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Query-driven Edge Node Selection in Distributed Learning Environments 39

Query-driven Edge Node Selection in Distributed Learning Env...

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IEEE 39th international conference on data Engineering (ICDE)

作者： Aladwani, Tahani Anagnostopoulos, Christos Kolomvatsos, Kostas Alghamdi, Ibrahim Deligianni, Fani Univ Glasgow Sch Comp Sci Glasgow Scotland Univ Thessaly Dept Informat & Telecommunicat Volos Greece Al Baha Univ Dept Comp Sci Fac Sci & Arts Baljurashi Al Baha Saudi Arabia

ISBN: (纸本)9798350322446

computing nodes in Edge computing environments share unlimited data. Such data are exploited to locally build Machine Learning (ML) models for applications such as predictive analytics, exploratory analysis, and smart applications. This edge node-centric local learning reduces the need for data transfer and centralization, which is affected by different factors such as data privacy, data size, communication overhead, and computing resource limitations. Therefore, a collaborative learning fashion at the network edge has appeared as a promising paradigm that enables multiple distributed (edge) nodes to train and deploy ML models cooperatively without infringement of data privacy. Nevertheless, the variety, distribution and quality of data vary between edge nodes. Hence, selecting unsuitable edge nodes can have a negative impact on the ML model performances. We have devised (i) an intelligent node selection mechanism per analytics query based on the range of the availability of required training data at the edge and (ii) variants of collaborative learning processes engaging the most suitable nodes for models training and inference. We evaluate the efficiency of our selection mechanism and collaborative learning and provide a comparative assessment with other methods found in the literature using real data. The results showcase that our mechanism significantly outperforms baseline approaches and existing node selection mechanisms in distributed computing environments.

关键词： Query-driven node selection Distributed learning data overlapping.

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

1st International Conference on Big Data Analytics for Cyber...

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

ISBN: (纸本)9789811525674

The proceedings contain 279 papers. The special focus in this conference is on Big data analytics for Cyber-Physical System in smart City. The topics include: Design of a scanning frame vertical shaft;application of big data to precision marketing in B2C e-commerce;application of information theory and cybernetics in resource configuration;structural optimization of service trade under the background of big data;analysis of the relationship between individual traits and marketing effect of e-commerce marketers based on large data analysis;Analysis of urban street microclimate data based on ENVI-met;big data security issues in smart cities;system test of party affairs work management information system in higher vocational colleges;design method of axial clearance adjustment gasket for mass production components based on big data application;exploration on the implementation path of drawing course under the information-based background;practical teaching mechanism of electronic commerce;development status and challenges of unmanned vehicle driving technology;Analysis and research of mine cable fault point finding method based on single chip microcomputer and FPGA technology;emotional analysis of sentences based on machine learning;application and research of basketball tactics teaching assisted by computer multimedia technology;accurate calculation of rotor loss of synchronous condenser based on the big data analysis;a parallel compressed data cube based on hadoop;development trends of customer satisfaction in China’s airline industry from 2016 to 2018 based on data analysis;intelligent outlet based on ZMCT103C and GSM;internal quality control and evaluation method of food microorganism detection;shared smart strollers.

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Application of Artificial Bee Colony Algorithm in intelligent Price Supervision System of Digital Economy 2

Application of Artificial Bee Colony Algorithm in Intelligen...

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2nd international conference on data analytics, computing and Artificial Intelligence, ICDACAI 2023

作者： Li, Weijun Wuxi Vocational Institute of Commerce School of Tourism & Culinary Arts Jiangsu Wuxi214100 China

ISBN: (纸本)9798350339765

With With the rapid development of the digital economy and the continuous expansion of the market, the demand for intelligent price regulation systems has become increasingly urgent, and relying solely on traditional regulatory methods is no longer sufficient to meet the market demand. Therefore, this article proposed an intelligent price supervision method based on artificial bee colony algorithm. Through the monitoring and analysis of the market price, the artificial bee colony algorithm can quickly find the rule and trend of the market pricing, and adjust the price through the optimization algorithm to achieve a good regulatory effect. This article designed and analyzed the system, and used data comparison to study the price intelligent supervision system. Through experimental verification, the security of the intelligent price supervision system based on artificial bee colony algorithm reached a maximum of 98%, which can meet the system requirements. © 2023 IEEE.

