Project or program health checks provide tremendous value to businesses and pay for themselves by multiples of magnitude. No matter how well a project or program is performing, there are always activities that can provide better value, reduce costs, or introduce more innovation. IT project and program health checks can help organizations reach their goals and dramatically improve Return on Investment (ROI). IT Project Health Checks: Driving Successful Implementation and Multiples of Business Value offers a proven approach for evaluating IT projects or programs in order to determine how they are performing and how the eventual outcome for the initiative is currently trending. The project or program health checks provide a set of techniques that produce actionable recommendations that can be applied for any combination of the following outcomes: Drive more business and technical value from a program Set a project or program back on track for successful implementation as defined by executive management Rescue a program that is heading towards failure Act as additional insurance for initiatives that are too important to fail Protect executive careers by creating transparency within the inner workings of complex initiatives. The book shows how a review can quickly identify whether an initiative needs to be rescued even when the project team is not aware that it is hurtling towards failure. It also provides techniques for driving business value even when a project team believes it's been stretched as much as possible. Other outcomes covered in this book include: Objectively develop a project Health-Check Scorecard that establishes how well a project is doing and the direction it is headed Demonstrate how to drive business value from an IT program regardless of how well or badly it is tracking Provide surgical advice to improve a project's outcome How to use the many templates and sample deliverables to get a quick start on your own health check. Designed to provide significant value to any member of a project team, program team, stakeholders, sponsors, business users, system integrators, trainers, and IT professionals, this book can help find opportunities to drive multiples of business value and exceed project success metrics.

This book provides in-depth insights into use cases implementing artificial intelligence (AI) applications at the edge. It covers new ideas, concepts, research, and innovation to enable the development and deployment of AI, the industrial internet of things (IIoT), edge computing, and digital twin technologies in industrial environments. The work is based on the research results and activities of the AI4DI (ECSEL JU) project, including an overview of industrial use cases, research, technological innovation, validation, and deployment. This book's sections build on the research, development, and innovative ideas elaborated for applications in five industries: automotive, semiconductor, industrial machinery, food and beverage, and transportation. The articles included under each of these five industrial sectors discuss AI-based methods, techniques, models, algorithms, and supporting technologies, such as IIoT, edge computing, digital twins, collaborative robots, silicon-born AI circuit concepts, neuromorphic architectures, and augmented intelligence, that are anticipating the development of Industry 5.0. Automotive applications cover use cases addressing AI-based solutions for inbound logistics and assembly process optimisation, autonomous reconfigurable battery systems, virtual AI training platforms for robot learning, autonomous mobile robotic agents, and predictive maintenance for machines on the level of a digital twin. AI-based technologies and applications in the semiconductor manufacturing industry address use cases related to AI-based failure modes and effects analysis assistants, neural networks for predicting critical 3D dimensions in MEMS inertial sensors, machine vision systems developed in the wafer inspection production line, semiconductor wafer fault classifications, automatic inspection of scanning electron microscope cross-section images for technology verification, anomaly detection on wire bond process trace data, and optical inspection. The use cases presented for machinery and industrial equipment industry applications cover topics related to wood machinery, with the perception of the surrounding environment and intelligent robot applications. AI, IIoT, and robotics solutions are highlighted for the food and beverage industry, presenting use cases addressing novel AI-based environmental monitoring; autonomous environment-aware, quality control systems for Champagne production; and production process optimisation and predictive maintenance for soybeans manufacturing. For the transportation sector, the use cases presented cover the mobility-as-a-service development of AI-based fleet management for supporting multimodal transport. This book highlights the significant technological challenges that AI application developments in industrial sectors are facing, presenting several research challenges and open issues that should guide future development for evolution towards an environment-friendly Industry 5.0. The challenges presented for AI-based applications in industrial environments include issues related to complexity, multidisciplinary and heterogeneity, convergence of AI with other technologies, energy consumption and efficiency, knowledge acquisition, reasoning with limited data, fusion of heterogeneous data, availability of reliable data sets, verification, validation, and testing for decision-making processes.

