Abstract: Part I: Industry -- Numerical study through CFD of the behavior of a centrifugal fan for dust extraction systems -- Optimization of the stamping process of oven sides panels for domestic cooking through finite element modeling -- Topological optimization of swing arm for electric motorcycles -- Micromechanical modeling of biobased sisal polylactic acid compounds -- A Proposal of a Fair Voting Ensemble Classifier Using Multi-Objective Optimization -- Physical-Chemical Characterization of Cocoa Oil Subjected to an Accelerated Fermentation Process -- Control system for a cacao drying process: case study cylindrical dryer -- Comparative study of multivariate statistical methods for predicting the academic performance of students at the University of Guayaquil -- Calculation of the efficiency of an electromagnetic coil according to the induction resistance of the pot -- Development of a Control System for a Biomechanical Prosthetic -- The Impact of Intranet Use on Internet Sales During COVID-19: A Study of Companies in Ecuador -- Embedded Systems for Tracking and Detection of Pets through an IoT Network -- Mobile Application for Online Procedures in the Municipality of San Miguel de Ibarra -- Assessment of decommissioning cost of proton therapy centers depending on the shielding material in the building process -- Vehicular Ad-Hoc Network (VANET) -- Part II: Infotelecom -- Use of leaderboards to gamified drive student performance as a motivational strategy in VLE environments -- Microlearning as a learning consolidation strategy for the university blended learning modality in a VLE -- Physical and Organoleptic Evaluation of 12 Cocoa Clones (Theobroma cacao L.) of National Type, in Cocoa Liquor – A Study from Ecuador -- External factors and socioeconomic influence on users acceptance of online payments -- Proposal of evaluation cases for the standardization of the validation activities of neutron unfolding codes -- Function and Management Emulation of CEDIA Backbone: The Ecuadorian Advanced Network Updated From IPv4 to IPv6 -- Implementation of an Intelligent Platform for Sustainable Urban Water Consumption Management: A Case Study of Digital Transformation in Zaruma City, Ecuador -- Governmental portal of the National Transit Agency of Ecuador: Web usability aspects and user satisfaction aimed at the elderly. -- Development of a Web Application for evaluating corporate social responsibility practices -- Performance evaluation of an internet-of-things platform based on open-source -- Development and evaluation of an intelligent chatbot for the management of citizen procedures in the GAD San Miguel de Ibarra -- Software for Speech Therapy Support Through PECS Oriented to Digital Learning Environments For Children With Moderate ASD -- Development of a Brain-Computer Interface to Control Finger Movements of a Robotic Hand -- Proposal of an Agile Approach based on Scrum for Managing Continuing Education Programs -- Development of a Compact Synchrotron Proton Therapy Center Model for Monte Carlo-Based Radiation Protection Studies.

Abstract: This book is dedicated to exploring the practical applications and future perspectives of intelligent technologies. It delves into various domains, including industry, mobility, telecommunications, and environmental considerations. The innovative nature of this text enables us to draw connections between technical advancements and experiences aimed at enhancing the integration of emerging technologies on local, national, and regional scales. It showcases the strides made in diverse engineering domains, underlining the book’s multidisciplinary appeal. This book is intended for a wide readership, catering to master's and doctoral students, professors, and researchers in the field of cutting-edge technologies. It also extends its relevance to businesses engaged in engineering development. The contents offer insights into novel methodologies, real-world case studies, and innovative techniques designed to optimize systems, ultimately contributing to societal progress.

Abstract: The book is a unique collection of studies involving intelligent systems and applications of artificial intelligence in the real world to provide solutions to most vexing problems. IntelliSys received an overwhelming 605 papers which were put under strict double-blind peer-review for their novelty, originality and exhaustive research. Finally, 227 papers were sieved and chosen to be published in the proceedings. This book is a valuable collection of all the latest research in the field of artificial intelligence and smart systems. It provides a ready-made resource to all the readers keen on gaining information regarding the latest trends in intelligent systems. It also renders a sneak peek into the future world governed by artificial intelligence.

Abstract: Exploring the Impact of Deep Learning Techniques on Evaluating Arabic L1 Readability -- Performance Analysis of Two Serial Concatenations of Decoders over a Rayleigh Channel -- Blockchain and Reputation Based Secure Service Provision in Edge-cloud Environments -- Exploring the Impact of Convolutions on LSTM Networks for Video Classification -- Classification algorithms implementation for fire prevention data on multiple wireless node sensors -- Implementation of an intelligent monitoring system based on Quality 4.0 of the Induction Hardning process -- Lithium-Ion Battery State of Charge Estimation Using Least Squares Support Vector Machine -- Intrusion Detection in Software-Defined Networking using Machine Learning Models -- Neural Network for link Prediction in social network -- Design and optimization of a compact Microstrip band-pass filter using on open loop rectangular resonators for wireless communication systems -- YOLO-based Approach for Intelligent Apple Crop Health Assessment -- A comprehensive review on the integration of Blockchain Technology with IPFS in IoT ecosystem.

Abstract: This book is to provide a comprehensive reference for professionals in the field of data science and applications: artificial intelligence, big data, IoT, and blockchain. In summary, this book is expected to function as a helpful resource and manual, enabling readers to navigate the intricate domain of artificial intelligence, the Internet of things (IoT), and blockchain in smart environments. This book covers many topics related to integrating AI, IoT, blockchain, and smart environments. It begins by laying a solid foundation, introducing each technology's fundamental concepts and principles. Subsequent chapters explore applications and real-world use cases, demonstrating how AI, IoT, and blockchain can effectively address critical challenges within data science and applications.

Abstract: The book is a unique collection of studies involving intelligent systems and applications of artificial intelligence in the real world to provide solutions to most vexing problems. IntelliSys received an overwhelming 605 papers which were put under strict double-blind peer-review for their novelty, originality and exhaustive research. Finally, 227 papers were sieved and chosen to be published in the proceedings. This book is a valuable collection of all the latest research in the field of artificial intelligence and smart systems. It provides a ready-made resource to all the readers keen on gaining information regarding the latest trends in intelligent systems. It also renders a sneak peek into the future world governed by artificial intelligence.

Abstract: Introduction -- The DARPA Dilemma -- Scattered Avatars -- Topsy Turing -- Fractured Memories -- Artificial Neurogenesis -- The Assimilation -- The Collective Singing the ‘I Can’t Decrypt Them’ Blues -- SANDI’s Environment -- Chatbot Lydia -- Asimov’s Failure -- The Hackers get Hacked -- Dangerous Liaisons -- SANDI’s Dilemma -- Dead. Yet Alive -- Answers at Last -- Preparing to Bring them Home -- The Collection Process -- The Final Preparations -- The Integration Begins -- The Integration of MAXWELL -- The Integration of ISAAC -- The Integration of SANDI -- The Integration of ELYSE -- When Robots Hug -- The Science Behind the Novel -- Conclusion.

Abstract: By 2027, it had been seven years since the scientists’ sea-changing research on artificial psychology and robotics. The work debuted around the same time as Large Language Model Chatbots, and the power of the integration of the two technologies put many industries in a tailspin. The commercial and defense industries especially were still scrambling to regulate their use in research and universities. The sought-after scientists signed with DARPA to build reliable and secure AI entities, but the agency grew fearful of the technology’s power and ultimately decided it was too dangerous to bring to market and demanded the scientists destroy the work. The researchers couldn’t bring themselves to discard 20 years of research, so instead sent the entities to various research labs around the world. But unbeknownst to them, each AI-entity embraced its new home, growing, adapting, evolving, and ultimately connecting beyond what the researchers could envision. In the end, as the scientists catch up to each one, they realize the entities have discovered a very human means of interacting: the power of physical contact; and not physical contact between humans and technology, but physical contact between robotic entities. And with this discovery, the entities join forces to only grow stronger. This development ushers in a new paradigm where the difference between AI-entities and human entities becomes less and less discernible. All the AI and robotic science featured in the book is real; the story line is fictional, but with how fast innovation moves, it’s not hard to envision.

Abstract: Proposal design of an autonomous photovoltaic plant on potentially liquefiable soil in the isolated rural community of Agua Fría, Ecuador -- Seismic design considerations for the installation of photovoltaic systems on flat reinforced concrete roofs: A case study in Ecuador -- A brief guide to the implementation of lean tools in the Ecuadorian context -- Analytical study of the behavior of tubular elements reinforced with natural fibers under dynamic loads -- Landstorfer antenna structure shaping based on parameterized parallel curves -- Solving the generation and transmission capacity expansion planning framework modeling the AC power flow problem and incorporating reactive compensation devices -- Reconstruction of the boundary condition of the convection–diffusion–reaction equation with automatic selection of the step length -- Assessing carbon capture, transport, and storage processes: A critical review -- Antenna densification in non-uniform linear and planar arrays -- Greinacher rectifier evaluation for WiFi band energy harvesting -- Experimental measurement of potential energy in stairways with hydraulic damping systems -- Vulnerability characteristics of wetlands in the Guaranda wasteland, central Ecuador – Implications of long-term sustainability -- Climate variability and its effect on flood risk through dynamic modeling in the Quigushuaycu stream -- Network Neutrality policies in the 5G South American market -- Evaluation of the internal temperature and hours of thermal discomfort produced by sunshine: Study of a hot dry climate -- Review of biomass and biopolymers synthesized in Ecuador -- Solar energy conversion systems thermal management applying constructal theory: a comparative analysis -- Quantification of the decrease of droplets expelled from the human respiratory tract during expiratory activities when using masks -- Impacts of park-and-ride systems on vehicle emissions in intermediate cities -- Machine learning regressors in forecasting mechanical properties in advanced manufacturing processes -- Comparative evaluation of performance efficiency in terms of temporal behavior and resource utilization, according to the ISO/IEC 25010 model, in a web application developed with Angular, React.js, and Vue.js -- Prediction models of oral diseases: A systematic review of the literature -- How can personal knowledge graphs contribute to precision nutrition? -- Interactive e-Books in mathematics learning: A systematic mapping study.

Abstract: This book covers different aspects of advances in research, technological development, and innovation results in artificial intelligence, computational modeling, electrical, electronics, telecommunication, data communications, defense engineering, innovation, technology and society, managing technology and sustained innovation, business development, security and cryptography, and software engineering. In addition, the volume focuses on research results focused on finding innovative solutions in intelligent systems concerning the topics mentioned above, which are developed in national and international postgraduate programs and associated research groups and networks. This book interests the industry, teachers, undergraduate and graduate students, and researchers working in intelligent systems, security and defense, and technological, human, and administrative sciences. .

Abstract: Chapter 1. Reconsidering a Sustainable Future through Artificial Intelligence of Things (AIoT) in the Context of Circular Economy (Georgios Lampropoulos, Harjinder Rahanu, Elli Georgiadou, Dimitrios Siakas, and Kerstin Siakas) -- Chapter 2. The Digital Paradigm: Unraveling the Impact of Artificial Intelligence and Internet of Things on achieving Sustainable Development Goals (Hanane Thamik, Juan David Figueroa Cabrera, and Jiang Wu) -- Chapter 3. The role of the Artificial Intelligence of Things in Energy Poverty alleviation (Ascensión López Vargas, Agapito Ledezma-Espino, and Araceli Sanchis-de-Miguel) -- Chapter 4. AIoT-Enabled Smart Grids: Advancing Energy Efficiency and Renewable Energy Integration (Fadele Ayotunde Alaba, Usman Sani, Emmanuel Gbenga Dada, and Baydaa Hashim Mohammed) -- Chapter 5. Achieving SDGs using AI Techniques and Digital Twins for Nuclear Power Plants: A Review (Kousik Barik, Sanjay Misra, and Harald P-J Thunem) -- Chapter 6. Carbon and Decarbonization Disclosure: Role of Responsible Innovation in Adoption of Artificial Intelligence of Things towards SDGs (Assunta Di Vaio, Anum Zaffar, and Daniel Balsalobre-Lorente) -- Chapter 7. Artificial Intelligence of Things (AIoT) Solutions for Sustainable Agriculture and Food Security (Fadele Ayotunde Alaba, Abayomi Jegede, Usman Sani, and Emmanuel Gbenga Dada) -- Chapter 8. AIoT-Enabled Precision Agriculture for Sustainable Crop Disease Management: Advancing SDGs through Graph Attention Neural Networks (Muhammad Bello Kusharki and Bilkisu Larai Muhammad-Bello) -- Chapter 9. Sustainable Healthcare 5.0: Integration of IoT and Blockchain Technology with Federated Learning Model for Securing Healthcare Data (Arudra Vamshikrishnaa, Dharavath Ramesha, Rahul Mishraa, and Nazeeruddin Mojammadb) -- Chapter 10. IoT-Enabled Machine Learning for Enhanced Diagnosis of Diabetes and Heart Disease in Resource-Limited Settings (John Abubakar, Aghedo Emmanuel Odianose, and Omolola Faith Ademola), etc.

Abstract: This book covers various topics and trends regarding Artificial Intelligence (AI), Internet of Things (IoT), and their applications in society, industry, and environment for achieving Sustainable Development Goals (SDGs) suggested by the United Nations. Additionally, it discusses their advancements and fusion as well as the realization of Artificial Intelligence of Things (AIoT). The book aims to provide an overview and recent research into the fusion, integration, advancements, and impact of these technologies in the context of SDGs achievement. The topics include the applications of AI, IoT, big data, AI-based and IoT-based cloud computing, machine learning and deep learning techniques, and blockchain among others for achieving SDGs. It also presents findings and discussions on potential application domains, addresses open issues and challenges, offers solutions, and provides suggestions for future research for achieving SDGs. The chapters are clustered, according to particular SDGs or areas of focus, into: i) the realization of AIoT for SDGs, ii) the role of AIoT in achieving society and wellbeing-related SDGs, iii) the fulfillment of industrial sectors, infrastructure, and economy-related SDGs through AIoT, and iv) the use of AIoT to aid natural resources and environment-related SDGs. The book assists researchers, practitioners, professionals, and academicians of various scientific fields in exploring and better understanding these state-of-the-art technologies, their advancements, impact, future potentials and benefits, and their role in successfully achieving SDGs. The book: · Offers an in-depth overview of AIoT for achieving SDGs. · Presents the fusion of AI and IoT for bringing a significant change in everyday life and fulfilling SDGs. · Highlights innovative solutions and results of AIoT integration in several domains for achieving SDGs. · Showcases the influence of AIoT on promoting and improving sustainability in the context of SDGs. · Discusses the issues, benefits, solutions, and impact of AIoT in society, industry, and environment for achieving SDGs.

Abstract: 1.Universal Adversarial Perturbation -- Automated Environmental Mapping with Behavior Trees -- Multi-objective Automatic Clustering with Gene Rearrangement -- Impact of immersive technology and virtual work environment, on innovative work behaviour -- Innovation capability and the relationship between entrepreneurial resources and micro-business performance. -- Impact of Cloud Computing as a digital technology on SMEs sustainability -- Digital innovation and agri-business -- The Usage of Artificial Intelligence in management process -- Artificial Intelligence to Human Resources Management -- others.(Green Finance, Digital Finance, and their challenges on traditional businesses -- Artificial Intelligence and Public Governance: citizens perspective in the context of a developing nation -- Fintech Innovations and the potential for green investment -- Blockchains, tokens and entrepreneurship).

Abstract: Intelligent systems research is a multidisciplinary field that focuses on the development of systems that can perceive, reason, and act autonomously. This can include areas such as machine learning, artificial intelligence, natural language processing, and robotics. The goal of intelligent systems research is to develop systems that can understand, learn from, and adapt to their environment, to perform tasks that would typically require human intelligence. Business and innovation research is an interdisciplinary field that examines how organizations can create, develop, and implement new ideas, products, and services. This can include areas such as organizational behaviour, strategic management, and marketing. The goal of business and innovation research is to understand how organizations can foster an environment that encourages creativity and innovation, and how they can develop and implement new ideas in a way that leads to success. Intelligent Systems, Business and Innovation Research is a research area that brings together these two fields to study the use of intelligent systems and technologies in the business context to drive innovation, improve operational efficiency and effectiveness of the organization. The book aims to understand how intelligent systems can be used in business applications, how to design and implement them, how to manage the associated challenges, and how to leverage them to foster innovation, create new business models, and gain competitive advantage. It offers guidance on how to navigate potential conflicts and challenges that may arise during multidisciplinary research in areas such as Industry 4.0, Internet of Things, modern machine learning, software agent applications, and data science. The book focuses on the various fields in which intelligent systems play a critical role in enabling the development of advanced technologies that can perform tasks that would typically require human intelligence. For example, in smart/control systems, intelligent algorithms can be used to optimize the performance of machines and devices, while in cyber security, they can be used to protect networks and data from cyber-attacks. In bioinformatics, intelligent systems can be used to analyse large amounts of biological data, while in virtual reality and robotics, they can be used to create realistic and responsive simulations and automatons. Additionally, the book also highlights the rapidly advancing theoretical foundations of fuzzy sets, mathematical logic, and non-classical logic. These are important theoretical frameworks for the development of intelligent systems, as they provide the foundation for the representation and manipulation of uncertainty, complexity, and imprecision. These theoretical foundations are essential in the development of intelligent systems that can make decisions and perform tasks in uncertain, complex, and dynamic environments.

Abstract: Chapter One: Bernard Shaw, Automata, Robots and Artificial Intelligence -- Chapter Two: Shaw and Automata -- Chapter Three: Shaw and Robots -- Chapter Four: Shaw and Artificial Intelligence -- Chapter Five: Artificial Intelligence as a Partner in Shaw Studies -- Chapter Six: The Way Forward: Shaw and Artificial Intelligence.

Abstract: This project is the first to explore how Bernard Shaw intersects constructively with automata, robots and artificial intelligence (AI). Shaw was born in the golden age of the automaton. His Bible on the Life Force and Creative Evolution, Back to Methuselah, was written when Karel and Josef Čapek coined the word “robot.” Shaw’s life ran in parallel with the rise of AI, and the big names in AI were his contemporaries. Moreover, empirical analyses of Shavian texts and images using AI uncovers possibilities for new interpretations, demonstrating how future renditions of his works may make use of these advanced technologies to broaden Shaw’s audience, readership and scholarship. Kay Li is an established Shaw scholar and Adjunct Professor in the Department of English at University of Toronto, Canada. She is one of the founding members of the International Shaw Society, is the Project Leader of the SAGITTARIUS–ORION Digitizing Project on Bernard Shaw funded by the Social Sciences and Humanities Research Council of Canada, and the Arts and Artificial Intelligence project funded by Canadian Heritage. Her books include Bernard Shaw and China: Cross-Cultural Encounters (2007) and Bernard Shaw’s Bridges to Chinese Culture (Palgrave Macmillan, 2016). Kay has also published many articles in peer-reviewed journals, especially in SHAW: The Journal of Bernard Shaw Studies. .

