http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
COMPUTATIONAL INTELLIGENCE AND BLOCKCHAIN IN COMPLEX SYSTEMS
system security and interdisciplinary applications
Computational Intelligence and Blockchain in Complex Systems provides readers with a guide to understanding the dynamics of AI, Machine Learning, and Computational Intelligence in Blockchain, and how these rapidly developing technologies are revolutionizing a variety of interdisciplinary research fields and applications. The book examines the role of Computational Intelligence and Machine Learning in the development of algorithms to deploy Blockchain technology across a number of applications, including healthcare, insurance, smart grid, smart contracts, digital currency, precision agriculture, and supply chain. The authors cover the unique and developing intersection between cyber security and Blockchain in modern networks, as well as in-depth studies on cyber security challenges and multidisciplinary methods in modern Blockchain networks. Readers will find mathematical equations throughout the book as part of the underlying concepts and foundational methods, especially the complex algorithms involved in Blockchain security aspects for hashing, coding, and decoding. Computational Intelligence and Blockchain in Complex Systems provides readers with the most in-depth technical guide to the intersection of Computational Intelligence and Blockchain, two of the most important technologies for the development of next generation complex systems.Covers the research issues and concepts of Machine Learning technology in Blockchain Provides in-depth information about handling and managing personal data by Machine Learning methods in Blockchain Help readers understand the links between Computational Intelligence, Blockchain, Complex Systems, and developing secure applications in multidisciplinary sectors.
Front Cover -- Computational Intelligence and Blockchain in Complex Systems -- Copyright Page -- Dedication -- Contents -- List of contributors -- 1 An overview of future cyber security applications using AI and blockchain technology -- 1.1 Introduction -- 1.2 Previous work extent -- 1.3 Using blockchain technologies in cyber security -- 1.4 Blockchain applications in cybersecurity -- 1.5 The application of artificial intelligence technologies in cyber security -- 1.6 The benefits of artificial intelligence in cybersecurity -- 1.7 Here are a few advantages and applications of artificial intelligence in cybersecurity -- 1.8 Conclusion -- References -- 2 A survey of issues, possibilities, and solutions for a blockchain and AI-powered Internet of things -- 2.1 Introduction -- 2.2 The volume of prior work -- 2.3 Internet of things driven by 6G -- 2.4 What is blockchain, anyway? -- 2.5 Blockchain with artificial intelligence: challenges, opportunities, and solutions for the 6G internet of things -- 2.6 Discussion -- 2.7 Conclusion -- References -- 3 A simple online payment system using blockchain technology -- 3.1 Introduction -- 3.1.1 Objectives -- 3.2 Research and design -- 3.2.1 Blockchain technology and its application on online payment systems -- 3.2.2 Designing the architecture of the online payment system -- 3.2.3 Integration of the Metamask API into the online payment system using Python -- 3.2.4 User interface design of the proposed system -- 3.3 Conclusions -- References -- 4 Efficient spam email classification logistic regression model trained by modified social network search algorithm -- 4.1 Introduction -- 4.2 Background and literature review -- 4.2.1 Logistic regression -- 4.2.2 Metaheuristic optimization -- 4.3 Proposed hybrid metaheuristics -- 4.3.1 Introduced social network search algorithm -- 4.3.2 Novel initialization scheme.
4.3.3 Strategy for preserving population heterogeneity -- 4.3.4 Inner functioning and complexity of the proposed algorithm -- 4.4 Experiments and comparative analysis -- 4.4.1 Dataset and preprocessing -- 4.4.2 Experimental setup -- 4.4.3 Obtained simulation outcomes and comparative analysis -- 4.5 Conclusion -- References -- 5 Reviewing artificial intelligence and blockchain innovations: transformative applications in the energy sector -- 5.1 Introduction -- 5.2 Literature review -- 5.2.1 Background of blockchain technology -- 5.2.2 Distributed energy resources, a new paradigm -- 5.2.3 Consensus algorithms -- 5.3 Applications of artificial intelligence and blockchain in the energy industry -- 5.3.1 Artificial intelligence in solar energy: yield performance predictions -- 5.3.2 Using artificial intelligence to improve energy performance -- 5.3.3 Artificial intelligence in grid management -- 5.3.4 Solar coin use on blockchain for renewables -- 5.3.5 Trading in energy (blockchain using peer-to-peer and artificial intelligence technologies) -- 5.3.6 Intelligent grids -- 5.3.7 Grid security -- 5.3.8 Grid administration and efficiency -- 5.3.9 Increased productivity -- 5.3.10 Predictive analytics -- 5.3.11 Storage of energy -- 5.3.12 Trading in energy -- 5.3.13 Power theft and energy fraud detection -- 5.3.14 Microgrids -- 5.3.15 Customer engagement -- 5.4 Use cases -- 5.4.1 Powerledger -- 5.4.2 Energy web foundation -- 5.4.3 Verv -- 5.5 Discussions -- 5.5.1 Comparison between Solana and the Ethereum network -- 5.5.1.1 Tesla power and Powerlegder -- 5.6 Conclusion -- References -- 6 Using artificial intelligence in education applications -- 6.1 Introduction -- 6.2 Extent of past work -- 6.3 Materials and methods -- 6.4 Result and discussion -- 6.5 Conclusion -- References.