A groundbreaking treatise by one of the great mathematicians of our age, who outlines a style of thinking by which great ideas are conceived. What inspires and spurs on a great idea? Can we train ourselves to think in a way that will enable world-changing understandings and insights to emerge? Richard Hamming said we can. He first inspired a generation of engineers, scientists, and researchers in 1986 with "You and Your Research," an electrifying sermon on why some scientists do great work, why most don't, why he did, and why you can-and should-too. The Art of Doing Science and Engineering is the full expression of what "You and Your Research" outlined. It's a book about thinking; more specifically, a style of thinking by which great ideas are conceived. The book is filled with stories of great people performing mighty deeds-but they are not meant simply to be admired. Instead, they are to be aspired to, learned from, and surpassed. Hamming consistently returns to Shannon's information theory, Einstein's theory of relativity, Grace Hopper's work on high-level programming, Kaiser's work on digital fillers, and his own work on error-correcting codes. He also recounts a number of his spectacular failures as clear examples of what to avoid. Originally published in 1996 and adapted from a course that Hamming taught at the US Naval Postgraduate School, this edition includes an all-new foreword by designer, engineer, and founder of Dynamicland Bret Victor, plus more than 70 redrawn graphs and charts. The Art of Doing Science and Engineering is a reminder that a capacity for learning and creativity are accessible to everyone. Hamming was as much a teacher as a scientist, and having spent a lifetime forming and confirming a theory of great people and great ideas, he prepares the next generation for even greater distinction.

The book augurs to be a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives orient to offer an overview to the elementary concepts and practices appropriate to DIP as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to: Applications and tools for image processing, fundamentals with several implementation examples Concepts of image formation, OpenCV installation with step-by-step screen shots Concepts behind intensity, brightness and contrast, color models Ways by which noises are created in an image and the possible remedial measures Edge detection, Image segmentation, classification, regression, Classification algorithms Importance of frequency domain in image processing field Relevant code snippets and the MATLAB codes, several interesting set of simple programs in OpenCV and Python to aid learning and for complete understanding The video lectures for specific topics through YouTube by the authors enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quiz, review questions etc., fully prepares the readers for further study. Graduate Students, Post Graduate students, Researchers, and anyone in general interested in Image Processing, Computer Vision, Machine Learning domains etc. can find this book an excellent starting point for information and as an able ally.

As Information Technology continues to evolve as a key strategic enabler, many establishments feel the need to think more holistically about how IT can support corporate sustainability efforts. This book aims to recognize these efforts and best practices in numerous business settings. Sustainability is expensive, and requires collaboration between many different areas of the business. The solution to growing burden of carbon emission lies within the technology innovation as continued advancements in processes make businesses lean and smart. The multidisciplinary approach the book uses will be appreciated by students, academics and researchers in Information Technology, Management, Corporate, and Sustainability Champions. Print edition not for sale in South Asia (India, Sri Lanka, Nepal, Bangladesh, Pakistan and Bhutan)

Exam board: OCR Level: A-level Subject: Computer Science First teaching: September 2015 First exams: Summer 2017 Strengthen your students' understanding and upgrade their confidence and exam skills with our OCR Computer Science workbooks, full of self-contained exercises to consolidate knowledge and exam practice questions to improve performance. Written by an experienced Computer Science author, these full colour workbooks provide stimulus materials on all AS and A-level topics, followed by sets of questions designed to develop and test skills in the unit. * Thoroughly prepares students for their examinations as they work through numerous practice questions that cover every question type in the specification. * Helps students identify their revision needs and see how to target the top grades using online answers for each question. * Encourages ongoing revision throughout the course as students progressively develop their skills in class and at home. * Packed full with consolidation and exam practice questions, these workbooks can save valuable preparation time and expense, with self-contained exercises that don't need photocopying and provide instant lesson and homework solutions for specialist and non-specialist teachers. * Ensures that students feel confident tackling their exams as they know what to expect in each section.

Data analytics underpin our modern data-driven economy. This textbook explains the relevance of data analytics at the firm and industry levels, tracing the evolution and key components of the field, and showing how data analytics insights can be leveraged for business results. The first section of the text covers key topics such as data analytics tools, data mining, business intelligence, customer relationship management, and cybersecurity. The chapters then take an industry focus, exploring how data analytics can be used in particular settings to strengthen business decision-making. A range of sectors are examined, including financial services, accounting, marketing, sport, health care, retail, transport, and education. With industry case studies, clear definitions of terminology, and no background knowledge required, this text supports students in gaining a solid understanding of data analytics and its practical applications. PowerPoint slides, a test bank of questions, and an instructor's manual are also provided as online supplements. This will be a valuable text for undergraduate level courses in data analytics, data mining, business intelligence, and related areas.

