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检索条件"任意字段=2nd International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering"

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Neurodynamic Optimization Approaches to parallel Data Selection in the Era of Big Data

Neurodynamic Optimization Approaches to Parallel Data Select...

引用

2015 2nd international conference on Modelling,Identification and Control(MIC 2015)

作者： Jun Wang Department of Mechanical & Automation Engineering The Chinese University of Hong Kong

In the present information era, huge amount of data to be processed daily. In contrast of conventional sequential data processing techniques, parallel data processing approaches can expedite the processes and more efficiently deal with big data. In the last few decades, neural computation emerged as a popular area for parallel and distributed data processing. The data processing applications of neural computation included, but not limited to, data sorting, data selection, data mining, data fusion, and data reconciliation. In this talk, neurodynamic approaches to parallel data processing will be introduced, reviewed, and compared. In particular, my talk will compare several mathematical problem formulations of well-known multiple winners-take-all problem and present several recurrent neural networks with reducing model complexity. Finally, the best one with the simplest model complexity and maximum computational efficiency will be highlighted. Analytical and Monte Carlo simulation results will be shown to demonstrate the computing characteristics and performance of the continuous-time and discrete-time models. The applications to parallel sorting, rank-order filtering, and data retrieval will be also discussed.

关键词： Neurodynamic Optimization Approaches to parallel Data Selection in the Era of Big Data

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Developing an Edge based predictive maintenance system for transformer using low-cost sensors

Developing an Edge based predictive maintenance system for t...

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Artificial Intelligence in Education and Industry 4.0 (IDICAIEI), DMIHER international conference on

作者： Pratiksha Pradeep Baji Nitin L. Gavankar Mayur Mahambrey Sonali S. Rokade Computer Science and Engineering Walchand College of Engineering Sangli Maharashtra India Research & Development Siemens Verna Goa India

ISBN: (数字)9798331528713

ISBN: (纸本)9798331528720

Transformers are essential for ensuring the reliable distribution and transmission of electrical power. Traditional maintenance procedures, which are generally reactive and schedule-driven, can result in costly breakdowns and unanticipated expenses. This research offers an edge-based predictive maintenance system for transformers that uses powerful machine learning techniques and five temperature sensors strategically distributed throughout the transformer in non-invasive manner. The system uses edge computing to handle real-time temperature data locally, allowing for more precise and accurate anomaly detection and predictive analytics. This strategy enables proactive maintenance, timely interventions, and less operational disturbances. The proposed methodology optimises maintenance schedules, lowers downtime, and increases grid reliability, providing a viable method for managing essential infrastructure and improving overall grid dependability.

关键词： Temperature sensors Temperature distribution Accuracy Image edge detection Tiny machine learning Transformers Sensor systems Real-time systems Maintenance Predictive maintenance

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Design of High Real-Time and Multi-Point Temperature Monitoring System

Design of High Real-Time and Multi-Point Temperature Monitor...

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2011 2nd Asia-Pacific conference on Wearable computing Systems (APWCS 2011);2011 international conference on Intelligent Control and Information Technology(ICICIT 2011)

作者： Ding Bo Xu Lei-Jun Zhao Bu-Hui School of Electrical and Information Engineering of Jiangsu University

This paper introduces an IP core for temperature monitoring a distributed and multi-point temperature monitoring system based on the designed IP core that has fast response time and is capable of parallel *** temperature measuring chip DS18B20 as the control object,we implement both initialization and read/write controls of it in our IP *** correctness of our IP core is verified using Modelsim-based *** our IP core,we also implement a multiplexed real-time temperature monitoring system using the DE2 development *** test results show that the designed system meets the stringent requirements of multi-channel and parallel processing *** implemented system also has the advantage of high portability and good real-timer performance.

关键词： real time,IP core,temperature monitoring,Nios II,SOPC

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Path Planning of Mobile Robot Based on an Improved Genetic Algorithm

Path Planning of Mobile Robot Based on an Improved Genetic A...

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Digital Twins and parallel Intelligence (DTPI), IEEE international conference on

作者： Zenghua Chen Gang Xiong Sheng Liu Zhen Shen Yue Li State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China School of Automobile Chang'an University Xi'an China

ISBN: (数字)9781665492270

ISBN: (纸本)9781665492287

In order to solve the problem of premature convergence of the basic genetic algorithm when planning the robot running path, the basic genetic algorithm is improved and optimized. Different population initialization methods are used to initialize multiple populations randomly, so as to improve the diversity of populations; Improve the adaptive strategy and elite strategy of crossover and mutation operators to improve the convergence speed of the algorithm; Add the path tortuosity as the planning index in the fitness function to make the planned path smoother, and add constraints to the model to avoid obstacles; Finally, through the transformation of the coding paradigm of the above improved genetic algorithm, it can run on Flink distributed cluster to obtain faster solution speed, so as to meet the efficiency requirements of path planning in large-scale robot cluster system. The optimized algorithm is compared with the basic genetic algorithm. The simulation results show that the improved algorithm is efficient in robot path planning.

