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Fault-tolerant Control and Diagnosis for Integer and Fractional-order Systems: Fundamentals of Fractional Calculus and Differential Algebra with Real-Time Applications (Studies in Systems, Decision and Control #328)
by Rafael Martínez-Guerra Fidel Meléndez-Vázquez Iván Trejo-ZúñigaThis book is about algebraic and differential methods, as well as fractional calculus, applied to diagnose and reject faults in nonlinear systems, which are of integer or fractional order. This represents an extension of a very important and widely studied problem in control theory, namely fault diagnosis and rejection (using differential algebraic approaches), to systems presenting fractional dynamics, i.e. systems whose dynamics are represented by derivatives and integrals of non-integer order. The authors offer a thorough overview devoted to fault diagnosis and fault-tolerant control applied to fractional-order and integer-order dynamical systems, and they introduce new methodologies for control and observation described by fractional and integer models, together with successful simulations and real-time applications. The basic concepts and tools of mathematics required to understand the methodologies proposed are all clearly introduced and explained. Consequently, the book is useful as supplementary reading in courses of applied mathematics and nonlinear control theory. This book is meant for engineers, mathematicians, physicists and, in general, to researchers and postgraduate students in diverse areas who have a minimum knowledge of calculus. It also contains advanced topics for researchers and professionals interested in the area of states and faults estimation.
Fauna in Soil Ecosystems: Recycling Processes, Nutrient Fluxes, and Agricultural Production (Books in Soils, Plants, and the Environment)
by Gero BenckiserOffers an integrated presentation of the microbial, agronomic and recycling aspects of soil faunal potentials, emphasizing agricultural ecosystems and furnishing methods for modelling food webs. The text covers morphology, reproduction, abundances, basic requirements, competition, predation, parasitism, nutrient cycling and phytopathological intera
Faxed: The Rise and Fall of the Fax Machine (Johns Hopkins Studies in the History of Technology)
by Jonathan CoopersmithThe intriguing story of the rise and fall—and unexpected persistence—of the fax machine illustrates the close link between technology and culture.Co-Winner of the Hagley Prize in Business History of the Business History ConferenceFaxed is the first history of the facsimile machine—the most famous recent example of a tool made obsolete by relentless technological innovation. Jonathan Coopersmith recounts the multigenerational, multinational history of the device from its origins to its workplace glory days, in the process revealing how it helped create the accelerated communications, information flow, and vibrant visual culture that characterize our contemporary world.Most people assume that the fax machine originated in the computer and electronics revolution of the late twentieth century, but it was actually invented in 1843. Almost 150 years passed between the fax’s invention in England and its widespread adoption in tech-savvy Japan, where it still enjoys a surprising popularity. Over and over again, faxing’s promise to deliver messages instantaneously paled before easier, less expensive modes of communication: first telegraphy, then radio and television, and finally digitalization in the form of email, the World Wide Web, and cell phones. By 2010, faxing had largely disappeared, having fallen victim to the same technological and economic processes that had created it. Based on archival research and interviews spanning two centuries and three continents, Coopersmith’s book recovers the lost history of a once-ubiquitous technology. Written in accessible language that should appeal to engineers and policymakers as well as historians, Faxed explores themes of technology push and market pull, user-based innovation, and "blackboxing" (the packaging of complex skills and technologies into packages designed for novices) while revealing the inventions inspired by the fax, how the demand for fax machines eventually caught up with their availability, and why subsequent shifts in user preferences rendered them mostly passé.
Fe-Based Amorphous Alloys with High Glass Forming Ability
by Qingjun ChenThis book systematically discusses the physical properties, corrosion resistance, application in 3D printing, and amorphous degradation properties of Fe-based amorphous alloys. Through an in-depth analysis of the structure and properties of amorphous alloys, the book reveals their potential advantages and practical performance in various industrial applications. In particular, the detailed study of corrosion resistance provides a valuable reference for researchers and practitioners in the field of materials science and engineering. The detailed experimental methods and results presented in this book are of great interest to readers, as it will provide them with the latest scientific data and practical applications. The book features numerous beautiful illustrations, detailed data tables, and innovative presentation formats designed to help readers more intuitively understand complex scientific concepts. At the same time, the book also incorporates a variety of teaching methods, making it suitable not only as a reference book for professional research, but also for the use of textbooks in higher education courses.
