Factor) for judging whether or not to rearrange a tree region when membership changes. Mutation operation in Genetic Algorithm (GA) is also employed to find an attached node for a new adding node.Simulation showed that our algorithm performs well and is better than static heuristic algorithms, in term of cost especially.
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.
Parallel Algorithm and Dynamic Exponent for Diffusion-limited Aggregation
Moriarty, K J M; Greenlaw, R
1997-01-01
A parallel algorithm for ``diffusion-limited aggregation'' (DLA) is described and analyzed from the perspective of computational complexity. The dynamic exponent z of the algorithm is defined with respect to the probabilistic parallel random-access machine (PRAM) model of parallel computation according to $T \\sim L^{z}$, where L is the cluster size, T is the running time, and the algorithm uses a number of processors polynomial in D_2 is the second generalized dimension. Simulations of DLA are carried out to measure D_2 and to test scaling assumptions employed in the complexity analysis of the parallel algorithm. It is plausible that the parallel algorithm attains the minimum possible value of the dynamic exponent in which case z characterizes the intrinsic history dependence of DLA.
Dynamic Uniform Scaling for Multiobjective Genetic Algorithms
DEFF Research Database (Denmark)
Pedersen, Gerulf; Goldberg, David E.
2004-01-01
Before Multiobjective Evolutionary Algorithms (MOEAs) can be used as a widespread tool for solving arbitrary real world problems there are some salient issues which require further investigation. One of these issues is how a uniform distribution of solutions along the Pareto non-dominated front c...
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.
Dynamic programming algorithm for detecting dim infrared moving targets
He, Lisha; Mao, Liangjing; Xie, Lijun
2009-10-01
Infrared (IR) target detection is a key part of airborne infrared weapon system, especially the detection of poor dim moving IR target embedded in complex context. This paper presents an improved Dynamic Programming (DP) algorithm in allusion to low Signal to Noise Ratio (SNR) infrared dim moving targets under cluttered context. The algorithm brings the dim target to prominence by accumulating the energy of pixels in the image sequence, after suppressing the background noise with a mathematical morphology preprocessor. As considering the continuity and stabilization of target's energy and forward direction, this algorithm has well solved the energy scattering problem that exists in the original DP algorithm. An effective energy segmentation threshold is given by a Contrast-Limited Adaptive Histogram Equalization (CLAHE) filter with a regional peak extraction algorithm. Simulation results show that the improved DP tracking algorithm performs well in detecting poor dim targets.
Multi-particle collision dynamics algorithm for nematic fluids.
Shendruk, Tyler N; Yeomans, Julia M
2015-07-01
Research on transport, self-assembly and defect dynamics within confined, flowing liquid crystals requires versatile and computationally efficient mesoscopic algorithms to account for fluctuating nematohydrodynamic interactions. We present a multi-particle collision dynamics (MPCD) based algorithm to simulate liquid-crystal hydrodynamic and director fields in two and three dimensions. The nematic-MPCD method is shown to successfully reproduce the features of a nematic liquid crystal, including a nematic-isotropic phase transition with hysteresis in 3D, defect dynamics, isotropic Frank elastic coefficients, tumbling and shear alignment regimes and boundary condition-dependent order parameter fields. PMID:26035731
A Hybrid Immigrants Scheme for Genetic Algorithms in Dynamic Environments
Institute of Scientific and Technical Information of China (English)
Shengxiang Yang; Renato Tinós
2007-01-01
Dynamic optimization problems are a kind of optimization problems that involve changes over time. They pose a serious challenge to traditional optimization methods as well as conventional genetic algorithms since the goal is no longer to search for the optimal solution(s) of a fixed problem but to track the moving optimum over time. Dynamic optimization problems have attracted a growing interest from the genetic algorithm community in recent years. Several approaches have been developed to enhance the performance of genetic algorithms in dynamic environments. One approach is to maintain the diversity of the population via random immigrants. This paper proposes a hybrid immigrants scheme that combines the concepts of elitism, dualism and random immigrants for genetic algorithms to address dynamic optimization problems. In this hybrid scheme, the best individual, i.e., the elite, from the previous generation and its dual individual are retrieved as the bases to create immigrants via traditional mutation scheme. These elitism-based and dualism-based immigrants together with some random immigrants are substituted into the current population, replacing the worst individuals in the population. These three kinds of immigrants aim to address environmental changes of slight, medium and significant degrees respectively and hence efficiently adapt genetic algorithms to dynamic environments that are subject to different severities of changes. Based on a series of systematically constructed dynamic test problems, experiments are carried out to investigate the performance of genetic algorithms with the hybrid immigrants scheme and traditional random immigrants scheme. Experimental results validate the efficiency of the proposed hybrid immigrants scheme for improving the performance of genetic algorithms in dynamic environments.
Quantum Dynamical Entropies and Gács Algorithmic Entropy
Directory of Open Access Journals (Sweden)
Fabio Benatti
2012-07-01
Full Text Available Several quantum dynamical entropies have been proposed that extend the classical Kolmogorov–Sinai (dynamical entropy. The same scenario appears in relation to the extension of algorithmic complexity theory to the quantum realm. A theorem of Brudno establishes that the complexity per unit time step along typical trajectories of a classical ergodic system equals the KS-entropy. In the following, we establish a similar relation between the Connes–Narnhofer–Thirring quantum dynamical entropy for the shift on quantum spin chains and the Gács algorithmic entropy. We further provide, for the same system, a weaker linkage between the latter algorithmic complexity and a different quantum dynamical entropy proposed by Alicki and Fannes.
Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites
Directory of Open Access Journals (Sweden)
Maocai Wang
2014-01-01
Full Text Available Imaging satellite scheduling is an NP-hard problem with many complex constraints. This paper researches the scheduling problem for dynamic tasks oriented to some emergency cases. After the dynamic properties of satellite scheduling were analyzed, the optimization model is proposed in this paper. Based on the model, two heuristic algorithms are proposed to solve the problem. The first heuristic algorithm arranges new tasks by inserting or deleting them, then inserting them repeatedly according to the priority from low to high, which is named IDI algorithm. The second one called ISDR adopts four steps: insert directly, insert by shifting, insert by deleting, and reinsert the tasks deleted. Moreover, two heuristic factors, congestion degree of a time window and the overlapping degree of a task, are employed to improve the algorithm’s performance. Finally, a case is given to test the algorithms. The results show that the IDI algorithm is better than ISDR from the running time point of view while ISDR algorithm with heuristic factors is more effective with regard to algorithm performance. Moreover, the results also show that our method has good performance for the larger size of the dynamic tasks in comparison with the other two methods.
Institute of Scientific and Technical Information of China (English)
WANG; Shunjin; ZHANG; Hua
2006-01-01
The problem of preserving fidelity in numerical computation of nonlinear ordinary differential equations is studied in terms of preserving local differential structure and approximating global integration structure of the dynamical system.The ordinary differential equations are lifted to the corresponding partial differential equations in the framework of algebraic dynamics,and a new algorithm-algebraic dynamics algorithm is proposed based on the exact analytical solutions of the ordinary differential equations by the algebraic dynamics method.In the new algorithm,the time evolution of the ordinary differential system is described locally by the time translation operator and globally by the time evolution operator.The exact analytical piece-like solution of the ordinary differential equations is expressd in terms of Taylor series with a local convergent radius,and its finite order truncation leads to the new numerical algorithm with a controllable precision better than Runge Kutta Algorithm and Symplectic Geometric Algorithm.
An enhanced dynamic hash TRIE algorithm for lexicon search
Yang, Lai; Xu, Lida; Shi, Zhongzhi
2012-11-01
Information retrieval (IR) is essential to enterprise systems along with growing orders, customers and materials. In this article, an enhanced dynamic hash TRIE (eDH-TRIE) algorithm is proposed that can be used in a lexicon search in Chinese, Japanese and Korean (CJK) segmentation and in URL identification. In particular, the eDH-TRIE algorithm is suitable for Unicode retrieval. The Auto-Array algorithm and Hash-Array algorithm are proposed to handle the auxiliary memory allocation; the former changes its size on demand without redundant restructuring, and the latter replaces linked lists with arrays, saving the overhead of memory. Comparative experiments show that the Auto-Array algorithm and Hash-Array algorithm have better spatial performance; they can be used in a multitude of situations. The eDH-TRIE is evaluated for both speed and storage and compared with the naïve DH-TRIE algorithms. The experiments show that the eDH-TRIE algorithm performs better. These algorithms reduce memory overheads and speed up IR.
Functional clustering algorithm for the analysis of dynamic network data
Feldt, S.; Waddell, J; Hetrick, V. L.; Berke, J. D.; Żochowski, M
2009-01-01
We formulate a technique for the detection of functional clusters in discrete event data. The advantage of this algorithm is that no prior knowledge of the number of functional groups is needed, as our procedure progressively combines data traces and derives the optimal clustering cutoff in a simple and intuitive manner through the use of surrogate data sets. In order to demonstrate the power of this algorithm to detect changes in network dynamics and connectivity, we apply it to both simulat...
An Algorithm of Sensor Management Based on Dynamic Target Detection
Institute of Scientific and Technical Information of China (English)
LIUXianxing; ZHOULin; JINYong
2005-01-01
The probability density of stationary target is only evolved at measurement update, but the probability density of dynamic target is evolved not only at measurement update but also during measurements, this paper researches an algorithm of dynamic targets detection. Firstly, it presents the evolution of probability density at measurement update by Bayes' rule and the evolution of probability density during measurements by Fokker-Planck differential equations, respectively. Secondly, the method of obtaining information entropy by the probability density is given and sensor resources are distributed based on the evolution of information entropy viz. the maximization of information gain. Simulation results show that compared with the algorithm of serial search, this algorithm is feasible and effective when it is used to detect dynamic target.
Crime Busting Model Based on Dynamic Ranking Algorithms
Directory of Open Access Journals (Sweden)
Yang Cao
2013-01-01
Full Text Available This paper proposed a crime busting model with two dynamic ranking algorithms to detect the likelihood of a suspect and the possibility of a leader in a complex social network. Signally, in order to obtain the priority list of suspects, an advanced network mining approach with a dynamic cumulative nominating algorithm is adopted to rapidly reduce computational expensiveness than most other topology-based approaches. Our method can also greatly increase the accuracy of solution with the enhancement of semantic learning filtering at the same time. Moreover, another dynamic algorithm of node contraction is also presented to help identify the leader among conspirators. Test results are given to verify the theoretical results, which show the great performance for either small or large datasets.
Left ventricular border recognition using a dynamic search algorithm
International Nuclear Information System (INIS)
Initial results obtained with a simple, fully automated algorithm for detection of left ventricular boundaries are presented. The strength of this approach is the use of dynamic programming search techniques, which allow determination of local border points to be influenced by the entire global border location. The relative contributions of mask mode subtraction and the dynamic search technique are evaluated with respect to accurate border definition. These computer-determined ventricular borders are compared with hand-traced borders on subtracted and unsubtracted images. The modular dynamic search algorithm is shown to perform better than previously described algorithms, which generally require operator interaction. It is also shown that for both manual and automated techniques, ventricular borders derived from subtracted images may be significantly different from borders derived from nonsubtracted images
Novel algorithm for distributed replicas management based on dynamic programming
Institute of Scientific and Technical Information of China (English)
Wang Tao; Lu Xianliang; Hou Mengshu
2006-01-01
Replicas can improve the data reliability in distributed system. However, the traditional algorithms for replica management are based on the assumption that all replicas have the uniform reliability, which is inaccurate in some actual systems. To address such problem, a novel algorithm is proposed based on dynamic programming to manage the number and distribution of replicas in different nodes. By using Markov model, replicas management is organized as a multi-phase process, and the recursion equations are provided. In this algorithm, the heterogeneity of nodes, the expense for maintaining replicas and the engaged space have been considered. Under these restricted conditions, this algorithm realizes high data reliability in a distributed system. The results of case analysis prove the feasibility of the algorithm.
An improved harmony search algorithm with dynamically varying bandwidth
Kalivarapu, J.; Jain, S.; Bag, S.
2016-07-01
The present work demonstrates a new variant of the harmony search (HS) algorithm where bandwidth (BW) is one of the deciding factors for the time complexity and the performance of the algorithm. The BW needs to have both explorative and exploitative characteristics. The ideology is to use a large BW to search in the full domain and to adjust the BW dynamically closer to the optimal solution. After trying a series of approaches, a methodology inspired by the functioning of a low-pass filter showed satisfactory results. This approach was implemented in the self-adaptive improved harmony search (SIHS) algorithm and tested on several benchmark functions. Compared to the existing HS algorithm and its variants, SIHS showed better performance on most of the test functions. Thereafter, the algorithm was applied to geometric parameter optimization of a friction stir welding tool.
Lorentz Covariant Canonical Symplectic Algorithms for Dynamics of Charged Particles
Wang, Yulei; Qin, Hong
2016-01-01
In this paper, the Lorentz covariance of algorithms is introduced. Under Lorentz transformation, both the form and performance of a Lorentz covariant algorithm are invariant. To acquire the advantages of symplectic algorithms and Lorentz covariance, a general procedure for constructing Lorentz covariant canonical symplectic algorithms (LCCSA) is provided, based on which an explicit LCCSA for dynamics of relativistic charged particles is built. LCCSA possesses Lorentz invariance as well as long-term numerical accuracy and stability, due to the preservation of discrete symplectic structure and Lorentz symmetry of the system. For situations with time-dependent electromagnetic fields, which is difficult to handle in traditional construction procedures of symplectic algorithms, LCCSA provides a perfect explicit canonical symplectic solution by implementing the discretization in 4-spacetime. We also show that LCCSA has built-in energy-based adaptive time steps, which can optimize the computation performance when th...
A Dynamic Hashing Algorithm Suitable for Embedded System
Directory of Open Access Journals (Sweden)
Li Jianwei
2013-06-01
Full Text Available With the increasing of the data numbers, the linear hashing will be a lot of overflow blocks result from Data skew and the index size of extendible hash will surge so as to waste too much memory. This lead to the above two Typical Dynamic hashing algorithm don’t suitable for embedded system that need certain real-time requirements and memory resources are very scarce. To solve this problem, this paper was proposed a dynamic hashing algorithm suitable for embedded system combining with the characteristic of extendible hashing and linear hashing.it is no overflow buckets and the index size is proportional to the adjustment number.
Dynamics of Quantum Adiabatic Evolution Algorithm for Number Partitioning
Smelyanskiy, Vadius; vonToussaint, Udo V.; Timucin, Dogan A.; Clancy, Daniel (Technical Monitor)
2002-01-01
We have developed a general technique to study the dynamics of the quantum adiabatic evolution algorithm applied to random combinatorial optimization problems in the asymptotic limit of large problem size n. We use as an example the NP-complete Number Partitioning problem and map the algorithm dynamics to that of an auxiliary quantum spin glass system with the slowly varying Hamiltonian. We use a Green function method to obtain the adiabatic eigenstates and the minimum exitation gap, gmin = O(n2(sup -n/2)), corresponding to the exponential complexity of the algorithm for Number Partitioning. The key element of the analysis is the conditional energy distribution computed for the set of all spin configurations generated from a given (ancestor) configuration by simultaneous flipping of a fixed number of spins. For the problem in question this distribution is shown to depend on the ancestor spin configuration only via a certain parameter related to the energy of the configuration. As the result, the algorithm dynamics can be described in terms of one-dimensional quantum diffusion in the energy space. This effect provides a general limitation of a quantum adiabatic computation in random optimization problems. Analytical results are in agreement with the numerical simulation of the algorithm.
von Maltzahn, Robyn; Durrheim, Kevin
2008-01-01
This paper contests the major emphasis placed on the multidimensional nature of poverty measurement. Instead, it argues that poverty pictures created by different measures and at different units of analysis tend to converge. This argument is derived from a comparison of poverty pictures created using income and asset-based measures at the national…
Time-Based Dynamic Trust Model Using Ant Colony Algorithm
Institute of Scientific and Technical Information of China (English)
TANG Zhuo; LU Zhengding; LI Kai
2006-01-01
The trust in distributed environment is uncertain, which is variation for various factors. This paper introduces TDTM, a model for time-based dynamic trust. Every entity in the distribute environment is endowed with a trust-vector, which figures the trust intensity between this entity and the others. The trust intensity is dynamic due to the time and the inter-operation between two entities, a method is proposed to quantify this change based on the mind of ant colony algorithm and then an algorithm for the transfer of trust relation is also proposed. Furthermore, this paper analyses the influence to the trust intensity among all entities that is aroused by the change of trust intensity between the two entities, and presents an algorithm to resolve the problem. Finally, we show the process of the trusts'change that is aroused by the time' lapse and the inter-operation through an instance.
Node-Dependence-Based Dynamic Incentive Algorithm in Opportunistic Networks
Directory of Open Access Journals (Sweden)
Ruiyun Yu
2014-01-01
Full Text Available Opportunistic networks lack end-to-end paths between source nodes and destination nodes, so the communications are mainly carried out by the “store-carry-forward” strategy. Selfish behaviors of rejecting packet relay requests will severely worsen the network performance. Incentive is an efficient way to reduce selfish behaviors and hence improves the reliability and robustness of the networks. In this paper, we propose the node-dependence-based dynamic gaming incentive (NDI algorithm, which exploits the dynamic repeated gaming to motivate nodes relaying packets for other nodes. The NDI algorithm presents a mechanism of tolerating selfish behaviors of nodes. Reward and punishment methods are also designed based on the node dependence degree. Simulation results show that the NDI algorithm is effective in increasing the delivery ratio and decreasing average latency when there are a lot of selfish nodes in the opportunistic networks.
A NEW ALGORITHM OF TIME STEPPING IN DYNAMIC VISCOELASTIC PROBLEMS
Institute of Scientific and Technical Information of China (English)
杨海天; 高强; 郭杏林; 邬瑞锋
2001-01-01
A new scheme of time stepping for solving the dynamic viscoelastic problems are presented. By expanding variables at a discrete time interval, FEM based recurrent formulae are derived. A self-adaptive algorithm for different sizes of time steps can be carried out to improve computing accuracy. Numerical validation shows satisfactory performance.
DYNAMIC REQUEST DISPATCHING ALGORITHM FOR WEB SERVER CLUSTER
Institute of Scientific and Technical Information of China (English)
Yang Zhenjiang; Zhang Deyun; Sun Qindong; Sun Qing
2006-01-01
Distributed architectures support increased load on popular web sites by dispatching client requests transparently among multiple servers in a cluster. Packet Single-Rewriting technology and client address hashing algorithm in ONE-IP technology which can ensure application-session-keep have been analyzed, an improved request dispatching algorithm which is simple, effective and supports dynamic load balance has been proposed. In this algorithm, dispatcher evaluates which server node will process request by applying a hash function to the client IP address and comparing the result with its assigned identifier subset; it adjusts the size of the subset according to the performance and current load of each server, so as to utilize all servers' resource effectively. Simulation shows that the improved algorithm has better performance than the original one.
Decentralized Control of Dynamic Routing with a Neural Network Algorithm
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
A state-dependent routing algorithm based on the neural network model, which takes advantage of other dynamic routing algorithm for circuit-switched network, is given in [1]. But, the Algorithm in [1] is a centralized control model with complex O (N7), therefore, is difficult to realize by hardware. A simplified algorithm is put forward in this paper, in which routing can be controlled decentralizedly, and its complexity is reduced to O (10N3). Computer simulations are made in a fully connected test network with eight nodes. The results show that the centralized control model has very effective performance that can match RTNR, and the centralized control model is not as good as the centralized one but better than DAR-1.
Parallel conjugate gradient algorithms for manipulator dynamic simulation
Fijany, Amir; Scheld, Robert E.
1989-01-01
Parallel conjugate gradient algorithms for the computation of multibody dynamics are developed for the specialized case of a robot manipulator. For an n-dimensional positive-definite linear system, the Classical Conjugate Gradient (CCG) algorithms are guaranteed to converge in n iterations, each with a computation cost of O(n); this leads to a total computational cost of O(n sq) on a serial processor. A conjugate gradient algorithms is presented that provide greater efficiency using a preconditioner, which reduces the number of iterations required, and by exploiting parallelism, which reduces the cost of each iteration. Two Preconditioned Conjugate Gradient (PCG) algorithms are proposed which respectively use a diagonal and a tridiagonal matrix, composed of the diagonal and tridiagonal elements of the mass matrix, as preconditioners. Parallel algorithms are developed to compute the preconditioners and their inversions in O(log sub 2 n) steps using n processors. A parallel algorithm is also presented which, on the same architecture, achieves the computational time of O(log sub 2 n) for each iteration. Simulation results for a seven degree-of-freedom manipulator are presented. Variants of the proposed algorithms are also developed which can be efficiently implemented on the Robot Mathematics Processor (RMP).
A Dynamic Approach to Weighted Suffix Tree Construction Algorithm
Directory of Open Access Journals (Sweden)
Binay Kumar Pandey
2011-02-01
Full Text Available In present time weighted suffix tree is consider as a one of the most important existing data structure used for analyzing molecular weighted sequence. Although a static partitioning based parallel algorithm existed for the construction of weighted suffix tree, but for very long weighted DNA sequences it takes significant amount of time. However, in our implementation of dynamic partition based parallel weighted suffix tree construction algorithm on cluster computing makes it possible to significantly accelerate the construction of weighted suffix tree.
Dynamic bandwidth allocation algorithm for full-band utilization
Institute of Scientific and Technical Information of China (English)
Han Guodong; Wang Hui; Wu Jiangxing
2006-01-01
To improve and optimize the bandwidth utilization for multi-service packet transporting system, a kind of Dynamic Full Bandwidth Utilized (DFBU) allocation algorithm allowing a single link to use far beyond its fair share bandwidth is presented. Three important parameters as the bound on max and minimum bandwidth, the maximum packet delay and the minimum bandwidth utilization are discussed and analyzed. Results of experiments show that the DFBU-algorithm is capable of making a single link in the system use all the spare bandwidth (up to full-bandwidth) while the performance of fairness and QoS requirement is still guaranteed.
Dynamic Routing Algorithm for Increasing Robustness in Satellite Networks
Institute of Scientific and Technical Information of China (English)
LI Dong-ni; ZHANG Da-kun
2008-01-01
In low earth orbit(LEO)and medium earth orbit(MEO)satellite networks,the network topology changes rapidly because of the high relative speed movement of satellites.When some inter-satellite links (ISLs)fail,they can not be repaired in a short time.In order to increase the robustness for LEO/MEO satellite networks,an effective dynamic routing algorithm is proposed.All the routes to a certain node are found by constructing a destination oriented acyclic directed graph(DOADG)with the node as the destination.In this algorithm,multiple routes are provided,loop-free is guaranteed,and as long as the DOADG maintains,it is not necessary to reroute even if some ISLs fail.Simulation results show that comparing to the conventional routing algorithms,it is more efficient and reliable,costs less transmission overhead and converges faster.
Multiscale Reaction-Diffusion Algorithms: PDE-Assisted Brownian Dynamics
Franz, Benjamin
2013-06-19
Two algorithms that combine Brownian dynami cs (BD) simulations with mean-field partial differential equations (PDEs) are presented. This PDE-assisted Brownian dynamics (PBD) methodology provides exact particle tracking data in parts of the domain, whilst making use of a mean-field reaction-diffusion PDE description elsewhere. The first PBD algorithm couples BD simulations with PDEs by randomly creating new particles close to the interface, which partitions the domain, and by reincorporating particles into the continuum PDE-description when they cross the interface. The second PBD algorithm introduces an overlap region, where both descriptions exist in parallel. It is shown that the overlap region is required to accurately compute variances using PBD simulations. Advantages of both PBD approaches are discussed and illustrative numerical examples are presented. © 2013 Society for Industrial and Applied Mathematics.
Iterative Dynamic Diversity Evolutionary Algorithm for Constrained Optimization
Institute of Scientific and Technical Information of China (English)
GAO Wei-Shang; SHAO Cheng
2014-01-01
Evolutionary algorithms (EAs) were shown to be effective for complex constrained optimization problems. However, inflexible exploration in general EAs would lead to losing the global optimum nearby the ill-convergence regions. In this paper, we propose an iterative dynamic diversity evolutionary algorithm (IDDEA) with contractive subregions guiding exploitation through local extrema to the global optimum in suitable steps. In IDDEA, a novel optimum estimation strategy with multi-agents evolving diversely is suggested to eﬃciently compute dominance trend and establish a subregion. In addition, a subregion converging iteration is designed to redistrict a smaller subregion in current subregion for next iteration, which is based on a special dominance estimation scheme. Meanwhile, an infimum penalty function is embedded into IDDEA to judge agents and penalize adaptively the unfeasible agents with the lowest fitness of feasible agents. Furthermore, several engineering design optimization problems taken from the specialized literature are successfully solved by the present algorithm with high reliable solutions.
A dynamic fuzzy clustering method based on genetic algorithm
Institute of Scientific and Technical Information of China (English)
ZHENG Yan; ZHOU Chunguang; LIANG Yanchun; GUO Dongwei
2003-01-01
A dynamic fuzzy clustering method is presented based on the genetic algorithm. By calculating the fuzzy dissimilarity between samples the essential associations among samples are modeled factually. The fuzzy dissimilarity between two samples is mapped into their Euclidean distance, that is, the high dimensional samples are mapped into the two-dimensional plane. The mapping is optimized globally by the genetic algorithm, which adjusts the coordinates of each sample, and thus the Euclidean distance, to approximate to the fuzzy dissimilarity between samples gradually. A key advantage of the proposed method is that the clustering is independent of the space distribution of input samples, which improves the flexibility and visualization. This method possesses characteristics of a faster convergence rate and more exact clustering than some typical clustering algorithms. Simulated experiments show the feasibility and availability of the proposed method.
A novel dynamical community detection algorithm based on weighting scheme
Li, Ju; Yu, Kai; Hu, Ke
2015-12-01
Network dynamics plays an important role in analyzing the correlation between the function properties and the topological structure. In this paper, we propose a novel dynamical iteration (DI) algorithm, which incorporates the iterative process of membership vector with weighting scheme, i.e. weighting W and tightness T. These new elements can be used to adjust the link strength and the node compactness for improving the speed and accuracy of community structure detection. To estimate the optimal stop time of iteration, we utilize a new stability measure which is defined as the Markov random walk auto-covariance. We do not need to specify the number of communities in advance. It naturally supports the overlapping communities by associating each node with a membership vector describing the node's involvement in each community. Theoretical analysis and experiments show that the algorithm can uncover communities effectively and efficiently.
Computational Fluid Dynamics. [numerical methods and algorithm development
1992-01-01
This collection of papers was presented at the Computational Fluid Dynamics (CFD) Conference held at Ames Research Center in California on March 12 through 14, 1991. It is an overview of CFD activities at NASA Lewis Research Center. The main thrust of computational work at Lewis is aimed at propulsion systems. Specific issues related to propulsion CFD and associated modeling will also be presented. Examples of results obtained with the most recent algorithm development will also be presented.
A SYMPLECTIC ALGORITHM FOR DYNAMICS OF RIGID BODY
Institute of Scientific and Technical Information of China (English)
LU Ying-jie; REN Ge-xue
2006-01-01
For the dynamics of a rigid body with a fixed point based on the quaternion and the corresponding generalized momenta, a displacement-based symplectic integration scheme for differential-algebraic equations is proposed and applied to the Lagrange's equations based on dependent generalized momenta. Numerical experiments show that the algorithm possesses such characters as high precision and preserving system invariants.More importantly, the generalized momenta based Lagrange's equations show unique advantages over the traditional Lagrange's equations in symplectic integrations.
SENSITIVITY ANALYSIS BASED ON LANCZOS ALGORITHM IN STRUCTURAL DYNAMICS
Institute of Scientific and Technical Information of China (English)
李书; 王波; 胡继忠
2003-01-01
The sensitivity calculating formulas in structural dynamics was developed byutilizing the mathematical theorem and new definitions of sensitivities. So the singularityproblem of sensitivity with repeated eigenvalues is solved completely. To improve thecomputational efficiency, the reduction system is obtained based on Lanczos vectors. Afterincorporating the mathematical theory with the Lanczos algorithm, the approximatesensitivity solution can be obtained. A numerical example is presented to illustrate theperformance of the method.
Cone Algorithm of Spinning Vehicles under Dynamic Coning Environment
Directory of Open Access Journals (Sweden)
Shuang-biao Zhang
2015-01-01
Full Text Available Due to the fact that attitude error of vehicles has an intense trend of divergence when vehicles undergo worsening coning environment, in this paper, the model of dynamic coning environment is derived firstly. Then, through investigation of the effect on Euler attitude algorithm for the equivalency of traditional attitude algorithm, it is found that attitude error is actually the roll angle error including drifting error and oscillating error, which is induced directly by dynamic coning environment and further affects the pitch angle and yaw angle through transferring. Based on definition of the cone frame and cone attitude, a cone algorithm is proposed by rotation relationship to calculate cone attitude, and the relationship between cone attitude and Euler attitude of spinning vehicle is established. Through numerical simulations with different conditions of dynamic coning environment, it is shown that the induced error of Euler attitude fluctuates by the variation of precession and nutation, especially by that of nutation, and the oscillating frequency of roll angle error is twice that of pitch angle error and yaw angle error. In addition, the rotation angle is more competent to describe the spinning process of vehicles under coning environment than Euler angle gamma, and the real pitch angle and yaw angle are calculated finally.
Dynamic hybrid algorithms for MAP inference in discrete MRFs.
Alahari, Karteek; Kohli, Pushmeet; Torr, Philip H S
2010-10-01
In this paper, we present novel techniques that improve the computational and memory efficiency of algorithms for solving multilabel energy functions arising from discrete mrfs or crfs. These methods are motivated by the observations that the performance of minimization algorithms depends on: 1) the initialization used for the primal and dual variables and 2) the number of primal variables involved in the energy function. Our first method (dynamic alpha-expansion) works by "recycling" results from previous problem instances. The second method simplifies the energy function by "reducing" the number of unknown variables present in the problem. Further, we show that it can also be used to generate a good initialization for the dynamic alpha-expansion algorithm by "reusing" dual variables. We test the performance of our methods on energy functions encountered in the problems of stereo matching and color and object-based segmentation. Experimental results show that our methods achieve a substantial improvement in the performance of alpha-expansion, as well as other popular algorithms such as sequential tree-reweighted message passing and max-product belief propagation. We also demonstrate the applicability of our schemes for certain higher order energy functions, such as the one described in [1], for interactive texture-based image and video segmentation. In most cases, we achieve a 10-15 times speed-up in the computation time. Our modified alpha-expansion algorithm provides similar performance to Fast-PD, but is conceptually much simpler. Both alpha-expansion and Fast-PD can be made orders of magnitude faster when used in conjunction with the "reduce" scheme proposed in this paper. PMID:20724761
Dynamic airspace configuration algorithms for next generation air transportation system
Wei, Jian
The National Airspace System (NAS) is under great pressure to safely and efficiently handle the record-high air traffic volume nowadays, and will face even greater challenge to keep pace with the steady increase of future air travel demand, since the air travel demand is projected to increase to two to three times the current level by 2025. The inefficiency of traffic flow management initiatives causes severe airspace congestion and frequent flight delays, which cost billions of economic losses every year. To address the increasingly severe airspace congestion and delays, the Next Generation Air Transportation System (NextGen) is proposed to transform the current static and rigid radar based system to a dynamic and flexible satellite based system. New operational concepts such as Dynamic Airspace Configuration (DAC) have been under development to allow more flexibility required to mitigate the demand-capacity imbalances in order to increase the throughput of the entire NAS. In this dissertation, we address the DAC problem in the en route and terminal airspace under the framework of NextGen. We develop a series of algorithms to facilitate the implementation of innovative concepts relevant with DAC in both the en route and terminal airspace. We also develop a performance evaluation framework for comprehensive benefit analyses on different aspects of future sector design algorithms. First, we complete a graph based sectorization algorithm for DAC in the en route airspace, which models the underlying air route network with a weighted graph, converts the sectorization problem into the graph partition problem, partitions the weighted graph with an iterative spectral bipartition method, and constructs the sectors from the partitioned graph. The algorithm uses a graph model to accurately capture the complex traffic patterns of the real flights, and generates sectors with high efficiency while evenly distributing the workload among the generated sectors. We further improve
Algorithms for optimal sequencing of dynamic multileaf collimators
Energy Technology Data Exchange (ETDEWEB)
Kamath, Srijit [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States); Sahni, Sartaj [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States); Palta, Jatinder [Department of Radiation Oncology, University of Florida, Gainesville, FL (United States); Ranka, Sanjay [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States)
2004-01-07
Dynamic multileaf collimator (DMLC) intensity modulated radiation therapy (IMRT) is used to deliver intensity modulated beams using a multileaf collimator (MLC), with the leaves in motion. DMLC-IMRT requires the conversion of a radiation intensity map into a leaf sequence file that controls the movement of the MLC while the beam is on. It is imperative that the intensity map delivered using the leaf sequence file be as close as possible to the intensity map generated by the dose optimization algorithm, while satisfying hardware constraints of the delivery system. Optimization of the leaf-sequencing algorithm has been the subject of several recent investigations. In this work, we present a systematic study of the optimization of leaf-sequencing algorithms for dynamic multileaf collimator beam delivery and provide rigorous mathematical proofs of optimized leaf sequence settings in terms of monitor unit (MU) efficiency under the most common leaf movement constraints that include leaf interdigitation constraint. Our analytical analysis shows that leaf sequencing based on unidirectional movement of the MLC leaves is as MU efficient as bi-directional movement of the MLC leaves.
A Dynamic Job Scheduling Algorithm for Parallel System
Institute of Scientific and Technical Information of China (English)
张建; 陆鑫达; 加力
2003-01-01
One of the fundamental problems in parallel and distributed systems is deciding how to allocate jobs toprocessors. The goals of job scheduling in a parallel environment are to minimize the parallel execution time of ajob and try to balance the user's desire with the system's desire. The users always want their jobs be completed asquickly as possible, while the system wants to service as many jobs as possible. In this paper, a dynamic job-scheduling algorithm was introduced. This algorithm tries to utilize the information of a practical system to allo-cate the jobs more evenly. The communication time between the processor and scheduler is overlapped with thecomputation time of the processor. So the communication overhead can be little. The principle of scheduling thejob is based on the desirability of each processor. The scheduler would not allocate a new job to a processor that isalready fully utilized. The execution efficiency of the system will be increased. This algorithm also can be reused inother complex algorithms.
Dynamic programming and graph algorithms in computer vision.
Felzenszwalb, Pedro F; Zabih, Ramin
2011-04-01
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 nontrivial guarantees concerning solution quality. In this paper, we 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.
GBT Dynamic Scheduling System: Algorithms, Metrics, and Simulations
Balser, D. S.; Bignell, C.; Braatz, J.; Clark, M.; Condon, J.; Harnett, J.; O'Neil, K.; Maddalena, R.; Marganian, P.; McCarty, M.; Sessoms, E.; Shelton, A.
2009-09-01
We discuss the scoring algorithm of the Robert C. Byrd Green Bank Telescope (GBT) Dynamic Scheduling System (DSS). Since the GBT is located in a continental, mid-latitude region where weather is dominated by water vapor and small-scale effects, the weather plays an important role in optimizing the observing efficiency of the GBT. We score observing sessions as a product of many factors. Some are continuous functions while others are binary limits taking values of 0 or 1, any one of which can eliminate a candidate session by forcing the score to zero. Others reflect management decisions to expedite observations by visiting observers, ensure the timely completion of projects, etc. Simulations indicate that dynamic scheduling can increase the effective observing time at frequencies higher than 10 GHz by about 50% over one full year. Beta tests of the DSS during Summer 2008 revealed the significance of various scheduling constraints and telescope overhead time to the overall observing efficiency.
Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms
Knudson, Matthew D.; Colby, Mitchell; Tumer, Kagan
2014-01-01
Dynamic flight environments in which objectives and environmental features change with respect to time pose a difficult problem with regards to planning optimal flight paths. Path planning methods are typically computationally expensive, and are often difficult to implement in real time if system objectives are changed. This computational problem is compounded when multiple agents are present in the system, as the state and action space grows exponentially. In this work, we use cooperative coevolutionary algorithms in order to develop policies which control agent motion in a dynamic multiagent unmanned aerial system environment such that goals and perceptions change, while ensuring safety constraints are not violated. Rather than replanning new paths when the environment changes, we develop a policy which can map the new environmental features to a trajectory for the agent while ensuring safe and reliable operation, while providing 92% of the theoretically optimal performance
Simple reversible molecular dynamics algorithms for Nosé-Hoover chain dynamics
Jang, Seogjoo; Voth, Gregory A.
1997-12-01
Reversible algorithms for Nosé-Hoover chain (NHC) dynamics are developed by simple extensions of Verlet-type algorithms: leap frog, position Verlet, and velocity Verlet. Tests for a model one dimensional harmonic oscillator show that they generate proper canonical distributions and are stable even with a large time step. Using these algorithms, the effects of the Nosé mass and chain length are examined. For a chain length of two, the sampling efficiency is much more sensitive to the Nosé mass than for a longer chain of length four. This indicates that the chain length in general should be longer than two. The noniterative nature of the algorithms allows them to be easily adapted for constraint dynamics. For the most general case where multiple NHC's are coupled to a system with constraints, a correction of the first Nosé acceleration is required, which is derived from the continuity equation on a constrained hypersurface of the phase space. Tests for model systems of two and three coupled harmonic oscillators with one normal mode constrained show that these algorithms, in combination with the corrected dynamical equations, sample the canonical distributions for the unconstrained degrees of freedom.
Energy Technology Data Exchange (ETDEWEB)
Huang, Xiaobiao, E-mail: xiahuang@slac.stanford.edu; Safranek, James
2014-09-01
Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.
Algorithms for computational fluid dynamics n parallel processors
International Nuclear Information System (INIS)
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
Dynamic behavior of shortest path routing algorithms for communication networks
Bertsekas, D. P.
1980-06-01
Several proposed routing algorithms for store and forward communication networks, including one currently in operation in the ARPANET, route messages along shortest paths computed by using some set of link lengths. When these lengths depend on current traffic conditions as they must in an adaptive algorithm, dynamic behavior questions such as stability convergence, and speed of convergence are of interest. This paper is the first attempt to analyze systematically these issues. It is shown that minimum queuing delay path algorithms tend to exhibit violent oscillatory behavior in the absence of a damping mechanism. The oscillations can be damped by means of several types of schemes, two of which are analyzed in this paper. In the first scheme a constant bias is added to the queuing delay thereby providing a preference towards paths with a small number of links. In the second scheme the effects of several past routings are averaged as, for example, when the link lengths are computed and communicated asynchronously throughout the network.
Bidirectional Dynamic Diversity Evolutionary Algorithm for Constrained Optimization
Directory of Open Access Journals (Sweden)
Weishang Gao
2013-01-01
Full Text Available Evolutionary algorithms (EAs were shown to be effective for complex constrained optimization problems. However, inflexible exploration-exploitation and improper penalty in EAs with penalty function would lead to losing the global optimum nearby or on the constrained boundary. To determine an appropriate penalty coefficient is also difficult in most studies. In this paper, we propose a bidirectional dynamic diversity evolutionary algorithm (Bi-DDEA with multiagents guiding exploration-exploitation through local extrema to the global optimum in suitable steps. In Bi-DDEA potential advantage is detected by three kinds of agents. The scale and the density of agents will change dynamically according to the emerging of potential optimal area, which play an important role of flexible exploration-exploitation. Meanwhile, a novel double optimum estimation strategy with objective fitness and penalty fitness is suggested to compute, respectively, the dominance trend of agents in feasible region and forbidden region. This bidirectional evolving with multiagents can not only effectively avoid the problem of determining penalty coefficient but also quickly converge to the global optimum nearby or on the constrained boundary. By examining the rapidity and veracity of Bi-DDEA across benchmark functions, the proposed method is shown to be effective.
Integrated dynamic shared protection algorithm for GMPLS networks
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
The path protection approach is widely investigated as a survivability solution for GMPLS networks, which has the advantage of efficient capacity utilization. However, there is a problem of the path protection approach that searching a disjoint backup path for a primary path is often unsuccessful. In order to resolve this problem, an integrated dynamic shared protection (IDSP) algorithm is proposed. The main idea of the proposed algorithm is that the path protection approach is first used to establish a backup path for the primary path; if the establishment is unsuccessful, then the primary path is dynamically divided into segments whose hop count are not fixed but not more than the limitation calculated by the equations introduced. In this proposal, backup bandwidth sharing is allowed to improve the capacity utilization ratio, which makes the link cost function quite different from previous ones. Simulation experiments are presented to demonstrate the efficiency of the proposed method compared with previous methods. Numerical results show that IDSP can not only achieve low protection failure probability but can also gain a better tradeoff between the protection overbuild and the average recovery time.
Dynamic characterization of oil fields, complex stratigraphically using genetic algorithms
International Nuclear Information System (INIS)
A novel methodology is presented in this paper for the characterization of highly heterogeneous oil fields by integration of the oil fields dynamic information to the static updated model. The objective of the oil field's characterization process is to build an oil field model, as realistic as possible, through the incorporation of all the available information. The classical approach consists in producing a model based in the oil field's static information, having as the process final stage the validation model with the dynamic information available. It is important to clarify that the term validation implies a punctual process by nature, generally intended to secure the required coherence between productive zones and petrophysical properties. The objective of the proposed methodology is to enhance the prediction capacity of the oil field's model by previously integrating, parameters inherent to the oil field's fluid dynamics by a process of dynamic data inversion through an optimization procedure based on evolutionary computation. The proposed methodology relies on the construction of the oil field's high-resolution static model, escalated by means of hybrid techniques while aiming to preserve the oil field's heterogeneity. Afterwards, using an analytic simulator as reference, the scaled model is methodically modified by means of an optimization process that uses genetic algorithms and production data as conditional information. The process's final product is a model that observes the static and dynamic conditions of the oil field with the capacity to minimize the economic impact that generates production historical adjustments to the simulation tasks. This final model features some petrophysical properties (porosity, permeability and water saturation), as modified to achieve a better adjustment of the simulated production's history versus the real one history matching. Additionally, the process involves a slight modification of relative permeability, which has
A Dynamic Multistage Hybrid Swarm Intelligence Optimization Algorithm for Function Optimization
Daqing Wu; Jianguo Zheng
2012-01-01
A novel dynamic multistage hybrid swarm intelligence optimization algorithm is introduced, which is abbreviated as DM-PSO-ABC. The DM-PSO-ABC combined the exploration capabilities of the dynamic multiswarm particle swarm optimizer (PSO) and the stochastic exploitation of the cooperative artificial bee colony algorithm (CABC) for solving the function optimization. In the proposed hybrid algorithm, the whole process is divided into three stages. In the first stage, a dynamic multiswarm PSO is c...
A Multiagent Dynamic Assessment Approach for Water Quality Based on Improved Q-Learning Algorithm
Jianjun Ni; Li Ren; Minghua Liu; Daqi Zhu
2013-01-01
The dynamic water quality assessment is a challenging and critical issue in water resource management systems. To deal with this complex problem, a dynamic water assessment model based on multiagent technology is proposed, and an improved Q-learning algorithm is used in this paper. In the proposed Q-learning algorithm, a fuzzy membership function and a punishment mechanism are introduced to improve the learning speed of Q-learning algorithm. The dynamic water quality assessment for different ...
A hybrid algorithm for parallel molecular dynamics simulations
Mangiardi, Chris M
2016-01-01
This article describes an algorithm for hybrid parallelization and SIMD vectorization of molecular dynamics simulations with short-ranged forces. The parallelization method combines domain decomposition with a thread-based parallelization approach. The goal of the work is to enable efficient simulations of very large (tens of millions of atoms) and inhomogeneous systems on many-core processors with hundreds or thousands of cores and SIMD units with large vector sizes. In order to test the efficiency of the method, simulations of a variety of configurations with up to 74 million atoms have been performed. Results are shown that were obtained on multi-core systems with AVX and AVX-2 processors as well as Xeon-Phi co-processors.
RETRACTED ARTICLE: Dynamic voltage restorer controller using grade algorithm
Directory of Open Access Journals (Sweden)
S. Deepa
2015-12-01
Full Text Available This paper deals with the terminology and various issues about power quality problems. This problem occurs owing to voltage sag, swell, harmonics, and surges. The sustained overvoltage and undervoltage originated from power system may often damage/or disrupt computerized process. Voltage sags and harmonics disturb the power quality and this can be overcome by custom power device called dynamic voltage restorer (DVR. The DVR is normally installed between the source voltage and critical or sensitive load. The vital role of DVR depends on the efficiency of the control technique involved in switching circuit of the inverter. In this paper, Combination of improved grade algorithm with fuzzy membership function is used to decide the Proportional-Integral coefficients. The DVR works well both in balanced and unbalanced conditions of voltages. The simulation results show the efficiency of the proposed method.
A local algorithm for detecting community structures in dynamic networks
Massaro, Emanuele; Guazzini, Andrea; Passarella, Andrea; Bagnoli, Franco
2013-01-01
The emergence and the global adaptation of mobile devices has influenced human interactions at the individual, community, and social levels leading to the so called Cyber-Physical World (CPW) convergence scenario [1]. One of the most important features of CPW is the possibility of exploiting information about the structure of social communities of users, that manifest through joint movement patterns and frequency of physical co-location: mobile devices of users that belong to the same social community are likely to "see" each other (and thus be able to communicate through ad hoc networking techniques) more frequently and regularly than devices outside of the community. In mobile opportunistic networks, this fact can be exploited, for example, to optimize networking operations such as forwarding and dissemination of messages. In this paper we present a novel local cognitive-inspired algorithm for revealing the structure of these dynamic social networks by exploiting information about physical encounters, logge...
VST telescope dynamic analisys and position control algorithms
Schipani, P
2001-01-01
The VST (VLT Survey Telescope) is a 2.6 m class Alt-Az telescope to be installed on Cerro Paranal in the Atacama desert, Northern Chile, in the European Southern Observatory (ESO) site. The VST is a wide-field imaging facility planned to supply databases for the ESO Very Large Telescope (VLT) science and carry out stand-alone observations in the UV to I spectral range. So far no telescope has been dedicated entirely to surveys; the VST will be the first survey telescope to start the operation, as a powerful survey facility for the VLT observatory. This paper will focus on the axes motion control system. The dynamic model of the telescope will be analyzed, as well as the effect of the wind disturbance on the telescope performance. Some algorithms for the telescope position control will be briefly discussed.
Parallel Genetic Algorithms with Dynamic Topology using Cluster Computing
Directory of Open Access Journals (Sweden)
ADAR, N.
2016-08-01
Full Text Available A parallel genetic algorithm (PGA conducts a distributed meta-heuristic search by employing genetic algorithms on more than one subpopulation simultaneously. PGAs migrate a number of individuals between subpopulations over generations. The layout that facilitates the interactions of the subpopulations is called the topology. Static migration topologies have been widely incorporated into PGAs. In this article, a PGA with a dynamic migration topology (D-PGA is proposed. D-PGA generates a new migration topology in every epoch based on the average fitness values of the subpopulations. The D-PGA has been tested against ring and fully connected migration topologies in a Beowulf Cluster. The D-PGA has outperformed the ring migration topology with comparable communication cost and has provided competitive or better results than a fully connected migration topology with significantly lower communication cost. PGA convergence behaviors have been analyzed in terms of the diversities within and between subpopulations. Conventional diversity can be considered as the diversity within a subpopulation. A new concept of permeability has been introduced to measure the diversity between subpopulations. It is shown that the success of the proposed D-PGA can be attributed to maintaining a high level of permeability while preserving diversity within subpopulations.
DEFF Research Database (Denmark)
Rong, Aiying; Hakonen, Henri; Lahdelma, Risto
2009-01-01
efficiency of the plants. We introduce in this paper the DRDP-RSC algorithm, which is a dynamic regrouping based dynamic programming (DP) algorithm based on linear relaxation of the ON/OFF states of the units, sequential commitment of units in small groups. Relaxed states of the plants are used to reduce...
AN ADVANCED DYNAMIC FEEDBACK AND RANDOM DISPATCHING LOAD-BALANCING ALGORITHM FOR GMLC IN 3G
Institute of Scientific and Technical Information of China (English)
Liao Jianxin; Zhang Hao; Zhu Xiaomin
2006-01-01
Based on the system architecture and software structure of GMLC (Gateway Mobile Location Center) in 3G (third generation), a new dynamic load-balancing algorithm is proposed. It bases on dynamic feedback and imports the increment for admitting new request into the load forecast. It dynamically adjusts the dispatching probability according to the remainder process capability of each node. Experiments on the performance of algorithm have been carried out in GMLC and the algorithm is compared with Pick-KX algorithm and DFB (Dynamic FeedBack) algorithm in average throughput and average response time. Experiments results show that the average throughput of the proposed algorithm is about five percents higher than that of the other two algorithms and the average response time is four percents higher under high system loading condition.
Ab initio multiple cloning algorithm for quantum nonadiabatic molecular dynamics
Makhov, Dmitry V.; Glover, William J.; Martinez, Todd J.; Shalashilin, Dmitrii V.
2014-08-01
We present a new algorithm for ab initio quantum nonadiabatic molecular dynamics that combines the best features of ab initio Multiple Spawning (AIMS) and Multiconfigurational Ehrenfest (MCE) methods. In this new method, ab initio multiple cloning (AIMC), the individual trajectory basis functions (TBFs) follow Ehrenfest equations of motion (as in MCE). However, the basis set is expanded (as in AIMS) when these TBFs become sufficiently mixed, preventing prolonged evolution on an averaged potential energy surface. We refer to the expansion of the basis set as "cloning," in analogy to the "spawning" procedure in AIMS. This synthesis of AIMS and MCE allows us to leverage the benefits of mean-field evolution during periods of strong nonadiabatic coupling while simultaneously avoiding mean-field artifacts in Ehrenfest dynamics. We explore the use of time-displaced basis sets, "trains," as a means of expanding the basis set for little cost. We also introduce a new bra-ket averaged Taylor expansion (BAT) to approximate the necessary potential energy and nonadiabatic coupling matrix elements. The BAT approximation avoids the necessity of computing electronic structure information at intermediate points between TBFs, as is usually done in saddle-point approximations used in AIMS. The efficiency of AIMC is demonstrated on the nonradiative decay of the first excited state of ethylene. The AIMC method has been implemented within the AIMS-MOLPRO package, which was extended to include Ehrenfest basis functions.
