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This book discusses the computational geometry, topology and physics of digital images and video frame sequences. This trio of computational approaches encompasses the study of shape complexes, optical vortex nerves and proximities embedded in triangulated video frames and single images, while computational geometry focuses on the geometric structures that infuse triangulated visual scenes. The book first addresses the topology of cellular complexes to provide a basis for an introductory study of the computational topology of visual scenes, exploring the fabric, shapes and structures typically found in visual scenes. The book then examines the inherent geometry and topology of visual scenes, and the fine structure of light and light caustics of visual scenes, which bring into play catastrophe theory and the appearance of light caustic folds and cusps. Following on from this, the book introduces optical vortex nerves in triangulated digital images. In this context, computational physics is synonymous with the study of the fine structure of light choreographed in video frames. This choreography appears as a sequence of snapshots of light reflected and refracted from surface shapes, providing a solid foundation for detecting, analyzing and classifying visual scene shapes.
Over the past 60 years, artificial intelligence has grown from an academic field of research to a ubiquitous array of tools used in everyday technology. Despite its many recent successes, certain meaningful facets of computational intelligence have yet to be thoroughly explored, such as a wide array of complex mental tasks that humans carry out easily, yet are difficult for computers to mimic. A prime example of a domain in which human intelligence thrives, but machine understanding is still fairly limited, is music. Over recent decades, many researchers have used computational tools to perform tasks like genre identification, music summarization, music database querying, and melodic segmentation. While these are all useful algorithmic solutions, we are still a long way from constructing complete music agents able to mimic (at least partially) the complexity with which humans approach music. One key aspect that hasn't been sufficiently studied is that of sequential decision-making in musical intelligence. Addressing this gap, the book focuses on two aspects of musical intelligence: music recommendation and multi-agent interaction in the context of music. Though motivated primarily by music-related tasks, and focusing largely on people's musical preferences, the work presented in this book also establishes that insights from music-specific case studies can also be applicable in other concrete social domains, such as content recommendation.Showing the generality of insights from musical data in other contexts provides evidence for the utility of music domains as testbeds for the development of general artificial intelligence techniques.Ultimately, this thesis demonstrates the overall value of taking a sequential decision-making approach in settings previously unexplored from this perspective.
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 book explores various renewal processes in the context of probability theory, uncertainty theory and chance theory. It also covers the applications of these renewal processes in maintenance models and insurance risk models. The methods used to derive the limit of the renewal rate, the reward rate, and the availability rate are of particular interest, as they can easily be extended to the derivation of other models. Its comprehensive and systematic treatment of renewal processes, renewal reward processes and the alternating renewal process is one of the book's major features, making it particularly valuable for readers who are interested in learning about renewal theory. Given its scope, the book will benefit researchers, engineers, and graduate students in the fields of mathematics, information science, operations research, industrial engineering, etc.
The history of robotics and artificial intelligence in many ways is also the history of humanity's attempts to control such technologies. From the Golem of Prague to the military robots of modernity, the debate continues as to what degree of independence such entities should have and how to make sure that they do not turn on us, its inventors. Numerous recent advancements in all aspects of research, development and deployment of intelligent systems are well publicized but safety and security issues related to AI are rarely addressed. This book is proposed to mitigate this fundamental problem. It is comprised of chapters from leading AI Safety researchers addressing different aspects of the AI control problem as it relates to the development of safe and secure artificial intelligence. The book is the first edited volume dedicated to addressing challenges of constructing safe and secure advanced machine intelligence. The chapters vary in length and technical content from broad interest opinion essays to highly formalized algorithmic approaches to specific problems. All chapters are self-contained and could be read in any order or skipped without a loss of comprehension.
