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• Asset valuation, acquisition, and disposal options
• Product-service transformation, and product-service systems
• Asset operations and maintenance strategies
• Sustainable asset operations and maintenance processes
• Dynamic modelling and simulation of asset operations and maintenance
• Reliability and resilience engineering
• IOT and applications of smart and intelligent sensing and instrumentation
• Condition monitoring, diagnostics, prognostics, and asset health indexing
• Industry 4.0 platforms and interoperability of ICT systems
• Augmented and virtual reality applications
• Asset condition, risk, resilience and vulnerability assessments
• Asset management and decision support systems
• Applications of international and local guidelines and standards
• Refurbishment, renovation, replacement, upgrade decisions and actions
• Human dimensions and asset management performance
• Blockchain applications.
• Role of cybersecurity in assetmanagement
• Asset management in the energy sector
• Asset management in the healthcare sector
• Asset management in the food and beverage industry
• Asset management in the petrochemicalindustry
• Monitoring, diagnostics and prognosticsforsmart maintenance
• Asset management in Agro-allied sector
• Air and Sea ports infrastructure and facilities
• Adventure and wildlife parks infrastructure and facilities
• City and metropolitan infrastructure and facilities.

This book gathers selected peer-reviewed papers from the 16th World Congress on Engineering Asset Management (WCEAM), held in Seville from 57 October 2022. This book covers a wide range of topics in Engineering Asset Management, including: Asset management and decision support system Industry 4.0 tools and its impact on asset management Monitoring, diagnostics and prognostics for smart maintenance Asset life cycle management Asset management in the industrial sector Human dimensions and asset management performance Infrastructure Asset management Asset condition, risk, resilience, and vulnerability assessments Asset operations and maintenance strategies Reliability and resilience engineering Applications of international and local guidelines and standards The breadth and depth of this state-of-the-art, comprehensive proceedings make it an excellent resource for asset management practitioners, researchers and academics, as well as undergraduate and postgraduate students.

• Chapter 1. Advancing STEM education and innovation in a time of distance learning: case studies in China
• Chapter 2. Could innovation activities improve the students learning process?: making the students work for it -also online
• Chapter 3. Didactic strategies for meaningful learning
• Chapter 4. Differentiation for the gifted: opportunities provided by distance-online education
• Chapter 5. Frameworks for pedagogy, methodologies, and technologies in distance learning processes
• Chapter 6. Increasing women's chances in STEM fields and combating challenges
• Chapter 7. Microlearning in physics teaching: an innovative proposal
• Chapter 8. Mobile gamification to integrate face-to-face and virtual students: synchronous and asynchronous
• Chapter 9. New challenges to teaching technical disciplines in architecture schools: from energy simulation to online tools
• Chapter 10. Teaching fire safety in schools of architecture: the Spanish case
• Chapter 11. Technology transformation through skilled teachers in teaching accountancy
• Chapter 12. The barriers ethnically diverse girls face in STEAM
• Chapter 13. The importance of STEM fields in higher education in a post-pandemic world
• Chapter 14. Transformative innovation in course design for STEM-based e-learning
• Chapter 15. Use of online technologies, open hardware, and open-software for advanced architecture design

Due to the recent global pandemic, educators of science and technology have had to pivot and adapt their delivery to create alternative virtual means of delivery. The COVID-19 pandemic has influenced a rapid change in teaching and learning in higher education. It is reshaping curriculum demands, the 21st century digital competence challenges, and learning technologies. These changes in education are likely to endure well past the COVID-19 pandemic, making it crucial for educators to consider teaching and learning under the perspectives of digital education and innovation. Advancing STEM Education and Innovation in a Time of Distance Learning highlights the contemporary trends and challenges in science, technology, mathematics, and engineering education. The chapters present findings and discussions of relevant research studies and theoretical frameworks for the provision of science, technology, engineering, and technical subjects. It not only presents successful practice examples from before and during the COVID-19 pandemic, but also provides useful information to assist educators in understanding the demands and challenges of digital education. Covering topics such as ethnically diverse students, foreign language learning, and mobile gamification, this premier reference source is an essential resource for educators and administrators of both K-12 and higher education, pre-service teachers, teacher educators, librarians, government officials, researchers, and academicians.
(source: Nielsen Book Data)

• An Integrated Approach for Robot Selection under Utopia Environment
• A Novel Soft Computing Technique for Hydroxyapatite Coatings Selection for Orthopedic Prosthesis
• Remote Production Monitoring System
• Application of Wavelet Neural Network for Electric Field Estimation
• Development of an industrial control virtual reality module for the application of electrical switchgear in practical applications
• Coordination of Wind Turbines and Battery Energy Storage Systems in Micro Grid
• Weather-aware selection of wireless technologies for neighborhood area network of Indian smart grid
• Intelligent System for Diagnosis of Pulmonary Tuberculosis Using Ensemble Method
• Alcoholic addiction detection based on EEG signals using Deep convolutional neural network
• Application of machine learning algorithms for cataract detection.

This book comprises select proceedings of the 1st International Conference on Computational Intelligence for Engineering and Management Applications (CIEMA - 2022). This book emphasizes applications of computational intelligence including machine intelligence, data analytics, and optimization algorithms for solving fundamental and advanced engineering and management problems. This book serves as a valuable resource for researchers, industry professionals, academicians, and doctoral scholars in engineering, production, thermal, materials, design, computer engineering, natural sciences, and management who work on computational intelligence. The book also serves researchers who are willing to use computational intelligence algorithms in real-time applications.

• Preface
• Chapter 1. STEM In- and Out-of-School
• Chapter 1. Engineering With Empathy in the Build a Better Book Project: Meaningful Making Supports STEM Participation
• Chapter 2. The Mobile Making Program: Supporting Maker-Based STEM Engagement Among Youth During Out-of-School Time
• Chapter 3. The Design of an Out-of-School Program Focused on Community-Centered Engineering Challenges
• Chapter 4. Using Human-Centered Design to Partner for Continuous Program Improvement of STEM Programming
• Chapter 5. Supporting STEM Career Knowledge and Interest for Rural Grade Two Students Through a University-School Partnership
• Chapter 6. Development of a Low-Cost Affordable Inquiry-Based System-Thinking STEM Prospectus: Food, Water, and Energy Learning Module Workbooks
• Chapter 2. STEM in the Community
• Chapter 7. Identity-Centered STEM Curricula for Black Girls: An Intersectional Intervention for Black Girl Joy
• Chapter 8. There is a disparity between the number of men and women in STEM fields. The disparity is further exacerbated when considering the percentage of women from underrepresented backgrounds in the STEM workforce. However, early and...
• Chapter 9. Enhancing Middle Grade Students' Interest and Learning in a Community-Engaged Summer STEM Competition
• Chapter 10. Zoology Pathway Program: Partnering for Student Success
• Chapter 11. Mutually Beneficial School-Industry Partnerships in STEM Education: An Aspirational Case Study
• Compilation of References
• About the Contributors
• Index.

