Databases / Data management Books

Book SynopsisIn a world of rapid and unpredictable change, the problem with strategic planning is that if you follow your plan through to the end, you will get exactly what you used to want. What you need is a framework for planning and implementing a strategy that is agile enough to adapt to a dynamic environment but focused enough to deliver. That framework is the Dynamic Balanced Scorecard. The original Balanced Scorecard system has proven the most popular, successful and enduring framework for strategy execution over the last 25 years. Comprising a Strategy Map and a scorecard of KPIs, targets and initiatives, the framework helped organizations distil a strategy into actionable components and measure progress towards a strategic vision, while also implementing and monitoring the actions that drove change. However, for all its success, the Balanced Scorecard system now needs to evolve for the digital age. Until now, building the system, rolling it out enterprise-wide and adapting it to external changes has been a lengthy process. While the fundamental principles of the system are still sound and relevant, it needs to become nimbler and more responsive. The book provides a step-by-step guide to agile strategy management: from formulation to implementation to learning and adapting. For each of the steps, the book explains how Dynamic Balanced Scorecards, fit for the digital age, are built and deployed.Table of Contents1 Digital Era Strategy Management: From planning to dynamic decision making 2 From Industrial to Digital-Era-based Strategies3 Agile Strategy Setting4 Strategy Mapping in Disruptive Times5 How to Build an Agile and Adaptive Balanced Scorecard6 Driving Rapid Enterprise Alignment7 Aligning the Financial and Operational Drivers of Strategic Success8 Developing Strategy-aligned Project Management Capabilities9 Unleashing the Power of Analytics for Strategic Learning and Adapting10 How to Ensure a Strategy-Aligned Leadership11 How to Ensure a Strategy-Aligned Culture12 Ensuring Employee Sense of Purpose in the Digital Era13 Further Developments, Driving Sustainable Value through Collaborative Strategy Maps and Scorecards14 Conclusion and 25 Key Strategic Questions

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Book SynopsisThis textbook examines database systems from the viewpoint of a software developer. This perspective makes it possible to investigate why database systems are the way they are. It is of course important to be able to write queries, but it is equally important to know how they are processed. We e.g. don’t want to just use JDBC; we also want to know why the API contains the classes and methods that it does. We need a sense of how hard is it to write a disk cache or logging facility. And what exactly is a database driver, anyway?The first two chapters provide a brief overview of database systems and their use. Chapter 1 discusses the purpose and features of a database system and introduces the Derby and SimpleDB systems. Chapter 2 explains how to write a database application using Java. It presents the basics of JDBC, which is the fundamental API for Java programs that interact with a database. In turn, Chapters 3-11 examine the internals of a typical database engine. Each chapter covers a different database component, starting with the lowest level of abstraction (the disk and file manager) and ending with the highest (the JDBC client interface); further, the respective chapter explains the main issues concerning the component, and considers possible design decisions. As a result, the reader can see exactly what services each component provides and how it interacts with the other components in the system. By the end of this part, s/he will have witnessed the gradual development of a simple but completely functional system. The remaining four chapters then focus on efficient query processing, and focus on the sophisticated techniques and algorithms that can replace the simple design choices described earlier. Topics include indexing, sorting, intelligent buffer usage, and query optimization.This text is intended for upper-level undergraduate or beginning graduate courses in Computer Science. It assumes that the reader is comfortable with basic Java programming; advanced Java concepts (such as RMI and JDBC) are fully explained in the text. The respective chapters are complemented by “end-of-chapter readings” that discuss interesting ideas and research directions that went unmentioned in the text, and provide references to relevant web pages, research articles, reference manuals, and books. Conceptual and programming exercises are also included at the end of each chapter. Students can apply their conceptual knowledge by examining the SimpleDB (a simple but fully functional database system created by the author and provided online) code and modifying it.Table of Contents1. Database Systems.- 2. JDBC.- 3. Disk and File Management.- 4. Memory Management.- 5. Transaction Management.- 6. Record Management.- 7. Metadata Management.- 8. Query Processing.- 9. Parsing.- 10. Planning.- 11. JDBC Interfaces.- 12. Indexing.- 13. Materialization and Sorting.- 14. Effective Buffer Utilization.- 15. Query Optimization.

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Book SynopsisThis Festschrift was published in honor of Hans L. Bodlaender on the occasion of his 60th birthday. The 14 full and 5 short contributions included in this volume show the many transformative discoveries made by H.L. Bodlaender in the areas of graph algorithms, parameterized complexity, kernelization and combinatorial games. The papers are written by his former Ph.D. students and colleagues as well as by his former Ph.D. advisor, Jan van Leeuwen.Chapter “Crossing Paths with Hans Bodlaender: A Personal View on Cross-Composition for Sparsification Lower Bounds” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.Table of ContentsSeeing Arboretum for the (partial k) Trees.- Collaborating With Hans: Some Remaining Wonderments.- Hans Bodlaender and the Theory of Kernelization Lower Bounds.- Algorithms, Complexity, and Hans.- Lower Bounds for Dominating Set in Ball Graphs and for Weighted Dominating Set in Unit-Ball Graphs.- As Time Goes By: Reflections on Treewidth for Temporal Graphs.- Possible and Impossible Attempts to Solve the Treewidth Problem via ILPs.- Crossing Paths with Hans Bodlaender: A Personal View on Cross-Composition for Sparsification Lower Bounds.- Efficient Graph Minors Theory and Parameterized Algorithms for (Planar) Disjoint Paths.- Four shorts stories on surprising algorithmic uses of treewidth.- Algorithms for NP-Hard Problems via Rank-related Parameters of Matrices.- A Survey on Spanning Tree Congestion.- Surprising Applications of Treewidth Bounds for Planar Graphs.- Computing tree decompositions.- Experimental analysis of treewidth.- A Retrospective on (Meta) Kernelization.- Games, Puzzles and Treewidth.- Fast Algorithms for Join Operations on Tree Decompositions.

