Download or read book Advances in Artificial Intelligence and Data Engineering written by Niranjan N. Chiplunkar and published by Springer Nature. This book was released on 2020-08-13 with total page 1456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected peer-reviewed papers from the International Conference on Artificial Intelligence and Data Engineering (AIDE 2019). The topics covered are broadly divided into four groups: artificial intelligence, machine vision and robotics, ambient intelligence, and data engineering. The book discusses recent technological advances in the emerging fields of artificial intelligence, machine learning, robotics, virtual reality, augmented reality, bioinformatics, intelligent systems, cognitive systems, computational intelligence, neural networks, evolutionary computation, speech processing, Internet of Things, big data challenges, data mining, information retrieval, and natural language processing. Given its scope, this book can be useful for students, researchers, and professionals interested in the growing applications of artificial intelligence and data engineering.

Download or read book Advances in Model and Data Engineering written by Shapiro Paul and published by . This book was released on 2019-11 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Recent Advances in Artificial Intelligence and Data Engineering written by Pushparaj Shetty D. and published by Springer Nature. This book was released on 2021-10-31 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents select proceedings of the International Conference on Artificial Intelligence and Data Engineering (AIDE 2020). Various topics covered in this book include deep learning, neural networks, machine learning, computational intelligence, cognitive computing, fuzzy logic, expert systems, brain-machine interfaces, ant colony optimization, natural language processing, bioinformatics and computational biology, cloud computing, machine vision and robotics, ambient intelligence, intelligent transportation, sensing and sensor networks, big data challenge, data science, high performance computing, data mining and knowledge discovery, and data privacy and security. The book will be a valuable reference for beginners, researchers, and professionals interested in artificial intelligence, robotics and data engineering.

Download or read book Modeling Simulation Based Data Engineering written by Bernard P. Zeigler and published by Elsevier. This book was released on 2007-08-07 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Engineering has become a necessary and critical activity for business, engineering, and scientific organizations as the move to service oriented architecture and web services moves into full swing. Notably, the US Department of Defense is mandating that all of its agencies and contractors assume a defining presence on the Net-centric Global Information Grid. This book provides the first practical approach to data engineering and modeling, which supports interoperabililty with consumers of the data in a service- oriented architectures (SOAs). Although XML (eXtensible Modeling Language) is the lingua franca for such interoperability, it is not sufficient on its own. The approach in this book addresses critical objectives such as creating a single representation for multiple applications, designing models capable of supporting dynamic processes, and harmonizing legacy data models for web-based co-existence. The approach is based on the System Entity Structure (SES) which is a well-defined structure, methodology, and practical tool with all of the functionality of UML (Unified Modeling Language) and few of the drawbacks. The SES originated in the formal representation of hierarchical simulation models. So it provides an axiomatic formalism that enables automating the development of XML dtds and schemas, composition and decomposition of large data models, and analysis of commonality among structures. Zeigler and Hammond include a range of features to benefit their readers. Natural language, graphical and XML forms of SES specification are employed to allow mapping of legacy meta-data. Real world examples and case studies provide insight into data engineering and test evaluation in various application domains. Comparative information is provided on concepts of ontologies, modeling and simulation, introductory linguistic background, and support options enable programmers to work with advanced tools in the area. The website of the Arizona Center for Integrative Modeling and Simulation, co-founded by Zeigler in 2001, provides links to downloadable software to accompany the book. The only practical guide to integrating XML and web services in data engineering Introduces linguistic levels of interoperability for effective information exchange Covers the interoperability standards mandated by national and international agencies Complements Zeigler's classic THEORY OF MODELING AND SIMULATION

Download or read book Data Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Download or read book Current Trends and Advances in Computer Aided Intelligent Environmental Data Engineering written by Goncalo Marques and published by Elsevier. This book was released on 2022-03-22 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: Current Trends and Advances in Computer-Aided Intelligent Environmental Data Engineering merges computer engineering and environmental engineering. The book presents the latest finding on how data science and AI-based tools are being applied in environmental engineering research. This application involves multiple domains such as data science and artificial intelligence to transform the data collected by intelligent sensors into relevant and reliable information to support decision-making. These tools include fuzzy logic, knowledge-based systems, particle swarm optimization, genetic algorithms, Monte Carlo simulation, artificial neural networks, support vector machine, boosted regression tree, simulated annealing, ant colony algorithm, decision tree, immune algorithm, and imperialist competitive algorithm. This book is a fundamental information source because it is the first book to present the foundational reference material in this new research field. Furthermore, it gives a critical overview of the latest cross-domain research findings and technological developments on the recent advances in computer-aided intelligent environmental data engineering. Captures the application of data science and artificial intelligence for a broader spectrum of environmental engineering problems Presents methods and procedures as well as case studies where state-of-the-art technologies are applied in actual environmental scenarios Offers a compilation of essential and critical reviews on the application of data science and artificial intelligence to the entire spectrum of environmental engineering