"Locally or individually, STEM programs provide additional opportunities to engage K-12 students, including those from marginalized groups, with the support of STEM outreach organizations through the co-construction and implementation of STEM activities during school, out of school, at home, and in the community. Research suggests that community-engaged partnerships forge relationships that can enhance and sustain K-12 STEM education efforts between K-12 districts and the scholarly community. There is a need to highlight community-engaged teaching and scholarship produced from partnerships between K-12 school districts and STEM outreach organizations.Developing and Sustaining STEM Programs Across the K-12 Education Landscape describes the purpose of the collaboration between K-12 school districts and STEM outreach organizations, the STEM activities that participating K-12 students engage in, and the impacts on STEM learners that emerge from the partnership. Covering topics such as continuous program improvement, school-industry partnerships, and student success, this premier reference source is an excellent resource for educational leaders and administrators, pre-service and in-service educators, teacher educators, researchers, and academicians."-- Provided by publisher.

• 1. Large classes in STEM education--potential and challenges / Anna K. Wood and Nicolas Labrosse
• 2. Active learning in large classes / Anna K. Wood
• 3. Practical approaches to active learning / Alison Voice
• 4. Using classroom observation tools to characterize large classes / Anna K. Wood and George Kinnear
• 5. Authentic and inclusive (summative) assessments / Firas Moosvi and Simon Bates
• 6. Computer-marked assessment and concept inventories / Sally Jordan
• 7. Case study 1 : an introductory physics course / Ross K. Galloway
• 8. Case study 2 : tailored active blended learning in a foundation year chemistry module / Simon J. Lancaster, Daniel Elford and Eleanor Gill
• 9. Case study 3 : an introductory linear algebra course / Pamela Docherty
• 10. Case study 4 : personalised learning by student-posed questions during biology lectures / Heather McQueen
• 11. Case study 5 : the learning assistant model for engaging students / Valerie K. Otero
• 12. Effective teaching in large classes; looking through and beyond the COVID-19 pandemic / Simon Bates and Firas Moosvi.

This book provides an accessible and research-informed introduction to teaching large classes, aimed at teachers from across the STEM subjects, at all stages of their careers, who want to provide the most effective teaching and learning experiences for their students. A central theme throughout is that active learning is an important aspect of good-quality teaching. This is explored in detail through both practical guidance for implementing such techniques as well as through an accessible introduction to the theoretical and pedagogical issues that underpin its use, supported by case studies. The text provides an introduction for university teachers interested in using approaches such as the flipped classroom, and offers discussion on how to quantify activities within classrooms through observation tools, and what the future of teaching large classes might look like. Part of IOP Series in Physics Education.

• Researching engineering faculty members' teaching at Chinese Universities : the design of the study
• Teaching expectations in China's latest university
• Engineering education reforms : the ideal standards
• Status quo and innovations
• Structural conditionings shaping engineering faculty members' teaching
• The work of cultural conditionings
• The reflexive imperative of teaching in engineering education
• Exploring teaching agency in quantitative terms
• Drawing the strands together : the social realist explanations

• Preface / Sharon Nelson-Barber and Pauline W.U. Chinn
• Foreword - An Indigenous Sense of Place / Gregory Cajete
• Part I. Culture, Language, Knowledge, and Place as Foundation for Learning
• Chapter 1. Native Astronomy: A Skyward View / Greg Cajete
• Chapter 2. Listening to the People: Reforming science education through incorporation of Chuukese traditional knowledge / Margarita B. Cholymay
• Chapter 3. E Imi I ke Alanui, To Find the Way: A Native Hawaiian educator's Journey / ALYSON NAPUA BARROWS
• Chapter 4. KahuaAo: Science education through Hawaiian-language newspapers / Jason K. Ellinwood and Johanna Kapmaikai Stone
• Chapter 5. O kekumukekaao, The story is the source: The discipline of ancestral stories in nurturing Native Hawaiian scientists / Huihui Kanahele-Mossman
• Chapter 6. Developing a Framework for Integrating Systems of Local Indigenous Knowledge with Climate Education in the Mariana Islands / Sharon Nelson-Barber, Elizabeth Diaz Rechebei, Jose Tilipao Limes, Zanette Johnson
• Chapter 7. Culturally responsive science education for rural students: Connecting school science with local heritages in Thailand / Nantana Taptamat
• Part II. Research that Tells Our Stories and Informs Policy and Practice
• Chapter 8. Perspective taking and psychological distance in childrens picture books: differences between Native and Non-native authored books / Megan Bang, Jasmine Gurneau, Lori Faber, Ananda Marin, Michael Marin, Douglas Medin, Sandra Waxman, Jennifer Woodring
• Chapter 9. Integrating Place, Indigenous and Western Science: Implications for Teacher Agency, Expertise, and Identity / Pauline W.U. Chinn
• Chapter 10. Keystone characteristics that support cultural resilience in Karen refugee parents / Susan Harper
• Chapter 11. Symmetry and halving: A way to teach mathematical foundations, based on the everyday knowledge of Yupiaq and Caroline Islanders / Jerry Lipka, Dora Andrew-Irhke, Miuty Nokar, David Koester, Donald H. Rubenstein, Walkie Charles, Evelyn Yanes, Cal Hachibma, Raphael Jimmy
• Chapter 12. Understanding the geology of the Colombian Amazon through indigenous eyes: educational potential of an ethnogeology of the Uitoto territory / Carolina Londoo, Steven Semken, Elizabeth Brandt, Cristina Garzon
• Chapter 13. Indigenous rural students' attitudes and perceptions about ethnoscience in STEM instruction / Sharon Nelson-Barber, Elise Trumbull, Ursula Sexton, Zanette Johnson
• Chapter 14. Researching Mori and Mori-medium science education / Georgina Stewart
• Chapter 15. Forum Kaupapa Mori science: A science fiction? / Elizabeth Mckinley.

• Evolution of Internet of Things (IoT) : past, present, and future for manufacturing systems / Vaishnavi Vadivelu, Moganapriya Chinnasamy, Manivannan Rajendran, Hari Chandrasekaren, and Rajasekar Rathanasamy
• Fourth industrial revolution : industry 4.0 / Maheswari Rajamanickam, Elizabeth Nirmala John Gerard Royan, Gowtham Ramaswamy, Manivannan Rajendran, and Vaishnavi Vadivelu
• Interaction of internet of things and sensors for machining / Manivannan Rajendran, Kamesh Nagarajan, Vaishnavi Vadivelu, Harikrishna Kumar Mohankumar, and Sathish Kumar Palaniappan
• Application on internet of things (IoT) in the automotive industry / Solomon Jenoris Muthiya, Shridhar Anaimuthu, Joshuva Arockia Dhanraj, Nandakumar Selvaraju, Gutha Manikanta, and C. Dineshkumar
• IoT for food and beverage manufacturing / Manju Sri Anbupalani, Gobinath Velu Kaliyannan, and Santhosh Sivaraj
• Opportunities : machine learning for industrial IoT applications / Poongodi C., Sayeekumar M., Meenakshi C., and Hari Prasath K.
• Role of IoT in industry predictive maintenance / Gobinath Velu Kaliyannan, Manju Sri Anbupalani, Suganeswaran Kandasamy, Santhosh Sivaraj, and Raja Gunasekaran
• Role of IoT in product development / Bhuvanesh Kumar M., Balaji N. S., Senthil S. M., and Sathiya P.
• Benefits of IoT in automated systems / Adithya K. and Girimurugan R.
• Integration of IoT in energy management / Ganesh Angappan, Santhosh Sivaraj, Premkumar Bhuvaneshwaran, Mugilan Thanigachalam, Sarath Dekar, and Rajasekar Rathanasamy
• Role of IoT in the renewable energy sector / Veerakumar Chinnasamy and Honghyun Cho.

