Abstract: An Artificial Intelligence-based Concept and Survey for Personalized Learning in schools in the Republic of Bulgaria -- 0/1 1-D bin packing problem solved by a recent nature-inspired optimizer -- Orca predator algorithm for feature selection -- Skeleton Detection Using MediaPipe as a Tool for Musculoskeletal Disorders Analysis -- Pipeline leakage detection via Extreme Seeking Entropy -- Secure Data Transmission Scheme in Wireless Sensor Network Resisting Unknown Lethal Threats -- Deep Reinforcement Learning-Based Task Offloading in Multi-access Edge Computing for Marine IoT -- Information and Communication Skills for Higher Learners Competence Model -- Smart solution for public lighting in the municipality -- A Review Paper On Biometric Authentication And Geospatial Data – Case of Zambia.

Abstract: This book presents cutting-edge research and methodologies in software engineering, specifically focusing on systems and network systems. It showcases novel development approaches and network system optimizations, highlighting the field's dynamic evolution. The book is designed for experts, scholars, and professionals, offering insights and tools crucial for advancing the software engineering landscape. Its diverse content makes it an invaluable resource for seasoned professionals and those new to the field, inspiring and enriching readers' understanding of software engineering's future directions.

Abstract: Effect of Social Networking Advertisements (SNAs) On Attitudes and Purchase Intention towards Brand Products -- Design of Optimal Waste Management System using IOT and Machine Learning Technique in Educational institutions -- An enhanced Woelfel Image Noise Filter -- PAPR and SER Performance Analysis of OFDMA and SCFDMA -- VLSI Implementation of an 8051 Microcontroller using VHDL and Re- corrective Measure using AI -- A survey of Internet of Things frameworks for crowd management system.

Abstract: This book provides a systematic and comprehensive overview of cognitive intelligence and AI-enabled IoT ecosystem and machine learning, capable of recognizing the object pattern in complex and large data sets. A remarkable success has been experienced in the last decade by emulating the brain–computer interface. It presents the applied cognitive science methods and AI-enabled technologies that have played a vital role at the core of practical solutions for a wide scope of tasks between handheld apps and industrial process control, autonomous vehicles, IoT, intelligent learning environment, game theory, human computer interaction, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The book contains contents highlighting artificial neural networks that are analogous to the networks of neurons that comprise the brain and have given computers the ability to distinguish an image of a cat from one of a coconut, to spot pedestrians with enough accuracy to direct a self-driving car, and to recognize and respond to the spoken word. The chapters in this book focus on audiences interested in artificial intelligence, machine learning, fuzzy, cognitive and neurofuzzy-inspired computational systems, their theories, mechanisms, and architecture, which underline human and animal behavior, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step execution and explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions on applications of machine learning, artificial intelligence, and cognitive science such as healthcare products, AI-enabled IoT, gaming, medical, and engineering. Overall, this book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and academics in the field of machine learning and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.

Abstract: Interpretable Rules with a Simplified Data Representation - a Case Study with the EMBER dataset -- Spatial econometric models: the pursuit of an accurate spatial structure with an application to labor market -- Use of Neighborhood-based Bridge Node Centrality Tuple for Preferential Vaccination of Nodes to Reduce the Number of Infected Nodes in a Complex Real-World Network -- Social Media Applications’ Privacy Policies for facilitating Digital Living -- Modeling the Alienability of an Electronic Document -- Particular Analysis of Regression Effect Sizes Applied on Big Data Set -- Foreign Languages Teaching Technologies and Methods in Traditional and Distance Forms of Learning -- Application of Fuzzy Logic for Evaluating Student Learning Outcomes in E-Learning -- The meaning of business and software architecture in the enterprise architecture -- Research of the Correlation Between the Results of Detection the Liveliness of a Face and its Identification by Facial Recognition Systems -- Profit Prediction Model for Steel Enterprises Based on Input and Output Prices.

Abstract: These proceedings offer an insightful exploration of integrating data analytics in system engineering. This book highlights the essential role of data in driving innovation, optimizing processes, and solving complex challenges in the field. Targeted at industry professionals, researchers, and enthusiasts, this book serves as a comprehensive resource, providing actionable insights and showcasing transformative applications of data in engineering. It is a must-read for anyone keen on understanding and participating in the ongoing evolution of system engineering in our data-centric world.

Abstract: This book is a collection of high-quality peer-reviewed research papers presented at The International Conference on Intelligent Systems and Smart Technologies (I2ST’23) held at the Faculty of Science and Technology of Hassan First University, Morocco, on January 17–18, 2023. I2ST'23 is a forum for presenting new advances and research results in the fields of information, communication, and smart technologies. The book discusses significant issues relating to machine learning, smart technologies, and data analytics. The main and distinctive topics covered are: I) AI& Intelligent, II) Systems Smart Technologies, III) Communications and Networking, IV) Software Engineering & Web Applications, V) Information Technology, and VI) Software Engineering & Web Applications.

Abstract: Digital transformation and Disruptive Technologies -- Cloud Computing and DevOps on Managing Projects -- Product Differentiation Strategy between Cost Leadership Strategy and Order-Winners -- Customisation Strategy and Product Variety on Operational Performance -- Demand Forecasting on Effective Supply Chain with Mediating Role of Strategic Planning -- Information Sharing and Delivery Time on Customer Happiness.

Abstract: This book takes a unique approach by exploring the connection between cybersecurity, digitalization, and business intelligence. In today's digital landscape, cybersecurity is a crucial aspect of business operations. Meanwhile, organizations continue to leverage digital technologies for their day-to-day operations. They must be aware of the risks associated with cyber-attacks and implement robust cybersecurity measures to protect their assets. It provides practical insights and solutions to help businesses better understand the impact of cybersecurity on their digitalization and business intelligence strategies. It provides practical insights and solutions for implementing cybersecurity measures in organizations and covers a wide range of topics, including threat intelligence, risk management, compliance, cloud security, and IoT security. The book takes a holistic approach and explores the intersection of cybersecurity, digitalization, and business intelligence and examines the possible challenges and opportunities.

Abstract: Introduction -- Part 1: Type-1 Fuzzy Sets and Systems -- Short Primers on Type-1 Fuzzy Sets and Fuzzy Logic -- Type-1 Fuzzy Logic Systems -- Part 2: Type-2 Fuzzy Sets -- Sources of Uncertainty -- Type-2 Fuzzy Sets -- Operations on and Properties OF Type-2 Fuzzy Sets -- Type-2 Relations and Compositions -- Centroid of a Type-2 Fuzzy Set: Type-Reduction -- Part 3: Type-2 Fuzzy Logic Systems -- Mamdani Interval Type-2 Fuzzy Logic Systems (IT2 FLSS) -- TSK Interval Type-2 Fuzzy Logic Systems -- General Type-2 Fuzzy Logic Systems (GT2 FLSS) -- Conclusion.

Abstract: The third edition of this textbook presents a further updated approach to fuzzy sets and systems that can model uncertainty — i.e., “type-2” fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications, from time-series forecasting to knowledge mining to classification to control and to explainable AI (XAI). This latest edition again begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty, leading to type-2 fuzzy sets and systems. New material is included about how to obtain fuzzy set word models that are needed for XAI, similarity of fuzzy sets, a quantitative methodology that lets one explain in a simple way why the different kinds of fuzzy systems have the potential for performance improvements over each other, and new parameterizations of membership functions that have the potential for achieving even greater performance for all kinds of fuzzy systems. For hands-on experience, the book provides information on accessing MATLAB, Java, and Python software to complement the content. The book features a full suite of classroom material.

Abstract: Determination of additional braking force for hydraulic cylinder piston -- Modular spindle tooling of the machining center with increased resource -- Optical fiber behavior under inert atmosphere -- Natural vibrations of a turbine blade during milling -- Maintenance of hydraulic components on multifunctional stands -- configuration of SRR-metamaterial based 2*1 array-type RGW antenna with cantilever beam switching technique -- Step, servo and hub motor based hybrid PCB processing and prototyping device design and analysis. .

Abstract: This book provides both researchers in the academia, students, and industrial experts the chance to exchange new ideas, build relations, and find virtual partners. It is a scientific event whose proceedings have set a very high standard. ICORSE’s distinctive feature is represented by its breadth of topics: mechatronics, integronics and adaptronics; reliable systems engineering; cyber-physical systems; optics; theoretical and applied mechanics; robotics; modelling and simulation; smart integrated control systems; computer imaging processing; smart bio-medical and bio-mechatronic systems; MEMS and NEMS; new materials; sensors and transducers; nano-chemistry, physical chemistry of biological systems; micro- and nanotechnology; system optimization; communications, renewable energy and environmental engineering. They all come together to deliver a clear picture of the state of the art reached in these areas so far.

Abstract: Nowadays, data analysis is becoming an appealing topic due to the emergence of new data types, dimensions, and sources. This motivates the development of probabilistic/statistical approaches and tools to cope with these data. Different communities of experts, namely statisticians, mathematicians, computer scientists, engineers, econometricians, and psychologists are more and more interested in facing this challenge. As a consequence, there is a clear need to build bridges between all these communities for Data Science. This book contains more than fifty selected recent contributions aiming to establish the above referred bridges. These contributions address very different and relevant aspects such as imprecise probabilities, information theory, random sets and random fuzzy sets, belief functions, possibility theory, dependence modelling and copulas, clustering, depth concepts, dimensionality reduction of complex data and robustness.

Abstract: A Bi-objective Evolutionary Algorithm to Improve the Service Quality for On-demand Mobility -- A Dynamic Circular Hough Transform Based Iris Segmentation -- A Game Theoretic Framework for Interpretable Student Performance Model -- A New Telecom Churn Prediction Model Based on Multi Layer Stacking Architecture -- A Novel Hybrid Classification Approach for Predict Performance Student in e-learning -- A Proposed Big Data Architecture using Data Lakes for Education Systems -- A SVM Approach for Assessing Traffic Congestion State by Similarity Measures -- A Tool for the Analysis, Characterization, and Evaluation of Serious Games in Teaching -- Analysis and Examination of the Bus Control Center(BCC) System: Burulaş Example -- Analyze Symmetric and Asymmetric Encryption Techniques by Securing Facial Recognition System -- Aspect-Based Sentiment Analysis of Indonesian Language Hotel Reviews using Long Short-Term Memory with an Attention Mechanism -- Big Data and Machine Learning in Healthcare: Concepts, Technologies, and Opportunities -- Classification of Credit Applicants using SVM Variants Coupled with Filter-Based Feature Selection -- Classification of Hate Speech Language Detection on social media: Preliminary Study for Improvement -- CoAP and MQTT: Characteristics and Security.

Abstract: This book covers selected research works presented at the fifth International Conference on Networking, Information Systems and Security (NISS 2022), organized by the Research Center for Data and Information Sciences at the National Research and Innovation Agency (BRIN), Republic of Indonesia, and Moroccan Mediterranean Association of Sciences and Sustainable Development, Morocco, during March 30–31, 2022, hosted in online mode in Bandung, Indonesia. Building on the successful history of the conference series in the recent four years, this book aims to present the paramount role of connecting researchers around the world to disseminate and share new ideas in intelligent information systems, cyber-security, and networking technologies. The 49 chapters presented in this book were carefully reviewed and selected from 115 submissions. They focus on delivering intelligent solutions through leveraging advanced information systems, networking, and security for competitive advantage and cost savings in modern industrial sectors as well as public, business, and education sectors. Authors are eminent academicians, scientists, researchers, and scholars in their respective fields from across the world.

Abstract: Deep and machine learning is the state-of-the-art at providing models, methods, tools and techniques for developing autonomous and intelligent systems which can revolutionise industrial and commercial applications in various fields such as online commerce, intelligent transportation, healthcare and medicine, etc. The ground-breaking technology of blockchain also enables decentralisation, immutability, and transparency of data and applications. This event aims to enable synergy between these areas and provide a leading forum for researchers, developers, practitioners, and professionals from public sectors and industries to meet and share the latest solutions and ideas in solving cutting-edge problems in the modern information society and the economy. The conference focuses on specific challenges in deep (and machine) learning, big data and blockchain. Some of the key topics of interest include (but are not limited to): Deep/Machine learning based models Statistical models and learning Data analysis, insights and hidden pattern Data visualisation Security threat detection Data classification and clustering Blockchain security and trust Blockchain data management.

Abstract: Application of Convolutional Neural Network for the Gene Expression Data Classification -- Formation of Subsets of Co-Expressed Gene Expression Profiles Based on Joint Use of Fuzzy Inference System, Statistical Criteria and Shannon Entropy -- Mathematical Model of Preparing Process of Bulk Cargo for Transportation by Vessel -- Computer Simulation of Joule-Thomson Effect Based on the Use of Real Gases -- Simulating Soil Organic Carbon Turnover with a Layered Model and Improved Moisture and Temperature Impacts -- Optimization of Coagulant Dosing Process for Water Purification Based on Artificial Neural Networks -- Methodology for Solving Forecasting Problems Based on Machine Learning Methods -- The Comprehensive Model of Using In-Depth Consolidated Multimodal Learning to Study Trading Strategies in the Securities Market -- Mathematical and Computer Model of the Tree Crown Ignition Process from a Mobile Grassroots Fire -- Features of Complex Application of the Formal Method of EVENT-B for Development of Environmental Management Systems -- Ecology Objects Recognition by Optimized Inverse Filtration Of Textured Background -- Information Technology to Assess the Enterprises' Readiness for Innovative Transformations Using Markov Chains -- Method to Find the Original Source of COVID-19 by Genome Sequence and Probability of Electron Capture -- Leader-Follower Strategy of Fixed-Wing Unmanned Aerial Vehicles via Split Rejoin Maneuvers -- Prognostic Assessment of COVID-19 Vaccination Levels.

