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Machine Learning Methods for Behaviour Analysis and Anomaly Detection in Video (Springer Theses)
by Olga IsupovaThis thesis proposes machine learning methods for understanding scenes via behaviour analysis and online anomaly detection in video. The book introduces novel Bayesian topic models for detection of events that are different from typical activities and a novel framework for change point detection for identifying sudden behavioural changes.Behaviour analysis and anomaly detection are key components of intelligent vision systems. Anomaly detection can be considered from two perspectives: abnormal events can be defined as those that violate typical activities or as a sudden change in behaviour. Topic modelling and change-point detection methodologies, respectively, are employed to achieve these objectives.The thesis starts with the development of learning algorithms for a dynamic topic model, which extract topics that represent typical activities of a scene. These typical activities are used in a normality measure in anomaly detection decision-making. The book also proposes a novel anomaly localisation procedure. In the first topic model presented, a number of topics should be specified in advance. A novel dynamic nonparametric hierarchical Dirichlet process topic model is then developed where the number of topics is determined from data. Batch and online inference algorithms are developed.The latter part of the thesis considers behaviour analysis and anomaly detection within the change-point detection methodology. A novel general framework for change-point detection is introduced. Gaussian process time series data is considered. Statistical hypothesis tests are proposed for both offline and online data processing and multiple change point detection are proposed and theoretical properties of the tests are derived. The thesis is accompanied by open-source toolboxes that can be used by researchers and engineers.
Machine Learning Methods in Systems: Proceedings of 13th Computer Science On-line Conference 2024, Vol. 4 (Lecture Notes in Networks and Systems #1126)
by Radek Silhavy Petr SilhavyThis book requires an in-depth exploration of machine learning and its integration into system engineering. This book presents contemporary research methodologies, with a strong focus on the innovative application of machine learning techniques in developing and optimizing systems. It includes the meticulously reviewed proceedings from the Machine Learning Methods in Systems session of the 13th Computer Science Online Conference 2024 (CSOC 2024), held virtually in April 2024.
Machine Learning Modeling for IoUT Networks: Internet of Underwater Things (SpringerBriefs in Computer Science)
by Ahmad A. Aziz El-Banna Kaishun WuThis book discusses how machine learning and the Internet of Things (IoT) are playing a part in smart control of underwater environments, known as Internet of Underwater Things (IoUT). The authors first present seawater’s key physical variables and go on to discuss opportunistic transmission, localization and positioning, machine learning modeling for underwater communication, and ongoing challenges in the field. In addition, the authors present applications of machine learning techniques for opportunistic communication and underwater localization. They also discuss the current challenges of machine learning modeling of underwater communication from two communication engineering and data science perspectives.
Machine Learning, Optimization, and Data Science: 6th International Conference, LOD 2020, Siena, Italy, July 19–23, 2020, Revised Selected Papers, Part II (Lecture Notes in Computer Science #12566)
by Giuseppe Nicosia Varun Ojha Emanuele La Malfa Giorgio Jansen Vincenzo Sciacca Panos Pardalos Giovanni Giuffrida Renato UmetonThis two-volume set, LNCS 12565 and 12566, constitutes the refereed proceedings of the 6th International Conference on Machine Learning, Optimization, and Data Science, LOD 2020, held in Siena, Italy, in July 2020. The total of 116 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 209 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.
Machine Learning Paradigms: Advances in Deep Learning-based Technological Applications (Learning and Analytics in Intelligent Systems #18)
by George A. Tsihrintzis Lakhmi C. JainAt the dawn of the 4th Industrial Revolution, the field of Deep Learning (a sub-field of Artificial Intelligence and Machine Learning) is growing continuously and rapidly, developing both theoretically and towards applications in increasingly many and diverse other disciplines. The book at hand aims at exposing its reader to some of the most significant recent advances in deep learning-based technological applications and consists of an editorial note and an additional fifteen (15) chapters. All chapters in the book were invited from authors who work in the corresponding chapter theme and are recognized for their significant research contributions. In more detail, the chapters in the book are organized into six parts, namely (1) Deep Learning in Sensing, (2) Deep Learning in Social Media and IOT, (3) Deep Learning in the Medical Field, (4) Deep Learning in Systems Control, (5) Deep Learning in Feature Vector Processing, and (6) Evaluation of Algorithm Performance. This research book is directed towards professors, researchers, scientists, engineers and students in computer science-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of the most recent deep learning-based technological applications. An extensive list of bibliographic references at the end of each chapter guides the readers to probe deeper into their application areas of interest.
