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...
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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.
The proceedings contain 279 papers. The special focus in this conference is on Big dataanalytics for Cyber-Physical System in smart City. The topics include: Design of a scanning frame vertical shaft;application of b...
ISBN:
(纸本)9789811525674
The proceedings contain 279 papers. The special focus in this conference is on Big dataanalytics 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.
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 ...
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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 f...
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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 headqu...
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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.
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 envir...
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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.
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...
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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.
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 ...
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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 dataanalytics, intelligentcomputing etc...
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The proceedings contain 46 papers. The special focus in this conference is on dataanalytics, intelligentcomputing, and Cyber Security. The topics include: Automated Detection of Skin Lesions Using Back Propagation N...
ISBN:
(纸本)9789811941610
The proceedings contain 46 papers. The special focus in this conference is on dataanalytics, intelligentcomputing, 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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