| data science in structural engineering: Structural Health Monitoring Based on Data Science Techniques Alexandre Cury, Diogo Ribeiro, Filippo Ubertini, Michael D. Todd, 2021-10-23 The modern structural health monitoring (SHM) paradigm of transforming in situ, real-time data acquisition into actionable decisions regarding structural performance, health state, maintenance, or life cycle assessment has been accelerated by the rapid growth of “big data” availability and advanced data science. Such data availability coupled with a wide variety of machine learning and data analytics techniques have led to rapid advancement of how SHM is executed, enabling increased transformation from research to practice. This book intends to present a representative collection of such data science advancements used for SHM applications, providing an important contribution for civil engineers, researchers, and practitioners around the world. |
| data science in structural engineering: Data Science for Civil Engineering Rakesh K. Jain, Prashant Shantaram Dhotre, Deepak Tatyasaheb Mane, Parikshit Narendra Mahalle, 2023-05-10 This book explains use of data science-based techniques for modeling and providing optimal solutions to complex problems in civil engineering. It discusses civil engineering problems like air, water and land pollution, climate crisis, transportation infrastructures, traffic and travel modes, mobility services, and so forth. Divided into two sections, the first one deals with the basics of data science and essential mathematics while the second section covers pertinent applications in structural and environmental engineering, construction management, and transportation. Features: Details information on essential mathematics required to implement civil engineering applications using data science techniques. Discusses broad background of data science and its fundamentals. Focusses on structural engineering, transportation systems, water resource management, geomatics, and environmental engineering. Includes python programming libraries to solve complex problems. Addresses various real-world applications of data science based civil engineering use cases. This book aims at senior undergraduate students in Civil Engineering and Applied Data Science. |
| data science in structural engineering: Data-Driven Science and Engineering Steven L. Brunton, J. Nathan Kutz, 2022-05-05 A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®. |
| data science in structural engineering: Data Science in Engineering, Volume 9 Ramin Madarshahian, Francois Hemez, 2021-10-04 Data Science and Engineering Volume 9: Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics, 2021, the ninth volume of nine 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: Data Science in Engineering Applications Engineering Mathematics Computational Methods in Engineering |
| data science in structural engineering: Data Science in Engineering, Volume 10 Ramin Madarshahian, François Hemez, 2023-12-07 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 structural engineering: Artificial Intelligence in Structural Engineering Ian Smith, 1998-07-15 This book presents the state of the art of artificial intelligence techniques applied to structural engineering. The 28 revised full papers by leading scientists were solicited for presentation at a meeting held in Ascona, Switzerland, in July 1998. The recent advances in information technology, in particular decreasing hardware cost, Internet communication, faster computation, increased bandwidth, etc., allow for the application of new AI techniques to structural engineering. The papers presented deal with new aspects of information technology support for the design, analysis, monitoring, control and diagnosis of various structural engineering systems. |
| data science in structural engineering: Hybrid Metaheuristics in Structural Engineering Gebrail Bekdaş, Sinan Melih Nigdeli, 2023-06-15 From the start of life, people used their brains to make something better in design in ordinary works. Due to that, metaheuristics are essential to living things, and several inspirations from life have been used in the generation of new algorithms. These algorithms have unique features, but the usage of different features of different algorithms may give more effective optimum results in means of precision in optimum results, computational effort, and convergence. This book is a timely book to summarize the latest developments in the optimization of structural engineering systems covering all classical approaches and new trends including hybrids metaheuristic algorithms. Also, artificial intelligence and machine learning methods are included to predict optimum results by skipping long optimization processes. The main objective of this book is to introduce the fundamentals and current development of methods and their applications in structural engineering. |
| data science in structural engineering: Foundations of Data Science for Engineering Problem Solving Parikshit Narendra Mahalle, Gitanjali Rahul Shinde, Priya Dudhale Pise, Jyoti Yogesh Deshmukh, 2021-08-21 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. |