Machine Learning Refined: Foundations, Algorithms, and Applications
by Jeremy Watt Reza Borhani Aggelos KatsaggelosWith its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for graduate courses on machine learning and for individual reference and self-study.
Machine Learning, revised and updated edition: The New Ai (The MIT Press Essential Knowledge series)
by Ethem AlpaydinA concise overview of machine learning--computer programs that learn from data--the basis of such applications as voice recognition and driverless cars.Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition--as well as some we don't yet use everyday, including driverless cars. It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpaydin offers a concise and accessible overview of "the new AI." This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias. Alpaydin, author of a popular textbook on machine learning, explains that as "Big Data" has gotten bigger, the theory of machine learning--the foundation of efforts to process that data into knowledge--has also advanced. He describes the evolution of the field, explains important learning algorithms, and presents example applications. He discusses the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances; and reinforcement learning, when an autonomous agent learns to take actions to maximize reward. In a new chapter, he considers transparency, explainability, and fairness, and the ethical and legal implications of making decisions based on data.
Machine Learning Support for Fault Diagnosis of System-on-Chip
by Patrick Girard Shawn Blanton Li-C. WangThis book provides a state-of-the-art guide to Machine Learning (ML)-based techniques that have been shown to be highly efficient for diagnosis of failures in electronic circuits and systems. The methods discussed can be used for volume diagnosis after manufacturing or for diagnosis of customer returns. Readers will be enabled to deal with huge amount of insightful test data that cannot be exploited otherwise in an efficient, timely manner. After some background on fault diagnosis and machine learning, the authors explain and apply optimized techniques from the ML domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturing. These techniques can be used for failure isolation in logic or analog circuits, board-level fault diagnosis, or even wafer-level failure cluster identification. Evaluation metrics as well as industrial case studies are used to emphasize the usefulness and benefits of using ML-based diagnosis techniques.
Machine Learning Techniques for Smart City Applications: Trends and Solutions (Advances in Science, Technology & Innovation)
by D. Jude HemanthThis book discusses the application of different machine learning techniques to the sub-concepts of smart cities such as smart energy, transportation, waste management, health, infrastructure, etc. The focus of this book is to come up with innovative solutions in the above-mentioned issues with the purpose of alleviating the pressing needs of human society. This book includes content with practical examples which are easy to understand for readers. It also covers a multi-disciplinary field and, consequently, it benefits a wide readership including academics, researchers, and practitioners.
Machine Learning Technologies and Applications: Proceedings of ICACECS 2020 (Algorithms for Intelligent Systems)
by C. Kiran Mai A. Brahmananda Reddy K. Srujan RajuThis book comprises the best deliberations with the theme “Machine Learning Technologies and Applications” in the “International Conference on Advances in Computer Engineering and Communication Systems (ICACECS 2020),” organized by the Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology. The book provides insights into the recent trends and developments in the field of computer science with a special focus on the machine learning and big data. The book focuses on advanced topics in artificial intelligence, machine learning, data mining and big data computing, cloud computing, Internet of things, distributed computing and smart systems.
Machine Learning: Theoretical Foundations and Practical Applications (Studies in Big Data #87)
by Manjusha Pandey Siddharth Swarup RautarayThis edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 9–12 January 2020 in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network learning, knowledge acquisition and learning, knowledge intensive learning, machine learning and information retrieval, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms.
Machine Learning under Malware Attack
by Raphael Labaca CastroMachine learning has become key in supporting decision-making processes across a wide array of applications, ranging from autonomous vehicles to malware detection. However, while highly accurate, these algorithms have been shown to exhibit vulnerabilities, in which they could be deceived to return preferred predictions. Therefore, carefully crafted adversarial objects may impact the trust of machine learning systems compromising the reliability of their predictions, irrespective of the field in which they are deployed. The goal of this book is to improve the understanding of adversarial attacks, particularly in the malware context, and leverage the knowledge to explore defenses against adaptive adversaries. Furthermore, to study systemic weaknesses that can improve the resilience of machine learning models.
