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On Fuzzy Clustering Algorithms for Nominal Data

On Fuzzy Clustering Algorithms for Nominal Data

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international Symposium on Soft computing and intelligent Systems (SCIS)

作者： Yuchi Kanzawa Shibaura Institute of Technology Tokyo Japan

ISBN: (数字)9781728197326

ISBN: (纸本)9781728197333

This paper presents three fuzzy clustering algorithms for nominal data. The first algorithm is similar to a conventional algorithm for vectorial data developed by introducing variables for controlling the cluster size. The second algorithm is similar to a conventional algorithm for vectorial data developed by regularizing another conventional algorithm for vectorial data with Kullback-Leibler divergence. The third algorithm is developed by regularizing the first algorithm mentioned above with q-divergence. Finally, some numerical experiments are conducted to investigate the features of the proposed algorithms.

关键词： Clustering algorithms Cats Partitioning algorithms Optimization Linear programming Indexes standards

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study of the Functioning of the distributed Computer System with a Resource Control Mechanism Based on a Network-Centric Approach 10

Study of the Functioning of the Distributed Computer System ...

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10th IEEE international conference on intelligent Data Acquisition and Advanced computing Systems - technology and Applications (IDAACS)

作者： Mukhin, Vadym Vyshnivskyi, Viktor Kornaga, Yaroslav Herasymenko, Oksana Bazaka, Yuriy Bazaliy, Maxim Natl Tech Univ Ukraine Igor Sikorsky Kiev Polytech Inst Pr Pobedy 37 UA-03056 Kiev Ukraine State Univ Telecommun Solomenska St UA-03680 Kiev Ukraine Taras Shevchenko Natl Univ Kiev Volodymyrska St64-13 UA-01601 Kiev Ukraine

ISBN: (纸本)9781728140698

The task to increase the scalability of the distributed computer systems (DCS) arises the new challenges for developing of the effective resources control mechanisms for such systems. This issue is particularly significant for the distributed computer systems with a decentralized resource control mechanism. The paper describes a resource reservation mechanism which allow to prevent the total loading of DCS computational resources. This research is devoted to the study of the functioning of the resource control system (RCS) based on a networkcentric approach in the context of resource reservations.

关键词： distributed computer system decentralized resources control network-centric approach task structure resourses reservation

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Partitioning large-scale property graph for efficient distributed query processing 21

Partitioning large-scale property graph for efficient distri...

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21st IEEE international conference on High Performance computing and Communications, 17th IEEE international conference on Smart City and 5th IEEE international conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Pang, Haohan Gan, Peng Yuan, Pingpeng Jin, Hai Hua, Qiangsheng National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab. Clusters and Grid Computing Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781728120584

Recently, many communities have published their domain knowledge in the form of graphs. A significant trend is that the relations between pairs of nodes in the graph have become so complex that these data can be treated as property graphs. Complex properties imply semantic constraints which can distinguish elements of property graph into different semantic-related aspects. If the property graph can be partitioned according to these aspects, cross-partition communication would be reduced when evaluating SPARQL queries, for the reason that a query can often be evaluated in a single aspect. Conventional graph partition methods, however, pay little attention to semantic constraints in property graphs. To solve this problem, we propose a new property graph partition method for query optimization. First, we propose the property semantic reachable path as basic partition element, with which to capture the semantic-related aspects in a property graph. Second, to combine paths into partitions, we develop a space-efficient algorithm which merges vertices rather than entire paths. Extensive experiments over representative property graph data confirm the effectiveness of our semantic awareness approach. The performance of our approach is comparable with leading competitors, in terms of load balance, data redundancy, and network overhead. © 2019 IEEE.

关键词： Semantics

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Music Tagging and Similarity Analysis for Recommendation System 1st

Music Tagging and Similarity Analysis for Recommendation Sys...

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1st international conference on Computational Intelligence in Pattern Recognition, CIPR 2019

作者： Kumar, Laxman Mitra, Anirban Mittal, Mamta Sanghvi, Vatsal Roy, Sudipta Setua, Sanjit Kumar Department of Computer Science and Engineering U.V. Patel College of Engineering Ganpat University Mehsana Kherva384012 India Department of Computer Science and Engineering Academy of Technology AdisaptagramWest Bengal712121 India Department of Computer Science and Engineering Calcutta University Technology Campus JD-2 Sector-III Salt Lake Kolkata700098 India Department of Computer Science & Engineering G. B. Pant Government Engineering College Okhla New Delhi110020 India Mallinckrodt Institute of Radiology Department Washington University in St. Louis 510 South Kingshighway Boulevard St. LouisMO63110-1076 United States

