Bøker utgitt av Elsevier Science

Numerical Machine Learning is a simple textbook on machine learning that bridges the gap between mathematics theory and practice. The book uses numerical examples with small datasets and simple Python codes to provide a complete walkthrough of the underlying mathematical steps of seven commonly used machine learning algorithms and techniques, including linear regression, regularization, logistic regression, decision trees, gradient boosting, Support Vector Machine, and K-means Clustering. Through a step-by-step exploration of concrete numerical examples, the students (primarily undergraduate and graduate students studying machine learning) can develop a well-rounded understanding of these algorithms, gain an in-depth knowledge of how the mathematics relates to the implementation and performance of the algorithms, and be better equipped to apply them to practical problems. Key features -Provides a concise introduction to numerical concepts in machine learning in simple terms -Explains the 7 basic mathematical techniques used in machine learning problems, with over 60 illustrations and tables -Focuses on numerical examples while using small datasets for easy learning -Includes simple Python codes -Includes bibliographic references for advanced reading The text is essential for college and university-level students who are required to understand the fundamentals of machine learning in their courses.

"Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics? provides a comprehensive overview and update of the mass-action law-based unified dose-effect biodynamics, pharmacodynamics, bioinformatics, and the combination index theorem for synergy definition (MAL-BD/PD/BI/CI). Contents advocate the fundamental MAL-PD/BI/CI/BI principle for biomedical R&D, clinical trials protocol design computerized data analysis, illustrates the MAL-dynamics theory with sample analysis, and includes data entry and automated computer report print-outs. In 11 sections "Mass-Action Law Dynamics Theory and Algorithm for Translational and Precision Medicine Informatics? leads the reader from an introduction and overview, to trial protocols and MAL-PD/CI approach for biomedical R&D in vitro and in animals. It describes the current Landscape of International FDA Drug Evaluation, Clinical Pharmacology, and Clinical Trials Guidance. This is a valuable resource for biomedical researchers, healthcare professionals, and students seeking to harness the power of data informatics in precision medicine.

Ethics in Online AI-Based Systems: Risks and Opportunities in Current Technological Trends creates a space to explore the ethical relevance that new technologies under development may have. Stimulating reflection and considerations with respect to the design, deployment, and use of technology helps readers guide current and future technological advancements from an ethically informed position to ensure that such advancements contribute towards solving current global and social challenges that we, as a society, have today. This will not only be useful for researchers and professional engineers, but also for educators, policy makers, and ethicists. Recent technological advancements have deeply transformed society and the way people interact with each other. Instantaneous communication platforms have allowed connections with other people, forming global communities and creating unprecedented opportunities in many sectors, making access to online resources more ubiquitous by reducing limitations imposed by geographical distance and temporal constrains. These technological developments bear ethically relevant consequences with their deployment, and legislations often lag behind such advancements. Because the appearance and deployment of these technologies happen much faster than legislative procedures, the way these technologies affect social interactions have profound ethical effects before any legislative regulation can be built in order to prevent and mitigate those effects.

Comprehensive, yet concise and clinically oriented, the new edition of Ocular Pathology brings you the very latest advances of every aspect of ocular pathology. From updated information on today's imaging techniques, to the implementation of genetic data to better understand disease, this esteemed medical reference book promises to keep you at the forefront of your field.Consult this title on your favorite e-reader, conduct rapid searches, and adjust font sizes for optimal readability.Take advantage of clinical "e;pearls"e; that offer you the benefits of proven strategies.Quickly reference information with help from a convenient outline format, ideal for today's busy physician. Visualize every concept by viewing 1,900 illustrations, 1,600 of which are in full color, from the collections of internationally renowned leaders in ocular pathology.Understand the role of VEGF and other factors in the pathobiology of diabetic complications, as well as the pathobiology of myocilin and the TIGR gene in the development of glaucoma. Review the latest features related to the pathobiology of central corneal thickness.Stay abreast of the latest in ocular pathology with coverage of the classification system for retinoblastoma; immunopathology of herpes keratitis; and genetic features of persistent hyperplastic primary vitreous.