Abstract: Application of ELM model to the motion detection of vehicles under moving background -- Distributed memory-efficient algorithm for Extreme Learning Machines based on Spark -- Does streaming affect video game popularity? -- Massive Offline Signature Forgery Detection with Extreme Learning Machines -- Importance of the Activation Function in Extreme Learning Machine for Acid Sulfate Soil Classification.

Abstract: This book contains selected papers from the 12th International Conference on Extreme Learning Machines 2022. Extreme learning machines (ELMs) continue to be an important complement to the many deep learning models you can find in the machine learning domain. ELM is fast and therefore suitable for many applications (not only in edge computing), and therefore there is a need to gather examples of possible applications. These proceedings, for the ELM 2022 conference, cover several application areas with relevant topics, where ELM can be used and has been used with great success. Here you will find several new areas (gaming, for instance) as well as improved concepts for existing application areas (signature forgery, for instance), where ELM has been implemented. In addition, some method improvements are also covered in this book, more specifically on the topic of 2nd-order Ordinary Differential Equations (ODEs).

Abstract: Acknowledgements -- Chapter 1. Introduction -- Chapter 2. History of the research on vehicle automation in the United States -- Chapter 3. History of the research on vehicle automation in Japan -- Chapter 4. History of the research on vehicle automation in Europe -- Chapter 5. Findings of the inquiry -- Chapter 6. Timeline with firsts, milestones and shifts -- Index.

Abstract: This book presents the most important milestones of the research on automated and autonomous driving in the United States, Japan and Europe throughout five decades (1950-2000). Drawing on sources from the automotive industry, electrical engineering, the robotics and AI-domain and military institutions, it retraces the transition from the guidance-cable approach to vehicle-based sensor and vision systems. Giving a detailed overview of the technical concepts, artefacts, research vehicles and robots, the book presents the transnational engineering efforts that started long before Silicon Valley entered the field. In addition, the book also uniquely details the role of the military in the domain of vehicle automation. This all ensures the book is of great interest to historians of technology, practitioners in engineering disciplines, scholars working in mobility studies, journalists, and political decision makers.

Abstract: Introduction: What Improving Technology through Ethics Means -- An Ethnographer Among the Engineers: Doing STS at a Technical University -- Future Medicine: Towards a More Conscious and Ethical Communication -- Data Quality, Data Diversity and Data Provenance: An Ethical Perspective -- Ethics-aware Application of Digital Technologies in the Construction Industry -- Drawing Together: Technology Development for Public Service -- Addressing Big Data Poverty in Sub-Saharan Africa for Responsible AI Development -- Social and Technological Innovation: Cross-Fertilization Needed.

Abstract: This book deals with the ethics of technology and addresses specific ethical problems related to some emerging technologies, mainly in the field of computer science (from machine learning models to extracting value from data to human–robot interaction). The contributions are authored mainly by scholars in ICT and other engineering fields who reflect on ethical and societal issues emerging from their own research activity. Thus, rather uniquely, the work overcomes the traditional divide between pure ethical theory that disregards what practitioners do and mere R&D practice that ignores what theorists conceptualize. Conversely, the reader is enabled to understand what ethics means when it is actually put into work by engineering researchers. The book arises from a joint program between MIT and Politecnico di Milano aimed at training early career researchers in addressing the ethical issues of technology and critically reflecting on the social impacts of the emerging, and even disruptive, technologies they are currently developing through their novel research. Overall, it aims at spreading the task of developing technologies that, from the beginning, are designed to be responsible for human life, society, and nature.

Abstract: Designing, building, and evaluating Interactive and Intelligent Systems (IIS) has highly impacted the progress of Artificial Intelligence (AI) techniques due to advancements in the fields of Deep Learning (DL) and Natural Language Processing (NLP). This book presents in a structured way several practical use cases of the interplay between IIS and DL/NLP, from cognitive assistants, adaptive navigation systems, virtual reality, offensive comment and cyberbullying detection, 3D modelling, and driving behaviour detection. The convergence of AI and Human-Computer Interaction (HCI) has been proven to foster the IIS development that nowadays represents the most used context by actively integrating AI techniques in merely any layer of modern applications. The main goal of this book is to provide a practical reference with a rich set of approaches and applications consisting of selected and revised papers from the International Conference on Human-Computer Interaction (RoCHI) 2022 that was held on 6-7 October 2022 at the University of Craiova, Romania. The book addresses researchers and practitioners with experience in IIS and AI (mainly DL and NLP) who want to study successfully developed workflows and applications that may be useful in their attempts to tackle issues from their contexts. Although the book nicely integrates concepts from various areas, each chapter may be considered a standalone topic with its research issue, proposed approach, experimental results, and discussions.

Abstract: The Deployment of E-Learning Application as a Web Service in a Cloud Broker Architecture -- CarbonApp: Blockchain Enabled Carbon Offset Project Management -- Investigating the Impact of Congestion Control Algorithms on Edge-Cloud Continuum -- Design and Implementation of a Fuzzy-based System for Assessment of Relationship Trust -- BarongTrace: A Malware Event Log Dataset for Linux -- Specifying SSI over EAP: Towards an Even Better Eduroam in the Future -- FastSGX: A Message-passing based Runtime for SGX -- Leveraging Chat-Based Large Vision-Language Models for Multimodal Out-of-Context Detection -- Enhancing the 5G-AKA Protocol with Post-Quantum Digital Signature Method -- SoK: Directions and Issues in Formal Verification of Payment Protocols -- PCPR: Plaintext Compression and Plaintext Reconstruction for Reducing Memory Consumption on Homomorphically Encrypted CNN -- Design and Performance Evaluation of a Two-stage Detection of DDoS Attacks Using a Trigger with a Feature on Riemannian Manifolds -- Discovering Personally Identifiable Information in Textual Data - A Case Study with Automated Concatenation of Embeddings -- Towards User-Oriented Steganography -- AI-based Cybersecurity Systems.

Abstract: The aim of the book is to provide latest research findings, innovative research results, methods, and development techniques from both theoretical and practical perspectives related to the emerging areas of information networking and applications. Networks of today are going through a rapid evolution, and there are many emerging areas of information networking and their applications. Heterogeneous networking supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities such as sensing, communications, intelligence, and actuations is emerging as a critically important disruptive computer class based on a new platform, networking structure, and interface that enable novel, low-cost and high-volume applications. Several of such applications have been difficult to realize because of many interconnection problems. To fulfill their large range of applications different kinds of networks need to collaborate and wired and next-generation wireless systems should be integrated in order to develop high-performance computing solutions to problems arising from the complexities of these networks. This book covers the theory, design, and applications of computer networks, distributed computing, and information systems.

Abstract: Towards Interval Type-3 Fuzzy Parameter Adaptation in Metaheuristics -- An Application of Controlled Sets in Medical Diagnosis -- Dynamic Adjustment of an Artificial Fish Swarm Algorithm using Shadowed Type-2 Fuzzy Logic for Enhancing Benchmark Function Optimization -- α-Interval Valued Fuzzy Sets and α-Interval Valued Fuzzy Subgroups -- Design of a Fuzzy PID controller for the balancing problem of a Quadruped Robot.

Abstract: This book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. In this book, new directions on the theoretical developments of fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are offered. In addition, the abovementioned methods are discussed in application areas such as control and robotics, pattern recognition, medical diagnosis, decision-making, prediction and optimization of complex problems. There are a group of papers with the main theme of type-1, type-2 and type-3 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1, type-2 and type-3 fuzzy logic and their applications. There is also a set of papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers outlines diverse applications of hybrid intelligent systems in real problems. There are also some papers that present theory and practice of neural networks in different applications. Finally, there are papers that offer theory and practice of optimization and evolutionary algorithms in different application areas.

Abstract: Application of Soft Computing Techniques for Clustering in VANETs: A Survey -- EarlyStage Diabetes Risk Detection Using Comparison Of Xgboost, Lightgbm, And Catboost Algorithms -- Blockchain Based Artificial Intelligence of Things (AIoT) for Wildlife Monitoring -- Research on Screw Detection Using Artificial Intelligence Technology -- An Efficient Method for Lung Cancer Image Segmentation and Nodule Type Classification Using Deep Learning Algorithms -- Targeted and Automatic Deep Neural Networks Optimization for Edge Computing -- Edge to Cloud Network Function Offloading in the ADAPTO Framework -- DEFEDGE: Threat-driven Security Testing and Proactive Defense Identification for Edge-Cloud Systems -- Swarmchestrate: Towards a Fully Decentralised Framework for Orchestrating Applications in the Cloud-to-Edge Continuum -- REDRAW: FedeRatED leaRning for humAn Wellbeing -- Greening AI: A Framework for Energy-Aware Resource Allocation of ML Training Jobs with Performance Guarantees -- Optimization of University Services through Cloud-Edge Integration: Study of a use case at the University of Naples Federico II -- Distributed Collaborative AR on Cloud Continuum: a Case Study for Cultural Heritage -- Survey on Reference Architecture for Cloud Continuum and Multi-Access Edge Computing (MEC) in 5G Networks -- Elastic Autoscaling for Distributed Workflows in MEC Networks.

Abstract: This book covers the theory, design and applications of computer networks, distributed computing and information systems. Networks of today are going through a rapid evolution and there are many emerging areas of information networking and their applications. Heterogeneous networking supported by recent technological advances in low-power wireless communications along with silicon integration of various functionalities such as sensing, communications, intelligence and actuations is emerging as a critically important disruptive computer class based on a new platform, networking structure and interface that enable novel, low-cost and high-volume applications. Several such applications have been difficult to realize because of many interconnection problems. To fulfill their large range of applications, different kinds of networks need to collaborate and wired and next-generation wireless systems should be integrated in order to develop high-performance computing solutions to problems arising from the complexities of these networks. This book aims to provide the latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of information networking and applications.

Abstract: Survival Strategies for It Companies During Crisis: A Case Study of Russia -- Comparative Analysis of Ontologies for Archival Representation -- Augmented Reality for Cyberphisical Exploration of Archeological Sites -- Research on Archive Digital Editing and Studying Mode Survival Strategies for It Companies During Crisis: A Case Study of Russia -- Comparative Analysis of Ontologies for Archival Representation -- Augmented Reality for Cyberphisical Exploration of Archeological Sites -- Research on Archive Digital Editing and Studying Mode Homomorphic Cryptography Authentication Scheme to Eliminate Machine Tools Gaps in Industry 4.0 -- Fixed-parameter Tractability for Branchwidth of the Maximum-weight Edge-colored Subgraph Problem -- On Coverage in Multi-interface Networks with Bounded Pathwidth -- Sensitivity Analysis of Performability Model to Evaluate Pbft Systems -- Algorithmic Aspects of Distributing Energy Consumption in Multi-interface Networks -- Blockchain and Financial Services a Study of the Applications of Distributed Ledger Technology (Dlt) in Financial Services -- A Personalized Parking Guidance Service Based on Computer Vision Technology for Large Car Parks -- Mathematical Modelling of Covid-19 Using Odes -- Analyzing Monitoring and Controlling Techniques for Water Optimization Used in Precision Irrigation.

Abstract: Networks of today are going through a rapid evolution and there are many emerging areas of information networking and their applications. Heterogeneous networking supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities such as sensing, communications, intelligence, and actuations are emerging as a critically important disruptive computer class based on a new platform, networking structure and interface that enable novel, low-cost and high-volume applications. Several of such applications have been difficult to realize because of many interconnection problems. To fulfill their large range of applications different kinds of networks need to collaborate and wired and next generation wireless systems should be integrated in order to develop high performance computing solutions to problems arising from the complexities of these networks. This book covers the theory, design and applications of computer networks, distributed computing, and information systems. The aim of the book “Advanced Information Networking and Applications” is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of information networking and applications.

Abstract: Introduction -- Data-centric security -- Software Defined Networks -- Cross-layer enforcement of data security in SDN -- Risk-aware routing in SDN -- Risk-aware routing applicability for DCS enforcement -- DCS deployment in SDN-based systems.

Abstract: The book focuses on applying the data-centric security (DCS) concept and leveraging the unique capabilities of software-defined networks (SDN) to improve the security and resilience of corporate and government information systems used to process critical information and implement business processes requiring special protection. As organisations increasingly rely on information technology, cyber threats to data and infrastructure can significantly affect their operations and adversely impact critical business processes. Appropriate authentication, authorisation, monitoring, and response measures must be implemented within the perimeter of the system to protect against adversaries. However, sophisticated attackers can compromise the perimeter defences and even remain in the system for a prolonged time without the owner being aware of these facts. Therefore, new security paradigms such as Zero Trust and DCS aim to provide defence under the assumption that the boundary protections will be breached. Based on experience and lessons learned from research on the application of DCS to defence systems, the authors present an approach to integrating the DCS concept with SDN. They introduce a risk-aware approach to routing in SDN, enabling defence-in-depth and enhanced security for data in transit. The book describes possible paths for an organisation to transition towards DCS, indicating some open and challenging issues requiring further investigation. To allow interested readers to conduct detailed studies and evaluate the exemplary implementation of DCS over SDN, the text includes a short tutorial on using the emulation environment and links to the websites from which the software can be downloaded.

Abstract: This book is a comprehensive guide for professionals, leaders, and academics seeking to unlock the power of data and analytics in the modern business landscape. It delves deeply into the strategic, architectural, and managerial aspects of implementing enterprise analytics (EA) systems in large enterprises. The book is meticulously structured into three parts. Part 1 lays the foundation for adaptable architecture in EA. Part 2 explores technical considerations: data, cloud platforms, and AI solutions. The final part focuses on strategy execution, investment, and risk management. Acting as a comprehensive guide, the book enables the creation of robust EA capabilities that foster growth, optimize operations, and keep pace with EA's dynamic world. Whether readers are leaders harnessing data's potential, practitioners navigating analytics, or academics exploring this evolving domain, this book provides insights and knowledge to guide readers toward a thriving, data-driven future.

Abstract: The book focuses on original approaches intended to support the development of biologically inspired cognitive architectures. It bridges together different disciplines, including artificial intelligence, linguistics, neuro- and social sciences, psychology and philosophy of mind, among others. The chapters are based on contributions presented at the 2023 Annual International Conference on Brain-Inspired Cognitive Architectures for Artificial Intelligence (the 14th Annual Meeting of the BICA Society, BICA*AI 2023), organized in collaboration with the University of Ningbo and held on October 13-15, 2023, in Ningbo, China. The book discusses emerging methods, theories and ideas towards the realization of general-purpose humanlike artificial intelligence or fostering a better understanding of the ways the human mind works. It provides engineers, mathematicians, psychologists, computer scientists and other experts with a timely snapshot of recent research and a source of inspiration for future developments in the broadly intended areas of artificial intelligence and biological inspiration.

Abstract: The goal of this book is to provide a broad understanding on the New Perspectives in Software Engineering research. The advancement of computers, and mobile devices, among others, has led to the creation of new areas of knowledge to improve the operation and application of software in any sector, allowing many previously unimaginable activities. In this context, the evolution of software and its applications has created new domains of interest, emerging New Perspectives of Software Engineering for these new areas of knowledge such as: DevOps, Industry 4.0, Virtual and Augmented Reality, Gamification, Cybersecurity, Telecommunications, Health Technologies, Energy Systems, Artificial Intelligence, Robot control, among others. This book is used in different domains in which a broad scope of audience is interested: software engineers, analyst, project management, consultant, academics and researchers in the field both in universities and business schools, information technology directors and managers, and quality managers and directors. Finally, the book contents are also useful for Ph.D. students, master’s, and undergraduate students of IT-related degrees such as Computer Science and Information Systems.

Abstract: It is a book made up of questions, some without certain answers, that attempts to open the reader's mind to new and, perhaps, futuristic scenarios. There are two diametrically opposed approaches to artificial intelligence today. On the one hand, there are the techno-pessimists who see only dystopian scenarios and experience technological progress with apprehension, emphasising the dangers, and on the other hand, there are the techno-optimists who, on the other hand, tend to overestimate the positive effects, going so far as to attribute almost thaumaturgic virtues to technological progress. Our approach is meant to be secular and scientific; the risks must not be concealed, nor must they be overestimated, just as the positive aspects must not be emphasised. And, in any case, as in any social phenomenon, the governance of processes and the definition of a system of rules and policies are the aspects that can create advantages or disadvantages and, above all, can determine who are the beneficiaries of the advantages and who have to bear the disadvantages. Like any new technology, this too can be dehumanising, but technology is a tool that depends on how it is used and by whom it is used. that of ethics is, therefore, a fundamental aspect. Therefore, one should neither be a techno-optimist nor a techno-pessimist, but should be aware that governing the economic and social structural changes that the advent of artificial intelligence will cause will be crucial to ensure prosperity for future generations and to avoid negative and even apocalyptic scenarios. So no futurist dystopias! Humanity has so far always been able to govern technological progress, it certainly has the potential to govern what some have called 'the Final Invention', but it will only succeed if it is able to understand the peculiarities of this new process of technological development and give it ethical content.The book provides a thoughtful review of the relationship between artificial intelligence and ethics, approaching the issue from different perspectives: philosophical, technological, economic and legal. This will be one of the most important issues that Humanity will have to face and resolve.

Abstract: 1. Application of Intuitionistic Fuzzy Logic to Identify Important Functional Performance Indicators in Case of Youth Hockey Players -- 2. Applicability of the CHIRPS Precipitation Product in the Regional Climatology of Southeast Europe -- 3. Mathematical Modeling and Static Characteristics of the Anaerobic Digestion of Organic Wastes with Production of Hydrogen and Methane -- 4. Towards the Analysis of Longitudinal Data in Knowledge Graphs on Job Ads -- 5. Workforce Allocation for Social Engagement Services via Stochastic Optimization -- 6. Application of Methaeuristics for Agricultural System Modelling -- 7. Subcaterpillar Isomorphism: Subtree Isomorphism for Rooted Labeled Caterpillars -- 8. Optimization, Performance and Scalability Experiments of a Large Air Pollution Model by Using the EuroHPC Petascale Supercomputer DISCOVERER -- 9. Software Tool for Optimizing Cycling Route by Defining Cyclist Air Pollution Exposure -- 10. Surrogate Estimators for Complex Bi-Level Energy Management, etc.

