* Centers the experiences of designers at every stage of their careers and development. * Defines and explains the idea of professional identity for designers across contexts. * Concludes segments with specific takeaways, reflection activities, and quotes from real-world designers.

By the end of this book, the reader will understand: the difficulties of finding a needle in a haystack; creative solutions to address the problem; unique ways of engineering features and solving the problem of the lack of data (e.g. synthetic data). Additionally, the reader will be able to: avoid mistakes resulting from a lack of understanding; search for appropriate methods of feature engineering; locate the relevant technological solutions within the general context of decision-making.

Unique selling point: Focuses solely on entity-relationship model diagramming and design Core audience: Undergraduate CS students and professionals Place in the market: Undergraduate textbook

Helps readers to transition from traditional statistics to modern data science Reviews the pros and cons of open source and commercial software packages, and their proper applications in specific situations. Explores data using dynamic methods rather than counting on dichotomous thinking. Considers alternate models using ensemble models and model comparison rather than fixing a preconceived hypothesis/model on a single method. Shows how to find the hidden pattern in the data by dynamic visualization rather than over-relying on numeric results.

Unique selling point: Focuses solely on entity-relationship model diagramming and design Core audience: Undergraduate CS students and professionals Place in the market: Undergraduate textbook

Machine Learning, Cyber Security, and Blockchain in Smart Environment: Application and Challenges provides far-reaching insights into the recent techniques forming the backbone of smart environments, and addresses the vulnerabilities that give rise to the challenges in real-word implementation. The book focuses on the benefits related to the emerging applications such as machine learning, blockchain and cyber security. Key Features: Introduces the latest trends in the fields of machine learning, blockchain and cyber security Discusses the fundamentals, challenges and architectural overviews with concepts Explores recent advancements in machine learning, blockchain, and cyber security Examines recent trends in emerging technologies This book is primarily aimed at graduates, researchers, and professionals working in the areas of machine learning, blockchain, and cyber security.

The primary goal of this book is to address the issues faced by teachers in the adoption of digital tools into their teaching and their students learning. This book also addresses the issues confronting educators in the integration of digital technologies into their teaching and their students' learning. Such issues include a skepticism of the added value of technology to educational learning outcomes, the perception of the requirement to keep up with the fast pace of technological innovation, a lack of knowledge of affordable educational digital tools and a lack of understanding of pedagogical strategies to embrace digital technologies in their teaching. This book presents theoretical perspectives of learning and teaching today's digital students with technology and proposes a pragmatic and sustainable framework for teachers' professional learning to embed digital technologies into their repertoire of teaching strategies in a systematic, coherent and comfortable manner so that technology integration becomes an almost effortless pedagogy in their day-to-day teaching. Some of the objectives are given below: Shares valuable insights into the influence of technology on teaching and learning in higher education Provides deeper insights on higher education and sustainability interact Studies innovations from various perspectives Investigates how the educators and students apply the unique innovative and emotional dimensions in modern age of learning Provides a timely overview of changes in education reforms and policy research globally Evaluates the problematic relationship between globalization, the state, and education reforms.

Unique selling point:* Focuses on the relationship between organizational culture and change effectiveness with a focus on communication systemsCore audience:* Intended for IT and business management professionals Place in the market:* Will go alongside the main author's other books to give a full picture of IT systems being utilised within business management

Security Analytics for the Internet of Everything compiles the latest trends, technologies, and applications in this emerging field. It includes chapters covering emerging security trends, cyber governance, artificial intelligence in cybersecurity, and cyber challenges. Contributions from leading international experts are included. The target audience for the book is graduate students, professionals, and researchers working in the fields of cybersecurity, computer networks, communications, and the Internet of Everything (IoE). The book also includes some chapters written in a tutorial style so that general readers can easily grasp some of the ideas.

