Software Engineering Books

Book SynopsisAs Web-based systems and e-commerce carry businesses into the 21st century, databases are becoming workhorses that shoulder each and every online transaction. For organizations to have effective 24/7 Web operations, they need powerhouse databases that deliver at peak performance-all the time. High Performance Web Databases: Design, Development, and Deployment arms you with every essential technique from design and modeling to advanced topics such as data conversion, performance tuning, Web access and interfacing legacy systems, and securityTable of ContentsDatabase Planning and Getting Started. Information Gathering and Analysis. Managing Business Rules. Performance Modeling Methods. Performance Design and Development. Database Integrity and Quality. Distributed Databases, Portability, and Interoperability. Database Integration with the Internet and the Web. Data Migration, Conversion, and Legacy Applications. Performance Tuning. Data Administration and Operations. Data Base Security.

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Book SynopsisIn Offshore Software Development: Making It Work, hands-on managers of Offshore solutions help you answer these questions:What is Offshore and why is it an IT imperative? What do you need to do to successfully evaluate an Offshore solution? How do you avoid common pitfalls? How do you confront security and geopolitical risk? How do you handle issues related to displaced workers? The author applies her considerable experience in the analysis of such Offshore issues as the financial growth of the Offshore industry, keys to success in initiating a program, choosing and managing vendors, risk mitigation, and employee impacts. A detailed program checklist outlines the steps for successful Offshore execution, providing real-world exposure and guidance to a movement that has become a fixture in the IT realm. About the AuthorTandy Gold is a 20-year veteran of the technology industry who is focused on entrepreneuTable of ContentsTHE OFFSHORE IMPERATIVE. Crunching the offshore numbers: What the financials portend. Getting started in offshore. Choosing an offshore vendor: A look at the offshore maturity model. A HANDS-ON OFFSHORE PROGRAM MANAGEMENT TOOLKIT. Choosing locations for offshore: Country pros and cons. The offshore program checklist: What's really different? THE OFFSHORE PROGRAM CHALLENGE. Managing employee impact: Villain or savior? Managing risk through an offshore network security architecture. Putting it all together: Top 10 Do's and Don'ts of Offshore.

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Book SynopsisPatterns, Models, and Application Development, a new book from two experts in C++, integrates a methodology for program development and covers three main categories: object modeling as a program design tool, design patterns and their modeling in C++ language structures, and a discussion of the implementation of PC hardware-related features. It addresses the gap between the ability to code and the ability to program.Table of ContentsIntroduction. Fundamentals of Systems Engineering. System Description and Specification. Foundations of Object-Oriented Systems. Object-Oriented Analysis. Object-Oriented Design. Indirection. C++ Object-Oriented Constructs. Reusability. Static Inheritance Constructs. Dynamic Binding Constructs. Object Composition Constructs. Class Patterns and Templates. Multifile Programs. Bibliography. Index. NTI/Sales Copy

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Book SynopsisThe pervasiveness of software in business makes it crucial that software engineers and developers understand how software development impacts an entire organization. Strategic Software Engineering: An Interdisciplinary Approach presents software engineering as a strategic, business-oriented, interdisciplinary endeavor, rather than simply a technical process, as it has been described in previous publications.The book addresses technical, scientific, and management aspects of software development in a way that is accessible to a wide audience. It provides a detailed, critical review of software development models and processes, followed with a strategic assessment of how process models evolved over time and how to improve them. The authors then focus on the relation between problem-solving techniques and strategies for effectively confronting real-world business problems. They also analyze the impact of interdisciplinary factors on software development, including the role of peopTable of ContentsThe process and its models. Strategies for solving software problems. Interdisciplinary factors in software development.

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Book SynopsisThis book is designed to address the randomness of the literature on software documentation. As anyone interested in software documentation is aware, the field is highly synthetic; information about software documentation may be found in engineering, computer science training, technical communication, management, education and so on. Perspectives on Software Documentation contains a variety of perspectives, all tied together by the shared need to make software products more usable.Table of ContentsIntroduction: Research Sources in Software Documentation Thomas T. BarkerPART 1: INQUIRIESEducation and Research Prologue for Teaching Software Documentation Henrietta Nickels Shirk Style and Software Documentation: A Central Concern Cynthia L. SelfeThe Influence of Cognitive Science A Schematic Approach to User Knowledge and Software Documentation Production Jay Lieberman Cognitive Writing: A New Approach to Organizing Technical Material Paula BellIssues of Design Software Documentation and Human-Factors Design Joe Chew The Hidden Effects of Computer Engineering on User Documentation Andrew Oram Problems of Form in Software Documentation Nancy E. CohenPART 2: INNOVATIONS Managing Software Documentation Building and Managing a Documentation Project Team D. Michael Willoughby Side-by-Side: A Model for Simultaneous Documentation and System Development Doann Houghton-Alico Automated Documentation: A Complete Cycle Helen D. KleinImproving the Quality of Software Documentation Process Implementation—The Key to Quality Documentation Scott E. Hubbard Information Product Testing: An Integral Part of Information Development Roger A. Grice and Lenore S. RidgwaySoftware Documentation of the Future—Online Writing and Editing Online Information Marlene C. Semple Online Reference System Design and Development Bruno Petrauskas Index Contributors

