Computers

Unlock the power of Python in ArcGIS® Pro with this definitive, easy-to-follow guide designed for users with limited programming or scripting experience.

Get started learning to write Python scripts to automate tasks in ArcGIS Pro with Python Scripting for ArcGIS Pro. This book begins with the fundamentals of Python programming and then dives into how to write useful Python scripts that work with spatial data in ArcGIS Pro. You’ll learn how to use geoprocessing tools; describe, create, and update data; and execute specialized tasks. With step-by-step instructions, practical examples, and insightful guidance, you’ll be able to write scripts that will automate and improve your ArcGIS Pro workflows.

This third edition has been revised for ArcGIS Pro 3.2 and Python 3.9.18 and includes updated images; a fully updated chapter 2; and expanded chapters 4, 8, 9, and 10.

The key topics you will learn include:

• Python fundamentals
• Setting up a Python editor
• Automating geoprocessing tasks using ArcPy™
• Exploring and manipulating spatial and tabular data
• Working with geometries using cursors
• Working with rasters and map algebra
• Map scripting
• Debugging and error handling

Helpful points to remember, key terms, and review questions are included at the end of each chapter to reinforce your understanding of Python. Corresponding data and tutorials are available online.

Whether you’re new to Python or already have some experience, Python Scripting for ArcGIS Pro is the go-to resource for learning the versatility of Python coding to solve problems and enhance productivity and efficiency in ArcGIS Pro.

The myth of good AI offers a bold new approach to understanding artificial intelligence and its implications for human security. Dismantling the ‘good AI’ narrative pedalled by tech giants, the book exposes the full extent of AI’s nefarious impact on society.
Drawing on a wide range of literature, the book provides a gripping synthesis of debates in philosophy, medicine, media, psychology, international affairs, economics and politics. It charts the full spectrum of AI-related themes and explores what implications AI has for our future, while equipping the reader with strategies for survival.

As the field of Artificial Intelligence continues to evolve, Generative AI has emerged as a powerful tool in the realm of software development. AI models capable of generating high-quality, human-like code can significantly accelerate the software development process, assist in troubleshooting, and even automate tasks traditionally performed by human developers.

Generative AI models, such as OpenAI, DeepMind, and others, are already demonstrating the ability to write functional code, generate documentation, and assist in code review. These models are not only reducing the time it takes to develop applications but are also making software development more accessible to a broader audience, including non-technical users.

This book is intended to serve as a comprehensive guide for developers, technology leaders, and anyone interested in understanding how to leverage Generative AI in software development. It will cover the underlying technology behind these models, practical use cases, integration into development workflows, and ethical considerations. Additionally, it explores how the democratization of coding through AI will shape the future of software engineering.

By providing insights into real-world applications and best practices for integrating generative AI into the software lifecycle, this book empowers readers to stay ahead of the technological curve in a rapidly evolving industry.

There are many myths about Artificial Intelligence (AI) relating to what it is and what it can and cannot do. The people making decisions on AI projects are often not technologically savvy and unable to find easy answers. The spending on and the returns from AI projects are not necessarily straightforward. Part of the reason for this is the lack of understanding of the impact of critical decision criteria. AI touches on many ethical concepts - data privacy, validity, and, more importantly, its potential misuse. AI often replaces human decision-making, as managers do not clearly understand the implications of those choices. This book provides an easy and accessible guide for practitioners without a technological background to understand AI. It guides the reader through the fundamental issues confronting decision-makers. It offers advice on ‘how to ask relevant questions’ using the 15 decision scales. There is currently no comparable book on the market that acts as a pocketbook management reference guide for the AI layman.

The general theme of this book is to present the applications of artificial intelligence (AI) in test development. In particular, this book includes research and successful examples of using AI technology in automated item generation, automated test assembly, automated scoring, and computerized adaptive testing. By utilizing artificial intelligence, the efficiency of item development, test form construction, test delivery, and scoring could be dramatically increased.

Chapters on automated item generation offer different perspectives related to generating a large number of items with controlled psychometric properties including the latest development of using machine learning methods. Automated scoring is illustrated for different types of assessments such as speaking and writing from both methodological aspects and practical considerations. Further, automated test assembly is elaborated for the conventional linear tests from both classical test theory and item response theory perspectives. Item pool design and assembly for the linear-on-the-fly tests elaborates more complications in practice when test security is a big concern. Finally, several chapters focus on computerized adaptive testing (CAT) at either item or module levels. CAT is further illustrated as an effective approach to increasing test-takers’ engagement in testing.

