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• 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.

• 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.

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.

• Section 1. Pre-service and in-service teacher development. Chapter 1. Integrating physics into a mathematics content course for preservice K8 elementary teachers ; Chapter 2. Scaffolding hypothesis formation and testing during simulation coding ; Chapter 3. Effective use of technology for teaching in STEM ; Chapter 4. The impact of teacher leaders in STEM education
• Section 2. Secondary and higher education. Chapter 5. Active learning and the pythagorean theorem through dynamic geometry and robotic optimization: the case of Kaitlyn ; Chapter 6. Using Desmos and GeoGebra to engage students and develop conceptual understanding of mathematics ; Chapter 7. Effective use of embedded platforms in the development of experiments for enhancing the interests of STEAM students in Mexico ; Chapter 8. Technology-enhanced mathematics trails for out-of-school learning of the application of mathematics ; Chapter 9. Using technology to enhance student engagement in STEM subjects in higher education
• Section 3. Middle school and elementary school. Chapter 10. The influence of online mathematics activity on elementary school students' engagement and learning in a high-needs contexts ; Chapter 11. Impact of virtual field trips on elementary students' interest in science and STEM ; Chapter 12. Relationships between mathematics self-beliefs, exposure to ICT in school, and achievement on PISA 2012 paper- and computer-based mathematics assessments ; Chapter 13. Math snacks: a history of cultivating digital game-based learning environments.

Teacher and student access to technology in both schools and at home continues to rise. Due to this increase, there is a need to examine how technology is supporting teaching and learning in STEM classrooms from early childhood through college-level mathematics. To ensure it is utilized appropriately, further study on the use of technology in classrooms where students are learning science, technology, engineering, and mathematics content is required. Technology Integration and Transformation in STEM Classrooms offers meaningful and comprehensive examples of implementing technology to support STEM teaching and learning and provides a deeper understanding of how to ensure technology is used to enhance the learning environment. The book also details how educators can select effective learning tools for their classrooms. Covering key topics such as student engagement, active learning, teacher leaders, and e-learning, this reference work is ideal for administrators, policymakers, educational leaders, researchers, academicians, scholars, practitioners, instructors, and students.
(source: Nielsen Book Data)

• Foreword / Miranda Feliciano Tyson
• The age of inference / John R. McConnell, Sarah B. Dugger, and Philip C. Short
• Nature of the scientific enterprise / Harvey Henson
• The nature of science education : relativity of theory / Philip C. Short
• Mathematics : language, modeling, and comparison assisting inference / Mary Barone Martin, Tammy Jones, Dovie Kimmins, and Teresa Schmidt
• Statistics : developing impactful teaching and learning / Mary Barone Martin, Tammy Jones, and Teresa Schmidt
• Statistics : assessing success in the inference process / Mary Barone Martin, Tammy Jones, and Teresa Schmidt
• Children's literature resources to support authentic science practices and environmental decision-making : The conservation tales series / Tom J. McConnell and Barbara Giorgio-Booher
• Supporting statistical literacies in the context of a data visualization project with elementary students / Lynn Hodge, Joy Bertling, and Shande King
• Green literacy K-5 : nurturing a scientific mindset / Jen Cullerton Johnson and Mary K. Gove
• Complex multimodal text sets to support science literacy / William Romine, Amy Lannin, Torrey Palmer, Delinda van Garderen, Rachel Juergensen, Cassandra M. Smith, and William Folk
• Power up or put away? Using mobile phones for authentic student investigations / Kristin T. Rearden and Blanche O'Bannon
• Self-regulated learning theory to build scientific mindsets for diversity in STEM / Giuseppina Mattietti and Erin E. Peters-Burton
• A case for the model-based reasoning classroom / Arthur Beauchamp and Cynthia Passmore
• Cultivating a scientific mindset through inquiry-based science learning utilizing nasa resources for educators / Leslie Huling and Virginia Resta
• Bridging the disconnect between how we do and teach science : cultivating a scientific mindset in an era of data-driven education / Jana Bouwma-Gearhart
• The scientific method card game : applications for any educational context / Kallina M. Dunkle
• Toward a design-centered scientific mindset : closing the opportunity gaps via 3D design and printing in STEM teacher education / Lingguo Bu, Harvey Henson, and Euginia Nyirenda
• Developing critical literacy skills among diverse learners during the age of inference / Laveria F. Hutchison
• Content and pedagogical knowledge for teaching confidence intervals in a post p < 0.05 world / Jennifer J. Kaplan and Kristen E. Roland
• The multidimensional learning goals for making inferences with data / Ryan Seth Jones, Anna Strimaitis Grinath, and Fonya Scott
• Expectations and disciplinary blends / L. Jeneva Clark, R. Alexander Bentley, Nicholas N. Nagle, and Vasileios Maroulas
• Machine learning : a new lens for integrating computational thinking and science in the high school classroom / Michael Daley, Zhen Bai, Raffaella Borasi, and Dave Miller
• Becoming a postmodern STEM teacher leader in the age of inference / Rebekah Hammack
• Seeking homeostasis in a heteroscedastic world : a sense of the stakes in the age of inference / Philip C. Short, Donna F. Short, and John R. McConnell

In an age where we are inundated with information, the ability to discern verifiable information to make proper decisions and solve problems is ever more critical. Modern science, which espouses a systematic approach to making "inferences, " requires a certain mindset that allows for a degree of comfort with uncertainty. This book offers inspirations and ideas for cultivating the proper mindset for the studying, teaching, and practicing of science that will be useful for those new to as well as familiar with the field. Although a paradigm shift from traditional instruction is suggested in the National Framework for K-12 science, this volume is intended to help educators develop a personal mental framework in which to transition from a teacher-centered, didactical approach to a studentcentered, evidence-guided curriculum. While the topics of the book derive from currently published literature on STEM education as they relate to the National Framework for K-12 Science and the Three-Dimensional science instruction embedded in the Next Generation Science Standards, this book also examines these topics in the context of a new societal age posited as the "Age of Inference" and addresses how to make sense of the ever-increasing deluge of information that we are experiencing by having a scientific and properly discerning mindset.
(source: Nielsen Book Data)

• Chapter 1: The foundation of SREThis chapter lays out the foundation of Site Resiliency Engineering, founded by Google. From the base concepts of how IT Operations and Developers need to collaborate, to how SRE helps organizations in running business-critical workloads without major downtime Chapter 2: Service Level Management definitions and acronyms and their meaning in a real-life context This Chapter describes all common Service Level Agreements (SLA) definitions and acronyms, looked at from a real-world scenario to provide a clear understanding o Some examples, SLA, SLO, MTTF, MTBF, MTTR, ... Chapter 3: Architecting Resilient Infrastructure as a Service (IaaS) Solutions in Azure SRE is all about providing ultimate uptime of your organization's workloads, and this chapter will cover that in relation to Azure IaaS Compute solutions. Explaining the Azure reference architecture for high-available storage, networking and Virtual Machine computing, describing Availability Sets and Zones and ScaleSets as main scenarios. It will also touch on preparing for Disaster Recovery with Azure Backup and Azure Site Recovery, helping you to quickly mitigate outages in case of a failure Chapter 4: Architecting Resilient Platform as a Service (PaaS) Solutions in Azure Following on the scenario of Virtual Machines, this chapter details similar reference architectures for Platform Services such as App Services with Web Apps, but also touching on data solutions like Azure SQL and Azure Cosmos DB Chapter 5: Architecting Resilient Serverless and Microservices architectures in Azure This third chapter in the reference architecture topic describes how to build high-available, business-critical scenarios using Serverless Functions and Azure LogicApps, as well as Microservices scenarios using Azure Container Instance and Azure Kubernetes Service (AKS). Chapter 6: Automation to enable SRE with Azure DevOps Pipelines / GitHub Actions Automation is the cornerstone to SRE, allowing businesses to not only deploy new workloads in a easy way, but also relying on SRE to avoid critical outages or, when an outage occurs, relying on automation to mitigate the problem as fast as possible. Sharing several examples from both Azure DevOps Pipelines and GitHub Actions, this chapter provides the reader a lot of real-life examples to reuse in their own environment Chapter 7: Efficiently handling blameless post-mortems Post-Mortems are the way to look back at what caused the outage, and describe any lessons learned for the future, helping in avoiding a similar outage in the future, or assist in quickly fixing an identical incident. Blameless is where the focus is on finding the root-cause of the problem, without pinpointing any individual or team as being the victim. This chapter describes how an open culture around post-mortems dramatically helps in optimizing SRE and the overall company culture around managing and running IT systems and application workloads.
• Chapter 8: Monitoring as the key to knowledge
• Besides the automated deployments, monitoring is the 2nd big technical topic in any SRE scenario. You can't manage what you don't know. This chapter provides an overview of Azure Monitor and Log Analytics, which forms the foundation of monitoring Azure and Hybrid-running workloads. Starting from metrics for the different Azure services touched on in earlier chapters, this chapter also covers how to export logs to 3rd party solutions such as Splunk or integrating dashboarding tools like Grafana .
• (source: Nielsen Book Data)

Gain a foundational understanding of SRE and learn its basic concepts and architectural best practices for deploying Azure IaaS, PaaS, and microservices-based resilient architectures. The book starts with the base concepts of SRE operations and developer needs, followed by definitions and acronyms of Service Level Agreements in real-world scenarios. Moving forward, you will learn how to build resilient IaaS solutions, PaaS solutions, and microservices architecture in Azure. Here you will go through Azure reference architecture for high-available storage, networking and virtual machine computing, describing Availability Sets and Zones and Scale Sets as main scenarios. You will explore similar reference architectures for Platform Services such as App Services with Web Apps, and work with data solutions like Azure SQL and Azure Cosmos DB. Next, you will learn automation to enable SRE with Azure DevOps Pipelines and GitHub Actions. You'll also gain an understanding of how an open culture around post-mortems dramatically helps in optimizing SRE and the overall company culture around managing and running IT systems and application workloads. You'll be exposed to incent management and monitoring practices, by making use of Azure Monitor/Log Analytics/Grafana, which forms the foundation of monitoring Azure and Hybrid-running workloads. As an extra, the book covers two new testing solutions: Azure Chaos Studio and Azure Load Testing. These solutions will make it easier to test the resilience of your services. After reading this book, you will understand the underlying concepts of SRE and its implementation using Azure public cloud. What Will You Learn: Learn SRE definitions and metrics like SLI/SLO/SLA, Error Budget, toil, MTTR, MTTF, and MTBF Understand Azure Well-Architected Framework (WAF) and Disaster Recovery scenarios on Azure Understand resiliency and how to design resilient solutions in Azure for different architecture types and services Master core DevOps concepts and the difference between SRE and tools like Azure DevOps and GitHub Utilize Azure observability tools like Azure Monitor, Application Insights, KQL or Grafana Understand Incident Response and Blameless Post-Mortems and how to improve collaboration using ChatOps practices with Microsoft tools Who Is This Book For: IT operations administrators, engineers, security team members, as well as developers or DevOps engineers.
(source: Nielsen Book Data)

• Data Science: Systems.- Big Data Management for Policy Support in Sustainable Development.- Development of the Research Data Archive at OIST.- Symbolic Regression and Graph Neural Networks for Interpretable Scientic Discovery.- A front-end framework selection assistance system with customizable quantification indicators based on analysis of repository and community data.- DATA SCIENCE: Architectures.- Autonomous real-time science-driven follow-up of survey transients.- Deep Learning Application for Reconstruction of Large-Scale Structure of the Universe.- Identification of Distinctive Behavior Patterns of Bots and Human Teams in Soccer.- Cosmic density field reconstruction with a sparsity prior using images of distant galaxies.- Big Data Analytics in Domain-Specific Systems.- Blockchain Enabled System for Interoperable Healthcare.- Skin cancer recognition for low resolution images.- Forecasting AQI data with IoT Enabled Indoor Air Quality Monitoring System.- Journey of Database Migration From RDBMS to NoSQL Data Stores.- Information Interchange of Web Data Resources.- Cascaded Anomaly Detection with Coarse Sampling in Distributed Systems.- Video Indexing System based on Multimodal Information Extraction using combination of ASR and OCR.- GA-ProM: A Genetic Algorithm for Discovery of Complete Process Models from Unbalanced logs.- Experimenting with Assamese Handwritten Character Recognition.- Business Analytics.- Approximate Fault-tolerant Data Stream Aggregation for Edge Computing.- Internet of Things Integrated with Multi-level Authentication for Secured IoT Data Stream through TLS/SSL Layer.- Enhanced Bond Energy Algorithm for Vertical Fragmentation of IoT Data in a Fog Environment.- Approximate Query Processing with Error Guarantees. .
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 9th International Conference on Big Data Analytics, BDA 2021, which took place virtually during December 7-9, 2021.The 15 full papers and 1 short paper included in this volume were carefully reviewed and selected from 60 submissions. They were organized in topical sections as follows: Data science: systems; data science: architectures; big data analytics in healthcare support systems, information interchange of web data resources; and business analytics.
(source: Nielsen Book Data)

• Introduction: Design Make Play for Equity, Inclusion, and Agency
• Harouna Ba, Katherine McMillan Culp, and Margaret Honey
• Part I Designing for Visitors' Agency
• Chapter 1 Designing for Agency in Informal STEM Learning Environments
• Susan M. Letourneau
• Chapter 2 From Explaining to Engaging Visitors: Transforming the Facilitator's Role
• Priya Mohabir, Dorothy Bennett, C. James Liu, and Daisy Tetecatl
• Chapter 3 Narratives, Empathy, and Engineering: Creating Inclusive Engineering Activities
• Susan M. Letourneau, Dorothy Bennett, Amelia Merker, Satbir Multani, C. James Liu, Yessenia Argudo, and Dana Schloss
• Chapter 4 Co-Designing Learning Dashboards for Informal Educators
• Elham Beheshti, Leilah Lyons, Aditi Mallavarapu, Wren Thompson, Betty Wallingford, and Stephen Uzzo
• Part II Relinquishing Power and Authority in Informal Settings
• Chapter 5 Museum-Community Engagement to Support STEM Learning
• Andres Henriquez and Marcia Bueno
• Chapter 6 Big Data for Little Kids: Developing an Inclusive Program for Young Learners and Their Families
• C. James Liu, Kate Maschak, Delia Meza, Susan M. Letourneau, and Yessenia Argudo
• Chapter 7 Designing Maker Programs for Family Engagement
• David Wells, Susan M. Letourneau, and Samantha Tumolo
• Chapter 8 Innovation Institute: Follow the Youth
• David Wells, Elham Beheshti, and Danny Kirk
• Part III Playing and Learning Across Settings
• Chapter 9 See, Touch, and Feel Math: Digital Design for English Language Learners
• Dorothy Bennett, Tara Chudoba, Xiomara Flowers, and Heidi Slouffman
• Chapter 10 Learning Physics through Embodied Play in a School Setting
• Harouna Ba, Christina O'Malley, Yessenia Argudo, and Laycca Umer
• Chapter 11 Integrating Computational Thinking Across the Elementary Curriculum: A Professional Development Approach
• Anthony Negron
• Chapter 12 The Pack: Playfully Embodying Computational and Systems Thinking
• Leilah Lyons, Stephen Uzzo, Harouna Ba, and Wren Thompson.
• (source: Nielsen Book Data)

This pioneering book offers a resource for educators, policymakers, researchers, exhibit designers, and program developers that illuminates creative, cutting-edge ways to inspire, engage, and motivate young people about STEM learning in both informal and formal education settings. A follow-up to the popular book Design, Make, Play (2013), this volume combines new research, innovative case studies, and practical advice from the New York Hall of Science (NYSCI) to define and illustrate a vision for creative and immersive learning, focusing on STEM learning experiences that are truly equitable and inclusive, and that foster learners' agency. Featuring contributions from program developers, facilitators, educators, exhibit designers, and researchers, the book provides real-world examples from informal and formal settings that fill the need for high-quality STEM learning opportunities that are accessible to all learners, including groups underrepresented in STEM education and careers. Chapters of the book describe strategies such as using narratives to make engineering learning more inclusive, engaging English language learners in digital design, focusing on whole-family learning, and introducing underserved students to computational thinking through an immersive computer game. This book offers both a challenge and a guide to all STEM educators in museums, science centers, and other informal and formal education settings who are seeking out ambitious and more equitable forms of engagement. With leading-edge research and practical advice, the book provides appealing and accessible forms of engagement that will support a diverse range of audiences and deepen their approach to creative STEM learning.
(source: Nielsen Book Data)

• 1. Introduction
• 2. Symmetries and conservation theorems
• 2.1. Symmetry : a brief historical introduction
• 2.2. Symmetry in science
• 2.3. Symmetries in dynamic systems
• 2.4. From symmetry to gauge theory
• 2.5. Conclusion

• 3. Spontaneous symmetry breaking
• 3.1. Symmetry breaking
• 3.2. Historical overview and early evolution
• 3.3. Symmetry breaking in particle physics
• 3.4. Condensed matter, superfluidity and Bose-Einstein condensate
• 3.5. Spontaneously broken global symmetry
• 3.6. Higgs mechanism

• 4. Explicit symmetry breaking and electromagnetic radiation
• 4.1. Explicit symmetry breaking of electrodynamic systems
• 4.2. Electromagnetic radiation under non-conserved Noether current
• 4.3. Explicit symmetry breaking and free electron lasers
• 4.4. Electromagnetic radiation under explicit symmetry breaking of filter circuits

• 5. Symmetry breaking in transformation of force fields
• 5.1. Introduction
• 5.2. Broken symmetry in electrodynamic systems, Gauge symmetry and radiation
• 5.3. Symmetry breaking and reversibility

• 6. Piezoelectric antennas
• 7. Radiation from a superconducting loop
• 7.1. Superconducting antennas
• 7.2. Experimental setup
• 7.3. Results
• 7.4. Analysis

• 8. Broken symmetries in thermodynamics
• 8.1. Introduction
• 8.2. Entropy changes under potential gradients
• 8.3. Entropy production
• 8.4. Entropy changes under symmetry breaking
• 8.5. Entropy reduction in dissipative systems
• 8.6. Conclusion

The book aims to unravel some of the nature's mysteries by correlating the nature of fields and the transformations in their symmetries. It begins with a brief background on the foundation of symmetry and its meaning in fields such as architecture, mathematics, and physics. A special focus of the book is on the concept of symmetries in electromagnetism and explicit symmetry breaking which generates radiation. Despite the extensive developments of the concept of broken symmetry in different domains of physics, it has yet to be applied within the context of classical electromagnetism and related engineering applications in a broader context. The main audience for the book includes industry specialists and scientists working in the field of antennas and wireless technologies. The book is also highly useful to research scientists working within electromagnetics

• Intro
• Preface
• Contents
• Editors and Contributors
• A Bandwidth-Efficient and Quick Response Traffic Congestion Control QoS Approach for VANET in 6G
• 1 Introduction
• 2 Types of Communication in VANET
• 3 Literature Survey
• 4 Traffic Congestion Control QoS (TCCQ) Approach for Better Bandwidth Utilization
• 4.1 Steps for Bandwidth Utilization and Quick Traffic Response
• 4.2 Flowchart of TCCQ
• 5 Simulation Parameters
• 6 Result Description
• 6.1 Throughput Analysis and Overhead Analysis
• 6.2 PDR Analysis and Overall Analysis
• 7 Conclusion and Future Work
• References