Abstract: This book contains of 39 scientific papers which include the results of research regarding the current directions in the fields of data mining, machine learning and decision-making. This book is devoted to current problems of artificial and computational intelligence including decision-making systems. Collecting, analysis and processing information are the current directions of modern computer science. Development of new modern information and computer technologies for data analysis and processing in various fields of data mining and machine learning create the conditions for increasing effectiveness of the information processing by both the decrease of time and the increase of accuracy of the data processing. The papers are divided in terms of their topic into three sections. The first section "Analysis and Modeling of Hybrid Systems and Processes" contains of 11 papers, and the second section "Theoretical and Applied Aspects of Decision-Making Systems" contains of 11 ones too. There are 17 papers in the third section "Data Engineering, Computational Intelligence and Inductive Modeling". The book is focused to scientists and developers in the fields of data mining, machine learning and decision-making systems.

Abstract: Methods for Analyzing Cognitive Architecture -- Cognitive Resonance and the Architecture Issues of Cognitive Information Systems -- Dyspraxia: an experimental clinical model for the study of the embodied cognition -- Role of Presence, Memory and Spatial Ability in a Desktop Virtual Reality -- Experiences and guidelines for developing 3D VR curricula.

Abstract: Considering the emergence of artificial intelligence, virtual and augmented reality, 3D video and television, and holography, it is logical that we should also begin to create applications and businesses driven by these technologies. The 12 chapters of Accentuated Innovations in Cognitive Info-Communication focus on the research and development of state-of-the-art information in Cognitive Info-Communication. This interdisciplinary research area has emerged as a synergy between Info-Communication and Cognitive Sciences. It presents a synthetic, holistic combination of coherent technologies that will become increasingly important in the coming decade. It is a teaching and reference guide for VR, robotics, virtual classrooms and institutions, and medicine at the undergraduate and postgraduate levels. The discussed book is an immersive learning experience for students and teachers worldwide. In addition, it applies to other fields such as healthcare, performing arts, and television.

Abstract: This book is of interest to practitioners, researchers and graduate students seeking to apply existing techniques, to learn about the state of the art, or to explore novel concepts, in the theory and application of fuzzy sets and logic. Human knowledge and judgement are essential in both designing technological systems and in evaluating their outcomes. However, humans think and communicate in imprecise concepts, not numbers. Fuzzy sets and logic are well-known, widely used approaches to bridging this gap, which have been studied for nearly 60 years. NAFIPS 2022 brought together researchers studying both the theoretical foundations of fuzzy logic and its application to real-world problems. Their work examined fuzzy solutions to problems as diverse as astronomy, chemical engineering, economics, energy engineering, health care, and transportation engineering. Many papers combined fuzzy logic with interval or probabilistic computing, neural networks, and genetic algorithms.

Abstract: An Introduction to Artificial Intelligence in Healthcare -- Radiomics: Approach to Precision Medicine -- Artificial Intelligence Based Strategies for Data-Driven Radial MRI. .

Abstract: Artificial intelligence (AI) and machine learning (ML) have transformed many standard and conventional methods in undertaking health and well-being issues of humans. AL/ML-based systems and tools play a critical role in this digital and big data era to address a variety of medical and healthcare problems, improving treatments and quality of care for patients. This edition on AI and ML for healthcare consists of two volumes. The first presents selected AI and ML studies on medical imaging and healthcare data analytics, while the second unveils emerging methodologies and trends in AI and ML for delivering better medical treatments and healthcare services in the future. In this first volume, progresses in AI and ML technologies for medical image, video, and signal processing as well as health information and data analytics are presented. These selected studies offer readers theoretical and practical knowledge and ideas pertaining to recent advances in AI and ML for effective and efficient image and data analytics, leading to state-of-the-art AI and ML technologies for advancing the healthcare sector.

Abstract: Future of Work and Work Systems: Machine Learning & Artificial Intelligence for Designing Smart, Safe, Healthy & Ethical Work in Financial Services -- Supporting production management in the fourth industrial revolution: a framework based on shop-floor data -- Perceived Usability in User-Centered Design: Analysis of Usability Aspects for Improving Human-Machine System -- Synthesizing Construction Professionals’ Perceived Measures of Mitigating Contractors’ Opportunism -- Systematic Review of the Relationship between Advanced Production Management and Workplace Safety.

Abstract: This book provides practical guidance and awareness for a growing body of knowledge developing across a variety of disciplines and many countries. This book is a celebration of the Gavriel Salvendy International Symposium (GSIS) and provides a survey of topics and emerging areas of interest in human–automation interaction. This book for the GSIS emphasizes main thematic areas: manufacturing, services and user experience. Main areas of coverage include Section A: Advanced Production Management and Production Control; Section B: Healthcare Automation; Section C: Measuring and Modeling Human Performance; Section D: Usability and User Experience; Section E: Safety Management and Occupational Ergonomics; Section F: Manufacturing and Services; Section G: Data and Probabilistic Information; Section H: Training and Collaboration Technologies. Contributions from especially early career researchers were featured as part of this (virtual) symposium and celebration. Gavriel Salvendy initiated the conferences that run annually as Human–Computer Interaction International and Applied Human Factors and Ergonomics International (AHFE), both within the Lecture Notes in Springer. The book is inclusive of human–computer interaction and human factors and ergonomics principles, yet it is intended to serve a much wider audience that has interest in automation and human modeling. The emerging need for human–automation interaction expertise has developed from an ever-growing availability and presence of automation in our everyday lives. .

Abstract: The seventh Future Technologies Conference 2022 was organized in a hybrid mode. It received a total of 511 submissions from learned scholars, academicians, engineers, scientists and students across many countries. The papers included the wide arena of studies like Computing, Artificial Intelligence, Machine Vision, Ambient Intelligence and Security and their jaw- breaking application to the real world. After a double-blind peer review process 177 submissions have been selected to be included in these proceedings. One of the prominent contributions of this conference is the confluence of distinguished researchers who not only enthralled us by their priceless studies but also paved way for future area of research. The papers provide amicable solutions to many vexing problems across diverse fields. They also are a window to the future world which is completely governed by technology and its multiple applications. We hope that the readers find this volume interesting and inspiring and render their enthusiastic support towards it.

Abstract: This book presents a collection of articles on the advanced and interdisciplinary application of innovative technologies. Scientific investigations and results of the conference 13th Days of Bosnian-Herzegovinian American Academy of Art and Sciences held in Sarajevo, Bosnia and Herzegovina, June 23-26, 2022, are presented in this book. The up-to-date advances in various fields of engineering have been presented through numerous papers spanning the disciplines of civil engineering, mechanical engineering, advanced electrical power systems, computer modeling and simulations for engineering applications, computer science and artificial intelligence, geodesy and geoinformation, data science and geographic information systems and information and communication technologies. The editors would like to extend special gratitude to all the chairs of the planned symposia of the 13th Days of BHAAAS for their dedicated work in the production of this book.

Abstract: This book contains the proceedings of the CIMPS Conference held on October 19-21, 2022, Hipócrates University, Acapulco de Juárez, Guerrero, México, that is dedicated to Software Engineering, in particular, software processes improvement, computer security and communication technology, artificial intelligence and data analysis (big data) with a focus on innovation and/or entrepreneurship, bringing together the academic sectors, governmental and industrial that promote the comprehensive development of a culture of research, innovation and competitiveness of organizations dedicated to and/or that make use of Information and Communication Telecommunications. This book presents software engineering with impact in a combination of different fields: Organizational Models, Standards and Methodologies, Knowledge Management, Software Systems, Applications and Tools, Information and Communication Technologies, Information security, Artificial intelligence, Data Analysis. It is used in different domains in which a broad scope of audience is interested in: • Software engineers • Analyst • Project management • Consultant • Professors in academia • Students • Corporate heads of firms • Senior general managers • Managing directors • Board directors • Academics and researchers in the field both in universities and business schools • Information technology directors and managers • Quality managers and directors • Libraries and information centres serving the needs of the above This book contents are also useful for Ph.D. students, master’s and undergraduate students of IT-related degrees such as Computer Science, Information Systems. .

Abstract: A provincial indicator to describe potential Artificial Intelligence -- Transitions, Harmony and the Mediterranean: the Case of the Harmonic Innovation Hub -- Sustainability in manufacturing. From a model of transition to the transition of the model -- An International Classification of Volunteers Using Artificial Intel-ligence Methods -- A multicriteria approach to the market of electric/hybrid vehicles using TOPSIS method -- Sustainable technologies in urban and architectural renovation of public residential estates -- The contemporaneity of the smart city -- Towards harmonious and sustainable cities.

Abstract: This book aims to deal with the main advances in the study of artificial intelligence, the digital and circular economy and innovation from a multidisciplinary perspective. Whoever governs the artificial intelligence will hold the keys to the world and the future. This consideration explains the growing role of artificial intelligence in our lives and the need to understand its mechanisms. This book presents original research articles addressing various aspects of artificial intelligence applied to economics, law, management, and optimization. The topics discussed include, economics, territorial policies, law, resource allocation strategies, information technology, and learning for inclusion. Combining the input of contributing professors and researchers from Italian and other foreign universities, the book is of interest to students, researchers, and practitioners, as well as members of the public in general, interested in the world of the artificial intelligence and economics. .

Abstract: This book is suitable for researchers and practitioners in biology, medicine and health sciences and bioinformatics. The success of bioinformatics and computational biology in recent years has been driven by research through computational tools and techniques that are essential for data analysis in modern biology and medicine. Systems biology is a related research area that has been replacing the reductionist view that dominated biology research in the last decades, requiring the coordinated efforts of biological researchers with those related to data analysis, mathematical modelling, computer simulation and optimization. The accumulation and exploitation of large-scale databases prompt new computational technology and for research into these issues. In this context, many widely successful computational models and tools used by biologists in these initiatives, such as clustering and classification methods for gene expression data, are based on computer science/ artificial intelligence (CS/AI) techniques. In fact, these methods have been helping in tasks related to knowledge discovery, modelling and optimization tasks, aiming at the development of computational models so that the response of biological complex systems to any perturbation can be predicted. This proceedings of the 16th International Conference on Practical Applications of Computational Biology and Bioinformatics (PACBB), held in L’Aquila (Italy) from July 13 to 15, 2022, contains ten original contributions of authors from many different countries (Bahrain, Canada, France, Italy, Portugal, Saudi Arabia, Spain, and UK) and different subfields in bioinformatics and computational biology. It is also suitable for artificial intelligence researchers interested in exploring applications in biology and health sciences and computational models.

Abstract: Part I: Neuroinformatics and Artificial Intelligence -- Tree Inventory with LiDAR Data -- Towards Reliable Solar Atmospheric Parameters Neural-Based Inference -- Addressing Task Prioritization in Model-based Reinforcement Learning -- Automatic Generation of Conversational Skills from Dialog Datasets -- Part II: Neural Networks and Cognitive Sciences. Adaptive Behavior and Evolutionary Simulation -- Individual Topology Structure of Eye Movement Trajectories -- Neural Network Providing the Involvement of Voluntary Attention into the Processing and Conscious Perception of Sensory Information -- Alpha Rhythm Dynamics During Spoken Word Recognition -- Robotic Devices Control Based on Neuromorphic Classifiers of Imaginary Motor Commands -- A Software System for Training Motor Imagery in Virtual Reality -- On the Importance of Diversity -- “MYO-chat” – A New Computer Control System for People with Disabilities -- Low-bit Quantization of Transformer for Audio Speech Recognition -- A Model of Predicting and Using Regularities by an Autonomous Agent -- A Review of One-Shot Neural Architecture Search Methods -- Does a Recurrent Neural Network Use Reflection During a Reflexive Game? -- A Gender Genetic Algorithm and its Comparison with Conventional Genetic Algorithm -- Associations of Morphometric Changes of the Brain with the Levels of IGF1, a Multifunctional Growth Factor, and with Systemic Immune Parameters Reflect the Disturbances of Neuroimmune Interactions in Patients with Schizophrenia -- Part III: Modern Methods and Technologies in Neurobiology -- Dynamics of Background and Evoked Activity of Neurons in the Auditory Cortex of the Unanaesthetized Cat -- Search for Markers of Moderate Cognitive Disorders through Phase Synchronization between Rhythmic Photostimulus and EEG Pattern -- Astrocytes Enhance Image Representation Encoded in Spiking Neural Network -- Classification of Neuron Type Based on Average Activity -- Comparative Analysis of Statistical and Neural Network Classification Methods on the Example of Synthesized Data in the Stimulus-Independent Brain-Computer Interface Paradigm -- Shunting Effect of Synaptic Channels Located on Presynaptic Terminal -- Analysis of Appearances, Formation and Evolution of Biological Functional Systems -- The Reinforcement Learning Theory, Value Function, and the Nature of Value Function Calculation by the Insular Cortex -- To the Role of Inferior Olives in Cerebellar Neuromechanics -- Individual Differences in Mismatch-Induced c-Fos Expression in the Retrosplenial Cortex in Rats: Shift in Activity is Layer-Specific -- Sleep of Poor and Good Nappers under the Afternoon Exposure to Weak 2-Hz/8-Hz Electromagnetic Fields -- Part IV: Applications of Neural Networks -- Classification of Light Microscopy Image Using Probabilistic Bayesian Neural Network -- SPICE Model of Analog Content-Addressable Memory Based on 2G FeFET Crossbar -- IQ-GAN: Instance Quantized Image Synthesis -- Specifics of Crossbar Resistor Arrays -- Recurrent and Graph Neural Networks for Particle Tracking at the BMN Experiment -- Modeling of a Neural Network Algorithm for Suppressing Non-Stationary Interference in an Adaptive Antenna Array -- Learning Various Locomotion Skills from Scratch with Deep Reinforcement Learning -- Center3dAugNet: Effect of Rotation Representation on One-Stage Joint Car Detection and 6D-Pose Estimation -- Global memory transformer for processing long documents -- Development of the Convolutional Neural Network for Defining the Renal Pathology Using Computed Tomography Images -- Possibility of Using Various Architectures of Convolutional Neural Networks in the Problem of Determining the Type of Rhythm -- DeepPavlov Topics: Topic Classification Dataset for Conversational Domain in English -- Multi-Input Convolutional Neural Networks in Real-Time Semantic Segmentation Tasks -- Integration of Data and Algorithms in Solving Inverse Problems of Spectroscopy of Solutions by Machine Learning Methods -- Investigation of Pareto Front of Neural Network Approximation of Solution of Laplace Equation in Two Statements: with Discontinuous Initial Conditions or with Measurement Data? -- Multitask learning for extensive object description to improve scene understanding on monocular video -- Use of Classification Algorithms to Predict the Grade of Geomagnetic Disturbance -- Information processing in spiking neuron-astrocyte network in ageing -- Multilingual Case-insensitive Named Entity Recognition -- Multi-level Pipeline for Data Mining with Similar Structure -- Creating a Brief Review of Judicial Practice Using Clustering Methods -- Part V: Neural Network Theory, Concepts and Architectures -- "Gas” instead of “Liquid”: which Liquid State Machine is Better? -- Using a Resistor Array to Tackle Optimization Problems -- Generative Adversarial Networks as an Approach to Unsupervised Link Prediction Problem -- DGAC: Dialog Graph AutoConstruction up on Data with a Regular Structure -- Relay System of Differential Equations with Delay as a Perceptron Model -- Analysis of Predictive Capabilities of Adaptive Multilayer Models with Physics-Based Architecture for Duffing Oscillator? -- An Attempt to Formalize the Formulation of the Network Architecture Search Problem for Convolutional Neural Networks -- Use of Conditional Variational Autoencoders and Partial Least Squares in Solving an Inverse Problem of Spectroscopy -- On the Similarities between Denoising Diffusion Models and Autoencoders.