Ab initio multiple cloning algorithm for quantum nonadiabatic molecular dynamics
Energy Technology Data Exchange (ETDEWEB)
Makhov, Dmitry V.; Shalashilin, Dmitrii V. [Department of Chemistry, University of Leeds, Leeds LS2 9JT (United Kingdom); Glover, William J.; Martinez, Todd J. [Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, USA and SLAC National Accelerator Laboratory, Menlo Park, California 94025 (United States)
2014-08-07
We present a new algorithm for ab initio quantum nonadiabatic molecular dynamics that combines the best features of ab initio Multiple Spawning (AIMS) and Multiconfigurational Ehrenfest (MCE) methods. In this new method, ab initio multiple cloning (AIMC), the individual trajectory basis functions (TBFs) follow Ehrenfest equations of motion (as in MCE). However, the basis set is expanded (as in AIMS) when these TBFs become sufficiently mixed, preventing prolonged evolution on an averaged potential energy surface. We refer to the expansion of the basis set as “cloning,” in analogy to the “spawning” procedure in AIMS. This synthesis of AIMS and MCE allows us to leverage the benefits of mean-field evolution during periods of strong nonadiabatic coupling while simultaneously avoiding mean-field artifacts in Ehrenfest dynamics. We explore the use of time-displaced basis sets, “trains,” as a means of expanding the basis set for little cost. We also introduce a new bra-ket averaged Taylor expansion (BAT) to approximate the necessary potential energy and nonadiabatic coupling matrix elements. The BAT approximation avoids the necessity of computing electronic structure information at intermediate points between TBFs, as is usually done in saddle-point approximations used in AIMS. The efficiency of AIMC is demonstrated on the nonradiative decay of the first excited state of ethylene. The AIMC method has been implemented within the AIMS-MOLPRO package, which was extended to include Ehrenfest basis functions.
Dynamic load balancing algorithm for molecular dynamics based on Voronoi cells domain decompositions
Energy Technology Data Exchange (ETDEWEB)
Fattebert, J.-L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Richards, D.F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Glosli, J.N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2012-12-01
We present a new algorithm for automatic parallel load balancing in classical molecular dynamics. It assumes a spatial domain decomposition of particles into Voronoi cells. It is a gradient method which attempts to minimize a cost function by displacing Voronoi sites associated with each processor/sub-domain along steepest descent directions. Excellent load balance has been obtained for quasi-2D and 3D practical applications, with up to 440·10^{6} particles on 65,536 MPI tasks.
A Density Based Dynamic Data Clustering Algorithm based on Incremental Dataset
Directory of Open Access Journals (Sweden)
K. R.S. Kumar
2012-01-01
Full Text Available Problem statement: Clustering and visualizing high-dimensional dynamic data is a challenging problem. Most of the existing clustering algorithms are based on the static statistical relationship among data. Dynamic clustering is a mechanism to adopt and discover clusters in real time environments. There are many applications such as incremental data mining in data warehousing applications, sensor network, which relies on dynamic data clustering algorithms. Approach: In this work, we present a density based dynamic data clustering algorithm for clustering incremental dataset and compare its performance with full run of normal DBSCAN, Chameleon on the dynamic dataset. Most of the clustering algorithms perform well and will give ideal performance with good accuracy measured with clustering accuracy, which is calculated using the original class labels and the calculated class labels. However, if we measure the performance with a cluster validation metric, then it will give another kind of result. Results: This study addresses the problems of clustering a dynamic dataset in which the data set is increasing in size over time by adding more and more data. So to evaluate the performance of the algorithms, we used Generalized Dunn Index (GDI, Davies-Bouldin index (DB as the cluster validation metric and as well as time taken for clustering. Conclusion: In this study, we have successfully implemented and evaluated the proposed density based dynamic clustering algorithm. The performance of the algorithm was compared with Chameleon and DBSCAN clustering algorithms. The proposed algorithm performed significantly well in terms of clustering accuracy as well as speed.
Identification of Dynamic Parameters Based on Pseudo-Parallel Ant Colony Optimization Algorithm
Institute of Scientific and Technical Information of China (English)
ZHAO Feng-yao; MA Zhen-yue; ZHANG Yun-liang
2007-01-01
For the parameter identification of dynamic problems, a pseudo-parallel ant colony optimization (PPACO) algorithm based on graph-based ant system (AS) was introduced. On the platform of ANSYS dynamic analysis, the PPACO algorithm was applied to the identification of dynamic parameters successfully. Using simulated data of forces and displacements, elastic modulus E and damping ratio ξ was identified for a designed 3D finite element model, and the detailed identification step was given. Mathematical example and simulation example show that the proposed method has higher precision, faster convergence speed and stronger antinoise ability compared with the standard genetic algorithm and the ant colony optimization (ACO) algorithms.
Analysis of Ant Colony Optimization and Population-Based Evolutionary Algorithms on Dynamic Problems
DEFF Research Database (Denmark)
Lissovoi, Andrei
This thesis presents new running time analyses of nature-inspired algorithms on various dynamic problems. It aims to identify and analyse the features of algorithms and problem classes which allow efficient optimization to occur in the presence of dynamic behaviour. We consider the following...
Dynamic shared segment protection algorithm with differentiated reliability in GMPLS networks
Institute of Scientific and Technical Information of China (English)
Wang Yan; Zheng Junhui; Zeng Jiazhi
2009-01-01
To improve the resource utilization ratio and shorten the recovery time of the shared path protection with differentiated reliability (SPP-DiR) algorithm, an algorithm called dynamic shared segment protection with differentiated reliability (DSSP-DiR) is proposed for survivable GMPLS networks. In the proposed algorithm, a primary path is dynamically divided into several segments according to the differentiated reliability requirements of the customers. In the SPP-DiR algorithm, the whole primary path should be protected, while in the DSSP-DiR algorithm, only partial segments on the primary path need to be protected, which can reduce more backup bandwidths than that in the SPP-DiR algorithm. Simulation results show that the DSSP-DiR algorithm achieves higher resource utilization ratio, lower protection failure probability, and shorter recovery time than the SPP-DiR algorithm.
A DYNAMICAL SYSTEM ALGORITHM FOR SOLVING A LEAST SQUARES PROBLEM WITH ORTHOGONALITY CONSTRAINTS
Institute of Scientific and Technical Information of China (English)
黄建国; 叶中行; 徐雷
2001-01-01
This paper introduced a dynamical system (neural networks) algorithm for solving a least squares problem with orthogonality constraints, which has wide applications in computer vision and signal processing. A rigorous analysis for the convergence and stability of the algorithm was provided. Moreover, a so called zero-extension technique was presented to keep the algorithm always convergent to the needed result for any randomly chosen initial data. Numerical experiments illustrate the effectiveness and efficiency of the algorithm.
Development of new flux splitting schemes. [computational fluid dynamics algorithms
Liou, Meng-Sing; Steffen, Christopher J., Jr.
1992-01-01
Maximizing both accuracy and efficiency has been the primary objective in designing a numerical algorithm for computational fluid dynamics (CFD). This is especially important for solutions of complex three dimensional systems of Navier-Stokes equations which often include turbulence modeling and chemistry effects. Recently, upwind schemes have been well received for their capability in resolving discontinuities. With this in mind, presented are two new flux splitting techniques for upwind differencing. The first method is based on High-Order Polynomial Expansions (HOPE) of the mass flux vector. The second new flux splitting is based on the Advection Upwind Splitting Method (AUSM). The calculation of the hypersonic conical flow demonstrates the accuracy of the splitting in resolving the flow in the presence of strong gradients. A second series of tests involving the two dimensional inviscid flow over a NACA 0012 airfoil demonstrates the ability of the AUSM to resolve the shock discontinuity at transonic speed. A third case calculates a series of supersonic flows over a circular cylinder. Finally, the fourth case deals with tests of a two dimensional shock wave/boundary layer interaction.
Qi, Wei; Zhang, Chi; Fu, Guangtao; Zhou, Huicheng
2016-02-01
It is widely recognized that optimization algorithm parameters have significant impacts on algorithm performance, but quantifying the influence is very complex and difficult due to high computational demands and dynamic nature of search parameters. The overall aim of this paper is to develop a global sensitivity analysis based framework to dynamically quantify the individual and interactive influence of algorithm parameters on algorithm performance. A variance decomposition sensitivity analysis method, Analysis of Variance (ANOVA), is used for sensitivity quantification, because it is capable of handling small samples and more computationally efficient compared with other approaches. The Shuffled Complex Evolution method developed at the University of Arizona algorithm (SCE-UA) is selected as an optimization algorithm for investigation, and two criteria, i.e., convergence speed and success rate, are used to measure the performance of SCE-UA. Results show the proposed framework can effectively reveal the dynamic sensitivity of algorithm parameters in the search processes, including individual influences of parameters and their interactive impacts. Interactions between algorithm parameters have significant impacts on SCE-UA performance, which has not been reported in previous research. The proposed framework provides a means to understand the dynamics of algorithm parameter influence, and highlights the significance of considering interactive parameter influence to improve algorithm performance in the search processes.
Maintenance of Process Control Algorithms based on Dynamic Program Slicing
DEFF Research Database (Denmark)
Hansen, Ole Fink; Andersen, Nils Axel; Ravn, Ole
2010-01-01
Today’s industrial control systems gradually lose performance after installation and must be regularly maintained by means of adjusting parameters and modifying the control algorithm, in order to regain high performance. Industrial control algorithms are complex software systems, and it is partic......Today’s industrial control systems gradually lose performance after installation and must be regularly maintained by means of adjusting parameters and modifying the control algorithm, in order to regain high performance. Industrial control algorithms are complex software systems......, and it is particularly difficult to locate causes of performance loss, while readjusting the algorithm once the cause of performance loss is actually realized and found is relatively simple. In this paper we present a software-engineering approach to the maintenance problem, which provides tools for exploring...... the behavior of a control algorithm, enables maintenance personnel to focus on only relevant parts of the algorithm and semi-automatically locate the part of the algorithm that is responsible for the reduced performance. The solution is tuning-free and can be applied to installed and running systems without...
Community-based advocacy training: applying asset-based community development in resident education.
Hufford, Laura; West, Daniel C; Paterniti, Debora A; Pan, Richard J
2009-06-01
Communities and Physicians Together (CPT) at University of California, Davis Health System provides a novel approach to teaching residents to be effective community advocates. Founded in 1999, CPT is a partnership between a pediatric residency program, five community collaboratives located in diverse neighborhoods, and a grassroots child advocacy organization. Using the principles of Asset-Based Community Development, the program emphasizes establishing partnerships with community members and organizations to improve child health and identifies community assets and building capacity. Community members function as the primary faculty for CPT.The authors describe the CPT curriculum, which teaches residents to build partnerships with their assigned community. Residents have three, two-week blocks each year for CPT activities and maintain a longitudinal relationship with their community. In the first year, collaborative coordinators from each community orient residents to their community. Residents identify community assets and perform activities designed to provide them with a community member's perspective. In the second and third years, residents partner with community members and organizations to implement a project to improve the health of children in that community. CPT also provides faculty development to community partners including a workshop on medical culture and resident life. A qualitative evaluation demonstrated residents' attitudes of their role as pediatricians in the community changed with CPT.CPT is unique because it provides a model of service learning that emphasizes identifying and utilizing strengths and building capacity. This approach differs from the traditional medical model, which emphasizes deficits and needs. PMID:19474556
A HYBRID GRANULARITY PARALLEL ALGORITHM FOR PRECISE INTEGRATION OF STRUCTURAL DYNAMIC RESPONSES
Institute of Scientific and Technical Information of China (English)
Yuanyin Li; Xianlong Jin; Genguo Li
2008-01-01
Precise integration methods to solve structural dynamic responses and the corre-sponding time integration formula are composed of two parts: the multiplication of an exponential matrix with a vector and the integration term. The second term can be solved by the series solu-tion. Two hybrid granularity parallel algorithms are designed, that is, the exponential matrix and the first term are computed by the fine-grained parallel algorithm and the second term is com-puted by the coarse-grained parallel algorithm. Numerical examples show that these two hybrid granularity parallel algorithms obtain higher speedup and parallel efficiency than two existing parallel algorithms.
Recursive Dynamic Algorithm of Open-Chain Multibody System
Directory of Open Access Journals (Sweden)
Ming Lu
2014-01-01
Full Text Available Open-chain multibody systems have been extensively studied because of their widespread application. Based on the structural characteristics of such a system, the relationship between its hinged bodies was transformed into recursive constraint relationships among the position, velocity, and acceleration of the bodies. The recursive relationships were used along with the Huston-Kane method to select the appropriate generalized coordinates and determine the partial velocity of each body and to develop an algorithm of the entire system. The algorithm was experimentally validated; it has concise steps and low susceptibility to error. Further, the algorithm can readily solve and analyze open-chain multibody systems.
Directory of Open Access Journals (Sweden)
Zhihua Zhang
2016-01-01
Full Text Available Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO. Rechenberg’s 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter.
Zhang, Zhihua; Sheng, Zheng; Shi, Hanqing; Fan, Zhiqiang
2016-01-01
Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS) algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO). Rechenberg's 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter. PMID:27212938
Dynamic platform-independent meta-algorithms for graph-partitioning
Schwartz, Victor Scott
1998-01-01
Approved for public release, distribution is unlimited A dynamic platform-independent solver is developed for use with network and graph algorithms of operations research. This solver allows analysts to solve a large variety of problems without writing code. Algorithms from a library can be integrated into a meta-algorithm which also provides easy monitoring of solution progress. The solver, DORS, is demonstrated by heuristically solving a graph-partitioning problem to minimize the number ...
Institute of Scientific and Technical Information of China (English)
DU Mao-Kang; HE Bo; WANG Yong
2011-01-01
Recently, the cryptosystem based on chaos has attracted much attention. Wang and Yu (Commun. Nonlin. Sci. Numer. Simulat. 14(2009)574) proposed a block encryption algorithm based on dynamic sequences of multiple chaotic systems. We analyze the potential Saws in the algorithm. Then, a chosen-plaintext attack is presented. Some remedial measures are suggested to avoid the flaws effectively. Furthermore, an improved encryption algorithm is proposed to resist the attacks and to keep all the merits of the original cryptosystem.
NONLINEAR FILTER METHOD OF GPS DYNAMIC POSITIONING BASED ON BANCROFT ALGORITHM
Institute of Scientific and Technical Information of China (English)
ZHANGQin; TAOBen-zao; ZHAOChao-ying; WANGLi
2005-01-01
Because of the ignored items after linearization, the extended Kalman filter (EKF) becomes a form of suboptimal gradient descent algorithm. The emanative tendency exists in GPS solution when the filter equations are ill-posed. The deviation in the estimation cannot be avoided. Furthermore, the true solution may be lost in pseudorange positioning because the linearized pseudorange equations are partial solutions. To solve the above problems in GPS dynamic positioning by using EKF, a closed-form Kalman filter method called the two-stage algorithm is presented for the nonlinear algebraic solution of GPS dynamic positioning based on the global nonlinear least squares closed algorithm--Bancroft numerical algorithm of American. The method separates the spatial parts from temporal parts during processing the GPS filter problems, and solves the nonlinear GPS dynamic positioning, thus getting stable and reliable dynamic positioning solutions.
A Dynamic Traffic Signal Timing Model and its Algorithm for Junction of Urban Road
DEFF Research Database (Denmark)
Cai, Yanguang; Cai, Hao
2012-01-01
As an important part of Intelligent Transportation System, the scientific traffic signal timing of junction can improve the efficiency of urban transport. This paper presents a novel dynamic traffic signal timing model. According to the characteristics of the model, hybrid chaotic quantum...... evolutionary algorithm, genetic algorithms and particle swarm optimization....
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; Chen, Zhe
2015-01-01
Anew approach, Dynamic Minimal Spanning Tree (DMST) algorithm, whichisbased on the MST algorithm isproposed in this paper to optimizethe cable connectionlayout for large scale offshore wind farm collection system. The current carrying capacity of the cable is considered as the main constraint....... It is amore economicalway for cable connection configurationdesignof offshore wind farm collection system....
Dynamic route guidance algorithm based algorithm based on artificial immune system
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
To improve the performance of the K-shortest paths search in intelligent traffic guidance systems,this paper proposes an optimal search algorithm based on the intelligent optimization search theory and the memphor mechanism of vertebrate immune systems.This algorithm,applied to the urban traffic network model established by the node-expanding method,can expediently realize K-shortest paths search in the urban traffic guidance systems.Because of the immune memory and global parallel search ability from artificial immune systems,K shortest paths can be found without any repeat,which indicates evidently the superiority of the algorithm to the conventional ones.Not only does it perform a better parallelism,the algorithm also prevents premature phenomenon that often occurs in genetic algorithms.Thus,it is especially suitable for real-time requirement of the traffic guidance system and other engineering optimal applications.A case study verifies the efficiency and the practicability of the algorithm aforementioned.
Force-Based Incremental Algorithm for Mining Community Structure in Dynamic Network
Institute of Scientific and Technical Information of China (English)
Bo Yang; Da-You Liu
2006-01-01
Community structure is an important property of network. Being able to identify communities can provide invaluable help in exploiting and understanding both social and non-social networks. Several algorithms have been developed up till now. However, all these algorithms can work well only with small or moderate networks with vertexes of order 104.Besides, all the existing algorithms are off-line and cannot work well with highly dynamic networks such as web, in which web pages are updated frequently. When an already clustered network is updated, the entire network including original and incremental parts has to be recalculated, even though only slight changes are involved. To address this problem, an incremental algorithm is proposed, which allows for mining community structure in large-scale and dynamic networks. Based on the community structure detected previously, the algorithm takes little time to reclassify the entire network including both the original and incremental parts. Furthermore, the algorithm is faster than most of the existing algorithms such as Girvan and Newman's algorithm and its improved versions. Also, the algorithm can help to visualize these community structures in network and provide a new approach to research on the evolving process of dynamic networks.
Zhihua Zhang; Zheng Sheng; Hanqing Shi; Zhiqiang Fan
2016-01-01
Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS) algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO). Rechenberg’s 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossov...
Double Four-Bar Crank-Slider Mechanism Dynamic Balancing by Meta-Heuristic Algorithms
Habib Emdadi; Mahsa Yazdanian; Mir Mohammad Ettefagh; Mohammad-Reza Feizi-Derakhshi
2013-01-01
In this paper, a new method for dynamic balancing of double four-bar crank slider mechanism by meta- heuristic-based optimization algorithms is proposed. For this purpose, a proper objective function which is necessary for balancing of this mechanism and corresponding constraints has been obtained by dynamic modeling of the mechanism. Then PSO, ABC, BGA and HGAPSO algorithms have been applied for minimizing the defined cost function in optimization step. The optimization results have been stu...
Adaptive-mesh algorithms for computational fluid dynamics
Powell, Kenneth G.; Roe, Philip L.; Quirk, James
1993-01-01
The basic goal of adaptive-mesh algorithms is to distribute computational resources wisely by increasing the resolution of 'important' regions of the flow and decreasing the resolution of regions that are less important. While this goal is one that is worthwhile, implementing schemes that have this degree of sophistication remains more of an art than a science. In this paper, the basic pieces of adaptive-mesh algorithms are described and some of the possible ways to implement them are discussed and compared. These basic pieces are the data structure to be used, the generation of an initial mesh, the criterion to be used to adapt the mesh to the solution, and the flow-solver algorithm on the resulting mesh. Each of these is discussed, with particular emphasis on methods suitable for the computation of compressible flows.
Information dynamics algorithm for detecting communities in networks
Massaro, E; Bagnoli, F; Liò, P
2011-01-01
The problem of community detection is relevant in many scientific disciplines, from social science to statistical physics. Given the impact of community detection in many areas, such as psychology and social sciences, we have addressed the issue of modifying existing well performing algorithms by incorporating elements of the domain application fields, i.e. domain-inspired. We have focused on a psychology and social network - inspired approach which may be useful for further strengthening the link between social network studies and mathematics of community detection. Here we introduce a community-detection algorithm derived from the van Dongen's Markov Cluster algorithm (MCL) method by considering networks' nodes as agents capable to take decisions. In this framework we have introduced a memory factor to mimic a typical human behavior such as the oblivion effect. The method is based on information diffusion and it includes a non-linear processing phase. We test our method on two classical community benchmark ...
AN IMPLICIT SERIES PRECISE INTEGRATION ALGORITHM FOR STRUCTURAL NONLINEAR DYNAMIC EQUATIONS
Institute of Scientific and Technical Information of China (English)
Li Yuanyin; Jin Xianlong; Wang Yuanqing
2005-01-01
Nonlinear dynamic equations can be solved accurately using a precise integration method. Some algorithms exist, but the inversion of a matrix must be calculated for these algorithms. If the inversion of the matrix doesn't exist or isn't stable, the precision and stability of the algorithms will be affected. An explicit series solution of the state equation has been presented. The solution avoids calculating the inversion of a matrix and its precision can be easily controlled. In this paper, an implicit series solution of nonlinear dynamic equations is presented.The algorithm is more precise and stable than the explicit series solution and isn't sensitive to the time-step. Finally, a numerical example is presented to demonstrate the effectiveness of the algorithm.
DARAL: A Dynamic and Adaptive Routing Algorithm for Wireless Sensor Networks.
Estévez, Francisco José; Glösekötter, Peter; González, Jesús
2016-01-01
The evolution of Smart City projects is pushing researchers and companies to develop more efficient embedded hardware and also more efficient communication technologies. These communication technologies are the focus of this work, presenting a new routing algorithm based on dynamically-allocated sub-networks and node roles. Among these features, our algorithm presents a fast set-up time, a reduced overhead and a hierarchical organization, which allows for the application of complex management techniques. This work presents a routing algorithm based on a dynamically-allocated hierarchical clustering, which uses the link quality indicator as a reference parameter, maximizing the network coverage and minimizing the control message overhead and the convergence time. The present work based its test scenario and analysis in the density measure, considered as a node degree. The routing algorithm is compared with some of the most well known routing algorithms for different scenario densities. PMID:27347962
An Algorithm for the Stochastic Simulation of Gene Expression and Heterogeneous Population Dynamics
Charlebois, Daniel A; Fraser, Dawn; Kaern, Mads
2011-01-01
We present an algorithm for the stochastic simulation of gene expression and heterogeneous population dynamics. The algorithm combines an exact method to simulate molecular-level fluctuations in single cells and a constant-number Monte Carlo method to simulate time-dependent statistical characteristics of growing cell populations. To benchmark performance, we compare simulation results with steadystate and time-dependent analytical solutions for several scenarios, including steadystate and time-dependent gene expression, and the effects on population heterogeneity of cell growth, division, and DNA replication. This comparison demonstrates that the algorithm provides an efficient and accurate approach to simulate how complex biological features influence gene expression. We also use the algorithm to model gene expression dynamics within "bet-hedging" cell populations during their adaption to environmental stress. These simulations indicate that the algorithm provides a framework suitable for simulating and ana...
DARAL: A Dynamic and Adaptive Routing Algorithm for Wireless Sensor Networks
Estévez, Francisco José; Glösekötter, Peter; González, Jesús
2016-01-01
The evolution of Smart City projects is pushing researchers and companies to develop more efficient embedded hardware and also more efficient communication technologies. These communication technologies are the focus of this work, presenting a new routing algorithm based on dynamically-allocated sub-networks and node roles. Among these features, our algorithm presents a fast set-up time, a reduced overhead and a hierarchical organization, which allows for the application of complex management techniques. This work presents a routing algorithm based on a dynamically-allocated hierarchical clustering, which uses the link quality indicator as a reference parameter, maximizing the network coverage and minimizing the control message overhead and the convergence time. The present work based its test scenario and analysis in the density measure, considered as a node degree. The routing algorithm is compared with some of the most well known routing algorithms for different scenario densities. PMID:27347962
Optimization in Quaternion Dynamic Systems: Gradient, Hessian, and Learning Algorithms.
Xu, Dongpo; Xia, Yili; Mandic, Danilo P
2016-02-01
The optimization of real scalar functions of quaternion variables, such as the mean square error or array output power, underpins many practical applications. Solutions typically require the calculation of the gradient and Hessian. However, real functions of quaternion variables are essentially nonanalytic, which are prohibitive to the development of quaternion-valued learning systems. To address this issue, we propose new definitions of quaternion gradient and Hessian, based on the novel generalized Hamilton-real (GHR) calculus, thus making a possible efficient derivation of general optimization algorithms directly in the quaternion field, rather than using the isomorphism with the real domain, as is current practice. In addition, unlike the existing quaternion gradients, the GHR calculus allows for the product and chain rule, and for a one-to-one correspondence of the novel quaternion gradient and Hessian with their real counterparts. Properties of the quaternion gradient and Hessian relevant to numerical applications are also introduced, opening a new avenue of research in quaternion optimization and greatly simplified the derivations of learning algorithms. The proposed GHR calculus is shown to yield the same generic algorithm forms as the corresponding real- and complex-valued algorithms. Advantages of the proposed framework are illuminated over illustrative simulations in quaternion signal processing and neural networks. PMID:26087504
Dynamic gate algorithm for multimode fiber Bragg grating sensor systems
DEFF Research Database (Denmark)
Ganziy, Denis; Jespersen, O.; Woyessa, Getinet;
2015-01-01
-to-noise ratio and different peak shapes. Our simulations and experiments demonstrate that the DGA method is fast and robust with better stability and accuracy than conventional algorithms. This makes it very attractive for future implementation in sensing systems, especially based on multimode fiber Bragg...
PACE: A dynamic programming algorithm for hardware/software partitioning
DEFF Research Database (Denmark)
Knudsen, Peter Voigt; Madsen, Jan
1996-01-01
with a hardware area constraint and the problem of minimizing hardware area with a system execution time constraint. The target architecture consists of a single microprocessor and a single hardware chip (ASIC, FPGA, etc.) which are connected by a communication channel. The algorithm incorporates a realistic...
Optimization in Quaternion Dynamic Systems: Gradient, Hessian, and Learning Algorithms.
Xu, Dongpo; Xia, Yili; Mandic, Danilo P
2016-02-01
The optimization of real scalar functions of quaternion variables, such as the mean square error or array output power, underpins many practical applications. Solutions typically require the calculation of the gradient and Hessian. However, real functions of quaternion variables are essentially nonanalytic, which are prohibitive to the development of quaternion-valued learning systems. To address this issue, we propose new definitions of quaternion gradient and Hessian, based on the novel generalized Hamilton-real (GHR) calculus, thus making a possible efficient derivation of general optimization algorithms directly in the quaternion field, rather than using the isomorphism with the real domain, as is current practice. In addition, unlike the existing quaternion gradients, the GHR calculus allows for the product and chain rule, and for a one-to-one correspondence of the novel quaternion gradient and Hessian with their real counterparts. Properties of the quaternion gradient and Hessian relevant to numerical applications are also introduced, opening a new avenue of research in quaternion optimization and greatly simplified the derivations of learning algorithms. The proposed GHR calculus is shown to yield the same generic algorithm forms as the corresponding real- and complex-valued algorithms. Advantages of the proposed framework are illuminated over illustrative simulations in quaternion signal processing and neural networks.
EVOLUTIONARY NEURAL NETWORKS ALGORITHM FOR THE DYNAMIC FREQUENCY ASSIGNMENT PROBLEM
Directory of Open Access Journals (Sweden)
Jamal Elhachmi
2011-06-01
Full Text Available Wireless communication is used in many different situations such as mobile telephony, radio and TV broadcasting, satellite communication, wireless LANs, and military operations. In each of these situations a frequency assignment problem arises with application-specific characteristics. Researchers have developed different modelling ideas for each of the features of the problem, such as the handling of interference among radio signals, the availability of frequencies, and the optimization criterion. This paper presents a new approach for solving the problem of frequency allocation based on using initially a partial solution respecting all constraints according to a greedy algorithm. This partial solution is then used for the construction of our stimulation in the form of a neural network. In a second step, the approach will use searching techniques used in conjunction with iterative algorithms for theoptimization of the parameters and topology of the network. The iterative algorithms used are named hierarchical genetic algorithms (HGA. Our approach has been tested on standard benchmark problems called Philadelphia problems of frequency assignment. The results obtained are equivalent to those of current methods. Moreover, our approach shows more efficiency in terms of flexibility and autonomy.
Probabilistic dynamic deployment of wireless sensor networks by artificial bee colony algorithm.
Ozturk, Celal; Karaboga, Dervis; Gorkemli, Beyza
2011-01-01
As the usage and development of wireless sensor networks are increasing, the problems related to these networks are being realized. Dynamic deployment is one of the main topics that directly affect the performance of the wireless sensor networks. In this paper, the artificial bee colony algorithm is applied to the dynamic deployment of stationary and mobile sensor networks to achieve better performance by trying to increase the coverage area of the network. A probabilistic detection model is considered to obtain more realistic results while computing the effectively covered area. Performance of the algorithm is compared with that of the particle swarm optimization algorithm, which is also a swarm based optimization technique and formerly used in wireless sensor network deployment. Results show artificial bee colony algorithm can be preferable in the dynamic deployment of wireless sensor networks. PMID:22163942
Institute of Scientific and Technical Information of China (English)
Liu Jie; Shi Shu-Ting; Zhao Jun-Chan
2013-01-01
The three most widely used methods for reconstructing the underlying time series via the recurrence plots (RPs) of a dynamical system are compared with each other in this paper.We aim to reconstruct a toy series,a periodical series,a random series,and a chaotic series to compare the effectiveness of the most widely used typical methods in terms of signal correlation analysis.The application of the most effective algorithm to the typical chaotic Lorenz system verifies the correctness of such an effective algorithm.It is verified that,based on the unthresholded RPs,one can reconstruct the original attractor by choosing different RP thresholds based on the Hirata algorithm.It is shown that,in real applications,it is possible to reconstruct the underlying dynamics by using quite little information from observations of real dynamical systems.Moreover,rules of the threshold chosen in the algorithm are also suggested.
Multi-constraint quality of service routing algorithm for dynamic topology networks
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
An adaptive multi-QoS routing algorithm called AMQRA is proposed for dynamic topology networks,such as satellite networks and Ad-hoc networks.The AMQRA is a distributed and mobile-agents-based routing algorithm,which combines ant quantity system (AQS) with ant colony optimization (ACO) that is used in AntNet routing algorithm.In dynamic topology networks,the AMQRA achieves timely optimization for concave metric QoS constraint and fast convergence.The proposed routing algorithm is simulated in Iridium satellite constellation on OPNET.The results show that AMQRA not only outperforms the AntNet in convergence rate in dynamic topology networks but also can optimize concave metric QoS constraint and reasonably allot bandwidth to the load to avoid networks congestion.
Dynamic Deployment of Wireless Sensor Networks by Biogeography Based Optimization Algorithm
Directory of Open Access Journals (Sweden)
Luo Liu
2012-06-01
Full Text Available As the usage and development of wireless sensor networks increases, problems related to these networks are becoming apparent. Dynamic deployment is one of the main topics that directly affects the performance of the wireless sensor networks. In this paper, biogeography-based optimization is applied to the dynamic deployment of static and mobile sensor networks to achieve better performance by trying to increase the coverage area of the network. A binary detection model is considered to obtain realistic results while computing the effectively covered area. Performance of the algorithm is compared with that of the artificial bee colony algorithm, Homo-H-VFCPSO and stud genetic algorithm that are also population-based optimization algorithms. Results show biogeography-based optimization can be preferable in the dynamic deployment of wireless sensor networks.
Directory of Open Access Journals (Sweden)
Orly Yadid-Pecht
2013-10-01
Full Text Available Tone mapping algorithms are used to adapt captured wide dynamic range (WDR scenes to the limited dynamic range of available display devices. Although there are several tone mapping algorithms available, most of them require manual tuning of their rendering parameters. In addition, the high complexities of some of these algorithms make it difficult to implement efficient real-time hardware systems. In this work, a real-time hardware implementation of an exponent-based tone mapping algorithm is presented. The algorithm performs a mixture of both global and local compression on colored WDR images. An automatic parameter selector has been proposed for the tone mapping algorithm in order to achieve good tone-mapped images without manual reconfiguration of the algorithm for each WDR image. Both algorithms are described in Verilog and synthesized for a field programmable gate array (FPGA. The hardware architecture employs a combination of parallelism and system pipelining, so as to achieve a high performance in power consumption, hardware resources usage and processing speed. Results show that the hardware architecture produces images of good visual quality that can be compared to software-based tone mapping algorithms. High peak signal-to-noise ratio (PSNR and structural similarity (SSIM scores were obtained when the results were compared with output images obtained from software simulations using MATLAB.
Resource Matchmaking Algorithm using Dynamic Rough Set in Grid Environment
Ataollahi, Iraj
2009-01-01
Grid environment is a service oriented infrastructure in which many heterogeneous resources participate to provide the high performance computation. One of the bug issues in the grid environment is the vagueness and uncertainty between advertised resources and requested resources. Furthermore, in an environment such as grid dynamicity is considered as a crucial issue which must be dealt with. Classical rough set have been used to deal with the uncertainty and vagueness. But it can just be used on the static systems and can not support dynamicity in a system. In this work we propose a solution, called Dynamic Rough Set Resource Discovery (DRSRD), for dealing with cases of vagueness and uncertainty problems based on Dynamic rough set theory which considers dynamic features in this environment. In this way, requested resource properties have a weight as priority according to which resource matchmaking and ranking process is done. We also report the result of the solution obtained from the simulation in GridSim s...
Performance analysis of dynamic load balancing algorithm for multiprocessor interconnection network
Directory of Open Access Journals (Sweden)
M.U. Bokhari
2016-09-01
Full Text Available Multiprocessor interconnection network have become powerful parallel computing system for real-time applications. Nowadays the many researchers posses studies on the dynamic load balancing in multiprocessor system. Load balancing is the method of dividing the total load among the processors of the distributed system to progress task's response time as well as resource utilization whereas ignoring a condition where few processors are overloaded or underloaded or moderately loaded. However, in dynamic load balancing algorithm presumes no priori information about behaviour of tasks or the global state of the system. There are numerous issues while designing an efficient dynamic load balancing algorithm that involves utilization of system, amount of information transferred among processors, selection of tasks for migration, load evaluation, comparison of load levels and many more. This paper enlightens the performance analysis on dynamic load balancing strategy (DLBS algorithm, used for hypercube network in multiprocessor system.
Advanced Dynamically Adaptive Algorithms for Stochastic Simulations on Extreme Scales
Energy Technology Data Exchange (ETDEWEB)
Xiu, Dongbin [Purdue Univ., West Lafayette, IN (United States)
2016-06-21
The focus of the project is the development of mathematical methods and high-performance com- putational tools for stochastic simulations, with a particular emphasis on computations on extreme scales. The core of the project revolves around the design of highly e cient and scalable numer- ical algorithms that can adaptively and accurately, in high dimensional spaces, resolve stochastic problems with limited smoothness, even containing discontinuities.
A local flocking algorithm of multi-agent dynamic systems
Pei, Huiqin; Chen, Shiming; Lai, Qiang
2015-11-01
In this paper, the local flocking of multi-agent systems is investigated, which means all agents form some groups of surrounding multiple targets with the partial information exchange. For the purpose of realising local multi-flocking, a control algorithm of local flocking is proposed, which is a biologically inspired approach that assimilates key characteristics of flocking and anti-flocking. In the process of surrounding mobile targets through the control algorithm, all agents can adaptively choose between two work modes to depend on the variation of visual field and the number of pursuing agents with the mobile target. One is a flocking pursuing mode which is that some agents pursue each mobile target, the other is an anti-flocking searching mode that means with the exception of the pursing agents of mobile targets, other agents respectively hunt for optimal the mobile target with a closest principle between the agent and the target. In two work modes, the agents are controlled severally via the different control protocol. By the Lyapunov theorem, the stability of the second-order multi-agent system is proven in detail. Finally, simulation results verify the effectiveness of the proposed algorithm.
Indian Academy of Sciences (India)
A Rama Mohan Rao; T V S R Appa Rao; B Dattaguru
2004-02-01
The work reported in this paper is motivated by the need to develop portable parallel processing algorithms and codes which can run on a variety of hardware platforms without any modiﬁcations. The prime aim of the research work reported here is to test the portability of the parallel algorithms and also to study and understand the comparative efﬁciencies of three parallel algorithms developed for implicit time integration technique. The standard message passing interface (MPI) is used to develop parallel algorithms for computing nonlinear dynamic response of large structures employing implicit time-marching scheme. The parallel algorithms presented in this paper are developed under the broad framework of non-overlapped domain decomposition technique. Numerical studies indicate that the parallel algorithm devised employing the conventional form of Newmark time integration algorithm is faster than the predictor–corrector form. It is also accurate and highly adaptive to ﬁne grain computations. The group implicit algorithm is found to be extremely superior in performance when compared to the other two parallel algorithms. This algorithm is better suited for large size problems on coarse grain environment as the resulting submeshes will obviously be large and thus permit larger time steps without losing accuracy.
Stable algorithm for event detection in event-driven particle dynamics
Bannerman, Marcus N.; Strobl, Severin; Formella, Arno; Poeschel, Thorsten
2012-01-01
Event-Driven Particle Dynamics is a fast and precise method to simulate particulate systems of all scales. In this work it is demonstrated that, despite the high accuracy of the method, the finite machine precision leads to simulations entering invalid states where the dynamics are undefined. A general event-detection algorithm is proposed which handles these situations in a stable and efficient manner. This requires a definition of the dynamics of invalid states and leads to improved algorit...
Dynamic Communication Performance Enhancement in Hierarchical Torus Network by Selection Algorithm
Directory of Open Access Journals (Sweden)
MM Hafizur Rahman
2012-03-01
Full Text Available A Hierarchical Torus Network (HTN is a 2D-torus network of multiple basic modules, in which the basic modules are 3D-torus networks that are hierarchically interconnected for higher-level networks. The static network performance of the HTN and its dynamic communication performance using the deterministic, dimension-order routing algorithm have already been evaluated and shown to be superior to the performance of other conventional and hierarchical interconnection networks. However, the assessment of the dynamic communication performance improvement of HTN by the efficient use of both the physical link and virtual channels has not yet been evaluated. This paper addresses three adaptive routing algorithms -- link-selection, channel-selection, and a combination of link-selection and channel-selection -- for the efficient use of physical links and virtual channels of an HTN to enhance dynamic communication performance. It also proves that the proposed adaptive routing algorithms are deadlock-free with 3 virtual channels. The dynamic communication performances of an HTN is evaluated by using dimension-order routing and proposed adaptive routing algorithms under various traffic patterns. It is found that the dynamic communication performance of an HTN using these adaptive routing algorithms are better than when the dimension-order routing is used, in terms of network throughput.
Evolutionary decision-makings for the dynamic weapon-target assignment problem
Institute of Scientific and Technical Information of China (English)
CHEN Jie; XIN Bin; PENG ZhiHong; DOU LiHua; ZHANG Juan
2009-01-01
The dynamic weapon-target assignment (DWTA) problem is an important issue In the field of military command and control.An asset-based DWTA optimization model was proposed with four kinds of constraints considered,including capability constraints,strategy constraints,resource constraints and engagement feasibility constraints.A general "virtual"representation of decisions was presented to facilitate the generation of feasible decisions.The representation is in essence the permutation of all assignment pairs.A construction procedure converts the permutations into real feasible decisions.In order to solve this problem,three evolutionary decision-making algorithms,Including a genetic algorithm and two memeitc algorithms,were developed.Experimental results show that the memetic algorithm based on greedy local search can generate obviously better DWTA decisions,especially for large-scale problems,than the genetic algorithm and the memetic algorithm based on steepest local search.
Detectability thresholds and optimal algorithms for community structure in dynamic networks
Ghasemian, Amir; Clauset, Aaron; Moore, Cristopher; Peel, Leto
2015-01-01
We study the fundamental limits on learning latent community structure in dynamic networks. Specifically, we study dynamic stochastic block models where nodes change their community membership over time, but where edges are generated independently at each time step. In this setting (which is a special case of several existing models), we are able to derive the detectability threshold exactly, as a function of the rate of change and the strength of the communities. Below this threshold, we claim that no algorithm can identify the communities better than chance. We then give two algorithms that are optimal in the sense that they succeed all the way down to this limit. The first uses belief propagation (BP), which gives asymptotically optimal accuracy, and the second is a fast spectral clustering algorithm, based on linearizing the BP equations. We verify our analytic and algorithmic results via numerical simulation, and close with a brief discussion of extensions and open questions.
A New Multiobjective Evolutionary Algorithm for Community Detection in Dynamic Complex Networks
Directory of Open Access Journals (Sweden)
Guoqiang Chen
2013-01-01
Full Text Available Community detection in dynamic networks is an important research topic and has received an enormous amount of attention in recent years. Modularity is selected as a measure to quantify the quality of the community partition in previous detection methods. But, the modularity has been exposed to resolution limits. In this paper, we propose a novel multiobjective evolutionary algorithm for dynamic networks community detection based on the framework of nondominated sorting genetic algorithm. Modularity density which can address the limitations of modularity function is adopted to measure the snapshot cost, and normalized mutual information is selected to measure temporal cost, respectively. The characteristics knowledge of the problem is used in designing the genetic operators. Furthermore, a local search operator was designed, which can improve the effectiveness and efficiency of community detection. Experimental studies based on synthetic datasets show that the proposed algorithm can obtain better performance than the compared algorithms.
An FDTD algorithm for simulating light propagation in anisotropic dynamic gain media
Al-Jabr, A. A.
2014-05-02
Simulating light propagation in anisotropic dynamic gain media such as semiconductors and solid-state lasers using the finite difference time-domain FDTD technique is a tedious process, as many variables need to be evaluated in the same instant of time. The algorithm has to take care of the laser dynamic gain, rate equations, anisotropy and dispersion. In this paper, to the best of our knowledge, we present the first algorithm that solves this problem. The algorithm is based on separating calculations into independent layers and hence solving each problem in a layer of calculations. The anisotropic gain medium is presented and tested using a one-dimensional set-up. The algorithm is then used for the analysis of a two-dimensional problem.
A new simulation algorithm for lattice QCD with dynamical quarks
Bunk, B.; Jansen, K.; Jegerlehner, B.; Lüscher, M.; Simma, H.; Sommer, R
1994-01-01
A previously introduced multi-boson technique for the simulation of QCD with dynamical quarks is described and some results of first test runs on a $6^3\\times12$ lattice with Wilson quarks and gauge group SU(2) are reported.
Evaluation of dynamic bandwidth allocation algorithms in GPON networks
DEFF Research Database (Denmark)
Ozimkiewicz, J.; Ruepp, Sarah Renée; Dittmann, Lars;
2010-01-01
In this paper, two approaches for Dynamic Bandwidth Allocation in GPON networks are proposed, and validated through simulations in the OPNET modeler. One approach address a Status Reporting scheme, where the bandwidth allocation originates from the client request. The second use a centralized Non...... services....
Capacitated Dynamic Facility Location Problem Based on Tabu Search Algorithm
Institute of Scientific and Technical Information of China (English)
KUANG Yi-jun; ZHU Ke-jun
2007-01-01
Facility location problem is a kind of NP-Hard combinational problem. Considering ever-changing demand sites, demand quantity and releasing cost, we formulate a model combining tabu search and FCM (fuzzy clustering method) to solve the eapacitated dynamic facility location problem. Some results are achieved and they show that the proposed method is effective.
A genetic algorithm for dynamic parameters reverse deduction of integrated anchorage system
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
In the analysis of the system of anchoring bar and wall rock in small strain and longitudinal vibration dynamic response, the influence of the cement grouting as well as the rock layer on the anchor bar can be evaluated as the two kinds of parameters: the dynamic stiffness and the damp, which are the vital reference of the anchorage quality. Based on the analytic solution to the dynamic equation of the integrated anchor bar, the new approach which combines genetic algorithm and the toolbox of Matlab is applied to solve the problem of multi-parameters reverse deduction for integrated anchorage system in dynamic testing. Using the traits of the self-organizing, self-adapting and the fast convergence speed of the genetic algorithm, the optimum of all possible solutions to dynamic parameters is obtained by calculating the project instances. Examples show that the method presented in this paper is effective and reliable.
A functional clustering algorithm for the analysis of dynamic network data
Feldt, S.; Waddell, J; Hetrick, V. L.; Berke, J. D.; Zochowski, M.
2008-01-01
We formulate a novel technique for the detection of functional clusters in discrete event data. The advantage of this algorithm is that no prior knowledge of the number of functional groups is needed, as our procedure progressively combines data traces and derives the optimal clustering cutoff in a simple and intuitive manner through the use of surrogate data sets. In order to demonstrate the power of this algorithm to detect changes in network dynamics and connectivity, we apply it to both s...
A Dynamic Programming Algorithm on Project-Gang Investment Decision-Making
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The investment decision-making of Project-Gang, the projects that are associated with one another on economy and technique, is studied. In order to find out the best Scheme that can make the maximum profit, a dynamic programming algorithm on the investment decision-making of Project-Gang is brought forward, and this algorithm can find out the best Scheme of distributing the m resources to the n Items in the time of O(m2n).
A dynamic programming algorithm for the space allocation and aisle positioning problem
Peter Bodnar; Jens Lysgaard
2014-01-01
The space allocation and aisle positioning problem (SAAPP) in a material handling system with gravity flow racks is the problem of minimizing the total number of replenishments over a period subject to practical constraints related to the need for aisles granting safe and easy access to storage locations. In this paper, we develop an exact dynamic programming algorithm for the SAAPP. The computational study shows that our exact algorithm can be used to find optimal solutions for numerous SAAP...
Wu, Xia; Wu, Genhua
2014-08-01
Geometrical optimization of atomic clusters is performed by a development of adaptive immune optimization algorithm (AIOA) with dynamic lattice searching (DLS) operation (AIOA-DLS method). By a cycle of construction and searching of the dynamic lattice (DL), DLS algorithm rapidly makes the clusters more regular and greatly reduces the potential energy. DLS can thus be used as an operation acting on the new individuals after mutation operation in AIOA to improve the performance of the AIOA. The AIOA-DLS method combines the merit of evolutionary algorithm and idea of dynamic lattice. The performance of the proposed method is investigated in the optimization of Lennard-Jones clusters within 250 atoms and silver clusters described by many-body Gupta potential within 150 atoms. Results reported in the literature are reproduced, and the motif of Ag61 cluster is found to be stacking-fault face-centered cubic, whose energy is lower than that of previously obtained icosahedron.
Fault Tolerant Algorithm Based on Dynamic and Active Load Balancing for Redundant Services
Institute of Scientific and Technical Information of China (English)
Jun-Feng Tian; Jun-Wei Zhang; Feng-Xian Wang
2004-01-01
A new Some-Read-Any-Write (SRAW) fault tolerant algorithm for redundant services is presented that allows a system to adjust failures dynamically in order to keep the availability and improve the performance. SRAW is based upon dynamic and active load balancing. By introducing dynamic and active load balancing scheme into redundant services, not only the processing speed of requests can be greatly improved, but also the load balancing can be simply and efficiently achieved. Integrated with consistency protocol in this paper, SRAW can also be applied to state services. The performance of SRAW algorithm is also analyzed, and comparisons with other fault tolerant algorithms, especially with RAWA, indicate that SRAW efficiently improves the performance of redundant services with guaranteeing system availability.
Energy Technology Data Exchange (ETDEWEB)
Trudnowski, Daniel J.; Pierre, John W.; Zhou, Ning; Hauer, John F.; Parashar, Manu
2008-05-31
The frequency and damping of electromechanical modes offer considerable insight into the dynamic stability properties of a power system. The performance properties of three block-processing algorithms from the perspective of near real-time automated stability assessment are demonstrated and examined. The algorithms are: the extended modified Yule Walker (YW); extended modified Yule Walker with Spectral analysis (YWS); and numerical state-space subspace system identification(N4SID) algorithm. The YW and N4SID have been introduced in previous publications while the YWS is introduced here. Issues addressed include: stability assessment requirements; automated subset selecting identified modes; using algorithms in an automated format; data assumptions and quality; and expected algorithm estimation performance.
A Dynamic Multistage Hybrid Swarm Intelligence Optimization Algorithm for Function Optimization
Directory of Open Access Journals (Sweden)
Daqing Wu
2012-01-01
Full Text Available A novel dynamic multistage hybrid swarm intelligence optimization algorithm is introduced, which is abbreviated as DM-PSO-ABC. The DM-PSO-ABC combined the exploration capabilities of the dynamic multiswarm particle swarm optimizer (PSO and the stochastic exploitation of the cooperative artificial bee colony algorithm (CABC for solving the function optimization. In the proposed hybrid algorithm, the whole process is divided into three stages. In the first stage, a dynamic multiswarm PSO is constructed to maintain the population diversity. In the second stage, the parallel, positive feedback of CABC was implemented in each small swarm. In the third stage, we make use of the particle swarm optimization global model, which has a faster convergence speed to enhance the global convergence in solving the whole problem. To verify the effectiveness and efficiency of the proposed hybrid algorithm, various scale benchmark problems are tested to demonstrate the potential of the proposed multistage hybrid swarm intelligence optimization algorithm. The results show that DM-PSO-ABC is better in the search precision, and convergence property and has strong ability to escape from the local suboptima when compared with several other peer algorithms.
A study on the dynamic tie points ASI algorithm in the Arctic Ocean
Institute of Scientific and Technical Information of China (English)
HAO Guanghua; SU Jie
2015-01-01
Sea ice concentration is an important parameter for polar sea ice monitoring. Based on 89 GHz AMSR-E (Advanced Microwave Scanning Radiometer for Earth Observing System) data, a gridded high-resolution passive microwave sea ice concentration product can be obtained using the ASI (the Arctic Radiation And Turbulence Interaction Study (ARTIST) Sea Ice) retrieval algorithm. Instead of using fixed-point values, we developed ASI algorithm based on daily changed tie points, called as the dynamic tie point ASI algorithm in this study. Here the tie points are expressed as the brightness temperature polarization difference of open water and 100% sea ice. In 2010, the yearly-averaged tie points of open water and sea ice in Arctic are estimated to be 50.8 K and 7.8 K, respectively. It is confirmed that the sea ice concentrations retrieved by the dynamic tie point ASI algorithm can increase (decrease) the sea ice concentrations in low-value (high-value) areas. This improved the sea ice concentrations by present retrieval algorithm from microwave data to some extent. Comparing with the products using fixed tie points, the sea ice concentrations retrieved from AMSR-E data by using the dynamic tie point ASI algorithm are closer to those obtained from MODIS (Moderate-resolution Imaging Spectroradiometer) data. In 40 selected cloud-free sample regions, 95% of our results have smaller mean differences and 75% of our results have lower root mean square (RMS) differences compare with those by the fixed tie points.