FeFET Devices, Trends, Technology and Applications
by Balwinder Raj Shiromani Balmukund Rahi Nandakishor YadavFeFET Devices, Trends, Technology and Applications is essential for anyone seeking an in-depth understanding of the latest advancements in ferroelectric devices, as it offers comprehensive insights into research techniques, novel materials, and the historical context of semiconductor development. This book serves as an encyclopedia of knowledge for state-of-the-art research techniques for the miniaturization of ferroelectric devices. This volume explores characteristics, novel materials used, modifications in device structure, and advancements in model FET devices. Though many devices following Moore’s Law and More-Moore are proposed, a complete history of existing and proposed semiconductor devices is now available here. This resource focuses on developments and research in emerging ferroelectric FET devices and their applications, providing unique coverage of topics covering recent advancements and novel concepts in the field of miniaturized ferroelectric devices.
Fearless Flyer: Ruth Law and Her Flying Machine
by Heather LangA National Science Teachers Association Best STEM BookDiscover a thrilling moment in history when pioneering aviator Ruth Law attempted to do what no other aviator had done before: fly nonstop from Chicago to New York. On November 19, 1916, at 8:25 a.m., Ruth Law took off on a flight from Chicago to New York City that aviation experts thought was doomed. Sitting at the controls of her small bi-plane, exposed to the elements, Law battled fierce winds and numbing cold. When her engine ran out of fuel, she glided for two miles and landed at Hornell, New York. Even though she fell short of her goal, she had broken the existing cross-country distance record. And with her plane refueled, she got back in the air and headed for New York City where crowds waited to greet her. This story is perfect to share during Women's History Month or anytime during the year!
Feasibility Model of Solar Energy Plants by ANN and MCDM Techniques
by Mrinmoy Majumder Apu K. SahaThis Brief highlights a novel model to find out the feasibility of any location to produce solar energy. The model utilizes the latest multi-criteria decision making techniques and artificial neural networks to predict the suitability of a location to maximize allocation of available energy for producing optimal amount of electricity which will satisfy the demand from the market. According to the results of the case studies further applications are encouraged.
Feasibility of Using Mycoherbicides for Controlling Illicit Drug Crops
by Committee on Mycoherbicides for Eradicating Illicit Drug CropsThe control of illicit-drug trafficking and drug use is a difficult and complex process that involves a variety of prevention, control, treatment, and law enforcement strategies. Eradication strategies for controlling illicit-drug crops are used to target the beginning of the drug-supply chain by preventing or reducing crop yields. Mycoherbicides have been proposed as an eradication tool to supplement the current methods of herbicide spraying, mechanical removal, and manual destruction of illicit-drug crops. Some people regard them as preferable to chemical herbicides for controlling illicit-drug crops because of their purported specificity to only one plant species or a few closely related species. As living microorganisms, they have the potential to provide long-term control if they can persist in the environment and affect later plantings. Research on mycoherbicides against illicit-drug crops has focused on three pathogens: Fusarium oxysporum f. sp. cannabis for cannabis (Cannabis sativa), F. oxysporum f. sp. erythroxyli for coca (Erythroxylum coca and E. novogranatense), and Crivellia papaveracea or Brachycladium papaveris (formerly known as Pleospora papaveracea and Dendryphion penicillatum, respectively) for opium poppy (Papaver somniferum). Feasibility of Using Mycoherbicides for Controlling Illicit Drug Crops addresses issues about the potential use of the proposed mycoherbicides: their effectiveness in eradicating their target plants; the feasibility of their large-scale industrial manufacture and delivery; their potential spread and persistence in the environment; their pathogenicity and toxicity to nontarget organisms, including other plants, fungi, animals, and humans; their potential for mutation and resulting effects on target plants and nontarget organisms; and research and development needs. On the basis of its review, the report concludes that the available data are insufficient to determine the effectiveness of the specific fungi proposed as mycoherbicides to combat illicit-drug crops or to determine their potential effects on nontarget plants, microorganisms, animals, humans, or the environment. However, the committee offers an assessment of what can and cannot be determined at the present time regarding each of the issues raised in the statement of task.