• A Comparative Study on Evolution of Natural Language Processing and Natural Language Understanding
• 1 Introduction
• 1.1 Natural Language Processing (NLP)
• 1.2 Natural Language Understanding (NLU)
• 1.3 Objective of the Study
• 2 System and Materials
• 2.1 Glance of Study
• 3 Analysis and Discussion
• 4 Conclusion
• References
• A Dynamic Online Shopping Website for Incorporating Different Business in a Single Platform
• 1 Introduction
• 2 Literature Survey
• 3 Proposed Work
• 4 Result and Discussion
• 5 Conclusion
• References

• A Greedy Load Balancing Strategy with Optimal Constraints for Edge Computing in Industrial Cloud Environment
• 1 Introduction
• 2 Hybrid Optimization Techniques in Cloud Load Balancing
• 3 Greedy Search Awareness Fuzzy Schedule
• 4 Results and Discussion
• 5 Conclusions
• References
• A Novel Approach for a Vision-Based Physical Distancing Monitoring System for COVID-19 Using Deep Learning Techniques
• 1 Introduction
• 2 Related Work
• 3 Proposed System
• 3.1 Algorithm
• 3.2 Proposed System Approach
• 4 Experimental Setup
• 5 Result
• 6 Conclusion and Future Work
• References

• A Review of Network Optimization on the Internet of Things
• 1 Introduction
• 1.1 Motivation
• 1.2 M2M, IoT, and IoE
• 2 Network Optimization
• 2.1 Network Optimization in IoT
• 3 Discussion on for IoT Network Optimization
• 3.1 Network Routing
• 3.2 Heterogeneity
• 3.3 Scalability
• 3.4 Quality of Service (QoS)
• 3.5 Security
• 4 Literature Survey
• 5 Conclusion
• References
• A Study on Social Engineering Attacks in Cybersecurity
• 1 Introduction
• 2 Social Engineering Attacks
• 2.1 Attacks Classification
• 3 Prevention Mechanisms
• 4 Mitigation Mechanisms
• 5 Comparison

• 6 Challenges
• 7 Conclusion
• References
• A Study on the Performance of the Faculty Members and Its Impact on Their Academic Rating during the Pandemic Wave One Period
• 1 Introduction
• 1.1 Review of Literature
• 1.2 Research Methodology
• 1.3 Findings
• 1.4 Limitations
• 1.5 Conclusion
• 1.6 Suggestions
• References
• A Survey on Various Techniques and Proposals for Improving the Cryptocurrency Protocol
• 1 Introduction
• 2 Literature Survey
• 3 Results Chart
• 4 Future Work
• 5 Conclusion
• References

This book features a collection of high-quality, peer-reviewed research papers presented at the 9th International Conference on Innovations in Computer Science & Engineering (ICICSE 2021), held at Guru Nanak Institutions, Hyderabad, India, on September 3-4, 2021. It covers the latest research in data science and analytics, cloud computing, machine learning, data mining, big data and analytics, information security and privacy, wireless and sensor networks and IoT applications, artificial intelligence, expert systems, natural language processing, image processing, computer vision, and artificial neural networks.
(source: Nielsen Book Data)

• 1. Introduction
• 2. What is knowledge anyway? Obtaining clarity on knowledge and its role in society
• 3. An anti-intellectual approach to knowledge and learning
• 4. Design as a problem for school that reveals the problem of school
• 5. The uses and abuses of science and technology
• 6. The interaction of human and non-human agency
• 7. Rethinking education for social change.
• (source: Nielsen Book Data)

- Offers a curriculum perspective on making - Connects contemporary issues of innovation and makerspaces to the needs of students - Helps demystify the role of innovation in education - Written for those wishing to carry out effective making in the classroom and beyond.
(source: Nielsen Book Data)

• Preface Author Bios
• Section I Introduction Overview of Research Research Integrity
• Section II Find Your Idea of Research How to Select Research Topics Literature Review and Formulating a Problem How to Generate Research Ideas
• Section III Bring Your Idea to the Reality How to Design Algorithms How to Do Experiments How to Write a Paper
• Section IV Your Work Out and Make Impacts Paper Submission and Publication Reference and Research Impact Resource, Advisor, and Time Management
• Section V Recap and Conclusion Critical Remarks and Chapters Recap Appendix Bibliography Index.
• (source: Nielsen Book Data)

Engineering and science research can be difficult for beginners because scientific research is fraught with constraints and disciplines. Research and Technical Writing for Science and Engineering breakdowns the entire process of conducting engineering and scientific research. This book covers those fascinating guidelines and topics on conducting research, as well as how to better interact with your advisor. Key Features: advice on conducting a literature review, conducting experiments, and writing a good paper summarizing your findings. provides a tutorial on how to increase the impact of research and how to manage research resources. By reflecting on the cases discussed in this book, readers will be able to identify specific situations or dilemmas in their own lives, as the authors provide comprehensive suggestions based on their own experiences.
(source: Nielsen Book Data)

• Preface Acknowledgement List of Figures and Tables Notes on Contributors
• PART 1: STEAM Education Perspectives 1 Introduction: Transformative STEAM Education for Sustainable Development: Beyond Traditional STEM Education Elisabeth (Lily) Taylor and Peter Charles Taylor
• 2 Ethical Dilemma Story Pedagogy: Values Learning and Ethical Understanding for a Sustainable World Elisabeth (Lily) Taylor
• 3 Why Are We Teaching Factorisation at a Time When the Planet Is Getting Hotter Every Year? Conceiving STEAM Education through an East-West Symbiosis Bal Chandra Luitel
• PART 2: STEAM Teacher Education Practices 4 Transformative Teacher Education for Sustainability: From STEM to STE(A)M Elisabeth (Lily) Taylor
• 5 STEAM Focused Problem-Based Learning: Building Trust Rachel Sheffield and Michelle de Kok
• 6 Chemistry Teacher Education for Sustainability: Ethical Dilemma STEAM Teaching Model Yuli Rahmawati and Alin Mardiah
• 7 Dancing with Mathematics: An Auto
• (source: Nielsen Book Data)

We are currently experiencing an unprecedented era in the history of the planet. Our addiction to fossil fuels and powerful technologies is dangerously altering the Earth's natural systems, giving rise to well-documented global crises of climate change, plastic pollution of the oceans, and tragic loss of biocultural diversity. These crises have created a unique challenge for STEM educators, given that STEM disciplinary knowledge and skills are often viewed as the panacea to the world's economic and environmental problems. This popular view tends to focus narrowly, however, on students learning scientific, technological, engineering and mathematical concepts about the world out there, thereby ignoring the crucial role education must play in shaping students' attitudes and values - their inner worlds - that drive moral agency to live and work in sustainable ways. It is moral agency that empowers socially and environmentally responsible citizens to tackle global crises. In this timely book you will read inspiring stories of how professional educators in STEM-related fields have embraced transformative learning and arts education to develop and implement integrated STEAM education programs and practices that are preparing young people with special capabilities and values to actively contribute to the sustainable development of a world in crisis.
(source: Nielsen Book Data)

• 1. Blind image watermarking with efficient dual restoration feature / Rishi Sinhal, Tarun Kumar Sharma, Irshad Ahmad Ansari and Varun Bajaj
• 2. Secure, robust and imperceptible image watermarking scheme based on sharp frequency localized contourlet transform / Esmaeil Najafi
• 3. Content watermarking and data hiding in multimedia security / Jay Gohil, Jay Patel and Manan Shah
• 4. Recent advances in reversible watermarking in an encrypted domain / Hanzhou Wu
• 5. An analysis of deep steganography and steganalysis / Mahdie Abazar, Peyman Masjedi, Ali Ghorbani, Mohammad Taheri and Seyed Mostafa FakhrAhmad
• 6. Recent trends in reversible data hiding techniques / V.M. Manikandan
• 7. Anatomized study of security solutions for multimedia : deep learning-enabled authentication, cryptography and information hiding / Ameya Kshirsagar and Manan Shah
• 8. New lightweight image encryption algorithm for the Internet of Things and wireless multimedia sensor networks / Amina Msolli, Abdelhamid Helali, Hassen Maaref and Ridha Mghaieth
• 9. Applying the capabilities of machine learning for multimedia security : an analysis / Suja Cherukullapurath Mana and T. Sasipraba
• 10. Assistive communication technology options for elderly care / Marjo Rissanen and Antti Rissanen
• 11. Deep learning approach for scenario-based abnormality detection / M. Suresha, S. Kuppa and D.S. Raghu Kumar
• 12. Ear recognition for multimedia security / Sagar G. Sangodkar, Niranjan Suthar, Akash Palde, Parmeshwar Birajadar and Vikram M. Gadre
• 13. Secure multimedia management : currents trends and future avenues / Vishal Rajput and Sunil Kumar Jauhar

Modern internet-enabled devices and fast communication technologies have ushered in a revolution in sharing of digital images and video. This may be for social reasons or for commercial and industrial applications. Attackers can steal this data or manipulate it for their own uses, causing financial and emotional damage to the owners. This drives the need for advanced security solutions and the need to continuously develop and maintain security measures in an ever-evolving battle against fraud and malicious intent. There are various techniques employed in protecting digital media and information, such as digital watermarking, cryptography, stenography, data encryption, and more. In addition, sharing platforms and connected nodes themselves may be open to vulnerabilities and can suffer from security breaches. This book reviews present state-of-the-art research related to the security of digital imagery and video, including developments in machine learning applications. It is particularly suited for those that bridge the academic world and industry, allowing readers to understand the security concerns in the multimedia domain by reviewing present and evolving security solutions, their limitations, and future research directions

• Foreword / Miranda Feliciano Tyson
• The age of inference / John R. McConnell, Sarah B. Dugger, and Philip C. Short
• Nature of the scientific enterprise / Harvey Henson
• The nature of science education : relativity of theory / Philip C. Short
• Mathematics : language, modeling, and comparison assisting inference / Mary Barone Martin, Tammy Jones, Dovie Kimmins, and Teresa Schmidt
• Statistics : developing impactful teaching and learning / Mary Barone Martin, Tammy Jones, and Teresa Schmidt
• Statistics : assessing success in the inference process / Mary Barone Martin, Tammy Jones, and Teresa Schmidt
• Children's literature resources to support authentic science practices and environmental decision-making : The conservation tales series / Tom J. McConnell and Barbara Giorgio-Booher
• Supporting statistical literacies in the context of a data visualization project with elementary students / Lynn Hodge, Joy Bertling, and Shande King
• Green literacy K-5 : nurturing a scientific mindset / Jen Cullerton Johnson and Mary K. Gove
• Complex multimodal text sets to support science literacy / William Romine, Amy Lannin, Torrey Palmer, Delinda van Garderen, Rachel Juergensen, Cassandra M. Smith, and William Folk
• Power up or put away? Using mobile phones for authentic student investigations / Kristin T. Rearden and Blanche O'Bannon
• Self-regulated learning theory to build scientific mindsets for diversity in STEM / Giuseppina Mattietti and Erin E. Peters-Burton
• A case for the model-based reasoning classroom / Arthur Beauchamp and Cynthia Passmore
• Cultivating a scientific mindset through inquiry-based science learning utilizing nasa resources for educators / Leslie Huling and Virginia Resta
• Bridging the disconnect between how we do and teach science : cultivating a scientific mindset in an era of data-driven education / Jana Bouwma-Gearhart
• The scientific method card game : applications for any educational context / Kallina M. Dunkle
• Toward a design-centered scientific mindset : closing the opportunity gaps via 3D design and printing in STEM teacher education / Lingguo Bu, Harvey Henson, and Euginia Nyirenda
• Developing critical literacy skills among diverse learners during the age of inference / Laveria F. Hutchison
• Content and pedagogical knowledge for teaching confidence intervals in a post p < 0.05 world / Jennifer J. Kaplan and Kristen E. Roland
• The multidimensional learning goals for making inferences with data / Ryan Seth Jones, Anna Strimaitis Grinath, and Fonya Scott
• Expectations and disciplinary blends / L. Jeneva Clark, R. Alexander Bentley, Nicholas N. Nagle, and Vasileios Maroulas
• Machine learning : a new lens for integrating computational thinking and science in the high school classroom / Michael Daley, Zhen Bai, Raffaella Borasi, and Dave Miller
• Becoming a postmodern STEM teacher leader in the age of inference / Rebekah Hammack
• Seeking homeostasis in a heteroscedastic world : a sense of the stakes in the age of inference / Philip C. Short, Donna F. Short, and John R. McConnell.

In an age where we are inundated with information, the ability to discern verifiable information to make proper decisions and solve problems is ever more critical. Modern science, which espouses a systematic approach to making "inferences, " requires a certain mindset that allows for a degree of comfort with uncertainty. This book offers inspirations and ideas for cultivating the proper mindset for the studying, teaching, and practicing of science that will be useful for those new to as well as familiar with the field. Although a paradigm shift from traditional instruction is suggested in the National Framework for K-12 science, this volume is intended to help educators develop a personal mental framework in which to transition from a teacher-centered, didactical approach to a studentcentered, evidence-guided curriculum. While the topics of the book derive from currently published literature on STEM education as they relate to the National Framework for K-12 Science and the Three-Dimensional science instruction embedded in the Next Generation Science Standards, this book also examines these topics in the context of a new societal age posited as the "Age of Inference" and addresses how to make sense of the ever-increasing deluge of information that we are experiencing by having a scientific and properly discerning mindset.
(source: Nielsen Book Data)

• Foreword by Deborah Santiago
• Introduction: An Asset-Based Approach to Advancing Latina Students in STEM: Increasing Resilience, Participation, and Success
• Elsa M. Gonzalez and Miranda Wilson
• PART 1: Examining Literature, Theory, and Data to Inform Policy
• Chapter 1: Latinas in STEM: A Review of the Literature Using a Psychosociocultural Lens
• Kristan M. Venegas and Araceli Espinoza-Wade
• Chapter 2: Developing A Conceptual Framework for Computing Identity Development for Latina Undergraduate Students
• Sarah L. Rodriguez, Charles Lu, and Daisy Ramirez
• Chapter 3: The Pathway to the PhD: Latinas as STEM Doctorates from 1975-2010
• Frank Fernandez, Hyun Kyoung Ro, Miranda Wilson, and Veronica Crawford
• Chapter 4: "Cuida Tu Casa y Deja la Ajena": Focusing on Retention as a Self-Perpetuating Engine for Recruiting Latina Faculty in STEM
• Aurora Kamimura
• Chapter 5: How Many Latinas in STEM Benefit from High-Impact Practices? Examining Participation by Social Class and Immigrant Status
• Sanga Kim, Selyna Perez Beverly, and Hyun Kyoung Ro
• PART 2: Reading (Hearing) Testimonios of Latinas in STEM
• Chapter 6: Empowering Latina STEM Majors at a Public R1 Doctoral University and Hispanic-Serving Institution in Texas: Strategies for Success
• Elsa M. Gonzalez, Mauricio Molina, and Sarah Churchill Turner
• Chapter 7: First-Generation Latina Engineering Students' Aspirational Counterstories
• Tamara T. Coronella
• Chapter 8: Latinas Undergraduates in Engineering/Computer Science on the US-Mexico Border: Identity, Social Capital, and Persistence
• Erika Mein, Helena Mucino Guerra, and Lidia Herrera-Rocha
• Chapter 9: "I Learned How to Divide at 25": A Counter-Narrative of How one Latina's Agency and Resilience Lead Her Towards an Engineering Pathway
• Dina Verdin
• Chapter 10: Leadership through the Lenses of Latinas: Undergraduate College Students in STEM-Related Disciplines at Regional HSIs
• Hilda Cecilia Contreras Aguirre, Rosa Banda, and Elsa M. Gonzalez
• Chapter 11: "There Was Something Missing": How Latinas Construct Compartmentalized Identities in STEM
• Ariana L. Garcia, Blanca Rincon, and Juanita K. Hinojosa
• Afterword: Six Steps Forward for Studying Diversity, Equity, and Inclusion in STEM
• Frank Fernandez
• .
• (source: Nielsen Book Data)

This timely volume challenges the ongoing underrepresentation of Latina women in science, technology, engineering and mathematics (STEM), and highlights resilience as a critical communal response to increasing their representation in degree programs and academic posts. An Asset-Based Approach to Advancing Latina Students in STEM documents the racialized and gendered experiences of Latinas studying and researching in STEM in US colleges, and centers resilience as a critical mechanism in combating deficit narratives. Adopting an asset-based approach, chapters illustrate how Latinas draw on their cultural background as a source of individual and communal strength, and indicate how this cultural wealth must be nurtured and used to inform leadership and policy to motivate, encourage, and support Latinas on the pathway to graduate degrees and successful STEM careers. By highlighting strategies to increase personal resilience and institutional retention of Latina women, the text offers key insights to bolstering diversity in STEM. This text will primarily appeal to academics, scholars, educators, and researchers in the fields of STEM education. It will also benefit those working in broader areas of higher education and multicultural education, as well as those interested in the advancement of minorities inside and outside of academia. Elsa M. Gonzalez is Assistant Professor of Higher Education at the University of Houston, USA. Frank Fernandez is Assistant Professor of Higher Education at the University of Mississippi, USA. Miranda Wilson earned a Ph.D. in Higher Education Leadership and Policy Studies at the University of Houston, USA.
(source: Nielsen Book Data)

• Why better, more equitable science education should be a national priority
• A vision for better, more equitable science education
• How far are we from this vision for all students?
• How do we get there?
• Recommendations
• How can we learn from these efforts?
• In conclusion
• References
• For further reading
• Committee member biosketches
• Acknowledgments

Scientific thinking and understanding are essential for all people navigating the world, not just for scientists and other science, technology, engineering and mathematics (STEM) professionals. Knowledge of science and the practice of scientific thinking are essential components of a fully functioning democracy. Science is also crucial for the future STEM workforce and the pursuit of living wage jobs. Yet, science education is not the national priority it needs to be, and states and local communities are not yet delivering high quality, rigorous learning experiences in equal measure to all students from elementary school through higher education. Call to Action for Science Education: Building Opportunity for the Future articulates a vision for high quality science education, describes the gaps in opportunity that currently exist for many students, and outlines key priorities that need to be addressed in order to advance better, more equitable science education across grades K-16. This report makes recommendations for state and federal policy makers on ways to support equitable, productive pathways for all students to thrive and have opportunities to pursue careers that build on scientific skills and concepts. Call to Action for Science Education challenges the policy-making community at state and federal levels to acknowledge the importance of science, make science education a core national priority, and empower and give local communities the resources they must have to deliver a better, more equitable science education. Table of Contents Front Matter Summary Introduction Why Better, More Equitable Science Education Should Be a National Priority A Vision for Better, More Equitable Science Education How Far Are We from This Vision for All Students? How Do We Get There? Recommendations How Can We Learn from These Efforts? In Conclusion References For Further Reading Committee Member Biosketches Acknowledgments.
(source: Nielsen Book Data)

• Introduction.- Application in the frontier research of science and technology.- Progress of e-Science in major projects.- Achievements of informatization in interdisciplinary.
• (source: Nielsen Book Data)