A Novel Dynamic Bandwidth Assignment Algorithm for Multi-Services EPONs
Institute of Scientific and Technical Information of China (English)
CHEN Xue; ZHANG Yang; HUANG Xiang; DENG Yu; SUN Shu-he
2005-01-01
In this paper we propose a novel Dynamic Bandwidth Assignment (DBA) algorithm for Ethernet-based Passive Optical Networks (EPON) which offers multiple kinds of services. To satisfy crucial Quality of Service (QoS) requirement for Time Division Multiplexing (TDM) service and achieve fair and high bandwidth utilization simultaneously, the algorithm integrates periodic, for TDM service, and polling granting for Ethernet service. Detailed simulation shows that the algorithm guarantees carrier-grade QoS for TDM service, high bandwidth utilization and good fairness of bandwidth assignment among Optical Network Units (ONU).
Institute of Scientific and Technical Information of China (English)
鄢田云; 张翠芳; 靳蕃
2003-01-01
Identification simulation for dynamical system which is based on genetic algorithm (GA) and recurrent multilayer neural network (RMNN) is presented. In order to reduce the inputs of the model, RMNN which can remember and store some previous parameters is used for identifier. And for its high efficiency and optimization, genetic algorithm is introduced into training RMNN. Simulation results show the effectiveness of the proposed scheme. Under the same training algorithm, the identification performance of RMNN is superior to that of nonrecurrent multilayer neural network (NRMNN).
Fuzzy Dynamic Discrimination Algorithms for Distributed Knowledge Management Systems
Directory of Open Access Journals (Sweden)
Vasile MAZILESCU
2010-12-01
Full Text Available A reduction of the algorithmic complexity of the fuzzy inference engine has the following property: the inputs (the fuzzy rules and the fuzzy facts can be divided in two parts, one being relatively constant for a long a time (the fuzzy rule or the knowledge model when it is compared to the second part (the fuzzy facts for every inference cycle. The occurrence of certain transformations over the constant part makes sense, in order to decrease the solution procurement time, in the case that the second part varies, but it is known at certain moments in time. The transformations attained in advance are called pre-processing or knowledge compilation. The use of variables in a Business Rule Management System knowledge representation allows factorising knowledge, like in classical knowledge based systems. The language of the first-degree predicates facilitates the formulation of complex knowledge in a rigorous way, imposing appropriate reasoning techniques. It is, thus, necessary to define the description method of fuzzy knowledge, to justify the knowledge exploiting efficiency when the compiling technique is used, to present the inference engine and highlight the functional features of the pattern matching and the state space processes. This paper presents the main results of our project PR356 for designing a compiler for fuzzy knowledge, like Rete compiler, that comprises two main components: a static fuzzy discrimination structure (Fuzzy Unification Tree and the Fuzzy Variables Linking Network. There are also presented the features of the elementary pattern matching process that is based on the compiled structure of fuzzy knowledge. We developed fuzzy discrimination algorithms for Distributed Knowledge Management Systems (DKMSs. The implementations have been elaborated in a prototype system FRCOM (Fuzzy Rule COMpiler.
Adaptive Dynamic Programming for Control Algorithms and Stability
Zhang, Huaguang; Luo, Yanhong; Wang, Ding
2013-01-01
There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming for Control approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-...
Quantum phase estimation algorithms with delays: effects of dynamical phases
Wei, L. F.; Nori, Franco
2003-01-01
The unavoidable finite time intervals between the sequential operations needed for performing practical quantum computing can degrade the performance of quantum computers. During these delays, unwanted relative dynamical phases are produced due to the free evolution of the superposition wave-function of the qubits. In general, these coherent "errors" modify the desired quantum interferences and thus spoil the correct results, compared to the ideal standard quantum computing that does not cons...
A Dynamic Programming Algorithm for the k-Haplotyping Problem
Institute of Scientific and Technical Information of China (English)
Zhen-ping Li; Ling-yun Wu; Yu-ying Zhao; Xiang-sun Zhang
2006-01-01
The Minimum Fragments Removal (MFR) problem is one of the haplotyping problems: given a set of fragments, remove the minimum number of fragments so that the resulting fragments can be partitioned into k classes of non-conflicting subsets. In this paper, we formulate the k-MFR problem as an integer linear programming problem, and develop a dynamic programming approach to solve the k-MFR problem for both the gapless and gap cases.
The generation algorithm of arbitrary polygon animation based on dynamic correction
Directory of Open Access Journals (Sweden)
Hou Ya Wei
2016-01-01
Full Text Available This paper, based on the key-frame polygon sequence, proposes a method that makes use of dynamic correction to develop continuous animation. Firstly we use quadratic Bezier curve to interpolate the corresponding sides vector of polygon sequence consecutive frame and realize the continuity of animation sequences. And then, according to Bezier curve characteristic, we conduct dynamic regulation to interpolation parameters and implement the changing smoothness. Meanwhile, we take use of Lagrange Multiplier Method to correct the polygon and close it. Finally, we provide the concrete algorithm flow and present numerical experiment results. The experiment results show that the algorithm acquires excellent effect.
An elementary singularity-free Rotational Brownian Dynamics algorithm for anisotropic particles
Energy Technology Data Exchange (ETDEWEB)
Ilie, Ioana M.; Briels, Wim J. [Computational Biophysics, Faculty of Science and Technology, University of Twente, P.O. Box 217, 7500 AE Enschede (Netherlands); MESA+ Institute for Nanotechnology, University of Twente, P.O. Box 217, 7500 AE Enschede (Netherlands); Otter, Wouter K. den, E-mail: w.k.denotter@utwente.nl [Computational Biophysics, Faculty of Science and Technology, University of Twente, P.O. Box 217, 7500 AE Enschede (Netherlands); MESA+ Institute for Nanotechnology, University of Twente, P.O. Box 217, 7500 AE Enschede (Netherlands); Multi Scale Mechanics, Faculty of Engineering Technology, University of Twente, P.O. Box 217, 7500 AE Enschede (Netherlands)
2015-03-21
Brownian Dynamics is the designated technique to simulate the collective dynamics of colloidal particles suspended in a solution, e.g., the self-assembly of patchy particles. Simulating the rotational dynamics of anisotropic particles by a first-order Langevin equation, however, gives rise to a number of complications, ranging from singularities when using a set of three rotational coordinates to subtle metric and drift corrections. Here, we derive and numerically validate a quaternion-based Rotational Brownian Dynamics algorithm that handles these complications in a simple and elegant way. The extension to hydrodynamic interactions is also discussed.
A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path.
Xie, Zhiqiang; Shao, Xia; Xin, Yu
2016-01-01
To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective.
A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path.
Xie, Zhiqiang; Shao, Xia; Xin, Yu
2016-01-01
To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective. PMID:27490901
A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path
Xie, Zhiqiang; Shao, Xia; Xin, Yu
2016-01-01
To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective. PMID:27490901
A structural dynamic factor model for the effects of monetary policy estimated by the EM algorithm
DEFF Research Database (Denmark)
Bork, Lasse
This paper applies the maximum likelihood based EM algorithm to a large-dimensional factor analysis of US monetary policy. Specifically, economy-wide effects of shocks to the US federal funds rate are estimated in a structural dynamic factor model in which 100+ US macroeconomic and financial time...... factor loadings, which is important for the response heterogeneity. Thirdly, the monetary policy rate is not a latent factor representation but measured without error and interacts dynamically with the factors in the estimation. Finally, the dynamic factor model is estimated by the one-step maximum...... likelihood based EM algorithm as an alternative to Bayesian methods and two-step principal component methods. Based on a large panel from 1959:01 to 2012:06 I estimate a number of model specifications and find that the dynamic responses of a monetary policy shock are theoretically more plausible...
Donev, A; Stillinger, F H; Donev, Aleksandar; Torquato, Salvatore; Stillinger, Frank H.
2004-01-01
In the first part of a series of two papers, we present in considerable detail a collision-driven molecular dynamics algorithm for a system of nonspherical particles, within a parallelepiped simulation domain, under both periodic or hard-wall boundary conditions. The algorithm extends previous event-driven molecular dynamics algorithms for spheres. We present a novel partial-update near-neighbor list (NNL) algorithm that is superior to previous algorithms at high densities, without compromising the correctness of the algorithm. This efficiency of the algorithm is further increased for systems of very aspherical particles by using bounding sphere complexes (BSC). In the second part of this series of papers we apply the algorithm presented in the first part of this series of papers to systems of hard ellipses and ellipsoids. The theoretical machinery needed to treat such particles, including the overlap potentials, is developed in full detail. We describe an algorithm for predicting the time of collision for tw...
Probabilistic Dynamic Deployment of Wireless Sensor Networks by Artificial Bee Colony Algorithm
Dervis Karaboga; Celal Ozturk; Beyza Gorkemli
2011-01-01
As the usage and development of wireless sensor networks are increasing, the problems related to these networks are being realized. Dynamic deployment is one of the main topics that directly affect the performance of the wireless sensor networks. In this paper, the artificial bee colony algorithm is applied to the dynamic deployment of stationary and mobile sensor networks to achieve better performance by trying to increase the coverage area of the network. A probabilistic detection model is ...
Chaudhuri, Arindam
2013-01-01
We present a dynamic algorithm for solving the Longest Common Subsequence Problem using Ant Colony Optimization Technique. The Ant Colony Optimization Technique has been applied to solve many problems in Optimization Theory, Machine Learning and Telecommunication Networks etc. In particular, application of this theory in NP-Hard Problems has a remarkable significance. Given two strings, the traditional technique for finding Longest Common Subsequence is based on Dynamic Programming which cons...
Lu, Jianfeng
2016-01-01
In the spirit of the fewest switches surface hopping, the frozen Gaussian approximation with surface hopping (FGA-SH) method samples a path integral representation of the non-adiabatic dynamics in the semiclassical regime. An improved sampling scheme is developed in this work for FGA-SH based on birth and death branching processes. The algorithm is validated for the standard test examples of non-adiabatic dynamics.
Rogério M. Branco; Antônio S. Coelho; Sérgio F. Mayerle
2016-01-01
This paper discusses the application of heuristic-based evolutionary technique in search for solutions concerning the dynamic job-shop scheduling problems with dependent setup times and alternate routes. With a combinatorial nature, these problems belong to an NP-hard class, with an aggravated condition when in realistic, dynamic and therefore, more complex cases than the traditional static ones. The proposed genetic algorithm executes two important functions: choose the routes using dispatch...
Algorithm to illustrate context using dynamic lighting effects
John, Roshy M.; Balasubramanian, T.
2007-09-01
With the invention of Ultra-Bright LED, solid state lighting has come to something which is much more efficient and energy saving when compared to conventional incandescent or fluorescent lighting. With the use of proper driver electronics now a days it is possible to install solid state lighting systems with the cost same as that of any other lighting technology. This paper is a part of the research project we are doing in our lab, which deals with using ultra bright LEDs of different colors for lighting applications. The driver electronics are made in such a way that, the color and brightness of the lights will change according to context. For instance, if one of the users is reading a story or listening to music in a Personal Computer or in a hand held device such as a PDA, the lighting systems and the HVAC (Heating Ventilation Air-conditioning) systems will change dramatically according to the content of the story or the music. The vulnerability of solid-state lighting helps to accomplish such an effect. Such a type of system will help the reader to feel the story mentally and physically as well. We developed complete driver electronics for the system using multiple microcomputers and a full software suite which uses complex algorithms to decode the context from text or music and synchronize it to lighting and HVAC information. The paper also presents some case-study statistics which shows the advantage of using the system to teach kindergarten children, deaf and dumb children and for language learning classes.
Dynamic load balance scheme for the DSMC algorithm
Li, Jin; Geng, Xiangren; Jiang, Dingwu; Chen, Jianqiang
2014-12-01
The direct simulation Monte Carlo (DSMC) algorithm, devised by Bird, has been used over a wide range of various rarified flow problems in the past 40 years. While the DSMC is suitable for the parallel implementation on powerful multi-processor architecture, it also introduces a large load imbalance across the processor array, even for small examples. The load imposed on a processor by a DSMC calculation is determined to a large extent by the total of simulator particles upon it. Since most flows are impulsively started with initial distribution of particles which is surely quite different from the steady state, the total of simulator particles will change dramatically. The load balance based upon an initial distribution of particles will break down as the steady state of flow is reached. The load imbalance and huge computational cost of DSMC has limited its application to rarefied or simple transitional flows. In this paper, by taking advantage of METIS, a software for partitioning unstructured graphs, and taking the total of simulator particles in each cell as a weight information, the repartitioning based upon the principle that each processor handles approximately the equal total of simulator particles has been achieved. The computation must pause several times to renew the total of simulator particles in each processor and repartition the whole domain again. Thus the load balance across the processors array holds in the duration of computation. The parallel efficiency can be improved effectively. The benchmark solution of a cylinder submerged in hypersonic flow has been simulated numerically. Besides, hypersonic flow past around a complex wing-body configuration has also been simulated. The results have displayed that, for both of cases, the computational time can be reduced by about 50%.
Chimeric alignment by dynamic programming: Algorithm and biological uses
Energy Technology Data Exchange (ETDEWEB)
Komatsoulis, G.A.; Waterman, M.S. [Univ. of Southern California, Los Angeles, CA (United States)
1997-12-01
A new nearest-neighbor method for detecting chimeric 16S rRNA artifacts generated during PCR amplification from mixed populations has been developed. The method uses dynamic programming to generate an optimal chimeric alignment, defined as the highest scoring alignment between a query and a concatenation of a 5{prime} and a 3{prime} segment from two separate entries from a database of related sequences. Chimeras are detected by studying the scores and form of the chimeric and global sequence alignments. The chimeric alignment method was found to be marginally more effective than k-tuple based nearest-neighbor methods in simulation studies, but its most effective use is in concert with k-tuple methods. 15 refs., 3 figs., 1 tab.
Community Detection in Dynamic Social Networks Based on Multiobjective Immune Algorithm
Institute of Scientific and Technical Information of China (English)
Mao-Guo Gong; Ling-Jun Zhang; Jing-Jing Ma; Li-Cheng Jiao
2012-01-01
Community structure is one of the most important properties in social networks,and community detection has received an enormous amount of attention in recent years.In dynamic networks,the communities may evolve over time so that pose more challenging tasks than in static ones.Community detection in dynamic networks is a problem which can naturally be formulated with two contradictory objectives and consequently be solved by multiobjective optimization algorithms.In this paper,a novel multiobjective immune algorithm is proposed to solve the community detection problem in dynamic networks.It employs the framework of nondominated neighbor immune algorithm to simultaneously optimize the modularity and normalized mutual information,which quantitatively measure the quality of the community partitions and temporal cost,respectively.The problem-specific knowledge is incorporated in genetic operators and local search to improve the effectiveness and efficiency of our method.Experimental studies based on four synthetic datasets and two real-world social networks demonstrate that our algorithm can not only find community structure and capture community evolution more accurately but also be more steadily than the state-of-the-art algorithms.
Institute of Scientific and Technical Information of China (English)
SUN Fan; DU Wenli; QI Rongbin; QIAN Feng; ZHONG Weimin
2013-01-01
The solutions of dynamic optimization problems are usually very difficult due to their highly nonlinear and multidimensional nature.Genetic algorithm(GA)has been proved to be a feasible method when the gradient is difficult to calculate.Its advantage is that the control profiles at all time stages are optimized simultaneously,but its convergence is very slow in the later period of evolution and it is easily trapped in the local optimum.In this study,a hybrid improved genetic algorithm(HIGA)for solving dynamic optimization problems is proposed to overcome these defects.Simplex method(SM)is used to perform the local search in the neighborhood of the optimal solution.By using SM,the ideal searching direction of global optimal solution could be found as soon as possible and the convergence speed of the algorithm is improved.The hybrid algorithm presents some improvements,such as protecting the best individual,accepting immigrations,as well as employing adaptive crossover and Gaussian mutation operators.The efficiency of the proposed algorithm is demonstrated by solving several dynamic optimization problems.At last,HIGA is applied to the optimal production of secreted protein in a fed batch reactor and the optimal feed-rate found by HIGA is effective and relatively stable.
A parallel dynamic programming algorithm for multi-reservoir system optimization
Li, Xiang; Wei, Jiahua; Li, Tiejian; Wang, Guangqian; Yeh, William W.-G.
2014-05-01
This paper develops a parallel dynamic programming algorithm to optimize the joint operation of a multi-reservoir system. First, a multi-dimensional dynamic programming (DP) model is formulated for a multi-reservoir system. Second, the DP algorithm is parallelized using a peer-to-peer parallel paradigm. The parallelization is based on the distributed memory architecture and the message passing interface (MPI) protocol. We consider both the distributed computing and distributed computer memory in the parallelization. The parallel paradigm aims at reducing the computation time as well as alleviating the computer memory requirement associated with running a multi-dimensional DP model. Next, we test the parallel DP algorithm on the classic, benchmark four-reservoir problem on a high-performance computing (HPC) system with up to 350 cores. Results indicate that the parallel DP algorithm exhibits good performance in parallel efficiency; the parallel DP algorithm is scalable and will not be restricted by the number of cores. Finally, the parallel DP algorithm is applied to a real-world, five-reservoir system in China. The results demonstrate the parallel efficiency and practical utility of the proposed methodology.
Directory of Open Access Journals (Sweden)
Zhang Xuejun
2015-04-01
Full Text Available The continuous growth of air traffic has led to acute airspace congestion and severe delays, which threatens operation safety and cause enormous economic loss. Flight assignment is an economical and effective strategic plan to reduce the flight delay and airspace congestion by reasonably regulating the air traffic flow of China. However, it is a large-scale combinatorial optimization problem which is difficult to solve. In order to improve the quality of solutions, an effective multi-objective parallel evolution algorithm (MPEA framework with dynamic migration interval strategy is presented in this work. Firstly, multiple evolution populations are constructed to solve the problem simultaneously to enhance the optimization capability. Then a new strategy is proposed to dynamically change the migration interval among different evolution populations to improve the efficiency of the cooperation of populations. Finally, the cooperative co-evolution (CC algorithm combined with non-dominated sorting genetic algorithm II (NSGA-II is introduced for each population. Empirical studies using the real air traffic data of the Chinese air route network and daily flight plans show that our method outperforms the existing approaches, multi-objective genetic algorithm (MOGA, multi-objective evolutionary algorithm based on decomposition (MOEA/D, CC-based multi-objective algorithm (CCMA as well as other two MPEAs with different migration interval strategies.
Hierarchical adaptive stereo matching algorithm for obstacle detection with dynamic programming
Institute of Scientific and Technical Information of China (English)
Ming BAI; Yan ZHUANG; Wei WANG
2009-01-01
An adaptive weighted stereo matching algorithm with multilevel and bidirectional dynamic programming based on ground control points(GCPs) is presented.To decrease time complexity without losing matching precision,using a multilevel search scheme,the coarse matching is processed in typical disparity space image,while the fine matching is processed in disparity-offset space image.In the upper level,GCPs are obtained by enhanced volumetric iterative algorithm enforcing the mutual constraint and the threshold constraint.Under the supervision of the highly reliable GCPs,bidirec-tional dynamic programming framework is employed to solve the inconsistency in the optimization path.In the lower level,to reduce running time,disparity-offset space is proposed to efficiently achieve the dense disparity image.In addition,an adaptive dual support-weight strategy is presented to aggregate matching cost,which considers photometric and geomet-ric information.Further,post-processing algorithm can ameliorate disparity results in areas with depth discontinuities and related by occlusions using dual threshold algorithm,where missing stereo information is substituted from surrounding re-gions.To demonstrate the effectiveness of the algorithm,we present the two groups of experimental results for four widely used standard stereo data sets,including discussion on performance and comparison with other methods,which show that the algorithm has not only a fast speed,but also significantly improves the efficiency of holistic optimization.
Coherency Identification of Generators Using a PAM Algorithm for Dynamic Reduction of Power Systems
Directory of Open Access Journals (Sweden)
Seung-Il Moon
2012-11-01
Full Text Available This paper presents a new coherency identification method for dynamic reduction of a power system. To achieve dynamic reduction, coherency-based equivalence techniques divide generators into groups according to coherency, and then aggregate them. In order to minimize the changes in the dynamic response of the reduced equivalent system, coherency identification of the generators should be clearly defined. The objective of the proposed coherency identification method is to determine the optimal coherent groups of generators with respect to the dynamic response, using the Partitioning Around Medoids (PAM algorithm. For this purpose, the coherency between generators is first evaluated from the dynamic simulation time response, and in the proposed method this result is then used to define a dissimilarity index. Based on the PAM algorithm, the coherent generator groups are then determined so that the sum of the index in each group is minimized. This approach ensures that the dynamic characteristics of the original system are preserved, by providing the optimized coherency identification. To validate the effectiveness of the technique, simulated cases with an IEEE 39-bus test system are evaluated using PSS/E. The proposed method is compared with an existing coherency identification method, which uses the K-means algorithm, and is found to provide a better estimate of the original system.
Two-stage evolutionary algorithm for dynamic multicast routing in mesh network
Institute of Scientific and Technical Information of China (English)
Li ZHU; Zhi-shu LI; Liang-yin CHEN; Yan-hong CHENG
2008-01-01
In order to share multimedia transmissions in mesh networks and optimize the utilization of network resources, this paper presents a Two-stage Evolutionary Algorithm (TEA), i.e., unicast routing evolution and multicast path composition, for dynamic multicast routing. The TEA uses a novel link-duplicate-degree encoding, which can encode a multicast path in the link-duplicate-degree and decode the path as a link vector easily. A dynamic algorithm for adding nodes to or removing nodes from a multicast group and a repairing algorithm are also covered in this paper. As the TEA is based on global evaluation, the quality of the multicast path remains stabilized without degradation when multicast members change over time. Therefore, it is not necessary to rearrange the multicast path during the life cycle of the multicast sessions. Simulation results show that the TEA is efficient and convergent.
Xu, Jiuping; Zeng, Ziqiang; Han, Bernard; Lei, Xiao
2013-07-01
This article presents a dynamic programming-based particle swarm optimization (DP-based PSO) algorithm for solving an inventory management problem for large-scale construction projects under a fuzzy random environment. By taking into account the purchasing behaviour and strategy under rules of international bidding, a multi-objective fuzzy random dynamic programming model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform fuzzy random parameters into fuzzy variables that are subsequently defuzzified by using an expected value operator with optimistic-pessimistic index. The iterative nature of the authors' model motivates them to develop a DP-based PSO algorithm. More specifically, their approach treats the state variables as hidden parameters. This in turn eliminates many redundant feasibility checks during initialization and particle updates at each iteration. Results and sensitivity analysis are presented to highlight the performance of the authors' optimization method, which is very effective as compared to the standard PSO algorithm.
DOUBLE FOUR-BAR CRANK-SLIDER MECHANISM DYNAMIC BALANCING BY META-HEURISTIC ALGORITHMS
Directory of Open Access Journals (Sweden)
Habib Emdadi
2013-09-01
Full Text Available In this paper, a new method for dynamic balancing of double four-bar crank slider mechanism by metaheuristic-based optimization algorithms is proposed. For this purpose, a proper objective function which is necessary for balancing of this mechanism and corresponding constraints has been obtained by dynamic modeling of the mechanism. Then PSO, ABC, BGA and HGAPSO algorithms have been applied for minimizing the defined cost function in optimization step. The optimization results have been studied completely by extracting the cost function, fitness, convergence speed and runtime values of applied algorithms. It has been shown that PSO and ABC are more efficient than BGA and HGAPSO in terms of convergence speed and result quality. Also, a laboratory scale experimental doublefour-bar crank-slider mechanism was provided for validating the proposed balancing method practically.
Double Four-Bar Crank-Slider Mechanism Dynamic Balancing by Meta-Heuristic Algorithms
Directory of Open Access Journals (Sweden)
Habib Emdadi
2013-09-01
Full Text Available In this paper, a new method for dynamic balancing of double four-bar crank slider mechanism by meta-heuristic-based optimization algorithms is proposed. For this purpose, a proper objective function which is necessary for balancing of this mechanism and corresponding constraints has been obtained by dynamic modeling of the mechanism.Then PSO, ABC, BGA and HGAPSO algorithms have been applied for minimizing the defined cost function in optimization step. The optimization results have been studied completely by extracting the cost function, fitness, convergence speed and run time values of applied algorithms. It has been shown that PSO and ABC are more efficient than BGA and HGAPSO in terms of convergence speed and result quality. Also, a laboratory scale experimental double four-bar crank-slider mechanism was provided for validating the proposedbalancing method practicall
Novotny, M.A.
2010-02-01
The efficiency of dynamic Monte Carlo algorithms for off-lattice systems composed of particles is studied for the case of a single impurity particle. The theoretical efficiencies of the rejection-free method and of the Monte Carlo with Absorbing Markov Chains method are given. Simulation results are presented to confirm the theoretical efficiencies. © 2010.
Construction of a Parallel Algorithm to Solve the Multiphase Gas Dynamics Problem
Directory of Open Access Journals (Sweden)
B. Rybakin
1995-11-01
Full Text Available This paper considers questions of an effective use of multiprocessor computing system to implement a parallel algorithm solving the multiphase gas dynamics problem. A technique is offered to parallelize the two-dimensional explicit differential scheme to implement it on multiprocessor systems with distributed memory (MIMD architecture.
DEFF Research Database (Denmark)
Meng, Lexuan; Dragicevic, Tomislav; Guerrero, Josep M.;
2014-01-01
. Accordingly, this paper proposes a dynamic consensus algorithm based distributed optimization method aiming at improving the system efficiency while offering higher expandability and flexibility when compared to centralized control. Hardware-in-the-loop (HIL) results are shown to demonstrate the effectiveness...
Genetic Algorithm-based Dynamic Vehicle Route Search using Car-to-Car Communication
Directory of Open Access Journals (Sweden)
KIM, J.
2010-11-01
Full Text Available Suggesting more efficient driving routes generate benefits not only for individuals by saving commute time, but also for society as a whole by reducing accident rates and social costs by lessening traffic congestion. In this paper, we suggest a new route search algorithm based on a genetic algorithm which is more easily installable into mutually communicating car navigation systems, and validate its usefulness through experiments reflecting real-world situations. The proposed algorithm is capable of searching alternative routes dynamically in unexpected events of system malfunctioning or traffic slow-downs due to accidents. Experimental results demonstrate that our algorithm searches the best route more efficiently and evolves with universal adaptability.
A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat
Liu, Jian; Li, Dezhang; Liu, Xinzijian
2016-07-01
We introduce a novel simple algorithm for thermostatting path integral molecular dynamics (PIMD) with the Langevin equation. The staging transformation of path integral beads is employed for demonstration. The optimum friction coefficients for the staging modes in the free particle limit are used for all systems. In comparison to the path integral Langevin equation thermostat, the new algorithm exploits a different order of splitting for the phase space propagator associated to the Langevin equation. While the error analysis is made for both algorithms, they are also employed in the PIMD simulations of three realistic systems (the H2O molecule, liquid para-hydrogen, and liquid water) for comparison. It is shown that the new thermostat increases the time interval of PIMD by a factor of 4-6 or more for achieving the same accuracy. In addition, the supplementary material shows the error analysis made for the algorithms when the normal-mode transformation of path integral beads is used.
Directory of Open Access Journals (Sweden)
Ziyi Fu
2012-10-01
Full Text Available According to the upstream TDM in the system of Ethernet passive optical network (EPON, this paper proposes a novel dynamic bandwidth allocation algorithm which supports the mechanism with correction-based the multiple services estimation. To improve the real-time performance of the bandwidth allocation, this algorithm forecasts the traffic of high priority services, and then pre-allocate bandwidth for various priority services is corrected according to Gaussian distribution characteristics, which will make traffic prediction closer to the real traffic. The simulation results show that proposed algorithm is better than the existing DBA algorithm. Not only can it meet the delay requirement of high priority services, but also control the delay abnormity of low priority services. In addition, with rectification scheme, it obviously improves the bandwidth utilization.
New dynamic routing algorithm based on MANET in LEO/MEO satellite network
Institute of Scientific and Technical Information of China (English)
LI Zhe; LI Dong-ni; WANG Guang-xing
2006-01-01
The features of low earth orbit/medium earth orbit (LEO/MEO) satellite networks routing algorithm based on inter-satellite link are analyzed and the similarities between satellite networks and mobile Ad Hoc network (MANET) are pointed out.The similar parts in MANET routing protocol are used in the satellite network for reference.A new dynamic routing algorithm based on MANET in LEO/MEO satellite networks,which fits for the LEO/MEO satellite communication system,is proposed.At the same time,the model of the algorithm is simulated and features are analyzed.It is shown that the algorithm has strong adaptability.It can give the network high autonomy,perfect function,low system overhead and great compatibility.
Directory of Open Access Journals (Sweden)
Chaowei Wang
2013-01-01
Full Text Available This paper proposes an advanced dynamic framed-slotted ALOHA algorithm based on Bayesian estimation and probability response (BE-PDFSA to improve the performance of radio frequency identification (RFID system. The Bayesian estimation is introduced to improve the accuracy of the estimation algorithm for lacking a large number of observations in one query. The probability response is used to adjust responsive probability of the unrecognized tags to make the responsive tag number equal to the frame length. In this way, we can solve the problem of high collision rate with the increase of tag number and improve the throughput of the whole system. From the simulation results, we can see that the algorithm we proposed can greatly improve the stability of RFID system compared with DFSA and other commonly used algorithms.
A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat.
Liu, Jian; Li, Dezhang; Liu, Xinzijian
2016-07-14
We introduce a novel simple algorithm for thermostatting path integral molecular dynamics (PIMD) with the Langevin equation. The staging transformation of path integral beads is employed for demonstration. The optimum friction coefficients for the staging modes in the free particle limit are used for all systems. In comparison to the path integral Langevin equation thermostat, the new algorithm exploits a different order of splitting for the phase space propagator associated to the Langevin equation. While the error analysis is made for both algorithms, they are also employed in the PIMD simulations of three realistic systems (the H2O molecule, liquid para-hydrogen, and liquid water) for comparison. It is shown that the new thermostat increases the time interval of PIMD by a factor of 4-6 or more for achieving the same accuracy. In addition, the supplementary material shows the error analysis made for the algorithms when the normal-mode transformation of path integral beads is used.
Supercomputer algorithms for reactivity, dynamics and kinetics of small molecules
International Nuclear Information System (INIS)
Even for small systems, the accurate characterization of reactive processes is so demanding of computer resources as to suggest the use of supercomputers having vector and parallel facilities. The full advantages of vector and parallel architectures can sometimes be obtained by simply modifying existing programs, vectorizing the manipulation of vectors and matrices, and requiring the parallel execution of independent tasks. More often, however, a significant time saving can be obtained only when the computer code undergoes a deeper restructuring, requiring a change in the computational strategy or, more radically, the adoption of a different theoretical treatment. This book discusses supercomputer strategies based upon act and approximate methods aimed at calculating the electronic structure and the reactive properties of small systems. The book shows how, in recent years, intense design activity has led to the ability to calculate accurate electronic structures for reactive systems, exact and high-level approximations to three-dimensional reactive dynamics, and to efficient directive and declaratory software for the modelling of complex systems
Pluchino, Alessandro; Latora, Vito
2008-01-01
We have recently introduced an efficient method for the detection and identification of modules in complex networks, based on the de-synchronization properties (dynamical clustering) of phase oscillators. In this paper we apply the dynamical clustering tecnique to the identification of communities of marine organisms living in the Chesapeake Bay food web. We show that our algorithm is able to perform a very reliable classification of the real communities existing in this ecosystem by using different kinds of dynamical oscillators. We compare also our results with those of other methods for the detection of community structures in complex networks.
Institute of Scientific and Technical Information of China (English)
ZhangLiangjie; LiYanda; 等
1997-01-01
In this paper,a dynamic bandwidth allocation technique based on fuzz neural networks(FNNs) and genetic algorithm(GA)is proposed for preventive congestion control in ATM network.The traffic model based on FNN does not need the descriptive traffic parameters in detail,which greatly depend on the user's terminal.Genetic algorithm is used to predict the equivalent bandwidth of the accepted traffic in real-time.Thus,the proposed scheme can estimate the dynamic bandwidth of the network in the time scale from the call arrival to the call admission/rejection due to the fuzzy-tech and GA hardware implementation.Simulation results show that the scheme can perform accurate dynamic bandwidth allocation to DN/OFF bursty traffic in accordance with the required quality of service(QOS),and the bandwidth utilization is improved from the overall point of view.
Lin, Yuan; Samei, Ehsan
2016-07-01
Dynamic perfusion imaging can provide the morphologic details of the scanned organs as well as the dynamic information of blood perfusion. However, due to the polyenergetic property of the x-ray spectra, beam hardening effect results in undesirable artifacts and inaccurate CT values. To address this problem, this study proposes a segmentation-free polyenergetic dynamic perfusion imaging algorithm (pDP) to provide superior perfusion imaging. Dynamic perfusion usually is composed of two phases, i.e., a precontrast phase and a postcontrast phase. In the precontrast phase, the attenuation properties of diverse base materials (e.g., in a thorax perfusion exam, base materials can include lung, fat, breast, soft tissue, bone, and metal implants) can be incorporated to reconstruct artifact-free precontrast images. If patient motions are negligible or can be corrected by registration, the precontrast images can then be employed as a priori information to derive linearized iodine projections from the postcontrast images. With the linearized iodine projections, iodine perfusion maps can be reconstructed directly without the influence of various influential factors, such as iodine location, patient size, x-ray spectrum, and background tissue type. A series of simulations were conducted on a dynamic iodine calibration phantom and a dynamic anthropomorphic thorax phantom to validate the proposed algorithm. The simulations with the dynamic iodine calibration phantom showed that the proposed algorithm could effectively eliminate the beam hardening effect and enable quantitative iodine map reconstruction across various influential factors. The error range of the iodine concentration factors ([Formula: see text]) was reduced from [Formula: see text] for filtered back-projection (FBP) to [Formula: see text] for pDP. The quantitative results of the simulations with the dynamic anthropomorphic thorax phantom indicated that the maximum error of iodine concentrations can be reduced from
Optimal GPS/accelerometer integration algorithm for monitoring the vertical structural dynamics
Meng, Xiaolin; Wang, Jian; Han, Houzeng
2014-11-01
The vertical structural dynamics is a crucial factor for structural health monitoring (SHM) of civil structures such as high-rise buildings, suspension bridges and towers. This paper presents an optimal GPS/accelerometer integration algorithm for an automated multi-sensor monitoring system. The closed loop feedback algorithm for integrating the vertical GPS and accelerometer measurements is proposed based on a 5 state extended KALMAN filter (EKF) and then the narrow moving window Fast Fourier Transform (FFT) analysis is applied to extract structural dynamics. A civil structural vibration is simulated and the analysed result shows the proposed algorithm can effectively integrate the online vertical measurements produced by GPS and accelerometer. Furthermore, the accelerometer bias and scale factor can also be estimated which is impossible with traditional integration algorithms. Further analysis shows the vibration frequencies detected in GPS or accelerometer are all included in the integrated vertical defection time series and the accelerometer can effectively compensate the short-term GPS outages with high quality. Finally, the data set collected with a time synchronised and integrated GPS/accelerometer monitoring system installed on the Nottingham Wilford Bridge when excited by 15 people jumping together at its mid-span are utilised to verify the effectiveness of this proposed algorithm. Its implementations are satisfactory and the detected vibration frequencies are 1.720 Hz, 1.870 Hz, 2.104 Hz, 2.905 Hz and also 10.050 Hz, which is not found in GPS or accelerometer only measurements.
An Event-Driven Hybrid Molecular Dynamics and Direct Simulation Monte Carlo Algorithm
Energy Technology Data Exchange (ETDEWEB)
Donev, A; Garcia, A L; Alder, B J
2007-07-30
A novel algorithm is developed for the simulation of polymer chains suspended in a solvent. The polymers are represented as chains of hard spheres tethered by square wells and interact with the solvent particles with hard core potentials. The algorithm uses event-driven molecular dynamics (MD) for the simulation of the polymer chain and the interactions between the chain beads and the surrounding solvent particles. The interactions between the solvent particles themselves are not treated deterministically as in event-driven algorithms, rather, the momentum and energy exchange in the solvent is determined stochastically using the Direct Simulation Monte Carlo (DSMC) method. The coupling between the solvent and the solute is consistently represented at the particle level, however, unlike full MD simulations of both the solvent and the solute, the spatial structure of the solvent is ignored. The algorithm is described in detail and applied to the study of the dynamics of a polymer chain tethered to a hard wall subjected to uniform shear. The algorithm closely reproduces full MD simulations with two orders of magnitude greater efficiency. Results do not confirm the existence of periodic (cycling) motion of the polymer chain.
Directory of Open Access Journals (Sweden)
Jingjing Ma
2014-01-01
Full Text Available Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms.
Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng
2014-01-01
Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms.
A dynamic material discrimination algorithm for dual MV energy X-ray digital radiography.
Li, Liang; Li, Ruizhe; Zhang, Siyuan; Zhao, Tiao; Chen, Zhiqiang
2016-08-01
Dual-energy X-ray radiography has become a well-established technique in medical, industrial, and security applications, because of its material or tissue discrimination capability. The main difficulty of this technique is dealing with the materials overlapping problem. When there are two or more materials along the X-ray beam path, its material discrimination performance will be affected. In order to solve this problem, a new dynamic material discrimination algorithm is proposed for dual-energy X-ray digital radiography, which can also be extended to multi-energy X-ray situations. The algorithm has three steps: α-curve-based pre-classification, decomposition of overlapped materials, and the final material recognition. The key of the algorithm is to establish a dual-energy radiograph database of both pure basis materials and pair combinations of them. After the pre-classification results, original dual-energy projections of overlapped materials can be dynamically decomposed into two sets of dual-energy radiographs of each pure material by the algorithm. Thus, more accurate discrimination results can be provided even with the existence of the overlapping problem. Both numerical and experimental results that prove the validity and effectiveness of the algorithm are presented. PMID:27239987
An adaptive mass algorithm for Car-Parrinello and Ehrenfest ab initio molecular dynamics
Kadir, Ashraful; Szepessy, Anders
2014-01-01
Ehrenfest and Car-Parrinello molecular dynamics are computational alternatives to approximate Born-Oppenheimer molecular dynamics without solving the electron eigenvalue problem at each time-step. A non-trivial issue is to choose the artificial electron mass parameter appearing in the Car-Parrinello method to achieve both good accuracy and high computational efficiency. In this paper, we propose an algorithm, motivated by the Landau-Zener probability, to systematically choose an artificial mass dynamically, which makes the Car-Parrinello and Ehrenfest molecular dynamics methods dependent only on the problem data. Numerical experiments for simple model problems show that the time-dependent adaptive artificial mass parameter improves the efficiency of the Car-Parrinello and Ehrenfest molecular dynamics.
Kumar, Rohit
2016-05-01
We discuss the stability of fragments identified by secondary algorithms used to construct fragments within quantum molecular dynamics model. For this purpose we employ three different algorithms for fragment identification. 1) The conventional minimum spanning tree (MST) method based on the spatial correlations, 2) an improved version of MST with additional binding energy constraints of cold nuclear matter, 3) and that of hot matter. We find significant role of thermal binding energies over cold matter binding energies. Significant role is observed for fragment multiplicities and stopping of fragments. Whereas insignificant effect is observed on fragment's flow.
Dynamic learning rates algorithm for BPNN to forecast time series of dam security
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Time series data of dam security have a large number of observed values and should be forecasted accurately in time.Neural networks have the powerful approach ablilities of arbitrary functions and have been broadly utilized in many domains.In this paper,a dynamic learning rate training algorithm of hack-propagation neural networks for time series forecasting is proposed and the networks with this algorithm are built to forecast time series of dam security.The application results demonostrate the efficiency of modelling and the effictiveness of forecasting.
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Standardi, Laura; Edlund, Kristian;
2014-01-01
This paper presents a warm-started Dantzig–Wolfe decomposition algorithm tailored to economic model predictive control of dynamically decoupled subsystems. We formulate the constrained optimal control problem solved at each sampling instant as a linear program with state space constraints, input...... limits, input rate limits, and soft output limits. The objective function of the linear program is related directly to the cost of operating the subsystems, and the cost of violating the soft output constraints. Simulations for large-scale economic power dispatch problems show that the proposed algorithm...
Dynamic Routing Algorithm Based on the Channel Quality Control for Farmland Sensor Networks
Directory of Open Access Journals (Sweden)
Dongfeng Xu
2014-04-01
Full Text Available This article reports a Dynamic Routing Algorithm for Farmland Sensor Networks (DRA-FSN based on channel quality control to improve energy efficiency, which combines the distance and communication characteristics of farmland wireless sensor network. The functional architecture of the DRA-FSN algorithm, routing establish the mechanisms, the communication transmission mechanism, the global routing beacon return mechanism, abnormal node handling mechanism and sensor networks timing control mechanisms were designed in detail in this article. This article also evaluates and simulated the performance of DRA-FSN algorithm in different conditions from energy efficiency, packet energy consumption and packet distribution balance by comparing DRA-FSN algorithm with DSDV, EAP algorithm. Simulations showed that the DRA-FSN was more energy efficient than EAP and DSDV, the DRA-FSN algorithm overcame the shortcoming that capacity and bandwidth of the routing table correspondingly increase as more and more nodes joining the network. It has better performance in scalability and network loading balance
Koch, Caleb; Winfrey, Leigh
2014-10-01
Natural Gas is a major energy source in Europe, yet political instabilities have the potential to disrupt access and supply. Energy resilience is an increasingly essential construct and begins with transmission network design. This study proposes a new way of thinking about modelling natural gas flow. Rather than relying on classical economic models, this problem is cast into a time-dependent Hamiltonian dynamics discussion. Traditional Natural Gas constraints, including inelastic demand and maximum/minimum pipe flows, are portrayed as energy functions and built into the dynamics of each pipe flow. Doing so allows the constraints to be built into the dynamics of each pipeline. As time progresses in the model, natural gas flow rates find the minimum energy, thus the optimal gas flow rates. The most important result of this study is using dynamical principles to ensure the output of natural gas at demand nodes remains constant, which is important for country to country natural gas transmission. Another important step in this study is building the dynamics of each flow in a decentralized algorithm format. Decentralized regulation has solved congestion problems for internet data flow, traffic flow, epidemiology, and as demonstrated in this study can solve the problem of Natural Gas congestion. A mathematical description is provided for how decentralized regulation leads to globally optimized network flow. Furthermore, the dynamical principles and decentralized algorithm are applied to a case study of the Fluxys Belgium Natural Gas Network.
Weeks, Cindy Lou
1986-01-01
Experiments were conducted at NASA Ames Research Center to define multi-tasking software requirements for multiple-instruction, multiple-data stream (MIMD) computer architectures. The focus was on specifying solutions for algorithms in the field of computational fluid dynamics (CFD). The program objectives were to allow researchers to produce usable parallel application software as soon as possible after acquiring MIMD computer equipment, to provide researchers with an easy-to-learn and easy-to-use parallel software language which could be implemented on several different MIMD machines, and to enable researchers to list preferred design specifications for future MIMD computer architectures. Analysis of CFD algorithms indicated that extensions of an existing programming language, adaptable to new computer architectures, provided the best solution to meeting program objectives. The CoFORTRAN Language was written in response to these objectives and to provide researchers a means to experiment with parallel software solutions to CFD algorithms on machines with parallel architectures.
Incremental Density-Based Link Clustering Algorithm for Community Detection in Dynamic Networks
Directory of Open Access Journals (Sweden)
Fanrong Meng
2016-01-01
Full Text Available Community detection in complex networks has become a research hotspot in recent years. However, most of the existing community detection algorithms are designed for the static networks; namely, the connections between the nodes are invariable. In this paper, we propose an incremental density-based link clustering algorithm for community detection in dynamic networks, iDBLINK. This algorithm is an extended version of DBLINK which is proposed in our previous work. It can update the local link community structure in the current moment through the change of similarity between the edges at the adjacent moments, which includes the creation, growth, merging, deletion, contraction, and division of link communities. Extensive experimental results demonstrate that iDBLINK not only has a great time efficiency, but also maintains a high quality community detection performance when the network topology is changing.
Directory of Open Access Journals (Sweden)
Diamantidis A. C.
2004-01-01
Full Text Available In this study, the buffer allocation problem (BAP in homogeneous, asymptotically reliable serial production lines is considered. A known aggregation method, given by Lim, Meerkov, and Top (1990, for the performance evaluation (i.e., estimation of throughput of this type of production lines when the buffer allocation is known, is used as an evaluative method in conjunction with a newly developed dynamic programming (DP algorithm for the BAP. The proposed algorithm is applied to production lines where the number of machines is varying from four up to a hundred machines. The proposed algorithm is fast because it reduces the volume of computations by rejecting allocations that do not lead to maximization of the line's throughput. Numerical results are also given for large production lines.
Dynamic Routing Algorithm for Reliability and Energy Efficiency in Wireless Sensor Networks
Choi, Seong-Yong; Kim, Jin-Su; Han, Seung-Jin; Choi, Jun-Hyeog; Rim, Kee-Wook; Lee, Jung-Hyun
What are important in wireless sensor networks are energy efficiency, reliable data transmission, and topological adaptation to the change of external environment. This study proposes dynamic routing algorithm that satisfies the above-mentioned conditions at the same time using a dynamic single path in wireless sensor networks. In our proposed algorithm, each node transmits data through the optimal single path using hop count to the sink and node average energy according to the change of external environment. For reliable data transmission, each node monitors its own transmission process. If a node detects a damaged path, it switches from the damaged path to the optimal path and, by doing so, enhances network reliability. In case of a topological change, only the changed part is reconstructed instead of the whole network, and this enhances the energy efficiency of the network.
Thickness determination in textile material design: dynamic modeling and numerical algorithms
Xu, Dinghua; Ge, Meibao
2012-03-01
Textile material design is of paramount importance in the study of functional clothing design. It is therefore important to determine the dynamic heat and moisture transfer characteristics in the human body-clothing-environment system, which directly determine the heat-moisture comfort level of the human body. Based on a model of dynamic heat and moisture transfer with condensation in porous fabric at low temperature, this paper presents a new inverse problem of textile thickness determination (IPTTD). Adopting the idea of the least-squares method, we formulate the IPTTD into a function minimization problem. By means of the finite-difference method, quasi-solution method and direct search method for one-dimensional minimization problems, we construct iterative algorithms of the approximated solution for the IPTTD. Numerical simulation results validate the formulation of the IPTTD and demonstrate the effectiveness of the proposed numerical algorithms.
Directory of Open Access Journals (Sweden)
Bruno H. Dias
2010-01-01
Full Text Available This paper presents a new approach for the expected cost-to-go functions modeling used in the stochastic dynamic programming (SDP algorithm. The SDP technique is applied to the long-term operation planning of electrical power systems. Using state space discretization, the Convex Hull algorithm is used for constructing a series of hyperplanes that composes a convex set. These planes represent a piecewise linear approximation for the expected cost-to-go functions. The mean operational costs for using the proposed methodology were compared with those from the deterministic dual dynamic problem in a case study, considering a single inflow scenario. This sensitivity analysis shows the convergence of both methods and is used to determine the minimum discretization level. Additionally, the applicability of the proposed methodology for two hydroplants in a cascade is demonstrated. With proper adaptations, this work can be extended to a complete hydrothermal system.
Tracking and Following Algorithms of Mobile Robots for Service Activities in Dynamic Environments
Directory of Open Access Journals (Sweden)
Feng-Li Lian
2015-02-01
Full Text Available By providing the capability of following a human target in an appropriate manner, the robot can assist people in various ways under different environments. One of the main difficulties when performing human tracking and following is the occlusion problem caused by static as well as dynamic obstacles. The aim of the paper is to tackle the occlusion problem by planning a robotic trajectory of maximizing target visibility and following the moving target. Initially, a laser range finder is used to detect the human target and then robustly track the target using the Kalman filter. Afterward, a human following algorithm based on a look-ahead algorithm, DWA*, is implemented to pursue the target while avoiding any static or dynamic obstacles. Fundamental experiments have been extensively tested to evaluate robot maneuvers and several field tests are conducted in more complex environments such as student cafeteria, computer center, and university library.
Spectrum of the Dirac operator and multigrid algorithm with dynamical staggered fermions
International Nuclear Information System (INIS)
Complete spectra of the staggered Dirac operator D are determined in quenched four-dimensional SU(2) gauge fields, and also in the presence of dynamical fermions. Periodic as well as antiperiodic boundary conditions are used. An attempt is made to relate the performance of multigrid (MG) and conjugate gradient (CG) algorithms for propagators with the distribution of the eigenvalues of D. The convergence of the CG algorithm is determined only by the condition number k and by the lattice size. Since k's do not vary signigicantly when quarks become dynamic, CG convergence in unquenched fields can be predicted from quenched simulations. On the other hand, MG convergence is not affected by k but depends on the spectrum in a more subtle way. (orig.)
Study on algorithm of dynamic uncalibrated eye-in-hand visual servoing system
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Currently, most visual servoing system must be calibrated, while it is impossible to calibrate cameras and robot models precisely in industrial practice, so a novel dynamic uncalibrated eye-in-hand visual servoing system of tracking a moving target is proposed. The method does not require calibration of camera and robot kinematic models. Vision guided algorithm for tracking dynamic image is developed through minimizing nonlinear objective function. For the large residual has not been approximated in dynamic environment and the change of composite image Jacobian with time increment has not been computed in visual servoing system now,large residuals are dynamic approximated and the change of composite image Jacobian at each iterative step is computed.Simulation results demonstrate the validity of these approaches.
Dynamic Fuzzy Controlled RWA Algorithm for IP/GMPLS over WDM Networks
Institute of Scientific and Technical Information of China (English)
I-Shyan Hwang; I-Feng Huang; Shin-Cheng Yu
2005-01-01
This paper proposes a dynamic RWA scheme using fuzzy logic control on IP/GMPLS over WDM networks to achieve the best quality of network transmission. The proposed algorithm dynamically allocates network resources and reserves partial bandwidth based on the current network status, which includes the request bandwidth, average utilization for each wavelength and its coefficient of variance (C.V.) of data traffic, to determine whether the connection can be set up. Five fuzzy sets for request bandwidth, average rate and C.V. of data traffic are used to divide the variable space: very large (LP), large (SP), normal (ZE), small (SN), and very small (LN). Setting the fuzzy limit is a key part in the proposed algorithm. The simulation of scenarios in this paper has two steps. In the first step, the adaptive fuzzy limits are evaluated based on average transmission cost pertaining to ten network statuses. The second step is to compare the proposed algorithm with periodic measurement of traffic (PMT) in ATM networks in six network situations to show that the proposed FC-RWA algorithm can provide better network transmission.