Abstract: This book describes new theories and applications of artificial neural networks, with a special focus on answering questions in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large-scale neural models, brain–computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XXIV International Conference on Neuroinformatics, held on October 17–21, 2022, in Moscow, Russia.

Abstract: This book is a remarkable collection of chapters covering a wide domain of topics related to artificial intelligence and its applications to the real world. The conference attracted a total of 494 submissions from many academic pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer-reviewed process. Of the total submissions, 176 submissions have been selected to be included in these proceedings. It is difficult to imagine how artificial intelligence has become an inseparable part of our life. From mobile phones, smart watches, washing machines to smart homes, smart cars, and smart industries, artificial intelligence has helped to revolutionize the whole globe. As we witness exponential growth of computational intelligence in several directions and use of intelligent systems in everyday applications, this book is an ideal resource for reporting latest innovations and future of AI. Distinguished researchers have made valuable studies to understand the various bottlenecks existing in different arenas and how they can be overcome with the use of intelligent systems. This book also provides new directions and dimensions of future research work. We hope that readers find the volume interesting and valuable.

Abstract: Automatic system based on Riesz MV-algebras, for predictive maintenance of bearings of industrial equipment using temperature sensors -- Smart contracts: A valuable technology in ERP e-commerce systems and for customer experience -- A nursing mobile robot for COVID19 patients using a RPI and mobile device -- Electric vehicles between recycling and sustainable development -- A new way of controlling traffic data inside a Smart City based on IoT devices and communication protocols designed for preserving perfect anonymity -- Research on the storage of integrated pipe corridor monitoring data based on blockchain technology -- Short-Term Covid-19 Incidence Prediction in Countries Using Clustering and Regression Analysis -- Importance of flexibility in design and organizational structure -- Green AI from Kirchhoff to Shannon.

Abstract: The book contains 37 papers presented at the ninth edition of the International Conference of Computers, Communications and Control—ICCCC-2022 held in Oradea and Băile Felix, Romania. A balanced selection of both methodological and application-oriented papers has been made to reflect several recent worldwide trends and results. The book is organized into five sections: a) integrated solutions in computer-based control, b) advanced control systems integrating computers and communications, c) soft computing including fuzzy system approach, d) decision making and support systems, and e) trustworthy and green design. The study of the papers contained in the book is useful for researchers, consultants, and postgraduate students in computer science and design, applied informatics, control systems, and industrial engineering. The book is also used as auxiliary material for student-level courses such as artificial intelligence, computational intelligence, and decision support systems.

Abstract: The seventh Future Technologies Conference 2022 was organized in a hybrid mode. It received a total of 511 submissions from learned scholars, academicians, engineers, scientists and students across many countries. The papers included the wide arena of studies like Computing, Artificial Intelligence, Machine Vision, Ambient Intelligence and Security and their jaw- breaking application to the real world. After a double-blind peer review process 177 submissions have been selected to be included in these proceedings. One of the prominent contributions of this conference is the confluence of distinguished researchers who not only enthralled us by their priceless studies but also paved way for future area of research. The papers provide amicable solutions to many vexing problems across diverse fields. They also are a window to the future world which is completely governed by technology and its multiple applications. We hope that the readers find this volume interesting and inspiring and render their enthusiastic support towards it.

Abstract: Passenger Flow Control in Subway Station with Card-Swiping Data -- On Anomaly Detection in Graphs as Node Classification -- Agriculture Stimulates Chinese GDP: A Machine Learning Approach -- Short Message Service Spam Detection using BERT -- A Study on the Application of Big Data Technology in the Excavation of Intangible Cultural Resources -- Student Achievement Predictive Analytics Based on Educational Data Mining -- Prediction and Analysis of COVID-19's Prevention and Control Based on AnyLogic in the Background of Big Data -- Distributed Multi-source Service Data Stream Processing Technology and Application in Power Grid Dispatching System -- NVLSM: Virtual Split Compaction on Non-volatile Memory in LSM-tree KV Stores -- Evaluation of the Performance Character of SPIRIT Value through Pancasila Education during the Covid-19 Pandemic -- Is it Possible to Instilling Character SPIRIT Values through Civic Education during COVID-19 Pandemic? -- An Adaptive Self-detection and Self-classification Approach Using Matrix Eigenvector Trajectory -- Super-Resolution Virtual Scene of Flight Simulation Based on Convolutional Neural Networks -- User Assignment for Full-Duplex Multi-user System with Distributed Aps -- CDN Service Detection Method Based on Machine Learning -- A Decision Method for Missile Target Allocation -- A Physical Ergonomics Study on Adaptation and Discomfort of Student’s E-Learning in the Philippines during the COVID-19 Pandemic.

Abstract: This book consists of selected and peer-reviewed papers presented at 2022 4th International Conference on Big Data Engineering and Technology (BDET), held during April 22–24, 2022, in Singapore. As IT infrastructure and data management technologies have become critical assets and capabilities for today’s enterprises, this book aims to be part of the effort in contributing to their development. In particular, the BDET conference series aims to provide the much needed forum for researchers and practitioners across the world who are actively engaged in advancing research and raising awareness of the many challenges in the diverse field of big data engineering and technology to share their research outcomes and bounce ideas off their international colleagues. Over the last few years, the conference series has brought together the latest developments of novel theory in big data, algorithm and applications, emerging standards for big data, big data infrastructure, MapReduce and cloud computing, big data visualization, big data curation and management, big data semantics, scientific discovery and intelligence, which collectively form parts of the cyber-physical systems of interest. It is hoped that the book will prove useful to students, researchers, and professionals working in the field of big data engineering and applications in cyber-physical systems.

Abstract: Decidability of real-valued S4 Go¨del logic -- Basic logic versus multi-adjoint logic -- Fuzzy logic programming with generalized quantifiers -- Fuzzy relations: the fundament for fuzzy rough approximation, fuzzy concept analysis and fuzzy mathematical morphology -- Information bireducts and its relationship with reducts -- On the applicability of fuzzy lines in circular Hough transform in lesion segmentation on liver CT images -- Directional properties of semi-aggregation functions -- Generalized Phi-Transform of Aggregation Functions on Bounded Lattices -- Sugeno Integral for Atanassov Intuitionistic Fuzzy Sets -- Facilitating the simulation of domestic energy systems through linguistic representations -- Experiments with the Discrete Bacterial Memetic Evolutionary Algorithm for solving the Cumulative Capacitated Vehicle Routing Problem -- Fuzzy Inference System-like Aggregation Operator (FISAO) for Fuzzy Signatures -- Context of a local congruence concept reduction -- One-sided concept lattices by blocks -- From Fuzzy Partitions to Riemannian Manifolds -- Discrete universal fuzzy integrals -- Energy determined membership function of viscoelastic models -- Advances in forgery detection of driving licences using truthfulness degrees -- A formal method for driver identification -- Analysis and identification of forensic events using non-parametric density estimation -- Fuzzy signature based model in material handling management -- On Choquet integral in ranking crimes -- The Effects of Knowledge Extraction Approaches on Cryptanalysis Studies and Analysis of the Success of Chaos-Based Countermeasures.

Abstract: The recent book of the series continues the collection of articles dealing with the important and efficient combination of traditional and novel mathematical approaches with various computational intelligence techniques, with a stress of fuzzy systems, and fuzzy logic. Complex systems are theoretically intractable, as the need of time and space resources (e.g., computer capacity) exceed any implementable extent. How is it possible that in the practice, such problems are usually manageable with an acceptable quality by human experts? They apply expert domain knowledge and various methods of approximate modeling and corresponding algorithms. Computational intelligence is the mathematical tool box that collects techniques which are able to model such human interaction, while (new) mathematical approaches are developed and used everywhere where the complexity of the sub-task allows it. The innovative approaches in this book give answer to many questions on how to solve “unsolvable” problems.

Abstract: Cross-Cutting Support of Decision Making for Forming Personalized Learning Spaces -- Personalized Learning in an Intelligent Educational System -- Electronic-Service Learning to Sustain Instruction with Civic Engagement during the COVID-19 Pandemic -- Evaluating E-Learning Process on Virtual Classroom Systems using an ISO-based model -- SERVE as instructional design for low-connectivity online self-directed modules -- From Threads to Textiles: Building an Ontology for the Indigenous Fabrics of the Ifugao -- TraCon: A novel dataset for real-time traffic cones detection using deep learning -- A Comparison of Machine Learning Methods for Modeling Dengue Incidence in Local Communities.

Abstract: This book summarizes the research findings presented at the 2nd International Conference on Novel & Intelligent Digital Systems (NiDS 2022). NiDS 2022 was implemented virtually due to COVID-19 restrictions, on September 29-30, 2022, under the auspices of the Institute of Intelligent Systems. NiDS lays special emphasis on the novelties of intelligent systems and on the interdisciplinary research which enables, supports, and enhances artificial intelligence (AI) in software development. It promotes high-quality research, creating a forum for the exploration of challenges and new advances in AI, and addresses experts, researchers, and scholars in the fields of artificial and computational intelligence in systems and in computer sciences in general, enabling them to learn more about pertinent, strongly related, and mutually complementary fields. The conference promotes an exchange of ideas, reinforcing and expanding the network of researchers, academics, and market representatives.

Abstract: Algebraic function induced Banach space valued ordinary and fractional neural network approximations -- Gudermannian function induced Banach space valued ordinary and fractional neural network approximations -- Generalized symmetrical sigmoid function induced Banach space valued ordinary and fractional neural network approximations -- Abstract multivariate algebraic function induced neural network approximations -- General multivariate arctangent function induced neural network approximations -- Abstract multivariate Gudermannian function induced neural network approximations -- Generalized symmetrical sigmoid function induced neural network multivariate approximation -- Quantitative Approximation by Kantorovich-Choquet quasi-interpolation neural network operators revisited -- Quantitative Approximation by Kantorovich-Shilkret quasi-interpolation neural network operators revisited -- Voronsovkaya Univariate and Multivariate asymptotic expansions for sigmoid functions induced quasi-interpolation neural network operators revisited -- Univariate Fuzzy Fractional various sigmoid function activated neural network approximations revisited -- Multivariate Fuzzy Approximation by Neural Network Operators induced by several sigmoid functions revisited -- Multivariate Fuzzy-Random and stochastic various activation functions activated Neural Network Approximations.

Abstract: This book is about the generalization and modernization of approximation by neural network operators. Functions under approximation and the neural networks are Banach space valued. These are induced by a great variety of activation functions deriving from the arctangent, algebraic, Gudermannian, and generalized symmetric sigmoid functions. Ordinary, fractional, fuzzy, and stochastic approximations are exhibited at the univariate, fractional, and multivariate levels. Iterated-sequential approximations are also covered. The book’s results are expected to find applications in the many areas of applied mathematics, computer science and engineering, especially in artificial intelligence and machine learning. Other possible applications can be in applied sciences like statistics, economics, etc. Therefore, this book is suitable for researchers, graduate students, practitioners, and seminars of the above disciplines, also to be in all science and engineering libraries.

Abstract: An Introduction to Federated and Transfer Learning -- Federated Learning for Resource-Constrained IoT Devices: Panoramas and State of the Art -- Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms -- Cross-silo Federated Neural Architecture Search for Heterogeneous and Cooperative Systems -- A Unifying Framework for Federated Learning -- A Contract Theory based Incentive Mechanism for Federated Learning -- A Study of Blockchain-based Federated Learning -- Swarm Meta Learning -- Rethinking Importance Weighting for Transfer Learning -- Transfer Learning via Representation Learning -- Modeling Individual Humans via a Secondary Task Transfer Learning Method -- From Theoretical to Practical Transfer Learning: The Adapt Library -- Lyapunov Robust Constrained-MDPs for Sim2Real Transfer Learning -- A Study on Efficient Reinforcement Learning Through Knowledge Transfer -- Federated Transfer Reinforcement Learning for Autonomous Driving.

