الصفحة 60
الصفحة 60
Magnetic Resonance of Myelination and Myelin Disorders
The book has been extensively revised and expanded to do justice to the rapid advances in MR technology, molecular biochemistry, and genetics and the discovery of new disease entities with prominent white matter involvement. Forty chapters have been added, and the number of illustrations has risen considerably. The ability to confirm the presence of genetic alterations in a number of disorders allows more advantageous presentation of the phenotypic variation as expressed in differ.
Magnetic Resonance Imaging in Ischemic Stroke
The imaging of stroke has undergone significant changes owing to the rapid progress in imaging technology. This volume, comprising three parts, is designed to provide a comprehensive summary of the current role of MR imaging in patients with ischemic stroke. The first part outlines the clinical presentations of stroke and discusses the diagnostic efficacy and therapeutic impact of MR imaging. The second and third parts form the core of the volume, and are based on a novel approach in that the topic is presented from two very different viewpoints. Part 2 provides a detailed presentation of the distinguishing features of stroke from the radiologist's perspective. By contrast, part 3 addresses the needs of the clinician, documenting specific stroke syndromes and their correlates on MR imaging. The overall aim has been to create a well-illustrated volume with broad appeal that links pathology, radiology and stroke medicine in an informative manner.
Magnetic Nanostructures in Modern Technology ; Spintronics, Magnetic MEMS and Recording
A team of outstanding scientists in the field of modern magnetic nanotechnologies illustrates the state of the art in several areas of advanced magneto-electronic devices, magnetic micro-electromechanical systems and high density information storage technologies.The physics and chemistry of nano-scale systems have made rapid advances and there are real prospects of translating exciting scientific findings into a new generation of processes and high technology products with a potential impact on several industrial sectors. In particular the development of nano-structured magnetic materials plays a leading role in the increasing miniaturization of devices with superior performances.
Magnetic nanoparticles in human health and medicine : Current medical applications and alternative therapy of cancer
Progress in improving diagnosis by magnetic resonance imaging (MRI) and using non-invasive and non-toxic magnetic nanoparticles for targeted drug delivery. Focusing on cancer diagnosis and therapy, the book covers both fundamental principles and advanced theoretical and experimental research on the magnetic properties, biocompatibilization, biofunctionalization, and application of magnetic nanoparticles in nanobiotechnology and nanomedicine.
Magnetic Heterostructures : Advances and Perspectives in Spinstructures and Spintransport
Magnetic heterostructures constitute an important field in magnetism and nanotechnology, which has developed over the past fifteen years due to important advances in epitaxial- growth techniques and lithographic processes. Magnetic heterostructures combine different physical properties which do not exist in nature. Examples are semiconductors/ferromagnets, superconductors/ferromagnets, and ferromagnets/antiferromagnets. These combinations display rich and novel physical properties different from those that exit in any single one of them. Interlayer exchange coupling, exchange bias, proximity effects, giant magneto-resistance, tunneling magneto-resistance, spininjection and spintransport are examples of new physical phenomena that rely on the combination of different materials layers
Magnesium Technology : Metallurgy, Design Data, Applications
Magnesium, with a density of 1.74 g/cm², is the lightest structural metal and magnesium are increasingly chosen for weight-critical applications such as in land-based transport systems. "Magnesium Technology" substantially updates and complements existing reference sources on this key material. It assembles international contributions from seven countries covering a wide range of research programs into new alloys with the requisite property profiles, i.e., the current state of both research and technological applications of magnesium. In particular, the international team of authors covers key topics, such as: casting and wrought alloys; fabrication methods; corrosion and protection; engineering requirements and strategies, with examples from the automobile, aerospace, and consumer-goods industries, and recycling.
Magnesium Injection Molding
Injection molding of metallic alloys is a modern and environment-friendly technology with universal features, capable of implementing many conventional and novel processing methods based on semisolid and liquid routes. After its application to magnesium and recent commercialization, it is used to manufacture millions of light-weight, fully-recyclable components for various markets, including consumer electronics housings, automotive parts, sporting goods, household devices and office equipment.