This book broadly explores the latest developments of IoT and its integration into mechanical and manufacturing engineering. It details the fundamental concepts and recent developments in IoT & Industry 4.0 with special emphasis on the mechanical engineering platform for such issues as product development and manufacturing, environmental monitoring, automotive applications, energy management, and renewable energy sectors. Topics and related concepts are portrayed comprehensively so that readers can develop expertise and knowledge in the field of IoT. It is packed with reference tables and schematic diagrams for the most commonly used processes and techniques, thereby providing a resource on the basic principles and application of IoT in manufacturing sectors.

• Evolution of Internet of Things (IoT) : past, present, and future for manufacturing systems / Vaishnavi Vadivelu, Moganapriya Chinnasamy, Manivannan Rajendran, Hari Chandrasekaren, and Rajasekar Rathanasamy
• Fourth industrial revolution : industry 4.0 / Maheswari Rajamanickam, Elizabeth Nirmala John Gerard Royan, Gowtham Ramaswamy, Manivannan Rajendran, and Vaishnavi Vadivelu
• Interaction of internet of things and sensors for machining / Manivannan Rajendran, Kamesh Nagarajan, Vaishnavi Vadivelu, Harikrishna Kumar Mohankumar, and Sathish Kumar Palaniappan
• Application on internet of things (IoT) in the automotive industry / Solomon Jenoris Muthiya, Shridhar Anaimuthu, Joshuva Arockia Dhanraj, Nandakumar Selvaraju, Gutha Manikanta, and C. Dineshkumar
• IoT for food and beverage manufacturing / Manju Sri Anbupalani, Gobinath Velu Kaliyannan, and Santhosh Sivaraj
• Opportunities : machine learning for industrial IoT applications / Poongodi C., Sayeekumar M., Meenakshi C., and Hari Prasath K.
• Role of IoT in industry predictive maintenance / Gobinath Velu Kaliyannan, Manju Sri Anbupalani, Suganeswaran Kandasamy, Santhosh Sivaraj, and Raja Gunasekaran
• Role of IoT in product development / Bhuvanesh Kumar M., Balaji N. S., Senthil S. M., and Sathiya P.
• Benefits of IoT in automated systems / Adithya K. and Girimurugan R.
• Integration of IoT in energy management / Ganesh Angappan, Santhosh Sivaraj, Premkumar Bhuvaneshwaran, Mugilan Thanigachalam, Sarath Dekar, and Rajasekar Rathanasamy
• Role of IoT in the renewable energy sector / Veerakumar Chinnasamy and Honghyun Cho.

This book broadly explores the latest developments of IoT and its integration into mechanical and manufacturing engineering. It details the fundamental concepts and recent developments in IoT & Industry 4.0 with special emphasis on the mechanical engineering platform for such issues as product development and manufacturing, environmental monitoring, automotive applications, energy management, and renewable energy sectors. Topics and related concepts are portrayed comprehensively so that readers can develop expertise and knowledge in the field of IoT. It is packed with reference tables and schematic diagrams for the most commonly used processes and techniques, thereby providing a resource on the basic principles and application of IoT in manufacturing sectors.

• Intro
• Foreword
• Fifty Years is a Long Time-However You Count Them-But Impact Counts More....
• Preface
• Contents
• 1 The History of IGIP
• 1.1 A Glance at the History of Engineering Education
• 1.2 The Significance of Technical Teacher Training in Europe in the Second Part of the Twentieth Century
• 1.3 The Foundation of IGIP
• 1.4 The Creation of IGIP Structure
• 1.5 The Fundamentals of Engineering Pedagogy
• 1.6 The First IGIP Prototype Curriculum
• References
• 2 The Activities of IGIP
• 2.1 Ing.Paed. IGIP Register and the Development of the Second IGIP Prototype Curriculum

• 2.2 The Development of the Third IGIP Prototype Curriculum
• 2.3 The Development of the Fourth IGIP Prototype Curriculum
• 2.4 Establishment of IGIP Training Centers
• 2.5 International and Regional IGIP Conferences on Engineering Pedagogy
• 2.6 IGIP Presidency, Executive Committee, Membership and Dynamics of the Changes
• 2.6.1 IGIP Membership
• 2.6.2 Scientific Advisory Board
• 2.6.3 IGIP Presidents and General Secretaries
• 2.6.4 Executive Committee
• 2.6.5 International Monitoring Committee
• 2.6.6 Working Groups
• 2.7 Engineering Pedagogy Research
• 2.8 IGIP Awards

• 2.9 Cooperation with Sister Organizations
• 2.10 International Journal of Engineering Pedagogy (iJEP)
• 2.11 Conclusions
• References
• Appendix 1 Series of Publications on Engineering Pedagogy
• Appendix 2 The First IGIP Curriculum
• Appendix 3 IGIP Criteria for Accreditation of Engineering Pedagogy Studies
• 1. IGIP Accreditation Criteria for Engineering Pedagogy
• 1.1 Introduction
• 1.2 Goals of IGIP Accreditation
• 1.3 IGIP Accreditation Criteria
• 1.3.1 Accreditation Criterion (a): Organisation of the Program
• 1.3.1.1 Independent Course of Studies for Engineering Pedagogy

• 1.3.1.2 Integrated Program for Engineering Pedagogy
• 1.3.2 Accreditation Criterion (b): Entrance Requirements for First Year Students
• 1.3.2.1 Within Independent Course of Studies for Engineering Pedagogy
• 1.3.2.2 Within Integrated Program for Engineering Pedagogy
• 1.3.3 Accreditation Criterion (c): Skills/Abilities of the Graduates
• 1.3.4 Accreditation Criterion (d): Engineering Pedagogy Curriculum
• 1.3.5 Accreditation Criterion (e): Lecturers and Professors
• 1.3.6 Accreditation Criterion (f): Institutional Resources

