Colonialism and the Modernist Moment in the Early Novels of Jean Rhys explores the postcolonial significance of Rhys s modernist period work, which depicts an urban scene more varied than that found in other canonical representations of the period. Arguing against the view that Rhys comes into her own as a colonial thinker only in the post-WWII period of her career, this study examines the austere insights gained by Rhys s active cultivation of her fringe status vis-a-vis British social life and artistic circles, where her sharp study of the aporias of marginal lives and the violence of imperial ideology is distilled into an artistic statement positing the outcome of the imperial venture as a state of homelessness across the board, for colonized and metropolitans alike. Bringing to view heretofore overlooked emigre populations, or their children, alongside locals, Rhys s urbanites struggle to construct secure lives not simply as a consequence of commodification, alienation, or voluntary expatriation, but also as a consequence of marginalization and migration. This view of Rhys s early work asserts its vital importance to postcolonial studies, an importance that has been overlooked owing to an over hasty critical consensus that only one of her early novels contains significant colonial content. Yet, as this study demonstrates, proper consideration of colonial elements long considered only incidental illuminates a colonial continuum in Rhys s work from her earliest publications. "

Dealing with the volume, complexity, and diversity of data currently being generated by scientific experiments and simulations often causes scientists to waste productive time. Scientific Data Management: Challenges, Technology, and Deployment describes cutting-edge technologies and solutions for managing and analyzing vast amounts of data, helping scientists focus on their scientific goals.

The book begins with coverage of efficient storage systems, discussing how to write and read large volumes of data without slowing the simulation, analysis, or visualization processes. It then focuses on the efficient data movement and management of storage spaces and explores emerging database systems for scientific data. The book also addresses how to best organize data for analysis purposes, how to effectively conduct searches over large datasets, how to successfully automate multistep scientific process workflows, and how to automatically collect metadata and lineage information.

This book provides a comprehensive understanding of the latest techniques for managing data during scientific exploration processes, from data generation to data analysis. Enhanced by numerous detailed color images, it includes real-world examples of applications drawn from biology, ecology, geology, climatology, and more.

Check out Dr. Shoshani discuss the book during an interview with International Science Grid This Week (iSGTW): http: //www.isgtw.org/?pid=1002259

The need for analytics skills is a source of the burgeoning growth in the number of analytics and decision science programs in higher education developed to feed the need for capable employees in this area. The very size and continuing growth of this need means that there is still space for new program development. Schools wishing to pursue business analytics programs intentionally assess the maturity level of their programs and take steps to close the gap. Teaching Data Analytics: Pedagogy and Program Design is a reference for faculty and administrators seeking direction about adding or enhancing analytics offerings at their institutions. It provides guidance by examining best practices from the perspectives of faculty and practitioners. By emphasizing the connection of data analytics to organizational success, it reviews the position of analytics and decision science programs in higher education, and to review the critical connection between this area of study and career opportunities. The book features: A variety of perspectives ranging from the scholarly theoretical to the practitioner applied An in-depth look into a wide breadth of skills from closely technology-focused to robustly soft human connection skills Resources for existing faculty to acquire and maintain additional analytics-relevant skills that can enrich their current course offerings. Acknowledging the dichotomy between data analytics and data science, this book emphasizes data analytics rather than data science, although the book does touch upon the data science realm. Starting with industry perspectives, the book covers the applied world of data analytics, covering necessary skills and applications, as well as developing compelling visualizations. It then dives into pedagogical and program design approaches in data analytics education and concludes with ideas for program design tactics. This reference is a launching point for discussions about how to connect industry's need for skilled data analysts to higher education's need to design a rigorous curriculum that promotes student critical thinking, communication, and ethical skills. It also provides insight into adding new elements to existing data analytics courses and for taking the next step in adding data analytics offerings, whether it be incorporating additional analytics assignments into existing courses, offering one course designed for undergraduates, or an integrated program designed for graduate students.