The award-winning author of The Music of the Primes explores the future of creativity and how machine learning will disrupt, enrich, and transform our understanding of what it means to be human. Can a well-programmed machine do anything a human can-only better? Complex algorithms are choosing our music, picking our partners, and driving our investments. They can navigate more data than a doctor or lawyer and act with greater precision. For many years we've taken solace in the notion that they can't create. But now that algorithms can learn and adapt, does the future of creativity belong to machines, too? It is hard to imagine a better guide to the bewildering world of artificial intelligence than Marcus du Sautoy, a celebrated Oxford mathematician whose work on symmetry in the ninth dimension has taken him to the vertiginous edge of mathematical understanding. In The Creativity Code he considers what machine learning means for the future of creativity. The Pollockizer can produce drip paintings in the style of Jackson Pollock, Botnik spins off fanciful (if improbable) scenes inspired by J. K. Rowling, and the music-composing algorithm Emmy managed to fool a panel of Bach experts. But do these programs just mimic, or do they have what it takes to create? Du Sautoy argues that to answer this question, we need to understand how the algorithms that drive them work-and this brings him back to his own subject of mathematics, with its puzzles, constraints, and enticing possibilities. While most recent books on AI focus on the future of work, The Creativity Code moves us to the forefront of creative new technologies and offers a more positive and unexpected vision of our future cohabitation with machines. It challenges us to reconsider what it means to be human-and to crack the creativity code.
This book presents a systematic review of research concerning processes and systems in Emergency Departments (EDs), the issues faced by EDs, and their solutions to ensure the delivery of proper and ideal healthcare services for patients through superior quality process management. The book evaluates two decades of data, from 2000 to 2019, in order to examine the processes used in ED operations.
ISAmI is the International Symposium on Ambient Intelligence, aiming to bring together researchers from various disciplines that constitute the scientific field of Ambient Intelligence to present and discuss the latest results, new ideas, projects and lessons obtained from recent experiences in building AmI systems. This volume presents the papers that have been accepted in this first edition. These papers reports on innovative results and advances achieved recently in this area.
This book gathers the proceedings of the KES-IDT-2018 conference, held in Gold Coast, Queensland, Australia, on June 20-22, 2018 The conference provided opportunities to present and discuss the latest research results, promoting knowledge transfer and the generation of new ideas in the field of intelligent decision-making. The range of topics explored is wide, and includes methods for decision-making, decision support, data analysis, modeling and many more in areas such as finance, economics, management, engineering and transportation. The book contains several sections devoted to specific topics, such as: * Decision-Making Theory for Economics * Advances in Knowledge-based Statistical Data Analysis * On Knowledge-Based Digital Ecosystems & Technologies for Smart and Intelligent Decision Support Systems * Soft Computing Models in Industrial and Management Engineering * Computational Media Computing and its Applications * Intelligent Decision-Making Technologies * Digital Architectures and Decision Management
The book provides insights into International Conference on Smart Innovations in Communications and Computational Sciences (ICSICCS 2017) held at North West Group of Institutions, Punjab, India. It presents new advances and research results in the fields of computer and communication written by leading researchers, engineers and scientists in the domain of interest from around the world. The book includes research work in all the areas of smart innovation, systems and technologies, embedded knowledge and intelligence, innovation and sustainability, advance computing, networking and informatics. It also focuses on the knowledge-transfer methodologies and innovation strategies employed to make this happen effectively. The combination of intelligent systems tools and a broad range of applications introduce a need for a synergy of disciplines from science and technology. Sample areas include, but are not limited to smart hardware, software design, smart computing technologies, intelligent communications and networking, web and informatics and computational sciences.
This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers.
Agents act on the basis of their beliefs and these beliefs change as they interact with other agents. In this book the authors propose and explain general logical tools for handling change. These tools include preferential reasoning, theory revision, and reasoning in inheritance systems, and the authors use these tools to examine nonmonotonic logic, deontic logic, counterfactuals, modal logic, intuitionistic logic, and temporal logic.
This book will be of benefit to researchers engaged with artificial intelligence, and in particular agents, multiagent systems and nonmonotonic logic.
This book constitutes the refereed proceedings of the 13th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2016, held in Columbia, SC, USA, in July 2016. The 57 revised full papers presented were carefully reviewed and selected from 77 submissions. The papers are organized in the following topical sections: knowledge sharing, re-use and preservation; collaborative development architectures; interoperability and systems integration; lean product development and the role of PLM; PLM and innovation; PLM tools; cloud computing and PLM tools; traceability and performance; building information modeling; big data analytics and business intelligence; information lifecycle management; industry 4.0; metrics, standards and regulation; and product, service and systems.
The author first introduces the basic framework for cultural algorithms and he then explains the social structure of a cultural system as a mechanism for the distribution of problem-solving information throughout a population. Three different models for social organizations are presented: the homogeneous (nuclear family), heterogeneous (expanded family), and subculture (descent groups) social models. The chapters that follow compare the learning capabilities of these social organizations relative to problems of varying complexity. The book concludes with a discussion of how the results can impact our understanding of social evolution.