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Book SynopsisAims to helps you become a better manager. This book talks about scheduling and managing resources, and helping team members grow and prosper. It provides tips for: delegating; using feedback and goal-setting; developing influence; handling one-on-one meetings; coaching and mentoring; deciding what work to do and what not to do; and more.Table of ContentsForeword Preface Introduction Week 1: Learning about the People and the Work Monday Morning Managing One Person at a Time Tuesday Morning Keep a Finger on the Pulse Wednesday Afternoon Friday Afternoon Gather Data about Current Work Now Try This Bibliography for Chapter Week 2: Bringing Order to the Chaos Tuesday Afternoon Create the Project Portfolio Thursday . Fast-Forward Matching the Roles with the People Plan to Integrate New Team Members Friday Morning, Sam's Second Week on the Job Managing the Project Portfolio Now Try This Bibliography for Chapter Week 3: Building the Team Monday Morning Thursday Morning Creating Shared Goals Monday Morning Provide Timely Feedback When Feedback Doesn't Correct the Situation Now Try This Bibliography for Chapter Week 4: Managing Day by Day Monday Create Individual Goals for Each Person Monday Midmorning Coaching for Success Later That Same Day Learning to Influence Monday Afternoon Capitalizing on Feedback Opportunities Now Try This Bibliography for Chapter Week 5: Discovering Lurking Problems Recognize Messy Problems Friday Morning Solving Problems as a Management Team Now Try This Bibliography for Chapter Week 6: Building Capability Monday Morning Learning to Delegate Wednesday End of Day Notice and Appreciate Changes and Contributions Back to Monday Manage Yourself Still Monday Develop the People in Your Group Every Week Now Try This Bibliography for Chapter Week 7: Dealing with Corporate Realities Tuesday Late Morning Manage Your Boss, Stand Up for Your Team Tuesday Just Before Noon After Lunch Thursday Leading Your Team through a Change in Priorities Now Try This Epilogue What Management Is Now Try This Bibliography for Chapter Techniques for Practicing Great Management 1. Guidelines for Effective Coaching 2. Setup for Successful Delegation 3. Facilitation Essentials for Managers 4. Guide to Giving Effective Feedback 5. Welcoming New Hires 6. Setting SMART Goals 7. What Goes on Inside our Heads 8. Manage by Walking Around & Listening 9. Run Effective Meetings 10. Making One-on-Ones Work 11. Preparing for Influence 12. Solving Problems: Create New Situations 13. Project Portfolio Planning Tips Bibliography for Chapter Bibliography

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Book SynopsisThis textbook seeks to foster a deep understanding of the field by introducing the industry integrated circuit (IC) design flow and offering tape-out or pseudo tape-out projects for hands-on practice, facilitating project-based learning (PBL) experiences.Integrated Circuit Design: IC Design Flow and Project-Based Learning aims to equip readers for entry-level roles as IC designers in the industry and as hardware design researchers in academia. The book commences with an overview of the industry IC design flow, with a primary focus on register-transfer level (RTL) design, the automation of simulation and verification, and system-on-chip (SoC) integration. To build connections between RTL design and physical hardware, FPGA (field-programmable gate array) synthesis and implementation is utilized to illustrate the hardware description and performance evaluation. The second objective of this book is to provide readers with practical, hands-on experience through tape-out or

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Book SynopsisFoundations of Reinforcement Learning with Applications in Finance aims to demystify Reinforcement Learning, and to make it a practically useful tool for those studying and working in applied areas especially finance.Reinforcement Learning is emerging as a powerful technique for solving a variety of complex problems across industries that involve Sequential Optimal Decisioning under Uncertainty. Its penetration in high-profile problems like self-driving cars, robotics, and strategy games points to a future where Reinforcement Learning algorithms will have decisioning abilities far superior to humans. But when it comes getting educated in this area, there seems to be a reluctance to jump right in, because Reinforcement Learning appears to have acquired a reputation for being mysterious and technically challenging.This book strives to impart a lucid and insightful understanding of the topic by emphasizing the foundational mathematics and implemTrade Review“This book is a nice addition to the literature on Reinforcement Learning (RL), offering comprehensive coverage of both foundational RL techniques and their applications in the field of finance. It has the potential to be a foundational reference for both practitioners and researchers in finance. The book delves into essential RL concepts such as Markov Decision Processes (MDPs), Dynamic Programming, Policy Optimization, Actor-Critic models, Multi-armed Bandits, and Regret Bounds.Despite its finance-oriented approach, individuals without an extensive financial background but possessing a decent machine learning (ML) background will find it easy to read this book.By encompassing all of the major asset classes including equities, fixed income and derivatives, the book caters to a broad range of readers, enabling them to apply RL techniques to diverse financial scenarios. In summary, this book is an outstanding resource that combines RL fundamentals with practical applications in finance.” – Natesh Pillai, Department of Statistics, Harvard University, Unites States of AmericaTable of ContentsSection I. Processes and Planning Algorithms. 1. Markov Processes. 2. Markov Decision Processes. 3. Dynamic Programming Algorithms. 4. Function Approximation and Approximate Dynamic Programming. Section II. Modeling Financial Applications. 5. Utility Theory. 6. Dynamic Asset-Allocation and Consumption. 7. Derivatives Pricing and Hedging. 8. Order-Book Trading Algorithms. Section III. Reinforcement Learning Algorithms. 9. Monte-Carlo and Temporal-Difference for Prediction. 10. Monte-Carlo and Temporal-Difference for Control. 11. Batch RL, Experience-Replay, DQN, LSPI, Gradient TD. 12. Policy Gradient Algorithms. Section IV. Finishing Touches. 13. Multi-Armed Bandits: Exploration versus Exploitation. 14. Blending Learning and Planning. 15. Summary and Real-World Considerations. Appendices.