Organize, plan, and build an exceptional data analytics team within your organization In Minding the Machines: Building and Leading Data Science and Analytics Teams, AI and analytics strategy expert Jeremy Adamson delivers an accessible and insightful roadmap to structuring and leading a successful analytics team. The book explores the tasks, strategies, methods, and frameworks necessary for an organization beginning their first foray into the analytics space or one that is rebooting its team for the umpteenth time in search of success. In this book, you'll discover: A focus on the three pillars of strategy, process, and people and their role in the iterative and ongoing effort of building an analytics team Repeated emphasis on three guiding principles followed by successful analytics teams: start early, go slow, and fully commit The importance of creating clear goals and objectives when creating a new analytics unit in an organization Perfect for executives, managers, team leads, and other business leaders tasked with structuring and leading a successful analytics team, Minding the Machines is also an indispensable resource for data scientists and analysts who seek to better understand how their individual efforts fit into their team's overall results.

This book addresses the issues of information, digital and intellectual technologies in economics and management. The International Scientific and Practical Conference "Digital and Information Technologies in Economics and Management" (DITEM2021) was held on November 2, 2021, on the Microsoft Teams platform due to COVID-19. A distinctive feature of the book is that it presented reports of authors from Italy, South Korea, Poland, Armenia, Republic of Belarus and the Russian Federation. Researchers from different countries presented the process of transition of economic activities to the information and digital path of development and presented the main directions and developments that can improve the efficiency and development of the economy and management. The book may be useful to state and regional authorities, international and supranational organizations, the scientific and professional community.

* Targests readers with a background in programming, interested in an introduction/refresher in statistical hypothesis testing * Uses Python throughout * Provides the reader with the opportunity of using the book whenever needed rather than following a sequential path.

The Green and Virtual Data Center sets aside the political aspects of what is or is not considered green to instead focus on the opportunities for organizations that want to sustain environmentally-friendly economical growth. If you are willing to believe that IT infrastructure resources deployed in a highly virtualized manner can be combined with other technologies to achieve simplified and cost-effective delivery of services in a green, profitable manner, this book is for you.

Savvy industry veteran Greg Schulz provides real-world insight, addressing best practices, server, software, storage, networking, and facilities issues concerning any current or next-generation virtual data center that relies on underlying physical infrastructures. Coverage includes:

• Energy and data footprint reduction
• Cloud-based storage and computing
• Intelligent and adaptive power management
• Server, storage, and networking virtualization
• Tiered servers and storage, network, and data centers
• Energy avoidance and energy efficiency

Many current and emerging technologies can enable a green and efficient virtual data center to support and sustain business growth with a reasonable return on investment. This book presents virtually all critical IT technologies and techniques to discuss the interdependencies that need to be supported to enable a dynamic, energy-efficient, economical, and environmentally-friendly green IT data center. This is a path that every organization must ultimately follow.

Take a tour of the Green and Virtual Data Center website.

CRC Press is pleased to announce that The Green and Virtual Data Center has been added to Intel Corporation's Recommended Reading List. Intel's Recommended Reading program provides technical professionals a simple and handy reference list of what to read to stay abreast of new technologies. Dozens of industry technologists, corporate fellows, and engineers have helped by suggesting books and reviewing the list. This is the most comprehensive reading list available for professional computer developers.

An effective DBA is an efficient DBA. And if you work with SQL Server, dbatools is a lifesaver. With over 500 commands, this free and open source PowerShell module has the horsepower to automate just about every task you can imagine-and then some! Learn dbatools in a Month of Lunches teaches you techniques that will make you more effective-and efficient-than you ever thought possible. Learn dbatools in a Month of Lunches is a practical hands-on guide to automating SQL Server with PowerShell and the awesome dbatools module. You'll master techniques you can immediately put into practice, from daily duties like backups and restores right through to performing security audits. Stabilize and standardize your SQL server environment, and simplify your tasks by building automation, alerting, and reporting with this powerful tool. Each lesson delivers another skill that you can use to speed through your core tasks as a SQL Server DBA! About the Technology Want to automate tasks for thousands of SQL servers at once? Want to migrate an entire SQL server using just the command line? dbatools can do all that-and more. A free and open source PowerShell module, dbatools offers over 500 commands for automating SQL Server from the command line. Boasting advanced options unavailable in official tools, dbatools makes it easy to automate tasks including mass exports for simplified disaster recovery, tempdb configuration, and improving an instance's security posture.