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Book SynopsisThis book provides innovative ideas on achieving sustainable development and using green technologies to conserve our ecosystem. Innovation is the successful exploitation of a new idea. Through innovation, we can achieve MORE while using LESS. Innovations in science & technology will not only help mankind as a whole, but also contribute to the economic growth of individual countries. It is essential that the global problem of environmental degradation be addressed immediately, and thus, we need to rethink the concept of sustainable development. Indeed, new environmentally friendly technologies are fundamental to attaining sustainable development. The book shares a wealth of innovative green technological ideas on how to preserve and improve the quality of the environment, and how to establish a more resource-efficient and sustainable society. The book provides an interdisciplinary approach to addressing various technical issues and capitalizing on advances in computing & optimization for scientific & technological development, smart information, communication, bio-monitoring, smart cities, food quality assessment, waste management, environmental aspects, alternative energies, sustainable infrastructure development, etc. In short, it offers valuable information and insights for budding engineers, researchers, upcoming young minds and industry professionals, promoting awareness for recent advances in the various fields mentioned above. Table of ContentsChapter 1: A Treatise on Distributed Generation Control.- Chapter 2: Approach for the prevention of Audio Piracy.- Chapter 3: Quality assessment of kaji lemon (Citrus limon) juice under ultrasound and pasteurization processing conditions.- Chapter 4: Optimal Parameter Extraction of PEM Fuel Cell using an Effective Approach.- Chapter 5: A Survey on Feature Extraction Methods for EEG based Emotion Recognition.- Chapter 6: Block Steganography Based Secure Key Encryption To Improve Data Security.- Chapter 7: Texture analysis for rice grain classification using wavelet decomposition and back propagation neural network.- Chapter 8: An analytics-based envelope neural net approach to forecasting memory leakage in an enterprise applications environment.

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Book SynopsisThis book strikes a healthy balance between theory and applications, ensuring that it doesn’t offer a set of tools with no mathematical roots. It is intended as a comprehensive and largely self-contained introduction to probability and statistics for university students from various faculties, with accompanying implementations of some rudimentary statistical techniques in the language R. The content is divided into three basic parts: the first includes elements of probability theory, the second introduces readers to the basics of descriptive and inferential statistics (estimation, hypothesis testing), and the third presents the elements of correlation and linear regression analysis. Thanks to examples showing how to approach real-world problems using statistics, readers will acquire stronger analytical thinking skills, which are essential for analysts and data scientists alike. Table of ContentsElements of Probability Theory.- Descriptive and Inferential Statistics.- Linear Regression and Correlation.

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Book SynopsisThis 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.Trade Review“The authors have written a comprehensive broad-audience treatment of sequential Monte Carlo (SMC) methods, covering all its major and diverse applications. … The book is structured as an advanced Ph.D.-level textbook.” (Michael Ludkovski, Mathematical Reviews, May, 2022)Table of Contents1 Preface.- 2 Introduction to state-space models.- 3 Beyond state-space models.- 4 Introduction to Markov processes.- 5 Feynman-Kac models: definition, properties and recursions.- 6 Finite state-spaces and hidden Markov models.- 7 Linear-Gaussian state-space models.- 8 Importance sampling.- 9 Importance resampling.- 10 Particle filtering.- 11 Convergence and stability of particle filters.- 12 Particle smoothing.- 13 Sequential quasi-Monte Carlo.- 14 Maximum likelihood estimation of state-space models.- 15 Markov chain Monte Carlo.- 16 Bayesian estimation of state-space models and particle MCMC.- 17 SMC samplers.- 18 SMC2, sequential inference in state-space models.- 19 Advanced topics and open problems.

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Book SynopsisThis textbook offers an easy-to-follow, practical guide to modern data analysis using the programming language R. The chapters cover topics such as the fundamentals of programming in R, data collection and preprocessing, including web scraping, data visualization, and statistical methods, including multivariate analysis, and feature exercises at the end of each section. The text requires only basic statistics skills, as it strikes a balance between statistical and mathematical understanding and implementation in R, with a special emphasis on reproducible examples and real-world applications. This textbook is primarily intended for undergraduate students of mathematics, statistics, physics, economics, finance and business who are pursuing a career in data analytics. It will be equally valuable for master students of data science and industry professionals who want to conduct data analyses.Trade Review“It was very interesting to go through the pages of this book. The authors should be commended for writing a thorough book about complex concepts of data analysis in R that could, however, be read easily. I warmly recommend this book to students of statistics but also to professionals who would like to acquire advanced analytical skills or improve their competencies in R, especially nowadays with R very popular amongst data analysts.” (Georgios Nikolopoulos, ISCB News, iscb.info, Issue 71, June, 2021)Table of ContentsPreface.- 1 Introduction.- 2 Introduction to R.- 3 Databases in R.- 4 Visualization.- 5 Data Analysis with R.- R Packages and Funtions.

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Book SynopsisThis two-volume set LNCS 12131 and LNCS 12132 constitutes the refereed proceedings of the 17th International Conference on Image Analysis and Recognition, ICIAR 2020, held in Póvoa de Varzim, Portugal, in June 2020.The 54 full papers presented together with 15 short papers were carefully reviewed and selected from 123 submissions. The papers are organized in the following topical sections: image processing and analysis; video analysis; computer vision; 3D computer vision; machine learning; medical image and analysis; analysis of histopathology images; diagnosis and screening of ophthalmic diseases; and grand challenge on automatic lung cancer patient management.Due to the corona pandemic, ICIAR 2020 was held virtually only.Table of ContentsMachine Learning.- Medical Image and Analysis.- Analysis of Histopathology Images.- Diagnosis and Screening of Ophthalmic Diseases.- Grand Challenge on Automatic Lung Cancer Patient Management.