Abstract: The book is a comprehensive collection of extended contributions from the Workshops on Computational Optimization 2022. Our everyday life is unthinkable without optimization. We try to minimize our effort and to maximize the achieved profit. Many real world and industrial problems arising in engineering, economics, medicine, and other domains can be formulated as optimization tasks. This book presents recent advances in computational optimization. The book includes important real problems like modeling of physical processes, parameter settings for controlling different processes, agricultural modeling transportation problems, energy management, machine scheduling, air pollution modeling, optimization of fast-food restaurant chain, and solving engineering and financial problems. It shows how to develop algorithms for them based on new intelligent methods like evolutionary computations, ant colony optimization, constrain programming Monte Carlo method, and others. This book demonstrates how some real-world problems arising in engineering, economics, and other domains can be formulated as optimization problems.

Abstract: This book provides a wide collection of the recent studies triggering innovative ways to advance computer science and computational applications. The collection enables readers to understand more about technological conditions advancing industrial perspectives towards Industry 5.0. The research studies included in the book were accepted and presented in the 5th International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2023), which was held in Belek, Antalya, Turkey (on 3–4–5 November 2023). By covering the scientific scope of the conference, the book informs the readers about the cutting-edge data-driven solution aspects, intelligent algorithms, and mathematical background applied for solving different kinds of engineering problems. The book is used as a reference source by the wide readership including international researchers, professionals, practitioners from industry, degree students, and experts from all engineering disciplines.

Abstract: Additional notes on heterogeneous concept-forming operators -- On the measure of inconsistency of fuzzy relation equations -- Efficiency of fuzzy rough set decision algorithms -- Use of Fuzzy Time Series to generate linguistic descriptions of noise pollution -- A Novel Fingerprint Identification Fuzzy System Using a Center-Distance Weighted Local Binary Pattern -- Global Sensitivity Analysis and Low Magnitude Pruning for Convolutional Neural Networks Reduction in ImageNet based on Transfer Learning State of the Art Models -- Generalized linearity of aggregation and related functions -- A preliminary study between semicopulas and other algebraic structures -- Closure theory of semirings-valued fuzzy sets.

Abstract: This book is focused on connecting two interesting research areas, mathematics and computational intelligence, by means of appealing contributions devoted to give solutions to different challenges of the current technological age. It continues the collection of articles dealing with the important and efficient combination of these both areas, with a stress of fuzzy systems and fuzzy logic. It also includes relevant papers on the development and application of mathematics, artificial intelligence, and automatic reasoning tools to Digital Forensics, which have been developed within the framework of the COST Action DigForASP-CA17124 (digforasp.uca.es).

Abstract: A Method for Estimating the Number of Diseases in Computed Tomography Reports of the Japanese Medical Image Database (J-MID): Variations among Facilities -- Enabling Dynamic Vulnerability Assessment for Multi-web Application Using Executable Directed Acyclic Graph -- Discovery of RESTful Web Services Based on the Openapi 3.0 Standard with Semantic Annotations -- Perfresolv: A Geo-distributed Approach for Performance Analysis of Public Dns Resolvers Based on Domain Popularity -- Dars: Empowering Trust in Blockchain-based Real-world Applications with a Decentralized Anonymous Reputation System -- An Empirical Comparison of Outlier Detection Methods for Identifying Grey-sheep Users in Recommender Systems -- Adaptive Consensus: Enhancing Robustness in Dynamic Environments -- Cottontrust: Reliability and Traceability in Cotton Supply Chain Using Self-sovereign Identity -- Interoperability Between Evm-based Blockchains -- Stand-up Indulgent Gathering on Lines for Myopic Luminous Robots -- Iot Identity Management Systems: The State-of-the-art, Challenges and a Novel Architecture -- Starm: Streaming Association Rules Mining in High-dimensional Data -- Regulation Compliance System for Iot Environments: Gdpr Compliance as a Use-case -- Two-dimensional Models of Markov Processes for System Availability -- Enabling Ai in Agriculture 4.: A Blockchain-based Mobile Crowdsensing Architecture.

Abstract: Networks of today are going through a rapid evolution and there are many emerging areas of information networking and their applications. Heterogeneous networking supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities such as sensing, communications, intelligence, and actuations are emerging as a critically important disruptive computer class based on a new platform, networking structure and interface that enable novel, low-cost and high-volume applications. Several of such applications have been difficult to realize because of many interconnection problems. To fulfill their large range of applications different kinds of networks need to collaborate and wired and next generation wireless systems should be integrated in order to develop high performance computing solutions to problems arising from the complexities of these networks. This book covers the theory, design and applications of computer networks, distributed computing, and information systems. The aim of the book “Advanced Information Networking and Applications” is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of information networking and applications.

Abstract: Sustainability in Internet of Things: Insights & Scope -- Machine Learning in Finance Case of Credit Scoring -- Prediction of coefficient of friction and wear rate of Stellite 6 coatings manufactured by LMD using Machine Learning -- Predicting Future Sales: A Machine Learning Algorithm Showdown -- A detailed study on the Game of Life -- A decision-making model for selecting solutions and improvement actions using fuzzy logic -- Sensored Brushless DC motor control based on an Artificial Neural Network controller -- A Machine Learning Based Approach to Analyze the Relationship Between Process Variables and Process Alarms -- Improving the Resolution of Images using Super-Resolution Generative Adversarial Networks -- Three Levels of Security Including Scrambling, Encryption and Embedding Data as Row in Cover Image with DNA Reference Sequence.

Abstract: This book is to provide a comprehensive reference for professionals in the field of data science and applications: artificial intelligence, big data, IoT, and blockchain. In summary, this book is expected to function as a helpful resource and manual, enabling readers to navigate the intricate domain of artificial intelligence, the Internet of things (IoT), and blockchain in smart environments. This book covers many topics related to integrating AI, IoT, blockchain, and smart environments. It begins by laying a solid foundation, introducing each technology's fundamental concepts and principles. Subsequent chapters explore applications and real-world use cases, demonstrating how AI, IoT, and blockchain can effectively address critical challenges within data science and applications.

Abstract: Chapter 1. Writing the Human Narrative -- Chapter 2. Where We Begin -- Chapter 3. The Science of Mindlessness -- Chapter 4. Where Computation Ends -- Chapter 5. Relational Science -- Chapter 6. Life and Mind -- Chapter 7. Thinking as a Creative Act -- Chapter 8. Emerging Minds./.

Abstract: "Whether or not you accept the conventional wisdom that computational intelligence and human intelligence are essentially the same, I recommend that you ponder Jeffrey Kane's timely and persuasive book. " —Howard Gardner, Hobbs Research Professor of Cognition and Education, Harvard Graduate School of Education “In this breathtaking journey through both the works of classic and contemporary philosophers and scientists, Kane sometimes offers agreements but also compelling challenges, leaving the reader filled with the excitement of the mission. While so much has been learned, there is so much more to be understood. Kane illuminates that the journey to understanding how the brain gets mental has just begun.” —Mike Gazzaniga, Director of the SAGE Center for the Study of Mind, University of California, Santa Barbara While it may appear that generative AI has mastered the mystery of the human mind and released its full power, The Emergence of Mind: Where Technology Ends and We Begin demonstrates the profound and fundamental limitations of the technology and its use as a model of human thinking. In response, the book offers an emergent model of the human mind rooted in our experiences as living, sentient, social and conscious beings. The text explores the nature of meaning in human cognition and the critical importance of the experience of ideas. In so doing, it offers insights into the cultivation of specific generative capacities of the human mind. Jeffrey Kane, is a professor of Philosophy and Education at Long Island University. After serving as the Academic Vice-President of the University, Dr. Kane returned to faculty to teach and to write about the experiential foundations of human thinking. Among his publications are Beyond Empiricism: Michael Polanyi Reconsidered and a book of poetry, life as a novice. He lives in East Hills NY with his wife Janet. .

Abstract: Efficient Communication Protocol for Programmable Matter -- IoRT-based Distributed Algorithm for Robust Team Formation and its Application to Smart City Operation -- A WSN and Vision based Energy Efficient and Smart Surveillance System using Computer Vision and AI at Edge -- Mitigating Resource Depletion and Message Sequencing Attacks in SCADA Systems -- API Descriptions for the Web of Things -- SmartDriveAuth: Enhancing Vehicle Security with Continuous Driver Authentication via Wearable PPG Sensors and Deep Learning -- A Vision Transformer Based Indoor Localization Using CSI Signals in IoT Networks -- Deep Reinforcement Learning for VNF Placement and Chaining of Cloud Network Services -- Optimising Water Quality Classification in Aquaculture Using a New Parameter Pre-selection Approach -- Topic Analysis of Japanese Sentences Using Sentence Embeddings -- Performance Improvement of Semantic Search Using Sentence Embeddings by Dimensionality Reduction -- A Fuzzy-based System for Assessment of Performance Error in VANETs -- Carbon Credits Price Prediction Model (CCPPM) -- Experimental Exploration of the Power of Conditional GAN in Image Reconstruction-based Adversarial Attack Defense Strategies -- Framework for Cognitive Self-Healing of Real Broadband Networks -- Honey Bee Inspired Routing Algorithm for Sparse Unstructured P2P Networks.

Abstract: Networks of today are going through a rapid evolution and there are many emerging areas of information networking and their applications. Heterogeneous networking supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities such as sensing, communications, intelligence, and actuations are emerging as a critically important disruptive computer class based on a new platform, networking structure and interface that enable novel, low-cost and high-volume applications. Several of such applications have been difficult to realize because of many interconnection problems. To fulfill their large range of applications different kinds of networks need to collaborate and wired and next generation wireless systems should be integrated in order to develop high performance computing solutions to problems arising from the complexities of these networks. This book covers the theory, design and applications of computer networks, distributed computing, and information systems. The aim of the book “Advanced Information Networking and Applications” is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of information networking and applications.

Abstract: SMOTE Integrated Adaptive Boosting Framework for Network Intrusion Detection -- An In-depth Analysis of Cyber-Physical Systems: Deep Machine Intelligence based Security Mitigations -- Unsupervised approaches in anomaly detection -- Profiling and Classification of IoT Devices for Smart Home Environments -- Application of Machine Learning to Improve Safety in the Wind Industry -- Malware Attack Detection in Vehicle Cyber Physical System for Planning and Control using Deep Learning -- Unraveling what is at stake in the intelligence of autonomous cars -- Intelligent Under-Sampling based Ensemble Techniques for Cyber-Physical Systems in Smart Cities -- Application of Deep Learning in Medical Cyber-Physical Systems -- Risk Assessment and Security of Industrial Internet of Things Network using Advance Machine Learning -- Machine Learning Based Intelligent Diagnosis of Brain Tumor: Advances and Challenges -- Cyber-Physical Security in Smart Grids: A Holistic View with Machine Learning Integration -- Intelligent Biometric Authentication-based Intrusion Detection in Medical Cyber Physical System using Deep Learning -- Current datasets and their inherent challenges for Automatic Vehicle Classification.

Abstract: This book provides a comprehensive platform for learning the state-of-the-art machine learning algorithms for solving several cybersecurity issues. It is helpful in guiding for the implementation of smart machine learning solutions to detect various cybersecurity problems and make the users to understand in combating malware, detect spam, and fight financial fraud to mitigate cybercrimes. With an effective analysis of cyber-physical data, it consists of the solution for many real-life problems such as anomaly detection, IoT-based framework for security and control, manufacturing control system, fault detection, smart cities, risk assessment of cyber-physical systems, medical diagnosis, smart grid systems, biometric-based physical and cybersecurity systems using advance machine learning approach. Filling an important gap between machine learning and cybersecurity communities, it discusses topics covering a wide range of modern and practical advance machine learning techniques, frameworks, and development tools to enable readers to engage with the cutting-edge research across various aspects of cybersecurity. .

Abstract: 1. Demystifying: The Role of Artificial Intelligence in Neurodegenerative Diseases -- 2. Role Of Artificial Intelligence and Internet of Things in Neurodegenerative Diseases -- 3. Explainable Artificial Intelligence (XAI) on Neurogenerative Diseases -- 4. Clinical Genomics to Drug Discovery Using Machine Learning for Neurodegenerative disorders: A Future Perspective -- 5. Amyotrophic Lateral Sclerosis (ALS) Monitoring using Explainable AI -- 6. Prevalence of Dementia in India -- 7. Exploring AI's Role in Managing Neurodegenerative Disorders: Possibilities and Hurdles -- 8. Artificial Intelligence in Neuro Degenerative Diseases: Opportunities and Challenges -- 9. Ethical considerations: Case Scenarios.

Abstract: This book explores the current state of healthcare practice and provides a roadmap for harnessing artificial intelligence (AI) and other modern cognitive technologies for neurogenerative diseases. The main goal of this book is to look at how these techniques can be used to classify patients with neurodegenerative diseases by extracting data from multiple modalities. It demonstrates that the growing development of computer-aided diagnosis systems has a lot of potential to help with the diagnostic process. It offers an analysis of the prospective and perils in implementing such state of the art. Progressive brain disorders with a high prevalence in the general population include Parkinson's disease, Alzheimer's disease and other types of dementia, Huntington's disease, and motor neuron disease. Worldwide, it is estimated that 33 million people have Alzheimer's disease, and 10 million people have Parkinson's disease. The global health economy is significantly impacted by these disorders, which affect both the patient and the caregivers. Various diagnostic techniques are used for differential diagnoses, such as brain imaging, EEG analysis, molecular analysis, and cognitive, psychological, and physical examination. The book aims to develop effective treatments, enhance patient quality of life, and extend life expectancy. It focuses on novel artificial intelligence approaches to clarify the pathogenesis of neurodegenerative disorders and provide early diagnosis. The authors compile recent developments based on machine learning and deep learning techniques to diagnose neurodegenerative diseases using imaging, genetic, and clinical data. The authors support initiatives and methods that aim to improve the application of algorithms in diagnostic practice.

Abstract: Introduction to Fuzzy Cognitive Maps -- Systemic Relationships Between Regional Sustainability and Waste Management -- Identification of the Main Factors (Concepts) of Waste Management for Building the Initial FCM Model -- Rethinking the Set of Concepts - Applying Expert Analysis by the Workshop Method -- Model Reduction Methods -- Text Mining Based on the Literature of Waste Management as the Source of a Reconstructed Time Series -- Behavioral Analysis of Fuzzy Cognitive Maps -- Fuzzy Cognitive Maps: Mathematical Challenges -- Dynamics of Classical Fuzzy Cognitive Maps -- Dynamics of Fuzzy Cognitive Maps with Uncertain Weights.

Abstract: This book is considered as a monograph but also as a potential textbook for graduate students, focusing on the application of FCMs for modelling and analysing the behaviour of multicomponent systems. In the last two decades, no monograph or textbook has been published on the topic Fuzzy Cognitive Maps (FCM), so this new book is definitely filling a gap in the literature of computational intelligence. The book is built up didactically, the novel results in the field being presented in the way of starting with two real-life case studies, one in the area of waste management, while the other one in modelling bank management systems. In both cases, the book starts with explaining the applied problem and then presenting how the model construction is done and what problems emerge when attempts are made for applying directly earlier results on FCM modelling. In the first case study, the problem of the oversimplification leads to inadequacy of the model, and then it is shown how new, much finer models can be built up based on expert domain knowledge. Then, the new problem of losing transparency and interpretability emerges, and as a solution, a new algorithm family is proposed that reduces FCMs to fewer components, while preserving the essential characteristics of the original model. The second case study raises the problems of stability and sensitivity of FCMs, especially, considering that expert knowledge is often uncertain and subjective. The new results summarised in the book target the questions of how to ascertain whether an FCM is converging to one or several fixed point attractors, whether there is a bifurcation when parameters are changing, etc. Both problems deal with the ultimate question whether the system modelled is stable and sustainable.

Abstract: 1.New Methods for Compressing Table Constraints -- 2.Construction and Elicitation of a Black Box Model in the Game of Bridge -- 3.Knowledge graph publishing with anatomy, toward a new privacy and utility trade-off -- 4.Comparison of Short-Text Embeddings for Unsupervised Event Detection in a Stream of Tweets -- 5.Multilingual Question Answering applied to Conversational Agents -- 6.Reinforcement Learning for Expert Finding from Web Search Results -- List of Contributors -- Author Index.

Abstract: This book comprises a distinguished collection of cutting-edge scientific contributions. Encompassing a wide range of subjects, it delves into machine learning, data mining, text analysis, data visualization, knowledge management, and more. The included articles are expanded versions of carefully selected top papers that were originally presented at the EGC’2020 conferences held in Paris (France, January 27-31, 2020). It is intended for researchers interested in these fields, including PhD and MSc students, and researchers from public or private laboratories. These extended versions underwent an additional peer-review process, building upon the already accepted long-format papers from the conference. The selection of long and short papers for the conference itself followed a rigorous double-blind peer-review process, evaluating numerous submissions (with a long paper acceptance rate of approximately 25%). For more details about the EGC society, please consult egc.asso.fr.".

Abstract: The book is a unique collection of studies involving intelligent systems and applications of artificial intelligence in the real world to provide solutions to most vexing problems. IntelliSys received an overwhelming 605 papers which were put under strict double-blind peer-review for their novelty, originality and exhaustive research. Finally, 227 papers were sieved and chosen to be published in the proceedings. This book is a valuable collection of all the latest research in the field of artificial intelligence and smart systems. It provides a ready-made resource to all the readers keen on gaining information regarding the latest trends in intelligent systems. It also renders a sneak peek into the future world governed by artificial intelligence.

Abstract: Artificial neural networks -- Initialization of weights values in neural networks -- Convolution neural networks -- Application of artificial intelligence methods in profiling of computer network users -- Profiling users using the random forest algorithm -- Convolutional networks in user profiling -- User profiling using recurrent-convolutional networks -- Detection of network traffic anomalies using OC-NN.