"China's e-Science Blue Book 2020" has been jointly compiled by the Chinese Academy of Sciences, Cyberspace Administration of China, Ministry of Education of the PRC, Ministry of Science and Technology of the PRC, China Association for Science and Technology, Chinese Academy of Social Sciences, National Natural Science Foundation of China and the Chinese Academy of Agricultural Sciences. It was focusing on the new situation, new progress and new achievements of China's e-Scientific in the past two years. During the "13th Five-Year Plan" period, Chinese scholars make full use of advanced information technology to carry out scientific research work, and have achieved a series of major scientific and technological achievements. This book has collected 28 research reports about China's e-Science application in the past two years to introduce the application in the frontier research of science and technology, the progress of e-Science in major projects and the achievements of informatization in interdisciplinary. As such it provides a valuable reference resource for researchers and students in this area and promotes further e-Science research.
(source: Nielsen Book Data)

• List of Figures List of Tables Preface Glossary of Terms Continuous Random Variables Rectangular Distribution Exponential Distribution Beta Distribution Arcsine Distribution Gamma Distribution Cosine Distribution Normal Distribution Cauchy Distribution Bibliography Authors' Biographies Index.
• (source: Nielsen Book Data)

This is an introductory book on continuous statistical distributions and its applications. It is primarily written for graduate students in engineering, undergraduate students in statistics, econometrics, and researchers in various fields. The purpose is to give a self-contained introduction to most commonly used classical continuous distributions in two parts. Important applications of each distribution in various applied fields are explored at the end of each chapter. A brief overview of the chapters is as follows. Chapter 1 discusses important concepts on continuous distributions like location-and-scale distributions, truncated, size-biased, and transmuted distributions. A theorem on finding the mean deviation of continuous distributions, and its applications are also discussed. Chapter 2 is on continuous uniform distribution, which is used in generating random numbers from other distributions. Exponential distribution is discussed in Chapter 3, and its applications briefly mentioned. Chapter 4 discusses both Beta-I and Beta-II distributions and their generalizations, as well as applications in geotechnical engineering, PERT, control charts, etc. The arcsine distribution and its variants are discussed in Chapter 5, along with arcsine transforms and Brownian motion. This is followed by gamma distribution and its applications in civil engineering, metallurgy, and reliability. Chapter 7 is on cosine distribution and its applications in signal processing, antenna design, and robotics path planning. Chapter 8 discusses the normal distribution and its variants like lognormal, and skew-normal distributions. The last chapter of Part I is on Cauchy distribution, its variants and applications in thermodynamics, interferometer design, and carbon-nanotube strain sensing. A new volume (Part II) covers inverse Gaussian, Laplace, Pareto, 𝜒 2, T, F, Weibull, Rayleigh, Maxwell, and Gumbel distributions.
(source: Nielsen Book Data)

• List of Figures List of Tables Preface Glossary of Terms Continuous Random Variables Rectangular Distribution Exponential Distribution Beta Distribution Arcsine Distribution Gamma Distribution Cosine Distribution Normal Distribution Cauchy Distribution Bibliography Authors' Biographies Index.
• (source: Nielsen Book Data)

This is an introductory book on continuous statistical distributions and its applications. It is primarily written for graduate students in engineering, undergraduate students in statistics, econometrics, and researchers in various fields. The purpose is to give a self-contained introduction to most commonly used classical continuous distributions in two parts. Important applications of each distribution in various applied fields are explored at the end of each chapter. A brief overview of the chapters is as follows. Chapter 1 discusses important concepts on continuous distributions like location-and-scale distributions, truncated, size-biased, and transmuted distributions. A theorem on finding the mean deviation of continuous distributions, and its applications are also discussed. Chapter 2 is on continuous uniform distribution, which is used in generating random numbers from other distributions. Exponential distribution is discussed in Chapter 3, and its applications briefly mentioned. Chapter 4 discusses both Beta-I and Beta-II distributions and their generalizations, as well as applications in geotechnical engineering, PERT, control charts, etc. The arcsine distribution and its variants are discussed in Chapter 5, along with arcsine transforms and Brownian motion. This is followed by gamma distribution and its applications in civil engineering, metallurgy, and reliability. Chapter 7 is on cosine distribution and its applications in signal processing, antenna design, and robotics path planning. Chapter 8 discusses the normal distribution and its variants like lognormal, and skew-normal distributions. The last chapter of Part I is on Cauchy distribution, its variants and applications in thermodynamics, interferometer design, and carbon-nanotube strain sensing. A new volume (Part II) covers inverse Gaussian, Laplace, Pareto, 𝜒 2, T, F, Weibull, Rayleigh, Maxwell, and Gumbel distributions.
(source: Nielsen Book Data)

• List of Figures List of Tables Preface Glossary of Terms Inverse Gaussian Distribution Birnbaum--Saunders Distribution Pareto Distribution Laplace Distribution Central Chi-squared Distribution Student's &#x1d683
• Distribution &#x1d675
• Distribution Weibull Distribution Rayleigh Distribution Maxwell Distribution Gumbel Distribution Bibliography Authors' Biographies Index.
• (source: Nielsen Book Data)

This is the second part of our book on continuous statistical distributions. It covers inverse-Gaussian, Birnbaum-Saunders, Pareto, Laplace, central X2, T, F, Weibull, Rayleigh, Maxwell, and extreme value distributions. Important properties of these distribution are documented, and most common practical applications are discussed. This book can be used as a reference material for graduate courses in engineering statistics, mathematical statistics, and econometrics. Professionals and practitioners working in various fields will also find some of the chapters to be useful. Although an extensive literature exists on each of these distributions, we were forced to limit the size of each chapter and the number of references given at the end due to the publishing plan of this book that limits its size. Nevertheless, we gratefully acknowledge the contribution of all those authors whose names have been left out. Some knowledge in introductory algebra and college calculus is assumed throughout the book. Integration is extensively used in several chapters, and many results discussed in Part I (Chapters 1 to 9) of our book are used in this volume. Chapter 10 is on Inverse Gaussian distribution and its extensions. The Birnbaum-Saunders distribution and its extensions along with applications in actuarial sciences is discussed in Chapter 11. Chapter 12 discusses Pareto distribution and its extensions. The Laplace distribution and its applications in navigational errors is discussed in the next chapter. This is followed by central chi-squared distribution and its applications in statistical inference, bioinformatics and genomics. Chapter 15 discusses Student's T distribution, its extensions and applications in statistical inference. The F distribution and its applications in statistical inference appears next. Chapter 17 is on Weibull distribution and its applications in geology and reliability engineering. Next two chapters are on Rayleigh and Maxwell distributions and its applications in communications, wind energy modeling, kinetic gas theory, nuclear and thermal engineering, and physical chemistry. The last chapter is on Gumbel distribution, its applications in the law of rare exceedances.
(source: Nielsen Book Data)

Maybe you have a good grasp of disciplinary core ideas and science and engineering practices-critical parts of the Next Generation Science Standards-but you are looking for more resources about integrating crosscutting concepts (CCCs). Or maybe you understand CCCs but want to know more about how to make them part of your students' toolkit for exploring science phenomena or engineering problems, both now and in the future. Regardless of your needs, Crosscutting Concepts is your guide. It shows how to design and implement three-dimensional instruction for all students by understanding the potential of CCCs to strengthen science and engineering teaching and learning. Crosscutting Concepts helps you do the following: Grasp the foundational issues that undergird crosscutting concepts. You'll find out how CCCs can change your instruction, engage your students, and broaden access and inclusion of all students into your science classroom. Gain in-depth insights into individual crosscutting concepts. You'll learn how to use each CCC across disciplines, understand the challenges students face in learning CCCs, and adopt exemplary teaching strategies. Discover how CCCs can strengthen the way you teach key topics in science. These topics include the nature of matter, plant growth, and weather and climate, as well as engineering design. Understand related implications for science teaching. These topics include student assessment and teacher professional collaboration. Throughout Crosscutting Concepts, vignettes drawn from the authors' own classroom experiences will help you put theory into practice. Instructional Applications show how CCCs can strengthen your planning. Classroom Snapshots feature practical ways to use CCCs in discussions and lessons. Useful for teachers at all grade levels, this book will enrich your own understanding while showing you how to use CCCs for both classroom teaching and real-world problem solving.
(source: Nielsen Book Data)

• Automatic Standardization of Data based on Machine Learning and Natural Language Processing.- Scoring Algorithm Identifying Anomalous Behavior in Enterprise Network.-APPLICATION OF BAYESIAN AUTOMATED HYPERPARAMETER TUNING ON CLASSIFIERS PREDICTING CUSTOMER RETENTION IN BANKING INDUSTRY.- Quantum Machine Learning: A Review and Current Status.- Survey of Transfer Learning and a Case Study of Emotion Recognition using Inductive Approach.- An Efficient Algorithm for Complete Linkage Clustering with a Merging Threshold.
• (source: Nielsen Book Data)

This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. Gathering peer-reviewed research papers presented at the Fourth International Conference on Data Management, Analytics and Innovation (ICDMAI 2020), held on 17-19 January 2020 at the United Services Institute (USI), New Delhi, India, it addresses cutting-edge topics and discusses challenges and solutions for future development. Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry. .
(source: Nielsen Book Data)

• Structural Relationship Between Environmental Uncertainty, Dynamic Capacity and Business Performance in Smart Supply Chain Environment.- Analysis of the Relative Importance of Coaching Service Quality.- Determinants of Technology-Based Self-Service Acceptance.- Study on Security and Privacy of E-Government Services.- Applying Hofstede's Culture Theory in the Comparison between Vietnam and Korean E-government Adoption.- 3D Printing Signboard Production using 3D Modeling Design.- Design of Artificial Intelligence for Smart Risk Pre-Review System at the KC EMC.- Regularized Categorical Embedding for Effective Demand Forecasting of Bike Sharing System.- Research on Implementation of User Authentication Based on Gesture Recognition of Human.
• (source: Nielsen Book Data)

This edited book presents scientific results of the International Semi-Virtual Workshop on Data Science and Digital Transformation in the Fourth Industrial Revolution (DSDT 2020) which was held on October 15, 2020, at Soongsil University, Seoul, Korea. The aim of this workshop was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The workshop organizers selected the best papers from those papers accepted for presentation at the workshop. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 17 of the conference's most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science. .
(source: Nielsen Book Data)

A peer-reviewed, multi-disciplinary, open access journal affiliated with the E Scholarly Community Encyclopedia (www.encyclopedia.pub) intended to highlight research articles and reviews originally posted on the parent platform

• Section 1. Chapter 1. A voice from the field: one teacher's perspective on educator-scientist-student partnerships ; Chapter 2. Meet them where they are (a perspective that works both ways): reflections on scientist-educator collaborations
• Section 2. Chapter 3. The role of the knowledgeable other in student-scientist-teacher partnerships: examining triads in second grade classrooms ; Chapter 4. "The way i think about scientists has changed": measuring the impact of virtual scientists on middle school students' perceptions of scientists ; Chapter 5. Enriching the lives of high school teenagers with science caf©♭s ; Chapter 6. Learning about the authentic nature of scientific work from professional scientists: preparation for research participation and mentoring
• Section 3. Chapter 7. An interdisciplinary model to diversify STEM participation: college, high school, and industry partnerships ; Chapter 8. University students: schoolteacher partnership with newly developed technologies ; Chapter 9. Connecting pre-service teachers to astronauts and the international space station through an educational downlink: an out-of-this-world experience
• Section 4. Chapter 10. Training students to conduct outreach in an informal science learning environment ; Chapter 11. Real-world connections with conservation science through zoos and aquariums ; Chapter 12. The potential for science centers in student-teacher-scientist partnerships: explorations from one museum

"This book will serve as a resource for those in STEM education, both in formal settings and informal settings and bring together all different kinds of student- scientist- teacher partnerships programs with research documentation in one source"-- Provided by publisher

• Data Science.- ICTs Applications.- Industry 4.0.- Technology and Environment.- Biomedical Sensors and Wearables Systems.
• (source: Nielsen Book Data)

This book constitutes refereed proceedings of the 9th Conference on Information and Communication Technologies of Ecuador, TICEC 2021, held at the Universidad Politecnica Salesiana (UPS) campus in November 2021. The conference was organized in hybrid mode. The 24 full papers were carefully reviewed and selected from 126 qualified submissions. The papers cover a great variety of topics, such as data mining, neural networks, cyberphysical systems, telemedicine, traffic simulation, geospatial information, human-machine interaction, cloud computing, and others. The contributions are divided into the following thematic blocks: Data Science, ICTs Applications, Industry 4.0, Technology and Environment, Biomedical Sensors and Wearables Systems. .
(source: Nielsen Book Data)

• Part I. Blockchain and Cryptocurrency
• Part II. Computer Law and Security
• Part III. Digital Accounting and Auditing
• Part IV. Digital Business and Finance
• Part V. Digital Education
• Part VI. Digital Engineering
• Part VII. Machine learning
• Part VIII. Smart Cities in Digital Age
• Part IX. Health Policy and Management
• Part X. Information management.

This book presents the proceedings of the 2020 International Conference on Integrated Science in Digital Age, which was jointly supported by the Institute of Certified Specialists (Russia) and Springer, and was held on May 1-3, 2020. The conference provided an international forum for researchers and practitioners to present and discuss the latest innovations, trends, results, experiences and concerns in the various areas of integrated science in the digital age. The main goal of the conference was to efficiently disseminate original findings in the natural and social sciences, covering topics such as blockchain & cryptocurrency; computer law & security; digital accounting & auditing; digital business & finance; digital economics; digital education; digital engineering; machine learning; smart cities in the digital age; health policy & management; and information management.
(source: Nielsen Book Data)

• 1. Introduction
• 2. Setting the Stage: Why Is Convergence Important?
• 3. Overview of National Center for Science and Engineering Statistics Data Collections, Data Products, and Its Previous Work in This Area
• 4. Conceptualizing Convergence
• 5. Convergence as Practiced
• 6. Outcomes and Impacts of Convergence
• 7. Measurement Efforts
• 8. Feasibility and Implementation
• 9. Summary of Key Themes and Thoughts to Move the Work Forward
• Appendix A: Workshop Agenda
• Appendix B: Biographical Sketches of the Steering Committee Members and Workshop Speakers
• Committee on National Statistics.

This Proceedings of a Workshop summarizes the presentations and discussions at the Workshop on the Implications of Convergence for How the National Center for Science and Engineering Statistics (NCSES) Measures the Science and Engineering Workforce, which was held virtually and livestreamed on October 22-23, 2020. The workshop was convened by the Committee on National Statistics to help NCSES, a division of the National Science Foundation, set an agenda to inform its methodological research and better measure and assess the implications of convergence for the science and engineering workforce and enterprise. The workshop brought together scientists and researchers from multiple disciplines, along with experts in science policy, university administration, and other stakeholders to review and provide input on defining and measuring convergence and its impact on science and scientists.
(source: Nielsen Book Data)

• Global Optimization Approach for the Ascent Problem of Multi-stage Launchers
• A Robust Predictive Control Formulation for Heliogyro Blade Stability
• Piecewise Polynomial Taylor Expansions-The Generalization of Faà di Bruno's Formula
• Grid-Enhanced Polylithic Modeling and Solution Approaches for Hard Optimization Problems
• Model Predictive Q-Learning (MPQ-L) for Bilinear Systems
• SCOUT: Scheduling Core Utilization to Optimize the Performance of Scientific Computing Applications on CPU/Coprocessor-Based Cluster
• Chainer-XP: A Flexible Framework for ANNs Run on the Intel® Xeon PhiTM Coprocessor
• Inverse Problems in Designing New Structural Materials
• Coupled Electromagnetic Field and Electric Circuit Simulation: A Waveform Relaxation Benchmark
• SCIP-Jack: An Exact High Performance Solver for Steiner Tree Problems in Graphs and Related Problems
• Physical Parameter Identification with Sensors or Actuators Spanning Multiple DOF's
• Monotonization of a Family of Implicit Schemes for the Burgers Equation
• The Insensitivity of the Iterative Learning Control Inverse Problem to Initial Run When Stabilized by a New Stable Inverse
• Strategy Optimization in Sports via Markov Decision Problems
• An Application of RASPEN to Discontinuous Galerkin Discretisation for Richards' Equation in Porous Media Flow
• On the Development of Batch Stable Inverse Indirect Adaptive Control of Systems with Unstable Discrete-Time Inverse
• An Improved Conjugate Gradients Method for Quasi-linear Bayesian Inverse Problems, Tested on an Example from Hydrogeology
• Idiosyncrasies of the Frequency Response of Discrete-Time Equivalents of Continuous-Time System.