关键词： Sociology Clustering algorithms Path planning Planning Trajectory Statistics Collision avoidance

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2nd international conference on computing, Communication, and Learning, CoCoLe 2023

2nd International Conference on Computing, Communication, an...

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2nd international conference on computing, Communication, and Learning, CoCoLe 2023

ISBN: (纸本)9783031569975

The proceedings contain 25 papers. The special focus in this conference is on computing, Communication, and Learning. The topics include: Yolo and RetinaNet Ensemble Transfer Learning Detector: Application in Pavement Distress;stock Market Prediction Performance Analysis by Using Machine Learning Regressor Techniques;nearest Neighbor and Decision Tree Based cloud Service QoS Classification;object Recognition Through Content Based Feature Extraction and Classification of Sounds in IoT Environment;detection of Malicious Activity on Credit Cards Using Machine Learning;agent-Based Modeling for Optimum Location Selection: Enhancing Day-Ahead Market Analysis for Microgrid Integration;a Comparative Approach for Skin Cancer Detection Using Artificial Bee Colony;a Hybrid Approach to Enhance Software Quality by Sentiment Analysis of Developer;unsupervised Sentiment Analysis of Amazon Fine Food Reviews Using Fuzzy Logic;sentiment Analysis of Crypto Currency Trading Applications in India Using Machine Learning;Graph Similarity Join (GSJ) Approach to Detect Near Duplicate Text Documents;three Factor Authentication Scheme for Telecare Medical Information System;an Effective Threshold Based Technique for Retinal Image Blood Vessel Segmentation on Fundus Image Using Average and Gaussian Filters;substantiation System Using Facial Recognition and Principal Component Analysis;impact of Stress on Faculties’ Attitudes: A Study of Higher Education Institutes;dynamic Cross-Layer Communication Design for Multi-objective Optimization in Wireless Sensor Networks;Implementation of Weighted parallel Interference Cancellation Technique for Multi User Detection in UWA Communication;analysis and Comparison of Firefly Algorithm for Measuring Convergence Rate in distributed Environment;A Comparative Study on Social Behavior of Tribes and Non Tribes in ITDA Paderu by Using Network Science;raster Big Data Processing Using Spark with GeoTrellis.

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Block-SDoTcloud: Enhancing Security of cloud Storage through Blockchain-based SDN in IoT Network

Block-SDoTCloud: Enhancing Security of Cloud Storage through...

引用

Sustainable Technologies for Industry 4.0 (STI), international conference on

作者： Anichur Rahman Md. Jahidul Islam Md. Saikat Islam Khan Sumaiya Kabir Ahmed Iqbal Pritom Md. Razaul Karim National Institute of Textile Engineering and Research (NITER) Green University of Bangladesh Mawlana Bhashani Science and Technology University

ISBN: (数字)9781665404891

ISBN: (纸本)9781665404907

Software Defined Networking (SDN) and Blockchain (BC) are the most recent research trends in emerging technology. These technologies have currently been used in the IoT networking environment for various purposes, such as protection, stability, scalability, confidentiality, and so on. Such techniques can be used in this regard to effectively provide security, privacy, and confidentiality to cloud storage. In this paper, the authors proposed Block-SDoTcloud architecture to significantly enhance security within the cloud storage network. In order to give the cloud storage environment the requisite facilities, two leading technologies, i.e., SDN and Blockchain were applied. The centralized SDN controller provided the proposed model with tremendous reliability, versatility, and load balancing in one side while on the other hand, a distributed Blockchain created a deep trust between the transaction levels resulting into effective protection for the presented scheme. The efficiency of the proposed architecture is justified through close observation of simulation with a careful selection of relevant parameters.

