Order affects the results you get: Different orders of presenting material can lead to qualitatively and quantitatively different learning outcomes. These differences occur in both natural and artificial learning systems. In Order to Learn shows how order effects are crucial in human learning, instructional design, machine learning, and both symbolic and connectionist cognitive models. Each chapter explains a different aspect of how the order in which material is presented can strongly influence what is learned by humans and theoretical models of learning in a variety of domains. In addition to data, models are provided that predict and describe order effects and analyze how and when they will occur. The introductory and concluding chapters compile suggestions for improving learning through better sequences of learning materials, including how to take advantage of order effects that encourage learning and how to avoid order effects that discourage learning. Each chapter also highlights questions that may inspire further research. Taken together, these chapters show how order effects in different areas can and do inform each other. In Order to Learn will be of interest to researchers and students in cognitive science, education, machine learning.

This book provides foundations for the understanding and design of computation-efficient algorithms and protocols for those interactions with environment, i.e., wireless communication systems. The book provides a systematic treatment of the theoretical foundation and algorithmic tools necessarily in the design of computation-efficient algorithms and protocols in stochastic scheduling. The problems addressed in the book are of both fundamental and practical importance. Target readers of the book are researchers and advanced-level engineering students interested in acquiring in-depth knowledge on the topic and on stochastic scheduling and their applications, both from theoretical and engineering perspective.

Space and time are inextricably linked. Reasoning about space often involves reasoning about change in spatial configurations. Qualitative spatial information theory encompasses spatial as well as temporal representation and reasoning. Qualitative Spatio-Temporal Representation and Reasoning: Trends and Future Directions is a contribution to the emerging discipline of qualitative spatial information theory within artificial intelligence. This collection of research covers both theory and application-centric research and provides a comprehensive perspective on the emerging area of qualitative spatio-temporal representation and reasoning. This revolutionary new field is increasingly becoming a core issue within mobile computing, GIS/spatial information systems, databases, computer vision as well as knowledge discovery and data mining.

This book constitutes the refereed post-conference proceedings of the Third IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2020, held in Chennai, India, in February 2020.The 19 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 94 submissions. The papers are organized in the following topical sections: computational intelligence for text analysis; computational intelligence for image and video analysis; and data science.

This book gathers the proceedings of the Multidisciplinary International Conference of Research Applied to Defense and Security (MICRADS), held at the Eloy Alfaro Military Academy (ESMIL) in Quito, Ecuador, on May 13-15,2020. It covers a broad range of topics in systems, communication, and defense; strategy and political-administrative vision in defense; and engineering and technologies applied to defense. Given its scope, it offers a valuable resource for practitioners, researchers, and students alike.

This book is based on the authors' research on the stabilization and fault-tolerant control of batch processes, which are flourishing topics in the field of control system engineering. It introduces iterative learning control for linear/nonlinear single/multi-phase batch processes; iterative learning optimal guaranteed cost control; delay-dependent iterative learning control; and iterative learning fault-tolerant control for linear/nonlinear single/multi-phase batch processes. Providing important insights and useful methods and practical algorithms that can potentially be applied in batch process control and optimization, it is a valuable resource for researchers, scientists, and engineers in the field of process system engineering and control engineering.

This book highlights the emerging field of intelligent computing and developing smart systems. It includes chapters discussing the outcome of challenging research related to distributed computing, smart machines and their security related research, and also covers next-generation communication techniques and the networking technologies that have the potential to build the future communication infrastructure. Bringing together computing, communications and other aspects of intelligent and smart computing, it contributes to developing a roadmap for future research on intelligent systems.

Computational intelligence is rapidly becoming an essential part of reliability engineering. This book offers a wide spectrum of viewpoints on the merger of technologies. Leading scientists share their insights and progress on reliability engineering techniques, suitable mathematical methods, and practical applications. Thought-provoking ideas are embedded in a solid scientific basis that contribute to the development the emerging field. This book is for anyone working on the most fundamental paradigm-shift in resilience engineering in decades. Scientists benefit from this book by gaining insight in the latest in the merger of reliability engineering and computational intelligence. Businesses and (IT) suppliers can find inspiration for the future, and reliability engineers can use the book to move closer to the cutting edge of technology.