Download or read book Emerging Research in Data Engineering Systems and Computer Communications written by P. Venkata Krishna and published by Springer Nature. This book was released on 2020-02-10 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected papers presented at the 2nd International Conference on Computing, Communications and Data Engineering, held at Sri Padmavati Mahila Visvavidyalayam, Tirupati, India from 1 to 2 Feb 2019. Chiefly discussing major issues and challenges in data engineering systems and computer communications, the topics covered include wireless systems and IoT, machine learning, optimization, control, statistics, and social computing.

Download or read book Data Engineering written by Olaf Wolkenhauer and published by John Wiley & Sons. This book was released on 2004-04-07 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although data engineering is a multi-disciplinary field withapplications in control, decision theory, and the emerging hot areaof bioinformatics, there are no books on the market that make thesubject accessible to non-experts. This book fills the gap in thefield, offering a clear, user-friendly introduction to the maintheoretical and practical tools for analyzing complex systems. Anftp site features the corresponding MATLAB and Mathematical toolsand simulations. Market: Researchers in data management, electrical engineering,computer science, and life sciences.

Download or read book Advances in Machine Learning Applications in Software Engineering written by Zhang, Du and published by IGI Global. This book was released on 2006-10-31 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides analysis, characterization and refinement of software engineering data in terms of machine learning methods. It depicts applications of several machine learning approaches in software systems development and deployment, and the use of machine learning methods to establish predictive models for software quality while offering readers suggestions by proposing future work in this emerging research field"--Provided by publisher.

Download or read book Advances in Model and Data Engineering in the Digitalization Era written by Ladjel Bellatreche and published by Springer Nature. This book was released on 2021-10-06 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed papers of the workshops held at the 10th International Conference on New Trends in Model and Data Engineering, MEDI 2021, held in Tallinn, Estonia, in June 2021: Workshop on moDeling, vErification and Testing of dEpendable CriTical systems, DETECT 2021; Symposium on Intelligent and Autonomous Systems, SIAS 2021; Worjshop on Control Software: Methods, Models, and Languages, CSMML 2021; Blockchain for Inter-Organizational Collaboration, BIOC 2021; The International Health Data Workshop, HEDA 2021. The 20 full and the 4 short workshop papers presented were carefully reviewed and selected from 61 submissions. The papers are organized according to the workshops: Workshop on moDeling, vErification and Testing of dEpendable CriTical systems, DETECT 2021; Symposium on Intelligent and Autonomous Systems, SIAS 2021; Worjshop on Control Software: Methods, Models, and Languages, CSMML 2021; Blockchain for Inter-Organizational Collaboration, BIOC 2021; The International Health Data Workshop, HEDA 2021.

Download or read book Data Engineering on Azure written by Vlad Riscutia and published by Simon and Schuster. This book was released on 2021-08-17 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build a data platform to the industry-leading standards set by Microsoft’s own infrastructure. Summary In Data Engineering on Azure you will learn how to: Pick the right Azure services for different data scenarios Manage data inventory Implement production quality data modeling, analytics, and machine learning workloads Handle data governance Using DevOps to increase reliability Ingesting, storing, and distributing data Apply best practices for compliance and access control Data Engineering on Azure reveals the data management patterns and techniques that support Microsoft’s own massive data infrastructure. Author Vlad Riscutia, a data engineer at Microsoft, teaches you to bring an engineering rigor to your data platform and ensure that your data prototypes function just as well under the pressures of production. You'll implement common data modeling patterns, stand up cloud-native data platforms on Azure, and get to grips with DevOps for both analytics and machine learning. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Build secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify. About the book In Data Engineering on Azure you’ll learn the skills you need to build and maintain big data platforms in massive enterprises. This invaluable guide includes clear, practical guidance for setting up infrastructure, orchestration, workloads, and governance. As you go, you’ll set up efficient machine learning pipelines, and then master time-saving automation and DevOps solutions. The Azure-based examples are easy to reproduce on other cloud platforms. What's inside Data inventory and data governance Assure data quality, compliance, and distribution Build automated pipelines to increase reliability Ingest, store, and distribute data Production-quality data modeling, analytics, and machine learning About the reader For data engineers familiar with cloud computing and DevOps. About the author Vlad Riscutia is a software architect at Microsoft. Table of Contents 1 Introduction PART 1 INFRASTRUCTURE 2 Storage 3 DevOps 4 Orchestration PART 2 WORKLOADS 5 Processing 6 Analytics 7 Machine learning PART 3 GOVERNANCE 8 Metadata 9 Data quality 10 Compliance 11 Distributing data