In summary, the book includes both theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to automate the process of test development. While some of these automation processes have become common practices such as automated test assembly, automated scoring, and computerized adaptive testing, some others such as automated item generation calls for more research and exploration. When new AI methods are emerging and evolving, it is expected that researchers can expand and improve the methods for automating different steps in test development to enhance the automation features and practitioners can adopt quality automation procedures to improve assessment practices.

The book provides best practices from online educators who are engaged in online teaching and program development in Christian higher education. It also explores the distinct aspects of teaching and developing online courses and programs from a Christian perspective and within Christian higher education institutions. As such it is can serve as a ready resource for academic administrators and professors, novices and veterans at online program development and instruction.

Feeling guilty about not networking enough? Stop! You can learn how to network effectively without attending networking events, collecting business cards, or getting a lot of LinkedIn followers. How? By learning how to Connect the Dots.

Written by Inga Carboni, Ph.D., Connect the Dots is a fun, fast-paced, and fact-based book for working professionals seeking to take the next step in their careers. The truth is that networking is not about managing impressions or projecting your personal brand. Effective networkers build, nurture, and leverage relationships, real relationships built on genuine connection. When done correctly, networking isn’t sleazy or manipulative. Instead, it’s empowering, for you, for all the people you know, and for all the people they know.

Connect the Dots: How to Build, Nurture, and Leverage Your Network to Achieve Your Personal and Professional Goals offers a combination of personal stories, business anecdotes, self-assessments, exercises, and concrete guidelines grounded in the latest scientific research. Connect the Dots focuses on developing your personal power and leadership skills by creating effective networks and networking effectively. This book is designed to benefit everyone, from young professionals to senior managers to human resource professionals to C-suite executives.

Unleash the power of your network by learning how to connect the dots to make your network work for you.

The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner.

Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted form this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups.

Data mining applications are seen in finance (banking, brokerage, insurance), marketing (customer relationships, retailing, logistics, travel), as well as in manufacturing, health care, fraud detection, home-land security, and law enforcement.

The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner.

Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups.

Data mining applications are in finance (banking, brokerage, and insurance), marketing (customer relationships, retailing, logistics, and travel), as well as in manufacturing, health care, fraud detection, homeland security, and law enforcement.

Crossing the Bridge of the Digital Divide: A Walk with Global Leaders explores the combined effect of the rapid growth of information as an increasingly fragmented information base, a large component of which is available only to people with money and/or acceptable institutional affiliations. In the recent past, the outcome of these challenges has been characterized as the 'digital divide' between the information 'haves' and 'have nots' along racial and socio economic lines that seem to widen as time passes. To address the issues of digital equity and digital inequality in an effort to bridge the digital divide, educational scholars, researchers and practitioners are in positions to ensure equitable opportunities are made available for people of all ages, races, ability, sexual orientation, and ethnicity in support of social justice for bridging the digital divide. The digital divide addresses issues concerning equal opportunity, equity and access that have an effect on the development of marginalized and otherwise disenfranchised populations within and across systems nationally and internationally.

The contributing authors- representing Unites States, Canada, South Africa, New Zealand, and the UK - posit that education institutions can serve as the bridge to close the digital divide for students who do not have access to information technology in their homes. At a time when more computers are made available in schools than ever before, the digital divide continues to widen and fewer people in the lowest SES groups are given the opportunity to join the world of computer technology and the internet. As a result, the influence of leadership activity on institutional racism, gender discrimination, inequality of opportunity, inequity of educational processes, digital exclusion, and justice have gained currency and attention.

The contributing national and international authors examine the digital divide in terms of social justice leadership, equity and access. It is within this context that the authors offer discussions from a lens of their choice, i.e. conceptual, review of literature, epistemological, etc. By adopting an educational approach to bridging the digital divide, researchers and practitioners can connect and extend long established lines of conceptual and empirical inquiry aimed at improving organizational practices and thereby gain insights that might be otherwise overlooked, or assumed. This holds great promise for generating, refining, and testing theories of leadership for equity and access, and helps strengthen already vibrant lines of inquiry on social justice.