This is the first of two volumes that together provide an overview of the latest advances in the generation and application of digital twins in bioprocess design and optimization.Both processes have undergone significant changes over the past few decades, moving from data-driven approaches into the 21st-century digitalization of the bioprocess industry. Moreover, the high demand for biotechnological products calls for efficient methods during research and development, as well as during tech transfer and routine manufacturing. In this regard, one promising tool is the use of digital twins, which offer a virtual representation of the bioprocess. They reflect the mechanistics of the biological system and the interactions between process parameters, key performance indicators and product quality attributes in the form of a mathematical process model. Furthermore, digital twins allow us to use computer-aided methods to gain an improved process understanding, to test and plan novel bioprocesses, and to efficiently monitor them. This book explains the mathematical structure of digital twins, their development and the model's respective parts, as well as concepts for the knowledge-driven generation and structural variability of digital twins. Covering fundamentals as well as applications, the two volumes offer the ideal introduction to the topic for researchers in academy and industry alike.

This book presents practical as well as conceptual insights into the latest trends, tools, techniques and methodologies of blockchains for the Internet of Things. The decentralised Internet of Things (IoT) not only reduces infrastructure costs, but also provides a standardised peer-to-peer communication model for billions of transactions. However, there are significant security challenges associated with peer-to-peer communication. The decentralised concept of blockchain technology ensures transparent interactions between different parties, which are more secure and reliable thanks to distributed ledger and proof-of-work consensus algorithms. Blockchains allow trustless, peer-to-peer communication and have already proven their worth in the world of financial services. The blockchain can be implanted in IoT systems to deal with the issues of scale, trustworthiness and decentralisation, allowing billions of devices to share the same network without the need for additional resources. This book discusses the latest tools and methodology and concepts in the decentralised Internet of Things. Each chapter presents an in-depth investigation of the potential of blockchains in the Internet of Things, addressing the state-of-the-art in and future perspectives of the decentralised Internet of Things. Further, industry experts, researchers and academicians share their ideas and experiences relating to frontier technologies, breakthrough and innovative solutions and applications.

This book discusses the use of efficient metaheuristic algorithms to solve diverse power system problems, providing an overview of the various aspects of metaheuristic methods to enable readers to gain a comprehensive understanding of the field and of conducting studies on specific metaheuristic algorithms related to power-system applications. By bridging the gap between recent metaheuristic techniques and novel power system methods that benefit from the convenience of metaheuristic methods, it offers power system practitioners who are not metaheuristic computation researchers insights into the techniques, which go beyond simple theoretical tools and have been adapted to solve important problems that commonly arise. On the other hand, members of the metaheuristic computation community learn how power engineering problems can be translated into optimization tasks, and it is also of interest to engineers and application developers. Further, since each chapter can be read independently, the relevant information can be quickly found. Power systems is a multidisciplinary field that addresses the multiple approaches used for design and analysis in areas ranging from signal processing, and electronics to computational intelligence, including the current trend of metaheuristic computation.

The author presents Probatio, a toolkit for building functional DMI (digital musical instruments) prototypes, artifacts in which gestural control and sound production are physically decoupled but digitally mapped. He uses the concept of instrumental inheritance, the application of gestural and/or structural components of existing instruments to generate ideas for new instruments. To support analysis and combination, he then leverages a traditional design method, the morphological chart, in which existing artifacts are split into parts, presented in a visual form and then recombined to produce new ideas. And finally he integrates the concept and the method in a concrete object, a physical prototyping toolkit for building functional DMI prototypes: Probatio. The author's evaluation of this modular system shows it reduces the time required to develop functional prototypes. The book is useful for researchers, practitioners, and graduate students in the areas of musical creativity and human-computer interaction, in particular those engaged in generating, communicating, and testing ideas in complex design spaces.