关键词： Optimization

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An Efficient Ensemble Model for Forecasting Time Series Analysis of Crypto Currency data Using Machine Learning

An Efficient Ensemble Model for Forecasting Time Series Anal...

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2021 IEEE international conference on Innovative computing, intelligent Communication and smart Electrical Systems, ICSES 2021

作者： Saravanakumar, C. Lakshmi, S. Kanaga Prakash, M. Vijayakumar, M. Arun, C. St. Joseph's Institute of Technology Department of Information Technology Chennai India Sri Muthukumaran Institute of Technology Department of Management Studies Chennai India Data Science and Analytics Center Karpagam College of Engineering Coimbatore India St. Joseph's Institute of Technology Department of Computer Science and Engineering Chennai India R.M.K College of Engineering and Technology Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9781665435215

Time series data are analyzed for predicting the future based on the consistent time period using statistical methods. These analyses are based on the data which are extracted from different sources. Existing method for performing the forecasting process does not fit into the crypto currency data. GARCH and ARIMA models with intelligent mechanisms provide the solution but it is not at the proper level. RNN model takes the data from preexisting intervals and decides the next time series data which is represented as a directed graph. Two types of behavior are considered namely spatial and temporal. The linear model uses the homogeneous data and heterogeneous data analysis is based on the nonlinear model. The nodes and layers are connected based on the input and corresponding activation unit. The memory model is attached to the RNN model for making persistent storage for keeping the processed data for a longer time. The proposed model uses the ensemble method for integrating various RNN models for achieving a high level of accuracy. © 2021 IEEE.

关键词： Time series analysis

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Application of the Big data Technology in the Chain Operation Management

Application of the Big Data Technology in the Chain Operatio...

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international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Tang, Xiaohua Sichuan Technol & Business Coll Dujiangyan 611830 Sichuan Peoples R China

ISBN: (纸本)9783030152352;9783030152345

The chain operation of enterprises has been gradually improved in today's society, and now it has already begun to have an excellent management mode. In the operation of the chain enterprises, the corporate headquarters plays a decisive role. It is the flag of all the subsidiaries and sub-organizations. Therefore, it is necessary for the corporate headquarters to play an excellent management function and bring the excellent corporate cultures into play to the chain enterprises. This paper, based on the big data technology, analyzes its application strategies in the chain operation management.

关键词： Chain operation Management work Big data technology Application

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Multi-Reference Based Target Tracking for TDOA Systems

Multi-Reference Based Target Tracking for TDOA Systems

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IEEE international conference on Big data and smart computing (BigComp)

作者： Baek, Jaeuk Lee, ChangEun Park, Sangjoon ETRI Intelligent Convergence Res Lab Daejeon 34129 South Korea

ISBN: (纸本)9781728189246

In military and civilian applications, target localization is one of the crucial techniques to improve spatial awareness and enable location services without human intervention. However, in a noisy and cluttered environment, it is challenging to achieve high estimation accuracy due to inherent measurement error and clutter-reflected measurement via non-line of sight (NLOS) link between radar sensors and target. In this paper, we propose a multi-reference based target localization (MRTL) process to estimate the location of targets using time difference of arrival (TDOA) measurement. Compared to single reference TDOA systems where target localization may fail in some cases due to sensor-target geometry and TDOA error, the proposed MRTL can he a reliable and robust solution by utilizing multiple reference sensors simultaneously. Simulation results are provided to demonstrate the performance of our proposed MRTL process.

关键词： TDOA Real time localization Target tracking Radar system

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An Entropy-Based Technique for conferences Ranking 3rd

An Entropy-Based Technique for Conferences Ranking

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international conference on data Management, analytics and Innovation (ICDMAI)

作者： Majeed, Fiaz Ul Haq, Rana Azhar Univ Gujrat Fac Comp & Informat Technol Dept Informat Technol Gujrat Pakistan Univ Gujrat Fac Comp & Informat Technol Dept Comp Sci Gujrat Pakistan

ISBN: (纸本)9789813299498;9789813299481

Ranking of conferences is carried out to guide the researchers so as to publish their work in top-level venues. Existing works are needed to be improved in regard to accuracy. In this paper, we have proposed a ranking technique of conference papers named as influence language model (InLM). It uses entropy to calculate score for the purpose of ranking. It identifies level of the paper as well as level of the conference based on entropy score. Experiments have been performed on bigger dataset. The results reflect better position in comparison to the existing systems.