Abstract: This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well as its connection with transfer learning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications.

Abstract: Novel Dynamometer: the Gripwise -- Software Configurable Hardware-based Remote Laboratory System -- Software Configurable Hardware-based Remote Laboratory System -- Printed Wearable Accessories For Electrochemical Applications -- AES Hardware Implementation Based On FPGA With Improved Throughput -- The Impact of Digitization on the Romanian Music Therapists -- New Laccase Portable Monitor -- Remote Microelectronics Experimentation based on VISIR Remote Laboratory: Expanding VISIR Functionalities -- Development Of a Simulator Tool For Teaching The Autonomous Vehicles Behavior -- Work in Progress: Hardware Design of a Smart Wristband Used for Epileptic Seizure Detection.

Abstract: Nowadays, online technologies are the core of most fields of engineering and the whole society and are inseparable connected for example with Internet of Things & Industrial Internet of Things (Industry 4.0), Online & Biomedical Engineering, Data Science, Machine Learning, and Artificial Intelligence, Cross & Mixed Reality, and Remote Working Environments. to name only a few. Since the first REV conference in 2004, we tried to focus on the upcoming use of the Internet for engineering tasks and the opportunities as well as challenges around it. Consequently, the motto of this year’s REV2022 was “Artificial Intelligence and Online Engineering”. In a globally connected world, the interest in online collaboration, teleworking, remote services, and other digital working environments is rapidly increasing. In response to that, the general objective of this conference is to contribute and discuss fundamentals, applications, and experiences in the field of Online and Remote Engineering, Virtual Instrumentation and other related new technologies like Cross Reality, Data Science & Big Data, Internet of Things & Industrial Internet of Things, Industry 4.0, Cyber-Security, and M2M & Smart Objects. Another objective of the conference is to discuss guidelines and new concepts for engineering education in higher and vocational education institutions, including emerging technologies in learning, MOOCs & MOOLs, and Open Resources. REV2022 was the 19th in a series of annual events concerning the area of Online Engineering. It has been organized in cooperation with The British University in Egypt (BUE), Cairo, as a hybrid event from February 28 until March 02, 2022.

Abstract: Introduction -- Intelligence Analysis -- Foundations of the computational techniques -- Applying Situation Awareness to Intelligence Analysis -- Decision making through what-if analysis -- System modelling with graphs -- Behaviour modelling with fuzzy signatures -- Concept drift analysis with structures of opposition -- Comparing different approaches for implementing probability based rough set operators -- Data streaming scenarios -- Dealing with continuous variables: neighborhood and dominance based rough sets.

Abstract: This book focuses on the definition and implementation of data-driven computational tools supporting decision-making along heterogeneous intelligence scenarios. Intelligence analysis includes methodologies, activities, and tools aimed at obtaining complex information from a set of isolated data gathered from different sensors. The tools aim at increasing the level of situation awareness of decision-makers through the construction of abstract structures supporting human operators in reasoning and making decisions. This book appeals to students, professionals, and academic researchers in computational intelligence and approximate reasoning applications. It is a comprehensive textbook on the subject, supported with case studies and practical examples in Python. The readers will learn how to define decision support systems for the intelligence analysis through the application of situation awareness and granular computing for information processing. .

Abstract: This book covers the 12th International Conference in Methodologies and Intelligent Systems for Technology Enhanced Learning which was hosted by the University of L'Aquila and was held in L'Aquila (Italy) from July 13 to 15, 2022. The conference has established itself as a consolidated fertile forum where scholars and professionals from the international community, with a broad range of expertise in the TEL field, share results and compare experiences. Technologies in TEL are capable of delivering smart, personalized, tailored, and motivating learning solutions. Methods are coming from different fields, such as education, psychology, medicine, computer science, and from diverse communities, where collaboration and co-working are used.

Abstract: This book contains a selection of papers accepted for presentation and discussion at ROBOT 2022—Fifth Iberian Robotics Conference, held in Zaragoza, Spain, on November 23-25, 2022. ROBOT 2022 is part of a series of conferences that are a joint organization of SEIDROB—Sociedad Española para la Investigación y Desarrollo en Robótica/Spanish Society for Research and Development in Robotics, and SPR—Sociedade Portuguesa de Robótica/Portuguese Society for Robotic. ROBOT 2022 builds upon several previous successful events, including three biennial workshops and the four previous editions of the Iberian Robotics Conference, and is focused on presenting the research and development of new applications, on the field of Robotics, in the Iberian Peninsula, although open to research and delegates from other countries. ROBOT 2022 featured four plenary talks on state-of-the-art subjects on robotics and 15 special sessions, plus a main/general robotics track. In total, after a careful review process, 98 high-quality papers were selected for publication, with a total of 219 unique authors, from 22 countries.

Abstract: This book brings the recent collection of smart technologies. Smart cities challenges and key requirements are discussed through the technological solutions, IoT, cloud computing, block chain and artificial intelligence. Firstly, the key technologies contributing to the smart cities research are identified. Then, the most popular ones are covered in context to their theoretical and practical applications. Smart cities technologies are one of the recent research areas. Every day new technological solutions are coming to make smart cities more sustainable. The book explores the integration of main key technologies for smart cities which are IoT & cloud computing, data science, AI and block chain & Industry 4.0. Moreover, some integrated solutions using AI, data science and IoT will attract the attention of end users. Primary market of the book is aimed toward the undergraduate and master students. IoT, cloud computing, artificial intelligence and block chain are elective courses at the bachelor level in the engineering domain, and its application areas in context to smart cities are covered in this book. The book is a good source of reference for their master dissertations. Ph.D. students or scholars who are working on these key technologies like IoT & cloud, AI, data science, block chain & Industry 4.0 will find this book as a constant source of reference for their ongoing research. Smart city planners, architects and municipal experts may also find this book useful.

Abstract: Introduction to Engineering Applications of Social Welfare -- Routing in Wireless Sensor Networks – Energy Welfare -- Ambulance Dispatching – Preparedness Welfare -- Group Decision Making in Intelligent Shared Environments – Preference Welfare -- Task Allocation in Multi-Robot Systems – Resource Welfare -- Resource Sharing in Cyber-Physical Systems – Utility Welfare -- Conclusion, Limitations, and Research Opportunities.

Abstract: This book presents social welfare functions as a unified multidisciplinary framework for various resource allocation problems. By measuring the impact of local decisions on broader society, social welfare functions enable “socialized” decisions and thereby produce an emergent property that “global” balance and welfare emerge from “local” welfare-maximizing behaviors. Social welfare functions are originally used in economics to quantify income welfare, jointly considering average and inequality to arrive at better measures of welfare than average alone. Wishing the readers to find opportunities for their problems of interest, this book introduces research results of social welfare functions applied in five different engineering applications, defining welfare metrics pertaining to the characteristics of the application. The “energy welfare” in wireless sensor network measures richness of distributed sensors in energy. The “preparedness welfare” in emergency medical services quantifies the preparedness level of an entire service area by aggregating preparedness levels of individual zones. The “preference welfare” in intelligent shared environments represents the opinions of real people for groups. The “resource welfare” in multi-robot task allocation quantifies the efficiency of utilizing distributed resources across robots. The “utility welfare” in complex cyber-physical systems quantifies the impact of local resource sharing decisions on the broader task communities.

Abstract: The book is a collection of high-quality peer-reviewed research papers presented at the 18th International Symposium of Organizational Sciences (SymOrg 2022) held in Belgrade, Serbia, from June 11 to June 14, 2022. The aim of the book is providing stimulative framework for readers to explore viable alternatives and indicate implications for the post-pandemic world. Researchers from academia and industry present their original work focusing on different aspects of sustainable management and digital transformation including blockchain technology, business analytics, e-business, innovation, digital operations and logistics management, financial industry, public administration, lean business systems, digital transformation projects, human resources, marketing and communication, and quality and standardization. The chapters are useful for industry experts, research institutions, universities, and all others who share a common interest in contemporary organizational sciences.

Abstract: Blended Learning in the Foundational Design Studio -- Supporting the Semi-Automatic Feedback Provisioning on Programming Assignments -- A Case Study on Students' Opinions about Adaptive and Classical Tests -- A New Metric to help Teachers Unveil Meaningful Learning in Concept Maps -- Mini-games to motivate and engage users in learning recycling rules -- Effects of VR on Learning Experience and Success -- Educational Code-Review Tool: A First Glimpse -- Automatic Educational Concept Extraction Using NLP -- Design and Computational Thinking with IoTgo: What Teachers Think -- Serious Games for Autism based on Immersive Virtual Reality: a Lens on Methodological and Technological Challenges.

Abstract: The 12th International Conference in Methodologies and Intelligent Systems for Technology Enhanced Learning was hosted by the University of L'Aquila and was held in L'Aquila (Italy) from July 13 to 15, 2022. The conference has established itself as a consolidated fertile forum where scholars and professionals from the international community, with a broad range of expertise in the TEL field, share results and compare experiences Technologies in TEL are capable of delivering smart, personalized, tailored, and motivating learning solutions. Methods are coming from different fields, such as education, psychology, medicine, computer science, and from diverse communities, where collaboration and co-working are used.

Abstract: Question-Answering System over Knowledge Graphs using Analogical-Problem-Solving Approach -- Fuzzy Transform on Manifolds -- Fuzzy Transform on Manifolds -- Freedom of Will, Physics, and Human Intelligence: An Idea -- SDN delay prediction using machine learning algorithms -- Stochastic Simulations of Airborne Particles in a Fibre Matrix -- Similar Vietnamese Document Detection in Online Assignment Submission System -- A Study of Causal Modeling with Time Delay for Frost Forecast Using Machine Learning from Data.

Abstract: This book describes current and potential use of artificial intelligence and computational intelligence techniques in biomedicine and other application areas. Medical applications range from general diagnostics to processing of X-ray images to e-medicine-related privacy issues. Medical community understandably prefers methods that have been successful other on other application areas, where possible mistakes are not that critical. This book describes many promising methods related to deep learning, fuzzy techniques, knowledge graphs, and quantum computing. It also describes the results of testing these new methods in communication networks, education, environmental studies, food industry, retail industry, transportation engineering, and many other areas. This book helps practitioners and researchers to learn more about computational intelligence methods and their biomedical applications—and to further develop this important research direction.

Abstract: Unsupervised Numerical Reasoning to Extract Phenotypes from Clinical Text by Leveraging External Knowledge -- Customized Training of Pretrained Language Models to Detect Post Intents in Online Health Support Groups -- EXPECT-NLP: An Integrated Pipeline and User Interface for Exploring Patient Preferences Directly from Patient-Generated Text.

Abstract: This book aims to highlight the latest achievements in the use of AI and multimodal artificial intelligence in biomedicine and healthcare. Multimodal AI is a relatively new concept in AI, in which different types of data (e.g. text, image, video, audio, and numerical data) are collected, integrated, and processed through a series of intelligence processing algorithms to improve performance. The edited volume contains selected papers presented at the 2022 Health Intelligence workshop and the associated Data Hackathon/Challenge, co-located with the Thirty-Sixth Association for the Advancement of Artificial Intelligence (AAAI) conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. This book provides information for researchers, students, industry professionals, clinicians, and public health agencies interested in the applications of AI and Multimodal AI in public health and medicine.

Abstract: Understanding Risk -- Standard Risk Metrics -- Risk in Digital Assets -- Networks of Risk -- Analyzing Rare Risks -- Humans in the Network.

Abstract: This book presents a foray into the fascinating process of risk management, beginning from classical methods and approaches to understanding risk all the way into cutting-age thinking. Risk management by necessity must lie at the heart of governing our ever more complex digital societies. New phenomena and activities necessitate a new look at how individuals, firms, and states manage the uncertainty they must operate in. Initial chapters provide an introduction to traditional methods and show how they can be built upon to better understand the workings of the modern economy. Later chapters review digital activities and assets like cryptocurrencies showing how such emergent risks can be conceptualized better. Network theory figures prominently and the book demonstrates how it can be used to gauge the risk in the digital sectors of the economy. Predicting the unpredictable black swan events is also discussed in view of a wider adoption of economic simulations. The journey concludes by looking at how individuals perceive risk and make decisions as they operate in a virtual social network. This book interests the academic audience, but it also features insights and novel research results that are relevant for practitioners and policymakers. .

Abstract: A-IDE: A Non-intrusive Cross-platform Development Environment for AVR Programming in Assembly -- Develop a Horizontal Virtual Frame by Adding Field of View Restrictions to Reduce VR Sickness -- Represent Score as the Measurement of User Influence on Twitter -- The Experience of Developing a FAT File System Module in the Rust Programming Language -- Factors Influencing Consumers’ Online Grocery Shopping under the New Normal -- Skeletal Muscle Segmentation at the Third Lumbar Vertebral Level in Radiotherapy CT Images -- Speed-up Single Shot Detector on GPU with CUDA -- An Empirical Study on the Economic Factors Affecting on the Export of Defense Industry Using Hofstede’s Cul-ture Dimension Theory -- A Study on the Application of Blockchain Technology in Non-Governmental Organizations -- Confidential Documents Sharing Model based on Blockchain Environment -- Distance Based Clustering Method for the Wireless Sen-sor Network -- Study on OSINT-based security control monitoring utilization plan -- A Study on the Strategy of SWOT Extraction in the Metavers Platform Review Data : Using NLP Techniques -- Does facial expression accurately reveal true emotion? Evidence from EEG signal -- NSGA-II-AMO: a Faster Genetic Algorithm for QWSCP.

Abstract: This book presents scientific results of the 23rd ACIS International Summer Virtual Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD2022-Summer) which was held on July 4-6, 2022, at Kyoto City, Japan. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications, and tools) of computer and information science and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the best papers from those papers accepted for presentation at the workshop. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 15 of most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science.