This book includes high-quality papers presented at the International Conference on Data Science and Management (ICDSM 2019), organised by the Gandhi Institute for Education and Technology, Bhubaneswar, from 22 to 23 February 2019. It features research in which data science is used to facilitate the decision-making process in various application areas, and also covers a wide range of learning methods and their applications in a number of learning problems. The empirical studies, theoretical analyses and comparisons to psychological phenomena described contribute to the development of products to meet market demands.

This book proposes neural networks algorithms and advanced machine learning techniques for processing nonlinear dynamic signals such as audio, speech, financial signals, feedback loops, waveform generation, filtering, equalization, signals from arrays of sensors, and perturbations in the automatic control of industrial production processes. It also discusses the drastic changes in financial, economic, and work processes that are currently being experienced by the computational and engineering sciences community. Addresses key aspects, such as the integration of neural algorithms and procedures for the recognition, the analysis and detection of dynamic complex structures and the implementation of systems for discovering patterns in data, the book highlights the commonalities between computational intelligence (CI) and information and communications technologies (ICT) to promote transversal skills and sophisticated processing techniques. This book is a valuable resource for a. The academic research community b. The ICT market c. PhD students and early stage researchers d. Companies, research institutes e. Representatives from industry and standardization bodies

This textbook covers the broader field of artificial intelligence. The chapters for this textbook span within three categories: Deductive reasoning methods: These methods start with pre-defined hypotheses and reason with them in order to arrive at logically sound conclusions. The underlying methods include search and logic-based methods. These methods are discussed in Chapters 1through 5. Inductive Learning Methods: These methods start with examples and use statistical methods in order to arrive at hypotheses. Examples include regression modeling, support vector machines, neural networks, reinforcement learning, unsupervised learning, and probabilistic graphical models. These methods are discussed in Chapters~6 through 11. Integrating Reasoning and Learning: Chapters~11 and 12 discuss techniques for integrating reasoning and learning. Examples include the use of knowledge graphs and neuro-symbolic artificial intelligence. The primary audience for this textbook are professors and advanced-level students in computer science. It is also possible to use this textbook for the mathematics requirements for an undergraduate data science course. Professionals working in this related field many also find this textbook useful as a reference.

This book presents explorable XR environments-their rationale, concept, architectures as well as methods and tools for spatial-temporal composition based on domain knowledge, including geometrical, presentational, structural and behavioral elements. Explorable XR environments enable monitoring, analyzing, comprehending, examining and controlling users' and objects' behavior and features as well as users' skills, experience, interests and preferences. The E-XR approach proposed in this book relies on two main pillars. The first is knowledge representation technologies, such as logic programming, description logics and the semantic web, which permit automated reasoning and queries. The second is imperative programming languages, which are a prevalent solution for building XR environments. Potential applications of E-XR are in a variety of domains, e.g., education, training, medicine, design, tourism, marketing, merchandising, engineering and entertainment. The book's readers will understand the emerging domain of explorable XR environments with their possible applications. Special attention is given to an in-depth discussion of the field with taxonomy and classification of the available related solutions. Examples and design patterns of knowledge-based composition and exploration of XR behavior are provided, and an extensive evaluation and analysis of the proposed approach is included. This book helps researchers in XR systems, 3D modeling tools and game engines as well as lecturers and students who search for clearly presented information supported by use cases. For XR and game programmers as well as graphic designers, the book is a valuable source of information and examples in XR development. Professional software and web developers may find the book interesting as the proposed ideas are illustrated by rich examples demonstrating design patterns and guidelines in object-oriented, procedural and declarative programming.