Advanced Mathematical Applications in Data Science comprehensively explores the crucial role mathematics plays in the field of data science. Each chapter is contributed by scientists, researchers, and academicians. The 13 chapters cover a range of mathematical concepts utilized in data science, enabling readers to understand the intricate connection between mathematics and data analysis. The book covers diverse topics, including, machine learning models, the Kalman filter, data modeling, artificial neural networks, clustering techniques, and more, showcasing the application of advanced mathematical tools for effective data processing and analysis. With a strong emphasis on real-world applications, the book offers a deeper understanding of the foundational principles behind data analysis and its numerous interdisciplinary applications. This reference is an invaluable resource for graduate students, researchers, academicians, and learners pursuing a research career in mathematical computing or completing advanced data science courses. Key Features: -Comprehensive coverage of advanced mathematical concepts and techniques in data science.-Contributions from established scientists, researchers, and academicians.-Real-world case studies and practical applications of mathematical methods.-Focus on diverse areas, such as image classification, carbon emission assessment, customer churn prediction, and healthcare data analysis.-In-depth exploration of data science's connection with mathematics, computer science, and artificial intelligence.-Scholarly references for each chapter.-Suitable for readers with high school-level mathematical knowledge, making it accessible to a broad audience in academia and industry.

This volume is a comprehensive guide to the industrial use of polymer composites. Edited contributions demonstrate the application of these materials for different industrial sectors. The book covers the benefits, future potential, and manufacturing techniques of different types of polymers. Contributors also address challenges in using nanopolymers in these industries. Readers will find valuable insights into the current demand and supply of polymer composites and future scope for research and development in this field of polymer science. The volume presents seven chapters, each exploring a different application of polymer composites. Chapter 1 discusses the use of polymer additives for improving classical concrete and the workability and durability of polymer composite concrete. Chapter 2 explores the use of polymer nanocomposites in packaging, including smart/intelligent packaging, modified atmosphere packaging, and vacuum packaging. Chapter 3 delves into the use of polymer composites in tissue engineering, including manufacturing techniques and various applications. Chapter 4 explores energy storage applications for polymer composites, while Chapter 5 discusses their use in microbial fuel cells. Chapter 6 explores the use of carbon nanotubes in polymer composite gas sensors. Finally, Chapter 7 discusses the use of polymer composites in automotive applications. This is an ideal reference for researchers, scientists, engineers, and professionals in the fields of materials science, polymer science, engineering, and nanotechnology. The content is also suitable for graduate and postgraduate students studying industrial manufacturing.

This book is a detailed reference guide on deep learning and its applications. It aims to provide a basic understanding of deep learning and its different architectures that are applied to process images, speech, and natural language. It explains basic concepts and many modern use cases through fifteen chapters contributed by computer science academics and researchers. By the end of the book, the reader will become familiar with different deep learning approaches and models, and understand how to implement various deep learning algorithms using multiple frameworks and libraries. This book is divided into three parts. The first part explains the basic operating understanding, history, evolution, and challenges associated with deep learning. The basic concepts of mathematics and the hardware requirements for deep learning implementation, and some of its popular frameworks for medical applications are also covered. The second part is dedicated to sentiment analysis using deep learning and machine learning techniques. This book section covers the experimentation and application of deep learning techniques and architectures in real-world applications. It details the salient approaches, issues, and challenges in building ethically aligned machines. An approach inspired by traditional Eastern thought and wisdom is also presented. The final part covers artificial intelligence approaches used to explain the machine learning models that enhance transparency for the benefit of users. A review and detailed description of the use of knowledge graphs in generating explanations for black-box recommender systems and a review of ethical system design and a model for sustainable education is included in this section. An additional chapter demonstrates how a semi-supervised machine learning technique can be used for cryptocurrency portfolio management. The book is a timely reference for academicians, professionals, researchers and students at engineering and medical institutions working on artificial intelligence applications.

Droplet and Digital Microfluidics: Ideation to Implementation is a detailed introduction to the dynamics of droplet and digital microfluidics, also featuring coverage of new methods and applications. The explosion of applications of microelectromechanical systems (MEMS) in recent years has driven demand for expertise and innovation in fluid flow in the microchannels they contain. In this book, detailed descriptions of methods for biological and chemical applications of microfluidics are provided, along with supporting foundational knowledge. In addition, the principles of droplet and digital microfluidics are explained, along with their different applications and governing physics. New additions to the technological knowledgebase that enable advances in droplet and digital microfluidics include machine learning and exciting future avenues for research.