Abstract: Natural Language Processing Based on a Text Graph Convolutional Network -- An Alternative Metric to Support Case Base Maintenance in Case-Based Reasoning Processes -- A GAN-BERT Based Approach for Bengali Text Classification with a Few Labeled Examples -- Algorithmic Dependent-Type Theory of Situated Information and Context Assessments -- Delayed and Periodic Execution of Tasks in the Jadescript Programming Language -- Comparison of algorithms for the detection of Plasmodium falciparum: A review of machine learning based approaches -- Proposal for measuring the effectiveness of an intelligent control system for traffic crossings -- A Method to Predict the Relative Performance of Stocks Using Financial Meta-indicators.

Abstract: DCAI 2022 is a forum to present applications of innovative techniques for studying and solving complex problems in artificial intelligence and computing areas. The present edition brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This year’s technical program will present both high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 61 papers were submitted, by authors from 28 different countries representing a truly “wide area network” of research activity. The DCAI’22 technical program has selected 32 full papers and, as in past editions, it will be special issues in ranked journals. This symposium is organized by the University of L'Aquila (Italy). We would like to thank all the contributing authors, the members of the Program Committee and the sponsors (IBM, Indra, Dipartimento di Ingegneria e Scienze dell'Informazione e Matematica dell'Università degli Studi dell'Aquila, Armundia Group, Whitehall Reply, T.C. Technologies And Comunication S.R.L., LCL Industria Grafica, AIR Institute, AEPIA, APPIA).

Abstract: Introduction -- Competitive Analysis of a Potential Digital Workplace Solution for Business Management and Employee Engagement -- The Impact of Chabot’s on Business Strategy -- Technology Entrepreneurship and Innovation -- Applications of Blockchain in the Pharmaceutical Industry -- The perceived value of Internship experience of Entrepreneurship graduates on Entrepreneurial intention -- Design of the Business Model of the Online Platform In Charge -- The digital transformation of the aerospace industry in the Community of Madrid -- Disruptive technologies and businesses -- Conclusion.

Abstract: This book presents the most recent innovations, trends, and challenges in several aspects of Industry 4.0, including the key technologies and business impacts. The book is relevant to a variety of stakeholders due to Industry 4.0’s broad impact in many fields. Topics include digital workplace solutions for employee engagement, entrepreneurship and innovation, and Blockchain for business security. The authors cover Industry 4.0 both from a theoretical and applicable standpoint. Describes Industry 4.0 and its effect on technology, entrepreneurship, and innovation; Presents Industry 4.0’s technological advances, trends, challenges, and their impact on business strategy; Includes information relevant to researchers, professors, students, and professionals interested Industry 4.0.

Abstract: This book presents the latest research on software engineering application in informatics. The fields of software engineering, informatics, computer science, and artificial intelligence are critical for study in the intelligent systems issue space. This is the first part of the refereed proceedings of the 6th Computational Methods in Systems and Software 2022 (CoMeSySo 2022). The CoMeSySo 2022 conference, which is being hosted online, is breaking down barriers. CoMeSySo 2021 aims to provide a worldwide venue for debate of the most recent high-quality research findings.

Abstract: This book brings together the most recent, quality research papers accepted and presented in the 3rd International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2021) held in Antalya, Turkey between 1-3 October 2021. Objective of the content is to provide important and innovative research for developments-improvements within different engineering fields, which are highly interested in using artificial intelligence and applied mathematics. As a collection of the outputs from the ICAIAME 2021, the book is specifically considering research outcomes including advanced use of machine learning and careful problem designs on human-centred aspects. In this context, it aims to provide recent applications for real-world improvements making life easier and more sustainable for especially humans. The book targets the researchers, degree students, and practitioners from both academia and the industry.

Abstract: Vera Angelova, Sensitivity of the nonlinear matrix equation -- Adjoint State Optimization Algorithm for Prediction of Honeybee Population Losses -- Study of time series connected to an innovative window heat transfer system -- Coefficient Identification for SEIR Model and Economic Forecasting in the Propagation of COVID–19 -- Recovering the Time-Dependent Volatility and Interest Rate in European Options from Nonlocal Price Measurements by Adjoint Equation Optimization -- Comparison of four classification methods on small-sample-size synthetic RNA-seq data -- Sensitivity Analysis of a Large-Scale Air Pollution Model by Using Effective Stochastic Approaches -- Two-Way Intuitionistic Fuzzy Analysis of Variance for COVID-19 Cases in Europe by Season and Location Factors -- A Generic Nonlinear Evolution Equation of Magnetic Type I. Reductions.

Abstract: This book gathers the peer-reviewed proceedings of the 15th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM'20, held in Sofia, Bulgaria. The general theme of BGSIAM'20 was industrial and applied mathematics with particular focus on mathematical physics, numerical analysis, high-performance computing, optimization and control, mathematical biology, stochastic modeling, machine learning, digitization and imaging, advanced computing in environmental, and biomedical and engineering applications.

Abstract: Introduction -- AI and Its Wider Impact -- Public Administration and Technology in Malta -- AI Adoption. .

Abstract: The book presents a unique study on the Artificial Intelligence (AI) readiness of public administrations focusing on the Maltese public administration as a case study. This was conducted following the launch of the Malta AI National Strategy in 2019. Since the Maltese public administration is the driving force behind the integration of AI solutions nationwide, the research is deemed necessary to understand whether the public workforce itself is ready to face the oncoming AI revolution. The researchers applied a mixed-methods approach to gain insight and a broader perspective of the status quo concerning AI adoption. Important considerations that stem from this study include the need for increased AI knowledge among public administrators since the majority of respondents reported a lack of awareness of AI technologies and their deployment. Understanding AI-related advantages must be accompanied by a robust instructional effort at all levels of education. It was unanimously agreed that the early inclusion of AI-related courses in the Maltese educational system will aid in developing a future AI-savvy workforce. Furthermore, upskilling and reskilling the public officers will facilitate knowledgeable human capital and proficiencies required to effectively integrate AI solutions within society. The study concludes by recommending several critical reforms within governments that will improve the AI-readiness factor of any Public Administration.

Abstract: A Generic Multicore CPU Parallel Implementation of Fractional Order Digital Image Moment -- Computer-Aided Road Inspection: Systems and Algorithms -- Computer Stereo Vision for Autonomous Driving -- A Survey on GPU-based Visual Trackers -- Accelerating the Process of Copy-Move Forgery Detection using Multi-core CPUs Parallel Architecture -- Parallel Image Processing Applications using Raspberry Pi.

Abstract: This comprehensive book is primarily intended for researchers, computer vision specialists, and high-performance computing specialists who are interested in parallelizing computer vision techniques for the sake of accelerating the run-time of computer vision methods. This book covers different penalization methods on different parallel architectures such as multi-core CPUs and GPUs. It is also a valuable reference resource for researchers at all levels (e.g., undergraduate and postgraduate) who are seeking real-life examples of speeding up the computer vision methods’ run-time.

Abstract: A Review of Multi-Agent Systems used in Industrial Applications -- Alignment of Digital Twin Systems with the RAMI 4.0 Model using Multi-agent Systems -- A Design Process for Holonic Cyber-Physical Systems using the ARTI and BASE Architectures -- A Recommendation Strategy Proposal for an Energy Community Modelled as a Multi-Agent System -- Toward a Hybrid Cloud Sawmill Digital Twin based on Active Learning -- A Digital Twin Generic Architecture for Data-Driven Cyber-Physical Production Systems -- Modelling Manufacturing Systems for Digital Twin through Communicating Finite State Machines -- Challenges of Material Handling System Design in the Context of Industry 4.0 -- Safety Design and Verification in Reconfigurable Assembly Systems -- Designing a Multi Agent Control System for a Reconfigurable Manufacturing System.

Abstract: The scientific theme of the book is “Virtualisation – a multifaceted key enabler of Industry 4.0 from holonic to cloud manufacturing” which is addressed in the framework of cyber-physical system development. The book approaches cyber-physical systems for manufacturing with emergent digital technologies: Internet of Things, digital twins (based on the virtualization of production models embedded in the design, virtual commissioning, optimization and resilience of processes and fault tolerance of resources), big data, cloud control and computing, machine learning and cobots, that are applied in the book’s chapters to industry and service sectors such as manufacturing, energy, logistics, construction and health care. The novelty of this approach consists in interpreting and applying the characteristics of RAMI4.0—the reference architecture model of the Industry 4.0 framework—as combinations of virtualized cyber-physical system elements and IT components in life cycle value stream models. The general scope of the book is to foster innovation in smart and sustainable manufacturing and logistics systems and in this context to promote concepts, methods and solutions for the digital transformation of manufacturing through service orientation in holonic and agent-based control with distributed intelligence. The book’s readership is comprised by researchers and engineers working in the manufacturing value chain area who develop and use digital control solutions in the “Industry of the Future” vision. The book also addresses to master’s and Ph.D. students enrolled in Engineering Sciences programs.

Abstract: Optical Information Cryptosystem Based on Structured Phase Encoding -- Encryption Decryption with Optical Transform -- Optical Cryptosystems Based on Spiral Phase Modulation -- Image Cryptosystem for Different Kinds of Image Using Improved Arnold Map -- Image Encryption Using A Chaotic/Hyperchaotic Multidimensional Discrete System -- Video Cryptosystem Using Chaotic Systems -- Neural Network Image Restoration Techniques.

Abstract: This book provides the readers with a comprehensive overview of principles methodologies and recent advances in image, signal, and video processing using different system. This book is used as the handbook of postgraduates course, such as image processing, signal processing, and optical information security.

Abstract: Part 1: State-of-the-art -- Everyday Cyber Safety for Students -- Machine Learning Approaches for Kids’ E-learning Monitoring -- Factors influencing on online education outcomes– an empirical study based on Kids’ parents -- Review on the Social Media Management Techniques against kids Harmful Information -- Review of Information Security Management Frameworks -- Database Forensics Field and Children Crimes -- From exhibitionism to addiction, or cyber threats among children and adolescents -- Part II: Cyberbullying and Kids cyber security -- Protection of Users Kids on Twitter Platform using Naïve Bayes -- The Impact of Fake News Spread on Social Media on The Children in Indonesia During Covid-19 -- A Preventive Approach to Weapons Detection for Children Using Quantum Deep Learning -- Learning Arabic for Kids online Using Google Classroom -- Child Emotion Recognition Via Custom Lightweight CNN Architecture -- Cybercrime Sentimental Analysis for Child YouTube Video Dataset Using Hybrid Support Vector Machine With Ant Colony Optimization Algorithm -- Cyberbullying Awareness Through Sentiment Analysis Based On Twitter -- The Impact of Fake News on Kid’s Life from the Holy Al-Qur'an Perspective -- Early Prediction of Dyslexia Risk Factors in Kids through Machine Learning Techniques -- Development of Metamodel for Information Security Risk Management -- Detecting Kids Cyberbullying Using Transfer Learning Approach from Transformer Fine-Tuning Models -- YouTube Sentiment Analysis: Performance Model Evaluation.

Abstract: This book introduces and presents the newest up-to-date methods, approaches and technologies on how to detect child cyberbullying on social media as well as monitor kids E-learning, monitor games designed and social media activities for kids. On a daily basis, children are exposed to harmful content online. There have been many attempts to resolve this issue by conducting methods based on rating and ranking as well as reviewing comments to show the relevancy of these videos to children; unfortunately, there still remains a lack of supervision on videos dedicated to kids. This book also introduces a new algorithm for content analysis against harmful information for kids. Furthermore, it establishes the goal to track useful information of kids and institutes detection of kid’s textual aggression through methods of machine and deep learning and natural language processing for a safer space for children on social media and online and to combat problems, such as lack of supervision, cyberbullying, kid’s exposure to harmful content. This book is beneficial to postgraduate students and researchers' concerns on recent methods and approaches to kids' cybersecurity.

Abstract: We are starting to enter a post-COVID-19 life. While this pandemic has made everyone’s life challenging, it also expedited the transition of our everyday lives into a new form, often called “The New Normal.” Although many people often use the terminology, perhaps we still do not have consensus about what it is and what it should be like. However, one thing that is clear namely that robotics and artificial intelligence technologies are playing a critical role in this transition phase of our everyday lives. We saw the emergence of last-mile delivery robots on the street, AI-embedded service robots in restaurants, uninhabited shops, non-face-to-face medical services, conferences and talks in metaverses, and AI-based online education programs. This book is an edition that aims at serving researchers and practitioners in related fields with a timely dissemination of the recent progress in the areas of robotics and artificial intelligence. This book is based on a collection of papers presented at the 10th International Conference on Robot Intelligence Technology and Applications (RiTA), held at Griffith University in the Gold Coast, Queensland, Australia. The conference was held in a hybrid format on December 7–9, 2022, with the main theme “Artificial, Agile, Acute Robot Intelligence.” For better readability, the total of 41 papers are grouped into five chapters: Chapter I: Motion Planning and Control; Chapter II: Vision and Image Processing; Chapter III: Unmanned Aerial Vehicles and Autonomous Vehicles; Chapter IV: Learning and Classification; and Chapter V: Environmental and Societal Robotic Applications. The articles were accepted through a rigorous peer-review process and presented at the RiTA 2022 conference. Also, they were updated, and final versions of the manuscripts were produced after in-depth discussions during the conference. We would like to thank all the authors and editors for contributing to this edition.

