Bøger i Learning and Analytics in Intelligent Systems serien

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

This book aims to provide information about significant advances of Fuzzy Logic in software systems to researchers, scientists, educators, students, software engineers and developers. In particular, this book explains how Fuzzy Logic, can be used in software systems to automatically predict, model, decide, diagnose, recommend etc.. In more details, Fuzzy Logic is an artificial intelligent technique that is ideal for successfully addressing, , the uncertainty, imprecision and vagueness that exist in many diverse scientific and technological areas. It was introduced by Lotfi A. Zadeh of the University of California at Berkeley, as a methodology for computing with words. This ability of Fuzzy Logic allows the representation of imprecise and vague data in a more realistic way. Therefore, Fuzzy Logic-based systems can simulate the human reasoning and decision-making processes, addressing the human subjectivity. Fuzzy Logic-based software systems are referred to any software that concerns anautomated program or process that is used in everyday life, like heating or air-conditioning system, or in the scientific world, like a medical diagnostic system, which uses Fuzzy Logic in order to perform reasoning. A Fuzzy Logic-based system consists of three basic modules: Fuzzifier, Inference Engine and Defuzzifier. The Fuzzifier accepts as input numerical data and assigns them to fuzzy sets with some degree of membership, converting crisp data to fuzzy sets. The Inference Engine applies fuzzy rules over the defined fuzzy sets and produces outputs based on linguistic information. The Defuzzifier, converts fuzzy values into crisp values. The use of Fuzzy Logic in software systems constitutes a compelling and active research area in recent years, especially due to the increased interest in artificial intelligence. In the view of the above, this book presents thoroughly the Fuzzy Logic theory and the structure and operation of a Fuzzy Logic-based system. It also explains the role ofFuzzy Logic in artificial intelligence and smart applications, presenting how it can improve the efficiency and effectiveness of automatic processes and tasks. Furthermore, the book describes techniques of artificial intelligence with which the fuzzy logic is combined and how. Furthermore, this book presents several Fuzzy Logic-based software systems in the discipline of medicine, education, decision making and recommendation, natural language processing, automotive engineering and industry, heating, ventilation and air-conditioning, navigation, scheduling, network traffic and security. Thereby, this book can provide deep insights and valuable information not only to readers of computer science-related disciplines, but also to readers, who come from a variety of disciplines and are interesting in systems that perform tasks related to their discipline, in a more efficient way.

The management of an educational system is referred to as educational administration. It includes providing leadership for student education, establishing curriculum, carrying out assessments, and managing people and material resources to reach certain goals. It also includes the management of processes within a school system to ensure specific outcomes are achieved. Moreover, educational administration is critical because it allows schools to present opportunities for students to study. As technological advancements drive digital transformation and globalization, teachers may assist students in acquiring the technological skills needed to succeed in future careers. Also, the significance of integrating technology in education administration is to efficiently reach more students and facilitate customized learning through MOOCs, Virtual classrooms, video courses and augmented reality (AR) etc. It not only helps in imparting education but also helps in monitoring the student performanceby collecting respective data. This book approaches Educational Technology & Administration while keeping in view these requirements. It not only identifies the gaps in existing educational policies but also suggests new research directions to make the teaching-learning procedure more efficient, accessible and easier. It further recommends development of new innovative policies, practices and reforms encouraging the scope of experimentation while ensuring quality. This book is targeted towards educators working closely in this field, researchers, policy makers and academic administrators working collaboratively towards the enhancement of the education system.