This proceedings volume highlights a selection of papers presented at the 7th International Conference on High Performance Scientific Computing, which took place in Hanoi, Vietnam, during March 19-23, 2018. The conference has been organized by the Institute of Mathematics of the Vietnam Academy of Science and Technology, the Interdisciplinary Center for Scientific Computing (IWR) of Heidelberg University and the Vietnam Institute for Advanced Study in Mathematics. The contributions cover a broad, interdisciplinary spectrum of scientific computing and showcase recent advances in theory, methods, and practical applications. Subjects covered include numerical simulation, methods for optimization and control, machine learning, parallel computing and software development, as well as the applications of scientific computing in mechanical engineering, airspace engineering, environmental physics, decision making, hydrogeology, material science and electric circuits.
(source: Nielsen Book Data)

• Existence Results for Impulsive Partial Functional Fractional Differential Equation with State Dependent Delay.- A Novel Method for Solving Nonlinear Jerk Equations.- Solving a New Type of Fractional Differential Equation by Reproducing Kernel Method.- An Efficient Approach for the Model of Thrombin Receptor Activation Mechanism with Mittag-Leffler Function.- Stability Analysis of Bifurcated Limit Cycles in a Labor Force Evolution Model.- Existence and Uniqueness Results of Fractional Differential Equations with Fuzzy Data.- Approximate Efficient Solutions of Nonsmooth Vector Optimization Problems Via Approximate Vector Variational Inequalities.- Existence of Entropy Solutions for Anisotropic Elliptic Nonlinear Problem in Weighted Sobolev Spaces.- Well-posedness and Stability for the Viscous Primitive Equations of Geophysics in Critical Fourier-Besov-Morrey Spaces.- Regional controllability of a Class of Time-Fractional Systems.- Quadratic Optimal Control for Bilinear Systems.- Regional Observability of Linear Fractional Systems Involving Riemann-Liouville Fractional Derivative.- Stability Analysis of Fractional Differential Systems Involving Riemann-Liouville derivative.- Deformed Joint Free Distributions of Semicircular Elements Induced by Multi Orthogonal Projections.
• (source: Nielsen Book Data)

This book is a collection of original research papers as proceedings of the 6th International Congress of the Moroccan Society of Applied Mathematics organized by Sultan Moulay Slimane University, Morocco, during 7th-9th November 2019. It focuses on new problems, applications and computational methods in the field of nonlinear analysis. It includes various topics including fractional differential systems of various types, time-fractional systems, nonlinear Jerk equations, reproducing kernel Hilbert space method, thrombin receptor activation mechanism model, labour force evolution model, nonsmooth vector optimization problems, anisotropic elliptic nonlinear problem, viscous primitive equations of geophysics, quadratic optimal control problem, multi-orthogonal projections and generalized continued fractions. The conference aimed at fostering cooperation among students, researchers and experts from diverse areas of applied mathematics and related sciences through fruitful deliberations on new research findings. This book is expected to be resourceful for researchers, educators and graduate students interested in applied mathematics and interactions of mathematics with other branches of science and engineering. .
(source: Nielsen Book Data)

• Introduction: OST Programs as STEM Support for Females, Lynda R.Wiest, Heather Glynn Crawford-Ferre, and Jafeth E. Sanchez. FEMMES STEM Program for Girls, Kathy Ziyue Dai, Nina Kuprasertkul, and Deborah Liu. Expanding Your Horizons: An Out-of-School-Time STEM Conference for Girls, Judith Iriarte-Gross, Myra Norman, and Monika Whitfield. STEM for Girls: A One-Day Event to Improve Girls' Attitudes Toward STEM, Julia S. Ribeiro, Michelle E. Kossack, and Tina Jeoh. Girls in Engineering, Math, and Science (GEMS): A Successful Program for Middle School Girls and College Women in Southwest Florida, Zanna Beharry, Katie Johnson, and Laura Frost. Science Technology Engineering Preview Summer (STEPS) at the University of St. Thomas, Deborah Besser and AnnMarie Thomas. The Girls in STEM Program, Sean Hill and Jafeth E. Sanchez. Tech Savvy: The Difference a Day Makes to Facilitate STEM Interest in Girls and the Adults in Their Lives, Tamara E. Brown. Exploring the Impact of Out-of-School STEM Experiences for Girls, Jacqueline D. Spears, Chardie L. Baird, and Beth A. Montelone. Conclusion: Short-Term OST STEM Programs for Females, Lynda R. Wiest, Heather Glynn Crawford-Ferre, and Jafeth E. Sanchez. About the Editors. About the Contributors.
• (source: Nielsen Book Data)

Vol. II: Short-Term Programs features eight OST STEM programs for females from across the United States that run oneto three days in length, in most cases, a single day. In this book, the chapter authors describe their programs, the effectiveness of those programs, and practical implications of their program evaluation data. This book series is the first of its kind to offer researchers, educators, school administrators, policy makers, and others detailed insight intothe promise and practice of out-of-school-time STEM programs for females. Science, technology, engineering, and mathematics (STEM) disciplines play a pivotal role in societal progress and economic prosperity, in addition to enhancing individual lives. However, U.S. students lack strong STEM performance in an international context. The pool of STEM-proficient workers is thus insufficient to fuel the nation, with females being one group that is noticeably absent. Out-of-school-time (OST) programs, which are on the rise, are increasingly suggested as a way to support andencourage underrepresented groups in STEM. Participants in OST programs have shown improved achievement, interest, and confidence in STEM, as well as greater awareness of STEM role models and careers.
(source: Nielsen Book Data)

When covid-19 struck, we know that people stopped commuting to work and traveling. But what insights about these changes can we get from publicly available data? In this coding session, Reuven Lerner (author of "Pandas Workout") will explore data from New York taxis before and during the pandemic.

• Introductory Concepts of Metaheuristic Computation
• A Metaheuristic Scheme Based on the Hunting Model of Yellow Saddle Goatfish
• Metaheuristic Algorithm Based on Hybridization of Invasive Weed Optimization asnd Estimation Distribution Methods
• Corner Detection Algorithm Based on Cellular Neural Networks (CNN) and Differential Evolution (DE)
• Clustering Model Based on the Human Visual System
• Metaheuristic Algorithms for Wireless Sensor Networks
• Metaheuristic Algorithms Applied to the Inventory Problem.

This book includes two objectives. The first goal is to present advances and developments which have proved to be effective in their application to several complex problems. The second objective is to present the performance comparison of various metaheuristic techniques when they face complex optimization problems. The material has been compiled from a teaching perspective. Most of the problems in science, engineering, economics, and other areas can be translated as an optimization or a search problem. According to their characteristics, some problems can be simple that can be solved by traditional optimization methods based on mathematical analysis. However, most of the problems of practical importance in engineering represent complex scenarios so that they are very hard to be solved by using traditional approaches. Under such circumstances, metaheuristic has emerged as the best alternative to solve this kind of complex formulations. This book is primarily intended for undergraduate and postgraduate students. Engineers and application developers can also benefit from the book contents since it has been structured so that each chapter can be read independently from the others, and therefore, only potential interesting information can be quickly available for solving an industrial problem at hand. .
(source: Nielsen Book Data)

• Preface
• 1. STEM and Literature: Exploring New Options - Gloria D. Campbell-Whatley and Diane Rodriguez From Mainstreaming to Inclusion: The Journey Begins The Birth of Multi-Tiered Support Systems (MTSS) Students with Disabilities in the Urban Environment The Benefits of STEM and Literature Summary and Other Tidbits
• 2. Culturally Responsive Problem Based Learning (CRPBL) - Gloria D. Campbell-Whatley and Richard Reynolds PBLs Best Practices: Finding Solutions Innovations in Instruction for Problem Based Learning in STEM Culturally Responsive Teaching Culturally Responsive PBL (CRPBL) Summary: Recommendations for Teachers
• 3. Selection of Reading Materials, Technology, and STEM Activities - Diane Rodriguez, Jugnu Agrawal, Justin Coles, and Gary Hoag Using Literature to Teach STEM in the Interdisciplinary Classroom: Selecting a Book Using High Leverage Practices and Strategies for Students with Disabilities Supporting Learning in Virtual Environment/Distance Learning Summary
• 4. Science and Literature - Gloria Campbell-Whatley, Kim Reddig, and Deondra Gladney Science and Literature for Adolescents Careers Teachers Application Tips Summary of Lessons Lesson 4
• .1: Science Vocabulary, The Twilight Saga Lesson 4
• .2: Science on Cells, The Immortal Life of Henrietta Lacks Lesson 4
• .3: Science and Clean Water, The Boy Who Harnessed the Wind Lesson 4
• .4: Medicine and Drugs, Percy Jackson and the Lightning Thief Lesson 4
• .5: Gravity, Weight, and Mass, Ender's Game Lesson 4
• .6: Respiratory System, After Earth Lesson 4
• .7: Genetics, Gattaca Lesson 4
• .8: Energy, The Matrix Lesson 4
• .9: Desert Plants and Animals, Holes Lesson 4
• .10: Assistive Technology, Star Wars
• 5. Mathematics and Literature - Jugnu Agrawal, Gary Hoag, Ozalle Toms, Ann Jolly, Elizabeth Reyes, and Ashley Voggt Mathematics and Adolescents Teacher Application Tips Careers Lesson Plans Lesson 5
• .1: Statistics and Probability, To Kill a Mockingbird Lesson 5
• .2: Basic Algebra and Statistics, The Hunger Games Lesson 5
• .3: Business Plan, Born a Crime Lesson 5
• .4: Geometry and Calculus, Hidden Figures Lesson 5
• .5: Mysticism of the Pyramids, The Giver Lesson 5
• .6: Weather Mathematics, The Chronicles of Narnia Lesson 5
• .7: Geometry, Flatland
• 6. Engineering and Literature - Diane Rodriguez, Gloria Campbell-Whatley, Kevin Otero , Hassan Payano, Maria Payano, Eileen Interiano, and Sharon Hunter Engineering for Adolescents Careers Tips for Teachers Summary of Lessons Lesson 6
• .1: Engineering Robotics, The Maze Runner Lesson 6
• .2: Engineering Construction and Building, Harry Potter Lesson 6
• .3: Drone Engineering, Men in Black Lesson 6
• .4: Engineering Trains, The Snowpiercer Lesson 6
• .5: Satellite Engineering, Star Trek Lesson 6
• .6: Engineering Cyborgs, The Terminator Lesson 6
• .7: Software Engineering, Jumanji Lesson 6
• .8: Aerospace Engineering, Minority Report Lesson 6
• .9: Engineering and Space Travel, The Martian Lesson 6
• .10: Biofuels, Back to the Future
• 7. Technology and Literature - Jugnu Agrawal and Wen-Hsuan Chang Technology Related Careers Teacher Application Tips Summary of the Unit Lesson 7
• .1: Identifying Credible Sources, Hidden Figures Lesson 7
• .2: The Use of Citation sand Presentations, Hidden Figures Lesson 7
• .3: Making use of Digital Media, Hidden Figures Lesson 7
• .4: Using Technology to Update Writing Products, Hidden Figures Lesson 7
• .5: Digital Citizenship and Technology Integration, Hidden Figures Lesson 7
• .6: Webcams and Identifying Central Themes, Hidden Figures Lesson 7
• .7: Digital Footprint, Hidden Figures Lesson 7
• .8: Assistive Technology Innovations, Hidden Figures Lesson 7
• .9: Digital Story Telling, Hidden Figures Lesson 7
• .10: 3D Print, Hidden Figures Index About the Authors.
• (source: Nielsen Book Data)

This innovative STEAM guide will help general and special education teachers to increase effective instruction with adolescents (grades 5-10). The authors show teachers how to link STEM concepts with popular fiction and film selections as a catalyst to launch student interactions, discussions, projects, and investigations. This approach will promote problem solving and reasoning skills by initiating the scientific process, rather than simply presenting established facts. The book includes a wealth of lesson plans that connect abstract STEM ideas to realistic experiences that students encounter. Sample lessons call on students to produce drawings and models that move STEM to STEAM. Grounded in popular film and the 31 books most read by adolescent students, the text includes teaching strategies found to be effective with traditionally underserved students and those with disabilities.Book Features: Standards-based STEM lessons are interrelated and interwoven with writing, reading, speaking, and other skills. Practical ideas and hands-on activities for engaging adolescents in both traditional and virtual environments. Guidance for working with diverse populations, such as students with different abilities, culturally and linguistic diverse students, translingual students, and transnational students. Includes full lessons, templates, and handouts.
(source: Nielsen Book Data)

• Addressing False Information and Abusive Language in Digital Space Using Intelligent Approaches.- Application and Perspectives of Convolutional Neural Networks in Digital Intelligence.- Obstacle Awareness Subsystem for Higher Exoskeleton Safety.- Knowledge-Based Approaches to Intelligent Data Analysis.- Intelligent Analysis of Data Streams.- Large Astronomical Time Series Pre-processing for Classification using Artificial Neural Networks.- Requirements for Information Modelling in Manufacturing.- Attribute exploration in formal concept analysis and measuring of pupils' computational thinking.- Flower Master Index for relational database selection and joining.
• (source: Nielsen Book Data)

This book aims to provide readers with up-to-date knowledge on how to make these technologies smarter. Humanity is now going through difficult times to fight the Covid-19 pandemic. Simultaneously, in these difficult times of physical separation, we can also realize how much digital society technology helps us cope with many difficulties that bring us this time. The authors focus on selected research challenges for intelligent digital society and state-of-the-art methods of how to face them. The book's subtitle suggests that a core concept that the reader can study from various points of view in particular book chapters is the knowledge. The knowledge that can help us intelligently face different digital society challenges (Part I of this book); the knowledge extracted from available big data employing intelligent analysis techniques (Part II). For efficient processing and analysis of data, there is a strong need for smart data and information modeling techniques (Part III).
(source: Nielsen Book Data)

This book constitutes the proceedings of the First International Conference on Emerging Trends in Engineering (ICETE), held at University College of Engineering and organised by the Alumni Association, University College of Engineering, Osmania University, in Hyderabad, India on 22-23 March 2019. The proceedings of the ICETE are published in three volumes, covering seven areas: Biomedical, Civil, Computer Science, Electrical & Electronics, Electronics & Communication, Mechanical, and Mining Engineering. The 215 peer-reviewed papers from around the globe present the latest state-of-the-art research, and are useful to postgraduate students, researchers, academics and industry engineers working in the respective fields. Volume 2 presents papers on the theme "Advances in Decision Sciences, Image Processing, Security and Computer Vision - International Conference on Emerging Trends in Engineering (ICETE)". It includes state-of-the-art technical contributions in the areas of electronics and communication engineering and electrical and electronics engineering, discussing the latest sustainable developments in fields such as signal processing and communications; GNSS and VLSI; microwaves and antennas; signal, speech and image processing; power systems; and power electronics

• Introduction.- The Use of Cloud Computing for Engineering Applications.- From the office to the cloud, why should you care?.- Generating a Model.- Building a Prototype.- Motion Studies.- MATLAB PRIMER.- Shell Installation.
• (source: Nielsen Book Data)

This book explains the use of cloud computing systems for engineering applications to satisfy the need for enterprise level, state-of-the-art computational capacities at an affordable cost. As huge costs are involved in the maintenance and timely renovation of computational capabilities, particularly for projects that require significant computational capacity, cloud services can achieve considerable savings for users and organizations engaged in engineering research and development. Dr. Stradi-Granados explains how to extract a maximum value from every dollar invested in cloud computer server. The types of facilities located around the world that lease their resources to customers interested in reducing the internal overhead and implementation time. The volume features chapters on model generation, motion studies, and prototyping is ideal for students, researchers, practitioners, and facility's managers across a range of engineering domains.
(source: Nielsen Book Data)

• Introduction to the Finite Element Method.- Rods and Trusses.- Euler-Bernoulli Beams and Frames.- Timoshenko Beams.- Plane Elements.- Classical Plate Elements.- Three-Dimensional Elements.- Principles of Linear Dynamics.- Integration Methods for Transient Problems.- Appendix A: Mathematics.- Appendix B: Mechanics.- Appendix C: Units and Conversion.- Appendix D: Summary of Stiffness Matrices.
• (source: Nielsen Book Data)

This book is the 2nd edition of an introduction to modern computational mechanics based on the finite element method. It includes more details on the theory, more exercises, and more consistent notation; in addition, all pictures have been revised. Featuring more than 100 pages of new material, the new edition will help students succeed in mechanics courses by showing them how to apply the fundamental knowledge they gained in the first years of their engineering education to more advanced topics. In order to deepen readers' understanding of the equations and theories discussed, each chapter also includes supplementary problems. These problems start with fundamental knowledge questions on the theory presented in the respective chapter, followed by calculation problems. In total, over 80 such calculation problems are provided, along with brief solutions for each. This book is especially designed to meet the needs of Australian students, reviewing the mathematics covered in their first two years at university. The 13-week course comprises three hours of lectures and two hours of tutorials per week.
(source: Nielsen Book Data)

• Intro
• Preface
• Contents
• Acronyms
• List of Figures
• Chapter 1: Introduction to the Data Science Framework
• 1.1 About Data Science
• 1.2 About the EDISON Project
• 1.3 About EDISON Data Science Framework (EDSF)
• 1.4 About This Book
• Chapter 2: Data Science Competences
• 2.1 Overview of Frameworks for Computer Science and Data Science Competences Definitions
• 2.1.1 Big Data Interoperability Framework, NIST NBDIF
• 2.1.2 e-Competence Framework, e-CF
• 2.1.3 Information Technology Competency Model, ACM IT-CM
• 2.1.4 OŔeilly Strata Industry Research

• 2.1.5 Other Studies, Reports and Projects on Defining Data Science Competences
• 2.2 Definition of Data Science Competences, Skills and Knowledge
• 2.2.1 3-Dimensional Competences Model
• 2.2.1.1 CF-DS Competences
• 2.2.1.2 CF-DS Skills
• 2.2.1.3 Knowledge Topics
• 2.2.2 Data Analytics Competences, Skills and Knowledge (DSDA)
• 2.2.3 Data Engineering Competences, Skills and Knowledge (DSDEG)
• 2.2.4 Data Management Competences, Skills and Knowledge (DSDM)
• 2.2.5 Research Methods and Project Management Competences, Skills and Knowledge, DSRPM

• 2.2.6 Domain-Specific Competences Group (DSDK)
• 2.3 Data Science Additional Skills
• 2.3.1 Group B Skills
• 2.3.2 Transversal Skills
• 2.3.2.1 Data Science Professional or Attitude Skills (DSPS) (Thinking and Acting Like a Data Scientist)
• 2.3.2.2 Twenty-First-Century Skills (SK21) (Aka ``Soft ́́Skills)
• Chapter 3: Data Science Body of Knowledge
• 3.1 Overview of Related Bodies of Knowledge
• 3.1.1 Computer Science Body of Knowledge (ACM-IEEE CS-BoK)
• 3.1.2 Foundational Information and Communication Technologies Body of Knowledge (EC ICT-BoK)

• 3.1.3 Software Engineering Body of Knowledge (IEEE SWEBOK)
• 3.1.4 Business Analytics Body of Knowledge (IIBA BABOK)
• 3.1.5 Data Management Body of Knowledge (DAMA DMBOK)
• 3.1.6 Project Management Professional Body of Knowledge (PMBOK)
• 3.2 Definition of a Data Science Body of Knowledge (DS-BoK)
• 3.2.1 Data Analytics Knowledge Area Group (KAG1-DSDA)
• 3.2.1.1 Statistical Methods Knowledge Area
• 3.2.1.2 Machine Learning Methods Knowledge Area
• 3.2.1.3 Data Mining Knowledge Area
• 3.2.1.4 Text Data Mining Knowledge Area
• 3.2.1.5 Predictive Analytics Knowledge Area

• 3.2.1.6 Computational Modelling, Simulation and Optimisation Knowledge Area
• 3.2.2 Data Engineering Knowledge Area Group (KAG2-DSENG)
• 3.2.2.1 Big Data Infrastructure and Technologies Knowledge Area
• 3.2.2.2 Infrastructure and Platforms for Data Science Applications Knowledge Area
• 3.2.2.3 Cloud Computing Technologies for Big Data and Data Analytics Knowledge Area
• 3.2.2.4 Data and Applications Security Knowledge Area
• 3.2.2.5 Big Data Systems Organisation and Engineering Knowledge Area
• 3.2.2.6 Data Science (Big Data) Applications Design Knowledge Area

This edited book first consolidates the results of the EU-funded EDISON project (Education for Data Intensive Science to Open New science frontiers), which developed training material and information to assist educators, trainers, employers, and research infrastructure managers in identifying, recruiting and inspiring the data science professionals of the future. It then deepens the presentation of the information and knowledge gained to allow for easier assimilation by the reader. The contributed chapters are presented in sequence, each chapter picking up from the end point of the previous one. After the initial book and project overview, the chapters present the relevant data science competencies and body of knowledge, the model curriculum required to teach the required foundations, profiles of professionals in this domain, and use cases and applications. The text is supported with appendices on related process models. The book can be used to develop new courses in data science, evaluate existing modules and courses, draft job descriptions, and plan and design efficient data-intensive research teams across scientific disciplines.

