The only book of its kind to look at how our legal system needs to change to accommodate a world in which machines, in addition to people, make decisions. For years, robots were solely a matter of science fiction. Today, artificial intelligence technologies serve to accelerate our already fast-paced lives even further. From Apple's Siri to the Google Car to GPS, machines and technologies that make decisions and take action without direct human supervision have become commonplace in our daily lives. As a result, laws must be amended to protect companies that produce robots and the people that buy and use them. This book provides an extensive examination of how numerous legal areas-including liability, traffic, zoning, and international and constitutional law-must adapt to the widespread use of artificial intelligence in nearly every area of our society. The author scrutinizes the laws governing such fields as transportation, medicine, law enforcement, childcare, and real estate development. Describes court cases, regulations, and statutes that are affected by the technological advances of artificial intelligence Eschews overtly technical or legalistic discussions to provide clear, accessible information Discusses a number of popular, topical, and controversial technologies, providing historical background for each and their legal implications Focuses on devices that are already in use to illustrate where the law falls short in governing artificial intelligence and how legal models should be amended

Due to growing technologies for learning processes, universities are making modifications in the development and construction of courses and services they offer. ""Monitoring and Assessment in Online Collaborative Environments: Emergent Computational Technologies for E-Learning Support"" focuses on new models and systems that perform efficient evaluation of student activity in Internet-based education. Containing research from leading international experts, this Premier Reference Source introduces original case studies and experiences of educators worldwide regarding e-learning activities.

This book presents recently developed computational approaches for the study of reactive materials under extreme physical and thermodynamic conditions. It delves into cutting edge developments in simulation methods for reactive materials, including quantum calculations spanning nanometer length scales and picosecond timescales, to reactive force fields, coarse-grained approaches, and machine learning methods spanning microns and nanoseconds and beyond. These methods are discussed in the context of a broad range of fields, including prebiotic chemistry in impacting comets, studies of planetary interiors, high pressure synthesis of new compounds, and detonations of energetic materials. The book presents a pedagogical approach for these state-of-the-art approaches, compiled into a single source for the first time. Ultimately, the volume aims to make valuable research tools accessible to experimentalists and theoreticians alike for any number of scientific efforts, spanning many different types of compounds and reactive conditions.

This book has a focus on the development and deployment of the Industrial Internet of Things (IIoT) paradigm, discussing frameworks, methodologies, benefits and limitations, as well as providing case studies of employing the IoT vision in the industrial domain. IIoT is becoming an attractive business reality for many organisations such as manufacturing, logistics, oil and gas, energy and other utilities, mining, aviation, and many more. The opportunities for this paradigm are huge, and according to one report, the IIoT market is predicted to reach $125 billion by 2021. The driving philosophy behind the IIoT is that smart machines are better than humans at accurately capturing, analysing and communicating real-time data. The underlying technologies include distributed computing, machine learning, artificial intelligence, and machine-to-machine communication, with a typical IIoT system consisting of intelligent systems (applications, controllers, sensors, and security mechanisms), data communication infrastructure (cloud computing, edge computing, etc.), data analytics (to support business intelligence and corporate decision making), and most importantly the human element. The promised benefits of the IIoT include enhanced safety, better reliability, smart metering, inventory management, equipment tracking, and facilities management. There are, however, numerous issues that are also becoming the focus of active research, such as concerns regarding service availability, data security, and device communication. Lack of ubiquitous interoperability between heterogeneous devices is also a major concern. This book intends to fill a gap in the IIoT literature by providing the scientific contributions and latest developments from researchers and practitioners of international repute, focusing on frameworks, methodologies, benefits, and inherent issues/barriers to connected environments, especially in industrial settings. The intended audience includes network specialists, hardware engineers, and security experts who wish to adopt newer approaches for device connectivity, IoT security, and sensor-based devices design. University level students, researchers and practitioners will also find the latest innovation in technology and newer approaches relevant to the IIoT from a distributed computing perspective.

This book presents a complete and accurate study of arithmetic and algebraic circuits. The first part offers a review of all important basic concepts: it describes simple circuits for the implementation of some basic arithmetic operations; it introduces theoretical basis for residue number systems; and describes some fundamental circuits for implementing the main modular operations that will be used in the text. Moreover, the book discusses floating-point representation of real numbers and the IEEE 754 standard. The second and core part of the book offers a deep study of arithmetic circuits and specific algorithms for their implementation. It covers the CORDIC algorithm, and optimized arithmetic circuits recently developed by the authors for adders and subtractors, as well as multipliers, dividers and special functions. It describes the implementation of basic algebraic circuits, such as LFSRs and cellular automata. Finally, it offers a complete study of Galois fields, showing some exemplary applications and discussing the advantages in comparison to other methods. This dense, self-contained text provides students, researchers and engineers, with extensive knowledge on and a deep understanding of arithmetic and algebraic circuits and their implementation.

