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检索条件"任意字段=6th IEEE International Conference on Distributed Computing in Sensor Systems"

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A New Model of Automatic Repowering Management Based on distributed Architecture 6

A New Model of Automatic Repowering Management Based on Dist...

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6th international conference on Power and Energy Applications, ICPEA 2023

作者： Li, Jiayi Zhou, Guanheng Xu, Bo Qi, Wenjun Zhong, Zhiying Fu, Xiaohui Jiangsu Frontier Electric Power Technology Co. Ltd. Smart Grid Service Center Nanjing China

ISBN: (纸本)9798350359053

In order to closely implement the headquarters strategy of constructing excellent service engineering and continuously improving service efficiency proposed by State Grid, and comprehensively improve the time efficiency of users' electricity consumption after payment of bills, based on intelligent electricity meters, and based on the active power restoration (automatic restoration after tripping) function of remote fee-control electricity meters, and through the optimization and upgrading of the digitized business processes of the two sets of systems of electric power marketing and power consumption collection, the Company explored and constructed a new mode of power restoration management based on the distributed architecture and carried out a pilot application. By optimizing and upgrading the digital business processes of the two systems of power marketing and power consumption collection, we explore the construction of a new model of power restoration management based on distributed architecture and carry out pilot applications to realize the restoration of power delivery within 2 hours after the user pays the fee. this paper firstly analyzes the working principle of traditional power outage and restoration, and then introduces the new mode of management based on distributed architecture and the realization of business process transformation in the two systems. Finally, the application effectiveness potential of the new model is described and further research directions are proposed. © 2023 ieee.

关键词： Electric power utilization

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the Influence-Maximizing Node Selection Algorithm Based on Local Isolated Centrality in Large-scale networks Implemented by distributed Graph computing 24

The Influence-Maximizing Node Selection Algorithm Based on L...

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24th ieee international conference on High Performance computing and Communications, 8th ieee international conference on Data Science and systems, 20th ieee international conference on Smart City and 8th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Chen, Piaoyang Lei, Rong Deng, Mingsen School of Information Guizhou University of Finance and Economics Guiyang China

ISBN: (纸本)9798350319934

Identifying influence-maximizing (IM) nodes is an effective strategy for designing efficient communication networks or contain the spreading of information for rumors and epidemics with limited budgets. With the growing of the sizes of the social networks, finding solutions to the problem of intfuence - maximizing vertices becomes more and more challenging. Tra-ditionally, the number of users finally affected was the focus. However, the information diffusion speed was becoming a bottle-neck of IM problems. In this paper, we proposed a locality-aware vertex selection strategy based on local isolation centrality (LIC), while the information diffusion experiments used the Independent Cascade (IC) model. the computing scheme was implemented by a distributed graph computing framework. the superiority of the LIC algorithm was confirmed by evaluated on three real-world datasets. It was indistinguishable from algorithms such as K-shell, H-index, degree centrality (DC), local centrality (LC), and VoteRank at the diffusion cascade scale. But it showed better superiority in diffusion speed. More importantly, by comparing LIC with the VoteRank algorithm, which was the closest algorithm on diffusion speed to that of LIC, the huge advantage of the LIC algorithm in terms of time cost was found. We believe that the locality-aware LIC algorithm was more suitable for the influence-maximization problem in very large-scale social networks. © 2022 ieee.

关键词： Bottles

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An Energy Dispatch Mechanism Based on Double Auction with Multiple Rounds for a Microgrid 23

An Energy Dispatch Mechanism Based on Double Auction with Mu...

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23rd ieee international conference on High Performance computing and Communications, 7th ieee international conference on Data Science and systems, 19th ieee international conference on Smart City and 7th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Liu, Weirong Ma, Cheng Cheng, Yijun Jiang, Fu Rong, Jieqi Peng, Jun School of Computer Science and Engineering Central South University Changsha China School of Automation Central South University Changsha China

ISBN: (纸本)9781665494571

In a microgrid, distributed energy resources (DERs) can supply energy for consumers. How to schedule energy between DERs and consumers and reduce the dependence on the main power grid is of extreme importance for a microgrid. In this paper, a multi-round double auction mechanism is proposed to achieve coordinated and optimal energy dispatch, which allows multiple sellers to trade energy with multiple buyers through adjusting prices dynamically in each round until the buyers' bids are not less than the sellers' asks. Different from existing auctions, the excessive energy of one seller can be divided and traded to multiple buyers, and one buyer can purchase the energy from multiple sellers. the simulation results show that the proposed mechanism significantly reduces auction rounds and the dependence on the main power grid and improves auction utility when compared with the existing double auction. © 2021 ieee.

关键词： Schedules Smart cities Energy resources Simulation Microgrids distributed power generation Resource management

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Real-Time Motion Analysis of Middle-Aged and Aged people Using IMU sensor 6

Real-Time Motion Analysis of Middle-Aged and Aged people Usi...