ISBN: (纸本)9789811390418

Many of the websites follow the system of retrieving and recommending music based on the metadata. Metadata is generally a text file that attached to the music file has title and genre. Without attached metadata, it is very difficult for such websites to recommend or retrieve music. A regularly utilized rundown of the fundamental components incorporates pitch, timber, surface, volume, span, and frame. In the proposed methodology to process such a vast amount of data, the distributed storage and data processing systems like Hadoop and Spark has been used. Hadoop distributed File System has been used for storing the music files and extracting feature information. Kafka queues has been used for asynchronous feature extraction in the background and finally Spark has been used for feature analysis using machine learning algorithms. This Proposed automated system for assigning genres for music provides very promising accuracy with a high true positive value. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Metadata

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A Modified Query Processing Algorithm Based on Dynamic Clustering for Big Data Applications 1st

A Modified Query Processing Algorithm Based on Dynamic Clust...

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1st international conference on Artificial Intelligence and Computer Visions, AICV 2020

作者： Darwish, Saad M. Elsaidy, Ramy D. Mesbah, Saleh Department of Information Technology Institute of Graduate Studies and Research Alexandria University 163 Horreya Avenue El-Shatby P.O. Box 832 Alexandria21526 Egypt College of Computing and Information Technology Arab Academy for Science Technology and Maritime Transport Abo-Keer Alexandria Egypt

ISBN: (纸本)9783030442880

Existing approaches for query processing are insufficient to provide accurate results quickly in a big data environment due to the needing to identify approximation measures and execution time for the queries are increasing. The practical results are obtained through the clustering process. However, how to scale up and speed up clustering algorithms with minimum sacrifice to the clustering quality remain a big problem. The main contribution of this work is to propose a modified dynamic distributed clustering approach applicable in spatial query processing for big data. The dynamic nature of the approach comes from the fact that it does not need to give the number of correct clusters in advance. The suggested model works through two main phases: the first phase builds local clusters based on its portion of the entire dataset;this stage takes full advantage of task parallelism paradigm based on Spark framework;whereas the second phase aggregate the local clusters in such a way that the final clusters are compact and accurate. Experimental results show that the approach is scalable and produces results of high quality for spatial query processing. © 2020, Springer Nature Switzerland AG.

关键词： Query processing

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SLAs-aware online task scheduling based on deep reinforcement learning method in cloud environment 21

SLAs-aware online task scheduling based on deep reinforcemen...

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作者： Ran, Longyu Shi, Xiaoyu Shang, Mingsheng Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing400714 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781728120584

As increasingly traditional applications migrate to the cloud, load balancing without sacrificing the performances of cloud-based applications is a highly challenging problem in cloud computing. Existing solutions focusing on online task scheduling have the inefficient issue, due to the highly dynamic nature of cloud workloads and the virtual machines (VMs) with heterogeneous hardware configurations. To address this issue, dependent on the strong perception and decision-making ability of deep reinforcement learning (DRL) in automatic control problems, we propose a deep reinforcement learning based task scheduling method, which can dynamic assign submitted tasks to different VMs. In details, we formulate the task scheduling as a dynamical optimal problem with constraints, and then adopt the deep deterministic policy gradients (DDPG) network to find the optimal task assignment solution with meeting the Service Level Agreements (SLAs) requirements. It makes the optimal scheduling decision only dependent on learning directly from its experience without any prior knowledge. The experimental results using the actual Alibaba cloud workload tracings show that compared with other existing solutions, our proposed task scheduling method can effectively reduce the average response time of tasks with guaranteeing the load balancing among VMs, when facing of dynamical workloads. © 2019 IEEE.

关键词： Reinforcement learning

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Minimum cost task assignment for vehicle-based crowdsensing with deterministic and nondeterministic trajectory 21

Minimum cost task assignment for vehicle-based crowdsensing ...

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作者： Tu, Meimei Li, Peng Zhang, Tao Zhou, Qiang Liu, Qin College of Computer Science and Technology Wuhan University of Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing Real-time Industrial System China Department of Computer Science New York Institute of Technology United States School of Cyber Science and Engineering Wuhan University China

ISBN: (纸本)9781728120584

Vehicle-based crowdsensing (VCS) is a special case in crowdsourcing, and task assignment is a basic and important problem. In this paper, we investigate the minimum cost task assignment (MCTA) problem for vehicle-based crowdsensing. The VCS platform hopes to recruit some vehicles to complete given spatial-temporal tasks with the minimum cost. As vehicle trajectories are dynamic, we divide the MCTA problem into two sub-problems, the deterministic trajectory (D-MCTA) problem, and nondeterministic trajectory (N-MCTA) problem. For D-MCTA problem, we prove that the D-MCTA problem is NP-hard, and we propose a greedy algorithm to solve this problem. For N-MCTA problem, firstly, we determine the probability of each vehicle's trajectory through the logistic regression method. Then, we exploit the semi-Markov method to calculate the probability of each vehicle executing the task. Moreover, a greedy algorithm is proposed and the theoretical analysis is given. Finally, extensive simulations have been conducted to show the performance of our proposed algorithms is superior to the other algorithms. © 2019 IEEE.

