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检索条件"任意字段=16th International Conference and Workshops on Algorithms and Computation"

共 216 条记录，以下是121-130 订阅

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Estimating of computation time of parallel algorithm of computations of dynamic processes in GPU systems

Estimating of computation time of parallel algorithm of comp...

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international conference on computational Problems of Electrical Engineering (CPEE)

作者： Marcin Cegielski Institute of Information Technology Lodz University of Technology Lodz Poland

A parallel process of computation of dynamic processes is based on a diakoptic theory of the portioning of the system into the sub-systems, that are computed independent of each other, in the fixed time intervals. Every process is defined by the complexity of computation. this complexity is changed in the time of process of computations. these properties are utilized to implement computation in parallel systems. Currently the growth of parallel systems has been observed for several years. In this article, idea of GPU computations and parallel algorithms are presented. the results of computation on tested parallel system are shown and interpreted.

关键词： Decision support systems

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An approach to optimize the proportional-integral-derivative controller system

An approach to optimize the proportional-integral-derivative...

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international Carpathian Control conference (ICCC)

作者： S. Dadvandipour N. Khalili Dizaji S. Rosshan Entezar Faculty of Mechanics and Information Science University of Miskolc

this paper aims at using imperialist competitive algorithm based fuzzy logic (FICA), to control an automatic voltage regulator (AVR) in order to increase the stability and obtain more controllability of the system. For the stabilization of the automatic voltage regulator a proportional-integral-derivative controller (PID) was used. We applied the FICA, which is the combination of the imperialist competitive algorithm (ICA) and fuzzy logic to determine the optimal coefficients of the proportional-integral-derivative controller (PID). the new algorithm solves the main problems of the imperialist competitive algorithm (ICA), which are entrapped in local optimum points and low-speed convergence. this way, the control of the effective parameters of the (ICA) likes as the assimilation coefficient and the cost of colonies is performed with high accuracy and speed. We will show that the results obtained with the proposed intelligent algorithm (FICA), have higher convergence rate and more accuracy in comparison with the other algorithms.

关键词： Convergence Fuzzy logic Evolutionary computation Optimization Correlation Aerospace electronics

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Efficient hardware multiplier design for pairing computation

Efficient hardware multiplier design for pairing computation

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international conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)

作者： Chiraz Massoud Anissa Sghaier Medien Zeghid Mohssen Machhout Faculty of Sciences Laboratory of Electronics and Microelectronics Monastir

ISBN: (纸本)9781467392358

In Public Key Cryptography, the most costly arithmetic operation is first inversion then multiplication. there aren't big researches concerning modular inversion, it exist two famous algorithms which are Fermat and Extended Euclid algorithms. All researches are oriented to the modular multiplier, it exist a big number of methods to compute it. the goal of our paper is to present a of a 256-bits multiplier design, to compute pairings at security level of 128-bits. Our hardware architecture exploits FPGA features (Fast Carry Chain and DSP), for this reason, it's less constrained in memory and power consumption. these performances prove the limitations of the restrained environment. Our design is coded in VHDL language and synthesized using Xilinx ISE 14.5 on Virtex 6 FPGA XC6VLX240T devices. Our multiplier used only 1665 slices and 3 DSP, it runs at 149.8 MHz clock frequency.

关键词： Computer architecture Algorithm design and analysis Digital signal processing Adders Hardware Field programmable gate arrays Clocks

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Efficient computation of Group Optimal Sequenced Routes in Road Networks

Efficient Computation of Group Optimal Sequenced Routes in R...

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international conference on Mobile Data Management

作者： Samiha Samrose Tanzima Hashem Sukarna Barua Mohammed Eunus Ali Mohammad Hafiz Uddin Md. Iftekhar Mahmud Mohammad Hafiz Uddin BUET Dhaka Bangladesh Bangladesh University of Engineering and Technology Dhaka Dhaka District BD

the proliferation of location-based social networks allows people to access location-based services as a group. We address Group Optimal Sequenced Route (GOSR) queries that enable a group to plan a trip with a minimum aggregate trip distance. the trip starts from the source locations of the group members, goes via a predefined sequence of different point of interests (POIs) such as a restaurant, shopping center and movie theater, and ends at the destination locations of the group members. the aggregate trip distance can be the total or the maximum trip distance of the group members. We introduce a novel approach to efficiently compute group optimal sequenced routes in road networks. We exploit elliptical properties to refine the POI search space and develop efficient algorithms for GOSR queries. Experiments show that our approach outperforms a naive approach significantly in terms of processing time and I/Os.