| data science in structural engineering: ICT for Smart Water Systems: Measurements and Data Science Andrea Scozzari, Steve Mounce, Dawei Han, Francesco Soldovieri, Dimitri Solomatine, 2020-11-28 Today, Information and Communication Technologies (ICT) have a pervasive presence in almost every aspect of the management of water. There is no question that the collection of big data from sensing and the insights gained by smart analytics can bring massive benefits. This book focuses on new perspectives for the monitoring, assessment and control of water systems, based on tools and concepts originating from the ICT sector. It presents a portrait of up-to-date sensing techniques for water, and introduces concepts and implications with the analysis of the acquired data. Particular attention is given to the advancements in developing novel devices and data processing approaches. The chapters guide the reader through multiple disciplinary contexts, without aiming to be exhaustive, but with the effort to present relevant topics in such a highly multi-disciplinary framework. This book will be of interest to advanced students, researchers and stakeholders at various levels. |
| data science in structural engineering: The Ethical Frontier of AI and Data Analysis Kumar, Rajeev, Joshi, Ankush, Sharan, Hari Om, Peng, Sheng-Lung, Dudhagara, Chetan R., 2024-03-04 In the advancing fields of artificial intelligence (AI) and data science, a pressing ethical dilemma arises. As technology continues its relentless march forward, ethical considerations within these domains become increasingly complex and critical. Bias in algorithms, lack of transparency, data privacy breaches, and the broader societal repercussions of AI applications are demanding urgent attention. This ethical quandary poses a formidable challenge for researchers, academics, and industry professionals alike, threatening the very foundation of responsible technological innovation. Navigating this ethical minefield requires a comprehensive understanding of the multifaceted issues at hand. The Ethical Frontier of AI and Data Analysis is an indispensable resource crafted to address the ethical challenges that define the future of AI and data science. Researchers and academics who find themselves at the forefront of this challenge are grappling with the evolving landscape of AI and data science ethics. Underscoring the need for this book is the current lack of clarity on ethical frameworks, bias mitigation strategies, and the broader societal implications, which hinder progress and leave a void in the discourse. As the demand for responsible AI solutions intensifies, the imperative for this reliable guide that consolidates, explores, and advances the dialogue on ethical considerations grows exponentially. |
| data science in structural engineering: The Role of Advanced Technologies in Structural Engineering for More Resilient Communities National Academies of Sciences, Engineering, and Medicine, Policy and Global Affairs, Roundtable on Risk, Resilience, and Extreme Events, 2020-09-22 In an effort to develop relationships and promote dialogue and community exchange, the National Academies’ Resilient America Roundtableâ€in partnership with the American Society of Civil Engineers (ASCE), Structural Engineering Institute (SEI), and the Advances in Information Technology Committeeâ€co-hosted a one-day workshop on September 26, 2017. The event brought together experts, practitioners, and researchers from the public, private, and academic sectors to: 1) enhance resilience and promote faster recovery by exploring the role of advanced technologies and structural performance data in existing infrastructure and built systems; 2) discuss the future role of advanced technologies and design practice in promoting community resilience; and 3) identify research gaps or opportunities in development and use of advanced technologies and design for building resilient infrastructure. This publication summarizes the presentations and discussions from the workshop. |
| data science in structural engineering: Machine Learning and Data Science Techniques for Effective Government Service Delivery Ogunleye, Olalekan Samuel, 2024-03-27 In our data-rich era, extracting meaningful insights from the vast amount of information has become a crucial challenge, especially in government service delivery where informed decisions are paramount. Traditional approaches struggle with the enormity of data, highlighting the need for a new approach that integrates data science and machine learning. The book, Machine Learning and Data Science Techniques for Effective Government Service Delivery, becomes a vital resource in this transformation, offering a deep understanding of these technologies and their applications. Within the complex landscape of modern governance, this book stands as a solution-oriented guide. Recognizing data's value in the 21st century, it navigates the world of data science and machine learning, enhancing the mechanics of government service. By addressing citizens' evolving needs, these advanced methods counter inefficiencies in traditional systems. Tailored for experts across technology, academia, and government, the book bridges theory and practicality. Covering foundational concepts and innovative applications, it explores the potential of data-driven decision-making for a more efficient and citizen-centric government future. |
