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Data-Centric Business and Applications: Advancements in Information and Knowledge Management, Volume 1 (Lecture Notes on Data Engineering and Communications Technologies #213)
by Solomiia Fedushko Peter Štarchoň Katarína GubíniováThis book explores the profound impact of data on company operations, decision-making, and application development. The book delves into sophisticated information and knowledge management principles, including data governance, analytics, knowledge discovery, and artificial intelligence. The subject encompasses data-centric business models, emerging technology, and ethical considerations. Each chapter is authored by an expert in the area who offers important insights into the influence of data on the advancement of business and application development. The material herein is appropriate for a diverse audience, encompassing academics, practitioners, business professionals, and researchers. The editors sincerely appreciate the writers for their significant contributions, which have been crucial in developing an essential resource for studying and advancing data-centric businesses and applications.
Data-Centric Business and Applications: Towards Software Development (Volume 4) (Lecture Notes on Data Engineering and Communications Technologies #40)
by Aneta Poniszewska-Marańda Natalia Kryvinska Stanisław Jarząbek Lech MadeyskiThis book explores various aspects of software creation and development as well as data and information processing. It covers relevant topics such as business analysis, business rules, requirements engineering, software development processes, software defect prediction, information management systems, and knowledge management solutions. Lastly, the book presents lessons learned in information and data management processes and procedures.
Data-Centric Business and Applications: ICT Systems-Theory, Radio-Electronics, Information Technologies and Cybersecurity (Volume 5) (Lecture Notes on Data Engineering and Communications Technologies #48)
by Tamara Radivilova Dmytro Ageyev Natalia KryvinskaThis book addresses the challenges and opportunities of information/data processing and management. It also covers a range of methods, techniques and strategies for making it more efficient, approaches to increasing its usage, and ways to minimize information/data loss while improving customer satisfaction. Information and Communication Technologies (ICTs) and the Service Systems associated with them have had an enormous impact on businesses and our day-to-day lives over the past three decades, and continue to do so. This development has led to the emergence of new application areas and relevant disciplines, which in turn present new challenges and opportunities for service system usage. The book provides practical insights into various aspects of ICT technologies for service systems: Techniques for information/data processing and modeling in service systems Strategies for the provision of information/data processing and management Methods for collecting and analyzing information/data Applications, benefits, and challenges of service system implementation Solutions to increase the performance of various service systems using the latest ICT technologies
Data-Centric Business and Applications: Modern Trends in Financial and Innovation Data Processes 2023. Volume 2 (Lecture Notes on Data Engineering and Communications Technologies #194)
by Andriy Semenov Iryna Yepifanova Jana KajanováThis book examines aspects of financial and investment processes, as well as the application of information technology mechanisms to business and industrial management, using the experience of the Ukrainian economy as an example. An effective tool for supporting business data processing is combining modern information technologies and the latest achievements in economic theory. The variety of industrial sectors studied supports the continuous acquisition and use of efficient business analysis in organizations. In addition, the book elaborates on multidisciplinary concepts, examples, and practices that can be useful for researching the evolution of developments in the field. Also, in this book, there is a description of analysis methods for making decisions in business, finance, and innovation management.
Data-Centric Business and Applications: Modern Trends in Financial and Innovation Data Processes 2023. Volume 1 (Lecture Notes on Data Engineering and Communications Technologies #195)
by Andriy Semenov Iryna Yepifanova Jana KajanováThis book examines aspects of financial and investment processes, as well as the application of information technology mechanisms to business and industrial management, using the experience of the Ukrainian economy as an example. An effective tool for supporting business data processing is combining modern information technologies and the latest achievements in economic theory. The variety of industrial sectors studied supports the continuous acquisition and use of efficient business analysis in organizations. In addition, the book elaborates on multidisciplinary concepts, examples, and practices that can be useful for researching the evolution of developments in the field. Also, in this book, there is a description of analysis methods for making decisions in business, finance, and innovation management.
Data-Centric Business and Applications: Modern Trends in Financial and Innovation Data Processes 2024 (Lecture Notes on Data Engineering and Communications Technologies #240)
by Andriy Semenov Iryna Yepifanova Jana KajanováThe combination of the latest developments in economic theory with contemporary information technologies may be considered as a powerful instrument for the processing of commercial data. This book employs the Ukrainian economy as a case study to examine the multifaceted aspects of financial and investment processes, as well as the utilization of information technology mechanisms in company and industrial management. The range of industrial sectors that have been investigated facilitates application of effective business analysis in enterprises. Furthermore, the book provides detailed insights into transdisciplinary ideas, practices, and examples that may be beneficial when examining evolutional developments in this area. Additionally, this book presents analytical techniques for decision-making in business, finance, and innovation management.