Featherweight 221: The Perfect Portable And Its Stitches Across History
by Nancy Johnson-SrebroA comprehensive history of the treasured Singer sewing machine from the author of Big Block One-Star Quilts by Magic.Enjoy an entertaining look at the history of the Featherweight sewing machine with this expanded third edition updated with the latest research. It’s packed with photos, stories, and handy information, like how to date and troubleshoot your machine. It’s a fun read for quilters, Featherweight owners, and history buffs.
Feature Engineering and Computational Intelligence in ECG Monitoring
by Chengyu Liu Jianqing LiThis book discusses feature engineering and computational intelligence solutions for ECG monitoring, with a particular focus on how these methods can be efficiently used to address the emerging challenges of dynamic, continuous & long-term individual ECG monitoring and real-time feedback. By doing so, it provides a “snapshot” of the current research at the interface between physiological signal analysis and machine learning. It also helps clarify a number of dilemmas and encourages further investigations in this field, to explore rational applications of feature engineering and computational intelligence in ECG monitoring. The book is intended for researchers and graduate students in the field of biomedical engineering, ECG signal processing, and intelligent healthcare.
Feature Extraction in Medical Image Retrieval: A New Design of Wavelet Filter Banks
by Amol D. Rahulkar Aswini Kumar SamantarayMedical imaging is fundamental to modern healthcare, and its widespread use has resulted in creation of image databases. These repositories contain images from a diverse range of modalities, multidimensional as well as co-aligned multimodality images. These image collections offer opportunity for evidence-based diagnosis, teaching, and research. Advances in medical image analysis over last two decades shows there are now many algorithms and ideas available that allow to address medical image analysis tasks in commercial solutions with sufficient performance in terms of accuracy, reliability and speed. Content-based image retrieval (CBIR) is an image search technique that complements the conventional text-based retrieval of images by using visual features, such as color, texture, and shape, as search criteria. This book emphasizes the design of wavelet filter-banks as efficient and effective feature descriptors for medical image retrieval.Firstly, a generalized novel design of a family of multiplier-free orthogonal wavelet filter-banks is presented. In this, the dyadic filter coefficients are obtained based on double-shifting orthogonality property with allowable deviation from original filter coefficients. Next, a low complex symmetric Daub-4 orthogonal wavelet filter-bank is presented. This is achieved by slightly altering the perfect reconstruction condition to make designed filter-bank symmetric and to obtain dyadic filter coefficients. In third contribution, the first dyadic Gabor wavelet filter-bank is presented based on slight alteration in orientation parameter without disturbing remaining Gabor wavelet parameters. In addition, a novel feature descriptor based on the design of adaptive Gabor wavelet filter-bank is presented. The use of Maximum likelihood estimation is suggested to measure the similarity between the feature vectors of heterogeneous medical images. The performance of the suggested methods is evaluated on three different publicly available databases namely NEMA, OASIS and EXACT09. The performance in terms of average retrieval precision, average retrieval recall and computational time are compared with well-known existing methods.