| data science in structural engineering: Machine Learning, Optimization, and Data Science Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Panos Pardalos, Giuseppe Di Fatta, Giovanni Giuffrida, Renato Umeton, 2023-03-09 This two-volume set, LNCS 13810 and 13811, constitutes the refereed proceedings of the 8th International Conference on Machine Learning, Optimization, and Data Science, LOD 2022, together with the papers of the Second Symposium on Artificial Intelligence and Neuroscience, ACAIN 2022. The total of 84 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 226 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications. |
| data science in structural engineering: The Grants Register 2023 Palgrave Macmillan, 2022-09-28 The Grants Register 2023 is the most authoritative and comprehensive guide available of postgraduate and professional funding worldwide. It contains international coverage of grants in almost 60 countries, both English and non-English speaking; information on subject areas, level of study, eligibility and value of awards; and information on over 6,000 awards provided by over 1,300 awarding bodies. Awarding bodies are arranged alphabetically with a full list of awards to allow for comprehensive reading. The Register contains full contact details including telephone, fax, email and websites as well as details of application procedures and closing dates. It is updated annually to ensure accurate information. |
| data science in structural engineering: Proceedings of the 6th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures Xiang-Lin Gu, Masoud Motavalli, Alper Ilki, Qian-Qian Yu, 2024-02-27 This book is a compilation of selected papers from the 6th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures (SMAR 2022). The work focuses on the state-of-the-practice and recent advances in testing and monitoring technology, in structural modeling and assessment methods, and in the application of advanced materials for structural rehabilitation. The contents make valuable contributions to international professors, research scientists, professional engineers, postdoctoral fellows and postgraduate students. |
| data science in structural engineering: Campus Plus 2024 Infokerala Communications Pvt Ltd, 2024-06-01 Education stands as the cornerstone of societal advancement, igniting personal growth and laying the foundation for prosperous nations. It is through education that individuals unlock their potential, broaden their horizons, and envision a future brimming with opportunities. India, renowned for its diverse heritage and rich cultural fabric, boasts an education system that has nurtured brilliant minds and contributed immensely to intellectual and economic progress. Within India, the state of Kerala shines as a beacon of enlightenment in the realm of education. Nestled amidst verdant landscapes, tranquil backwaters, and a vibrant cultural milieu, Kerala's educational institutions offer a unique blend of traditional wisdom and modern pedagogical approaches. This coffee table book, Campus Plus, delves into the intricacies of India's educational landscape, with a special emphasis on Kerala's esteemed institutions. Through captivating narratives, stunning visuals, and insightful anecdotes, it takes readers on a journey through the campuses that have shaped Kerala's intellectual framework. It unravels stories of achievement and transformation, highlighting the symbiotic relationship between ancient knowledge systems and contemporary advancements in research and technology. As you immerse yourself in the pages of Campus Plus, you'll gain a deeper appreciation for India's educational mosaic. You'll discover the visionaries, educators, and students whose contributions have propelled the nation forward. This book celebrates the power of education and pays homage to institutions that have nurtured generations of leaders. It invites readers to explore, understand, and celebrate Kerala's educational tapestry - a testament to the fusion of tradition and innovation. Join us on this enriching journey through Campus Plus, where the past converges with the present, and aspirations take flight toward a brighter tomorrow. |
| data science in structural engineering: Campus Plus 2022 Infokerala Communications Pvt Ltd, 2022-07-11 India, bounded by the majestic Himalayan ranges in the North and edged by an endless stretch of golden beaches, is the land of hoary tradition and cultural diversity. A vivid kaleidoscope of landscapes, glorious historical sites and royal cities, misty mountain hideaways, colourful people, rich civilizations and festivities craft India Incredible. Recent years have witnessed the educational scene, especially the higher education sector in the State undergoing a sea change in respect of quality, diversity and accessibility in tune with the global trends. Kerala’s surge in the educational front is to be viewed in the backdrop of the country’s great legacy in education. India has been a major seat of learning for thousands of years. The country was home to Takshashila, the first university in the world and Aryabhama, the inventor of the digit Zero. In fact, education in Kerala has now become more value-added and affordable, thanks to the proactive initiatives of the State Government and the active involvement of the private sector. Moreover, in the higher education market, Kerala has a significant edge in respect of cost which means that there would be a growing influx of candidates into the state from outside the state for better and affordable professional education in the days to come. With the most sought-after professionals and an excellent network of institutes, Kerala is becoming the very preferred educational destination in the world. And, we are equipped for you with some elucidations which step-up her significance on the educational map. In Campus Plus, we propose some valuable information along with a number of educational institutes in the State which will be useful for the students and parents in the higher education scenario. |