While much has been written about strategic information systems planning, the integration of strategic planning with portfolio management has been ignored, leaving the potential benefits of their combined approach to planning yet to be explored. ""Strategic Information Technology and Portfolio Management"" bridges the knowledge between information technology planning, enterprise architecture, and IT portfolio management taking into account their financial impact. Intended for IT professionals, researchers, and academicians, this book provides techniques and tools appropriate for building application portfolios and developing strategies which increase financial performance.

This book discusses important topics for engineering and managing software startups, such as how technical and business aspects are related, which complications may arise and how they can be dealt with. It also addresses the use of scientific, engineering, and managerial approaches to successfully develop software products in startup companies. The book covers a wide range of software startup phenomena, and includes the knowledge, skills, and capabilities required for startup product development; team capacity and team roles; technical debt; minimal viable products; startup metrics; common pitfalls and patterns observed; as well as lessons learned from startups in Finland, Norway, Brazil, Russia and USA. All results are based on empirical findings, and the claims are backed by evidence and concrete observations, measurements and experiments from qualitative and quantitative research, as is common in empirical software engineering. The book helps entrepreneurs and practitioners to become aware of various phenomena, challenges, and practices that occur in real-world startups, and provides insights based on sound research methodologies presented in a simple and easy-to-read manner. It also allows students in business and engineering programs to learn about the important engineering concepts and technical building blocks of a software startup. It is also suitable for researchers at different levels in areas such as software and systems engineering, or information systems who are studying advanced topics related to software business.

Outsourcing is currently one of the hottest topics in business practices and in particular in the field of management information systems (MIS) education. Outsourcing Management Information Systems focuses on concepts, processes, and methodologies for firms who are planning to undertake, or are currently involved in, outsourcing decisions in the field of management information systems. Outsourcing Management Information Systems helps MIS managers to manage outsourcing projects by establishing performance metrics, including: appropriate risk factor considerations, structuring a centralized architecture that best suits the organization, and avoiding the case study pitfalls reported in the literature.

As recently as 1968, computer scientists were uncertain how best to interconnect even two computers. The notion that within a few decades the challenge would be how to interconnect millions of computers around the globe was too far-fetched to contemplate. Yet, by 1988, that is precisely what was happening. The products and devices developed in the intervening years-such as modems, multiplexers, local area networks, and routers-became the linchpins of the global digital society. How did such revolutionary innovation occur? This book tells the story of the entrepreneurs who were able to harness and join two factors: the energy of computer science researchers supported by governments and universities, and the tremendous commercial demand for Internetworking computers. The centerpiece of this history comes from unpublished interviews from the late 1980s with over 80 computing industry pioneers, including Paul Baran, J.C.R. Licklider, Vint Cerf, Robert Kahn, Larry Roberts, and Robert Metcalfe. These individuals give us unique insights into the creation of multi-billion dollar markets for computer-communications equipment, and they reveal how entrepreneurs struggled with failure, uncertainty, and the limits of knowledge.

This book is a collection of contributions honouring Arnon Avron's seminal work on the semantics and proof theory of non-classical logics. It includes presentations of advanced work by some of the most esteemed scholars working on semantic and proof-theoretical aspects of computer science logic. Topics in this book include frameworks for paraconsistent reasoning, foundations of relevance logics, analysis and characterizations of modal logics and fuzzy logics, hypersequent calculi and their properties, non-deterministic semantics, algebraic structures for many-valued logics, and representations of the mechanization of mathematics. Avron's foundational and pioneering contributions have been widely acknowledged and adopted by the scientific community. His research interests are very broad, spanning over proof theory, automated reasoning, non-classical logics, foundations of mathematics, and applications of logic in computer science and artificial intelligence. This is clearly reflected by the diversity of topics discussed in the chapters included in this book, all of which directly relate to Avron's past and present works. This book is of interest to computer scientists and scholars of formal logic.

