Data Science In Engineering Volume 10

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Data Science In Engineering Volume 10

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Author : Ramin Madarshahian
language : en
Publisher: Springer Nature
Release Date : 2023-12-07

Data Science In Engineering Volume 10 written by Ramin Madarshahian and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-07 with Computers categories.

Data Science in Engineering, Volume 10: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics, 2023, the tenth volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Data Science in Engineering, including papers on: Novel Data-driven Analysis Methods Deep Learning Gaussian Process Analysis Real-time Video-based Analysis Applications to Nonlinear Dynamics and Damage Detection High-rate Structural Monitoring and Prognostics

Data Science In Engineering Vol 10

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Author : Thomas Matarazzo
language : en
Publisher: Springer Nature
Release Date : 2024-10-16

Data Science In Engineering Vol 10 written by Thomas Matarazzo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-16 with Computers categories.

Data Science in Engineering, Volume 10: Proceedings of the 42nd IMAC, A Conference and Exposition on Structural Dynamics, 2024, the tenth volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Data Science in Engineering, including papers on: Novel Data-driven Analysis Methods Deep Learning Gaussian Process Analysis Real-time Video-based Analysis Applications to Nonlinear Dynamics and Damage Detection Data-driven System Prognostics

Data Mining For Scientific And Engineering Applications

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Author : R.L. Grossman
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-01

Data Mining For Scientific And Engineering Applications written by R.L. Grossman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-01 with Computers categories.

Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.

Data Driven Science And Engineering

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Author : Steven L. Brunton
language : en
Publisher: Cambridge University Press
Release Date : 2022-05-05

Data Driven Science And Engineering written by Steven L. Brunton and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-05 with Computers categories.

A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Foundations Of Data Science For Engineering Problem Solving

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Author : Parikshit Narendra Mahalle
language : en
Publisher:
Release Date : 2022

Foundations Of Data Science For Engineering Problem Solving written by Parikshit Narendra Mahalle and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.

This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.

Perspectives On Data Science For Software Engineering

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Author : Tim Menzies
language : en
Publisher: Morgan Kaufmann
Release Date : 2016-07-14

Perspectives On Data Science For Software Engineering written by Tim Menzies and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-14 with Computers categories.

Perspectives on Data Science for Software Engineering presents the best practices of seasoned data miners in software engineering. The idea for this book was created during the 2014 conference at Dagstuhl, an invitation-only gathering of leading computer scientists who meet to identify and discuss cutting-edge informatics topics. At the 2014 conference, the concept of how to transfer the knowledge of experts from seasoned software engineers and data scientists to newcomers in the field highlighted many discussions. While there are many books covering data mining and software engineering basics, they present only the fundamentals and lack the perspective that comes from real-world experience. This book offers unique insights into the wisdom of the community's leaders gathered to share hard-won lessons from the trenches. Ideas are presented in digestible chapters designed to be applicable across many domains. Topics included cover data collection, data sharing, data mining, and how to utilize these techniques in successful software projects. Newcomers to software engineering data science will learn the tips and tricks of the trade, while more experienced data scientists will benefit from war stories that show what traps to avoid. - Presents the wisdom of community experts, derived from a summit on software analytics - Provides contributed chapters that share discrete ideas and technique from the trenches - Covers top areas of concern, including mining security and social data, data visualization, and cloud-based data - Presented in clear chapters designed to be applicable across many domains

Data Driven Engineering Design

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Author : Ang Liu
language : en
Publisher: Springer Nature
Release Date : 2021-10-09

Data Driven Engineering Design written by Ang Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-09 with Technology & Engineering categories.

This 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.

Innovations In Computer Science And Engineering

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Author : H. S. Saini
language : en
Publisher: Springer Nature
Release Date : 2021-04-23

Innovations In Computer Science And Engineering written by H. S. Saini and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-23 with Technology & Engineering categories.

This book features a collection of high-quality, peer-reviewed research papers presented at the 8th International Conference on Innovations in Computer Science & Engineering (ICICSE 2020), held at Guru Nanak Institutions, Hyderabad, India, on 28–29 August 2020. It covers the latest research in data science and analytics, cloud computing, machine learning, data mining, big data and analytics, information security and privacy, wireless and sensor networks and IoT applications, artificial intelligence, expert systems, natural language processing, image processing, computer vision and artificial neural networks.

Crc Handbook Of Phase Equilibria And Thermodynamic Data Of Aqueous Polymer Solutions

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Author : Christian Wohlfarth
language : en
Publisher: CRC Press
Release Date : 2012-08-10

Crc Handbook Of Phase Equilibria And Thermodynamic Data Of Aqueous Polymer Solutions written by Christian Wohlfarth and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-10 with Science categories.

A large amount of experimental data has been published since the debut of the original CRC Handbook of Thermodynamic Data of Aqueous Polymer Solutions. Incorporating new and updated material, the CRC Handbook of Phase Equilibria and Thermodynamic Data of Aqueous Polymer Solutions provides a comprehensive collection of thermodynamic data of polymer solutions. It helps readers quickly retrieve necessary information from the literature, and assists researchers in planning new measurements where data are missing. A valuable resource for the modern chemistry field, the Handbook clearly details how measurements were conducted and methodically explains the nomenclature. It presents data essential for the production and use of polymers as well as for understanding the physical behavior and intermolecular interactions in polymer solutions.

Emerging Research In Data Engineering Systems And Computer Communications

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Author : P. Venkata Krishna
language : en
Publisher: Springer Nature
Release Date : 2020-02-10

Emerging Research In Data Engineering Systems And Computer Communications written by P. Venkata Krishna and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-10 with Computers categories.

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.