| data science in structural engineering: Artificial Intelligence in Construction Engineering and Management Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski, 2021-06-18 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. |
| data science in structural engineering: Proceedings of International Conference on Machine Intelligence and Data Science Applications Manish Prateek, 2021 This 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, on September 4 and 5, 2020. The book starts by addressing 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 image processing, natural language processing, computer vision, sentiment analysis, and speech and gesture analysis have been included with upfront details. The book concludes with interdisciplinary applications like legal, health care, smart society, cyber physical system and smart agriculture. The book is a good reference for computer science engineers, lecturers/researchers in machine intelligence discipline and engineering graduates. |
| data science in structural engineering: Computational Intelligence in Data Science Mieczyslaw Lech Owoc, |
| data science in structural engineering: Handbook of Research on Data Science and Cybersecurity Innovations in Industry 4.0 Technologies Murugan, Thangavel, E., Nirmala, 2023-09-21 Disruptive innovations are now propelling Industry 4.0 (I4.0) and presenting new opportunities for value generation in all major industry segments. I4.0 technologies' innovations in cybersecurity and data science provide smart apps and services with accurate real-time monitoring and control. Through enhanced access to real-time information, it also aims to increase overall effectiveness, lower costs, and increase the efficiency of people, processes, and technology. The Handbook of Research on Data Science and Cybersecurity Innovations in Industry 4.0 Technologies discusses the technological foundations of cybersecurity and data science within the scope of the I4.0 landscape and details the existing cybersecurity and data science innovations with I4.0 applications, as well as state-of-the-art solutions with regard to both academic research and practical implementations. Covering key topics such as data science, blockchain, and artificial intelligence, this premier reference source is ideal for industry professionals, computer scientists, scholars, researchers, academicians, practitioners, instructors, and students. |
| data science in structural engineering: Recent Developments in Electronics and Communication Systems KVS Ramachandra Murthy, S. Kumar, M. Kumar Singh, 2023-01-31 Often, no single field or expert has all the information necessary to solve complex problems, and this is no less true in the fields of electronics and communications systems. Transdisciplinary engineering solutions can address issues arising when a solution is not evident during the initial development stages in the multidisciplinary area. This book presents the proceedings of RDECS-2022, the 1st international conference on Recent Developments in Electronics and Communication Systems, held on 22 and 23 July 2022 at Aditya Engineering College, Surampalem, India. The primary goal of RDECS-2022 was to challenge existing ideas and encourage interaction between academia and industry to promote the sort of collaborative activities involving scientists, engineers, professionals, researchers, and students that play a major role in almost all fields of scientific growth. The conference also aimed to provide an arena for showcasing advancements and research endeavors being undertaken in all parts of the world. A large number of technical papers with rich content, describing ground-breaking research from participants from various institutes, were submitted for presentation at the conference. This book presents 108 of these papers, which cover a wide range of topics ranging from cloud computing to disease forecasting and from weather reporting to the detection of fake news. Offering a fascinating overview of recent research and developments in electronics and communications systems, the book will be of interest to all those working in the field. |
| data science in structural engineering: Advanced Materials and Structural Engineering Jong Wan Hu, 2016-02-03 The ICAMEST 2015 Conference covered new developments in advanced materials and engineering structural technology. Applications in civil, mechanical, industrial and material science are covered in this book. Providing high-quality, scholarly research, addressing developments, applications and implications in the field of structural health monitoring, construction safety and management, sensors and measurements. This volume contains new models for nonlinear structural analysis and applications of modeling identification. Furthermore, advanced chemical materials are discussed with applications in mechanical and civil engineering and for the maintenance of new materials. In addition, a new system of pressure regulating and water conveyance based on small and middle hydropower stations is discussed. An experimental investigation of the ultimate strength and behavior of the three types of steel tubular K-joints was presented. Furthermore, real-time and frequency linear and nonlinear modeling performance of materials of structures contents were concluded with the notion of a fully brittle material, and this approach is implemented in the book by outlining a finite-element method for the prediction of the construction performance and cracking patterns of arbitrary structural concrete forms. This book is an ideal reference for practicing engineers in material, mechanical and civil engineering and consultants (design, construction, maintenance), and can also be used as a reference for students in mechanical and civil engineering courses. |
