Big Data Analytics and Software Defined Networking (SDN) are helping to drive the management of data and usage of the extraordinary increase of computer processing power provided by Cloud Data Centres (CDCs). SDN helps CDCs run their services more efficiently by enabling managers to configure, manage, secure, and optimize the network resources very quickly. Big-Data Analytics in turn has entered CDCs to harvest the massive computing powers and deduct information that was never reachable by conventional methods. Big Data and Software Defined Networks investigates areas where Big-Data and SDN can help each other in delivering more efficient services. SDN can help Big-Data applications overcome one of their major challenges: message passing among cooperative nodes. Through proper bandwidth allocation and prioritization, critical surges of Big-Data flows can be better handled to effectively reduce their impacts on CDCs. Big-Data, in turn, can help SDN controllers better analyze collected network information and make more efficient decisions about the allocation of resources to different network flows.

This book recapitulates the major developments in Decision Support Systems (DSS) over the last 30 years in order to evaluate the research areas of decision making and in which direction the field should proceed. As it attempts to find a consensus about the next steps for the future of DSS research, the book also enforces the trends and new technologies currently in use. The book examines topics such as decision analysis for enterprise systems and non-hierarchical networks, integrated solutions for decision support and knowledge management in distributed environments, decision support system evaluation and analysis through social networks, and e-learning and its application to real environments. It clearly presents the evidence to support their cases and attempts to promote an extensive and objective discussion. In addition, the book also reflects on approaches to dead-end ideas and failures in DSS to better understand the lessons learned. The contributions for this book have been written by thought leaders and influential researchers from the EURO Working Group of Decision Support Systems (EWG-DSS).

The essays in this open access volume identify the key ingredients for success in capitalizing on public investments in scientific projects and the development of large-scale research infrastructures. Investment in science - whether in education and training or through public funding for developing new research tools and technologies - is a crucial priority. Authors from big research laboratories/organizations, funding agencies and academia discuss how investing in science can produce societal benefits as well as identifying future challenges for scientists and policy makers. The volume cites different ways to assess the socio-economic impact of Research Infrastructures and their role as hubs of global collaboration, creativity and innovation. It highlights the different benefits stemming from fundamental research at the local, national and global level, while also inviting us to rethink the notion of "benefit" in the 21st century. Public investment is required to maintain the pace of technological and scientific advancements over the next decades. Far from advocating a radical transformation and massive expansion in funding, the authors suggest ways for maintaining a strong foundation of science and research to ensure that we continue to benefit from the outputs. The volume draws inspiration from the first "Economics of Big Science" workshop, held in Brussels in 2019 with the aim of creating a new space for dialogue and interaction between representatives of Big Science organizations, policy makers and academia. It aspires to provide useful reading for policy makers, scientists and students of science, who are increasingly called upon to explain the value of fundamental research and adopt the language and logic of economics when engaging in policy discussions.

This book presents best selected papers presented at the 4th International Conference on Smart Computing and Informatics (SCI 2020), held at the Department of Computer Science and Engineering, Vasavi College of Engineering (Autonomous), Hyderabad, Telangana, India. It presents advanced and multi-disciplinary research towards the design of smart computing and informatics. The theme is on a broader front which focuses on various innovation paradigms in system knowledge, intelligence and sustainability that may be applied to provide realistic solutions to varied problems in society, environment and industries. The scope is also extended towards the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in various disciplines of science, technology and health care.

This book features a collection of high-quality, peer-reviewed papers presented at International Conference on Ubiquitous Intelligent Systems (ICUIS 2021) organized by Shree Venkateshwara Hi-Tech Engineering College, Tamil Nadu, India, during April 16-17, 2021. The book covers topics such as cloud computing, mobile computing and networks, embedded computing frameworks, modeling and analysis of ubiquitous information systems, communication networking models, big data models and applications, ubiquitous information processing systems, next-generation ubiquitous networks and protocols, advanced intelligent systems, Internet of things, wireless communication and storage networks, intelligent information retrieval techniques, AI-based intelligent information visualization techniques, cognitive informatics, smart automation systems, healthcare informatics and bioinformatics models, security and privacy of intelligent information systems, and smart distributed information systems.