How can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at such solutions, as well as case studies demonstrating how these theoretical ideas can be translated into practical applications in the geosciences, pavement engineering, etc. In all these developments, the authors' objectives were to provide accurate estimates of the resulting uncertainty; to offer solutions that require reasonably short computation times; to offer content that is accessible for engineers; and to be sufficiently general - so that readers can use the book for many different problems. The authors also describe how to make decisions under different types of uncertainty. The book offers a valuable resource for all practical engineers interested in better ways of gauging uncertainty, for students eager to learn and apply the new techniques, and for researchers interested in processing heterogeneous uncertainty.
James Lovelock, creator of the Gaia hypothesis and the greatest environmental thinker of our time, has produced an astounding new theory about future of life on Earth. He argues that the anthropocene - the age in which humans acquired planetary-scale technologies - is, after 300 years, coming to an end. A new age - the novacene - has already begun. New beings will emerge from existing artificial intelligence systems. They will think 10,000 times faster than we do and they will regard us as we now regard plants - as desperately slow acting and thinking creatures. But this will not be the cruel, violent machine takeover of the planet imagined by sci-fi writers and film-makers. These hyper-intelligent beings will be as dependent on the health of the planet as we are. They will need the planetary cooling system of Gaia to defend them from the increasing heat of the sun as much as we do. And Gaia depends on organic life. We will be partners in this project. It is crucial, Lovelock argues, that the intelligence of Earth survives and prospers. He does not think there are intelligent aliens, so we are the only beings capable of understanding the cosmos. Maybe, he speculates, the novacene could even be the beginning of a process that will finally lead to intelligence suffusing the entire cosmos. At the age 100, James Lovelock has produced the most important and compelling work of his life.
This book describes the teleoperated android Geminoid, which has a very humanlike appearance, movements, and perceptions, requiring unique developmental techniques. The book facilitates understanding of the framework of android science and how to use it in real human societies. Creating body parts of soft material by molding an existing person using a shape-memory form provides not only the humanlike texture of the body surface but also safe physical interaction, that is, humanlike interpersonal interaction between people and the android. The teleoperation also highlights novel effects in telecommunication. Operators of the Geminoid feel the robot's body as their own, and people encountering the teleoperated Geminoid perceive the robot's body as being possessed by the operator as well.Where does the feeling of human presence come from? Can we transfer or reproduce human presence by technology? Geminoid may help to answer these questions.
** #1 Wall Street Journal Bestseller ** In this essential book written by a rural native and Silicon Valley veteran, Microsoft's Chief technology officer tackles one of the most critical issues facing society today: the future of artificial intelligence and how it can be realistically used to promote growth, even in a shifting employment landscape. There are two prevailing stories about AI: for heartland low- and middle-skill workers, a dystopian tale of steadily increasing job destruction; for urban knowledge workers and the professional class, a utopian tale of enhanced productivity and convenience. But there is a third way to look at this technology that will revolutionize the workplace and ultimately the world. Kevin Scott argues that AI has the potential to create abundance and opportunity for everyone and help solve some of our most vexing problems. As the chief technology officer at Microsoft, he is deeply involved in the development of AI applications, yet mindful of their potential impact on workers-knowledge he gained firsthand growing up in rural Virginia. Yes, the AI Revolution will radically disrupt economics and employment for everyone for generations to come. But what if leaders prioritized the programming of both future technology and public policy to work together to find solutions ahead of the coming AI epoch? Like public health, the space program, climate change and public education, we need international understanding and collaboration on the future of AI and work. For Scott, the crucial question facing all of us is this: How do we work to ensure that the continued development of AI allows us to keep the American Dream alive? In this thoughtful, informed guide, he offers a clear roadmap to find the answer.
This book focuses on approximations under the presence of ordinary and fractional smoothness, presenting both the univariate and multivariate cases. It also explores approximations under convexity and a new trend in approximation theory -approximation by sublinear operators with applications to max-product operators, which are nonlinear and rational providing very fast and flexible approximations. The results presented have applications in numerous areas of pure and applied mathematics, especially in approximation theory and numerical analysis in both ordinary and fractional senses. As such this book is suitable for researchers, graduate students, and seminars of the above disciplines, and is a must for all science and engineering libraries.
