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Stochastic Formulation of Newton's Acceleration

Stochastic Formulation of Newton's Acceleration

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9th international conference on Large-Scale Scientific Computations (LSSC)

作者： Schwaha, P. Nedjalkov, M. Selberherr, S. Sellier, J. M. Dimov, I. Georgieva, R. Bulgarian Acad Sci Inst Parallel Proc Acad G Bontchev Str Bl25A BU-1113 Sofia Bulgaria TU Wien Inst Microelect A-1040 Vienna Austria AVL List GmbH A-8020 Graz Austria

ISBN: (纸本)9783662438800;9783662438794

the theoretical equivalence of the Wigner and ballistic Boltzmann equations for up to quadratic electric potentials provides the convenient opportunity to evaluate stochastic algorithms for the solution of the former equation with the analytic solutions of the latter equation - Liouville trajectories corresponding to acceleration due to a constant electric field. the direct application of this idea is impeded by the fact that the analytic transformation of the first equation into the second involves generalized functions. In particular, the Wigner potential acts as a derivative of the delta function which gives rise to a Newtonian accelerating force. the second problem is related to the discrete nature of the Wigner momentum space. these peculiarities incorporate unphysical effects in the approximate Wigner solution, which tends to the Boltzmann counterpart in a limiting case only.

关键词： Delta functions

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Advanced architectures distributed systems for the implementation of neural networks

Advanced architectures distributed systems for the implement...

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international conference on Emerging eLearning technologies and applications (ICETA)

作者： M. Čopjak M. Tomášek J. Hurtuk Dept. of Computers and Informatics FEI TU of Košice Slovak Republic Dept. of Computers and Informatics FEI TU of Koš¡ice Slovak Republic

Many industries nowadays use management and decision making based on artificial neural networks. However, the major drawback of neural networks lies in their time and computational complexity. the problem with computational complexity could be eliminated using sharing of the computing needs on multiple computing nodes. this article focuses on the architectural design of a distributed system, which aims to solve large neural networks. the article describes the technology GPGPU and the next part of the article deals with an overview of methods for speeding up the calculation and distribution of artificial neural network. the main section describes the design of a model architecture description of the algorithm that allows correct data distribution on computational nodes.

关键词： Graphics processing units Computer architecture parallel processing Neurons Hardware Biological neural networks

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computing static schedule for the hosts in a real-time distributed system with component based applications

Computing static schedule for the hosts in a real-time distr...

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international conference on Industrial and Information Systems, ICIIS

作者： Julius Canute Atul Kumar International Institute of Information Technology (lIlT) Bangalore India Siemens Corporate Research and Technologies Bangalore India

We consider cyclic real-time applications built using nearly autonomous components. these components can run on any of the available hosts subject to certain constraints. the hosts in the system are allowed to be heterogeneous and they can have different cycle times for real time execution. Given a set of component based applications and a set of available hosts, we propose a solution for the problem of finding an optimum deployment. the deployment problem can be reduced to the problem of finding feasible static schedules for each host in the system that satisfy the real-time periodic execution requirements of all the applications. We propose a deterministic algorithm for finding static schedules for all the hosts in the system. the approach models the possible partial schedules at each step as nodes in a virtual tree. A breadth first traversal is conducted to construct the tree and complete the schedule. A node is removed from the tree if it cannot lead to a correct schedule. If more than one solutions are possible then the `best' solution is selected based on the optimization criteria.

关键词： Schedules Real-time systems Resource management Electronic mail Optimization Software Complexity theory

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Hierarchical speech recognition system using MFCC feature extraction and dynamic spiking RSOM

Hierarchical speech recognition system using MFCC feature ex...

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ACIS international conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed computing (SNPD)

作者： Behi Tarek Arous Najet Ellouze Noureddine Laboratory of Signal Universitc Tunis EI Manar Tunisia Laboratory of Signal Image and Information Technologies National Engineering school of tunis Enit Université Tunis El Manar Tunisia

In this paper, we propose new variants of unsupervised and competitive learning algorithms designed to deal with temporal sequences. these algorithms combine features from Spiking Neural Networks (SNNs) and the advantages of the hierarchical self organizing map (HSOM). the first variant named Hierarchical Dynamic recurrent spiking self-organizing map (HD-RSSOM) is characterized by the integration of a temporal controller component to regulate the firing activity of the spiking neurons. the second variant is a hierarchical model which represents a multi-layer extension of HD-RSSOM model. the case study of the proposed HSOM variants is phonemes and words recognition in continuous speech. the applied HSOM variants serve as tools for developing intelligent systems and pursuing artificial intelligence applications.