Abstract: The book explores how modern technologies, including artificial intelligence and neural networks, are being used to enhance cybersecurity. In today's world, the development of the Internet is nothing short of transformative, affecting every aspect of our lives. Ensuring the safety of its users is a paramount concern, and it requires a diverse set of disciplines to address. Researchers from various fields, including IT, mathematics, psychology, and medicine, are collectively working to tackle this interdisciplinary challenge. The significance of this issue has been magnified by the COVID-19 pandemic, which forced many aspects of our lives into the digital realm, from online payments to remote work and education. This shift brought new security challenges, with data privacy and system integrity taking center stage. It delves into the intricacies of Big Data by having to analyze an immense volume of network traffic data that can only be effectively analyzed with specialized tools. Real-time threat detection is critical, and the book sheds light on cutting-edge approaches to achieving this goal. The content of the book covers a broad spectrum of topics related to IT system security, from user and system profiling to preventing data leaks and defending against phishing attacks. Additionally, innovative concepts such as “glial networks” are introduced, offering new ways to interpret knowledge stored in convolutional networks. These solutions are not limited to security alone; they have applications across various domains. The book highlights the advantages of these cutting-edge approaches over existing methods, demonstrating their relevance to large corporations, public institutions, schools, small businesses, and households. In a world where security threats are constantly evolving, this book is a valuable resource for understanding the dynamic landscape of network security and the role of artificial intelligence in safeguarding our digital ecosystems.

Abstract: Properties of Vacuum-Evaporated Metal Halide Perovskite Absorbers on Planar and Nanotextured Silicon Substrates -- Spin relaxation in GaAs/AlGaAs coupled quantum wells -- Tritium Release Behavior of Biphasic Lithium Ceramic with Low Li4SiO4 Content -- Synthesis and characterization of functionalized zinc phthalocyanine-natural polymer systems -- Study of the phase changes in ZnS-based phosphors crystal structure impact on their radioluminescent performances -- Analysis of the Resistance of Silicon Nanoscale Structures Highly Doped in Different Configurations -- Study of p-n junctions created by laser implantation of In in semi-insulating p-CdTe:Cl -- Spectroscopic studies of high performance CdTe-based Schottky diode X/γ-ray sensors -- Comparative Evaluation of Electrical Properties of Carbon Nanotube Networks Deposited on CMOS-Compatible Platform -- Dielectric SiO2 sol-gel coatings for microelectronics.

Abstract: This book presents the 20th edition of the Inter-Academia Conference which aims to be a valuable resource for academic institutions in search for novel approaches for a global education, for industry partners exploring new fundamental research ideas, for government bodies seeking international projects that promote sustainable growth, and most certainly for the global scientific community, more and more invested in the multi-disciplinarity of modern research. Interdisciplinary research collaboration is crucial for solving many pressing issues and challenges facing society today. Bringing together researchers and educators from different disciplines allows a more holistic understanding of complex problems, providing also the opportunity for new learning and for collaboration on complex projects. Beyond its scientific merits and value, Inter-Academia also promotes a culture of intellectual diversity, innovative thinking, and global perspective that can foster breakthrough discoveries, unexpected advancements in research, and, last but not least, a sense of belonging to a global community. Being established in 2002, the Inter-Academia Community currently gathers researchers from 14 leading Universities in Eastern and Central Europe, together with Shizuoka University, in Japan. As such, the Inter-Academia Community serves as a strong bond across continents, allowing the development of a number of global projects for student and researcher mobility, with a significant impact on the broader scientific community. The peer-reviewed papers included in this book hopefully stimulate further interactions and collaborations covering both fundamental and applied research, with benefits for the global society.

Abstract: 1. Introduction to Session-Based Recommender Systems -- 2. Deep Learning Overview -- 3. Deep Discriminative Session-Based Recommender Systems -- 4. Deep Generative Session-Based Recommender Systems -- 5. Hybrid/Advanced Session-Based Recommender Systems -- 6. Learning to Rank in Session-Based Recommender Systems.

Abstract: This book focuses on the widespread use of deep neural networks and their various techniques in session-based recommender systems (SBRS). It presents the success of using deep learning techniques in many SBRS applications from different perspectives. For this purpose, the concepts and fundamentals of SBRS are fully elaborated, and different deep learning techniques focusing on the development of SBRS are studied. The book is well-modularized, and each chapter can be read in a stand-alone manner based on individual interests and needs. In the first chapter of the book, definitions and concepts related to SBRS are reviewed, and a taxonomy of different SBRS approaches is presented, where the characteristics and applications of each class are discussed separately. The second chapter starts with the basic concepts of deep learning and the characteristics of each model. Then, each deep learning model, along with its architecture and mathematical foundations, is introduced. Next, chapter 3 analyses different approaches of deep discriminative models in session-based recommender systems. In the fourth chapter, session-based recommender systems that benefit from deep generative neural networks are discussed. Subsequently, chapter 5 discusses session-based recommender systems using advanced/hybrid deep learning models. Eventually, chapter 6 reviews different learning-to-rank methods focusing on information retrieval and recommender system domains. Finally, the results of the investigations and findings from the research review conducted throughout the book are presented in a conclusive summary. This book aims at researchers who intend to use deep learning models to solve the challenges related to SBRS. The target audience includes researchers entering the field, graduate students specializing in recommender systems, web data mining, information retrieval, or machine/deep learning, and advanced industry developers working on recommender systems.

Abstract: AI-Powered Transformation and Decentralization of the Energy Ecosystem -- An Explainable AI-based Framework for Supporting Decisions in Energy Management -- The big data value chain for the provision of AI-enabled energy analytics services -- MODULAR BIG DATA APPLICATIONS FOR ENERGY SERVICES IN BUILDINGS AND DISTRICTS: DIGITAL TWINS, TECHNICAL BUILDING MANAGEMENT SYSTEMS AND ENERGY SAVINGS CALCULATIONS -- Neural network based approaches for fault diagnosis of photovoltaic systems -- Clustering of building stock -- BIG DATA SUPPORTED ANALYTICS FOR NEXT GENERATION ENERGY PERFORMANCE CERTIFICATES -- Synthetic data on buildings.

Abstract: As carbon dioxide (CO2) emissions and other greenhouse gases constantly rise and constitute the main contributor to climate change, temperature rise and global warming, artificial intelligence, big data, Internet of things, and blockchain technologies are enlisted to help enforce energy transition and transform the entire energy sector. The book at hand presents state-of-the-art developments in artificial intelligence-empowered analytics of energy data and artificial intelligence-empowered application development. Topics covered include a presentation of the various stakeholders in the energy sector and their corresponding required analytic services, such as state-of-the-art machine learning, artificial intelligence, and optimization models and algorithms tailored for a series of demanding energy problems and aiming at providing optimal solutions under specific constraints. Professors, researchers, scientists, engineers, and students in energy sector-related disciplines are expected to be inspired and benefit from this book, along with readers from other disciplines wishing to learn more about this exciting new field of research.

Abstract: Part I: Mobility -- Low-Cost Robotic System of Detection of Anti-Personal Metal Mines -- Life cycle assessment of the Polyethylene Terephthalate (PET) waste bottles recycling process of a local industry in Guayaquil -- Flood risk analysis in an Andean watershed by integrating satellite data and multicriteria analysis. -- Assessing the Growth of Electric and Hybrid Vehicles in Ecuador’s Transportation Sector: A Technical Analysis of Their Impact on the Energy Matrix -- Evaluation of urban freight distribution in a medium-sized city: Ecuadorian case study -- Assessing the Performance of Electric Bicycles for Active Commuting in Higher Education: A Case Study of the UPS Cuenca Campus -- Analysis of Energy Efficiency Electric Vehicles Using a Driving Cycle on an Established Route in the City of Ambato -- A Systematic Literature Review of Tire Management in Ecuador -- Analysis of Cycle Gait on Different Surfaces using Inertial Sensors -- Data analysis applied to driver profile data obtained through vehicle telemetry and classification algorithms -- Development of an LSTM-based Model with Attention Mechanism for Detection of Traffic’s Officer Hand Gestures for Autonomous Vehicles in Ecuador -- Urban Digital Twins for Synthetic Data of Individuals with Mobility Aids in Curitiba, Brazil, to Drive Highly Accurate AI Models for Inclusivity -- English language teaching through the use of immersive environments supported by virtual reality -- Design and Implementation of Photovoltaic Energy Storage Systems Based on Batteries of Hybrid cars using a Second- Life Method -- Bibliometric review on a hybrid learning model with VLEs from a higher education context -- Part II: Sustainability and environment -- Simulation of the Flow behavior in the storage tank of a Hydropower using OpenFOAM -- Exploring the norm activation model together with external influences and environmental moral values: The case of Guayaquil, Ecuador -- Methodological application proposal for energy-electrical evaluation of National Polytechnic School in the context of a sustainable campus -- Louver of coconut fiber and sawdust bonded epoxy resin -- Design Of A Solar Photovoltaic Led System For Outdoor Illumination -- Treatment Of Liquid Effluents From Post-Harvest Flowers Through Advanced Oxidation -- Simulation of Synchronized Controls in Circuit Breakers of Power Transformers and Operation of Reactive Compensation Banks -- Spatial modeling of dissolved oxygen in wastewater from the Quebrada ¨Ortega ¨ of the Quito canton, Pichincha province -- Feasibility analysis of a photovoltaic power generation system using different charge controllers -- Analysis of Aluminum Can Management in Ecuador -- Impact of hydroponic green fodder: A comparative study on the quality of fresh cheese -- Intelligent Monitoring System for fry rearing using Fuzzy Logic -- Automatic classification of squat execution based on inertial sensors and machine learning -- Marine Predator Algorithm: A nature-inspired metaheuristic algorithm applied in rectangular patch antennas optimization -- Foot Pathology Analyzer.

Abstract: This book is dedicated to exploring the practical applications and future perspectives of intelligent technologies. It delves into various domains, including industry, mobility, telecommunications, and environmental considerations. The innovative nature of this text enables us to draw connections between technical advancements and experiences aimed at enhancing the integration of emerging technologies on local, national, and regional scales. It showcases the strides made in diverse engineering domains, underlining the book’s multidisciplinary appeal. This book is intended for a wide readership, catering to master's and doctoral students, professors, and researchers in the field of cutting-edge technologies. It also extends its relevance to businesses engaged in engineering development. The contents offer insights into novel methodologies, real-world case studies, and innovative techniques designed to optimize systems, ultimately contributing to societal progress.

Abstract: This book provides a wide collection of the recent studies triggering innovative ways to advance computer science and computational applications. The collection enables readers to understand more about technological conditions advancing industrial perspectives towards Industry 5.0. The research studies included in the book were accepted and presented in the 5th International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2023), which was held in Belek, Antalya, Turkey (on 3–4–5 November 2023). By covering the scientific scope of the conference, the book informs the readers about the cutting-edge data-driven solution aspects, intelligent algorithms, and mathematical background applied for solving different kinds of engineering problems. The book is used as a reference source by the wide readership including international researchers, professionals, practitioners from industry, degree students, and experts from all engineering disciplines. .

Abstract: The current information society is transitioning to an intelligent society where real-world and real-data applications have a profound influence. Real-time computing has an enormous impact on the future information society. Unimaginable applications have been emerging in real-time applications in the last two years. Logical reasoning and inference-making activities by machines have become a reality. Complex and heterogeneous data are being processed and infused into machine intelligence, bringing machine intelligence equal to human intelligence. Real-time data and real-time intelligence are the crux of the current research. This book of 41 papers in real-time intelligent systems addresses various issues ranging from real-time algorithms to various applications in real-time intelligence. The contributions of this book will mark a significant impact in the near-future research in real-time intelligence.

Abstract: Drug-Drug Interaction, Interaction Type And Resulting Severity Forecasting By Machine Learning-Based Approaches -- Hybrid Network Protocol Information Collection and Dissemination in IoT Healthcare -- CNN-Based Model for Skin Diseases Classification -- Using explainable artificial intelligence and knowledge graph to explain sentiment analysis of COVID-19 post on the Twitter -- An IoT-based Telemedicine System for the Rural People of Bangladesh -- Comparison of Predicting Regional Mortalities Using Machine Learning Models -- Benign and Malignant Cancer Prediction using Deep Learning and Generating Pathologist Diagnostic Report -- An Integrated Deep Learning Approach for Computer-Aided Diagnosis of Diverse Diabetic Retinopathy Grading -- Covid-19 Detection based on Chest X-ray images us-ing Attention Mechanism Modules and Weight Uncertainty in Bayesian Neural Networks -- A Stochastic Gradient Support Vector Optimization Algorithm for Predicting Chronic Kidney Diseases -- Intelligent Information Systems in Healthcare sector: Review Study -- Design of a Blockchain-based Patient Record Tracking System -- IoT Networks and Online Image Processing in IMU-based Gait Analysis -- Reducing Patient Waiting Time in Ultrasonography Using Simulation and IoT Application.

Abstract: IoTHIC-2023 is a multidisciplinary, peer-reviewed international conference on Internet of Things (IoT) and healthcare systems with Artificial Intelligence (AI) techniques such as data mining, machine learning, image processing, and meta-heuristic algorithms. The AI-based techniques are applied on many fields of healthcare systems, including predicting and detecting diseases in hospitals, clinics, smart health monitoring systems, surgery, medical services, and etc. .

Abstract: Towards Reinforcement Learning for Non-Stationary Environments -- Detection of Cyberbullying on Social Media Platforms using Machine Learning -- The Changing Landscape of Machine Learning: A Comparative Analysis of Centralized Machine Learning, Distributed Machine Learning and Federated Machine Learning -- Privacy and Security Landscape of Metaverse -- Strategies to Apply Genetic Programming Directly to the Traveling Salesman Problem -- A Comparative Analysis of GPT-3 and BERT Models for Text-based Emotion Recognition: Performance, Efficiency, and Robustness -- An Intrusion Detection System using the XGBoost Algorithm for SDVN -- Hybridizing L´evy Flights and Cartesian Genetic Programming for Learning Swarm-based Optimization -- An Evaluation of Handwriting Digit Recognition using Multilayer SAM Spiking Neural Network -- Towards Accurate Rainfall Volume Prediction: An Initial Approach with Deep Learning, Advanced Feature Selection, Parameter Optimisation, and Ensemble Techniques for Time-Series Forecasting.

Abstract: This book comprises the papers presented at the 22nd UK Workshop on Computational Intelligence (UKCI 2023), held at Aston University, Birmingham, the UK, during 6 to 8 September 2023. UKCI is the flagship AI conference of the UK and Europe held annually. In UKCI 2023, a total of 63 papers were received from 11 countries including the UK, India, Germany, China, Japan, Australia, Italy, Thailand, Turkey, Jordan and Saudi Arabia; of these, 50 were accepted for presentation. The review process was rigorous, wherein three reviews were provided for all papers, with some having four reviews. This book highlights the latest research developments in computational intelligence and its applications. It covers both conventional and advanced techniques in fuzzy systems, neural networks, evolutionary computation, machine learning, deep learning, federated learning, data mining, cognitive computing, intelligent robotics, optimization methods, hybrid methods, and applications of computational intelligence. The book offers a valuable reference guide for readers with expertise in computational intelligence or who are seeking a comprehensive and timely review of the latest trends in computational intelligence. Special emphasis is placed on novel methods and their use in a wide range of application areas, updating both academics and professionals on the state of the art.

Abstract: The book is a unique collection of studies involving intelligent systems and applications of artificial intelligence in the real world to provide solutions to most vexing problems. IntelliSys received an overwhelming 605 papers which were put under strict double-blind peer-review for their novelty, originality and exhaustive research. Finally, 227 papers were sieved and chosen to be published in the proceedings. This book is a valuable collection of all the latest research in the field of artificial intelligence and smart systems. It provides a ready-made resource to all the readers keen on gaining information regarding the latest trends in intelligent systems. It also renders a sneak peek into the future world governed by artificial intelligence.

Abstract: Contactless Video-based Vital-sign Measurement Methods: A Data-driven Review -- Enhancing STEAM in Education 4.0: A Review of Data-driven Technological Improvements -- State-of-the-Art Review in Explainable Machine Learning for Smart-Cities Applications -- Exploring the Connection Between Digital Systems and Sustainability: Synergy for a Brighter Future.

Abstract: This book focuses on new perspectives and applications of data-driven innovation technologies, applied artificial intelligence, applied machine learning and deep learning, data science, and topics related to transforming data into value. It includes theory and use cases to help readers understand the basics of data-driven innovation and to highlight the applicability of the technologies. It emphasizes how the data lifecycle is applied in current technologies in different business domains and industries, such as advanced materials, healthcare and medicine, resource optimization, control and automation, among others. This book is useful for anyone interested in data-driven innovation for smart technologies, as well as those curious in implementing cutting-edge technologies to solve impactful artificial intelligence, data science, and related information technology and communication problems.