Wireless Sensor Networks (WSNs) and the Internet of Things are facing tremendous advances both in terms of energy-efficiency as well as in the number of available applications. Consequently, there are challenges that need to be tackled for the future generation of WSNs. After giving an overview of the WSN protocols and IEEE 802.15.4 standard, this book proposes IEEE 802.15.4 Medium Access Control (MAC) sub-layer performance enhancements by employing not only RTS/CTS combined with packet concatenation but also scheduled channel poling (MC-SCP). Results have shown that the use of the RTS/CTS mechanism improves channel efficiency by decreasing the deferral time before transmitting a data packet. Furthermore, the Sensor Block Acknowledgment MAC (SBACK-MAC) protocol enables more efficiency as it allows the aggregation of several acknowledgement responses in one special Block Acknowledgment (BACK) Response packet. The throughput and delay performance have been mathematically derived under both ideal conditions (a channel environment with no transmission errors) and non-ideal conditions (with transmission errors). Simulation results successfully validate the proposed analytical models. This research reveals the importance of an appropriate design for the MAC sub-layer protocol for the desired WSN application. Depending on the mission of the WSN application, different protocols are required. Therefore, the overall performance of a WSN application certainly depends on the development and application of suitable e.g., MAC, network layer protocols.

This book features research presented and discussed during the Research & Innovation Forum (Rii Forum) 2020. As such, this book offers a unique insight into emerging topics, issues and developments pertinent to the fields of technology, innovation and education and their social impact. Papers included in this book apply inter- and multi-disciplinary approaches to query such issues as technology-enhanced teaching and learning, smart cities, information systems, cognitive computing and social networking. What brings these threads of the discussion together is the question of how advances in computer science - which are otherwise largely incomprehensible to researchers from other fields - can be effectively translated and capitalized on so as to make them beneficial for society as a whole. In this context, Rii Forum and Rii Forum proceedings offer an essential venue where diverse stakeholders, including academics, the think tank sector and decision-makers, can engage in a meaningful dialogue with a view to improving the applicability of advances in computer science.

Complexes of physically interacting proteins constitute fundamental functional units that drive almost all biological processes within cells. A faithful reconstruction of the entire set of protein complexes (the "complexosome") is therefore important not only to understand the composition of complexes but also the higher level functional organization within cells. Advances over the last several years, particularly through the use of high-throughput proteomics techniques, have made it possible to map substantial fractions of protein interactions (the "interactomes") from model organisms including Arabidopsis thaliana (a flowering plant), Caenorhabditis elegans (a nematode), Drosophila melanogaster (fruit fly), and Saccharomyces cerevisiae (budding yeast). These interaction datasets have enabled systematic inquiry into the identification and study of protein complexes from organisms. Computational methods have played a significant role in this context, by contributing accurate, efficient, and exhaustive ways to analyze the enormous amounts of data. These methods have helped to compensate for some of the limitations in experimental datasets including the presence of biological and technical noise and the relative paucity of credible interactions. In this book, we systematically walk through computational methods devised to date (approximately between 2000 and 2016) for identifying protein complexes from the network of protein interactions (the protein-protein interaction (PPI) network). We present a detailed taxonomy of these methods, and comprehensively evaluate them for protein complex identification across a variety of scenarios including the absence of many true interactions and the presence of false-positive interactions (noise) in PPI networks. Based on this evaluation, we highlight challenges faced by the methods, for instance in identifying sparse, sub-, or small complexes and in discerning overlapping complexes, and reveal how a combination of strategies is necessary to accurately reconstruct the entire complexosome.

This book describes the development of an intrusion detection system for online poker, which uses player's game strategy as the behavioral profile. The system is improved by modifications to the similarity measure functions and different ways of representing behavioral signatures. The system is further enhanced by inclusion of spatial, temporal and contextual information about the environment alongside the user's behavior. Possibility of creation of artificial behavioral profiles and use of such profiles for spoofing of behavior-based security systems is investigated and promising results are achieved. In a somewhat related research, recognizing importance of games in our experiments, it is proven that poker is a game of skill. Finally, a number of games are analyzed in terms of their spatial ontologies.

This textbook treats graph colouring as an algorithmic problem, with a strong emphasis on practical applications. The author describes and analyses some of the best-known algorithms for colouring graphs, focusing on whether these heuristics can provide optimal solutions in some cases; how they perform on graphs where the chromatic number is unknown; and whether they can produce better solutions than other algorithms for certain types of graphs, and why. The introductory chapters explain graph colouring, complexity theory, bounds and constructive algorithms. The author then shows how advanced, graph colouring techniques can be applied to classic real-world operational research problems such as designing seating plans, sports scheduling, and university timetabling. He includes many examples, suggestions for further reading, and historical notes, and the book is supplemented by an online suite of downloadable code. The book is of value to researchers, graduate students, and practitioners in the areas of operations research, theoretical computer science, optimization, and computational intelligence. The reader should have elementary knowledge of sets, matrices, and enumerative combinatorics.