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Book SynopsisHealth information technology (HIT) is a critical component of the modern healthcare system. Yet to be effective and safely implemented in healthcare organizations and physicians and patients' lives, it must be usable and useful. User Experience (UX) research is required throughout the full system design lifecycle of HIT products, which involve a user-centered and human- centered approach. This book discusses UX research frameworks, study designs, methods, data-analysis techniques, and a variety of data collection instruments and tools that can be used to conduct UX research in the healthcare space, all of which involve HIT and digital health. This book is for academics and scholars to be used to design studies for graduate dissertation work, in independent research, or as a textbook for UX/usability courses in health informatics or related health information and communication courses. This book is also useful for UX practitioners because it provides guidance on how to design a userTable of Contents1. Introduction. 2. Definitions: Usability, UX, and UCD. 3. Audience Analysis and Usability Determinants. 4. Quantitative and Qualitative Methods. 5. Mixed-Methods Study Design and Rigor. 6. Content Analysis. 7. Discovery UX Research Studies. 8. Usability Inspection Methods. 9. Quantitative Usability Testing Methods and Metrics. 10. Post-Study Surveys and Retrospective Questionnaires. 11. Conclusion. References. Appendix A. Sample Informed Consent Form. Appendix B. System Usability Scale. Appendix C. Quick Reference Sheet for Study Sample Sizes for Common UX Research.

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Book SynopsisAs more and more engineering departments and companies choose to use Python, this book provides an essential introduction to this open-source, free-to-use language. Expressly designed to support first-year engineering students, this book covers engineering and scientific calculations, Python basics, and structured programming.Based on extensive teaching experience, the text uses practical problem solving as a vehicle to teach Python as a programming language. By learning computing fundamentals in an engaging and hands-on manner, it enables the reader to apply engineering and scientific methods with Python, focusing this general language to the needs of engineers and the problems they are required to solve on a daily basis. Rather than inundating students with complex terminology, this book is designed with a leveling approach in mind, enabling students at all levels to gain experience and understanding of Python. It covers such topics as structured programming, graphics, matrTable of ContentsChapter 1 Engineering and Scientific CalculationsChapter 2 Computer-Based CalculationsChapter 3 Python BasicsChapter 4 Structured Programming with PythonChapter 5 Graphics—MatplotlibChapter 6 Array and Matrix OperationsChapter 7 Solving Single Algebraic EquationsChapter 8 Solving Sets of Algebraic EquationsChapter 9 Solving Differential EquationsChapter 10 Working with Data

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Book SynopsisRevised for a new second edition, Intermediate C Programming provides a stepping-stone for intermediate-level students to go from writing short programs to writing real programs well. It shows students how to identify and eliminate bugs, write clean code, share code with others, and use standard Linux-based tools, such as ddd and valgrind.This second edition provides expanded coverage of these topics with new material focused on software engineering, including version control and unit testing. The text enhances their programming skills by explaining programming concepts and comparing common mistakes with correct programs. It also discusses how to use debuggers and the strategies for debugging as well as studies the connection between programming and discrete mathematics.Including additional student and instructor resources available online, this book is particularly appealing as a classroom resource.Table of ContentsList of FiguresList of TablesForeword for the First EditionRecommendations for the First EditionPrefaceAcknowledgementsSource CodeAuthor and ArtistI Storage: Memory and File1. Program Execution2. Stack Memory3. Prevent, Detect and Remove Bugs4. Pointers5. Writing and Testing Programs6. Strings7. Heap Memory8. Programming Problems Using Heap Memory9. Reading and Writing Files10. Programming Problems Using File11. Array Index, Security and Trends12. Version ControlII Recursion13. Concept14. Recursive C Functions15. Integer Partition16. Programming Problems Using RecursionIII Structure17. Programmer-Defined Data Types18. Programming Problems Using Structure19. Linked Lists20. Programming Problems Using Linked List21. Binary Search Tree22. Parallel Programming Using Threads23. Unit TestIV Applications24. Find the Exit of a Maze25. Sudoku26. Image Processing27. Huffman CompressionIndexEpilogue: The Computer Engineer as Tool-User

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Book SynopsisThis book provides a detailed description of machine learning algorithms in data analytics, data science life cycle, Python for machine learning, linear regression, logistic regression, and so forth. It addresses the concepts of machine learning in a practical sense providing complete code and implementation for real-world examples in electrical, oil and gas, e-commerce, and hi-tech industries. The focus is on Python programming for machine learning and patterns involved in decision science for handling data. Features: Explains the basic concepts of Python and its role in machine learning. Provides comprehensive coverage of feature engineering including real-time case studies. Perceives the structural patterns with reference to data science and statistics and analytics. Includes machine learning-based structured exercises. Appreciates different algorithmic concepts of machine learningTable of Contents1. Introduction 2. Overview of Python for Machine Learning 3. Data Analytics Life Cycle for Machine Learning 4. Unsupervised Learning 5. Supervised Learning: Regression 6. Supervised Learning: Classification 7. Feature Engineering 8. Reinforcement Learning 9. Case Studies for Decision Sciences Using Python

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Book SynopsisCarter's new book, DesignedUp, is a useful guide for the modern design practitioner who sits at the intersection of the IT consultancy and agency world someone who chooses to plot their own course across many companies' diverse set of interests instead of being loyal to just one. In doing so, they have selected an exciting path that will bring them many heralded victories and challenging pitfalls, which Carter has aptly navigated over her impressive career. If you have been in the field for a while, I think you will find Carter's book to be a refreshing antidote to any career doldrums you may have. Dr. John Maeda, VP of Design and Artificial Intelligence, MicrosoftDesigners have long asked for a seat at the table.' What Emma Carter has done is given them the roadmap to not only get that seat, but to redesign the table to fit what tech-driven organisations need to succeed today. Jeff Gotthelf, Author Lean UX and Sense & RespondAre you strTable of Contents1. DesignedUp traits 2. Design agency life vs large consultancy life 3. Design leader in an agile consultancy world4. Proving the power and value of design 5. Don’t become the worst version of yourself 6. Up your influence 7. One final note