Machine Learning with Health Care Perspective: Machine Learning and Healthcare (Learning and Analytics in Intelligent Systems #13)
by Jyotir Moy Chatterjee Vishal JainThis unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how chronic disease is being redefined through patient-led data learning, the book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges.
Machine Medical Ethics
by Simon Peter van Rysewyk Matthijs PontierThe essays in this book, written by researchers from both humanities and science, describe various theoretical and experimental approaches to adding medical ethics to a machine, what design features are necessary in order to achieve this, philosophical and practical questions concerning justice, rights, decision-making and responsibility in medical contexts, and accurately modeling essential physician-machine-patient relationships. In medical settings, machines are in close proximity with human beings: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old and with medical professionals. Machines in these contexts are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for empathy and emotion detection necessary? What about consciousness? This collection is the first book that addresses these 21st-century concerns.
The Machine Penalty: The Consequences of Seeing Artificial Intelligence as Less Than Human
by Daniel B. ShankThis book makes the argument that comparing AI to humans leads us to diminish similar outcomes from AI across situations. This may be taking a human&’s advice for a restaurant recommendation over an AI&’s or believing that AI can&’t be as biased as people can when denying loans to others. This machine penalty is caused both by comparing humans and AI in terms of appearance, identity, behavior, mind, and essence, and by situations involving controllable, personal, important, subjective, or moral decisions. It can be applied across many different situations, where we diminish different AI outcomes. We penalize machines&’ influence when they give advice, fairness when they evaluate people, blame when they cause harm, value when they produce art, and satisfaction when they provide companionship. The result is immediate consequences in those domains and downstream consequences for society. This monograph brings together diverse research from human-computer interaction, psychology, sociology, and communication including theories such as Computers Are Social Actors, anthropomorphism, mind perception, and algorithm aversion to present an expansive argument and evidence for the machine penalty.
The Machine Question: Critical Perspectives on AI, Robots, and Ethics (The\mit Press Ser.)
by David J. GunkelAn investigation into the assignment of moral responsibilities and rights to intelligent and autonomous machines of our own making.One of the enduring concerns of moral philosophy is deciding who or what is deserving of ethical consideration. Much recent attention has been devoted to the "animal question"—consideration of the moral status of nonhuman animals. In this book, David Gunkel takes up the "machine question": whether and to what extent intelligent and autonomous machines of our own making can be considered to have legitimate moral responsibilities and any legitimate claim to moral consideration.The machine question poses a fundamental challenge to moral thinking, questioning the traditional philosophical conceptualization of technology as a tool or instrument to be used by human agents. Gunkel begins by addressing the question of machine moral agency: whether a machine might be considered a legitimate moral agent that could be held responsible for decisions and actions. He then approaches the machine question from the other side, considering whether a machine might be a moral patient due legitimate moral consideration. Finally, Gunkel considers some recent innovations in moral philosophy and critical theory that complicate the machine question, deconstructing the binary agent–patient opposition itself.Technological advances may prompt us to wonder if the science fiction of computers and robots whose actions affect their human companions (think of HAL in 2001: A Space Odyssey) could become science fact. Gunkel's argument promises to influence future considerations of ethics, ourselves, and the other entities who inhabit this world.