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Book SynopsisThis open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.Table of ContentsFoundations.- Chapter 1. Ecosystem of Big Data.- Chapter 2. Knowledge Graphs: The Layered Perspective.- Chapter 3. Big Data Outlook, Tools, and Architectures.- Architecture.- Chapter 4. Creation of Knowledge Graphs.- Chapter 5. Federated Query Processing.- Chapter 6. Reasoning in Knowledge Graphs: An Embeddings Spotlight.- Methods and Solutions.- Chapter 7. Scalable Knowledge Graph Processing using SANSA.- Chapter 8. Context-Based Entity Matching for Big Data.- Applications.- Chapter 9. Survey on Big Data Applications.- Chapter 10. Case Study from the Energy Domain.

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Book SynopsisThis book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral clustering are derived as powerful tools. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.Table of Contents1 Introduction.- 2 Prerequisites from Matrix Analysis.- 3 Multivariate Distributions and Moments.- 4 Dimensionality Reduction.- 5 Classification and Clustering.- 6 Support Vector Machines.- 7 Machine Learning.- Index.

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Book SynopsisDatabase technology is an important subject in Computer Science. Every large company and nation needs a database to store information. The technology has evolved from file systems in the 60’s, to Hierarchical and Network databases in the 70’s, to relational databases in the 80’s, object-oriented databases in the 90’s, and to XML documents and NoSQL today. As a result, there is a need to reengineer and update old databases into new databases. This book presents solutions for this task.In this fourth edition, Chapter 9 - Heterogeneous Database Connectivity (HDBC) offers a database gateway platform for companies to communicate with each other not only with their data, but also via their database. The ability of sharing a database can contribute to the applications of Big Data and surveys for decision support systems. The HDBC gateway solution collects input from the database, transfers the data into its middleware storage, converts it into a common data format such as XML documents, and then distributes them to the users. HDBC transforms the common data into the target database to meet the user’s requirements, acting like a voltage transformer hub. The voltage transformer converts the voltage to a voltage required by the users. Similarly, HDBC transforms the database to the target database required by the users.This book covers reengineering for data conversion, integration for combining databases and merging databases and expert system rules, normalization for eliminating duplicate data from the database, and above all, HDBC connects all legacy databases to one target database for the users.The authors provide a forum for readers to ask questions and the answers are given by the authors and the other readers on the Internet. Table of ContentsPreface.- Information Systems Reengineering, Integration and Normalization.- Database and Expert System Technology.- Schema Transition.- Data Conversion.- Database Program Translation.- Schema Integration.- Database and Expert-Systems Integration.- Data Normalization.- Heterogeneous Database Connectivity.- Conclusion.

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Book SynopsisThese lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models. These advanced modelling techniques can easily be applied using computer code samples written in Python and Stan which are integrated into the main text. Importantly, the reader will learn methods for assessing model fit, and to choose between rival modelling approaches. Table of ContentsUncertainty and Decisions.- Prior and Likelihood Representation.- Graphical Modeling.- Parametric Models.- Computational Inference.- Bayesian Software Packages.- Model choice.- Linear Models.- Nonparametric Models.- Nonparametric Regression.- Clustering and Latent Factor Models.- Conjugate Parametric Models.

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Book SynopsisThis book introduces higher-degree research students and early career academics to scientific research as occurring in the field of information systems and adjacent fields, such as computer science, management science, organization science, and software engineering. Instead of focusing primarily on research methods as many other textbooks do, it covers the entire research process, from start to finish, placing particular emphasis on understanding the cognitive and behavioural aspects of research, such as motivation, modes of inquiry, theorising, planning for research, planning for publication, and ethical challenges in research. Comprehensive but also succinct and compact, the book guides beginning researchers in their quest to do scholarly work and to assist them in developing their own answers and strategies over the course of their work. Jan Recker explains in this book the fundamental concepts that govern scientific research and then moves on to introduce the basic steps every researcher undertakes: choosing research questions, developing theory, building a research design, employing research methods, and finally writing academic papers. He also covers essentials of ethical conduct of scientific research. This second edition contains major updates on all these elements plus significant expansions on relevant research methods such as design research and computational methods, a rewritten and extended chapter on theory development, and expansions to the chapters on research methods, scientific publishing, and research ethics. A companion website provides pedagogical materials and instructions for using this book in teaching.Table of ContentsPart I: Basic Principles of Research.- Introduction.- Information Systems Research as a Science.- Part II: Conducting Research.- Planning Your Research.- Theorising.- Research Methods.- Part III: Publishing Research.- Writing IS Research Articles.- Ethical Considerations in Research.- Concluding Remarks.

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Book SynopsisThis book addresses the emerging paradigm of data-driven engineering design. In the big-data era, data is becoming a strategic asset for global manufacturers. This book shows how the power of data can be leveraged to drive the engineering design process, in particular, the early-stage design.Based on novel combinations of standing design methodology and the emerging data science, the book presents a collection of theoretically sound and practically viable design frameworks, which are intended to address a variety of critical design activities including conceptual design, complexity management, smart customization, smart product design, product service integration, and so forth. In addition, it includes a number of detailed case studies to showcase the application of data-driven engineering design. The book concludes with a set of promising research questions that warrant further investigation.Given its scope, the book will appeal to a broad readership, including postgraduate students, researchers, lecturers, and practitioners in the field of engineering design.Table of ContentsData-driven Engineering Design.- User-Generated Content Analysis for Customer Needs Elicitation.- Data-driven Conceptual Design.- Management of Constraints, Complexities, and Contradictions in the Data Era.- Blockchain-based Data-driven Smart Customisation.- Data-driven Design of Smart Product.- Data-driven Smart Product Service System.- Digital Twin for Data-driven Engineering Design.- Enabling Technologies of Data-driven Engineering Design.