Practical Petrophysics, Second Edition, Volume 62 provides a comprehensive overview of building a petrophysical model. All aspects from the principles of data acquisition through analysis to reporting are covered. This is not intended to be a review of specific tools and measurements, nor is it simply a recipe book. The book aims to teach the fundamental principles that underlie the commonly used tools and techniques but also to encourage pragmatism and avoid reading too much into what is always imperfect data.

Aliphatic Alkylation in Petroleum Refining provides a fundamental understanding on the alkylation process, from molecular-level interfacial properties to macroscopic industry plants. Since the direct distillation of oil fractions does not satisfy the whole demand for fuel feedstocks, processes such as reforming, isomerization, and alkylation are needed to fulfill the market requirements within the gasoline pool. From the processes mentioned above, this book covers one of the most important refining processes due to the high quality of the alkylate with high research octane number (RON). Although the Aliphatic alkylation with H2SO4 and HF as catalysts have been industrialized for many years, there still exists lots of problems due to the complex heterogeneous reaction, such as the thermodynamics, reaction mechanism, molecular-level interfacial properties, and so on.

The Science and Art of Sensory Processing Sensitivity provides an up-to-date and novel scientific perspective on the biologically based Sensory Processing Sensitivity (SPS) trait- which is associated with enhanced awareness, depth of cognitive processing, and heightened responsivity to the environment and other individuals. This second volume by B.P. Acevedo, following "The Highly Sensitive Brain," takes a scientific perspective on its exploration of SPS, but adds to the existing body of literature on high sensitivity by including an enhanced discussion on the proposed mechanisms linking it with depression, anxiety, and burnout. In addition, this second volume explores SPS’ relationship to other relevant personality traits, such as the Big Five, creativity, and sensation seeking; and sheds light on how their varying combinations give rise to different outcomes for highly sensitive persons (HSPs). A unique contribution of this volume is its detailed examination of the role of culture, gender, biology, aging, and the environment (including the workplace) on the expression (or repression) of high sensitivity. Also, unlike previous books, this volume takes a broad perspective on outcomes related to being highly sensitive to shine a light on the non-trivial issue plaguing many HSPs: diminished quality of life, happiness, and well-being. As such, a major contribution of the second volume on the science of SPS, is its extensive description of scientifically-based techniques that might improve the quality of life for those with high SPS. Thus, this volume may appeal to a wide audience, including both HSPs and those in their social network (friends, partners, physicians, parents, educators, and clinicians) who wish to better understand SPS, those with the trait, and how to enhance well-being among the highly sensitive.

Clinician's Guide to Headache: Head, Neck and Face Pain Syndromes is a comprehensive reference that covers what headache specialists encounter in day-to-day headache practice settings. This practical volume is relevant as a primary reference for neurologists and other headache specialists looking for a resource on complex, acute headache management. Developments in the field are highlighted, including biologics and invasive and non-invasive neuromodulation. Chapters focus on anatomy and pathophysiology, neuroradiology, acute and chronic headaches, and clinically relevant sections on diagnosis and biases, consultation settings, placebos and nocebos, as well as the set-up of a comprehensive headache center. With a foundation based on recent developments in pathophysiology and anatomy, this volume provides an overview of headache disorders with a case-based approach.

Polymer Composites Derived from Animal Sources presents a systematic review of recent developments in this important research field. The book provides a thorough introduction to the various types of animal-based material resources currently available and discusses their morphology, extraction process, sustainability, formation, properties, and applications. Emphasis is placed on applications of polymer composites derived from wool, silk, chicken, bovine, marine life, and animal waste. Different types of processing techniques are discussed in detail as well as chemical modification, interfacial adhesion, and the structure-property relationship. The book will be a valuable reference resource for academic and industrial researchers, and materials scientists and engineers working on the research and development of natural-based composites derived from animal sources.