| data science in structural engineering: Life-Cycle of Structures and Infrastructure Systems Fabio Biondini, Dan M. Frangopol, 2023-06-28 Life-Cycle of Structures and Infrastructure Systems contains the lectures and papers presented at IALCCE 2023- The Eighth International Symposium on Life-Cycle Civil Engineering, held at Politecnico di Milano, Milan, Italy, 2-6 July, 2023. This book contains the full papers of 514 contributions presented at IALCCE 2023, including the Fazlur R. Khan Plenary Lecture, nine Keynote Lectures, and 504 technical papers from 45 countries. The papers cover recent advances and cutting-edge research in the field of life-cycle civil engineering, including emerging concepts and innovative applications related to life-cycle design, assessment, inspection, monitoring, repair, maintenance, rehabilitation, and management of structures and infrastructure systems under uncertainty. Major topics covered include life-cycle safety, reliability, risk, resilience and sustainability, life-cycle damaging processes, life-cycle design and assessment, life-cycle inspection and monitoring, life-cycle maintenance and management, life-cycle performance of special structures, life-cycle cost of structures and infrastructure systems, and life-cycle-oriented computational tools, among others. This Open Access Book provides both an up-to-date overview of the field of life-cycle civil engineering and significant contributions to the process of making more rational decisions to mitigate the life-cycle risk and improve the life-cycle reliability, resilience, and sustainability of structures and infrastructure systems exposed to multiple natural and human-made hazards in a changing climate. It will serve as a valuable reference to all concerned with life-cycle of civil engineering systems, including students, researchers, practicioners, consultants, contractors, decision makers, and representatives of managing bodies and public authorities from all branches of civil engineering. |
| data science in structural engineering: Structural Health Monitoring of Civil Infrastructure Systems Vistasp M. Karbhari, Farhad Ansari, 2009-08-25 Structural health monitoring is an extremely important methodology in evaluating the 'health' of a structure by assessing the level of deterioration and remaining service life of civil infrastructure systems. This book reviews key developments in research, technologies and applications in this area of civil engineering. It discusses ways of obtaining and analysing data, sensor technologies and methods of sensing changes in structural performance characteristics. It also discusses data transmission and the application of both individual technologies and entire systems to bridges and buildings.With its distinguished editors and international team of contributors, Structural health monitoring of civil infrastructure systems is a valuable reference for students in civil and structural engineering programs as well as those studying sensors, data analysis and transmission at universities. It will also be an important source for practicing civil engineers and designers, engineers and researchers developing sensors, network systems and methods of data transmission and analysis, policy makers, inspectors and those responsible for the safety and service life of civil infrastructure. - Reviews key developments in research, technologies and applications - Discusses systems used to obtain and analyse data and sensor technologies - Assesses methods of sensing changes in structural performance |
| data science in structural engineering: Frontiers in Built Environment, editor’s picks 2023 Izuru Takewaki, 2024-03-19 Dear readers of Frontiers in Built Environment, As the Field Chief Editor for Frontiers in Built Environment, I am happy to present this curated selection of papers that have made a significant impact within our community. Among the large number of submissions that we received, these 14 papers represent some of the best published in 2023, the year when the journal attained its first impact factor. With many high-quality papers to consider, in selecting these 14 articles we faced the challenging task of how to include papers from across the 15 distinct sections of the journal whilst at the same time achieving a sense of cohesion to the ebook overall. However, amidst this diversity, we noticed a convergence in our highest-quality papers around three pivotal themes that are central to our journal’s mission: resilience, sustainability, and technology. In this way, despite the broad range of topics covered within both our journal and this selection, this ebook can truly be considered representative of our journal as a whole. These carefully chosen papers encompass high-quality original research and comprehensive reviews, which also embody the ethos of innovation and excellence that defines our journal. As the Field Chief Editor, I am thankful to all authors who have enriched our journal with their high-caliber work. I extend sincere appreciation to the dedicated efforts of our editors and reviewers, whose invaluable contributions have been instrumental in shaping Frontiers in Built Environment in 2023. |