Technological advances have helped to enhance disaster resilience through better risk reduction, response, mitigation, rehabilitation and reconstruction. In former times, it was local and traditional knowledge that was mainly relied upon for disaster risk reduction. Much of this local knowledge is still valid in today's world, even though possibly in different forms and contexts, and local knowledge remains a shared part of life within the communities. In contrast, with the advent of science and technology, scientists and engineers have become owners of advanced technologies, which have contributed significantly to reducing disaster risks across the globe. This book analyses emerging technologies and their effects in enhancing disaster resilience. It also evaluates the gaps, challenges, capacities required and the way forward for future disaster management. A wide variety of technologies are addressed, focusing specifically on new technologies such as cyber physical systems, geotechnology, drone, and virtual reality (VR)/ augmented reality (AR). Other sets of emerging advanced technologies including an early warning system and a decision support system are also reported on. Moreover, the book provides a variety of discussions regarding information management, communication, and community resilience at the time of a disaster. This book's coverage of different aspects of new technologies makes it a valuable resource for students, researchers, academics, policymakers, and development practitioners.

Big data and data science are transforming our world today in ways we could not have imagined at the beginning of the twenty-first century. The accompanying wave of innovation has sparked advances in healthcare, engineering, business, science, and human perception, among others. The tremendous advances in computing power and intelligent techniques have opened many opportunities for managing data and investigating data in virtually every field, and the scope of data science is expected to grow over the next decade. These future research achievements will solve old challenges and create new opportunities for growth and development. Thus, the research presented in this book is interdisciplinary and covers themes embracing emotions, artificial intelligence, robotics applications, sentiment analysis, smart city problems, assistive technologies, speech melody, and fall and abnormal behavior detection. The book is directed to the researchers, practitioners, professors and students interested in recent advances in methodologies and applications of data science. An introduction to the topic is provided, and research challenges and future research opportunities are highlighted throughout.

Investigative Data Mining for Security and Criminal Detection is the first book to outline how data mining technologies can be used to combat crime in the 21st century. It introduces security managers, law enforcement investigators, counter-intelligence agents, fraud specialists, and information security analysts to the latest data mining techniques and shows how they can be used as investigative tools. Readers will learn how to search public and private databases and networks to flag potential security threats and root out criminal activities even before they occur.
The groundbreaking book reviews the latest data mining technologies including intelligent agents, link analysis, text mining, decision trees, self-organizing maps, machine learning, and neural networks. Using clear, understandable language, it explains the application of these technologies in such areas as computer and network security, fraud prevention, law enforcement, and national defense. International case studies throughout the book further illustrate how these technologies can be used to aid in crime prevention.
Investigative Data Mining for Security and Criminal Detection will also serve as an indispensable resource for software developers and vendors as they design new products for the law enforcement and intelligence communities.

Key Features:
* Covers cutting-edge data mining technologies available to use in evidence gathering and collection
* Includes numerous case studies, diagrams, and screen captures to illustrate real-world applications of data mining
* Easy-to-read format illustrates current and future data mining uses in preventative law enforcement, criminal profiling, counter-terrorist initiatives, and forensic science
* Introduces cutting-edge technologies in evidence gathering and collection, using clear non-technical language
* Illustrates current and future applications of data mining tools in preventative law enforcement, homeland security, and other areas of crime detection and prevention
* Shows how to construct predictive models for detecting criminal activity and for behavioral profiling of perpetrators
* Features numerous Web links, vendor resources, case studies, and screen captures illustrating the use of artificial intelligence (AI) technologies

This book constitutes the refereed proceedings of six International Workshops held as parallel events of the 17th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2021, virtually and in Hersonissos, Crete, Greece, in June 2021: the 6th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2021; Artificial Intelligence in Biomedical Engineering and Informatics Workshop, AI-BIO 2021; Workshop on Defense Applications of AI, DAAI 2021; Distributed AI for Resource-Constrained Platforms Workshop, DARE 2021; Energy Efficiency and Artificial Intelligence Workshop, EEAI 2021; and the 10th Mining Humanistic Data Workshop, MHDW 2021. The 24 full papers and 16 short papers presented at these workshops were carefully reviewed and selected from 72 submissions. The papers presented at 5G-PINE focus on the latest AI applications in the telecommunication industry and AI in modern 5G-oriented telecommunications infrastructures. The papers chosen for AI-BIO 2021 present research on the subject of AI, in its broadest sense, in biomedical engineering and health informatics. The DAAI 2021 papers aim at presenting recent evolutions in artificial intelligence applicable to defense and security applications. The papers selected for DARE 2021 address a variety of pertinent and challenging topics within the scope of distributed AI for resource-constrained platforms. The papers presented at EEAI 2021 aim to bring together interdisciplinary approaches that focus on the application of AI-driven solutions for increasing and improving energy efficiency of residential and tertiary buildings and of occupant behavior. The MHDW papers focus on topics such as recommendation systems, sentiment analysis, pattern recognition, data mining, and time series.