Combining theory and practice, this updated new edition provides a complete overview of how to create deep and meaningful quests for games. It uses the Unity game engine in conjunction with Fungus and other free plugins to provide an accessible entry into quest design. The book begins with an introduction to the theory and history of quests in games, before covering four theoretical components of quests: their spaces, objects, actors, and challenges. Each chapter also includes a practical section, with accompanying exercises and suggestions for the use of specific technologies for four crucial aspects of quest design: * level design * quest item creation * NPC and dialogue construction * scripting This book will be of great interest to all game designers looking to create new, innovative quests in their games. It will also appeal to new media researchers, as well as humanities scholars in the fields of mythology and depth-psychology that want to bring computer-assisted instruction into their classroom in an innovative way. The companion website includes lecture and workshop slides, and can be accessed at: www.designingquests.com

Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group. The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in: Ticket pricing Season ticket member retention Fan engagement Sponsorship valuation Customer relationship management Digital marketing Market research Data visualization. This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations. Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics.

This book offers a comprehensive and detailed guide to accomplishing and perfecting a photorealistic look in digital content across visual effects, architectural and product visualization, and games. Emmy award-winning VFX supervisor Eran Dinur offers readers a deeper understanding of the complex interplay of light, surfaces, atmospherics, and optical effects, and then discusses techniques to achieve this complexity in the digital realm, covering both 3D and 2D methodologies. In addition, the book features artwork, case studies, and interviews with leading artists in the fields of VFX, visualization, and games. Exploring color, integration, light and surface behaviour, atmospherics, shading, texturing, physically-based rendering, procedural modelling, compositing, matte painting, lens/camera effects, and much more, Dinur offers a compelling, elegant guide to achieving photorealism in digital media and creating imagery that is seamless from real footage. Its broad perspective makes this detailed guide suitable for VFX, visualization and game artists and students, as well as directors, architects, designers, and anyone who strives to achieve convincing, believable visuals in digital media.

Nothing has been more prolific over the past century than human/machine interaction. Automobiles, telephones, computers, manufacturing machines, robots, office equipment, machines large and small; all affect the very essence of our daily lives. However, this interaction has not always been efficient or easy and has at times turned fairly hazardous. Cognitive Systems Engineering (CSE) seeks to improve this situation by the careful study of human/machine interaction as the meaningful behavior of a unified system. Written by pioneers in the development of CSE, Joint Cognitive Systems: Foundations of Cognitive Systems Engineering offers a principled approach to studying human work with complex technology. The authors use a top-down, functional approach and emphasize a proactive (coping) perspective on work that overcomes the limitations of the structural human information processing view. They describe a conceptual framework for analysis with concrete theories and methods for joint system modeling that can be applied across the spectrum of single human/machine systems, social/technical systems, and whole organizations. The book explores both current and potential applications of CSE illustrated by examples. Understanding the complexities and functions of the human/machine interaction is critical to designing safe, highly functional, and efficient technological systems. This is a critical reference for students, designers, and engineers in a wide variety of disciplines.

The ethics of data and analytics, in many ways, is no different than any endeavor to find the "right" answer. When a business chooses a supplier, funds a new product, or hires an employee, managers are making decisions with moral implications. The decisions in business, like all decisions, have a moral component in that people can benefit or be harmed, rules are followed or broken, people are treated fairly or not, and rights are enabled or diminished. However, data analytics introduces wrinkles or moral hurdles in how to think about ethics. Questions of accountability, privacy, surveillance, bias, and power stretch standard tools to examine whether a decision is good, ethical, or just. Dealing with these questions requires different frameworks to understand what is wrong and what could be better. Ethics of Data and Analytics: Concepts and Cases does not search for a new, different answer or to ban all technology in favor of human decision-making. The text takes a more skeptical, ironic approach to current answers and concepts while identifying and having solidarity with others. Applying this to the endeavor to understand the ethics of data and analytics, the text emphasizes finding multiple ethical approaches as ways to engage with current problems to find better solutions rather than prioritizing one set of concepts or theories. The book works through cases to understand those marginalized by data analytics programs as well as those empowered by them. Three themes run throughout the book. First, data analytics programs are value-laden in that technologies create moral consequences, reinforce or undercut ethical principles, and enable or diminish rights and dignity. This places an additional focus on the role of developers in their incorporation of values in the design of data analytics programs. Second, design is critical. In the majority of the cases examined, the purpose is to improve the design and development of data analytics programs. Third, data analytics, artificial intelligence, and machine learning are about power. The discussion of power-who has it, who gets to keep it, and who is marginalized-weaves throughout the chapters, theories, and cases. In discussing ethical frameworks, the text focuses on critical theories that question power structures and default assumptions and seek to emancipate the marginalized.