• 1.3.7 Accreditation Criterion (g): Quality Control and Feedback
• 1.4 Application for Accreditation
• 2. Organisation Forms of Engineering Pedagogy Programs in Different Education Systems
• 2.1 Diversity of National Systems
• 2.2 A Common European Approach: The Bologna Declaration
• 2.3 Integrating the Engineering Pedagogy Programs Into the European University System
• 3. Educational Process
• 4. Competencies in Engineering Pedagogy
• 4.1 Technical Competencies
• 4.2 Pedagogical, Social, Psychological and Ethical Competencies
• 4.3 Didactical Skills and Subject Expertise

This book is dedicated to the history and contemporary activities of IGIP that occupies a unique position among world organizations who are focused on Engineering Education. We are currently in the process of transforming education at all levels. This applies in particular to the professional and academic education and training of engineers. To face these current real-world challenges, higher education has to find innovative ways to quickly respond to these new needs. This and completely new technologies in education require specifically new and adapted approaches in Engineering Pedagogy. This book is a continuation of IGIPs tradition to summarize and analyze intermediate results and foresee the main trends of further development of Engineering Pedagogy. It is written for the 50th anniversary of IGIP and contains valuable historic information as well as memories and opinions of IGIP members and specialists in Engineering Pedagogy. This book is intended for teachers at technical colleges and universities, students, post-graduates, administrative staff of educational institutions, staff of state educational ministries and committees, members of other societies with interest in Engineering Education, staff of personnel agencies, and everyone who is interested in Engineering Education and Pedagogy. Interested readership includes furthermore policymakers, academic researchers in pedagogy and learning theory, schoolteachers, the learning industry, further and continuing education lecturers, etc.

Children are intrigued by moving objects, even more so when they can engineer the movement. This volume in the STEM for Our Youngest Learners Series uses ramps and pathways as a context to provide children ages 3-8 opportunities to engage in STEM every day. Ramps and Pathways is a meaningful and fun way for children to develop engineering habits of mind as they explore concepts in force and motion, properties of objects, and how those properties affect their movement. In the process, children develop spatial thinking that is essential for future careers in STEM. The text also offers guidance for arranging the physical, intellectual, social-emotional, and promotional environments of a classroom to embrace the natural integration of literacy learning. Each volume in this series includes guidance for forming partnerships with families and administrators that support STEM learning, vignettes showing educators and children engaging in inquiry learning, tips for selecting materials, modifications and accommodations for diverse learners, ways to establish adult learning communities that support professional development, and more.Book Features: Alignment with both the Head Start Early Learning Outcomes Framework (ELOF) and the NGSS Science and Engineering Practices, with specific descriptions of how those science and engineering practices in Ramps and Pathways look and feel in Pre-K-2 classrooms. Examples of how to integrate literacy learning in a meaningful way. Descriptions of how the open-ended nature of ramps and pathways aligns with the Universal Design for Learning Framework (UDL). Guidance to help teachers anticipate and plan for all children to become purposeful, motivated, resourceful, knowledgeable, strategic, and goal-directed about learning. Examples of how to stage, introduce, and support children's designs to develop engineering habits of mind (systems thinking, optimism, creativity, communication, collaboration, attention to ethical considerations). A meaningful and healthy context to grow children's executive function skills (EFs), including inhibitory control, working memory, and cognitive flexibility.
(source: Nielsen Book Data)

• Chapter 1: The Hub
• Chapter 2: Programming
• Chapter 3: Building Elements
• Chapter 4: Gears
• Chapter 5: Mechanisms
• Chapter 6: Motors
• Chapter 7: The Motion Sensor
• Chapter 8: The Distance Sensor
• Chapter 9: The Color Sensor
• Appendix A: Parts List.

LEGO Mindstorms and SPIKE Prime are great products with vast capabilities, but are often so complex that many people don't know how to use them. LEGO provides a walk-through of a few projects to build, which are cool, but after building these many people get stuck on "now what?" This book answers that question by showing the underlying principles required to build their own ideas. This book is a hands-on tour of how machines work with LEGO -- there's nothing like building a machine with your own to hands to understand how it works. It includes aspects of software engineering, mechanical engineering, and electrical engineering. As parts and associated engineering concepts are presented, they will be shown in their practical use with graphical step-by-step assembly instructions. The concepts conveyed are mostly learned through building examples, with text explanation to reinforce the ideas being learned. Every engineering concept has a building example to go with it, in a quick build of less than 15 assembly steps. At the end of each chapter there's a project to tie the concepts of the chapter together of a little more complexity, involving 15 to 30 steps. These assembly steps are drawn with a computer aided design program that looks like the diagrams that LEGO produces for its products, so you'll be familiar with the look of the assembly directions. You will: Layout a Word Blocks or Python computer program from scratch See how LEGO building elements are meant to be assembled Manipulate the power source of a rotating shaft from an electric motor Use gears to alter the speed and torque of a power train Change the motion from a rotating shaft to a desired action Basic mechanisms (turntable, differential, cam, ratchet, etc.) to Use sensors (motion, distance, light, color) to make interactive inventions Integrate mechanical, software, and electrical subsystems in a project.

• Introduction
• Nail
• Wheel
• Spring
• Magnet
• Lens
• String
• Pump
• Conclusion.

"An ambitious but accessible book exploring how seven simple engineering inventions from the pump to the spring have shaped our world, by the engineer who designed the Shard"--Publisher's description.

• Cover
• Title Page
• Copyright Page
• Contents
• Preface
• Acknowledgment
• Part 1: Soft Computing and Evolutionary-Based Optimization
• Chapter 1 Improved Grey Wolf Optimizer with Levy Flight to Solve Dynamic Economic Dispatch Problem with Electric Vehicle Profiles
• 1.1 Introduction
• 1.2 Problem Formulation
• 1.2.1 Power Output Limits
• 1.2.2 Power Balance Limits
• 1.2.3 Ramp Rate Limits
• 1.2.4 Electric Vehicles
• 1.3 Proposed Algorithm
• 1.3.1 Overview of Grey Wolf Optimizer
• 1.3.2 Improved Grey Wolf Optimizer with Levy Flight
• 1.3.3 Modeling of Prey Position with Levy Flight Distribution
• 1.4 Simulation and Results
• 1.4.1 Performance of Improved GWOLF on Benchmark Functions
• 1.4.2 Performance of Improved GWOLF for Solving DED for the Different Charging Probability Distribution
• 1.5 Conclusion
• References
• Chapter 2 Comparison of YOLO and Faster R-CNN on Garbage Detection
• 2.1 Introduction
• 2.2 Garbage Detection
• 2.2.1 Transfer Learning-Technique
• 2.2.2 Inception-Custom Model
• 2.3 Experimental Results
• 2.3.1 Results Obtained Using YOLO Algorithm
• 2.3.2 Results Obtained Using Faster R-CNN
• 2.4 Future Scope
• 2.5 Conclusion
• References
• Chapter 3 Smart Power Factor Correction and Energy Monitoring System
• 3.1 Introduction
• 3.2 Block Diagram
• 3.2.1 Power Factor Concept
• 3.2.2 Power Factor Calculation
• 3.3 Simulation
• 3.4 Conclusion
• References
• Chapter 4 ANN-Based Maximum Power Point Tracking Control Configured Boost Converter for Electric Vehicle Applications
• 4.1 Introduction
• 4.2 Block Diagram
• 4.3 ANN-Based MPPT for Boost Converter
• 4.4 Closed Loop Control
• 4.5 Simulation Results
• 4.6 Conclusion
• References
• Chapter 5 Single/Multijunction Solar Cell Model Incorporating Maximum Power Point Tracking Scheme Based on Fuzzy Logic Algorithm
• 5.1 Introduction