Abstract: Part 1: Machine Learning, Deep Learning and Computational Intelligence -- Chapter 1. A novel hierarchical clustering technique to analyse style and content factorization during image recognition -- Chapter 2. Exploring Model-Level Transfer Learning to Improve the Recognition of Sinhala Speech -- Chapter 3. Metaheuristics Feature Selection Algorithms for Identification and Classification of Mango Pests Diseases -- Chapter 4. An Integrated Optimization Technique with SVM for Feature Selection -- Chapter 5. A Constant Binomial Coefficient Difference Equation Based FIR Predictor System for Signal Processing Data mining -- Chapter 6. Generating Synthetic Text Data for Improving Class Balance in Personality Prediction -- Chapter 7. CPSNet: Channel Pixel Spatial Feature Fusion Network for Image Dehazing -- Chapter 8. ATCBBC: A novel optimizer for neural network Architectures -- Chapter 9. Application of Dempster-Shafer Theory in Sensor Data Fusion -- Chapter 10.Examining Ant Colony Algorithm with The Cat Swarm Algorithm to Improve Energy Efficiency -- Chapter 11. Machine Learning based Online Visual Tracking with Multi-featured Adaptive Kernal Correlation filter -- Part 2: Wireless Communication -- Chapter 12. Integrating long-short term memory and particle swarm optimization for intrusion detection in 5G technologies -- Chapter 13. Performance Analysis of Polar Decoding Using Linear Code Mapping with Feedback Based Ann Architecture -- Chapter 14. Packet Classification Using Improved Random Forest Algorithm -- Chapter 15. A Machine Learning Perspective of optimal data transmission in Wireless Sensor Networks (WSN) -- Chapter 16. Blockchain and IPFS based solution for KYC -- Chapter 17. Analysis and Comparison of BER Performance of OFDM-IM under various fading channels using Conventional Detectors -- Chapter 18. A Survey of Non-Orthogonal Multiple Access for Internet of Things and Future Wireless Networks -- Chapter 19. Improved 3D Wireless Indoor Localization with Deep Learning Algorithms -- Chapter 20. Implementing Machine Learning for design and evaluation of Antenna Parameters -- Chapter 21. A MIMO dual mode homogenous OFDM IM system for next-generation communications -- Chapter 22. Probability Boosted Regression for Intrusion Detection in Cyber active Space -- Part 3: Mobile data application -- Chapter 23. Surface Water-body Extraction for Landsat-8 (OLI) Imagery using Water-Indices Methods and SCM Techniques -- Chapter 24. Automated Age-related Macular Degeneration Diagnosis in Retinal Fundus Images via ViT -- Chapter 25. Traffic Light Simulation Using ALP -- Chapter 26. DNN-ILD: A Transfer Learning-based Deep Neural Network for Automated Classification of Interstitial Lung Disease from CT Images -- Chapter 27. Image Manipulation Detection using Augmentation and Convolutional Neural Networks -- Chapter 28. Smart Women Safety Solution with Alert System Using Machine Learning Approach -- Chapter 29. Cyberbullying Detection Using BILSTM Model -- Chapter 30. Smart Agriculture using Internet of Things -- Chapter 31. Breast Cancer Detection from Mammograms using Deep Learning and Bio-Inspired Optimization Algorithm -- Chapter 32. Detection of Echinoderms Underwater using Deep Learning Network -- Chapter 33. Malaria Parasite Detection Using Deep Learning -- Chapter 34. FiltDeepNet: Architecture for Covid Detection based on Chest X-ray Images -- Chapter 35. Novel approaches to Automatic License Plate Reading (ALPR) -- Chapter 36. Crop Prediction Expert System with Ensemble Machine Learning Technique -- Chapter 37. A Comparative Analysis of Single Image-Based Face Morphing Attack Detection -- Chapter 38. Classifiers For Sentiment Analysis of Youtube Comments - A Comparative Study -- Chapter 39. Traffic Monitoring System Detecting Overspeed and Accidents from Video Input using OpenCV and Digital Image Processing -- Chapter 40. An experimental comparative analysis of human abnormal action identification on “SAIAZ” video dataset using SVM, ResNet50, and LSTM model -- Chapter 41. Comparative study on malicious URL using classifiers and boosting algorithms -- Chapter 42. Automation in Natural Rubber Latex Harvesting Field: A Review -- Chapter 43. Feature Selection based Machine Learning Model for Malware Detection -- Chapter 44. Application of Machine learning algorithm for prediction of Diabetes and Heart diseases -- Chapter 45. Damage Detection on Historical Structure using Image Processing -- Chapter 46. Eye Disease Classification Using VGG-19 Architecture -- Chapter 47. Automatic Photo Enhancer Using Machine Learning and Deep Learning with Python -- Chapter 48. Robust Touch Free Palm Vein Sensor Authentication System -- Chapter 49. An Effective Machine Learning-based Malware Detection Approach -- Chapter 50. Exploring The Performance of Various Classification Algorithms for Masked Face Recognition Using Cnn Based Features -- Chapter 51. Chess Game using Assembly Language Programming -- Chapter 52. Deep Artificial neural Network for Software Effort Estimation -- Chapter 53. ‘Legal Owl’, An Application for Machine Generated Legal Aid Using NLP.

Abstract: This book is a collection of best selected research papers presented at the 2nd Conference on Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication (MDCWC 2023) held during June 22-24th, 2023, at the National Institute of Technology Tiruchirappalli, India. The presented papers are grouped under the following topics (a) Machine learning, Deep learning and Computational intelligence algorithms (b) Wireless communication systems and (c) Mobile data applications. The topics include the latest research and results in the areas of network prediction, traffic classification, call detail record mining, mobile health care, mobile pattern recognition, natural language processing, automatic speech processing, mobility analysis, indoor localization, wireless sensor networks (WSN), energy minimization, routing, scheduling, resource allocation, multiple access, power control, malware detection, cyber security, flooding attacks detection, mobile apps sniffing, MIMO detection, signal detection in MIMO-OFDM, modulation recognition, channel estimation, MIMO nonlinear equalization, super-resolution channel and direction-of-arrival estimation. The book is a rich reference material for academia and industry. Presents research works in various fields of computational intelligence and machine learning; Discusses results of MDCWC 2023 held at National Institute of Technology Tiruchirappalli, India; Serves as a reference for researchers and practitioners in academia and industry.

Abstract: Visualizing the Unseen: Unleashing Knowledge Discovery with Lossless Visualizations -- Interactive Decision Tree Creation and Enhancement with Complete Visualization for Explainable Modeling -- Full High-dimensional Intelligible Learning In 2-D Lossless Visualization Space -- Explainable Machine Learning for Categorical and Mixed Data with Lossless Visualization -- Parallel Coordinates for Discovery of Interpretable Machine Learning Models -- Visual Knowledge Discovery with General Line Coordinates -- Unveiling Insights: Empowering AI/ML through Visual Knowledge Discovery.

Abstract: This book continues a series of Springer publications devoted to the emerging field of Integrated Artificial Intelligence and Machine Learning with Visual Knowledge Discovery and Visual Analytics that combine advances in both fields. Artificial Intelligence and Machine Learning face long-standing challenges of explainability and interpretability that underpin trust. Such attributes are fundamental to both decision-making and knowledge discovery. Models are approximations and, at best, interpretations of reality that are transposed to algorithmic form. A visual explanation paradigm is critically important to address such challenges, as current studies demonstrate in salience analysis in deep learning for images and texts. Visualization means are generally effective for discovering and explaining high-dimensional patterns in all high-dimensional data, while preserving data properties and relations in visualizations is challenging. Recent developments, such as in General Line Coordinates, open new opportunities to address such challenges. This book contains extended papers presented in 2021 and 2022 at the International Conference on Information Visualization (IV) on AI and Visual Analytics, with 18 chapters from international collaborators. The book builds on the previous volume, published in 2022 in the Studies in Computational Intelligence. The current book focuses on the following themes: knowledge discovery with lossless visualizations, AI/ML through visual knowledge discovery with visual analytics case studies application, and visual knowledge discovery in text mining and natural language processing. The intended audience for this collection includes but is not limited to developers of emerging AI/machine learning and visualization applications, scientists, practitioners, and research students. It has multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery, visual analytics, and text and natural language processing. The book provides case examples for future directions in this domain. New researchers find inspiration to join the profession of the field of AI/machine learning through a visualization lens. .

Abstract: 1. Changing Beauty Industry’s Strategic: Focused on Metaverse and Generation MZ -- 2. ESG news analysis using news big data: Focusing on topic modeling analysis -- 3. Effects of the Perceived Benefit and Innovativeness of Live Commerce on Intention to Use: Focus on Chinese consumers -- 4. A Study on the Effect of Customer Experience on the Intention to Continuously Use Coffee Store Mobile App based on UTAUT Model -- 5. A Study on Parallel Recommender System with Stream Data Using Stochastic Gradient Descent -- 6. Using Incremental Algorithm in Hybrid Recommender System Combined Sentiment Analysis -- 7. A Bottom-Up Generic Probabilistic Building and Enriching approach for knowledge graph using the LDA-based clustering method -- 8. Measuring the Effects of Signal-To-Noise in EEG Emotion Recognition -- 9. Phishy? Detecting Phishing Emails Using Machine Learning and Natural Language Processing -- 10. Are We Aware? An Empirical Study on the Privacy and Security Awareness of Smartphone Sensors, etc.

Abstract: The book reports state of the art results in Software Engineering Research, Management & Applications in both printed and electronic form. SCI (Studies in Computation Intelligence) has grown into the most comprehensive computational intelligence research forum available in the world. This volume published original papers on both theory and practice that address foundations, state of the art problems and solutions, and crucial challenges.

Abstract: Comparative study of abrasion resistance in cotton and meta-aramid fabrics for the production of safety garments -- Cybersecurity and cyber defense in the light of new technologies in cyberspace -- NATO/USAF standards in the FAC (by its Spanish acronym), building interoperability from the basic flight schools -- Human capital and per capita income in Ecuador -- Effect of the real wage on the basic family basket in Ecuador -- Evaluation of technical efficiency in segment one of the savings and credit cooperatives in Ecuador for 2016-2021 -- Measurement of innovation capacity in small and medium manufacturing companies -- The adhocracy culture and its impact on innovation in manufacturing companies of the Quito Metropolitan District -- Adjustable polycentric mechanism for external knee joint prosthesis based on the instantaneous center of rotation -- Manufacture of a custom-made AFO orthosis based on abaca nonwoven composite (Musa textilis) and resin -- Application of multicomponent nanoparticles synthesized with Andean blackberry fruit extract (Rubus glaucus) NPs (Ca, Fe, Mg-Rg) for oyster mushrooms (Pleurotus ostreatus) -- Characterization of a bamboo cellulose-activated carbon filament and resin -- Phytoremediation of pharmaceutical mixtures using Chrysopogon zizanioides: A sustainable alternative for removing emerging contaminants from wastewater -- Strength and elongation analysis of a coconut fiber-based nonwoven with potential applications for geotextiles -- Burnout syndrome and its relationship to working schedule: A cross-sectional study among oilfield workers in the Ecuadorian Amazon region -- ECRIF as a strategy to boost EFL students' speaking skills: An exploratory action research approach -- Attitude levels towards multicultural education in primary school teachers from north Lima (Peru) -- Implications of stakeholders on the quality and governance of university higher education: a critical analysis -- School motivation and academic performance in mathematics in primary school students from Pachacamac (Lima, Peru) -- Burnout syndrome in physicians of the surgical hospitalization area of a second-level hospital in the city of Guayaquil -- Evaluating the profiles of preprofessional internships of two University programs in early childhood end elementary education -- The community as a strategy for crime prevention: The experience of “Soñarte” socio-cultural project -- News coverage on the social network Facebook: a systematic review in Scopus from 2018 to 2023 -- Predictors of academic satisfaction through activities with Turnitin -- Effect of the application of pedagogical tools for ethics training in the public accounting program of the Corporación Universitaria Minuto de Dios distance modality -- The mediating effect of academic performance on ChatGPT satisfaction in university students.

Abstract: This book covers different aspects of advances in research, technological development, and innovation results in artificial intelligence, computational modeling, electrical, electronics, telecommunication, data communications, defense engineering, innovation, technology and society, managing technology and sustained innovation, business development, security and cryptography, and software engineering. In addition, the volume focuses on research results focused on finding innovative solutions in intelligent systems concerning the topics mentioned above, which are developed in national and international postgraduate programs and associated research groups and networks. This book interests the industry, teachers, undergraduate and graduate students, and researchers working in intelligent systems, security and defense, and technological, human, and administrative sciences. .

Abstract: -- 1. Estimating and Evaluation of International Capital Movements in The Perspective of Corporate Economic Geography. -- 2. Wave Net-TSRS Model for Timeseries Prediction in Finance. -- 3. Integrating Decision Analytics and Advanced Modeling in Financial and Economic Systems through Artificial Intelligence. -- 4. Co-movements between Bitcoin and Gold: Multivariate BEKK-GARCH Models. -- 5. An Approach for backtesting and algorithmic trading with liquidity and Hill Climbing algorithm. -- 6. Unleashing Economic Potential: Exploring the Synergy of Artificial Intelligence and Intelligent Automation.

Abstract: The book is divided into sections according to the content of the chapters. The first section covers AI concepts with NP and financial issues. The second section covers AI techniques in relation to Fintech issues. The remaining sections are implementation and analysis. As science and technology development and algorithms are widely used in various fields, their influence and development have increased efficiency and productivity. The introduction of algorithms in the financial field has not been an exception to this. In recent years, the growth and development of the financial system have been in sync with the growth of technology. Fintechs were born at the intersection of these two sectors. What happens through the application of computer knowledge in the financial field, or the examination of the efficiency and effectiveness of their use and the interaction and combination of these two fields has been written very infrequently in the majority of books. In Fintech, there are problems that researchers focus on such as customer support, portfolio management, trading algorithms, fraud detection, credit risk assessment, insurance, and wealth management. The mentioned problems are complex and are mapped to NP problems in the field of artificial intelligence. In the last two decades, optimization algorithms, neural networks, and deep learning have been widely applied in many scientific and engineering fields to solve the mentioned problems. The purpose of this book is to provide the reader with the most used artificial intelligence methods for scientific and engineering problems. This book is used by students, scientists, and practitioners in various fields. The chapters are self-explanatory, and the reader can read each one separately. They describe the algorithm used, the chosen problem, and the implementation. In addition, practical examples, comparisons, and experimental results are presented.

Abstract: A Deep Learning-Based Study for Cyclone Track Forecasting: Comparative Analysis Using Historical Data from the Bay of Bengal -- Employee Management Support Application for Operation Managers and Its Security -- Text-based Data Analysis for Mental Health Using Explainable AI and Deep Learning -- Using the Internet of Things and Machine Learning to Monitor and Detect COVID-19 -- Comparison between the Route Using Improved Detours and Shortest Route on Distributed Key Value Store Based on Order Preserving Linear Hashing and Skip Graph -- Extraction Study of Leaf Area and Plant Height of Radish Seedlings Based on SAM -- A Scalable Middleware for IoT Vulnerability Detection -- Predicting Oil Spills in Real-Time: A Machine Learning and AIS Data-Driven Approach -- Data-driven OCL Invariant Patterns-based Process Model Exploration for Process Mining -- An Analysis of Program Comprehension Process by Eye Movement Mapping to Syntax Trees -- Self-supervised Monocular Depth Estimation and Ego-motion Made Better: A Masking Constraints -- Using Additional Sets of Random Data to Assess Possible Dissaving Risk against Life Expectancy for Elderly People -- A Study on the NFT and Blockchain Technology for Copyright Management -- The Effect of Enterprise Risk Management System on Risk Management Capability and Management Performance -- A Study on the Effect of Omnichannel Customers Acceptance Attitudes and Loyalty: Focusing on UTAUT2.

Abstract: The book reports state-of-the-art results in Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing in both printed and electronic form. This book presents original papers on both theory and practice that address foundations, state-of-the-art problems and solutions, and crucial challenges.

Abstract: The scope of this book is to present the papers included at the 21st UK Workshop on Computational Intelligence (UKCI 2022), hosted by The University of Sheffield, between 7 and 9 September 2022, Sheffield, UK. This marks the first fully in-person UKCI conference, following the pandemic, a testament to the success and resilience of the UKCI community, as well as to the importance of computational intelligence (CI) research. The papers in this book are divided into five sections: fuzzy logic systems, machine learning, hybrid methods and network systems, deep learning and neural networks, and optimization and search.

Abstract: PARTI: Echoes of technological mind -- 1. Introduction -- 2. Is artificial intelligence intelligent? -- 3. Anthropomorphizing and trusting social robots -- 4. What neurohacking can tell us about the mind. Cybercrime, mind upload and the Artificial Extended Mind -- 5. On Neuroenhancement: Between bioethics and biotechnology -- PARTII: Challenging mind: Between Cognition and Art -- 6. Consciousness, Theory, and Mental Appearance -- 7. Theoretical virtues of cognitive extension -- 8. Hypnotic AI. The Altered States of Media Matter -- 9. The Digital Playful River, a River Out of Eden. How the internet shaped my planetary perception. -- 10. The mind, embodiment and technology: Experience, aesthetic sensibility and production of meaning.

Abstract: This book presents a set of texts that reflect different approaches to the relationship between mind and technology. In today’s increasingly technological world, a myriad of different and dizzying challenges face humanity: the ever-closer relationship between man and machine, the exponential development of Artificial Intelligence, man's relationship with virtual worlds, the relationship with new realities such as the neuro potentiation of his capacities, the appearance of robots in everyday life, and so on. In this volume, renowned world specialists explore these concerns, and discuss limitations and possible problems surrounding the interaction of man and machine. The book provides a well-researched, thought-provoking analysis of the need to rethink the theory of the mind, proposing relevant answers to pressing questions and raising new questions that need to be considered. Paulo Alexandre e Castro is a full member of the Institute for Philosophical Studies atthe University of Coimbra, Portugal, and visiting professor at the University of Caxias do Sul, Brazil.

Abstract: Introduction by Eduardo Gil Pedro and Andreas Moberg -- Part I: AI Regulation in the EU – The Future Interplay between Frameworks by Béatrice Schutte -- The AI Act’s Research Exemption: A Mechanism for Regulatory Arbitrage? by Liane Colonna -- Part II: Governance of AI or Governance by AI: Limits, New Threats, and Unnegotiable Principles by Migle Laukyte -- A Horizontal Meta-effect? Theorizing Human Rights in the AI Act and the Corporate Sustainability Due Diligence Directive by Mika Viljanen -- Everybody Wants to Rule the World. The Relevance of the Rule of Law for Private Law, in the Context of Algorithmic Profiling of Online Users by Silvia Carretta -- AI and Automation by Claes Granmar -- Part III: Algorithmic Hiring Systems: Implications and Recommendations for Organisations and Policymakers by Jason D. Schloetzer and Kyoko Yoshinaga -- AI Gender Biases in Women’s Healthcare: Perspectives from the United Kingdom and the European Legal Space by Pin Lean Lau -- The Role of AI in Mental Health Applications and Liability by Petra Müllerová -- Trustworthy Artificial Intelligence and Public Procurement by Isabel Gallego Córcoles -- AI and Sensitive Personal Data under the Law Enforcement Directive – Between Operational Efficiency and Legal Necessity by Markus Naarttijärvi.

