In the digital economy, a new type of business activity, digital entrepreneurship, has developed rapidly and required breakthrough technologies such as blockchain, big data, cloud technologies, and more. There is a need for a comprehensive resource that provides all-encompassing insight into the essence, special aspects, models, and international best practices of e-business based on various digital technologies in various high-tech markets. Digital Technologies for Entrepreneurship in Industry 4.0 provides theoretical frameworks and recent results of research in this sphere. It substantiates digital entrepreneurship, discusses the practical experience of its implementation, and develops the scientific and methodological recommendations for the development of its infrastructural provision and regulation of provision of its competitiveness. Covering topics such as investment attractiveness, corporate reporting modernization, and public-private partnership mechanisms, this premier reference source is an excellent resource for entrepreneurs, business executives and managers, investors, IT managers, students and faculty of higher education, researchers, and academicians.

Advances in Computers, Volume 119, presents innovations in computer hardware, software, theory, design, and applications, with this updated volume including new chapters on Fast Execution of RDF Queries Using Apache Hadoop, A Study of DVFS Methodologies for Multicore Systems with Islanding Feature, Effectiveness of State-of-the-art Dynamic Analysis Techniques in Identifying Diverse Android Malware and Future Enhancements, Eyeing the Patterns: Data Visualization Using Doubly-Seriated Color Heatmaps, Eigenvideo for Video Indexing.

Methods and Techniques in Deep Learning Introduces multiple state-of-the-art deep learning architectures for mmWave radar in a variety of advanced applications Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions provides a timely and authoritative overview of the use of artificial intelligence (AI)-based processing for various mmWave radar applications. Focusing on practical deep learning techniques, this comprehensive volume explains the fundamentals of deep learning, reviews cutting-edge deep metric learning techniques, describes different typologies of reinforcement learning (RL) algorithms, highlights how domain adaptation (DA) can be used for improving the performance of machine learning (ML) algorithms, and more. Throughout the book, readers are exposed to product-ready deep learning solutions while learning skills that are relevant for building any industrial-grade, sensor-based deep learning solution. A team of authors with more than 70 filed patents and 100 published papers on AI and sensor processing illustrates how deep learning is enabling a range of advanced industrial, consumer, and automotive applications of mmWave radars. In-depth chapters cover topics including multi-modal deep learning approaches, the elemental blocks required to formulate Bayesian deep learning, how domain adaptation (DA) can be used for improving the performance of machine learning algorithms, and geometric deep learning are used for processing point clouds. In addition, the book: Discusses various advanced applications and how their respective challenges have been addressed using different deep learning architectures and algorithms Describes deep learning in the context of computer vision, natural language processing, sensor processing, and mmWave radar sensors Demonstrates how deep parametric learning reduces the number of trainable parameters and improves the data flow Presents several human-machine interface (HMI) applications such as gesture recognition, human activity classification, human localization and tracking, in-cabin automotive occupancy sensing Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions is an invaluable resource for industry professionals, researchers, and graduate students working in systems engineering, signal processing, sensors, data science, and AI.

Systems Analysis and Synthesis: Bridging Computer Science and Information Technology presents several new graph-theoretical methods that relate system design to core computer science concepts, and enable correct systems to be synthesized from specifications. Based on material refined in the author's university courses, the book has immediate applicability for working system engineers or recent graduates who understand computer technology, but have the unfamiliar task of applying their knowledge to a real business problem. Starting with a comparison of synthesis and analysis, the book explains the fundamental building blocks of systems-atoms and events-and takes a graph-theoretical approach to database design to encourage a well-designed schema. The author explains how database systems work-useful both when working with a commercial database management system and when hand-crafting data structures-and how events control the way data flows through a system. Later chapters deal with system dynamics and modelling, rule-based systems, user psychology, and project management, to round out readers' ability to understand and solve business problems.