Feature Learning and Understanding: Algorithms and Applications (Information Fusion and Data Science)
by Henry Leung Haitao Zhao Zhihui Lai Xianyi ZhangThis book covers the essential concepts and strategies within traditional and cutting-edge feature learning methods thru both theoretical analysis and case studies. Good features give good models and it is usually not classifiers but features that determine the effectiveness of a model. In this book, readers can find not only traditional feature learning methods, such as principal component analysis, linear discriminant analysis, and geometrical-structure-based methods, but also advanced feature learning methods, such as sparse learning, low-rank decomposition, tensor-based feature extraction, and deep-learning-based feature learning. Each feature learning method has its own dedicated chapter that explains how it is theoretically derived and shows how it is implemented for real-world applications. Detailed illustrated figures are included for better understanding. This book can be used by students, researchers, and engineers looking for a reference guide for popular methods of feature learning and machine intelligence.
Feature Profile Evolution in Plasma Processing Using On-wafer Monitoring System
by Seiji SamukawaThis book provides for the first time a good understanding of the etching profile technologies that do not disturb the plasma. Three types of sensors are introduced: on-wafer UV sensors, on-wafer charge-up sensors and on-wafer sheath-shape sensors in the plasma processing and prediction system of real etching profiles based on monitoring data. Readers are made familiar with these sensors, which can measure real plasma process surface conditions such as defect generations due to UV-irradiation, ion flight direction due to charge-up voltage in high-aspect ratio structures and ion sheath conditions at the plasma/surface interface. The plasma etching profile realistically predicted by a computer simulation based on output data from these sensors is described.
Feature and Dimensionality Reduction for Clustering with Deep Learning (Unsupervised and Semi-Supervised Learning)
by Frederic Ros Rabia RiadThis book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with particular attention to the knowledge discovery question. The authors first present a synthesis of the major recent influencing techniques and "tricks" participating in recent advances in deep clustering, as well as a recall of the main deep learning architectures. Secondly, the book highlights the most popular works by “family” to provide a more suitable starting point from which to develop a full understanding of the domain. Overall, the book proposes a comprehensive up-to-date review of deep feature selection and deep clustering methods with particular attention to the knowledge discovery question and under a multi-criteria analysis. The book can be very helpful for young researchers, non-experts, and R&D AI engineers.
Fed-Batch Cultures
by Henry C. Lim Hwa Sung ShinMany, if not most, industrially important fermentation and bioreactor operations are carried out in fed-batch mode, producing a wide variety of products. In spite of this, there is no single book that deals with fed-batch operations. This is the first book that presents all the necessary background material regarding the 'what, why and how' of optimal and sub-optimal fed-batch operations. Numerous examples are provided to illustrate the application of optimal fed-batch cultures. This unique book, by world experts with decades of research and industrial experience, is a must for researchers and industrial practitioners of fed-batch processes (modeling, control and optimization) in biotechnology, fermentation, food, pharmaceuticals and waste treatment industries.
Federal Aviation Regulations/Aeronautical Information Manual 2014: Federal Aviation Regulations/aeronautical Information Manual (Far/aim: Federal Aviation Regulations And The Aeronautical Information Manual Ser.)
by Federal Aviation AdministrationIf you’re an aviator or aviation enthusiast, you cannot be caught with an out-of-date edition of the FAR/AIM. In today’s environment, there is no excuse for ignorance of the rules of the US airspace system. In the newest edition of the FAR/AIM, all regulations, procedures, and illustrations are brought up to date to reflect current FAA data. This handy reference book is an indispensable resource for members of the aviation community, as well as for aspiring pilots looking to get a solid background in the rules, requirements, and procedures of flight training. Not only does this manual present all the current FAA regulations, it also includes: A study guide for specific pilot training certifications and ratings A pilot/controller glossary Standard instrument procedures Parachute operations Airworthiness standards for products and parts The NASA Aviation Safety reporting form Important FAA contact informationThis is the most complete guide to the rules of aviation available anywhere. Don’t take off without the FAR/AIM!
Federal Financial Incentives to Induce Early Experience Producing Unconventional Liquid Fuels
by Frank Camm James T. Bartis Vi-Nhuan Le Charles J. BushmanThe government, as a principal, may seek to induce a private investor, as anagent, to build and operate an unconventional-oil production plant topromote early production experience with such plants. Facing significantuncertainty about the future, it also wants to limit the cost to the publicof doing this. This report offers an analytic way to design and assesspackages of policy instruments that the government can use to achieve itsgoal.