Abstract: Bubbling Pressure in Clay Soils as a Physical Quantity and Approximation Parameter -- Geodetic Observations of Building Settlings on Weak Water-Saturated Clay Soils -- Paleogeography of the Black and Azov Seas and Their Coasts in Pleistocene and Holocene (Within the Krasnodar Region of Russia) -- Methodology for Developing a Geoinformation Project for Rational Nature Management of the Land and Property Complex of Russian Northern Territories -- The Pyrological Situation in the Steppe Regions of North Eurasia and Adjacent Territories: FIRMS Data Analysis for the Multi-year Period -- The Ecological State of Vegetation in Urban Areas of Various Administrative Districts of Ulan-Ude: A Comprehensive Assessment -- Territorial Features of Manifesting Hazardous Hydrological Phenomena in the Altai Republic -- Synanthropization and Species Diversity of Floodplain Ecosystems of the Ob-Irtysh Basin -- Assessment of Surface Water Quality in the Markha River Basin on the Territory of the Nyurba Ulus (District) of the Republic of Sakha (Yakutia) -- A Fractal Character of the Multidimensional Ecological Niche: Formation in Real Habitats in South Trans Urals. .

Abstract: This book enables readers to develop a multidisciplinary understanding of natural, human-made, and coupled human-natural systems. The authors explore the structure, function, and dynamic mechanisms of various systems, both natural and human-made, as well as analyze their reciprocal interactions under the concept of “coupled human-natural systems.” The chapters challenge traditional planning and management assumptions and strategies for natural resources, human-altered systems, and the environment. Acknowledging the critical role of effective regulations, policies, and governance structures, the authors analyze advanced research and practices on policy design for managing natural, human-made, and coupled human-natural systems. They conduct impact evaluation and integrative ecosystems assessment, as well as discuss policy interventions and decision-making strategies. They acknowledge the localization of policy design, considering regional and global dynamics that shape responses of local human-made and coupled human-natural systems. A special collection of chapters analyzes legal foundations for sustainable development and strong institution. The authors explore models from both natural and social sciences to obtain and present significant research results. The book is a dispensable source of sustainability research and practice in human-made, natural, and coupled human-natural systems. It is for the scholars, practitioners, and advanced graduate students interested in systems theories, methodologies, and applications.

Abstract: Computational Thinking Design Application for STEAM Education -- Education Data for Science: Case of Lithuania -- Imbalanced Data Classification Approach Based on Clustered Training Set -- Baltic States in Global Value Chains: Quantifying International Production Sharing at Bilateral and Sectoral Levels -- The Soft Power Of Understanding Social Media Dynamics: A Data-Driven Approach -- Bootstrapping Network Autoregressive Models for Testing Linearity -- Novel data science methodologies for essential genes identification based on network analysis -- Acoustic Analysis for Vocal Fold Assessment - Challenges, Trends, and Opportunities -- The Paradigm of an Explainable Artificial Intelligence (XAI) and Data Science (DS) Based Decision Support System (DSS) -- Stock Portfolio Risk-Return Ratio Optimisation using Grey Wolf Model -- Towards Seamless Execution of Deep Learning Application on Heterogeneous HPC Systems.

Abstract: This book provides an overview of a wide range of relevant applications and reveals how to solve them. Many of the latest applications in finance, technology, education, medicine and other important and relevant fields are data-driven. The volumes of data are enormous. Specific methods need to be developed or adapted to solve a particular problem. It illustrates data science in applications. These applications have in common the discovery of knowledge in data and the use of this knowledge to make real decisions. The set of examples presented serves as a recipe book for their direct application to similar problems or as a guide for the development of new, more sophisticated approaches. The intended readership is data scientists looking for appropriate solutions to their problems. In addition, the examples provided serves as material for lectures at universities.

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 interconnections 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 volume covers the theory, design and applications of computer networks, distributed computing and information systems. The aim of the volume “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 -- (Rational) Individual Decision Making: Main Ideas -- (Rational) Group Decision Making: General Formulas and a New Simplified Derivation of These Formulas -- How We Can Control Group Decision Making By Modifying the Proposed Options -- The Fact That We Can Only Have Approximate Estimates Explains Why Buying and Selling Prices Are Different -- The “No Trade Theorem” Paradox -- People Make Decisions Based on Clusters Containing Actual Values -- When Revolutions Succeed -- How People Combine Utility Values -- Biased Perception of Time -- Few-Parametric Spatial Models and How They Explain Bhutan Landscape Anomaly -- Dynamic Triggering of Earthquakes -- Applications to Computing: Representing Functions in Quantum -- and Reversible Computing.

Abstract: This book describes new techniques for making decisions in situations with uncertainty and new applications of decision-making techniques. The main emphasis is on situations when it is difficult to decrease uncertainty. For example, it is very difficult to accurately predict human economic behavior, so in economics, it is very important to take this uncertainty into account when making decisions. Other areas where it is difficult to decrease uncertainty are geosciences and teaching. The book analyzes the general problem of decision making and shows how its results can be applied to economics, geosciences, and teaching. Since all these applications involve computing, the book also shows how these results can be applied to computing, including deep learning and quantum computing. The book is recommended to researchers, practitioners, and students who want to learn more about decision making under uncertainty—and who want to work on remaining challenges.

Abstract: Advances in the use of artificial intelligence and sensor technologies for managing industrial workplace safety -- Implementation of deep learning to prevent peak-driven power outages within manufacturing systems -- Reproductive autonomy conformity assessment of purposed AI system -- The projects evaluation and selection by using MCDM and intuitionistic fuzzy sets -- Cost effectiveness analysis of real and in silico clinical trials for stent deployment based on decision tree.

Abstract: The book is covering knowledge and results in theory, methodology, and applications of artificial intelligence and machine learning in academia and industry. Nowadays, artificial intelligence has been used in every company where intelligence elements are embedded inside sensors, devices, machines, computers and networks. The chapters in this book integrated approach toward global exchange of information on technological advances, scientific innovations, and the effectiveness of various regulatory programs toward AI application in medicine, biology, chemistry, financial, games, law, and engineering. Readers can find AI application in industrial workplace safety, manufacturing systems, medical imaging, biomedical engineering application, different computational paradigm, COVID-19, liver tracking, drug delivery system, and cost-effectiveness analysis. Real examples from academia and industry give beyond state of the art for application of AI and ML in different areas. These chapters are extended papers from the First Serbian International Conference on Applied Artificial Intelligence (SICAAI), which was held in Kragujevac, Serbia, on May 19–20, 2022.

Abstract: Chapter 1: Application of interval type-2 fuzzy logic control approach to the lower-limb exoskeleton -- Chapter 2: A Simplified Model of an Interval Type-2 Takagi-Sugeno Fuzzy PID Controller using 1- D Input Space -- Chapter 3: Fractional order Type-2 fuzzy Logic controllers -- Chapter 4: Artificial Bee Colony Optimized a new Precompensated Interval Type-2 Fuzzy Logic Controller for a Magnetic Levitation System -- Chapter 5: Application of Type-2 Fuzzy Logic Controllers in Renewable Energy Systems. .

Abstract: This book covers the introduction, theory, development and applications of type-2 fuzzy logic systems, which represent the current state-of-the-art in various domains such as control applications, power plants, health care, image processing, mathematical applications etc. The book is also rich in discussing different applications in order to give the researchers a flavor of how type-2 fuzzy logic is designed for different types of problems. Type-2 fuzzy logic systems are now used extensively in engineering applications for many purposes. In simple language, this book covers the practical use of type-2 fuzzy logic and its optimization through different training methods. Furthermore, this book maintains the relationship between mathematics and practical implementations in the real world. This book chapter also contains the proper comparisons with available literature work. It shows that the presented enhanced techniques have better results. This book would serve as a handy reference guide for a variety of readers, primarily targeting research scholars, undergraduate and postgraduate researchers and practicing engineers working in Type-2 fuzzy logic systems and their applications. .

Abstract: The book (proceedings of the 4th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR) 2022) introduces key topics from artificial intelligence algorithms and programming organisations and explains how they contribute to health care, manufacturing, law, finance, retail, real estate, accountancy, digital marketing, and various other fields. Although artificial intelligence (AI) has generated a lot of hype over the past ten years, these consequences on how we live, work, and play are still in their infancy and will likely have a significant impact in the future. The supremacy of AI in areas like speech and picture recognition, navigational apps, personal assistants for smartphones, ride-sharing apps, and many other areas is already well established. The book is primarily meant for academics, researchers, and engineers who want to employ AI applications to address real-world issues. The authors hope that businesses and technology creators will also find it appealing to utilise in industry. .

Abstract: Critical Infrastructures Resilience in the Context of a Physical Protection System -- Smart City Security based on Meta-Security Framework for Digital Twins -- On-Premise Artificial Intelligence as a Service for Small and Medium Size Setups -- Incentives in Surplus Food Distribution for Smart Cities and Beyond: An Activity Aware Solution -- Evaluation of Smart Charging Integrated with Smart Energy Management and Advance Booking in an eMobility Urban Living Lab -- Vehicle Allocation Algorithm Improving User Satisfaction in Ride -- A City Airspace Testbed for Drone Networks in Future Smart Cities -- A Feasibility Study of Tethered Autonomous Moving Cells for Smart City -- Relationship among Different Types of Input and Model Accuracies in LSTM Driver Models. Watch-from-inside: 3D sensing system to monitor the outside from inside -- Federated Learning with Client Selection in Resource-uncertain Wireless Networks: Simulation and Proof of Concept Experiments.

Abstract: This book presents advances on the state of the art in smart cities systems and applications based on the proof of concept and prototyping for smart cities in an interdisciplinary context of engineering and information sciences. Smart cities have emerged as highly complex technological endeavors that combine knowledge and technology from many disciplines ranging from information sciences to engineering. Due to their complex nature, the modeling, development, and prototyping of applications in smart cities present a myriad of challenges, including technical, economic, and social ones, across application subdomains such as smart transportation, social welfare, tourism, and smart industry. It becomes difficult or sometimes impossible to provide a solution for such potential research issues and challenges from a traditional disciplinary-approach only; to tackle such research issues and to make the paradigm of smart cities a reality, interdisciplinary approaches are deemed necessary. Readers, developers, practitioners, and policy-makers in the field find in the book insights, experiences, findings, and perspectives on smart cities applications with an emphasis on real-life prototyping, beyond the confines of laboratory experiments.

Abstract: The latest advancements in software engineering are featured in this book, which contains the refereed proceedings of the part of the 12th Computer Science Online Conference 2023 (CSOC 2023), held online in April 2023. The software engineering research in system science session is focusing on the importance of software engineering in the field of system science. This section provides a platform for researchers to share their insights on modern research methodologies, machine learning, and statistical learning techniques in software engineering research. The session provides a unique opportunity for researchers and industry experts to explore the latest trends in software engineering and inspire future research directions. This session brings together experts from different fields to present their research and discuss the latest challenges and opportunities. One of the key themes of this session is the application of artificial intelligence in software engineering. Researchers are exploring how techniques can be used to automate various aspects of software engineering, such as testing, debugging, and maintenance. This helps improve the quality and efficiency of software development processes.

Abstract: Opinion Mining on Paul W. S. Anderson’s Monster Hunter from Chinese Social Media Using Sentiment Analysis -- Kevin Kwan’s Crazy Rich Asians: Opinion Mining and Emotion Detection on Fans' Comments on Social Media -- Voltage Profile Improvement and Active Power Loss Reduction Through Network Reconfiguration Using Dingo Optimizer -- Machine Learning and Marketing Campaign: Innovative Approaches and Creative Techniques for Increasing Efficiency and Profit -- A Bottom-up 2-Stage Approach for Constructing Arabic Knowledge Graph -- Augmented Reality as a Learning Media to Improve Vocabulary Learning Among Preschoolers -- Towards the Prediction of Students’ Performance Using Educators’ Domain Knowledge -- Learners’ Performance Evaluation Using Genetic Algorithms -- Tomato Plant Leaf Disease Identification and Classification Using Deep Learning -- Using Deep Learning for the Detection of Ocular Diseases Caused by Diabetes -- Intelligent Chatbots for Electronic Commerce: A Customer Perspective -- A Hybrid Sentiment based SVM with Metaheuristic Algorithms for Cryptocurrency Forecasting -- A Comparison Study of Machine Learning Algorithms for Credit Risk Prediction -- Forecasting Tourist Arrivals using a Combination of Long Short-Term Memory and Fourier Series -- Age and Gender Classification from Retinal Fundus Using Deep Learning -- Heart Disease Prediction Using a group of Machine and Deep Learning Algorithms -- Tweet Recommendation System Based on TA Algorithm and Natural Language Processing -- Deep Learning Based for Cryptocurrency Assistive System.

Abstract: This book presents the papers included in the proceedings of the 3rd International Conference of Advanced Computing and Informatics (ICACin’22) that was held in Casablanca, Morocco, on October 15–16, 2022. A total of 98 papers were submitted to the conference, but only 60 papers were accepted and published in this book with an acceptance rate of 61%. The book presents several hot research topics which include artificial intelligence and data science, big data analytics, Internet of Things (IoT) and smart cities, information security, cloud computing and networking, and computational informatics.

Abstract: This book is composed by the papers written in English and accepted for presentation and discussion at The 2023 International Conference on Information Technology & Systems (ICITS'23), held at Universidad Nacional de San Antonio Abad del Cusco, in Cusco, Peru, between the 24th and the 26th of April 2023. ICIST is a global forum for researchers and practitioners to present and discuss recent findings and innovations, current trends, professional experiences and challenges of modern information technology and systems research, together with their technological development and applications. The main topics covered are: information and knowledge management; organizational models and information systems; software and systems modelling; software systems, architectures, applications and tools; multimedia systems and applications; computer networks, mobility and pervasive systems; intelligent and decision support systems; big data analytics and applications; human–computer interaction; ethics, computers & security; health informatics; information technologies in education, and Media, Applied Technology and Communication. .