关键词： cloud computing Blockchain Computer architecture Stability analysis Security Software defined networking Load modeling

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Terms Development of Additive Manufacturing

Terms Development of Additive Manufacturing

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Digital Twins and parallel Intelligence (DTPI), IEEE international conference on

作者： Tariku Sinshaw Tamir Gang Xiong Jingchao Jiang Zhen Shen Ehtisham Lodhi Hub Ali Li Wan Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin Hong Kong Intelligent Manufacturing Center Qingdao Academy of Intelligent Industries Qingdao China Ten Dimensions (Guangdong) Technology Co. Ltd Foshan China

ISBN: (数字)9781665492270

ISBN: (纸本)9781665492287

Nowadays, additive manufacturing has been increasingly developed and applied in many fields. As a rapid development of additive manufacturing, similar terms are appeared, such as 3D printing, freeform fabrication, rapid tooling, rapid manufacturing, direct digital manufacturing, layer manufacturing, additive process, 4D printing, 3D bioprinting, and 3D biofabrication. This paper reports and analyze the development of these terms. Moreover, it tries to give the readers a comprehensive understanding of these terms and their development.

关键词： Fabrication Additives Three-dimensional displays Three-dimensional printing Market research Digital twins Biological materials

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A Cost-effective parallel Algorithm of Distribution Network Reconfiguration on Hadoop Cluster

A Cost-effective Parallel Algorithm of Distribution Network ...

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2017 2nd international conference on Materials Science,Machinery and Energy engineering(MSMEE 2017)

作者： Wanxing Sheng Keyan Liu Shupeng Zhou Song Jin Wei Tang China Electric Power Research Institute Department of Electronic and Communication Engineering North China Electric Power University College of Information and Electrical Engineering China Agricultural University

Rapid construction of electric power systems leads to a large increase in quantities of network nodes and data, complicating network reconstruction issue significantly. However, the traditional serial algorithms can not reach a satisfactory computation speed;while some proposed parallel algorithms prior are only applicable to specialized cluster. In this paper, we propose a parallel algorithm of distribution network reconstruction conducted on cost-effective Hadoop cluster. Our algorithm complies with Map-Reduce distributed computing framework. It can process the data of each network node in parallel, thus accelerating power flow calculation. Moreover, our algorithm combines depth-first and breath-first principles together in branch traversals, which substantially improves the probability in finding the optimal solution. Feasibility and effectiveness of the proposed algorithm are verified on a Hadoop cluster.

关键词： Distribution network Map-reduce parallelization Power flow calculation Reconfiguration

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Research on Computer Aided French Audiovisual Intelligence System

Research on Computer Aided French Audiovisual Intelligence S...

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Sensors, Electronics and Computer engineering (ICSECE), IEEE international conference on

作者： Fengyi Sun Xianda School of Economics and Humanities Shanghai International Studies University Shanghai China

ISBN: (数字)9798350373646

ISBN: (纸本)9798350373653

Aiming at the existing problems in French education, a set of intelligent French teaching system with independent intellectual property rights is designed and implemented. Based on cloud computing, the system realizes the effective integration of various network resources distributed between servers and users. It effectively improves the query efficiency of network resources. The system assesses and evaluates students' knowledge and learning outcomes based on their cognitive and knowledge acquisition preferences. This project intends to study the pseudo-color display based on C# programming. Through nonlinear transformation, the correspondence between spectral intensity and color is constructed to achieve the purpose of pseudo-color display. It is applied to the display of language graph and the interface design of speech signal. In addition, the function of sound playback is added to the display of the spectrum, so that it can be reproduced in a “visual” way. This algorithm has the characteristics of simple program, flexible man-machine interface and small demand for instruments. It can be done on a normal PC. Through simulation and verification, the method has a good effect. Finally, the proposed algorithm is verified by computer simulation experiment.

关键词： Visualization Image color analysis Education Transfer functions User interfaces Sensor systems and applications Servers Logic Speech processing Programming profession

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MAP-REDUCE BASED CRAWLER FOR MICROBLOG

MAP-REDUCE BASED CRAWLER FOR MICROBLOG

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2012 IEEE 2nd international conference on cloud computing and Intelligence Systems

作者： Yidong Cui Ruiqing Huang School of Software Engineering Beijing University of Posts and Telecommunications

Recently, microblog has been a popular tool for the public to express themselves. So fetching the data in microblog is very important for public opinion monitoring. This paper presents a Map-Reduce based crawler for fetching microblog data, which overwhelms traditional web crawler and api-based microblog crawler on scalability, transparent storage and generalization. In the paper, we first build a model for microblog network to confirm what and how our crawler will crawl from the net, then integrate Map-Reduce framework with our crawler, design the implementation details and finally make experimental tests. We run our crawler on Hadoop clusters and store the fetched data in Hbase. The experimental results show that using Map-Reduce framework can greatly improve the crawling efficiency.

关键词： Map-reduce Hadooop Hbase parallel crawler Microblog

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