This book strikes a healthy balance between theory and applications, ensuring that it doesn't offer a set of tools with no mathematical roots. It is intended as a comprehensive and largely self-contained introduction to probability and statistics for university students from various faculties, with accompanying implementations of some rudimentary statistical techniques in the language R. The content is divided into three basic parts: the first includes elements of probability theory, the second introduces readers to the basics of descriptive and inferential statistics (estimation, hypothesis testing), and the third presents the elements of correlation and linear regression analysis. Thanks to examples showing how to approach real-world problems using statistics, readers will acquire stronger analytical thinking skills, which are essential for analysts and data scientists alike.

Smart Technologies and Design for Healthy Built Environment connects smart technology to a healthy built environmentthat builds upon the sustainable building movement.It provides an overall summary of the state-of-the-art technologies that are applied in the built environment. The book covers a broad spectrum of smart technology categories ranging from dynamic operability, energy efficiency, self-regulating and self-learning systems, and responsive systems. The foreseeable challenges that are associated with smart technologies are discussed and outlined in the book. Firstly, this book provides a snapshot of state-of-the-art smart technologies being applied in the built environment. It covers a broad spectrum of smart technology categories, ranging from dynamic operability, energy efficiency, self-regulating and self-learning systems, to responsive systems. Secondly, this book provides in-depth analysis of the four primary components of health (biological, physical, physiological and psychological); their effects on wellbeing and cognitive performance are introduced as well. Thirdly, it connects smart technologies to those health-influencing factors by reviewing three completed smart building projects. This book can also serve as a basis for education and discussion among professionals and students of diverse backgrounds who are interested in smart technologies, smart building, and healthy building. Smart Technologies and Design for Healthy Built Environment serves as the basis for education and discussions among professionals and students who are interested in smart technologies, smart building and healthy building, as it bridges the gap between smart technologies and a healthy built environment. The book also provides a foundation for anyone who is interested in the impact of smart technology on the health of built environment.

Proceedings from the 2013 LTEC conference in Kaohsiung, Taiwan. The papers examine diverse aspects of Learning Technology for Education in Cloud environments, including social, technical and infrastructure implications. Also addressed is the question of how cloud computing can be used to design applications to support real time on demand learning using technologies. The workshop proceedings provide opportunities for delegates to discuss the latest research in TEL (Technology Enhanced Learning) and its impacts for learners and institutions, using cloud technologies.

This open access book presents an overview and step-by-step explanation of process management. It starts with the individual participants' perspectives on their work in a process and its structuring and harmonization, and then moves on to its specification in a model and how it is embedded in the organizational and IT environment of the company. Lastly, the book examines the joint processing of instances in the resulting socio-technical systems. A corresponding illustration, which expands with the overview, enables readers to gain a comprehensive understanding of business process management. The book presents various facets of business process management from the perspective of the participants, and introduces a selection of models that have proved useful in practice. The design of such models supports the transition from a more-or-less unstructured or unsatisfactory way of working to a structured process that corresponds to the ideas of the company and its customers. The book is intended for professionals in industry as well as students in the field of business information systems who are looking for guidelines on how to discover, create and implement real-world processes.

This book constitutes the refereed post-conference proceedings of the Fourth IFIP International Cross-Domain Conference on Internet of Things, IFIPIoT 2021, held virtually in November 2021. The 15 full papers presented were carefully reviewed and selected from 33 submissions. Also included is a summary of two panel sessions held at the conference. The papers are organized in the following topical sections: challenges in IoT Applications and Research, Modernizing Agricultural Practice Using IoT, Cyber-physical IoT systems in Wildfire Context, IoT for Smart Health, Security, Methods.

