Maintaining the advanced technical focus found in Developing Essbase Applications, this second volume is another collaborative effort by some of the best and most experienced Essbase practitioners from around the world. Developing Essbase Applications: Hybrid Techniques and Practices reviews technology areas that are much-discussed but still very new, including Exalytics and Hybrid Essbase. Covering recent improvements to the Essbase engine, the book illustrates the impact of new reporting and analysis tools and also introduces advanced Essbase best practices across a variety of features, functions, and theories. Some of this book's chapters are in the same vein as the previous volume: hardware, engines, and languages. Others cover new ground with Oracle Business Intelligence Enterprise Edition, design philosophy, benchmarking concepts, and multiple client tools. As before, these subjects are covered from both the technical and best practice perspectives. This updated volume continues in the tradition of its bestselling predecessor by defining, investigating, and explaining Essbase concepts like no other resource. It also includes use cases that transform abstract theory into practical examples you can easily relate to your own Essbase environment. Illustrating the recent expansion of Essbase functionality, this book provides the up-to-date understanding you need to explore the full depth of the Essbase technology stack. Although the book presents detailed tutorial chapters that can be read on their own, reading the entire book will provide you with a similar understanding as some of the most experienced Essbase practitioners from around the world.

This book constitutes the refereed post-conference proceedings of the IFIP TC 3 Open Conference on Computers in Education, OCCE 2020, held in Mumbai, India, in January 2020. The 11 full papers and 4 short papers included in this volume were carefully reviewed and selected from 57 submissions. The papers discuss key emerging topics and evolving practices in the area of educational computing research. They are organized in the following topical sections: computing education; learners' and teachers' perspectives; teacher professional development; the industry perspective; and further aspects.

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.

Every day we need to solve large problems for which supercomputers are needed. High performance computing (HPC) is a paradigm that allows to efficiently implement large-scale computational tasks on powerful supercomputers unthinkable without optimization. We try to minimize our effort and to maximize the achieved profit. Many challenging real world problems arising in engineering, economics, medicine and other areas can be formulated as large-scale computational tasks. The volume is a comprehensive collection of extended contributions from the High performance computing conference held in Borovets, Bulgaria, September 2019. This book presents recent advances in high performance computing. The topics of interest included into this volume are: HP software tools, Parallel Algorithms and Scalability, HPC in Big Data analytics, Modelling, Simulation & Optimization in a Data Rich Environment, Advanced numerical methods for HPC, Hybrid parallel or distributed algorithms. The volume is focused on important large-scale applications like Environmental and Climate Modeling, Computational Chemistry and Heuristic Algorithms.

This book introduces novel methods for leak and blockage detection in pipelines. The leak happens as a result of ageing pipelines or extreme pressure forced by operational error or valve rapid variation. Many factors influence blockage formation in pipes like wax deposition that leads to the formation and eventual growth of solid layers and deposition of suspended solid particles in the fluids. In this book, initially, different categories of leak detection are overviewed. Afterwards, the observability and controllability of pipeline systems are analysed. Control variables can be usually presented by pressure and flow rates at the start and end points of the pipe. Different cases are considered based on the selection of control variables to model the system. Several theorems are presented to test the observability and controllability of the system. In this book, the leakage flow in the pipelines is studied numerically to find the relationship between leakage flow and pressure difference. Removing leakage completely is almost impossible; hence, the development of a formal systematic leakage control policy is the most reliable approach to reducing leakage rates.

This book addresses the need for materials which can help the IS researcher determine which qualitative methods are most appropriate for addressing their particular research questions. It draws on the collective expertise of distinguished scholars to explore concrete issues they have encountered in the use of a particular qualitative method.

Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning, and metaheuristics. Written by world-leading academic researchers who are extremely experienced in industrial applications, this self-contained book is the first of its kind that provides comprehensive background knowledge, particularly practical guidelines, and state-of-the-art techniques. New algorithms are carefully explained, further elaborated with pseudocode or flowcharts, and full working source code is made freely available. This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms. Applications of data-driven optimization ranging from aerodynamic design, optimization of industrial processes, to deep neural architecture search are included.

This book is a collection of selected papers presented at the First International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC), held as an online conference due to COVID-19 (initially to be held in Macao, Special Administration Region (SAR) of China), during September 15-17, 2020. It includes novel and innovative work from experts, practitioners, scientists and decision-makers from academia and industry. It brings multi-disciplines together on IIoT, data science, cloud computing, software engineering approaches to design, development, testing and quality of products and services.