关键词： Vehicles

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Budget constraint roadside units placement for traffic flows monitoring system with reliability in vehicular networks 21

Budget constraint roadside units placement for traffic flows...

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作者： Jiang, Peng Li, Peng Zhang, Tao Huang, Weiyi He, Heng Nie, Lei Liu, Qin College of Computer Science and Technology Wuhan University of Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing Real-time Industrial System China Department of Computer Science New York Institute of Technology United States School of Cyber Science and Engineering Wuhan University China

ISBN: (纸本)9781728120584

In Traffic Flows Monitoring System (TFMS), the key problem is how to install Roadside Units (RSUs) reliably to monitor traffic flows with the constrained budget. The reliability of Traffic Flows Monitoring System(TFMS) is determined by the number of RSUs each traffic flow pass through, and the RSUs placement number is determined by the budget and the placement strategy. In this paper, we investigate the budget constraint RSUs placement problem for traffic flows monitoring system with reliability in vehicular networks. Given a budget constraint, the problem is how to install RSUs to ensure the reliability of TFMS, that is each traffic flow pass through RSUs as many as possible with the limited budget. We prove that this problem is NP-hard. Then, we propose two greedy algorithms to solve the problem according to the pigeonhole principle. Moreover, approximation ratios of proposed algorithms are given. Finally, we verify the feasibility of proposed algorithms through extensive experiments, and the results show that the proposed algorithms are superior to the other algorithms. © 2019 IEEE.

关键词： Reliability

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A Teaching Concept Towards Digitalization at the LEAD Factory of Graz University of technology 21st

A Teaching Concept Towards Digitalization at the LEAD Factor...

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21st international conference on Interactive Collaborative Learning (ICL) / 47th IGIP international conference on Engineering Pedagogy - Teaching and Learning in a Digital World

作者： Hulla, Maria Karre, Hugo Hammer, Markus Ramsauer, Christian Graz Univ Technol Graz Austria

ISBN: (纸本)9783030119355;9783030119348

The ongoing digital transformation is offering significant potentials in the manufacturing industry. As a result, competences for digital technologies and their implementation are in great demand. In this context, a digitalization teaching concept has been introduced in the learning factory of Graz University of technology. The aim of this paper is to identify competencies that will be required from the future workforce, to discuss if learning factories are suitable for transferring those competencies and to introduce a digitalization teaching concept. This teaching concept consists of alternating and complementary theoretical and practical training sessions. The training aims to enhance understanding of how digital technologies can improve the production process, how digital technologies and strategies can be implemented in a company, and how value is created with business models based on digitalization.

关键词： Digitalization teaching concept Learning factory Digitalization projects Digital learning environment

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Improving read performance of lsm-tree based KV stores via dual grained caches 21

Improving read performance of lsm-tree based KV stores via d...

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作者： Li, Xiang Xu, Guangping Fan, Hao Lu, Hongli Tang, Bo Xue, Yanbing Zong, Ziliang School of Computer Science and Engineering Tianjin University of Technology Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin China Key Laboratory of Computer Vision and System Ministry of Education China Department of Computer Science Texas State University San MarcosTX United States

ISBN: (纸本)9781728120584

Key-value (KV) stores based on the Log-structure Merge tree (LSM-tree) have been widely used in modern storage systems (e.g. LevelDB and RocksDB) to achieve high write throughput. However, conventional LSM-tree design has high latency for random read operations, especially in the workloads with concurrent read and write operations. This paper proposes a dual-grained cache scheme to improve the performance of LSM-tree based KV stores, in which a coarse-grained cache improves read performance by leveraging spatial locality and a fine-grained cache tracks the frequently accessed KV pairs. We implement the dual-grained caching on a LSM-tree simulator and evaluate its performance using various Yahoo! Cloud Service Benchmark (YCSB) workloads. Our experimental results show that the proposed way of dual-grained caches can significantly improve the read performance of KV stores without sacrificing the advantages of the LSM-tree for write-intensive workloads. © 2019 IEEE.

关键词： Compaction Throughput conferences Indexes Computer science Benchmark testing distributed databases

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