This book focusses on the Internet of Things (IoT) and Data Mining for Modern Engineering and Healthcare Applications and the recent technological advancements in Microwave Engineering, Communication and applicability of newly developed Solid State Technologies in Bio-medical Engineering and Health-Care. The Reader will be able to know the recent advancements in Microwave Engineering including novel techniques in Microwave Antenna Design and various aspects of Microwave Propagation. This book aims to showcase, the various aspects of Communication, Networking, Data Mining, Computational Biology, Bioinformatics, Bio-Statistics and Machine Learning. In this book, recent trends in Solid State Technologies, VLSI and applicability of modern Electronic Devices in Bio-informatics and Health-Care is focused. Furthermore, this book showcases the modern optimization techniques in Power System Engineering, Machine Design and Power Systems. This Book highlights the Internet of Things (IoT) and Data Mining for Modern Engineering and Healthcare Applications and the recent technological advancements in Microwave Engineering, Communication and applicability of newly developed Solid State Technologies in Bio-medical Engineering and Health-Care for day-to-day applications. Societal benefits of Microwave Technologies for smooth and hustle-free life are also areas of major focus. Microwave Engineering includes recent advancements and novel techniques in Microwave Antenna Design and various aspects of Microwave Propagation. Day-to-Day applicability of modern communication and networking technologies are a matter of prime concern. This book aims to showcase, the various aspects of Communication, Networking, Data Mining, Computational Biology, Bioinformatics, Bio-Statistics and Machine Learning. Role of Solid Sate Engineering in development of modern electronic gadgets are discussed. In this book, recent trends in Solid State Technologies, VLSI and applicability of modern Electronic Devices in Bio-informatics and Biosensing Devices for Smart Health care are also discussed. Features: This book features Internet of Things (IoT) and Data Mining for Modern Engineering and Healthcare Applications and the recent technological advancements in Microwave Engineering, Communication and applicability of newly developed Solid State Technologies in Bio-medical Engineering and Smart Health-Care Technologies Showcases the novel techniques in Internet of Things (IoT) integrated Microwave Antenna Design and various aspects of Microwave Communication Highlights the role of Internet of Things (IoT) various aspects of Communication, Networking, Data Mining, Computational Biology, Bioinformatics, Bio-Statistics and Machine Learning Reviews the role of Internet of Things (IoT) in Solid State Technologies, VLSI and applicability of modern Electronic Devices in Bio-informatics and Health-Care In this book, role of Internet of Things (IoT) in Power System Engineering, Optics, RF and Microwave Energy Harvesting and Smart Biosensing Technologies are also highlighted

Semantic web technologies (SWTs) offer the richest machine-interpretable (rather than just machine-processable) and explicit semantics that are being extensively used in various domains and industries. This book provides a roadmap for semantic web technologies (SWTs) and highlights their role in a wide range of domains including cloud computing, Internet of Things, big data, sensor network, and so forth. It also explores the prospects of these technologies including different data interchange formats, query languages, ontologies, Linked Data, and notations. The role of SWTs in 'epidemic Covid-19', 'e-learning platforms and systems', 'block chain', 'open online courses', and 'visual analytics in healthcare' is described as well. This book: Explores all the critical aspects of semantic web technologies (SWTs) Discusses the impact of SWTs on cloud computing, Internet of Things, big data, and sensor network Offers a comprehensive examination of the emerging research in the areas of SWTs and their related domains Provides a template to develop a wide range of smart and intelligent applications Includes latest applications and examples with real data This book is aimed at researchers and graduate students in computer science, informatics, web technology, cloud computing, and Internet of Things.

Introduces the GUHA method of mechanizing hypothesis formation as a data mining tool. Presents examples of data mining with enhanced association rules, histograms, contingency tables and action rules. Provides examples of data mining for exception rules and examples of subgroups discovery. Outlines possibilities of GUHA in business intelligence and big data. Overviews related theoretical results and challenges related to mechanizing hypothesis formation.

* Centers the experiences of designers at every stage of their careers and development. * Defines and explains the idea of professional identity for designers across contexts. * Concludes segments with specific takeaways, reflection activities, and quotes from real-world designers.

This book provides a concise but comprehensive guide to the disciplines of database design, construction, implementation, and management. Based on the authors' professional experience in the software engineering and IT industries before making a career switch to academia, the text stresses sound database design as a necessary precursor to successful development and administration of database systems. The discipline of database systems design and management is discussed within the context of the bigger picture of software engineering. Students are led to understand from the outset of the text that a database is a critical component of a software infrastructure, and that proper database design and management is integral to the success of a software system. Additionally, students are led to appreciate the huge value of a properly designed database to the success of a business enterprise. The text was written for three target audiences. It is suited for undergraduate students of computer science and related disciplines who are pursuing a course in database systems, graduate students who are pursuing an introductory course to database, and practicing software engineers and information technology (IT) professionals who need a quick reference on database design. Database Systems: A Pragmatic Approach, 3rd Edition discusses concepts, principles, design, implementation, and management issues related to database systems. Each chapter is organized into brief, reader-friendly, conversational sections with itemization of salient points to be remembered. This pragmatic approach includes adequate treatment of database theory and practice based on strategies that have been tested, proven, and refined over several years. Features of the third edition include: Short paragraphs that express the salient aspects of each subject Bullet points itemizing important points for easy memorization Fully revised and updated diagrams and figures to illustrate concepts to enhance the student's understanding Real-world examples Original methodologies applicable to database design Step-by-step, student-friendly guidelines for solving generic database systems problems Opening chapter overviews and concluding chapter summaries Discussion of DBMS alternatives such as the Entity-Attributes-Value model, NoSQL databases, database-supporting frameworks, and other burgeoning database technologies A chapter with sample assignment questions and case studies This textbook may be used as a one-semester or two-semester course in database systems, augmented by a DBMS (preferably Oracle). After its usage, students will come away with a firm grasp of the design, development, implementation, and management of a database system.

