While simulation has a vast area of application, this textbook focuses on the use of simulation to analyse business processes. It provides an up-to-date coverage of all stages of the discrete-event simulation (DES) process, covering important areas such as conceptual modelling, modelling input data, verification and validation and simulation output analysis. The book is comprehensive yet uncomplicated, covering the theoretical aspects of the subject and the practical elements of a typical simulation project, demonstrated by cases, examples and exercises. It also shows how simulation relates to new developments in machine learning, big data analytics and conceptual modelling techniques. Guidance is provided on how to build DES models using the Arena, Simio and Simul8 simulation software, and tutorials for using the software are incorporated throughout. Simulation Modelling offers a uniquely practical and end-to-end overview of the subject, which makes it perfect required or recommended reading for advanced undergraduate and postgraduate students studying business simulation and simulation modelling as part of operations research, business analytics, supply chain management and computer science courses.

In today's information society, to make a real and lasting impact on human welfare takes applications of information technology aimed at enhancing access to all. HUSITA7-The 7th International Conference of Human Services Information Technology Applications: Digital Inclusion-Building a Digital Inclusive Society presents diverse viewpoints from around the globe, examining the latest applications of digital technology for social work education and practice. These conference presentations from respected international authorities discuss the application of ICT (information and communication technology) in various facets of human service to achieve the goal of a digital inclusive society where all have access to education and informational resources. HUSITA7-The 7th International Conference of Human Services Information Technology Applications examines the development and use of information technology in professional training, including the strengths and limitations of e-learning in social work curriculums along with the rationale behind a learning object approach. Research includes findings from educators in Canada describing the development and implementation of e-learning in social work programs and the qualitative study of technological content in an MSW curriculum. Various types of Web-based learning approaches are explored with an eye toward providing more effective teaching strategies. Various technological advances and approaches toward individual empowerment are described to facilitate greater societal inclusiveness. The book is well referenced and includes several helpful tables and figures. Topics in HUSITA7-The 7th International Conference of Human Services Information Technology Applications include: the learning object approach of e-learning for social work education challenges implementing e-learning in social work education a research study of the relationship between technology content in social work education and technology use in social work practice international partnerships in Web-based teaching effective integration of emotion into the content of Web-based learning the use of indigenous knowledge in content the use of Web CT for effective address of issues such as quality of teaching and communication bringing about social inclusion through effective digital government how technological advances impact assistive technology research on the Internet self-efficacy in older person's learning of ICT a communication tool for the speech impaired improving social work service effectiveness through knowledge management (KM) the "SenSui" disability information resource in Japan HUSITA7-The 7th International Conference of Human Services Information Technology Applications is enlightening reading for librarians, social educators, social work students, researchers interested in ICT, and human service professionals.

The methodological needs of environmental studies are unique in the breadth of research questions that can be posed, calling for a textbook that covers a broad swath of approaches to conducting research with potentially many different kinds of evidence. Fully updated to address new developments such as the effects of the internet, recent trends in the use of computers, remote sensing, and large data sets, this new edition of Research Methods for Environmental Studies is written specifically for social science-based research into the environment. This revised edition contains new chapters on coding, focus groups, and an extended treatment of hypothesis testing. The textbook covers the best-practice research methods most used to study the environment and its connections to societal and economic activities and objectives. Over five key parts, Kanazawa introduces quantitative and qualitative approaches, mixed methods, and the special requirements of interdisciplinary research, emphasizing that methodological practice should be tailored to the specific needs of the project. Within these parts, detailed coverage is provided on key topics including the identification of a research project, hypothesis testing, spatial analysis, the case study method, ethnographic approaches, discourse analysis, mixed methods, survey and interview techniques, focus groups, and ethical issues in environmental research. Drawing on a variety of extended and updated examples to encourage problem-based learning and fully addressing the challenges associated with interdisciplinary investigation, this book will be an essential resource for students embarking on courses exploring research methods in environmental studies.

Everyone talks innovation and we can all point to random examples of innovation inside of healthcare information technology, but few repeatable processes exist that make innovation more routine than happenstance. How do you create and sustain a culture of innovation? What are the best practices you can refine and embed as part of your organization’s DNA? What are the potential outcomes for robust healthcare transformation when we get this innovation mystery solved? Through timely essays from leading experts, the first edition showcased the widely adopted healthcare innovation model from HIMSS and how providers could leverage to increase their velocity of digital transformation. Regardless of its promise, innovation has been slow in healthcare. The second edition takes the critical lessons learned from the first edition, expands and refreshes the content as a result of changes in the industry and the world. For example, the pandemic really shifted things. Now providers are more ready and interested to innovate. In the past year alone, significant disruptors (such as access to digital health) have entered the provider space threatening the existence of many hospitals and practices. This has served as a giant wake-up call that healthcare has shifted. And finally, there is more emphasis today than before on the concept of patient and clinician experience. Perhaps hastened by the pandemic, the race is on for innovations that will help address clinician burnout while better engaging patients and families. Loaded with numerous case studies and stories of successful innovation projects, this book helps the reader understand how to leverage innovation to help fulfill the promise of healthcare information technology in enabling superior business and clinical outcomes.