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Book SynopsisThe Lean Approach to Digital Transformation: From Customer to Code and From Code to Customer is organized into three parts that expose and develop the three capabilities that are essential for a successful digital transformation: 1. Understanding how to co-create digital services with users, whether they are customers or future customers. This ability combines observation, dialogue, and iterative experimentation. The approach proposed in this book is based on the Lean Startup approach, according to an extended vision that combines Design Thinking and Growth Hacking. Companies must become truly customer-centric, from observation and listening to co-development. The revolution of the digital age of the 21st century is that customer orientation is more imperative -- the era of abundance, usages rate of change, complexity of experiences, and shift of power towards communities -- are easier, using digital tools and digital communities. 2. DevelopiTable of ContentsPart 1: Digital transformation: Customer orientation and homeostasis Chapter 1 Why a digital transformation? Chapter 2 Homeostasis: continuous adaptation to change Chapter 3 Lean Startup: Lean principles applied to co-creation Part II: Exponential information systems Chapter 4 The Information System as a foundation for digital transformation Chapter 5 Artificial intelligence and machine learning Chapter 6 Governance, architecture and situational potential Part III: Software platforms and service factories Chapter 7 DevOps and software factories Chapter 8 Putting platforms at the service of digital transformation Conclusion

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Book SynopsisPython for Scientific Computing andArtificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI).This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling.Features: No prior experience of programming is required Online GitHub repository available with codes for readers to practice Table of ContentsSection I. An Introduction to Python. 1. The IDLE Integrated Development Learning Environment. 2. Anaconda, Spyder and the Libraries NumPy, Matplotlib and SymPy. 3. Jupyter Notebooks and Google Colab. 4. Python for AS-Level (High School) Mathematics. 5. Python for A-Level (High School) Mathematics. Section II. Python for Scientific Computing. 6. Biology. 7. Chemistry. 8. Data Science. 9. Economics. 10. Engineering. 11. Fractals and Multifractals. 12. Image Processing. 13. Numerical Methods for Ordinary and Partial Differential Equations. 14. Physics. 15. Statistics. Section III. Artificial Intelligence. 16. Brain Inspired Computing. 17. Neural Networks and Neurodynamics. 18. TensorFlow and Keras. 19. Recurrent Neural Networks. 20. Convolutional Neural Networks, TensorBoard, and Further Reading. 21. Answers and Hints to Exercises.

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Book SynopsisTelepresence: Actual and Virtual explores the history of telepresence from the 1948 developments of masterslave manipulation, through to current telepresence technology used in space, undersea, surgery and telemedicine, operations in nuclear and other hazardous environments, policing and surveillance, agriculture, construction, mining, warehousing, education, amusement, social media, and other contexts. It also describes the various operator hand and body controls and the corresponding telerobotic actuation of robotic hands, arms, and locomotion. This book reviews the sensing and control technology, its history and likely future, and discusses the many research and policy issues that are raised. The book also takes up key questions relating to social and ethical issues, given that a person's mechanical reach is becoming unlimited, enabling one to perform mischievous or harmful acts without identification, and what that portends for future developments in telepresence, includiTable of Contents1. EARLY HISTORY OF ROBOTIC TELEPRESENCE AND VIRTUAL REALITY. 2. ELEMENTS OF THE TECHNOLOGY. 3. WHAT IS TELEPRESENCE? WHAT IS REALITY?. 4. APPLICATIONS. 5. CHALLENGES FOR ROBOTIC TELEPRESENCE AND VIRTUAL REALITY. APPENDIX 1. RESPONSES TO POLLING. APPENDIX 2. BIBLIOGRAPHY.

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Book SynopsisAgile Software Development is an introduction to agile software development methods. Agile methods try to diminish complexity, increase transparency, and reach a deployable product in a shorter time frame. Agile methods use an iterative and incremental approach to minimize risks and to avoid maldevelopment. The book gives a short introduction to agile methods and agile software development principles. It serves as a study book and as a reference manual. Based on the official Scrum Guide, the book also covers other topics such as best practices for agile software development and agile testing. It targets practitioners who want to start with agile software development, as well as developers or project managers who already use agile methodologies. The book can be read from the beginning, but each chapter has been written in a way so it can be read individually.Table of Contents1. Introduction 2. Classical Model 3. Agile Methods 4. Scrum 5. Best Practices for the Dev Team 6. Testing 7. Appendix

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Book SynopsisThis book is one of its own kind. It is not an encyclopedia or a hands-on tutorial that traps readers in the tutorial hell. It is a distillation of just one common Python user's learning experience. The experience is packaged with exceptional teaching techniques, careful dependence unraveling and, most importantly, passion.Learning Advanced Python by Studying Open Source Projects helps readers overcome the difficulty in their day-to-day tasks and seek insights from solutions in famous open source projects. Different from a technical manual, this book mixes the technical knowledge, real-world applications and more theoretical content, providing readers with a practical and engaging approach to learning Python.Throughout this book, readers will learn how to write Python code that is efficient, readable and maintainable, covering key topics such as data structures, algorithms, object-oriented programming and more. The author's passion for Python shines through in tTable of ContentsIntroductionChapter 1 ◾ The Data Model of PythonChapter 2 ◾ Selected Topics of Python ClassesChapter 3 ◾ Concurrency in PythonChapter 4 ◾ Asynchronous Programming in PythonChapter 5 ◾ Power Up Your Python FunctionsChapter 6 ◾ Selected OOP Design Best PracticesChapter 7 ◾ Testing in a Pistachio Shell