Institute of Scientific and Technical Information of China (English)
LIU Xiao; WANG Cheng-en
2005-01-01
This paper addresses a single item dynamic lot-sizing model with inventory capacity and out-sourcing. The goal is to minimize the total costs of production, setup, inventory holding and out-sourcing. Two versions of an out-sourcing model with time-varying costs are considered: stock out case and conservation case. Zero Inventory Order property has been found and some new properties are obtained in an optimal solution. Dynamic programming algorithms are developed to solve the problem in strongly polynomial time respectively. Furthermore, some numerical results demonstrate that the approach proposed is efficient and applicable.
Lelu, Alain; Cuxac, Pascal
2008-01-01
We address here two major challenges presented by dynamic data mining: 1) the stability challenge: we have implemented a rigorous incremental density-based clustering algorithm, independent from any initial conditions and ordering of the data-vectors stream, 2) the cognitive challenge: we have implemented a stringent selection process of association rules between clusters at time t-1 and time t for directly generating the main conclusions about the dynamics of a data-stream. We illustrate these points with an application to a two years and 2600 documents scientific information database.
Institute of Scientific and Technical Information of China (English)
LI Qiang; WU Jianxin; SUN Yan
2009-01-01
Dynamic optimization of electromechanical coupling system is a significant engineering problem in the field of mechatronics. The performance improvement of electromechanical equipment depends on the system design parameters. Aiming at the spindle unit of refitted machine tool for solid rocket, the vibration acceleration of tool is taken as objective function, and the electromechanical system design parameters are appointed as design variables. Dynamic optimization model is set up by adopting Lagrange-Maxwell equations, Park transform and electromechanical system energy equations. In the procedure of seeking high efficient optimization method, exponential function is adopted to be the weight function of particle swarm optimization algorithm. Exponential inertia weight particle swarm algorithm(EPSA), is formed and applied to solve the dynamic optimization problem of electromechanical system. The probability density function of EPSA is presented and used to perform convergence analysis. After calculation, the optimized design parameters of the spindle unit are obtained in limited time period. The vibration acceleration of the tool has been decreased greatly by the optimized design parameters. The research job in the paper reveals that the problem of dynamic optimization of electromechanical system can be solved by the method of combining system dynamic analysis with reformed swarm particle optimization. Such kind of method can be applied in the design of robots, NC machine, and other electromechanical equipments.
A Generalized Speckle Tracking Algorithm for Ultrasonic Strain Imaging Using Dynamic Programming
Jiang, Jingfeng; Hall, Timothy J.
2009-01-01
This study developed an improved motion estimation algorithm for ultrasonic strain imaging that employs a dynamic programming technique. In this paper, we model the motion estimation task as an optimization problem. Since tissue motion under external mechanical stimuli often should be reasonably continuous, a set of cost functions combining correlation and various levels of motion continuity constraint were used to regularize the motion estimation. To solve the optimization problem with a rea...
Directory of Open Access Journals (Sweden)
Stanimirović Ivan
2009-01-01
Full Text Available We introduce a heuristic method for the single resource constrained project scheduling problem, based on the dynamic programming solution of the knapsack problem. This method schedules projects with one type of resources, in the non-preemptive case: once started an activity is not interrupted and runs to completion. We compare the implementation of this method with well-known heuristic scheduling method, called Minimum Slack First (known also as Gray-Kidd algorithm, as well as with Microsoft Project.
Yunlong Yu; Le Ru; Sheng Mao; Kangning Sun; Qiangqiang Yu; Kun Fang
2016-01-01
Airborne highly dynamic ad hoc UAV network has features of high node mobility, fast changing network topology, and complex application environment. The performance of traditional routing algorithms is so poor over aspects such as end to end delay, data packet delivery ratio, and routing overhead that they cannot provide efficient communication for multi-UAVs carrying out missions synergistically. A bionic optimization based stability and congestion aware routing algorithm—BSCAR algorithm—is p...
DYNAMIC K-MEANS ALGORITHM FOR OPTIMIZED ROUTING IN MOBILE AD HOC NETWORKS
Directory of Open Access Journals (Sweden)
Zahra Zandieh Shirazi
2016-04-01
Full Text Available In this paper, a dynamic K-means algorithm to improve the routing process in Mobile Ad-Hoc networks (MANETs is presented. Mobile ad-hoc networks are a collocation of mobile wireless nodes that can operate without using focal access points, pre-existing infrastructures, or a centralized management point. In MANETs, the quick motion of nodes modifies the topology of network. This feature of MANETS is lead to various problems in the routing process such as increase of the overhead massages and inefficient routing between nodes of network. A large variety of clustering methods have been developed for establishing an efficient routing process in MANETs. Routing is one of the crucial topics which are having significant impact on MANETs performance. The K-means algorithm is one of the effective clustering methods aimed to reduce routing difficulties related to bandwidth, throughput and power consumption. This paper proposed a new K-means clustering algorithm to find out optimal path from source node to destinations node in MANETs. The main goal of proposed approach which is called the dynamic K-means clustering methods is to solve the limitation of basic K-means method like permanent cluster head and fixed cluster members. The experimental results demonstrate that using dynamic K-means scheme enhance the performance of routing process in Mobile ad-hoc networks.
Detectability Thresholds and Optimal Algorithms for Community Structure in Dynamic Networks
Ghasemian, Amir; Zhang, Pan; Clauset, Aaron; Moore, Cristopher; Peel, Leto
2016-07-01
The detection of communities within a dynamic network is a common means for obtaining a coarse-grained view of a complex system and for investigating its underlying processes. While a number of methods have been proposed in the machine learning and physics literature, we lack a theoretical analysis of their strengths and weaknesses, or of the ultimate limits on when communities can be detected. Here, we study the fundamental limits of detecting community structure in dynamic networks. Specifically, we analyze the limits of detectability for a dynamic stochastic block model where nodes change their community memberships over time, but where edges are generated independently at each time step. Using the cavity method, we derive a precise detectability threshold as a function of the rate of change and the strength of the communities. Below this sharp threshold, we claim that no efficient algorithm can identify the communities better than chance. We then give two algorithms that are optimal in the sense that they succeed all the way down to this threshold. The first uses belief propagation, which gives asymptotically optimal accuracy, and the second is a fast spectral clustering algorithm, based on linearizing the belief propagation equations. These results extend our understanding of the limits of community detection in an important direction, and introduce new mathematical tools for similar extensions to networks with other types of auxiliary information.
Institute of Scientific and Technical Information of China (English)
Mohammed A.M. Ibrahim; Lu Xinda; M. SaifMokbel
2005-01-01
The rapid growth of interconnected high performance workstations has produced a new computing paradigm called clustered of workstations computing. In these systems load balance problem is a serious impediment to achieve good performance. The main concern of this paper is the implementation of dynamic load balancing algorithm,asynchronous Round Robin (ARR), for balancing workload of parallel tree computation depth-first-search algorithm on Cluster of Heterogeneous Workstations (COW) Many algorithms in artificial intelligence and other areas of computer science are based on depth first search in implicitty defined trees. For these algorithms a loadbalancing scheme is required, which is able to evenly distribute parts of an irregularly shaped tree over the workstations with minimal interprocessor communication and without prior knowledge of the tree's shape. For the( ARR ) algorithm only minimal interpreeessor communication is needed when necessary and it runs under the MPI (Message passing interface) that allows parallel execution on heterogeneous SUN cluster of workstation platform. The program code is written in C language and executed under UNIX operating system (Solaris version).
Toh, H
1997-08-01
Two approximations were introduced into the double dynamic programming algorithm, in order to reduce the computational time for structural alignment. One of them was the so-called distance cut-off, which approximately describes the structural environment of each residue by its local environment. In the approximation, a sphere with a given radius is placed at the center of the side chain of each residue. The local environment of a residue is constituted only by the residues with side chain centers that are present within the sphere, which is expressed by a set of center-to-center distances from the side chain of the residue to those of all the other constituent residues. The residues outside the sphere are neglected from the local environment. Another approximation is associated with the distance cut-off, which is referred to here as the delta N cut-off. If two local environments are similar to each other, the numbers of residues constituting the environments are expected to be similar. The delta N cut-off was introduced based on the idea. If the difference between the numbers of the constituent residues of two local environments is greater than a given threshold value, delta N, the evaluation of the similarity between the local environments is skipped. The introduction of the two approximations dramatically reduced the computational time for structural alignment by the double dynamic programming algorithm. However, the approximations also decreased the accuracy of the alignment. To improve the accuracy with the approximations, a program with a two-step alignment algorithm was constructed. At first, an alignment was roughly constructed with the approximations. Then, the epsilon-suboptimal region for the alignment was determined. Finally, the double dynamic programming algorithm with full structural environments was applied to the residue pairs within the epsilon-suboptimal region to produce an improved alignment.
Dynamic Air-Route Adjustments - Model,Algorithm,and Sensitivity Analysis
Institute of Scientific and Technical Information of China (English)
GENG Rui; CHENG Peng; CUI Deguang
2009-01-01
Dynamic airspace management (DAM) is an important approach to extend limited air space resources by using them more efficiently and flexibly.This paper analyzes the use of the dynamic air-route adjustment (DARA) method as a core procedure in DAM systems.DARA method makes dynamic decisions on when and how to adjust the current air-route network with the minimum cost.This model differs from the air traffic flow management (ATFM) problem because it considers dynamic opening and closing of air-route segments instead of only arranging flights on a given air traffic network and it takes into account several new constraints,such as the shortest opening time constraint.The DARA problem is solved using a two-step heuristic algorithm.The sensitivities of important coefficients in the model are analyzed to determine proper values for these coefficients.The computational results based on practical data from the Beijing ATC region show that the two-step heuristic algorithm gives as good results as the CPLEX in less or equal time in most cases.
Vijay Alagappan, A.; Narasimha Rao, K. V.; Krishna Kumar, R.
2015-02-01
Tyre models are a prerequisite for any vehicle dynamics simulation. Tyre models range from the simplest mathematical models that consider only the cornering stiffness to a complex set of formulae. Among all the steady-state tyre models that are in use today, the Magic Formula tyre model is unique and most popular. Though the Magic Formula tyre model is widely used, obtaining the model coefficients from either the experimental or the simulation data is not straightforward due to its nonlinear nature and the presence of a large number of coefficients. A common procedure used for this extraction is the least-squares minimisation that requires considerable experience for initial guesses. Various researchers have tried different algorithms, namely, gradient and Newton-based methods, differential evolution, artificial neural networks, etc. The issues involved in all these algorithms are setting bounds or constraints, sensitivity of the parameters, the features of the input data such as the number of points, noisy data, experimental procedure used such as slip angle sweep or tyre measurement (TIME) procedure, etc. The extracted Magic Formula coefficients are affected by these variants. This paper highlights the issues that are commonly encountered in obtaining these coefficients with different algorithms, namely, least-squares minimisation using trust region algorithms, Nelder-Mead simplex, pattern search, differential evolution, particle swarm optimisation, cuckoo search, etc. A key observation is that not all the algorithms give the same Magic Formula coefficients for a given data. The nature of the input data and the type of the algorithm decide the set of the Magic Formula tyre model coefficients.
Analysis of limit forces on the vehicle wheels using an algorithm of Dynamic Square Method
Brukalski, M.
2016-09-01
This article presents a method named as Dynamic Square Method (DSM) used for dynamic analysis of a vehicle equipped with a four wheel drive system. This method allows determination of maximum (limit) forces acting on the wheels. Here, the maximum longitudinal forces acting on the wheels are assumed and then used to predict whether they can be achieved by a specific dynamic motion or whether the actual friction forces under a given wheel is large enough to transfer lateral forces. For the analysis of DSM a four wheel vehicle model is used. On the basis of this characteristic it is possible to determine the maximum longitudinal force acting on the wheels of the given axle depending on the lateral acceleration of the vehicle. The results of this analysis may be useful in the development of a control algorithm used for example in active differentials.
Nair, T R Gopalakrishnan; Yashoda, M B
2011-01-01
In Internet Routing, the static shortest path (SP) problem has been addressed using well known intelligent optimization techniques like artificial neural networks, genetic algorithms (GAs) and particle swarm optimization. Advancement in wireless communication lead more and more mobile wireless networks, such as mobile networks [mobile ad hoc networks (MANETs)] and wireless sensor networks. Dynamic nature of the network is the main characteristic of MANET. Therefore, the SP routing problem in MANET turns into dynamic optimization problem (DOP). Here the nodes ae made aware of the environmental condition, thereby making it intelligent, which goes as the input for GA. The implementation then uses GAs with immigrants and memory schemes to solve the dynamic SP routing problem (DSPRP) in MANETS. In our paper, once the network topology changes, the optimal solutions in the new environment can be searched using the new immigrants or the useful information stored in the memory. Results shows GA with new immigrants sho...
Fijany, Amir
1993-01-01
In this paper parallel 0(log N) algorithms for dynamic simulation of single closed-chain rigid multibody system as specialized to the case of a robot manipulatoar in contact with the environment are developed.
A regional density distribution based wide dynamic range algorithm for infrared camera systems
Park, Gyuhee; Kim, Yongsung; Joung, Shichang; Shin, Sanghoon
2014-10-01
Forward Looking InfraRed (FLIR) imaging system has been widely used for both military and civilian purposes. Military applications include target acquisition and tracking, night vision system. Civilian applications include thermal efficiency analysis, short-ranged wireless communication, weather forecasting and other various applications. The dynamic range of FLIR imaging system is larger than one of commercial display. Generally, auto gain controlling and contrast enhancement algorithm are applied to FLIR imaging system. In IR imaging system, histogram equalization and plateau equalization is generally used for contrast enhancement. However, they have no solution about the excessive enhancing when luminance histogram has been distributed in specific narrow region. In this paper, we proposed a Regional Density Distribution based Wide Dynamic Range algorithm for Infrared Camera Systems. Depending on the way of implementation, the result of WDR is quite different. Our approach is single frame type WDR algorithm for enhancing the contrast of both dark and white detail without loss of bins of histogram with real-time processing. The significant change in luminance caused by conventional contrast enhancement methods may introduce luminance saturation and failure in object tracking. Proposed method guarantees both the effective enhancing in contrast and successive object tracking. Moreover, since proposed method does not using multiple images on WDR, computation complexity might be significantly reduced in software / hardware implementation. The experimental results show that proposed method has better performance compared with conventional Contrast enhancement methods.
An Efficient Algorithm for Contact Angle Estimation in Molecular Dynamics Simulations
Directory of Open Access Journals (Sweden)
Sumith YD
2015-01-01
Full Text Available It is important to find contact angle for a liquid to understand its wetting properties, capillarity and surface interaction energy with a surface. The estimation of contact angle from Non Equilibrium Molecular Dynamics (NEMD, where we need to track the changes in contact angle over a period of time is challenging compared to the estimation from a single image from an experimental measurement. Often such molecular simulations involve finite number of molecules above some metallic or non-metallic substrates and coupled to a thermostat. The identification of profile of the droplet formed during this time will be difficult and computationally expensive to process as an image. In this paper a new algorithm is explained which can efficiently calculate time dependent contact angle from a NEMD simulation just by processing the molecular coordinates. The algorithm implements many simple yet accurate mathematical methods available, especially to remove the vapor molecules and noise data and thereby calculating the contact angle with more accuracy. To further demonstrate the capability of the algorithm a simulation study has been reported which compares the contact angle influence with different thermostats in the Molecular Dynamics (MD simulation of water over platinum surface.
DLJ：A Dynamic Line—Justification Algorithm for Test Generation
Institute of Scientific and Technical Information of China (English)
陈庆方; 魏道政
1993-01-01
Lne justification is a basic factor in affecting the efficiency of algorithms for test generation.The existence of reconvergent fanouts in the circuit under test results in backtracks in the process of line justification.In order to reduce the number of backtracks and shorten the processing time between backtracks,we present a new algorithm called DLJ(dynamic line justification)in whic two techniques are employed.1.A cost function called “FOCOST” is proposed as heuristic information to represent the cost of justifying a certain line.Whn the relations among the lines being justified are“and”,the line having the highest FOCOST should be chosen.When the relations are“or”,the line having the lowest FOCOST should be chosen.The computing of the FOCOST of lines is very simple.2.Disjoint justification cubes dynamically generated to perform backtracks make the backtrack number of the algorithm minimal.When the backtrace with cube C1 does not yield a solution,the next cube to be chosen is C'2=C2-{C1,C2}.Experimental results demonstrate that the combination of the two techniques effectively reduces the backtracks and accelerates the test generation.
Directory of Open Access Journals (Sweden)
Rogério M. Branco
2016-07-01
Full Text Available This paper discusses the application of heuristic-based evolutionary technique in search for solutions concerning the dynamic job-shop scheduling problems with dependent setup times and alternate routes. With a combinatorial nature, these problems belong to an NP-hard class, with an aggravated condition when in realistic, dynamic and therefore, more complex cases than the traditional static ones. The proposed genetic algorithm executes two important functions: choose the routes using dispatching rules when forming each individual from a defined set of available machines and, also make the scheduling for each of these individuals created. The chromosome codifies a route, or the selected machines, and also an order to process the operations. In essence , each individual needs to be decoded by the scheduler to evaluate its time of completion, so the fitness function of the genetic algorithm, applying the modified Giffler and Thomson’s algorithm, obtains a scheduling of the selected routes in a given planning horizon. The scheduler considers the preparation time between operations on the machines and can manage operations exchange respecting the route and the order given by the chromosome. The best results in the evolutionary process are individuals with routes and processing orders optimized for this type of problema.
Directory of Open Access Journals (Sweden)
Yanhua Jiang
2014-09-01
Full Text Available This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate and side slip angle, which are the two most important parameters that describe the motion of a wheeled vehicle. Additionally, the pitch angle is also considered since the planar-motion hypothesis often fails due to the dynamic characteristics of wheel suspensions and tires in real-world environments. Linearization is used to calculate a closed-form solution of the motion parameters that works as a hypothesis generator in a RAndom SAmple Consensus (RANSAC scheme to reduce the complexity in solving equations involving trigonometric. All inliers found are used to refine the winner solution through minimizing the reprojection error. Finally, the algorithm is applied to real-time on-board visual localization applications. Its performance is evaluated by comparing against the state-of-the-art monocular visual odometry methods using both synthetic data and publicly available datasets over several kilometers in dynamic outdoor environments.
Staged optimization algorithms based MAC dynamic bandwidth allocation for OFDMA-PON
Liu, Yafan; Qian, Chen; Cao, Bingyao; Dun, Han; Shi, Yan; Zou, Junni; Lin, Rujian; Wang, Min
2016-06-01
Orthogonal frequency division multiple access passive optical network (OFDMA-PON) has being considered as a promising solution for next generation PONs due to its high spectral efficiency and flexible bandwidth allocation scheme. In order to take full advantage of these merits of OFDMA-PON, a high-efficiency medium access control (MAC) dynamic bandwidth allocation (DBA) scheme is needed. In this paper, we propose two DBA algorithms which can act on two different stages of a resource allocation process. To achieve higher bandwidth utilization and ensure the equity of ONUs, we propose a DBA algorithm based on frame structure for the stage of physical layer mapping. Targeting the global quality of service (QoS) of OFDMA-PON, we propose a full-range DBA algorithm with service level agreement (SLA) and class of service (CoS) for the stage of bandwidth allocation arbitration. The performance of the proposed MAC DBA scheme containing these two algorithms is evaluated using numerical simulations. Simulations of a 15 Gbps network with 1024 sub-carriers and 32 ONUs demonstrate the maximum network throughput of 14.87 Gbps and the maximum packet delay of 1.45 ms for the highest priority CoS under high load condition.
Dias, Maluge Pubuduni Imali; Wong, Elaine
2013-04-22
In this work, we present a comparative study of two just-in-time (JIT) dynamic bandwidth allocation algorithms (DBAs), designed to improve the energy-efficiency of the 10 Gbps Ethernet passive optical networks (10G-EPONs). The algorithms, termed just-in-time with varying polling cycle times (JIT) and just-in-time with fixed polling cycle times (J-FIT), are designed to achieve energy-savings when the idle time of an optical network unit (ONU) is less than the sleep-to-active transition time. This is made possible by a vertical-cavity surface-emitting laser (VCSEL) ONU that can transit into sleep or doze modes during its idle time. We evaluate the performance of the algorithms in terms of polling cycle time, power consumption, percentage of energy-savings, and average delay. The energy-efficiency of a VCSEL ONU that can transition into sleep or doze mode is compared to an always-ON distributed feedback (DFB) laser ONU. Simulation results indicate that both JIT and J-FIT DBA algorithms result in improved energy-efficiency whilst J-FIT performs better in terms of energy-savings at low network loads. The J-FIT DBA however, results in increased average delay in comparison to the JIT DBA. Nonetheless, this increase in average delay is within the acceptable range to support the quality of service (QoS) requirements of the next-generation access networks.
A Dynamic Noise Level Algorithm for Spectral Screening of Peptide MS/MS Spectra
Directory of Open Access Journals (Sweden)
Xu Hua
2010-08-01
Full Text Available Abstract Background High-throughput shotgun proteomics data contain a significant number of spectra from non-peptide ions or spectra of too poor quality to obtain highly confident peptide identifications. These spectra cannot be identified with any positive peptide matches in some database search programs or are identified with false positives in others. Removing these spectra can improve the database search results and lower computational expense. Results A new algorithm has been developed to filter tandem mass spectra of poor quality from shotgun proteomic experiments. The algorithm determines the noise level dynamically and independently for each spectrum in a tandem mass spectrometric data set. Spectra are filtered based on a minimum number of required signal peaks with a signal-to-noise ratio of 2. The algorithm was tested with 23 sample data sets containing 62,117 total spectra. Conclusions The spectral screening removed 89.0% of the tandem mass spectra that did not yield a peptide match when searched with the MassMatrix database search software. Only 6.0% of tandem mass spectra that yielded peptide matches considered to be true positive matches were lost after spectral screening. The algorithm was found to be very effective at removal of unidentified spectra in other database search programs including Mascot, OMSSA, and X!Tandem (75.93%-91.00% with a small loss (3.59%-9.40% of true positive matches.
QoS-aware dynamic bandwidth allocation algorithm for Gigabit-capable PONS
Institute of Scientific and Technical Information of China (English)
WANG Xin; ZHAO Yang; GU Wanyi
2007-01-01
The Gigabit-capable passive optical network (GPON)technology is being considered as a promising solution for the next-generation broadband access network.Since the network topology of the GPON is point-to-multipoint,a media access control called dynamic bandwidth allocation(DBA)algorithm is an important factor for determining the performance of the GPON.In this paper,we propose a new DBA algorithm to effectively and fairly allocate bandwidths among end users.This DBA algorithm supports difierentiated services-a cmcial requirement for a converged broadband access network with heterogeneous traffic.In this article we first reviewed the signaling and configuration of the DBA,and then proposed a new DBA scheme that implemented QoS-based priority for this need to maximally satisfy the requirements of all optical network units(ONUs)and provide difierentiated services.Analyses and simulation results show that the new algorithm can improve the bandwidth utilization and realize the fairness for both different ONUs and services.
BiCAMWI: A Genetic-Based Biclustering Algorithm for Detecting Dynamic Protein Complexes.
Lakizadeh, Amir; Jalili, Saeed
2016-01-01
Considering the roles of protein complexes in many biological processes in the cell, detection of protein complexes from available protein-protein interaction (PPI) networks is a key challenge in the post genome era. Despite high dynamicity of cellular systems and dynamic interaction between proteins in a cell, most computational methods have focused on static networks which cannot represent the inherent dynamicity of protein interactions. Recently, some researchers try to exploit the dynamicity of PPI networks by constructing a set of dynamic PPI subnetworks correspondent to each time-point (column) in a gene expression data. However, many genes can participate in multiple biological processes and cellular processes are not necessarily related to every sample, but they might be relevant only for a subset of samples. So, it is more interesting to explore each subnetwork based on a subset of genes and conditions (i.e., biclusters) in a gene expression data. Here, we present a new method, called BiCAMWI to employ dynamicity in detecting protein complexes. The preprocessing phase of the proposed method is based on a novel genetic algorithm that extracts some sets of genes that are co-regulated under some conditions from input gene expression data. Each extracted gene set is called bicluster. In the detection phase of the proposed method, then, based on the biclusters, some dynamic PPI subnetworks are extracted from input static PPI network. Protein complexes are identified by applying a detection method on each dynamic PPI subnetwork and aggregating the results. Experimental results confirm that BiCAMWI effectively models the dynamicity inherent in static PPI networks and achieves significantly better results than state-of-the-art methods. So, we suggest BiCAMWI as a more reliable method for protein complex detection. PMID:27462706
Kodali, Anuradha
In this thesis, we develop dynamic multiple fault diagnosis (DMFD) algorithms to diagnose faults that are sporadic and coupled. Firstly, we formulate a coupled factorial hidden Markov model-based (CFHMM) framework to diagnose dependent faults occurring over time (dynamic case). Here, we implement a mixed memory Markov coupling model to determine the most likely sequence of (dependent) fault states, the one that best explains the observed test outcomes over time. An iterative Gauss-Seidel coordinate ascent optimization method is proposed for solving the problem. A soft Viterbi algorithm is also implemented within the framework for decoding dependent fault states over time. We demonstrate the algorithm on simulated and real-world systems with coupled faults; the results show that this approach improves the correct isolation rate as compared to the formulation where independent fault states are assumed. Secondly, we formulate a generalization of set-covering, termed dynamic set-covering (DSC), which involves a series of coupled set-covering problems over time. The objective of the DSC problem is to infer the most probable time sequence of a parsimonious set of failure sources that explains the observed test outcomes over time. The DSC problem is NP-hard and intractable due to the fault-test dependency matrix that couples the failed tests and faults via the constraint matrix, and the temporal dependence of failure sources over time. Here, the DSC problem is motivated from the viewpoint of a dynamic multiple fault diagnosis problem, but it has wide applications in operations research, for e.g., facility location problem. Thus, we also formulated the DSC problem in the context of a dynamically evolving facility location problem. Here, a facility can be opened, closed, or can be temporarily unavailable at any time for a given requirement of demand points. These activities are associated with costs or penalties, viz., phase-in or phase-out for the opening or closing of a
Directory of Open Access Journals (Sweden)
Hatm Alkadeki
2015-12-01
Full Text Available The IEEE 802.11 backoff algorithm is very important for controlling system throughput over contentionbased wireless networks. For this reason, there are many studies on wireless network performance focus on developing backoff algorithms. However, most existing models are based on saturated traffic loads, which are not a real representation of actual network conditions. In this paper, a dynamic control backoff time algorithm is proposed to enhance both delay and throughput performance of the IEEE 802.11 distributed coordination function. This algorithm considers the distinction between high and low traffic loads in order to deal with unsaturated traffic load conditions. In particular, the equilibrium point analysis model is used to represent the algorithm under various traffic load conditions. Results of extensive simulation experiments illustrate that the proposed algorithm yields better performance throughput and a better average transmission packet delay than related algorithms.
Bhole, Gaurav; Anjusha, V. S.; Mahesh, T. S.
2016-04-01
A robust control over quantum dynamics is of paramount importance for quantum technologies. Many of the existing control techniques are based on smooth Hamiltonian modulations involving repeated calculations of basic unitaries resulting in time complexities scaling rapidly with the length of the control sequence. Here we show that bang-bang controls need one-time calculation of basic unitaries and hence scale much more efficiently. By employing a global optimization routine such as the genetic algorithm, it is possible to synthesize not only highly intricate unitaries, but also certain nonunitary operations. We demonstrate the unitary control through the implementation of the optimal fixed-point quantum search algorithm in a three-qubit nuclear magnetic resonance (NMR) system. Moreover, by combining the bang-bang pulses with the crusher gradients, we also demonstrate nonunitary transformations of thermal equilibrium states into effective pure states in three- as well as five-qubit NMR systems.
Speed improvement of B-snake algorithm using dynamic programming optimization.
Charfi, Maher; Zrida, Jalel
2011-10-01
This paper presents a novel approach to contour approximation carried out by means of the B-snake algorithm and the dynamic programming (DP) optimization technique. Using the proposed strategy for contour point search procedure, computing complexity is reduced to O(N×M(2)), whereas the standard DP method has an O(N×M(4)) complexity, with N being the number of contour sample points and M being the number of candidates in the search space. The storage requirement was also decreased from N×M(3) to N×M memory elements. Some experiments on noise corrupted synthetic image, magnetic resonance, and computer tomography medical images have shown that the proposed approach results are equivalent to those obtained by the standard DP algorithm.
A DYNAMIC FAULT TOLERANT ALGORITHM FOR IMPROVISING PERFORMANCE OF MULTIMEDIA SERVICES
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Multimedia Services has drawn much attention from both industrial and academic researchers due to the emerging consumer market, how to provide High-Availability service is one of most important issues to take into account. In this paper, a dynamic fault tolerant algorithm is presented for highly available distributed multimedia service, then by introducing SLB(server load balancing) into fault tolerance and switching servers in different ways according to their functions, the proposed schema can preserve reliability and real-time of the system .The analysis and experiments indicate that resuming server's faulty by this method is smooth and transparent to the client The proposed algorithm is effectively improving the reliability of the multimedia service.
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Eskandar Gholipour
2013-02-01
Full Text Available Power-system dynamic stability improvement by a static synchronous series compensator (SSSC based damping controller is thoroughly investigated in this paper. In order to design the optimal parameters of the controller, Imperialist Competitive Algorithm (ICA is employed to search for the optimal controller parameters. Both local and remote signals are considered in the present study and the performance of the proposed controllers with variations in the signal transmission delays has been investigated. The performances of the proposed controllers are evaluated under different disturbances for both single-machine-infinite-bus and multi-machine power systems. Finally, the results of ICA method are compared with the results of Genetic Algorithm (GA.
DEFF Research Database (Denmark)
Tonelli, Oscar; Berardinelli, Gilberto; Tavares, Fernando Menezes Leitão;
2013-01-01
among the cells, a non-viable solution. Cognitive Radio (CR) and Dynamic Spectrum Access (DSA) are the research paradigms which are expected to provide the network nodes the capabilities for an autonomous and efficient selection of the spectrum resources. In this paper we present the first experimental...... activities with the Autonomous Component Carrier Selection (ACCS) algorithm, a distributed solution for interference management among small neighboring cells. A preliminary evaluation of the algorithm performance is provided considering its live execution on a software defined radio network testbed......Next generation wireless networks aim at a significant improvement of the spectral efficiency in order to meet the dramatic increase in data service demand. In local area scenarios user-deployed base stations are expected to take place, thus making the centralized planning of frequency resources...
Directory of Open Access Journals (Sweden)
Y. Li
2015-01-01
Full Text Available We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System (GNSS based radio occultation (RO measurements. The new algorithm estimates background and observation error covariance matrices with geographically-varying uncertainty profiles and realistic global-mean correlation matrices. The error covariance matrices estimated by the new approach are more accurate and realistic than in simplified existing approaches and can therefore be used in statistical optimization to provide optimal bending angle profiles for high-altitude initialization of the subsequent Abel transform retrieval of refractivity. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.6 (OPSv5.6 algorithm, using simulated data on two test days from January and July 2008 and real observed CHAMP and COSMIC measurements from the complete months of January and July 2008. The following is achieved for the new method's performance compared to OPSv5.6: (1 significant reduction in random errors (standard deviations of optimized bending angles down to about two-thirds of their size or more; (2 reduction of the systematic differences in optimized bending angles for simulated MetOp data; (3 improved retrieval of refractivity and temperature profiles; (4 produces realistically estimated global-mean correlation matrices and realistic uncertainty fields for the background and observations. Overall the results indicate high suitability for employing the new dynamic approach in the processing of long-term RO data into a reference climate record, leading to well characterized and high-quality atmospheric profiles over the entire stratosphere.
A graph based algorithm for adaptable dynamic airspace configuration for NextGen
Savai, Mehernaz P.
The National Airspace System (NAS) is a complicated large-scale aviation network, consisting of many static sectors wherein each sector is controlled by one or more controllers. The main purpose of the NAS is to enable safe and prompt air travel in the U.S. However, such static configuration of sectors will not be able to handle the continued growth of air travel which is projected to be more than double the current traffic by 2025. Under the initiative of the Next Generation of Air Transportation system (NextGen), the main objective of Adaptable Dynamic Airspace Configuration (ADAC) is that the sectors should change to the changing traffic so as to reduce the controller workload variance with time while increasing the throughput. Change in the resectorization should be such that there is a minimal increase in exchange of air traffic among controllers. The benefit of a new design (improvement in workload balance, etc.) should sufficiently exceed the transition cost, in order to deserve a change. This leads to the analysis of the concept of transition workload which is the cost associated with a transition from one sectorization to another. Given two airspace configurations, a transition workload metric which considers the air traffic as well as the geometry of the airspace is proposed. A solution to reduce this transition workload is also discussed. The algorithm is specifically designed to be implemented for the Dynamic Airspace Configuration (DAC) Algorithm. A graph model which accurately represents the air route structure and air traffic in the NAS is used to formulate the airspace configuration problem. In addition, a multilevel graph partitioning algorithm is developed for Dynamic Airspace Configuration which partitions the graph model of airspace with given user defined constraints and hence provides the user more flexibility and control over various partitions. In terms of air traffic management, vertices represent airports and waypoints. Some of the major
Genetic algorithm-fuzzy based dynamic motion planning approach for a mobile robot
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Presents the mobile robots dynamic motion planning problem with a task to find an obstacle-free route that requires minimum travel time from the start point to the destination point in a changing environment, due to the obstacle's moving. An Genetic Algorithm fuzzy(GA-Fuzzy)based optimal approach proposed to find any obstacle-free path and the GA used to select the optimal one, points ont that using this learned knowledge off line, a mobile robot can navigate to its goal point when it faces new scenario on-line. Concludes with the opti mal rule base given and the simulation results showing its effectiveness.
Binary interaction algorithms for the simulation of flocking and swarming dynamics
Albi, Giacomo
2012-01-01
Microscopic models of flocking and swarming takes in account large numbers of interacting individ- uals. Numerical resolution of large flocks implies huge computational costs. Typically for $N$ interacting individuals we have a cost of $O(N^2)$. We tackle the problem numerically by considering approximated binary interaction dynamics described by kinetic equations and simulating such equations by suitable stochastic methods. This approach permits to compute approximate solutions as functions of a small scaling parameter $\\varepsilon$ at a reduced complexity of O(N) operations. Several numerical results show the efficiency of the algorithms proposed.
An efficient dissipative particle dynamics-based algorithm for simulating electrolyte solutions
Medina, Stefan; Wang, Zhen-Gang; Schmid, Friederike
2014-01-01
We propose an efficient simulation algorithm based on the dissipative particle dynamics (DPD) method for studying electrohydrodynamic phenomena in electrolyte fluids. The fluid flow is mimicked with DPD particles while the evolution of the concentration of the ionic species is described using Brownian pseudo particles. The method is designed especially for systems with high salt concentrations, as explicit treatment of the salt ions becomes computationally expensive. For illustration, we apply the method to electro-osmotic flow over patterned, superhydrophobic surfaces. The results are in good agreement with recent theoretical predictions.
Institute of Scientific and Technical Information of China (English)
LIN Xiangguo; LIANG Yong
2005-01-01
The processing of nonlinear data was one of hot topics in surveying and mapping field in recent years.As a result, many linear methods and nonlinear methods have been developed.But the methods for processing generalized nonlinear surveying and mapping data, especially for different data types and including unknown parameters with random or nonrandom, are seldom noticed.A new algorithm model is presented in this paper for processing nonlinear dynamic multiple-period and multiple-accuracy data derived from deformation monitoring network.
Yan, Yiming; Zhang, Ye; Gao, Fengjiao
2012-12-01
This article proposes a `dynamic' artificial bee colony (D-ABC) algorithm for solving optimizing problems. It overcomes the poor performance of artificial bee colony (ABC) algorithm, when applied to multi-parameters optimization. A dynamic `activity' factor is introduced to D-ABC algorithm to speed up convergence and improve the quality of solution. This D-ABC algorithm is employed for multi-parameters optimization of support vector machine (SVM)-based soft-margin classifier. Parameter optimization is significant to improve classification performance of SVM-based classifier. Classification accuracy is defined as the objection function, and the many parameters, including `kernel parameter', `cost factor', etc., form a solution vector to be optimized. Experiments demonstrate that D-ABC algorithm has better performance than traditional methods for this optimizing problem, and better parameters of SVM are obtained which lead to higher classification accuracy.
EZDCP:A new static task scheduling algorithm with edge-zeroing based on dynamic critical paths
Institute of Scientific and Technical Information of China (English)
陈志刚; 华强胜
2003-01-01
A new static task scheduling algorithm named edge-zeroing based on dynamic critical paths is proposed.The main ideas of the algorithm are as follows: firstly suppose that all of the tasks are in different clusters; secondly, select one of the critical paths of the partially clustered directed acyclic graph; thirdly, try to zero one of graph communication edges; fourthly, repeat above three processes until all edges are zeroed; finally, check the generated clusters to see if some of them can be further merged without increasing the parallel time. Comparisons of the previous algorithms with edge-zeroing based on dynamic critical paths show that the new algorithm has not only a low complexity but also a desired performance comparable or even better on average to much higher complexity heuristic algorithms.
Dynamics of student modeling: A theory, algorithms, and application to quantum mechanics
Bao, Lei
A good understanding of how students understand physics is of great importance for developing and delivering effective instructions. This research is an attempt to develop a coherent theoretical and mathematical framework to mode the student learning of physics. The theoretical foundation is based on useful ideas from theories in cognitive science, education, and physics education. The emphasis of this research is made on the development of a mathematical representation to model the important mental elements and the dynamics of these elements, and on numerical algorithms that allow quantitative evaluations of conceptual learning in physics. In part I, a model-based theoretical framework is proposed. Based on the theory, a mathematical representation and a set of data analysis algorithms are developed. This new method is called Model Analysis, which can be used to obtain quantitative evaluations on student models with data from multiple-choice questions. Two specific algorithms are discussed with great detail. The first algorithm is the concentration factor. It measures how student responses on multiple-choice questions are distributed. A significant concentration on certain choices of the questions often implies common student models corresponding to those choices. The second algorithm analyzes student responses to form student model vectors and student model density matrix. By decomposing the density matrix, we can obtain quantitative evaluations of specific models used by students. Application examples with data from FCI, FMCE, and Wave Test are discussed along with special treatments of the data to deal with the unique features of the different tests. Implications on test design techniques are also discussed with the results from the examples. Based on the theory and algorithms developed in part I, research is conducted to investigate student understandings of quantum mechanics. Common student models on classical prerequisites and important quantum concepts are
Jain, A.; Man, G. K.
1993-01-01
This paper describes the Dynamics Algorithms for Real-Time Simulation (DARTS) real-time hardware-in-the-loop dynamics simulator for the National Aeronautics and Space Administration's Cassini spacecraft. The spacecraft model consists of a central flexible body with a number of articulated rigid-body appendages. The demanding performance requirements from the spacecraft control system require the use of a high fidelity simulator for control system design and testing. The DARTS algorithm provides a new algorithmic and hardware approach to the solution of this hardware-in-the-loop simulation problem. It is based upon the efficient spatial algebra dynamics for flexible multibody systems. A parallel and vectorized version of this algorithm is implemented on a low-cost, multiprocessor computer to meet the simulation timing requirements.
Institute of Scientific and Technical Information of China (English)
Li Yuan-xiang; Liu Dong-mei
2003-01-01
With the frequent information accesses from users to the Internet, it is important to organize and allocate information resources properly on different web servers. This paper considers the following protblem: Due to the capacity limitation of each single web server, it is impossible to put all information resources on one web server. Hence it is an important problem to put them on several different servers suchas: (1) the amount of information resources assigned on any server is less than its capacity; (2) the access bottleneck can be avoided. In order to solve the problem in which the access frequency is variable, this paper proposes a dynamic optimal modeling. Based on the computational complexity results, the paper further focuses on the genetic algorithm for solving the dynamic problem. Finally we give the simulation results and conclusions.
Inchworm Monte Carlo for exact non-adiabatic dynamics I. Theory and algorithms
Chen, Hsing-Ta; Reichman, David R
2016-01-01
In this paper we provide a detailed description of the inchworm Monte Carlo formalism for the exact study of real-time non-adiabatic dynamics. This method optimally recycles Monte Carlo information from earlier times to greatly suppress the dynamical sign problem. Using the example of the spin-boson model, we formulate the inchworm expansion in two distinct ways: The first with respect to an expansion in the system-bath coupling and the second as an expansion in the diabatic coupling. The latter approach motivates the development of a cumulant version of the inchworm Monte Carlo method, which has the benefit of improved scaling. This paper deals completely with methodology, while the companion paper provides a comprehensive comparison of the performance of the inchworm Monte Carlo algorithms to other exact methodologies as well as a discussion of the relative advantages and disadvantages of each.
An Optimized Dynamic Scene Change Detection Algorithm for H.264/AVC Encoded Video Sequences
Directory of Open Access Journals (Sweden)
Giorgio Rascioni
2010-01-01
Full Text Available Scene change detection plays an important role in a number of video applications, including video indexing, semantic features extraction, and, in general, pre- and post-processing operations. This paper deals with the design and performance evaluation of a dynamic scene change detector optimized for H.264/AVC encoded video sequences. The detector is based on a dynamic threshold that adaptively tracks different features of the video sequence, to increase the whole scheme accuracy in correctly locating true scene changes. The solution has been tested on suitable video sequences resembling real-world videos thanks to a number of different motion features, and has provided good performance without requiring an increase in decoder complexity. This is a valuable issue, considering the possible application of the proposed algorithm in post-processing operations, such as error concealment for video decoding in typical error prone video transmission environments, such as wireless networks.
Computational Fluid Dynamics Based Bulbous Bow Optimization Using a Genetic Algorithm
Institute of Scientific and Technical Information of China (English)
Shahid Mahmood; Debo Huang
2012-01-01
Computational fluid dynamics (CFD) plays a major role in predicting the flow behavior of a ship.With the development of fast computers and robust CFD software,CFD has become an important tool for designers and engineers in the ship industry.In this paper,the hull form of a ship was optimized for total resistance using CFD as a calculation tool and a genetic algorithm as an optimization tool.CFD based optimization consists of major steps involving automatic generation of geometry based on design parameters,automatic generation of mesh,automatic analysis of fluid flow to calculate the required objective/cost function,and finally an optimization tool to evaluate the cost for optimization.In this paper,integration of a genetic algorithm program,written in MATLAB,was carried out with the geometry and meshing software GAMBIT and CFD analysis software FLUENT.Different geometries of additive bulbous bow were incorporated in the original hull based on design parameters.These design variables were optimized to achieve a minimum cost function of “total resistance”.Integration of a genetic algorithm with CFD tools proves to be effective for hull form optimization.
Andrade, Andre; Costa, Marcelo; Paolucci, Leopoldo; Braga, Antônio; Pires, Flavio; Ugrinowitsch, Herbert; Menzel, Hans-Joachim
2015-01-01
The aim of this study was to present a new training algorithm using artificial neural networks called multi-objective least absolute shrinkage and selection operator (MOBJ-LASSO) applied to the classification of dynamic gait patterns. The movement pattern is identified by 20 characteristics from the three components of the ground reaction force which are used as input information for the neural networks in gender-specific gait classification. The classification performance between MOBJ-LASSO (97.4%) and multi-objective algorithm (MOBJ) (97.1%) is similar, but the MOBJ-LASSO algorithm achieved more improved results than the MOBJ because it is able to eliminate the inputs and automatically select the parameters of the neural network. Thus, it is an effective tool for data mining using neural networks. From 20 inputs used for training, MOBJ-LASSO selected the first and second peaks of the vertical force and the force peak in the antero-posterior direction as the variables that classify the gait patterns of the different genders.
An Analytical Measuring Rectification Algorithm of Monocular Systems in Dynamic Environment
Directory of Open Access Journals (Sweden)
Deshi Li
2016-01-01
Full Text Available Range estimation is crucial for maintaining a safe distance, in particular for vision navigation and localization. Monocular autonomous vehicles are appropriate for outdoor environment due to their mobility and operability. However, accurate range estimation using vision system is challenging because of the nonholonomic dynamics and susceptibility of vehicles. In this paper, a measuring rectification algorithm for range estimation under shaking conditions is designed. The proposed method focuses on how to estimate range using monocular vision when a shake occurs and the algorithm only requires the pose variations of the camera to be acquired. Simultaneously, it solves the problem of how to assimilate results from different kinds of sensors. To eliminate measuring errors by shakes, we establish a pose-range variation model. Afterwards, the algebraic relation between distance increment and a camera’s poses variation is formulated. The pose variations are presented in the form of roll, pitch, and yaw angle changes to evaluate the pixel coordinate incensement. To demonstrate the superiority of our proposed algorithm, the approach is validated in a laboratory environment using Pioneer 3-DX robots. The experimental results demonstrate that the proposed approach improves in the range accuracy significantly.
Directory of Open Access Journals (Sweden)
P.Nirmala
2014-08-01
Full Text Available In this paper, an optimal design of FIR filter is carried out using a “Dynamic Regional Harmony Search algorithm (DRHS with Opposition and Local Learning”. The Harmony Search (HS is a robust optimization algorithm which mimics the musician’s improvisation method and has been used by many researchers for solving and optimizing various real-world optimization problems and numerical solutions. For optimizing the functionality of the FIR filter, DRHS algorithm which is an enhanced variant of the HS algorithm is adopted to avoid pre-mature convergence and stagnation. BY adopting DRHS algorithm the low pass, high pass, band pass and band stop FIR filters are constructed and their performances are evaluated and compared with the other existing optimization techniques. A comparison of the DRHS with other optimization algorithms for constructing FIR filter clearly shows the DRHS finds the optimal solution and the convergence is clearly guaranteed.
Directory of Open Access Journals (Sweden)
Mohammad Abaee Shoushtary
2014-01-01
Full Text Available This paper describes a new hybrid algorithm extracted from honey bee mating optimization (HBMO algorithm (for robot travelling distance minimization and tabu list technique (for obstacle avoidance for team robot system. This algorithm was implemented in a C++ programming language on a Pentium computer and simulated on simple cylindrical robots in a simulation software. The environment in this simulation was dynamic with moving obstacles and goals. The results of simulation have shown validity and reliability of new algorithm. The outcomes of simulation have shown better performance than ACO and PSO algorithm (society, nature algorithms with respect to two well-known metrics included, ATPD (average total path deviation and AUTD (average uncovered target distance.
A matrix product algorithm for stochastic dynamics on locally tree-like graphs
Barthel, Thomas; de Bacco, Caterina; Franz, Silvio
In this talk, I describe a novel algorithm for the efficient simulation of generic stochastic dynamics of classical degrees of freedom defined on the vertices of locally tree-like graphs. Such models correspond for example to spin-glass systems, Boolean networks, neural networks, or other technological, biological, and social networks. Building upon the cavity method and ideas from quantum many-body theory, the algorithm is based on a matrix product approximation of the so-called edge messages - conditional probabilities of vertex variable trajectories. The matrix product edge messages (MPEM) are constructed recursively. Computation costs and accuracy can be tuned by controlling the matrix dimensions of the MPEM in truncations. In contrast to Monte Carlo simulations, the approach has a better error scaling and works for both, single instances as well as the thermodynamic limit. Due to the absence of cancellation effects, observables with small expectation values can be evaluated accurately, allowing for the study of decay processes and temporal correlations with unprecedented accuracy. The method is demonstrated for the prototypical non-equilibrium Glauber dynamics of an Ising spin system. Reference: arXiv:1508.03295.
Graph Theoretic Foundations of Multibody Dynamics Part II: Analysis and Algorithms.
Jain, Abhinandan
2011-10-01
This second, of a two part paper, uses concepts from graph theory to obtain a deeper understanding of the mathematical foundations of multibody dynamics. The first part [7] established the block-weighted adjacency (BWA) matrix structure of spatial operators associated with serial and tree topology multibody system dynamics, and introduced the notions of spatial kernel operators (SKO) and spatial propagation operators (SPO). This paper builds upon these connections to show that key analytical results and computational algorithms are a direct consequence of these structural properties and require minimal assumptions about the specific nature of the underlying multibody system. We formalize this notion by introducing the notion of SKO models for general tree-topology multibody systems. We show that key analytical results, including mass matrix factorization, inversion, and decomposition hold for all SKO models. It is also shown that key low-order scatter/gather recursive computational algorithms follow directly from these abstract-level analytical results. Application examples to illustrate the concrete application of these general results are provided. The paper also describes a general recipe for developing SKO models. The abstract nature of SKO models allows the application of these techniques to a very broad class of multibody systems. PMID:22102791
FPGA implementation of dynamic channel assignment algorithm for cognitive wireless sensor networks
Martínez, Daniela M.; Andrade, Ángel G.
2015-07-01
The reliability of wireless sensor networks (WSNs) in industrial applications can be thwarted due to multipath fading, noise generated by industrial equipment or heavy machinery and particularly by the interference generated from other wireless devices operating in the same spectrum band. Recently, cognitive WSNs (CWSNs) were proposed to improve the performance and reliability of WSNs in highly interfered and noisy environments. In this class of WSN, the nodes are spectrum aware, that is, they monitor the radio spectrum to find channels available for data transmission and dynamically assign and reassign nodes to low-interference condition channels. In this work, we present the implementation of a channel assignment algorithm in a field-programmable gate array, which dynamically assigns channels to sensor nodes based on the interference and noise levels experimented in the network. From the results obtained from the performance evaluation of the CWSN when the channel assignment algorithm is considered, it is possible to identify how many channels should be available in the network in order to achieve a desired percentage of successful transmissions, subject to constraints on the signal-to-interference plus noise ratio on each active link.
Zhang, Sheng-Fei; Xu, Jun-Bo; Wen, Hao; Bhattacharjee, Subir
2011-08-01
Heavy crude oil consists of thousands of compounds, a significant fraction of which have fairly large molecular weights and complex structures. Our work aims at constructing a meso-scale platform to explore this complex fluid in terms of microstructure, phase behavior, stability and rheology. In the present study, we focus on the treatment of the structures of fused aromatic rings as rigid body fragments in fractions such as asphaltenes and resins. To derive the rotational motion of rigid bodies in a non-conservative force field, we conduct a comparison of three rigid body rotational algorithms integrated into a standard dissipative particle dynamics (DPD) simulation. The simulation results confirm the superiority of the Quaternion method. To ease any doubt concerning the introduction of rigid bodies into DPD, the performance of the Quaternion method was tested carefully. Finally, the aggregation dynamics of asphaltene in very diluted toluene was investigated. The nanoaggregates are found to experience forming, breaking up and reforming. The sizes of the asphaltene monomer and nanoaggregate are identified. The diffusion coefficient of diluted asphaltene in toluene is similar to that found experimentally. All these results verify the rotational algorithm and encourage us to extend this platform to study the rheological and colloidal characteristics of heavy crude oils in the future.
