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Civil Engineering Learning Technology by Robert Mitchell Lloyd,Carolynne Moore Pdf
The field of civil engineering offers specific challenges to the higher education sector. Civil engineerings blend of management design and analysis requires people with a combination of academic and experimental knowledge and skill-based abilities.This volume brings together papers by leading practitioners in the field of learning technology, within the discipline of civil engineering, to facilitate the sharing of experience, knowledge and expertise.
Probabilistic Machine Learning for Civil Engineers by James-A. Goulet Pdf
An introduction to key concepts and techniques in probabilistic machine learning for civil engineering students and professionals; with many step-by-step examples, illustrations, and exercises. This book introduces probabilistic machine learning concepts to civil engineering students and professionals, presenting key approaches and techniques in a way that is accessible to readers without a specialized background in statistics or computer science. It presents different methods clearly and directly, through step-by-step examples, illustrations, and exercises. Having mastered the material, readers will be able to understand the more advanced machine learning literature from which this book draws. The book presents key approaches in the three subfields of probabilistic machine learning: supervised learning, unsupervised learning, and reinforcement learning. It first covers the background knowledge required to understand machine learning, including linear algebra and probability theory. It goes on to present Bayesian estimation, which is behind the formulation of both supervised and unsupervised learning methods, and Markov chain Monte Carlo methods, which enable Bayesian estimation in certain complex cases. The book then covers approaches associated with supervised learning, including regression methods and classification methods, and notions associated with unsupervised learning, including clustering, dimensionality reduction, Bayesian networks, state-space models, and model calibration. Finally, the book introduces fundamental concepts of rational decisions in uncertain contexts and rational decision-making in uncertain and sequential contexts. Building on this, the book describes the basics of reinforcement learning, whereby a virtual agent learns how to make optimal decisions through trial and error while interacting with its environment.
Compendium of Civil Engineering Education Strategies by Hudson Jackson,Kassim Tarhini Pdf
This book compiles proven strategies and information on civil engineering education and the skills necessary for successful practice of civil engineering such as critical thinking, design thinking, leadership, and communication skills. It also addresses other relevant topics including professional ethics, global perspectives, assessment, recruitment, retention, and more. It is designed so that each chapter can be used separately or in combination with other chapters to help enhance and foster student learning as well as development of skills required for engineering practice. Features Includes overviews of successful academic approaches for each topic including implementation examples in every chapter Explains how assessment and the resulting data can be used for holistic evaluation and improvement of student learning Addresses the complexities of moral and professional ethics in engineering Highlights the importance of adopting a global perspective and the successful strategies that have been used or considered in educating resilient, globally minded engineers Compendium of Civil Engineering Education Strategies: Case Studies and Examples serves as a useful guide for engineering faculty, practitioners, and graduate students considering a career in academia. Academic faculty and working professionals will find the content helpful as instructional and reference material in developing and assessing career skills. It is also useful for intellectually curious students who want a deeper understanding and appreciation of the need for professional development and life-long learning.
A Primer on Machine Learning Applications in Civil Engineering by Paresh Chandra Deka Pdf
Machine learning has undergone rapid growth in diversification and practicality, and the repertoire of techniques has evolved and expanded. The aim of this book is to provide a broad overview of the available machine-learning techniques that can be utilized for solving civil engineering problems. The fundamentals of both theoretical and practical aspects are discussed in the domains of water resources/hydrological modeling, geotechnical engineering, construction engineering and management, and coastal/marine engineering. Complex civil engineering problems such as drought forecasting, river flow forecasting, modeling evaporation, estimation of dew point temperature, modeling compressive strength of concrete, ground water level forecasting, and significant wave height forecasting are also included. Features Exclusive information on machine learning and data analytics applications with respect to civil engineering Includes many machine learning techniques in numerous civil engineering disciplines Provides ideas on how and where to apply machine learning techniques for problem solving Covers water resources and hydrological modeling, geotechnical engineering, construction engineering and management, coastal and marine engineering, and geographical information systems Includes MATLAB® exercises
Technology and Tools in Engineering Education by Prathamesh P. Churi,Vishal Kumar,Utku Kose,N. T. Rao Pdf
This book explores the innovative and research methods of the teaching-learning process in Engineering field. It focuses on the use of technology in the field of education. It also provides a platform to academicians and educationalists to share their ideas and best practices. The book includes specific pedagogy used in engineering education. It offers case studies and classroom practices which also include those used in distance mode and during the COVID-19 pandemic. It provides comparisons of national and international accreditation bodies, directions on cost-effective technology, and it discusses advanced technologies such as VR and augmented reality used in education. This book is intended for research scholars who are pursuing their masters and doctoral studies in the engineering education field as well as teachers who teach undergraduate and postgraduate courses to engineering students.
Handbook of Research on Multidisciplinary Perspectives on Managerial and Leadership Psychology by Johnson, Rick D. Pdf
The subject of leadership and managerial psychology exists as a sub-branch of psychology within the fields of industrial and organizational psychology. There still appears to be ongoing debate regarding the core pathology for gaining managerial expertise in professional roles relative to having suitable leadership skills and managerial knowledge beyond the direct daily work involved in organizations. Professional organizations inherently include varied levels of sensitive human interactions, which further necessitates their management professionals to have leadership styles that are adjustable contingent on a given situation. Relative to this edited book, managerial psychology is being utilized in a way that may subsequently seek to develop a series of scientific theory principles where the focus is to develop managerial axioms that advance contemporary existing knowledge surrounding professional management logic. The Handbook of Research on Multidisciplinary Perspectives on Managerial and Leadership Psychology provides value uncovered by a collaboration of generalists and specialists who bring professional managerial and leadership opinions to light through narratives and research inclusive of fundamental theory principles that can be applied in practice and academia. This edited reference is focused on the enhancement of management research through managerial psychology while highlighting topics including business process knowledge, management in diverse discipline situations and professions, corporate leadership responsibility, leadership of self and others, and leadership psychology in a variety of different fields of work. This book is ideally designed for leadership and management professionals, academicians, students, and researchers in the fields of knowledge management, administrative sciences and management, leadership development, education, and organization development sub-branches or specialty practices.
Artificial Intelligence Applications for Sustainable Construction by Moncef L. Nehdi,Harish Chandra Arora,Krishna Kumar,Robertas Damaševičius,Aman Kumar Pdf
Artificial Intelligence Applications for Sustainable Construction presents the latest developments in AI and ML technologies applied to real-world civil engineering concerns. With an increasing amount of attention on the environmental impact of every industry, more construction projects are going to require sustainable construction practices. This volume offers research evidence, simulation results, and case studies to support this change. Sustainable construction, in fact, not only uses renewable and recyclable materials when building new structures or repairing deteriorating ones, but also adopts all possible methods to reduce energy consumption and waste. The concisely written but comprehensive, practical knowledge put forward by this international group of highly specialized editors and contributors will prove to be beneficial to engineering students and professionals alike. Presents convincing “success stories that encourage application of AI-powered tools to civil engineering Provides a wealth of valuable technical information to address and resolve many challenging construction problems Illustrates the most recent shifts in thinking and practice for sustainable construction
Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering by Gebrail Bekdas,Sinan Melih Nigdeli,Melda Yucel Pdf
"This book examines the application of artificial intelligence and machine learning civil, mechanical, and industrial engineering"--