Macro-Engineering : A Challenge for the Future
Macro-engineering involves the large-scale modification and manipulation of natural systems for the benefit of mankind. The primary goals of some Earth-based macroprojects described in this book are power production, land reclamation, food production, climate change, environment, water, transport and coastal protection. Other Earth or space projects considered here have a more futuristic ring, but our present-day technical skill makes their realization possible. Earth-based macroprojects usually combine different aspects and aims. They have a major impact on the ecology of a region and the inhabitants' means of living (like tourism, fishing, shipping). Its effects may be felt worldwide, like the rise in global sea level after the damming and evaporation of large ocean gulfs for power production, or the change in climate following the regional reduction of solar insolation.
Machine learning in healthcare : Fundamentals and recent applications
Discusses how to build various ML algorithms and how they can be applied to improve healthcare systems. Healthcare applications of AI are innumerable: medical data analysis, early detection and diagnosis of disease, providing objective-based evidence to reduce human errors, curtailing inter- and intra-observer errors, risk identification and interventions for healthcare management, real-time health monitoring, assisting clinicians and patients for selecting appropriate medications, and evaluating drug responses. Extensive demonstrations and discussion on the various principles of machine learning and its application in healthcare is provided, along with solved examples and exercises.
Machine Learning in Computer Vision
The goal of this book is to address the use of several important machine learning techniques into computer vision applications. An innovative combination of computer vision and machine learning techniques has the promise of advancing the field of computer vision, which contributes to better understanding of complex real-world applications. The effective usage of machine learning technology in real-world computer vision problems requires understanding the domain of application, abstraction of a learning problem from a given computer vision task, and the selection of appropriate representations for the learnable (input) and learned (internal) entities of the system. In this book, we address all these important aspects from a new perspective: that the key element in the current computer revolution is the use of machine learning to capture the variations in visual appearance, rather than having the designer of the model accomplish this. As a bonus, models learned from large datasets are likely to be more robust and more realistic than the brittle all-design models.
Machine Learning for Multimedia Content Analysis
Challenges in complexity and variability of multimedia data have led to revolutions in machine learning techniques. Multimedia data, such as digital images, audio streams and motion video programs, exhibit richer structures than simple, isolated data items. A number of pixels in a digital image collectively conveys certain visual content to viewers. A TV video program consists of both audio and image streams that unfold the underlying story. To recognize the visual content of a digital image, or to understand the underlying story of a video program, we may need to label sets of pixels or groups of image and audio frames jointly.
Machine learning for cyber-physical systems: selected papers from the international conference ML4CPS 2023
Contains selected papers from the international conference ML4CPS – Machine Learning for Cyber-Physical Systems, which was held in Hamburg (Germany), from 29 to 31 March 2023. Cyber-physical systems are adaptive and learning: they analyze their environment and, based on observations, learn patterns, associations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnostics. Machine learning is the key technology for these developments.
Machine Learning for Cyber Physical Systems : Selected papers from the International Conference ML4CPS 2018
Presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.
Machine Learning for Cyber Agents : Attack and Defence
The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter.
Machine learning for biomedical application
Biomedicine is a multidisciplinary branch of medical science that consists of many scientific disciplines, e.g., biology, biotechnology, bioinformatics, and genetics; moreover, it covers various medical specialties. In recent years, this field of science has developed rapidly. This means that a large amount of data has been generated, due to (among other reasons) the processing, analysis, and recognition of a wide range of biomedical signals and images obtained through increasingly advanced medical imaging devices. The analysis of these data requires the use of advanced IT methods, which include those related to the use of artificial intelligence, and in particular machine learning. It is a summary of the Special Issue “Machine Learning for Biomedical Application”, briefly outlining selected applications of machine learning in the processing, analysis, and recognition of biomedical data, mostly regarding biosignals and medical images.
Machine learning approach for cloud data analytics in IoT
Covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications. Elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.
Machine learning and deep learning in medical data analytics and healthcare applications
Introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments.
Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks
Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.
Machine Learning and Big Data Analytics Paradigms : Analysis, Applications and Challenges
Intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.
Low-Temperature Physics
This book provides a concise but thorough introduction to important phenomena of low-temperature physics. It is ideally suited as a textbook for advanced undergraduates but will also be valuable for graduate students, scientists and engineers working in this field. Clear explanations of both theoretical and experimental approaches coupled with carefully selected problems will enable students to gain a firm understanding of even the most recent research developments.