Machine-to-Machine Communications: Architectures, Technology, Standards, and Applications
by Vojislav B. Mišić Jelena MišićWith the number of machine-to-machine (M2M)-enabled devices projected to reach 20 to 50 billion by 2020, there is a critical need to understand the demands imposed by such systems. Machine-to-Machine Communications: Architectures, Technology, Standards, and Applications offers rigorous treatment of the many facets of M2M communication, including it
A Machine to Move Ocean and Earth: The Making of the Port of Los Angeles and America
by James Tejani"[An] enthralling debut…a beguiling history of Southern California, early industrial development, and U.S. empire." —Publishers Weekly (starred review) A deeply researched narrative of the creation of the Port of Los Angeles, a central event in America’s territorial expansion and rise as a global economic power. The Port of Los Angeles is all around us. Objects we use on a daily basis pass through it: furniture, apparel, electronics, automobiles, and much more. The busiest container port in the Western hemisphere, it claims one-sixth of all US ocean shipping. Yet despite its centrality to our world, the port and the story of its making have been neglected in histories of the United States. In A Machine to Move Ocean and Earth, historian James Tejani corrects that significant omission, charting the port’s rise out of the mud and salt marsh of San Pedro estuary—and showing how the story of the port is the story of modern, globalized America itself. By the mid-nineteenth century, Americans had identified the West Coast as the republic’s destiny, a gateway to the riches of the Pacific. In a narrative spanning decades and stretching to Washington, DC, the Pacific Northwest, Civil War Richmond, Southwest deserts, and even overseas to Europe, Hawaii, and Asia, Tejani demonstrates how San Pedro came to be seen as all-important to the nation’s future. It was not virgin land, but dominated by powerful Mexican estates that would not be dislodged easily. Yet American scientists, including the great surveyor George Davidson, imperialist politicians such as Jefferson Davis and William Gwin, and hopeful land speculators, among them the future Union Army general Edward Ord, would wrest control of the estuary, and set the scene for the violence, inequality, and engineering marvels to come. San Pedro was no place for a harbor, Tejani reveals. The port was carved in defiance of nature, using new engineering techniques and massive mechanical dredgers. Business titans such as Collis Huntington and Edward H. Harriman brought their money and corporate influence to the task. But they were outmatched by government reformers, laying the foundations for the port, for the modern city of Los Angeles, and for our globalized world. Interweaving the natural history of San Pedro into this all-too-human history, Tejani vividly describes how a wild coast was made into the engine of American power. A story of imperial dreams and personal ambition, A Machine to Move Ocean and Earth is necessary reading for anyone who seeks to understand what the United States was, what it is now, and what it will be.
Machine Tool Metrology
by Graham T. SmithMaximizing reader insights into the key scientific disciplines of Machine Tool Metrology, this text will prove useful for the industrial-practitioner and those interested in the operation of machine tools. Within this current level of industrial-content, this book incorporates significant usage of the existing published literature and valid information obtained from a wide-spectrum of manufacturers of plant, equipment and instrumentation before putting forward novel ideas and methodologies. Providing easy to understand bullet points and lucid descriptions of metrological and calibration subjects, this book aids reader understanding of the topics discussed whilst adding a voluminous-amount of footnotes utilised throughout all of the chapters, which adds some additional detail to the subject. Featuring an extensive amount of photographic-support, this book will serve as a key reference text for all those involved in the field.
Machine Tool Reliability
by Bhupesh K. Lad Divya Shrivastava Makarand S. KulkarniThis book explores the domain of reliability engineering in the context of machine tools. Failures of machine tools not only jeopardize users' ability to meet their due date commitments but also lead to poor quality of products, slower production, down time losses etc. Poor reliability and improper maintenance of a machine tool greatly increases the life cycle cost to the user. Thus, the application area of the present book, i.e. machine tools, will be equally appealing to machine tool designers, production engineers and maintenance managers. The book will serve as a consolidated volume on various dimensions of machine tool reliability and its implications from manufacturers and users point of view. From the manufacturers' point of view, it discusses various approaches for reliability and maintenance based design of machine tools. In specific, it discusses simultaneous selection of optimal reliability configuration and maintenance schedules, maintenance optimization under various maintenance scenarios and cost based FMEA. From the users' point of view, it explores the role of machine tool reliability in shop floor level decision- making. In specific, it shows how to model the interactions of machine tool reliability with production scheduling, maintenance scheduling and process quality control.
Machine Tool Vibrations and Cutting Dynamics
by Brandon C. Gegg C. Steve Suh Albert C. Luo"Machine Tool Vibrations and Cutting Dynamics" covers the fundamentals of cutting dynamics from the perspective of discontinuous systems theory. It shows the reader how to use coupling, interaction, and different cutting states to mitigate machining instability and enable better machine tool design. Among the topics discussed are; underlying dynamics of cutting and interruptions in cutting motions; the operation of the machine-tool systems over a broad range of operating conditions with minimal vibration and the need for high precision, high yield micro- and nano-machining.