This book aims to provide some insights into recently developed bio-inspired algorithms within recent emerging trends of fog computing, sentiment analysis, and data streaming as well as to provide a more comprehensive approach to the big data management from pre-processing to analytics to visualization phases. The subject area of this book is within the realm of computer science, notably algorithms (meta-heuristic and, more particularly, bio-inspired algorithms). Although application domains of these new algorithms may be mentioned, the scope of this book is not on the application of algorithms to specific or general domains but to provide an update on recent research trends for bio-inspired algorithms within a specific application domain or emerging area. These areas include data streaming, fog computing, and phases of big data management. One of the reasons for writing this book is that the bio-inspired approach does not receive much attention but shows considerable promise and diversity in terms of approach of many issues in big data and streaming. Some novel approaches of this book are the use of these algorithms to all phases of data management (not just a particular phase such as data mining or business intelligence as many books focus on); effective demonstration of the effectiveness of a selected algorithm within a chapter against comparative algorithms using the experimental method. Another novel approach is a brief overview and evaluation of traditional algorithms, both sequential and parallel, for use in data mining, in order to provide an overview of existing algorithms in use. This overview complements a further chapter on bio-inspired algorithms for data mining to enable readers to make a more suitable choice of algorithm for data mining within a particular context. In all chapters, references for further reading are provided, and in selected chapters, the author also include ideas for future research.

The two-volume set IFIP AICT 591 and 592 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2020, held in Novi Sad, Serbia, in August/September 2020.The 164 papers presented were carefully reviewed and selected from 199 submissions. They discuss globally pressing issues in smart manufacturing, operations management, supply chain management, and Industry 4.0. The papers are organized in the following topical sections: Part I: advanced modelling, simulation and data analytics in production and supply networks; advanced, digital and smart manufacturing; digital and virtual quality management systems; cloud-manufacturing; cyber-physical production systems and digital twins; IIOT interoperability; supply chain planning and optimization; digital and smart supply chain management; intelligent logistics networks management; artificial intelligence and blockchain technologies in logistics and DSN; novel production planning and control approaches; machine learning and artificial intelligence; connected, smart factories of the future; manufacturing systems engineering: agile, flexible, reconfigurable; digital assistance systems: augmented reality and virtual reality; circular products design and engineering; circular, green, sustainable manufacturing; environmental and social lifecycle assessments; socio-cultural aspects in production systems; data-driven manufacturing and services operations management; product-service systems in DSN; and collaborative design and engineering Part II: the Operator 4.0: new physical and cognitive evolutionary paths; digital transformation approaches in production management; digital transformation for more sustainable supply chains; data-driven applications in smart manufacturing and logistics systems; data-driven services: characteristics, trends and applications; the future of lean thinking and practice; digital lean manufacturing and its emerging practices; new reconfigurable, flexible or agile production systems in the era of industry 4.0; operations management in engineer-to-order manufacturing; production management in food supply chains; gastronomic service system design; product and asset life cycle management in the circular economy; and production ramp-up strategies for product

This book is the world's first book on 6G Mobile Wireless Networks that aims to provide a comprehensive understanding of key drivers, use cases, research requirements, challenges and open issues that are expected to drive 6G research. In this book, we have invited world-renowned experts from industry and academia to share their thoughts on different aspects of 6G research. Specifically, this book covers the following topics: 6G Use Cases, Requirements, Metrics and Enabling Technologies, PHY Technologies for 6G Wireless, Reconfigurable Intelligent Surface for 6G Wireless Networks, Millimeter-wave and Terahertz Spectrum for 6G Wireless, Challenges in Transport Layer for Tbit/s Communications, High-capacity Backhaul Connectivity for 6G Wireless, Cloud Native Approach for 6G Wireless Networks, Machine Type Communications in 6G, Edge Intelligence and Pervasive AI in 6G, Blockchain: Foundations and Role in 6G, Role of Open-source Platforms in 6G, and Quantum Computing and 6G Wireless. The overarching aim of this book is to explore the evolution from current 5G networks towards the future 6G networks from a service, air interface and network perspective, thereby laying out a vision for 6G networks. This book not only discusses the potential 6G use cases, requirements, metrics and enabling technologies, but also discusses the emerging technologies and topics such as 6G PHY technologies, reconfigurable intelligent surface, millimeter-wave and THz communications, visible light communications, transport layer for Tbit/s communications, high-capacity backhaul connectivity, cloud native approach, machine-type communications, edge intelligence and pervasive AI, network security and blockchain, and the role of open-source platform in 6G. This book provides a systematic treatment of the state-of-the-art in these emerging topics and their role in supporting a wide variety of verticals in the future. As such, it provides a comprehensive overview of the expected applications of 6G with a detailed discussion of their requirements and possible enabling technologies. This book also outlines the possible challenges and research directions to facilitate the future research and development of 6G mobile wireless networks.