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Book SynopsisDigital Image Processing with C++: Implementing Reference Algorithms with the CImg Library presents the theory of digital image processing and implementations of algorithms using a dedicated library. Processing a digital image means transforming its content (denoising, stylizing, etc.), or extracting information to solve a given problem (object recognition, measurement, motion estimation, etc.). This book presents the mathematical theories underlying digital image processing, as well as their practical implementation through examples of algorithms implemented in the C++ language using the free and easy-to-use CImg library.Chapters cover the field of digital image processing in a broad way and propose practical and functional implementations of each method theoretically described. The main topics covered include filtering in spatial and frequency domains, mathematical morphology, feature extraction and applications to segmentation, motion estimation, multispecTable of ContentsI INTRODUCTION TO Clmg1. Introduction. 2. Getting Started With the CImg Library. 2.1 Objective: subdivide an image into blocks. 2.2 Setup and first program. 2.3 Computing the variations. 2.4 Computing the block decomposition. 2.5 Rendering of the decomposition. 2.6 Interactive visualization. 2.7 Final source code II IMAGE PROCESSING USING CImg3. Point Processing Transformations. 3.1 Image operations. 3.2 Histogram operations. 4. Mathematical Morphology. 4.1 Binary images. 4.2 Gray-level images. 4.3 Some applications. 5. Filtering. 5.1 Spatial filtering. 5.2 Recursive filtering. 5.3 Frequency filtering. 5.4 Diffusion filtering. 6. Feature Extraction. 6.1 Points of interest. 6.2 Hough transform. 6.3 Texture features. 7. Segmentation. 7.1 Edge-based approaches. 7.2 Region-based approaches. 8. Motion Estimation. 8.1 Optical flow: dense motion estimation. 8.2 Sparse estimation. 9. Multispectral Approaches. 9.1 Dimension reduction. 9.2 Color imaging. 10. 3D Visualisation. 10.1 Structuring of 3D mesh objects. 10.2 3D plot of a function z = f (x;y). 10.3 Creating complex 3D objects. 10.4 Visualization of a cardiac segmentation in MRI. 11. And So Many Other Things. 11.1 Compression by transform (JPEG). 11.2 Tomographic reconstruction. 11.3 Stereovision. 11.4 Interactive deformation using RBF. List of CImg Codes.References.Index.

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Book SynopsisA bestseller in its French edition, this book is original in its construction and its success in the French market demonstrates its appeal. It is based on three principles: (1) An organization of the chapters by families of algorithms: exhaustive search, divide and conquer, etc. On the contrary, there is no chapter devoted only to a systematic exposure of, say, algorithms on strings. Some of these will be found in different chapters. (2) For each family of algorithms, an introduction is given to the mathematical principles and the issues of a rigorous design, with one or two pedagogical examples. (3) For the most part, the book details 150 problems, spanning seven families of algorithms. For each problem, a precise and progressive statement is given. More importantly, a complete solution is detailed, with respect to the design principles that have been presented; often, some classical errors are pointed out. Roughly speaking, two-thirds of the book is devoted to the detailed rational cTable of ContentsTable of ContentsPreface Mathematics and Computer Science: Some Useful Notions Complexity of an Algorithm Specifications, Invariants, Iteration Reduce and Conquer, Recursion Generate and Test Branch and Bound Greedy Algorithms Divide and Conquer Dynamic Programming NotationsList of ProblemsBibliographyIndex

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Book SynopsisThe book comprehensively covers a wide range of evolutionary computer vision methods and applications, feature selection and extraction for training and classification, and metaheuristic algorithms in image processing. It further discusses optimized image segmentation, its analysis, pattern recognition, and object detection.Features: Discusses machine learning-based analytics such as GAN networks, autoencoders, computational imaging, and quantum computing Covers deep learning algorithms in computer vision Showcases novel solutions such as multi-resolution analysis in imaging processing, and metaheuristic algorithms for tackling challenges associated with image processing Highlight optimization problems such as image segmentation and minimized feature design vector Presents platform and simulation tools for image processing and segmentation The book aims to get the readers familiar with the fundamentals ofTable of ContentsChapter 1 A Review Approach on Deep Learning Algorithms in Computer VisionChapter 2 Object Extraction from Real Time Color Images Using Edge Based ApproachChapter 3 Deep Learning Techniques for Image Captioning Chapter 4 Deep Learning Based Object Detection for Computer Vision Tasks: A Survey of Methods & Applications Chapter 5 Deep Learning Algorithms for Computer Vision: A Deep Insight into Principles and Applications Chapter 6Handwritten Equation Solver Using Convolutional Neural Network Chapter 7Agriware: Crop Suggester System by Estimating the Soil Nutrient Indicators Chapter 8A Machine Learning Based Expeditious Covid-19 Prediction Model Through Clinical Blood Investigations Chapter 9Comparison of Image Based and Audio Based Techniques for Bird-Species Identification Chapter 10Detection of Ichthyosis Vulgaris Using SVM Chapter 11Chest X-Ray Diagnosis and Report Generation: Deep Learning Approach Chapter 12Deep Learning Based Automatic Image Caption Generation for Visually Impaired People Chapter 13Empirical Analysis of Machine Learning Techniques Under Class Imbalance and Incomplete DatasetsChapter 14 Gabor Filter As Feature Extractor in Anomaly Detection from Radiology Images Chapter 15Discriminative Features Selection from Zernike Moments for Shape Based Image Retrieval SystemChapter 16Corrected Components of Zernike Moments for Improved Content Based Image Retrieval: A Comprehensive StudyChapter 17Translate And Recreate Text in An Image Chapter 18Multi-Label Indian Scene Text Language Identification: Benchmark Dataset and Deep Ensemble BaselineChapter 19AI Based Wearables for Healthcare Applications: A Survey of Smart Watches Chapter 20Nature Inspired Computing for Optimization Chapter 21Automated Smart Billing Cart for Fruits

