The First Complete Guide to DevOps for Software Architects DevOps promises to accelerate the release of new software features and improve monitoring of systems in production, but its crucial implications for software architects and architecture are often ignored. In DevOps: A Software Architect’s Perspective, three leading architects address these issues head-on. The authors review decisions software architects must make in order to achieve DevOps’ goals and clarify how other DevOps participants are likely to impact the architect’s work. They also provide the organizational, technical, and operational context needed to deploy DevOps more efficiently, and review DevOps’ impact on each development phase. The authors address cross-cutting concerns that link multiple functions, offering practical insights into compliance, performance, reliability, repeatability, and security. This guide demonstrates the authors’ ideas in action with three real-world case studies: datacenter replication for business continuity, management of a continuous deployment pipeline, and migration to a microservice architecture. Comprehensive coverage includes • Why DevOps can require major changes in both system architecture and IT roles • How virtualization and the cloud can enable DevOps practices • Integrating operations and its service lifecycle into DevOps • Designing new systems to work well with DevOps practices • Integrating DevOps with agile methods and TDD • Handling failure detection, upgrade planning, and other key issues • Managing consistency issues arising from DevOps’ independent deployment models • Integrating security controls, roles, and audits into DevOps • Preparing a business plan for DevOps adoption, rollout, and measurement
THE FIRST PRACTICAL GUIDE FOR OPERATIONALIZING RESPONSIBLE AI ̃FROM MUL TI°LEVEL GOVERNANCE MECHANISMS TO CONCRETE DESIGN PATTERNS AND SOFTWARE ENGINEERING TECHNIQUES. AI is solving real-world challenges and transforming industries. Yet, there are serious concerns about its ability to behave and make decisions in a responsible way. Operationalizing responsible AI is about providing concrete guidelines to a wide range of decisionmakers and technologists on how to govern, design, and build responsible AI systems. These include governance mechanisms at the industry, organizational, and team level; software engineering best practices; architecture styles and design patterns; system-level techniques connecting code with data and models; and trade-offs in design decisions. Responsible AI includes a set of practices that technologists (for example, technology-conversant decision-makers, software developers, and AI practitioners) can undertake to ensure the AI systems they develop or adopt are trustworthy throughout the entire lifecycle and can be trusted by those who use them. The book offers guidelines and best practices not just for the AI part of a system, but also for the much larger software infrastructure that typically wraps around the AI. First book of its kind to cover the topic of operationalizing responsible AI from the perspective of the entire software development life cycle. Concrete and actionable guidelines throughout the lifecycle of AI systems, including governance mechanisms, process best practices, design patterns, and system engineering techniques. Authors are leading experts in the areas of responsible technology, AI engineering, and software engineering. Reduce the risks of AI adoption, accelerate AI adoption in responsible ways, and translate ethical principles into products, consultancy, and policy impact to support the AI industry. Online repository of patterns, techniques, examples, and playbooks kept up-to-date by the authors. Real world case studies to demonstrate responsible AI in practice. Chart the course to responsible AI excellence, from governance to design, with actionable insights and engineering prowess found in this defi nitive guide.
The age of nanotechnology is upon us. Engineering at the molecular level is no longer a computer-generated curiosity and is beginning to affect the lives of everyone. Molecules which can respond to their environment and the smart machines we can build with them are and will continue to be a vital part of this 21st-century revolution. Liming Dai presents the latest work on many newly-discovered intelligent macromolecular systems and reviews their uses in nano-devices. Intelligent Macromolecules for Smart Devices features: - An accessible assessment of the properties and materials chemistry of all the major classes of intelligent macromolecules from optoelectronic biomacromolecules to dendrimers, artificial opals and carbon nanotubes - In-depth analysis of various smart devices including a critique of the suitability of different molecules for building each type of device - A concise compilation of the practical applications of intelligent macromolecules including sensors and actuators, polymer batteries, carbon-nanotube supercapacitors, novel lasing species and photovoltaic cells As an exposition of cutting-edge research against a backdrop of comprehensive review, Intelligent Macromolecules for Smart Devices will be an essential addition to the bookshelf of academic and industrial researchers in nanotechnology. Graduate and senior undergraduate students looking to make their mark in this field of the future will also find it most instructive.