This book presents soft computing techniques and applications used in healthcare systems, along with the latest advancements. Written as a guide for assessing the roles that these techniques play, the book also highlights implementation strategies, lists problem-solving solutions, and paves the way for future research endeavors in smart and next-generation healthcare systems. This book provides applications of soft computing techniques related to healthcare systems and can be used as a reference guide for assessing the roles that various techniques, such as machine learning, fuzzy logic, and statical mathematics, play in the advancements of smart healthcare systems. The book presents the basics as well as the advanced concepts to help beginners, as well as industry professionals, get up to speed on the latest developments in healthcare systems. The book examines descriptive, predictive, and social network techniques and discusses analytical tools and the important role they play in finding solutions to problems in healthcare systems. A framework of robust and novel healthcare techniques is highlighted, as well as implementation strategies and a setup for future research endeavors. Healthcare Systems Using Soft Computing Techniques is a valuable resource for researchers and postgraduate students in healthcare systems engineering, computer science, information technology, and applied mathematics. The book introduces beginners to-and at the same time brings industry professionals up to speed with-the important role soft computing techniques play in smart healthcare systems.

A comprehensive guide to automated statistical data cleaning The production of clean data is a complex and time-consuming process that requires both technical know-how and statistical expertise. Statistical Data Cleaning brings together a wide range of techniques for cleaning textual, numeric or categorical data. This book examines technical data cleaning methods relating to data representation and data structure. A prominent role is given to statistical data validation, data cleaning based on predefined restrictions, and data cleaning strategy. Key features: Focuses on the automation of data cleaning methods, including both theory and applications written in R. Enables the reader to design data cleaning processes for either one-off analytical purposes or for setting up production systems that clean data on a regular basis. Explores statistical techniques for solving issues such as incompleteness, contradictions and outliers, integration of data cleaning components and quality monitoring. Supported by an accompanying website featuring data and R code. This book enables data scientists and statistical analysts working with data to deepen their understanding of data cleaning as well as to upgrade their practical data cleaning skills. It can also be used as material for a course in data cleaning and analyses.

For Database Systems and Database Design and Application courses offered at the junior, senior, and graduate levels in Computer Science departments. ? Written by well-known computer scientists, this accessible and succinct introduction to database systems focuses on database design and use. The authors provide in-depth coverage of databases from the point of view of the database designer, user, and application programmer, leaving implementation for later courses. It is the first database systems text to cover such topics as UML, algorithms for manipulating dependencies in relations, extended relational algebra, PHP, 3-tier architectures, data cubes, XML, XPATH, XQuery, XSLT. ? Supplements: ? Access Student and Instructor Resources at www.prenhall.com/ullman Author Website (Open Access) ? http://infolab.stanford.edu/~ullman/fcdb.html ? ?

Explains the basic concepts of Python and its role in machine learning Provides comprehensive coverage of feature-engineering including real-time case studies Perceive the structural patterns with reference to data science and statistics and analytics Includes machine learning based structured exercises Appreciates different algorithmic concepts of machine learning including unsupervised, supervised and reinforcement learning