Download or read book Advances and Applications in Model Driven Engineering written by Díaz, Vicente García and published by IGI Global. This book was released on 2013-08-31 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: As organizations and research institutions continue to emphasize model-driven engineering (MDE) as a first-class approach in the software development process of complex systems, the utilization of software in multiple domains and professional networks is becoming increasingly vital. Advances and Applications in Model-Driven Engineering explores this relatively new approach in software development that can increase the level of abstraction of development of tasks. This publication covers the issues of bridging the gaps between various disciplines within software engineering and computer science. Professionals, researchers, and students will discover the most current tools and techniques available in the field to maximize efficiency of model-driven software development.

Download or read book Advanced Data Analysis and Modelling in Chemical Engineering written by Denis Constales and published by Elsevier. This book was released on 2016-08-23 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Data Analysis and Modeling in Chemical Engineering provides the mathematical foundations of different areas of chemical engineering and describes typical applications. The book presents the key areas of chemical engineering, their mathematical foundations, and corresponding modeling techniques. Modern industrial production is based on solid scientific methods, many of which are part of chemical engineering. To produce new substances or materials, engineers must devise special reactors and procedures, while also observing stringent safety requirements and striving to optimize the efficiency jointly in economic and ecological terms. In chemical engineering, mathematical methods are considered to be driving forces of many innovations in material design and process development. Presents the main mathematical problems and models of chemical engineering and provides the reader with contemporary methods and tools to solve them Summarizes in a clear and straightforward way, the contemporary trends in the interaction between mathematics and chemical engineering vital to chemical engineers in their daily work Includes classical analytical methods, computational methods, and methods of symbolic computation Covers the latest cutting edge computational methods, like symbolic computational methods

Download or read book Proceedings of the International Conference on Data Engineering and Communication Technology written by Suresh Chandra Satapathy and published by Springer. This book was released on 2016-08-24 with total page 841 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume book contains research work presented at the First International Conference on Data Engineering and Communication Technology (ICDECT) held during March 10–11, 2016 at Lavasa, Pune, Maharashtra, India. The book discusses recent research technologies and applications in the field of Computer Science, Electrical and Electronics Engineering. The aim of the Proceedings is to provide cutting-edge developments taking place in the field data engineering and communication technologies which will assist the researchers and practitioners from both academia as well as industry to advance their field of study.

Download or read book Advances in Model and Data Engineering in the Digitalization Era written by Philippe Fournier-Viger and published by Springer Nature. This book was released on 2023-01-09 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes short papers and DETECT 2022 workshop papers, presented during the 11th International Conference on Model and Data Engineering, MEDI 2022, held in Cairo, Egypt, in November 2022. The 11 short papers presented were selected from the total of 65 submissions. This volume also contains the 4 accepted papers from the DETECT 2022 workshop, held at MEDI 2022. The volume focuses on advances in data management and modelling, including topics such as data models, data processing, database theory, database systems technology, and advanced database applications.

Download or read book Data Engineering and Data Science written by Kukatlapalli Pradeep Kumar and published by John Wiley & Sons. This book was released on 2023-08-29 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: DATA ENGINEERING and DATA SCIENCE Written and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the “one-stop shop” for the concepts and applications of data science and engineering for data scientists across many industries. The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesn’t need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information. In this exciting new volume, the team of editors and contributors sketch the broad outlines of data engineering, then walk through more specific descriptions that illustrate specific data engineering roles. Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This book brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.

Download or read book Advances in Computer Science for Engineering and Education written by Zhengbing Hu and published by Springer Nature. This book was released on 2022-04-27 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains high-quality refereed research papers presented at the Fifth International Conference on Computer Science, Engineering, and Education Applications (ICCSEEA2022), which took place in Kyiv, Ukraine, on February 21–22, 2022, and was organized by the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute," National Aviation University, and the International Research Association of Modern Education and Computer Science. State-of-the-art studies in computer science, artificial intelligence, engineering methodologies, genetic coding systems, deep learning with medical applications, and knowledge representation with educational applications are among the topics covered in the book. For academics, graduate students, engineers, management practitioners, and undergraduate students interested in computer science and its applications in engineering and education, this book is a valuable resource.