Artificial Intelligence in Cancer: Diagnostic to Tailored Treatment provides theoretical concepts and practical techniques of AI and its applications in cancer management, building a roadmap on how to use AI in cancer at different stages of healthcare. It discusses topics such as the impactful role of AI during diagnosis and how it can support clinicians to make better decisions, AI tools to help pathologists identify exact types of cancer, how AI supports tumor profiling and can assist surgeons, and the gains in precision for oncologists using AI tools. Additionally, it provides information on AI used for survival and remission/recurrence analysis. The book is a valuable source for bioinformaticians, cancer researchers, oncologists, clinicians and members of the biomedical field who want to understand the promising field of AI applications in cancer management.

Due to the growing prevalence of artificial intelligence technologies, schools, museums, and art galleries will need to change traditional ways of working and conventional thought processes to fully embrace their potential. Integrating virtual and augmented reality technologies and wearable devices into these fields can promote higher engagement in an increasingly digital world. Virtual and Augmented Reality in Education, Art, and Museums is an essential research book that explores the strategic role and use of virtual and augmented reality in shaping visitor experiences at art galleries and museums and their ability to enhance education. Highlighting a range of topics such as online learning, digital heritage, and gaming, this book is ideal for museum directors, tour developers, educational software designers, 3D artists, designers, curators, preservationists, conservationists, education coordinators, academicians, researchers, and students.

Data has never mattered more. Our lives are increasingly shaped by it and how it is defined, collected and used. But who counts in the collection, analysis and application of data? This important book is the first to look at queer data - defined as data relating to gender, sex, sexual orientation and trans identity/history. The author shows us how current data practices reflect an incomplete account of LGBTQ lives and helps us understand how data biases are used to delegitimise the everyday experiences of queer people. Guyan demonstrates why it is important to understand, collect and analyse queer data, the benefits and challenges involved in doing so, and how we might better use queer data in our work. Arming us with the tools for action, this book shows how greater knowledge about queer identities is instrumental in informing decisions about resource allocation, changes to legislation, access to services, representation and visibility.

Malware Diffusion Models for Wireless Complex Networks: Theory and Applications provides a timely update on malicious software (malware), a serious concern for all types of network users, from laymen to experienced administrators. As the proliferation of portable devices, namely smartphones and tablets, and their increased capabilities, has propelled the intensity of malware spreading and increased its consequences in social life and the global economy, this book provides the theoretical aspect of malware dissemination, also presenting modeling approaches that describe the behavior and dynamics of malware diffusion in various types of wireless complex networks. Sections include a systematic introduction to malware diffusion processes in computer and communications networks, an analysis of the latest state-of-the-art malware diffusion modeling frameworks, such as queuing-based techniques, calculus of variations based techniques, and game theory based techniques, also demonstrating how the methodologies can be used for modeling in more general applications and practical scenarios.

Virtual reality (VR) refers to technologies that use headsets to generate realistic images, sounds and other sensations that replicate a real-world environment or create an imaginary setting. VR also simulates a user's physical presence in this environment. In virtual reality, six degrees of freedom allows users to not only look around, but also to move around the virtual world and look from above, below or behind objects. To have a true VR experience, the hardware must provide six degrees of freedom, using both orientation tracking (rotational) and positional tracking (translation). This book is addressed to video experts who want to understand the basics of 3D representations and multi-camera video processing to target new immersive media applications. Unlike single camera video coding, future VR technologies address new challenges that arise beyond compression-only, including the pre- and post-processing (depth acquisition and 3D rendering). This book is inspired by the MPEG-I (immersive media) and JPEG-PLENO (plenoptic media) standardization activities, and offers a glimpse of their underlying technologies.