• 1. Maxwell's equations, potentials, and boundary conditions
• 1.1. The time-domain Maxwell's equations
• 1.2. Frequency domain Maxwell's equations
• 1.3. Field determination by radial components

• 2. Electrostatics and magnetostatics
• 2.1. Energy related theorems in electrostatics
• 2.2. Principle of virtual displacement for static fields
• 2.3. Theorems related to harmonic functions

• 3. Gauge invariance for electromagnetic fields
• 3.1. Gauge invariance for general material media
• 3.2. Gauge invariance in homogenized media

• 4. Causality and dispersion
• 4.1. Causal systems
• 4.2. Dispersive systems
• 4.3. Causal properties of scattering amplitude

• 5. Uniqueness, energy, and momentum
• 5.1. Uniqueness theorem
• 5.2. Energy and momentum

• 6. Duality principle and Babinet's principle
• 6.1. Duality principle and Babinet's principle

• 7. Electromagnetic reciprocity
• 7.1. Reciprocity theorems in the frequency and time domains
• 7.2. Compensation theorem

• 8. Reactance theorems
• 8.1. Reactance theorems for networks and antennas

• 9. Geometrical optics and Fermat's principle
• 9.1. Geometrical optics and Fermat's principle
• 9.2. Gradient metasurfaces and the generalized Snell's law

• 10. Integral field representations
• 10.1. Integral representation of fields
• 10.2. Integral equations, physical optics, and Bojarski's identity

• 11. Induction theorem and optical theorem
• 11.1. Induction and forward scattering theorems

• 12. Eigenfunctions, Green's functions, and completeness
• 12.1. Hilbert space
• 12.2. Sturm-Liouville problem and Green's functions
• 12.3. Classification of operators and their properties
• 12.4. Sum of two commutative operators

• 13. Electromagnetic degrees of freedom
• 13.1. DoF between communicating volumes in free space
• 13.2. Antenna gain limitations due to finite DoF

• 14. Projection slice theorem and computed tomography
• 14.1. Radon transform and projection slice theorem
• 14.2. Computed tomography

• 15. Free-space Green's function and its application in various coordinates
• 15.1. Various forms of the free-space Green's function
• 15.2. Canonical problems in various coordinate systems

• 16. Asymptotic analysis
• 16.1. Branch cuts for wave propagation
• 16.2. Complex waves
• 16.3. Asymptotic evaluation of integrals
• 16.4. Examples in wave propagation
• 16.5. Modified saddle point technique

• 17. Covariant formulation of Maxwell's equations
• 17.1. Preliminaries of tensor calculus
• 17.2. The covariant form of Maxwell's equations in Euclidean pseudo-space
• 17.3. Maxwell's equations in an arbitrary spacetime
• 17.4. Covariant form of Maxwell's equations in stationary matter
• 17.5. Transformational electromagnetics

• 18. Maxwell's equations in the sense of distributions
• 18.1. Preliminaries of distributions
• 18.2. Derivation of boundary conditions using distributions

• 19. Stochastic representations of wave phenomena
• 19.1. Preliminaries of stochastic calculus
• 19.2. Stochastic processes and Brownian motion
• 19.3. Itô integral and Itô-Doeblin formula
• 19.4. Solution of PDEs by stochastic technique, Feynman-Kac formulas

Engineering Electrodynamics: A collection of theorems, principles, and field representations deals with key theorems and principles that form the pillars on which engineering electromagnetics rests. In contrast to previous books, the emphasis here is on the underlying mathematical theme that binds these specific geometries. The relevant background material for the understanding of the various theorems is included in the book. After the theorems and principles are expounded, detailed examples are worked out, which further shed light on the those involved. This book also includes comprehensive material on some recent developments such as transformational electromagnetics. Detailed account on relevant complex variable theory, Bessel functions, and associated Legendre functions in the appendices make this book self-contained and suitable for graduate and advanced study

• Part I - Introduction
• 1. Research and Development
• 2. Process and Preparation Part II - Project Organization
• 3. The Project Hierarchy
• 4. The Project Task Part III - Knowledge Representation
• 5. An Epistemological Journey
• 6. Categories and Types of Knowledge
• 7. Roles of Knowledge Propositions
• 8. The Limits of Knowledge Part IV - The Scientific Method
• 12. Overview
• 13. Analysis
• 14. Hypothesis
• 15. Synthesis
• 16. Validation Appendices Index.
• (source: Nielsen Book Data)

Getting it Right: R&D Methods for Science and Engineering, Second Edition, is an authoritative guide to the methodologies that produce coherent and complete R&D projects. Based on the author's experience in large industrial firms, this book addresses the avoidance of common pitfalls that engineers and scientists routinely face in industry and academia. Special emphasis is placed on the comprehensive analysis of project problems, requirements, objectives, the use of standard and consistent terminology and procedures, the design of rigorous and reproducible experiments, the appropriate reduction and interpretation of project results, and the effective communication of project design, methods, results, and conclusions, embedded in a clear and modern framework of the Scientific Method. This fully updated new edition also includes an extended case study from industry, additional material about the evolution of knowledge and science and technology and a special focus on the discovery and nurture of technical innovation, both of which reinforce the importance of adherence to the described methodology in both academic and industrial venues. Professional engineers and researchers will find a highly consistent and practical reference for the rigorous conduct and clear communication of complex R&D projects. Students will also find a palatable introduction to the critical concepts of knowing, doing, and Getting it Right.
(source: Nielsen Book Data)

• Part I - Introduction
• 1. Research and Development
• 2. Process and Preparation Part II - Project Organization
• 3. The Project Hierarchy
• 4. The Project Task Part III - Knowledge Representation
• 5. An Epistemological Journey
• 6. Categories and Types of Knowledge
• 7. Roles of Knowledge Propositions
• 8. The Limits of Knowledge Part IV - The Scientific Method
• 12. Overview
• 13. Analysis
• 14. Hypothesis
• 15. Synthesis
• 16. Validation Appendices Index.
• (source: Nielsen Book Data)

Getting it Right: R&D Methods for Science and Engineering, Second Edition, is an authoritative guide to the methodologies that produce coherent and complete R&D projects. Based on the author's experience in large industrial firms, this book addresses the avoidance of common pitfalls that engineers and scientists routinely face in industry and academia. Special emphasis is placed on the comprehensive analysis of project problems, requirements, objectives, the use of standard and consistent terminology and procedures, the design of rigorous and reproducible experiments, the appropriate reduction and interpretation of project results, and the effective communication of project design, methods, results, and conclusions, embedded in a clear and modern framework of the Scientific Method. This fully updated new edition also includes an extended case study from industry, additional material about the evolution of knowledge and science and technology and a special focus on the discovery and nurture of technical innovation, both of which reinforce the importance of adherence to the described methodology in both academic and industrial venues. Professional engineers and researchers will find a highly consistent and practical reference for the rigorous conduct and clear communication of complex R&D projects. Students will also find a palatable introduction to the critical concepts of knowing, doing, and Getting it Right.
(source: Nielsen Book Data)

• A Prescriptive Analytical Logic Model Incorporated with Analytic Hierarchy Process for Software Application Error Analysis
• Simplified Framework of Natural Language Processing for Structure Management of Current-Age Data
• Design and Software Implementation of Heuristic and Suboptimal Strategies for the Mancala/Kalah Game
• Sector-Selective Hybrid Scheme Facilitating Hardware Supportability Over Image Compression
• Performance Evaluation of Joint Rate-Distortion Model of Video Codec
• To Defeat DDoS Attacks in Cloud Computing Environment Using Software Defined Networking (SDN)
• Oriented Petri Nets as Means of Describing a Human-Computer Interaction
• FPGA Based Transient Fault Generate and Fault Tolerant for Asynchronous and Synchronous Circuits
• Designing an Energy Efficient Routing for Subsystems Sensors in Internet of Things Eco-System Using Distributed Approach
• The Compare of Solo Programming and Pair Programming Strategies in a Scrum Team: A Multi-agent Simulation
• Fair Random Access with Track-Based SNR Scheduling for Full-Duplex Wireless Powered Communication Networks
• A DTN Gateway-Based Architecture for Web Access in Space Internet
• Multi-objective Scheduling Optimization for ETL Tasks in Cluster Environment
• An LSTM-Based Encoder-Decoder Model for State-of-Charge Estimation of Lithium-Ion Batteries
• Analysis of Social Engineering Attacks Using Exploit Kits
• Bipolar Disorder: A Pathway Towards Research Progress in Identification and Classification
• Managing Electronic Waste with Recycling: A Review of Developing and Developed Regions
• Trajectory Modeling in a Pursuit Problem with Curvature Restrictions
• An Approach to Using Templates for Modeling Exceptions in Terms of Petri Nets
• Performance Bottleneck Analysis and Optimization Framework in Concurrent Environments
• Matlab Code Generation and Consumption
• The Problem of Preventing the Development of Critical Combinations of Events in Large-Scale Systems
• Using Software Package "Multimeat-Expert" for Modeling and Optimization of Composition Chopped Meat Product with Vegetable Additive
• Application of Machine Learning for Document Classification and Processing in Adaptive Information Systems
• SNR-Based TDMA Scheduling with Continuous Energy Transfer for Wireless Powered Communication Networks
• Comparative Analysis of Software Development Life Cycle Models (SDLC). Plus 27 more papers.

This book gathers the refereed proceedings of the Intelligent Algorithms in Software Engineering Section of the 9th Computer Science On-line Conference 2020 (CSOC 2020), held on-line in April 2020. Software engineering research and its applications to intelligent algorithms have now assumed an essential role in computer science research. In this book, modern research methods, together with applications of machine and statistical learning in software engineering research, are presented. .
(source: Nielsen Book Data)

• Preface Acknowledgments Introduction: Python and Array Operations Introduction to PyTorch Introduction to Deep Learning Deep Transfer Learning Case Study: Practical Implementation Through Transfer Learning Bibliography Author's Biography.
• (source: Nielsen Book Data)

This book provides a short introduction and easy-to-follow implementation steps of deep learning using Google Cloud Platform. It also includes a practical case study that highlights the utilization of Python and related libraries for running a pre-trained deep learning model.In recent years, deep learning-based modeling approaches have been used in a wide variety of engineering domains, such as autonomous cars, intelligent robotics, computer vision, natural language processing, and bioinformatics. Also, numerous real-world engineering applications utilize an existing pre-trained deep learning model that has already been developed and optimized for a related task. However, incorporating a deep learning model in a research project is quite challenging, especially for someone who doesn't have related machine learning and cloud computing knowledge. Keeping that in mind, this book is intended to be a short introduction of deep learning basics through the example of a practical implementation case. The audience of this short book is undergraduate engineering students who wish to explore deep learning models in their class project or senior design project without having a full journey through the machine learning theories. The case study part at the end also provides a cost-effective and step-by-step approach that can be replicated by others easily.
(source: Nielsen Book Data)

• Introduction to Programming
• C++ Basics
• Delving into Object-Oriented Programming
• Memory Management
• Advanced Object-Oriented Programming
• Computer Arithmetic
• Basics of Parallel Programming
• Appendix.

A complete textbook and reference for engineers to learn the fundamentals of computer programming with modern C++ Introduction to Programming with C++ for Engineers is an original presentation teaching the fundamentals of computer programming and modern C++ to engineers and engineering students. Professor Cyganek, a highly regarded expert in his field, walks users through basics of data structures and algorithms with the help of a core subset of C++ and the Standard Library, progressing to the object-oriented domain and advanced C++ features, computer arithmetic, memory management and essentials of parallel programming, showing with real world examples how to complete tasks. He also guides users through the software development process, good programming practices, not shunning from explaining low-level features and the programming tools. Being a textbook, with the summarizing tables and diagrams the book becomes a highly useful reference for C++ programmers at all levels. Introduction to Programming with C++ for Engineers teaches how to program by: Guiding users from simple techniques with modern C++ and the Standard Library, to more advanced object-oriented design methods and language features Providing meaningful examples that facilitate understanding of the programming techniques and the C++ language constructions Fostering good programming practices which create better professional programmers Minimizing text descriptions, opting instead for comprehensive figures, tables, diagrams, and other explanatory material Granting access to a complementary website that contains example code and useful links to resources that further improve the reader's coding ability Including test and exam question for the reader's review at the end of each chapter Engineering students, students of other sciences who rely on computer programming, and professionals in various fields will find this book invaluable when learning to program with C++.
(source: Nielsen Book Data)

• Introduction to Programming
• C++ Basics
• Delving into Object-Oriented Programming
• Memory Management
• Advanced Object-Oriented Programming
• Computer Arithmetic
• Basics of Parallel Programming
• Appendix

A complete textbook and reference for engineers to learn the fundamentals of computer programming with modern C++ Introduction to Programming with C++ for Engineers is an original presentation teaching the fundamentals of computer programming and modern C++ to engineers and engineering students. Professor Cyganek, a highly regarded expert in his field, walks users through basics of data structures and algorithms with the help of a core subset of C++ and the Standard Library, progressing to the object-oriented domain and advanced C++ features, computer arithmetic, memory management and essentials of parallel programming, showing with real world examples how to complete tasks. He also guides users through the software development process, good programming practices, not shunning from explaining low-level features and the programming tools. Being a textbook, with the summarizing tables and diagrams the book becomes a highly useful reference for C++ programmers at all levels. Introduction to Programming with C++ for Engineers teaches how to program by: Guiding users from simple techniques with modern C++ and the Standard Library, to more advanced object-oriented design methods and language features Providing meaningful examples that facilitate understanding of the programming techniques and the C++ language constructions Fostering good programming practices which create better professional programmers Minimizing text descriptions, opting instead for comprehensive figures, tables, diagrams, and other explanatory material Granting access to a complementary website that contains example code and useful links to resources that further improve the reader's coding ability Including test and exam question for the reader's review at the end of each chapter Engineering students, students of other sciences who rely on computer programming, and professionals in various fields will find this book invaluable when learning to program with C++.
(source: Nielsen Book Data)

• Introduction
• Number Systems
• Algebraic Equations
• Scalar Calculus
• Vector Calculus.

This state of the art book takes an applications based approach to teaching mathematics to engineering and applied sciences students. The book lays emphasis on associating mathematical concepts with their physical counterparts, training students of engineering in mathematics to help them learn how things work. The book covers the concepts of number systems, algebra equations and calculus through discussions on mathematics and physics, discussing their intertwined history in a chronological order. The book includes examples, homework problems, and exercises. This book can be used to teach a first course in engineering mathematics or as a refresher on basic mathematical physics. Besides serving as core textbook, this book will also appeal to undergraduate students with cross-disciplinary interests as a supplementary text or reader.

• Cell Structure and Biochemical Reactions.- Cellular Homeostasis and Membrane Potential.- The Action Potential.- Cellular Transport and Communication.- Pharmacokinetics.- Tissue Mechanics.- Cardiovascular System I: The Heart.- Cardiovascular System II: The Vasculature.- Respiratory System.- Nervous System.
• (source: Nielsen Book Data)

This book provides an introduction to qualitative and quantitative aspects of human physiology. It examines biological and physiological processes and phenomena, including a selection of mathematical models, showing how physiological problems can be mathematically formulated and studied. It also illustrates how a wide range of engineering and physics topics, such as electronics, fluid dynamics, solid mechanics and control theory can be used to describe and understand physiological processes and systems. Throughout the text, there are introductions to measuring and quantifying physiological processes using both signaling and imaging technologies. This new edition includes updated material on pathophysiology, metabolism and the TCA cycle, as well as more advanced worked examples. This book describes the basic structure and models of cellular systems, the structure and function of the cardiovascular system, and the electrical and mechanical activity of the heart, and provides an overview of the structure and function of the respiratory and nervous systems. It also includes an introduction to the basic concepts and applications of reaction kinetics, pharmacokinetic modelling and tracer kinetics. It appeals to final year biomedical engineering undergraduates and graduates alike, as well as to practising engineers new to the fields of bioengineering or medical physics. .
(source: Nielsen Book Data)

• Preface Acknowledgments Probability Random Variables Distributions of Sample Mean and Sample SD Confidence and Prediction Intervals Hypothesis Testing Linear Regression Authors' Biographies Index.
• (source: Nielsen Book Data)

One of the most important subjects for all engineers and scientists is probability and statistics. This book presents the basics of the essential topics in probability and statistics from a rigorous standpoint. The basics of probability underlying all statistics is presented first and then we cover the essential topics in statistics, confidence intervals, hypothesis testing, and linear regression. This book is suitable for any engineer or scientist who is comfortable with calculus and is meant to be covered in a one-semester format.
(source: Nielsen Book Data)

• Preface Acknowledgments Probability Random Variables Distributions of Sample Mean and Sample SD Confidence and Prediction Intervals Hypothesis Testing Linear Regression Authors' Biographies Index.
• (source: Nielsen Book Data)

One of the most important subjects for all engineers and scientists is probability and statistics. This book presents the basics of the essential topics in probability and statistics from a rigorous standpoint. The basics of probability underlying all statistics is presented first and then we cover the essential topics in statistics, confidence intervals, hypothesis testing, and linear regression. This book is suitable for any engineer or scientist who is comfortable with calculus and is meant to be covered in a one-semester format.
(source: Nielsen Book Data)

Science education's two-fold challenge is clear: Schools need to (1) align their curricula with contemporary state standards and (2) meet the growing demand for STEM education. What's not as clear: how to meet the challenge if your school doesn't have the right instructional materials. STEM, Standards, and Strategies for High-Quality Units is designed to address both these needs. Thought leader and curriculum expert Rodger W. Bybee has assembled a guide to creating coherent, high-quality classroom materials that support the standards and STEM. The book provides practical background information and activities that can be adapted by individual teachers, professional learning communities, and professional developers.
(source: Nielsen Book Data)

• Basics.- SimTalk and Dialogs.- Modeling of Production Processes.- Information Flow, Controls.- Working with random values.- Simulation of transport processes.- Simulation of Robots and Handling Equipment.- Warehousing and Procurement.- Simulation of Workers.- The Fluids Library.- 2D and 3D Visualization.- Integrate Energy Consumption and Costs.- Statistics.- Data Exchange and Interfaces.
• (source: Nielsen Book Data)

This book systematically introduces readers to the development of simulation models as well as the implementation and evaluation of simulation experiments with Tecnomatix Plant Simulation. Intended for all Plant Simulation users whose work involves complex tasks, it also offers an easy start for newcomers. Particular attention has been paid to introducing the simulation flow language SimTalk and its use in various aspects of simulation. In over 200 examples, the author demonstrates how to combine the blocks for simulation models and how to employ SimTalk in complex control and analysis tasks. The content ranges from a description of the basic functions of the material flow blocks to more advanced topics such as the implementation of database-supported warehouse control by using the SQLite interface, and the exchange of data using XML, ActiveX, COM or DDE. .
(source: Nielsen Book Data)

• Introduction.- Getting Around to Building an Electronic Brain.- Journey Through Nanotechnologies.- Reverse Engineering Video Games.- Modeling the Brain with Analog Electronics.- Design Automation.- Analog Circuits and Neuromorphic Circuits.- Making VLSI Design Accessible.- The Future: Rising Women Stars in Microelectronics.- Conclusion.
• (source: Nielsen Book Data)

This book contains stories of women engineers' paths through the golden age of microelectronics, stemming from the invention of the transistor in 1947. These stories, like the biographies of Marie Curie and the National Geographic's stories of Jane Goodall's research that inspired the authors will inspire and guide readers along unconventional pathways to contributions to microelectronics that we can only begin to imagine. The book explores why and how the women writing here chose their career paths and how they navigated their careers. This topic is of interest to a vast audience, from students to professionals to university advisers to industry CEOs, who can imagine the advantages of a future with a diverse work force. Provides insight into women's early contributions to the field of microelectronics and celebrates the challenges they overcame; Presents compelling innovations from academia, research, and industry into advances, applications, and the future of microelectronics; Includes a fascinating look into topics such as nanotechnologies, video games, analog electronics, design automation, and neuromorphic circuits.
(source: Nielsen Book Data)