Renison, C Alicia; Fernandes, Kyle D; Naidoo, Kevin J
2015-07-01
This article describes an extension of the quantum supercharger library (QSL) to perform quantum mechanical (QM) gradient and optimization calculations as well as hybrid QM and molecular mechanical (QM/MM) molecular dynamics simulations. The integral derivatives are, after the two-electron integrals, the most computationally expensive part of the aforementioned calculations/simulations. Algorithms are presented for accelerating the one- and two-electron integral derivatives on a graphical processing unit (GPU). It is shown that a Hartree-Fock ab initio gradient calculation is up to 9.3X faster on a single GPU compared with a single central processing unit running an optimized serial version of GAMESS-UK, which uses the efficient Schlegel method for s- and l-orbitals. Benchmark QM and QM/MM molecular dynamics simulations are performed on cellobiose in vacuo and in a 39 Å water sphere (45 QM atoms and 24843 point charges, respectively) using the 6-31G basis set. The QSL can perform 9.7 ps/day of ab initio QM dynamics and 6.4 ps/day of QM/MM dynamics on a single GPU in full double precision. © 2015 Wiley Periodicals, Inc. PMID:25975864
A Dynamic Health Assessment Approach for Shearer Based on Artificial Immune Algorithm
Directory of Open Access Journals (Sweden)
Zhongbin Wang
2016-01-01
Full Text Available In order to accurately identify the dynamic health of shearer, reducing operating trouble and production accident of shearer and improving coal production efficiency further, a dynamic health assessment approach for shearer based on artificial immune algorithm was proposed. The key technologies such as system framework, selecting the indicators for shearer dynamic health assessment, and health assessment model were provided, and the flowchart of the proposed approach was designed. A simulation example, with an accuracy of 96%, based on the collected data from industrial production scene was provided. Furthermore, the comparison demonstrated that the proposed method exhibited higher classification accuracy than the classifiers based on back propagation-neural network (BP-NN and support vector machine (SVM methods. Finally, the proposed approach was applied in an engineering problem of shearer dynamic health assessment. The industrial application results showed that the paper research achievements could be used combining with shearer automation control system in fully mechanized coal face. The simulation and the application results indicated that the proposed method was feasible and outperforming others.
A Dynamic Health Assessment Approach for Shearer Based on Artificial Immune Algorithm.
Wang, Zhongbin; Xu, Xihua; Si, Lei; Ji, Rui; Liu, Xinhua; Tan, Chao
2016-01-01
In order to accurately identify the dynamic health of shearer, reducing operating trouble and production accident of shearer and improving coal production efficiency further, a dynamic health assessment approach for shearer based on artificial immune algorithm was proposed. The key technologies such as system framework, selecting the indicators for shearer dynamic health assessment, and health assessment model were provided, and the flowchart of the proposed approach was designed. A simulation example, with an accuracy of 96%, based on the collected data from industrial production scene was provided. Furthermore, the comparison demonstrated that the proposed method exhibited higher classification accuracy than the classifiers based on back propagation-neural network (BP-NN) and support vector machine (SVM) methods. Finally, the proposed approach was applied in an engineering problem of shearer dynamic health assessment. The industrial application results showed that the paper research achievements could be used combining with shearer automation control system in fully mechanized coal face. The simulation and the application results indicated that the proposed method was feasible and outperforming others.
Al-Jabr, Ahmad Ali
2013-01-01
This paper presents methods of simulating gain media in the finite difference time-domain (FDTD) algorithm utilizing a generalized polarization formulation. The gain can be static or dynamic. For static gain, Lorentzian and non-Lorentzian models are presented and tested. For the dynamic gain, rate equations for two-level and four-level models are incorporated in the FDTD scheme. The simulation results conform with the expected behavior of wave amplification and dynamic population inversion.
Energy Technology Data Exchange (ETDEWEB)
Shimojo, Fuyuki; Hattori, Shinnosuke [Collaboratory for Advanced Computing and Simulations, Department of Physics and Astronomy, Department of Computer Science, and Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California 90089-0242 (United States); Department of Physics, Kumamoto University, Kumamoto 860-8555 (Japan); Kalia, Rajiv K.; Mou, Weiwei; Nakano, Aiichiro; Nomura, Ken-ichi; Rajak, Pankaj; Vashishta, Priya [Collaboratory for Advanced Computing and Simulations, Department of Physics and Astronomy, Department of Computer Science, and Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California 90089-0242 (United States); Kunaseth, Manaschai [Collaboratory for Advanced Computing and Simulations, Department of Physics and Astronomy, Department of Computer Science, and Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California 90089-0242 (United States); National Nanotechnology Center, Pathumthani 12120 (Thailand); Ohmura, Satoshi [Collaboratory for Advanced Computing and Simulations, Department of Physics and Astronomy, Department of Computer Science, and Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California 90089-0242 (United States); Department of Physics, Kumamoto University, Kumamoto 860-8555 (Japan); Department of Physics, Kyoto University, Kyoto 606-8502 (Japan); Shimamura, Kohei [Collaboratory for Advanced Computing and Simulations, Department of Physics and Astronomy, Department of Computer Science, and Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California 90089-0242 (United States); Department of Physics, Kumamoto University, Kumamoto 860-8555 (Japan); Department of Applied Quantum Physics and Nuclear Engineering, Kyushu University, Fukuoka 819-0395 (Japan)
2014-05-14
We introduce an extension of the divide-and-conquer (DC) algorithmic paradigm called divide-conquer-recombine (DCR) to perform large quantum molecular dynamics (QMD) simulations on massively parallel supercomputers, in which interatomic forces are computed quantum mechanically in the framework of density functional theory (DFT). In DCR, the DC phase constructs globally informed, overlapping local-domain solutions, which in the recombine phase are synthesized into a global solution encompassing large spatiotemporal scales. For the DC phase, we design a lean divide-and-conquer (LDC) DFT algorithm, which significantly reduces the prefactor of the O(N) computational cost for N electrons by applying a density-adaptive boundary condition at the peripheries of the DC domains. Our globally scalable and locally efficient solver is based on a hybrid real-reciprocal space approach that combines: (1) a highly scalable real-space multigrid to represent the global charge density; and (2) a numerically efficient plane-wave basis for local electronic wave functions and charge density within each domain. Hybrid space-band decomposition is used to implement the LDC-DFT algorithm on parallel computers. A benchmark test on an IBM Blue Gene/Q computer exhibits an isogranular parallel efficiency of 0.984 on 786 432 cores for a 50.3 × 10{sup 6}-atom SiC system. As a test of production runs, LDC-DFT-based QMD simulation involving 16 661 atoms is performed on the Blue Gene/Q to study on-demand production of hydrogen gas from water using LiAl alloy particles. As an example of the recombine phase, LDC-DFT electronic structures are used as a basis set to describe global photoexcitation dynamics with nonadiabatic QMD (NAQMD) and kinetic Monte Carlo (KMC) methods. The NAQMD simulations are based on the linear response time-dependent density functional theory to describe electronic excited states and a surface-hopping approach to describe transitions between the excited states. A series of
Shimojo, Fuyuki; Hattori, Shinnosuke; Kalia, Rajiv K.; Kunaseth, Manaschai; Mou, Weiwei; Nakano, Aiichiro; Nomura, Ken-ichi; Ohmura, Satoshi; Rajak, Pankaj; Shimamura, Kohei; Vashishta, Priya
2014-05-01
We introduce an extension of the divide-and-conquer (DC) algorithmic paradigm called divide-conquer-recombine (DCR) to perform large quantum molecular dynamics (QMD) simulations on massively parallel supercomputers, in which interatomic forces are computed quantum mechanically in the framework of density functional theory (DFT). In DCR, the DC phase constructs globally informed, overlapping local-domain solutions, which in the recombine phase are synthesized into a global solution encompassing large spatiotemporal scales. For the DC phase, we design a lean divide-and-conquer (LDC) DFT algorithm, which significantly reduces the prefactor of the O(N) computational cost for N electrons by applying a density-adaptive boundary condition at the peripheries of the DC domains. Our globally scalable and locally efficient solver is based on a hybrid real-reciprocal space approach that combines: (1) a highly scalable real-space multigrid to represent the global charge density; and (2) a numerically efficient plane-wave basis for local electronic wave functions and charge density within each domain. Hybrid space-band decomposition is used to implement the LDC-DFT algorithm on parallel computers. A benchmark test on an IBM Blue Gene/Q computer exhibits an isogranular parallel efficiency of 0.984 on 786 432 cores for a 50.3 × 106-atom SiC system. As a test of production runs, LDC-DFT-based QMD simulation involving 16 661 atoms is performed on the Blue Gene/Q to study on-demand production of hydrogen gas from water using LiAl alloy particles. As an example of the recombine phase, LDC-DFT electronic structures are used as a basis set to describe global photoexcitation dynamics with nonadiabatic QMD (NAQMD) and kinetic Monte Carlo (KMC) methods. The NAQMD simulations are based on the linear response time-dependent density functional theory to describe electronic excited states and a surface-hopping approach to describe transitions between the excited states. A series of techniques
Directory of Open Access Journals (Sweden)
H.Z. Igamberdiyev
2014-07-01
Full Text Available Dynamic systems condition estimation regularization algorithms in the conditions of signals and hindrances statistical characteristics aprioristic uncertainty are offered. Regular iterative algorithms of strengthening matrix factor elements of the Kalman filter, allowing to adapt the filter to changing hindrance-alarm conditions are developed. Steady adaptive estimation algorithms of a condition vector in the aprioristic uncertainty conditions of covariance matrixes of object noise and the measurements hindrances providing a certain roughness of filtration process in relation to changing statistical characteristics of signals information parameters are offered. Offered practical realization results of the dynamic systems condition estimation algorithms are given at the adaptive management systems synthesis problems solution by technological processes of granulation drying of an ammophos pulp and receiving ammonia.
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; Chen, Cong;
2016-01-01
The approach in this paper hads been developed to optimize the cable connection layout of large scale offshore wind farms. The objective is to minimize the Levelised Production Cost (LPC) og an offshore wind farm by optimizing the cable connection configuration. Based on the minimum spanning tree...... (MST) algorithm, an improved algorithm, the Dynamic Minimum Spanning Tree (DMST) algorithm is proposed. The current carrying capacity of the cable is considered to be the main constraint and the cable sectional area is changed dynamically. An irregular shaped wind farm is chosen as the studie case...... and the results are compared with the layout obtained by a traditional MST algorithm. Simulation results show that the proposed method is an effective way for offshore wind farm collection system layout design....
Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects
Mandal, Saptarshi
2016-01-01
Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1) participants interrogate dynamic multielement objects that can overlap on the display and (2) visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were addressed by (1) developing dynamic areas of interests (AOIs) in the form of either convex or rectangular shapes to represent the moving and shape-changing multielement objects, (2) introducing the concept of AOI gap tolerance (AGT) that controls the size of the AOIs to address the overlapping and visual angle error issues, and (3) finding a near optimal AGT value. The approach was tested in the context of air traffic control (ATC) operations where air traffic controller specialists (ATCSs) interrogated multiple moving aircraft on a radar display to detect and control the aircraft for the purpose of maintaining safe and expeditious air transportation. In addition, we show how eye tracking analysis results can differ based on how we define dynamic AOIs to determine eye fixations on moving objects. The results serve as a framework to more accurately analyze eye tracking data and to better support the analysis of human performance. PMID:27725830
Energy Technology Data Exchange (ETDEWEB)
Madduri, Kamesh; Bader, David A.
2009-02-15
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication traffic, and scientific computing can be intuitively modeled as graphs. We present the first study of novel high-performance combinatorial techniques for analyzing large-scale information networks, encapsulating dynamic interaction data in the order of billions of entities. We present new data structures to represent dynamic interaction networks, and discuss algorithms for processing parallel insertions and deletions of edges in small-world networks. With these new approaches, we achieve an average performance rate of 25 million structural updates per second and a parallel speedup of nearly28 on a 64-way Sun UltraSPARC T2 multicore processor, for insertions and deletions to a small-world network of 33.5 million vertices and 268 million edges. We also design parallel implementations of fundamental dynamic graph kernels related to connectivity and centrality queries. Our implementations are freely distributed as part of the open-source SNAP (Small-world Network Analysis and Partitioning) complex network analysis framework.
Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects
Directory of Open Access Journals (Sweden)
Ziho Kang
2016-01-01
Full Text Available Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1 participants interrogate dynamic multielement objects that can overlap on the display and (2 visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were addressed by (1 developing dynamic areas of interests (AOIs in the form of either convex or rectangular shapes to represent the moving and shape-changing multielement objects, (2 introducing the concept of AOI gap tolerance (AGT that controls the size of the AOIs to address the overlapping and visual angle error issues, and (3 finding a near optimal AGT value. The approach was tested in the context of air traffic control (ATC operations where air traffic controller specialists (ATCSs interrogated multiple moving aircraft on a radar display to detect and control the aircraft for the purpose of maintaining safe and expeditious air transportation. In addition, we show how eye tracking analysis results can differ based on how we define dynamic AOIs to determine eye fixations on moving objects. The results serve as a framework to more accurately analyze eye tracking data and to better support the analysis of human performance.
Siberia snow depth climatology derived from SSM/I data using a combined dynamic and static algorithm
Grippa, M.; Mognard, N.; Le, Toan T.; Josberger, E.G.
2004-01-01
One of the major challenges in determining snow depth (SD) from passive microwave measurements is to take into account the spatiotemporal variations of the snow grain size. Static algorithms based on a constant snow grain size cannot provide accurate estimates of snow pack thickness, particularly over large regions where the snow pack is subjected to big spatial temperature variations. A recent dynamic algorithm that accounts for the dependence of the microwave scattering on the snow grain size has been developed to estimate snow depth from the Special Sensor Microwave/Imager (SSM/I) over the Northern Great Plains (NGP) in the US. In this paper, we develop a combined dynamic and static algorithm to estimate snow depth from 13 years of SSM/I observations over Central Siberia. This region is characterised by extremely cold surface air temperatures and by the presence of permafrost that significantly affects the ground temperature. The dynamic algorithm is implemented to take into account these effects and it yields accurate snow depths early in the winter, when thin snowpacks combine with cold air temperatures to generate rapid crystal growth. However, it is not applicable later in the winter when the grain size growth slows. Combining the dynamic algorithm to a static algorithm, with a temporally constant but spatially varying coefficient, we obtain reasonable snow depth estimates throughout the entire snow season. Validation is carried out by comparing the satellite snow depth monthly averages to monthly climatological data. We show that the location of the snow depth maxima and minima is improved when applying the combined algorithm, since its dynamic portion explicitly incorporate the thermal gradient through the snowpack. The results obtained are presented and evaluated for five different vegetation zones of Central Siberia. Comparison with in situ measurements is also shown and discussed. ?? 2004 Elsevier Inc. All rights reserved.
Maes, K.; Iliopoulos, A.; Weijtjens, W.; Devriendt, C.; Lombaert, G.
2016-08-01
Offshore wind turbines are exposed to continuous wind and wave excitation. The monitoring of high periodic strains at critical locations is important to assess the remaining lifetime of the structure. At some critical locations below the water level, direct measurements of the strains are not feasible. Response estimation techniques can then be used to estimate the strains from a limited set of response measurements and a system model. This paper compares a Kalman filtering algorithm, a joint input-state estimation algorithm, and a modal expansion algorithm, for the estimation of dynamic strains in the tower of an offshore monopile wind turbine. The algorithms make use of a model of the structure and a limited number of response measurements for the prediction of the strain responses. The strain signals obtained from the response estimation algorithms are compared to the actual measured strains in the tower.
International Nuclear Information System (INIS)
A chaotic sequence based differential evolution (DE) approach for solving the dynamic economic dispatch problem (DEDP) with valve-point effect is presented in this paper. The proposed method combines the DE algorithm with the local search technique to improve the performance of the algorithm. DE is the main optimizer, while an approximated model for local search is applied to fine tune in the solution of the DE run. To accelerate convergence of DE, a series of constraints handling rules are adopted. An initial population obtained by using chaotic sequence exerts optimal performance of the proposed algorithm. The combined algorithm is validated for two test systems consisting of 10 and 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. The proposed combined method outperforms other algorithms reported in literatures for DEDP considering valve-point effects.
AbouEisha, Hassan M.
2014-06-06
In this paper we present a dynamic programming algorithm for finding optimal elimination trees for computational grids refined towards point or edge singularities. The elimination tree is utilized to guide the multi-frontal direct solver algorithm. Thus, the criterion for the optimization of the elimination tree is the computational cost associated with the multi-frontal solver algorithm executed over such tree. We illustrate the paper with several examples of optimal trees found for grids with point, isotropic edge and anisotropic edge mixed with point singularity. We show the comparison of the execution time of the multi-frontal solver algorithm with results of MUMPS solver with METIS library, implementing the nested dissection algorithm.
A Fair Dynamic Quantum Algorithm%一种公平的动态轮转算法
Institute of Scientific and Technical Information of China (English)
胡赛; 赵碧海; 熊慧军
2012-01-01
时间片轮转算法作为一种经典的调度算法得到了广泛的应用.针对时间片轮转算法的调度策略和时间片长度的选取等问题开展深入的研究,提出了一种改进的动态轮转算法,算法是短作业优先算法、多级队列算法和时间片轮转算法的综合和发展.利用生灭过程理论建立了时间片轮转算法和动态轮转算法的性能模型,分析了两种算法的平均等待时间和平均周转时间,引入性能提高百分比的概念对比两种算法的差异.实验结果和理论分析均表明改进算法的性能优于传统的时间片轮转算法.%As a classic scheduling algorithm, round robin algorithm has been widely applied. According to the scheduling policy and the selection of the length of time slice for the round robin algorithm, a large number of in-depth studies are carried out. An improved dynamic quantum algorithm is proposed. The algorithm is the development and integration of shortest job first algorithm, multi-level queue scheduling algorithm and round robin algorithm. The performance models of the round robin algorithm and the dynamic quantum algorithm are built by using the theory of birth-death process, including average waiting time and average turnaround time of the two algorithms. The concept of performance improvement percentage is introduced in order to show the differences between the two algorithms. Both theoretical analysis and experimental results indicate that the performance of the improved algorithm is better than the traditional algorithm. The advantages of the improved algorithm become more obviously when the number of tasks increase and the rate of service improves.
Institute of Scientific and Technical Information of China (English)
王雅琳; 陈冬冬; 陈晓方; 蔡国民; 阳春华
2015-01-01
Region partition (RP) is the key technique to the finite element parallel computing (FEPC), and its performance has a decisive influence on the entire process of analysis and computation. The performance evaluation index of RP method for the three-dimensional finite element model (FEM) has been given. By taking the electric field of aluminum reduction cell (ARC) as the research object, the performance of two classical RP methods, which are Al-NASRA and NGUYEN partition (ANP) algorithm and the multi-level partition (MLP) method, has been analyzed and compared. The comparison results indicate a sound performance of ANP algorithm, but to large-scale models, the computing time of ANP algorithm increases notably. This is because the ANP algorithm determines only one node based on the minimum weight and just adds the elements connected to the node into the sub-region during each iteration. To obtain the satisfied speed and the precision, an improved dynamic self-adaptive ANP (DSA-ANP) algorithm has been proposed. With consideration of model scale, complexity and sub-RP stage, the improved algorithm adaptively determines the number of nodes and selects those nodes with small enough weight, and then dynamically adds these connected elements. The proposed algorithm has been applied to the finite element analysis (FEA) of the electric field simulation of ARC. Compared with the traditional ANP algorithm, the computational efficiency of the proposed algorithm has been shortened approximately from 260 s to 13 s. This proves the superiority of the improved algorithm on computing time performance.
Metric-tensor flexible-cell algorithm for isothermal-isobaric molecular dynamics simulations
Hernández, E
2001-01-01
An extended Hamiltonian approach to conduct isothermal-isobaric molecular dynamics simulations with full cell flexibility is presented. The components of the metric tensor are used as the fictitious degrees of freedom for the cell, thus avoiding the problem of spurious cell rotations and artificial symmetry breaking effects present in the original Parrinello-Rahman scheme. This is complemented by the Nose-Poincare approach for isothermal sampling. The combination of these two approaches leads to equations of motion that are Hamiltonian in structure, and which can therefore be solved numerically using recently developed powerful symplectic integrators. One such integrator, the generalised leap-frog, is employed to provide a numerical algorithm for integrating the isothermal-isobaric equations of motion obtained.
Muda, Lindasalwa; Elamvazuthi, I
2010-01-01
Digital processing of speech signal and voice recognition algorithm is very important for fast and accurate automatic voice recognition technology. The voice is a signal of infinite information. A direct analysis and synthesizing the complex voice signal is due to too much information contained in the signal. Therefore the digital signal processes such as Feature Extraction and Feature Matching are introduced to represent the voice signal. Several methods such as Liner Predictive Predictive Coding (LPC), Hidden Markov Model (HMM), Artificial Neural Network (ANN) and etc are evaluated with a view to identify a straight forward and effective method for voice signal. The extraction and matching process is implemented right after the Pre Processing or filtering signal is performed. The non-parametric method for modelling the human auditory perception system, Mel Frequency Cepstral Coefficients (MFCCs) are utilize as extraction techniques. The non linear sequence alignment known as Dynamic Time Warping (DTW) intro...
Parameter Matching Analysis of Hydraulic Hybrid Excavators Based on Dynamic Programming Algorithm
Directory of Open Access Journals (Sweden)
Wei Shen
2013-01-01
Full Text Available In order to meet the energy saving requirement of the excavator, hybrid excavators are becoming the hot spot for researchers. The initial problem is to match the parameter of each component, because the system is tending to be more complicated due to the introduction of the accumulator. In this paper, firstly, a new architecture is presented which is hydraulic hybrid excavator based on common pressure rail combined switched function (HHES. Secondly, the general principle of dynamic programming algorithm (DPA is explained. Then, the method by using DPA for parameter matching of HHES is described in detail. Furthermore, the DPA is translated into the M language for simulation. Finally, the calculation results are analyzed, and the optimal matching group is obtained.
An Evolutionary Algorithm Approach to Link Prediction in Dynamic Social Networks
Bliss, Catherine A; Danforth, Christopher M; Dodds, Peter Sheridan
2013-01-01
Many real world, complex phenomena have underlying structures of evolving networks where nodes and links are added and removed over time. A central scientific challenge is the description and explanation of network dynamics, with a key test being the prediction of short and long term changes. For the problem of short-term link prediction, existing methods attempt to determine neighborhood metrics that correlate with the appearance of a link in the next observation period. Recent work has suggested that the incorporation of user-specific metadata and usage patterns can improve link prediction, however methodologies for doing so in a systematic way are largely unexplored in the literature. Here, we provide an approach to predicting future links by applying an evolutionary algorithm to weights which are used in a linear combination of sixteen neighborhood and node similarity indices. We examine Twitter reciprocal reply networks constructed at the time scale of weeks, both as a test of our general method and as a...
Tang, Yu-Hang
2013-01-01
We present a scalable dissipative particle dynamics simulation code, fully implemented on the Graphics Processing Units (GPUs) using a hybrid CUDA/MPI programming model, which achieves 10-30 times speedup on a single GPU over 16 CPU cores and almost linear weak scaling across a thousand nodes. A unified framework is developed within which the efficient generation of the neighbor list and maintaining particle data locality are addressed. Our algorithm generates strictly ordered neighbor lists in parallel, while the construction is deterministic and makes no use of atomic operations or sorting. Such neighbor list leads to optimal data loading efficiency when combined with a two-level particle reordering scheme. A faster in situ generation scheme for Gaussian random numbers is proposed using precomputed binary signatures. We designed custom transcendental functions that are fast and accurate for evaluating the pairwise interaction. The correctness and accuracy of the code is verified through a set of test cases ...
A Dynamic Algorithm for Facilitated Charging of Plug-In Electric Vehicles
Taheri, Nicole; Ye, Yinyu
2011-01-01
Plug-in Electric Vehicles (PEVs) are a rapidly developing technology that can reduce greenhouse gas emissions and change the way vehicles obtain power. PEV charging stations will most likely be available at home and at work, and occasionally be publicly available, offering flexible charging options. Ideally, each vehicle will charge during periods when electricity prices are relatively low, to minimize the cost to the consumer and maximize societal benefits. A Demand Response (DR) service for a fleet of PEVs could yield such charging schedules by regulating consumer electricity use during certain time periods, in order to meet an obligation to the market. We construct an automated DR mechanism for a fleet of PEVs that facilitates vehicle charging to ensure the demands of the vehicles and the market are met. Our dynamic algorithm depends only on the knowledge of a few hundred driving behaviors from a previous similar day, and uses a simple adjusted pricing scheme to instantly assign feasible and satisfactory c...
Comprehensive proton dose algorithm using pencil beam redefinition and recursive dynamic splitting
Gottschalk, Bernard
2016-01-01
We compute, from first principles, the absolute dose or fluence distribution per incident proton charge in a known heterogeneous terrain exposed to known proton beams. The algorithm is equally amenable to scattered or scanned beams. All objects in the terrain (including collimators) are sliced into slabs, of any convenient thickness, perpendicular to the nominal beam direction. Transport is by standard Fermi-Eyges theory. Transverse heterogeneities are handled by breaking up pencil beams (PBs) either by conventional redefinition or a new form of 2D recursive dynamic splitting: the mother PB is replaced, conserving emittance and charge, by seven daughters of equal transverse size. One has 1/4 the charge and travels in the mother's direction and six have 1/8 the charge, are arranged hexagonally and radiate from the mother's virtual point source. The longitudinal (energy-like) variable is pv (proton momentum times speed). Each material encountered is treated on its own merits, not referenced to water. Slowing do...
A novel dynamic frame rate control algorithm for H.264 low-bit-rate video coding
Institute of Scientific and Technical Information of China (English)
Yang Jing; Fang Xiangzhong
2007-01-01
The goal of this paper is to improve human visual perceptual quality as well as coding efficiency of H.264 video at low bit rate conditions by adaptively adjusting the number of skipped frames. The encoding frames ale selected according to the motion activity of each frame and the motion accumulation of successive frames. The motion activity analysis is based on the statistics of motion vectors and with consideration of the characteristics of H. 264 coding standard. A prediction model of motion accumulation is proposed to reduce complex computation of motion estimation. The dynamic encoding frame rate control algorithm is applied to both the frame level and the GOB (Group of Macroblocks) level. Simulation is done to compare the performance of JM76 with the proposed frame level scheme and GOB level scheme.
Directory of Open Access Journals (Sweden)
Saraiva J. T.
2012-10-01
Full Text Available The basic objective of Transmission Expansion Planning (TEP is to schedule a number of transmission projects along an extended planning horizon minimizing the network construction and operational costs while satisfying the requirement of delivering power safely and reliably to load centres along the horizon. This principle is quite simple, but the complexity of the problem and the impact on society transforms TEP on a challenging issue. This paper describes a new approach to solve the dynamic TEP problem, based on an improved discrete integer version of the Evolutionary Particle Swarm Optimization (EPSO meta-heuristic algorithm. The paper includes sections describing in detail the EPSO enhanced approach, the mathematical formulation of the TEP problem, including the objective function and the constraints, and a section devoted to the application of the developed approach to this problem. Finally, the use of the developed approach is illustrated using a case study based on the IEEE 24 bus 38 branch test system.
Dynamic Protection-at-Lightpath Algorithms in Traffic-Grooming WDM Mesh Networks
Institute of Scientific and Technical Information of China (English)
HERongxi; WENHaibo; LILemin
2005-01-01
Under the constraints of the number of transceivers per node and wavelength continuity, we investigate the problem of provisioning Protection-at-lightpath (PAL) level for connections with different bandwidth granularities in traffic-grooming WDM mesh networks. We first develop a new Protection graph model (PGM) to represent current state of the network, i.e., the information about transceivers, wavelengths, protected lightpath, bandwidth, etc. We then present two grooming policies for PAL, which are called Minimal wavelength-link policy (MWP) and Minimal transceiver policy (MTP). Based on the PGM, we propose two dynamic PAL algorithms with MWP and MTP respectively, which are called Minimal wavelength-link method (MWM) and Minimal transceiver method (MTM). At last we compare the performance of MWM and MTM with other methods utilizing different grooming policies presented in previous literatures via simulations. Our results show that MWM and MTM outperform other methods significantly and MWM has a better performance than MTM.
The neighbor list algorithm for a parallelepiped box in molecular dynamics simulations
Institute of Scientific and Technical Information of China (English)
CUI ZhiWei; SUN Yi; QU JianMin
2009-01-01
In classic molecular dynamics (MD) simulations, the conventional Verlet table, cell linked list and many other techniques have been adopted to increase the computational efficiency. However, these methods are only applicable in cubic systems. In this work, the above techniques along with the metric-tensor method are extended to handle NP ensembles, so that MD simulations can be carried out under the most general loading conditions. In order to do so, a particular spatial Cartesian reference frame is proposed to determine the scaling matrix. Also, a combination method, taking the advantages of the improved Verlet table and cell linked list, is established to identify the neighbor atoms very quickly in a parallelepiped box. An example using Lennard-Jones potential is presented to verify the validity of the proposed algorithm.
Energy Technology Data Exchange (ETDEWEB)
Chandrasekhar Potluri,; Madhavi Anugolu; Marco P. Schoen; D. Subbaram Naidu
2013-08-01
In this work, an array of three surface Electrography (sEMG) sensors are used to acquired muscle extension and contraction signals for 18 healthy test subjects. The skeletal muscle force is estimated using the acquired sEMG signals and a Non-linear Wiener Hammerstein model, relating the two signals in a dynamic fashion. The model is obtained from using System Identification (SI) algorithm. The obtained force models for each sensor are fused using a proposed fuzzy logic concept with the intent to improve the force estimation accuracy and resilience to sensor failure or misalignment. For the fuzzy logic inference system, the sEMG entropy, the relative error, and the correlation of the force signals are considered for defining the membership functions. The proposed fusion algorithm yields an average of 92.49% correlation between the actual force and the overall estimated force output. In addition, the proposed fusionbased approach is implemented on a test platform. Experiments indicate an improvement in finger/hand force estimation.
A Novel Dynamic Adjusting Algorithm for Load Balancing and Handover Co-Optimization in LTE SON
Institute of Scientific and Technical Information of China (English)
Wen-Yu Li; Xiang Zhang; Shu-Cong Jia; Xin-Yu Gu; Lin Zhang; Xiao-Yu Duan; Jia-Ru Lin
2013-01-01
With the development of mobile internet and multi-media service,advanced techniques need to be applied in wireless network to improve user experience.Long term evolution (LTE) systems,which can offer up to 100Mbps downlink date rates,have been deployed in USA and Korea.However,because plenty of complex physical layer algorithms are utilized,network planning and optimization become heavy burdens for LTE network operators.Self-organizing network (SON) is a promising method to overcome this problem by automatically selecting and adjusting key parameters in LTE systems.In this paper,we present a dynamic adjusting algorithm to improve both handover and load balancing performance by introducing a weighted co-satisfaction factor (CSF).Analysis and system level simulation are conducted to exhibit the performance improvement of the proposed scheme.Results show that the proposed method outperforms the conventional solutions in terms of the network handover success ratio and load balancing gains significantly.
Setiawan, A.; Wangsaputra, R.; Martawirya, Y. Y.; Halim, A. H.
2016-02-01
This paper deals with Flexible Manufacturing System (FMS) production rescheduling due to unavailability of cutting tools caused either of cutting tool failure or life time limit. The FMS consists of parallel identical machines integrated with an automatic material handling system and it runs fully automatically. Each machine has a same cutting tool configuration that consists of different geometrical cutting tool types on each tool magazine. The job usually takes two stages. Each stage has sequential operations allocated to machines considering the cutting tool life. In the real situation, the cutting tool can fail before the cutting tool life is reached. The objective in this paper is to develop a dynamic scheduling algorithm when a cutting tool is broken during unmanned and a rescheduling needed. The algorithm consists of four steps. The first step is generating initial schedule, the second step is determination the cutting tool failure time, the third step is determination of system status at cutting tool failure time and the fourth step is the rescheduling for unfinished jobs. The approaches to solve the problem are complete-reactive scheduling and robust-proactive scheduling. The new schedules result differences starting time and completion time of each operations from the initial schedule.
A new neuro-fuzzy training algorithm for identifying dynamic characteristics of smart dampers
International Nuclear Information System (INIS)
This paper proposes a new algorithm, named establishing neuro-fuzzy system (ENFS), to identify dynamic characteristics of smart dampers such as magnetorheological (MR) and electrorheological (ER) dampers. In the ENFS, data clustering is performed based on the proposed algorithm named partitioning data space (PDS). Firstly, the PDS builds data clusters in joint input–output data space with appropriate constraints. The role of these constraints is to create reasonable data distribution in clusters. The ENFS then uses these clusters to perform the following tasks. Firstly, the fuzzy sets expressing characteristics of data clusters are established. The structure of the fuzzy sets is adjusted to be suitable for features of the data set. Secondly, an appropriate structure of neuro-fuzzy (NF) expressed by an optimal number of labeled data clusters and the fuzzy-set groups is determined. After the ENFS is introduced, its effectiveness is evaluated by a prediction-error-comparative work between the proposed method and some other methods in identifying numerical data sets such as ‘daily data of stock A’, or in identifying a function. The ENFS is then applied to identify damping force characteristics of the smart dampers. In order to evaluate the effectiveness of the ENFS in identifying the damping forces of the smart dampers, the prediction errors are presented by comparing with experimental results. (paper)
HIERARCHICAL GENETIC ALGORITHM FOR DYNAMIC CHANNEL UNITS ALLOCATION IN TDCDMA/ TDD SYSTEM
Directory of Open Access Journals (Sweden)
Kuo-Ming Hung
2009-11-01
Full Text Available Hierarchical Genetic Algorithms (HGA as a tool for search and optimizing methodology have now reached a mature stage. The minimum resource facility to carry user traffic, termed a channel unit (CU,is composed of a one time-slot and one code in the TD-CDMA/TDD system. The control of the number of CUs depends on the traffic load solves varied and asymmetrical traffic problems in the 3G system. In acellular network, the call arrival rate, call duration and the communication overhead between the base stations and the control center are vague and uncertain, regardless of whether the criteria of concern are nonlinear, constrained, discrete or NP hard. In this paper, the HGA is used to tackle the neural network (NN topology as well as the fuzzy logic controller for the dynamic CU allocation scheme in wireless cellular networks. Therefore, we propose a new efficient HGA CUs Allocation (HGACA in cellular networks. It aims to efficiently satisfy the diverse quality-of-service (QoS requirements of multimedia traffic. The results show our algorithm has a lower blocking rate, lower dropping rate, less update overhead, and shorter channel-acquisition delay than previous methods.
A Novel Dynamic Algorithm for IT Outsourcing Risk Assessment Based on Transaction Cost Theory
Directory of Open Access Journals (Sweden)
Guodong Cong
2015-01-01
Full Text Available With the great risk exposed in IT outsourcing, how to assess IT outsourcing risk becomes a critical issue. However, most of approaches to date need to further adapt to the particular complexity of IT outsourcing risk for either falling short in subjective bias, inaccuracy, or efficiency. This paper proposes a dynamic algorithm of risk assessment. It initially forwards extended three layers (risk factors, risks, and risk consequences of transferring mechanism based on transaction cost theory (TCT as the framework of risk analysis, which bridges the interconnection of components in three layers with preset transferring probability and impact. Then, it establishes an equation group between risk factors and risk consequences, which assures the “attribution” more precisely to track the specific sources that lead to certain loss. Namely, in each phase of the outsourcing lifecycle, both the likelihood and the loss of each risk factor and those of each risk are acquired through solving equation group with real data of risk consequences collected. In this “reverse” way, risk assessment becomes a responsive and interactive process with real data instead of subjective estimation, which improves the accuracy and alleviates bias in risk assessment. The numerical case proves the effectiveness of the algorithm compared with the approach forwarded by other references.
Zhang, Ruili; He, Yang; Xiao, Jianyuan; Liu, Jian; Qin, Hong; Tang, Yifa
2016-01-01
Relativistic dynamics of a charged particle in time-dependent electromagnetic fields has theoretical significance and a wide range of applications. It is often multi-scale and requires accurate long-term numerical simulations using symplectic integrators. For modern large-scale particle simulations in complex, time-dependent electromagnetic field, explicit symplectic algorithms are much more preferable. In this paper, we treat the relativistic dynamics of a particle as a Hamiltonian system on the cotangent space of the space-time, and construct for the first time explicit symplectic algorithms for relativistic charged particles of order 2 and 3 using the sum-split technique and generating functions.
Hybrid methods in planetesimal dynamics (I) : Description of a new composite algorithm
Glaschke, Patrick; Spurzem, Rainer
2011-01-01
The formation and evolution of protoplanetary systems, the breeding grounds of planet formation, is a complex dynamical problem that involves many orders of magnitudes. To serve this purpose, we present a new hybrid algorithm that combines a Fokker-Planck approach with the advantages of a pure direct-summation N-body scheme, with a very accurate integration of close encounters for the orbital evolution of the larger bodies with a statistical model, envisaged to simulate the very large number of smaller planetesimals in the disc. Direct-summation techniques have been historically developped for the study of dense stellar systems such as open and globular clusters and, within some limits imposed by the number of stars, of galactic nuclei. The number of modifications to adapt direct-summation N-body techniques to planetary dynamics is not undemanding and requires modifications. These include the way close encounters are treated, as well as the selection process for the "neighbour radius" of the particles and the...
Elenchezhiyan, M; Prakash, J
2015-09-01
In this work, state estimation schemes for non-linear hybrid dynamic systems subjected to stochastic state disturbances and random errors in measurements using interacting multiple-model (IMM) algorithms are formulated. In order to compute both discrete modes and continuous state estimates of a hybrid dynamic system either an IMM extended Kalman filter (IMM-EKF) or an IMM based derivative-free Kalman filters is proposed in this study. The efficacy of the proposed IMM based state estimation schemes is demonstrated by conducting Monte-Carlo simulation studies on the two-tank hybrid system and switched non-isothermal continuous stirred tank reactor system. Extensive simulation studies reveal that the proposed IMM based state estimation schemes are able to generate fairly accurate continuous state estimates and discrete modes. In the presence and absence of sensor bias, the simulation studies reveal that the proposed IMM unscented Kalman filter (IMM-UKF) based simultaneous state and parameter estimation scheme outperforms multiple-model UKF (MM-UKF) based simultaneous state and parameter estimation scheme.
A unified pore-network algorithm for dynamic two-phase flow
Sheng, Qiang; Thompson, Karsten
2016-09-01
This paper describes recent work on image-based network modeling of multiphase flow. The algorithm expands the range of flow scenarios and boundary conditions that can be implemented using dynamic network modeling, the most significant advance being the ability to model simultaneous injection of immiscible fluids under either transient or steady-state conditions using non-periodic domains. Pore-scale saturation distributions are solved rigorously from two-phase mass conservation equations simultaneously within each pore. Results show that simulations using a periodic network fail to track saturation history because periodic domains limit how the bulk saturation can evolve over time. In contrast, simulations using a non-periodic network with fractional flow as the boundary condition can account for behavior associated with both hysteresis and saturation history, and can capture phenomena such as the long pressure and saturation tails that are observed during dynamic drainage processes. Results include a sensitivity analysis of relative permeability to different model variables, which may provide insight into mechanisms for a variety of transient, viscous dominated flow processes.
Sun, Lin; Wei, Jing; Wang, Jian; Mi, Xueting; Guo, Yamin; Lv, Yang; Yang, Yikun; Gan, Ping; Zhou, Xueying; Jia, Chen; Tian, Xinpeng
2016-06-01
Conventional cloud detection methods are easily affected by mixed pixels, complex surface structures, and atmospheric factors, resulting in poor cloud detection results. To minimize these problems, a new Universal Dynamic Threshold Cloud Detection Algorithm (UDTCDA) supported by a priori surface reflectance database is proposed in this paper. A monthly surface reflectance database is constructed using long-time-sequenced MODerate resolution Imaging Spectroradiometer surface reflectance product (MOD09A1) to provide the surface reflectance of the underlying surfaces. The relationships between the apparent reflectance changes and the surface reflectance are simulated under different observation and atmospheric conditions with the 6S (Second Simulation of the Satellite Signal in the Solar Spectrum) model, and the dynamic threshold cloud detection models are developed. Two typical remote sensing data with important application significance and different sensor parameters, MODIS and Landsat 8, are selected for cloud detection experiments. The results were validated against the visual interpretation of clouds and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation cloud measurements. The results showed that the UDTCDA can obtain a high precision in cloud detection, correctly identifying cloudy pixels and clear-sky pixels at rates greater than 80% with error rate and missing rate of less than 20%. The UDTCDA cloud product overall shows less estimation uncertainty than the current MODIS cloud mask products. Moreover, the UDTCDA can effectively reduce the effects of atmospheric factors and mixed pixels and can be applied to different satellite sensors to realize long-term, large-scale cloud detection operations.
A QoS-Based Dynamic Queue Length Scheduling Algorithm in Multiantenna Heterogeneous Systems
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Verikoukis Christos
2010-01-01
Full Text Available The use of real-time delay-sensitive applications in wireless systems has significantly grown during the last years. Therefore the designers of wireless systems have faced a challenging issue to guarantee the required Quality of Service (QoS. On the other hand, the recent advances and the extensive use of multiple antennas have already been included in several commercial standards, where the multibeam opportunistic transmission beamforming strategies have been proposed to improve the performance of the wireless systems. A cross-layer-based dynamically tuned queue length scheduler is presented in this paper, for the Downlink of multiuser and multiantenna WLAN systems with heterogeneous traffic requirements. To align with modern wireless systems transmission strategies, an opportunistic scheduling algorithm is employed, while a priority to the different traffic classes is applied. A tradeoff between the maximization of the throughput of the system and the guarantee of the maximum allowed delay is obtained. Therefore, the length of the queue is dynamically adjusted to select the appropriate conditions based on the operator requirements.
高动态星跟踪方法%Highly dynamic star tracking algorithm
Institute of Scientific and Technical Information of China (English)
金雁; 江洁; 张广军
2013-01-01
阐述了高动态星敏感器星图的特点,指出了目前星跟踪方法的不足.针对这些不足,提出了一种基于卡尔曼预测的高动态星跟踪方法.根据高动态星敏感器运动特性,建立了星体目标在图像坐标系下运动模型,根据星体运动模型,对卡尔曼滤波器进行了自适应修正.利用经自适应修正的卡尔曼滤波器预测出参考星位置,再利用临星逼近法进行跟踪匹配.最后给出了利用上述方法进行星体位置预测及星跟踪结果.实验结果表明,在5(°)/s动态条件下星体位置预测偏差小于5像素,星跟踪成功率高于95％,并且载体动态特性的变化对星体跟踪成功率影响较小.%The character of high dynamic star sensor' s sky image and the deficiency of existing star tracking algorithm at home and abroad were presented.Aiming at these deficiencies, a new star tracking algorithm based on Kalman prediction was put forward.The model of stars' movement was set up based on the character of the star sensor' s movement.The adaptive Kalman filter was used to predict the position of the reference stars.The star was matched and tracked by Star Neighborhood Approach.At the end of the article, the prediction and tracking results were presented.The experiment results indicate that the star position prediction errors are less than 5 pixels under the dynamic condition of 5 (° )/s, and the success rate of tracking is up to 95%.The method can adapt for high dynamic star sensor and improve the success rates of tracking availably.
The settling dynamics of flocculating mud-sand mixtures: Part 1—Empirical algorithm development
Manning, Andrew James; Baugh, John V.; Spearman, Jeremy R.; Pidduck, Emma L.; Whitehouse, Richard J. S.
2011-03-01
European estuaries tend to be regarded as being either predominantly muddy or sandy. In some estuaries, the cohesive and non-cohesive fractions can become segregated. However, recent laboratory tests have revealed that mud and sand from many coastal locations can exhibit some degree of flocculation. A clear understanding of the dynamic behaviour of sediments in the nearshore region is of particular importance for estuarine management groups who want to be able to accurately predict the transportation routes and fate of the suspended sediments. To achieve this goal, numerical computer simulations are usually the chosen tools. In order to use these models with any degree of confidence, the user must be able to provide the model with a reasonable mathematical description of spatial and temporal mass settling fluxes. However, the majority of flocculation models represent purely muddy suspensions. This paper assesses the settling characteristics of flocculating mixed-sediment suspensions through the synthesis of data, which was presented as a series of algorithms. Collectively, the algorithms were referred to as the mixed-sediment settling velocity (MSSV) empirical model and could estimate the mass settling flux of mixed suspensions. The MSSV was based entirely on the settling and mass distribution patterns demonstrated by experimental observations, as opposed to pure physical theory. The selection of the algorithm structure was based on the concept of macroflocs—the larger aggregate structures—and smaller microflocs, representing constituent particles of the macroflocs. The floc data was generated using annular flume simulations and the floc properties measured using the video-based LabSFLOC instrumentation. The derived algorithms are valid for suspended sediment concentrations and turbulent shear stress values ranging between 0.2-5 g l-1 and 0.06-0.9 Pa, respectively. However, the MSSV algorithms were principally derived using manufactured mixtures of Tamar
International Nuclear Information System (INIS)
This HDR is dedicated to the research in the framework of fast transient dynamics for industrial fluid-structure systems carried in the Laboratory of Dynamic Studies from CEA, implementing new numerical methods for the modelling of complex systems and the parallel solution of large coupled problems on supercomputers. One key issue for the proposed approaches is the limitation to its minimum of the number of non-physical parameters, to cope with constraints arising from the area of usage of the concepts: safety for both nuclear applications (CEA, EDF) and aeronautics (ONERA), protection of the citizen (EC/JRC) in particular. Kinematic constraints strongly coupling structures (namely through unilateral contact) or fluid and structures (with both conformant or non-conformant meshes depending on the geometrical situation) are handled through exact methods including Lagrange Multipliers, with consequences on the solution strategy to be dealt with. This latter aspect makes EPX, the simulation code where the methods are integrated, a singular tool in the community of fast transient dynamics software. The document mainly relies on a description of the modelling needs for industrial fast transient scenarios, for nuclear applications in particular, and the proposed solutions built in the framework of the collaboration between CEA, EDF (via the LaMSID laboratory) and the LaMCoS laboratory from INSA Lyon. The main considered examples are the tearing of the fluid-filled tank after impact, the Code Disruptive Accident for a Generation IV reactor or the ruin of reinforced concrete structures under impact. Innovative models and parallel algorithms are thus proposed, allowing to carry out with robustness and performance the corresponding simulations on supercomputers made of interconnected multi-core nodes, with a strict preservation of the quality of the physical solution. This was particularly the main point of the ANR RePDyn project (2010-2013), with CEA as the pilot. (author)
Institute of Scientific and Technical Information of China (English)
范勤勤; 王循华; 颜学峰
2015-01-01
A modified harmony search algorithm with co-evolutional control parameters (DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual (i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.
International Nuclear Information System (INIS)
In this paper, an improved algorithm based on Pattern Search method (PS) to solve the Dynamic Economic Dispatch is proposed. The algorithm maintains the essential unit ramp rate constraint, along with all other necessary constraints, not only for the time horizon of operation (24 h), but it preserves these constraints through the transaction period to the next time horizon (next day) in order to avoid the discontinuity of the power system operation. The Dynamic Economic and Emission Dispatch problem (DEED) is also considered. The load balance constraints, operating limits, valve-point loading and network losses are included in the models of both DED and DEED. The numerical results clarify the significance of the improved algorithm and verify its performance.
DEFF Research Database (Denmark)
Schmidt, Lasse; Andersen, Torben O.
2016-01-01
consideration are applied for position tracking control of a hydraulic valve-cylinder drive exhibiting strong variations in inertia- and gravitational loads, and furthermore suffer from profound valve dynamics. Results demonstrate that both the twisting- and super twisting algorithms may be successfully applied...
Directory of Open Access Journals (Sweden)
Syed Mahamud Hossein
2013-09-01
Full Text Available Storing, transmitting and security of DNA sequences are well known research challenge. The problem has got magnified with increasing discovery and availability of DNA sequences. We have represent DNA sequence compression algorithm based on Dynamic Look Up Table (DLUT and modified Huffman technique. DLUT consists of 43(64 bases that are 64 sub-stings, each sub-string is of 3 bases long. Each sub-string are individually coded by single ASCII code from 33(! to 96(` and vice versa. Encode depends on encryption key choose by user from four base pair {a,t.g and c}and decode also require decryption key provide by the encoded user. Decoding must require authenticate input for encode the data. The sub-strings are combined into a Dynamic Look up Table based pre-coding routine. This algorithm is tested on reverse; complement & reverse complement the DNA sequences and also test on artificial DNA sequences of equivalent length. Speed of encryption and security levels are two important measurements for evaluating any encryption system. Due to proliferate of ubiquitous computing system, where digital contents are accessible through resource constraint biological database security concern is very important issue. A lot of research has been made to find an encryption system which can be run effectively in those biological databases. Information security is the most challenging question to protect the data from unauthorized user. The proposed method may protect the data from hackers. It can provide the three tier security, in tier one is ASCII code, in tier two is nucleotide (a,t,g and c choice by user and tier three is change of label or change of node position in Huffman Tree. Compression of the genome sequences will help to increase the efficiency of their use. The greatest advantage of this algorithm is fast execution, small memory occupation and easy implementation. Since the program to implement the technique have been written originally in the C language
Directory of Open Access Journals (Sweden)
Luman Zhao
2015-01-01
Full Text Available A thrust allocation method was proposed based on a hybrid optimization algorithm to efficiently and dynamically position a semisubmersible drilling rig. That is, the thrust allocation was optimized to produce the generalized forces and moment required while at the same time minimizing the total power consumption under the premise that forbidden zones should be taken into account. An optimization problem was mathematically formulated to provide the optimal thrust allocation by introducing the corresponding design variables, objective function, and constraints. A hybrid optimization algorithm consisting of a genetic algorithm and a sequential quadratic programming (SQP algorithm was selected and used to solve this problem. The proposed method was evaluated by applying it to a thrust allocation problem for a semisubmersible drilling rig. The results indicate that the proposed method can be used as part of a cost-effective strategy for thrust allocation of the rig.
