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001453384 019__ $$a1352971730
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001453384 0247_ $$a10.1007/978-981-19-5403-0$$2doi
001453384 035__ $$aSP(OCoLC)1352412768
001453384 040__ $$aYDX$$beng$$cYDX$$dGW5XE$$dEBLCP$$dOCLCF$$dOCLCQ
001453384 049__ $$aISEA
001453384 050_4 $$aQA76.9.H85
001453384 08204 $$a004.01/9$$223/eng/20221212
001453384 1112_ $$aInternational Conference on Human-Centric Smart Computing$$n(1st :$$d2022 :$$cOnline)
001453384 24510 $$aHuman-centric smart computing :$$bproceedings of ICHCSC 2022 /$$cSiddhartha Bhattacharyya, Jyoti Sekhar Banerjee, Mario Köppen, editors.
001453384 2463_ $$aICHCSC 2022
001453384 260__ $$aSingapore :$$bSpringer,$$c2023.
001453384 300__ $$a1 online resource.
001453384 4901_ $$aSmart innovation, systems and technologies ;$$vv. 316
001453384 500__ $$aIncludes author index.
001453384 5050_ $$aIntro -- Advisory Committee -- Technical Programme Committee -- Scientific Committee -- Preface -- Contents -- About the Editors -- 1 Breast MRI Registration Using Gorilla Troops Optimization -- 1.1 Introduction -- 1.1.1 Transformation -- 1.1.2 Normalized Mutual Information -- 1.2 Related Work -- 1.2.1 Registration of Medical Images -- 1.2.2 Medical Images Registration Approach -- 1.3 Proposed Methodology -- 1.3.1 GTO Algorithm -- 1.4 Result and Discussion -- 1.4.1 Dataset -- 1.4.2 Statistical Significance with NMI -- 1.5 Conclusion -- 1.6 Future Scope -- References
001453384 5058_ $$a2 Forward and Backward Key Secrecy Preservation Scheme for Medical Internet of Things -- 2.1 Introduction -- 2.2 Related Work -- 2.3 The Proposed Scheme -- 2.3.1 Initialization Phase -- 2.3.2 Registration Phase -- 2.3.3 Login Phase -- 2.3.4 Authentication and Key Negotiation Phase -- 2.4 Security Analysis and Performance Evaluation -- 2.4.1 Security Evaluation -- 2.4.2 Performance Evaluation -- 2.5 Conclusion and Future Work -- References -- 3 Systematic Study of Detection Mechanism for Network Intrusion in Cloud, Fog, and Internet of Things Using Deep Learning -- 3.1 Introduction
001453384 5058_ $$a3.2 NIDS Using Deep Learning in Internet of Things (IoT) Network -- 3.2.1 NIDS Using Deep Belief Network (DBN) in IoT -- 3.2.2 NIDS Using Convolutional Neural Network (CNN) in IoT -- 3.2.3 NIDS Using Autoencoder (AE) in IoT -- 3.2.4 Integration of Long Short-Term Memory (LSTM) and CNN in IoT -- 3.3 NIDS Using Deep Learning in Cloud Network -- 3.3.1 NIDS Using AE in Cloud Network -- 3.3.2 NIDS Using Restricted Boltzmann Machine (RBM) in Cloud Network -- 3.3.3 Integration of LSTM, Recurrent Neural Network (RNN), Deep Neural Network (DNN), and DBN in Cloud Network
001453384 5058_ $$a3.3.4 NIDS Using Deep Learning (DL) and Machine Learning (ML) Techniques in Cloud Network -- 3.4 NIDS Using Deep Learning (DL) in Fog Network -- 3.4.1 NIDS Using Convolutional Neural Network (CNN) in Fog Network -- 3.4.2 NIDS Using AE in Fog Network -- 3.4.3 NIDS Using RNN in Fog Network -- 3.4.4 NIDS Using LSTM in Fog Network -- 3.4.5 NIDS Using Deep Learning (DL) and Machine Learning (ML) Techniques in Fog Network -- 3.5 NIDS Using Deep Learning in Edge Network -- 3.5.1 NIDS Using CNN in Edge Network -- 3.5.2 NIDS Using DBN in Edge Network -- 3.6 Conclusion -- References
001453384 5058_ $$a4 Creation and Statistical Analysis of a Corpus for Indian Ankylosing Spondylitis Patients with Focus on COVID-19 -- 4.1 Introduction -- 4.2 Questionnaire Creation -- 4.3 Statistical Analysis -- 4.3.1 Discussions -- 4.4 Conclusion -- References -- 5 Workload Prediction of Virtual Machines Using Integrated Deep Learning Approaches Over Cloud Data Centers -- 5.1 Introduction -- 5.2 Background of the Research -- 5.3 Forecasting Workload with a Deep Learning Model -- 5.3.1 Convolutional Neural Network Model -- 5.3.2 Long Short-Term Memory Based Model
001453384 506__ $$aAccess limited to authorized users.
001453384 520__ $$aThis book includes high-quality research papers presented at the First International Conference on Human-Centric Smart Computing (ICHCSC 2022), organized by the University of Engineering and Management, Jaipur, India, on 2729 April 2022. The topics covered in the book are human-centric computing, hyper connectivity, and data science. The book presents innovative work by leading academics, researchers, and experts from industry.
001453384 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed December 12, 2022).
001453384 650_0 $$aHuman-computer interaction$$vCongresses.
001453384 650_0 $$aArtificial intelligence$$vCongresses.
001453384 655_0 $$aElectronic books.
001453384 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001453384 7001_ $$aBhattacharyya, Siddhartha,$$d1975-
001453384 7001_ $$aBanerjee, Jyoti Sekhar.
001453384 7001_ $$aKöppen, Mario,$$d1964-
001453384 77608 $$iPrint version: $$z981195402X$$z9789811954023$$w(OCoLC)1334722785
001453384 830_0 $$aSmart innovation, systems, and technologies ;$$v316.
001453384 852__ $$bebk
001453384 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-19-5403-0$$zOnline Access$$91397441.1
001453384 909CO $$ooai:library.usi.edu:1453384$$pGLOBAL_SET
001453384 980__ $$aBIB
001453384 980__ $$aEBOOK
001453384 982__ $$aEbook
001453384 983__ $$aOnline
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