• Using Flipped Classroom Settings to Shift the Focus of a General Chemistry Course from Topic Knowledge to Learning and Problem-Solving Skills: A Tale of Students Enjoying the Class They Were Expecting to Hate / Ramella, Daniele, College of Science and Technology-Department of Chemistry, Temple University, 1901 North 13th Street, Philadelphia, Pennsylvania 19122, United States; Brock, Benjamin E., CAT-Center for Advancement of Teaching, Temple University, Philadelphia, Pennsylvania 19122, United States, School of Education, Temple University, Philadelphia, Pennsylvania 19122, United States; Velopolcek, Maria K., Department of Chemistry, Duke University, Durham, North Carolina 27701, United States; Winters, Kyle P., School of Dentistry, Temple University, Philadelphia, Pennsylvania 19140, United States / http://dx.doi.org/10.1021/bk-2019-1322.ch001
• Combining Pre-class Preparation with Collaborative In-Class Activities to Improve Student Engagement and Success in General Chemistry / Blaser, Mark / http://dx.doi.org/10.1021/bk-2019-1322.ch002
• Using Clicker-Based Group Work Facilitated by a Modified Peer Instruction Process in a Highly Successful Flipped General Chemistry Classroom / Pollozi, Shejla, Department of Chemistry, Lehman College of the City University of New York, 250 Bedford Park Boulevard West, Bronx, New York 10468, United States, Ph.D. Program in Chemistry, The Graduate Center of the City University of New York, New York, New York 10016, United States; Haddad, Ibrahim, Department of Chemistry, Lehman College of the City University of New York, 250 Bedford Park Boulevard West, Bronx, New York 10468, United States; Tyagi, Aanchal, Department of Chemistry, Lehman College of the City University of New York, 250 Bedford Park Boulevard West, Bronx, New York 10468, United States; Mills, Pamela, Department of Chemistry, Lehman College of the City University of New York, 250 Bedford Park Boulevard West, Bronx, New York 10468, United States, Ph.D. Program in Chemistry, The Graduate Center of the City University of New York, New York, New York 10016, United States; McGregor, Donna, Department of Chemistry, Lehman College of the City University of New York, 250 Bedford Park Boulevard West, Bronx, New York 10468, United States, Ph.D. Program in Chemistry, The Graduate Center of the City University of New York, New York, New York 10016, United States / http://dx.doi.org/10.1021/bk-2019-1322.ch003
• Maximizing Learning Efficiency in General Chemistry / Cracolice, Mark S., Department of Chemistry & Biochemistry, University of Montana, Missoula, Montana 59812, United States; Queen, Matt, Department of Biological and Physical Sciences, Montana State University Billings, 1500 University Drive, Billings, Montana 59101, United States / http://dx.doi.org/10.1021/bk-2019-1322.ch004
• Flipping General Chemistry in Small Classes: Students' Perception and Success / Hutchinson-Anderson, Kelly M. / http://dx.doi.org/10.1021/bk-2019-1322.ch005
• Active Learning in the Large Lecture Hall Format / LaBrake, Cynthia / http://dx.doi.org/10.1021/bk-2019-1322.ch006
• Large-Scale, Team-Based Curriculum Transformation and Student Engagement in General Chemistry I and II / Lamont, Liana B., Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States; Stoll, Lindy K., Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States; Pesavento, Theresa M., Department of Academic Technology, University of Wisconsin-Madison, 1305 Linden Drive, Madison, Wisconsin 53706, United States; Bain, Rachel L., Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States; Landis, Clark R., Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States; Sibert, Edwin L., Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States / http://dx.doi.org/10.1021/bk-2019-1322.ch007
• Active Learning in Hybrid-Online General Chemistry / Miller, Dionne A. / http://dx.doi.org/10.1021/bk-2019-1322.ch008
• A Course Transformation to Support First-Year Chemistry Education for Engineering Students / Addison, Christopher J.; Núñez, José Rodríguez / http://dx.doi.org/10.1021/bk-2019-1322.ch009
• Flipped Classroom Learning Environments in General Chemistry: What Is the Impact on Student Performance in Organic Chemistry? / Eichler, Jack F., Department of Chemistry, University of California, Riverside, Riverside, California 92521, United States; Peeples, Junelyn, Department of Chemistry, University of California, Riverside, Riverside, California 92521, United States / http://dx.doi.org/10.1021/bk-2019-1322.ch010
• Editors' Biographies / http://dx.doi.org/10.1021/bk-2019-1322.ot001

• Cover; Half Title Page; Title Page; Copyright Page; About the Author; Table of Contents; Preface;
• Chapter 1 Introduction to Data Mining; 1.1. What is Data Mining?; 1.2. Terminology Used in Data Mining; 1.3. Data Mining Process; 1.4. CRISP-DM Process Model; 1.5. SEMMA; 1.6. Data Warehousing Overview; 1.7. OLAP: Online Analytical Processing; 1.8. Data Mining Techniques;
• Chapter 2 Applications of Data Mining in Management; 2.1. Telecommunications; 2.2. Finance Industry; 2.3. Bankruptcy Prediction; 2.4. Credit Risk Analysis; 2.5. Targeted Marketing; 2.6. Company Performance Prediction

• 2.7. Banking Fraud Detection2.8. Investment Banking; 2.9. Online Security In Data Mining; 2.10. Retail Industry
• Marketing And Sales; 2.11. Energy Domain; 2.12. Education; Chapter 3 Applications of Data Mining in Engineering; 3.1. Introduction; 3.2. Software Systems; 3.3. Applications in Software Management; 3.4. Applications in Software Development Tasks; 3.5. Applications in Software Development Research; 3.6. Practical Application of Data Mining In Software Engineering; 3.7. MapReduce; Chapter 4 Applications of Data Mining In Medicine; 4.1. Introduction; Index

• Introduction.- Problem Description and Related Work.- Concept.- Fuzzy Rulebase Systems.- Parameters and most Possible Ranges.- Rulebase Construction.- Constrained Defuzzification.- Data Comparison.- Experiments.- Conclusion.
• (source: Nielsen Book Data)

This book provides readers with an insight into the development of a novel method for regridding gridded spatial data, an operation required to perform the map overlay operation and apply map algebra when processing spatial data. It introduces the necessary concepts from spatial data processing and fuzzy rulebase systems and describes the issues experienced when using current regridding algorithms. The main focus of the book is on describing the different modifications needed to make the problem compatible with fuzzy rulebases. It offers a number of examples of out-of-the box thinking to handle aspects such as rulebase construction, defuzzification, spatial data comparison, etc. At first, the emphasis is put on the newly developed method, and additional datasets containing information on the underlying spatial distribution of the data are identified. After this, an artificial intelligent system (in the form of a fuzzy inference system) is constructed using this knowledge and then applied on the input data to perform the regridding. The book offers an example of how an apparently simple problem can pose many different challenges, even when trying to solve it with existing soft computing technologies. The workflow and solutions to solve these challenges are universal and may therefore be broadly applied into other contexts.
(source: Nielsen Book Data)

• Foreword
• Ryan Kelsey & Sue Cui 1. That None Shall Perish
• Kelly Mack, Kate Winter 2. Theoretical Underpinnings of TIDES: Priorities, Processes, & Promise
• Melvin Hall, Jamie Bracey, Eileen Parsons, Tykeia Robinson 3. Cybernetic Girls Can Be Pinky: Strategies to Recruit and Retain Latinas into STEM in the Context of Faculty-to-Student Empowerment
• Lilliam Casillas-Martinez & Wilson Gonzalez-Espada 4. Changing Faculty Culture to Promote Diversity, Equity, and Inclusion in STEM Education
• Jennifer Speed, Donald L. Pair, Mehdi Zargham, Zhongmei Yao, Suzanne Franco 5. In Search of Hidden but Accessible Truths: Coding for All at Queens College
• Eva M. Fernandez & Christopher Vickery 6. Fostering an Environment for all Students to Succeed in Computer Science: Integrating Culturally Responsive Pedagogies with Curricula Redesign
• Kiron Sharma, Laila Khreisat, Diana Cvitan, Gurjot Singh 7. TIDES Interventions Addressing Recruitment and Retention of White Women and Women of Color
• Mark Matlin, Elizabeth McCormack, Douglas Blank, Jennifer Spohrer 8. Culturally Responsive Computational Science through Research Experience in Core Curriculum Courses
• Lior Shamir, Franco Delogy, Melinda Weinstein, Hsiao-Ping Moore 9. A Journey of Discovery
• Alla Grinberg, Raymond Gonzales, Monica Parrish Trent 10. Equity through Access to Computer Science Learning at Pitzer College
• Katie Purvis-Roberts & Thomas Poon 11. Challenging Us to Change
• Helen H. Hu, Patricia B. Campbell, Jessica C. Johnston, Brian Avery, Greg Gagne, Julie Stewart 12. The Rising TIDE of Wright State University: Context, Connections, and Consequences
• Travis Doom, John Gallagher, Michael Raymer, Kathleen Timmerman 13. Music as the Icebreaker for Learning to Code
• Ani Nahapetian 14. Interventions Addressing Recruitment and Retention of Underrepresented Minority Groups in Undergraduate STEM Disciplines
• Cleo Hughes Darden, Roni M. Ellington, Jigish Zaveri, Sanjay Bapna, Linda Akil, Stella Hargett, Prabir Bhattacharya, Ali Emdad, Asamoah Nkwanta 15. Strengthening Computer and Mathematical Sciences Engagement and Learning
• Sambit Bhattacharya, Daniel Okunbor, Chekad Sarami, Perry Gillespie, Radoslav Nickolov 16. Measurement and Assessment
• Kate Winter and Gabriele Haynes.
• (source: Nielsen Book Data)

By the end of this decade, the U.S. economy will annually create hundreds of thousands of new jobs requiring a bachelor's degree in STEM fields, particularly computer science. This increasing need for computer scientists, coupled with an inconsistent agenda for managing dramatic shifts in the demographic landscape of higher education, compromises our competitiveness in scientific discovery and innovation. As higher education seeks to address this issue, the need for more culturally responsive approaches to undergraduate STEM teaching also increases.This book uses the power of reflection, storytelling, and data to holistically demonstrate the effectiveness of a novel professional development intervention for STEM faculty - Teaching to Increase Diversity and Equity in STEM, or TIDES - that significantly increased faculty self-efficacy in implementing culturally responsive pedagogies. In it, the editors combine the authentic voices of authors from multiple institutional contexts and individual worldviews to assimilate and synthesize broad theoretical concepts into practice in usable ways, while also offering concrete applicable examples of strategies and solutions that serve as an important comprehensive reference for all undergraduate educators and administrators. This practical guide provides a durable platform for building capacity in understanding of the cultural complexities and institutional realities of recruiting and retaining diverse students in STEM, particularly the computer sciences.
(source: Nielsen Book Data)

• 1. Don't get bent out of shape : memory wire
• 2. Harnessing the color of nature : structural color and iridescence
• 3. From sludge to nobility : artificial dye
• 4. By the teeth of your skin : shark skin and bacteria
• 5. A sticky situation : gecko feet adhesives
• 6. It's hip to be square : seahorse tails
• 7. Corn flakes : waste not, want not
• 8. Get fired up with friction lights : matches
• 9. That's a wrap : plastic
• 10. A sticky discovery : the invention of post-it notes
• 11. Putty in your hands : the unintended discovery of silly putty
• 12. Sweet and sour : the rise and fall ... and rise ... of saccharin
• 13. Saving lives through an accident : safety glass
• 14. A wearable water filter : the sari
• 15. From ship to staircase : the history of the slinky
• 16. Man of stainless steel : the discovery of a new alloy
• 17. Super glue : accidentally discovered twice
• 18. Teflon : a refrigerator gas accident
• 19. Vaseline : the "wonder jelly"
• 20. I'm rubber and you're glue : vulcanized rubber
• 21. Peering into the unknown : the discovery of x-rays
• 22. Velcro : engineering mimics nature.

Who knew that gecko feet inspired scientists to develop a stickier adhesive or that cockleburs in dog fur led to the invention of Velcro? Discovery Engineering uses these and other surprising cases of innovations sparked by accidental observations to teach about the amazing role of serendipity in science. The case studies in this new resource are a lively way to integrate engineering into your physical science classes. Middle and high school students will learn to understand fundamental science processes while trying out their own ideas for unexpected applications. Each of the book's 22 investigations starts with a real case of accidental inspiration that students explore through primary documents or historical accounts. Then it's time for the students to become the innovators. They're tasked to do research, examine data and physical materials, and use their own creativity to design new products or problem-solving applications. The investigations are easy to implement and flexible enough to use in part or as a whole. Students will learn one or more science concepts as they're exposed to background on the unpredictable nature of science. And they'll be intrigued by investigations with titles such as "By the Teeth of Your Skin: Shark Skin and Bacteria" and "The Slinky: From Ship to Staircase." Try this book and see what happens! The result may be more engaged students-and more great ideas about how gecko feet can inspire solutions to everyday problems.
(source: Nielsen Book Data)

• Introduction.- Part I: Theoretical Background.- Brief Introduction to Statistical Machine Learning.- Brief Introduction to Computational Intelligence.- Part II: Theoretical Fundamentals of the Proposed Approach.- Empirical Approach - Introduction.- Empirical Fuzzy Sets and Systems.- Anomaly Detection - Empirical Approach.- Data Partitioning - Empirical Approach.- Autonomous Learning Multi-Model Systems.- Transparent Deep Rule-Based Classifiers.- Part III: Applications of the Proposed Approach.- Applications of Autonomous Anomaly Detection.
• (source: Nielsen Book Data)

This book provides a 'one-stop source' for all readers who are interested in a new, empirical approach to machine learning that, unlike traditional methods, successfully addresses the demands of today's data-driven world. After an introduction to the fundamentals, the book discusses in depth anomaly detection, data partitioning and clustering, as well as classification and predictors. It describes classifiers of zero and first order, and the new, highly efficient and transparent deep rule-based classifiers, particularly highlighting their applications to image processing. Local optimality and stability conditions for the methods presented are formally derived and stated, while the software is also provided as supplemental, open-source material. The book will greatly benefit postgraduate students, researchers and practitioners dealing with advanced data processing, applied mathematicians, software developers of agent-oriented systems, and developers of embedded and real-time systems. It can also be used as a textbook for postgraduate coursework; for this purpose, a standalone set of lecture notes and corresponding lab session notes are available on the same website as the code. Dimitar Filev, Henry Ford Technical Fellow, Ford Motor Company, USA, and Member of the National Academy of Engineering, USA: "The book Empirical Approach to Machine Learning opens new horizons to automated and efficient data processing." Paul J. Werbos, Inventor of the back-propagation method, USA: "I owe great thanks to Professor Plamen Angelov for making this important material available to the community just as I see great practical needs for it, in the new area of making real sense of high-speed data from the brain." Chin-Teng Lin, Distinguished Professor at University of Technology Sydney, Australia: "This new book will set up a milestone for the modern intelligent systems." Edward Tunstel, President of IEEE Systems, Man, Cybernetics Society, USA: "Empirical Approach to Machine Learning provides an insightful and visionary boost of progress in the evolution of computational learning capabilities yielding interpretable and transparent implementations.".
(source: Nielsen Book Data)

• Preface to the second edition
• Preface to the first edition
• 1. Introduction to experimentation
• 2. Characteristics of experimental data
• 3. Graphical presentation of data
• 4. Dealing with uncertainties
• 5. Statistical approach to variability in measurements
• 6. Fitting a line to x-y data using the method of least squares
• 7. Report writing and presentations
• 8. Using Excel to present and analyse data
• 9. Computer-aided data capture
• Appendix 1
• Appendix 2
• Solutions to exercises and problems
• Further reading
• References
• Index.
• (source: Nielsen Book Data)

Responding to the developments of the past twenty years, Les Kirkup has thoroughly updated his popular book on experimental methods, while retaining the extensive coverage and practical advice from the first edition. Many topics from that edition remain, including keeping a record of work, how to deal with measurement uncertainties, understanding the statistical basis of data analysis and reporting the results of experiments. However, with new technologies influencing how experiments are devised, carried out, analyzed, presented and reported, this new edition reflects the digital changes which have taken place and the increased emphasis on the importance of communication skills in reporting results. Bringing together key elements of experimental methods into one coherent book, it is perfect for students seeking guidance with their experimental work, including how to acquire, analyse and present data. Exercises, worked examples and end-of-chapter problems are provided throughout the book to reinforce fundamental principles.
(source: Nielsen Book Data)

• Chapter 1. Introduction.-
• Chapter 2. Krill Herd Algorithm.-
• Chapter 3. Literature Review.-
• Chapter 4. Proposed Methodology.-
• Chapter 5. Experimental Results.-
• Chapter 6. Conclusion and Future Work.- References.- List Of Publications.
• (source: Nielsen Book Data)

This book puts forward a new method for solving the text document (TD) clustering problem, which is established in two main stages: (i) A new feature selection method based on a particle swarm optimization algorithm with a novel weighting scheme is proposed, as well as a detailed dimension reduction technique, in order to obtain a new subset of more informative features with low-dimensional space. This new subset is subsequently used to improve the performance of the text clustering (TC) algorithm and reduce its computation time. The k-mean clustering algorithm is used to evaluate the effectiveness of the obtained subsets. (ii) Four krill herd algorithms (KHAs), namely, the (a) basic KHA, (b) modified KHA, (c) hybrid KHA, and (d) multi-objective hybrid KHA, are proposed to solve the TC problem; each algorithm represents an incremental improvement on its predecessor. For the evaluation process, seven benchmark text datasets are used with different characterizations and complexities. Text document (TD) clustering is a new trend in text mining in which the TDs are separated into several coherent clusters, where all documents in the same cluster are similar. The findings presented here confirm that the proposed methods and algorithms delivered the best results in comparison with other, similar methods to be found in the literature.
(source: Nielsen Book Data)

• The entrepreneurs. Love of the unknown / Sandra Glucksmann
• A lab of my own / Ethan Perlstein
• A mathematical modeler / Beth Reid
• A long-standing interest / Christopher Loose
• Startup or large venture / Z. Jane Wang
• A company with values / Richard Lethin
• A bigger picture / Jennifer Park
• Personal connections and serendipity / Stephen Fantone
• Tangible products / Kathy Gisser
• From healthcare to robotics / Daniel Theobald
• Adapting and creating / Daniel Goodman
• My dream job / Wanda Austin
• From outsider to collaborator / David Galas
• Trouble-shooter and leader / Norman Augustine
• Leaning business by finding a market / Richard Post

• The academics. The right environment / Jessica Seeliger
• The advantage of not fitting in / Stephon Alexander
• The long way round / Kathleen Fisher
• A flash of inspiration / Tamara Doering
• A change of direction / Michael O'Hanlon
• An unfair advantage / David Spergel
• Solving puzzles / Shirley Tilghman
• Communicating and computing / William Press
• Always experimenting / Richard Miles
• A mentor and a dream / Rainer Weiss
• The public servants. Improving the situation / Jennifer Roberts
• Reclaiming my dream / Renee Horton
• Choosing a balanced life / Jami Valentine
• Flexibility and change / Deirdre Olynick
• Risks, leaps and a support network / Kimberly Budil
• Pioneering gender equality / Wendy Cieslak
• Disappointments and successes / Ellen Stofan
• Breaking barriers and leading teams / Ellen Pawlikowski
• Engineering a leader / Paul Nielsen
• Vision and teamwork / John Mather
• Quiet science and nuclear threats / Jay Davis
• Summary. Life and career lessons : learning from lives, views and stories