Abstract: Overview of the Book -- Causal Inference Preliminary -- Causal Effect Estimation: Basic Methodologies -- Causal Inference on Graphs -- Causal Effect Estimation: Recent Progress, Challenges, and Opportunities -- Fair Machine Learning Through the Lens of Causality -- Causal Explainable AI -- Causal Domain Generalization -- Causal Inference and Natural Language Processing -- Causal Inference and Recommendations -- Causality Encourage the Identifiability of Instance-Dependent Label Noise -- Causal Interventional Time Series Forecasting on Multi-horizon and Multi-series Data -- Continual Causal Effect Estimation -- Summary.

Abstract: This book provides a deep understanding of the relationship between machine learning and causal inference. It covers a broad range of topics, starting with the preliminary foundations of causal inference, which include basic definitions, illustrative examples, and assumptions. It then delves into the different types of classical causal inference methods, such as matching, weighting, tree-based models, and more. Additionally, the book explores how machine learning can be used for causal effect estimation based on representation learning and graph learning. The contribution of causal inference in creating trustworthy machine learning systems to accomplish diversity, non-discrimination and fairness, transparency and explainability, generalization and robustness, and more is also discussed. The book also provides practical applications of causal inference in various domains such as natural language processing, recommender systems, computer vision, time series forecasting, and continual learning. Each chapter of the book is written by leading researchers in their respective fields. Machine Learning for Causal Inference explores the challenges associated with the relationship between machine learning and causal inference, such as biased estimates of causal effects, untrustworthy models, and complicated applications in other artificial intelligence domains. However, it also presents potential solutions to these issues. The book is a valuable resource for researchers, teachers, practitioners, and students interested in these fields. It provides insights into how combining machine learning and causal inference can improve the system's capability to accomplish causal artificial intelligence based on data. The book showcases promising research directions and emphasizes the importance of understanding the causal relationship to construct different machine-learning models from data.

Abstract: Foundations of Decision -- Technique for Order Preferences by Similarity to Ideal Solutions (TOPSIS) in uncertainty environment -- The Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) in uncertainty environment -- The Multi-Objective Optimization Ratio Analysis (MOORA) in uncertainty environment.

Abstract: Authored by a leading expert in the field, this book introduces an innovative methodology that harnesses the power of fuzzy logic to enhance decision-making in multi-attribute scenarios. In a world of complexity and uncertainty, effective decision-making is paramount. Springer proudly presents a cutting-edge publication that revolutionizes decision analysis: "Fuzzy Decision Analysis: Multi-attribute Decision-Making Approach." This book stands at the forefront of decision analysis, introducing the integration of fuzzy logic into multi-attribute decision-making. It is a transformative journey into the realm of advanced decision analysis. It book not only equips you with the knowledge to comprehend the theoretical underpinnings but also empowers you to apply these insights in practical scenarios. This book serves as your indispensable companion. Its comprehensive coverage serves as a beacon, guiding you through the intricate maze of fuzzy logic and multi-attribute decision-making, ultimately empowering you to embrace innovation and master the art of making well-informed decisions in an ever-changing world.

Abstract: ew Media Arts – the Thinking Space for Digitality -- Pick my brain: Thoughts on anatomical representations of the human inner body from renaissance, baroque paintings, and book illustrations of the Modern Age to current medical imaging visualizations -- A Framework of Networked Art as a Diagram that is an Image as a Map that is a Plan and that is a Space as a Territory. .

Abstract: This book of 21 chapters shares endeavors associated to the human trait of creative expression within, across, and between digital media in wide-ranging contexts making the contents perfect as a course study book uptake within related educations. Globally located chapter authors share their comprehensive artisan perspectives from works associated with regional cultures, diversities of interpretations, and widespread scopes of meanings. Contents illustrate contemporary works reflecting thought-provoking comprehensions, functions, and purposes, posit as contributing toward shifting of boundaries within the field. Original to this approach is the reflective offerings on creating digitally beyond typical psychological analysis/rapportage. The book's general scope and key uses are thus to contribute to scholarly discussions toward informing future projects by having an intended wide readership including from within educations, to artisans, and wider interested public. Chapter 7 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Abstract: Part I: Core Problems -- Chapter 1: Neural Network Models for Time Series Data -- Chapter 2: Self-Supervised Learning from Unlabeled IoT Data -- Chapter 3: On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models -- Chapter 4: Out of Distribution Detection -- Chapter 5: Model Compression for Edge Computing -- Part II: Distributed Problems -- Chapter 6: Communication Efficient Distributed Learning -- Chapter 7: Coreset-based Data Reduction for Machine Learning at the Edge -- Chapter 8: Lightweight Collaborative Perception at the Edge -- Chapter 9: Dynamic Placement of Services at the Edge -- Chapter 10: Joint Service Placement and Request Scheduling at the Edge -- Part III: Cross-cutting Thoughts -- Chapter 11: Criticality-based Data Segmentation and Resource Allocation in Machine Inference Pipelines -- Chapter 12: Model Operationalization at Edge Devices.

Abstract: It is undeniable that the recent revival of artificial intelligence (AI) has significantly changed the landscape of science in many application domains, ranging from health to defense and from conversational interfaces to autonomous cars. With terms such as “Google Home”, “Alexa”, and “ChatGPT” becoming household names, the pervasive societal impact of AI is clear. Advances in AI promise a revolution in our interaction with the physical world, a domain where computational intelligence has always been envisioned as a transformative force toward a better tomorrow. Depending on the application family, this domain is often referred to as Ubiquitous Computing, Cyber-Physical Computing, or the Internet of Things. The underlying vision is driven by the proliferation of cheap embedded computing hardware that can be integrated easily into myriads of everyday devices from consumer electronics, such as personal wearables and smart household appliances, to city infrastructure and industrial process control systems. One common trait across these applications is that the data that the application operates on come directly (typically via sensors) from the physical world. Thus, from the perspective of communication network infrastructure, the data originate at the network edge. From a performance standpoint, there is an argument to be made that such data should be processed at the point of collection. Hence, a need arises for Edge AI -- a genre of AI where the inference, and sometimes even the training, are performed at the point of need, meaning at the edge where the data originate. The book is broken down into three parts: core problems, distributed problems, and other cross-cutting issues. It explores the challenges arising in Edge AI contexts. Some of these challenges (such as neural network model reduction to fit resource-constrained hardware) are unique to the edge environment. They need a novel category of solutions that do not parallel more typical concerns in mainstream AI. Others are adaptations of mainstream AI challenges to the edge space. An example is overcoming the cost of data labeling. The labeling problem is pervasive, but its solution in the IoT application context is different from other contexts. This book is not a survey of the state of the art. With thousands of publications appearing in AI every year, such a survey is doomed to be incomplete on arrival. It is also not a comprehensive coverage of all the problems in the space of Edge AI. Different applications pose different challenges, and a more comprehensive coverage should be more application specific. Instead, this book covers some of the more endemic challenges across the range of IoT/CPS applications. To offer coverage in some depth, we opt to cover mainly one or a few representative solutions for each of these endemic challenges in sufficient detail, rather that broadly touching on all relevant prior work. The underlying philosophy is one of illustrating by example. The solutions are curated to offer insight into a way of thinking that characterizes Edge AI research and distinguishes its solutions from their more mainstream counterparts.

Abstract: A Literature-Based Perspective on Human-Centered Design and Evaluation of Interfaces for Virtual Reality in Robotics -- A Multi-Modal Feedback Communication Interface for Human Working Posture Adjustments -- An Optimal Human-Based Control Approach for Mobile Human-Robot Collaboration -- Approximating Robot Reachable Space Using Convex Polytopes -- Complexity and Similarity Metrics for Unsupervised Identification of Programming Methods for Robot Cooking Tasks -- Damping Design for Robot Manipulators.

Abstract: This book contains seventeen contributions in the form of independent chapters, covering a broad range of topics related to human–robot interaction at physical and cognitive levels. Each chapter represents a novel piece of work presented during HFR 2022 by researchers in the different areas of robotics, where new theories, methodologies, technologies, challenges, and empirical and experimental studies are discussed. Additionally, this compilation is rich in viewpoints due to the multidisciplinary nature of its authors. Hence, this book represents an excellent opportunity for academics, researchers, and industry partners to get acquainted with the most recent work on human–robot interaction.

Abstract: This book presents the latest research on Ambient Intelligence including software and applications. Ambient Intelligence (AmI) is a paradigm emerging from Artificial Intelligence, where computers are used as proactive tools assisting people with their day-to-day activities, making everyone’s life more comfortable. The inclusion of computational power and communication technologies in everyday objects is growing, and their embedding into our environments should be as invisible as possible. In order for AmI to be successful, human interaction with computing power and embedded systems in the surroundings should be smooth and happen without people actually noticing it. The only awareness people should have arises from AmI: more safety, comfort and wellbeing, emerging in a natural and inherent way. ISAmI is the International Symposium on Ambient Intelligence, aiming to bring together researchers from various disciplines that constitute the scientific field of AmI to present and discuss the latest results, new ideas, projects and lessons learned.

Abstract: symKrypt: A Lightweight Symmetric-Key Cryptography for Diverse Applications -- PK-BERT: Knowledge Enhanced Pre-trained Models with Prompt for Few-shot Learning -- Typhoon Track Prediction Based on TimeForce CNN-LSTM Hybrid Model -- The Novel Characterizing Method of Collective Behavior Pattern in PSO -- Research on Box Office Prediction of Commercial Films Based on Internet Search Index and Multilayer Perceptron -- A DCRC Model For Text Classification -- Hierarchical Medical Classification based on DLCF -- Noise Detection and Classification in Chagasic ECG Signals based on One-Dimensional Convolutional Neural Networks -- Based on the analysis of interrelation between parallel distributed computer system and network -- Improvement of DGA Long Tail Problem Based on Transfer Learning -- A Phonetics and Semantics-Based Chinese Short Text Fusion Algorithm -- Feature Extension for Chinese Short Text Based on Tongyici Cilin -- Task-Level Consistency Semi-Supervised Based Domain Adaptation for Lung Nodules Segmentation -- Malaria Blood Smears Object Detection based on Convolutional DCGAN and CNN Deep Learning Architectures.

Abstract: This book presents scientific results of the 22nd IEEE/ACIS International Conference on Computer and Information Science (ICIS 2022) held on June 26-28, 2022 in Zhuhai China. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications, and tools) of computer and information science and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the best papers from those papers accepted for presentation at the conference. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 14 of the conference’s most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science.

Abstract: Part I: Fundamentals and Backgrounds -- Evolutionary Computation -- Deep Neural Networks -- Part II: Evolutionary Deep Neural Architecture Search for Unsupervised DNNs -- Architecture Design for Stacked AEs and DBNs -- Architecture Design for Convolutional Auto-Encoders -- Architecture Design for Variational Auto-Encoders -- Part III: Evolutionary Deep Neural Architecture Search for Supervised DNNs -- Architecture Design for Plain CNNs -- Architecture Design for RBs and DBs Based CNNs -- Architecture Design for Skip-Connection Based CNNs -- Hybrid GA and PSO for Architecture Design -- Internet Protocol Based Architecture Design -- Differential Evolution for Architecture Design -- Architecture Design for Analyzing Hyperspectral Images -- Part IV: Recent Advances in Evolutionary Deep Neural Architecture Search -- Encoding Space Based on Directed Acyclic Graphs -- End-to-End Performance Predictors -- Deep Neural Architecture Pruning -- Deep Neural Architecture Compression -- Distribution Training Framework for Architecture Design.

Abstract: This book systematically narrates the fundamentals, methods, and recent advances of evolutionary deep neural architecture search chapter by chapter. This will provide the target readers with sufficient details learning from scratch. In particular, the method parts are devoted to the architecture search of unsupervised and supervised deep neural networks. The people, who would like to use deep neural networks but have no/limited expertise in manually designing the optimal deep architectures, will be the main audience. This may include the researchers who focus on developing novel evolutionary deep architecture search methods for general tasks, the students who would like to study the knowledge related to evolutionary deep neural architecture search and perform related research in the future, and the practitioners from the fields of computer vision, natural language processing, and others where the deep neural networks have been successfully and largely used in their respective fields.

Abstract: Reversible Data Hiding in Encrypted Image Based on MSB Inversion -- Comments on the Visual Binary QR Code -- NLP-based Hardware Solution for Censoring Audio on Over-the-top (OTT) Media Services -- Efficient Steganographic Method Based on Modulo Cube -- Reversible Data Hiding Based on Bidirectional Generalized Integer Transform -- An RFID Ownership Transfer based on Multiple Owners with Different Weights -- Fuzzy C-Means based Feature Selection Mechanism for Wireless Intrusion Detection -- Real Time Drowsiness Detection Based on Facial Dynamic Features -- Collision Avoidance in Crowded Zone using Adversarial Reinforcement Learning -- Reconfigurable PM2.5 Sensor Green Deployment Mechanism Based on Blockchain Technology.

Abstract: This book aims to attract researchers and practitioners who are working in information technology and computer science. This edited book is about basics and high-level concepts regarding blockchain technology and application, multimedia security, information processing, security of network, cloud and IoT, cryptography and information hiding, cyber-security and evidence investigations, and learning and intelligent computing. It is becoming increasingly important to develop adaptive, intelligent computing-centric, energy-aware, secure, and privacy-aware mechanisms in high-performance computing and IoT applications. The book serves as a useful guide for industry persons and also helps beginners to learn things from basic to advance in the area of better computing paradigm. Our aim is intended to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research results in security-related areas. We believe that this book not only presents novel and interesting ideas but also will stimulate interesting discussions from the participants and inspire new ideas.