As new technological challenges are perpetually arising, Artificial Intelligence research interests are focusing on the incorporation of improvement abilities into machines in an effort to make them more efficient and more useful. Recent reports indicate that the demand for scientists with Artificial Intelligence skills significantly exceeds the market availability and that this shortage will intensify further in the years to come. A potential solution includes attracting more women into the field, as women currently make up only 26 percent of Artificial Intelligence positions in the workforce.  The present book serves a dual purpose: On one hand, it sheds light on the very significant research led by women in areas of Artificial Intelligence, in hopes of inspiring other women to follow studies in the area and get involved in related research. On the other hand, it highlights the state-of-the-art and current research in selected Artificial Intelligence areas and applications. The book consists of an editorial note and an additional thirteen (13) chapters, all authored by invited women-researchers who work on various Artificial Intelligence areas and stand out for their significant research contributions. In more detail, the chapters in the book are organized into three parts, namely (i) Advances in Artificial Intelligence Paradigms, (ii) Advances in Artificial Intelligence Applications, and (iii) Recent Trends in Artificial Intelligence Areas and Applications. This research book is directed towards professors, researchers, scientists, engineers and students in Artificial Intelligence-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of the most recent Artificial Intelligence-based technologies. An extensive list of bibliographic references at the end of each chapter guides the readers to probe further into the Artificial Intelligence areas of interest to them.

This book contains extended versions of the works and new research results presented at the 14th International Joint Conference on Knowledge-based Software Engineering (JCKBSE2022). JCKBSE2022 was originally planned to take place in Larnaca, Cyprus. Unfortunately, the COVID-19 pandemic forced it to be rescheduled as an online conference. JCKBSE is a well-established international biennial conference that focuses on the applications of Artificial Intelligence on Software Engineering. The 14th International Joint Conference on Knowledge-based Software Engineering (JCKBSE2022) was organized by the Department of Informatics of the University of Piraeus, Greece. This book is a valuable resource for experts and researchers in the field of (knowledge-based) software engineering. It is also valuable to general readers in the fields of artificial and computational intelligence and, more generally, computer science, wishing to learn more about the exciting field of (knowledge-based) software engineering and its applications. An extensive list of bibliographic references at the end of each chapter helps readers to probe deeper into the application areas of interest to them.

This book contributes to the area of ongoing global risks and the area of forthcoming global risks, particularly necessary for the implementation of very important interdisciplinary research activities.

Chapter 1.Smart Dustbin: A Reward Provider.- Chapter 2.Cyclic Exploration-based Whale Optimization to Linear Discriminant Regression Classification for Face Recognition.- Chapter 3.Auction System in Food Supply Chain Management using Blockchain.- Chapter 4.The Mechanism of Generating the Automated Java Unit Test Cases by achieving Maximum Code Coverage.- Chapter 5.Line Stability Index Based Voltage Stability Assessment Placing Series Compensation of TCSC.- Chapter 6.Preventing Crime Using Advanced Artificial Intelligence Techniques.- Chapter 7.Issue Resolution Process: Salesforce.- Chapter 8.Automated Member Enrollment: Health Insurance Agency.- Chapter 9.Comprehensive Analysis of State of the Art Techniques for VQA.- Chapter 10.Study of State of Arts Methods for Event Extraction.- Chapter 11.A Survey on Identification of Illegal Wildlife Trade.- Chapter 12.An approach for optimizing algorithms which find k1-most demanding products.- Chapter 13.Homomorphic Analysis of Privacy-Preserving Psychological Medical Records.- Chapter 14.Prediction of Rice Plant Diseases based on Soil and Weather conditions.- Chapter 15.An improved web information system through identification of faculty browsing patterns in affiliated engineering institutions.

This book discusses various open issues in software engineering, such as the efficiency of automated testing techniques, predictions for cost estimation, data processing, and automatic code generation.

This book highlights the analytics and optimization issues in industry, to propose new approaches, and to present applications of innovative approaches in real facilities. It will also be helpful for researchers, graduate and undergraduate students with an interest in the fields of Artificial Intelligence and Industrial problems.

