001463625 000__ 06170cam\a22006977i\4500
001463625 001__ 1463625
001463625 003__ OCoLC
001463625 005__ 20230601003330.0
001463625 006__ m\\\\\o\\d\\\\\\\\
001463625 007__ cr\cn\nnnunnun
001463625 008__ 230501s2023\\\\si\a\\\\o\\\\\101\0\eng\d
001463625 020__ $$a9789819922338$$qelectronic book
001463625 020__ $$a981992233X$$qelectronic book
001463625 020__ $$z9789819922321$$qprint
001463625 0247_ $$a10.1007/978-981-99-2233-8$$2doi
001463625 035__ $$aSP(OCoLC)1378033256
001463625 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dEBLCP
001463625 049__ $$aISEA
001463625 050_4 $$aQA76.9.B45$$bI58 2023
001463625 08204 $$a005.7$$223/eng/20230501
001463625 1112_ $$aInternational Conference on Big Data Intelligence and Computing$$d(2022 :$$cDenarau Island, Fiji)
001463625 24510 $$aBig data intelligence and computing :$$bInternational Conference, DataCom 2022, Denarau Island, Fiji, December 8-10, 2022, Proceedings /$$cChing-Hsien Hsu, Mengwei Xu, Hung Cao, Hojjat Baghban, A. B. M. Shawkat Ali, editors.
001463625 2463_ $$aDataCom 2022
001463625 264_1 $$aSingapore :$$bSpringer,$$c2023.
001463625 300__ $$a1 online resource (xviii, 560 pages) :$$billustrations (some color).
001463625 336__ $$atext$$btxt$$2rdacontent
001463625 337__ $$acomputer$$bc$$2rdamedia
001463625 338__ $$aonline resource$$bcr$$2rdacarrier
001463625 4901_ $$aLecture notes in computer science,$$x1611-3349 ;$$v13864
001463625 500__ $$aIncludes author index.
001463625 5050_ $$aIntro -- Preface -- Organization -- Contents -- Big Data Algorithm and Systems -- Tiansuan Constellation -- 1 Introduction -- 2 Related Work -- 2.1 Design Overview -- 2.2 Edge Computing and AI in Space -- 3 Method -- 3.1 Datasets -- 3.2 Model Design -- 3.3 Hardware -- 4 Experimental Results -- 4.1 The Comparison -- 4.2 Future Work -- 5 Conclusion -- References -- Adopting a Deep Learning Split-Protocol Based Predictive Maintenance Management System for Industrial Manufacturing Operations -- 1 Introduction -- 2 Literature Reviews -- 3 Overview of Predictive Maintenance and Industries 4.0
001463625 5058_ $$a4 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
001463625 5058_ $$a9 System Architectures and PDM in Industries 4.0 -- 10 AI-Enabled Split-Migration Architecture -- 11 Implementation Details -- 12 Conclusion -- References -- A Digital Twin for Bus Operation in Public Urban Transportation Systems -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Simulation of Urban Mobility (SUMO) -- 3.2 Configuring SUMO to Reproduce Observed Traffic -- 3.3 Bus Operation Digital Twin (BODIT) -- 4 Experiments -- 4.1 Description of the Scenario -- 4.2 Experimental Setup -- 5 Results -- 6 Conclusion and Future Work -- References
001463625 5058_ $$aPredicting 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
001463625 5058_ $$a2 Background of the Study -- 2.1 Ethical Implications of AI in Talent Management -- 2.2 The Application of AI in Talent Management -- 2.3 Career Services in Higher Education -- 2.4 Theories in Technological Adoption -- 3 Design Science Methodology -- 4 Proposed AI Oriented TM Approach -- 5 Discussion and Conclusion -- References -- Development of Bilingual Chatbot for University Related FAQs Using Natural Language Processing and Deep Learning -- 1 Introduction -- 2 Background -- 2.1 What is a Chatbot and How it Works? -- 3 Methodology -- 3.1 Existing Studies -- 4 Proposed Chatbot
001463625 506__ $$aAccess limited to authorized users.
001463625 520__ $$aThis book constitutes the proceedings of the International Conference on Big Data Intelligence and Computing, DataCom 2022, which took place in Denarau Island, Fiji, in December 2022. The 30 full papers included in this volume were carefully reviewed and selected from 88 submissions. The papers detail big data analytics solutions, distributed computation paradigms, on-demand services, autonomic systems, and pervasive applications.
001463625 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed May 1, 2023).
001463625 650_0 $$aBig data$$vCongresses.
001463625 650_0 $$aArtificial intelligence$$vCongresses.
001463625 655_0 $$aElectronic books.
001463625 7001_ $$aHsu, Ching-Hsien,$$eeditor.$$1https://orcid.org/0000-0002-2440-2771
001463625 7001_ $$aXu, Mengwei,$$eeditor.
001463625 7001_ $$aCao, Hung,$$eeditor.
001463625 7001_ $$aBaghban, Hojjat,$$eeditor.$$0(orcid)0000-0003-3193-3770$$1https://orcid.org/0000-0003-3193-3770
001463625 7001_ $$aShawkat Ali, A. B. M.,$$eeditor.
001463625 830_0 $$aLecture notes in computer science ;$$v13864.$$x1611-3349
001463625 852__ $$bebk
001463625 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-2233-8$$zOnline Access$$91397441.1
001463625 909CO $$ooai:library.usi.edu:1463625$$pGLOBAL_SET
001463625 980__ $$aBIB
001463625 980__ $$aEBOOK
001463625 982__ $$aEbook
001463625 983__ $$aOnline
001463625 994__ $$a92$$bISE