Zhang, Dashan; Guo, Jie; Lei, Xiujun; Zhu, Changan
2016-01-01
The development of image sensor and optics enables the application of vision-based techniques to the non-contact dynamic vibration analysis of large-scale structures. As an emerging technology, a vision-based approach allows for remote measuring and does not bring any additional mass to the measuring object compared with traditional contact measurements. In this study, a high-speed vision-based sensor system is developed to extract structure vibration signals in real time. A fast motion extraction algorithm is required for this system because the maximum sampling frequency of the charge-coupled device (CCD) sensor can reach up to 1000 Hz. Two efficient subpixel level motion extraction algorithms, namely the modified Taylor approximation refinement algorithm and the localization refinement algorithm, are integrated into the proposed vision sensor. Quantitative analysis shows that both of the two modified algorithms are at least five times faster than conventional upsampled cross-correlation approaches and achieve satisfactory error performance. The practicability of the developed sensor is evaluated by an experiment in a laboratory environment and a field test. Experimental results indicate that the developed high-speed vision-based sensor system can extract accurate dynamic structure vibration signals by tracking either artificial targets or natural features. PMID:27110784
A Scalable O(N) Algorithm for Large-Scale Parallel First-Principles Molecular Dynamics Simulations
Energy Technology Data Exchange (ETDEWEB)
Osei-Kuffuor, Daniel [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Fattebert, Jean-Luc [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2014-01-01
Traditional algorithms for first-principles molecular dynamics (FPMD) simulations only gain a modest capability increase from current petascale computers, due to their O(N^{3}) complexity and their heavy use of global communications. To address this issue, we are developing a truly scalable O(N) complexity FPMD algorithm, based on density functional theory (DFT), which avoids global communications. The computational model uses a general nonorthogonal orbital formulation for the DFT energy functional, which requires knowledge of selected elements of the inverse of the associated overlap matrix. We present a scalable algorithm for approximately computing selected entries of the inverse of the overlap matrix, based on an approximate inverse technique, by inverting local blocks corresponding to principal submatrices of the global overlap matrix. The new FPMD algorithm exploits sparsity and uses nearest neighbor communication to provide a computational scheme capable of extreme scalability. Accuracy is controlled by the mesh spacing of the finite difference discretization, the size of the localization regions in which the electronic orbitals are confined, and a cutoff beyond which the entries of the overlap matrix can be omitted when computing selected entries of its inverse. We demonstrate the algorithm's excellent parallel scaling for up to O(100K) atoms on O(100K) processors, with a wall-clock time of O(1) minute per molecular dynamics time step.
A genetic algorithm for a bi-objective mathematical model for dynamic virtual cell formation problem
Moradgholi, Mostafa; Paydar, Mohammad Mahdi; Mahdavi, Iraj; Jouzdani, Javid
2016-05-01
Nowadays, with the increasing pressure of the competitive business environment and demand for diverse products, manufacturers are force to seek for solutions that reduce production costs and rise product quality. Cellular manufacturing system (CMS), as a means to this end, has been a point of attraction to both researchers and practitioners. Limitations of cell formation problem (CFP), as one of important topics in CMS, have led to the introduction of virtual CMS (VCMS). This research addresses a bi-objective dynamic virtual cell formation problem (DVCFP) with the objective of finding the optimal formation of cells, considering the material handling costs, fixed machine installation costs and variable production costs of machines and workforce. Furthermore, we consider different skills on different machines in workforce assignment in a multi-period planning horizon. The bi-objective model is transformed to a single-objective fuzzy goal programming model and to show its performance; numerical examples are solved using the LINGO software. In addition, genetic algorithm (GA) is customized to tackle large-scale instances of the problems to show the performance of the solution method.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
A global optimization approach to turbine blade design based on hierarchical fair competition genetic algorithms with dynamic niche (HFCDN-GAs) coupled with Reynolds-averaged Navier-Stokes (RANS) equation is presented. In order to meet the search theory of GAs and the aerodynamic performances of turbine, Bezier curve is adopted to parameterize the turbine blade profile, and a fitness function pertaining to optimization is designed. The design variables are the control points' ordinates of characteristic polygon of Bezier curve representing the turbine blade profile. The object function is the maximum lift-drag ratio of the turbine blade. The constraint conditions take into account the leading and trailing edge metal angle, and the strength and aerodynamic performances of turbine blade. And the treatment method of the constraint conditions is the flexible penalty function. The convergence history of test function indicates that HFCDN-GAs can locate the global optimum within a few search steps and have high robustness. The lift-drag ratio of the optimized blade is 8.3% higher than that of the original one. The results show that the proposed global optimization approach is effective for turbine blade.
International Nuclear Information System (INIS)
In this work, we show that the set of primes can be obtained through dynamical processes. Indeed, we see that behind their generation there is an apparent stochastic process; this is obtained with the combination of two processes: a 'zig-zag' between two classes of primes and an intermittent process (that is a selection rule to exclude some prime candidates of the classes). Although we start with a stochastic process, the knowledge of its inner properties in terms of zig-zagging and intermittent processes gives us a deterministic and analytic way to generate the distribution of prime numbers. Thanks to genetic algorithms and evolution systems, as we will see, we answer some of most relevant questions of the last two centuries, that is 'How can we know a priori if a number is prime or not? Or similarly, does the generation of number primes follow a specific rule and if yes what is its form? Moreover, has it a deterministic or stochastic form?' To reach these results we start to analyze prime numbers by using binary representation and building a hierarchy among derivative classes. We obtain for the first time an explicit relation for generating the full set Pn of prime numbers smaller than n or equal to n
Enhanced high dynamic range 3D shape measurement based on generalized phase-shifting algorithm
Wang, Minmin; Zhou, Canlin; Zhang, Chaorui; Si, Shuchun; Li, Hui; Lei, Zhenkun; Li, YanJie
2016-01-01
It is a challenge for Phase Measurement Profilometry (PMP) to measure objects with a large range of reflectivity variation across the surface. Saturated or dark pixels in the deformed fringe patterns captured by the camera will lead to phase fluctuations and errors. Jiang et al. proposed a high dynamic range real-time 3D shape measurement method without changing camera exposures. Three inverted phase-shifted fringe patterns are used to complement three regular phase-shifted fringe patterns for phase retrieval when any of the regular fringe patterns are saturated. But Jiang's method still has some drawbacks: (1) The phases in saturated pixels are respectively estimated by different formulas for different cases. It is shortage of an universal formula; (2) it cannot be extended to four-step phase-shifting algorithm because inverted fringe patterns are the repetition of regular fringe patterns; (3) only three unsaturated intensity values at every pixel of fringe patterns are chosen for phase demodulation, lying i...
Directory of Open Access Journals (Sweden)
E.Kayalvizhi
2015-08-01
Full Text Available Mitigation of global warming gases from burning gasoline for transportation in vehicles is one of the biggest and most complex issues the world has ever faced. In an intention to eradicate the environmental crisis caused due to global warming, electric vehicles were been introduced that are powered by electric motor which works on the energy stored in a battery pack. Inspired by the research on power management in electric vehicles, this paper focuses on the development of an energy management system for electric vehicles (EMSEV to optimally balance the energy from battery pack. The proposed methodology uses firefly optimization algorithm to optimize the power consumption of the devices like electric motor, power steering, air conditioner, power window, automatic door locks, radio, speaker, horn, wiper, GPS, internal and external lights etc., from the battery in electric vehicles. Depending upon the distance to cover and the battery availability, the devices are made to switch down automatically through dynamic EDF scheduling. CAN protocol is used for effective communication between the devices and the controller. Simulation results are obtained using MATLAB.
Comparison of parametric FBP and OS-EM reconstruction algorithm images for PET dynamic study
Energy Technology Data Exchange (ETDEWEB)
Oda, Keiichi; Uemura, Koji; Kimura, Yuichi; Senda, Michio [Tokyo Metropolitan Inst. of Gerontology (Japan). Positron Medical Center; Toyama, Hinako; Ikoma, Yoko
2001-10-01
An ordered subsets expectation maximization (OS-EM) algorithm is used for image reconstruction to suppress image noise and to make non-negative value images. We have applied OS-EM to a digital brain phantom and to human brain {sup 18}F-FDG PET kinetic studies to generate parametric images. A 45 min dynamic scan was performed starting injection of FDG with a 2D PET scanner. The images were reconstructed with OS-EM (6 iterations, 16 subsets) and with filtered backprojection (FBP), and K1, k2 and k3 images were created by the Marquardt non-linear least squares method based on the 3-parameter kinetic model. Although the OS-EM activity images correlated fairly well with those obtained by FBP, the pixel correlations were poor for the k2 and k3 parametric images, but the plots were scattered along the line of identity and the mean values for K1, k2 and k3 obtained by OS-EM were almost equal to those by FBP. The kinetic fitting error for OS-EM was no smaller than that for FBP. The results suggest that OS-EM is not necessarily superior to FBP for creating parametric images. (author)
Mathews, David H.; Disney, Matthew D.; Childs, Jessica L.; Schroeder, Susan J.; Zuker, Michael; Turner, Douglas H.
2004-01-01
A dynamic programming algorithm for prediction of RNA secondary structure has been revised to accommodate folding constraints determined by chemical modification and to include free energy increments for coaxial stacking of helices when they are either adjacent or separated by a single mismatch. Furthermore, free energy parameters are revised to account for recent experimental results for terminal mismatches and hairpin, bulge, internal, and multibranch loops. To demonstrate the applicability of this method, in vivo modification was performed on 5S rRNA in both Escherichia coli and Candida albicans with 1-cyclohexyl-3-(2-morpholinoethyl) carbodiimide metho-p-toluene sulfonate, dimethyl sulfate, and kethoxal. The percentage of known base pairs in the predicted structure increased from 26.3% to 86.8% for the E. coli sequence by using modification constraints. For C. albicans, the accuracy remained 87.5% both with and without modification data. On average, for these sequences and a set of 14 sequences with known secondary structure and chemical modification data taken from the literature, accuracy improves from 67% to 76%. This enhancement primarily reflects improvement for three sequences that are predicted with <40% accuracy on the basis of energetics alone. For these sequences, inclusion of chemical modification constraints improves the average accuracy from 28% to 78%. For the 11 sequences with <6% pseudoknotted base pairs, structures predicted with constraints from chemical modification contain on average 84% of known canonical base pairs. PMID:15123812
Beccaria, M.; Presilla, C.; DeAngelis, G. F.; Jona-Lasinio, G.
1999-11-01
We present a simple derivation of a Feynman-Kac type formula to study fermionic systems. In this approach the real time or the imaginary time dynamics is expressed in terms of the evolution of a collection of Poisson processes. This formula leads to a family of algorithms parametrized by the values of the jump rates of the Poisson processes. From these an optimal algorithm can be chosen which coincides with the Green Function Monte Carlo method in the limit when the latter becomes exact.
International Nuclear Information System (INIS)
This work has been consecrated to the modular simulation of a PWR 925 MWe power plant's dynamic and to the design of a multivariable algorithm control: a mathematical model of a plant type was developed. The programs were written on a structured manner in order to maximize flexibility. A multivariable control algorithm based on pole placement with output feedback was elaborated together with its correspondent program. The simulation results for different normal transients were shown and the capabilities of the new method of multivariable control are illustrated through many examples
Valentini, Paolo; Schwartzentruber, Thomas E.
2009-12-01
A novel combined Event-Driven/Time-Driven (ED/TD) algorithm to speed-up the Molecular Dynamics simulation of rarefied gases using realistic spherically symmetric soft potentials is presented. Due to the low density regime, the proposed method correctly identifies the time that must elapse before the next interaction occurs, similarly to Event-Driven Molecular Dynamics. However, each interaction is treated using Time-Driven Molecular Dynamics, thereby integrating Newton's Second Law using the sufficiently small time step needed to correctly resolve the atomic motion. Although infrequent, many-body interactions are also accounted for with a small approximation. The combined ED/TD method is shown to correctly reproduce translational relaxation in argon, described using the Lennard-Jones potential. For densities between ρ=10-4 kg/m and ρ=10-1 kg/m, comparisons with kinetic theory, Direct Simulation Monte Carlo, and pure Time-Driven Molecular Dynamics demonstrate that the ED/TD algorithm correctly reproduces the proper collision rates and the evolution toward thermal equilibrium. Finally, the combined ED/TD algorithm is applied to the simulation of a Mach 9 shock wave in rarefied argon. Density and temperature profiles as well as molecular velocity distributions accurately match DSMC results, and the shock thickness is within the experimental uncertainty. For the problems considered, the ED/TD algorithm ranged from several hundred to several thousand times faster than conventional Time-Driven MD. Moreover, the force calculation to integrate the molecular trajectories is found to contribute a negligible amount to the overall ED/TD simulation time. Therefore, this method could pave the way for the application of much more refined and expensive interatomic potentials, either classical or first-principles, to Molecular Dynamics simulations of shock waves in rarefied gases, involving vibrational nonequilibrium and chemical reactivity.
Directory of Open Access Journals (Sweden)
R. Sukumar
2009-01-01
Full Text Available Problem statement: In order to minimize the overall network traffic in a multiserver system, the number of users served by each server (and hence the group size should remain constant. As the underlying traffic fluctuates, a split and merge scheme is implemented in a physical server to achieve load balancing. Approach: Minimizing the number of servers during the merge operation is NP hard and to achieve these two algorithms namely FFD bin packing algorithm and LL algorithm were proposed to find the near optimal values of destination servers. Results: The performance of these algorithms were analyzed and compared based on several parameters. Conclusion: Results showed that LL algorithm outperforms FFD algorithm.
Li, Liang
2016-01-01
In coherent detection employing digital signal processing, chromatic dispersion (CD) can be compensated effectively in the electrical domain. In practical optical transport networks, the signal lightpaths between two terminal nodes can be different due to current network conditions. Accordingly, the transmission distance and the accumulated dispersion in the lightpath cannot be predicted. Therefore, the adaptive compensation of dynamic dispersion such as the use of least-mean-square (LMS) algorithm is necessary in such optical fiber networks to enable a flexible routing and switching. In this paper, we present a detailed analysis on the adaptive dispersion compensation using the LMS algorithms in coherent optical transmission networks. Numerical simulations have been carried out accordingly. It can be found that the variable-step-size LMS equalizer can achieve the adaptive CD equalization with a lower complexity, compared to the traditional LMS algorithm.
Fast time-reversible algorithms for molecular dynamics of rigid-body systems
Kajima, Yasuhiro; Hiyama, Miyabi; Ogata, Shuji; Kobayashi, Ryo; Tamura, Tomoyuki
2012-06-01
In this paper, we present time-reversible simulation algorithms for rigid bodies in the quaternion representation. By advancing a time-reversible algorithm [Y. Kajima, M. Hiyama, S. Ogata, and T. Tamura, J. Phys. Soc. Jpn. 80, 114002 (2011), 10.1143/JPSJ.80.114002] that requires iterations in calculating the angular velocity at each time step, we propose two kinds of iteration-free fast time-reversible algorithms. They are easily implemented in codes. The codes are compared with that of existing algorithms through demonstrative simulation of a nanometer-sized water droplet to find their stability of the total energy and computation speeds.
Study on Contact Algorithm of Dynamic Explicit FEM for Sheet Forming Simulation
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Based on existing algorithms, a newly developed contact search algorithm is proposed. The new algorithm consists of global search, local searching, local tracking and penetration calculation processes. It requires no iteration steps. It can deal with not only general tool surfaces with vertical walls, but also tool surfaces meshed with elements having very poor aspect ratios. It is demonstrated that the FE code employing this new contact search algorithm becomes more reliable, efficient and accurate for sheet metal forming sim ulation than conventional ones.
Jou, Jonathan D; Jain, Swati; Georgiev, Ivelin S; Donald, Bruce R
2016-06-01
Sparse energy functions that ignore long range interactions between residue pairs are frequently used by protein design algorithms to reduce computational cost. Current dynamic programming algorithms that fully exploit the optimal substructure produced by these energy functions only compute the GMEC. This disproportionately favors the sequence of a single, static conformation and overlooks better binding sequences with multiple low-energy conformations. Provable, ensemble-based algorithms such as A* avoid this problem, but A* cannot guarantee better performance than exhaustive enumeration. We propose a novel, provable, dynamic programming algorithm called Branch-Width Minimization* (BWM*) to enumerate a gap-free ensemble of conformations in order of increasing energy. Given a branch-decomposition of branch-width w for an n-residue protein design with at most q discrete side-chain conformations per residue, BWM* returns the sparse GMEC in O([Formula: see text]) time and enumerates each additional conformation in merely O([Formula: see text]) time. We define a new measure, Total Effective Search Space (TESS), which can be computed efficiently a priori before BWM* or A* is run. We ran BWM* on 67 protein design problems and found that TESS discriminated between BWM*-efficient and A*-efficient cases with 100% accuracy. As predicted by TESS and validated experimentally, BWM* outperforms A* in 73% of the cases and computes the full ensemble or a close approximation faster than A*, enumerating each additional conformation in milliseconds. Unlike A*, the performance of BWM* can be predicted in polynomial time before running the algorithm, which gives protein designers the power to choose the most efficient algorithm for their particular design problem. PMID:26744898
Jou, Jonathan D; Jain, Swati; Georgiev, Ivelin S; Donald, Bruce R
2016-06-01
Sparse energy functions that ignore long range interactions between residue pairs are frequently used by protein design algorithms to reduce computational cost. Current dynamic programming algorithms that fully exploit the optimal substructure produced by these energy functions only compute the GMEC. This disproportionately favors the sequence of a single, static conformation and overlooks better binding sequences with multiple low-energy conformations. Provable, ensemble-based algorithms such as A* avoid this problem, but A* cannot guarantee better performance than exhaustive enumeration. We propose a novel, provable, dynamic programming algorithm called Branch-Width Minimization* (BWM*) to enumerate a gap-free ensemble of conformations in order of increasing energy. Given a branch-decomposition of branch-width w for an n-residue protein design with at most q discrete side-chain conformations per residue, BWM* returns the sparse GMEC in O([Formula: see text]) time and enumerates each additional conformation in merely O([Formula: see text]) time. We define a new measure, Total Effective Search Space (TESS), which can be computed efficiently a priori before BWM* or A* is run. We ran BWM* on 67 protein design problems and found that TESS discriminated between BWM*-efficient and A*-efficient cases with 100% accuracy. As predicted by TESS and validated experimentally, BWM* outperforms A* in 73% of the cases and computes the full ensemble or a close approximation faster than A*, enumerating each additional conformation in milliseconds. Unlike A*, the performance of BWM* can be predicted in polynomial time before running the algorithm, which gives protein designers the power to choose the most efficient algorithm for their particular design problem.
Acharya, Ayan; Konar, Amit; Janarthanan, Ramadoss
2008-01-01
Ant Colony Optimization (ACO) is a metaheuristic for solving difficult discrete optimization problems. This paper presents a deterministic model based on differential equation to analyze the dynamics of basic Ant System algorithm. Traditionally, the deposition of pheromone on different parts of the tour of a particular ant is always kept unvarying. Thus the pheromone concentration remains uniform throughout the entire path of an ant. This article introduces an exponentially increasing pheromone deposition approach by artificial ants to improve the performance of basic Ant System algorithm. The idea here is to introduce an additional attracting force to guide the ants towards destination more easily by constructing an artificial potential field identified by increasing pheromone concentration towards the goal. Apart from carrying out analysis of Ant System dynamics with both traditional and the newly proposed deposition rules, the paper presents an exhaustive set of experiments performed to find out suitable p...
de Souza, Isaac D T; Silva, Sergio N; Teles, Rafael M; Fernandes, Marcelo A C
2014-01-01
The development of new embedded algorithms for automation and control of industrial equipment usually requires the use of real-time testing. However, the equipment required is often expensive, which means that such tests are often not viable. The objective of this work was therefore to develop an embedded platform for the distributed real-time simulation of dynamic systems. This platform, called the Real-Time Simulator for Dynamic Systems (RTSDS), could be applied in both industrial and academic environments. In industrial applications, the RTSDS could be used to optimize embedded control algorithms. In the academic sphere, it could be used to support research into new embedded solutions for automation and control and could also be used as a tool to assist in undergraduate and postgraduate teaching related to the development of projects concerning on-board control systems. PMID:25320906
Energy Technology Data Exchange (ETDEWEB)
Osei-Kuffuor, Daniel [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Fattebert, Jean-Luc [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2014-01-01
We present the first truly scalable first-principles molecular dynamics algorithm with O(N) complexity and controllable accuracy, capable of simulating systems with finite band gaps of sizes that were previously impossible with this degree of accuracy. By avoiding global communications, we provide a practical computational scheme capable of extreme scalability. Accuracy is controlled by the mesh spacing of the finite difference discretization, the size of the localization regions in which the electronic wave functions are confined, and a cutoff beyond which the components of the overlap matrix can be omitted when computing selected elements of its inverse. We demonstrate the algorithm's excellent parallel scaling for up to 101 952 atoms on 23 328 processors, with a wall-clock time of the order of 1 min per molecular dynamics time step and numerical error on the forces of less than 7x10^{-4} Ha/Bohr.
Stick-slip algorithm in a tangential contact force model for multi-body system dynamics
International Nuclear Information System (INIS)
Contact force of Multi-body dynamics (MBD) system can be classified two parts. First is a normal force and the other is a tangential force called friction force. And the friction force can be represented by two states such as stick and slip. The stick-slip phenomenon is simply described as a simple contact model which is a rigid body contacted on a sloped surface. If the calculated friction coefficient between the body and sloped surface is less than the static friction coefficient, the body should be stuck. If the calculated friction coefficient is greater than the static friction coefficient, the body will be sliding along the surface. The phenomenon is called as stick and slip state of friction, respectively. Usually many researchers and commercial MBD software used a coulomb friction force model which is defined with an only function of relative velocity. This kind of friction force model will be called a conventional friction force model in this paper. A big problem of the conventional model can not describe a stick state of friction phenomenon. In the case of conventional friction force model, the body will be sliding even though friction state is stick. Because, the relative velocity must have a non-zero value in order to generate the friction force. To solve this kind of problem, we propose a stick-slip friction force model including a spring like force. In the case of stick-slip friction force model, the body can be stuck on the sloped surface because the friction force will be a non-zero value, even though the relative velocity approaches zero. We defined a relative displacement variable called stiction deformation. In this paper, the stick-slip friction model is proposed and applied in the contact algorithm of MBD system. And then two friction models are compared with numerical examples. With the proposed stick-slip friction model, more realistic results are achieved
Chaotic algorithms: A numerical exploration of the dynamics of a stiff photoconductor model
International Nuclear Information System (INIS)
The photoconducting property of semiconductors leads, in general, to a very complex kinetics for the charge carriers due to the non-equilibrium processes involved. In a semi-conductor with one type of trap, the dynamics of the photo-conducting process are described by a set of ordinary coupled non-linear differential equations given by where n and p are the free electron and hole densities, and m the trapped electron density at time t. So far, there is no known closed solution for these set of non-linear differential equations, and therefore, numerical integration techniques have to be employed, as, for example, the standard procedure of the Runge-Kutta (RK) method. Now then, each one of the mechanisms of generation, recombination, and trapping has its own lifetime, which means that different time constants are to be expected in the time dependent behavior of the photocurrent. Thus, depending on the parameters of the model, the system may become stiff if the time scales between n, m, and p separate considerably. This situation may impose a considerable stress upon a fixed step numerical algorithm as the RK, which may produce then unreliable results, and other methods have to be considered. Therefore, the purpose of this note is to examine, for a critical range of parameters, the results of the numerical integration of the stiff system obtained by standard numerical schemes, such as the single-step fourth-order Runge-Kutta method and the multistep Gear method, the latter being appropriate for a rigid system of equations. 7 refs., 2 figs
Mántaras, Daniel A.; Luque, Pablo; Nava, Javier A.; Riva, Paolo; Girón, Pablo; Compadre, Diego; Ferran, Jordi
2013-10-01
A key factor to understand the vehicle dynamic behaviour is to know as accurately as possible the interaction that occurs between the tyre and the road, since it depends on many factors that influence the dynamic response of the vehicle. This paper aims to develop a methodology in order to characterise the tyre-road behaviour, applying it to obtain the tyre-road grip coefficient. This methodology is based on the use of dynamic simulation of a virtual model, integrated into a genetic algorithm that identifies the tyre-road friction coefficient in order to adjust the response obtained by simulation to real data. The numerical model was developed in collaboration with SEAT Technical Centre and it was implemented in multibody dynamic simulation software Adams®, from MSC®.
Rhode, Kawal; Lambrou, Tryphon; Hawkes, David J.; Hamilton, George; Seifalian, Alexander M.
2000-06-01
We have developed a weighted optical flow algorithm for the extraction of instantaneous blood velocity from dynamic digital x-ray images of blood vessels. We have carried out in- vitro validation of this technique. A pulsatile physiological blood flow circuit was constructed using sections of silicone tubing to simulate blood vessels with whole blood as the fluid. Instantaneous recording of flow from an electromagnetic flow meter (EMF) provided the gold standard measurement. Biplanar dynamic digital x-ray images of the blood vessel with injection of contrast medium were acquired at 25 fps using a PC frame capture card. Imaging of a Perspex calibration cube allowed 3D reconstruction of the vessel and determination of true dimensions. Blood flow waveforms were calculated off-line on a Sun workstation using the new algorithm. The correlation coefficient between instantaneous blood flow values obtained from the EMF and the x-ray method was r equals 0.871, n equals 1184, p less than 0.0001. The correlation coefficient for average blood flow was r equals 0.898, n equals 16, p less than 0.001. We have successfully demonstrated that our new algorithm can measure pulsatile blood flow in a vessel phantom. We aim to use this algorithm to measure blood flow clinically in patients undergoing vascular interventional procedures.
Ramos, A; Talaia, P; Queirós de Melo, F J
2016-01-01
The main goal of this work was to develop an approached model to study dynamic behavior and prediction of the stress distribution in an in vitro Charnley cemented hip arthroplasty. An alternative version of the described pseudo-dynamic procedure is proposed by using the time integration Newmark algorithm. An internal restoring force vector is numerically calculated from the displacement, velocity, and acceleration vectors. A numerical model of hip replacement was developed to analyze the deformation of a dynamically stressed structure for all time steps. The experimental measurement of resulting internal forces generated in the structure (internal restoring force vector) is the second fundamental step of the pseudo-dynamic procedure. These data (as a feedback) are used by the time integration algorithm, which allows updating of the structure's shape for the next displacement, velocity, and acceleration vectors. In the field of Biomechanics, the potentialities of this method contribute to the determination of a dynamically equivalent in vitro stress field of a cemented hip prosthesis; implant fitted in patients with a normal mobility or practice sports. Consequences of the stress distribution in the implant zone that underwent cyclic fatigue loads were also discussed by using a finite element model. Application of this method in Biomechanics appears as a useful tool in the approximate stress field characterization of the peak stress state. Results show a peak value around two times the static situation, more for making possible the prediction of future damage and a programed clinical examination in patients using hip prosthesis. PMID:25483822
Dynamic adaptation cuckoo search algorithm%动态适应布谷鸟搜索算法
Institute of Scientific and Technical Information of China (English)
张永韡; 汪镭; 吴启迪
2014-01-01
介绍一种新的生物启发算法--布谷鸟搜索(CS)及其相关的Lévy飞行搜索机制。为了进一步提高算法的适应性，将反馈引入算法框架，建立了CS算法参数的闭环控制系统。将Rechenberg的1/5法则作为进化的评价指标，引入学习因子平衡种群的多样性和集中性，提出动态适应布谷鸟算法(DACS)。最后，通过数值实验验证了所提出算法的有效性。%A novel bio-inspired algorithm, cuckoo search(CS), is introduced along with the related Lévy flight mechanism. In order to improve the adaptation of this algorithm, a feedback control scheme of algorithm parameters is adopted in CS. By utilizing Rechenberg’s 1/5 criteria to evaluate evolution process, and introducing the learning factor, the diversification and intensification of population are well balanced. The dynamic adaptation cuckoo search(DACS) algorithm is proposed. Finally, numerical experiment results show the effectiveness of the proposed algorithm.
Guo, Jie; Zhu, Chang`an
2016-01-01
The development of optics and computer technologies enables the application of the vision-based technique that uses digital cameras to the displacement measurement of large-scale structures. Compared with traditional contact measurements, vision-based technique allows for remote measurement, has a non-intrusive characteristic, and does not necessitate mass introduction. In this study, a high-speed camera system is developed to complete the displacement measurement in real time. The system consists of a high-speed camera and a notebook computer. The high-speed camera can capture images at a speed of hundreds of frames per second. To process the captured images in computer, the Lucas-Kanade template tracking algorithm in the field of computer vision is introduced. Additionally, a modified inverse compositional algorithm is proposed to reduce the computing time of the original algorithm and improve the efficiency further. The modified algorithm can rapidly accomplish one displacement extraction within 1 ms without having to install any pre-designed target panel onto the structures in advance. The accuracy and the efficiency of the system in the remote measurement of dynamic displacement are demonstrated in the experiments on motion platform and sound barrier on suspension viaduct. Experimental results show that the proposed algorithm can extract accurate displacement signal and accomplish the vibration measurement of large-scale structures.
DEFF Research Database (Denmark)
Rong, Aiying; Hakonen, Henri; Lahdelma, Risto
2008-01-01
in the system, the number of periods over the planning horizon and the time for solving a single-period economic dispatch problem. We have compared the DP-RSC1 algorithm with realistic power plants against the unit decommitment algorithm and the traditional priority listing method. The results show that the DP...
A Dynamic Resource Synchronizer Mutual Exclusion Algorithm for Wired/Wireless Distributed Systems
Directory of Open Access Journals (Sweden)
Ahmed Sharieh
2008-01-01
Full Text Available A mobile host has small memory, relatively slow processor, low power batteries, and communicate over low bandwidth wireless communication links. Existing mutual exclusion algorithms for distributed systems are not enough for mobile systems because of several limitations. In this study, a mutual exclusion algorithm that is more suitable for mobile computer systems is developed. The algorithm tends to minimize the number of messages needed to be transmitted in the system, by reducing the number of sites involved in the mutual exclusion decision, and reducing the amount of storage needed at different sites of the system.
Directory of Open Access Journals (Sweden)
Balen Julie
2010-09-01
Full Text Available Abstract Background There are growing concerns regarding inequities in health, with poverty being an important determinant of health as well as a product of health status. Within the People's Republic of China (P.R. China, disparities in socio-economic position are apparent, with the rural-urban gap of particular concern. Our aim was to compare direct and proxy methods of estimating household wealth in a rural and a peri-urban setting of Hunan province, P.R. China. Methods We collected data on ownership of household durable assets, housing characteristics, and utility and sanitation variables in two village-wide surveys in Hunan province. We employed principal components analysis (PCA and principal axis factoring (PAF to generate household asset-based proxy wealth indices. Households were grouped into quartiles, from 'most wealthy' to 'most poor'. We compared the estimated household wealth for each approach. Asset-based proxy wealth indices were compared to those based on self-reported average annual income and savings at the household level. Results Spearman's rank correlation analysis revealed that PCA and PAF yielded similar results, indicating that either approach may be used for estimating household wealth. In both settings investigated, the two indices were significantly associated with self-reported average annual income and combined income and savings, but not with savings alone. However, low correlation coefficients between the proxy and direct measures of wealth indicated that they are not complementary. We found wide disparities in ownership of household durable assets, and utility and sanitation variables, within and between settings. Conclusion PCA and PAF yielded almost identical results and generated robust proxy wealth indices and categories. Pooled data from the rural and peri-urban settings highlighted structural differences in wealth, most likely a result of localized urbanization and modernization. Further research is needed
Halder, Amiya
2012-01-01
This paper proposes a Genetic Algorithm based segmentation method that can automatically segment gray-scale images. The proposed method mainly consists of spatial unsupervised grayscale image segmentation that divides an image into regions. The aim of this algorithm is to produce precise segmentation of images using intensity information along with neighborhood relationships. In this paper, Fuzzy Hopfield Neural Network (FHNN) clustering helps in generating the population of Genetic algorithm which there by automatically segments the image. This technique is a powerful method for image segmentation and works for both single and multiple-feature data with spatial information. Validity index has been utilized for introducing a robust technique for finding the optimum number of components in an image. Experimental results shown that the algorithm generates good quality segmented image.
A Dynamic Load Balancing Algorithm in Computational Grid Using Fair Scheduling
Directory of Open Access Journals (Sweden)
U.Karthick Kumar
2011-09-01
Full Text Available Grid Computing has emerged as an important new field focusing on resource sharing. One of the most challenging issues in Grid Computing is efficient scheduling of tasks. In this paper, we propose a Load balancing algorithm for fair scheduling, and we compare it to other scheduling schemes such as the Earliest Deadline First, Simple Fair Task order, Adjusted Fair Task Order and Max Min Fair Scheduling for a computational grid. It addresses the fairness issues by using mean waiting time. It scheduled the task by using fair completion time and rescheduled by using mean waiting time of each task to obtain load balance. This algorithm scheme tries to provide optimal solution so that it reduces the execution time and expected price for the execution of all the jobs in the grid system is minimized. The performance of the proposed algorithm compared with other algorithm by using simulation.
A monolithic homotopy continuation algorithm with application to computational fluid dynamics
Brown, David A.; Zingg, David W.
2016-09-01
A new class of homotopy continuation methods is developed suitable for globalizing quasi-Newton methods for large sparse nonlinear systems of equations. The new continuation methods, described as monolithic homotopy continuation, differ from the classical predictor-corrector algorithm in that the predictor and corrector phases are replaced with a single phase which includes both a predictor and corrector component. Conditional convergence and stability are proved analytically. Using a Laplacian-like operator to construct the homotopy, the new algorithm is shown to be more efficient than the predictor-corrector homotopy continuation algorithm as well as an implementation of the widely-used pseudo-transient continuation algorithm for some inviscid and turbulent, subsonic and transonic external aerodynamic flows over the ONERA M6 wing and the NACA 0012 airfoil using a parallel implicit Newton-Krylov finite-difference flow solver.
Institute of Scientific and Technical Information of China (English)
FANG Ming-chung; LEE Zi-yi
2013-01-01
This paper develops a nonlinear mathematical model to simulate the dynamic motion behavior of the barge equipped with the portable outboard Dynamic Positioning (DP) system in short-crested waves.The self-tuning Proportional-Derivative (PD) controller based on the neural network algorithm is applied to control the thrusters for optimal adjustment of the barge position in waves.In addition to the wave,the current,the wind and the nonlinear drift force are also considered in the calculations.The time domain simulations for the six-degree-of-freedom motions of the barge with the DP system are solved by the 4th order Runge-Kutta method which can compromise the efficiency and the accuracy of the simulations.The technique of the portable alternative DP system developed here can serve as a practical tool to assist those ships without being equipped with the DP facility while the dynamic positioning missions are needed.
A Routing Algorithm Based on Dynamic Forecast of Vehicle Speed and Position in VANET
Shukui Zhang; Haojing Huang
2013-01-01
Considering city road environment as the background, by researching GPSR greedy algorithm and the movement characteristics of vehicle nodes in VANET, this paper proposes the concept of circle changing trends angle in vehicle speed fluctuation curve and the movement domain and designs an SWF routing algorithm based on the vehicle speed point forecasted and the changing trends time computation. Simulation experiments are carried out through using a combination of NS-2 and VanetMobiSim software....
International Nuclear Information System (INIS)
Purpose: In dynamic multileaf collimator (MLC) motion tracking with complex intensity-modulated radiation therapy (IMRT) fields, target motion perpendicular to the MLC leaf travel direction can cause beam holds, which increase beam delivery time by up to a factor of 4. As a means to balance delivery efficiency and accuracy, a moving average algorithm was incorporated into a dynamic MLC motion tracking system (i.e., moving average tracking) to account for target motion perpendicular to the MLC leaf travel direction. The experimental investigation of the moving average algorithm compared with real-time tracking and no compensation beam delivery is described. Methods: The properties of the moving average algorithm were measured and compared with those of real-time tracking (dynamic MLC motion tracking accounting for both target motion parallel and perpendicular to the leaf travel direction) and no compensation beam delivery. The algorithm was investigated using a synthetic motion trace with a baseline drift and four patient-measured 3D tumor motion traces representing regular and irregular motions with varying baseline drifts. Each motion trace was reproduced by a moving platform. The delivery efficiency, geometric accuracy, and dosimetric accuracy were evaluated for conformal, step-and-shoot IMRT, and dynamic sliding window IMRT treatment plans using the synthetic and patient motion traces. The dosimetric accuracy was quantified via a γ-test with a 3%/3 mm criterion. Results: The delivery efficiency ranged from 89 to 100% for moving average tracking, 26%-100% for real-time tracking, and 100% (by definition) for no compensation. The root-mean-square geometric error ranged from 3.2 to 4.0 mm for moving average tracking, 0.7-1.1 mm for real-time tracking, and 3.7-7.2 mm for no compensation. The percentage of dosimetric points failing the γ-test ranged from 4 to 30% for moving average tracking, 0%-23% for real-time tracking, and 10%-47% for no compensation. Conclusions
Li, Shuo; Peng, Jun; Liu, Weirong; Zhu, Zhengfa; Lin, Kuo-Chi
2013-01-01
Recent research has indicated that using the mobility of the actuator in wireless sensor and actuator networks (WSANs) to achieve mobile data collection can greatly increase the sensor network lifetime. However, mobile data collection may result in unacceptable collection delays in the network if the path of the actuator is too long. Because real-time network applications require meeting data collection delay constraints, planning the path of the actuator is a very important issue to balance the prolongation of the network lifetime and the reduction of the data collection delay. In this paper, a multi-hop routing mobile data collection algorithm is proposed based on dynamic polling point selection with delay constraints to address this issue. The algorithm can actively update the selection of the actuator's polling points according to the sensor nodes' residual energies and their locations while also considering the collection delay constraint. It also dynamically constructs the multi-hop routing trees rooted by these polling points to balance the sensor node energy consumption and the extension of the network lifetime. The effectiveness of the algorithm is validated by simulation. PMID:24451455
Directory of Open Access Journals (Sweden)
2015-03-01
Full Text Available The dynamic economic load dispatch is one of the main problems of power systems generation and operation. The objective is to schedule power generation for units over a certain period of time, while satisfying operating constraints and load demand in each interval. Wind farms, as renewable energy resources are playing an increasing role in electricity generation. In this paper, a computational framework is presented to solve the dynamic economic emission dispatch problem with inclusion of wind farms considering their associated constraints. An optimization algorithm called modified co-evolutionary particle swarm optimization (MCPSO is proposed to solve the problem. In the proposed algorithm, two kinds of swarms evolve interactively where one of them is used to calculate the penalty factors (constraints handling and the other is used for searching good solutions (optimization process. In addition, some modifications such as using an inertia weight that decreases linearly during the simulation are made to improve the performance of the algorithm. Finally, the validity and superiority of the proposed method are demonstrated by simulation results on a modiﬁed IEEE benchmark system including six thermal units and two wind farms.
Directory of Open Access Journals (Sweden)
P. Kavipriya
2014-03-01
Full Text Available Orthogonal Variable Spreading Factor (OVSF codes would give variable data rate transmissions for different bandwidth supplies in Wideband CDMA (WCDMA networks. These OVSF codes are used for the channelization of codes in WCDMA. In WCDMA, effective utilization of OVSF codes has become an active area of research as the number of codes is very limited. It is a fact that the successor and predecessor codes of OVSF cannot be used simultaneously when a specific code is used in OVSF as their encoded sequences become indistinguishable. Consequently, OVSF code tree has inadequate number of available codes. Thus, this research study uses Adaptive Genetic Algorithm (AGA based approach for dynamic OVSF code assignment in WCDMA networks. Different from existing Conventional Code Assignment (CCA and dynamic code assignment schemes, population is adaptively constructed according to existing traffic density in the OVSF code-tree. In existing technique in order to improve the ability of the GA, ‘‘dominance and diploidy’’ structure is employed to adapt to changing traffic conditions. Because in SGA algorithm cannot convergence if the new user is included into the existing OVSF code tree while SGA is running to find optimum OVSF code tree, SGA cannot adapt its structure to this unexpected variation. This problem can be overcome by the Modified Adaptive Genetic Algorithm (MAGA. Performance of the proposed MAGA approach is evaluated in terms of blocking probability and spectral efficiency and is compared with SGA, D&D GA.
Shivakumar, R
2010-01-01
The Application of Bio Inspired Algorithms to complicated Power System Stability Problems has recently attracted the researchers in the field of Artificial Intelligence. Low frequency oscillations after a disturbance in a Power system, if not sufficiently damped, can drive the system unstable. This paper provides a systematic procedure to damp the low frequency oscillations based on Bio Inspired Genetic (GA) and Particle Swarm Optimization (PSO) algorithms. The proposed controller design is based on formulating a System Damping ratio enhancement based Optimization criterion to compute the optimal controller parameters for better stability. The Novel and contrasting feature of this work is the mathematical modeling and simulation of the Synchronous generator model including the Steam Governor Turbine (GT) dynamics. To show the robustness of the proposed controller, Non linear Time domain simulations have been carried out under various system operating conditions. Also, a detailed Comparative study has been don...
Biswas, Abhishek; Ranjan, Desh; Zubair, Mohammad; He, Jing
2015-09-01
The determination of secondary structure topology is a critical step in deriving the atomic structures from the protein density maps obtained from electron cryomicroscopy technique. This step often relies on matching the secondary structure traces detected from the protein density map to the secondary structure sequence segments predicted from the amino acid sequence. Due to inaccuracies in both sources of information, a pool of possible secondary structure positions needs to be sampled. One way to approach the problem is to first derive a small number of possible topologies using existing matching algorithms, and then find the optimal placement for each possible topology. We present a dynamic programming method of Θ(Nq(2)h) to find the optimal placement for a secondary structure topology. We show that our algorithm requires significantly less computational time than the brute force method that is in the order of Θ(q(N) h).
Yu, Xiao; Yuan, Ximei; Dong, Enzeng; Ríha, Kamil
2016-07-01
Banded blurred Infrared image segmentation is a challenging topic since banded blurred infrared images are characterized by high noise, low contrast, and weak edges. Based on the interconnected and networked collaborative mechanism between innate immune factors and adaptive immune factors, this paper presents an immune dynamical algorithm with two-dimensional minimum distance immune field to solve this puzzle. Firstly, using the original characteristics as antigen surface molecular patterns, innate immune factors in the first layer of immune dynamical network extract banded blurred regions from the whole banded blurred infrared image region. Secondly, innate immune factors in the second layer of immune dynamical network extract new characteristics to design the complex of major histocompatibility complex (MHC) and antigen peptide. Lastly, adaptive immune factors in the last layer will extract object and background antigens from all the banded blurred image antigens, and design the optimal immune field of every adaptive immune factors. Experimental results on hand trace infrared images verified that the proposed algorithm could efficiently extract targets from images, and produce better extraction accuracy.
Directory of Open Access Journals (Sweden)
Xiaoyan Lei
2016-01-01
Full Text Available A model for dynamic analysis of the vehicle-track nonlinear coupling system is established by the finite element method. The whole system is divided into two subsystems: the vehicle subsystem and the track subsystem. Coupling of the two subsystems is achieved by equilibrium conditions for wheel-to-rail nonlinear contact forces and geometrical compatibility conditions. To solve the nonlinear dynamics equations for the vehicle-track coupling system, a cross iteration algorithm and a relaxation technique are presented. Examples of vibration analysis of the vehicle and slab track coupling system induced by China’s high speed train CRH3 are given. In the computation, the influences of linear and nonlinear wheel-to-rail contact models and different train speeds are considered. It is found that the cross iteration algorithm and the relaxation technique have the following advantages: simple programming; fast convergence; shorter computation time; and greater accuracy. The analyzed dynamic responses for the vehicle and the track with the wheel-to-rail linear contact model are greater than those with the wheel-to-rail nonlinear contact model, where the increasing range of the displacement and the acceleration is about 10%, and the increasing range of the wheel-to-rail contact force is less than 5%.
International Nuclear Information System (INIS)
Highlights: • Dynamic load economic dispatch with wind power (DLEDW) model is established. • Markov chains combined with scenario analysis method are used to predict wind power. • Chance constrained technique is used to simulate the impacts of wind forecast error. • Improved artificial physical optimization algorithm is proposed to solve DLEDW. • Heuristic search strategies are applied to handle the constraints of DLEDW. - Abstract: Wind power, a kind of promising renewable energy resource, has recently been getting more attractive because of various environmental and economic considerations. But the penetration of wind power with its fluctuation nature has made the operation of power system more intractable. To coordinate the reliability and operation cost, this paper established a stochastic model of dynamic load economic dispatch with wind integration (DLEDW). In this model, constraints such as ramping up/down capacity, prohibited operating zone are considered and effects of valve-point are taken into account. Markov chains combined with scenario analysis method is used to generate predictive values of wind power and chance constrained programming (CCP) is applied to simulate the impacts of wind power fluctuation on system operation. An improved artificial physical optimization algorithm is presented to solve the DLEDW problem. Heuristic strategies based on the priority list and stochastic simulation techniques are proposed to handle the constraints. In addition, a local chaotic mutation strategy is applied to overcome the disadvantage of premature convergence of artificial physical optimization algorithm. Two test systems with and without wind power integration are used to verify the feasibility and effectiveness of the proposed method and the results are compared with those of gravitational search algorithm, particle swarm optimization and standard artificial physical optimization. The simulation results demonstrate that the proposed method has a
Energy Technology Data Exchange (ETDEWEB)
Silveira, L.M.; Kamon, M.; Elfadel, I.; White, J. [Massachusetts Inst. of Technology, Cambridge, MA (United States)
1996-12-31
Model order reduction based on Krylov subspace iterative methods has recently emerged as a major tool for compressing the number of states in linear models used for simulating very large physical systems (VLSI circuits, electromagnetic interactions). There are currently two main methods for accomplishing such a compression: one is based on the nonsymmetric look-ahead Lanczos algorithm that gives a numerically stable procedure for finding Pade approximations, while the other is based on a less well characterized Arnoldi algorithm. In this paper, we show that for certain classes of generalized state-space systems, the reduced-order models produced by a coordinate-transformed Arnoldi algorithm inherit the stability of the original system. Complete Proofs of our results will be given in the final paper.
Parallel algorithm of trigonometric collocation method in nonlinear dynamics of rotors
Directory of Open Access Journals (Sweden)
Musil T.
2007-11-01
Full Text Available A parallel algorithm of a numeric procedure based on a method of trigonometric collocation is presented for investigating an unbalance response of a rotor supported by journal bearings. After a condensation process the trigonometric collocation method results in a set of nonlinear algebraic equations which is solved by the Newton-Raphson method. The order of the set is proportional to the number of nonlinear bearing coordinates and terms of the finite Fourier series. The algorithm, realized in the MATLAB parallel computing environment (DCT/DCE, uses message passing technique for interacting among processes on nodes of a parallel computer. This technique enables portability of the source code both on parallel computers with distributed and shared memory. Tests, made on a Beowulf cluster and a symmetric multiprocessor, have revealed very good speed-up and scalability of this algorithm.
A Bee Optimization Algorithm for Scheduling a Job Dynamically in Grid Environment
Directory of Open Access Journals (Sweden)
P. Rajeswari M. Prakash
2011-12-01
Full Text Available Grid computing is based on large scale resources sharing in a widely connected network. Grid scheduling is defined as the process of making scheduling decisions involving allocating jobs to resources over multiple administrative domains. Scheduling is the one of the key issues in the research. Matchmaking is a key aspect in the grid environment. Matching a job with available suitable resources has to satisfy certain constraints. Resource discovery is one of the key issues for job scheduling in the grid environment. The proposed Bee optimization algorithm is to analyze Quality of Service (QoS metrics such as service class, job type in the heterogeneous grid environment. QoS parameters play a major role in selecting grid resources and optimizing resources effectively and efficiently. The output of the proposed algorithm is compared with max-min and min-min algorithm.
QoS-Based Dynamic Multicast Routing Design Using Genetic Algorithms
Institute of Scientific and Technical Information of China (English)
YUANYouwei; YANLamei
2004-01-01
This paper addresses the problem of determining minimum cost paths to nodes in a Multicast group satisfying delay bounds and delay variation bounds. This study explores the use of Genetic algorithms (GAs) for solving the multicast routing problems when multiple Quality of services (QoS) requirements are presented. Our simulation results indicate that it is critical to select a suitable representation method and a set of appropriate parameters in order to obtain good performance. For a medium network, the probability from 0.02 to 0.2 seems to work better than those of too small or too large. As compared with the other optimal algorithm, the proposed algorithm gives better performance in terms of the success rate, the tree cost, the number of exchanged messages and the convergence time.
Stable algorithm for event detection in event-driven particle dynamics: logical states
Strobl, Severin; Bannerman, Marcus N.; Pöschel, Thorsten
2016-07-01
Following the recent development of a stable event-detection algorithm for hard-sphere systems, the implications of more complex interaction models are examined. The relative location of particles leads to ambiguity when it is used to determine the interaction state of a particle in stepped potentials, such as the square-well model. To correctly predict the next event in these systems, the concept of an additional state that is tracked separately from the particle position is introduced and integrated into the stable algorithm for event detection.
Stable algorithm for event detection in event-driven particle dynamics: Logical states
Strobl, Severin; Poeschel, Thorsten
2015-01-01
Following the recent development of a stable event-detection algorithm for hard-sphere systems, the implications of more complex interaction models are examined. The relative location of particles leads to ambiguity when it is used to determine the interaction state of a particle in stepped potentials, such as the square-well model. To correctly predict the next event in these systems, the concept of an additional state that is tracked separately from the particle position is introduced and integrated into the stable algorithm for event detection.
Real-time multibody system dynamic simulation. II - A parallel algorithm and numerical results
Energy Technology Data Exchange (ETDEWEB)
Tsai, Fuh-Feng; Haug, E.J. (Iowa, University, Iowa City (United States))
1991-06-01
In designing a parallel algorithm, an essential requirement is to distribute tasks evenly among all processors. The velocity state recursive Newton-Euler formulation, however, has embedded recurrence relations that must be executed in forward and backward computational path sequences. Here, an algorithm is developed which reduces the critical path time by extracting some operations from the forward and backward computational paths and distributing them evenly among the processors. Numerical examples are presented to show that real-time simulation can be achieved for moderately complex mechanical systems using a shared memory multiprocessor. 6 refs.
Dynamics Assessment of Grid-Synchronization Algorithms for Single-Phase Grid-Connected Converters
DEFF Research Database (Denmark)
Han, Yang; Luo, Mingyu; Guerrero, Josep M.