Machine Tools: An Industry 4.0 Perspective (Computers in Engineering Design and Manufacturing)
by Wasim Ahmed Khan Khalid Rahman Ghulam Hussain Ghulam Abbas Wang XiaopingThis book introduces the applications of Industry 4.0 in machine tools through an overview of the latest available digital technologies. It focuses on digital twining, communication between industrial controls, motion, and input/output devices, along with sustainability in SMEs. Machine Tools: An Industry 4.0 Perspective focuses on the digital twining of machine tools, which improves the life of the machines and provides a method of operating a factory during times of complete lockdown resulting from various conditions. It presents an overview of the communication between industrial controls, motion, and input/output devices through standardized digital interfaces such as SERCOS and USB. The book goes on to discuss industrial cybersecurity systems applicable to discrete manufacturing, which includes cyberattacks and human errors, and address the security aspects related to software, hardware, and data. The book also explores the application of big data for different stages of production and illustrates the uses such as predictive maintenance, product quality, product life cycle management (PLM), and more. This book is an ideal reference for undergraduate, graduate, and postgraduate students of industrial, mechanical, and mechatronics engineering, along with professionals, and general readers.
Machine Tools Production Systems 1: Machine Types and Application Fields (Lecture Notes in Production Engineering)
by Christian Brecher Manfred WeckThe first part of the Machine Tools and Production Systems Compendium presents the wide range of machine tools and a comprehensive overview of different machine types. Based on the categorization of manufacturing processes according to the German standard DIN 8580, the different areas of application of machine tools are delineated and the various machine designs, the mechanical structure as well as the functions of the machine types are explained. Numerous three-dimensional illustrations of the principles, color photos, section drawings and schematic diagrams supplement the explanations and provide visual support. First, the machine types for the different manufacturing processes are described — before the multi-machine systems are explained. This is followed by a detailed presentation of the various equipment components of machine tools. In the last newly introduced chapter, the volume is concluded by a comprehensive and detailed explanation of three design examples of selected machine tools based on assembly drawings.The German Machine Tools and Production Systems Compendium has been completely revised. The previous five-volume series has been condensed into three volumes in the new ninth edition with colored technical illustrations throughout. This first English edition is a translation of the German ninth edition.
Machine Tools Production Systems 2: Design, Calculation and Metrological Assessment (Lecture Notes in Production Engineering)
by Christian Brecher Manfred WeckThe first part of this volume provides the user with assistance in the selection and design of important machine and frame components. It also provides help with machine design, calculation and optimization of these components in terms of their static, dynamic and thermoelastic behavior. This includes machine installation, hydraulic systems, transmissions, as well as industrial design and guidelines for machine design. The second part of this volume deals with the metrological investigation and assessment of the entire machine tool or its components with respect to the properties discussed in the first part of this volume. Following an overview of the basic principles of measurement and measuring devices, the procedure for measuring them is described. Acceptance of the machine using test workpieces and the interaction between the machine and the machining process are discussed in detail.The German Machine Tools and Manufacturing Systems Compendium has been completely revised. The previous five-volume series has been condensed into three volumes in the new ninth edition with color technical illustrations throughout. This first English edition is a translation of the German ninth edition.
Machine Tools Production Systems 3: Mechatronic Systems, Control and Automation (Lecture Notes in Production Engineering)
by Christian Brecher Manfred WeckThe first part of this third volume focuses on the design of mechatronic components, in particular the feed drives of machine tools used to generate highly dynamic drive movements. Engineering guides for the selection and design of important machine components, the control technology of feed drives, and the measuring systems required for position capture are presented. Another focus is on process and diagnostic equipment for manufacturing machines and systems. The second part describes control concepts including programming methods for various applications of modern production systems. Programmable logic controllers (PLC), numerical controllers (NC) and robot controllers (RC) are part of these presentations. In the context of automated manufacturing systems, the various levels of the automation pyramid and the importance of control systems are also outlined. Finally, the volume deals with the engineering of machines and plants. The German Machine Tools and Production Systems Compendium has been completely revised. The previous five-volume series has been condensed into three volumes in the new ninth edition with colored technical illustrations throughout. This first English edition is a translation of the German ninth edition.