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6th international conference on Intelligent computing and Control systems, ICICCS 2022

作者： Srija, S. Devaraj, Ashokkumar Karthik, Varshini Srm Institute of Science and Technology Dept. of Bio-Medical Engineering Chennai India

ISBN: (纸本)9781665410359

Walking is a vital feature of locomotion. Foot problems develop with age. Young people walk faster, take longer steps, and take more steps per minute than the elderly. Several foot complications arise in the middle-aged and elderly, such as fall-related injuries, knee pain, foot sores, osteoarthritis, irregular gait, etc. the complications could be identified using motion analysis. Kinematic parameters like accelerations, step length, flexion and extension angles are used in gait analysis. these parameters are measured using the IMU sensor. Depending on this parameter, the designer/user can identify any abnormalities in gait. therefore, a prototype has been developed using an IMU sensor and a microcontroller (Arduino Uno and Raspberry Pi 3). the gait of various participants was recorded using the developed prototype and camera setup. the data collected has been processed and plotted into graphs. the recorded videos were analysed using Kinovea software. the various kinematic parameters, such as step length, acceleration, and knee angles, were found. Aged people have decreased knee flexion compared to middle-aged people. Even the acceleration was low for the elderly. While comparing the acceleration attained by the prototype and the Kinovea software, there was a minor difference. there was a delay observed in the acquisition of the data. therefore, this prototype's flaws will be resolved in future research. © 2022 ieee.

关键词： Motion analysis

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ReSLB: Load Balanced Workflow for distributed Deep Learning Mass Spectrometry Database 24

ReSLB: Load Balanced Workflow for Distributed Deep Learning ...

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作者： Mocheng, Li Yang, Liu Yang, Ou Zhiguang, Chen Nong, Xiao Tao, Chen College of Computer National University of Defense Technology Institute for Quantum Information State Key Laboratory of High Performance Computing Changsha China College of Computer National University of Defense Technology Changsha China School of Computer Sun Yat-sen University Guangzhou China Beijing China

ISBN: (纸本)9798350319934

the proteomics data analysis pipeline based on the shotgun method requires efficient data processing methods. the parallel algorithm of mass spectrometry database search faces the problems of rapidly expanding database size but low scalability. the heterogeneous database search algorithm based on deep learning is an effective way to solve this problem. Still, the deep learning-based distributed parallel database search algorithm is lacking. this paper analyzes the database searching computational load using a neural network and designs ReSLB, a workflow for the restricted search of mass spectrometry data based on GPU cluster and neural network scoring algorithm. this work aims to ensure the high scalability of future deep learning-based mass spectrometry distributed databases. In the performance estimation of 256 GPUs, the load imbalance of less than 30% and the parallel efficiency of 60% are achieved. Compared with state-of-the-art, the time cost is reduced by 75%, and the parallel efficiency from 1 to 256 GPUs is 3.6x higher than that. © 2022 ieee.

关键词： Mass spectrometry

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An Efficient Integrated approach of Fuzzy C-Means Map Reduce for Weather Forecasting Data Collection 6

An Efficient Integrated approach of Fuzzy C-Means Map Reduce...

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6th international conference on Information systems and Computer Networks, ISCON 2023

作者： Sathyamoorthy, Malathy Kumar, Rakesh Vanitha, C.N. Sharma, Bhisham Syamraj, V. Chowdhury, Subrata Kongu Engineering College Tamil Nadu Erode638060 India GLA University Department of Computer Engineering and Applications Mathura India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Sreenivasa Institute of Technology and Management Studies Department of Computer Science and Engineering Andra Pradesh Chittoor India

ISBN: (纸本)9798350346961

Networks of specialized, geographically scattered wireless sensors that track and record environmental physical conditions and transmit the gathered information to a central point are known as wireless sensor networks. Simply Wireless sensor networks are networks of sensors that collect data about the environment. Wireless sensor networks are ideal for real-time projects that require the collection of data. these networks can be deployed for various tasks such as monitoring temperature and humidity this system will collect data about the areas affected. By the earthquake to give warning in advance to these people living those areas. through the use of sensors networks, device will be able to predict the level of flooding in an area and provide helpful forecasts to the people living in the affected areas. A machine learning-based fuzzy c-means algorithm is used as the proposed algorithm and input in the form of a dataset.. © 2023 ieee.

关键词： Wireless sensor networks

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Marine Predator Algorithm for Optimal Placement of EV Charging Station with Optimal Power Factor of DG on Distribution Network 6

Marine Predator Algorithm for Optimal Placement of EV Chargi...

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6th international conference on Contemporary computing and Informatics, IC3I 2023

作者： Pratap, Arvind Tiwari, Prabhakar Maurya, Rakesh Madan Mohan Malaviya University of Technology Department of Electrical Engineering Gorakhpur India Sardar Vallabhbhai National Institute of Technology Department of Electrical Engineering Surat India

ISBN: (纸本)9798350304480

Electric vehicles (EVs) may provide an ecologically sustainable way of transportation. EV charging stations (EVCS) are being developed worldwide to encourage the widespread adoption of EVs. However, the adoption of EVs on a large scale necessitates for the strategic positioning of EVCS across the distribution network. In this paper, the goal of integrating distributed Generation (DG) with real and reactive power correction capabilities is to mitigate the negative impacts of EVCS load on the distribution network. For optimal siting, sizing and operating power factor of DGs with EVCS, nature inspired Marine Predator Algorithm (MPA) is employed. Multiple objective functions, such as active power losses, voltage deviation, the investment cost of DG units, and the voltage stability index, are taken into account. Several scenarios of different number of DG units with EVCS installations are considered to assess the efficacy of the proposed method on 33 and 69-bus radial power distribution systems. the MPA outcomes are also verified by comparing them with the outcomes of the dragonfly algorithm. © 2023 ieee.