Data-Centric Business and Applications: Advancements in Information and Knowledge Management, Volume 3 (Lecture Notes on Data Engineering and Communications Technologies #212)
by Peter Štarchoň Solomiia Fedushko Katarína GubíniováEmbark on a journey into the future of business with a groundbreaking book that explores the dynamic interplay between data and business, unlocking its transformative power in strategy, decision-making, and application development. Dive deep into cutting-edge topics such as data governance, analytics, knowledge discovery, and AI, and gain an in-depth understanding of managing, analyzing, and extracting insights from complex data sets. This book's holistic approach sets this book apart, seamlessly integrating the latest information and knowledge management concepts. From integrating data-centric approaches into business models to addressing considerations in data-driven decisions, the diverse topics covered will provide invaluable insights into the central role of data in shaping the future of business and applications. This book sheds light on the ongoing advances in structural management, demonstrating how previously understood knowledge, technologies, and data can pave the way for sustainable solutions in the face of innovation, meet insight, and allow businesses to thrive in the digital age.
Data-Centric Security in Software Defined Networks (Studies in Big Data #149)
by Marek Amanowicz Sebastian Szwaczyk Konrad WronaThe book focuses on applying the data-centric security (DCS) concept and leveraging the unique capabilities of software-defined networks (SDN) to improve the security and resilience of corporate and government information systems used to process critical information and implement business processes requiring special protection. As organisations increasingly rely on information technology, cyber threats to data and infrastructure can significantly affect their operations and adversely impact critical business processes. Appropriate authentication, authorisation, monitoring, and response measures must be implemented within the perimeter of the system to protect against adversaries. However, sophisticated attackers can compromise the perimeter defences and even remain in the system for a prolonged time without the owner being aware of these facts. Therefore, new security paradigms such as Zero Trust and DCS aimto provide defence under the assumption that the boundary protections will be breached. Based on experience and lessons learned from research on the application of DCS to defence systems, the authors present an approach to integrating the DCS concept with SDN. They introduce a risk-aware approach to routing in SDN, enabling defence-in-depth and enhanced security for data in transit. The book describes possible paths for an organisation to transition towards DCS, indicating some open and challenging issues requiring further investigation. To allow interested readers to conduct detailed studies and evaluate the exemplary implementation of DCS over SDN, the text includes a short tutorial on using the emulation environment and links to the websites from which the software can be downloaded.
Data Classification and Incremental Clustering in Data Mining and Machine Learning (EAI/Springer Innovations in Communication and Computing)
by Sanjay Chakraborty Sk Hafizul Islam Debabrata SamantaThis book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master in machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naïve Bayes, Decision tree, Random forest, Support vector machine etc,) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques.
Data Communication and Networks: Proceedings of GUCON 2019 (Advances in Intelligent Systems and Computing #1049)
by Lakhmi C. Jain George A. Tsihrintzis Valentina E. Balas Dilip Kumar SharmaThis book gathers selected high-quality papers presented at the International Conference on Computing, Power and Communication Technologies 2019 (GUCON 2019), organized by Galgotias University, India, in September 2019. The content is divided into three sections – data mining and big data analysis, communication technologies, and cloud computing and computer networks. In-depth discussions of various issues within these broad areas provide an intriguing and insightful reference guide for researchers, engineers and students alike.
Data Communications Network Auditing
by Bruce GriffisThis book contains product specific information based on Cisco router command line interface, and IBM's Net view. It is designed to help us understand the "parts and pieces" of communications and determine how components fit together, and what they look like on your bill.
Data Control: Major Challenge for the Digital Society
by Jean-Louis MoninoBusinesses are becoming increasingly aware of the importance of data and information. As such, they are eager to develop ways to "manage" them, to enrich them and take advantage of them. Indeed, the recent explosion of a phenomenal amount of data, and the need to analyze it, brings to the forefront the well-known hierarchical model: "Data, Information, Knowledge". "Data"– this new intangible manna – is produced in real time. It arrives in a continuous stream and comes from a multitude of sources that are generally heterogeneous. This accumulation of data of all kinds is generating new activities designed to analyze these huge amounts of information. It is therefore necessary to adapt and try new approaches, methods, new knowledge and new ways of working. This leads to new properties and new issues as a logical reference must be created and implemented. At the company level, this mass of data is difficult to manage; interpreting it is the predominant challenge.
