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Introduction to Reliable Distributed Programming
Guerraoui and Rodrigues present an introductory description of fundamental reliable distributed programming abstractions as well as algorithms to implement these abstractions. The authors follow an incremental approach by first introducing basic abstractions in simple distributed environments, before moving to more sophisticated abstractions and more challenging environments. Each core chapter is devoted to one specific class of abstractions, covering reliable delivery, shared memory, consensus and various forms of agreement. This textbook comes with a companion set of running examples implemented in Java. These can be used by students to get a better understanding of how reliable distributed programming abstractions can be implemented and used in practice. Combined, the chapters deliver a full course on reliable distributed programming. The book can also be used as a complete reference on the basic elements required to build reliable distributed applications.
Introduction to Relativistic Continuum Mechanics
This mathematically-oriented introduction takes the point of view that students should become familiar, at an early stage, with the physics of relativistic continua and thermodynamics within the framework of special relativity. Therefore, in addition to standard textbook topics such as relativistic kinematics and vacuum electrodynamics, the reader will be thoroughly introduced to relativistic continuum and fluid mechanics. Emphasis in the presentation is on the 3+1 splitting technique, widely used in general relativity for introducing the relative observers point of view.
Introduction to Reconfigurable Computing : Architectures, Algorithms, and Applications
“Introduction to Reconfigurable Computing” provides a comprehensive study of the field Reconfigurable Computing. It provides an entry point to the novice willing to move in the research field reconfigurable computing, FPGA and system on programmable chip design. The book can also be used as teaching reference for a graduate course in computer engineering, or as reference to advance electrical and computer engineers. It provides a very strong theoretical and practical background to the field of reconfigurable computing, from the early Estrin’s machine to the very modern architecture like coarse-grained reconfigurable device and the embedded logic devices.
Introduction to Project Management : A Source Book for Traditional PM Basics
Presents the fundamentals of project management in simple language and an easy-to-understand format. It is targeted principally at those who are learning or desiring to learn project management as well as those who are already taking project management as a course of study or as a profession
Introduction to Programming with Fortran : with coverage of Fortran 90, 95, 2003 and 77
Introduction to Programming with Fortran contains: lots of clear and simple examples highlighting the key language features of the most recent versions of Fortran – Fortran 2003, 95 and 90. practical examples based on ISO TR 15580 and ISO TR 15581 which are widely supported and cover the ISO TR on Enhanced Modules – particularly important to large code suites common problems that occur when programming which are highlighted via clear examples and solutions Introduction to Programming with Fortran is an essential introduction for beginners as well as a concise reference for professionals. Overall the book gives a very effective hands-on coverage of Fortran, valuable to students and practitioners alike.
Introduction to Probability with Statistical Applications
This textbook is an introduction to probability and statistics for non-mathematics majors who do not need the exhaustive detail and mathematical depth provided in more comprehensive treatments of the subject. The presentation covers the mathematical laws of random phenomena, including discrete and continuous random variables, expectation and variance, and common probability distributions such as the binomial, Poisson, and normal distributions. Main statistical concepts considered are point and interval estimates, hypothesis testing, power function, various statistical tests: z, t, chi-square and Kolmogorov-Smirnov.
Introduction to Planetary Science : The Geological Perspective
This textbook is intended to be used in a lecture course for college students majoring in the Earth Sciences. Planetary Science provides an opportunity for these students to apply a wide range of subject matter pertaining to the Earth to the study of other planets of the solar system and their principal satellites. As a result, students gain a wider perspective of the different worlds that are accessible to us and they are led to recognize the Earth as the only oasis in space where we can live without life-support systems.The subject matter is presented in 24 chapters that lead the reader through the solar system starting with historical perspectives on space exploration and the development of the scientific method. The presentations concerning the planets and their satellites emphasize that their origin and subsequent evolution can be explained by applications of certain basic principles of physics, chemistry, and celestial mechanics and that the surface features of the solid bodies in the solar system can be interpreted by means of the principles of geology.
Introduction to Physics and Chemistry of Combustion : Explosion, Flame, Detonation
Most of the material covered in this book deals with the fundamentals of chemistry and physics of key processes and fundamental mechanisms for various combustion and combustion-related phenomena in gaseous combustible mixture. It provides the reader with basic knowledge of burning processes and mechanisms of reaction wave propagation
Introduction to Permanent Plug and Abandonment of Wells
This book offers a timely guide to challenges and current practices to permanently plug and abandon hydrocarbon wells. With a focus on offshore North Sea, it analyzes the process of plug and abandonment of hydrocarbon wells through the establishment of permanent well barriers.
Introduction to Partial Differential Equations: A Computational Approach
Mathematics is playing an ever more important role in the physical and biological sciences, provoking a blurring of boundaries between scientific disciplines and a resurgence of interest in the modern as well as the cl- sical techniques of applied mathematics. This renewal of interest, both in research and teaching, has led to the establishment of the series: Texts in Applied Mathematics (TAM). The development of new courses is a natural consequence of a high level of excitement on the research frontier as newer techniques, such as numerical and symbolic computer systems, dynamical systems, and chaos mix with and reinforce the traditional methods of applied mathematics. Thus, the purpose of this textbook series is to meet the current and future needs of these advances and encourage the teaching of new courses.