关键词： conference ranking Language model Influence language model Entropy Scientific research

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E-crime Management System for Future smart City

E-crime Management System for Future Smart City

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international conference on data Processing Techniques and Applications for Cyber-Physical Systems, DPTA 2019

作者： Kamruzzaman, M.M. Jouf University SakakaAl-Jouf Saudi Arabia

ISBN: (纸本)9789811514678

Architecture of an E-crime management system for future smart city is proposed in this paper. The architecture is divided into four main components: Police Station, Server, Internet and Citizen of smart city. Citizen of smart city can use any type of microcomputer such as: smart phone, tablet, laptop or desktop to register a case from online. Specification of server to make it secure and reliable is listed in this paper. Investigation center is equipped with Forensic Services, Artificial intelligence and analytics module and connected with the main server. All information related to investigation and criminals can be stored in this system for further proceeding. At present, part of the proposed architecture is designed and implemented which is also described in this paper. © 2020, Springer Nature Singapore Pte Ltd.

关键词： smart city

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smart cities: Progress and Problems in India

Smart cities: Progress and Problems in India

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2018 IEEE international conference on Advances in computing, Communication Control and Networking, ICACCCN 2018

作者： Gupta, Priyanka Gupta, Rajan Vivekananda Institute of Professional Studies GGSIPU New Delhi India

ISBN: (纸本)9781538641194

The urge of urbanization is increasing at a rapid rate worldwide. It ensues the emergence and use of various digital technologies like Internet of Things, Cloud computing, Big data analytics, intelligent computing etc. The one important and most hyped application of such technologies is smart Cities. This concept revitalizesthe whole city by strengthening its core competencies. It automates every sector like transportation, homes, traffic, agriculture, water and electricity supply, waste management, health, education etc. This notion is implementing in various parts of the world leading to the new level of urbanization. The perception of this powerful approach in India is presented in this paper. The current stage of this project and the possible roadblocks in implementing it in Indian scenario is also discussed in this manuscript. © 2018 IEEE.

关键词： smart city

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international conference on data analytics, intelligent computing, and Cyber Security, ICDIC 2020

International Conference on Data Analytics, Intelligent Comp...

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international conference on data analytics, intelligent computing, and Cyber Security, ICDIC 2020

ISBN: (纸本)9789811941610

The proceedings contain 46 papers. The special focus in this conference is on data analytics, intelligent computing, and Cyber Security. The topics include: Automated Detection of Skin Lesions Using Back Propagation Neural Network;Detection of COVID-19 Using CNN and ML Algorithms;Prioritization of Watersheds Using GIS and Fuzzy Analytical Hierarchy (FAHP) Method;a Narrative Framework with Ensemble Learning for Face Emotion Recognition;modified Cloud-Based Malware Identification Technique Using Machine Learning Approach;design and Deployment of the Road Safety System in Vehicular Network Based on a Distance and Speed;Diagnosis of COVID-19 Using Artificial Intelligence Techniques;classification of Credit Card Frauds Using Autoencoded Features;location Tracking via Bluetooth;shrimp Surfacing Recognition System in the Pond Using Deep Computer Vision;sign Language Recognition for Needy People Using Machine Learning Model;efficient Usage of Spectrum by Using Joint Optimization Channel Allocation Method;an intelligent Energy-Efficient Routing Protocol for Wearable Body Area Networks;enhanced Video Classification System with Convolutional Neural Networks Using Representative Frames as Input data;text Recognition from Images Using Deep Learning Techniques;early Detection and Diagnosis of Oral Cancer Using Fusioned Deep Neural Network;fine-tuning for Transfer Learning of ResNet152 for Disease Identification in Tomato Leaves;AI-Based Mental Fatigue Recognition and Responsive Recommendation System;BIVFN: Blockchain-Enabled intelligent Vehicular Fog Networks;Multiple Slotted Triple-Band PIFA Antenna for Wearable Medical Applications at 2.5–9 GHz;fish Classification System Using Customized Deep Residual Neural Networks on Small-Scale Underwater Images;multiple Face Recognition System Using OpenFace;EDAARP-Efficient and data-Aggregative Authentic Routing Protocol for Wireless Sensor Networks;preface.

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