Machine Learning and Artificial Intelligence in Chemical and Biological Sensing covers the theoretical background and practical applications of various ML/AI methods toward chemical and biological sensing. No comprehensive reference text has been available previously to cover the wide breadth of this topic. The book's editors have written the first three chapters to firmly introduce the reader to fundamental ML theories that can be used for chemical/biosensing. Subsequent chapters then cover the practical applications with contributions by various experts in the field. Sections show how ML and AI-based techniques can provide solutions for: 1) identifying and quantifying target molecules when specific receptors are unavailable 2) analyzing complex mixtures of target molecules, such as gut microbiome and soil microbiome 3) analyzing high-throughput and high-dimensional data, such as drug screening, molecular interaction, and environmental toxicant analysis, 4) analyzing complex data sets where fingerprinting approach is needed This book is written primarily for upper undergraduate students, graduate students, research staff, and faculty members at teaching and research universities and colleges who are working on chemical sensing, biosensing, analytical chemistry, analytical biochemistry, biomedical imaging, medical diagnostics, environmental monitoring, and agricultural applications.

Advanced Materials-based Thermally Enhanced Phase Change Materials: Fundamentals and Applications focuses on the use of advanced materials to enhance the thermal characteristics of phase change materials used to maximize heat transfer rate and thermal storage capability of PCMs. The book covers the various aspects of PCMs through characteristics and preparation to heat transfer enhancement with an emphasis on prominent applications. It progresses from a brief history to a literature review, definitions, recent advances, preparation techniques, thermophysical properties and heat transfer characteristics with mathematical models, performance-affecting factors, and applications and challenges of PCMs in manufacturing. This powerful tool for researchers and energy engineers offers cutting-edge materials advances, analysis and applications of phase change materials in manufacturing.

Water Sustainability and Hydrological Extremes: Quantity, Quality, and Security presents a study for the mitigation of hydrological extremes through case studies. The focus is on the effect of extremes on water quality and the fate of geogenic, microbial, anthropogenic pollutants in the water cycle, and the interaction of water quality and quantity variations. The book integrates rapidly growing diverse topics, such as co-occurrence variation in water quantity and quality, water supply, sanitation, and hygiene. Stakeholders' participation and raising awareness for sustainable management strategies for hydrological extremes and water management systems is also covered.This thorough guide serves as a pillar to postgraduate students and researchers as it's centered on discovering remediation and natural attenuation of hydrological extremes with a special emphasis on present and future challenges.

Fundamental Principles of Oxidative Stress in Metabolism and Reproduction: Prevention and Management is a comprehensive resource for anyone needing awareness and recognition of oxidative stress as a basic component of disease to determine the precise treatment plan considering the cause of the disease. It describes the effects of oxidative stress in the human body, the detection of metabolic changes, psychological impact and effect on reproductive outcomes. In addition, it discusses alterations at the cellular level occurring due to oxidative stress along with the genetic aspects involved in its pathogenesis.

Gallstone Formation, Diagnosis, Treatment, and Prevention describes the current scenario of gallstones and adopted treatment methods. It is a complete reference for researchers introducing new techniques to help prevent extreme treatments such as a cholecystectomy. This reference provides current knowledge and basic challenges of understanding gallstone formation, with all variations of composition, including complications of the treatment process. This content directs researchers to focus on gallstone mechanisms to design and develop new treatment methods. The book provides all possible factors for gallstone formation as well as preventative measures.

Besides their notable historical and cultural significance, heritage buildings crucially contribute to the economy of those countries that rely heavily on the tourism industry. Investigation and monitoring of the origins of deterioration and damage are therefore key to the preservation of architectural heritage. Diagnosis of Heritage Buildings by Non-Destructive Techniques offers an up-to-date overview of state-of-the-art knowledge by collating specialized studies written by an international group of experts in the field, while also examining the value of these non-intrusive methods through a number of real-life case studies which prove NDT techniques’ global relevance. The volume is an invaluable reference resource for students, researchers, and practitioners alike.

Polymer/Nanodiamond Nanocomposites: Fundamentals, Properties and Applications provides an up-to-date review of these materials. The structure, design, processing, and properties, as well as technological advancements, are all thoroughly discussed. Several practical and potential application areas are also identified such as tribological aerospace/automobile materials (thermally conducting, lubricant, and radiation shielding), coatings/anti-corrosion nanomaterials, shape memory nanocomposites, energy devices (Li ion batteries and solar cells), and biomedical nanomaterials (drug delivery, tissue engineering, biosensor, imaging). Current difficulties and potential opportunities are also discussed in detail. The book covers all aspects of these new novel materials' design, structure, manufacture, and applications, offering an up-to-date, comprehensive knowledge resource for materials scientists, researchers, and engineers.