Scientists offer personal accounts of the challenges, struggles, successes, U-turns, and satisfactions encountered in their careers in industry, academia, and government. This insightful book offers essential life and career lessons for newly minted STEM graduates and those seeking a career change. Thirty-six leading scientists and engineers (including two Nobel Prize winners) describe the challenges, struggles, successes, satisfactions, and U-turns encountered as they established their careers. Readers learn that there are professional possibilities beyond academia, as contributors describe the paths that took them into private industry and government as well as to college and university campuses. They discuss their varying preferences for solitary research or collaborative teamwork; their attempts to achieve work-life balance; and unplanned changes in direction that resulted in a more satisfying career. Women describe confronting overt sexism and institutional gender bias; scientists of color describe the experience of being outsiders in their field. One scientist moves from startup to startup, enjoying a career of serial challenges; another spends decades at one university; another has worked in academia, industry, and government. Some followed in the footsteps of parents; others were the first in their family to go to college. Many have changed fields, switched subjects, or left established organizations for something new. Taken together, these essays make it clear that there is not one path to a profession in science, but many. Contributors Stephon Alexander, Norman Augustine, Wanda Austin, Kimberly Budil, Wendy Cieslak, Jay Davis, Tamara Doering, Stephen D. Fantone, Kathleen Fisher, David Galas, Kathy Gisser, Sandra Glucksmann, Daniel Goodman, Renee Horton, Richard Lethin, Christopher Loose, John Mather, Richard Miles, Paul Nielsen, Michael O'Hanlon, Deirdre Olynick, Jennifer Park, Ellen Pawlikowski, Ethan Perlstein, Richard Post, William Press, Beth Reid, Jennifer Roberts, Jessica Seeliger, David Spergel, Ellen Stofan, Daniel Theobald, Shirley Tilghman, Jami Valentine, Z. Jane Wang, Rainer Weiss.
(source: Nielsen Book Data)

• Cultivating STEM Talent at Minority Serving Institutions: Challenges and Opportunities To Broaden Participation in STEM at Historically Black Colleges and Universities / Toldson, Ivory A. / http://dx.doi.org/10.1021/bk-2019-1328.ch001
• Role of the MSEIP Grant in the Success of STEM Undergraduate Research at Queensborough Community College and Beyond / Svoronos, Paris, Department of Chemistry, Queensborough Community College, Bayside, New York 11364, United States; Singh, Shalini, Department of Biological Sciences and Geology, Queensborough Community College, Bayside, New York 11364, United States; Gadura, Nidhi, Department of Biological Sciences and Geology, Queensborough Community College, Bayside, New York 11364, United States / http://dx.doi.org/10.1021/bk-2019-1328.ch002
• Engaging Students with Flipped Classrooms and Course-Based Undergraduate Research Experiences / Van Stry, Melanie; Gaber, Farag; Farrakhan-Gooch, Aminah; Jones, Candace; Sklensky, Diane; Ude, Mba / http://dx.doi.org/10.1021/bk-2019-1328.ch003
• Aiming toward an Effective Hispanic-Serving Chemistry Curriculum / Reimer, Lynn C.; Leslie, J. Michelle; Bidwell, Samantha L.; Isborn, Christine M.; Lair, Deborah; Menke, Erik; Stokes, Benjamin J.; Hratchian, Hrant P. / http://dx.doi.org/10.1021/bk-2019-1328.ch004
• Computational Chemistry and Biology Courses for Undergraduates at an HBCU: Cultivating a Diverse Computational Science Community / Dinadayalane, Tandabany, Department of Chemistry, Clark Atlanta University, 223 James P. Brawley Drive, S.W., Atlanta, Georgia 30314, United States; Bowen, Nathan J., Department of Biological Sciences, Clark Atlanta University, 223 James P. Brawley Drive, S.W., Atlanta, Georgia 30314, United States / http://dx.doi.org/10.1021/bk-2019-1328.ch005
• NanoHU: A Boundary-Spanning Education Model for Maximizing Human and Intellectual Capital / Claville, Michelle; Babu, Sainath; Boonthum-Denecke, Chutima; Fowlks, Edison; Hill, Emorcia; Lowe, Calvin; Parker, Brandon; Penn-Marshall, Michelle; Ramdon, Roopchan; Wallace, Brandon / http://dx.doi.org/10.1021/bk-2019-1328.ch006
• Design and Implementation of a STEM Student Success Program at Grambling State University / Walton, Connie R., Department of Chemistry, Grambling State University, Grambling, Louisiana 71245, United States; Akins, Corisma R., Department of Chemistry, Grambling State University, Grambling, Louisiana 71245, United States; Reddy, Yenumula, Department of Computer Science, Grambling State University, Grambling, Louisiana 71245, United States; Hubbard, Danny E., Department of Chemistry, Grambling State University, Grambling, Louisiana 71245, United States / http://dx.doi.org/10.1021/bk-2019-1328.ch007
• The Role of the ReBUILDetroit Scholars Program at Wayne State University in Broadening Participation in STEM / McIntee, Farron, Graduate School, Wayne State University, 5057 Woodward Avenue, Detroit, Michigan 48202, United States; Tabb, Jennifer, Graduate School, Wayne State University, 5057 Woodward Avenue, Detroit, Michigan 48202, United States; Hendrickson, Tamara, Department of Chemistry, Wayne State University, 5101 Cass Avenue, Detroit, Michigan 48202, United States; Mathur, Ambika, Graduate School, Wayne State University, 5057 Woodward Avenue, Detroit, Michigan 48202, United States; Hwalek, Melanie, SPEC Associates, 18000 West Nine Mile Road, Suite 525, Southfield, Michigan 48075, United States; Kagey, Jacob D., Department of Biology, University of Detroit Mercy, 4001 W. McNichols Road, Detroit, Michigan 48221, United States; Snyder, Katherine, College of Engineering and Science, University of Detroit Mercy, 4001 W. McNichols Road, Detroit, Michigan 48221, United States; Andreoli, Jeanne, Center for Research on Learning and Teaching, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, Michigan 48109, United States; Feig, Andrew L., Department of Chemistry, Wayne State University, 5101 Cass Avenue, Detroit, Michigan 48202, United States / http://dx.doi.org/10.1021/bk-2019-1328.ch008
• Using Scholars Programs To Enhance Success of Underrepresented Students in Chemistry, Biomedical Sciences, and STEM / Huggins, Michael T., Department of Chemistry, University of West Florida, 11000 University Parkway, Pensacola, Florida 32514, United States; Molek, Karen S., Department of Chemistry, University of West Florida, 11000 University Parkway, Pensacola, Florida 32514, United States; Cavnar, Peter, Department of Biology, University of West Florida, 11000 University Parkway, Pensacola, Florida 32514, United States; Godfrey, Laura, Durango, Colorado 81301, United States / http://dx.doi.org/10.1021/bk-2019-1328.ch009
• The MARC U*STAR Program at University of Maryland, Baltimore County, 1997-2018 / Robinson, Phyllis R., Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, Maryland 21250, United States; Godsay, Surbhi, Department of Psychology, University of Maryland, Baltimore County, Baltimore, Maryland 21250, United States; Moraga, Rukiya, Department of Psychology, University of Maryland, Baltimore County, Baltimore, Maryland 21250, United States; King, Jacqueline, Maximizing Access to Research Careers Undergraduate Student Training in Academic Research (MARC U*STAR) Program, University of Maryland, Baltimore County, Baltimore, Maryland 21250, United States / http://dx.doi.org/10.1021/bk-2019-1328.ch010
• Pathways to Careers in Science, Technology, Engineering, and Math / Prunuske, Amy J., Department of Microbiology and Immunology, Medical College of Wisconsin-Central Wisconsin, Wausau, Wisconsin 54401, United States; Clarke, Benjamin L., Department of Biomedical Sciences, University of Minnesota Medical School, Duluth campus, Duluth, Minnesota 55812, United States / http://dx.doi.org/10.1021/bk-2019-1328.ch011
• Leadership Dimensions for Broadening Participation in STEM: Increasing the Role of HBCUs and MSIs / Taylor, Orlando L.; Wynn, Melissa E. / http://dx.doi.org/10.1021/bk-2019-1328.ch012
• Bloom Where You Are Planted: Reflections on Effecting Campus Climate Change To Retain Minoritized Faculty Scholars in STEM Fields / Carter-Sowell, Adrienne R., Department of Psychological and Brain Sciences, Texas A&M University, College Station, Texas 77843, United States, Africana Studies Program, Texas A&M University, College Station, Texas 77843, United States; Vaid, Jyotsna, Department of Psychological and Brain Sciences, Texas A&M University, College Station, Texas 77843, United States; Stanley, Christine A., Department of Educational Administration, Texas A&M University, College Station, Texas 77843, United States; Petitt, Becky, Office for Equity, Diversity, and Inclusion, University of California, San Diego, La Jolla, California 92093, United States; Yennello, Sherry, Cyclotron Institute, Texas A&M University, College Station, Texas 77843, United States / http://dx.doi.org/10.1021/bk-2019-1328.ch013
• Maximizing Mentoring: Enhancing the Impact of Mentoring Programs and Initiatives through the Center for the Advancement of Teaching and Faculty Development at Xavier University of Louisiana / Coston, Tiera S., Center for the Advancement of Teaching and Faculty Development, Xavier University of Louisiana, New Orleans, Louisiana 70125, United States; Payton-Stewart, Florastina, Department of Chemistry, Xavier University of Louisiana, New Orleans, Louisiana 70125, United States / http://dx.doi.org/10.1021/bk-2019-1328.ch014

• Mentors, Mentors Everywhere: Weaving Informal and Formal Mentoring into a Robust Chemical Sciences Mentoring Quilt / Grant, C. S. / http://dx.doi.org/10.1021/bk-2019-1328.ch015
• Using Technology To Foster Peer Mentoring Relationships: Development of a Virtual Peer Mentorship Model for Broadening Participation of Underrepresented Racial and Ethnic Minority Women in STEM / Wendt, Jillian L., University of the District of Columbia, Division of Education, Health, & Social Work, Washington, DC 20008, United States; Rockinson-Szapkiw, Amanda, University of Memphis, College of Education, Memphis, Tennessee 38152, United States; Conway, Ayana, Virginia State University, College of Education, Petersburg, Virginia 23806, United States / http://dx.doi.org/10.1021/bk-2019-1328.ch016
• Editors' Biographies / http://dx.doi.org/10.1021/bk-2019-1328.ot001

This work uses empirical studies to examine how institutions can better attract and support students from diverse backgrounds in STEM disciplines. Covering practical topics including recruitment and mentoring and inspiring examples of innovative course programming, this book showcases specific institutions with a track record for investing in the inclusion and success of underrepresented groups. This is a valuable resource for institutions seeking to implement effective strategies to acquire, train, mentor, and retain talented individuals from historically underrepresented groups.
(source: Nielsen Book Data)

• Intelligent Systems.- Machine Vision.- Communications.- Security.- e-Learning, e-Business.
• (source: Nielsen Book Data)

This book highlights the emerging field of intelligent computing and developing smart systems. It includes chapters discussing the outcome of challenging research related to distributed computing, smart machines and their security related research, and also covers next-generation communication techniques and the networking technologies that have the potential to build the future communication infrastructure. Bringing together computing, communications and other aspects of intelligent and smart computing, it contributes to developing a roadmap for future research on intelligent systems.
(source: Nielsen Book Data)

• Chapter 1. On the incorporation of interval-valued fuzzy sets into the Bousi-Prolog system: declarative semantics, implementation and applications (Clemente Rubio-Manzano).- Chapter 2. The existence of generalized inverses of fuzzy matrices (Miroslav Ciric).- Chapter 3. Gender Detection of Twitter Users based on Multiple Information Sources (Marco Vicente)
• Chapter 4. On the n-ary generalization of dual bonds (Ondrej Kridlo).- Chapter 5. Brouwer's ideas and intuitionistic fuzziness (Krassimir Atanassov).- Chapter 6. Nature inspired clustering - use Cases of krill herd algorithm and flower pollination algorithm (Piotr A. Kowalski).- Chapter 7. On the lower limit for possibilistic correlation coefficient with identical marginal possibility distributions (Istvan A. Harmati).- Chapter 8. A generalized net model for the coordination and synchronization of human and computer-based expert type decision support activities (Evdokia Sotirova).- Chapter 9. Wavelet analysis and structural entropy based intelligent classification method for combustion engine cylinder surfaces (Szilvia Nagy).
• (source: Nielsen Book Data)

This book presents recent research in the field of interaction between computational intelligence and mathematics. In the current technological age, we face the challenges of tackling very complex problems - in the usual sense, but also in the mathematical and theoretical computer science sense. However, even the most up-to-date results in mathematics, are unable to provide exact solutions of such problems, and no further technical advances will ever make it possible to find general and exact solutions. Constantly developing technologies (including social technologies) necessitate handling very complex problems. This has led to a search for acceptably "good" or precise solutions, which can be achieved by the combination of traditional mathematical techniques and computational intelligence tools, in order to solve the various problems emerging in many different areas to a satisfactory degree. Important funding programs, such as the European Commission's current framework programme for research and innovation - Horizon 2020 - are devoted to the development of new instruments to deal with the current challenges. Without doubt, research topics associated with the interactions between computational intelligence and traditional mathematics play a key role. Presenting contributions from engineers, scientists and mathematicians, this book offers a series of novel solutions for meaningful and real-world problems that connect those research areas.
(source: Nielsen Book Data)

• Elementary C programming
• Parallel computing using OpenMP
• Distributed programming and MPI
• GPU programming and CUDA
• GPU programming and OpenCL
• Applications

Based on a course developed by the author, Introduction to High Performance Scientific Computing introduces methods for adding parallelism to numerical methods for solving differential equations. It contains exercises and programming projects that facilitate learning as well as examples and discussions based on the C programming language, with additional comments for those already familiar with C++. The text provides an overview of concepts and algorithmic techniques for modern scientific computing and is divided into six self-contained parts that can be assembled in any order to create an introductory course using available computer hardware. Part I introduces the C programming language for those not already familiar with programming in a compiled language. Part II describes parallelism on shared memory architectures using OpenMP. Part III details parallelism on computer clusters using MPI for coordinating a computation. Part IV demonstrates the use of graphical programming units (GPUs) to solve problems using the CUDA language for NVIDIA graphics cards. Part V addresses programming on GPUs for non-NVIDIA graphics cards using the OpenCL framework. Finally, Part VI contains a brief discussion of numerical methods and applications, giving the reader an opportunity to test the methods on typical computing problems

• Introduction.- Part I: Preliminaries.- Foundations of artificial neural networks.- Part II: Mathematical foundations.- General foundations.- Foundations of dynamical systems theory.- Part III: Mathematical models of the neuron.- Models of the whole neuron.- Models of parts of the neuron.- Part IV: Mathematical models of the perceptron.- General model of the perceptron.- Linear perceptrons.- Weakly nonlinear perceptrons.- Nonlinear perceptrons.- Concluding remarks and comments. .
• (source: Nielsen Book Data)

This book describes models of the neuron and multilayer neural structures, with a particular focus on mathematical models. It also discusses electronic circuits used as models of the neuron and the synapse, and analyses the relations between the circuits and mathematical models in detail. The first part describes the biological foundations and provides a comprehensive overview of the artificial neural networks. The second part then presents mathematical foundations, reviewing elementary topics, as well as lesser-known problems such as topological conjugacy of dynamical systems and the shadowing property. The final two parts describe the models of the neuron, and the mathematical analysis of the properties of artificial multilayer neural networks. Combining biological, mathematical and electronic approaches, this multidisciplinary book it useful for the mathematicians interested in artificial neural networks and models of the neuron, for computer scientists interested in formal foundations of artificial neural networks, and for the biologists interested in mathematical and electronic models of neural structures and processes. .
(source: Nielsen Book Data)

• M−Polar Fuzzy Sets and m−Polar Fuzzy Graphs
• Certain Types of m−Polar Fuzzy Graphs
• Certain Metrics in m− Polar Fuzzy Graphs
• m−Polar Fuzzy Labeling Graphs
• Certain Dominations in m−Polar Fuzzy Graphs
• m−polar Fuzzy Concept Lattice
• m−Polar Fuzzy Graph Structures
• m−Polar Fuzzy Hypergraphs
• m−Polar Fuzzy Matroids.

This book provides readers with an introduction to m-polar fuzzy graphs and m-polar fuzzy hypergraphs, covering both theories and applications. A special emphasis is given to m-polar fuzzy graphs at the aim of filling a gap in the literature, namely the absence of a mathematical approach to analyze multi-index, multipolar, and multi-attribute data. The book describes metrics and labeling in m-polar graphs, m-polar fuzzy matroids. It also discusses in detail important applications in decision-making problems and imaging processing. The book is expected to stimulate the curiosity of mathematics, computer scientists, and social scientists alike, and to provide both students and researchers with the necessary knowledge to understand and apply m−polar fuzzy graph theory.