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Book SynopsisThis book presents a framework for developing as well as a comprehensive collection of state-of-the-art process querying methods. Process querying combines concepts from Big Data and Process Modeling and Analysis with Business Process Intelligence and Process Analytics to study techniques for retrieving and manipulating models of real-world and envisioned processes to organize and extract process-related information for subsequent systematic use. The book comprises sixteen contributed chapters distributed over four parts and two auxiliary chapters. The auxiliary chapters by the editor provide an introduction to the area of process querying and a summary of the presented methods, techniques, and applications for process querying. The introductory chapter also examines a process querying framework. The contributed chapters present various process querying methods, including discussions on how they instantiate the framework components, thus supporting the comparison of the methods. The four parts are due to the distinctive features of the methods they include. The first three are devoted to querying event logs generated by IT-systems that support business processes at organizations, querying process designs captured in process models, and methods that address querying both event logs and process models. The methods in these three parts usually define a language for specifying process queries. The fourth part discusses methods that operate over inputs other than event logs and process models, e.g., streams of process events, or do not develop dedicated languages for specifying queries, e.g., methods for assessing process model similarity. This book is mainly intended for researchers. All the chapters in this book are contributed by active researchers in the research disciplines of business process management, process mining, and process querying. They describe state-of-the-art methods for process querying, discuss use cases of process querying, and suggest directions for future work for advancing the field. Yet, also other groups like business or data scientists and other professionals, lecturers, graduate students, and tool vendors will find relevant information for their distinctive needs.Chapter "Celonis PQL: A Query Language for Process Mining" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.Table of ContentsIntroduction to Process Querying.- Part I: Event Log Querying.- BP-SPARQL: A Query Language for Summarizing and Analyzing Big Process Data.- Data-Aware Process Oriented Query Language.- Process Instance Query Language and the Process Querying Framework.- Part II: Process Model Querying.- The Diagramed Model Query Language 2.0: Design, Implementation, and Evaluation.- VM*: A Family of Visual Model Manipulation Languages.- The BPMN Visual Query Language and Process Querying Framework.- Retrieving, Abstracting, and Changing Business Process Models with PQL.- QuBPAL: Querying Business Process Knowledge.- CRL and the Design-Time Compliance Management Framework.- Process Query Language.- Part III: Event Log and Process Model Querying.- Business Process Query Language.- Celonis PQL: A Query Language for Process Mining.- Part IV: Other Process Querying Methods.- Process Querying Using Process Model Similarity.- Logic-Based Approaches for Process Querying.- Process Model Similarity Techniques for Process Querying.- Complex Event Processing Methods for Process Querying.- Process Querying: Methods, Techniques, and Applications.

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Book SynopsisThis open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is structured in four parts: Part I “Foundations and Contexts” provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II “Data Space Technologies” subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various “Use Cases and Data Ecosystems” from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several “Solutions and Applications”, eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more. Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty.Table of ContentsPart I: Foundations and Context.- 1. The Evolution of Data Spaces.- 2. How to Build, Run, and Govern Data Spaces.- 3. International Data Spaces in a Nutshell.- 4. Role of Gaia-X in the European Data Space Ecosystem.- 5. Legal Aspects of IDS: Data Sovereignty—What Does It Imply?.- 6. Tokenomics: Decentralized Incentivization in the Context of Data Spaces.- Part II: Data Space Technologies.- 7. The IDS Information Model: A Semantic Vocabulary for Sovereign Data Exchange.- 8. Data Usage Control.- 9. Building Trust in Data Spaces.- 10. Blockchain Technology and International Data Spaces.- 11. Federated Data Integration in Data Spaces.- 12. Semantic Integration and Interoperability.- 13. Data Ecosystems: A New Dimension of Value Creation Using AI and Machine Learning.- 14. IDS as a Foundation for Open Data Ecosystems.- 15. Defining Platform Research Infrastructure as a Service (PRIaaS) for Future Scientific Data Infrastructure.- Part III: Use Cases and Data Ecosystems.- 16. Silicon Economy: Logistics as the Natural Data Ecosystem.- 17. Agricultural Data Space.- 18. Medical Data Spaces in Healthcare Data Ecosystems.- 19. Industrial Data Spaces.- 20. Energy Data Space.- 21. Mobility Data Space.- Part IV: Solutions and Applications.- 22. Data Sharing Spaces: The BDVA Perspective.- 23. Data Platform Solutions.- 24. FIWARE for Data Spaces.- 25. Sovereign Cloud Technologies for Scalable Data Spaces.- 26. Data Space Based on Mass Customization Model.- 27. Huawei and International Data Spaces.- International Collaboration Between Data Spaces and Carrier Networks.- 29. From Linear Supply Chains to Open Supply Ecosystems.- 30. Data Spaces: First Applications in Mobility and Industry.- 31. Competition, Security, and Transparency: Data in Connected Vehicles.- Data Space Functionality.- The Energy Data Space: The Path to a European Approach for Energy.

