Author: Robert Mitchell Lloyd
Publisher: Thomas Telford
ISBN: 9780727728395
Category : Technology & Engineering
Languages : en
Pages : 282
Book Description
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.
Civil Engineering Learning Technology
Author: Robert Mitchell Lloyd
Publisher: Thomas Telford
ISBN: 9780727728395
Category : Technology & Engineering
Languages : en
Pages : 282
Book Description
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.
Publisher: Thomas Telford
ISBN: 9780727728395
Category : Technology & Engineering
Languages : en
Pages : 282
Book Description
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
Author: James-A. Goulet
Publisher: MIT Press
ISBN: 0262358018
Category : Computers
Languages : en
Pages : 298
Book Description
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.
Publisher: MIT Press
ISBN: 0262358018
Category : Computers
Languages : en
Pages : 298
Book Description
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.
A Primer on Machine Learning Applications in Civil Engineering
Author: Paresh Chandra Deka
Publisher: CRC Press
ISBN: 0429836651
Category : Computers
Languages : en
Pages : 211
Book Description
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
Publisher: CRC Press
ISBN: 0429836651
Category : Computers
Languages : en
Pages : 211
Book Description
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
Compendium of Civil Engineering Education Strategies
Author: Hudson Jackson
Publisher: CRC Press
ISBN: 1000569233
Category : Technology & Engineering
Languages : en
Pages : 262
Book Description
This book compiles the latest strategies and information regarding civil engineering education, and the skills necessary for success that are tangential to engineering, including global perspectives, critical and design thinking skills, leadership skills, 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 promote the 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.
Publisher: CRC Press
ISBN: 1000569233
Category : Technology & Engineering
Languages : en
Pages : 262
Book Description
This book compiles the latest strategies and information regarding civil engineering education, and the skills necessary for success that are tangential to engineering, including global perspectives, critical and design thinking skills, leadership skills, 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 promote the 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.
Handbook of Research on Multidisciplinary Perspectives on Managerial and Leadership Psychology
Author: Johnson, Rick D.
Publisher: IGI Global
ISBN: 1799838129
Category : Psychology
Languages : en
Pages : 742
Book Description
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.
Publisher: IGI Global
ISBN: 1799838129
Category : Psychology
Languages : en
Pages : 742
Book Description
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.
Probabilistic Machine Learning
Author: Kevin P. Murphy
Publisher: MIT Press
ISBN: 0262369303
Category : Computers
Languages : en
Pages : 858
Book Description
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
Publisher: MIT Press
ISBN: 0262369303
Category : Computers
Languages : en
Pages : 858
Book Description
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
Looking Toward the Future of Technology-Enhanced Education: Ubiquitous Learning and the Digital Native
Author: Ebner, Martin
Publisher: IGI Global
ISBN: 1615206795
Category : Education
Languages : en
Pages : 556
Book Description
"This book evaluated the incorporation of technology into educational processes reviewing topics from primary and secondary school to higher education, from Second Life to wiki technology, from physical education to cultural learning"--Provided by publisher.
Publisher: IGI Global
ISBN: 1615206795
Category : Education
Languages : en
Pages : 556
Book Description
"This book evaluated the incorporation of technology into educational processes reviewing topics from primary and secondary school to higher education, from Second Life to wiki technology, from physical education to cultural learning"--Provided by publisher.
Engineering in K-12 Education
Author: National Research Council
Publisher: National Academies Press
ISBN: 030914471X
Category : Education
Languages : en
Pages : 595
Book Description
Engineering education in K-12 classrooms is a small but growing phenomenon that may have implications for engineering and also for the other STEM subjects-science, technology, and mathematics. Specifically, engineering education may improve student learning and achievement in science and mathematics, increase awareness of engineering and the work of engineers, boost youth interest in pursuing engineering as a career, and increase the technological literacy of all students. The teaching of STEM subjects in U.S. schools must be improved in order to retain U.S. competitiveness in the global economy and to develop a workforce with the knowledge and skills to address technical and technological issues. Engineering in K-12 Education reviews the scope and impact of engineering education today and makes several recommendations to address curriculum, policy, and funding issues. The book also analyzes a number of K-12 engineering curricula in depth and discusses what is known from the cognitive sciences about how children learn engineering-related concepts and skills. Engineering in K-12 Education will serve as a reference for science, technology, engineering, and math educators, policy makers, employers, and others concerned about the development of the country's technical workforce. The book will also prove useful to educational researchers, cognitive scientists, advocates for greater public understanding of engineering, and those working to boost technological and scientific literacy.