关键词： Aggregates Roads Position measurement Query processing Space exploration Planning

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Privacy preserving health data processing 16

Privacy preserving health data processing

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16th IEEE international conference on e-Health Networking, Applications and Services (Healthcom)

作者： Andersen, Anders Yigzaw, Kassaye Yitbarek Karlsen, Randi UiT Arcic Univ Norway Fac Sci & Technol Dept Comp Sci N-9037 Tromso Norway

ISBN: (纸本)9781479966448

the usage of electronic health data from different sources for statistical analysis requires a toolset where the legal, security and privacy concerns have been taken into consideration. the health data are typically located at different general practices and hospitals. the data analysis consists of local processing at these locations, and the locations become nodes in a computing graph. To support the legal, security and privacy concerns, the proposed toolset for statistical analysis of health data uses a combination of secure multi-party computation (SMC) algorithms, symmetric and public key encryption, and public key infrastructure (PKI) with certificates and a certificate authority (CA). the proposed toolset should cover a wide range of data analysis with different data distributions. To achieve this, large set of possible SMC algorithms and computing graphs have to be supported.

关键词： authorisation data analysis data privacy electronic health records graph theory public key cryptography statistical analysis CA PKI SMC algorithms certificate authority computing graph electronic health data processing public key encryption public key infrastructure secure multiparty computation Data privacy Encryption Privacy Public key Receivers Snow public key cryptography Data privacy Data analysis Public key encryption Certification authority Privacy secure multi-party computation Statistical analysis Statistical methods Public key Electronic Health Records Authorization cryptography Graph theory Receivers

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SAX-EFG: An Evolutionary Feature Generation Framework for Time Series Classification 14

SAX-EFG: An Evolutionary Feature Generation Framework for Ti...

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16th Genetic and Evolutionary computation conference (GECCO)

作者： Kamath, Uday Lin, Jessica De Jong, Kenneth George Mason Univ Fairfax VA 22030 USA

ISBN: (纸本)9781450326629

A variety of real world applications fit into the broad definition of time series classi fication. Using traditional machine learning approaches such as treating the time series sequences as high dimensional vectors have faced the well known "curse of dimensionality" problem. Recently, the field of time series classi fication has seen success by using preprocessing steps that discretize the time series using a Symbolic Aggregate ApproXimation technique (SAX) and using recurring subsequences ("motifs") as features. In this paper we explore a feature construction algorithm based on genetic programming that uses SAX-generated motifs as the building blocks for the construction of more complex features. the research shows that the constructed complex features improve the classi fication accuracy in a statistically signi ficant manner for many applications.

关键词： algorithms machine learning time-series classification genetic programming evolutionary computation

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Initial experiments in visualization of empirical attainment function differences using maximum intensity projection 14

Initial experiments in visualization of empirical attainment...

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16th Genetic and Evolutionary computation conference Companion, GECCO 2014 Companion

作者： Tušar, Tea Filipič, Bogdan Department of Intelligent Systems Jožef Stefan Institute Jožef Stefan International Postgraduate School Jamova cesta 39 SI-1000 Ljubljana Slovenia

ISBN: (纸本)9781450328814

In multiobjective optimization, the Empirical Attainment Function (EAF) can be used to determine which areas of the objective space are attained by an optimization algorithm. If two algorithms are to be compared, differences in EAF values show which areas of the objective space are more often attained by one of the algorithms. While the visualization of EAF values and differences is rather straightforward in 2D, the 3D case presents a great challenge as we need to visualize a large number of 3D cuboids. this paper presents a method for computing the cuboids with constant EAF values and reports on initial experiments using Maximum Intensity Projection, a very-well known volume rendering technique used in medicine.

关键词： Multiobjective optimization

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Applying OpenMP-based Parallel Implementations of NSGA-II and SPEA2 to Study Phylogenetic Relationships 16

Applying OpenMP-based Parallel Implementations of NSGA-II an...