Virtual Worlds are being increasingly used in business and education. With each day more people are venturing into computer generated online persistent worlds such as Second Life for increasingly diverse reasons such as commerce, education, research, and entertainment. This book explores the emerging ethical issues associated with these novel environments for human interaction and cutting-edge approaches to these new ethical problems. This volume’s goal is to put forward a number of these virtual world ethical issues of which research is only commencing. The developing literature specifically regarding virtual world ethics is a recent phenomenon. Research based on the phenomenon of virtual world life has only been developing in the past four years. This volume introduces pathbreaking work in a field which is only just beginning to take shape. It is ideal as both as a library reference and a supplementary text in upper-division courses focused on the issues of applied ethics and new media. It is unique in being one of the first volumes specifically addressed to ethical problems of the “metaverse”.

This volume includes articles from authors from around the world exploring topics such as: employing rationalist and casuistic approaches to the controversial topic of “virtual rape” yield an increased understanding of how virtual worlds ought to be designed, the relationship between the ethical and legal dimensions of virtual world users’ participation in “paratexts”, utilitarian consideration of harm and freedom in the case of virtual pedophilia, norms of research ethics in virtual worlds, the ethical implications of employing virtual worlds as tools for medical education and experimenting with healthcare services, the ethics of the collective action of virtual world communities, consideration of the virtue and potential of cosmopolitanism in virtual worlds, Deleuzian ethical approaches to the experience of the disabled in virtual worlds, the ethics of virtual world design, and the ethical implications of the “illusion of reality” presented by virtual worlds.

The general theme of this book is to present innovative psychometric modeling and methods. In particular, this book includes research and successful examples of modeling techniques for new data sources from digital assessments, such as eye-tracking data, hint uses, and process data from game-based assessments. In addition, innovative psychometric modeling approaches, such as graphical models, item tree models, network analysis, and cognitive diagnostic models, are included.

Chapters 1, 2, 4 and 6 are about psychometric models and methods for learning analytics. The first two chapters focus on advanced cognitive diagnostic models for tracking learning and the improvement of attribute classification accuracy. Chapter 4 demonstrates the use of network analysis for learning analytics. Chapter 6 introduces the conjunctive root causes model for the understanding of prerequisite skills in learning. Chapters 3, 5, 8, 9 are about innovative psychometric techniques to model process data. Specifically, Chapters 3 and 5 illustrate the usage of generalized linear mixed effect models and item tree models to analyze eye-tracking data. Chapter 8 discusses the modeling approach of hint uses and response accuracy in learning environment. Chapter 9 demonstrates the identification of observable outcomes in the game-based assessments. Chapters 7 and 10 introduce innovative latent variable modeling approaches, including the graphical and generalized linear model approach and the dynamic modeling approach.

In summary, the book includes theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to model and analyze multiple data sources from digital assessments. When computer-based assessments are emerging and evolving, it is important that researchers can expand and improve the methods for modeling and analyzing new data sources. This book provides a useful resource to researchers who are interested in the development of psychometric methods to solve issues in this digital assessment age.

As sensors spread across almost every industry, the internet of things is going to trigger a massive influx of big data. We delve into where IoT will have the biggest impact and what it means for the future of big data analytics. Internet of Things is changing the face of different sectors such as manufacturing, health-care, business, education etc. by completely redefining the way people, devices, and apps connect and interact with each other in the eco system. From personal fitness and wellness sensors, implantable devices to surgical robots – IoT is bringing in new tools and efficiencies in the ecosystem resulting in more integrated healthcare. Application of computational intelligence techniques is today considered as a key success factor to solve the growing scale and complexity of problems in the field of health care systems, agriculture, e-commerce etc.

The convergence of Computational intelligence, Big Data and IoT provides new opportunities and revolutionize business in huge way. This book will support industry and governmental agencies to facilitate and make sense of myriad connected devices in coming decade. This book offers the recent advancements in Computational Intelligence, IoT and Big Data Analytics.

• Development of models and algorithms for employing IoT based facilities in healthcare, industry, agriculture, e- commerce, manufacturing, business etc.
• Methods for collection, management retrieval and processing of Big Data in various domains.
• Provides taxonomy of challenges, issues and research directions in applications of computational intelligence techniques in different domains

With the exponential increase of digital assessment, different types of data in addition to item responses become available in the measurement process. One of the salient features in digital assessment is that process data can be easily collected. This non-conventional structured or unstructured data source may bring new perspectives to better understand the assessment products or accuracy and the process how an item product was attained. The analysis of the conventional and non-conventional assessment data calls for more methodology other than the latent trait modeling.