The five-volume set IFIP AICT 630, 631, 632, 633, and 634 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2021, held in Nantes, France, in September 2021.*The 378 papers presented were carefully reviewed and selected from 529 submissions. They discuss artificial intelligence techniques, decision aid and new and renewed paradigms for sustainable and resilient production systems at four-wall factory and value chain levels. The papers are organized in the following topical sections: Part I: artificial intelligence based optimization techniques for demand-driven manufacturing; hybrid approaches for production planning and scheduling; intelligent systems for manufacturing planning and control in the industry 4.0; learning and robust decision support systems for agile manufacturing environments; low-code and model-driven engineering for production system; meta-heuristics and optimization techniques for energy-oriented manufacturing systems; metaheuristics for production systems; modern analytics and new AI-based smart techniques for replenishment and production planning under uncertainty; system identification for manufacturing control applications; and the future of lean thinking and practice Part II: digital transformation of SME manufacturers: the crucial role of standard; digital transformations towards supply chain resiliency; engineering of smart-product-service-systems of the future; lean and Six Sigma in services healthcare; new trends and challenges in reconfigurable, flexible or agile production system; production management in food supply chains; and sustainability in production planning and lot-sizing Part III: autonomous robots in delivery logistics; digital transformation approaches in production management; finance-driven supply chain; gastronomic service system design; modern scheduling and applications in industry 4.0; recent advances in sustainable manufacturing; regular session: green production and circularity concepts; regular session: improvement models and methods for green and innovative systems; regular session: supply chain and routing management; regular session: robotics and human aspects; regular session: classification and data management methods; smart supply chain and production in society 5.0 era; and supply chain risk management under coronavirus Part IV: AI for resilience in global supply chain networks in the context of pandemic disruptions; blockchain in the operations and supply chain management; data-based services as key enablers for smart products, manufacturing and assembly; data-driven methods for supply chain optimization; digital twins based on systems engineering and semantic modeling; digital twins in companies first developments and future challenges; human-centered artificial intelligence in smart manufacturing for the operator 4.0; operations management in engineer-to-order manufacturing; product and asset life cycle management for smart and sustainable manufacturing systems; robotics technologies for control, smart manufacturing and logistics; serious games analytics: improving games and learning support; smart and sustainable production and supply chains; smart methods and techniques for sustainable supply chain management; the new digital lean manufacturing paradigm; and the role of emerging technologies in disaster relief operations: lessons from COVID-19 Part V: data-driven platforms and applications in production and logistics: digital twins and AI for sustainability; regular session: new approaches for routing problem solving; regular session: improvement of design and operation of manufacturing systems; regular session: crossdock and transportation issues; regular session: maintenance improvement and lifecycle management; regular session: additive manufacturing and mass customization; regular session: frameworks and conceptual modelling for systems and services efficiency; regular session: optimization of production and transportation systems; regular session: optimization of supply chain agility and reconfigurability; regular session: advanced modelling approaches; regular session: simulation and optimization of systems performances; regular session: AI-based approaches for quality and performance improvement of production systems; and regular session: risk and performance management of supply chains *The conference was held online.

This book provides a coherent and complete overview of various Question Answering (QA) systems. It covers three main categories based on the source of the data that can be unstructured text (TextQA), structured knowledge graphs (KBQA), and the combination of both. Developing a QA system usually requires using a combination of various important techniques, including natural language processing, information retrieval and extraction, knowledge graph processing, and machine learning. After a general introduction and an overview of the book in Chapter 1, the history of QA systems and the architecture of different QA approaches are explained in Chapter 2. It starts with early close domain QA systems and reviews different generations of QA up to state-of-the-art hybrid models. Next, Chapter 3 is devoted to explaining the datasets and the metrics used for evaluating TextQA and KBQA. Chapter 4 introduces the neural and deep learning models used in QA systems. This chapter includes the required knowledge of deep learning and neural text representation models for comprehending the QA models over text and QA models over knowledge base explained in Chapters 5 and 6, respectively. In some of the KBQA models the textual data is also used as another source besides the knowledge base; these hybrid models are studied in Chapter 7. In Chapter 8, a detailed explanation of some well-known real applications of the QA systems is provided. Eventually, open issues and future work on QA are discussed in Chapter 9. This book delivers a comprehensive overview on QA over text, QA over knowledge base, and hybrid QA systems which can be used by researchers starting in this field. It will help its readers to follow the state-of-the-art research in the area by providing essential and basic knowledge.