| data science in structural engineering: Proceedings of the 18th International Conference on Computing in Civil and Building Engineering Eduardo Toledo Santos, Sergio Scheer, 2020-07-14 This book gathers the latest advances, innovations, and applications in the field of information technology in civil and building engineering, presented at the 18th International Conference on Computing in Civil and Building Engineering (ICCCBE), São Paulo, Brazil, August 18-20, 2020. It covers highly diverse topics such as BIM, construction information modeling, knowledge management, GIS, GPS, laser scanning, sensors, monitoring, VR/AR, computer-aided construction, product and process modeling, big data and IoT, cooperative design, mobile computing, simulation, structural health monitoring, computer-aided structural control and analysis, ICT in geotechnical engineering, computational mechanics, asset management, maintenance, urban planning, facility management, and smart cities. Written by leading researchers and engineers, and selected by means of a rigorous international peer-review process, the contributions highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaborations. |
| data science in structural engineering: Data Science and Simulation in Transportation Research Janssens, Davy, 2013-12-31 Given its effective techniques and theories from various sources and fields, data science is playing a vital role in transportation research and the consequences of the inevitable switch to electronic vehicles. This fundamental insight provides a step towards the solution of this important challenge. Data Science and Simulation in Transportation Research highlights entirely new and detailed spatial-temporal micro-simulation methodologies for human mobility and the emerging dynamics of our society. Bringing together novel ideas grounded in big data from various data mining and transportation science sources, this book is an essential tool for professionals, students, and researchers in the fields of transportation research and data mining. |
| data science in structural engineering: Structural Health Monitoring of Large Civil Engineering Structures Hua-Peng Chen, 2018-01-29 A critical review of key developments and latest advances in Structural Health Monitoring technologies applied to civil engineering structures, covering all aspects required for practical application Structural Health Monitoring (SHM) provides the facilities for in-service monitoring of structural performance and damage assessment, and is a key element of condition based maintenance and damage prognosis. This comprehensive book brings readers up to date on the most important changes and advancements in the structural health monitoring technologies applied to civil engineering structures. It covers all aspects required for such monitoring in the field, including sensors and networks, data acquisition and processing, damage detection techniques and damage prognostics techniques. The book also includes a number of case studies showing how the techniques can be applied in the development of sustainable and resilient civil infrastructure systems. Structural Health Monitoring of Large Civil Engineering Structures offers in-depth chapter coverage of: Sensors and Sensing Technology for Structural Monitoring; Data Acquisition, Transmission, and Management; Structural Damage Identification Techniques; Modal Analysis of Civil Engineering Structures; Finite Element Model Updating; Vibration Based Damage Identification Methods; Model Based Damage Assessment Methods; Monitoring Based Reliability Analysis and Damage Prognosis; and Applications of SHM Strategies to Large Civil Structures. Presents state-of-the-art SHM technologies allowing asset managers to evaluate structural performance and make rational decisions Covers all aspects required for the practical application of SHM Includes case studies that show how the techniques can be applied in practice Structural Health Monitoring of Large Civil Engineering Structures is an ideal book for practicing civil engineers, academics and postgraduate students studying civil and structural engineering. |
| data science in structural engineering: Advances in Data Science, Cyber Security and IT Applications Auhood Alfaries, Hanan Mengash, Ansar Yasar, Elhadi Shakshuki, 2019-12-21 This book constitutes the refereed proceedings of the First International Conference on Intelligent Cloud Computing, ICC 2019, held in Riyadh, Saudi Arabia, in December 2019. The two-volume set presents 53 full papers, which were carefully reviewed and selected from 174 submissions. The papers are organized in topical sections on Cyber Security; Data Science; Information Technology and Applications; Network and IoT. |
