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Soft computing Applications Proceedings of the 7th international Workshop Soft computing Applications Sofa 2016

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2017年

作者： Valentina Emilia Balas Lakhmi C Jain Marius Mircea Balas

ISBN: (纸本)9783319625218;3319625217;9783319625249;3319625241;9783319625201

these two volumes constitute the Proceedings of the 7th international Workshop on Soft computing Applications (SOFA 2016), held on 2426 August 2016 in Arad, Romania. this edition was organized by Aurel Vlaicu University of Arad, Romania, University of Belgrade, Serbia, in conjunction with the Institute of Computer Science, Iasi Branch of the Romanian Academy, IEEE Romanian Section, Romanian Society of Control Engineering and Technical Informatics (SRAIT) - Arad Section, General Association of Engineers in Romania - Arad Section, and BTM Resources Arad. the soft computing concept was introduced by Lotfi Zadeh in 1991 and serves to highlight the emergence of computing methodologies in which the accent is on exploiting the tolerance for imprecision and uncertainty to achieve tractability, robustness and lower costs. Soft computing facilitates the combined use of fuzzy logic, neurocomputing, evolutionary computing and probabilistic computing, leading to the concept of hybrid intelligent systems. the rapid emergence of new tools and applications calls for a synergy of scientific and technological disciplines in order to reveal the great potential of soft computing in all domains. the conference papers included in these proceedings, published post-conference, were grouped into the following areas of research: Methods and Applications in Electrical Engineering Knowledge-Based Technologies for Web Applications, Cloud computing, Security algorithms and Computer Networks Biomedical Applications Image, Text and Signal Processing Machine Learning and Applications Business Process Management Fuzzy Applications, theory and Fuzzy Control Computational Intelligence in Education Soft computing & Fuzzy Logic in Biometrics (SCFLB) Soft computing algorithms Applied in Economy, Industry and Communication Technology Modelling and Applications in Textiles the book helps to disseminate advances in selected active research directions in the field of soft computing, along with current issu

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In-Situ Model Validation for Continuous Processes Using In-Network computing 7

In-Situ Model Validation for Continuous Processes Using In-N...

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IEEE 7th international conference on Industrial Cyber-Physical systems (ICPS)

作者： Kunze, Ike Scheurenberg, Dominik Tirpitz, Liam Geisler, Sandra Wehrle, Klaus Rhein Westfal TH Aachen Commun & Distributed Syst Aachen Germany Rhein Westfal TH Aachen Inst Automat Control Aachen Germany Rhein Westfal TH Aachen Data Stream Management & Anal Aachen Germany

ISBN: (纸本)9798350363029;9798350363012

the advancing industrial digitalization enables evolved process control schemes that rely on accurate models learned through data-driven approaches. While they provide high control performance and are robust to smaller deviations, a larger change in process behavior can pose significant challenges, in the worst case even leading to a damaged process plant. Hence, it is important to frequently assess the fit between the model and the actual process behavior. As the number of controlled processes and associated data volumes increase, the need for lightweight and fast reacting assessment solutions also increases. In this paper, we propose CIVIC, an in-network computing-based solution for Continuous In-situ Validation of Industrial Control models. In short, CIVIC monitors relevant process variables and detects different process states through comparison with a priori knowledge about the desired process behavior. this detection can then be leveraged to, e.g., shut down the process or trigger a reconfiguration. We prototype CIVIC on an Intel Tofino-based switch and apply it to a lab-scale water treatment plant. Our results show that we can achieve a high detection accuracy, proving that such monitoring systems are feasible and sensible.

关键词： Plant shutdowns

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Architecture - And workload-aware heterogeneous algorithms for sparse matrix vector multiplication 14

Architecture - And workload-aware heterogeneous algorithms f...

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7th ACM India computing conference, COMPUTE 2014

作者： Indarapu, Sivaramakrishna Bharadwaj Maramreddy, Manoj Kothapalli, Kishore International Institute of Information Technology Hyderabad500032 India

ISBN: (纸本)9781605588148

Multiplying a sparse matrix with a vector, denoted spmv, is a fundamental operation in linear algebra with several applications. Hence efficient and scalable implementation of spmv has been a topic of immense research. Recent efforts are aimed at implementations on GPUs, multicore architectures, and such emerging computational platforms. Owing to the highly irregular nature of spmv, it is observed that GPUs and CPUs can offer comparable performance. In this paper, we propose three heterogeneous algorithms for spmv that simultaneously utilize both the CPU and the GPU. this is shown to lead to better resource utilization apart from performance gains. Our experiments of the work division schemes on standard datasets indicate that it is not in general possible to choose the most appropriate scheme given a matrix. We therefore consider a class of sparse matrices that exhibit a scale-free nature and identify a scheme that works well for such matrices. Finally, we use simple and effective mechanisms to determine the appropriate amount of work to be alloted to the CPU and the GPU. Copyright 2014 ACM.

