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Human-Machine Shared Contexts
By 作者:William Lawless (Editor), Ranjeev Mittu (Editor), Donald Sofge (Editor)
pages 页数: 438 pages
Publisher Finelybook 出版社: Academic Press (23 Jun. 2020)
Language 语言: English
ISBN-10 书号:0128205431
ISBN-13 书号:9780128205433
Book Description to Finelybook sorting
Human-Machine Shared Contexts considers the foundations, metrics, and applications of human-machine systems. Editors and authors debate whether machines, humans, and systems should speak only to each other, only to humans, or to both and how. The book establishes the meaning and operation of “shared contexts” between humans and machines; it also explores how human-machine systems affect targeted audiences (researchers, machines, robots, users) and society, as well as future ecosystems composed of humans and machines.
This book explores how user interventions may improve the context for autonomous machines operating in unfamiliar environments or when experiencing unanticipated events; how autonomous machines can be taught to explain contexts By 作者:reasoning, inferences, or causality, and decisions to humans relying on intuition; and for mutual context, how these machines may interdependently affect human awareness, teams and society, and how these “machines” may be affected in turn. In short, can context be mutually constructed and shared between machines and humans? The editors are interested in whether shared context follows when machines begin to think, or, like humans, develop subjective states that allow them to monitor and report on their interpretations of reality, forcing scientists to rethink the general model of human social behavior. If dependence on machine learning continues or grows, the public will also be interested in what happens to context shared By 作者:users, teams of humans and machines, or society when these machines malfunction. As scientists and engineers “think through this change in human terms,” the ultimate goal is for AI to advance the performance of autonomous machines and teams of humans and machines for the betterment of society wherever these machines interact with humans or other machines.
This book will be essential reading for professional, industrial, and military computer scientists and engineers; machine learning (ML) and artificial intelligence (AI) scientists and engineers, especially those engaged in research on autonomy, computational context, and human-machine shared contexts; advanced robotics scientists and engineers; scientists working with or interested in data issues for autonomous systems such as with the use of scarce data for training and operations with and without user interventions; social psychologists, scientists and physical research scientists pursuing models of shared context; modelers of the internet of things (IOT); systems of systems scientists and engineers and economists; scientists and engineers working with agent-based models (ABMs); policy specialists concerned with the impact of AI and ML on society and civilization; network scientists and engineers; applied mathematicians (e.g., holon theory, information theory); computational linguists; and blockchain scientists and engineers.

Agile Game Development: Build, Play, Repeat, 2nd Edition
By 作者: Clinton Keith
Pub Date: 2020
ISBN: 9780136527817
Pages 页数: 576
Language 语言: English
Format: EPUB
Size: 10 Mb

Book Description to Finelybook sorting
In Agile Game Development , Clinton Keith offered game development team members the first complete blueprint for leveraging the power of Scrum and Agile methods to deliver games more efficiently, rapidly, and cost-effectively; create games that offer more entertainment value; and make life more fulfilling for every development team member. Now, reflecting his unsurpassed experience helping more than 150 game development studios succeed, Keith has thoroughly revamped his classic guide for today’s radically transformed industry. The only Certified Scrum Trainer to help build 20 AAA-level games, Keith is singularly well-placed to help game developers solve the problems they actually face. In this edition, he:

Addresses the modern challenges of mobile, free-to-play, and Massively Agile games
Adds a completely new section on large-scale Agile game development, and new chapters on managing the first release, forming and leading Agile teams, game pipelines, and more
Presents many new date stories about the experiences of actual game development teams, with actionable takeaways
Illuminates advanced Agile projects through new “Things to Try” sidebars
Covers Kanban and other Agile methodologies as well as Scrum
Around the world, thousands of professional game developers have already used Agile Game Development to dramatically improve their effectiveness — and enjoy their work more. This 2nd Edition offers today’s professionals even more value — no matter what types of games they’re developing, what development roles they play, or what environments they’re working in.
Contents
Part 1: The Problem and The Solution1. The Crisis Facing Game Development2. Agile and Lean
Part 2: Scrum and Kanban3. Scrum4. Sprints and Events5. Teams and Roles6. Kanban
Part 3: Agile Game Development7. User Stories8. Agile Planning9. Managing the First Release Finelybook 出版日期
Part 4: Agile Teamwork11. Agile Technology12. Agile Art and Audio13. Agile Design14. Agile QA and Production15. Team Formation16. Leadership
Part 5: Large and Live17. Scaled and Distributed Development with MAGE18. The Live Game Pipeline19. The Myths and Challenges of Agile20. Working with Stakeholders21. Agile Transitions22. Conclusion