Databases have become an integral part of modern life. Today's society is an information-driven society, and database technology has a direct impact on all aspects of daily life. Decisions are routinely made by organizations based on the information collected and stored in databases. Database management systems such as Oracle are crucial to apply data in industrial or commercial systems. Equally crucial is a graphical user interface (GUI) to enable users to access and manipulate data in databases. The Apache NetBeans IDE with Java is an ideal candidate for developing a GUI with programming functionality. Oracle Database Programming with Java: Ideas, Designs, and Implementations is written for college students and software programmers who want to develop practical and commercial database programming with Java and relational databases such as Oracle Database XE 18c. The book details practical considerations and applications of database programming with Java and is filled with authentic examples as well as detailed explanations. Advanced topics in Java Web, like Java Web Applications and Java Web Services, are covered in real project examples to show how to handle the database programming issues in the Apache NetBeans IDE environment. This book features: A real sample database, CSE _ DEPT, which is built with Oracle SQL Developer, provided and used throughout the book Step by step, detailed illustrations and descriptions of how to design and build a practical relational database Fundamental and advanced Java database programming techniques practical to both beginning students and experienced programmers Updated Java desktop and Web database programming techniques, such as Java Enterprise Edition 7, JavaServer Pages, JavaServer Faces, Enterprise Java Beans, Web applications and Web services, including GlassFish and Tomcat Web servers More than 30 real database programming projects with detailed illustrations Actual JDBC APIs and JDBC drivers, along with code explanations Homework and selected solutions for each chapter to strengthen and improve students' learning and understanding of the topics they have studied

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.

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

This new volume illustrates the diverse applications of IoT. The volume addresses the crucial issue of data safekeeping along with the development of a new cryptographic and security technology as well as a range of other advances in IoT. The volume looks at the application of IoT in medical technology and healthcare, including the design of IoT-based mobile healthcare units and a blockchain technique based smart health record system. Other topics include a blended IoT-enabled learning approach through a study employing clustering techniques, an IoT-enabled garbage disposal system with an advanced message notification system through an android application, IoT-based self-healing concrete that uses bacteria and environmental waste, an IoT-enabled trash-the-ash application that regulates flow, and more. The fresh and innovative advances that demonstrate computational intelligence and IoT in practice that are discussed in this volume will be informative for academicians, scholars, scientists, industry professionals, policymakers, government and non-government organizations, and others.

The main goal of Internet of Things (IoT) is to make secure, reliable, and fully automated smart environments. However, there are many technological challenges in deploying IoT. This includes connectivity and networking, timeliness, power and energy consumption dependability, security and privacy, compatibility and longevity, and network/protocol standards. Internet of Things and Secure Smart Environments: Successes and Pitfalls provides a comprehensive overview of recent research and open problems in the area of IoT research. Features: Presents cutting edge topics and research in IoT Includes contributions from leading worldwide researchers Focuses on IoT architectures for smart environments Explores security, privacy, and trust Covers data handling and management (accumulation, abstraction, storage, processing, encryption, fast retrieval, security, and privacy) in IoT for smart environments This book covers state-of-the-art problems, presents solutions, and opens research directions for researchers and scholars in both industry and academia.

As it is with building a house, most of the work necessary to build a data warehouse is neither visible nor obvious when looking at the completed product. While it may be easy to plan for a data warehouse that incorporates all the right concepts, taking the steps needed to create a warehouse that is as functional and user-friendly as it is theoretically sound, is not especially easy. That's the challenge that Building and Maintaininga Data Warehouse answers. Based on a foundation of industry-accepted principles, this work provides an easy-to-follow approach that is cohesive and holistic. By offering the perspective of a successful data warehouse, as well as that of a failed one, this workdetails those factors that must be accomplished and those that are best avoided. Organized to logically progress from more general to specific information, this valuable guide: Presents areas of a data warehouse individually and in sequence, showing how each piece becomes a working part of the whole Examines the concepts and principles that are at the foundation of every successful data warehouse Explains how to recognize and attend to problematic gaps in an established data warehouse Provides the big picture perspective that planners and executives require Those considering the planning and creation of a data warehouse, as well as those who've already built one will profit greatly from the insights garnered by the author during his years of creating and gathering information on state-of-the-art data warehouses that are accessible, convenient, and reliable.

Data Science: A First Introduction focuses on using the R programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective visualizations, and extract insights from data using classification, regression, clustering, and inference. The text emphasizes workflows that are clear, reproducible, and shareable, and includes coverage of the basics of version control. All source code is available online, demonstrating the use of good reproducible project workflows. Based on educational research and active learning principles, the book uses a modern approach to R and includes accompanying autograded Jupyter worksheets for interactive, self-directed learning. The book will leave readers well-prepared for data science projects. The book is designed for learners from all disciplines with minimal prior knowledge of mathematics and programming. The authors have honed the material through years of experience teaching thousands of undergraduates in the University of British Columbia's DSCI100: Introduction to Data Science course.