This book gathers the outcomes of the second ECCOMAS CM3 Conference series on transport, which addressed the main challenges and opportunities that computation and big data represent for transport and mobility in the automotive, logistics, aeronautics and marine-maritime fields. Through a series of plenary lectures and mini-forums with lectures followed by question-and-answer sessions, the conference explored potential solutions and innovations to improve transport and mobility in surface and air applications. The book seeks to answer the question of how computational research in transport can provide innovative solutions to Green Transportation challenges identified in the ambitious Horizon 2020 program. In particular, the respective papers present the state of the art in transport modeling, simulation and optimization in the fields of maritime, aeronautics, automotive and logistics research. In addition, the content includes two white papers on transport challenges and prospects. Given its scope, the book will be of interest to students, researchers, engineers and practitioners whose work involves the implementation of Intelligent Transport Systems (ITS) software for the optimal use of roads, including safety and security, traffic and travel data, surface and air traffic management, and freight logistics.

This book provides the key technologies involved in an organization's digital transformation. It offers a deep understanding of the key technologies (Blockchain, AI, Big Data, IoT, etc.) involved and details the impact, the decision-making process, and the interplay between technologies, business models, and operations. Managing the Digital Transformation: Aligning Technologies, Business Models, and Operations provides frameworks and models to support digital transformation projects. The book presents the importance of digital transformation as a resilience approach to the operations processes and business models. It covers the essential elements integrating the technology, the organizations, the operations, and supply chain management used to move toward digital transformation. Concepts and mini-case studies are included to provide a deeper understanding of digital transformation projects with a holistic view. The book also examines the role that digital transformation plays with consideration of inter-organizational and intra-organizational capabilities, along with the role of digital culture, the worker's skills, business models, reconfiguration, as well as an operations optimization angle. Practitioners, consultants, governments, managers, scholars, and anyone interested in digital transformation will find the contents of this book very useful.

Big Data in History introduces a project to create a world-historical archive that will trace the last four centuries of historical dynamics and change. The archive will link research on social, economic, and political affairs, plus health and climate, for societies throughout the world. The care, detail, and advanced technology that go into building such an archive are outlined in this book, and the benefits of gathering and disseminating data from our long history are clearly mapped out. Chapters address the archive's overall plan, how to interpret the past through a global archive, how to organize historical research on five continents, and the missions of gathering widespread records, linking local data into global patterns, and exploring the results. The concluding chapters summarize project plans and compare it with two major and successful projects in worldwide data: the modelling of climate and documenting the human genome.

This work provides an assessment of the current state of near field communication (NFC) security, it reports on new attack scenarios, and offers concepts and solutions to overcome any unresolved issues. The work describes application-specific security aspects of NFC based on exemplary use-case scenarios and uses these to focus on the interaction with NFC tags and on card emulation. The current security architectures of NFC-enabled cellular phones are evaluated with regard to the identified security aspects.

This book concentrates on the sustainable applications of the Blockchain Technology across multiple latest computational knowledge domains. It covers the feasible and practical collaboration of Blockchain Technology with latest Sustainable Smart Computing Technologies. It will target the vast applications of Blockchain in the field of Internet of Things, Artificial Intelligence, and Cybersecurity. The book effectively provides satisfactory information about the essentials of Blockchain and IoT to a typical pursuer alongside encouraging an examination researcher to distinguish some modern issue regions that rise up out of the intermingling of the two advancements. Besides, the creators talk about pertinent application zones, for example, smart city, e-social insurance, and so forth along the course of the book. * Covers the recent advancements in Blockchain technology * Discusses the applications of Blockchain technology for real life problems * Address the challenges related to implementation of Blockchain technology * Includes case studies * Includes the latest trends and area of research in Blockchain Technology This book is primarily aimed at graduates, researchers and professions working in the field of blockchain technology.

This book discusses the technological aspects for the implementation of Society 5.0. The foundation and recent advances of emerging technologies such as artificial intelligence, data science, Internet of Things, and Big Data for the realization of Society 5.0 are covered. Practical solutions to existing problems, examples, and case studies are also offered. Society 5.0 and the Future of Emerging Computational Technologies: Practical Solutions, Examples, and Case Studies discusses technologies such as machine learning, artificial intelligence, and Internet of Things for the implementation of Society 5.0. It offers a firm foundation and understanding of the recent advancements in various domains such as data analytics, neural networks, computer vision, and robotics, along with practical solutions to existing problems in fields such as healthcare, manufacturing industries, security, and infrastructure management. Applications and implementations are highlighted along with the correlation between technologies. Examples and case studies are presented throughout the book to augment text. This book can be used by research scholars in the engineering domain who wish to gain knowledge and contribute towards a modern and secure future society. The book will also be useful as a reference at universities for postgraduate students who are interested in technological advancements.

