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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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Efficiently Finding Top-K Items from Evolving distributed Data Streams

Efficiently Finding Top-K Items from Evolving Distributed Da...

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international conference on Semantics, Knowledge and Grid (SKG)

作者： Baoyuan Qi Gang Ma Zhongzhi Shi Wei Wang University of Chinese Academy of Sciences Beijing China Key Lab of Intelligent Information Processing Institute of Computing Technology Cas Beijing China Key Lab. of Intell. Inf. Process. Institute of Computing Technology Chinese Academy of Sciences Beijing CN Beijing Lexo Technologies Co. Ltd. Beijing China

ISBN: (纸本)9781479967162

the problem of efficiently finding top-k frequent items has attracted much attention in recent years. Storage constraints in the processing node and intrinsic evolving feature of the data streams are two main challenges. In this paper, we propose a method to tackle these two challenges based on space-saving and gossip-based algorithms respectively. Our method is implemented on SAMOA, a scalable advanced massive online analysis machine learning framework. the experimental results show its effectiveness and scalability.

关键词： Peer-to-peer computing Data mining distributed databases Protocols Machine learning algorithms Monitoring Radiation detectors

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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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HTSeq-Hadoop: Extending HTSeq for Massively parallel Sequencing Data Analysis Using Hadoop

HTSeq-Hadoop: Extending HTSeq for Massively Parallel Sequenc...

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IEEE international conference on e-Science and Grid computing

作者： Alexey Siretskiy Ola Spjuth Department of Information Technology Uppsala University Uppsala Department of Pharmaceutical Biosciences and Science for Life Laboratory Uppsala University

Hadoop is a convenient framework in e-Science enabling scalable distributed data analysis. In molecular biology, next-generation sequencing produces vast amounts of data and requires flexible frameworks for constructing analysis pipelines. We extend the popular HTSeq package into the Hadoop realm by introducing massively parallel versions of short read quality assessment as well as functionality to count genes mapped by the short reads. We use the Hadoop-streaming library which allows the components to run in both Hadoop and regular Linux systems and evaluate their performance in two different execution environments: A single node on a computational cluster and a Hadoop cluster in a private cloud. We compare the implementations with Apache Pig showing improved runtime performance of our developed methods. We also inject the components in the graphical platform Cloudgene to simplify user interaction.

关键词： Sequential analysis Bioinformatics Libraries Cloud computing Genomics Timing Linux

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Elastic Scaling of e-Infrastructures to Support Data-Intensive Research Collaborations

Elastic Scaling of e-Infrastructures to Support Data-Intensi...

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IEEE international conference on e-Science and Grid computing

作者： Marcos Nino-Ruiz Christopher Bayliss Gerson Galang Guido Grazioli Rosana Rabanal Martin Tomko Richard O. Sinnott Department of Computing and Information Systems University of Melbourne Vic Australia

For many research endeavours, e-Infrastructures need to provide predictable, on-demand access to large-scale computational resources with high data availability. these need to scale with the research communities requirements and use. One example of such an e-Infrastructure is the Australian Urban Research Infrastructure Network (AURIN -- ***) project, which supports Australia-wide research in and across the urban and built environment. this paper describes the architecture of the AURIN infrastructure and its support for access to distributed (federated) and highly heterogeneous data sets from a wide range of providers. We present how this architecture solution leverages the intersection of high throughput computing (HTC), infrastructure as a service (IaaS) Cloud services and big data technologies including use of NoSQL resources. the driving concept in this architecture and the focus of this paper is the ability for scaling up or down depending on resource demands at any given time. this is done automatically and on demand avoiding either under-or over-utilization of resources. this resource-optimization-driven infrastructure has been designed to ensure that peak loads can be predicted and successfully coped with, as well as avoid wasting resources during non-peak times. this overall management strategy has resulted in an e-Infrastructure that provides a flexible, evolving research environment that scales with research needs, rather than providing a rigid (static) end product.

关键词： Computer architecture Australia Cloud computing Software as a service Resource management distributed databases Java

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A MapReduce based parallel Algorithm for CIM Data Verification

A MapReduce based Parallel Algorithm for CIM Data Verificati...

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the 2014 10th international conference on Natural Computation (ICNC 2014) and the 2014 11th international conference on Fuzzy Systems and Knowledge Discovery (FSKD 2014)(第十届自然计算和第十一届模糊系统与知识发现国际会议)

作者： Yang Liu Lixiong Xu Xiaodong Shen Maozhen Li School of Electrical Engineering and Information Systems Sichuan University Chengdu China School of Engineering and Design Brunel University London UK

ISBN: (纸本)9781479951499

At present,the power system is building up on top of a series of auxiliary systems for examples communication systems,monitoring systems,marketing systems and so *** the systems work based on the shared power system data which are defined using Common Information Model(CIM).Due to diversiform reasons,errors may exist in the *** the verification technologies are *** far the researchers mainly focus on the accuracy of the ***,along with the volume of data increasing,efficiency has become an *** paper proposes a CIM verifying algorithm based on MapReduce in terms of efficiency *** experimental results show that it can enhance the performance of verification.