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Book SynopsisThis open access book summarizes knowledge about several file systems and file formats commonly used in mobile devices. In addition to the fundamental description of the formats, there are hints about the forensic value of possible artefacts, along with an outline of tools that can decode the relevant data. The book is organized into two distinct parts: Part I describes several different file systems that are commonly used in mobile devices. · APFS is the file system that is used in all modern Apple devices including iPhones, iPads, and even Apple Computers, like the MacBook series. · Ext4 is very common in Android devices and is the successor of the Ext2 and Ext3 file systems that were commonly used on Linux-based computers. · The Flash-Friendly File System (F2FS) is a Linux system designed explicitly for NAND Flash memory, common in removable storage devices and mobile devices, which Samsung Electronics developed in 2012. · The QNX6 file system is present in Smartphones delivered by Blackberry (e.g. devices that are using Blackberry 10) and modern vehicle infotainment systems that use QNX as their operating system. Part II describes five different file formats that are commonly used on mobile devices. · SQLite is nearly omnipresent in mobile devices with an overwhelming majority of all mobile applications storing their data in such databases. · The second leading file format in the mobile world are Property Lists, which are predominantly found on Apple devices.· Java Serialization is a popular technique for storing object states in the Java programming language. Mobile application (app) developers very often resort to this technique to make their application state persistent. · The Realm database format has emerged over recent years as a possible successor to the now ageing SQLite format and has begun to appear as part of some modern applications on mobile devices. · Protocol Buffers provide a format for taking compiled data and serializing it by turning it into bytes represented in decimal values, which is a technique commonly used in mobile devices. The aim of this book is to act as a knowledge base and reference guide for digital forensic practitioners who need knowledge about a specific file system or file format. It is also hoped to provide useful insight and knowledge for students or other aspiring professionals who want to work within the field of digital forensics. The book is written with the assumption that the reader will have some existing knowledge and understanding about computers, mobile devices, file systems and file formats.Table of ContentsPart I: Mobile File System Formats.- 1. APFS.- 2. Ext4.- 3. The Flash-Friendly File System (F2FS).- 4. QNX6.- Part II: Mobile File Formats.- 5. SQLite.- 6. Property Lists.- 7. Java Serialization.- 8. Realm.- 9. Protocol Buffers.

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Book SynopsisDieses Buch bietet einen Überblick über Data-Mining-Methoden, die durch Software veranschaulicht werden. Beim Wissensmanagement geht es um die Anwendung von menschlichem Wissen (Erkenntnistheorie) mit den technologischen Fortschritten unserer heutigen Gesellschaft (Computersysteme) und Big Data, sowohl bei der Datenerfassung als auch bei der Datenanalyse. Es gibt drei Arten von Analyseinstrumenten. Die deskriptive Analyse konzentriert sich auf Berichte über das, was passiert ist. Bei der prädiktiven Analyse werden statistische und/oder künstliche Intelligenz eingesetzt, um Vorhersagen treffen zu können. Dazu gehört auch die Modellierung von Klassifizierungen. Die diagnostische Analytik kann die Analyse von Sensoreingaben anwenden, um Kontrollsysteme automatisch zu steuern. Die präskriptive Analytik wendet quantitative Modelle an, um Systeme zu optimieren oder zumindest verbesserte Systeme zu identifizieren. Data Mining umfasst deskriptive und prädiktive Modellierung. Operations Research umfasst alle drei Bereiche. Dieses Buch konzentriert sich auf die deskriptive Analytik.Das Buch versucht, einfache Erklärungen und Demonstrationen einiger deskriptiver Werkzeuge zu liefern. Es bietet Beispiele für die Auswirkungen von Big Data und erweitert die Abdeckung von Assoziationsregeln und Clusteranalysen. Kapitel 1 gibt einen Überblick im Kontext des Wissensmanagements. Kapitel 2 erörtert einige grundlegende Softwareunterstützung für die Datenvisualisierung. Kapitel 3 befasst sich mit den Grundlagen der Warenkorbanalyse, und Kapitel 4 demonstriert die RFM-Modellierung, ein grundlegendes Marketing-Data-Mining-Tool. Kapitel 5 demonstriert das Assoziationsregel-Mining. Kapitel 6 befasst sich eingehender mit der Clusteranalyse. Kapitel 7 befasst sich mit der Link-Analyse. Die Modelle werden anhand geschäftsbezogener Daten demonstriert. Der Stil des Buches ist beschreibend und versucht zu erklären, wie die Methoden funktionieren, mit einigen Zitaten, aber ohne tiefgehende wissenschaftliche Referenzen. Die Datensätze und die Software wurden so ausgewählt, dass sie für jeden Leser, der über einen Computeranschluss verfügt, weithin verfügbar und zugänglich sind.Table of Contents

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Book SynopsisCognitive Infocommunications.- Internet of Digital Reality.- Cognitive Mobility.- Cognitive Aspects of Virtual Reality.- Relationship Between Navigational Experience and Spatial Abilities.- Sense of Presence in Desktop VR.

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Book SynopsisEnvironmental sustainability.- Healthcare.- Production systems.

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Book Synopsisbusiness and industries.- logistics and transportation systems.- monitor, control, and theoretical systems.