Systems Engineering for Business Process Change: New Directions is a collection of papers resulting from an EPSRC managed research programme set up to investigate the relationships between Legacy IT Systems and Business Processes. The papers contained in this volume report the results from the projects funded by the programme, which ran between 1997 and 2001. An earlier volume, published in 2000, reported interim results.
Bringing together researchers from diverse backgrounds in Computer Science, Information Systems, Engineering and Business Schools, this book explores the problems experienced by IT-dependent businesses that have to implement changing business processes in the context of their investment in legacy systems. The book presents some of the solutions investigated through the collaborations set up within the research programme.
Whether you are a researcher interested in the ideas that were generated by the research programme, or a user trying to understand the nature of the problems and their solutions, you cannot fail to be inspired by the writings contained in this volume.

This book highlights interdisciplinary insights, latest research results, and technological trends in Business Intelligence and Modelling in fields such as: Business Intelligence, Business Transformation, Knowledge Dissemination & Implementation, Modeling for Logistics, Business Informatics, Business Model Innovation, Simulation Modelling, E-Business, Enterprise & Conceptual Modelling, etc. The book is divided into eight sections, grouping emerging marketing technologies together in a close examination of practices, problems and trends. The chapters have been written by researchers and practitioners that demonstrate a special orientation in Strategic Marketing and Business Intelligence. This volume shares their recent contributions to the field and showcases their exchange of insights.

With the ever-present growth in technology, opportunities to explore and experience technology at an early age are increasingly important in order to develop problem-solving and thinking skills. ""Technology for Early Childhood Education and Socialization: Developmental Applications and Methodologies"" provides readers with valuable and authentic research on how technology relates to early childhood growth. Including international perspectives on technology and education from expert authors, this book discusses important issues of assessment, teacher education, special education, and family involvement in terms of technology.

The past few years have seen a major change in computing systems, as growing data volumes and stalling processor speeds require more and more applications to scale out to clusters. Today, a myriad data sources, from the Internet to business operations to scientific instruments, produce large and valuable data streams. However, the processing capabilities of single machines have not kept up with the size of data. As a result, organizations increasingly need to scale out their computations over clusters. At the same time, the speed and sophistication required of data processing have grown. In addition to simple queries, complex algorithms like machine learning and graph analysis are becoming common. And in addition to batch processing, streaming analysis of real-time data is required to let organizations take timely action. Future computing platforms will need to not only scale out traditional workloads, but support these new applications too. This book, a revised version of the 2014 ACM Dissertation Award winning dissertation, proposes an architecture for cluster computing systems that can tackle emerging data processing workloads at scale. Whereas early cluster computing systems, like MapReduce, handled batch processing, our architecture also enables streaming and interactive queries, while keeping MapReduce's scalability and fault tolerance. And whereas most deployed systems only support simple one-pass computations (e.g., SQL queries), ours also extends to the multi-pass algorithms required for complex analytics like machine learning. Finally, unlike the specialized systems proposed for some of these workloads, our architecture allows these computations to be combined, enabling rich new applications that intermix, for example, streaming and batch processing. We achieve these results through a simple extension to MapReduce that adds primitives for data sharing, called Resilient Distributed Datasets (RDDs). We show that this is enough to capture a wide range of workloads. We implement RDDs in the open source Spark system, which we evaluate using synthetic and real workloads. Spark matches or exceeds the performance of specialized systems in many domains, while offering stronger fault tolerance properties and allowing these workloads to be combined. Finally, we examine the generality of RDDs from both a theoretical modeling perspective and a systems perspective. This version of the dissertation makes corrections throughout the text and adds a new section on the evolution of Apache Spark in industry since 2014. In addition, editing, formatting, and links for the references have been added.

This book illustrates all the concepts of web mining from gathering the web data sources to discovering and representing the extracted knowledge. This book is ideal for many researchers and scholars who are interested in a reference book that involves all the techniques and algorithms that are applied to a Web environment. This book illustrates, analyzes, and compares all the techniques, applications, and algorithms that are used in Web mining categories and provides a thorough overview to undergraduates, postgraduates, and scholars who wish to learn more about Web and data mining. The goal of this book is to foster transformative, multidisciplinary, and novel approaches that introduce the practical approach of analyzing various web data sources and extracting knowledge by taking into consideration the unique challenges present in the environment. This book provides a complete overview of Web mining techniques and applications; it will be crucial for postgraduate students who want to understand the Web environment better and do not know the differences between Web mining and data mining. It will also be helpful for companies and organizations to discover practical solutions to handle their internet data in a more efficient way, as well as undergraduate students in software engineering and computer science engineering departments who do not have a complete reference book that offers them a full explanation about Web mining.