• 5.2 Modeling Structure
• 5.2.1 Single-Junction Solar Cell Model
• 5.2.2 Modeling of Multijunction Solar PV Cell
• 5.3 MPPT Design Techniques
• 5.3.1 Design of MPPT Scheme Based on P&amp
• O Technique
• 5.3.2 Design of MPPT Scheme Based on FLA
• 5.4 Results and Discussions
• 5.4.1 Single-Junction Solar Cell
• 5.4.2 Multijunction Solar PV Cell
• 5.4.3 Implementation of MPPT Scheme Based on P&amp
• O Technique
• 5.4.4 Implementation of MPPT Scheme Based on FLA
• 5.5 Conclusion
• References
• Chapter 6 Particle Swarm Optimization: An Overview, Advancements and Hybridization
• 6.1 Introduction
• 6.2 The Particle Swarm Optimization: An Overview
• 6.3 PSO Algorithms and Pseudo-Code
• 6.3.1 PSO Algorithm
• 6.3.2 Pseudo-Code for PSO
• 6.3.3 PSO Limitations
• 6.4 Advancements in PSO and Its Perspectives
• 6.4.1 Inertia Weight
• 6.4.2 Constriction Factors
• 6.4.3 Topologies
• 6.4.4 Analysis of Convergence
• 6.5 Hybridization of PSO
• 6.5.1 PSO Hybridization with Artificial Bee Colony (ABC)
• 6.5.2 PSO Hybridization with Ant Colony Optimization (ACO)
• 6.5.3 PSO Hybridization with Genetic Algorithms (GA)
• 6.6 Area of Applications of PSO
• 6.7 Conclusions
• References
• Chapter 7 Application of Genetic Algorithm in Sensor Networks and Smart Grid
• 7.1 Introduction
• 7.2 Communication Sector
• 7.2.1 Sensor Networks
• 7.3 Electrical Sector
• 7.3.1 Smart Microgrid
• 7.4 A Brief Outline of GAs
• 7.5 Sensor Network's Energy Optimization
• 7.6 Sensor Network's Coverage and Uniformity Optimization Using GA
• 7.7 Use GA for Optimization of Reliability and Availability for Smart Microgrid
• 7.8 GA Versus Traditional Methods
• 7.9 Summaries and Conclusions
• References
• Chapter 8 AI-Based Predictive Modeling of Delamination Factor for Carbon Fiber-Reinforced Polymer (CFRP) Drilling Process
• 8.1 Introduction

• 8.2 Methodology
• 8.3 AI-Based Predictive Modeling
• 8.3.1 Linear Regression
• 8.3.2 Random Forests
• 8.3.3 XGBoost
• 8.3.4 SVM
• 8.4 Performance Indices
• 8.4.1 Root Mean Squared Error (RMSE)
• 8.4.2 Mean Squared Error (MSE)
• 8.4.3 R2 (R-Squared)
• 8.5 Results and Discussion
• 8.5.1 Key Performance Metrics (KPIs) During the Model Training Phase
• 8.5.2 Key Performance Index Metrics (KPIs) During the Model Testing Phase
• 8.5.3 K Cross Fold Validation
• 8.6 Conclusions
• References
• Chapter 9 Performance Comparison of Differential Evolutionary Algorithm-Based Contour Detection to Monocular Depth Estimation for Elevation Classification in 2D Drone-Based Imagery
• 9.1 Introduction
• 9.2 Literature Survey
• 9.3 Research Methodology
• 9.3.1 Dataset and Metrics
• 9.4 Result and Discussion
• 9.5 Conclusion
• References
• Chapter 10 Bioinspired MOPSO-Based Power Allocation for Energy Efficiency and Spectral Efficiency Trade-Off in Downlink NOMA
• 10.1 Introduction
• 10.2 System Model
• 10.3 User Clustering
• 10.4 Optimal Power Allocation for EE-SE Tradeoff
• 10.4.1 Multiobjective Optimization Problem
• 10.4.2 Multiobjective PSO
• 10.4.3 MOPSO Algorithm for EE-SE Trade-Off in Downlink NOMA
• 10.5 Numerical Results
• 10.6 Conclusion
• References
• Chapter 11 Performances of Machine Learning Models and Featurization Techniques on Amazon Fine Food Reviews
• 11.1 Introduction
• 11.1.1 Related Work
• 11.2 Materials and Methods
• 11.2.1 Data Cleaning and Pre-Processing
• 11.2.2 Feature Extraction
• 11.2.3 Classifiers
• 11.3 Results and Experiments
• 11.4 Conclusion
• References
• Chapter 12 Optimization of Cutting Parameters for Turning by Using Genetic Algorithm
• 12.1 Introduction
• 12.2 Genetic Algorithm GA: An Evolutionary Computational Technique
• 12.3 Design of Multiobjective Optimization Problem

• 12.3.1 Decision Variables
• 12.3.2 Objective Functions
• 12.3.3 Bounds of Decision Variables
• 12.3.4 Response Variables
• 12.4 Results and Discussions
• 12.4.1 Single Objective Optimization
• 12.4.2 Results of Multiobjective Optimization
• 12.5 Conclusion
• References
• Chapter 13 Genetic Algorithm-Based Optimization for Speech Processing Applications
• 13.1 Introduction to GA
• 13.1.1 Enhanced GA
• 13.2 GA in Automatic Speech Recognition
• 13.2.1 GA for Optimizing Off-Line Parameters in Voice Activity Detection (VAD)
• 13.2.2 Classification of Features in ASR Using GA
• 13.2.3 GA-Based Distinctive Phonetic Features Recognition
• 13.2.4 GA in Phonetic Decoding
• 13.3 Genetic Algorithm in Speech Emotion Recognition
• 13.3.1 Speech Emotion Recognition
• 13.3.2 Genetic Algorithms in Speech Emotion Recognition
• 13.4 Genetic Programming in Hate Speech Using Deep Learning
• 13.4.1 Introduction to Hate Speech Detection
• 13.4.2 GA Integrated With Deep Learning Models for Hate Speech Detection
• 13.5 Conclusion
• References
• Chapter 14 Performance of P, PI, PID, and NARMA Controllers in the Load Frequency Control of a Single-Area Thermal Power Plant
• 14.1 Introduction
• 14.2 Single-Area Power System
• 14.3 Automatic Load Frequency Control (ALFC)
• 14.4 Controllers Used in the Simulink Model
• 14.4.1 PID Controller
• 14.4.2 PI Controller
• 14.4.3 P Controller
• 14.5 Circuit Description
• 14.6 ANN and NARMA L2 Controller
• 14.7 Simulation Results and Comparative Analysis
• 14.8 Conclusion
• References
• Part 2: Decision Science and Simulation-Based Optimization
• Chapter 15 Selection of Nonpowered Industrial Truck for Small Scale Manufacturing Industry Using Fuzzy VIKOR Method Under FMCDM Environment
• 15.1 Introduction
• 15.2 Fuzzy Set Theory
• 15.2.1 Some Important Fuzzy Definitions
• 15.2.2 Fuzzy Operations

