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Milanesi_EGEE`09_Barcellona
Milanesi_EGEE`09_Barcellona

... support, to provide a comprehensive and coherent view of the same objects in light of different data sources; • the third layer is mapping information gained about interacting objects into networks and pathways that may be used as basic models for the underlying cellular systems. ...
A Precorrected-FFT method for Electrostatic Analysis of Complicated
A Precorrected-FFT method for Electrostatic Analysis of Complicated

... electrical packaging, and design of microelectromechanical systems [2] require accurate electrostatic analysis of complicated three-dimensional (3-D) structures. Recent work on techniques for rapid electrostatic analysis for capacitance extraction have been based on random-walk methods [3], partitio ...
Solving 3D incompressible Navier-Stokes equations on hybrid CPU
Solving 3D incompressible Navier-Stokes equations on hybrid CPU

... In Eq. (1), V = (V1 ,V2 ,V3 )T (x1 , x2 , x3 ,t) is the 3D velocity vector and P = P(x1 , x2 , x3 ,t) is the fluid pressure. The Reynolds number Re is the ratio of the characteristic inertial and viscous forces. As Re increases, non-linear effects arising from the non-linear convection term ∇ · (V ⊗ ...
Random Walk With Continuously Smoothed Variable Weights
Random Walk With Continuously Smoothed Variable Weights

... variables in the flip heuristic. An obvious way to do this is to prefer variables that were not flipped recently, but this is an old idea used in several algorithms. HSAT, HWSAT, Novelty and R-Novelty prefer least-recently flipped variables, the latter incorporating a tabu tenure of 1 flip. Tie-bre ...
Information Gathering and Reward Exploitation of Subgoals for
Information Gathering and Reward Exploitation of Subgoals for

... Recent point-based planning algorithms have made impressive improvements by addressing one or the other of the above challenges: PBVI (Pineau, Gordon, and Thrun 2003), HSVI2 (Smith and Simmons 2004; 2005), FSVI (Shani, Brafman, and Shimony 2007) and SARSOP (Kurniawati, Hsu, and Lee 2008) work very s ...
Dynamic Programming
Dynamic Programming

... • If there were a less costly way to parenthesize Ai…k, we could substitute that one in the parenthesization of Ai…j and produce a parenthesization with a lower cost than the optimum  contradiction! • An optimal solution to an instance of the matrix-chain multiplication contains within it optimal s ...
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European and German Grid Projects

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Spinglass

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Analysis of Algorithms CS 465/665

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Solve Simple Linear Equation using Evolutionary Algorithm
Solve Simple Linear Equation using Evolutionary Algorithm

... Genetic algorithms can be used when no information is available about the gradient of the function at the evaluated points. The function itself does not need to be continuous or differentiable. Genetic algorithms can still achieve good results even in cases in which the function has several local mi ...
Part 3: Lattice: Quantum to Ising to RG
Part 3: Lattice: Quantum to Ising to RG

... same, physical quantities like the correlation length and the entropy are unchanged, but their description in terms of couplings and lattice constants has changed. In particular, the new lattice spacing is a´ =2a, but the correlation length is exactly the same ξ´ = ξ. Since we know that the correlat ...
convergence results for ant routing algorithms via stochastic approximation and optimization
convergence results for ant routing algorithms via stochastic approximation and optimization

... basic idea. These algorithms employ probe packets called ant packets (analogues of ants) to explore the network and measure various quantities related to network routing performance like link and path delays. These measurements are used to construct and update the routing tables at the network nodes ...
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Introduction to High Performance Computing

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Research Article Continuum Modeling and Control of Large Nonuniform

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Optimal Resource Allocation for MIMO Ad Hoc Cognitive Radio
Optimal Resource Allocation for MIMO Ad Hoc Cognitive Radio

... corresponding team optimization problem, is developed and its convergence proved. Each link in the network needs to solve a convex optimization problem per iteration, requiring only local feedback from the interfering links. C2) A semidistributed algorithm is developed based on primal decomposition ...
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ppt - M Sakthi Balan

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Numerical Methods for Computing Casimir

... developing numerical methods for Casimir interactions, from the time the phenomenon was first proposed in 1948 [28], can be explained by three factors. First, accurate measurements of Casimir forces were first reported only in 1997 [29] and experimental interest in complex Casimir geometries and mat ...
Research Article Classification of Textual E-Mail Spam
Research Article Classification of Textual E-Mail Spam

... A new method for clustering of spam messages collected in bases of antispam system is offered. The genetic algorithm is developed for solving clustering problems. The objective function is a maximization of similarity between messages in clusters, which is defined by k-nearest neighbor algorithm. App ...
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The poverty of selectionism and its relevance for the study of

Achieving Maximum Energy-Efficiency in Multi-Relay
Achieving Maximum Energy-Efficiency in Multi-Relay

... frequency division multiple access (OFDMA) cellular network, where the objective function is formulated as the ratio of the spectral-efficiency (SE) over the total power dissipation. It is proven that the fractional programming problem considered is quasi-concave so that Dinkelbach’s method may be e ...
Scaling Complex Applications
Scaling Complex Applications

... – On 2k processors or more – Each timestep, ideally, will be about 12-14 msec for ATPase – Within that time: each processor sends and receives : • Approximately 60-70 messages of 4-6 KB each – Communication layer and/or OS has small “hiccups” • No problem until 512 processors • Small rare hiccups ca ...
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Determination of Boiling Range of Xylene Mixed

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Diapositiva 1 - uni
Diapositiva 1 - uni

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Algorithm GENITOR

... signals that reach the next Si stations. Note that Si is a r.v. dependent on power and availability of retransmitter amplifiers. The aim of the system is to provide propagation of a signal from transmitter to receiver. The LMCCS was first introduced by Hwang & Yao [1] as a generalization of linear ...
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Natural computing

Natural computing, also called natural computation, is a terminology introduced to encompass three classes of methods: 1) those that take inspiration from nature for the development of novel problem-solving techniques; 2) those that are based on the use of computers to synthesize natural phenomena; and 3) those that employ natural materials (e.g., molecules) to compute. The main fields of research that compose these three branches are artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, fractal geometry, artificial life, DNA computing, and quantum computing, among others.Computational paradigms studied by natural computing are abstracted from natural phenomena as diverse as self-replication, the functioning of the brain, Darwinian evolution, group behavior, the immune system, the defining properties of life forms, cell membranes, and morphogenesis. Besides traditional electronic hardware, these computational paradigms can be implemented on alternative physical media such as biomolecules (DNA, RNA), or trapped-ion quantum computing devices.Dually, one can view processes occurring in nature as information processing. Such processes include self-assembly, developmental processes, gene regulation networks, protein-protein interaction networks, biological transport (active transport, passive transport) networks, and gene assembly in unicellular organisms. Efforts tounderstand biological systems also include engineering of semi-synthetic organisms, and understanding the universe itself from the point of view of information processing. Indeed, the idea was even advanced that information is more fundamental than matter or energy. The Zuse-Fredkin thesis, dating back to the 1960s, states that the entire universe is a huge cellular automaton which continuously updates its rules.Recently it has been suggested that the whole universe is a quantum computer that computes its own behaviour.
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