Description |
1 online resource (xviii, 560 pages) : illustrations (some color) |
Series |
Lecture notes in computer science, 1611-3349 ; 13864 |
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Lecture notes in computer science ; 13864. 1611-3349
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Contents |
Intro -- Preface -- Organization -- Contents -- Big Data Algorithm and Systems -- Tiansuan Constellation -- 1 Introduction -- 2 Related Work -- 2.1 Design Overview -- 2.2 Edge Computing and AI in Space -- 3 Method -- 3.1 Datasets -- 3.2 Model Design -- 3.3 Hardware -- 4 Experimental Results -- 4.1 The Comparison -- 4.2 Future Work -- 5 Conclusion -- References -- Adopting a Deep Learning Split-Protocol Based Predictive Maintenance Management System for Industrial Manufacturing Operations -- 1 Introduction -- 2 Literature Reviews -- 3 Overview of Predictive Maintenance and Industries 4.0 |
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4 Strategy to Adopt in Predictive Maintenance -- 4.1 Application of Machine Learning Methods to Predict Predictive Maintenance (PdM) -- 5 Pillars of the Total Predictive Maintenance in Industries 4.0 -- 6 Quantum Computing and Digital Manufacturing 4.0 -- 7 Reliability-Centered Maintenance (RCM) -- 7.1 Benefits of the RCM Approach -- 7.2 Key Principles of Reliability-Centered Maintenance (RCM) -- 8 Intelligent Asset Management (IAM and RCM-Controlled Predictive Maintenance) -- 8.1 Wings Within the IAM -- 8.2 Benefits that Could Be Achieved from AIN |
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9 System Architectures and PDM in Industries 4.0 -- 10 AI-Enabled Split-Migration Architecture -- 11 Implementation Details -- 12 Conclusion -- References -- A Digital Twin for Bus Operation in Public Urban Transportation Systems -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Simulation of Urban Mobility (SUMO) -- 3.2 Configuring SUMO to Reproduce Observed Traffic -- 3.3 Bus Operation Digital Twin (BODIT) -- 4 Experiments -- 4.1 Description of the Scenario -- 4.2 Experimental Setup -- 5 Results -- 6 Conclusion and Future Work -- References |
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Predicting Residential Property Valuation in Major Towns and Cities on Mainland Fiji -- 1 Introduction -- 2 Literature Review -- 2.1 Property Valuation Approaches -- 2.2 Feature Selection of Properties -- 2.3 Machine Learning Models for Property Predictions -- 3 Methodology -- 3.1 Data Analysis -- 3.2 Data Pre-processing -- 3.3 Data Visualization -- 4 Results and Discussion -- 4.1 Evaluation on Test Data -- 5 Conclusion -- 6 Limitations -- 7 Future Work -- References -- Designing an AI-Driven Talent Intelligence Solution: Exploring Big Data to Extend the TOE Framework -- 1 Introduction |
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2 Background of the Study -- 2.1 Ethical Implications of AI in Talent Management -- 2.2 The Application of AI in Talent Management -- 2.3 Career Services in Higher Education -- 2.4 Theories in Technological Adoption -- 3 Design Science Methodology -- 4 Proposed AI Oriented TM Approach -- 5 Discussion and Conclusion -- References -- Development of Bilingual Chatbot for University Related FAQs Using Natural Language Processing and Deep Learning -- 1 Introduction -- 2 Background -- 2.1 What is a Chatbot and How it Works? -- 3 Methodology -- 3.1 Existing Studies -- 4 Proposed Chatbot |
Summary |
This book constitutes the proceedings of the International Conference on Big Data Intelligence and Computing, DataCom 2022, which took place in Denarau Island, Fiji, in December 2022. The 30 full papers included in this volume were carefully reviewed and selected from 88 submissions. The papers detail big data analytics solutions, distributed computation paradigms, on-demand services, autonomic systems, and pervasive applications |
Notes |
Includes author index |
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Online resource; title from PDF title page (SpringerLink, viewed May 1, 2023) |
Subject |
Big data -- Congresses
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Artificial intelligence -- Congresses
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Artificial intelligence
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Big data
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Genre/Form |
proceedings (reports)
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Conference papers and proceedings
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Conference papers and proceedings.
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Actes de congrès.
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Form |
Electronic book
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Author |
Hsu, Ching-Hsien, editor.
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Xu, Mengwei, editor
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Cao, Hung, editor
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Baghban, Hojjat, editor.
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Shawkat Ali, A. B. M., editor.
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ISBN |
981992233X |
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9789819922338 |
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