2015-01-01
Several advanced phase-lock-loop (PLL) algorithms have been proposed for single-phase power electronic systems. Among these algorithms, the orthogonal signal generators (OSGs) are widely utilized to generate a set of in-quadrature signals, owing to its benefit of simple digital implementation...... and low computational burden. Meanwhile, some other techniques have been proposed to enhance system robustness and stability characteristics. In this paper, a comprehensive comparison among the OSG-based PLLs and the advanced single-phase PLLs is presented when the grid voltage undergoes disturbances...
Tang, Yu-Hang; Karniadakis, George Em
2014-11-01
We present a scalable dissipative particle dynamics simulation code, fully implemented on the Graphics Processing Units (GPUs) using a hybrid CUDA/MPI programming model, which achieves 10-30 times speedup on a single GPU over 16 CPU cores and almost linear weak scaling across a thousand nodes. A unified framework is developed within which the efficient generation of the neighbor list and maintaining particle data locality are addressed. Our algorithm generates strictly ordered neighbor lists in parallel, while the construction is deterministic and makes no use of atomic operations or sorting. Such neighbor list leads to optimal data loading efficiency when combined with a two-level particle reordering scheme. A faster in situ generation scheme for Gaussian random numbers is proposed using precomputed binary signatures. We designed custom transcendental functions that are fast and accurate for evaluating the pairwise interaction. The correctness and accuracy of the code is verified through a set of test cases simulating Poiseuille flow and spontaneous vesicle formation. Computer benchmarks demonstrate the speedup of our implementation over the CPU implementation as well as strong and weak scalability. A large-scale simulation of spontaneous vesicle formation consisting of 128 million particles was conducted to further illustrate the practicality of our code in real-world applications. Catalogue identifier: AETN_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AETN_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 1 602 716 No. of bytes in distributed program, including test data, etc.: 26 489 166 Distribution format: tar.gz Programming language: C/C++, CUDA C/C++, MPI. Computer: Any computers having nVidia GPGPUs with compute capability 3.0. Operating system: Linux. Has the code been
Cvetkovic, Sascha D.; Schirris, Johan; de With, Peter H. N.
2009-01-01
For real-time imaging in surveillance applications, visibility of details is of primary importance to ensure customer confidence. If we display High Dynamic-Range (HDR) scenes whose contrast spans four or more orders of magnitude on a conventional monitor without additional processing, results are unacceptable. Compression of the dynamic range is therefore a compulsory part of any high-end video processing chain because standard monitors are inherently Low- Dynamic Range (LDR) devices with maximally two orders of display dynamic range. In real-time camera processing, many complex scenes are improved with local contrast enhancements, bringing details to the best possible visibility. In this paper, we show how a multi-scale high-frequency enhancement scheme, in which gain is a non-linear function of the detail energy, can be used for the dynamic range compression of HDR real-time video camera signals. We also show the connection of our enhancement scheme to the processing way of the Human Visual System (HVS). Our algorithm simultaneously controls perceived sharpness, ringing ("halo") artifacts (contrast) and noise, resulting in a good balance between visibility of details and non-disturbance of artifacts. The overall quality enhancement, suitable for both HDR and LDR scenes, is based on a careful selection of the filter types for the multi-band decomposition and a detailed analysis of the signal per frequency band.
A generalized gamma(s)-family of self-starting algorithms for computational structural dynamics
Namburu, Raju R.; Tamma, Kumar K.
1992-01-01
A generalized gamma(s)-family of self-starting single-step formulations are presented in order to provide simplified yet effective dynamic attributes to include features towards eliminating the need to involve accelerations in the computational process for structural dynamic problems. By appropriately selecting the parameters pertaining to gamma(s)(s = 1, 2, 3), both explicit and implicit formulations are obtained. The stability and accuracy characteristics of the gamma(s)-family of representations are presented to validate the robustness of the formulations for structural dynamic problems. Numerous illustrative examples are described and the results are in excellent agreement and validate the applicability of these formulations for structural dynamic computations.
Sadeghi, Mehdi; Parto, Sahar; Arab, Shahriar; Ranjbar, Bijan
2005-06-20
We have used a statistical approach for protein secondary structure prediction based on information theory and simultaneously taking into consideration pairwise residue types and conformational states. Since the prediction of residue secondary structure by one residue window sliding make ambiguity in state prediction, we used a dynamic programming algorithm to find the path with maximum score. A score system for residue pairs in particular conformations is derived for adjacent neighbors up to ten residue apart in sequence. The three state overall per-residue accuracy, Q3, of this method in a jackknife test with dataset created from PDBSELECT is more than 70%. PMID:15936021
Naeem, Huma; Hussain, Mukhtar; Khan, Shoab A
2009-01-01
This paper presents a novel two-stage flexible dynamic decision support based optimal threat evaluation and defensive resource scheduling algorithm for multi-target air-borne threats. The algorithm provides flexibility and optimality by swapping between two objective functions, i.e. the preferential and subtractive defense strategies as and when required. To further enhance the solution quality, it outlines and divides the critical parameters used in Threat Evaluation and Weapon Assignment (TEWA) into three broad categories (Triggering, Scheduling and Ranking parameters). Proposed algorithm uses a variant of many-to-many Stable Marriage Algorithm (SMA) to solve Threat Evaluation (TE) and Weapon Assignment (WA) problem. In TE stage, Threat Ranking and Threat-Asset pairing is done. Stage two is based on a new flexible dynamic weapon scheduling algorithm, allowing multiple engagements using shoot-look-shoot strategy, to compute near-optimal solution for a range of scenarios. Analysis part of this paper presents ...
An improved bi-level algorithm for partitioning dynamic grid hierarchies.
Energy Technology Data Exchange (ETDEWEB)
Deiterding, Ralf (California Institute of Technology, Pasadena, CA); Johansson, Henrik (Uppsala University, Uppsala, Sweden); Steensland, Johan; Ray, Jaideep
2006-05-01
Structured adaptive mesh refinement methods are being widely used for computer simulations of various physical phenomena. Parallel implementations potentially offer realistic simulations of complex three-dimensional applications. But achieving good scalability for large-scale applications is non-trivial. Performance is limited by the partitioner's ability to efficiently use the underlying parallel computer's resources. Designed on sound SAMR principles, Nature+Fable is a hybrid, dedicated SAMR partitioning tool that brings together the advantages of both domain-based and patch-based techniques while avoiding their drawbacks. But the original bi-level partitioning approach in Nature+Fable is insufficient as it for realistic applications regards frequently occurring bi-levels as ''impossible'' and fails. This document describes an improved bi-level partitioning algorithm that successfully copes with all possible bi-levels. The improved algorithm uses the original approach side-by-side with a new, complementing approach. By using a new, customized classification method, the improved algorithm switches automatically between the two approaches. This document describes the algorithms, discusses implementation issues, and presents experimental results. The improved version of Nature+Fable was found to be able to handle realistic applications and also to generate less imbalances, similar box count, but more communication as compared to the native, domain-based partitioner in the SAMR framework AMROC.
AN EFFICIENT, BOX SHAPE INDEPENDENT NONBONDED FORCE AND VIRIAL ALGORITHM FOR MOLECULAR-DYNAMICS
Bekker, H.; Dijkstra, E.J; Renardus, M.K.R.; Berendsen, H.J.C.
1995-01-01
A notation is introduced and used to transform a conventional specification of the non-bonded force and virial algorithm in the case of periodic boundary conditions into an alternative specification. The implementation of the transformed specification is simpler and typically a factor of 1.5 faster
Worm Algorithm simulations of the hole dynamics in the t-J model
Prokof'ev, Nikolai; Ruebenacker, Oliver
2001-03-01
In the limit of small J 0.4t there is an ongoing argument that at smaller J spin-charge separation is still possible. Worm algorithm Monte Carlo simulations of the hole Green function for 0.1 hole spectral function in the thermodynamic limit.
NIC: a robust background extraction algorithm for foreground detection in dynamic scenes
Huynh-The, Thien; Banos, Oresti; Lee, Sungyoung; Kang, Byeong Ho; Kim, Eun-Soo; Le-Tien, Thuong
2016-01-01
This paper presents a robust foreground detection method capable of adapting to different motion speeds in scenes. A key contribution of this paper is the background estimation using a proposed novel algorithm, neighbor-based intensity correction (NIC), that identifies and modifies the motion pixels
Aguirregabiria, Victor
2009-01-01
This document describes program code for the solution and estimation of dynamic discrete games of incomplete information using the Nested Pseudo Likelihood (NPL) method in Aguirregabiria and Mira (2007). The code is illustrated using a dynamic game of store location by retail chains, and actual data from McDonalds and Burger King.
Directory of Open Access Journals (Sweden)
Aidin Delgoshaei
2016-09-01
Full Text Available Purpose: The issue resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resource over-allocating drawback is frequently seen after scheduling of a project in practice which causes a schedule to be useless. Modifying an over-allocated schedule is very complicated and needs a lot of efforts and time. In this paper, a new and fast tracking method is proposed to schedule large scale projects which can help project engineers to schedule the project rapidly and with more confidence. Design/methodology/approach: In this article, a forward approach for maximizing net present value (NPV in multi-mode resource constrained project scheduling problem while assuming discounted positive cash flows (MRCPSP-DCF is proposed. The progress payment method is used and all resources are considered as pre-emptible. The proposed approach maximizes NPV using unscheduled resources through resource calendar in forward mode. For this purpose, a Genetic Algorithm is applied to solve. Findings: The findings show that the proposed method is an effective way to maximize NPV in MRCPSP-DCF problems while activity splitting is allowed. The proposed algorithm is very fast and can schedule experimental cases with 1000 variables and 100 resources in few seconds. The results are then compared with branch and bound method and simulated annealing algorithm and it is found the proposed genetic algorithm can provide results with better quality. Then algorithm is then applied for scheduling a hospital in practice. Originality/value: The method can be used alone or as a macro in Microsoft Office Project® Software to schedule MRCPSP-DCF problems or to modify resource over-allocated activities after scheduling a project. This can help project engineers to schedule project activities rapidly with more accuracy in practice.
Pallab Banerjee; Talat Zabin; ShwetaKumai; Pushpa Kumari
2015-01-01
Round Robin Scheduling algorithm is designed especially for Real Time Operating system (RTOS). It is a preemptive CPU scheduling algorithm which switches between the processes when static time Quantum expires .Existing Round Robin CPU scheduling algorithm cannot be implemented in real time operating system due to their high context switch rates, large waiting time, large response time, large turnaround time and less throughput . In this paper a new algorithm is presented called Best Performan...
Directory of Open Access Journals (Sweden)
Ximing Wang
2015-04-01
Full Text Available To explore the problems associated with applying dynamic programming (DP in the energy management strategies of plug-in hybrid electric vehicles (PHEVs, a plug-in hybrid bus powertrain is introduced and its dynamic control model is constructed. The numerical issues, including the discretization resolution of the relevant variables and the boundary issue of their feasible regions, were considered when implementing DP to solve the optimal control problem of PHEVs. The tradeoff between the optimization accuracy when using the DP algorithm and the computational burden was systematically investigated. As a result of overcoming the numerical issues, the DP-based approach has the potential to improve the fuel-savings potential of PHEVs. The results from comparing the DP-based strategy and the traditional control strategy indicate that there is an approximately 20% improvement in fuel economy.
International Nuclear Information System (INIS)
Dynamic X ray tomography is a new medical imaging modality. In conventional scanner, a static cross-section of the patient is reconstructed from a set of x-ray projection acquired from the rotation around the patient of a X ray source and a set of detectors. In dynamic tomography a set of successive cross sections is reconstructed enabling the imaging of naturally moving organs such as the heart or organs in dynamic interaction with exterior elements. This is the case for CAS (computer assisted surgery) where we would like to control under CT imaging the progression of surgical tools (example: peri-cardiac punction). The diffusion of a contrast product (ex in angiography), or of a marker in nuclear imaging can also be studied dynamically. Thus dynamic tomography is becoming a very promising tool for the diagnostic of disease, the study of their evolution but also for guiding surgeons during CAS. (author)
Directory of Open Access Journals (Sweden)
Mohameed Sarhan Al_Duais
2015-01-01
Full Text Available The drawback of the Back Propagation (BP algorithm is slow training and easily convergence to the local minimum and suffers from saturation training. To overcome those problems, we created a new dynamic function for each training rate and momentum term. In this study, we presented the (BPDRM algorithm, which training with dynamic training rate and momentum term. Also in this study, a new strategy is proposed, which consists of multiple steps to avoid inflation in the gross weight when adding each training rate and momentum term as a dynamic function. In this proposed strategy, fitting is done by making a relationship between the dynamic training rate and the dynamic momentum. As a result, this study placed an implicit dynamic momentum term in the dynamic training rate. This αdmic = f(1/&etadmic . This procedure kept the weights as moderate as possible (not to small or too large. The 2-dimensional XOR problem and buba data were used as benchmarks for testing the effects of the ‘new strategy’. All experiments were performed on Matlab software (2012a. From the experiment’s results, it is evident that the dynamic BPDRM algorithm provides a superior performance in terms of training and it provides faster training compared to the (BP algorithm at same limited error.
Wang, Yong; Ma, Xiaolei; Liu, Yong; Gong, Ke; Henrickson, Kristian C; Henricakson, Kristian C; Xu, Maozeng; Wang, Yinhai
2016-01-01
This paper proposes a two-stage algorithm to simultaneously estimate origin-destination (OD) matrix, link choice proportion, and dispersion parameter using partial traffic counts in a congested network. A non-linear optimization model is developed which incorporates a dynamic dispersion parameter, followed by a two-stage algorithm in which Generalized Least Squares (GLS) estimation and a Stochastic User Equilibrium (SUE) assignment model are iteratively applied until the convergence is reached. To evaluate the performance of the algorithm, the proposed approach is implemented in a hypothetical network using input data with high error, and tested under a range of variation coefficients. The root mean squared error (RMSE) of the estimated OD demand and link flows are used to evaluate the model estimation results. The results indicate that the estimated dispersion parameter theta is insensitive to the choice of variation coefficients. The proposed approach is shown to outperform two established OD estimation methods and produce parameter estimates that are close to the ground truth. In addition, the proposed approach is applied to an empirical network in Seattle, WA to validate the robustness and practicality of this methodology. In summary, this study proposes and evaluates an innovative computational approach to accurately estimate OD matrices using link-level traffic flow data, and provides useful insight for optimal parameter selection in modeling travelers' route choice behavior. PMID:26761209
Directory of Open Access Journals (Sweden)
R. Lakshmipathi
2010-01-01
Full Text Available The Application of Bio Inspired Algorithms to complicated Power System Stability Problems has recently attracted the researchers in the field of Artificial Intelligence. Low frequency oscillations after a disturbance in a Power system, if not sufficiently damped, can drive the system unstable. This paper provides a systematic procedure to damp the low frequency oscillations based on Bio Inspired Genetic (GA and Particle Swarm Optimization (PSO algorithms. The proposed controller design is based on formulating a System Damping ratio enhancement based Optimization criterion to compute the optimal controller parameters for better stability. The Novel and contrasting feature of this work is the mathematical modeling and simulation of the Synchronous generator model including the Steam Governor Turbine (GT dynamics. To show the robustness of the proposed controller, Non linear Time domain simulations have been carried out under various system operating conditions. Also, a detailed Comparative study has been done to show the superiority of the Bio inspired algorithm based controllers over the Conventional Lead lag controller.
Directory of Open Access Journals (Sweden)
Yong Wang
Full Text Available This paper proposes a two-stage algorithm to simultaneously estimate origin-destination (OD matrix, link choice proportion, and dispersion parameter using partial traffic counts in a congested network. A non-linear optimization model is developed which incorporates a dynamic dispersion parameter, followed by a two-stage algorithm in which Generalized Least Squares (GLS estimation and a Stochastic User Equilibrium (SUE assignment model are iteratively applied until the convergence is reached. To evaluate the performance of the algorithm, the proposed approach is implemented in a hypothetical network using input data with high error, and tested under a range of variation coefficients. The root mean squared error (RMSE of the estimated OD demand and link flows are used to evaluate the model estimation results. The results indicate that the estimated dispersion parameter theta is insensitive to the choice of variation coefficients. The proposed approach is shown to outperform two established OD estimation methods and produce parameter estimates that are close to the ground truth. In addition, the proposed approach is applied to an empirical network in Seattle, WA to validate the robustness and practicality of this methodology. In summary, this study proposes and evaluates an innovative computational approach to accurately estimate OD matrices using link-level traffic flow data, and provides useful insight for optimal parameter selection in modeling travelers' route choice behavior.
Directory of Open Access Journals (Sweden)
Kwang Cheol Shin
2009-02-01
Full Text Available In the fields of production, manufacturing and supply chain management, Radio Frequency Identification (RFID is regarded as one of the most important technologies. Nowadays, Mobile RFID, which is often installed in carts or forklift trucks, is increasingly being applied to the search for and checkout of items in warehouses, supermarkets, libraries and other industrial fields. In using Mobile RFID, since the readers are continuously moving, they can interfere with each other when they attempt to read the tags. In this study, we suggest a Time Division Multiple Access (TDMA based anti-collision algorithm for Mobile RFID readers. Our algorithm automatically adjusts the frame size of each reader without using manual parameters by adopting the dynamic frame size adjustment strategy when collisions occur at a reader. Through experiments on a simulated environment for Mobile RFID readers, we show that the proposed method improves the number of successful transmissions by about 228% on average, compared with Colorwave, a representative TDMA based anti-collision algorithm.
Shin, Kwang Cheol; Park, Seung Bo; Jo, Geun Sik
2009-01-01
In the fields of production, manufacturing and supply chain management, Radio Frequency Identification (RFID) is regarded as one of the most important technologies. Nowadays, Mobile RFID, which is often installed in carts or forklift trucks, is increasingly being applied to the search for and checkout of items in warehouses, supermarkets, libraries and other industrial fields. In using Mobile RFID, since the readers are continuously moving, they can interfere with each other when they attempt to read the tags. In this study, we suggest a Time Division Multiple Access (TDMA) based anti-collision algorithm for Mobile RFID readers. Our algorithm automatically adjusts the frame size of each reader without using manual parameters by adopting the dynamic frame size adjustment strategy when collisions occur at a reader. Through experiments on a simulated environment for Mobile RFID readers, we show that the proposed method improves the number of successful transmissions by about 228% on average, compared with Colorwave, a representative TDMA based anti-collision algorithm. PMID:22399942
International Nuclear Information System (INIS)
This paper proposes a hybrid model based on genetic algorithm (GA) and system dynamics (SD) for coal production–environmental pollution load in China. GA has been utilized in the optimization of the parameters of the SD model to reduce implementation subjectivity. The chain of “Economic development–coal demand–coal production–environmental pollution load” of China in 2030 was predicted, and scenarios were analyzed. Results show that: (1) GA performs well in optimizing the parameters of the SD model objectively and in simulating the historical data; (2) The demand for coal energy continuously increases, although the coal intensity has actually decreased because of China's persistent economic development. Furthermore, instead of reaching a turning point by 2030, the environmental pollution load continuously increases each year even under the scenario where coal intensity decreased by 20% and investment in pollution abatement increased by 20%; (3) For abating the amount of “three types of wastes”, reducing the coal intensity is more effective than reducing the polluted production per tonne of coal and increasing investment in pollution control. - Highlights: ► We propos a GA-SD model for China's coal production-pollution prediction. ► Genetic algorithm (GA) can objectively and accurately optimize parameters of system dynamics (SD) model. ► Environmental pollution in China is projected to grow in our scenarios by 2030. ► The mechanism of reducing waste production per tonne of coal mining is more effective than others.
Osei-Kuffuor, Daniel; Fattebert, Jean-Luc
2014-03-01
We present a truly scalable First-Principles Molecular Dynamics algorithm with O(N) complexity and fully controllable accuracy, capable of simulating systems of sizes that were previously impossible with this degree of accuracy. By avoiding global communication, we have extended W. Kohn's condensed matter ``nearsightedness'' principle to a practical computational scheme capable of extreme scalability. Accuracy is controlled by the mesh spacing of the finite difference discretization, the size of the localization regions in which the electronic wavefunctions are confined, and a cutoff beyond which the components of the overlap matrix can be omitted when computing selected elements of its inverse. We demonstrate the algorithm's excellent parallel scaling for up to 100,000 atoms on 100,000 processors, with a wall-clock time of the order of one minute per molecular dynamics time step. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
Institute of Scientific and Technical Information of China (English)
WANG Chong; LI Jun; JING Ning; WANG Jun; CHEN Hao
2011-01-01
Traditionally,heuristic re-planning algorithms are used to tackle the problem of dynamic task planning for multiple satellites.However,the traditional heuristic strategies depend on the concrete tasks,which often affect the result's optimality.Noticing that the historical information of cooperative task planning will impact the latter planning results,we propose a hybrid learning algorithrn for dynamic multi-satellite task planning,which is based on the multi-agent reinforcement learning of policy iteration and the transfer learning.The reinforcement learning strategy of each satellite is described with neural networks.The policy neural network individuals with the best topological structure and weights are found by applying co-evolutionary search iteratively.To avoid the failure of the historical learning caused by the randomly occurring observation requests,a novel approach is proposed to balance the quality and efficiency of the task planning,which converts the historical leaming strategy to the current initial learning strategy by applying the transfer learning algorithm.The simulations and analysis show the feasibility and adaptability of the proposed approach especially for the situation with randomly occurring observation requests.
International Nuclear Information System (INIS)
We apply the Feynman-Kleinert Quasi-Classical Wigner (FK-QCW) method developed in our previous work [Smith et al., J. Chem. Phys. 142, 244112 (2015)] for the determination of the dynamic structure factor of liquid para-hydrogen and ortho-deuterium at state points of (T = 20.0 K, n = 21.24 nm−3) and (T = 23.0 K, n = 24.61 nm−3), respectively. When applied to this challenging system, it is shown that this new FK-QCW method consistently reproduces the experimental dynamic structure factor reported by Smith et al. [J. Chem. Phys. 140, 034501 (2014)] for all momentum transfers considered. This shows that FK-QCW provides a substantial improvement over the Feynman-Kleinert linearized path-integral method, in which purely classical dynamics are used. Furthermore, for small momentum transfers, it is shown that FK-QCW provides nearly the same results as ring-polymer molecular dynamics (RPMD), thus suggesting that FK-QCW provides a potentially more appealing algorithm than RPMD since it is not formally limited to correlation functions involving linear operators
Stable algorithm for event detection in event-driven particle dynamics: logical states
Strobl, Severin; Bannerman, Marcus N.; Poeschel, Thorsten
2015-01-01
Following the recent development of a stable event-detection algorithm for hard-sphere systems, the implications of more complex interaction models are examined. The relative location of particles leads to ambiguity when it is used to determine the interaction state of a particle in stepped potentials, such as the square-well model. To correctly predict the next event in these systems, the concept of an additional state that is tracked separately from the particle position is introduced and i...
Kanojia Sindhuben Babulal; Rajiv Ranjan Tewari
2010-01-01
The main focus of this article is to achieve prolonged network lifetime with overall energy efficiency in wireless sensor networks through controlled utilization of limited energy. Major percentage of energy in wireless sensor network is consumed during routing from source to destination, retransmission of data on packet loss. For improvement, cross layered algorithm is proposed for routing and retransmission scheme. Simulation and results shows that this approach can save the overall energy ...
The Stochastic Evolution of a Protocell: The Gillespie Algorithm in a Dynamically Varying Volume
Carletti, T.; Filisetti, A.
2012-01-01
In the present paper we propose an improvement of the Gillespie algorithm allowing us to study the time evolution of an ensemble of chemical reactions occurring in a varying volume, whose growth is directly related to the amount of some specific molecules, belonging to the reactions set. This allows us to study the stochastic evolution of a protocell, whose volume increases because of the production of container molecules. Several protocells models are considered and compared with the determi...
The stochastic evolution of a protocell. The Gillespie algorithm in a dynamically varying volume
Carletti, Timoteo
2011-01-01
In the present paper we propose an improvement of the Gillespie algorithm allowing us to study the time evolution of an ensemble of chemical reactions occurring in a varying volume, whose growth is directly related to the amount of some specific molecules, belonging to the reactions set. This allows us to study the stochastic evolution of a protocell, whose volume increases because of the production of container molecules. Several protocells models are considered and compared with the deterministic models.
Directory of Open Access Journals (Sweden)
Assaf Zaritsky
Full Text Available Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional
Adaptive Inverse Hyperbolic Tangent Algorithm for Dynamic Contrast Adjustment in Displaying Scenes
Chein-I Chang; Chuin-Mu Wang; Yen-Chieh Ouyang; Cheng-Yi Yu
2010-01-01
Abstract Contrast has a great influence on the quality of an image in human visual perception. A poorly illuminated environment can significantly affect the contrast ratio, producing an unexpected image. This paper proposes an Adaptive Inverse Hyperbolic Tangent (AIHT) algorithm to improve the display quality and contrast of a scene. Because digital cameras must maintain the shadow in a middle range of luminance that includes a main object such as a face, a gamma function is generally used fo...
Adaptive Inverse Hyperbolic Tangent Algorithm for Dynamic Contrast Adjustment in Displaying Scenes
Yu, Cheng-Yi; Ouyang, Yen-Chieh; Wang, Chuin-Mu; Chang, Chein-I.
2010-12-01
Contrast has a great influence on the quality of an image in human visual perception. A poorly illuminated environment can significantly affect the contrast ratio, producing an unexpected image. This paper proposes an Adaptive Inverse Hyperbolic Tangent (AIHT) algorithm to improve the display quality and contrast of a scene. Because digital cameras must maintain the shadow in a middle range of luminance that includes a main object such as a face, a gamma function is generally used for this purpose. However, this function has a severe weakness in that it decreases highlight contrast. To mitigate this problem, contrast enhancement algorithms have been designed to adjust contrast to tune human visual perception. The proposed AIHT determines the contrast levels of an original image as well as parameter space for different contrast types so that not only the original histogram shape features can be preserved, but also the contrast can be enhanced effectively. Experimental results show that the proposed algorithm is capable of enhancing the global contrast of the original image adaptively while extruding the details of objects simultaneously.
Adaptive Inverse Hyperbolic Tangent Algorithm for Dynamic Contrast Adjustment in Displaying Scenes
Directory of Open Access Journals (Sweden)
Wang Chuin-Mu
2010-01-01
Full Text Available Abstract Contrast has a great influence on the quality of an image in human visual perception. A poorly illuminated environment can significantly affect the contrast ratio, producing an unexpected image. This paper proposes an Adaptive Inverse Hyperbolic Tangent (AIHT algorithm to improve the display quality and contrast of a scene. Because digital cameras must maintain the shadow in a middle range of luminance that includes a main object such as a face, a gamma function is generally used for this purpose. However, this function has a severe weakness in that it decreases highlight contrast. To mitigate this problem, contrast enhancement algorithms have been designed to adjust contrast to tune human visual perception. The proposed AIHT determines the contrast levels of an original image as well as parameter space for different contrast types so that not only the original histogram shape features can be preserved, but also the contrast can be enhanced effectively. Experimental results show that the proposed algorithm is capable of enhancing the global contrast of the original image adaptively while extruding the details of objects simultaneously.
Adaptive Inverse Hyperbolic Tangent Algorithm for Dynamic Contrast Adjustment in Displaying Scenes
Directory of Open Access Journals (Sweden)
Chein-I Chang
2010-01-01
Full Text Available Contrast has a great influence on the quality of an image in human visual perception. A poorly illuminated environment can significantly affect the contrast ratio, producing an unexpected image. This paper proposes an Adaptive Inverse Hyperbolic Tangent (AIHT algorithm to improve the display quality and contrast of a scene. Because digital cameras must maintain the shadow in a middle range of luminance that includes a main object such as a face, a gamma function is generally used for this purpose. However, this function has a severe weakness in that it decreases highlight contrast. To mitigate this problem, contrast enhancement algorithms have been designed to adjust contrast to tune human visual perception. The proposed AIHT determines the contrast levels of an original image as well as parameter space for different contrast types so that not only the original histogram shape features can be preserved, but also the contrast can be enhanced effectively. Experimental results show that the proposed algorithm is capable of enhancing the global contrast of the original image adaptively while extruding the details of objects simultaneously.
Institute of Scientific and Technical Information of China (English)
Paweł CZARNUL
2014-01-01
This paper compares the quality and execution times of several algorithms for scheduling service based workflow applications with changeable service availability and parameters. A workflow is defined as an acyclic directed graph with nodes corresponding to tasks and edges to dependencies between tasks. For each task, one out of several available services needs to be chosen and scheduled to minimize the workflow execution time and keep the cost of service within the budget. During the exe-cution of a workflow, some services may become unavailable, new ones may appear, and costs and execution times may change with a certain probability. Rescheduling is needed to obtain a better schedule. A solution is proposed on how integer linear pro-gramming can be used to solve this problem to obtain optimal solutions for smaller problems or suboptimal solutions for larger ones. It is compared side-by-side with GAIN, divide-and-conquer, and genetic algorithms for various probabilities of service unavailability or change in service parameters. The algorithms are implemented and subsequently tested in a real BeesyCluster environment.
Fast Forward Dynamics Algorithm for Robot Arms Using Multi-Processing
Zomaya, A.Y.; A S Morris
1989-01-01
The computation of the direct dynamics problem (forward dynamics) plays a major role in the real-time computer modelling and simulation of robot manipulators. The efficient and computationally inexpensive solution of this problem facilitates the design of real-time robot simulators. In addition, it allows for a better understanding of the key elements affecting robot operations. This work proposes to solve this problem by employing parallel and distributed processing techniques. First, a para...
Energy Technology Data Exchange (ETDEWEB)
Williams, P.T.
1993-09-01
As the field of computational fluid dynamics (CFD) continues to mature, algorithms are required to exploit the most recent advances in approximation theory, numerical mathematics, computing architectures, and hardware. Meeting this requirement is particularly challenging in incompressible fluid mechanics, where primitive-variable CFD formulations that are robust, while also accurate and efficient in three dimensions, remain an elusive goal. This dissertation asserts that one key to accomplishing this goal is recognition of the dual role assumed by the pressure, i.e., a mechanism for instantaneously enforcing conservation of mass and a force in the mechanical balance law for conservation of momentum. Proving this assertion has motivated the development of a new, primitive-variable, incompressible, CFD algorithm called the Continuity Constraint Method (CCM). The theoretical basis for the CCM consists of a finite-element spatial semi-discretization of a Galerkin weak statement, equal-order interpolation for all state-variables, a 0-implicit time-integration scheme, and a quasi-Newton iterative procedure extended by a Taylor Weak Statement (TWS) formulation for dispersion error control. Original contributions to algorithmic theory include: (a) formulation of the unsteady evolution of the divergence error, (b) investigation of the role of non-smoothness in the discretized continuity-constraint function, (c) development of a uniformly H{sup 1} Galerkin weak statement for the Reynolds-averaged Navier-Stokes pressure Poisson equation, (d) derivation of physically and numerically well-posed boundary conditions, and (e) investigation of sparse data structures and iterative methods for solving the matrix algebra statements generated by the algorithm.
Institute of Scientific and Technical Information of China (English)
马超
2012-01-01
针对遗传算法和Dijkstra算法在求解动态权值系统中最短路径时的性能问题,采用比较法,将两种算法应用在同一个实际游戏模型中,对其算法的稳定性、智能性、时间复杂度进行对比测试.游戏模型模拟了各种条件下的动态权值系统.为了使遗传算法更加可靠,通过优化其变异过程使得收敛速度更快,可靠性更高.实验数据表明,遗传算法在每张地图上的得分数以及算法所用时间普遍高于Dijkstra算法,从而得出遗传算法在求解动态权值系统中最短路径问题时稳定性和预期效果明显好于Dijkstra算法,但其时间复杂度较高的结论.%Used a comparative approach to compare the performance of the genetic algorithm with the Dijkstra algorithm when solve the shortest path problem in the dynamic weight system. Did an experiment in the actual model with these two algorithms in order to test their stability, intelligence and time complexity. The game model makes" many kinds of dynamic weight system. In order to make the genetic algorithm more reliable, the new algorithm gets a way to optimize the process of mutation to make the speed of the genetic algorithm faster and the reliability better. The experiment data shows that most data of the genetic algorithm is higher than the Dijkstra algorithm. The experiment makes a conclusion that the stability and expected result of the genetic algorithm is better than the Dijkstra algorithm in the dynamic weight system,but the time complexity of algorithm is higher than the Dijkstra algorithm.
Institute of Scientific and Technical Information of China (English)
Huang; Ling; Liu; Yang; Xu; Jianfeng
2015-01-01
With the transformation of the Chinese economy from an extensive growth to intensive development, city development is also gradually turning from incremental construction to stock management. Community, as a basic unit of human settlements, is an important platform to build and improve the social governance capability. In 2013, Shiyoulu Jiedao Offi ce of Yuzhong District led the 1st urban community development planning, which was a milestone of Chongqing’s city regeneration and governance innovation. This paper focuses on two key issues: how to understand the community values and make the community development planning based on the above, and how to integrate with the local forces so that the community development planning can be integrated into the action plan. Combined with the practice of Minlecun Community Development Planning, using the concept of asset-based community development, a comprehensive survey is conducted on community assets(including three aspects of physical, human, and social capital), and a community comprehensive planning strategy is formulated which covers two parts: the optimization of community spaces and the upgrading of community governance. The paper explores the local-based community planning theories and methods from such aspects as value attitude, public participation, role transformation of urban planners, and others.
An improved method using factor division algorithm for reducing the order of linear dynamical system
Indian Academy of Sciences (India)
SHARAD KUMAR TIWARI; GAGANDEEP KAUR
2016-06-01
An improved method is proposed to determine the reduced order model of large scale linear time invariant system. The dominant poles of the low order system are calculated by clustering method. The selection of pole to the cluster point is based on the contributions of each pole in redefining time moment and redefiningMarkov parameters. The coefficients of the numerator polynomial for reduced model are obtained using a factor division algorithm. This method is computationally efficient and keeps up the stability and input output characteristic of the original arrangement
An Approach for State Observation in Dynamical Systems Based on the Twisting Algorithm
DEFF Research Database (Denmark)
Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.
2013-01-01
for the observation, not directly implying its applicability for state observation. However it is shown that in the discrete case this approach may be applied to obtain a real time derivative using an intermediate integral process. Furthermore, different types of gains for the algorithm are suggested...... and analyzed via Lyapunov arguments, and a special version of the observer is proposed specifically for hydraulic drives utilizing online available plant information. The proposed observer with different observer gains are subjected to simulation studies in order to evaluate the exact properties, and...
A discrete force allocation algorithm for modelling wind turbines in computational fluid dynamics
DEFF Research Database (Denmark)
Réthoré, Pierre-Elouan; Sørensen, Niels N.
2012-01-01
, this algorithm does not address the specific cases where discrete forces are present. The velocities and pressure exhibit some significant numerical fluctuations at the position where the body forces are applied. While this issue is limited in space, it is usually critical to accurately estimate the velocity...... inflows. Many CFD codes are designed with collocated variables layout. Although this approach has many attractive features, it can generate a numerical decoupling between the pressure and the velocities. This issue is addressed by the Rhie–Chow control volume momentum interpolation. However...
Special algorithm of enhancing underwater target-radiated dynamic line spectrum
Institute of Scientific and Technical Information of China (English)
Guo Yecai; Zhao Junwei; Chen Huawei
2005-01-01
Performance of traditional adaptive line enhancer (ALE) in suppressing Gaussian noise is low and can get worse at low input signal-to-noise ratio(SNR). For greatly overcoming these disadvantages, feature of fourth-order cumulant(FOC) different slices for quasi-stationary random process is analyzed, fourth order cumulant(FOC) different slice-based adaptive dynamic line enhancer is presented, and output SNR of the proposed enhancer is derived and bigger than that of the ALE via theoretical analysis. Simulation tests with the underwater moving target-radiated data have shown that the proposed enhancer outperforms the ALE in suppressing Gaussian noise and enhancing dynamic line spectrum feature.
A Component Mode Synthesis Algorithm for Multibody Dynamics of Wind Turbines
DEFF Research Database (Denmark)
Holm-Jørgensen, Kristian; Nielsen, Søren R.K.
2009-01-01
A system reduction scheme related to a multibody formulation of wind turbine dynamics is devised. Each substructure is described in its own frame of reference, which is moving freely in the vicinity of the moving substructure, in principle without any constraints to the rigid body part...... body dynamics of the substructure, and explicitly represent the coupling degrees of freedom at the interface to the adjacent substructures. The method has been demonstrated for a blade structure, which has been modelled as two substructures. Two modelling methods have been examined where the first...
Peralta, Richard C.; Forghani, Ali; Fayad, Hala
2014-04-01
Many real water resources optimization problems involve conflicting objectives for which the main goal is to find a set of optimal solutions on, or near to the Pareto front. E-constraint and weighting multiobjective optimization techniques have shortcomings, especially as the number of objectives increases. Multiobjective Genetic Algorithms (MGA) have been previously proposed to overcome these difficulties. Here, an MGA derives a set of optimal solutions for multiobjective multiuser conjunctive use of reservoir, stream, and (un)confined groundwater resources. The proposed methodology is applied to a hydraulically and economically nonlinear system in which all significant flows, including stream-aquifer-reservoir-diversion-return flow interactions, are simulated and optimized simultaneously for multiple periods. Neural networks represent constrained state variables. The addressed objectives that can be optimized simultaneously in the coupled simulation-optimization model are: (1) maximizing water provided from sources, (2) maximizing hydropower production, and (3) minimizing operation costs of transporting water from sources to destinations. Results show the efficiency of multiobjective genetic algorithms for generating Pareto optimal sets for complex nonlinear multiobjective optimization problems.
The adaptive dynamic community detection algorithm based on the non-homogeneous random walking
Xin, Yu; Xie, Zhi-Qiang; Yang, Jing
2016-05-01
With the changing of the habit and custom, people's social activity tends to be changeable. It is required to have a community evolution analyzing method to mine the dynamic information in social network. For that, we design the random walking possibility function and the topology gain function to calculate the global influence matrix of the nodes. By the analysis of the global influence matrix, the clustering directions of the nodes can be obtained, thus the NRW (Non-Homogeneous Random Walk) method for detecting the static overlapping communities can be established. We design the ANRW (Adaptive Non-Homogeneous Random Walk) method via adapting the nodes impacted by the dynamic events based on the NRW. The ANRW combines the local community detection with dynamic adaptive adjustment to decrease the computational cost for ANRW. Furthermore, the ANRW treats the node as the calculating unity, thus the running manner of the ANRW is suitable to the parallel computing, which could meet the requirement of large dataset mining. Finally, by the experiment analysis, the efficiency of ANRW on dynamic community detection is verified.
Maric, Tomislav; Marschall, Holger; Bothe, Dieter
2013-01-01
A new parallelized unsplit geometrical Volume of Fluid (VoF) algorithm with support for arbitrary unstructured meshes and dynamic local Adaptive Mesh Refinement (AMR), as well as for two and three dimensional computation is developed. The geometrical VoF algorithm supports arbitrary unstructured meshes in order to enable computations involving flow domains of arbitrary geometrical complexity. The implementation of the method is done within the framework of the OpenFOAM library for Computation...
Pulliam, T. H.; Steger, J. L.
1985-01-01
In 1977 and 1978, general purpose centrally space differenced implicit finite difference codes in two and three dimensions have been introduced. These codes, now called ARC2D and ARC3D, can run either in inviscid or viscous mode for steady or unsteady flow. Since the introduction of the ARC2D and ARC3D codes, overall computational efficiency could be improved by making use of a number of algorithmic changes. These changes are related to the use of a spatially varying time step, the use of a sequence of mesh refinements to establish approximate solutions, implementation of various ways to reduce inversion work, improved numerical dissipation terms, and more implicit treatment of terms. The present investigation has the objective to describe the considered improvements and to quantify advantages and disadvantages. It is found that using established and simple procedures, a computer code can be maintained which is competitive with specialized codes.
Dynamic Consensus Algorithm based Distributed Voltage Harmonic Compensation in Islanded Microgrids
DEFF Research Database (Denmark)
Meng, Lexuan; Tang, Fen; Firoozabadi, Mehdi Savaghebi;
2015-01-01
control to realize voltage harmonic compensation and accurate current sharing in multi-bus islanded microgrids. Low order harmonic components are considered as examples in this paper. Harmonic current sharing is also realized among distributed generators by applying the proposed methods. Plug......In islanded microgrids, the existence of nonlinear electric loads may cause voltage distortion and affect the performance of power quality sensitive equipment. Thanks to the prevalent utilization of interfacing power electronic devices and information/communication technologies, distributed...... generators can be employed as compensators to enhance the power quality on consumer side. However, conventional centralized control is facing obstacles because of the distributed fashion of generation and consumption. Accordingly, this paper proposes a consensus algorithm based distributed hierarchical...
A hybrid algorithm for coupling partial differential equation and compartment-based dynamics.
Harrison, Jonathan U; Yates, Christian A
2016-09-01
Stochastic simulation methods can be applied successfully to model exact spatio-temporally resolved reaction-diffusion systems. However, in many cases, these methods can quickly become extremely computationally intensive with increasing particle numbers. An alternative description of many of these systems can be derived in the diffusive limit as a deterministic, continuum system of partial differential equations (PDEs). Although the numerical solution of such PDEs is, in general, much more efficient than the full stochastic simulation, the deterministic continuum description is generally not valid when copy numbers are low and stochastic effects dominate. Therefore, to take advantage of the benefits of both of these types of models, each of which may be appropriate in different parts of a spatial domain, we have developed an algorithm that can be used to couple these two types of model together. This hybrid coupling algorithm uses an overlap region between the two modelling regimes. By coupling fluxes at one end of the interface and using a concentration-matching condition at the other end, we ensure that mass is appropriately transferred between PDE- and compartment-based regimes. Our methodology gives notable reductions in simulation time in comparison with using a fully stochastic model, while maintaining the important stochastic features of the system and providing detail in appropriate areas of the domain. We test our hybrid methodology robustly by applying it to several biologically motivated problems including diffusion and morphogen gradient formation. Our analysis shows that the resulting error is small, unbiased and does not grow over time. PMID:27628171
Dynamic Topology Re-Configuration in Multihop Cellular Networks Using Sequential Genetic Algorithm
Directory of Open Access Journals (Sweden)
B.Shantha Kumari
2014-10-01
Full Text Available Cellular communications has experienced explosive growth in the past two decades. Today millions of people around the world use cellular phones. Cellular phones allow a person to make or receive a call from almost anywhere. Likewise, a person is allowed to continue the phone conversation while on the move. Cellular communications is supported by an infrastructure called a cellular network, which integrates cellular phones into the public switched telephone network. The cellular network has gone through three generations.The first generation of cellular networks is analog in nature. To accommodate more cellular phone subscribers, digital TDMA (time division multiple access and CDMA (code division multiple access technologies are used in the second generation (2G to increase the network capacity. With digital technologies, digitized voice can be coded and encrypted. Therefore, the 2G cellular network is also more secure. The third generation (3G integrates cellular phones into the Internet world by providing highspeed packet-switching data transmission in addition to circuit-switching voice transmission. The 3G cellular networks have been deployed in some parts of Asia, Europe, and the United States since 2002 and will be widely deployed in the coming years. The high increase in traffic and data rate for future generations of mobile communication systems, with simultaneous requirement for reduced power consumption, makes Multihop Cellular Networks (MCNs an attractive technology. To exploit the potentials of MCNs a new network paradigm is proposed in this paper. In addition, a novel sequential genetic algorithm (SGA is proposed as a heuristic approximation to reconfigure the optimum relaying topology as the network traffic changes. Network coding is used to combine the uplink and downlink transmissions, and incorporate it into the optimum bidirectional relaying with ICI awareness. Numerical results have shown that the algorithms suggested in this
A Data Transmission Algorithm Based on Dynamic Grid Division for Coal Goaf Temperature Monitoring
Directory of Open Access Journals (Sweden)
Qingsong Hu
2014-01-01
Full Text Available WSN (wireless sensor network is a perfect tool of temperature monitoring in coal goaf. Based on the three-zone theory of goaf, the GtmWSN model is proposed, and its dynamic features are analyzed. Accordingly, a data transmission scheme, named DTDGD, is worked out. Firstly, sink nodes conduct dynamic grid division on the GtmWSN according to virtual semicircle. Secondly, each node will confirm to which grid it belongs based on grid number. Finally, data will be delivered to sink nodes with greedy forward and hole avoidance. Simulation results and field data showed that the GtmWSN and DTDGD satisfied the lifetime need of goaf temperature monitoring.
Dynamic video encryption algorithm for H.264/AVC based on a spatiotemporal chaos system.
Xu, Hui; Tong, Xiao-Jun; Zhang, Miao; Wang, Zhu; Li, Ling-Hao
2016-06-01
Video encryption schemes mostly employ the selective encryption method to encrypt parts of important and sensitive video information, aiming to ensure the real-time performance and encryption efficiency. The classic block cipher is not applicable to video encryption due to the high computational overhead. In this paper, we propose the encryption selection control module to encrypt video syntax elements dynamically which is controlled by the chaotic pseudorandom sequence. A novel spatiotemporal chaos system and binarization method is used to generate a key stream for encrypting the chosen syntax elements. The proposed scheme enhances the resistance against attacks through the dynamic encryption process and high-security stream cipher. Experimental results show that the proposed method exhibits high security and high efficiency with little effect on the compression ratio and time cost. PMID:27409446
Institute of Scientific and Technical Information of China (English)
ZHANG Li-wei; FENG Xiao-bo; WANG Chang-de
2005-01-01
On the basis of analysis the governing process of downstream water level gates AVIO and AVIS, a mathematical model for simulation of dynamic operation process of hydraulically automated irrigation canals installed with AVIO and AVIS gates is presented. the main point of this mathematical model is firstly applying a set of unsteady flow equations (St. Venant equations here) and treating the condition of gate movement as its dynamic boundary, and then decoupling this interaction of gate movement with the change of canal flow. In this process, it is necessary to give the gates' open-loop transfer function whose input is water level deviation and output is gate discharge. The result of this simulation for a practical reach has shown it has satisfactory accuracy.
A DYNAMIC FOOD CHAIN MODEL FOR HONG KONG BASED ON RADFOOD MODEL AND BIRCHALL—JAMES ALGORITHM
Institute of Scientific and Technical Information of China (English)
余君岳; 吴国斌; 等
1995-01-01
In this paper a dynamic food chain model for Hong Kong which simulates the transfer of radioactive substances from a fallout deposition via the food chain into the human bodies is built.The model is based on the RADFOOD model and the Birchall-James algorithm.The radionuclides 131I and 90Sr representing the short-term and long-term risk situations have been studied as sample cases.Various types of crops,and the dietary pattern of the public have been considered.The resulting internal radiation doses have been calculated.The results are obtained for food consumption starting at various time after the fallout deposition and for different consumption durations.
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
We give an equivalent construction of the infinitesimal time translation operator for partial differential evolution equation in the algebraic dynamics algorithm proposed by Shun-Jin Wang and his students. Our construction involves only simple partial differentials and avoids the derivative terms of δ function which appear in the course of computation by means of Wang-Zhang operator. We prove Wang’s equivalent theorem which says that our construction and Wang-Zhang’s are equivalent. We use our construction to deal with several typical equations such as nonlinear advection equation, Burgers equation, nonlinear Schrodinger equation, KdV equation and sine-Gordon equation, and obtain at least second order approximate solutions to them. These equations include the cases of real and complex field variables and the cases of the first and the second order time derivatives.
International Nuclear Information System (INIS)
This paper illustrates a method for choosing the optimal mix of wind capacity at several geographically dispersed locations. The method is based on a dynamic fuzzy search algorithm that can be applied to different optimization targets. We illustrate the method using two objective functions for the optimization: maximum economic benefit and maximum reliability. We also illustrate the sensitivity of the fuzzy economic benefit solutions to small perturbations of the capacity selections at each wind site. We find that small changes in site capacity and/or location have small effects on the economic benefit provided by wind power plants. We use electric load and generator data from Iowa, along with high-quality wind-speed data collected by the Iowa Wind Energy Institute
Luo, Dan; Ohya, Jun
2009-01-01
To achieve environments in which humans and mobile robots co-exist, technologies for recognizing hand gestures from the video sequence acquired by a dynamic camera could be useful for human-to-robot interface systems. Most of conventional hand gesture technologies deal with only still camera images. This paper proposes a very simple and stable method for extracting hand motion trajectories based on the Human-Following Local Coordinate System (HFLC System), which is obtained from the located human face and both hands. Then, we apply Condensation Algorithm to the extracted hand trajectories so that the hand motion is recognized. We demonstrate the effectiveness of the proposed method by conducting experiments on 35 kinds of sign language based hand gestures.
International Nuclear Information System (INIS)
This paper concerns the implementation of the Kalman Filter on an FPGA. This provides the reader with three major results. The Kalman Filter is based on matrix and vector operations. We have transformed it to a system where matrix inputs are avoided. From that model and floating point in random integer generation we implemented the Kalman Filter on an FPGA using the SPARTAN-3E board. Secondly, investigations on dynamic partial reconfiguration [DPR] were made and led to identifying operations that are involved in DPR. This paper provides the inventory of these operations. Thirdly, looking for the reconfiguration time of the Kalman Filter, we can state in seconds the clock cycle of any algorithm.
LEO星座网络动态源路由算法%Dynamic Source Routing Algorithm for LEO Satellite Networks
Institute of Scientific and Technical Information of China (English)
万鹏; 曹志刚; 王京林
2007-01-01
近年来,在低轨(LEO)卫星星座通信网络中采用网际协议(IP)路由算法的研究已经取得了一系列进展,文章论述了LEO星座通信网络的特点、拓扑结构和虚拟节点策略.在此基础上提出了基于泛洪路由的LEO星座动态源路由算法DSR-LSN(Dynamic Source Routing algorithm in LEO Satellite Networks),星座网络仿真表明,DSR-LSN算法具有网络路由状态稳定性好、时延小的优点.
A component mode synthesis algorithm for multibody dynamics of wind turbines
Holm-Jørgensen, K.; Nielsen, S. R. K.