This journal subline serves as a forum for stimulating and disseminating innovative research ideas, theories, emerging technologies, empirical investigations, state-of-the-art methods, and tools in all different genres of edutainment, such as game-based learning and serious games, interactive storytelling, virtual learning environments, VR-based education, and related fields. It covers aspects from educational and game theories, human-computer interaction, computer graphics, artificial intelligence, and systems design. The 19 papers presented in the 14th issue were organized in topical sections named: 3D modeling and visualization; image; e-learning and games; and miscellaneous.
Learn how to implement and build a neural network with this non-technical, project-based book as your guide. As you work through the chapters, you'll build an electronics project, providing a hands-on experience in training a network. There are no prerequisites here and you won't see a single line of computer code in this book. Instead, it takes a hardware approach using very simple electronic components. You'll start off with an interesting non-technical introduction to neural networks, and then construct an electronics project. The project isn't complicated, but it illustrates how back propagation can be used to adjust connection strengths or "weights" and train a network. By the end of this book, you'll be able to take what you've learned and apply it to your own projects. If you like to tinker around with components and build circuits on a breadboard, Neural Networks for Electronics Hobbyists is the book for you. What You'll Learn Gain a practical introduction to neural networks Review techniques for training networks with electrical hardware and supervised learning Understand how parallel processing differs from standard sequential programming Who This Book Is For Anyone interest in neural networks, from electronic hobbyists looking for an interesting project to build, to a layperson with no experience. Programmers familiar with neural networks but have only implemented them using computer code will also benefit from this book.
By presenting the latest advances in fuzzy sets and computing with words from around the globe, this book disseminates recent innovations in advanced intelligent technologies and systems. From intelligent control and intuitionistic fuzzy quantifiers to various data science and industrial applications, it includes a wide range of valuable lessons learned and ideas for future intelligent products and systems.
This book addresses the issue of Machine Learning (ML) attacks on Integrated Circuits through Physical Unclonable Functions (PUFs). It provides the mathematical proofs of the vulnerability of various PUF families, including Arbiter, XOR Arbiter, ring-oscillator, and bistable ring PUFs, to ML attacks. To achieve this goal, it develops a generic framework for the assessment of these PUFs based on two main approaches. First, with regard to the inherent physical characteristics, it establishes fit-for-purpose mathematical representations of the PUFs mentioned above, which adequately reflect the physical behavior of these primitives. To this end, notions and formalizations that are already familiar to the ML theory world are reintroduced in order to give a better understanding of why, how, and to what extent ML attacks against PUFs can be feasible in practice. Second, the book explores polynomial time ML algorithms, which can learn the PUFs under the appropriate representation. More importantly, in contrast to previous ML approaches, the framework presented here ensures not only the accuracy of the model mimicking the behavior of the PUF, but also the delivery of such a model. Besides off-the-shelf ML algorithms, the book applies a set of algorithms hailing from the field of property testing, which can help to evaluate the security of PUFs. They serve as a "toolbox", from which PUF designers and manufacturers can choose the indicators most relevant for their requirements. Last but not least, on the basis of learning theory concepts, the book explicitly states that the PUF families cannot be considered as an ultimate solution to the problem of insecure ICs. As such, it provides essential insights into both academic research on and the design and manufacturing of PUFs.
This book is a collection of selected papers from the 2011 International Conference on Communications, Electronics and Automation Engineering hold in Xi an, China, August 23-25, 2012. It presents some of the latest research findings in a broad range of interdisciplinary fields related to communications, electronics and automation engineering. Specific emphasis is placed on the following topics: automation control, data mining and statistics, simulation and mathematical modeling, human factors and cognitive engineering, web technology, optimization and algorithm, and network communications. The prime objective of the book is to familiarize the readers with cutting edge developments in the research of electronics and automation engineering with a variety of applications. Hopefully, the book can help researchers to identify research trends in many areas, to learn the new methods and tools, and to spark innovative ideas. "
This book includes recent research on Hybrid Intelligent Systems. It presents 35 selected papers from the 17th edition of the International Conference on Hybrid Intelligent Systems (HIS), which was held in Delhi, India from December 14 to 16, 2017. Reflecting the awareness in the respective academic communities that combined approaches are essential to solving the remaining tough problems in computational intelligence, the HIS is a premier conference focused on the hybridization of intelligent systems. The book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
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