Data Converters, Phase-Locked Loops, and Their Applications
by Tertulien NdjountcheWith a focus on designing and verifying CMOS analog integrated circuits, the book reviews design techniques for mixed-signal building blocks, such as Nyquist and oversampling data converters, and circuits for signal generation, synthesis, and recovery. The text details all aspects, from specifications to the final circuit, of the design of digital-to-analog converters, analog-to-digital converters, phase-locked loops, delay-locked loops, high-speed input/output link transceivers, and class D amplifiers. Special emphasis is put on calibration methods that can be used to compensate circuit errors due to device mismatches and semiconductor process variations. Gives an overview of data converters, phase- and delay-locked loop architectures,highlighting basic operation and design trade-offs. Focus on circuit analysis methods useful to meet requirements for a high-speed and power-efficient operation. Outlines design challenges of analog integrated circuits using state-of-the-art CMOS processes. Presents design methodologies to optimize circuit performance on both transistor and architectural levels. Includes open-ended circuit design case studies.
Data Driven: Truckers, Technology, and the New Workplace Surveillance
by Karen LevyA behind-the-scenes look at how digital surveillance is affecting the trucking way of lifeLong-haul truckers are the backbone of the American economy, transporting goods under grueling conditions and immense economic pressure. Truckers have long valued the day-to-day independence of their work, sharing a strong occupational identity rooted in a tradition of autonomy. Yet these workers increasingly find themselves under many watchful eyes. Data Driven examines how digital surveillance is upending life and work on the open road, and raises crucial questions about the role of data collection in broader systems of social control.Karen Levy takes readers inside a world few ever see, painting a bracing portrait of one of the last great American frontiers. Federal regulations now require truckers to buy and install digital monitors that capture data about their locations and behaviors. Intended to address the pervasive problem of trucker fatigue by regulating the number of hours driven each day, these devices support additional surveillance by trucking firms and other companies. Traveling from industry trade shows to law offices and truck-stop bars, Levy reveals how these invasive technologies are reconfiguring industry relationships and providing new tools for managerial and legal control—and how truckers are challenging and resisting them.Data Driven contributes to an emerging conversation about how technology affects our work, institutions, and personal lives, and helps to guide our thinking about how to protect public interests and safeguard human dignity in the digital age.
Data-Driven Analytics for the Geological Storage of CO2
by Shahab MohagheghData-driven analytics is enjoying unprecedented popularity among oil and gas professionals. Many reservoir engineering problems associated with geological storage of CO2 require the development of numerical reservoir simulation models. This book is the first to examine the contribution of artificial intelligence and machine learning in data-driven analytics of fluid flow in porous environments, including saline aquifers and depleted gas and oil reservoirs. Drawing from actual case studies, this book demonstrates how smart proxy models can be developed for complex numerical reservoir simulation models. Smart proxy incorporates pattern recognition capabilities of artificial intelligence and machine learning to build smart models that learn the intricacies of physical, mechanical and chemical interactions using precise numerical simulations. This ground breaking technology makes it possible and practical to use high fidelity, complex numerical reservoir simulation models in the design, analysis and optimization of carbon storage in geological formations projects.
Data-Driven Approach for Bio-medical and Healthcare (Data-Intensive Research)
by Nilanjan DeyThe book presents current research advances, both academic and industrial, in machine learning, artificial intelligence, and data analytics for biomedical and healthcare applications. The book deals with key challenges associated with biomedical data analysis including higher dimensions, class imbalances, smaller database sizes, etc. It also highlights development of novel pattern recognition and machine learning methods specific to medical and genomic data, which is extremely necessary but highly challenging. The book will be useful for healthcare professionals who have access to interesting data sources but lack the expertise to use data mining effectively.