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Book SynopsisGlobal Financial Markets and Cross-Cultural Marketing Approaches.- Enhancing IoT Finance: A Block-Chain-Integrated Financial Management Platform for Supply Chain Optimization.- T+1 Settlement and the Algorithmic Age: A New Era for Stock Valuation with Potential Market Froth.- Driving Financial Inclusion to Achieve Sustainable Development Goals: Collaborative FinTech Strategies in Developing Countries.- Role of Blockchain Technology in Advancing Sustainability Development: A Comprehensive Review.- An Empirical study on the Emerging Trends and Potential Challenges in advancing Digital Financial Services in India.- Regulatory challenges and opportunities for future fintech and green finance.- Empowering Rural Jharkhand: Adoption of Artificial Intelligence for Digital Financial Inclusion.- Decentralizing Talent for Sustainability in BlockChain.- From Greenwashing to Green Finance: Blockchain as a Catalyst for Transparency and Impact.- Green Finance: A Way to Boost the Indian Economy.- Blockchains Role in Green Finance: A Pathway to Sustainable Development.- Empirical Examination of Blockchain Technology in Organizational HRM: Comparing HR Employees & Non-HR Employees Perspectives.- Blockchain-Based Identity Management: Enhancing Security and Privacy in Digital Transactions.- Cryptocurrency in India: Its Journey and Legal Aspects.- Integrating Climate Finance into National Adaptation and Mitigation Strategies: Lessons from Global Case Studies.- Exploring Global Cryptocurrency Trends: A Specialized Analysis of the Indian Economic Landscape.- Blockchain Technology for Sustainable Financial Management: An Approach for Efficiency and Security.- Blockchain and Green Finance Scaling: Literature Synthesis and Future Research Agenda.- Analysing Trends and Impacts: A Bibliometric Study of Blockchain and Cryptocurrency Research.- Unveiling the Future of FinTech in the Dynamic Financial Market.

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Book Synopsis.- Doctoral Consortium..- Using Graph Theory for Clinical Data Management..- Advancing Legal NLP: Application of Pre-trained Language Models in the Legal Domain..- An application for scoliosis screening and follow-up: a first proposal..- Negation Detection in Italian: A Key Challenge in Sentiment Analysis..- Optimizing Federated Learning and Increasing Efficiency..- Integrating Pseudo-Time Series Analysis into Telemedicine: Enhancing Real-Time Disease Monitoring and Intervention..- Classifying Chest X-Ray Images with Deep Learning Techniques: Challenges and Explainable Analysis..- Scalable Deep Learning: Applications in Medicine..- Towards More Efficient and Improved Federated Learning..- Development of Explainable AI Methods for the Interpretation of Machine Learning Models in Bioinformatics and Medicine..- Deep Learning Techniques for Predicting Wildires in Calabria Italy Using Environmental Parameters..- 5th Workshop on Intelligent Data - From Data to Knowledge (DOING 2024)..- Capturing Analytical Intents from Text..- The Effect of Text Normalization on Mining Portuguese Man-of-War Instagram Posts..- A Preliminary Investigation: Strategies for Incorporating Logical Rules into Knowledge Graph Embeddings..- Construction of Open Data Sources for Data Interoperability in Brazilian Health Information Systems..- Brazilian Political Study with Topics Analysis and Complex Networks..- 3rd Workshop on Knowledge Graphs Analysis on a Large Scale (K-GALS 2024)..- Transforming Text into Knowledge with Graphs: Report of the GDR MADICS DOING Action..- Building Model-Driven Knowledge Graphs via Large Language Models..- 6th Workshop on Modern Approaches in Data Engineering and Information System Design (MADEISD 2024)..- Process Mining in Croatia's Judicial Auctions..- Towards the Utilization of AI-powered Assistance for Systematic Literature Review..- Estimating Information Efficiency of Bitcoin Inscriptions..- Deep Learning-Based Cellular Nuclei Segmentation Using Transformer Mode..- Towards a Model-Driven Approach to Enable Uniform Access to Vector Databases..- Employing Multiple Online Translation Services in a Multilingual Database Design Tool..- 3rd Workshop on Personalization and Recommender Systems (PERS 2024)..- Development of Collaborative Business Intelligence Framework for Tourism Analysis..- Session-based Recommendation with Graph Neural Networks with an Examination of the Impact of Local and Global Vectors..- Senselife: Service Recommendation and Frailty Prevention through Knowledge Models..- Evaluating Diversity in Sequential Group Recommendations..- Access methods and Query Processing..- A Reproducibility Study of Subgroup Discovery Algorithms (short)..- Discovery and Data Analysis..- A Compact and Efficient Data Structure for Line-based Processing of Series of Raster Data (short)..- Machine Learning..- FedeM: Federated Learning-Based Privacy-Preserving Record Matching (short)..- Estimating MPdist with SAX and Machine Learning (short)..- Large Language Models..- Entity Matching with Large Language Models as Weak and Strong labellers (short)..- LLMClean: Context-Aware Tabular Data Cleaning via LLM-Generated OFDs (short)..- Tutorials..- Data-driven Analysis for Monitoring Software Evolution..- On Customer Data Deduplication - Research vs. Industrial Perspective: Lessons Learned from a R&D Project in the Financial Sector.

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Book SynopsisOptimization of Electrical Systems Using the ant Colony Methodology A Systematic Review and Bibliometric Study.- Statistical Analysis of Climatic Variables for Potential Frost Prediction Application.- Maximizing Energy Efficiency A Comprehensive Approach Routing Optimization and Transformer Placement in Distribution Networks.

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Book SynopsisTechnology Implementation in Education Quality Assurance and Professions.- The impact of the use of artificial intelligence applications on the preparation of scientific research in the field of accounting at universities A practical study on a sample of teaching staff at Sudanese universities 2024.- Higher Education as a Proxy for Technology Its Impact on Chronic and Life Threatening Illnesses in MENA Countries.- Digital Transformation in Professional Education Status, Standards and Strategies for Airport Operation Courses.- Innovative Integration of Experiential Learning in Hospitality and Tourism Management Education A Systematic Review.- Intelligent Information System Leveraging AI and Machine Learning for University Course Registration and Academic Performance Enhancement in Educational Systems.- The Extent of Impact Digitalization on Large Accounting and Auditing Firms Worldwide.- Strategic Planning Competencies and Their Relationship with Crisis Management in Palestinian Schools.- A Proposed Model of Gender Differences in Metaverse Usage Intentions in Education An Innovation Resistance Theory Perspective.- Impact of Artificial Intelligence and Big Data on Auditing A study on the perception of auditors.- Dialectical relationship between the Arabic language education and Modern Technology.- Examining the Impact of Artificial Intelligence Adoption on Academic Writing among Business Students in Lebanese Higher Education.