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Book SynopsisComputer Arithmetic in Practice: Exercises and Programming is a simple, brief introductory volume for undergraduate and graduate students at university courses interested in understanding the foundation of computers. It is focused on numeric data formats and capabilities of computers to perform basic arithmetic operations. It discusses mainly such topics as: Basic concepts of computer architecture Assembly language programming skills Data formats used to express integer and real numbers Algorithms of basic arithmetic operations Short overview of nonlinear functions evaluation Discussion on limited number representation and computer arithmetic Exercises and programming tasks This book provides an accessible overview of common data formats used to write numbers in programming languages and how the computer performs four basic arithmetic operations from the point of view of the processor instruction set. ThTable of ContentsChapter 1: Basic concepts of computer architecture. Chapter 2: Numbers in fixed-point format. Chapter 3: Basic arithmetic on fixed-point numbers. Chapter 4: Numbers in floating-point format. Chapter 5: Basic arithmetic operations on floating-point numbers. Chapter 6: Limited quality of arithmetic operations. Appendices. Index. References.

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Book SynopsisYou hold in your hands a comprehensive guide to creating a flourishing software development practice - one that makes a powerful impact with the software it builds. This guide describes the unique aspects of creating software-based products. It also lays out the clear practical guidance thatâs necessary to construct and evolve a modern practice. This includes hiring, structuring teams properly, writing good code, leveraging test driven development, designing architecture, automating development processes with DevOps techniques, and - importantly - leading teams through the disruptive change that each of these can represent. Further, the first principles upon which these practices rest will be elaborated so that the reader can readily adapt the already practical techniques to the broadest possible set of real-world situations.

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Book SynopsisElements of Digital Transformation is a practitioner's guide to the digital transformation process. It is also a guide for managers in today's organizations that are accelerating digital transformation to modernize core technology capabilities and processes. The book discusses such key components of digital transformation as processes, principles and proven methods. It also covers such novel concepts in digital transformation as the first-time right framework, incident management transformation, digital factory, cloud migration, API-first approach and legacy modernization. Other highlights of the book include: A cloud migration framework along with a cloud migration methodology, rollout strategy and migration principles Principles and approaches for legacy modernization and process modernization Smart ticket management, smart problem management, proactive maintenance and ticket-avoidance architecture The novel digital factory approTable of ContentsPART I DIGITAL TRANSFORMATION INTRODUCTION 1. An Introduction to Digital Transformation 2. Digital Transformation Framework PART II MIGRATION AND MODERNIZATION 3. Legacy Modernization 4. Cloud Migration PART III DIGITAL TRANSFORMATION OF TECHNOLOGY 5. Services Transformation 6. Digital Factory for Digital Transformation 7. First Time Right Methodology in Digital Transformations 8. Experience Transformation 9. Transforming the Platform Performance 10. AI and Digital Transformation. PART IV DIGITAL TRANSFORMATION OF PROCESS 11. Agile Delivery in Digital Transformation 12. Digital Transformation of Incident Management Process PART V DIGITAL TRANSFORMATION OF OPERATIONS 13. Digital Transformation Operations 14. Automation through DevSecOps PART VI DIGITAL TRANSFORMATION CASE STUDIES 15. Digital Transformation Case Studies 16. Digital Transformation of Intranet Platforms

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Book SynopsisThis book introduces embedded software engineering and management methods, proposing the relevant testing theory and techniques that promise the final realization of automated testing of embedded systems.The quality and reliability of embedded systems have become a great concern, faced with the rising demands for the complexity and scale of system hardware and software. The authors propose and expound on the testing theory and techniques of embedded software systems and relevant environment construction technologies, providing effective solutions for the automated testing of embedded systems. Through analyzing typical testing examples of the complex embedded software systems, the authors verify the effectiveness of the theories, technologies and methods proposed in the book.In combining the fundamental theory and technology and practical solutions, this book will appeal to researchers and students studying computer science, software engineering, and embedded systems, aTable of Contents1. Introduction 2. Embedded System and Software 3. Embedded Software Engineering and Quality Characteristics 4. Embedded Software System Testing Techniques Based on Formal Methods 5. Real-time Embedded Software Automation Test Description Technology 6. Testing Technology of Intelligent Terminal Application Software System 7. Real-time Embedded Software System Testing Environment Construction Technology 8. Case Study of Real-time Embedded Software System Testing

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Book SynopsisUX research, the key to comprehending users'' behaviors, motivations, and preferences for developing delightful experiences, thrives on effective teamwork and collaboration. This comprehensive guide brings together the expertise and insights from seasoned researchers, cross-functional partners, and product leaders in order to transform how you collaborate and unlock the true potential of UX research.Key FeaturesIncludes a comprehensive selection of ready-to-use templatesIncorporates insights and advice from cross-functional stakeholdersOffers a wide range of strategies tailored to various expertise levels, catering to both novice and advanced practitionersPresents universally applicable methodologies and insights, equipping a diverse range of researchers, including consultants, vendors, and in-house professionalsFroTable of Contents1. Introduction, 2. Who Are (Your) Cross-Functional Partners and Why Is Their Buy-In Important?, 3. Mistakes That UX Researchers Make With Cross-Functional Partnerships, 4. Simple Strategies for Effective Cross-Functional Collaboration, 5. Advanced Strategies for Effective Cross-Functional Collaboration

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Book SynopsisThis textbook provides an excellent focus on the advanced topics of the power system protection philosophy and gives exciting analysis methods and a cover of the important applications in the power systems relaying. Each chapter opens with a historical profile or career talk, followed by an introduction that states the chapter objectives and links the chapter to the previous ones, and then the introduction for each chapter. All principles are presented in a lucid, logical, step-by-step approach. As much as possible, the authors avoid wordiness and detail overload that could hide concepts and impede understanding. In each chapter, the authors present some of the solved examples and applications using a computer program.Toward the end of each chapter, the authors discuss some application aspects of the concepts covered in the chapter using a computer program.In recognition of requirements by the Accreditation Board for Engineering and Technology (ABET) on integrating comTable of Contents1. Introduction to Power Protection Systems. 2. Protective Relays. 3. Protection Systems with SCADA Technology 4. Faults Analysis. 5. Fuses and Circuit Breakers. 6. Overcurrent Relay. 7. Transmission Line Protection. 8. Transformer Protection. 9. Generator, Motor, and Busbar Protection. 10. High-Impedance Faults. 11. Grounding of Power System.