Publisher: National Academies Press
ISBN: 030914471X
Category : Education
Languages : en
Pages : 595
Book Description
Engineering education in K-12 classrooms is a small but growing phenomenon that may have implications for engineering and also for the other STEM subjects-science, technology, and mathematics. Specifically, engineering education may improve student learning and achievement in science and mathematics, increase awareness of engineering and the work of engineers, boost youth interest in pursuing engineering as a career, and increase the technological literacy of all students. The teaching of STEM subjects in U.S. schools must be improved in order to retain U.S. competitiveness in the global economy and to develop a workforce with the knowledge and skills to address technical and technological issues. Engineering in K-12 Education reviews the scope and impact of engineering education today and makes several recommendations to address curriculum, policy, and funding issues. The book also analyzes a number of K-12 engineering curricula in depth and discusses what is known from the cognitive sciences about how children learn engineering-related concepts and skills. Engineering in K-12 Education will serve as a reference for science, technology, engineering, and math educators, policy makers, employers, and others concerned about the development of the country's technical workforce. The book will also prove useful to educational researchers, cognitive scientists, advocates for greater public understanding of engineering, and those working to boost technological and scientific literacy.
Teaching and Learning with Technology
Author: Roberto Dillon
Publisher: World Scientific
ISBN: 9814733598
Category : Education
Languages : en
Pages : 117
Book Description
"This is the conference proceedings for the 2015 Global Conference on Teaching and Learning with Technology (CTLT 2015), hosted by Aventis School of Management, Singapore. It includes papers by a group of international academics and researchers. It covers the most interesting ideas and applications related to the innovative use of technology within different learning environments."--
Publisher: World Scientific
ISBN: 9814733598
Category : Education
Languages : en
Pages : 117
Book Description
"This is the conference proceedings for the 2015 Global Conference on Teaching and Learning with Technology (CTLT 2015), hosted by Aventis School of Management, Singapore. It includes papers by a group of international academics and researchers. It covers the most interesting ideas and applications related to the innovative use of technology within different learning environments."--
Innovative Techniques in Instruction Technology, E-learning, E-assessment and Education
Author: Magued Iskander
Publisher: Springer Science & Business Media
ISBN: 140208739X
Category : Computers
Languages : en
Pages : 613
Book Description
Innovative Techniques in Instruction Technology, E-Learning, E-Assessment and Education is a collection of world-class paper articles addressing the following topics: (1) E-Learning including development of courses and systems for technical and liberal studies programs; online laboratories; intelligent testing using fuzzy logic; evaluation of on line courses in comparison to traditional courses; mediation in virtual environments; and methods for speaker verification. (2) Instruction Technology including internet textbooks; pedagogy-oriented markup languages; graphic design possibilities; open source classroom management software; automatic email response systems; tablet-pcs; personalization using web mining technology; intelligent digital chalkboards; virtual room concepts for cooperative scientific work; and network technologies, management, and architecture. (3) Science and Engineering Research Assessment Methods including assessment of K-12 and university level programs; adaptive assessments; auto assessments; assessment of virtual environments and e-learning. (4) Engineering and Technical Education including cap stone and case study course design; virtual laboratories; bioinformatics; robotics; metallurgy; building information modeling; statistical mechanics; thermodynamics; information technology; occupational stress and stress prevention; web enhanced courses; and promoting engineering careers. (5) Pedagogy including benchmarking; group-learning; active learning; teaching of multiple subjects together; ontology; and knowledge representation. (6) Issues in K-12 Education including 3D virtual learning environment for children; e-learning tools for children; game playing and systems thinking; and tools to learn how to write foreign languages.
Publisher: Springer Science & Business Media
ISBN: 140208739X
Category : Computers
Languages : en
Pages : 613
Book Description
Innovative Techniques in Instruction Technology, E-Learning, E-Assessment and Education is a collection of world-class paper articles addressing the following topics: (1) E-Learning including development of courses and systems for technical and liberal studies programs; online laboratories; intelligent testing using fuzzy logic; evaluation of on line courses in comparison to traditional courses; mediation in virtual environments; and methods for speaker verification. (2) Instruction Technology including internet textbooks; pedagogy-oriented markup languages; graphic design possibilities; open source classroom management software; automatic email response systems; tablet-pcs; personalization using web mining technology; intelligent digital chalkboards; virtual room concepts for cooperative scientific work; and network technologies, management, and architecture. (3) Science and Engineering Research Assessment Methods including assessment of K-12 and university level programs; adaptive assessments; auto assessments; assessment of virtual environments and e-learning. (4) Engineering and Technical Education including cap stone and case study course design; virtual laboratories; bioinformatics; robotics; metallurgy; building information modeling; statistical mechanics; thermodynamics; information technology; occupational stress and stress prevention; web enhanced courses; and promoting engineering careers. (5) Pedagogy including benchmarking; group-learning; active learning; teaching of multiple subjects together; ontology; and knowledge representation. (6) Issues in K-12 Education including 3D virtual learning environment for children; e-learning tools for children; game playing and systems thinking; and tools to learn how to write foreign languages.