This book covers the following main topics: A) information and knowledge management; B) organizational models and information systems; C) software and systems modeling; D) software systems, architectures, applications and tools; E) multimedia systems and applications; F) computer networks, mobility and pervasive systems; G) intelligent and decision support systems; H) big data analytics and applications; I) human-computer interaction; J) ethics, computers and security; K) health informatics; L) information technologies in education; M) information technologies in radio communications; N) technologies for biomedical applications. This book is composed by a selection of articles from The 2022 World Conference on Information Systems and Technologies (WorldCIST'22), held between April 12 and 14, in Budva, Montenegro. WorldCIST is a global forum for researchers and practitioners to present and discuss recent results and innovations, current trends, professional experiences, and challenges of modern information systems and technologies research, together with their technological development and applications.

Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges uniquely posed by this problem. Key Features: Introduces basic elements of health care data, especially for administrative claims data, including disease code, procedure codes, and drug codes Provides tailored supervised and unsupervised machine learning approaches for understanding and predicting the high utilizers Presents descriptive data driven methods for the high utilizer population Identifies a best-fitting linear and tree-based regression model to account for patients' acute and chronic condition loads and demographic characteristics

Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decision trees, kNN, splines, Bayesian inference, and importance sampling. More importantly, the data science methods are described in the context of wind energy applications, with specific wind energy examples and case studies. Please also visit the author's book site at https://aml.engr.tamu.edu/book-dswe. Features Provides an integral treatment of data science methods and wind energy applications Includes specific demonstration of particular data science methods and their use in the context of addressing wind energy needs Presents real data, case studies and computer codes from wind energy research and industrial practice Covers material based on the author's ten plus years of academic research and insights

Open Access Data is emerging as a source for cutting edge scholarship. This concise book provides guidance from generating a research idea to publishing results. Both young researchers and well-established scholars can use this book to upgrade their skills with respect to emerging data sources, analysis, and even post-publishing promotion. At the end of each chapter, a tutorial simulates a real example, allowing readers to apply what they learned about accessing open data, and analyzing this data to reach the results. This book can be of use by established researchers analyzing data, publishing, and actively promoting ongoing and research. Key selling features: Describes the steps, from A-Z, for doing open data research Includes interactive tutorials following each chapter Provides guidelines for readers so that they can use their own accessed open data Reviews recent software and websites promoting and enabling open data research Supplements websites which update recent open data sources

Making obscure knowledge about matrix decompositions widely available, Understanding Complex Datasets: Data Mining with Matrix Decompositions discusses the most common matrix decompositions and shows how they can be used to analyze large datasets in a broad range of application areas. Without having to understand every mathematical detail, the book helps you determine which matrix is appropriate for your dataset and what the results mean. Explaining the effectiveness of matrices as data analysis tools, the book illustrates the ability of matrix decompositions to provide more powerful analyses and to produce cleaner data than more mainstream techniques. The author explores the deep connections between matrix decompositions and structures within graphs, relating the PageRank algorithm of Google's search engine to singular value decomposition. He also covers dimensionality reduction, collaborative filtering, clustering, and spectral analysis. With numerous figures and examples, the book shows how matrix decompositions can be used to find documents on the Internet, look for deeply buried mineral deposits without drilling, explore the structure of proteins, detect suspicious emails or cell phone calls, and more. Concentrating on data mining mechanics and applications, this resource helps you model large, complex datasets and investigate connections between standard data mining techniques and matrix decompositions.

Computing and database management has shifted from cottage industry-style methods - the small independent researcher keeping records for a particular project - to state-of-the-art file storage systems, presentation, and distribution over the Internet. New and emerging techniques for recognition, compilation, and data management have made managing data a discipline in its own right. Covering all aspects of this data management, Biodiversity Databases: Techniques, Politics, and Applications brings together input from social scientists, programmers, database designers, and information specialists to delineate the political setting and give institutions platforms for the dissemination of taxonomic information.

