001475940 000__ 06138cam\\22006857a\4500
001475940 001__ 1475940
001475940 003__ OCoLC
001475940 005__ 20231003174625.0
001475940 006__ m\\\\\o\\d\\\\\\\\
001475940 007__ cr\un\nnnunnun
001475940 008__ 230812s2023\\\\si\\\\\\o\\\\\100\0\eng\d
001475940 019__ $$a1385450427
001475940 020__ $$a9789819932504$$q(electronic bk.)
001475940 020__ $$a9819932505$$q(electronic bk.)
001475940 020__ $$z9819932491
001475940 020__ $$z9789819932498
001475940 0247_ $$a10.1007/978-981-99-3250-4$$2doi
001475940 035__ $$aSP(OCoLC)1393307354
001475940 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE$$dYDX$$dEBLCP$$dOCLCQ
001475940 049__ $$aISEA
001475940 050_4 $$aQA76.76.E95
001475940 08204 $$a006.33
001475940 1112_ $$aInternational Conference on Advances in Data-driven Computing and Intelligent Systems$$d(2022 :$$cVelha Goa, India)
001475940 24510 $$aAdvances in data-driven computing and intelligent systems :$$bselected papers from ADCIS 2022.$$nVolume 1 /$$cSwagatam Das, Snehanshu Saha, Carlos A. Coello Coello, Jagdish Chand Bansal, editors.
001475940 2463_ $$aADCIS 2022
001475940 260__ $$aSingapore :$$bSpringer,$$c2023.
001475940 300__ $$a1 online resource (885 p.).
001475940 4901_ $$aLecture Notes in Networks and Systems Series ;$$vv.698
001475940 500__ $$a6 Conclusion
001475940 5050_ $$aIntro -- Preface -- Contents -- Editors and Contibutors -- Adaptive Volterra Noise Cancellation Using Equilibrium Optimizer Algorithm -- 1 Introduction -- 2 Problem Formulation -- 3 Proposed Equilibrium Optimizer Algorithm-Based Adaptive Volterra Noise Cancellation -- 3.1 Gbest -- 3.2 Exploration Stage (F) -- 3.3 Exploitation Stage (Rate of Generation G) -- 4 Simulation Outcomes -- 4.1 Qualitative Performance Analysis -- 4.2 Quantitative Performance Analysis -- 5 Conclusion and Scope -- References
001475940 5058_ $$aSHLPM: Sentiment Analysis on Code-Mixed Data Using Summation of Hidden Layers of Pre-trained Model -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 BERT -- 3.2 RoBERTa -- 3.3 SHLPM -- 4 Implementation Details -- 4.1 Dataset and Pre-processing -- 4.2 SHLPM-BERT -- 4.3 SHLPM-XLM-RoBERTa -- 5 Results and Discussion -- 6 Conclusion -- References -- Comprehensive Analysis of Online Social Network Frauds -- 1 Introduction -- 1.1 Statistics of Online Social Network Frauds -- 2 Interrelationship between OSN Frauds, Social Network Threats, and Cybercrime
001475940 5058_ $$a3 Types of Frauds in OSN -- 3.1 Social Engineering Frauds (SEF) -- 3.2 Human-Targeted Frauds (Child/Adults) -- 3.3 False Identity -- 3.4 Misinformation -- 3.5 E-commerce Fraud (Consumer Frauds) -- 3.6 Case Study for Facebook Security Fraud -- 4 OSN Frauds Detection Using Machine Learning -- 4.1 Pros and Cons -- 5 Conclusion -- References -- Electric Vehicle Control Scheme for V2G and G2V Mode of Operation Using PI/Fuzzy-Based Controller -- 1 Introduction -- 2 Motivation -- 3 System Description -- 4 Mathematical Model Equipments Used -- 4.1 Bidirectional AC-DC Converter
001475940 5058_ $$a4.2 Bidirectional Buck-Boost Converter -- 4.3 Battery Modeling -- 4.4 Control of 1-∅-Based Bidirectional AC-DC Converter Strategy -- 5 Fuzzy Logic Controller -- 6 Control Strategy -- 6.1 Constant Voltage Strategy -- 6.2 Constant Current Strategy -- 7 Results and Discussion -- 7.1 PI Controller -- 7.2 Fuzzy Logic Controller -- 7.3 Comparison of Harmonic Profile -- 8 Conclusion -- References -- Experimental Analysis of Skip Connections for SAR Image Denoising -- 1 Introduction -- 2 Related Works -- 2.1 Residual Network -- 2.2 Existing ResNet-Based Denoising Works
001475940 5058_ $$a3 Implementation of the Different Patterns of Skip Connections -- 3.1 Datasets and Pre-processing -- 3.2 Loss Function -- 4 Results and Discussions -- 4.1 Denoising Results on Synthetic Images -- 4.2 Denoising Results on Real SAR Images -- 5 Conclusion -- References -- A Proficient and Economical Approach for IoT-Based Smart Doorbell System -- 1 Introduction -- 2 Literature Review -- 3 System Design and Implementation -- 3.1 System Design -- 3.2 Implementation -- 4 Results and Discussion -- 4.1 Performance Results -- 4.2 Comparison with an Existing System -- 4.3 Cost Analysis -- 5 Limitations
001475940 506__ $$aAccess limited to authorized users.
001475940 520__ $$aThe volume is a collection of best selected research papers presented at International Conference on Advances in Data-driven Computing and Intelligent Systems (ADCIS 2022) held at BITS Pilani, K K Birla Goa Campus, Goa, India during 23 25 September 2022. It includes state-of-the art research work in the cutting-edge technologies in the field of data science and intelligent systems. The book presents data-driven computing; it is a new field of computational analysis which uses provided data to directly produce predictive outcomes. The book will be useful for academicians, research scholars, and industry persons.
001475940 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed August 14, 2023).
001475940 650_0 $$aExpert systems (Computer science)$$vCongresses.
001475940 650_0 $$aComputational intelligence$$vCongresses.
001475940 655_0 $$aElectronic books.
001475940 7001_ $$aDas, Swagatam.
001475940 7001_ $$aSaha, Snehanshu.
001475940 7001_ $$aCoello Coello, Carlos A.
001475940 7001_ $$aBansal, Jagdish Chand.
001475940 77608 $$iPrint version:$$aDas, Swagatam$$tAdvances in Data-Driven Computing and Intelligent Systems$$dSingapore : Springer,c2023$$z9789819932498
001475940 830_0 $$aLecture Notes in Networks and Systems Series.
001475940 852__ $$bebk
001475940 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-3250-4$$zOnline Access$$91397441.1
001475940 909CO $$ooai:library.usi.edu:1475940$$pGLOBAL_SET
001475940 980__ $$aBIB
001475940 980__ $$aEBOOK
001475940 982__ $$aEbook
001475940 983__ $$aOnline
001475940 994__ $$a92$$bISE