Introduction to organic and medicinal chemistry
Designed to be an undergraduate reference textbook for students of chemistry who aim to select degree modules geared towards medicinal chemistry. The first two chapters offer an overview of basic organic chemistry, followed by organic synthesis in Chapter 3, with an emphasis on the importance of synthetic procedures in relation to the chemistry of drug design. In Chapter 4, the book covers foundational aspects of biochemistry and biomedical science to provide a basis for students understanding where and how drugs work on selected targets. Later, the book explains how medicines have been created for selected topics in medicinal chemistry – namely against pathogens, cancer and neurological targets.
Introduction to Optics
Since the discovery of the laser in 1960 and optical fibers in 1970, optics has undergone dramatic changes that accentuate its multi-disciplinary character. This text covers essential concepts and reports the key developments and progress in current knowledge in the field. Inspired by the style of Richard Feynman, the method of presentation emphasizes "telling" optics, rather than deducing it from fundamental laws, as well as tactfully using mathematical tools so as not to obscure the physical phenomena of interest. For its excellent teaching approach, the book received the Arnulf-Francon Award of the French Optical Society. The concepts are formulated in a way such that the necessary mathematical tools do not hinder comprehension of the phenomena. Global in vision, the book can also be used as a reference. In addition to the traditional aspects of optics, it includes the tools and methods currently used by researchers and engineers, as well as explanation and implications of the most recent developments.
Introduction to Operating System Design and Implementation : The OSP 2 Approach
This book exposes students to many essential features of operating systems while at the same time isolating them from low-level, machine-dependent concerns. With its accompanying software, the book contains enough projects for up to three semesters.
Introduction to Numerical Methods in Differential Equations
This is a textbook for upper division undergraduates and beginning graduate students. Its objective is that students learn to derive, test and analyze numerical methods for solving differential equations, and this includes both ordinary and partial differential equations. In this sense the book is constructive rather than theoretical, with the intention that the students learn to solve differential equations numerically and understand the mathematical and computational issues that arise when this is done. An essential component of this is the exercises, which develop both the analytical and computational aspects of the material. The importance of the subject of the book is that most laws of physics involve differential equations, as do the modern theories on financial assets.
Introduction to Modern Time Series Analysis
This excellent textbook presents an introduction to the time series analysis. It provides a good source of information for graduate and master students in economics and statistics. It is a well-written and easy to read book, illustrated by 56 good examples. Also, many important references are listed at the end of each chapter.This book presents to beginners a readable and easily accessible introduction to modern developments in time series econometrics and financial time series with an emphasis on basic concepts and practical applications. The book is a textbook consisting of seven chapters the greatest merit of this textbook is that it enables readers to grasp the basic framework of time-series econometrics without relying on extensive reading
Introduction to Mathematical Systems Theory : Linear Systems, Identification and Control
This book provides an introduction to the theory of linear systems and control for students in business mathematics, econometrics, computer science, and engineering. The focus is on discrete time systems, which are the most relevant in business applications, as opposed to continuous time systems, requiring less mathematical preliminaries. The subjects treated are among the central topics of deterministic linear system theory: controllability, observability, realization theory, stability and stabilization by feedback, LQ-optimal control theory. Kalman filtering and LQC-control of stochastic systems are also discussed, as are modeling, time series analysis and model specification, along with model validation.
Introduction to Mathematical Methods in Bioinformatics
This book looks at the mathematical foundations of the models currently in use. This book is unique in the sense that it looks at the mathematical foundations of the models, which are crucial for correct interpretation of the outputs of the models.
Introduction to Machine Learning with Applications in Information Security
Provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn't prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec.
Introduction to Lie Algebras
This book provides an elementary introduction to Lie algebras. It starts with basic concepts. A section on low-dimensional Lie algebras provides readers with experience of some useful examples. This is followed by a discussion of solvable Lie algebras and a strategy towards a classification of finite-dimensional complex Lie algebras. The next chapters cover Engel's theorem, Lie's theorem and Cartan's criteria and introduce some representation theory. The root-space decomposition of a semisimple Lie algebra is discussed, and the classical Lie algebras studied in detail. The authors also classify root systems, and give an outline of Serre's construction of complex semisimple Lie algebras. An overview of further directions then concludes the book and shows the high degree to which Lie algebras influence present-day mathematics.The only prerequisite is some linear algebra and an appendix summarizes the main facts that are needed. The treatment is kept as simple as possible with no attempt at full generality.
Introduction to Intelligent Construction Technology of Transportation Infrastructure
Expounds on the related technologies of intelligent transportation infrastructure construction. Based on the essential characteristics of intelligent construction, "perception, analysis, decision-making, and execution," the basic structure of intelligent construction technology (ICT) is established. With the integration of engineering construction technologies, the analyses of the essence of intelligent algorithms and the feasibility of Artificial Intelligence (AI) are provided. The book introduces the essential characteristics of Big Data and the Internet of Things and their relationship with engineering construction. On this basis, the feasibility and implementation plan of intelligent technology applications in design, construction, and maintenance are analyzed and demonstrated with engineering examples.