A practical and logical guide to complex issues, the book explores the changes and challenges of the information age. It discusses projects developed to provide better access to all available biodiversity information. The chapters make the case for the need for representation of concepts in taxonomic databases. They explore issues involved in connecting databases with different user interfaces, the technical demands of linking databases that are not entirely uniform in structure, and the problems of user access and the control of data quality. The book highlights different approaches to addressing concerns associated with the taxonomic impediment and the low reproducibility of taxonomic data. It provides an in-depth examination of the challenge of making taxonomic information more widely available to users in the wider scientific community, in government, and the general population.

Learning analytics is one of the most important research issues in the field of educational technology. By analyzing logs and records in educational databases and systems, it can provide useful information to teachers, learners, and decision makers - information which they can use to improve teaching strategies, learning performances, and educational policies. However, it is a great challenge for most researchers to efficiently analyze educational data in a meaningful way. This book presents various learning analytics approaches and applications, including the process of determining the coding scheme, analyzing the collected data, and interpreting the findings. This book was originally published as a special issue of Interactive Learning Environments.

Examines the synergy between knowledge management, business intelligence, and content management Refers to detailed information about available toolsets Offers numerous tables and figures that enable quick understanding of the concepts discussed Includes 13 appendices that contain essential guides, templates, checklists, and more Knowledge management (KM) is the identification and analysis of available and required knowledge, and the subsequent planning and control of actions, to develop "knowledge assets" that enable businesses to generate profits and improve their competitive positions. This volume provides the framework for the strategic use of the information intelligence processes - business intelligence, content management, and knowledge management. In nine detailed chapters, the author explains every facet of these three subjects, enabling you to understand these sophisticated business concepts within the framework of information technology. Knowledge Management, Business Intelligence, and Content Management: The IT Practitioner's Guide discusses creation, protection, development, sharing, and management of information and intellectual assets through the use of business intelligence and other knowledge sharing and analytical techniques. About the Author Jessica Keyes is president of New Art Technologies, Inc., a high-technology and management consultancy, and is also founding partner of Manhattan Technology Group. Often a keynote speaker on the topics of competitive strategy, productivity, and quality, she is a founding board of directors member of the New York Software Industry Association, and has recently completed a 2-year term on the Mayor of New York City's Small Business Advisory Council. A noted columnist and correspondent, Keyes is the author of 19 books, including Auerbach Publications' Software Engineering Handbook, Software Configuration Management, and Implementing the IT Balanced Scorecard.

Open Source Data Warehousing and Business Intelligence is an all-in-one reference for developing open source based data warehousing (DW) and business intelligence (BI) solutions that are business-centric, cross-customer viable, cross-functional, cross-technology based, and enterprise-wide. Considering the entire lifecycle of an open source DW & BI implementation, its comprehensive coverage spans from basic concepts all the way through to customization. Highlighting the key differences between open source and vendor DW and BI technologies, the book identifies end-to-end solutions that are scalable, high performance, and stable. It illustrates the practical aspects of implementing and using open source DW and BI technologies to supply you with valuable on-the-project experience that can help you improve implementation and productivity. Emphasizing analysis, design, and programming, the text explains best-fit solutions as well as how to maximize ROI. Coverage includes data warehouse design, real-time processing, data integration, presentation services, and real-time reporting. With a focus on real-world applications, the author devotes an entire section to powerful implementation best practices that can help you build customer confidence while saving valuable time, effort, and resources.

"Social Data Analytics" is the first practical guide for professionals who want to employ social data for analytics and business intelligence (BI). This book provides a comprehensive overview of the technologies and platforms and shows you how to access and analyze the data. You'll explore the five major types of social data and learn from cases and platform examples to help you make the most of sentiment, behavioral, social graph, location, and rich media data. A four-step approach to the social BI process will help you access, evaluate, collaborate, and share social data with ease.