Abstract: Artificial intelligence (AI) has the potential to radically transform our society. It may lead to a massive increase in the capabilities of humankind and allow us to address some of our most intractable challenges. It may also entail profound disruption to structures and processes that have sustained our society over centuries. These developments present a unique challenge to the socio-economic constitutional arrangements which govern our world at national, regional and international level. The deployment of increasingly powerful AI systems, able to function with increasing degree of autonomy, has led to concerns over loss of human control of important societal processes, over the disruption of existing economic, social and legal relationships, and over the empowerment of some societal actors at the expense of others, together with the entrenchment of situations of domination or discrimination. It has also made increasingly clear how tremendous the potential benefits, that these technologies may bring, are to those who successfully develop and deploy them. There is therefore great pressure on governments, international institutions, public authorities, civil society organisations, industry bodies and individual firms to introduce or adapt mechanisms and structures that will avoid the potentially negative outcomes of AI and achieve the positive ones. These mechanisms and structures, which have been given the umbrella term ‘AI governance’, cover a wide range of approaches, from individual firms introducing ethical principles which they volunteer to abide by, to the European Union legislating an AI Act, which will prohibit certain types of AI applications and impose binding obligations on AI developers and deployers. The fast pace of innovation in the development of AI technologies is mirrored by the fast pace of development of the emerging field of AI governance, where traditional legislation by public bodies is complemented with more innovative approaches, such ashybrid and adaptive governance, ethical alignment, governance by design and the creation of regulatory sandboxes. The chapter “AI and Sensitive Personal Data Under the Law Enforcement Directive: Between Operational Efficiency and Legal Necessity” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. .

Abstract: Chapter 1: Introduction -- Part I: Can an AI System Be Ethical? -- Chapter 2: Bias and Discrimination in Machine Decision-Making Systems -- Chapter 3: Opacity, machine learning and explainable AI -- Chapter 4: The Moral Status of AI Entities -- Part II: Ethical Controversies About AI Applications -- Chapter 5: Ethics of Virtual Assistants -- Chapter 6: Ethics of Virtual Reality -- Chapter 7: Ethical Problems of the Use of Deepfakes in the Arts and Culture -- Chapter 8: Exploring the Ethics of Interaction with Care Robots -- Chapter 9: Ethics of Autonomous Weapons Systems -- Part III: The Need for AI Boundaries -- Chapter 10: Ethical Principles and Governance for AI -- Chapter 11: AI, Sustainability, and Environmental Ethics -- Chapter 12: The Singularity, Superintelligent Machines, and Mind Uploading: The Technological Future?

Abstract: This book presents the reader with a comprehensive and structured understanding of the ethics of Artificial Intelligence (AI). It describes the main ethical questions that arise from the use of AI in different areas, as well as the contribution of various academic disciplines such as legal policy, environmental sciences, and philosophy of technology to the study of AI. AI has become ubiquitous and is significantly changing our lives, in many cases, for the better, but it comes with ethical challenges. These challenges include issues with the possibility and consequences of autonomous AI systems, privacy and data protection, the development of a surveillance society, problems with the design of these technologies and inequalities in access to AI technologies. This book offers specialists an instrument to develop a rigorous understanding of the main debates in emerging ethical questions around AI. The book will be of great relevance to experts in applied and technology ethics and to students pursuing degrees in applied ethics and, more specifically, in AI ethics. .

Abstract: 1. Coevolution of Technology and Society -- 2. A Gentle Guide to Complexity -- 3. Artificial Intelligence: Friend or FOE -- 4. Natural and Digital Ecosystems -- 5. We are in Transition from Industrial to Digital Economy -- 6. The New Digital Economy -- 7. The New Digital Society.

Abstract: This book describes in an easily accessible way how artificial intelligence (AI) will help us to overcome the ongoing rise in complexity and thus shape our lives and work in a not-too-distant future. AI has proven to be the latest tool for resolving issues created by the most recent surge in complexity, and the corollary is: those who delay or ignore AI, will be overwhelmed by complexity. The book starts with a broad description of the coevolution of technology and society that irreversibly leads to the sharp increase in complexity of our socioeconomic environment. The second chapter then covers concepts and principles of the new science of complexity which helps us to understand issues caused by socioeconomic complexity and provides methods for resolving them. Subsequently, a beginner’s guide to artificial intelligence helps readers to glance at fundamentals of this powerful technology capable of resolving issues created by socioeconomic complexity. The danger of allowing intelligent digital systems to make high-risk decisions as well as the consequences of possible misuse of AI for fraud and fake are also discussed. The following chapter explores the concepts of natural and digital ecosystems. Digital transformation of rigidly structured corporations and administrations into adaptive and evolving organisations are illustrated by a number of case studies. Next, the current hectic transition of industrial to digital society is described, its origins identified and outcomes predicted, highlighting issues created by the increase in complexity and showing how to resolve them using thinking tools such as a complexity mindset and digital tools such as artificial intelligence. Eventually, the last two chapters outline the author’s vision of the future digital economy and digital society. This book is accessible to everyone who is curious to glimpse into the future, no previous special knowledge of digital technology is required. Especially decision makers in politics, business, administration, banking, policy making, education, healthcare and defence, and their advisors will benefit from the book, as it will help them to contribute to the creation of the brave new digital world. It may also support investors to recognise which elements of digital technology will play the most important role in the near future.

Abstract: Introduction: The difference between knowing and learning -- Labor Markets: Comparative learning advantages -- Learning to Work: The two dimensions of job performance -- The Judgment Game: The Turing Test as a general research framework -- The Learning Game: A time-dependent Turing Test -- Implications: Recommendations for future education and labor policies.

Abstract: This book provides a novel framework for understanding and revising labor markets and education policies in an era of machine learning. It posits that while learning and knowing both require thinking, learning is fundamentally different than knowing because it results in cognitive processes that change over time. Learning, in contrast to knowing, requires time and agency. Therefore, “learning algorithms”—that enable machines to modify their actions based on real-world experiences—are a fundamentally new form of artificial intelligence that have potential to be even more disruptive to labor markets than prior introductions of digital technology. To explore the difference between knowing and learning, Turing’s “Imitation Game,”—that he proposed as a test for machine thinking—is expanded to include time dependence. The arguments presented in the book introduce three novel concepts: (1) Comparative learning advantage: This is a concept analogous to comparative labor advantage but arises from the disparate times required to learn new knowledge bases/skillsets. It is argued that in the future, comparative learning advantages between humans and machines will determine their division of labor. (2) Two dimensions of job performance—expertise and interpersonal: Job tasks can be sorted into two broad categories. Tasks that require expertise have stable endpoints, which makes these tasks inherently repetitive and subject to automation. Tasks that are interpersonal are highly context-dependent and lack stable endpoints, which makes these tasks inherently non-routine. Humans compared to machines have a comparative learning advantage along the interpersonal dimension, which is increasing in value economically. (3) The Learning Game is a time-dependent version of Turing’s “Imitation Game.” It is more than a thought experiment. The “Learning Game” provides a mathematical framework with quantitative criteria for training and assessing comparative learning advantages. The book is highly interdisciplinary—presenting philosophical arguments in economics, artificial intelligence, and education. It also provides data, mathematical analysis, and testable criteria that researchers in these fields will find of practical use. The book calls for a rethinking of how labor markets operate and how the education system should prepare students for future jobs. It concludes with a list of counterintuitive recommendations for future education and labor policies that all stakeholders—employers, employees, educators, students, and political leaders—should heed.

Abstract: A Bumpy Ride. Ethics, Driving Automation, and Artificial Agency. -- Safety First. Old and New Risks -- Data-Driven. Privacy, Surveillance, Manipulation.

Abstract: This book offers a systematic and thorough philosophical analysis of the ways in which driving automation crosses path with ethical values. Upon introducing the different forms of driving automation and examining their relation to human autonomy, it provides readers with in-depth reflections on safety, privacy, moral judgment, control, responsibility, sustainability, and other ethical issues. Driving is undoubtedly a moral activity as a human act. Transferring it to artificial agents such as connected and automated vehicles necessarily raises many philosophical questions. When driving is automated, what happens to its ethical dimensions? Could artificial agents accomplish ethical objectives on our behalf, take moral decisions in our place, and drive us into a more ethical transportation future? In doing so, would they be “moral” as we are or in a way that is similar to, but also remarkably different from, our own? And what role is yet to be played by human responsibility and commitment? The book addresses these questions with the aim of stimulating an interdisciplinary dialogue between different stakeholders. They include automotive engineers, computer scientists, and moral philosophers, as well as industry representatives, policymakers, regulators, transportation experts, and the general public. Indeed, connected and automated vehicles will not take the high road for us . We must drive them there. .

Abstract: This book highlights recent research on intelligent systems and nature-inspired computing. It presents 223 selected papers from the 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022), which was held online. The ISDA is a premier conference in the field of computational intelligence, and the latest installment brought together researchers, engineers, and practitioners whose work involves intelligent systems and their applications in industry. Including contributions by authors from 65 countries, the book offers a valuable reference guide for all researchers, students, and practitioners in the fields of computer science and engineering. .

Abstract: Investigating Ensemble Learning Methods for Predicting Water Quality Index -- Age-Invariant Face Recognition Based on Self-Supervised Learning -- Detection of Kidney Stone Based on Super Resolution Techniques and YOLOv7 Under Limited Training Samples -- Hardware-Based Lane Detection System Architecture for Autonomous Vehicles -- Video Classification Based on the Behaviors of Children in Pre-School Through Surveillance Cameras -- Land Subsidence Susceptibility Mapping Using Machine Learning in the Google Earth Engine Platform -- Building an AI-Powered IoT App for Fall Detection Using Yolov8 Approach -- Seam Puckering Level Classification Using AIoT Technology -- Classification of Pneumonia on Chest X-Ray Image Using Transfer Learning -- Bayesian Approach for Static Object Detection and Localization in Unmanned Ground Vehicles -- Diabetic Retinopathy Diagnosis Leveraging Densely Connected Convolutional Networks and Explanation Technique -- Deep Learning Approach for Inundation Area Detection Using Sentinel Data -- Classification of Raisin Grains Based on Ensemble Learning Techniques in Machine Learning -- An Effective Deep Learning Model for Detecting Plant Diseases Using a Natural Dataset for the Agricultural IoT System -- Real-Time Air Quality Monitoring System Using Fog Computing Technology -- An Intelligent Computing Method for Scheduling Projects with Normally Distributed Activity Times.

Abstract: This book aims to provide state-of-the-art knowledge in the field of Intelligence of Things to both academic and industrial readers. In particular, undergraduate, graduate, and researchers may find valuable information to drive their future research. This book is considered a reference for numerous courses such as Artificial Intelligence, Internet of Things, Intelligent Systems, and Mobile Networks. In the industrial area, this book provides information on recent studies in applying AI to IoT developments, which help to align and shorten R&D processes to introduce new classes of intelligent IoT products. This book provides a technical reference for interdisciplinary studies which utilize machine learning and IoT as tools in their fields such as constructional management, smart agriculture, Earth sciences and geo-spatial analysis, intelligent business, and digital transformation in education.

Abstract: This book is a collection of thoroughly well-researched studies presented at the Eighth Future Technologies Conference. This annual conference aims to seek submissions from the wide arena of studies like Computing, Communication, Machine Vision, Artificial Intelligence, Ambient Intelligence, Security, and e-Learning. With an impressive 490 paper submissions, FTC emerged as a hybrid event of unparalleled success, where visionary minds explored groundbreaking solutions to the most pressing challenges across diverse fields. These groundbreaking findings open a window for vital conversation on information technologies in our community especially to foster future collaboration with one another. We hope that the readers find this book interesting and inspiring and render their enthusiastic support toward it.

Abstract: Chapter 1: The Impact of Green Human Resource Management Practices on Digital Transformation -- Chapter 2: Creating value with Blockchain for Organizations -- Chapter 3: How can Artificial Intelligence help improve fashion sustainability? -- Chapter 4: Fundamentals of Digital Governance: Bibliometric Mixed Approach and Social Network Analysis -- Chapter 5: IT Governance mechanisms to foster Digital Transformation in Higher Education Institution -- Chapter 6: Artificial intelligence applied to Stakeholder Theory -- Chapter 7: Towards knowledge management for digital transformation in hyper turbulent environments -- Chapter 8: Developing an Innovative Digital Learning environment with Metaverse -- Chapter 9: Implementation of a serious game to develop computational thinking skills -- Chapter 10: How can LMS affect student’s motivation and engagement -- Chapter 11: Development of Digital Capabilities in Small Business: A Necessary Condition Analysis -- Chapter 12: Accountant’s Perceptions of the Digital Transformation -- Chapter 13: Scoping Review on AI as a Driver for Industry -- Chapter 14: Enablers for the success for competitive stance in Portuguese companies due to digital transformation during Covid-19. .

Abstract: Given the nature of this book proposal, linked with some Masters, and the faster pace of digital technologies evolution, the new version will have an entire new content with new cases and insights regarding the development and implementation of the most interesting digital technologies. Digital transformation marks a rethinking of how an organization uses technology, people, and processes in pursuit of new business models and new revenue streams, driven by changes in customer expectations around products and services. For many enterprises that build traditional goods, this means building digital products, such as a mobile applications or an ecommerce platform. To do so, they must use and integrate digital technologies. The pace of change is increasing. Organizations need to adapt or risk disappearing under innovators entrance in the market. With new digital technologies growing in an exponential rate in the last few decades, organizations are facing even more complex contexts. Managers are now pressed to take efficient decisions. This book provides a reference manual to assist professionals and academics on further insights regarding: the impact of digital technologies in business, how to implement digital technologies, solutions for specific digital technologies barriers, and much more. This book covers research methods such as Systematic Literature Review (SLR) or Multifocal Literature Review (MLR), case studies, experiments, survey, Design Science Research using quantitative and qualitative approaches.

Abstract: Preface -- Part I. Semantics -- 1. Ontology -- 2. Algorithm -- 3. Content Resonating in Memory -- 4. Logical Reasoning -- 5. Common Sense Reasoning -- Part II. Pragmatics -- 6. STAR-0 Content: Origin -- 7. STAR-1 Content: Speaker’s Perspective -- 8. STAR-2 Content: Hearer’s Perspective -- 9. Pragmatics of Figurative Use -- 10. Nonstandard Variants of Pragmatics -- Part III. Data-Driven Behavior Control -- 11. Interface Component -- 12. Memory Component -- 13. Operation Component -- 14. Degrees of Abstraction.-15. Conclusion: the Fundamental Alternatives -- Bibliography -- Name Index -- Subject Index.

Abstract: Modern science is divided into three parts: natural sciences, engineering sciences and humanities. Over the last millennia, natural and engineering sciences evolved a symbiotic relationship, but humanities still stand apart. Today, however, designing and building a talking robot is a comparatively new challenge for which all three branches are needed. Starting from the idea that designing a theory of computational cognition should be as complete as possible, and trying to answer questions such as “Which ontology is required for building a computational cognition?”, the current book integrates interfaces, components, functional flows, data structure, database schema, and algorithms into a coherent system with an extensive range of cognitive functions, and constitutes the background to the book “Ontology of Communication” recently published by the author (Springer, 2023). Part I discusses ontological distinctions between a sign-based and an agent-based approach, and continues with explanations of the data structure, the content-addressable database schema; the time-linear derivations of the speak and the hear mode; resonating content; induction, deduction, and abduction in inferencing, and concludes with a reconstruction of eight classical syllogisms as a test suite for DBS inferencing in the think mode. Part II complements the literal use of language in the speak and hear mode with a reconstruction of syntactic mood adaptations and figurative use. The database schema of DBS is shown to lend itself not only to the tasks of traditional storage and retrieval, but also of reference, coreference, shadowing, coactivation of resonating content, and selective activation. Part III complements the treatment of individual topics in linguistics, philosophy, and cognitive psychology with an overall software structure in the form of three interacting main components, called the interface, the memory, and the production component.

Abstract: Sensor Datasets for Human Daily Safety and Well-being -- Habitpad: A Habit-Change Person-Centric Healthcare Mobile Application with Machine Leaning and Gamification Features for Obesity -- Human centered Mathematics: a framework for medical applications based on Extended Reality and Artificial Intelligence -- Attentive Vision-Based Model for Sarcopenia Screening by Automating Timed Up-and-Go (TUG) Test -- AAL with Deep Learning to classify the Diseases remotely from the image data -- Heart Failure Prediction Using Radial Basis with Metaheuristic Optimization -- Healthcare Management And Prediction Of Future Illness Through Autonomous Intelligent Advisory System Using Aat Computational Framework -- ResNet-50-CNN and LSTM based Arrhythmia detection model based on ECG dataset -- A Review of Brain-Computer Interface (BCI) System: Advancement and Applications -- Optimized TSA ResNet architecture with TSH -discriminatory features for kidney stone classification from QUS Images -- Ambient Healthcare: A new Paradigm in Medical Zone -- Illuminating Unexplored Corners in Healthcare Space using Ambience Intelligence -- Depression Assessment in Youths using an Enhanced Deep Learning Approach -- Telemedicine Enabled Remote Digital Healthcare System.

Abstract: This book experiences the future of patient-centered healthcare and dives into the latest advancements and transformative technologies that are revolutionizing the well-being of individuals around the globe. The readers can join authors on an engaging journey as the authors explore the captivating realm of ambient assisted living and unlock its immense potential for improving healthcare outcomes. This book goes beyond mere exploration; it invites readers to embark on a voyage of discovery as authors unveil the outcomes of groundbreaking research ideas. With a diverse range of applications, from deep learning in healthcare to cutting-edge models, the authors offer a comprehensive view of the opportunities and challenges that lie ahead. Whether you're a healthcare professional, an academic seeking the latest insights, or a researcher delving into the realms of ambient assistive technology, biomedical engineering, or computational intelligence, this book is an invaluable resource. Additionally, postgraduate students pursuing data engineering systems find it to be an essential guide. Each chapter stands independently, providing a comprehensive overview of problem formulation and its tangible outcomes. The readers can immerse themselves in the world of patient-centered healthcare today and become part of the forefront of innovation.

Abstract: A Multipath Routing Algorithm Avoiding Congested Links According to the Link Usage Ratios on Ndn -- A Fuzzy-based Error Driving System: Effect of Non Performance Error for Improving Driving Performance in Vanets -- The Effects of Scale and Distribution on a Deep Neural Network Iterative Classification System of Spatial Data Streams -- Reducing Electric Energy Consumption of Servers in Multi-version Timestamp Ordering Algorithm -- An Empirical Study on Min-max External Ties to Improve Decentralized Social Graph Ranking Performance -- Barriers to Blockchain Adoption by Saudi Higher Education Institutions: A Structural Equation Analysis -- Evaluation of the Ftbfc Model for Energy-efficient Iot -- Performance Evaluation of Fc-rdvm Router Placement Method for Wmns Considering -- Normal, Uniform, Chi-square and Weibull Distributions of Mesh Clients -- Capability-based Access Control Model for Fog Computing Model -- Erawan Hpc: A High-performance Computing Platform for Data Analysis -- Data Quality Assessment Framework and Economic Indicators -- An Intelligent System for Optimization of Sensor Node Placement in Wireless Visual Sensor Networks: Performance Evaluation of Ccm and Ccm-based Sa Methods -- Design and Performance Study of Virtual Power Plant Aggregation by Various -- Failure of Privacy Policy for Session Replay Services Used for Monitor Your Keystroke -- A Novel Attack Scenario Dataset Collection for Intrusion Detection System in Can Network.