关键词： distributed Generation EV charging stations Optimization Algorithm Power loss minimization Voltage Profile

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Data Fusion Opportunities in IoT and its Impact on Decision- Making Process of Organisations 6

Data Fusion Opportunities in IoT and its Impact on Decision-...

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6th international conference on Intelligent computing and Control systems, ICICCS 2022

作者： Ram, M Sethu Sreeram, Anusha Poongundran, Mahizharuvi Singh, Pawan Prajapati, Yogendra Narayan Myrzahmetova, Saltanat School of Engineering & Technology Department of Computer Science & Engineering Sri Padmavati Mahila India Operations & It Hyderabad India Department of Computer Science Madhya Pradesh Amarkantak India Abesit Department Name Cse U. P Ghaziabad India International Education Corporation Department of Design Almaty Kazakhstan

ISBN: (纸本)9781665410359

Use of big data, large observations and elements is a major issue in modern world, which creates difficulties in effective decision-making process. Multi-sensor data fusion technology is effective to use multi-sensors for collecting data from similar target and analyze, the collected data using various computer technology. this process in IoT (Internet of things) system can be used to form data with high accuracy and low reluctance to make effective decisions. Multi-sensor refers to a process, which combines observations from a number of different sensors for providing a robust and complete overview of the environment or any process of interest. Many nodes are included within IoT systems, which are composed with different sensor networks. In this sensor networks, many sensors works together to process different information and make effective *** research will define different use of data fusion opportunities in IoT system, in order to make effective decision in various organizations in Indian and other countries. the aim and objective of this research focusing on use of data fusion techniques, its advantages and disadvantages in IoT connected devices. As per literature findings, data fusion process for with the help of IoT sensors is effective to enhance the quality of data. Secondary thematic analysis has been considered in this study to collect data regarding data fusion with IoT sensors. As per the findings, timely data fusion is effective for organisation to enhance their decision-making process along with some effective challenges in future such as imperfect data, inconsistency, conflicting nature of data and several others. this can be mitigated through new technical intervention in organisation. © 2022 ieee.

关键词： Decision making

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Zero-Touch MEC Resources for Connected Autonomous Vehicles Managed by Federated Learning 9

Zero-Touch MEC Resources for Connected Autonomous Vehicles M...

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9th ieee international conference on Network Softwarization (ieee NetSoft) - Boosting Future Networks through Advanced Softwarization

作者： Ruiz de Mendoza, Carlos Cervello-Pastor, Cristina Univ Politecn Cataluna Dept Network Engn Barcelona Spain

ISBN: (纸本)9798350399806

this paper presents a Ph.D. thesis proposal for a novel solution in optimizing the placement of Connected Autonomous Vehicles (CAVs) Virtual Network Functions (VNFs) requests in Edge computing (EC) resources. Our Federated Deep Reinforcement Learning (FDRL) proposal will be designed to improve computation efficiency while minimizing service rejections and maximizing resource utilization, and ensuring the least costly path for CAVs. this approach will also be privacy-preserving, ensuring sensitive data remains secure and enables reliable, low-latency communication between CAVs, EC nodes, and the federated server. By utilizing distributed learning capabilities, FDRL allows multiple vehicles to learn from their local experience and make collective decisions, improving network systems performance.

关键词： B5G 6G Virtual Network Function Multi-access Edge computing A2C PPO DQN Federated Learning Deep Reinforcement Learning

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sensor-guided motions for robot-based component testing 6

Sensor-guided motions for robot-based component testing

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6th ieee international conference on Robotic computing, (IRC)

作者： Hanke, Julian Eymueller, Christian Poeppel, Alexander Reichmann, Julia Trauth, Anna Sause, Markus Reif, Wolfgang Univ Augsburg Inst Software & Syst Engn Augsburg Germany Univ Augsburg Inst Mat Resource Management Augsburg Germany

ISBN: (纸本)9781665472609

this paper presents the use of sensor-guided motions for robot-based component testing to compensate the robot's path deviations under load. We implemented two different sensor-guided motions consisting of a 3D camera system to minimize the absolute deviation and a force/torque sensor mounted directly to the robot's end effector to minimize occurring transverse forces and torques. We evaluated these two sensor-guided motions in our testing facility with a classical tensile test and a heavy-duty industrial robot. From the obtained results, it can be stated, that transverse forces as well as the absolute deviation were significantly reduced.

关键词： Industrial robots robot-based testing online compensation sensor-guided motions robotics

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