This book aims at helping software teams work more efficiently by setting up their own design processes In a world where being able to satisfy users' needs becomes a crucial element for products' existence, this book helps organizations understand design processes, allowing them efficiently deliver experiences that address the real problems of their audiences. This book offers a combination of theory and practice that will help its readers understand how to design efficient processes and apply this knowledge in their own work. A large volume of insights in the form of colorful images and doodles.

Explanatory Model Analysis Explore, Explain and Examine Predictive Models is a set of methods and tools designed to build better predictive models and to monitor their behaviour in a changing environment. Today, the true bottleneck in predictive modelling is neither the lack of data, nor the lack of computational power, nor inadequate algorithms, nor the lack of flexible models. It is the lack of tools for model exploration (extraction of relationships learned by the model), model explanation (understanding the key factors influencing model decisions) and model examination (identification of model weaknesses and evaluation of model's performance). This book presents a collection of model agnostic methods that may be used for any black-box model together with real-world applications to classification and regression problems.

Blue Team defensive advice from the biggest names in cybersecurity The Tribe of Hackers team is back. This new guide is packed with insights on blue team issues from the biggest names in cybersecurity. Inside, dozens of the world's leading Blue Team security specialists show you how to harden systems against real and simulated breaches and attacks. You'll discover the latest strategies for blocking even the most advanced red-team attacks and preventing costly losses. The experts share their hard-earned wisdom, revealing what works and what doesn't in the real world of cybersecurity. Tribe of Hackers Blue Team goes beyond the bestselling, original Tribe of Hackers book and delves into detail on defensive and preventative techniques. Learn how to grapple with the issues that hands-on security experts and security managers are sure to build into their blue team exercises. Discover what it takes to get started building blue team skills Learn how you can defend against physical and technical penetration testing Understand the techniques that advanced red teamers use against high-value targets Identify the most important tools to master as a blue teamer Explore ways to harden systems against red team attacks Stand out from the competition as you work to advance your cybersecurity career Authored by leaders in cybersecurity attack and breach simulations, the Tribe of Hackers series is perfect for those new to blue team security, experienced practitioners, and cybersecurity team leaders. Tribe of Hackers Blue Team has the real-world advice and practical guidance you need to advance your information security career and ready yourself for the blue team defense.

Constraint Satisfaction Problems (CSPs) are natural computational problems that appear in many areas of theoretical computer science. Exploring which CSPs are solvable in polynomial time and which are NP-hard reveals a surprising link with central questions in universal algebra. This monograph presents a self-contained introduction to the universal-algebraic approach to complexity classification, treating both finite and infinite-domain CSPs. It includes the required background from logic and combinatorics, particularly model theory and Ramsey theory, and explains the recently discovered link between Ramsey theory and topological dynamics and its implications for CSPs. The book will be of interest to graduate students and researchers in theoretical computer science and to mathematicians in logic, combinatorics, and dynamics who wish to learn about the applications of their work in complexity theory.

For the past 50 years, the advancements of technology have equipped architects with unique tools that have enabled the development of new computer-mediated design methods, fabrication techniques, and architectural expressions. Simultaneously, in contemporary architecture new frameworks emerged that have radically redefined the traditional conceptions of design, of the built environment, and of the role of architects. Cybernetic Architectures argues that such frameworks have been constructed in direct reference to cybernetic thinking, a thought model that emerged concurrently with the origins of informatics and that embodies the main assumptions, values, and ideals underlying the development of computer science. The book explains how the evolution of the computational perspective in architecture has been parallel to the construction of design issues in reference to the central ideas fostered by the cybernetic model. It unpacks and explains this crucial relationship, in the work of digital architects, between the use of information technology in design and the conception of architectural problems around an informational ontology. This book will appeal to architecture students and scholars interested in understanding the recent transformations in the architectural landscape related to the advent of computer-based design paradigms.

Showcasing the most influential developments, experiments, and architectures impacting the digital, surveillance, automotive, industrial, and medical sciences, Image Processing Technologies tracks the evolution and advancement of computer vision and image processing (CVIP) technologies, examining methods and algorithms for image analysis, optimization, segmentation, and restoration. It focuses on recent approaches and techniques in CVIP applications development and explores various coding methods for individual types of 3-D images. This text/reference brings researchers and specialists up-to-date on the latest innovations affecting multiple image processing environments.