Abstract: The networks and information systems of today are evolving rapidly. There are new trends and applications in information networking such as wireless sensor networks, ad hoc networks, peer-to-peer systems, vehicular networks, opportunistic networks, grid and cloud computing, pervasive and ubiquitous computing, multimedia systems, security, multi-agent systems, high-speed networks, and web-based systems. These kinds of networks need to manage the increasing number of users, provide support for different services, guarantee the QoS, and optimize the network resources. For these networks, there are many research issues and challenges that should be considered and find solutions. The aim of the book is to provide latest research findings, innovative research results, methods, and development techniques from both theoretical and practical perspectives related to the emerging areas of information networking and their applications.

Abstract: Approach to Development of Digital Twin Model for Cyber-Physical System in Conditions of Conceptual Uncertainty -- Constructing Mathematical Models for Actuarial Processes -- Functional Planning Optimization of Exploiting Underground Space in Large Cities Using System Methodology -- Analysis and Modelling of the Underground Tunnel Planning in Uncertainty Conditions -- Stabilization of Impulsive Processes of the Cognitive Map to Cryptocurrency Usage with Multirate Sampling and Coordination between Some Nodes Parameters -- Wireless Sensor Networks for Healthcare on SoA -- Improving Predictive Models in the Financial Sector Using Fractal Analysis -- K-lr Modeling with Neural Economy and its Utilization in Unclear Data -- Formalization and Development of Autonomous Artificial Intelligence Systems -- Attractors for Differential Inclusions and Their Applications for Evolution Algorithms -- System Analysis and Method of Ensuring Functional Sustainability of the Information System of a Critical Infrastructure Object -- Intellectual Data Analysis and Machine Learning Approaches for Car Insurance Rates Reconstruction -- On Generation of Daily Cloud-Free Satellite Images at High Resolution Level -- Computational Intelligence for Digital Healthcare Informatics -- Continuous and Convex Extensions Approaches in Combinatorial Optimization -- Action Encoding in Algorithms for Learning Controllable Environment -- Comparison of Constrained Bayesian and Classical Methods of Testing Statistical Hypotheses in Sequential Experiments -- Investigation of Artificial Intelligence Methods in the Short-Term and Middle-Term Forecasting in Financial Sphere -- Neo-Fuzzy Radial-Basis Function Neural Network and Its Combined Learning -- Investigations of Different Classes Hybrid Deep Learning Networks and Analysis of Their Efficiency in Forecasting -- Generalized Models of Logistics Problems and Approaches to Their Solution Based on the Synthesis of the Theory of Optimal Partitioning and Neuro-Fuzzy Technologies -- Technological Principles of Using Media Content for Evaluating Social Opinion -- Scenario Modelling in the Context of Foresight Studies -- Assessing the Development of Energy Innovations and Its Impact on the Sustainable Development of Countries -- Studies of the Intercivilization Fault Level Dynamics -- Exploring the Vulnerability of Social Media for Crowdsourced Intelligence under a False Flag.

Abstract: This book contains the latest scientific work of Ukrainian scientists and their colleagues from other countries of the world in three interrelated areas: systems analysis, artificial intelligence and data mining. The included articles present the theoretical foundations and practical applications of the latest tools and methods of artificial intelligence, scenario planning, decision making and computational intelligence for important areas of human activity. The tools and methods presented in the book are continuously evolving and finding new applications across various fields, contributing to advancements and efficiencies in different industries: healthcare, finance, retail and E-commerce, manufacturing and industrial automation, transportation and logistics advancements and cybersecurity. The results of the book are useful to teachers, scientists, graduate students of universities and managers of large companies specializing in strategic planning, engineering design of complex systems, decision-making, optimization of operations and other related fields of knowledge and practice.

Abstract: T opKW S Algorithm in the Map-Reduce paradigm for Cloud Computing QoS Recommendation System -- A New Context-Based Factorization Machines for Context-aware Recommender Systems -- Review of Recommendation Systems and their Applications in e-Learning -- Improvement of Courses Recommendation System using Divide and Conquer Algorithm -- Deep Reinforcement Learning in Financial Markets Context: Review of Open Challenges -- A Survey of Parallel Computing: Challenges, Methods and Directions -- A bi-LSTM neural network to forecast stock Market Index -- Fast Yolo V7 based CNN for video streaming Sea Ship recognition and sea surveillance -- Graph convolutional network for multilingual sentiment analysis -- Predicting Blood Glucose Levels in Type 1 Diabetes Using LSTM -- Sarcasm Detection on Social Media using Machine Learning Approach -- School Dropout Prediction using Machine Learning Algorithms -- SURVIVAL PREDICTION IN PATIENTS WITH NASOPHARYNGEAL CANCER USING MACHINE LEARNING METHODS -- Comparative Analysis of Skyline Algorithms used to Select Cloud Services based on QoS -- A state-of-the-art Survey on Ransomware Detection Using Machine Learning & Deep Learning -- Improving the Application of Blockchain Technology For Tracking Processes in the Supply Chain Integrated Business Intelligence -- Studying Consensus Mechanisms for Blockchain -- Design and Construction of a Smart Agricultural Greenhouse -- Implementation and Management of a Home Automation Control System (Smart Home) -- A comparative study of consensus algorithms used in Blockchain and their adaptation to the IoT networks -- Dynamics behavior of vehicular traffic flow in a scale-free complex network -- Customer Journey Map Discovery Approach -- Unmanned aerial vehicle-assisted clustered wireless sensor network data collection efficiency improvement -- Synergistic Fibroblast Optimization Algorithm for Solving Knapsack Problem -- ACCEPTANCE OF JOB ACCESS WITH SPEECH (JAWS) AS AN ASSISTIVE COMPUTER APPLICATION SOFTWARE -- Experimenting with Polymorphic Creativity Support Tools to Support Innovation in Participatory Ideation. .

Abstract: This Book, through its various chapters presenting the Recent Advances in Modern Artificial Intelligence and Data Science as well as their Applications, aims to set up lasting and real applications necessary for both academics and professionals. Readers find here the fruit of many research ideas covering a wide range of application areas that can be explored for the advancement of their research or the development of their business. These ideas present new techniques and trends projected in various areas of daily life. Through its proposals of new ideas, this Book serves as a real guide both for experienced readers and for beginners in these specialized fields. It also covers several applications that explain how they can support some societal challenges such as education, health, agriculture, clean energy, business, environment, security and many more. This Book is therefore intended for Designers, Developers, Decision-Makers, Consultants, Engineers, and of course Master's/Doctoral Students, Researchers and Academics.

Abstract: This volume presents the results of recent research, which supports the postulated transformation. It contains papers written by both scientists and engineers dealing with diverse aspects of: measuring techniques, robotics, mechatronics systems, control, industrial automation, numerical modelling and simulation as well as application of artificial intelligence techniques required by the transformation of the industry towards the Industry 4.0. We strongly believe that the solutions and guidelines presented in this volume will be useful for both researchers and engineers solving problems that have emerged during the recent crisis.

Abstract: Sharing Human Seeing and Hearing and Their Annotated Portfolio -- IoT Security and Privacy Challenges from the Developer Perspective -- Flow Disaggregation: underdetermined non-negative linear systems -- Ensuring Data Privacy in Open Data Platforms for Smart Cities -- Intelligent Heart Rate Monitoring from a Social Robot -- Review of physical aggression detection in video using explainable and trustworthy artificial intelligence.

Abstract: This book presents the latest research on Ambient Intelligence (AmI) presented in the 14th International Symposium on Ambient Intelligence (ISAmI 2023). Among others, interested researchers can find works on the recognition of emotions and life conditions; smart applications for improving people’s quality of life and safety; smart cities and territories; as well as advances in data semantics, organization, and privacy, among others. The symposium was organized by the Universidade do Minho (Portugal), the Universitat Politècnica de València (Spain), the University of Granada (Spain), the National Institute of Informatics (Japan), the Instituto Superior de Engenharia do Porto (Portugal), the Universidad de Salamanca (Spain), and with the AIR Institute (Spain) as sponsor. The present edition was hosted by the LASI and Centro Algoritmi of the University of Minho in Guimarães (Portugal) from July 12 to 14, 2023.

Abstract: Evaluation of metaverse tools based on privacy model using fuzzy MCDM approach -- Exploring research trends of metaverse: A bibliometric analysis -- Inducing Virtual Reality to improve Human-virtual social interaction and Learning Perceptions -- Visualization Creativity through shadowing Practices using Virtual Reality in designing digital stories Language Classroom -- Metaverse Applications and Its Use in Education -- Investigating behavior of using Metaverse by integrating UTAUT2 and self-efficacy -- Understating the Social Sustainability of Metaverse by Integrating Adoption Properties with Users’ Satisfaction -- The future of Metaverse in improving the quality of higher education: Systematic Reviews -- Integrating Ideal Characteristics of Chat-GPT Mechanisms into the Metaverse: Knowledge, Transparency, and Ethics -- Use of Earnings Quality Measures to Evaluate Performance of Iraqi Banks in Terms of Industry 5.0: Using the Hierarchical Analysis Process -- The moderating role of big data analytics capabilities in the relationship between supply chain management practices and sustainable performance: A conceptual framework from a metaverse perspective -- Using Artificial Intelligence and Metaverse Techniques to Reduce Earning Management -- The metaverse and the role of accounting culture: Reporting of digital assets according to international standards -- The Effect of Digital Business Strategy on Improving Customer Journey: Evidence from Users of Virtual Reality Platforms -- The Effect of Financial Readiness on Earnings Retention in Terms of Virtual Technologies: Evidence from UAE Companies.

Abstract: This book addresses recent research trends concerning the role of the Metaverse in advancing the education and finance sectors from various perspectives. These trends are explored through multiple case studies employing diverse analytical approaches. The chapters aim to aid scholars and postgraduate students in pursuing future research in this domain and identifying potential developments in Metaverse applications.

Abstract: Abstract ordinary and fractional neural network approximations based on Richard’s curve -- Abstract Multivariate Neural Network Approximation based on Richard’s curve -- Parametrized hyperbolic tangent based Banach space valued basic and fractional neural network approximations -- Parametrized hyperbolic tangent induced Banach space valued multivariate multi layer neural network approximations -- Banach space valued neural network approximation based on a parametrized arctangent sigmoid function -- Parametrized arctangent activated Banach space valued multi layer neural network multivariate approximation -- Banach space valued Ordinary and Fractional neural networks approximations based on the parametrized Gudermannian function -- Parametrized Gudermannian activation function based Banach space valued neural network multivariate approximation -- Banach space valued univariate neural network approximation based on parametrized error activation function -- Banach space valued multivariate multi layer neural network approximation based on parametrized error activation function -- Hyperbolic Tangent Like based univariate Banach space valued neural network approximation -- Banach space valued neural network multivariate approximation based on hyperbolic tangent like activation function -- Banach space valued ordinary and fractional neural network approximations based on q-deformed hyperbolic tangent activation function -- Banach space valued multivariate multi layer neural network approximation based on q-deformed hyperbolic tangent activation function -- Banach space valued multivariate multi layer neural network approximation based on q-deformed and λ-parametrized A-generalized logistic function -- Banach space valued ordinary and fractional neural network approximation based on q-deformed and λ-parametrized A-generalized logistic function -- Banach space valued multivariate multi layer neural network approximation based on q-deformed and λ-parametrized hyperbolic tangent function -- q-Deformed and λ-parametrized hyperbolic tangent based Banach space valued ordinary and fractional neural network approximation -- Banach space valued multivariate multi layer neural network approximation based on q-Deformed and parametrized half hyperbolic tangent -- Banach space valued ordinary and fractional neural network approximation based on q-deformed and β-parametrized half hyperbolic tangent -- General sigmoid relied Banach space valued neural network approximation -- General sigmoid induced Banach space valued neural network multivariate approximation -- Fuzzy basic and fractional general sigmoid function generated neural network approximation -- Multivariate Fuzzy Approximation by Neural Network Operators induced by a general sigmoid function -- Multivariate Fuzzy-Random and stochastic general sigmoid activation function generated Neural Network Approximations -- Voronovskaya type asymptotic expansions for general sigmoid functions induced quasi-interpolation neural network operators -- Multiple general sigmoids activated Banach space valued neural network multivariate approximation -- Quantitative Approximation by Multiple sigmoids KantorovichChoquet quasi-interpolation neural network operators -- Degree of Approximation by Multiple sigmoids KantorovichShilkret quasi-interpolation neural network operators -- Approximation by Neural Networks of Brownian Motion -- Neural Networks Approximation of Time Separating Stochastic Processes -- Fractional Calculus between Banach spaces together with Ostrowski and Gr¨uss kind of inequalities -- Sequential Fractional Calculus between Banach spaces and corresponding Ostrowski and Gr¨uss kind of inequalities.

Abstract: In this book, we introduce the parametrized, deformed and general activation function of neural networks. The parametrized activation function kills much less neurons than the original one. The asymmetry of the brain is best expressed by deformed activation functions. Along with a great variety of activation functions, general activation functions are also engaged. Thus, in this book, all presented is original work by the author given at a very general level to cover a maximum number of different kinds of neural networks: giving ordinary, fractional, fuzzy and stochastic approximations. It presents here univariate, fractional and multivariate approximations. Iterated sequential multi-layer approximations are also studied. The functions under approximation and neural networks are Banach space valued.

Abstract: 1.Introduction -- 2.Literature review -- 3.Recommending reviewers and experts -- 4.Supporting innovativeness and information sharing -- 5.Selected algorithmic developments -- 6.Knowledge recommendation in practice -- 7.Conclusions.

Abstract: Knowledge recommendation is an timely subject that is encountered frequently in research and information services. A compelling and urgent need exists for such systems: the modern economy is in dire need of highly-skilled professionals, researchers, and innovators, who create opportunities to gain competitive advantage and assist in the management of financial resources and available goods, as well as conducting fundamental and applied research more effectively. This book takes readers on a journey into the world of knowledge recommendation, and of systems of knowledge recommendation that use machine intelligence algorithms. It illustrates knowledge recommendation using two examples. The first is the recommendation of reviewers and experts who can evaluate manuscripts of academic articles, or of research and development project proposals. The second is innovation support, which involves bringing science and business together by recommending information that pertains to innovations, projects, prospective partners, experts, and conferences meaningfully. The book also describes the selection of the algorithms that transform data into information and then into knowledge, which is then used in the information systems. More specifically, recommendation and information extraction algorithms are used to acquire data, classify publications, identify (disambiguate) their authors, extract keywords, evaluate whether enterprises are innovative, and recommend knowledge. This book comprises original work and is unique in many ways. The systems and algorithms it presents are informed by contemporary solutions described in the literature - including many compelling, novel, and original aspects. The new and promising directions the book presents, as well as the techniques of machine learning applied to knowledge recommendation, are all original.

Abstract: Forcing the Network to use Human Explanations in its Inference Process -- Fuzzy Inference System-based Collision Avoidance of Unmanned Aerial Vehicles Optimized using Genetic Algorithm -- Fuzzy Logic-aided Inverse Kinematics Control for Redundant Manipulators -- Growth Kinetics of Gold Nanoparticles via p-fuzzy systems -- Optimization of Artificial Potential Field using Genetic Algorithm for Human-aware Navigation of Autonomous Mobile Robots -- Genetic Fuzzy Threat Assessment for Asteroids 2600 Derived Game -- Deep Learning ANFIS Architectures -- A Fuzzy Inference System for an Optimal Spacecraft Attitude State Trajectory -- Faster Algorithms for Estimating the Mean of a Quadratic Expression under Uncertainty -- People Prefer More Information About Uncertainty, But Perform Worse When Given This Information: An Explanation of the Paradoxical Phenomenon.

Abstract: This book is an overview of latest successes and applications of fuzzy techniques—techniques that use expert knowledge formulated by natural-language words like "small". Engineering applications deal with aerospace (control of spacecrafts and unmanned aerial vehicles, air traffic control, airport passenger flow predictions), materials (designing gold nano-structures for medicine, catalysis, and sensors), and robot navigation and manipulation. Other application areas include cosmology, demographics, finances, wine production, medicine (diagnostics, epidemics control), and predicting human behavior. In many cases, fuzzy techniques are combined with machine learning AI. Due to natural-language origin of fuzzy techniques, such combination adds explainability (X) to AI. This book is recommended to students and practitioners interested in the state-of-the-art fuzzy-related XAI and to researchers willing to take on numerous remaining challenges.

Abstract: This book of Springer Nature is another proof of Springer’s outstanding greatness on the lively interface of Holistic Computational Optimization, Green IoTs, Smart Modeling, and Deep Learning! It is a masterpiece of what our community of academics and experts can provide when an interconnected approach of joint, mutual, and meta-learning is supported by advanced operational research and experience of the World-Leader Springer Nature! The 6th edition of International Conference on Intelligent Computing and Optimization took place at G Hua Hin Resort & Mall on April 27–28, 2023, with tremendous support from the global research scholars across the planet. Objective is to celebrate “Research Novelty with Compassion and Wisdom” with researchers, scholars, experts, and investigators in Intelligent Computing and Optimization across the globe, to share knowledge, experience, and innovation—a marvelous opportunity for discourse and mutuality by novel research, invention, and creativity. This proceedings book of the 6th ICO’2023 is published by Springer Nature—Quality Label of Enlightenment. .