A new kind of manifesto for the working woman, with practical guidance on building wealth as well as inspiration for harnessing the freedom and power that comes from a breadwinning mindset. Women are now the main breadwinner in one-in-four households in the UK. Yet the majority of women still aren't being brought up to think like breadwinners. In fact, they're actively discouraged - by institutional bias and subconscious beliefs - from building their own wealth, pursuing their full earning potential, and providing for themselves and others financially. The result is that women earn less, owe more, and have significantly less money saved and invested for the future than men do. And if women do end up as the main breadwinner, they've been conditioned to feel reluctant and unprepared to manage the role. In Think Like a Breadwinner, financial expert Jennifer Barrett reframes what it really means to be a breadwinner by dismantling the narrative that women don't - and shouldn't - take full financial responsibility to create the lives they want. Featuring a wide variety of case studies from women at all stages of their careers and financial lives, Barrett shares the secrets of women who already think like breadwinners. Barrett reveals not only the importance of women building their own wealth, but also the freedom and power that comes with it. 'Barrett's manifesto is a must read for any woman at any stage of her career.' - Eve Rodsky, author of Fair Play

This book investigates multiple facets of the emerging discipline of Tangible, Embodied, and Embedded Interaction (TEI). This is a story of atoms and bits. We explore the interweaving of the physical and digital, toward understanding some of their wildly varying hybrid forms and behaviors. Spanning conceptual, philosophical, cognitive, design, and technical aspects of interaction, this book charts both history and aspirations for the future of TEI. We examine and celebrate diverse trailblazing works, and provide wide-ranging conceptual and pragmatic tools toward weaving the animating fires of computation and technology into evocative tangible forms. We also chart a path forward for TEI engagement with broader societal and sustainability challenges that will profoundly (re)shape our children's and grandchildren's futures. We invite you all to join this quest.

Advanced computational intelligence techniques have been designed and developed in recent years to cope with various big data challenges and provide fast and efficient analytics that assist in making critical decisions. With the rapid evolution and development of internet-based services and applications, this technology is receiving attention from researchers, industries, and academic communities and requires additional study. Convergence of Big Data Technologies and Computational Intelligent Techniques considers recent advancements in big data and computational intelligence across fields and disciplines and discusses the various opportunities and challenges of adoption. Covering topics such as deep learning, data mining, smart environments, and high-performance computing, this reference work is crucial for computer scientists, engineers, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

Cell phone apps share location information; software companies store user data in the cloud; biometric scanners read fingerprints; employees of some businesses have microchips implanted in their hands. In each of these instances we trade a share of privacy or an aspect of identity for greater convenience or improved security. What Robert M. Pallitto asks in Bargaining with the Machine is whether we are truly making such bargains freely - whether, in fact, such a transaction can be conducted freely or advisedly in our ever more technologically sophisticated world. Pallitto uses the social theory of bargaining to look at the daily compromises we make with technology. Specifically, he explores whether resisting these 'bargains' is still possible when the technologies in question are backed by persuasive, even coercive, corporate and state power. Who, he asks, is proposing the bargain? What is the balance of bargaining power? What is surrendered and what is gained? And are the perceived and the actual gains and losses the same - that is, what is hidden? At the center of Pallitto's work is the paradox of bargaining in a world of limited agency. Assurances that we are in control are abundant whether we are consumers, voters, or party to the social contract. But when purchasing goods from a technological behemoth like Amazon, or when choosing a candidate whose image is crafted and shaped by campaign strategists and media outlets, how truly free, let alone informed, are our choices? The tension between claims of agency and awareness of its limits is the site where we experience our social lives - and nowhere is this tension more pronounced than in the surveillance society. This book offers a cogent analysis of how that complex, contested, and even paradoxical experience arises as well as an unusually clear and troubling view of the consequential compromises we may be making.