OPTIMIZATION TECHNIQUES IN ENGINEERING The book describes the basic components of an optimization problem along with the formulation of design problems as mathematical programming problems using an objective function that expresses the main aim of the model, and how it is to be either minimized or maximized; subsequently, the concept of optimization and its relevance towards an optimal solution in engineering applications, is explained. This book aims to present some of the recent developments in the area of optimization theory, methods, and applications in engineering. It focuses on the metaphor of the inspired system and how to configure and apply the various algorithms. The book comprises 30 chapters and is organized into two parts: Part I -- Soft Computing and Evolutionary-Based Optimization; and Part II -- Decision Science and Simulation-Based Optimization, which contains application-based chapters. Readers and users will find in the book: An overview and brief background of optimization methods which are used very popularly in almost all applications of science, engineering, technology, and mathematics; An in-depth treatment of contributions to optimal learning and optimizing engineering systems; Maps out the relations between optimization and other mathematical topics and disciplines; A problem-solving approach and a large number of illustrative examples, leading to a step-by-step formulation and solving of optimization problems. Audience Researchers, industry professionals, academicians, and doctoral scholars in major domains of engineering, production, thermal, electrical, industrial, materials, design, computer engineering, and natural sciences. The book is also suitable for researchers and postgraduate students in mathematics, applied mathematics, and industrial mathematics

• Cover
• Title Page
• Copyright Page
• Contents
• Preface
• Acknowledgment
• Part 1: Soft Computing and Evolutionary-Based Optimization
• Chapter 1 Improved Grey Wolf Optimizer with Levy Flight to Solve Dynamic Economic Dispatch Problem with Electric Vehicle Profiles
• 1.1 Introduction
• 1.2 Problem Formulation
• 1.2.1 Power Output Limits
• 1.2.2 Power Balance Limits
• 1.2.3 Ramp Rate Limits
• 1.2.4 Electric Vehicles
• 1.3 Proposed Algorithm
• 1.3.1 Overview of Grey Wolf Optimizer
• 1.3.2 Improved Grey Wolf Optimizer with Levy Flight
• 1.3.3 Modeling of Prey Position with Levy Flight Distribution
• 1.4 Simulation and Results
• 1.4.1 Performance of Improved GWOLF on Benchmark Functions
• 1.4.2 Performance of Improved GWOLF for Solving DED for the Different Charging Probability Distribution
• 1.5 Conclusion
• References
• Chapter 2 Comparison of YOLO and Faster R-CNN on Garbage Detection
• 2.1 Introduction
• 2.2 Garbage Detection
• 2.2.1 Transfer Learning-Technique
• 2.2.2 Inception-Custom Model
• 2.3 Experimental Results
• 2.3.1 Results Obtained Using YOLO Algorithm
• 2.3.2 Results Obtained Using Faster R-CNN
• 2.4 Future Scope
• 2.5 Conclusion
• References
• Chapter 3 Smart Power Factor Correction and Energy Monitoring System
• 3.1 Introduction
• 3.2 Block Diagram
• 3.2.1 Power Factor Concept
• 3.2.2 Power Factor Calculation
• 3.3 Simulation
• 3.4 Conclusion
• References
• Chapter 4 ANN-Based Maximum Power Point Tracking Control Configured Boost Converter for Electric Vehicle Applications
• 4.1 Introduction
• 4.2 Block Diagram
• 4.3 ANN-Based MPPT for Boost Converter
• 4.4 Closed Loop Control
• 4.5 Simulation Results
• 4.6 Conclusion
• References
• Chapter 5 Single/Multijunction Solar Cell Model Incorporating Maximum Power Point Tracking Scheme Based on Fuzzy Logic Algorithm
• 5.1 Introduction.

• 5.2 Modeling Structure
• 5.2.1 Single-Junction Solar Cell Model
• 5.2.2 Modeling of Multijunction Solar PV Cell
• 5.3 MPPT Design Techniques
• 5.3.1 Design of MPPT Scheme Based on P&amp
• O Technique
• 5.3.2 Design of MPPT Scheme Based on FLA
• 5.4 Results and Discussions
• 5.4.1 Single-Junction Solar Cell
• 5.4.2 Multijunction Solar PV Cell
• 5.4.3 Implementation of MPPT Scheme Based on P&amp
• O Technique
• 5.4.4 Implementation of MPPT Scheme Based on FLA
• 5.5 Conclusion
• References
• Chapter 6 Particle Swarm Optimization: An Overview, Advancements and Hybridization
• 6.1 Introduction
• 6.2 The Particle Swarm Optimization: An Overview
• 6.3 PSO Algorithms and Pseudo-Code
• 6.3.1 PSO Algorithm
• 6.3.2 Pseudo-Code for PSO
• 6.3.3 PSO Limitations
• 6.4 Advancements in PSO and Its Perspectives
• 6.4.1 Inertia Weight
• 6.4.2 Constriction Factors
• 6.4.3 Topologies
• 6.4.4 Analysis of Convergence
• 6.5 Hybridization of PSO
• 6.5.1 PSO Hybridization with Artificial Bee Colony (ABC)
• 6.5.2 PSO Hybridization with Ant Colony Optimization (ACO)
• 6.5.3 PSO Hybridization with Genetic Algorithms (GA)
• 6.6 Area of Applications of PSO
• 6.7 Conclusions
• References
• Chapter 7 Application of Genetic Algorithm in Sensor Networks and Smart Grid
• 7.1 Introduction
• 7.2 Communication Sector
• 7.2.1 Sensor Networks
• 7.3 Electrical Sector
• 7.3.1 Smart Microgrid
• 7.4 A Brief Outline of GAs
• 7.5 Sensor Network's Energy Optimization
• 7.6 Sensor Network's Coverage and Uniformity Optimization Using GA
• 7.7 Use GA for Optimization of Reliability and Availability for Smart Microgrid
• 7.8 GA Versus Traditional Methods
• 7.9 Summaries and Conclusions
• References
• Chapter 8 AI-Based Predictive Modeling of Delamination Factor for Carbon Fiber-Reinforced Polymer (CFRP) Drilling Process
• 8.1 Introduction.