This book introduces some contemporary approaches on the application of fuzzy and hesitant fuzzy sets in machine learning tasks such as classification, clustering and dimension reduction. Many situations arise in machine learning algorithms in which applying methods for uncertainty modeling and multi-criteria decision making can lead to a better understanding of algorithms behavior as well as achieving good performances. Specifically, the present book is a collection of novel viewpoints on how fuzzy and hesitant fuzzy concepts can be applied to data uncertainty modeling as well as being used to solve multi-criteria decision making challenges raised in machine learning problems. Using the multi-criteria decision making framework, the book shows how different algorithms, rather than human experts, are employed to determine membership degrees. The book is expected to bring closer the communities of pure mathematicians of fuzzy sets and data scientists.

This book consists of chapters dedicated to the questions of cyber-physical system design and its usage for the chemical industry and new material design. Also, the contribution of the book covers scientific research and their results for cyber-physical systems design and application in the energy domain and solutions regarding engineering education for cyber-physical systems design. The book offers unique content for researchers and practitioners who are looking for new knowledge and skills in the framework of Industry 4.0 solutions. The book also benefits researchers and practitioners in chemistry and new material design and manufacturing to understand how cyber-physical systems can be applied to increase efficiency and performance. The target audience of the book are practitioners, enterprises representatives, scientists, Ph.D. and master students who perform scientific research or applications of cyber-physical systems in the concept of Industry 4.0.

This book combines energy economics and big data modeling analysis in energy conversion and management and comprehensively introduces the relevant theories, key technologies, and application examples of the smart energy economy. With the help of time series big data modeling results, energy economy managers develop reasonable and feasible pricing mechanisms of electricity price and improve the absorption capacity of the power grid. In addition, they also carry out scientific power equipment scheduling and cost-benefit analysis according to the results of data mining, so as to avoid the loss caused by accidental damage of equipment. Energy users adjust their power consumption behavior through the modeling results provided and achieve the effect of energy saving and emission reduction while reasonably reducing the electricity expenditure. This book provides an important reference for professionals in related fields such as smart energy, smart economy, energy Internet, artificial intelligence, energy economics and policy.

This second book by the author on WSNs focuses on the concepts of energy, and energy harvesting and management techniques. Definitions and terminologies are made clear without leaning on the relaxing assumption that they are already known or easily reachable, the reader is not to be diverted from the main course. Neatly drawn figures assist in viewing and imagining the offered topics. To make energy related topics felt and seen, the adopted technologies as well as their manufacturers are presented in details. With such a depth, this book is intended for a wide audience, it is meant to be helper and motivator, for the senior undergraduates, postgraduates, researchers, and practitioners; concepts and energy related applications are laid out, research and practical issues are backed by appropriate literature, and new trends are put under focus. For senior undergraduate students, it familiarizes with conceptual foundations and practical projects implementations. Also, it is intended for graduate students working on their thesis and in need of specific knowledge on WSNs and the related energy harvesting and management techniques. Moreover, it is targeting researchers and practitioners interested in features and applications of WSNs, and on the available energy harvesting and management projects and testbeds. Exercises at the end of each chapter are not just questions and answers; they are not limited to recapitulate ideas. Their design objective is not bound to be a methodical review of the provided concepts, but rather as a motivator for lot more of searching, finding, and comparing beyond what has been presented in the book.