This book investigates how schools, enterprises and families in China have coped with the formal online education in the light of government policy throughout the COVID-19 epidemic outbreak, with special focus on the problems they have encountered and possible solutions. Using grounded theory, over 1000 posts retrieved from public online forums were analyzed under a 4*4 framework, referring to four special time nodes (proposal period, exploratory period, full deployed period, exiting period) and four major subjects (government, schools, enterprises, families). The book identifies four main issues faced by massive online education during the epidemic: platform selection in proposal period, teacher training in exploratory period, resource integration in full deployed period, and flexibility of returning to schools in exiting period. These findings enlighten us with a deeper understanding of the process of online learning in an educational emergency, helping to develop best countermeasures in similar situations, as well as to provide paths to follow for other countries. The book will appeal to teachers, researchers and school administrators of the online education and education emergency management, as well as those who are interested in Chinese education during the COVID-19 outbreak in general.
Dynamics of Materials: Experiments, Models and Applications addresses the basic laws of high velocity flow/deformation and dynamic failure of materials under dynamic loading. The book comprehensively covers different perspectives on volumetric law, including its macro-thermodynamic basis, solid physics basis, related dynamic experimental study, distortional law, including the rate-dependent macro-distortional law reflecting strain-rate effect, its micro-mechanism based on dislocation dynamics, and dynamic experimental research based on the stress wave theory. The final section covers dynamic failure in relation to dynamic damage evolution, including the unloading failure of a crack-free body, dynamics of cracks under high strain-rate, and more. - Covers models for applications, along with the fundamentals of the mechanisms behind the models - Tackles the difficult interdisciplinary nature of the subject, combining macroscopic continuum mechanics with thermodynamics and macro-mechanics expression with micro-physical mechanisms - Provides a review of the latest experimental methods for the equation of state for solids under high pressure and the distortional law under high strain-rates of materials
This book was originally pubished in 2000. China is the largest developing country in the world and is still heavily based on agriculture. Currently, about 70 per cent of China's total of more than one bilion people live in rural areas, and about half of the total national labour force is involved in agricultural activities. It is clear that agriculture is the foundation for the development of the Chinese national economy. Within agriculture, the grain economy is the most important sector: indeed it has been recognised as a treasure in managing the country by all past Chinese dynasties. Ensuring enough grain supply to meet the demands of such a huge population seems to be a long-term goal for the Chinese government and this book explores whether China will be able to produce enough grain to keep pace with its population increases.
Mixture Modelling for Medical and Health Sciences provides a direct connection between theoretical developments in mixture modelling and their applications in real world problems. The book describes the development of the most important concepts through comprehensive analyses of real and practical examples taken from real-life research problems in
Computational fluid dynamics (CFD) has been widely applied in a wide variety of industrial applications, including aeronautics, astronautics, energy, chemical, pharmaceuticals, power and petroleum.This unique compendium documents the recent developments in CFD based on kinetic theories, introducing flux reconstruction strategies of kinetic methods for the simulation of complex incompressible and compressible flows, namely the lattice Boltzmann and the gas kinetic flux solvers (LBFS or GKFS). LBFS and GKFS combine advantages of both Navier-Stokes (N-S) solvers and kinetic solvers.Detailed derivations, evaluations and applications of LBFS and GKFS, and their advantages over conventional flux reconstruction strategies are analyzed and discussed in the volume.The must-have reference text is useful for scholars, researchers, professionals and students who are keen in CFD methods and numerical simulations.