Modern Computational Techniques for Engineering Applications presents recent computational techniques used in the advancement of modern grids with the integration of non-conventional energy sources like wind and solar energy. It covers data analytics tools for smart cities, smart towns, and smart computing for sustainable development. This book- Discusses the importance of renewable energy source applications wind turbines and solar panels for electrical grids. Presents optimization-based computing techniques like fuzzy logic, neural networks, and genetic algorithms that enhance the computational speed. Showcases cloud computing tools and methodologies such as cybersecurity testbeds and data security for better accuracy of data. Covers novel concepts on artificial neural networks, fuzzy systems, machine learning, and artificial intelligence techniques. Highlights application-based case studies including cloud computing, optimization methods, and the Industrial Internet of Things. The book comprehensively introduces modern computational techniques, starting from basic tools to highly advanced procedures, and their applications. It further highlights artificial neural networks, fuzzy systems, machine learning, and artificial intelligence techniques and how they form the basis for algorithms. It presents application-based case studies on cloud computing, optimization methods, blockchain technology, fog and edge computing, and the Industrial Internet of Things. It will be a valuable resource for senior undergraduates, graduate students, and academic researchers in diverse fields, including electrical engineering, electronics and communications engineering, and computer engineering.

Geotechnical works involve complex geo-engineering issues, which are reviewed in this volume presenting the very latest research and practice in computational mechanics in geotechnical engineering. Application of Computational Mechanics in Geotechnical Engineering V contains contributions on soil and rock excavations, underground structures and ground reinforcement; and on the construction of dams, embankments and rail track. Other papers consider the geomechanics of oil exploration and rock mechanics in mining; while environmental contributions include groundwater management. A wide range of methodologies are discussed: inversed methodologies, artificial intelligence and computational systems, which highlight future trends in the area of computational mechanics applied to geotechnical problems. The book will be of interest to researchers, academics, students, software developers, and practical engineers across the field of geotechnics.

The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

Digital Information and Knowledge Management examines how academic librarians can use knowledge management to provide an increasing amount of electronic information to an expanding user base. Several of the country's leading library administrators analyze these vital issues from the perspectives of both information providers and library users, exploring the challenges of selecting and managing electronic information and resources, making the most of knowledge management, and improving digital access to their users. Electronic resources have given the library new roles to fill and created a demand for librarians skilled in the acquisition, retrieval, and dissemination of digital information. Libraries and librarians have met the challenges presented by digital resources and have moved from building collections of print materials into the growing field of knowledge management. Digital Information and Knowledge Management offers insights into how librarians are making that transition to enhance the resources and services they can offer library users. Topics examined in Digital Information and Knowledge Management include: cooperative collection development the balance of print and electronic resources the evolution of digital resources in libraries the concept of knowledge management changes in research libraries knowledge management in academic libraries factors that influence the selection of electronic resources disseminating information about scholarly collections the need for a standardized method of information presentation successful approaches to managing digital information the digitalization of collections and historical materials how to maintain the connections between academic disciplines and libraries and much more! Digital Information and Knowledge Management is an essential professional resource for senior- and mid-level library administrators, and for acquisitions, reference, and collections librarians.

This book provides a comprehensive, easy-to-understand introductory guide to information, offering students the critical tools they need to shift their positioning from consumers and users to creators and critics. Searching, accessing, and using information are central to most daily lives. Yet, many users are not able to define what information is, identify who controls information, and create information to achieve a common good. In this book, Micky Lee teaches readers to critically interrogate key issues such as the categorization of information and knowledge throughout history, what digital divides are, why information is gender and race biased, how governments and corporations control citizens and consumers, as well as how we can resist unbalanced power relations. Readers will not only be able to relate these issues to "old" technologies, such as writing and printing, but will also be able to examine futurist technologies through the lenses of these enduring issues. A thoughtful and comprehensive overview, this is an ideal book for students and scholars of media studies, information and society, and communication and technology.