The book gathers the chapters of Cognitive InfoCommunication research relevant to a variety of application areas, including data visualization, emotion expression, brain-computer interfaces or speech technologies. It provides an overview of the kind of cognitive capabilities that are being analyzed and developed. Based on this common ground, it may become possible to see new opportunities for synergy among disciplines that were heretofore viewed as being separate. Cognitive InfoCommunication begins by modeling human cognitive states and aptitudes in order to better understand what the user of a system is capable of comprehending and doing. The patterns of exploration and the specific tools that are described can certainly be of interest and of great relevance for all researchers who focus on modeling human states and aptitudes. This innovative research area provides answers to the latest challenges in influence of cognitive states and aptitudes in order to facilitate learning or generally improve performance in certain cognitive tasks such as decision making. Some capabilities are purely human, while others are purely artificial, but in general this distinction is rarely clear-cut. Therefore, when discussing new human cognitive capabilities, the technological background which makes them possible cannot be neglected, and indeed often plays a central role. This book highlights the synergy between various fields that are perfectly fit under the umbrella of CogInfoCom and contribute to understanding and developing new, human-artificial intelligence hybrid capabilities. These, merged capabilities are currently appearing, and the importance of the role they play in everyday life are unique to the cognitive entity generation that is currently growing up.

One aspect of common sense reasoning is reasoning about normal cases, e.g. a physician will first try to interpret symptoms by a common disease, and will take more exotic possibilities only later into account. Such "normality" can be encoded, e.g. by
a relation, where case A is considered more normal than case B. This gives a standard semantics or interpretation to nonmonotonic reasoning (a branch of common sense reasoning), or, more formally, to nonmonotonic logics. We consider in this book the repercussions such normality relations and similar
constructions have on the resulting nonmonotonic logics, i.e. which types of logic are adequate for which kind of relation, etc.
We show in this book that some semantics correspond nicely to some logics, but also that other semantics do not correspond to any logics of the usual form.
Key features:
- provides a coherent picture of several formalisms of nonmonotonic logics.
- gives completeness and incompleteness results for many variants of preferential, distance based, and other semantics.
- gives probably the first systematic investigation of definability preservation and its consequences.
- gives new proof techniques for completeness results.
- is centered on semantics

This book contains new and useful materials concerning fuzzy fractional differential and integral operators and their relationship. As the title of the book suggests, the fuzzy subject matter is one of the most important tools discussed. Therefore, it begins by providing a brief but important and new description of fuzzy sets and the computational calculus they require. Fuzzy fractals and fractional operators have a broad range of applications in the engineering, medical and economic sciences. Although these operators have been addressed briefly in previous papers, this book represents the first comprehensive collection of all relevant explanations. Most of the real problems in the biological and engineering sciences involve dynamic models, which are defined by fuzzy fractional operators in the form of fuzzy fractional initial value problems. Another important goal of this book is to solve these systems and analyze their solutions both theoretically and numerically. Given the content covered, the book will benefit all researchers and students in the mathematical and computer sciences, but also the engineering sciences.

This book presents selected papers from The 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2019). Focusing on novel architecture theories, tools, methods, and procedures for digital design and construction in architecture, it promotes dialogs between architecture, engineer, computer science, robotics, and other relevant disciplines to establish a new way of production in the building industry in the digital age. The contents make valuable contributions to academic researchers and engineers in the industry. At the same time, it offers readers new ideas for the application of digital technology.