This two-volume work presents state-of-the-art mathematical theories and results on infinite-dimensional dynamical systems. Inertial manifolds, approximate inertial manifolds, discrete attractors and the dynamics of small dissipation are discussed in detail. The unique combination of mathematical rigor and physical background makes this work an essential reference for researchers and graduate students in applied mathematics and physics. The main emphasis in the first volume is on the mathematical analysis of attractors and inertial manifolds. This volume deals with the existence of global attractors, inertial manifolds and with the estimation of Hausdorff fractal dimension for some dissipative nonlinear evolution equations in modern physics. Known as well as many new results about the existence, regularity and properties of inertial manifolds and approximate inertial manifolds are also presented in the first volume. The second volume will be devoted to modern analytical tools and methods in infinite-dimensional dynamical systems. Contents Attractor and its dimension estimation Inertial manifold The approximate inertial manifold
This book gives an overview of the theoretical research on rogue waves and discusses solutions to rogue wave formation via the Darboux and bilinear transformations, algebro-geometric reduction, and inverse scattering and similarity transformations. Studies on nonlinear optics are included, making the book a comprehensive reference for researchers in applied mathematics, optical physics, geophysics, and ocean engineering. Contents The Research Process for Rogue Waves Construction of Rogue Wave Solution by the Generalized Darboux Transformation Construction of Rogue Wave Solution by Hirota Bilinear Method, Algebro-geometric Approach and Inverse Scattering Method The Rogue Wave Solution and Parameters Managing in Nonautonomous Physical Model
This work investigates the development of English as a Foreign Language (EFL) learners’ generic competence in reading, writing and translation within the particular Chinese classroom context. It provides a new perspective for the current teaching and research in reading, writing, translation within the EFL contexts and offers an insightful framework for pedagogical applications in language learning and teaching. Its findings will be extremely valuable not only in local situations, but also more generally in a wider regional and global context as well. The book employs a series of research tools, including pre-research and post-research questionnaires, pre-test and post-test of reading/writing/translation, multi-faceted writing portfolios (including reflection reports), textual analysis and in-depth interviews. It involves 209 participants from a primary university in Wuhan, among whom 171 are undergraduates and 38 are postgraduates. And it draws on the analysis of such varied multi-sourced data both qualitatively and quantitatively. Genre-based teaching is playing a critical role in initiating EFL learners into the discourse community of the target language. Developing EFL learners’ generic competence is viewed as the ultimate goal in the process of teaching and learning. This monograph effectively demonstrates that like genre-based English for Specific Purposes (ESP) pedagogies, it is also possible to take advantage of already acquired genre knowledge for use in EFL learning contexts. It offers an impressive view of the direction in which genre-based applications are likely to take in the coming years.
Visual attention is a relatively new area of study combining a number of disciplines: artificial neural networks, artificial intelligence, vision science and psychology. The aim is to build computational models similar to human vision in order to solve tough problems for many potential applications including object recognition, unmanned vehicle navigation, and image and video coding and processing. In this book, the authors provide an up to date and highly applied introduction to the topic of visual attention, aiding researchers in creating powerful computer vision systems. Areas covered include the significance of vision research, psychology and computer vision, existing computational visual attention models, and the authors' contributions on visual attention models, and applications in various image and video processing tasks. This book is geared for graduates students and researchers in neural networks, image processing, machine learning, computer vision, and other areas of biologically inspired model building and applications. The book can also be used by practicing engineers looking for techniques involving the application of image coding, video processing, machine vision and brain-like robots to real-world systems. Other students and researchers with interdisciplinary interests will also find this book appealing. Provides a key knowledge boost to developers of image processing applications Is unique in emphasizing the practical utility of attention mechanisms Includes a number of real-world examples that readers can implement in their own work: robot navigation and object selection image and video quality assessment image and video coding Provides codes for users to apply in practical attentional models and mechanisms