关键词： Training Speech recognition Neurons Speech Vectors Neural networks Mel frequency cepstral coefficient

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A distributed polygon retrieval algorithm using MapReduce

A distributed polygon retrieval algorithm using MapReduce

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international conference on Collaborative computing: Networking, applications and Worksharing (CollaborateCom)

作者： Qiulei Guo Balaji Palanisamy Hassan A. Karimi Geoinformatics Laboratory University of Pittsburgh

the proliferation of data acquisition devices like 3D laser scanners had led to the burst of large-scale spatial terrain data which imposes many challenges to spatial data analysis and computation. With the advent of several emerging collaborative cloud technologies, a natural and cost-effective approach to managing such large-scale data is to store and share such datasets in a publicly hosted cloud service and process the data within the cloud itself using modern distributed computing paradigms such as MapReduce. For several key spatial data analysis and computation problems, polygon retrieval is a fundamental operation which is often computed under real-time constraints. However, existing sequential algorithms fail to meet this demand effectively given that terrain data in recent years have witnessed an unprecedented growth in both volume and rate. In this work, we develop a MapReduce-based parallel polygon retrieval algorithm which aims at minimizing the IO and CPU loads of the map and reduce tasks during spatial data processing. the results of the preliminary experiments on a Hadoop cluster demonstrate that the proposed techniques are scalable and lead to more than 35% reduction in execution time of the polygon retrieval operation over existing distributed algorithms.

关键词： Random access memory three-dimensional displays Arrays Tin Elevators Earth

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Chive: A simulation tool for epidemic data replication protocols benchmarking

Chive: A simulation tool for epidemic data replication proto...

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international conference on Software Engineering and applications (ICSOFT-EA)

作者： A. Jiménez-Yáñez J. Navarro F. D. Muñoz-Escoí I. Arrieta-Salinas J. E. Armendáriz-Iñigo Dpto. Ingeniería Matemática e Informática Universidad Pública de Navarra Pamplona Spain Internet Technologies and Storage Research Group La Salle - Ramon Llull University Barcelona Spain Instituto Tecnológico de Informática Univ. Politécnica de Valéncia Valencia Spain

Epidemic data replication protocols are an interesting approach to address the scalability limitations of classic distributed databases. However, devising a system layout that takes full advantage of epidemic replication is a challenging task due to the high number of associated configuration parameters (e.g., replication layers, number of replicas per layer, etc.). the purpose of this paper is to present a Java-based simulation tool that simulates the execution of epidemic data replication protocols on user-defined configurations under different workloads. Conducted experiments show that by using the proposed approach (1) the internal dynamics of epidemic data replication protocols under a specific scenario are better understood, (2) the distributed database system design process is considerably speeded up, and (3) different system configurations can be rapidly prototyped.

关键词： Protocols distributed databases Measurement Metadata Scalability

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RAFlow: Read Ahead Accelerated I/O Flow through Multiple Virtual Layers

RAFlow: Read Ahead Accelerated I/O Flow through Multiple Vir...

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international conference on Networking, Architecture, and Storage (NAS)

作者： Zhaoning Zhang Kui Wu Huiba Li Jinghua Feng Yuxing Peng Xicheng Lu National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology China Computer Science Department University of Victoria B.C. Canada National Super Computing Center Tianjin China

Virtualization is the foundation for cloud computing, and the virtualization can not be achieved without software defined, elastic, flexible and scalable virtual layers. Unfortunately, if multiple virtual storage devices are chained together, the system may be subject to severe performance degradation. While the read-ahead (RA) mechanism in storage devices plays a very important role to improve I/O performance, RA may not be effective as expected for multiple virtualization layers, since it is originally designed for one layer only. When I/O requests are passed through a long I/O path, they may trigger a chain reaction and lead to unnecessary data transmission and thus bandwidth waste. In this paper, we study the dynamic behavior of RA through multiple I/O layers and demonstrate that if controlled well, RA can greatly accelerate I/O speed. We present RAFlow, a RA control mechanism, to effectively improve I/O performance by strategically expanding RA window at each layer. Our real-world experiments show that it can achieve 20% to 50% performance improvement in I/O paths with up to 8 virtualized storage devices.