| data science in structural engineering: Structural Health Monitoring (SHM) in Aerospace Structures Fuh-Gwo Yuan, 2016-03-01 Structural Health Monitoring (SHM) in Aerospace Structures provides readers with the spectacular progress that has taken place over the last twenty years with respect to the area of Structural Health Monitoring (SHM). The widespread adoption of SHM could both significantly improve safety and reduce maintenance and repair expenses that are estimated to be about a quarter of an aircraft fleet's operating costs. The SHM field encompasses transdisciplinary areas, including smart materials, sensors and actuators, damage diagnosis and prognosis, signal and image processing algorithms, wireless intelligent sensing, data fusion, and energy harvesting. This book focuses on how SHM techniques are applied to aircraft structures with particular emphasis on composite materials, and is divided into four main parts. Part One provides an overview of SHM technologies for damage detection, diagnosis, and prognosis in aerospace structures. Part Two moves on to analyze smart materials for SHM in aerospace structures, such as piezoelectric materials, optical fibers, and flexoelectricity. In addition, this also includes two vibration-based energy harvesting techniques for powering wireless sensors based on piezoelectric electromechanical coupling and diamagnetic levitation. Part Three explores innovative SHM technologies for damage diagnosis in aerospace structures. Chapters within this section include sparse array imaging techniques and phase array techniques for damage detection. The final section of the volume details innovative SHM technologies for damage prognosis in aerospace structures. This book serves as a key reference for researchers working within this industry, academic, and government research agencies developing new systems for the SHM of aerospace structures and materials scientists. - Provides key information on the potential of SHM in reducing maintenance and repair costs - Analyzes current SHM technologies and sensing systems, highlighting the innovation in each area - Encompasses chapters on smart materials such as electroactive polymers and optical fibers |
| data science in structural engineering: Enabling AI Applications in Data Science Aboul-Ella Hassanien, Mohamed Hamed N. Taha, Nour Eldeen M. Khalifa, 2020-09-23 This book provides a detailed overview of the latest developments and applications in the field of artificial intelligence and data science. AI applications have achieved great accuracy and performance with the help of developments in data processing and storage. It has also gained strength through the amount and quality of data which is the main nucleus of data science. This book aims to provide the latest research findings in the field of artificial intelligence with data science. |
| data science in structural engineering: Construction Materials and Their Properties for Fire Resistance and Insulation Paul O. Awoyera, M. Z. Naser, 2024-10-29 Construction Materials and Their Properties for Fire Resistance and Insulation covers the properties of novel types of concrete and other more conventional building materials in fire scenarios. The volume also stands out as an invaluable reference resource for its relevance to varied audiences both in academia and industry, spanning materials science, civil and structural engineering, and fire safety engineering. Ensuring buildings are fire safe starts at the very beginning of planning new builds or renovations. Hence, it's essential, in fact, that the right materials are chosen not only according to their load-bearing capabilities but also their susceptibility to decay and fire resistance. - Provides appropriate inputs for material behavior at elevated temperatures generated by fire, which is key to enable the assessment of various construction materials' fire performance - Illustrates the effects of fire on materials' performance to support decisions related to a building's safe structural rehabilitation - Includes probabilistic models, numerical studies, and application cases |
| data science in structural engineering: Federal Data Science Feras A. Batarseh, Ruixin Yang, 2017-09-21 Federal Data Science serves as a guide for federal software engineers, government analysts, economists, researchers, data scientists, and engineering managers in deploying data analytics methods to governmental processes. Driven by open government (2009) and big data (2012) initiatives, federal agencies have a serious need to implement intelligent data management methods, share their data, and deploy advanced analytics to their processes. Using federal data for reactive decision making is not sufficient anymore, intelligent data systems allow for proactive activities that lead to benefits such as: improved citizen services, higher accountability, reduced delivery inefficiencies, lower costs, enhanced national insights, and better policy making. No other government-dedicated work has been found in literature that addresses this broad topic. This book provides multiple use-cases, describes federal data science benefits, and fills the gap in this critical and timely area. Written and reviewed by academics, industry experts, and federal analysts, the problems and challenges of developing data systems for government agencies is presented by actual developers, designers, and users of those systems, providing a unique and valuable real-world perspective. - Offers a range of data science models, engineering tools, and federal use-cases - Provides foundational observations into government data resources and requirements - Introduces experiences and examples of data openness from the US and other countries - A step-by-step guide for the conversion of government towards data-driven policy making - Focuses on presenting data models that work within the constraints of the US government - Presents the why, the what, and the how of injecting AI into federal culture and software systems |