DevOps promises to accelerate the release of new software features and improve monitoring of systems in production, but its crucial implications for software architects and architecture are often ignored. In DevOps: A Software Architect's Perspective, three leading architects address these issues head-on. The authors review decisions software architects must make in order to achieve DevOps' goals and clarify how other DevOps participants are likely to impact the architect's work. They also provide the organizational, technical, and operational context needed to deploy DevOps more efficiently, and review DevOps' impact on each development phase. The authors also address cross-cutting concerns that link multiple functions, offering practical insights into compliance, performance, reliability, repeatability, and security. This guide demonstrates the authors' ideas in action with three real-world case studies: datacenter maintenance for business continuity, management of a continuous deployment pipeline, and migration to a microservice architecture. Comprehensive coverage includes • Why DevOps can require major changes in both system architecture and IT roles • How virtualization and the cloud can enable DevOps practices • Integrating operations and its service lifecycle into DevOps • Designing new systems to work well with DevOps practices • Overcoming cultural and communication differences between Dev and Ops • Integrating DevOps with agile methods and TDD • Handling failure detection, upgrade planning, and other key issues • Managing consistency issues arising from DevOps' independent deployment models • Integrating security controls, roles, and audits into DevOps • Preparing a business plan for DevOps adoption, rollout, and measurement
THE FIRST PRACTICAL GUIDE FOR OPERATIONALIZING RESPONSIBLE AI ̃FROM MUL TI°LEVEL GOVERNANCE MECHANISMS TO CONCRETE DESIGN PATTERNS AND SOFTWARE ENGINEERING TECHNIQUES. AI is solving real-world challenges and transforming industries. Yet, there are serious concerns about its ability to behave and make decisions in a responsible way. Operationalizing responsible AI is about providing concrete guidelines to a wide range of decisionmakers and technologists on how to govern, design, and build responsible AI systems. These include governance mechanisms at the industry, organizational, and team level; software engineering best practices; architecture styles and design patterns; system-level techniques connecting code with data and models; and trade-offs in design decisions. Responsible AI includes a set of practices that technologists (for example, technology-conversant decision-makers, software developers, and AI practitioners) can undertake to ensure the AI systems they develop or adopt are trustworthy throughout the entire lifecycle and can be trusted by those who use them. The book offers guidelines and best practices not just for the AI part of a system, but also for the much larger software infrastructure that typically wraps around the AI. First book of its kind to cover the topic of operationalizing responsible AI from the perspective of the entire software development life cycle. Concrete and actionable guidelines throughout the lifecycle of AI systems, including governance mechanisms, process best practices, design patterns, and system engineering techniques. Authors are leading experts in the areas of responsible technology, AI engineering, and software engineering. Reduce the risks of AI adoption, accelerate AI adoption in responsible ways, and translate ethical principles into products, consultancy, and policy impact to support the AI industry. Online repository of patterns, techniques, examples, and playbooks kept up-to-date by the authors. Real world case studies to demonstrate responsible AI in practice. Chart the course to responsible AI excellence, from governance to design, with actionable insights and engineering prowess found in this defi nitive guide.
The First Complete Guide to DevOps for Software Architects DevOps promises to accelerate the release of new software features and improve monitoring of systems in production, but its crucial implications for software architects and architecture are often ignored. In DevOps: A Software Architect’s Perspective, three leading architects address these issues head-on. The authors review decisions software architects must make in order to achieve DevOps’ goals and clarify how other DevOps participants are likely to impact the architect’s work. They also provide the organizational, technical, and operational context needed to deploy DevOps more efficiently, and review DevOps’ impact on each development phase. The authors address cross-cutting concerns that link multiple functions, offering practical insights into compliance, performance, reliability, repeatability, and security. This guide demonstrates the authors’ ideas in action with three real-world case studies: datacenter replication for business continuity, management of a continuous deployment pipeline, and migration to a microservice architecture. Comprehensive coverage includes • Why DevOps can require major changes in both system architecture and IT roles • How virtualization and the cloud can enable DevOps practices • Integrating operations and its service lifecycle into DevOps • Designing new systems to work well with DevOps practices • Integrating DevOps with agile methods and TDD • Handling failure detection, upgrade planning, and other key issues • Managing consistency issues arising from DevOps’ independent deployment models • Integrating security controls, roles, and audits into DevOps • Preparing a business plan for DevOps adoption, rollout, and measurement
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