关键词： Matrix algebra

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Techniques of Image Processing and Segmentation in Predicting Hydrocephalus using Magnetic Resonance Image 7

Techniques of Image Processing and Segmentation in Predictin...

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7th international conference on Advanced computing and Communication systems, ICACCS 2021

作者： Rajiga, S.V. Gunasekaran, M. Government Arts College Autonomous Pg and Research Department of Computer Science Salem -7 India Government Arts College Pg and Research Department of Computer Science Dharmapuri India

ISBN: (纸本)9781665405201

Children are most commonly affected by many neurological disorders now a days. One of the common disease is hydrocephalus occurring 1/1000 in infantile age group and also in adults as a result of congenital, acquired, tumors, spina bifida, bleeding or infection. Hydrocephalus may cause disability and even death when it is left untreated. Hydrocephalus occurs when, due to previous causes in the brain, excessive cerebrospinal fluid builds up in the brain. When diagnosing tumours and hydrocephalus, image processing plays a vital role. the gap between the visual representation of data captured by MRI and the information relevant to the individual is a major challenge in the medical field. the latest image processing and data mining technologies are used to classify images with high precision. this research paper suggest a definition of image processing and segmentation algorithms for the evaluation of hydrocephalus in children and the determination of its MRI volume. Earlier research work are intended for identifying Hydrocephalus from CT brain images. But in the proposed work MRI images are used for diagnosis. this paper presents techniques and algorithms of Image processing and Segmentation which will be very useful in diagnosing Hydrocephalus. © 2021 IEEE.

关键词： Magnetic resonance imaging

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Towards garbage collection mechanism for RTSJ-oriented embedded Java Processor

Towards garbage collection mechanism for RTSJ-oriented embed...

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10th IEEE international conference on Computer and Information Technology, CIT-2010, 7th IEEE international conference on Embedded Software and systems, ICESS-2010, 10th IEEE Int. Conf. Scalable computing and Communications, ScalCom-2010

作者： Hu, Guang Chai, Zhilei Zhao, Wenke Tu, Shiliang Department of Computer Science Shanghai International Studies University Shanghai China Department of Computer Science and Engineering Fudan University Shanghai China Siemens Corporate Technology Beijing China Center of Intelligent and High Performance Computing School of Information Technology Jiangnan University Wuxi China

ISBN: (纸本)9780769541082

Currently, Java has been gradually applied in embedded real-time area with the improvement by the Real-Time Specification for Java (RTSJ). Accordingly, a hardware Java execution engine for embedded real-time applications, JPOR-32 (32-bit Java Processor Optimized for RTSJ), is designed. Taking JPOR-32 for an example, this paper presents the garbage collection mechanism for RTSJ-oriented embedded processor in detail. JPOR-32 provides effective architectural support for garbage collection. And the object reference format of JPOR-32 provides supports for objects tracing and heap scanning. the support for write barrier of real-time concurrent GC is also performed. Moreover, JPOR- 32 provides optimized instruction level support for garbage collection. In addition, different garbage collection algorithms are compared on the base of the resource-constrained feature and the real-time requirement of the processor, and the hybrid garbage collectors are suggested. © 2010 IEEE.

关键词： Refuse collection

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Using Service Clustering and Self-Adaptive MOPSO-CD for QoS-Aware Cloud Service Selection 7

Using Service Clustering and Self-Adaptive MOPSO-CD for QoS-...

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7th international conference on Ambient systems, Networks and Technologies (ANT) / 6th international conference on Sustainable Energy Information Technology (SEIT)

作者： Spezzano, Giandomenico CNR ICAR Via P Bucci 7-11c Arcavacata Di Rende CS Italy

A promising way to effectively manage the composition of services in a heterogeneous and dynamic environment is to make workflow management able to self-adapt at runtime to react to changes in its environment by autonomously reconfiguring itself. Most of the proposed methodologies address this issue as a QoS-aware service selection problem in which a web service broker can dynamically select the "right" service that takes part in the composition, and adaptively change the bound service when the delivered QoS has changed. In this paper, we propose a self-organizing framework that uses a service clustering based discovery approach to effectively and efficiently support the selection of services in which runtime changes in the QoS of the services are taken into account. Two bio-inspired algorithms are designed to support a QoS-aware dynamic service selection mechanism. An ant-based clustering algorithm enhanced with a template mechanism that guides the artificial ants to move data items to construct and maintain a specific topology is adopted as a method for efficient service discovery. As a consequence, services can dynamically be discovered in a shorter time and with lower network traffic. To select the actual concrete services that best meet the user QoS requirements a Self-Adaptive Multi-Objective Particle Swarm Optimization Algorithm using crowding distance technique (MOPSO-CD) is executed using the topological map generated by the ant algorithm. In the end, simulation results show the effectiveness of the method proposed. (C) 2016 the Authors. Published by Elsevier B.V.