Natural language processing (NLP) methods and machine learning algorithms have been successfully applied in automated scoring. It has been explored in providing diagnostic feedback to test-takers in writing assessment. Recently, machine learning algorithms have been explored for cheating detection and cognitive diagnosis. When the measurement field promote the use of assessment data to provide feedback to improve teaching and learning, it is the right time to explore new methodology and explore the value added from other data sources. This book presents the use cases of machine learning and NLP in improving the assessment theory and practices in high-stakes summative assessment, learning, and instruction. More specifically, experts from the field addressed the topics related to automated item generations, automated scoring, automated feedback in writing, explainability of automated scoring, equating, cheating and alarming response detection, adaptive testing, and applications in science assessment. This book demonstrates the utility of machine learning and NLP in assessment design and psychometric analysis.

Computer science has emerged as a key driver of innovation in the 21st century. Yet preparing teachers to teach computer science or integrate computer science content into K-12 curricula remains an enormous challenge. Recent policy reports have suggested the need to prepare future teachers to teach computer science through pre-service teacher education programs. In order to prepare a generation of teachers who are capable of delivering computer science to students, however, the field must identify research-based examples, pedagogical strategies, and policies that can facilitate changes in teacher knowledge and practices.

The purpose of this book is to provide examples that could help guide the design and delivery of effective teacher preparation on the teaching of computer science.

This book identifies promising pathways, pedagogical strategies, and policies that will help teacher education faculty and pre-service teachers infuse computer science content into their curricula as well as teach stand-alone computing courses. Specifically, the book focuses on pedagogical practices for developing and assessing pre-service teacher knowledge of computer science, course design models for pre-service teachers, and discussion of policies that can support the teaching of computer science. The primary audience of the book is students and faculty in educational technology, educational or cognitive psychology, learning theory, teacher education, curriculum and instruction, computer science, instructional systems, and learning sciences.

This book will provide a comprehensive overview of business analytics, for those who have either a technical background (quantitative methods) or a practitioner business background. Business analytics, in the context of the 4th Industrial Revolution, is the “new normal” for businesses that operate in this digital age. This book provides a comprehensive primer and overview of the field (and related fields such as Business Intelligence and Data Science). It will discuss the field as it applies to financial institutions, with some minor departures to other industries. Readers will gain understanding and insight into the field of data science, including traditional as well as emerging techniques. Further, many chapters are dedicated to the establishment of a data-driven team – from executive buy-in and corporate governance to managing and quantifying the return of data-driven projects.

Computer science is increasingly becoming an essential 21st century skill. As school systems around the world recognize the importance of computer science, demand for teachers who have the knowledge and skills to deliver computer science instruction is rapidly growing. Yet a number of recent studies indicate that teachers report low confidence and limited understanding of computer science, frequently confusing basic computer literacy skills with computer science. This is true for both teachers at the K-8 level as well as secondary education teachers who frequently transition to computer science from other content areas, such as mathematics. As computer science is not yet included in most teacher preparation programs, professional development is a critical step in efforts to prepare in-service teachers to deliver high-quality computer science instruction. To date, however, research on best practices in computer science professional development has been severely lacking in the literature, making it difficult for researchers and practitioners alike to examine effective in-service preparation models.

This book provide examples of professional development approaches that help teachers integrate aspects of computing in existing curricula at the K-8 level or deliver stand-alone computer science courses at the secondary school level. Further, this book identifies computational competencies for teachers, promising pedagogical strategies that advance teacher learning, as well as alternative pathways for ongoing learning including microcredentials. The primary audience of the book is graduate students and faculty in educational technology, educational or cognitive psychology, learning theory, curriculum and instruction, computer science, instructional systems and learning sciences. Additionally, the book will serve as a valuable addition to education practitioners and curriculum developers as well as policy makers looking to increase the number of teachers who are prepared to deliver computing education.

Das REXX-Lexikon behandelt sämtliche Begriffe, Anweisungen und Funktionen, die für die Betriebssysteme PC-DOS, OS/2 und MVS/TSO von Bedeutung sind. Die Stichworte, die sich auf den "Grundwortschatz" von REXX beziehen, sind darüberhinaus auch für alle anderen Betriebssysteme geeignet (OS/400, UNIX, VM/CMS, VSE/ESA, Windows).