Introduction to Fiber-Optic Communications
By 作者:Rongqing Hui
pages 页数: 660 pages
Publisher Finelybook 出版社: Academic Press (25 Jun. 2019)
Language 语言: English
ISBN-10 书号:0128053453
ISBN-13 书号:9780128053454
Book Description to Finelybook sorting
Introduction to Fiber-Optic Communications provides students with the most up-to-date, comprehensive coverage of modern optical fiber communications and applications, striking a fine balance between theory and practice that avoids excessive mathematics and derivations. Unlike other textbooks currently available, this book covers all of the important recent technologies and developments in the field, including electro-optic modulators, coherent optical systems, and silicon integrated photonic circuits. Filled with practical, relevant worked examples and exercise problems, the book presents complete coverage of the topics that optical and communications engineering students need to be successful.
From principles of optical and optoelectronic components, to optical transmission system design, and from conventional optical fiber links, to more useful optical communication systems with advanced modulation formats and high-speed DSP, this book covers the necessities on the topic, even including today’s important application areas of passive optical networks, datacenters and optical interconnections.

Symfony 5: The Fast Track
By 作者:Fabien Potencier (Author)
pages 页数: 308 pages
Publisher Finelybook 出版社: Symfony SAS (November 8, 2019)
Language 语言: English
ISBN-10 书号:2918390372
ISBN-13 书号:9782918390374
Book Description to Finelybook sorting
Is it possible to quickly build a modern web application and love the process? With Symfony 5, you can. This book – written By 作者:Symfony’s creator – lays out a pragmatic approach to developing web applications with Symfony 5: from scratch to production. Whether you are discovering Symfony for the first time or refreshing your knowledge, this practical guide provides the definitive introduction to modern Symfony applications.

Enterprise Networking, Security, and Automation Companion Guide (CCNAv7)
By 作者: Cisco Networking Academy
Pub Date: 2020
ISBN: 9780136634324
Pages 页数: 750
Language 语言: English
Format: EPUB
Size: 60 Mb
Book Description to Finelybook sorting
Enterprise Networking, Security, and Automation (CCNA v7) Companion Guide is designed as a portable desk reference to use anytime, anywhere to reinforce the material from the Enterprise Networking, Security, and Automation course and organize your time.
The book’s features help you focus on important concepts to succeed in this course:

Chapter Objectives – Review core concepts By 作者:answering the focus questions listed at the beginning of each chapter.
Key Terms – Refer to the lists of networking vocabulary introduced and highlighted in context in each chapter.
Glossary – Consult the comprehensive Glossary with more than 250 terms.
Summary of Activities and Labs – Maximize your study time with this complete list of all associated practice exercises at the end of each chapter.
Check Your Understanding – Evaluate your readiness with the end-of-chapter questions that match the style of questions you see in the online course quizzes. The answer key explains each answer.
How To – Look for this icon to study the steps you need to learn to perform certain tasks.
Interactive Activities – Reinforce your understanding of topics with dozens of exercises from the online course identified throughout the book with this icon.
Packet Tracer Activities – Explore and visualize networking concepts using Packet Tracer exercises interspersed throughout the chapters and provided in the accompanying Labs & Study Guide book.
Videos – Watch the videos embedded within the online course.
Hands-on Labs – Work through all the course labs and additional Class Activities that are included in the course and published in the separate Labs & Study Guide.
Part of the Cisco Networking Academy Series from Cisco Press, books in this series support and complement the Cisco Networking Academy curriculum.

Image Processing and Acquisition using Python, 2nd Edition
By 作者: Ravishankar Chityala
Pub Date: 2020
ISBN: 9780367198084
Pages 页数: 451
Language 语言: English
Format: PDF
Size: 70 Mb
Book Description to Finelybook sorting
Image Processing and Acquisition using Python provides readers with a sound foundation in both image acquisition and image processing―one of the first books to integrate these topics together. By improving readers’ knowledge of image acquisition techniques and corresponding image processing, the book will help them perform experiments more effectively and cost efficiently as well as analyze and measure more accurately. Long recognized as one of the easiest languages for non-programmers to learn, Python is used in a variety of practical examples.
A refresher for more experienced readers, the first part of the book presents an introduction to Python, Python modules, reading and writing images using Python, and an introduction to images. The second part discusses the basics of image processing, including pre/post processing using filters, segmentation, morphological operations, and measurements. The second part describes image acquisition using various modalities, such as x-ray, CT, MRI, light microscopy, and electron microscopy. These modalities encompass most of the common image acquisition methods currently used By 作者:researchers in academia and industry.
Features

Covers both the physical methods of obtaining images and the analytical processing methods required to understand the science behind the images.
Contains many examples, detailed derivations, and working Python examples of the techniques.
Offers practical tips on image acquisition and processing.
Includes numerous exercises to test the reader’s skills in Python programming and image processing, with solutions to selected problems, example programs, and images available on the book’s web page.
New to this edition

Machine learning has become an indispensable part of image processing and computer vision, so in this new edition two new chapters are included: one on neural networks and the other on convolutional neural networks.
A new chapter on affine transform and many new algorithms.
Updated Python code aligned to the latest version of modules.
Contents
I Introduction to Images and Computing using Python. 1. Introduction to Python. 2. Computing using Python Modules. 3. Image and its Properties. II Image Processing using Python. 5. Image Enhancement. 6. Affine transformation. 7. Fourier Transform. 8 Segmentation. 9 Morphological Operations. 10. Image Measurements. 11. Neural network. 12. Convolutional neural network. III Image Acquisition. 13. X-Ray and Computed Tomography. 14. Magnetic Resonance Imaging. 15. Light Microscopes. 16. Electron Microscopes. Appendices.