As UAV technology is rapidly evolving, a pervasive need for a thorough investigation of its full capabilities has come to the forefront. Internet of Drone Things: Architectures, Approaches, and Applications fulfils this need enabling its readers to easily find the answers they are seeking by providing a comprehensive overview of the topic.This book, in fact, includes fundamental information related to IoDT architecture design and features; reviews the state of the art in hardware and software platforms to deploy, connect, and control drones or swarms of drones; and covers the latest developments in innovative drone-facilitated applications and services that can significantly improve efficiency, productivity, and sustainability of various operations in modern society and a growing number of its industries. Finally, experimental modeling and simulations are accompanied by prototyping examples, which are set to become the benchmark of next-level automation in the field.Internet of Drone Things: Architectures, Approaches, and Applications is, therefore, an invaluable resource for engineering students, researchers, and professionals, as well as sector experts who work to develop new drone standards or to identify new drone technology use and commercialization areas at an international level.

Reliability and Resilience in the Internet of Things explains the latest advances in reliability and resilience modeling, analysis, and design techniques for Internet of Things (IoT) systems. Over the last decade, IoT has developed rapidly, and it now spans diverse application domains such as healthcare, home automation, smart manufacturing, smart ocean, and smart agriculture. Due to the critical nature of these applications, it is imperative that the IoT systems operate reliably throughout the intended mission time. This timely book provides state-of the-art coverage on IoT reliability and resilience modeling, analysis, and design methods and solutions to help prevent costly malfunctions. From the viewpoint of engineers, researchers, and developers, reliability analysis and resilience design are key to the deployment and operation of IoT systems in critical applications, and this book contains the best advice on the subject available. It is a valuable resource for researchers in academia and industry interested in smart IoT systems and Industry 4.0.

Terramechanics and Off-Road Vehicle Engineering: Terrain Behaviour and Off-Road Mobility, Third Edition provides comprehensive coverage of terrain behavior, mechanics of wheel- and track-terrain interaction, and various types of models for cross-country performance, ranging from empirical, through theoretical, to physics-based engineering models. The physics-based models for wheeled and tracked vehicle performance developed under the direction of Prof. J.Y. Wong have been gaining increasingly wider acceptance by industry and governmental agencies. The mathematical models established for vehicle-terrain systems enable the engineering practitioner to evaluate a wide range of options and select an appropriate vehicle configuration for any given mission and environment. This long-anticipated revision presents the fields' significant developments over the past decade, both through updates to existing chapters and the inclusion of new material related to modeling applications in addition to a notable, state-of-the-art excursus on extra-terrestrial rovers.

Health Neuroscience is a new interdisciplinary field encompassing research from cognitive, affective, and social neuroscience, health psychology, physical and mental health, and science of behavior change. This new field addresses the longstanding gap among neuroscience, health, and behavior change within the context of health promotion.Fundamentals of Health Neuroscience explores key topics and research, including basic principles, psychological and neural processes, brain and body interactions, and gene x brain x environment interactions. This book also covers brain-based precision prevention and intervention strategies for health decisions and promotion across the lifespan. Chapters integrate the latest research findings and explores several key topics, such as: How does the brain serve both as a predictor and an outcome of health? How can people improve self-control and achieve physical and mental health effectively? What does brain plasticity and resilience tell us about optimal learning, performance, and development throughout our life? How is the sense of meaning in life affected by dopamine and reward systems in the brain?

Liposomes in Drug Delivery: What, Where, How and When to Deliver is a concise, well-structured reference covering all the important issues related to the potential of this technology. Organized to provide practical information to researchers from any discipline with a particular therapeutic or bio-active substance to deliver, this book helps readers understand if liposomes can be of benefit for their particular need, what is the best type of liposome to use according to what needs to be delivered, where/when to deliver it, and how to design/prepare/characterize/investigate/optimize liposome properties for a particular application. The book is structured in Four parts. The first covers in a concise but in-depth way, what liposomes are, which are the liposome types, advantages/disadvantages, and what is their stability, characterization methods, in vitro stability, and in vivo fate after different administration methods (routes). The second part focuses on the different mechanisms for liposomal drug delivery. Methodologies/technologies for manipulation of liposome structure/properties in order to design liposomes for particular delivery applications. Specific roadmaps for liposome design are discussed, including components to incorporate in liposomes for specific types of encapsulated molecules or specific routes of administration. The third part covers liposome applications for drug delivery. It focuses on specific delivery considerations for particular diseases. Finally, the fourth part covers methods of liposome fabrication.