Unit Integration Testing (UIT) had been a challenge because there was no tool that could help in XHR programming and unit integration validations in an efficient way until Cypress arrived. Cypress started releasing versions in 2015 and became popular in 2018 with version 2.0.0. This book explores Cypress scripts that help implement 'shift left testing', which is a dream come true for many software testers. Shift left occurs in the majority of testing projects, but could not be implemented fully because tools were unavailable and knowledge was lacking about the possibilities of testing early in the life cycle. Shift left is a key testing strategy to help testing teams focus less on defect identifications and more on developing practices to prevent defects. Cypress scripts can help front-end developers and quality engineers to work together to find defects soon after web components are built. These components can be tested immediately after they are built with Cypress Test Driven Development (TDD) scripts. Thus, defects can be fixed straight away during the development stage. Testing teams do not have to worry about finding these same defects in a later development stage because Cypress tests keep verifying components in the later stages. Defect fixing has become much cheaper with Cypress than when other tools are used. The book also covers Behaviour Driven Development (BDD)-based Gherkin scripts and the Cypress Cucumber preprocessor, which can improve test scenario coverage. Automated Software Testing with Cypress is written to fulfil the BDD and TDD needs of testing teams. Two distinct open source repositories are provided in Github to help start running Cypress tests in no time!

1. The book will begin by evaluating the state of the art of all Internet Of behaviors (IoB) while looking into their BI, Big Data, CDPs, etc. core building block 2. Offers in-depth examination of Internet Of behaviors, which supports 3. Includes handy quick-reference to help readers with regular with simple language rules; 4. This book goal is to record, analyse, comprehend, and respond to all forms of human behaviour in a way that allows people to be tracked and interpreted using developing technology advancements and advances in machine learning algorithms

In one modest-sized volume, this book offers three valuable sets of knowledge. First, it provides best practice guidance on virtually every large-scale task a modern manager may be involved in-from recruiting and hiring to onboarding and leading teams, and from employee engagement and retention to performance management and working with difficult employees. Second, it explains the essential concepts and practice of a range of effective leadership styles-including (but not limited to) servant leadership, crisis leadership, change agent leadership, and diversity and inclusion leadership. Third, it offers brief case studies from select CISOs and CSOs on how these management and leadership principles and practices play out in real-life workplace situations. The best practice essentials provided throughout this volume will empower aspiring leaders and also enable experienced managers to take their leadership to the next level. Many if not most CISOs and other leaders have had very little, if any, formal training in management and leadership. The select few that have such training usually obtained it through academic courses that take a theoretical, broad brush approach. In contrast, this book provides much actionable guidance in the nitty-gritty tasks that managers must do every day. Lack of management practical knowledge puts CISOs and CSOs at a disadvantage vis-a-vis other executives in the C-suite. They risk being pigeonholed as "security cops" rather than respected business leaders. Many articles on these subjects published in the press are too incomplete and filled with bad information. And combing through the few high-quality sources that are out there, such as Harvard Business Publishing, can take hundreds of dollars in magazine subscription and book purchase fees and weeks or months of reading time. This book puts all the essential information into your hands through a series of concise chapters authored by an award-winning writer.

Cryptology: Classical and Modern, Second Edition proficiently introduces readers to the fascinating field of cryptology. The book covers classical methods including substitution, transposition, Alberti, Vigenere, and Hill ciphers. It also includes coverage of the Enigma machine, Turing bombe, and Navajo code. Additionally, the book presents modern methods like RSA, ElGamal, and stream ciphers, as well as the Diffie-Hellman key exchange and Advanced Encryption Standard. When possible, the book details methods for breaking both classical and modern methods. The new edition expands upon the material from the first edition which was oriented for students in non-technical fields. At the same time, the second edition supplements this material with new content that serves students in more technical fields as well. Thus, the second edition can be fully utilized by both technical and non-technical students at all levels of study. The authors include a wealth of material for a one-semester cryptology course, and research exercises that can be used for supplemental projects. Hints and answers to selected exercises are found at the end of the book. Features: Requires no prior programming knowledge or background in college-level mathematics Illustrates the importance of cryptology in cultural and historical contexts, including the Enigma machine, Turing bombe, and Navajo code Gives straightforward explanations of the Advanced Encryption Standard, public-key ciphers, and message authentication Describes the implementation and cryptanalysis of classical ciphers, such as substitution, transposition, shift, affine, Alberti, Vigenere, and Hill