Essential C# 8.0 (7th Edition) (Addison-Wesley Microsoft Technology Series) 7th Edition
by Mark Michaelis (Author)
Series: Addison-Wesley Microsoft Technology Series
pages 页数: 1200 pages
Publisher Finelybook 出版社: Addison-Wesley Professional; 7 edition (October 25, 2020)
Language 语言: English
ISBN-10 书号:0135972264
ISBN-13 书号:9780135972267
Book Description to Finelybook sorting
Essential C# 8.0 is a well-organized, no-fluff guide to C# 8.0 for programmers at all levels of experience. Reflecting the most important C# features, it will help you write code that’s simple, powerful, robust, secure, and maintainable.
Author Mark Michaelis is a world-class C# expert: a long-time Microsoft MVP and Regional Director who also has served on Microsoft’s C# design review team. He presents a comprehensive tutorial and reference for the entire language, including expert coverage of key C# 8.0 enhancements. He illustrates key C# constructs with succinct examples, and presents best-practice coding guidelines.

By 作者: Noah Gift
Pub Date: 2020
ISBN: 9798616960641
Pages 页数: 177
Language 语言: English
Format: EPUB
Size: 16 Mb
Book Description to Finelybook sorting
>Getting started with testing can be hard, and this book aims make it all very easy By 作者:using examples and explaining the process in a straightforward way. Testing is a core principle of robust software implementations and should be a prime skill to master that can be applied to any project.

Python Command Line Tools: Design powerful apps with Click
By 作者: Noah Gift
Pub Date: 2020
ISBN: 9798649161619
Pages 页数: 117
Language 语言: English
Format: EPUB
Size: 10 Mb
Book Description to Finelybook sorting
Learn to the simplest and most powerful UI ever invented, the command-line. This book teaches you the skills to master creating Python command line tools using the Click framework.

Getting Started with Click
Understanding IPython
Testing with Click
Integrating Linux Commands with Click
Writing pure Bash or ZSH command-line tools
Using Click subcommands
Turbocharging Click with Numba High-Performance library
Integrating AWS Lambda and Click
Case Studies
War Stories

Deep Learning for Data Analytics: Foundations, Biomedical Applications, and Challenges Paperback – 14 Jun. 2020
by Himansu Das (Editor), Chittaranjan Pradhan (Editor), Nilanjan Dey (Editor)
pages 页数: 218 pages
Publisher Finelybook 出版社: Academic Press (14 Jun. 2020)
Language 语言: English
ISBN-10 书号:0128197641
ISBN-13 书号:9780128197646
Book Description to Finelybook sorting
Deep learning, a branch of Artificial Intelligence and machine learning, has led to new approaches to solving problems in a variety of domains including data science, data analytics and biomedical engineering. Deep Learning for Data Analytics: Foundations, Biomedical Applications and Challenges provides readers with a focused approach for the design and implementation of deep learning concepts using data analytics techniques in large scale environments. Deep learning algorithms are based on artificial neural network models to cascade multiple layers of nonlinear processing, which aids in feature extraction and learning in supervised and unsupervised ways, including classification and pattern analysis. Deep learning transforms data through a cascade of layers, helping systems analyze and process complex data sets. Deep learning algorithms extract high level complex data and process these complex sets to relatively simpler ideas formulated in the preceding level of the hierarchy. The authors of this book focus on suitable data analytics methods to solve complex real world problems such as medical image recognition, biomedical engineering, and object tracking using deep learning methodologies. The book provides a pragmatic direction for researchers who wish to analyze large volumes of data for business, engineering, and biomedical applications. Deep learning architectures including deep neural networks, recurrent neural networks, and deep belief networks can be used to help resolve problems in applications such as natural language processing, speech recognition, computer vision, bioinoformatics, audio recognition, drug design, and medical image analysis.

Presents the latest advances in Deep Learning for data analytics and biomedical engineering applications.
Discusses Deep Learning techniques as they are being applied in the real world of biomedical engineering and data science, including Deep Learning networks, deep feature learning, deep learning toolboxes, performance evaluation, Deep Learning optimization, deep auto-encoders, and deep neural networks
Provides readers with an introduction to Deep Learning, along with coverage of deep belief networks, convolutional neural networks, Restricted Boltzmann Machines, data analytics basics, enterprise data science, predictive analysis, optimization for Deep Learning, and feature selection using Deep Learning