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Volume 1 of Learning Professional Python is a resource for students who want to learn Python even if they don't have any programming knowledge and for teachers who want a comprehensive introduction to Python to use with their students. This book helps the students achieve their dream job in IT Industry and teaches the students in an easy, understandable manner while strengthening coding skills.Learning Professional Python: Volume 1 Objectives Become familiar with the features of Python programming language Introduce the object-oriented programming concepts Discover how to write Python code by following the object-oriented programming concepts Become comfortable with concepts such as classes, objects, inheritance, dynamic dispatch, interfaces, and packages Learn the Python generics and collections Develop exception handling and the multi

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Book SynopsisApplying Natural Language Processing (NLP) concepts to help humans in their daily life, this book discusses an automatic translation of an unstructured Natural Language Question (NLQ) into a Structured Query Language (SQL) statement. Using SQL as a Relational DataBase (RDB) interaction language, database administrators or general users with little to no SQL querying abilities are provided with all the knowledge necessary to perform queries on RDBs in an interactive manner.Key Features: Includes extensive and illustrative examples to simplify the discussed concepts Discusses a novel, and yet simple, approach to NLP Introduces a lightweight NLQ into SQL translation approach through the use of RDB MetaTables as a Hash table Extensive literature review and thorough background information on every tool, concept and technique applied Providing a unique approach to NLQ into SQTable of ContentsPreface. 1 Introduction. 2 Background Study. 3 Literature Review. 4 Implementation Plan. 5 Implementation User Case Scenario. 6 Implementation Testing and Performance Measurements. 7 Implementation Results Discussion. 8 Conclusion and Future Work. Appendix 1. Appendix 2. Appendix 3. Appendix 4. Appendix 5. Appendix 6. Appendix 7. Appendix 8. Appendix 9. Glossary. References. Index.

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Book SynopsisData is everywhere and it's growing at an unprecedented rate. But making sense of all that data is a challenge. Data Mining is the process of discovering patterns and knowledge from large data sets, and Data Mining with Python focuses on the hands-on approach to learning Data Mining. It showcases how to use Python Packages to fulfill the Data Mining pipeline, which is to collect, integrate, manipulate, clean, process, organize, and analyze data for knowledge.The contents are organized based on the Data Mining pipeline, so readers can naturally progress step by step through the process. Topics, methods, and tools are explained in three aspects: What it is as a theoretical background, why we need it as an application orientation, and how we do it as a case study.This book is designed to give students, data scientists, and business analysts an understanding of Data Mining concepts in an applicable way. Through interactive tutorials that can be run, modified,

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Book SynopsisVolume 2 of Learning Professional Python is a resource for students who want to learn Python even if they don't have any programming knowledge and for teachers who want a comprehensive introduction to Python to use with their students. This book helps the students achieve their dream job in the IT Industry and teaches the students in an easy, understandable manner while strengthening coding skills.Learning Professional Python: Volume 2 Objectives Become familiar with the features of Python programming language Introduce the object-oriented programming concepts Discover how to write Python code by following the object-oriented programming concepts Become comfortable with concepts such as classes, objects, inheritance, dynamic dispatch, interfaces, and packages Learn the Python generics and collections Develop exception handling and the mTable of ContentsPreface. Author Biographies. Chapter 1 Classes and Objects. Chapter 2 Inheritance. Chapter 3 Arrays. Chapter 4 Exception Handling. Chapter 5 Multi Threading. Chapter 6 Method Overloading and Operator Overloading. Chapter 7 GUI Programming. Chapter 8 File Handling. Chapter 9 Database Connectivity. Chapter 10 Case Study. INDEX.

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Book SynopsisGateway Routing Selection Schemes for PostâDisaster Recovery in Mobile Ad Hoc Networks bridges the gap by providing practical guidelines for an efficient design and performance evaluation of gateway selection schemes to manage load balancing. This book provides both a theoretical background and a practical evaluation of gateway selection methods using simulation methodology. Provides good coverage in a single text on a performance evaluation of gateway routing selection schemes for postâdisaster recovery Offers students, teachers, and researchers both theoretical and practical knowledge of system design and performance validation Enhances teaching and learning and research capability in gateway routing selection schemes Begins each chapter with a set of learning objectives and provides chapter summaries as well as review questions Provides illustrations, miniâprojects, and a list of acronyms Gateway Routing Selection Schemes for PostâDisaster Recovery in Mobile Ad Hoc Networks makes the teaching, learning, and researching of gateway routing selection schemes a more active process by using practical tools and exercises.