You'll learn everything you need to know to monitor social media and get an overview of the leading vendors in a crowded space of BI applications. By the end of this book, you will be well prepared for your organization s next social data analytics project.
Provides foundational understanding of new and emerging technologies-social data, collaboration, big data, advanced analyticsIncludes case studies and practical examples of success and failuresWill prepare you to lead projects and advance initiatives that will benefit you and your organization"

Today's database professionals must understand how to apply database systems to business processes and how to develop database systems for both business intelligence and Web-based applications. Database Development and Management explains all aspects of database design, access, implementation, application development, and management, as well as data analysis for business intelligence. This self-contained text gives students hands-on projects required for professionally developing and managing databases. It provides detailed instruction via an easy-to-follow, step-by-step case-based approach. Following an introduction to database components, the book uses case studies to illustrate the modeling process, covers table structures and normalization, and analyzes the transformation of a data model to a relational database. It explains the use of SQL in managing database objects and in querying databases, then discusses Transact-SQL and the views, indexes, and cursors that bridge databases and their applications. The book examines three major data-accessing techniques, and then shows how to develop sophisticated applications based upon the material included in previous chapters. It explores the use of databases in network environments, and details the multiple tasks handled by database administrators (DBAs). The text also discusses the OnLine Analytical Processing (OLAP) system, data warehousing, and other analysis tools that support business intelligence and decision making. It concludes with a review of data mining.

The rapid success of for-profit colleges and universities (FPCUs) only recently has caught the attention of scholars in academe. The continuing expansion of the proprietary higher education sector has lead to fundamental questions regarding the purpose and function of FPCUs. As new technologies continue to emerge, education is becoming of increasing import to employees seeking to upgrade their skills and employers in search of individuals who possess the necessary expertise and training to help their organizations succeed. For-profit institutions challenge traditional notions of the academy--such as shared governance, tenure, and academic freedom--by utilizing administrative practices that more aptly apply to the corporate arena. Moreover, they exclusively employ non-tenure-track faculty members. This study provides a framework for understanding faculty roles and responsibilities at for profit colleges and universities. The author employs a series of in-depth interviews with 53 faculty members, from four for-profit institutions. Utilizing a cultural framework, the study explores the attitudes, beliefs, and perceptions of faculty work with particular consideration given to faculty member's non-tenure-track status, participation in decision-making activities, and academic freedom. The study examines the culture of the faculty work by asking how the profit-seeking nature of the institution affects their efforts inside and outside of the classroom. The author introduces a new component to the cultural framework that illustrates how the close ties between FPCUs and business and industry affect the nature of faculty work.

This book presents different topics related to innovation, complexity, uncertainty, modeling and simulation, fuzzy logic, decision-making, aggregation operators, business and economic applications, among others. The chapters are the results of research presented at the International Workshop "Innovation, Complexity and Uncertainty in Economics and Business", held in Barcelona, in November 2019, by The Ibero-American Network for Competitiveness, Innovation and Development (REDCID in Spanish) and the Royal Academy of Economic and Financial Sciences (RACEF in Spanish). These papers are useful for junior and senior researchers in the area of economics and business.

Our world is rapidly becoming an Internet-based world, with tens of millions of homes, millions of businesses, and within a short period of time, possibly hundreds of millions of mobile professionals accessing the literal mother of all networks. One of the key problems affecting many Internet users, ranging from individual professionals to networking managers and administrators, is a lack of knowledge concerning Internet Protocol (IP) addressing. A detailed reference guide, The ABCs of IP Addressing provides you with the detailed information about the key challenges of IP addressing and designing networks that work efficiently. It takes you from the basics of the binary numbering system to advanced topics in subnetting, network address translation, and configuring workstations, servers and routers. The book contains network tools that prepare you for testing and troubleshooting and highlights the need for techniques that conserve the use of IP addressing as well as the creation of a next generation IP addressing structure. While structured on a chapter by chapter basis, wherever possible each chapter was written to be independent, making the book convenient and easy to use in a hectic work environment. While you may find it possible to design a network or configure a workstation to operate without a detailed knowledge of IP addressing, the end results are not very efficient. And in the quickly changing global business environment, inefficiency wastes your time and money, both valuable resources for gaining and maintaining the competitive edge. With The ABCs of IP Addressing you get the comprehensive coverage of applications and protocols that help you do your job faster and more effectively.