Artificial Intelligence Medicine: Technical Basis and Clinical Applications presents a comprehensive overview of the field, ranging from its history and technical foundations, to specific clinical applications and finally to prospects. Artificial Intelligence (AI) is expanding across all domains at a breakneck speed. Medicine, with the availability of large multidimensional datasets, lends itself to strong potential advancement with the appropriate harnessing of AI. The integration of AI can occur throughout the continuum of medicine: from basic laboratory discovery to clinical application and healthcare delivery. Integrating AI within medicine has been met with both excitement and scepticism. By understanding how AI works, and developing an appreciation for both limitations and strengths, clinicians can harness its computational power to streamline workflow and improve patient care. It also provides the opportunity to improve upon research methodologies beyond what is currently available using traditional statistical approaches. On the other hand, computers scientists and data analysts can provide solutions, but often lack easy access to clinical insight that may help focus their efforts. This book provides vital background knowledge to help bring these two groups together, and to engage in more streamlined dialogue to yield productive collaborative solutions in the field of medicine.

Based on scientific understanding and empirical evidence of how humans understand and interact with robotic and autonomous systems, the author reviews the concerns that have been raised around the deployment of AI and robots in human society, and the potential for disruption and harm. He explains why transparency ought to be a fundamental design consideration for Human Computer Interaction (HCI) and artificial intelligent systems. Starting with a survey of global research in the field and what transparency means in the wider context of trust, control and ethics, the author then introduces a transparent robot control architecture, and the impact of transparency using real-time displays. He presents a case study of a muttering robot, and covers current and upcoming standards for transparency, as well as future perspectives for the design, manufacture and operation of autonomous robotic systems. Specifically, chapters cover transparency in the wider context of trust; a transparent robot control architecture, the impact of transparency using real-time displays, transparency using audio - the Muttering Robot, the effects of appearance on transparency, synthesis and further work, and several examples of Instinct reactive planner commands. This book provides key insights into transparency in robots and autonomous systems for industry, academic researchers and engineers working on intelligent autonomous system design, human robot interaction, AI, and machine ethics. It also offers points of interest for professionals developing governmental or organisational policies and standards for the design of intelligent autonomous and AI systems, and government and standard bodies working in the emerging applications of AI.

Wireless sensor networks have a range of applications, including military uses and in environmental monitoring. When an area of interest is inaccessible by conventional means, such a network can be deployed in ways resulting in a random distribution of the sensors. Randomly Deployed Wireless Sensor Networks offers a probabilistic method to model and analyze these networks. The book considers the network design, coverage, target detection, localization and tracking of sensors in randomly deployed wireless networks, and proposes a stochastic model. It quantifies the relationship between parameters of the network and its performance, and puts forward a communication protocol. The title provides analyses and formulas, giving engineering insight into randomly deployed wireless sensor networks. Five chapters consider the analysis of coverage performance; working modes and scheduling mechanisms; the relationship between sensor behavior and network performance properties; probabilistic forwarding routing protocols; localization methods for multiple targets and target number estimation; and experiments on target localization and tracking with a Mica sensor system.

Molecular simulation allows researchers unique insight into the structures and interactions at play in fluids. Since publication of the first edition of Molecular Simulation of Fluids, novel developments in theory, algorithms and computer hardware have generated enormous growth in simulation capabilities. This 2nd edition has been fully updated and expanded to highlight this recent progress, encompassing both Monte Carlo and molecular dynamic techniques, and providing details of theory, algorithms and both serial and parallel implementations. Beginning with a clear introduction and review of theoretical foundations, the book goes on to explore intermolecular potentials before discussing the calculation of molecular interactions in more detail. Monte Carlo simulation and integrators for molecular dynamics are then discussed further, followed by non-equilibrium molecular dynamics and molecular simulation of ensembles and phase equilibria. The use of object-orientation is examined in detail, with working examples coded in C++. Finally, practical parallel simulation algorithms are discussed using both MPI and GPUs, with the latter coded in CUDA. Drawing on the extensive experience of its expert author, Molecular Simulation of Fluids: Theory, Algorithms, Object-Orientation, and Parallel Computing 2nd Edition is a practical, accessible guide to this complex topic for all those currently using, or interested in using, molecular simulation to study fluids.