• 8.2 Methodology
• 8.3 AI-Based Predictive Modeling
• 8.3.1 Linear Regression
• 8.3.2 Random Forests
• 8.3.3 XGBoost
• 8.3.4 SVM
• 8.4 Performance Indices
• 8.4.1 Root Mean Squared Error (RMSE)
• 8.4.2 Mean Squared Error (MSE)
• 8.4.3 R2 (R-Squared)
• 8.5 Results and Discussion
• 8.5.1 Key Performance Metrics (KPIs) During the Model Training Phase
• 8.5.2 Key Performance Index Metrics (KPIs) During the Model Testing Phase
• 8.5.3 K Cross Fold Validation
• 8.6 Conclusions
• References
• Chapter 9 Performance Comparison of Differential Evolutionary Algorithm-Based Contour Detection to Monocular Depth Estimation for Elevation Classification in 2D Drone-Based Imagery
• 9.1 Introduction
• 9.2 Literature Survey
• 9.3 Research Methodology
• 9.3.1 Dataset and Metrics
• 9.4 Result and Discussion
• 9.5 Conclusion
• References
• Chapter 10 Bioinspired MOPSO-Based Power Allocation for Energy Efficiency and Spectral Efficiency Trade-Off in Downlink NOMA
• 10.1 Introduction
• 10.2 System Model
• 10.3 User Clustering
• 10.4 Optimal Power Allocation for EE-SE Tradeoff
• 10.4.1 Multiobjective Optimization Problem
• 10.4.2 Multiobjective PSO
• 10.4.3 MOPSO Algorithm for EE-SE Trade-Off in Downlink NOMA
• 10.5 Numerical Results
• 10.6 Conclusion
• References
• Chapter 11 Performances of Machine Learning Models and Featurization Techniques on Amazon Fine Food Reviews
• 11.1 Introduction
• 11.1.1 Related Work
• 11.2 Materials and Methods
• 11.2.1 Data Cleaning and Pre-Processing
• 11.2.2 Feature Extraction
• 11.2.3 Classifiers
• 11.3 Results and Experiments
• 11.4 Conclusion
• References
• Chapter 12 Optimization of Cutting Parameters for Turning by Using Genetic Algorithm
• 12.1 Introduction
• 12.2 Genetic Algorithm GA: An Evolutionary Computational Technique
• 12.3 Design of Multiobjective Optimization Problem.

• 12.3.1 Decision Variables
• 12.3.2 Objective Functions
• 12.3.3 Bounds of Decision Variables
• 12.3.4 Response Variables
• 12.4 Results and Discussions
• 12.4.1 Single Objective Optimization
• 12.4.2 Results of Multiobjective Optimization
• 12.5 Conclusion
• References
• Chapter 13 Genetic Algorithm-Based Optimization for Speech Processing Applications
• 13.1 Introduction to GA
• 13.1.1 Enhanced GA
• 13.2 GA in Automatic Speech Recognition
• 13.2.1 GA for Optimizing Off-Line Parameters in Voice Activity Detection (VAD)
• 13.2.2 Classification of Features in ASR Using GA
• 13.2.3 GA-Based Distinctive Phonetic Features Recognition
• 13.2.4 GA in Phonetic Decoding
• 13.3 Genetic Algorithm in Speech Emotion Recognition
• 13.3.1 Speech Emotion Recognition
• 13.3.2 Genetic Algorithms in Speech Emotion Recognition
• 13.4 Genetic Programming in Hate Speech Using Deep Learning
• 13.4.1 Introduction to Hate Speech Detection
• 13.4.2 GA Integrated With Deep Learning Models for Hate Speech Detection
• 13.5 Conclusion
• References
• Chapter 14 Performance of P, PI, PID, and NARMA Controllers in the Load Frequency Control of a Single-Area Thermal Power Plant
• 14.1 Introduction
• 14.2 Single-Area Power System
• 14.3 Automatic Load Frequency Control (ALFC)
• 14.4 Controllers Used in the Simulink Model
• 14.4.1 PID Controller
• 14.4.2 PI Controller
• 14.4.3 P Controller
• 14.5 Circuit Description
• 14.6 ANN and NARMA L2 Controller
• 14.7 Simulation Results and Comparative Analysis
• 14.8 Conclusion
• References
• Part 2: Decision Science and Simulation-Based Optimization
• Chapter 15 Selection of Nonpowered Industrial Truck for Small Scale Manufacturing Industry Using Fuzzy VIKOR Method Under FMCDM Environment
• 15.1 Introduction
• 15.2 Fuzzy Set Theory
• 15.2.1 Some Important Fuzzy Definitions
• 15.2.2 Fuzzy Operations.

OPTIMIZATION TECHNIQUES IN ENGINEERING The book describes the basic components of an optimization problem along with the formulation of design problems as mathematical programming problems using an objective function that expresses the main aim of the model, and how it is to be either minimized or maximized; subsequently, the concept of optimization and its relevance towards an optimal solution in engineering applications, is explained. This book aims to present some of the recent developments in the area of optimization theory, methods, and applications in engineering. It focuses on the metaphor of the inspired system and how to configure and apply the various algorithms. The book comprises 30 chapters and is organized into two parts: Part I -- Soft Computing and Evolutionary-Based Optimization; and Part II -- Decision Science and Simulation-Based Optimization, which contains application-based chapters. Readers and users will find in the book: An overview and brief background of optimization methods which are used very popularly in almost all applications of science, engineering, technology, and mathematics; An in-depth treatment of contributions to optimal learning and optimizing engineering systems; Maps out the relations between optimization and other mathematical topics and disciplines; A problem-solving approach and a large number of illustrative examples, leading to a step-by-step formulation and solving of optimization problems. Audience Researchers, industry professionals, academicians, and doctoral scholars in major domains of engineering, production, thermal, electrical, industrial, materials, design, computer engineering, and natural sciences. The book is also suitable for researchers and postgraduate students in mathematics, applied mathematics, and industrial mathematics.

• Nonconforming spectral element method for Oseen equations and Navier Stokes equations
• Application of Gorilla troops' social intelligence in damage detection for a girder bridge
• Numerical Analyses for Evaluation of Factor of Safety Distribution Map
• A Hybrid Optimization Algorithm for Structural Health Monitoring
• Transient Analysis of Heat Transfer in a Trunk Under a Forest Fire Influence
• Design of an Auditorium Equipped with an Attached Solar Greenhouse Used to Improve Indoor Environmental Conditions
• K-means optimizer: An efficient Optimization Algorithm for predicting the uncertain material parameters in real structures
• A nonlinear approach to investigate the effect of sheet pile toe's embedded length on the lateral displacement derived from soft clay-deep excavation
• Damage Detection in a 3D Truss Structure Using Natural Frequencies and Metaheuristic Algorithms
• Effect of the incident wave angle on the hydrodynamic performance of a land-based OWC device
• Data-driven Kriging model for predicting concrete compressive strength and parameter correlation analysis.

