Post-Quantum Cryptography Algorithms and Approaches for IoT and Blockchain Security, Volume 138 the latest release in the Advances in Computers series, presents detailed coverage of innovations in computer hardware, software, theory, design and applications. Chapters in this new release include Quantum-safe Cryptography Approaches and Algorithms, Quantum Computing : An introduction, BPSK-BRO Framework for avoiding side channel attacks and multiphoton attacks in Quantum Key Distribution, Post-Quantum Cryptography Algorithms and Approaches for IoT and Blockchain Security-Chapter -Delineating the Blockchain Paradigm, Post Quantum Cryptographic approach for IoT Security, and more.Other chapters cover Post-Quantum Lightweight Cryptography Algorithms and Approaches for IoT and Blockchain Security, Quantum-enabled machine learning of Random Forest and Discrete Wavelet Transform for cryptographic technique, Delineating the Blockchain Paradigm, Significance of Post Quantum Cryptosystems in Internet of Medical Things (IoMT, Blockchain-inspired Decentralized Applications and Smart Contracts, and much more.
Role of Internet of Things and Machine Learning in Smart Healthcare, Volume 137 of the Advances in Computers series, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. Published since 1960, this series provides contributors with a medium to explore their subjects in greater depth and breadth than typical journal articles. Additionally, the book discusses the basic concepts of the Internet of Things (IoT) and Machine Learning (ML), along with their various applications in smart healthcare. It proposes novel techniques by integrating IoT, cloud computing, and ML algorithms to efficiently manage e-healthcare data and improve security. The volume also addresses research challenges and probable future directions in smart healthcare using IoT and ML, making it a comprehensive resource for researchers, practitioners, and students interested in advancing healthcare technologies.
Computer-Aided Diagnosis (CAD) Tools and Applications for 3D Medical Imaging, Volume 136 in the Advances in Computers series, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. Chapters in this updated release include Introduction to Computer-aided diagnosis (CAD) tools and applications, Enhancement of three-dimensional medical images, Machine Learning Based Techniques for Computer Aided Diagnosis, AI-based image processing techniques for the automatic segmentation of human organs, Watermarking over medical images, Compressive Sensing for 3D Medical Image Compression, and more.Additional chapters cover Image encryption of medical images, Image Registration for 3D Medical Images, Texture-based computations for processing volumetric dental image, Language Processing in the Brain :an fMRI Study, Research challenges and emerging futuristic evolution for 3D medical image processing, Software based medical image analysis, and Automated 3D Visualization and Volume Estimation of Hepatic Structures for Treatment Planning of Hepatocellular Carcinoma.
Encyclopedia of Mathematical Physics, Second Edition provides a complete resource for researchers, students, and lecturers with an interest in mathematical physics. The book enables readers to access basic information on topics peripheral to their own areas by providing a repository of core information that can be used to refresh even the experienced researcher’s memory and aid teachers in directing students to entries relevant to their course-work. The impressive amount of information in this work - approximately 270 chapters - has been distilled, organized into 10 distinct sections and presented as a complete reference tool to the userThe book is a stimulus for new researchers working in mathematical physics—or in areas using the methods originating from work in mathematical physics—providing them with focused, high-quality background information.
Advances in Computers, Volume 135 highlights advances in the field, with this new volume, Applications of Nature-inspired Computing and Optimization Techniques presenting interesting chapters on a variety of timely topics, including A Brief Introduction to Nature-inspired Computing, Optimization and Applications, Overview of Non-linear Interval Optimization Problems, Solving the Aircraft Landing Problem using the Bee Colony Optimization (BCO) Algorithm, Situation-based Genetic Network Programming to Solve Agent Control Problems, Small Signal Stability Enhancement of Large Interconnected Power System using Grasshopper Optimization Algorithm Tuned Power System Stabilizer, Air Quality Modelling for Smart Cities of India by Nature Inspired AI – A Sustainable Approach, and much more.Other sections cover Genetic Algorithm for the Optimization of Infectiological Parameter Values under Different Nutritional Status, A Novel Influencer Mutation Strategy for Nature-inspired Optimization Algorithms to Solve Electricity Price Forecasting Problem, Recent Trends in Human and Bio Inspired Computing: Use Case Study from Retail Perspective, Domain Knowledge Enriched Summarization of Legal Judgment Documents via Grey Wolf Optimization, and a host of other topics.
Artificial Intelligence and Machine Learning for Open-world Novelty, Volume 134 in the Advances in Computers series presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on AI and Machine Learning for Real-world problems, Graph Neural Network for learning complex problems, Adaptive Software platform architecture for Aerial Vehicle Safety Levels in real-world applications, OODA Loop for Learning Open-world Novelty Problems, Privacy-Aware Crowd Counting Methods for Real-World Environment, AI and Machine Learning for 3D Computer Vision Applications in Open-world, and PIM Hardware accelerators for real-world problems.Other sections cover Irregular Situations in Real-World Intelligent Systems, Offline Reinforcement Learning Methods for Real-world Problems, Addressing Uncertainty Challenges for Autonomous Driving in Real-World Environments, and more.
Applying Computational Intelligence for Social Good: Track, Understand and Build a Better World, Volume 132 presents views on how Computational Intelligent and ICT technologies can be applied to ease or solve social problems by sharing examples of research results from studies of social anxiety, environmental issues, mobility of the disabled, and problems in social safety. Sample chapters in this release include Why is implementing Computational Intelligence for social good so challenging? Principles and its Application, Smart crisis management system for road accidents using Geo-Spacial Machine Learning Techniques, Residential Energy Management System (REMS) Using Machine Learning, Text-Based Personality Prediction using XLNet, and much more.
Advances in Computers, Volume 131 is an eclectic volume inspired by recent issues of interest in research and development in computer science and computer engineering. Chapters in this new release include eHealth: enabling technologies, opportunities, and challenges, A Perspective on Cancer Data Management using Blockchain: Progress and Challenges, Cyber Risks on IoT Platforms and Zero Trust Solutions, A Lightweight Fingerprint Liveness Detection Method for Fingerprint Authentication System, and Collaborating Fog/Edge Computing with Industry 4.0 – Architecture, Challenges and Benefits, Raspberry Pi-s for Enterprise Cybersecurity Applications.
The 130th volume is an eclectic volume inspired by recent issues of interest in research and development in computer science and computer engineering. The volume is a collection of five chapters.
Principles of Big Graph: In-depth Insight, Volume 128 in the Advances in Computer series, highlights new advances in the field with this new volume presenting interesting chapters on a variety of topics, including CESDAM: Centered subgraph data matrix for large graph representation, Bivariate, cluster and suitability analysis of NoSQL Solutions for big graph applications, An empirical investigation on Big Graph using deep learning, Analyzing correlation between quality and accuracy of graph clustering, geneBF: Filtering protein-coded gene graph data using bloom filter, Processing large graphs with an alternative representation, MapReduce based convolutional graph neural networks: A comprehensive review. Fast exact triangle counting in large graphs using SIMD acceleration, A comprehensive investigation on attack graphs, Qubit representation of a binary tree and its operations in quantum computation, Modified ML-KNN: Role of similarity measures and nearest neighbor configuration in multi label text classification on big social network graph data, Big graph based online learning through social networks, Community detection in large-scale real-world networks, Power rank: An interactive web page ranking algorithm, GA based energy efficient modelling of a wireless sensor network, The major challenges of big graph and their solutions: A review, and An investigation on socio-cyber crime graph.