关键词： QoS-aware service selection Ant-based service clustering Particle swarm optimization Cloud computing

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An efficient search mechanism in unstructured P2P networks based on semantic group

An efficient search mechanism in unstructured P2P networks b...

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作者： Shen, Wenwu Su, Sen Shuang, Kai Yang, Fangchun Xia, Jingshu State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China International School Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9780769541082

Recently among various searching techniques, semantic-based searching has drawn significant attention. In this paper, we propose a novel and efficient search mechanism BF-SKIP (Biased walk, Flooding and Search with K-Iteration Preference). We use Vector Space Model (VSM) and relevance ranking algorithms to construct the overlay network. In BF-SKIP system, the search mechanism is divided into three stages (A, B and C). It significantly reduces the number of redundant messages and the number of visited nodes. Our analysis and simulation results show that the BF-SKIP scheme can outperform GES in terms of higher precision and lower search cost. © 2010 IEEE.

关键词： Semantics

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Optimizing PLASMA eigensolver on large shared memory systems 7

Optimizing PLASMA eigensolver on large shared memory systems

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7th Workshop on Latest Advances in Scalable algorithms for Large-Scale systems, ScalA 2016

作者： Liao, Cheng Silicon Graphics International Corp. 900 North McCarthy Blvd. MilpitasCA95035 United States

ISBN: (纸本)9781509052226

Performance of the PLASMA dense symmetric Eigensolver is optimized for large shared memory computer systems using multiple Householder domains for dense to band reduction and a communication reducing kernel for bulge chasing. the mr3-smp code by Petschow and Bientinesi is used for the tridiagonal eigensolution and the eigenvector back-transformations employ a 1D parallel decomposition. the input matrix, Householder vectors and scalars, are distributed among the CPU sockets with interleaved memory pages but the banded matrix, the eigenvectors, and temporary memory buffers are allocated and processed locally. Other considerations and optimization techniques also are presented. Numerical examples show the PLASMA eigensolver can out-perform ELPA and EIGENEXA significantly, for solving all the eigenpairs, if the problem size is sufficiently large, and the 2-stage eigensolution is generally better than its 1-stage counterpart on the latest x86-64 EP-4S CPUs with AVX2. © 2016 IEEE.

关键词： Eigenvalues and eigenfunctions

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Proceedings - 2021 IEEE international conference on Dependable, Autonomic and Secure computing, international conference on Pervasive Intelligence and computing, international conference on Cloud and Big Data computing and international conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2021

Proceedings - 2021 IEEE International Conference on Dependab...

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19th IEEE international conference on Dependable, Autonomic and Secure computing, 19th IEEE international conference on Pervasive Intelligence and computing, 7th IEEE international conference on Cloud and Big Data computing and 2021 international conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2021

ISBN: (纸本)9781665421744

the proceedings contain 148 papers. the topics discussed include: design and implementation of face recognition system based on raspberry pie;a privacy-preserving revocable framework in the deep-learning-as-a-service platform system based on non-software as a service;beyond homeostasis: a novel approach for assessing the stability and coherence of self-adaptive systems;a meta multi-agent reinforcement learning algorithm for multi-intersection traffic signal control;reducing model complexity and cost in the generation of efficient error detection mechanisms;quantitative security assurance case for in-vehicle embedded systems;chaos engineering for understanding consensus algorithms performance in permissioned blockchains;rethinking of reentrancy on the ethereum;self-attention based text matching model with generative pre-training;role-based approach as support for safety analysis of collaborative systems;optimizing dynamic timing analysis and reinforcement learning;impact of selective implementation on soft error detection through low-level re-execution;and applying neural networks for plant model simulation in embedded control system.

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Tuning struggle strategy in genetic algorithms for Scheduling in Computational Grids

Tuning struggle strategy in genetic algorithms for Schedulin...

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7th international conference on Computer Information systems and Industrial Management Applications

作者： Xhafa, Fatos Duran, Bernat Abraham, Ajith Dahal, Keshav P. Tech Univ Catalonia Dept Languages & Informat Syst Barcelona Spain Norwegian Univ Sci & Technol Ctr Excellence Quantifiable Qual Serv Trondheim Norway Univ Bradford Sch Informat Bradford BD7 1DP W Yorkshire England

ISBN: (纸本)9780769531847

Job Scheduling on Computational Grids is gaining importance due to the need for efficient large-scale Grid-enabled applications. Among different optimization techniques addressed for the problem, Genetic Algorithm (GA) is a popular class of solution methods. As GAs are high level algorithms, specific algorithms can be designed by choosing the genetic operators as well as the evolutionary strategies. In this paper we focus on Struggle GAs and their tuning for the scheduling of independent jobs in computational grids. Our results showed that a careful hash implementation for computing the similarity of solutions was able to alleviate the computational burden of Struggle GA and perform better than standard similarity measures.

关键词： Genetic algorithms

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