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Relational databases have been predominant for many years and are used throughout various industries. The current system faces challenges related to size and variety of data thus the NoSQL databases emerged. By joining these two database models, there is room for crucial developments in the field of computer science. Bridging Relational and NoSQL Databases is an innovative source of academic content on the convergence process between databases and describes key features of the next database generation. Featuring coverage on a wide variety of topics and perspectives such as BASE approach, CAP theorem, and hybrid and native solutions, this publication is ideally designed for professionals and researchers interested in the features and collaboration of relational and NoSQL databases.
This book presents proceedings of the 14th Days of Bosnian-Herzegovinian American Academy of Arts and Sciences held in Tuzla, BIH, June 1–4, 2023. Delve into the intellectual tapestry that emerged from this event, as we unveil our highly anticipated Conference Proceedings Book. This groundbreaking publication captures the essence of seven captivating technical sessions spanning from Civil Engineering through Power Electronics all the way to Data Sciences and Artificial Intelligence, each exploring a distinct realm of innovation and discovery. Uniting diverse disciplines, this publication catalyzes interdisciplinary collaboration, forging connections that transcend traditional boundaries. Within these pages, readers find a compendium of knowledge, insights, and research findings from leading researchers in their respective fields. The editors would like to extend special gratitude to the chairs of all symposia for their dedicated work in the production of this volume.
When it comes to optimization techniques, in some cases, the available information from real models may not be enough to construct either a probability distribution or a membership function for problem solving. In such cases, there are various theories that can be used to quantify the uncertain aspects. Optimization Techniques for Problem Solving in Uncertainty is a scholarly reference resource that looks at uncertain aspects involved in different disciplines and applications. Featuring coverage on a wide range of topics including uncertain preference, fuzzy multilevel programming, and metaheuristic applications, this book is geared towards engineers, managers, researchers, and post-graduate students seeking emerging research in the field of optimization.
With the ever-increasing volume of data, proper management of data is a challenging proposition to scientists and researchers, and given the vast storage space required, multimedia data is no exception in this regard. Scientists and researchers are investing great effort to discover new space-efficient methods for storage and archiving of this data. Intelligent Innovations in Multimedia Data Engineering and Management provides emerging research exploring the theoretical and practical aspects of storage systems and computing methods for large forms of data. Featuring coverage on a broad range of topics such as binary image, fuzzy logic, and metaheuristic algorithms, this book is ideally designed for computer engineers, IT professionals, technology developers, academicians, and researchers seeking current research on advancing strategies and computing techniques for various types of data.
Data mining techniques are commonly used to extract meaningful information from the web, such as data from web documents, website usage logs, and hyperlinks. Building on this, modern organizations are focusing on running and improving their business methods and returns by using opinion mining. Extracting Knowledge From Opinion Mining is an essential resource that presents detailed information on web mining, business intelligence through opinion mining, and how to effectively use knowledge retrieved through mining operations. While highlighting relevant topics, including the differences between ontology-based opinion mining and feature-based opinion mining, this book is an ideal reference source for information technology professionals within research or business settings, graduate and post-graduate students, as well as scholars.
Due to the increasing availability of affordable internet services, the number of users, and the need for a wider range of multimedia-based applications, internet usage is on the rise. With so many users and such a large amount of data, the requirements of analyzing large data sets leads to the need for further advancements to information processing. Big Data Processing With Hadoop is an essential reference source that discusses possible solutions for millions of users working with a variety of data applications, who expect fast turnaround responses, but encounter issues with processing data at the rate it comes in. Featuring research on topics such as market basket analytics, scheduler load simulator, and writing YARN applications, this book is ideally designed for IoT professionals, students, and engineers seeking coverage on many of the real-world challenges regarding big data.
Die regulatorischen Herausforderungen der Datenökonomie sind in aller Munde. Die vorliegende Studie leistet einen aktuellen Beitrag zur Konkretisierung und Präzisierung der Diskussion für Wissenschaft und Praxis aus immaterialgüter- und datenschutzrechtlicher Perspektive. Der Stand der lex lata wird für die Praxis und als Basis für weitere wissenschaftliche Diskussion umfassend aufbereitet. Dabei wird insbesondere auch der Geschäftsgeheimnisschutz nach dem aktuellen GeschGehG und der EU-Geschäftsgeheimnis-Richtlinie zentral mit behandelt. Zudem diskutieren die Autoren aktuelle Reformprojekte unter Berücksichtigung der Vorschläge der Kommission für den Digital Markets Act und den Digital Services Act. Auf dieser breiten Basis werden schließlich aus wissenschaftlicher Sicht weitere wesentliche Reformperspektiven aufgezeigt, die von den Leitgedanken der Innovation durch wirksamen Wettbewerb und Datenzugang sowie materieller Privatautonomie auf der Basis eines angemessenen Ausgleichs der einschlägigen Grundrechtspositionen bestimmt sind.
Bachelorarbeit aus dem Jahr 2018 im Fachbereich Informatik - Wirtschaftsinformatik, Note: 2,3, Fachhochschule der Wirtschaft Paderborn, Sprache: Deutsch, Abstract: Das Ziel dieser Arbeit ist es Vorteile des neuen Features Oracle Sharding zu erarbeiten und diese in einer Entscheidungsmatrix zusammenzufassen. Mithilfe der Matrix soll es möglich sein, Einsatzmöglichkeiten des Oracle Shardings abzuleiten. Dabei wird im Besonderen Wert auf das Erstellen einer Sharding Umgebung und dem Vergleich mit gleichartigen Technologien gelegt. Das Feature wird ganzheitlich analysiert im Bezug auf seine Vorteile gegenüber anderen Technologien. Diese Arbeit richtet sich an Entscheider, welche sich mit möglichen Technologien zur Skalierung von Datenbanken auseinander setzen, als auch an Datenbankadministratoren, die eine Sharding Umgebung umsetzen.
This book explores emerging practices in distance education that have been facilitated by the development of educational technology. The volume examines core themes in distance education including online education at scale, embodiment in online environments, connectivity in online education and the personalisation of learning experiences within online education. The first section of the book examines online teaching tools, and explores how they are being used to enhance and promote student learning. The second looks at some of the broader challenges encountered by online teachers and those responsible for designing online learning material. While this volume will be of significant interest to distance learning universities and colleges, it will also be a valuable resource to traditional Higher Education Institutions, who are increasingly searching for innovative ways to reach and teach their students. This edited collection will be of value to scholars of online education as well as practitioners and policy makers looking to enrich their notions of online pedagogy.
This book focuses on the analytic principles of business practice and big data. Specifically, it provides an interface between the main disciplines of engineering/technology and the organizational and administrative aspects of management, serving as a complement to books in other disciplines such as economics, finance, marketing and risk analysis. The contributors present their areas of expertise, together with essential case studies that illustrate the successful application of engineering management theories in real-life examples.