Federated Learning Over Wireless Edge Networks (Wireless Networks)
by Dusit Niyato Zehui Xiong Wei Yang Lim Jer Shyuan Ng Chunyan MiaoThis book first presents a tutorial on Federated Learning (FL) and its role in enabling Edge Intelligence over wireless edge networks. This provides readers with a concise introduction to the challenges and state-of-the-art approaches towards implementing FL over the wireless edge network. Then, in consideration of resource heterogeneity at the network edge, the authors provide multifaceted solutions at the intersection of network economics, game theory, and machine learning towards improving the efficiency of resource allocation for FL over the wireless edge networks. A clear understanding of such issues and the presented theoretical studies will serve to guide practitioners and researchers in implementing resource-efficient FL systems and solving the open issues in FL respectively.
Federated Learning Systems: Towards Next-Generation AI (Studies in Computational Intelligence #965)
by Mohamed Medhat Gaber Muhammad Habib ur RehmanThis book covers the research area from multiple viewpoints including bibliometric analysis, reviews, empirical analysis, platforms, and future applications. The centralized training of deep learning and machine learning models not only incurs a high communication cost of data transfer into the cloud systems but also raises the privacy protection concerns of data providers. This book aims at targeting researchers and practitioners to delve deep into core issues in federated learning research to transform next-generation artificial intelligence applications. Federated learning enables the distribution of the learning models across the devices and systems which perform initial training and report the updated model attributes to the centralized cloud servers for secure and privacy-preserving attribute aggregation and global model development. Federated learning benefits in terms of privacy, communication efficiency, data security, and contributors’ control of their critical data.
Federated Learning Systems: Towards Privacy-Preserving Distributed AI (Studies in Computational Intelligence #832)
by Mohamed Medhat Gaber Muhammad Habib ur RehmanThis book dives deep into both industry implementations and cutting-edge research driving the Federated Learning (FL) landscape forward. FL enables decentralized model training, preserves data privacy, and enhances security without relying on centralized datasets. Industry pioneers like NVIDIA have spearheaded the development of general-purpose FL platforms, revolutionizing how companies harness distributed data. Alternately, for medical AI, FL platforms, such as FedBioMed, enable collaborative model development across healthcare institutions to unlock massive value. Research advances in PETs highlight ongoing efforts to ensure that FL is robust, secure, and scalable. Looking ahead, federated learning could transform public health by enabling global collaboration on disease prevention while safeguarding individual privacy. From recommendation systems to cybersecurity applications, FL is poised to reshape multiple domains, driving a future where collaboration and privacy coexist seamlessly.
Federated Learning for Future Intelligent Wireless Networks
by Lei Zhang Gang Feng Yao Sun Chaoqun YouFederated Learning for Future Intelligent Wireless Networks Explore the concepts, algorithms, and applications underlying federated learning In Federated Learning for Future Intelligent Wireless Networks, a team of distinguished researchers deliver a robust and insightful collection of resources covering the foundational concepts and algorithms powering federated learning, as well as explanations of how they can be used in wireless communication systems. The editors have included works that examine how communication resource provision affects federated learning performance, accuracy, convergence, scalability, and security and privacy. Readers will explore a wide range of topics that show how federated learning algorithms, concepts, and design and optimization issues apply to wireless communications. Readers will also find: A thorough introduction to the fundamental concepts and algorithms of federated learning, including horizontal, vertical, and hybrid FL Comprehensive explorations of wireless communication network design and optimization for federated learning Practical discussions of novel federated learning algorithms and frameworks for future wireless networks Expansive case studies in edge intelligence, autonomous driving, IoT, MEC, blockchain, and content caching and distribution Perfect for electrical and computer science engineers, researchers, professors, and postgraduate students with an interest in machine learning, Federated Learning for Future Intelligent Wireless Networks will also benefit regulators and institutional actors responsible for overseeing and making policy in the area of artificial intelligence.
