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Data Science In Engineering And Management


Data Science In Engineering And Management
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Data Analytics For Engineering And Construction Project Risk Management


Data Analytics For Engineering And Construction Project Risk Management
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Author : Ivan Damnjanovic
language : en
Publisher:
Release Date : 2020

Data Analytics For Engineering And Construction Project Risk Management written by Ivan Damnjanovic and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Engineering categories.


This book provides a step-by-step guidance on how to implement analytical methods in project risk management. The text focuses on engineering design and construction projects and as such is suitable for graduate students in engineering, construction, or project management, as well as practitioners aiming to develop, improve, and/or simplify corporate project management processes. The book places emphasis on building data-driven models for additive-incremental risks, where data can be collected on project sites, assembled from queries of corporate databases, and/or generated using procedures for eliciting experts' judgments. While the presented models are mathematically inspired, they are nothing beyond what an engineering graduate is expected to know: some algebra, a little calculus, a little statistics, and, especially, undergraduate-level understanding of the probability theory. The book is organized in three parts and fourteen chapters. In Part I the authors provide the general introduction to risk and uncertainty analysis applied to engineering construction projects. The basic formulations and the methods for risk assessment used during project planning phase are discussed in Part II, while in Part III the authors present the methods for monitoring and (re)assessment of risks during project execution.



Handbook Of Data Science Approaches For Biomedical Engineering


Handbook Of Data Science Approaches For Biomedical Engineering
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Author : Valentina Emilia Balas
language : en
Publisher: Academic Press
Release Date : 2019-11-13

Handbook Of Data Science Approaches For Biomedical Engineering written by Valentina Emilia Balas and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-13 with Science categories.


Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering progress and the ways they are aligning with the latest technologies in IoT and big data. In addition, the book includes various real-time/offline medical applications that directly or indirectly rely on medical and information technology. Case studies in the field of medical science, i.e., biomedical engineering, computer science, information security, and interdisciplinary tools, along with modern tools and the technologies used are also included to enhance understanding. Today, the role of Big Data and IoT proves that ninety percent of data currently available has been generated in the last couple of years, with rapid increases happening every day. The reason for this growth is increasing in communication through electronic devices, sensors, web logs, global positioning system (GPS) data, mobile data, IoT, etc. - Provides in-depth information about Biomedical Engineering with Big Data and Internet of Things - Includes technical approaches for solving real-time healthcare problems and practical solutions through case studies in Big Data and Internet of Things - Discusses big data applications for healthcare management, such as predictive analytics and forecasting, big data integration for medical data, algorithms and techniques to speed up the analysis of big medical data, and more



Data Driven Science And 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®.



Data Science And Digital Business


Data Science And Digital Business
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Author : Fausto Pedro García Márquez
language : en
Publisher: Springer
Release Date : 2019-01-04

Data Science And Digital Business written by Fausto Pedro García Márquez and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-04 with Business & Economics categories.


This book combines the analytic principles of digital business and data science with business practice and big data. The interdisciplinary, contributed volume provides an interface between the main disciplines of engineering and technology and business administration. Written for managers, engineers and researchers who want to understand big data and develop new skills that are necessary in the digital business, it not only discusses the latest research, but also presents case studies demonstrating the successful application of data in the digital business.



Data Science In Engineering And Management


Data Science In Engineering And Management
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Author : Zdzislaw Polkowski
language : en
Publisher: CRC Press
Release Date : 2021-12-30

Data Science In Engineering And Management written by Zdzislaw Polkowski and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-30 with Business & Economics categories.


This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis. Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively. This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.



Big Data Cloud Computing Data Science Engineering


Big Data Cloud Computing Data Science Engineering
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Author : Roger Lee
language : en
Publisher: Springer
Release Date : 2018-08-13

Big Data Cloud Computing Data Science Engineering written by Roger Lee and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-13 with Technology & Engineering categories.


This book presents the outcomes of the 3rd IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2018), which was held on July 10–12, 2018 in Kanazawa. The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science, to share their experiences, and to exchange new ideas and information in a meaningful way. All aspects (theory, applications and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them are all explored here. The conference organizers selected the best papers from among those accepted for presentation. The papers were chosen on the basis of review scores submitted by members of the program committee and subsequently underwent further rigorous review. Following this second round of review, 13 of the conference’s most promising papers were selected for this Springer (SCI) book. We eagerly await the important contributions that we know these authors will make to the field of computer and information science.



Big Data And Data Science Engineering


Big Data And Data Science Engineering
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Author : Roger Lee
language : en
Publisher: Springer Nature
Release Date : 2025-05-23

Big Data And Data Science Engineering written by Roger Lee and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-23 with Computers categories.


This book reports state-of-the-art results in big data and data science engineering in both printed and electronic forms. Studies in computation intelligence (SCI) has grown into the most comprehensive computational intelligence research forum available in the world. This book publishes original papers on both theory and practice that address foundations, state-of-the-art problems and solutions, and crucial challenges.



Artificial Intelligence In Construction Engineering And Management


Artificial Intelligence In Construction Engineering And Management
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Author : Limao Zhang
language : en
Publisher: Springer Nature
Release Date : 2021-06-18

Artificial Intelligence In Construction Engineering And Management written by Limao Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-18 with Technology & Engineering categories.


This book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in construction but also enhancing the competitiveness globally.



Perspectives On Data Science For Software Engineering


Perspectives On Data Science For Software Engineering
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Author : Tim Menzies
language : en
Publisher: Morgan Kaufmann
Release Date : 2016-07-13

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 2016-07-13 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.



Data Analytics And Management


Data Analytics And Management
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Author : Ashish Khanna
language : en
Publisher: Springer Nature
Release Date : 2021-01-04

Data Analytics And Management written by Ashish Khanna and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-04 with Technology & Engineering categories.


This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2020), held at Jan Wyzykowski University, Poland, during June 2020. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students.