Human Organs-on-Chip: Novel Organ-on-a-Chip Techniques in Medicine paves the way for novel approaches that push forward in-vitro and in-vivo studies and fills a gap between laboratory and clinical use. The book's experienced authors share the knowledge they've developed with over a decade of research with organ-on-chips and multi-organ-on-chips. The book collects all of the developments in the field and sheds new light on possibilities to develop human on-chip measurement methods with the utilization of currently available measurement techniques including both invasive and non-invasive tests. This book will serve as a starting point for young researchers who are beginning their scientific journeys.

Green Imprinted Materials: From Design to Environmental and Food Applications provides a comprehensive overview of green aspects to MIPs. With a strong focus on food and environment, this book provides insights into the state-of-the-art and practice of green chemistry and its approaches to imprinting. Methodologies for the preparation of these materials, as well as their potential in developing sustainable separation and sensing processes in analytical and bioanalytical chemistry are critically discussed throughout the book. Future perspectives of green imprinting technology is also evaluated. This book is a valuable resource for researchers and graduate students in molecular imprinting science and technology and those interested in green chemistry and all those who wish to broaden their knowledge in the allied field.

Sustainable Development of Renewable Energy, Volume One in the Advances in Renewable Energy Technologies series, looks at the production performance of renewable energy sources and emerging production processes. Chapters cover some of the most dynamic developments, best practices, and future concepts in solar energy systems, energy storage, geothermal energy, bioenergy, wind energy, fuel cells, and hydrogen production. The book also includes recent regulations and worldwide policies. By reviewing these state-of-art advances, this book provides readers with an up-to-date source on renewable energy grid integration and its importance in aiding the energy transition. This is a valuable resource for graduates, researchers, professors, and industry professionals involved in the renewable energy sector, as well as advanced engineering courses dealing with renewable energy, sources, thermal and electrical energy production, and sustainability.

Fundamentals of Uncertainty Quantification for Engineers: Methods and Models provides a comprehensive introduction to uncertainty quantification (UQ) accompanied by a wide variety of applied examples, implementation details, and practical exercises to reinforce the concepts outlined in the book. Sections start with a review of the history of probability theory and recent developments of UQ methods in the domains of applied mathematics and data science. Major concepts of probability axioms, conditional probability, and Bayes’ rule are discussed and examples of probability distributions in parametric data analysis, reliability, risk analysis, and materials informatics are included. Random processes, sampling methods, and surrogate modeling techniques including multivariate polynomial regression, Gaussian process regression, multi-fidelity surrogate, support-vector machine, and decision tress are also covered. Methods for model selection, calibration, and validation are introduced next, followed by chapters on sensitivity analysis, stochastic expansion methods, Markov models, and non-probabilistic methods. The book concludes with a chapter describing the methods that can be used to predict UQ in systems, such as Monte Carlo, stochastic expansion, upscaling, Langevin dynamics, and inverse problems, with example applications in multiscale modeling, simulations, and materials design.

The Neuroscience of Bach's Music: Perception, Action, and Cognition Effects on the Brain is a comprehensive study of Johann Sebastian Bach's music through the lens of neuroscience, examining neuroscience using Bach's music as a tool. This book synthesizes cognitive neuroscience, music theory, and musicology to provide insights into human cognition and perception. It also explores how a neuroscience perspective can improve listening and performing experiences for Bach's music. Written by a physician-neuroscientist recognized for scholarly articles on Bach's music, this book uses specific examples to explore neuroscience across Bach's compositions. The book is structured to discuss the brain's action, perception, and cognition as connected to specific Bach concertos, tones, notes, and performances. Two guest contributors provide insight into exact mathematical, or topologic, and music theoretic aspects of Bach's music with implications for cognitive neuroscience.