Developments in Geographic Information Technology have raised the expectations of users. A static map is no longer enough; there is now demand for a dynamic representation. Time is of great importance when operating on real world geographical phenomena, especially when these are dynamic. Researchers in the field of Temporal Geographical Information Systems (TGIS) have been developing methods of incorporating time into geographical information systems. Spatio-temporal analysis embodies spatial modelling, spatio-temporal modelling and spatial reasoning and data mining. Advances in Spatio-Temporal Analysis contributes to the field of spatio-temporal analysis, presenting innovative ideas and examples that reflect current progress and achievements.

Most events and activities in today's world are ordinarily captured using photos, videos and other multimedia content. Such content has some limitation of storing data and fetching them effectively. Three-dimensional continuous PC animation is the most proper media to simulate these occasions and activities. This book focuses on futuristic trends and innovations in multimedia systems using big data, IoT and cloud technologies. The authors present recent advancements in multimedia systems as they relate to various application areas such as healthcare services and agriculture-related industries. The authors also discuss human-machine interface design, graphics modelling, rendering/animation, image/graphics techniques/systems and visualization. They then go on to explore multimedia content adaptation for interoperable delivery. Finally, the book covers cultural heritage, philosophical/ethical/societal/international issues, standards-related virtual technology and multimedia uses. This book is intended for computer engineers and computer scientists developing applications for multimedia and virtual reality and professionals working in object design and visualization, transformation, modelling and animation of the real world. Features: Focuses on futuristic trends and innovations in multimedia systems using big data, IoT and cloud technologies Offers opportunity for state-of-the-art approaches, methodologies and systems, and innovative use of multimedia-based emerging technology services in different application areas Discusses human-machine interface design, graphics modelling, rendering/animation, image/graphics techniques/systems and visualization Covers cultural heritage, philosophical/ethical/societal/international issues, standards-related virtual technology and multimedia uses Explores multimedia content adaptation for interoperable delivery and recent advancements in multimedia systems in context to various application areas such as healthcare services and agriculture-related fields Rajeev Tiwari is a Senior Associate Professor in the School of Computer Science at the University of Petroleum and Energy Studies, Dehradun, India. Neelam Duhan is an Associate Professor in the Department of Computer Engineering at J. C. Bose University of Science and Technology, YMCA, Faridabad, India. Mamta Mittal has 18 years of teaching experience, and her research areas include data mining, big data, machine learning, soft computing and data structure. Abhineet Anand is a Professor in the Computer Science and Engineering Department at Chitkara University, Punjab, India. Muhammad Attique Khan is a lecturer of the Computer Science Department at HITEC University, Taxila, Pakistan.

The true pioneers in electronic publishing put their bibliographic databases on tape and online in the 1960s. Nearly all of them had long experience with compiling information for distribution in printed form and a strong market connection. As a result of Soviet advances in science and space technology, American government support for information science and academic libraries flowed freely for a little over a decade, making possible tremendous advances in technology, in retrieval techniques and in sophisticated coverage. Advances in information technology and market conditions have encouraged many more participants to underwrite the development of databases that now extend into the arts, social sciences, business, and popular interests. These essays show how production statistics accompanied by statements of editorial coverage provide a fairly accurate reflection of output of many of the major disciplinary bibliographic databases. The urgent priority of information resources in the 1960s has encouraged comprehensive servicing of the formal research literature as published in journals and monographs. Authors have counted subject words, languages, origins, types of publication, and so on over several decades. This volume also includes articles on some databases that are not strictly bibliographic, such as the CMG database of college courses, which illuminates some of the changes in college textbook publishing. Information seekers will find the many tables of practical use, as guidance to what and how much may be found within each database. Analysts of publishing, of science policy, and of higher education will find information relevant to expenditures, human resources, and other indicators of education, research, and technology activity.