| data science in structural engineering: Library of Congress Subject Headings Library of Congress, Library of Congress. Subject Cataloging Division, Library of Congress. Office for Subject Cataloging Policy, 1994 |
| data science in structural engineering: Proceedings of The 17th East Asian-Pacific Conference on Structural Engineering and Construction, 2022 Guoqing Geng, Xudong Qian, Leong Hien Poh, Sze Dai Pang, 2023-03-13 This book presents articles from The 17th East Asian-Pacific Conference on Structural Engineering and Construction, 2022, organized by National University of Singapore. These peer-reviewed articles, authored by professional engineers, academics and researchers, highlight the recent research and developments in structural engineering and construction, embracing the theme- “Towards a Resilient and Sustainable City”. The papers presented in this proceeding provide in-depth discussions with key insights into the future research, development and engineering translation in structural engineering and construction. |
| data science in structural engineering: Advances in Structural Engineering Vasant Matsagar, 2014-12-12 The book presents research papers presented by academicians, researchers, and practicing structural engineers from India and abroad in the recently held Structural Engineering Convention (SEC) 2014 at Indian Institute of Technology Delhi during 22 – 24 December 2014. The book is divided into three volumes and encompasses multidisciplinary areas within structural engineering, such as earthquake engineering and structural dynamics, structural mechanics, finite element methods, structural vibration control, advanced cementitious and composite materials, bridge engineering, and soil-structure interaction. Advances in Structural Engineering is a useful reference material for structural engineering fraternity including undergraduate and postgraduate students, academicians, researchers and practicing engineers. |
| data science in structural engineering: Python Programming and Numerical Methods Qingkai Kong, Timmy Siauw, Alexandre Bayen, 2020-11-27 Python Programming and Numerical Methods: A Guide for Engineers and Scientists introduces programming tools and numerical methods to engineering and science students, with the goal of helping the students to develop good computational problem-solving techniques through the use of numerical methods and the Python programming language. Part One introduces fundamental programming concepts, using simple examples to put new concepts quickly into practice. Part Two covers the fundamentals of algorithms and numerical analysis at a level that allows students to quickly apply results in practical settings. - Includes tips, warnings and try this features within each chapter to help the reader develop good programming practice - Summaries at the end of each chapter allow for quick access to important information - Includes code in Jupyter notebook format that can be directly run online |
| data science in structural engineering: Cross Reality and Data Science in Engineering Michael E. Auer, Dominik May, 2020-08-20 Today, online technologies are at the core of most fields of engineering and society as a whole . This book discusses the fundamentals, applications and lessons learned in the field of online and remote engineering, virtual instrumentation, and other related technologies like Cross Reality, Data Science & Big Data, Internet of Things & Industrial Internet of Things, Industry 4.0, Cyber Security, and M2M & Smart Objects. Since the first Remote Engineering and Virtual Instrumentation (REV) conference in 2004, the event has focused on the use of the Internet for engineering tasks, as well as the related opportunities and challenges. In a globally connected world, interest in online collaboration, teleworking, remote services, and other digital working environments is rapidly increasing. In this context, the REV conferences discuss fundamentals, applications and experiences in the field of Online and Remote Engineering as well as Virtual Instrumentation. Furthermore, the conferences focus on guidelines and new concepts for engineering education in higher and vocational education institutions, including emerging technologies in learning, MOOCs & MOOLs, and open resources. This book presents the proceedings of REV2020 on “Cross Reality and Data Science in Engineering” which was held as the 17th in series of annual events. It was organized in cooperation with the Engineering Education Transformations Institute and the Georgia Informatics Institutes for Research and Education and was held at the College of Engineering at the University of Georgia in Athens (GA), USA, from February 26 to 28, 2020. |
| data science in structural engineering: Principles of Data Science Hamid R. Arabnia, Kevin Daimi, Robert Stahlbock, Cristina Soviany, Leonard Heilig, Kai Brüssau, 2020-07-08 This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists’ preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