7 Performance measurements of 12 different machine learning algorithms that make personalized psoriasis treatment recommend... -- 7.1 Introduction and literature review -- 7.2 Materials and methods -- 7.2.1 Logistic regression -- 7.2.2 Gaussian naive Bayes -- 7.2.3 K-Nearest neighbors -- 7.2.4 Support vector classification -- 7.2.5 Radial basis function -- 7.2.6 Artificial neural network -- 7.2.7 Cart algorithm -- 7.2.8 Random forest -- 7.2.9 Gradient boosting machines -- 7.2.10 XGBoost -- 7.2.11 LightGBM -- 7.2.12 CatBoost -- 7.3 Experimental results -- 7.4 Conclusion and future work -- References -- 8 Healthcare cybersecurity challenges: a look at current and future trends -- 8.1 Introduction -- 8.2 The amount of prior works -- 8.3 Difficulties -- 8.3.1 Security assurance for remote work -- 8.3.2 Endpoint device administration -- 8.3.3 The role of humans in cybersecurity -- 8.3.4 A disregard for security -- 8.3.5 Ineffective risk assessment communication at the board level -- 8.3.6 Poor business continuity strategies -- 8.3.7 Ineffective incident response coordination -- 8.3.8 A tight budget and the requirement to provide healthcare services uninterrupted -- 8.3.9 Dangerous medical cyber-physical systems -- 8.4 A review of current and future trends in cybersecurity challenges in healthcare -- 8.5 Discussion -- 8.5.1 Cyber-physical medical systems -- 8.5.2 Data privacy, confidentiality, and consent -- 8.5.3 Cloud computing -- 8.5.4 Malware -- 8.5.5 Security of health application (or "app") -- 8.5.6 Insider danger -- 8.6 Cybersecurity tools, defenses, and mitigation techniques -- 8.6.1 Cryptographic systems or other technological advances -- 8.6.2 Governance and risk assessment -- 8.6.3 Laws or other regulations -- 8.6.4 A comprehensive strategy for proactive cybersecurity culture -- 8.6.5 Instruction and simulated settings.
8.6.6 Cyber maturity and capability -- 8.6.7 Cyber-hygiene procedures -- 8.7 Conclusion -- References -- 9 EU artificial intelligence regulation -- 9.1 Introduction -- 9.2 Background of the regulation -- 9.2.1 Digital Decade targets and objectives -- 9.2.2 2030 Targets of European Union -- 9.2.3 Multicountry projects -- 9.2.4 Road map -- 9.3 Scope of the regulation -- 9.3.1 What is the Artificial Intelligence Act? -- 9.3.2 Risk assessment -- 9.3.3 Innovation and implementation -- 9.3.4 The harm requirement -- 9.3.5 Current European Union legislation comparison -- 9.4 Conclusion -- References -- 10 The issue of personality rıghts and artıfıcıal intellıgence -- 10.1 Introduction -- 10.2 Person and personality -- 10.2.1 Capacity to have right and capacity to act -- 10.3 Artificial intelligence and personality -- 10.3.1 Ideas that artificial intelligence can not have a legal personality -- 10.3.2 Ideas that artificial intelligence can have a legal personality -- 10.4 Conclusion -- References -- 11 Will artificial intelligence sit on the judge's bench? -- 11.1 Introduction -- 11.1.1 Is jurisdiction a means of solving problems? -- 11.2 Can artificial intelligence realize law? -- 11.3 Can artificial intelligence interpret or create law? -- 11.4 Conclusion -- References -- 12 The effectiveness of virtual reality-based technology on foreign language vocabulary teaching to children with attention... -- 12.1 Introduction -- 12.1.1 The impact that having attention deficit hyperactivity disorder has on a student's ability to succeed academically -- 12.1.2 The use of interventions for students diagnosed with attention deficit hyperactivity disorder -- 12.1.3 Interventions performed in a clinic -- 12.1.4 Technology in education -- 12.1.5 The environments for virtual reality education -- 12.2 Method -- 12.2.1 Participants -- 12.2.2 Materials.
12.2.2.1 Cinema video player plugin -- 12.2.2.2 Virtual reality-based teaching material -- 12.2.2.2.1 Equipment used -- 12.2.2.2.2 Preparing the learning environment -- 12.2.2.2.3 Adaptation to virtual reality -- 12.2.3 Intervention procedure -- 12.2.4 Limitations -- 12.2.5 Validity -- 12.2.5.1 Experimental control/internal validity -- 12.2.5.2 Inter-rater agreement -- 12.2.5.3 Fidelity -- 12.2.5.4 Social validity -- 12.3 Results -- 12.4 Conclusion -- References -- 13 BERT-IDS: an intrusion detection system based on bidirectional encoder representations from transformers -- 13.1 Introduction -- 13.2 Review of related works -- 13.3 Dataset -- 13.4 Method -- 13.5 Results and analysis -- 13.6 Conclusion -- References -- 14 Internet of Things and the electrocardiogram using artificial intelligence-a survey -- 14.1 Introduction -- 14.2 Literature study on electrocardiogram -- 14.2.1 What is electrocardiogram -- 14.2.2 Diseases the electrocardiogram detects -- 14.3 Electrocardiogram signal -- 14.4 Review of technique used in electrocardiogram -- 14.4.1 Genetic algorithm-back propagation neural network -- 14.4.2 Back propagation neural network -- 14.4.3 Artificial neural network -- 14.5 Conclusion -- References -- 15 Evaluation of artificial intelligence in education and its applications according to the opinions of school administrators -- 15.1 Introduction -- 15.2 Method -- 15.2.1 Model of the research -- 15.2.2 Data collection tool -- 15.2.3 Working group -- 15.2.4 Data collection -- 15.2.5 Analysis of data -- 15.3 Findings and comments -- 15.4 Conclusion and recommendations -- References -- 16 Evaluation of tourism developments with artificial intelligence according to the opinions of tourism hotel managers -- 16.1 Introduction -- 16.2 Artificial intelligence in tourism -- 16.3 Use of artificial intelligence in hotels -- 16.4 Methodology.
Includes bibliographical references and index.