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Book SynopsisIntroduction:Constructive dialogue between technology and pedagogy.- AI-Enhanced Ecological Learning Spaces.- Reimagining Learning Experiences with the Use of AI.- Generative AI integration in education: challenges and approaches.- Navigating AI in EducationTowards a System Approach for Design of Educational Changes.- AI in the Assessment Ecosystem: A HumanCentered AI Perspective.- The role of AI language assistants in dialogic education for collective intelligence.- AI powered adaptive formative assessment: Validity and reliability Evaluation.- Decimal Point: A Decade of Learning Science Findings with a Digital Learning Game.- Leveraging AI to Advance Science and Computing Education across Africa: Challenges, Progress and Opportunities.- Educating Manufacturing Operators by Extending Reality with AI.- Pedagogical Restructuring of Business Communication Courses: AI-Enhanced Prompt Engineering in an EFL Teaching Context.- AI in Language Education: The Impact of Machine Translation and ChatGPT.

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Book SynopsisMachine Learning Model for Prediction of Indicative Water Parameters on the Danube River based on Satellite Data.- XGBoost is all you need the case of forecasting transmitted heat energy in District Heating Systems.-  XAI4HEAT Towards demand-driven, AI facilitated, end-to-end management of District Heating Systems.- integrated Multi Criteria Decision Analysis Sizing Optimization and Demand Side Management for Defining Optimal System Configuration while Reducing Costs and CO2 Emissions.

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Book Synopsis1.Threshold-based algorithm for fall detection through an inertial sensor fixed at the head.- 2.Least Squares Optimization with incorporations from Haar Wavelet.- 3.Privacy Techniques in Health Data Mining.- 4.Network Segmentation and its Advancement in Containing Insider Threats.- 5.Constructing a proactive cyber resilient culture for better business outcomes.

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Book SynopsisIntroduction of data quality management.- Quality management in Data Science.- Pillars of data quality management.- Tools of data quality management.- Experimental designs for data quality control.- High-quality data collection in data markets.- Ghost data in data quality management.- Summary.

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Book Synopsis.- Processes And Data..- Digital Twin Data Provision within Engineering: An AAS PLM Implementation En-suring Interoperability..- Data Catalogs in an industrial SME context A systematic literature review..- Data Mesh: How to Implement the Paradigm Shift..- Improving Agile Maturity in Data Teams: A Framework for Enhanced Business Pro-cess Agility..- Synergizing Data Contracts and BPM to improve Process Interoperability: An Analy-sis of Gaps and Opportunities of Data Exchange Agreements in BPM Models..- Subject-Oriented Modeling, Philosophy, and Technology..- An Aspect-Oriented Extension of the Parallel Activity Specification Schema: A First Draft..- How Business Process Modeling Can Benefit from Rhetorical Structure Theory..- Modeling the Behavior of IoT Systems: A Subject-Oriented Reference Model..- Subject-Oriented Modeling Workflow Control Patterns with PASS..- Subject- and Process-oriented Comparison of Multi-Factor Authentication Methods..- S-BPM as an Alternative to BPMN in the Context of Low-Code: Applicability, User Experience and Transformation from S-BPM to BPMN..- Processes and Sustainability..- Faciliating the preparation of Life Cycle Assessment through Subject-Oriented Pro-cess Modeling: A methodological framework..- A Framework for Sustainable Web Design in the Era of Digital Transformation..- Green thoughts & creative spaces: An experimental study on influence of innovation labs on productivity and sustainability of process..- Towards Resilient Digital Supply Chains..- Good Process Practices..- Walking Away from Omelas: Towards a Comprehensive Model for Successful Adop-tion of Industry 4.0 Technologies in SMEs..- Interoperable Product Change Management within Engineering: A Digital Twin Ap-proach..- Next-Generation Business Process Management (BPM): A Systematic Literature Review of Cognitive Computing and Improvements in BPM..- Three Stances in Enterprise System Design..- Process Orientation in Authorities: Opportunities, Challenges and Best Practices..- Which good practices minimize procedural problems in IT workflows between au-thorities..- Meta-Prompt Engineering in ChatGPT-4 for AI-Generated BPM Reference Models.

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Book SynopsisChapter 1. Technology for assessing the readiness of information security specialists in the system of continuing education using game approaches.- Chapter 2. Access authentication and key distribution using physically unclonable functions, with SHA-256 as an example.- Chapter 3. Development of a framework for describing security incidents.- Chapter 4. Analysing information security risks when remotely connecting to the web interface.- Chapter 5. A safe and secure online system for bidding using blockchain technology.- Chapter 6. Theoretical framework for blockchain secured predictive maintenance learning model using digital twin.- Chapter 7. Advancements in Sybil attack detection: a comprehensive survey of machine learning-based approaches in wireless sensor networks.- Chapter 8. Guaranteed Output Delivery with More than 1/3 of Malicious Corruption for Client Server MPC Protocols and Applications.- Chapter 9. Methods of safe processing of user-entered information in information systems.- Chapter 10. Comparative analysis of methods for assessing confidence in the information security audit process.- Etc...

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Book SynopsisIntroduction.- Examples of statistical laws.- From data to laws.- Synthesis statistical laws in context.- Datasets and Codes.

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Book SynopsisImpact of employee engagement on job performance of IT employees.- Investigating Value Added Tax and customs duties on Retail Supply Chains in Clothing Industry.- Impact of Life Cycle Cost of Airfield Pavement on Airport Operations.- The Impact of Internal Marketing on Organizational Performance in UAE Healthcare Settings.