2009-10-01
A system reduction scheme related to a multibody formulation of wind turbine dynamics is devised. Each substructure is described in its own frame of reference, which is moving freely in the vicinity of the moving substructure, in principle without any constraints to the rigid body part of the motion of the substructure. The system reduction is based on a component mode synthesis method, where the response of the internal degrees of freedom of the substructure is described as the quasi-static response induced by the boundary degrees of freedom via the constraint modes superimposed in combination to a dynamic component induced by inertial effects and internal loads. The latter component is modelled by a truncated modal expansion in fixed interface undamped eigenmodes. The selected modal vector base for the internal dynamics ensures that the boundary degrees of freedom account for the rigid-body dynamics of the substructure, and explicitly represent the coupling degrees of freedom at the interface to the adjacent substructures. The method has been demonstrated for a blade structure, which has been modelled as two substructures. Two modelling methods have been examined where the first is by use of fixed-fixed eigenmodes for the innermost substructure and fixed-free eigenmodes for the outermost substructure. The other approach is by use of fixed-free eigenmodes for both substructures. The fixed-fixed method shows good correspondence with the full FE model which is not the case for the fixed-free method due to incompatible displacements and rotations at the interface between the two substructures. Moreover, the results from the reduced model by use of constant constraint modes and constant fixed interface modes over a large operating area for the wind turbine blade are almost identical to the full FE model.
Distributed Dynamic Memetic Algorithm Based Coding Aware Routing for Wireless Mesh Sensor Networks
Saeed Hamam; Ahmad S. Almogren
2016-01-01
Network coding has been confirmed as a potential technology to improve performance of wireless mesh networks (WMNs); network coding has great advantages for sensor networks like minimization of communication needed to collect sensor data and error recovery. A few network coding aware routings have been proposed. However, these mechanisms detect coding opportunities through local traffic pattern checking, which hardly obtains optimal routes. This paper proposes a Distributed Dynamic Memetic Al...
Parameter matching analysis of hydraulic hybrid excavators based on dynamic programming algorithm
Wei Shen; Jihai Jiang; Xiaoyu Su; Hamid Reza Karimi
2013-01-01
In order to meet the energy saving requirement of the excavator, hybrid excavators are becoming the hot spot for researchers. The initial problem is to match the parameter of each component, because the system is tending to be more complicated due to the introduction of the accumulator. In this paper, firstly, a new architecture is presented which is hydraulic hybrid excavator based on common pressure rail combined switched function (HHES). Secondly, the general principle of dynamic programmi...
An Evolutionary Algorithm Approach to Link Prediction in Dynamic Social Networks
Bliss, Catherine A.; Frank, Morgan R.; Danforth, Christopher M.; Dodds, Peter Sheridan
2013-01-01
Many real world, complex phenomena have underlying structures of evolving networks where nodes and links are added and removed over time. A central scientific challenge is the description and explanation of network dynamics, with a key test being the prediction of short and long term changes. For the problem of short-term link prediction, existing methods attempt to determine neighborhood metrics that correlate with the appearance of a link in the next observation period. Recent work has sugg...
Matthews, A P; Garenne, M L
2013-09-01
The matching algorithm in a dynamic marriage market model is described in this first of two companion papers. Iterative Proportional Fitting is used to find a marriage function (an age distribution of new marriages for both sexes), in a stable reference population, that is consistent with the one-sex age distributions of new marriages, and includes age preference. The one-sex age distributions (which are the marginals of the two-sex distribution) are based on the Picrate model, and age preference on a normal distribution, both of which may be adjusted by choice of parameter values. For a population that is perturbed from the reference state, the total number of new marriages is found as the harmonic mean of target totals for men and women obtained by applying reference population marriage rates to the perturbed population. The marriage function uses the age preference function, assumed to be the same for the reference and the perturbed populations, to distribute the total number of new marriages. The marriage function also has an availability factor that varies as the population changes with time, where availability depends on the supply of unmarried men and women. To simplify exposition, only first marriage is treated, and the algorithm is illustrated by application to Zambia. In the second paper, remarriage and dissolution are included.
Li, Liang; Jia, Gang; Chen, Jie; Zhu, Hongjun; Cao, Dongpu; Song, Jian
2015-08-01
Direct yaw moment control (DYC), which differentially brakes the wheels to produce a yaw moment for the vehicle stability in a steering process, is an important part of electric stability control system. In this field, most control methods utilise the active brake pressure with a feedback controller to adjust the braked wheel. However, the method might lead to a control delay or overshoot because of the lack of a quantitative project relationship between target values from the upper stability controller to the lower pressure controller. Meanwhile, the stability controller usually ignores the implementing ability of the tyre forces, which might be restrained by the combined-slip dynamics of the tyre. Therefore, a novel control algorithm of DYC based on the hierarchical control strategy is brought forward in this paper. As for the upper controller, a correctional linear quadratic regulator, which not only contains feedback control but also contains feed forward control, is introduced to deduce the object of the stability yaw moment in order to guarantee the yaw rate and side-slip angle stability. As for the medium and lower controller, the quantitative relationship between the vehicle stability object and the target tyre forces of controlled wheels is proposed to achieve smooth control performance based on a combined-slip tyre model. The simulations with the hardware-in-the-loop platform validate that the proposed algorithm can improve the stability of the vehicle effectively.
Indian Academy of Sciences (India)
KAMAL DEEP; PARDEEP K SINGH
2016-09-01
In this paper, an integrated mathematical model of multi-period cell formation and part operation tradeoff in a dynamic cellular manufacturing system is proposed in consideration with multiple part process route. This paper puts emphasize on the production flexibility (production/subcontracting part operation) to satisfy the product demand requirement in different period segments of planning horizon considering production capacity shortage and/or sudden machine breakdown. The proposed model simultaneously generates machine cells and part families and selects the optimum process route instead of the user specifying predetermined routes. Conventional optimization method for the optimal cell formation problem requires substantial amount of time and memory space. Hence a simulated annealing based genetic algorithm is proposed to explore the solution regions efficiently and to expedite the solution search space. To evaluate the computability of the proposed algorithm, different problem scenarios are adopted from literature. The results approve the effectiveness of theproposed approach in designing the manufacturing cell and minimization of the overall cost, considering various manufacturing aspects such as production volume, multiple process route, production capacity, machine duplication, system reconfiguration, material handling and subcontracting part operation.
Mori, Takaharu; Miyashita, Naoyuki; Im, Wonpil; Feig, Michael; Sugita, Yuji
2016-07-01
This paper reviews various enhanced conformational sampling methods and explicit/implicit solvent/membrane models, as well as their recent applications to the exploration of the structure and dynamics of membranes and membrane proteins. Molecular dynamics simulations have become an essential tool to investigate biological problems, and their success relies on proper molecular models together with efficient conformational sampling methods. The implicit representation of solvent/membrane environments is reasonable approximation to the explicit all-atom models, considering the balance between computational cost and simulation accuracy. Implicit models can be easily combined with replica-exchange molecular dynamics methods to explore a wider conformational space of a protein. Other molecular models and enhanced conformational sampling methods are also briefly discussed. As application examples, we introduce recent simulation studies of glycophorin A, phospholamban, amyloid precursor protein, and mixed lipid bilayers and discuss the accuracy and efficiency of each simulation model and method. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.
Hu, T C
2002-01-01
Newly enlarged, updated second edition of a valuable text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discusses binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. 153 black-and-white illus. 23 tables.Newly enlarged, updated second edition of a valuable, widely used text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discussed are binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. New to this edition: Chapter 9
Mundhenk, Terrell N.; Dhavale, Nitin; Marmol, Salvador; Calleja, Elizabeth; Navalpakkam, Vidhya; Bellman, Kirstie; Landauer, Chris; Arbib, Michael A.; Itti, Laurent
2003-10-01
In view of the growing complexity of computational tasks and their design, we propose that certain interactive systems may be better designed by utilizing computational strategies based on the study of the human brain. Compared with current engineering paradigms, brain theory offers the promise of improved self-organization and adaptation to the current environment, freeing the programmer from having to address those issues in a procedural manner when designing and implementing large-scale complex systems. To advance this hypothesis, we discus a multi-agent surveillance system where 12 agent CPUs each with its own camera, compete and cooperate to monitor a large room. To cope with the overload of image data streaming from 12 cameras, we take inspiration from the primate"s visual system, which allows the animal to operate a real-time selection of the few most conspicuous locations in visual input. This is accomplished by having each camera agent utilize the bottom-up, saliency-based visual attention algorithm of Itti and Koch (Vision Research 2000;40(10-12):1489-1506) to scan the scene for objects of interest. Real time operation is achieved using a distributed version that runs on a 16-CPU Beowulf cluster composed of the agent computers. The algorithm guides cameras to track and monitor salient objects based on maps of color, orientation, intensity, and motion. To spread camera view points or create cooperation in monitoring highly salient targets, camera agents bias each other by increasing or decreasing the weight of different feature vectors in other cameras, using mechanisms similar to excitation and suppression that have been documented in electrophysiology, psychophysics and imaging studies of low-level visual processing. In addition, if cameras need to compete for computing resources, allocation of computational time is weighed based upon the history of each camera. A camera agent that has a history of seeing more salient targets is more likely to obtain
AN IMPROVED CONTROL ALGORITHM FOR «DYNAMIC CAPACITOR» VAR COMPENSATOR
Directory of Open Access Journals (Sweden)
S.K. Podnebennaya
2015-11-01
Full Text Available Purpose. Modern approaches of VAR compensation are: using compensators with stepped regulation, STATCOMs, active power filters. Recently, more attention is paid to VAR compensator’s design based on the direct AC / AC converters, which are called dynamic capacitors. Methodology. The dynamic capacitor (D-CAP is the capacitor bank, which is connected to the mains through direct AC / AC buck converter. By varying the duty cycle of bidirectional switches, smooth control of reactive power can be achieved. However, in case of distorted mains voltage, D-CAP mains current will have a high THD. This is due to the fact that the D-CAP affects the frequency response of electric grid thus leading to the appearance of resonances. With non-sinusoidal mains voltage, capacitors are affected by harmonics. This reduces the reliability of the D-CAP, increasing the probability of their failure. To eliminate these drawbacks it is suggested to improve the D-CAP control system so that the input current of the dynamic capacitor is forced to be close to sinusoidal. This can be achieved if the duty cycle of the switching bi-directional switches is changed according to the proposed expression. Results. The research is done on a single-phase D-CAP with the proposed control system, its input current diagrams are shown. In contrast to the D-CAP with a constant duty cycle control, the resulting THD of its input current is much lower. Thus, the control system provides a form of the input current that is close to a sine wave. This reduces the influence of mains voltage harmonics on the D-CAP operation, increases its reliability and improves power quality. Originality. The proposed D-CAP control system ensures reliable operation with non-sinusoidal mains voltage. Practical value. Application of D-CAPs with the proposed control system allows for improved energy efficiency of electrical mains by providing VAR compensation and improving power quality.
A Pre-compensation Fuzzy Logic Algorithm Designed for the Dynamic Compensation Robotic System
Directory of Open Access Journals (Sweden)
Shouren Huang
2015-01-01
Full Text Available This paper deals with the issue of non-model-based position regulation for the dynamic compensation robotic system (DCRS, which has been proposed for cooperating with the existing main robotic systems, such as the common serial robotic arms, to accomplish high-speed and accurate manipulations. The dynamic compensation concept is realized by fusing a high-speed & light-weight compensation actuator as well as endpoint closed loop (ECL configured high-speed cameras. Within the context of the DCRS, the coarse motion, which is realized by the main robotic system, usually gives rise to negative dynamic impact on the compensation actuator that is configured to accomplish the fine motion. Through the analysis of a simplified model for the coupled two-plant system, relative velocity information between the two plants is found to play a role in the first order derivative of the displacement error. With the use of the relative position information from high-speed visual feedback, this paper proposes a new pre- compensation fuzzy logic control (PFLC approach for control of the compensation actuator. The PFLC method is model-independent and is realized with a cascade fuzzy inference structure that conveniently integrates the relative velocity term between the two plants into the error regulation, and therefore realizes the partial counteraction of the disturbance from the main robot easily without knowing the explicit mathematical models of the system. Comparison works between the proposed PFLC and approaches that take no consideration of the relative velocity information, such as proportional-derivative (PD control and conventional fuzzy logic control, are conducted. Simulations and experiments show the consistent effectiveness of the proposed approach.
Dynamic Optimization Algorithm for Flying Trajectory of a Free-flying Space Robot
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
A new method of dynamic optimization for the flying trajectory of a free-flying space robot based on its flying motion characteristics is presented. The continuous flying trajectory is broken into a number of segment and the control efforts and the duration of the segment are chosen as the optimization parameters. The objective function is made by using the weighted sum of the fuel used and the time spent, and the constraint equations are selected. Finally, the internal point punishment function method is adopted in the optimization program, and the results of computer simulation are given.
A Service Ratio-Based Dynamic Fair Queueing Algorithm for Packet Switching Networks
Institute of Scientific and Technical Information of China (English)
YIN De-bin; XIE Jian-ying; ZHANG Yan; WU Jian-zhen; SUN Hua-li
2008-01-01
A new weighted fair queeetng algodthm is proposed,which uses the novel flow-based service ratio parameters to schedule flows.This solves the main drawback of traditional weighted fair quoneing algorithmsthe packet-based calculation of the weight parameters.In addition,this paper proposes a novel service ratio calculation method and a queue management techaology.The former adjusts the service ratio parameters adaptively based on the dynamics of the packet lengths and then solves the unfairness problem induced by the variable packet length.The latter impgoves the utilization of the server's queue buffeg and reduces the delay jitter throegh restricting the buffer length for each flow.
An Improved Control Algorithm for High-order Nonlinear Systems with Unmodelled Dynamics
Institute of Scientific and Technical Information of China (English)
Na Duan; Fu-Nian Hu; Xin Yu
2009-01-01
In this paper, we consider a class of high-order nonlinear systems with unmodelled dynamics from the viewpoint of maintaining the desired control performance (e. g., asymptotical stability) and reducing the control effort. By introducing a new rescaling transformation, adopting an effective reduced-order observer, and choosing an ingenious Lyapunov function and appropriate design parameters, this paper designs an improved output-feedback controller. The output-feedback controller guarantees the globally asymptotical stability of the closed-loop system. Subsequently, taking a concrete system for an example, the smaller critical values for gain parameter and rescaling transformation parameter are obtained to effectively reduce the control effort.
International Nuclear Information System (INIS)
Background: In radioactive nuclides atmospheric diffusion models, the empirical dispersion coefficients were deduced under certain experiment conditions, whose difference with nuclear accident conditions is a source of deviation. A better estimation of the radioactive nuclide's actual dispersion process could be done by correcting dispersion coefficients with observation data, and Genetic Algorithm (GA) is an appropriate method for this correction procedure. Purpose: This study is to analyze the fitness functions' influence on the correction procedure and the forecast ability of diffusion model. Methods: GA, coupled with Lagrange dispersion model, was used in a numerical simulation to compare 4 fitness functions' impact on the correction result. Results: In the numerical simulation, the fitness function with observation deviation taken into consideration stands out when significant deviation exists in the observed data. After performing the correction procedure on the Kincaid experiment data, a significant boost was observed in the diffusion model's forecast ability. Conclusion: As the result shows, in order to improve dispersion models' forecast ability using GA, observation data should be given different weight in the fitness function corresponding to their error. (authors)
Flowfield-Dependent Mixed Explicit-Implicit (FDMEL) Algorithm for Computational Fluid Dynamics
Garcia, S. M.; Chung, T. J.
1997-01-01
Despite significant achievements in computational fluid dynamics, there still remain many fluid flow phenomena not well understood. For example, the prediction of temperature distributions is inaccurate when temperature gradients are high, particularly in shock wave turbulent boundary layer interactions close to the wall. Complexities of fluid flow phenomena include transition to turbulence, relaminarization separated flows, transition between viscous and inviscid incompressible and compressible flows, among others, in all speed regimes. The purpose of this paper is to introduce a new approach, called the Flowfield-Dependent Mixed Explicit-Implicit (FDMEI) method, in an attempt to resolve these difficult issues in Computational Fluid Dynamics (CFD). In this process, a total of six implicitness parameters characteristic of the current flowfield are introduced. They are calculated from the current flowfield or changes of Mach numbers, Reynolds numbers, Peclet numbers, and Damkoehler numbers (if reacting) at each nodal point and time step. This implies that every nodal point or element is provided with different or unique numerical scheme according to their current flowfield situations, whether compressible, incompressible, viscous, inviscid, laminar, turbulent, reacting, or nonreacting. In this procedure, discontinuities or fluctuations of an variables between adjacent nodal points are determined accurately. If these implicitness parameters are fixed to certain numbers instead of being calculated from the flowfield information, then practically all currently available schemes of finite differences or finite elements arise as special cases. Some benchmark problems to be presented in this paper will show the validity, accuracy, and efficiency of the proposed methodology.
Application of Dynamic Logic Algorithm to Inverse Scattering Problems Related to Plasma Diagnostics
Perlovsky, L.; Deming, R. W.; Sotnikov, V.
2010-11-01
In plasma diagnostics scattering of electromagnetic waves is widely used for identification of density and wave field perturbations. In the present work we use a powerful mathematical approach, dynamic logic (DL), to identify the spectra of scattered electromagnetic (EM) waves produced by the interaction of the incident EM wave with a Langmuir soliton in the presence of noise. The problem is especially difficult since the spectral amplitudes of the noise pattern are comparable with the amplitudes of the scattered waves. In the past DL has been applied to a number of complex problems in artificial intelligence, pattern recognition, and signal processing, resulting in revolutionary improvements. Here we demonstrate its application to plasma diagnostic problems. [4pt] Perlovsky, L.I., 2001. Neural Networks and Intellect: using model-based concepts. Oxford University Press, New York, NY.
一种新的动态自适应克隆选择并行算法%Dynamic Adaptive Clone Selection Parallel Algorithm
Institute of Scientific and Technical Information of China (English)
李红婵; 朱颢东
2011-01-01
提出一种新的动态自适应克隆选择并行算法.在每次迭代过程中,动态计算每个抗体的变异概率,根据抗体的亲和度将抗体种群动态分为记忆单元和一般抗体单元,以球面杂交方式对种群进行调整,加快算法的全局搜索速度.同时针对算法计算量大的缺点,设计对应的并行计算方法.实例结果表明,该算法耗时较少,收敛精度较高.%A new dynamic adaptive clone selection algorithm is proposed. Mutation probability of each antibody is dynamically calculated. According to antibody affinity, antibody populations are dynamically divided into memory antibody units and general antibody units. Subsequently, antibody populations are adjusted by sphere crossover, so that global search speed of the proposed algorithm is accelerated. Meanwhile, according to larger calculation and longer consumed time, parallel computation technology is introduced into the provided algorithm. The effectiveness and the feasibility of the proposed algorithm are verified by examples. Example shows that the proposed algorithm has less time-consuming and higher convergence precision.
Shrestha, Kalyan; Mompean, Gilmar; Calzavarini, Enrico
2016-02-01
A finite-volume (FV) discretization method for the lattice Boltzmann (LB) equation, which combines high accuracy with limited computational cost is presented. In order to assess the performance of the FV method we carry out a systematic comparison, focused on accuracy and computational performances, with the standard streaming lattice Boltzmann equation algorithm. In particular we aim at clarifying whether and in which conditions the proposed algorithm, and more generally any FV algorithm, can be taken as the method of choice in fluid-dynamics LB simulations. For this reason the comparative analysis is further extended to the case of realistic flows, in particular thermally driven flows in turbulent conditions. We report the successful simulation of high-Rayleigh number convective flow performed by a lattice Boltzmann FV-based algorithm with wall grid refinement.
Maric, Tomislav; Bothe, Dieter
2013-01-01
A new parallelized unsplit geometrical Volume of Fluid (VoF) algorithm with support for arbitrary unstructured meshes and dynamic local Adaptive Mesh Refinement (AMR), as well as for two and three dimensional computation is developed. The geometrical VoF algorithm supports arbitrary unstructured meshes in order to enable computations involving flow domains of arbitrary geometrical complexity. The implementation of the method is done within the framework of the OpenFOAM library for Computational Continuum Mechanics (CCM) using the C++ programming language with modern policy based design for high program code modularity. The development of the geometrical VoF algorithm significantly extends the method base of the OpenFOAM library by geometrical volumetric flux computation for two-phase flow simulations. For the volume fraction advection, a novel unsplit geometrical algorithm is developed, which inherently sustains volume conservation utilizing unique Lagrangian discrete trajectories located in the mesh points. ...
Shrestha, Kalyan; Mompean, Gilmar; Calzavarini, Enrico
2016-02-01
A finite-volume (FV) discretization method for the lattice Boltzmann (LB) equation, which combines high accuracy with limited computational cost is presented. In order to assess the performance of the FV method we carry out a systematic comparison, focused on accuracy and computational performances, with the standard streaming lattice Boltzmann equation algorithm. In particular we aim at clarifying whether and in which conditions the proposed algorithm, and more generally any FV algorithm, can be taken as the method of choice in fluid-dynamics LB simulations. For this reason the comparative analysis is further extended to the case of realistic flows, in particular thermally driven flows in turbulent conditions. We report the successful simulation of high-Rayleigh number convective flow performed by a lattice Boltzmann FV-based algorithm with wall grid refinement. PMID:26986438
Dejean, Alain; Azémar, Frédéric; Céréghino, Régis; Leponce, Maurice; Corbara, Bruno; Orivel, Jérôme; Compin, Arthur
2016-08-01
Ants, the most abundant taxa among canopy-dwelling animals in tropical rainforests, are mostly represented by territorially dominant arboreal ants (TDAs) whose territories are distributed in a mosaic pattern (arboreal ant mosaics). Large TDA colonies regulate insect herbivores, with implications for forestry and agronomy. What generates these mosaics in vegetal formations, which are dynamic, still needs to be better understood. So, from empirical research based on 3 Cameroonian tree species (Lophira alata, Ochnaceae; Anthocleista vogelii, Gentianaceae; and Barteria fistulosa, Passifloraceae), we used the Self-Organizing Map (SOM, neural network) to illustrate the succession of TDAs as their host trees grow and age. The SOM separated the trees by species and by size for L. alata, which can reach 60 m in height and live several centuries. An ontogenic succession of TDAs from sapling to mature trees is shown, and some ecological traits are highlighted for certain TDAs. Also, because the SOM permits the analysis of data with many zeroes with no effect of outliers on the overall scatterplot distributions, we obtained ecological information on rare species. Finally, the SOM permitted us to show that functional groups cannot be selected at the genus level as congeneric species can have very different ecological niches, something particularly true for Crematogaster spp., which include a species specifically associated with B. fistulosa, nondominant species and TDAs. Therefore, the SOM permitted the complex relationships between TDAs and their growing host trees to be analyzed, while also providing new information on the ecological traits of the ant species involved.
Dejean, Alain; Azémar, Frédéric; Céréghino, Régis; Leponce, Maurice; Corbara, Bruno; Orivel, Jérôme; Compin, Arthur
2016-08-01
Ants, the most abundant taxa among canopy-dwelling animals in tropical rainforests, are mostly represented by territorially dominant arboreal ants (TDAs) whose territories are distributed in a mosaic pattern (arboreal ant mosaics). Large TDA colonies regulate insect herbivores, with implications for forestry and agronomy. What generates these mosaics in vegetal formations, which are dynamic, still needs to be better understood. So, from empirical research based on 3 Cameroonian tree species (Lophira alata, Ochnaceae; Anthocleista vogelii, Gentianaceae; and Barteria fistulosa, Passifloraceae), we used the Self-Organizing Map (SOM, neural network) to illustrate the succession of TDAs as their host trees grow and age. The SOM separated the trees by species and by size for L. alata, which can reach 60 m in height and live several centuries. An ontogenic succession of TDAs from sapling to mature trees is shown, and some ecological traits are highlighted for certain TDAs. Also, because the SOM permits the analysis of data with many zeroes with no effect of outliers on the overall scatterplot distributions, we obtained ecological information on rare species. Finally, the SOM permitted us to show that functional groups cannot be selected at the genus level as congeneric species can have very different ecological niches, something particularly true for Crematogaster spp., which include a species specifically associated with B. fistulosa, nondominant species and TDAs. Therefore, the SOM permitted the complex relationships between TDAs and their growing host trees to be analyzed, while also providing new information on the ecological traits of the ant species involved. PMID:25684460
Low-complexity, high-speed, and high-dynamic range time-to-impact algorithm
Åström, Anders; Forchheimer, Robert
2012-10-01
We present a method suitable for a time-to-impact sensor. Inspired by the seemingly "low" complexity of small insects, we propose a new approach to optical flow estimation that is the key component in time-to-impact estimation. The approach is based on measuring time instead of the apparent motion of points in the image plane. The specific properties of the motion field in the time-to-impact application are used, such as measuring only along a one-dimensional (1-D) line and using simple feature points, which are tracked from frame to frame. The method lends itself readily to be implemented in a parallel processor with an analog front-end. Such a processing concept [near-sensor image processing (NSIP)] was described for the first time in 1983. In this device, an optical sensor array and a low-level processing unit are tightly integrated into a hybrid analog-digital device. The high dynamic range, which is a key feature of NSIP, is used to extract the feature points. The output from the device consists of a few parameters, which will give the time-to-impact as well as possible transversal speed for off-centered viewing. Performance and complexity aspects of the implementation are discussed, indicating that time-to-impact data can be achieved at a rate of 10 kHz with today's technology.
Running GCM physics and dynamics on different grids: Algorithm and tests
Molod, A.
2006-12-01
The major drawback in the use of sigma coordinates in atmospheric GCMs, namely the error in the pressure gradient term near sloping terrain, leaves the use of eta coordinates an important alternative. A central disadvantage of an eta coordinate, the inability to retain fine resolution in the vertical as the surface rises above sea level, is addressed here. An `alternate grid' technique is presented which allows the tendencies of state variables due to the physical parameterizations to be computed on a vertical grid (the `physics grid') which retains fine resolution near the surface, while the remaining terms in the equations of motion are computed using an eta coordinate (the `dynamics grid') with coarser vertical resolution. As a simple test of the technique a set of perpetual equinox experiments using a simplified lower boundary condition with no land and no topography were performed. The results show that for both low and high resolution alternate grid experiments, much of the benefit of increased vertical resolution for the near surface meridional wind (and mass streamfield) can be realized by enhancing the vertical resolution of the `physics grid' in the manner described here. In addition, approximately half of the increase in zonal jet strength seen with increased vertical resolution can be realized using the `alternate grid' technique. A pair of full GCM experiments with realistic lower boundary conditions and topography were also performed. It is concluded that the use of the `alternate grid' approach offers a promising way forward to alleviate a central problem associated with the use of the eta coordinate in atmospheric GCMs.
Spiegelman, M.; Wilson, C. R.
2011-12-01
A quantitative theory of magma production and transport is essential for understanding the dynamics of magmatic plate boundaries, intra-plate volcanism and the geochemical evolution of the planet. It also provides one of the most challenging computational problems in solid Earth science, as it requires consistent coupling of fluid and solid mechanics together with the thermodynamics of melting and reactive flows. Considerable work on these problems over the past two decades shows that small changes in assumptions of coupling (e.g. the relationship between melt fraction and solid rheology), can have profound changes on the behavior of these systems which in turn affects critical computational choices such as discretizations, solvers and preconditioners. To make progress in exploring and understanding this physically rich system requires a computational framework that allows more flexible, high-level description of multi-physics problems as well as increased flexibility in composing efficient algorithms for solution of the full non-linear coupled system. Fortunately, recent advances in available computational libraries and algorithms provide a platform for implementing such a framework. We present results from a new model building system that leverages functionality from both the FEniCS project (www.fenicsproject.org) and PETSc libraries (www.mcs.anl.gov/petsc) along with a model independent options system and gui, Spud (amcg.ese.ic.ac.uk/Spud). Key features from FEniCS include fully unstructured FEM with a wide range of elements; a high-level language (ufl) and code generation compiler (FFC) for describing the weak forms of residuals and automatic differentiation for calculation of exact and approximate jacobians. The overall strategy is to monitor/calculate residuals and jacobians for the entire non-linear system of equations within a global non-linear solve based on PETSc's SNES routines. PETSc already provides a wide range of solvers and preconditioners, from
Institute of Scientific and Technical Information of China (English)
王剑
2011-01-01
For traditional monetary policy instruments,there are many problems about dealing with more and more complicated economic conditions.Asset-based reserve requirements（ABRR） are the feasible choice for monetary policy innovation,which has significant advant%传统的货币政策工具已难以应对日益复杂的经济形势,基于资产的准备金制度在宏观调控、结构调整以及宏观审慎监管等方面都具有显著优势,是货币政策工具创新的一个可行选择。本文对该制度的作用机理、优势与局限性等问题进行了研究,并结合我国货币调控的实践得出一些启示与思考。
分布动载荷识别的并行算法研究%Study on parallel algorithm of the distributed dynamic load identification
Institute of Scientific and Technical Information of China (English)
殷海涛; 姜金辉; 张方; 侯友政
2012-01-01
The paper introduces parallel algorithm for distributed dynamic load identification calculation,to improve the serial algorithm problem of the high time-consuming and insufficient memory t for large-scale mathematical calculations. Based on the theory of one-dimension distributed dynamic identification,the CUDA parallel program of the dynamic load identification is developed. Example proves accuracy and efficiency of the parallel algorithm. The paper provides a new idea to improve the efficiency of the dynamic load identification.%引入并行算法用于求解分布动载荷识别,以改善串行算法造成的大规模数学计算带来的高耗时和内存不足的问题.以一维分布动载荷识别频域法为例,利用C/C++语言编写CUDA并行计算程序,实现了一维分布动载荷识别的并行计算,通过算例证明了并行计算的准确性和高效.为提高动载荷识别中的效率提供了新的思路.
Dynamic Adaptive RRT Path Planning Algorithm%动态自适应快速扩展树航迹规划算法研究
Institute of Scientific and Technical Information of China (English)
潘广贞; 秦帆; 张文斌
2013-01-01
快速扩展随机树(RRT)是航迹规划的重要算法,针对其难以直接应用于无人机航迹规划的问题,提出了动态自适应RRT算法.动态自适应RRT算法在随机点产生过程中加入无人机转弯角约束,使航迹更适合无人机直接跟踪；同时引入动态调节因子,根据环境中障碍密集程度调整规划步长,有效避免各类障碍.计算机实验结果表明动态自适应RRT算法在单航迹规划和多航迹规划中明显优于基本RRT算法和其它改进RRT算法,更适用于无人机航迹规划.%RRT is the important path planning algorithm. In view of its difficult to directly apply in UAVS path planning, this paper puts forwards the dynamic adaptive RRT algorithm. Adding turn corner constraints in the process of random point produce in order to make track for UAVS tracking more directly. At the same time, introduce dynamic adjustment factor, according to the environment of intensive degree to adjust the planning step length and avoid all kinds of barriers effectively. The computer experimental results show that the dynamic adaptive RRT algorithm in single path planning and more significantly than the basic path planning algorithm and other improvements RRT RRT algorithm, more applicable for UAVS path planning.
Institute of Scientific and Technical Information of China (English)
Yujie Wei; Yongheng Jiang; Dexian Huang⁎
2014-01-01
This paper introduces a practical solving scheme of gradetransition trajectory optimization (GTTO) problems under typical certificate-checking–updating framework. Due to complicated kinetics of polymerization, differential/algebraic equations (DAEs) always cause great computational burden and system non-linearity usual y makes GTTO non-convex bearing multiple optima. Therefore, coupled with the three-stage decomposi-tion model, a three-section algorithm of dynamic programming (TSDP) is proposed based on the general iteration mechanism of iterative programming (IDP) and incorporated with adaptivegrid allocation scheme and heuristic modifications. The algorithm iteratively performs dynamic programming with heuristic modifications under constant calculation loads and adaptively allocates the valued computational resources to the regions that can further improve the optimality under the guidance of local error estimates. TSDP is finally compared with IDP and interior point method (IP) to verify its efficiency of computation.
Energy Technology Data Exchange (ETDEWEB)
Choi, Myung Soo; Yang, Kyong Uk [Chonnam National University, Yeosu (Korea, Republic of); Kondou, Takahiro [Kyushu University, Fukuoka (Japan); Bonkobara, Yasuhiro [University of Miyazaki, Miyazaki (Japan)
2016-03-15
We developed a method for analyzing the free vibration of a structure regarded as a distributed system, by combining the Wittrick-Williams algorithm and the transfer dynamic stiffness coefficient method. A computational algorithm was formulated for analyzing the free vibration of a straight-line beam regarded as a distributed system, to explain the concept of the developed method. To verify the effectiveness of the developed method, the natural frequencies of straight-line beams were computed using the finite element method, transfer matrix method, transfer dynamic stiffness coefficient method, the exact solution, and the developed method. By comparing the computational results of the developed method with those of the other methods, we confirmed that the developed method exhibited superior performance over the other methods in terms of computational accuracy, cost and user convenience.
基于评价函数的动态协同任务调度算法%Evaluation function-based dynamic collaboration task scheduling algorithm
Institute of Scientific and Technical Information of China (English)
王璇; 颜景龙
2011-01-01
As the problems that resources change dynamically and tasks access in complex grid environment,a dynamic collaboration task scheduling based on the evaluation function was proposed.This algorithm solves the task cooperation scheduling in dynamic grid by using evaluation function of tasks and collaborators,which vary with time.Compared with distributed cooperation scheduling algorithm based on contract net,theoretical analysis and experimental results show that the algorithm is effective to reduce the system overhead and improve the resource allocation.%针对复杂网格环境中节点资源动态变化及大量任务协作访问的问题,提出一种基于评价函数的动态协作任务调度算法.该算法通过为网格中的协作任务与协作成员建立随时间变化的任务评价函数和协作成员评价函数,实现动态网格环境中的任务协同调度.理论分析与仿真实验表明：与基于合同网的分布式合作调度算法相比,本算法能够减小系统开销,提高资源分配效率.
I. Rafols; L. Leydesdorff
2009-01-01
The aggregated journal-journal citation matrix—based on the Journal Citation Reports (JCR) of the Science Citation Index—can be decomposed by indexers and/or algorithmically. In this study, we test the results of two recently available algorithms for the decomposition of large matrices against two c
International Nuclear Information System (INIS)
Purpose: Image-guided radiotherapy is an advanced 4D radiotherapy technique that has been developed in recent years. However, respiratory motion causes significant uncertainties in image-guided radiotherapy procedures. To address these issues, an innovative lung motion estimation model based on a robust point matching is proposed in this paper. Methods: An innovative robust point matching algorithm using dynamic point shifting is proposed to estimate patient-specific lung motion during free breathing from 4D computed tomography data. The correspondence of the landmark points is determined from the Euclidean distance between the landmark points and the similarity between the local images that are centered at points at the same time. To ensure that the points in the source image correspond to the points in the target image during other phases, the virtual target points are first created and shifted based on the similarity between the local image centered at the source point and the local image centered at the virtual target point. Second, the target points are shifted by the constrained inverse function mapping the target points to the virtual target points. The source point set and shifted target point set are used to estimate the transformation function between the source image and target image. Results: The performances of the authors’ method are evaluated on two publicly available DIR-lab and POPI-model lung datasets. For computing target registration errors on 750 landmark points in six phases of the DIR-lab dataset and 37 landmark points in ten phases of the POPI-model dataset, the mean and standard deviation by the authors’ method are 1.11 and 1.11 mm, but they are 2.33 and 2.32 mm without considering image intensity, and 1.17 and 1.19 mm with sliding conditions. For the two phases of maximum inhalation and maximum exhalation in the DIR-lab dataset with 300 landmark points of each case, the mean and standard deviation of target registration errors on the
Energy Technology Data Exchange (ETDEWEB)
Yi, Jianbing, E-mail: yijianbing8@163.com [College of Information Engineering, Shenzhen University, Shenzhen, Guangdong 518000, China and College of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi 341000 (China); Yang, Xuan, E-mail: xyang0520@263.net; Li, Yan-Ran, E-mail: lyran@szu.edu.cn [College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, Guangdong 518000 (China); Chen, Guoliang, E-mail: glchen@szu.edu.cn [National High Performance Computing Center at Shenzhen, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, Guangdong 518000 (China)
2015-10-15
Purpose: Image-guided radiotherapy is an advanced 4D radiotherapy technique that has been developed in recent years. However, respiratory motion causes significant uncertainties in image-guided radiotherapy procedures. To address these issues, an innovative lung motion estimation model based on a robust point matching is proposed in this paper. Methods: An innovative robust point matching algorithm using dynamic point shifting is proposed to estimate patient-specific lung motion during free breathing from 4D computed tomography data. The correspondence of the landmark points is determined from the Euclidean distance between the landmark points and the similarity between the local images that are centered at points at the same time. To ensure that the points in the source image correspond to the points in the target image during other phases, the virtual target points are first created and shifted based on the similarity between the local image centered at the source point and the local image centered at the virtual target point. Second, the target points are shifted by the constrained inverse function mapping the target points to the virtual target points. The source point set and shifted target point set are used to estimate the transformation function between the source image and target image. Results: The performances of the authors’ method are evaluated on two publicly available DIR-lab and POPI-model lung datasets. For computing target registration errors on 750 landmark points in six phases of the DIR-lab dataset and 37 landmark points in ten phases of the POPI-model dataset, the mean and standard deviation by the authors’ method are 1.11 and 1.11 mm, but they are 2.33 and 2.32 mm without considering image intensity, and 1.17 and 1.19 mm with sliding conditions. For the two phases of maximum inhalation and maximum exhalation in the DIR-lab dataset with 300 landmark points of each case, the mean and standard deviation of target registration errors on the
Progress research of dynamic algorithms in community detection%动态社区发现算法的研究进展
Institute of Scientific and Technical Information of China (English)
王莉军; 杨炳儒; 翟云; 谢永红
2011-01-01
This paper summaried the main research progress of dynamic community detection internationally recent years. Firstly, it analyzed the principle of dynamic algorithms in community detection from the three aspects, such as synchronization, spin and random walk. Secondly, it deeply analyzed and comprehensive compared the several dynamic algorithms in community detection currently. And last, pointed out the hot research issues of dynamic community detection and the major problems need to focus in the future.%综述了近年来国内外对动态社区发现的主要研究进展.从同步、自旋和随机游动三个方面分析了动态社区发现算法的原理.对目前存在的各种动态社区发现算法进行了深入剖析和全面比较,指出当前动态社区发现的研究热点及将来需要重点关注的主要问题.
Rafols, Ismael
2008-01-01
The aggregated journal-journal citation matrix -based on the Journal Citation Reports (JCR) of the Science Citation Index- can be decomposed by indexers and/or algorithmically. In this study, we test the results of two recently available algorithms for the decomposition of large matrices against two content-based classifications of journals: the ISI Subject Categories and the field/subfield classification of Glaenzel & Schubert (2003). The content-based schemes allow for the attribution of more than a single category to a journal, whereas the algorithms maximize the ratio of within-category citations over between-category citations in the aggregated category-category citation matrix. By adding categories, indexers generate between-category citations, which may enrich the database, for example, in the case of inter-disciplinary developments. The consequent indexer effects are significant in sparse areas of the matrix more than in denser ones. Algorithmic decompositions, on the other hand, are more heavily ...
Directory of Open Access Journals (Sweden)
Suresh Chandra Maurya
2011-07-01
Full Text Available In this paper DCA using modified Genetic Algorithm (MGA is applied to a Broadband Fixed Wireless Access (BFWA network that provides data services. The performance of the modified GA is compared using a simulation with other DCAs namely the Least Interfered (LI and Channel Segregation (CS and simple genetic algorithm. It is shown that the modified GA has the highest throughput and is more capable of adapting to interference and reconverging to a new stable state.
Improved Dynamic Adaptive Clone Selection Algorithm%改进型动态自适应克隆选择算法
Institute of Scientific and Technical Information of China (English)
刘俊辉; 李娜
2012-01-01
At present, clone selection algorithm is an intelligent optimization algorithm which is widely applied However, traditional clone selection algorithm has the deficiency of blind selection. In order to overcome this deficiency, an improved dynamic adaptive clone selection algorithm was proposed. Firstly, according to affinity, antibody population was dynamically divided into memory antibody units and general antibody units. And then, variation probability of each antibody which was dynamically corrected by means of affinity was used to carry out variation operatioa Subsequently, antibody population was adjusted by sphere crossover to generate new population. The selection and the global search speed of the proposed algorithm are improved through the afore-mentioned strategies. The effectiveness and the feasibility of the proposed algorithm are verified by simulation results.%克隆选择算法是日前应用较广的一种智能优化算法,但它在选择时具有一定的盲目性.为了克服它的这个不足,论文提出了一种改进型动态自适应克隆选择算法.在该算法中,首先根据抗体的亲和度将抗体群动态分为记忆单元和一般抗体单元,然后再借助抗体的亲和度修正抗体的变异概率并根据修正后的变异概率进行变异操作,紧接着以球面杂交方式对种群进行调整以产生新的种群.上述策略使得该算法在选择时具有一定的针对性,从而加快了它的全局搜索速度,仿真结果验证了所提算法的有效性、可行性.
Measurement of dynamic young's modulus using Mallat algorithm%基于Mallat算法的动弹性模量测量研究
Institute of Scientific and Technical Information of China (English)
王磊; 刘瑞安
2011-01-01
In the dynamic young's modulus test of concrete and other rigid materials, the system carries out Mallat algorithm by DSP (digital signal processor) platform, which simplifies the calculation of the dynamic young's modulus test in the frequency domain, based on the characters of resonant waveforms, such as non-stationary, transient, widespread of frequency etc. Using Mallat algorithm's advantages of multi-scale analysis, discrete displacement and smaller computation, the system can calculate quickly the resonant frequency of dynamic young's modulus signal's power spectrum. Experiment demonstrates that the Mallat algorithm can make the resonant frequency detection of dynamic young's modulus achieve high speed and high precision.%在混凝土等刚性材料的动弹性模量测量中,针对谐振测试波形的非平稳、瞬态且频率分布广等特点,系统基于DSP平台和Mallat算法,将动弹性模量测量简化到频域角度进行计算.利用Mallat算法的多尺度分析、位移离散化和计算量小等优点,可快速计算出动弹性模量的测试信号功率谱中共振频率.实验验证了Mallat算法对于动弹性模量中的谐振频率检测具有速度快、精确度高的优点.
Particle Swarm Optimization Algorithm with Dynamic Learning Objects%一种动态学习对象的粒子群优化算法
Institute of Scientific and Technical Information of China (English)
曹智方; 王国胤; 申元霞
2011-01-01
To overcome the disadvantage of Particle Swarm Optimization(PSO) algorithm such as premature, bad convergence precision, based on feedback of swarm diversity, a PSO algorithm with Dynamic Learning Objects(PSO-DLO) is presented. In the algorithm swarm diversity is used to control the learning objects, the strategy relieves the lost of swarm diversity, which is helpful for the global search. Experiments of three typical multi-modal functions indicate that the algorithm can effectively avoid premature and achieve better global search ability.%针对粒子群优化算法容易早熟、收敛精度低等问题,基于群体多样性反馈的思想,提出一种动态学习对象的粒子群优化算法.该算法采用群体多样性动态控制粒子的学习对象,减缓群体多样性的丧失速度,有利于群体的全局寻优.对3种典型多峰函数的仿真结果表明,该算法可以有效避免早熟问题,具有较好的全局寻优能力.
Directory of Open Access Journals (Sweden)
Carsten Kendziorra
Full Text Available This paper presents a phase detection algorithm for four-dimensional (4D cardiac computed tomography (CT analysis. The algorithm detects a phase, i.e. a specific three-dimensional (3D image out of several time-distributed 3D images, with high contrast in the left ventricle and low contrast in the right ventricle. The purpose is to use the automatically detected phase in an existing algorithm that automatically aligns the images along the heart axis. Decision making is based on the contrast agent distribution over time. It was implemented in KardioPerfusion--a software framework currently being developed for 4D CT myocardial perfusion analysis. Agreement of the phase detection algorithm with two reference readers was 97% (95% CI: 82-100%. Mean duration for detection was 0.020 s (95% CI: 0.018-0.022 s, which was 800 times less than the readers needed (16±7 s, p<03001. Thus, this algorithm is an accurate and fast tool that can improve work flow of clinical examinations.
Directory of Open Access Journals (Sweden)
R. Deepalakshmi
2014-01-01
Full Text Available Today, Internet of Things (IoT has introduced abundant bandwidth consumption and necessities in multimedia communications from online games to video-conferencing applications with the constraint of QoS requirements from time to time. The expected rapid proliferation of services would require performance unprecedented in the currently available best-effort routing algorithms. In, particular, the present routing mechanisms are based on the best-effort paradigm are unlikely to provide satisfactory end-to-end performance for services required in the real time applications. Thus, there is a definite need for architectures and algorithms that provide bandwidth guaranteed and QoS guarantees beyond those of the currently available ones. The proposed routing algorithm addressed the problem by computing low cost trees with delay bounded within the model wherein the bandwidth can be reserved and guaranteed once reserved on various links of the network there by providing QoS guarantees. This novel tree-pruning algorithm aids the bandwidth measurement tools by applying heuristic approach and the effectiveness of the algorithm is determined by two factors (i the end-to-end delay (ii the cost of routing. The new data structure significantly improves the running time complexity by O (log k for routing procedures under a variety of QoS constraints and checking tree routing runs in O(m+n^{2}.
An Improved Algorithm of LRFU-CLRFU Based on CAR Dynamic Adjustment%基于CAR动态调整的改进LRFU算法--CLRFU
Institute of Scientific and Technical Information of China (English)
王小林; 还璋武
2016-01-01
目前,已有LRFU( Least Recently Frequently Used)方法结合了访问时间和访问次数来优化缓存,但却无法适用于操作系统、存储系统、web应用等复杂场景。为了解决LRFU算法中无法动态调整λ以及现有自适应调整算法无法兼顾多种访问模式的问题,本文提出了一种基于CAR ( Clock with Adaptive Replacement)动态调整策略的改进LRFU算法———CLRFU,并将该算法与局部性定量分析模型相结合,能够在不同访问模式下动态调整λ。实验结果表明,CLRFU算法在线性、概率和强局部访问模式下都具有较好的适应性,提高了缓存整体命中率。%At present,existing LRFU ( Least Recently Frequently Used) method is a combination of access time and the number of ac-cess to optimize cache, but it will not apply to operating systems, storage systems, web applications and other complex scenes. In order to solve the LRFU algorithm in dynamic adjustmentλand the existing adaptive algorithm can't combine multiple access mode, this paper proposes a improved LRFU algorithm-CLRFU which is based on the CAR ( Clock with the Adaptive Replacement) , with local quantita-tive analysis model, the combination of dynamic adjustment λ to different access mode. The experimental results show that the CLRFU algorithm has good adaptability in linear, probability and the strong local access mode and improve the cache hit ratio as a whole.
Institute of Scientific and Technical Information of China (English)
钱忠根; 白延琴
2005-01-01
In this paper, primal-dual interior-point algorithm with dynamic step size is implemented for linear programming (LP) problems. The algorithms are based on a few kernel functions, including both self-regular functions and non-self-regular ones. The dynamic step size is compared with fixed step size for the algorithms in inner iteration of Newton step. Numerical tests show that the algorithms with dynamic step size are more efficient than those with fixed step size.
The Variable Size Memory-based Evolutionary Algorithm in Dynamic Environments%动态环境下基于可变记忆的进化算法
Institute of Scientific and Technical Information of China (English)
关守平; 尹晓峰
2011-01-01
常规基于记忆的进化算法在动态环境中往往达不到期望的效果,这主要是由于记忆体大小的限制.为此提出了动态环境下基于可变记忆的进化算法(IMEEA),其核心思想是算法中拥有两个种群,即搜索种群和记忆种群,同时采用过度变异策略来增加种群的多样性.算法中的两个种群有最小和最大的允许长度,并且种群的大小根据进化过程的进行而不断变化.仿真结果表明,在动态环境中IMEEA算法的跟踪误差要小于常规的记忆提高进化算法(MEEA),从而证明了所提算法的有效性.%Traditional memory-based evolutionary algorithms often may not achieve the desired performances in dynamic environments, which is mainly due to the fixed memory size. A variable size memory-based evolutionary algorithm is proposed. The improved memory enhanced evolutionary algorithm (IMEEA), which combines memory population and search population,and hyper-mutation is used to promote and maintain diversity. The two populations have minimum and maximum sizes allowed that change according to the stage of the evolutionary process. Simulation results show that the tracking error of the IMEEA is less than the memory enhanced evolutionary algorithm (MEEA), and then prove the effectiveness of this new algorithm.
Institute of Scientific and Technical Information of China (English)
黄松柏
2011-01-01
在虚拟场景中普遍采用基于OBB包围盒的碰撞检测技术,然而传统算法对于大数据量模型的检测仍然效率不高,难以保证实时性.在分析了OBB及其改进算法的基础上,采用改进的OBB中心计算方法,使包围盒能够更紧密的包围模型,提高碰撞检测的准确性和时间效率.在碰撞检测过程中动态地建立OBB层次结构,减少了时间复杂度和空间复杂度.分析和实验结果证明,改进后的算法在处理一般曲面模型尤其是大数据曲面模型时,碰撞检测的稳定性和效率都有明显提高.%The collision detection algorithm based on the orientation bounding box (OBB) is widely used in the virtual environment, but the traditional algorithm has low efficiency while processing the large surface models, and can't guarantees the real-time performance. An improved algorithm was developed based on a new method that computes the centre of the orientation bounding box, which ensures the bounding box enclosing the model more closely and improves the accuracy and time efficiency of collision detection. By using the algorithm, the OBB hierarchy tree can be built dynamically while collision detecting, and thus the time cost and memory cost could be decreased. The theoretical analysis and experiments prove that the improved algorithm enhances the stability and efficiency obviously while processing the collision detection of large surface models.
Dall'Anese, Emiliano; Dhople, Sairaj; Giannakis, Georgios B.
2014-01-01
This paper considers a collection of networked nonlinear dynamical systems, and addresses the synthesis of feedback controllers that seek optimal operating points corresponding to the solution of network-wide constrained optimization problems. Particular emphasis is placed on the solution of semidefinite programs (SDPs). The design of the feedback controller is grounded on a dual epsilon-subgradient approach, with the dual iterates utilized to dynamically update the dynamical-system reference...
Kartiwa, Iwa; Jung, Sang-Min; Hong, Moon-Ki; Han, Sang-Kook
2014-03-01
In this paper, we propose a novel fast adaptive approach that was applied to an OFDM-PON 20-km single fiber loopback transmission system to improve channel performance in term of stabilized BER below 2 × 10-3 and higher throughput beyond 10 Gb/s. The upstream transmission is performed through light source-seeded modulation using 1-GHz RSOA at the ONU. Experimental results indicated that the dynamic rate adaptation algorithm based on greedy Levin-Campello could be an effective solution to mitigate channel instability and data rate degradation caused by the Rayleigh back scattering effect and inefficient resource subcarrier allocation.