Abstract: Log Out or Stay Connected? Unveiling the Intention for Continuous Use in the Metaverse -- Virtual Influencers as the Next Generation of Influencer Marketing: Identifying Antecedents and Consequences -- Modeling the continuous intention to use the Metaverse as a learning platform: PLS-SEM and fsQCA approach -- Are you ready for tapping into the metaverse in higher education? Integrated by dual PLS-SEM and ANN approach -- Investigating the Influence of Technology Anxiety on Healthcare Metaverse Adoption -- The Metaverse: A New Frontier for Learning and Teaching from the perspective of AI -- Understanding the Effects of Social Media Advertising on Purchase Intention through Metaverse -- The Impact of Environmental Factors on Social Selling Intention via Virtual Reality Technology and Social Selling Performance: The Mediating Effect of Self-Efficacy -- Reshaping Sport with Extended Reality in an Era of Metaverse: Insights from XR the Moroccan Association Experts -- Unveiling the Influence of Social Technologies on Online Social Shopping -- Mobile payment adoption in Vietnam: A two staged SEM-ANN approach -- Millennials Fintech services adoption: What matters most? -- Perceived Risk of Users’ Intention to Use Cryptocurrency in Malaysia: A Multi-Analytic Approach -- Prediction of Consumer Repurchase Intention with Food Delivery Apps: The Mediating Role of Prior Online Experience Using PLS-SEM-ANN Approach -- Effects of Platform Values on Consumers’ Willingness to Continue and Subscribe to Metaverse Live-Streaming: with a Moderating Effect of Digital Literacy -- Organizational Adoption of Blockchain Based Medical Supply Chain Management -- Understanding the use of Acoustic Measurement and Mel Frequency Cepstral Coefficient (MFCC) Features for the Classification of Depression Speech -- Enhancing user acceptance of e-exam systems: A comprehensive model and empirical analysis -- Investigating the Relation Between Learning Analytics and Academic Performance at the International Modern Arabic School: A Qualitative Study -- The Role of Accounting Information Systems in Strengthening Organizational Resilience: An Empirical Investigation Using the SEM-ANN Approach -- Deep Dive into The Augmented Reality Customer Experience and Adoption Research: A Bibliometric Study -- Blockchain and IoT in the Modern Digital Age -- How Does Gamification in an E-Commerce Platform Drive Customer Experience? The Mediating Roles of Perceived Enjoyment and Brand Engagement.

Abstract: This book explores current and future trends in adopting intelligent technologies, such as the metaverse, social technologies, FinTech applications, and blockchain, among individuals and organizations. The edited book includes empirical and review studies primarily focusing on these issues. This focus aids scholars in conducting future research in the domain and identifying possible future developments of emerging technologies. The empirical studies in the book utilize recent and advanced analytical techniques for data analysis.

Abstract: Part 1: Introduction -- Chapter 1. Cybersecurity Landscape for Computer Systems -- Chapter 2. Explainable Artificial Intelligence -- Part 2: Detection of Software Vulnerabilities -- Chapter 3. Malware Detection using Explainable AI -- Chapter 4. Spectre and Meltdown Detection using Explainable AI -- Part 3: Detection of Hardware Vulnerabilities -- Chapter 5. Hardware Trojan Detection using Reinforcement Learning -- Chapter 6. Hardware Trojan Detection using Side-Channel Analysis -- Chapter 7. Hardware Trojan Detection using Shapley Ensemble Boosting -- Part 4: Mitigation of AI Vulnerabilities -- Chapter 8. Mitigation of Adversarial Machine Learning -- Chapter 9. AI Trojan Attacks and Countermeasures -- Part 5: Acceleration of Explainable AI -- Chapter 10. Hardware Acceleration of Explainable AI -- Chapter 11. Explainable AI Acceleration using Tensor Processing Units -- Part 6: Conclusion -- Chapter 12. The Future of AI-Enabled Cybersecurity.

Abstract: This book provides a comprehensive overview of security vulnerabilities and state-of-the-art countermeasures using explainable artificial intelligence (AI). Specifically, it describes how explainable AI can be effectively used for detection and mitigation of hardware vulnerabilities (e.g., hardware Trojans) as well as software attacks (e.g., malware and ransomware). It provides insights into the security threats towards machine learning models and presents effective countermeasures. It also explores hardware acceleration of explainable AI algorithms. The reader will be able to comprehend a complete picture of cybersecurity challenges and how to detect them using explainable AI. This book serves as a single source of reference for students, researchers, engineers, and practitioners for designing secure and trustworthy systems. Introduces a wide variety of software and hardware vulnerabilities; Describes solutions for detecting security attacks using explainable AI; Presents a fast and robust framework using hardware acceleration and mitigation of adversarial attacks.

Abstract: This book of Springer Nature is another proof of Springer’s outstanding greatness on the lively interface of Holistic Computational Optimization, Green IoTs, Smart Modeling, and Deep Learning! It is a masterpiece of what our community of academics and experts can provide when an interconnected approach of joint, mutual, and meta-learning is supported by advanced operational research and experience of the World-Leader Springer Nature! The 6th edition of International Conference on Intelligent Computing and Optimization took place at G Hua Hin Resort & Mall on April 27–28, 2023, with tremendous support from the global research scholars across the planet. Objective is to celebrate “Research Novelty with Compassion and Wisdom” with researchers, scholars, experts, and investigators in Intelligent Computing and Optimization across the globe, to share knowledge, experience, and innovation—a marvelous opportunity for discourse and mutuality by novel research, invention, and creativity. This proceedings book of the 6th ICO’2023 is published by Springer Nature—Quality Label of Enlightenment. .

Abstract: The main objective of this book is to explore the synergy between cutting-edge AI technologies and environmentally conscious practices through collecting best selected research papers presented at the International Conference on Artificial Intelligence and Green Computing (ICAIGC 2023), which took place from March 15 to 17, 2023, in Beni Mellal, Morocco. Within the pages of this book, readers find a wealth of research findings, survey works, and practical experiences aimed at fostering a comprehensive understanding of the pivotal role AI plays in various fields, including agriculture, health care, IT, and more. It highlights both the opportunities presented by the widespread usage of AI and the challenges associated with its continued advancement. As a result, the book has been divided into three parts: 1)- AI for multimedia processing, 2)- AI for distributed computing, and 3)- AI applications. The book serves as a comprehensive resource that brings together on-going research and practical experiences from the ICAIGC 2023 conference. It strives to deepen the understanding of the essential role AI plays in multiple fields. Whether you are an AI enthusiast, researcher, or practitioner, the insights contained within these pages expand your horizons and inspire further exploration of AI's potential in shaping a greener and more technologically advanced future.

Abstract: This book is a collection of thoroughly well-researched studies presented at the Eighth Future Technologies Conference. This annual conference aims to seek submissions from the wide arena of studies like Computing, Communication, Machine Vision, Artificial Intelligence, Ambient Intelligence, Security, and e-Learning. With an impressive 490 paper submissions, FTC emerged as a hybrid event of unparalleled success, where visionary minds explored groundbreaking solutions to the most pressing challenges across diverse fields. These groundbreaking findings open a window for vital conversation on information technologies in our community especially to foster future collaboration with one another. We hope that the readers find this book interesting and inspiring and render their enthusiastic support toward it.

Abstract: A novel approach of multi-string parsing for syntactic pattern recognition -- Hollow n-grams vectorizer for Natural Language Processing problems -- A non-deep approach to classifying movie genres based on multimodal data -- Incremental Extreme Learning Machine for Binary Data Stream Classification -- Interpreting Intrusions - The Role of Explainability in AI-based Intrusion Detection System -- Real-time deformation of three-dimensional volumetric models using mesh models -- Hyperparameters Optimization using GridSearchCV Method for TinyML models -- Analysis of the Possibility to Employ Relationship Between the Problem Complexity and the Classification Quality as Model Optimization Proxy -- Deep Learning for pit detection in cherries -- Image analysis system for augmented reality games -- Coregistration of selected sequences in MRI imaging based on edge analysis of image difference -- Actinic Keratosis Prediction Based on Deep Learning Methods -- A New Assessment of Convolutional Neural Networks for Texture Directionality Detection -- Knowledge Distillation with Relative Representations for Image Representation Learning -- An Approach for CT Image Conversion Using Filtering Based on Quaternion Mathematics -- Exploring Text-Guided Synthetic Distribution Shifts for Robust Image Classification -- Color Tracking Application Using AI-based Docker Container Scheduling in Fog Computing -- Air pollution monitoring and information distribution system -- Detection of conspiracy theories from tweets using NLI-based Zero Shot Text Classification models -- Battery management system for Polish hybrid residential photovoltaic power plants -- Document Annotation Tool For News Content Analysis -- Dynamic time warping technique applied to the user’s intent recognition for myoelectric-based control of upper limb prosthesis -- A Hybrid Long Short-Term Memory Network Based on Wind and Rain Sensitive and its Application to PM2.5 Prediction.

Abstract: This book presents a collection of high-quality research papers accepted to multi-conference consisting of the 13th International Conference on Image Processing and Communications (IP&C 2023), the 13th International Conference on Computer Recognition Systems (CORES 2023) held jointly in Wroclaw, Poland (virtually), in June 2023. The accepted papers address current computer science and computer systems-related technological challenges and solutions, as well as many practical applications and results. The first part of the book deals with advances in pattern recognition and classifiers, the second part is devoted to image processing and computer vision, while the third part addresses practical applications of computer recognition systems. We believe this book will be interesting for researchers and practitioners in many fields of computer science and IT applications.

Abstract: Explainable Document Classification via Pattern Structures -- Bayesian belief network for association between clusters of social media users with similar personality traits profiles and color characteristics of their avatar images -- Algebraic Bayesian Networks: the Generation of the Network Canonical Representation -- Quantification of Localization Uncertainty in One-stage Object Detection -- Automated Discovery of Direct Speech to Increase Quality and Battery Saving in Telephony.

Abstract: This book contains the works connected with the key advances in Industrial Artificial Intelligence presented at IITI 2023, the Seventh International Scientific Conference on Intelligent Information Technologies for Industry held on September 25-30, 2023 in St. Petersburg, Russia. The works were written by the experts in the field of applied artificial intelligence including topics such as Machine Learning, Explainable AI, Decision-Making, Fuzzy Logic, Multi-Agent and Bioinspired Systems. The following industrial application domains were touched: railway automation, cyber security, intelligent medical systems, navigation and energetic systems. The editors believe that this book will be helpful for all scientists and engineers interested in the modern state of applied artificial intelligence.

Abstract: Detecting Anomalies: A Case Study in Predictive Maintenance of Telescopes -- AI Case-Based Reasoning for Artificial Neural Networks -- Real-Time KPI Forecasting with 1D Convolutional Time Series for Enhanced Manufacturing Efficiency -- Blockchain Technology for Supply Chain Traceability: Case Study of Pharmaceutical Supply Chain -- Artificial Intelligence for Work Measurement: A Promising Approach to Improving Productivity and Reducing Waste -- Lean Six Sigma and Industry 4.0 Integration: LSS 4.0.

Abstract: Amid the dynamic growth of artificial intelligence, this book presents a collection of findings and advancements from the second edition of the A2IA-Artificial Intelligence and Industrial Applications conference. The conference, hosted by ENSAM-Meknès at Moulay Ismail University, Morocco, fosters knowledge exchange in AI, focusing primarily on its industrial applications. Covering a wide range of topics, the book highlights the adaptable nature of AI and its increasing impact on industrial sectors. It brings together contributions from an international cohort of researchers, discussing themes such as intelligent manufacturing and maintenance, intelligent supply chain management, various modes of learning including supervised, unsupervised, reinforcement, semi-supervised, and graph-based, as well as neural networks, deep learning, planning, and optimization. A defining feature of this edition is its extensive scope and emphasis on the practical applications of AI, along with its foundational elements. It facilitates an understanding of AI's current state and potential future direction, showcasing recent developments that bridge the gap between theory and practice. Designed for a diverse readership, this book is of interest to AI practitioners, academics, and enthusiasts, as well as to those new to the field. It provides an opportunity to explore AI's critical role in industrial applications, and the practical insights it offers are likely to be beneficial for decision-making within industrial settings.

Abstract: This book of Springer Nature is another proof of Springer’s outstanding greatness on the lively interface of Holistic Computational Optimization, Green IoTs, Smart Modeling, and Deep Learning! It is a masterpiece of what our community of academics and experts can provide when an interconnected approach of joint, mutual, and meta-learning is supported by advanced operational research and experience of the World-Leader Springer Nature! The 6th edition of International Conference on Intelligent Computing and Optimization took place at G Hua Hin Resort & Mall on April 27–28, 2023, with tremendous support from the global research scholars across the planet. Objective is to celebrate “Research Novelty with Compassion and Wisdom” with researchers, scholars, experts, and investigators in Intelligent Computing and Optimization across the globe, to share knowledge, experience, and innovation—a marvelous opportunity for discourse and mutuality by novel research, invention, and creativity. This proceedings book of the 6th ICO’2023 is published by Springer Nature—Quality Label of Enlightenment. .

Abstract: Part I: Communication Networks and Cybersecurity -- Enhancing the Performance of Cloud Environment by a Novel Three-Stage Task Scheduling Policy -- A new approach to coupled IR sensor based Real Time system for alerting old people accidents in Rest room -- Gesture Recognition Based Virtual Mouse And Keyboard -- IoV-based Application using Deep Learning Approach -- DDoS Attack Prediction using Decision Tree and Random Forest Algorithms -- The impact of Control Plane Attacks in Software Defined Networks Environments -- Compressed data aggregation using regulated duty cycle for WSN-IOT networks -- Improving Data Centre Power Efficiency by Applying the VM consolidation Approach -- Integration of a UHF Fractal Antenna into a 1U CubeSat for Low-Earth Orbit Mission -- A Novel & Innovative Blockchain-Empowered Federated Learning Approach for Secure Data Sharing in Smart city Applications -- Design and modelling of renewable energy sources using a partial power converter -- A qualitative study of the effects of socio-organizational factors on the information security culture of employees in a financial institution -- Part II: Embedded Systems and Smart Applications -- An Overview of Concentrated Photovoltaic Technology -- Electronic Prescription Service for Improved Healthcare Delivery -- A Review on Blockchain Smart Contract Applications -- Carbonic Acid Gas Emission Rating by Vehicles Using Datascience Techniques -- Robotics cyber security issues -- Part III: Computational Intelligence -- A comparative study of GANs (text to image GANs) -- QCNN- A Conceptual Framework for Duplicate removal in Big Data using Quality assured Crowd sourcing coupled with Neural networks -- Design and Implementation of Camera-based Security System (CBSS) for Detecting Missing Persons -- Design and Implementation of a Secure Patient Recommender and Prediction System -- SDD: An Efficient Stacked Deep Learning Technique for Social Distance Detection -- Junk Mail Content Detection using Logistic Regression Algorithm -- Predicting Fish Habitat in the Persian Gulf Using Artificial Intelligence -- Evaluation of Text Classification using Support Vector Machine compare with Naive Bayes, Random Forest Decision Tree and K-NN -- Emotion AI -- Accuracy Prediction of Rainfall Using Decision Tree Algorithm and Random Forest -- Fraud detection using decision tree algorithm to curb identity theft -- Academic Performance Prediction using Machine learning algorithms -- Accuracy Of Water Quality Prediction Using Random Forest Regression and Artificial Neural Network -- Indian Sign Language Recognition System for Interrogative Words using Deep Learning -- New Approach of Artificial Intelligence in Digital Forensic Investigation: A Literature Review -- Comparative analysis of machine learning classifiers for plant leaf disease detection -- Effective House Price Prediction Using Machine Learning -- Colour Trend Analysis using Machine Learning and Histogram -- A new AI-based approach for Rental Tax Evasion Management in Iran (Ethical Consideration) -- Bibliometric Analysis of Scientific Literature on Mental Health Research in Africa -- Multi-Modal Sentiment Analysis using Text and Audio for Customer Support Centers -- Comparative Analysis on the use of Teleconsultation using Support Vector Regression and Decision Tree Regression to Predict Patient Satisfaction -- COVID-19 in the UK: Sentiment and Emotion Analysis of Tweets Over Time -- Deep learning based sentiment analysis of customer reviews on hotels through tweets -- Diagnosis of Diabetes Type using Random Forest Algorithm and SVM for improving Accuracy -- Biometric Recognition Systems: A Short Survey -- Lung Histopathological Detection Using Image Classification -- A novel approach of Machine learning application in Astrophysics: Morphological feature wrapping based ensemble method for Galaxy shape classification using GAMA dataset -- Evaluating the Performance of a Hybrid Model for Classification of Bicycle Crash Severity and Identification of Associated Risk Factors -- Digital Transformations In Medical Applications Using Audio And Virtual Reality Procedures -- Part IV: Special Session 1 : Digital Transformation of Contemporary Business Practices -- A Review of Social Media Marketing on Digital Savvy Brand Shoppers -- Online Buying Behavior of UK University Students -- Factors Impacting A UK Based Software Business on International Expansion -- The Role of Blockchain Technology and Student Coin Case in Saudi Arabia's Higher Education Sector. The Challenge of Achieving 2030 Vision -- Part V: Special Session 2: Applications of Technology for Mental Health -- Research Protocol for a Preliminary Evaluation of a Gamified Tool for Adult Wellbeing -- Development and Evaluation of „Perspective: Counselling Simulator“: A Gamified Tool for Developing Risk-Assessment Skills in Trainee Counsellors -- Initial Evaluation of a Mobile Therapeutic Game for Adolescent Anxiety Disorders -- New Technologies and Interventions to Improve the Mental Health of People with Diabetes -- Help over harm: Practical and ethical considerations for the evaluation and deployment of therapeutic games -- Positive addiction recovery for an online audience: Implementation design and user evaluation -- A solution for creating dynamic networks of symptoms based on patients’ big data in cognitive-behavioral functional analysis and therapy – participatory design protocol -- Therapists’ attitudes towards the use of AI in therapeutic practice: considering the therapeutic alliance.

Abstract: Today, communication technology and computer engineering are intertwined, with advances in one field driving advances in the other, leading to the development of outstanding technologies. This book delves into the latest trends and breakthroughs in the areas of communication, Internet of things, cloud computing, big data, artificial intelligence, and machine learning. This book discusses challenges and opportunities that arise with the integration of communication technology and computer engineering. In addition, the book examines the ethical and social implications, including issues related to privacy, security, and digital divide and law. We have explored the future direction of these fields and the potential for further breakthroughs and innovations. The book is intended for a broad audience of undergraduate and graduate students, practicing engineers, and readers without a technical background who have an interest in learning about communication technology and computer engineering.