This book comprises the best deliberations with the theme ¿Smart Innovations in Mezzanine Technologies, Data Analytics, Networks and Communication Systems¿ in the ¿International Conference on Advances in Computer Engineering and Communication Systems (ICACECS 2020)¿, organized by the Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology. The book provides insights on the recent trends and developments in the field of computer science with a special focus on the mezzanine technologies and creates an arena for collaborative innovation. The book focuses on advanced topics in artificial intelligence, machine learning, data mining and big data computing, cloud computing, Internet on things, distributed computing and smart systems.

This book examines the conflicts arising from the implementation of privacy principles enshrined in the GDPR, and most particularly of the ``Right to be Forgotten'', on a wide range of contemporary organizational processes, business practices, and emerging computing platforms and decentralized technologies.

As the 4th Industrial Revolution is restructuring human societal organization into, so-called, ¿Society 5.0¿, the field of Machine Learning (and its sub-field of Deep Learning) and related technologies is growing continuously and rapidly, developing in both itself and towards applications in many other disciplines. Researchers worldwide aim at incorporating cognitive abilities into machines, such as learning and problem solving. When machines and software systems have been enhanced with Machine Learning/Deep Learning components, they become better and more efficient at performing specific tasks. Consequently, Machine Learning/Deep Learning stands out as a research discipline due to its worldwide pace of growth in both theoretical advances and areas of application, while achieving very high rates of success and promising major impact in science, technology and society. The book at hand aims at exposing its readers to some of the most significant Advances in Machine Learning/Deep Learning-based Technologies. The book consists of an editorial note and an additional ten (10) chapters, all invited from authors who work on the corresponding chapter theme and are recognized for their significant research contributions. In more detail, the chapters in the book are organized into five parts, namely (i) Machine Learning/Deep Learning in Socializing and Entertainment, (ii) Machine Learning/Deep Learning in Education, (iii) Machine Learning/Deep Learning in Security, (iv) Machine Learning/Deep Learning in Time Series Forecasting, and (v) Machine Learning in Video Coding and Information Extraction. This research book is directed towards professors, researchers, scientists, engineers and students in Machine Learning/Deep Learning-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of themost recent Machine Learning/Deep Learning-based technologies. An extensive list of bibliographic references at the end of each chapter guides the readers to probe further into the application areas of interest to them.

This book aims to bring together Researchers, Scientists, Engineers, Scholars and Students in the areas of computer engineering and information technology, and provides a forum for the dissemination of original research results, new ideas, Research and development, practical experiments, which concentrate on both theory and practices, for the benefit of the society. The book also provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of Computer Science and Information Technology in the context of Distributed computing, Big data, High performance computing, Internet-of-Things, and digital pedagogy. 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. This book aspires to convey researchers¿ experiences, to present excellent result analysis, future scopes, and challenges facing the field of computer science, information technology, telecommunication, and digital pedagogy. This book aims to attract researchers and practitioners who are working in Information Technology and Computer Science. This book is about basics and high level concepts regarding intelligent computing paradigm, communications, and digital learning process. The book serves as a useful guide for Undergraduates, Postgraduates and Research Scholar in the field of Computer Science, Information Technology, and Electronics Engineering. We believe that this volume not only presents novel and interesting ideas but also will stimulate interesting discussions from the participants and inspire new ideas.

This book summarizes the research findings presented at the 13th International Joint Conference on Knowledge-Based Software Engineering (JCKBSE 2020), which took place on August 24-26, 2020.

This edited book designs the Cognitive Computing in Human Cognition to analyze to improve the efficiency of decision making by cognitive intelligence.

Computational engineering (CE) is a relatively new discipline that addresses the development and application of computational models and simulations often coupled with high-performance computing to solve complex physical problems arising in engineering analysis and design in the context of natural phenomena.

This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics.

This book addresses many-criteria decision-making (MCDM), a process used to find a solution in an environment with several criteria. Accordingly, many current research efforts are focused on the implementation of biologically inspired algorithms (BIAs), which are well suited to solving uni-objective problems.

This book discusses fundamental and high-level concepts relating to intelligent computing and communications in the context of distributed computing, big data, high performance computing and the Internet of Things.