Data Driven Approach Towards Disruptive Technologies: Proceedings of MIDAS 2020 (Studies in Autonomic, Data-driven and Industrial Computing)
by T. P. Singh Ravi Tomar Tanupriya Choudhury Thinagaran Perumal Hussain Falih MahdiThis book is a compilation of peer-reviewed papers presented at the International Conference on Machine Intelligence and Data Science Applications, organized by the School of Computer Science, University of Petroleum & Energy Studies, Dehradun, India, during 4–5 September 2020. The book addresses the algorithmic aspect of machine intelligence which includes the framework and optimization of various states of algorithms. Variety of papers related to wide applications in various fields like data-driven industrial IoT, bioinformatics, network and security, autonomous computing and various other aligned areas. The book concludes with interdisciplinary applications like legal, health care, smart society, cyber-physical system and smart agriculture. All papers have been carefully reviewed. The book is of interest to computer science engineers, lecturers/researchers in machine intelligence discipline and engineering graduates.
Data Driven Approaches in Digital Education: 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, Tallinn, Estonia, September 12–15, 2017, Proceedings (Lecture Notes in Computer Science #10474)
by Katrien Verbert Hendrik Drachsler Élise Lavoué Mar Pérez-Sanagustín Julien BroisinThis book constitutes the proceedings of the 12th European Conference on Technology Enhanced Learning, EC-TEL 2017, held in Tallinn, Estonia, in September 2017. The 24 full papers, 23 short papers, 6 demo papers, and 22 poster papers presented in this volume were carefully reviewed and selected from 141 submissions. The theme for the 12th EC-TEL conference on Data Driven Approaches in Digital Education' aims to explore the multidisciplinary approaches that eectively illustrate how data-driven education combined with digital education systems can look like and what are the empirical evidences for the use of datadriven tools in educational practices.
Data Driven Approaches on Medical Imaging
by Bin Zheng Stefan Andrei Md Kamruzzaman Sarker Kishor Datta GuptaThis book deals with the recent advancements in computer vision techniques such as active learning, few-shot learning, zero shot learning, explainable and interpretable ML, online learning, AutoML etc. and their applications in medical domain. Moreover, the key challenges which affect the design, development, and performance of medical imaging systems are addressed. In addition, the state-of-the-art medical imaging methodologies for efficient, interpretable, explainable, and practical implementation of computer imaging techniques are discussed. At present, there are no textbook resources that address the medical imaging technologies. There are ongoing and novel research outcomes which would be useful for the development of novel medical imaging technologies/processes/equipment which can improve the current state of the art.The book particularly focuses on the use of data driven new technologies on medical imaging vision such as Active learning, Online learning, few shot learning, AutoML, segmentation etc.
Data-driven BIM for Energy Efficient Building Design (Spon Research)
by Saeed Banihashemi Hamed Golizadeh Farzad Pour RahimianThis research book aims to conceptualise the scale and spectrum of Building Information Modelling (BIM) and Artificial Intelligence (AI) approaches in energy efficient building design and develop its functional solutions with a focus towards four crucial aspects of building envelop, building layout, occupant behaviour and heating, ventilation and air-conditioning (HVAC) systems. Drawn from the theoretical development on the sustainability, informatics and optimisation paradigms in built environment, the energy efficient building design will be marked through the power of data and BIM intelligent agents during the design phase. It will be further developed via smart derivatives to reach a harmony in the systematic integration of energy efficient building design solutions; a gap which is missed in the extant literature and this book aims to fill that. This approach will inform a vision for future, provide a framework to shape and respond to our built environment and how it transforms the way we design and build. By considering the balance of BIM, AI and energy efficient outcomes, the future development of buildings will be regenerated in a direction that are sustainable in the long run. This book is essential reading for those in the AEC industry as well as computer scientists.
Data-driven Block Ciphers for Fast Telecommunication Systems
by Nikolai Moldovyan Alexander A. MoldovyanThe Most Progressive and Complete Guide to DDO-Based CiphersDevelopers have long recognized that ciphers based on Permutation Networks (PNs) and Controlled Substitution-Permutation Networks (CSPNs) allow for the implementation of a variety of Data Driven Operations (DDOs). These DDOs can provide fast encryption without incurring excessive
The Data-Driven Blockchain Ecosystem: Fundamentals, Applications, and Emerging Technologies
by Alex Khang Subrata Chowdhury Seema SharmaThis book focuses on futuristic approaches and designs for real-time systems and applications, as well as the fundamental concepts of including advanced techniques and tools in models of data-driven blockchain ecosystems. The Data-Driven Blockchain Ecosystem: Fundamentals, Applications, and Emerging Technologies discusses how to implement and manage processes for releasing and delivering blockchain applications. It presents the core of blockchain technology, IoT-based and AI-based blockchain systems, and various manufacturing areas related to Industry 4.0. The book illustrates how to apply design principles to develop and manage blockchain networks, and also covers the role that cloud computing plays in blockchain applications. All major technologies involved in blockchain-embedded applications are included in this book, which makes it useful to engineering students, researchers, academicians, and professionals interested in the core of blockchain technology.