This comprehensive guide walks readers through the entire process of getting and keeping a writing job in the games industry. It outlines exactly what a beginner needs to know about education requirements, finding opportunities, applying for roles, and acing studio interviews. Professional writers will learn how to navigate studio hierarchies, transfer roles and companies, work overseas, and keep developing their careers. Written by an experienced games writer with nearly two decades of industry knowledge, the book contains a wealth of interviews and perspectives with industry leaders, hiring managers, and developers from marginalized communities, all offering their tips and insights. Included are examples of materials such as job posts, writing samples, and portfolios, as well as chapter end challenges for readers to directly apply the skills they have learnt. This book will be of great interest to all beginner and aspiring games writers and narrative designers, as well as more experienced writers looking to hone their skills.

A definitive guide to contemporary video game studies, this second edition has been fully revised and updated to address the ongoing theoretical and methodological development of game studies. Expertly compiled by well-known video game scholars Mark J. P. Wolf and Bernard Perron, the Companion includes comprehensive and interdisciplinary models and approaches for analyzing video games, new perspectives on video games both as an art form and cultural phenomenon, explorations of the technical and creative dimensions of video games, and accounts of the political, social, and cultural dynamics of video games. Brand new to this second edition are essays examining topics such as preservation, augmented, mixed and virtual reality, eSports, disability, diversity, and identity, as well as a new section that specifically examines the industrial aspects of video games including digital distribution, game labor, triple-A games, indie games, and globalization. Each essay provides a lively and succinct summary of its target area, quickly bringing the reader up-to-date on the pertinent issues surrounding each aspect of the field, including references for further reading. A comprehensive overview of the present state of video game studies that will undoubtedly prove invaluable to students, scholars, and game designers alike.

This anthology contributes to creating awareness on how digital ageism operates in relation to the widely spread symbolic representations of old and young age, the (lack of) representation of diverse older individuals in the design, development, and discourses and in the actual algorithms and datasets. It also shows how individuals and institutions deal with digital ageism in everyday life. In the past decades, digital technologies permeated most aspects of everyday life and became ingrained into human existence. With a focus on how age is represented and experienced in relation to digital technologies leading to digital ageism, digitalisation's reinforcement of spirals of exclusion and loss of autonomy of some collectives is explored, when it could be natural for a great part of society and represent a sort of improvement. The book addresses social science students and scholars interested in everyday digital technologies, society and the power struggles about it, providing insights from different parts of the globe. By using different methods and touching upon different aspects of digital ageism and how it plays out in contemporary connected data societies, this volume will raise awareness, challenge power, initiate discussions and spur further research into this field.

This book illustrates the current work of leading multilevel modeling (MLM) researchers from around the world.

The book's goal is to critically examine the real problems that occur when trying to use MLMs in applied research, such as power, experimental design, and model violations. This presentation of cutting-edge work and statistical innovations in multilevel modeling includes topics such as growth modeling, repeated measures analysis, nonlinear modeling, outlier detection, and meta analysis.

This volume will be beneficial for researchers with advanced statistical training and extensive experience in applying multilevel models, especially in the areas of education; clinical intervention; social, developmental and health psychology, and other behavioral sciences; or as a supplement for an introductory graduate-level course.

This volume: * Uses the Coronavirus pandemic to explore the link between news sentiment and global financial markets * Shows how the COVID-19 crisis differs from the Global Financial Crisis of 2008 * Focuses on the Noise vs Signal in news sentiment * will be invaluable for business professionals, bankers, media professionals, and investment consultants.

The complementary nature of physically-based and data-driven models in their demand for physical insight and historical data, leads to the notion that the predictions of a physically-based model can be improved and the associated uncertainty can be systematically reduced through the conjunctive use of a data-driven model of the residuals. The objective of this thesis is to minimise the inevitable mismatch between physically-based models and the actual processes as described by the mismatch between predictions and observations. Principles based on information theory are used to detect the presence and nature of residual information in model errors that might help to develop a data-driven model of the residuals by treating the gap between the process and its (physically-based) model as a separate process. The complementary modelling approach is applied to various hydrodynamic and hydrological models to forecast the expected errors and accuracy, using neural network and fuzzy rule-based models. Complementary modelling offers the opportunity of incorporating processes and data that are not considered by the model, without affecting the routine operation of physically-based models. The possibility that information may be obtained which will help to improve the physically-based model is also demonstrated.