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Book SynopsisThis book delves into the critical realm of trust management within the Internet of Vehicles (IOV) networks, exploring its multifaceted implications on safety and security which forms part of the intelligent transportation system domain.IoV emerges as a powerful convergence, seamlessly amalgamating the Internet of Things (IoT) and the intelligent transportation systems (ITS). This is crucial not only for safety-critical applications but is also an indispensable resource for non-safety applications and efficient traffic flows. While this paradigm holds numerous advantages, the existence of malicious entities and the potential spread of harmful information within the network not only impairs its performance but also presents a danger to both passengers and pedestrians. Exploring the complexities arising from dynamicity and malicious actors, this book focuses primarily on modern trust management models designed to pinpoint and eradicate threats. This includes tackling the challe

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Book SynopsisThe fourth volume in a new series exploring the basics of Raspberry Pi Operating System administration, this installment builds on the insights provided in Volumes 1, 2, and 3 to provide a compendium of easy-to-use and essential Raspberry Pi OS administration for the novice user, with specific focus on ancillary topics that can be used with the Raspberry Pi OS based upon upstream Debian Bookworm release, and the Raspberry Pi 5.The overriding idea behind system administration of a modern, 21st-century Linux system such as the Raspberry Pi OS is the use of systemd to ensure that the Linux kernel works efficiently and effectively to provide these three foundation stones of computer operation and management: computer system concurrency, virtualization, and secure persistence. This fourth volume includes full-chapter explications, with many examples, of the following: the Zettabyte File System (ZFS) the X Window System, the Wayland protocol, XWayland, the Wayfir

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Book SynopsisSince the first edition of âœData Science and Analytics with Pythonâ we have witnessed an unprecedented explosion in the interest and development within the fields of Artificial Intelligence and Machine Learning. This surge has led to the widespread adoption of the book, not just among business practitioners, but also by universities as a key textbook. In response to this growth, this new edition builds upon the success of its predecessor, expanding several sections, updating the code to reflect the latest advancements in Python libraries and modules, and addressing the ever-evolving landscape of generative AI (GenAI).This updated edition ensures that the examples and exercises remain relevant by incorporating the latest features of popular libraries such as Scikit-learn, pandas, and Numpy. Additionally, new sections delve into cutting-edge topics like generative AI, reflecting the advancements and the expanding role these technologies play. This edition also addresses crucia

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Book SynopsisA Concise Introduction to Robot Programming with ROS2 provides the reader with the concepts and tools necessary to bring a robot to life through programming. It will equip the reader with the skills necessary to undertake projects with ROS2, the new version of ROS. It is not necessary to have previous experience with ROS2 as it will describe its concepts, tools, and methodologies from the beginning.Key Features Uses the two programming languages officially supported in ROS2 (C++, mainly, and Python) Approaches ROS2 from three different but complementary dimensions: the Community, Computation Graph, and the Workspace Includes a complete simulated robot, development and testing strategies, Behavior Trees, and Nav2 description, setup, and use A GitHub repository with code to assist readers It will appeal to motivated engineering students, engineers, and professionals working with robot programming.

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Book SynopsisAs an introduction to Python, this book allows readers to take a slow and steady approach to understanding Python code, explaining concepts, connecting programming with real-life examples, writing Python programs, and completing case studies.While there are many books, websites, and online courses about the topic, we break down Python programming into easily digestible lessons of less than 5 minutes each, following our BiteSize approach. Each lesson begins with a clear and short introduction to the topic. This gives you a strong base to start from and gets you ready for deeper learning. Then, you will see coding demonstrations that show the ideas discussed. These examples are simple and useful, helping you really understand the concepts. Youâll then practice tasks at different difficulty levels, so you can test your knowledge and increase your confidence. Youâll also play with case studies to solve real-world problems. Tips are included to show how you can incorporate generative AI into your learning toolkit, using it for feedback, practice exercises, code reviews, and exploring advanced topics. Recommended AI prompts can help you identify areas for improvement, review key concepts, and track your progress.This book is designed for absolute beginners with no prior programming experience. It is ideal for individuals with busy schedules or limited time for studying.

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Book SynopsisPython Experiments in Physics and Astronomy acts as a resource for science and engineering students or faculty who would like to see how a diverse selection of topics can be analyzed and simulated using Python programs.

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Book SynopsisAI-powered coding tools are revolutionizing software development, transforming programming from a specialized skill into an accessible educational practice across disciplines. This book investigates how tools such as Cursor AI, GitHub Copilot, and Replit's Ghostwriter are dismantling traditional barriers to entry for learnersâparticularly those from non-STEM backgroundsâby enabling natural language code generation, intelligent debugging, and interactive, project-based learning. Bridging the gap between theoretical instruction and practical application, the book serves as both a guide and a critical framework for integrating generative AI into curricula. It highlights how these tools expand the boundaries of programming education by supporting interdisciplinary applications, from literary analysis to creative writing, thereby making coding relevant and actionable for students in the humanities and beyond. The book equips educators with the tools and strategies necessary to incorporate AI-assisted programming into diverse academic contexts by offering lesson plans and adaptable project models. This resource is essential for instructors seeking to demystify coding, promote inclusivity in technical learning, and reimagine the role of software literacy in the twenty-first-century classroom.

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Book SynopsisThis practical book covers design approaches and technologies that make it possible to scale an application quickly and cost-effectively. Author Ian Gorton takes software architects and developers through the principles of foundational distributed systems.

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Book SynopsisLearning TypeScript takes beginner to intermediate JavaScript programmers from knowing nothing about "types" or a "type system" to full mastery of the fundamentals of TypeScript. It's more than a means to find bugs and typos--it's a useful system for declaring the way our JavaScript should work and helping us stick to it.

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Book SynopsisIn this insightful and entertaining book, Michael Lopp recalls his own make-or-break moments with Silicon Valley giants such as Apple, Slack, Pinterest, Palantir, Netscape, and Symantec to help you make better, more mindful career decisions.

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Book SynopsisWith this practical guide, power users and developers will discover ways to resolve everyday challenges by building end-to-end solutions with the Microsoft Power Platform.

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Book Synopsis

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