Data-Driven Clinical Decision-Making Using Deep Learning in Imaging (Studies in Big Data #152)
by Nilanjan Dey M. F. MridhaThis book explores cutting-edge medical imaging advancements and their applications in clinical decision-making. The book contains various topics, methodologies, and applications, providing readers with a comprehensive understanding of the field's current state and prospects. It begins with exploring domain adaptation in medical imaging and evaluating the effectiveness of transfer learning to overcome challenges associated with limited labeled data. The subsequent chapters delve into specific applications, such as improving kidney lesion classification in CT scans, elevating breast cancer research through attention-based U-Net architecture for segmentation and classifying brain MRI images for neurological disorders. Furthermore, the book addresses the development of multimodal machine learning models for brain tumor prognosis, the identification of unique dermatological signatures using deep transfer learning, and the utilization of generative adversarial networks to enhance breast cancer detection systems by augmenting mammogram images. Additionally, the authors present a privacy-preserving approach for breast cancer risk prediction using federated learning, ensuring the confidentiality and security of sensitive patient data. This book brings together a global network of experts from various corners of the world, reflecting the truly international nature of its research.
Data-Driven Controller Design: The H2 Approach (Communications and Control Engineering)
by Lucíola Campestrini Diego Eckhard Alexandre Sanfelice BazanellaData-Based Controller Design presents a comprehensive analysis of data-based control design. It brings together the different data-based design methods that have been presented in the literature since the late 1990's. To the best knowledge of the author, these data-based design methods have never been collected in a single text, analyzed in depth or compared to each other, and this severely limits their widespread application. In this book these methods will be presented under a common theoretical framework, which fits also a large family of adaptive control methods: the MRAC (Model Reference Adaptive Control) methods. This common theoretical framework has been developed and presented very recently. The book is primarily intended for PhD students and researchers - senior or junior - in control systems. It should serve as teaching material for data-based and adaptive control courses at the graduate level, as well as for reference material for PhD theses. It should also be useful for advanced engineers willing to apply data-based design. As a matter of fact, the concepts in this book are being used, under the author's supervision, for developing new software products in a automation company. The book will present simulation examples along the text. Practical applications of the concepts and methodologies will be presented in a specific chapter.
Data-Driven Decision Making for Product Service Systems
by Xavier Boucher Giuditta Pezzotta Roberto Sala Marco Bertoni Fabiana PirolaThis book is a compilation of theoretical and practical contributions aimed at facilitating the servitization of manufacturing companies, specifically focusing on data-driven decision-making within the context of Product-Service Systems (PSS). Providing a comprehensive overview, it discusses the latest breakthroughs in operational, tactical, and strategic decision-making for PSS, leveraging data-driven processes, methodologies, and tools. Therefore, the book significantly contributes to strengthening the knowledge on the use of data-driven decision-making methods and tools all the phases of the PSS lifecycle.From extended warranties and leasing to pay-per-use and other innovative configurations, manufacturing companies are increasingly adopting servitized business models and PSS to create additional value for their customers and users and create robust relationships with them, ensuring more reliable cash flows. In this setting, effective information management and the utilization of aggregated operational data have become essential for guiding strategic, tactical, and operational decisions.This book not only consolidates theoretical frameworks but also offers practical insights into data-driven decision-making in PSS, providing deep knowledge on how complex decisions can be taken along the various phases of the PSS lifecycle using data-driven methods and tools. Key areas of focus include: 1. In the Beginning of Life, introducing new services tailored to customer needs, disclosing new business opportunities in terms of revenues, and extending the PSS Middle of Life.2. Designing or re-designing assets and/or services, thereby influencing the PSS Beginning of Life.3. Enhancing daily decisions related to asset management to improve the PSS Middle of Life.4. Optimizing daily decisions related to service delivery and management, aimed at enhancing the PSS Middle of Life.5. Facilitating informed decisions on recycling, remanufacturing, refurbishing, and revamping, impacting the PSS End of Life.This book will be of interest to researchers and managers in industry as it offers insights that bridge the gap between theory and practical application in the evolving landscape of PSS.