Blockchain Driven Supply Chains and Enterprise Information Systems examines initiatives for blockchain implementation in supply chain management and the integration of blockchain technology with existing enterprise management applications. The authors aim to establish common ground to provide solutions and best practices in the supply chain field, while tackling the challenges faced when integrating blockchain in supply chain policy. Chapters address both design and implementation aspects of supply chain platforms and enterprise information systems, and provide real-world use cases and examples from industry that address the impacts of using blockchain in the modern supply chain.

This book is interesting and full of new ideas. It provokes the curiosity of the readers. The book targets both researchers and practitioners. The students and the researchers will acquire knowledge about ant colony optimization and its possible applications as well as practitioners will find new ideas and solutions of their combinatorial optimization and decision-making problems. Ant colony optimization is between the best method for solving difficult optimization problems arising in real life and industry. It has obtained distinguished results on some applications with very restrictive constraints. The reader will find theoretical aspects of ant method as well as applications on a variety of problems. The following applications could be mentioned: multiple knapsack problem, which is an important economical problem; grid scheduling problem; GPS surveying problem; E. coli cultivation modeling; wireless sensor network positioning; image edges detection; workforce planning.

The papers in this proceeding discuss current and future trends in wearable communications and personal health management through the use of wireless body area networks (WBAN). The authors posit new technologies that can provide trustworthy communications mechanisms from the user to medical health databases. The authors discuss not only on-body devices, but also technologies providing information in-body. Also discussed are dependable communications combined with accurate localization and behavior analysis, which will benefit WBAN technology and make the healthcare processes more effective. The papers were presented at the 13th EAI International Conference on Body Area Networks (BODYNETS 2018), Oulu, Finland, 02-03 October 2018.

This textbook introduces major topics that include quantum bits, superposition, entanglement, logic gates, quantum search algorithm, quantum Fourier transform, inverse quantum Fourier transform, Shor's order-finding algorithm and phase estimation. Everyone can write algorithms and programs in the cloud making using IBM's quantum computers that support IBM Q Experience which contains the composer, open quantum assembly language, simulators and real quantum devices. Furthermore, this book teaches you how to use open quantum assembly language to write quantum programs for dealing with complex problems. Through numerous examples and exercises, readers will learn how to write a quantum program with open quantum assembly language for solving any problem from start to complete. This book includes six main chapters: *Quantum Bits and Quantum Gates-learn what quantum bits are, how to declare and measure them, what quantum gates are and how they work on a simulator or a real device in the cloud. *Boolean Algebra and its Applications-learn how to decompose CCNOT gate into six CNOT gates and nine gates of one bit and how to use NOT gates, CNOT gates and CCNOT gates to implement logic operations including NOT, OR, AND, NOR, NAND, Exclusive-OR (XOR) and Exclusive-NOR (XNOR). *Quantum Search Algorithm and its Applications-learn core concepts of quantum search algorithm and how to write quantum programs to implement core concepts of quantum search algorithm for solving two famous NP-complete problems that are the satisfiability problem in n Boolean variables and m clauses and the clique problem in a graph with n vertices and q edges. *Quantum Fourier Transform and its Applications-learn core concepts of quantum Fourier transform and inverse quantum Fourier transform and how to write quantum programs to implement them for solving two real applications that are to compute the period and the frequency of two given oracular functions. *Order-Finding and Factoring-learn core concepts of Shor's order-finding algorithm and how to write quantum programs to implement Shor's order-finding algorithm for completing the prime factorization to 15. Phase Estimation and its Applications-learn core concepts of phase estimation and quantum counting and how to write quantum programs to implement them to compute the number of solution(s) in the independent set problem in a graph with two vertices and one edge.

Database Support for Workflow Management: The WIDE Project presents the results of the ESPRIT WIDE project on advanced database support for workflow management. The book discusses the state of the art in combining database management and workflow management technology, especially in the areas of transaction and exception management. This technology is complemented by a high-level conceptual workflow model and associated workflow application design methodology. In WIDE, advanced base technology is applied, like a distributed computing model based on the corba standard. The usability of the WIDE approach is documented in this book by a discussion of two real-world applications from the insurance and health care domains. Database Support for Workflow Management: The WIDE Project serves as an excellent reference, and may be used for advanced courses on database and workflow management systems.