Sustainable Computing and Intelligent Systems : Proceedings of SCIS 2024, Volume 2 (Lecture Notes in Networks and Systems)

Sustainable Computing and Intelligent Systems : Proceedings of SCIS 2024, Volume 2 (Lecture Notes in Networks and Systems)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 246 p.
  • 言語 ENG
  • 商品コード 9789819633135

Full Description

This book presents selected papers from International Conference on Sustainable Computing and Intelligent Systems (SCIS 2024), held on 9-10 September 2024, in University of Canberra, Bruce, Australia. The topics covered in the book are green computing, renewable energy integration, sustainable urban computing, IoT and sustainability, sustainable IoT applications, data analytics for sustainability, internet of things, information security, embedded systems, real-time systems, cloud computing, big data analysis, quantum computing, automation systems, intelligent IoT eHealth, bio-inspired intelligence, brain modeling and simulation, cognitive systems, cyber-physical systems, data analytics, data/web mining, data science, hybrid systems and intelligence for security.

Contents

Chapter 1: Efficient Intrusion Detection through Class Balancing and Feature Selection: A Case Study with SVM.- Chapter 2: A Provisional Study of Detecting Diabetes in Pregnant Women using Machine Learning Models.- Chapter 3: MCDM Methods for Selecting Sustainable Procurement Suppliers in Vietnam's Agricultural Supply Chain Operations.- Chapter 4: Improved Machine Learning Systems for Android Device Malware Detection.- Chapter 5: Unmasking Credit Card Fraud: Advanced Machine Learning and Linear Algebra Techniques for Enhanced Detection.- Chapter 6: Web Application for Insurance Fraud Detection using Machine Learning.- Chapter 7: A Hybrid Efficient Key Management Cloud Scheme for Identifying Insider Misbehaviors and Security Over Data Sharing.- Chapter 8: Advancements in Vedic Multiplier Design: A Comprehensive Review.- Chapter 9: Secure Image Encryption using AES with Chaotic Map-based S Box.- Chapter 10: Leveraging Transformer Models for Abstractive Summarization of Hindi Text.- etc.

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