Page 105
Page 105
Macroscopic Transport Equations for Rarefied Gas Flows : Approximation Methods in Kinetic Theory
This book discusses classical and modern methods to derive macroscopic transport equations for rarefied gases from the Boltzmann equation, for small and moderate Knudsen numbers, i.e.as well as the new order of magnitude method, which avoids the short-comings of the classical methods, but retains their benefits.
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.
Machining: Fundamentals and Recent Advances
Machining is one of the most important manufacturing processes. Parts manufactured by others processes often require further operations before the product is ready for application. Machining is the broad term used to describe the removal of material from a work-piece. Machining processes can be applied to work metallic and non-metallic materials such as polymers, wood, ceramics and composites.
Machine learning refined : Foundations, algorithms, and applications
Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization
Machine learning methods for reverse engineering of defective structured surfaces
Pascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces: parametrization of curves and surfaces, geometric primitive classification and inpainting of high-resolution textures. The proposed methods aim to improve the reconstruction quality while further automating the process. The contributions demonstrate that machine learning can be a viable part of the CAD reverse engineering pipeline.
Machine Learning in Document Analysis and Recognition
The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphicalcomponents of a document and to extract information. With ?rst papers dating back to the 1960’s, DAR is a mature but still gr- ing research?eld with consolidated and known techniques. Optical Character Recognition (OCR) engines are some of the most widely recognized pr- ucts of the research in this ?eld, while broader DAR techniques are nowadays studied and applied to other industrial and o?ce automation systems. In the machine learning community, one of the most widely known - search problems addressed in DAR is recognition of unconstrained handwr- ten characters which has been frequently used in the past as a benchmark for evaluating machine learning algorithms, especially supervised classi?ers.
Machine learning for cyber security ; 3rd International Conference, ML4CS 2020, Guangzhou, China, October 8–10, 2020, Proceedings, Part III
Constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi’an, China in October 2020. The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.
Machine Learning for Cyber Security ; 3rd International Conference, ML4CS 2020, Guangzhou, China, October 8–10, 2020, Proceedings, Part II
Constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi’an, China in October 2020. The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.
Machine Learning for Cyber Security ; 3rd International Conference, ML4CS 2020, Guangzhou, China, October 8–10, 2020, Proceedings, Part I
Constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi’an, China in October 2020. The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.
Machine Learning for Cyber Physical Systems : Selected papers from the International Conference ML4CPS 2020
Presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020.
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 civil and environmental engineers : A practical approach to data-driven analysis, explainability, and causality
Introduces engineers and engineering students to the applications of artificial intelligence (AI), machine learning (ML), and machine intelligence (MI) in relation to civil and environmental engineering projects and problems, presenting state-of-the-art methodologies and techniques to develop and implement algorithms in the engineering domain.
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 Applications in Civil Engineering
Discusses machine learning and deep learning models for different civil engineering applications. These models work for stochastic methods wherein internal processing is done using randomized prototypes. The book explains various machine learning model designs that will assist researchers to design multi domain systems with maximum efficiency. It introduces Machine Learning and its applications to different Civil Engineering tasks, including Basic Machine Learning Models for data pre-processing, models for data representation, classification models for Civil Engineering Applications, Bioinspired Computing models for Civil Engineering, and their case studies.
Machine Learning and Robot Perception
Presents some of the most recent research results in the area of machine learning and robot perception. The chapters represent new ways of solving real-world problems. This book will appeal to researchers, senior undergraduate/postgraduate students, application engineers and scientists.
Mac OS X Leopard : Beyond the Manual
Good computer books make assumptions about the reader: what they do and don't know when they pick up the book, and what they want to know when they put it down. For each reader this could be very different; therefore, a book that suits one person may not be the best for another. Mac OS X Leopard: Beyond the Manual makes some assumptions too, ones that tend to differ from other Mac OS X books. First of all, we assume that you have used a computer in that past: that you know how to use a mouse and you know the proper place to stick a DVD to get it to play in your computer. We won't be showing you these things. (We will, however, demonstrate to our Mac converts how to “right click” on a trackpad with only one button!).
Lunar and planetary rovers : The wheels of apollo and the Quest for Mars
Provides extensive quotes from the astronauts who drove the LRV on the Moon from interviews conducted especially for the book. It also details new material from interviews of engineers and managers at the Jet Propulsion Laboratory covering the robotic rovers, Sojourner, Sprit and Opportunity. The Foreword is written by David R. Scott, Commander of Apollo 15. Chapter 1: From Concept to Reality; Chapter 2: Lunar Roving Vehicle Subsystems; Chapter 3: Training for the Moon; Chapter 4: To the Hadley Plains; Chapter 4: Mysterious and Unknown Descartes; Chapter 5: Destiny at Taurus-Littrow; Chapter Six: The Quest for Mars-Chapter Seven: The New Vision of Exploration.
LRFD Bridge Design : Fundamentals and Applications
Examines and explains material from the 9th edition of the AASHTO LRFD Bridge Design Specifications, including deck and parapet design, load calculations, limit states and load combinations, concrete and steel I-girder design, bearing design, and more. With increased focus on earthquake resiliency, two separate chapters– one on conventional seismic design and the other on seismic isolation applied to bridges– will fully address this vital topic. The primary focus is on steel and concrete I-girder bridges, with regard to both superstructure and substructure design. / Includes several worked examples for a project bridge as well as actual bridges designed by the author / Examines seismic design concepts and design details for bridges / Presents the latest material based on the 9th edition of the LRFD Bridge Design Specifications / Covers fatigue, strength, service, and extreme event limit states / Includes numerous solved problems and exercises at the end of each chapter to illustrate the concepts presented
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.
Low-Power Low-Voltage Sigma-Delta Modulators in Nanometer CMOS
At the system level, a novel systematic study on the full feedforward Sigma-Delta topology is presented in this book. As a design example, a fourth-order single-loop full feedforward Sigma-Delta modulator design in a 130-nm pure digital CMOS technology is presented. This design is the first design using the full feedforward Sigma-Delta topology and reaches the highest conversion speed among all the 1-V Sigma-Delta modulators to date.