- Curating Social Data - Summarizing Social Data - Analyzing Social Data - Social Data Analytics Applications: Trust, Recommender Systems, Cognitive Analytics

Blockchain: Principles and Applications in IoT covers all the aspects of Blockchain and its application in IOT. The book focuses on Blockchain, its features, and the core technologies that are used to build the Blockchain network. The gradual flow of chapters traces the history of blockchain from cryptocurrencies to blockchain technology platforms and applications that are adopted by mainstream financial and industrial domains worldwide due to their ease of use, increased security and transparency. * Focuses on application of Blockchain on IoT domain * Focuses on Blockchain as a data repository * Most books on Blockchain cover bitcoins and crypto currency. This book will also cover blockchain in other areas like healthcare, supply chain management, etc * Covers consensus algorithms like PAROX, RAFT etc. and its applications This book is primarily aimed at graduates and researchers in computer science and IT.

Web Semantics Ontology provides an excellent overview of current research and development activities, while covering an extensive range of topics including ontological modeling, enterprise systems, querying and knowledge discovery, and a wide range of applications. Each chapter contains a thorough study of the topic, systematic proposed work, and a comprehensive list of references. The theoretical and practical aspects of Web semantics and ontology development combine to bring a unique perspective to this book. Researchers, software developers, and IT students who want to enhance their knowledge of issues relating to modeling, adopting, querying, discovering knowledge, and building ontologies and Web semantics will benefit from ""Web Semantics Ontology.

This book provides a general introduction to Sequential Monte Carlo (SMC) methods, also known as particle filters. These methods have become a staple for the sequential analysis of data in such diverse fields as signal processing, epidemiology, machine learning, population ecology, quantitative finance, and robotics. The coverage is comprehensive, ranging from the underlying theory to computational implementation, methodology, and diverse applications in various areas of science. This is achieved by describing SMC algorithms as particular cases of a general framework, which involves concepts such as Feynman-Kac distributions, and tools such as importance sampling and resampling. This general framework is used consistently throughout the book. Extensive coverage is provided on sequential learning (filtering, smoothing) of state-space (hidden Markov) models, as this remains an important application of SMC methods. More recent applications, such as parameter estimation of these models (through e.g. particle Markov chain Monte Carlo techniques) and the simulation of challenging probability distributions (in e.g. Bayesian inference or rare-event problems), are also discussed. The book may be used either as a graduate text on Sequential Monte Carlo methods and state-space modeling, or as a general reference work on the area. Each chapter includes a set of exercises for self-study, a comprehensive bibliography, and a "Python corner," which discusses the practical implementation of the methods covered. In addition, the book comes with an open source Python library, which implements all the algorithms described in the book, and contains all the programs that were used to perform the numerical experiments.

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.

* 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 introduces the field of Health Web Science and presents methods for information gathering from written social media data. It explores the availability and utility of the personal medical information shared on social media platforms and determines ways to apply this largely untapped information source to healthcare systems and public health monitoring. Introducing an innovative concept for integrating social media data with clinical data, it addresses the crucial aspect of combining experiential data from social media with clinical evidence, and explores how the variety of available social media content can be analyzed and implemented. The book tackles a range of topics including social media's role in healthcare, the gathering of shared information, and the integration of clinical and social media data. Application examples of social media for health monitoring, along with its usage in patient treatment are also provided. The book also considers the ethical and legal issues of gathering and utilizing social media data, along with the risks and challenges that must be considered when integrating social media data into healthcare choices. With an increased interest internationally in E-Health, Health 2.0, Medicine 2.0 and the recent birth of the discipline of Web Science, this book will be a valuable resource for researchers and practitioners investigating this emerging topic.

This book treats intellectual capital, smart technologies, and digitalization processes as levers of corporate competitiveness and global value creation. This book is based on theoretical and practical research output from the STEDIC SIDREA Group. It uses several methodologies to discover features and pillars on intellectual capital such as human capital, relational capital, and structural capital as well as smart technologies such as artificial intelligence, Internet of Things, big data, and digitalization.

This book highlights the state-of-the-art research on data usage, security, and privacy in the scenarios of the Internet of Things (IoT), along with related applications using Machine Learning and Big Data technologies to design and make efficient Internet-compatible IoT systems. ICT and Data Sciences brings together IoT and Machine Learning and provides the careful integration of both, along with many examples and case studies. It illustrates the merging of two technologies while presenting basic to high-level concepts covering different fields and domains such as the Hospitality and Tourism industry, Smart Clothing, Cyber Crime, Programming, Communications, Business Intelligence, all in the context of the Internet of Things. The book is written for researchers and practitioners, working in Information Communication Technology and Computer Science.

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