Abstract: ECG Signal Classification Based on Neural Network -- A Review of Long Short-Term Memory Approach for Time Series Analysis and Forecasting -- Applying Modified LBP For 2D ECG Images Classification -- Integrating Ontology with Imaging and Artificial Vision for a High-Level Semantic: A Review -- Agent-Based Simulations for Aircraft Boarding: A Critical Review -- Adaptive Systems and Materials Technologies in Civil Engineering: A review -- A New Method for EEG signals Classification Based on RBF NN -- Intelligent Fault Detection of Rotating Machinery Using Long-Short-Term Memory (LSTM) Network -- What People Post During the Movement Control Order (MCO): A Content Analysis of Instagram’s Top Posts -- A Comparative Study on the Recognition of English and Arabic Handwritten Digits Based on the Combination of Transfer Learning and Classifier.

Abstract: This book sheds light on the recent research directions in intelligent systems and their applications. It involves four main themes: artificial intelligence and data science, recent trends in software engineering, emerging technologies in education, and intelligent health informatics. The discussion of the most recent designs, advancements, and modifications of intelligent systems, as well as their applications, is a key component of the chapters contributed to the aforementioned subjects.

Abstract: Empirical Comparison of Heuristic Optimisation Methods for Automated Car Setup -- Metaheuristic algorithms in IoT: Optimized Edge Node Localization -- Jaya algorithm versus differential evolution: a comparative case study on optic disc localization in eye fundus images -- Minimum transmission power control for the Internet of Things with swarm intelligence algorithms -- An Enhanced Gradient Based Optimized Controller for Load Frequency Control of a Two Area Automatic Generation Control System -- A meta-heuristic algorithm based on the happiness model -- Application of Metaheuristic Techniques for Enhancing the Financial Profitability of Wind Power Generation Systems -- Optimization of Demand Response -- Fitting curves of ruminal degradation using a metaheuristic approach -- Optimizing a Real Case Assembly Line Balancing Problem Using Various Techniques -- Multi-Circle Detection Using Multimodal Optimization.

Abstract: This book is a collection of various methodologies that make it possible for metaheuristics and hyper-heuristics to solve problems that occur in the real world. This book contains chapters that make use of metaheuristics techniques. The application fields range from image processing to transmission power control, and case studies and literature reviews are included to assist the reader. Furthermore, some chapters present cutting-edge methods for load frequency control and IoT implementations. In this sense, the book offers both theoretical and practical contents in the form of metaheuristic algorithms. The researchers used several stochastic optimization methods in this book, including evolutionary algorithms and Swarm-based algorithms. The chapters were written from a scientific standpoint. As a result, the book is primarily aimed at undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics, but it can also be used in courses on Artificial Intelligence, among other things. Similarly, the material may be beneficial to research in evolutionary computation and artificial intelligence communities.

Abstract: This book presents many valuable tips for making decisions related to traffic flow in transport networks. The knowledge base in practical examples, as well as the decision support systems described in this book, finds interest among people who face the daily challenge of searching for advanced solutions and practical applications in road traffic engineering. The publication is therefore addressed to local authorities related to the planning and development of development strategies for selected areas with regard to transport (both in the urban and regional dimension) and to representatives of business and industry, as people directly involved in the implementation of traffic engineering solutions. The publication contains selected papers submitted to and presented at the 18th “Transport Systems. Theory and Practice” Scientific and Technical Conference organized by the Department of Transport Systems, Traffic Engineering and Logistics at the Faculty of Transport and Aviation Engineering at the Silesian University of Technology. The conference took place on September 19-20, 2022, in Katowice (Poland).

Abstract: This book constitutes the refereed proceedings of the 4th International Congress on Blockchain and Applications 2022, BLOCKCHAIN’22, held in L’Aquila, Italy, in July 2022. Among the scientific community, blockchain and artificial intelligence are a promising combination that will transform the production and manufacturing industry, media, finance, insurance, e-government, etc. Nevertheless, there is no consensus with schemes or best practices that would specify how blockchain and artificial intelligence should be used together. The 37 full papers presented in the main track were carefully reviewed and selected from more than 75 submissions. They contain the latest advances on blockchain and artificial intelligence and on their application domains, exploring innovative ideas, guidelines, theories, models, technologies, and tools and identifying critical issues and challenges that researchers and practitioners must deal with in the future research. The book also includes 3 papers from the WEB3-TRUST workshop and 2 papers from the Doctoral Consortium.

Abstract: Identification of Barriers to Ensuring Accessibility Standards for Tram Stops to the Needs of People with Disabilities -- The Use of Multi-Criteria Methods in the Problem of Selecting Vehicles for Oversize Cargo Transport -- Problems of Assessing the Technical Condition of Transport Means on the Example of the Means of Air Transport -- The Use of Automatic Passenger Counting Systems Data in Financial Settlement Models in Public Transport -- Comparative Analysis of Transport Tariffs and Operating Ticket Distribution Channels in Selected Agglomerations -- Commuter Rail Service Quality: A Case Study of Rhine-Ruhr Metropolitan Region -- Money is Not Everything - is Integrated Transport Only About Investments? -- Determination of Transport Plans in Urban Areas Considering Zero-Emission Vehicles -- Vehicle Choice for Sustainable Regional Railway.

Abstract: This book contains an abundance of numerical analyses based on significant data sets, illustrating the close affiliation between transport systems development and quality of life. How to ensure accessibility standards for public transport for people with special needs? Which multi-criteria methods can support the problem of vehicle selection in freight transport, and which ones should be taken into account in the case of problems related to regional rail transport? What kind of How to assess technical condition of transport means? What factors should be taken into account when assessing the quality of passenger service? How to include zero emission vehicles in the consideration of transport plans? This book provides you with answers to these and many other questions. With regard to the research results discussed and the selected solutions applied, the book primarily addresses the needs of three target groups: Scientists and researchers (ITS field) Local authorities (responsible for the transport systems at the urban and regional level) Representatives of business (traffic strategy management) and industry (manufacturers of ITS components). This book gathers selected papers presented at the 18th “Transport Systems. Theory and Practice” Scientific and Technical Conference organised by the Department of Transport Systems, Traffic Engineering and Logistics at the Faculty of Transport and Aviation Engineering of the Silesian University of Technology. The conference was held on 19-20 September 2022 in Katowice (Poland).

Abstract: Pretrained E-commerce Knowledge Graph Model for Product Classification -- A Novel Methodology for Object Detection in Highly Cluttered Images -- Extreme learning Machines for Offline Forged Signature Identification -- Randomized model structure selection approach for Extreme Learning Machine applied to Acid sulfate soils detection -- Online label distribution learning based on kernel extreme learning machine.

Abstract: This book contains papers from the International Conference on Extreme Learning Machine 2021, which was held in virtual on December 15–16, 2021. Extreme learning machines (ELM) aims to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental `learning particles’ filling the gaps between machine learning and biological learning (of which activation functions are even unknown). ELM represents a suite of (machine and biological) learning techniques in which hidden neurons need not be tuned: inherited from their ancestors or randomly generated. ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc.) as long as they are nonlinear piecewise continuous, independent of training data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that “random hidden neurons” capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers. This conference provides a forum for academics, researchers, and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. This book covers theories, algorithms, and applications of ELM. It gives readers a glance of the most recent advances of ELM.

Abstract: micro-ROS- Lab-scale Smart Factory Implementation Using ROS -- High Fidelity IMU and Wheel Encoder Models for ROS based AGV Simulations -- Autonomous Laser-Induced Breakdown Spectroscopy System for Chemical and Mineralogical Designation of Interplanetary.

Abstract: This book is the seventh volume of the successful book series on Robot Operating System: The Complete Reference, which started in 2016. The book's objective is to provide the reader with comprehensive coverage on the Robot Operating Systems (ROS) and the latest trends and contributed systems. ROS has been considered as the primary development framework for robotics applications. There are seven chapters organized into three parts. Part I presents one chapter dealing with ROS2 and presents a tutorial on using the MediaPipe framework with ROS2. In Part II, three chapters present new contributions of ROS frameworks and applications, including micro-ROS, Autonomous 3D Thermal Mapping of Disaster Environments, and Lab-scale Smart Factory Implementation Using ROS. Part III provides contributions on how to use ROS for cooperative robotics behaviors, particularly in platoon applications, in addition to developing new perception and control algorithms with sensing technologies. This book will be a valuable companion for ROS users and developers to learn more about ROS capabilities and features. .

Abstract: Data Integration in Practice: Academic Finance Analytics Case Study -- Proposal of an Aquarium Design Support Virtual Reality System -- The Source Code Maintenance Time Classifications from Code Smell -- Evolution Analysis of R&D Jobs Based on Patents’ Technology Efficacy Labeling -- The Model of Improving the Quality of Government Financial Reporting -- Fuzzy Mean Clustering Analysis Based on Glutamic Acid Fermentation Failure -- Mustahik Micro Business Incubation in Poverty Alleviation -- Schemes for a Transient Eddy-current Problem On an Unbounded Area -- Zakat Management Model Based on ICT -- Teaching Method of Advanced Mathematics combining PAD Classroom with ADDIE Model -- A Kind of Online Game Addictive Treatment Model about Young Person -- Research on E-commerce Customer Value Segmentation Model Based on Network Behavior -- Blockchain Applications for Mobility-as-a-Service Ecosystem: A Survey -- Construction of a Fully Homomorphic Encryption Scheme with Shorter Ciphertext and its Implementation on the CUDA Platform -- Traffic-oriented Shellcode Detection Based on VSM -- Supply Chain Finance Mediates The Effect of Trust and Commitment on Supply Chain Effectiveness.

Abstract: This book presents original contributions to the theories and practices of emerging Internet, data, and web technologies and their applicability in businesses, engineering, and academia. Internet has become the most proliferative platform for emerging large-scale computing paradigms. Among these, data and web technologies are two most prominent paradigms, in a variety of forms such as data centers, cloud computing, mobile cloud, mobile web services, and so on. These technologies altogether create a digital ecosystem whose corner stone is the data cycle, from capturing to processing, analysis, and visualization. The investigation of various research and development issues in this digital ecosystem is boosted by the ever-increasing needs of real-life applications, which are based on storing and processing large amounts of data. As a key feature, it addresses advances in the life-cycle exploitation of data generated from the digital ecosystem data technologies that create value for the knowledge and businesses toward a collective intelligence approach. Researchers, software developers, practitioners, and students interested in the field of data and web technologies find this book useful and a reference for their activity.

Abstract: Development and Extended Validation of a Lumped Parameter Prediction Model for Analysing Injury Parameters in a Vehicle Crash -- Integrating GPU-accelerated Tetrahedral Mesh Editing and Simulation -- Performance Study of Vertical Submersible Pump in Terms of Induced Loads and Vibrations -- Comparison of Modelling Approaches and Solvers on Harmonic Studies for Renewable Energy Integration -- Stretching Simulation of Viscoelastic Fluid with Spring Connection -- SysML and Petri Nets based Methodology for Analysis and Performance Evaluation in WSNs -- Growing Bioinspired Synthetic Landscape Ecologies and the Adequacy of Object Oriented Programming -- On Advanced Modeling of Compressors and Weighted Mix Iteration for Simulation of Gas Transport Networks -- Quasi-static Optimal Control Strategy of Lattice Boom Crane based on Large-scale Flexible Non-linear Dynamics -- Simulation Conditionally to a Subvariety and Application to Bayesian Optimization: A Dichotomous Approach -- A Python-based Mixed Discrete-Continuous Simulation Framework for Digital Twins.

Abstract: The present book includes a set of selected papers from the 11th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2021) that was held as an online event, from July 7 to 9, 2021. The conference brought together researchers and practitioners interested in methodologies and applications of modeling and simulation. New and innovative solutions are reported in this book. A selection was made after the conference, based also on the conference chairs assessment, reviewers’ assessment, quality of presentation and audience interest, so that this book includes the extended and revised versions of the very best papers of the conference.

Abstract: Editorial Note -- Artificial Intelligence as Dual-Use Technology -- Diabetic Retinopathy Detection using Transfer and Reinforcement Learning with effective image preprocessing and data augmentation techniques. .

Abstract: This book aims at updating the relevant computer science-related research communities, including professors, researchers, scientists, engineers and students, as well as the general reader from other disciplines, on the most recent advances in applications of methods based on Fusing Machine Learning Paradigms. Integrated or Hybrid Machine Learning methodologies combine together two or more Machine Learning approaches achieving higher performance and better efficiency when compared to those of their constituent components and promising major impact in science, technology and the society. The book consists of an editorial note and an additional eight chapters and is organized into two parts, namely: (i) Recent Application Areas of Fusion of Machine Learning Paradigms and (ii) Applications that can clearly benefit from Fusion of Machine Learning Paradigms. This book is directed toward professors, researchers, scientists, engineers and students in Machine Learning-related disciplines, as the hybridism presented, and the case studies described provide researchers with successful approaches and initiatives to efficiently address complex classification or regression problems. It is also directed toward readers who come from other disciplines, including Engineering, Medicine or Education Sciences, and are interested in becoming versed in some of the most recent Machine Learning-based technologies. Extensive lists of bibliographic references at the end of each chapter guide the readers to probe further into the application areas of interest to them.

Abstract: In this book, one hundred selected articles, in which the technology and science elite share, contribute to technology development, collaborate and evolve the latest cutting-edge technologies, open ecosystem resources, new innovative computing solutions, hands-on labs and tutorials, networking and community building, to ensure better integration of artificial intelligence into renewable energy systems. Innovation in computing continues at a growing pace. The key to success in this area is not only hardware, but also the ability to leverage rapid advances in artificial intelligence (including machine learning and deep learning), data analytics, data streaming, and cloud computing, which go hand in hand with intensive research activity on the underlying computational methods. The chapters in this book are organized into thematic sections on: advanced computing techniques; artificial intelligence; smart and sustainable cities; renewable energy systems; materials in renewable energy; smart energy efficiency; smart cities applications: recent developments and new trends; online, supervision of renewable energy platforms; predictive control in renewable systems; smart embedded systems for photovoltaic applications.