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16th IEEE international conference on Cluster Computing (CLUSTER)

作者： Santander-Jimenez, Sergio Vega-Rodriguez, Miguel A. Univ Extremadura Dept Technol Comp & Commun Caceres Spain

ISBN: (纸本)9781479955480

throughout the years, biological processing demands have been addressed by relying on the design of algorithmic approaches for parallel architectures. By taking advantage of multicore processor systems, we can deal with the main sources of complexity which explain the NP-hard nature of multiple problems in computational biology. In this work, we address the inference of phylogenetic topologies by using two multiobjective metaheuristics: Fast Non-Dominated Sorting Genetic Algorithm and Strength Pareto Evolutionary Algorithm 2. the additional complexity introduced by the multiobjective formulation of the problem motivates that parallel designs of these algorithms must be undertaken. For this purpose, OpenMP-based implementations of these two metaheuristics are applied. To evaluate the performance of these approaches, a comparative study has been conducted by performing experimentation on four nucleotide data sets. Our experiments suggest the relevance of these parallel algorithmic designs, improving the phylogenetic results reported by other multiobjective tools in reduced execution times.

关键词： Multiobjective optimization evolutionary computation parallel computing phylogeny reconstruction

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Track Loss versus computation Time Dilemma in Multitarget Ground Target Tracking Performance

Track Loss versus Computation Time Dilemma in Multitarget Gr...

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16th international conference on Information Fusion (FUSION)

作者： Korkmaz, Yusuf Baykal, Buyurman Middle E Tech Univ Dept Elect & Elect Engn TR-06531 Ankara Turkey

ISBN: (纸本)9786058631113

Tracking of multiple ground targets with airborne Ground Moving Target Indicator (GMTI) sensor measurements is a challenging problem where heavy and dense false alarms with high target density are inevitably encountered in the surveillance scenes. Hence, optimal approaches require heavy computational load where the duration of overall computation rises exponentially with the number of target tracks and measurements in observation per scan. Consequently, more practical suboptimal approaches, such as Linear Multi-Target (LM) approach, is explored due to linear number of operations in the number of target tracks with a negligible performance loss compared to optimal approaches. Although LM approach performs modestly adequate with significantly less computation duration than optimal approaches, it is highly susceptible to track loss, as in the rest of suboptimal approaches, when the targets are closely spaced and the number of targets and measurements are considerably high. Simulations are carried out in realistic test scenarios to compare single target tracking algorithms including IMM-PDA and IMM-IPDA algorithms;Optimal approaches in multitarget tracking including IMM-JPDA, IMM-IJPDA and IMM-JIPDA algorithms and an example of Linear Multi-target approaches in multitarget tracking including IMM-LMIPDA algorithm. Benchmarkings of these algorithms are done under RMSE performance, track loss and computation time evaluation results.

关键词： Target tracking multiple target tracking Targets algorithms operation number computational time Track ground Heavy Dilemma

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Dynamic Scheduling of Imprecise-computation Tasks on Real-Time Embedded Multiprocessors

Dynamic Scheduling of Imprecise-Computation Tasks on Real-Ti...

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IEEE 16th international conference on computational Science and Engineering (CSE)

作者： Yu, Heng Veeravalli, Bharadwaj Ha, Yajun Luo, Shaobo Natl Univ Singapore Dept Elect & Comp Engn Singapore 117548 Singapore

ISBN: (纸本)9781479948970

Adaptability as an emerging design trend for embedded systems has been of increasing interest. As the representative QoS-adaptable application/software model, Imprecise-computation (IC) gains growing attentions on its ability to provide scalable execution quality by trading-off system resources. Tight coupling between application temporal characteristics and execution quality makes scheduling imperative. While existing QoS-aware scheduling methods are applicable for uniprocessor scenarios, few efforts address the multiprocessor problem. Moreover, significant leakage contribution to energy consumption, due to advanced silicon processing technology, has further complicated the scheduling problem. In this paper, we present a dynamic scheduling algorithm for IC-modeled tasks on real-time embedded multiprocessor systems, aiming at maximizing runtime QoS under timing and energy constraints. Based on the idea of runtime slack reclamation, we firstly analyze the key factors that affect the QoS optimality during slack distribution. the optimality analysis, then, serves as a guideline for a dual-phase slack receiver selection scheme that identifies the best slack receiver candidates. Compared to state-of-the-art dynamic algorithms, our approach can achieve 54.9% more QoS increase with negligible runtime overhead.

关键词： dynamic scheduling Pulverized coal Multiprocessor system resources Runtime Quality of service Embedded systems Religious Missions

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