关键词： CIM,verification,MapReduce,cluster,distributed

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A Scalable Planetary Science Information Architecture for Big Science Data

A Scalable Planetary Science Information Architecture for Bi...

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IEEE international conference on e-Science and Grid computing

作者： Daniel Crichton John S. Hughes Sean Hardman Emily Law Reta Beebe thomas Morgan Edwin Grayzeck Jet Propulsion Laboratory California Institute of Technology Pasadena CA U.S.A. California Institute of Technology Pasadena CA US New Mexico State University Las Cruces NM US Goddard Space Flight Center Greenbelt MD USA Goddard Space Flight Center Greenbelt Maryland U.S.A.

Research has shown that the amount of data now available often overwhelms key functions of an information system. this situation necessitates the design of information architectures that scale to meet the challenges. the Planetary Data System, a NASA funded project, has developed an information architecture for the planetary science community that addresses this and other big science data issues noted in a National Research Council report regarding architectures for big data management and analysis and end-to-end data lifecycle management across diverse disciplines. the report identified enabling technology trends including distributed systems, service-oriented architectures, ontologies, models and information representation, scalable database systems, federated data security mechanisms, and technologies for moving big data. this paper will present the PDS4 information architecture, its successful implementation in a multi-discipline big-data environment.

关键词： Data models Standards distributed databases Computer architecture Unified modeling language Object oriented modeling Communities

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PShare: Ensuring location privacy in non-trusted systems through multi-secret sharing

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PERVASIVE AND MOBILE computing 2013年第3期9卷 339-352页

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

Location-based applications such as Facebook Places, Foursquare, or Loopt typically use location services to manage mobile object positions. However, exposing precise user positions raises user privacy concerns, especially if location service providers are not fully trusted. To enable the secure management of private user positions in non-trusted systems, we present two novel position sharing approaches based on the concept of multi-secret sharing. We improve existing geometric position sharing approaches by Durr et al. [2] and Skvortsov et al. [3] by considering continuous position updates and by increasing the robustness against various attacks. Furthermore, we present the first position sharing approach for symbolic location models. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Location-based applications Privacy Position sharing Location management

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Study on Quantum parallel Processing by Adiabatic Quantum Computation in Simon Problem 14

Study on Quantum Parallel Processing by Adiabatic Quantum Co...

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14th international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Nakayama, Shigeru Gang, Peng Iimura, Ichiro Kagoshima Univ Dept Inf Sci & Bio Engn Kagoshima 8900065 Japan Huizhou Univ Dept Comp Sci Huizhou 516007 Peoples R China Prefectural Univ Kumamoto Fac Adm Kumamoto 8628502 Japan

ISBN: (纸本)9781479924189

Adiabatic quantum computation has been proposed as quantum parallel processing with adiabatic evolution by using a superposition state to solve combinatorial optimization problem, then it has been applied to many problems like satisfiability problem. Among them, Deutsch and Deutsch-Jozsa problems have been tried to be solved by using adiabatic quantum computation. In this paper, we modify the adiabatic quantum computation and propose to solve Simon problem more efficiently by a method with higher observation probability.

关键词： quantum parallel processing quantum algorithm adiabatic quantum computation Simon problem combinatorial optimization problem

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DXRAM: A Persistent In-Memory Storage for Billions of Small Objects 14

DXRAM: A Persistent In-Memory Storage for Billions of Small ...

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14th international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Klein, Florian Schoettner, Michael Univ Dusseldorf Inst Informat D-40225 Dusseldorf Germany

ISBN: (纸本)9781479924189

Large-scale interactive applications and realtime data-processing are facing problems with traditional disk-based storage solutions. Because of the often irregular access patterns they must keep almost all data in RAM caches, which need to be manually synchronized with secondary storage and need a lot of time to be re-loaded in case of power outages. In this paper we propose a novel key-value storage keeping all data always in RAM by aggregating resources of potentially many nodes in a data center. We aim at supporting management of billions of small data objects (16-64 byte) like for example needed for storing graphs. A scalable low-overhead meta-data management is realized using a novel range-based ID approach combined with a super-overlay network. Furthermore, we provide persistence by a novel SSD-aware logging approach allowing to recover failed nodes very fast.

关键词： distributed systems distributed memory Fault tolerance Memory management

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