Federated Learning for IoT Applications (EAI/Springer Innovations in Communication and Computing)
by Sachin Kumar Satya Prakash Yadav Dharmendra Prasad Mahato Bhoopesh Singh BhatiThis book presents how federated learning helps to understand and learn from user activity in Internet of Things (IoT) applications while protecting user privacy. The authors first show how federated learning provides a unique way to build personalized models using data without intruding on users’ privacy. The authors then provide a comprehensive survey of state-of-the-art research on federated learning, giving the reader a general overview of the field. The book also investigates how a personalized federated learning framework is needed in cloud-edge architecture as well as in wireless-edge architecture for intelligent IoT applications. To cope with the heterogeneity issues in IoT environments, the book investigates emerging personalized federated learning methods that are able to mitigate the negative effects caused by heterogeneities in different aspects. The book provides case studies of IoT based human activity recognition to demonstrate the effectiveness of personalized federated learning for intelligent IoT applications, as well as multiple controller design and system analysis tools including model predictive control, linear matrix inequalities, optimal control, etc. This unique and complete co-design framework will benefit researchers, graduate students and engineers in the fields of control theory and engineering.
Federated Learning for Neural Disorders in Healthcare 6.0 (Future Generation Information Systems)
by Anindya Nag Reddy C, Kishor KumarThis reference text offers a relevant and thorough examination of the overlap between neuroscience and federated learning. It explores the complexities of utilizing federated learning algorithms for MRI data analysis, demonstrating how to improve the accuracy and efficiency of diagnostic procedures. The book covers topics such as the prediction and diagnosis of Alzheimer’s disease using neural networks and ensuring data privacy and security in federated learning for neural disorders.This book: Provides a thorough examination of the transformative impact of federated learning on the diagnosis, treatment, and understanding of brain disorders Focuses on combining federated learning with magnetic resonance imaging (MRI) data, which is a fundamental aspect of contemporary neuroimaging research Examines the use of federated learning as a promising approach for collaborative data analysis in healthcare, with a focus on maintaining privacy and security Explores the cutting-edge field of healthcare innovation by examining the interface of neuroscience and machine learning, with a specific focus on the breakthrough technique of federated learning Offers a comprehensive understanding of how federated learning may transform patient care, covering both theoretical ideas and practical examples It is primarily written for graduate students and academic researchers in electrical engineering, electronics, and communication engineering, computer science and engineering, and biomedical engineering.
Federated and Transfer Learning (Adaptation, Learning, and Optimization #27)
by Qiang Yang Matthew E. Taylor Roozbeh Razavi-Far Boyu WangThis book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well as its connection with transfer learning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications.
Feed Additives and Supplements for Ruminants
by Vinod Kumar Yata M. S. MaheshThis book comprehensively reviews various feed additives and supplements that are employed for ruminant production and health. It discusses important strategies of using additives and supplements through rumen fermentation, immunomodulation, nutrient utilization, and cellular metabolism that lead to enhanced milk production, body weight gain, feed efficiency, and reproduction. The book also presents the importance of nutritional supplements such as B-vitamins, advances in mineral nutrition, role of lesser-known trace elements, protected amino acids, slow-release nitrogen and rumen buffers on performance and health of ruminants. In addition, the book explores strategies for improving environmental stewardship of ruminant production by minimizing carbon footprint associated with greenhouse gas emissions, enhancing ruminant-derived food safety through mycotoxin binders, exogenous enzymes, probiotics, flavours, biochar, ionophores, seaweeds and natural phytogenic feed additives with an emphasis on plant secondary metabolites (tannins, saponins and essential oils, etc.). It also details information on silage additives, additives and supplements employed in successful calf rearing, transition cow management as well as to ameliorate the adversity of heat stress in ruminants. Overall, the book is valuable for veterinary and animal science researchers, animal producers, nutrition specialists, veterinarians, and livestock advisors.