This book gathers outstanding papers on numerical modeling in Civil Engineering (Volume 1) as part of the 2-volume proceedings of the 5th International Conference on Numerical Modeling in Engineering (NME 2022), which was held in Ghent, Belgium, on 23-24 August 2022. The overall objective of the conference was to bring together international scientists and engineers in academia and industry from fields related to advanced numerical techniques, such as the finite element method (FEM), boundary element method (BEM), isogeometric analysis (IGA), etc., and their applications to a wide range of engineering disciplines. This volume covers numerical simulations with industrial civil engineering applications such as bridges and dams, cyclic loading, fluid dynamics, structural mechanics, geotechnical engineering, thermal analysis, reinforced concrete structures, steel structures, and composite structures. The book is intended for academics, including graduate students and researchers, as well as industrial practitioners working in the numerical modelling in civil engineering topics.

• Optimization of ship energy efficiency considering navigational environment and safety
• Study on the consistency of a phase field modeling method and the determination of crack width
• Numerical Simulation Of Shear Wave Propagation Through Jointed Rocks
• A quasi-static computational model for fracture in multidomain structures with inclusions
• Updated Lagrangian Curvilinear Beam Element for 2D Large Displacement Analysis
• Modelling and simulation of micro-electro-mechanical systems for energy harvesting of random mechanical vibrations
• Revisiting a Model that Describes the Process of the Vocal Oscillation During Phonation, a Numerical Approach
• Shear stress and temperature analysis of Inconel 718 during the backward flow forming process using the finite element method
• Mechanical Design and Optimization of Large-Scale Parabolic Trough Solar Collectors for Industrial Applications
• Finite Element Modeling of Ultrasonic Nanocrystalline Surface Modification Process of Alloy 718. .

This book gathers outstanding papers on numerical modeling in Mechanical Engineering (Volume 2) as part of the 2-volume proceedings of the 5th International Conference on Numerical Modeling in Engineering (NME 2021), which was held in Ghent, Belgium, on August 23-24, 2022. The overall objective of the conference was to bring together international scientists and engineers in academia and industry from fields related to advanced numerical techniques, such as the finite element method (FEM), boundary element method (BEM), isogeometric analysis (IGA), and their applications to a wide range of engineering disciplines. This book addresses numerical simulations of various mechanical and materials engineering industrial applications such as aerospace applications, acoustic analysis, bio-mechanical applications, contact problems and wear, heat transfer analysis, vibration and dynamics, transient analysis, nonlinear analysis, composite materials, polymers, metal alloys, fracture mechanics, fatigue of materials, creep, mechanical behavior, micro-structure, phase transformation, and crystal plasticity. The book is intended for academics, including graduate students and researchers, as well as industrial practitioners working in the numerical modeling in mechanical engineering topics.

In this self-contained and rigorous book, undergraduate students of physics, chemistry and engineering will find comprehensive coverage of their introductory quantum mechanics courses, and graduate students will find important discussion of the advanced tools and concepts necessary to describe real world phenomena in nanoscience and technology.

• Investigating Noise:
• Attribution
• Dimensions of Attribution
• Design FMEA continued
• Further examples Severity and Occurrence Ratings
• Cassette Derailleur
• Object, Function and Design Solution Triads
• Updated Propulsion System State Flow Diagram
• Phase 3 of the OFTEN Framework
• Design Controls
• Current Design Controls Prevention
• Detection Ratings
• Current Design Controls Detection
• P-Diagram
• Noise Factor Types
• Noise and Control Factor Table
• Noise Factor Types
• Diverted Output
• Control Factors
• Design FMEA Recommended Action
• Comparison of Design FMEA and Noise and Control Factor Table
• Chapter 10 Developing Models
• Propulsive and Resistive Forces Acting on eBike
• Mathematical modelling
• External Interfaces with eBike Affecting Propulsion
• Noise and Control Factor Table for Propulsive Forces
• Noise Factors by Type
• Diverted Output
• Effect of Noise on model parameters
• Control Factors
• Framing Information; The Written Word
• Noise and Control Factor Table for Propulsive Forces
• Further detail
• eBike Propulsion System Noise Effect Simulator
• Variation in Resistive Power with Differing Noise Space
• Chapter 11 Preventing Failure
• Using Closed Questions
• Questioning for Information
• Elements that Affect Question Response
• Noise and Control Factor Table
• Further examples
• DFMEA Recommended Actions
• Robustness Strategies
• Different types
• Inclusion in NCF Table
• Hardware in Loop Setup for eBike
• Relative Effect of Resistive Forces on eBike Propulsion
• Chapter 12 Moving Levels
• Ranking eBike Features
• Brushless DC Mid-Drive Motor
• Systems Vee Model revisited
• eBike Motor
• High-level SSFD
• System State Flow Diagram
• Function Tree
• Comparison of Propulsion System and eBike Motor Boundary Diagrams
• eBike Motor Interface Analysis
• Interface Matrix
• Internal and External Interface Tables
• Comparison of Propulsion System and Motor Interface Tables
• Noise and Control Factor Table for Motor
• Comparison of Propulsion System and eBike Motor Design FMEAs
• eBike Interface Analysis and FMEA Partitioning and Decomposition
• Noise and Control Factor Table for Motor Optimisation Model
• DC Motor Characteristic Curves
• Brushless DC Motor Torque Curve
• Motor Simulation Model Parameters
• System Cascade eBike to Motor
• Chapter 13 Verifying the Design
• Review of Oe375 People Skills
• People Skills as a System
• Phase 4 of the OFTEN Framework
• System Vee; Systems Integration and Verification
• Design Verification at Different System Levels
• Noise and Control Factor Table for Propulsive Forces
• Design Verification Tests
• Distance to Failure
• Measures of System Robustness
• Noise and Control Factor Table for Motor
• Design Verification Tests
• Knowledge Gain and the OFTEN Framework
• Oe375 Programme Roadmap
• Retrospective View
• Chapter 14 Reviewing Achievements
• The Product Launch and Consequences for Oxton
• Appendix: Key Graphics
• Glossary
• References
• Index

• Introduction
• Consciousness
• Dependability Engineering
• Risk-conscious Culture
• Risk-based Engineering
• Risk Simulation
• Human Factors in Operation
• Operational Risk Management
• Artificial Intelligence Based Approach for Operator Support System
• Risk-Conscious Maintenance Management.

This book presents various concepts and applications related to risk-conscious operations management. It also provides an overview of the risk-based engineering fundamental to the concept of risk-conscious operations management. It presents the reliability concept to support Dependency Modelling, which includes hardware systems structures and components for reliability improvement and risk reduction. The book further develops and builds attributes and model for risk-conscious culture critical to characterize operational approach to risk and presents human factor modelling, where it works on developing an approach for human error precursor analysis. This book will be useful for students, researchers, academicians and professionals working on identifying risk and reliability issues in complex safety and mission critical systems. It will also be beneficial for industry risk-and-reliability experts and operational safety staff working in the complex engineering systems.