Tackling the cybersecurity challenge is a matter of survival for society at large. Cyber attacks are rapidly increasing in sophistication and magnitude-and in their destructive potential. New threats emerge regularly, the last few years having seen a ransomware boom and distributed denial-of-service attacks leveraging the Internet of Things. For organisations, the use of cybersecurity risk management is essential in order to manage these threats. Yet current frameworks have drawbacks which can lead to the suboptimal allocation of cybersecurity resources. Cyber insurance has been touted as part of the solution - based on the idea that insurers can incentivize companies to improve their cybersecurity by offering premium discounts - but cyber insurance levels remain limited. This is because companies have difficulty determining which cyber insurance products to purchase, and insurance companies struggle to accurately assess cyber risk and thus develop cyber insurance products. To deal with these challenges, this volume presents new models for cybersecurity risk management, partly based on the use of cyber insurance. It contains: A set of mathematical models for cybersecurity risk management, including (i) a model to assist companies in determining their optimal budget allocation between security products and cyber insurance and (ii) a model to assist insurers in designing cyber insurance products. The models use adversarial risk analysis to account for the behavior of threat actors (as well as the behavior of companies and insurers). To inform these models, we draw on psychological and behavioural economics studies of decision-making by individuals regarding cybersecurity and cyber insurance. We also draw on organizational decision-making studies involving cybersecurity and cyber insurance. Its theoretical and methodological findings will appeal to researchers across a wide range of cybersecurity-related disciplines including risk and decision analysis, analytics, technology management, actuarial sciences, behavioural sciences, and economics. The practical findings will help cybersecurity professionals and insurers enhance cybersecurity and cyber insurance, thus benefiting society as a whole. This book grew out of a two-year European Union-funded project under Horizons 2020, called CYBECO (Supporting Cyber Insurance from a Behavioral Choice Perspective).

The Ethics of Artificial Intelligence in Education identifies and confronts key ethical issues generated over years of AI research, development, and deployment in learning contexts. Adaptive, automated, and data-driven education systems are increasingly being implemented in universities, schools, and corporate training worldwide, but the ethical consequences of engaging with these technologies remain unexplored. Featuring expert perspectives from inside and outside the AIED scholarly community, this book provides AI researchers, learning scientists, educational technologists, and others with questions, frameworks, guidelines, policies, and regulations to ensure the positive impact of artificial intelligence in learning.

This volume provides the basis for contemporary privacy and social media research and informs global as well as local initiatives to address issues related to social media privacy through research, policymaking, and education. Renowned scholars in the fields of communication, psychology, philosophy, informatics, and law look back on the last decade of privacy research and project how the topic will develop in the next decade. The text begins with an overview of key scholarship in online privacy, expands to focus on influential factors shaping privacy perceptions and behaviors-such as culture, gender, and trust-and continues with specific examinations of concerns around vulnerable populations such as children and older adults. It then looks at how privacy is managed and the implications of interacting with artificial intelligence, concluding by discussing feasible solutions to some of the more pressing questions surrounding online privacy. This handbook will be a valuable resource for advanced students, scholars, and policymakers in the fields of communication studies, digital media studies, psychology, and computer science.

Make sure your students get the most from their online learning experiences Even though nearly every K-12 public school in the United States has broadband Internet access, the Web's vast potential as a teaching and learning tool has still not been realized. Web-based learning opportunities have been expensive, slow to develop, and time-consuming to implement, despite pressure on schools to adopt technology solutions that will cure their educational ills. Web-Based Learning in K-12 Classrooms: Opportunities and Challenges chronicles the up and downs of online learning and offers unique insights into its future, providing a comprehensive, curriculum-wide treatment of K-12 content areas (reading, science, mathematics, social studies), special education, counseling, virtual schools, exemplary schools, implementation issues, and educational Web sites. The Internet represents a powerful, complex set of technologies that offers your students access to unlimited knowledgebut that access doesn't replace the human interactions found in classrooms. Placing a student in front of a computer monitor is a supplement to classroom learning, not a substitute for it. Academics and education professionals address questions surrounding the key issues involved in successfully incorporating the wide range of Web-based learning opportunities (formal courses, demonstrations, simulations, collaborations, searches) into the classroom, including technology, content, and implementation. Web-Based Learning in K-12 Classrooms examines: inquiry-based learning online interaction displaying student work online Internet accessibility for students with disabilities initiating school counselors into e-learning technologies the role of government in virtual schools Web-based schools in California, Virginia, Pennsylvania, Vermont, and Texas a 13-category classification system for online educational resources the ATLAS model for program implementation evaluations of more than 1,000 pieces of online information (articles, research, reports, news, and statistics) and 900 Web applications (tutorials, drills, games, and tests) with evaluation criteria Web-Based Learning in K-12 Classrooms is a vital resource for educators interested in online learning applications across the K-12 curriculum.

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.

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.

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

Absolute clarity is the aim with a new generation of revision guide for the 2020s. This guide has been expertly compiled and edited by successful former teachers of Computer Science, highly experienced examiners and a good dollop of scientific research into what makes revision most effective. Past examinations questions are essential to good preparation, improving understanding and confidence. This guide has combined revision with tips and more practice questions than you could shake a stick at. All the essential ingredients for getting a grade you can be really proud of. Each specification topic has been referenced and distilled into the key points to make in an examination for top marks. Questions on all topics assessing knowledge, application and analysis are all specifically and carefully devised throughout this book.