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Book SynopsisChapter 1. Artistic Creativity in View of the Philosophy of Technology.- Chapter 2. Traditional and Cognitiviste Views of Conceivability.- Chapter 3. Traditional and Cognitiviste Views of Conceivability.- Chapter 4. The Phygital World: The Role of Imagination in the Development of Artificial Intelligence.- Chapter 5. Scientific and Literary Speech - How Fiction can Shape the Worldview of Scientists.- Chapter 6.  Scientific Fictions and Historical Reality.- Chapter 7. Thought Experiments: The Subjunctive Mood in History.- Chapter 8. Constructive and Predictive Capabilities of the Alternative History Genre.- Chapter 9. Multiplayer Online Games Become Reality:  A New Literary Genre.- Chapter 10. Artificial Intelligence as a Creator of Over-Normative Reality.- Chapter 11. Nomadism and Reality - Two scenarios for their interrelation and development.- Chapter 12. Emotive Lexis and a Scholar's Hypothetical Portrait.

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Book SynopsisChapter 1. Storytelling in higher education: a literature review.- Chapter 2. Using Vladimir Propp's Approach to Create Digital Storytelling when Teaching for Undergraduate Students.- Chapter 3. Cognitive Aspects of Immersive Teaching in Digital Educational Environments.- Chapter 4. Socio-pragmatic Vectors of Scenario-based Behavior in Teaching English to Future Linguists.- Chapter 5.Corpus Technologies for the Creation of Scenarios in Foreign Language Education.- Chapter 6. Generative Artificial Intelligence as a Tool for the Development and Evaluation of Student's Thinking.- Chapter 7.Integration of Storytelling Technology and the Moral Education of Student Personalities in Foreign Language Instruction.- Chapter 8. Fiction and Imagined Possibilities for the Formation of Spiritual and Moral Qualities in Technical University Students.- Chapter 9.Harmonizing Personality and Developing Imagination in the Training Face of Aggression. Chapter 10. The Scenario-motivational Model of Personal Formation of the Modern Specialist.-Etc...

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Book Synopsis.- Research Track..- How Effective are Time Series Models for Pandemic Forecasting?..- Research on Public Data Assets Valuation Combined With Expert Scoring Method..- Cross-Chain Analysis of Blockchain-Based Pharmaceutical Supply Chain Management Using NFTs..- A study of the impact of networked low-altitude drone operations on the performance of big data services..- Anti-Third-Party Infringement Based on the Perspective of Data Resource Holding Rights..- Application Track..- Defect Detection Network for TOPCon Solar Cells Based on Improved YOLOv5 and CBAM Mechanism..- 5 Steps for Enterprise Artificial Intelligence Governance and Compliance..- Enhancing Transparency and Efficiency in Energy Trading Management Systems for Electric Vehicles: The Role of Blockchain, IPFS, and NFTs..- Short Paper Track..- A Model of Big Data Analytics Applied to Teacher Evaluation Based on Enhanced Data Quality.

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Book SynopsisIs attention all we need.- Is the construction industry ready for AI.- AI for sustainability in the early project stages.- AI for Construction Risk Management.- Computer Vision for Asset and Facility Management.- Industry 5 0 in Construction Towards a More Human Centric and Ethical AI.

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Book SynopsisGeneral model for assessing the quality of socially significant activities as a part of Information Security Management.- Use of Blockchain Technology for Maintaining Authenticity and Credibility of Digital Information.- Detection of Anomalous Activity in Wireless Communication Channels.- Development of an Approach to Confidential Learning with Errors in the Design of Neural Networks.

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Book SynopsisAssessing Teachers Awareness of Digital and Technological Addiction Risks Among Secondary School Students in Jordan.- Determining the awareness level about consumer electronics waste A comparative study.- The impact of strategic entrepreneurship and administrative entrepreneurship on the job satisfaction of faculty members in Jordanian universities.- The Challenges Associated with the Internal Audit Practice and their Impact on its Performance Empirical Evidence from Listed Companies in Ghana.- The Role of AI Chatbots in Learning Writing Skills An Empirical study on the Use of ChatGPT among EFL Omani Students.

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Book SynopsisEvaluation of the Level of Efficiency of Time Management at the Enterprise Using the Theory of Fuzzy Sets.- Financial Security Management of Enterprises in Conditions of Uncertainty.- Integration of Operational and Economic Security of the Enterprise: Reorganization, Technologies, Risks & Outsourcing.- Financial Assurance for Tourism Development and Its Impact on the Economy of European Countries.- Innovative Mechanisms for Regulating the Social Welfare of Refugees: Demographic Collapse or Sustainable Development.- Innovative Management of Regional Business: Financial Technologies and IT Tools.

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Book Synopsis

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Book SynopsisTechnology Innovation and Business Performance.- Understanding the role of forensic accountants in due diligence within organizations and its impact on organizational learning.- Who is better in practicing Customer due diligence as an antimoney laundering tool for financial institutions Can internal auditors be forensic accountants Evidence from MENA Region.- The Impact of Intangible Investments on Nonfinancial Performance The Moderating Effect of the Political In stability of the Gaza War.- Understanding the Attitude of Senior High School Students Toward Utilizing ChatGPT as A Learning Tool A Quantitative Analysis.- Factors That Influence the effectiveness of AIS Implementation in SMEs in Jordan.- Do artificial intelligence enhance the efficiency of accounting information system Evidence from Bahrain.- The Influence of the Internet on Marketing Communication for Business Services.- Investigating AI generated code on the impact on software efficiency code quality factor.- The Impact of Motivation of Human Resources on Total Quality Management Mediated by Patient Satisfaction.- Exploring the deployment of business analytics tools  including metaheuristics across Saudi enterprises.

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