关键词： Radio access networks Acceleration distributed databases Performance evaluation Synchronization Benchmark testing Degradation

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K-medoids clustering based on MapReduce and optimal search of medoids

K-medoids clustering based on MapReduce and optimal search o...

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international conference on Computer Science & Education (ICCSE)

作者： Ying-ting Zhu Fu-zhang Wang Xing-hua Shan Xiao-yan Lv Railway Technology Research College China Academy of Railway Science Beijing China Institute of Computing Technologies China Academy of Railway Science Beijing China

ISBN: (纸本)9781479929528

When there are noises and outliers in the data, the traditional k-medoids algorithm has good robustness, however, that algorithm is only suitable for medium and small data set for its complex calculation. MapReduce is a programming model for processing mass data and suitable for parallel computing of big data. therefore, this paper proposed an improved algorithm based on MapReduce and optimal search of medoids to cluster big data. Firstly, according to the basic properties of triangular geometry, this paper reduced calculation of distances among data elements to help search medoids quickly and reduce the calculation complexity of k-medoids. Secondly, according to the working principle of MapReduce, Map function is responsible for calculating the distances between each data element and medoids, and assigns data elements to their clusters; Reduce function will check for the results from Map function, search new medoids by the optimal search strategy of medoids again, and return new results to Map function in the next MapReduce process. the experiment results showed that our algorithm in this paper has high efficiency and good effectiveness.

关键词： Computers Computational modeling Clustering algorithms

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JOMR: Multi-join optimizer technique to enhance map-reduce job

JOMR: Multi-join optimizer technique to enhance map-reduce j...

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the international conference on Informatics and Systems (INFOS)

作者： Mina Samir Shanoda Samah Ahmed Senbel Mohamed Helmy Khafagy College of Computing and Information Technology Arab Academy for Science and Technology Cairo Egypt Dept. of Computer Science Fayoum University Fayoum Egypt

Map-Reduce is a programming model and execution an environment developed by Google to process very large amounts of data. Query optimizer is needed to find more efficient plans for declarative SQL query. In classic database: join algorithms are optimized to execute the entire query result, but they ignore the importance of tables order especially in multi-join query. But we can see that the orders for tables are an important factor to get the best performance of a query plan and will be very effective in performance when join tables content huge number of rows in addition to more than one join operation. In this paper we proposed a new technique called JOMR (Join Order In Map-Reduce) that optimizes and enhances Map-Reduce job. this technique uses enhanced parallel Travel Salesman Problem (TSP) using Map-Reduce for improving the performance of query plans according to change the order for join tables. Also we build a cost model that supports our algorithm to find best join order. We will focus on Hive especially multi-join query and our experiments result for JOMR algorithm proving the effectiveness of our query optimizer and this performance is improved more when increasing the number of join and size of data.

关键词： Partitioning algorithms Query processing Algorithm design and analysis Mathematical model Educational institutions Informatics distributed computing

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Speed Protection Algorithms for Privacy-aware Location Management

Speed Protection Algorithms for Privacy-aware Location Manag...

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IEEE 9th international conference on Wireless and Mobile computing, Networking and Communications (WiMob)

作者： Wernke, Marius Duerr, Frank Rothermel, Kurt Univ Stuttgart Inst Parallel & Distributed Syst D-70569 Stuttgart Germany

ISBN: (纸本)9781457720147

Nowadays, millions of users share their complete movement trajectory online when using real-time traffic monitoring applications, pay-as-you-drive insurances, or when sharing their last road trip with friends. However, many users still hesitate to use location-based applications as they are not willing to reveal, for instance, their driving behavior or the occurrence of a speeding violation. therefore, we present novel speed protection algorithms protecting users from revealing a violation of given speed limits when using location-based applications. Our algorithms support time-based and distance-based position updates. To protect positions indicating a speeding violation, we either adjust temporal information by delaying position updates or adjust their spatial information. We evaluate our algorithms by using real world traces and show that the protected movement trajectory of the user is of high quality even after removing speeding violations.

关键词： Location-based applications speed protection movement trajectory location management location privacy

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