• 1. Introduction to Multimodal Scene Understanding Michael Ying Yang, Bodo Rosenhahn and Vittorio Murino
• 2. Multi-modal Deep Learning for Multi-sensory Data Fusion Asako Kanezaki, Ryohei Kuga, Yusuke Sugano and Yasuyuki Matsushita
• 3. Multi-Modal Semantic Segmentation: Fusion of RGB and Depth Data in Convolutional Neural Networks Zoltan Koppanyi, Dorota Iwaszczuk, Bing Zha, Can Jozef Saul, Charles K. Toth and Alper Yilmaz
• 4. Learning Convolutional Neural Networks for Object Detection with very little Training Data Christoph Reinders, Hanno Ackermann, Michael Ying Yang and Bodo Rosenhahn
• 5. Multi-modal Fusion Architectures for Pedestrian Detection Dayan Guan, Jiangxin Yang, Yanlong Cao, Michael Ying Yang and Yanpeng Cao
• 6. ThermalGAN: Multimodal Color-to-Thermal Image Translation for Person Re-Identification in Multispectral Dataset Vladimir A. Knyaz and Vladimir V. Kniaz
• 7. A Review and Quantitative Evaluation of Direct Visual-Inertia Odometry Lukas von Stumberg, Vladyslav Usenko and Daniel Cremers
• 8. Multimodal Localization for Embedded Systems: A Survey Imane Salhi, Martyna Poreba, Erwan Piriou, Valerie Gouet-Brunet and Maroun Ojail
• 9. Self-Supervised Learning from Web Data for Multimodal Retrieval Raul Gomez, Lluis Gomez, Jaume Gibert and Dimosthenis Karatzas
• 10. 3D Urban Scene Reconstruction and Interpretation from Multi-sensor Imagery Hai Huang, Andreas Kuhn, Mario Michelini, Matthais Schmitz and Helmut Mayer
• 11. Decision Fusion of Remote Sensing Data for Land Cover Classification Arnaud Le Bris, Nesrine Chehata, Walid Ouerghemmi, Cyril Wendl, Clement Mallet, Tristan Postadjian and Anne Puissant
• 12. Cross-modal learning by hallucinating missing modalities in RGB-D vision Nuno Garcia, Pietro Morerio and Vittorio Murino.
• (source: Nielsen Book Data)

Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections - for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful.
(source: Nielsen Book Data)

• 1. Introduction to Multimodal Scene Understanding Michael Ying Yang, Bodo Rosenhahn and Vittorio Murino
• 2. Multi-modal Deep Learning for Multi-sensory Data Fusion Asako Kanezaki, Ryohei Kuga, Yusuke Sugano and Yasuyuki Matsushita
• 3. Multi-Modal Semantic Segmentation: Fusion of RGB and Depth Data in Convolutional Neural Networks Zoltan Koppanyi, Dorota Iwaszczuk, Bing Zha, Can Jozef Saul, Charles K. Toth and Alper Yilmaz
• 4. Learning Convolutional Neural Networks for Object Detection with very little Training Data Christoph Reinders, Hanno Ackermann, Michael Ying Yang and Bodo Rosenhahn
• 5. Multi-modal Fusion Architectures for Pedestrian Detection Dayan Guan, Jiangxin Yang, Yanlong Cao, Michael Ying Yang and Yanpeng Cao
• 6. ThermalGAN: Multimodal Color-to-Thermal Image Translation for Person Re-Identification in Multispectral Dataset Vladimir A. Knyaz and Vladimir V. Kniaz
• 7. A Review and Quantitative Evaluation of Direct Visual-Inertia Odometry Lukas von Stumberg, Vladyslav Usenko and Daniel Cremers
• 8. Multimodal Localization for Embedded Systems: A Survey Imane Salhi, Martyna Poreba, Erwan Piriou, Valerie Gouet-Brunet and Maroun Ojail
• 9. Self-Supervised Learning from Web Data for Multimodal Retrieval Raul Gomez, Lluis Gomez, Jaume Gibert and Dimosthenis Karatzas
• 10. 3D Urban Scene Reconstruction and Interpretation from Multi-sensor Imagery Hai Huang, Andreas Kuhn, Mario Michelini, Matthais Schmitz and Helmut Mayer
• 11. Decision Fusion of Remote Sensing Data for Land Cover Classification Arnaud Le Bris, Nesrine Chehata, Walid Ouerghemmi, Cyril Wendl, Clement Mallet, Tristan Postadjian and Anne Puissant
• 12. Cross-modal learning by hallucinating missing modalities in RGB-D vision Nuno Garcia, Pietro Morerio and Vittorio Murino.
• (source: Nielsen Book Data)

Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections - for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful.
(source: Nielsen Book Data)

• Ccompartmental Switched Systems.- Markovian Jump Systems.- Boolean Networks.- Positive Delay Systems.
• (source: Nielsen Book Data)

This book presents high-quality original contributions on positive systems, including those with positivity in compartmental switched systems, Markovian jump systems, Boolean networks, interval observer design, fault detection, and delay systems. It comprises a selection of the best papers from POSTA 2018, the 6th International Conference on Positive Systems, which was held in Hangzhou, China, in August 2018. The POSTA conference series represents a targeted response to the growing need for research that reports on and critically discusses a wide range of topics concerning the theory and applications of positive systems. The book offers valuable insights for researchers in applied mathematics, control theory and their applications.
(source: Nielsen Book Data)

• Chapter 1. Contraction methods for correlation clustering: the order is important (Laszlo Aszalos).-
• Chapter 2. Optimisation of Preparedness and Response of Health services in major crises using the IMPRESS platform (Nina Dobrinkova).-
• Chapter 3. The new approach for dynamic optimization with variability constraints (Pawel Drag).-
• Chapter 4. Intercriteria Analisys of ACO Performance for Workforce Planning Problem (Olympia Roeva).-
• Chapter 5. Is Prufer Code encoding always a bad idea? (Hanno Hildmann).-
• Chapter 6. A model for wireless-access network topology and a PSO-based approach for its optimization (Hanno Hildmann).-
• Chapter 7. InterCriteria Analysis Approach for Comparison of Simple and Multi-population Genetic Algorithms Performance (Maria Angelova).-
• Chapter 8. Structure Optimization and Learning of Fuzzy Cognitive Map with the use of Evolutionary Algorithm and Graph Theory Metrics (Katarzyna Poczeta).-
• Chapter 9. Fuzziness in the Berth Allocation Problem (Flabio Gutierrez).-
• Chapter 10. Identifying Clusters in Spatial Data via Sequential Importance Sampling (Nishanthi Raveendran).-
• Chapter 11. Multiobjective Optimization Grover Adaptive Search (Benjamin Baran.-
• Chapter 12. Discovering Knowledge from Predominantly Repetitive Data by InterCriteria Analysis (Olympia Roeva).
• (source: Nielsen Book Data)

Our everyday lives are practically unthinkable without optimization. We constantly try to minimize our effort and to maximize the reward or progress achieved. Many real-world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. This volume presents a comprehensive collection of extended contributions from the 2017 Workshop on Computational Optimization. Presenting recent advances in computational optimization, it addresses important concrete applications, e.g. the modeling of physical processes, wildfire modeling, modeling processes in chemical engineering, workforce planning, wireless access network topology, parameter settings for controlling various processes, berth allocation, identification of homogeneous domains, and quantum computing. The book shows how to develop algorithms for them based on new intelligent methods like evolutionary computations, ant colony optimization, constrain programming and others.
(source: Nielsen Book Data)

It is essential for todayaEURO (TM)s students to learn about science and engineering in order to make sense of the world around them and participate as informed members of a democratic society. The skills and ways of thinking that are developed and honed through engaging in scientific and engineering endeavors can be used to engage with evidence in making personal decisions, to participate responsibly in civic life, and to improve and maintain the health of the environment, as well as to prepare for careers that use science and technology. The majority of Americans learn most of what they know about science and engineering as middle and high school students. During these years of rapid change for studentsaEURO (TM) knowledge, attitudes, and interests, they can be engaged in learning science and engineering through schoolwork that piques their curiosity about the phenomena around them in ways that are relevant to their local surroundings and to their culture. Many decades of education research provide strong evidence for effective practices in teaching and learning of science and engineering. One of the effective practices that helps students learn is to engage in science investigation and engineering design. Broad implementation of science investigation and engineering design and other evidence-based practices in middle and high schools can help address present-day and future national challenges, including broadening access to science and engineering for communities who have traditionally been underrepresented and improving studentsaEURO (TM) educational and life experiences. Science and Engineering for Grades 6-12: Investigation and Design at the Center revisits AmericaaEURO (TM)s Lab Report: Investigations in High School Science in order to consider its discussion of laboratory experiences and teacher and school readiness in an updated context. It considers how to engage todayaEURO (TM)s middle and high school students in doing science and engineering through an analysis of evidence and examples. This report provides guidance for teachers, administrators, creators of instructional resources, and leaders in teacher professional learning on how to support students as they make sense of phenomena, gather and analyze data/information, construct explanations and design solutions, and communicate reasoning to self and others during science investigation and engineering design. It also provides guidance to help educators get started with designing, implementing, and assessing investigation and design.
(source: Nielsen Book Data)

• Intelligent Computational Techniques for the Better World 2020.- Optimization of the cropping pattern using Cuckoo Search Technique.- A Review on Epileptic Seizure Detection and Prediction Using Soft Computing Techniques.- Deep learning architectures for Object Detection and Classification.- AI Powered Partially Parallelized Scheme for Multi Factor Authentication.- Performance Measures.
• (source: Nielsen Book Data)

This book is intended to provide a systematic overview of so-called smart techniques, such as nature-inspired algorithms, machine learning and metaheuristics. Despite their ubiquitous presence and widespread application to different scientific problems, such as searching, optimization and /or classification, a systematic study is missing in the current literature. Here, the editors collected a set of chapters on key topics, paying attention to provide an equal balance of theory and practice, and to outline similarities between the different techniques and applications. All in all, the book provides an unified view on the field on intelligent methods, with their current perspective and future challenges. .
(source: Nielsen Book Data)

• Preface
• Introduction
• PART.I. What Drove the Scientists to the Cold War?: In the Case of Physicists.
• Chapter 1: "Jealousy" and "Discord:" The Conflicts among Physicists during the War.
• Chapter 2. "Ideology" or "Harassment"? : "The Physics Conference" Unopened.
• PART II, Some Aspects of the Soviet Cold War Research and Developments.
• Chapter 3. "Foresight" or "Survival"? : Rocket Development and the Ministry of Armament
• Chapter 4. Plunder of Technology: Jet Plane Development and German Technology
• Chapter 5. "Concealed Rivalry": The Early Days of Computer Development.
• PART III. "Hope" and "Anxiety:" Soviet Science at the Dawn of the Nuclear Age.
• Chapter 6, Obninsk, 1955: The World's First Nuclear Power Plant and "The Atomic Diplomacy" by Soviet Scientists.
• Chapter 7. "A Double-edged Sword:" Radiation Studies and the Normalization of Biological Sciences.
• Chapter 8. Anna Vasil'evna Kozlova (1906-19080): The Fate of the Data on the Casualties of Hiroshima, Nagasaki, and Bikini.
• Conclusion
• Index.
• (source: Nielsen Book Data)

The 1950s were a vital time in the history of science. In accordance with the intensification of the Cold War, many scientific talents were mobilized to several military-related research and development projects not only in the United States, but also in the Soviet Union. Contrary to the expectation of General Leslie Groves, a leader of the Manhattan Project, the Soviet Union succeeded in their nuclear weapon development in a very short time. And then, by the end of the decade, mankind reached the dawn of the Atomic Age proper with the beginning of the operation of the world's first civil nuclear power plant in Obninsk in 1954. The risky and costly developments of new weapons such as rockets, jet warplanes, and computers were achieved by the Soviet Union in a very short time after World War in spite of the heavy economic damage caused by the battles with German troops in Soviet territory. Why were such a great number of scientific talents mobilized to various Soviet Cold War research and development projects? What were the true natures, and real consequences of the rushed Cold War projects? How did Soviet scientists approach the nuclear age? Thanks to the study of formerly classified Soviet archives, a more nuanced view of Soviet society has become possible. To resolve the above-mentioned questions, Ichikawa analyses the complicated interactions among various factors, including the indigenous contradictions in the historical development of science in the Soviet Union; conflicts among the related interest groups; relationships with the political leadership and the military, the role of ideology and others.
(source: Nielsen Book Data)

• 1. Introduction
• Part I. Hypothesis Testing: 2. Binary hypothesis testing
• 3. Multiple hypothesis testing
• 4. Composite hypothesis testing
• 5. Signal detection
• 6. Convex statistical distances
• 7. Performance bounds for hypothesis testing
• 8. Large deviations and error exponents for hypothesis testing
• 9. Sequential and quickest change detection
• 10. Detection of random processes
• Part II. Estimation: 11. Bayesian parameter estimation
• 12. Minimum variance unbiased estimation
• 13. Information inequality and Cramer-Rao lower bound
• 14. Maximum likelihood estimation
• 15. Signal estimation.
• (source: Nielsen Book Data)

This book is a mathematically accessible and up-to-date introduction to the tools needed to address modern inference problems in engineering and data science, ideal for graduate students taking courses on statistical inference and detection and estimation, and an invaluable reference for researchers and professionals. With a wealth of illustrations and examples to explain the key features of the theory and to connect with real-world applications, additional material to explore more advanced concepts, and numerous end-of-chapter problems to test the reader's knowledge, this textbook is the 'go-to' guide for learning about the core principles of statistical inference and its application in engineering and data science. The password-protected solutions manual and the image gallery from the book are available online.
(source: Nielsen Book Data)

• "Switching" and "Persistence" Redefined: The Complexity of STEM Persistence.- The Significance of Interest and Choice.- High School to College: Student Preparation and Transition.- Learning Experiences in Gateway Courses and their Consequences.- Learning Experiences throughout STEM Majors.- Teaching Practices: Observed and Evaluated.- The Processes of Switching and Relocation.- Factors Beyond College that Shape Career Choices.- What Enables Persistence?.- Summary and Conclusions.
• (source: Nielsen Book Data)

Talking about Leaving Revisited discusses findings from a five-year study that explores the extent, nature, and contributory causes of field-switching both from and among "STEM" majors, and what enables persistence to graduation. The book reflects on what has and has not changed since publication of Talking about Leaving: Why Undergraduates Leave the Sciences (Elaine Seymour & Nancy M. Hewitt, Westview Press, 1997). With the editors' guidance, the authors of each chapter collaborate to address key questions, drawing on findings from each related study source: national and institutional data, interviews with faculty and students, structured observations and student assessments of teaching methods in STEM gateway courses. Pitched to a wide audience, engaging in style, and richly illustrated in the interviewees' own words, this book affords the most comprehensive explanatory account to date of persistence, relocation and loss in undergraduate sciences. Comprehensively addresses the causes of loss from undergraduate STEM majors-an issue of ongoing national concern. Presents critical research relevant for nationwide STEM education reform efforts. Explores the reasons why talented undergraduates abandon STEM majors. Dispels popular causal myths about why students choose to leave STEM majors. This volume is based upon work supported by the Alfred P. Sloan Foundation Award No. 2012-6-05 and the National Science Foundation Award No. DUE 1224637.
(source: Nielsen Book Data)

• List of Figures
• List of Contributors
• Forward: Meeting Methodological Challenges
• [Maria Pilar Jimenez-Aleixandre]
• 1. Framing Issues of theory and methods for the study of science and engineering education
• [Gregory Kelly & Judith Green]
• 2. Making science and gender in kindergarten
• [Alicia McDyre]
• 3. Multimodal analysis of decision making in elementary engineering
• [Carmen Vanderhoof]
• 4. Translanguaging about socioscientific issues in middle school science
• [Peter Licona]
• 5. Learning through improvement from failure in elementary engineering design projects
• [Matt Johnson]
• 6. An Interactional Ethnography Perspective to Analyze Informal Formative Assessments (IFAs) to Build Epistemic and Conceptual Coherence in Science Learning
• [Asli Sezen-Barrie & Rachel Mulvaney]
• 7. Emotional discourse as constructed in environmental science
• [Beth Hufnagel]
• 8. Discourse of professional pedagogical vision in teacher education
• [Arzu Tanis Ozcelik & Scott McDonald]
• 9. Analyzing the generative nature of science teachers' professional development discourse
• [Amy Ricketts]
• 10. Commentary: Constructing transparency in designing and conducting multilayered research in science and engineering education: Potentials and challenges of ethnographically informed discourse-based methodologies
• [Audra Skukauskaite]
• 11. Commentary: Research methods for the advancement of possibility knowledge and practice in science and engineering education
• [Kristiina Kumpulainen]
• Appendix A: How we look at discourse: Definitions of sociolinguistic units
• [Judith Green & Gregory J. Kelly].
• (source: Nielsen Book Data)

Introducing original methods for integrating sociocultural and discourse studies into science and engineering education, this book provides a much-needed framework for how to conduct qualitative research in this field. The three dimensions of learning identified in the Next Generation Science Standards (NGSS) create a need for research methods that examine the sociocultural components of science education. With cutting-edge studies and examples consistent with the NGSS, this book offers comprehensive research methods for integrating discourse and sociocultural practices in science and engineering education and provides key tools for applying this framework for students, pre-service teachers, scholars, and researchers.
(source: Nielsen Book Data)

• A proposal of hybrid fuzzy clustering algorithm with application in fault diagnosis.- Solving a Fuzzy Tourist Trip Design Problem with Clustered Points of Interest.- Fully Fuzzy Linear Programming Model For the Berth Allocation Problem with Two Quays.- Ideal reference method with linguistic labels: a comparison with LTOPSIS.- Fuzzy cognitive maps for evaluating software usability.- Ideal reference method with linguistic labels: a comparison with LTOPSIS.- A proposal of hybrid fuzzy clustering algorithm with application in fault diagnosis.
• (source: Nielsen Book Data)

This book offers a timely overview of fuzzy and rough set theories and methods. Based on selected contributions presented at the International Symposium on Fuzzy and Rough Sets, ISFUROS 2017, held in Varadero, Cuba, on October 24-26, 2017, the book also covers related approaches, such as hybrid rough-fuzzy sets and hybrid fuzzy-rough sets and granular computing, as well as a number of applications, from big data analytics, to business intelligence, security, robotics, logistics, wireless sensor networks and many more. It is intended as a source of inspiration for PhD students and researchers in the field, fostering not only new ideas but also collaboration between young researchers and institutions and established ones.
(source: Nielsen Book Data)

• Foreword Christopher Emdin List of Tables Acknowledgments
• 1 Vignettes 2 Introducing the Purpose and the Ethnographe 3 The School and Student Context 4 The Students and Their Journeys 5 Engaging and Persisting in STEM: Shaping the Transition to College 6 Tying the Roots Together: Conclusions, Implications, and Future Directions for Building stem Trajectories
• References.
• (source: Nielsen Book Data)

In Without a Margin for Error, the author chronicles the journeys of young adults in an under-served urban community who are new to the English language into STEM (science, technology, engineering, and mathematics-related) fields from high school through college. He distills lessons, themes, and policy recommendations from the trails blazed by these students toward altering the status quo around college access and STEM success for often-marginalized but highly resilient young adults with much to contribute to their new nation, their communities, and the world. While drawing on a critical ethnography of over three dozen inspiring young adults, seven students are chronicled in greater depth to bring to life crucial conversations for redefining college readiness, access, and success in STEM fields.
(source: Nielsen Book Data)

• Advanced Computing in Engineering.- Computer Supported Construction Management.- Life-Cycle Design Support.- Monitoring and Control Algorithms in Engineering.- BIM and Engineering Ontologies.
• (source: Nielsen Book Data)

This double volume set ( LNAI 10863-10864) constitutes the refereed proceedings of the 25th International Workshop, EG-ICE 2018, held in Lausanne, Switzerland, in June 2018. The 58 papers presented in this volume were carefully reviewed and selected from 108 submissions. The papers are organized in topical sections on Advanced Computing in Engineering, Computer Supported Construction Management, Life-Cycle Design Support, Monitoring and Control Algorithms in Engineering, and BIM and Engineering Ontologies.
(source: Nielsen Book Data)

• Identification of the Conjugate Pair to Estimating Object Distance: An Application of the Ant Colony Algorithm.-Design of Palm Acupuncture Points Indicator
• Low-rank Representation and Locality-constrained Regression for Robust Low-Resolution Face Recognition
• Face Recognition Benchmark with ID Photos
• Scene Relighting using a Single Reference Image through Material Constrained Layer Decomposition
• Applying Adaptive Actor-critic Learning to Human Upper Lime Lifting Motion
• A Demand-based Allocation Mechanism for Virtual Machine
• A Joint Hierarchy Model for Action Recognition Using Kinect
• QoS-Based Medical Program Evolution
• An Improved 3D Surface Reconstruction Method based on Three Wavelength Phase Shift Profilometry
• The Research on the Lung Tumor Imaging based on the Electrical Impedance Tomography
• Combining CNN and MRF for Road Detection
• The Increasing of Discrimination Accuracy of Waxed Apples based on Hyperspectral Imaging Optimized by Spectral Correlation Analysis
• A Diffeomorphic Demons Approach to Statistical Shape Modeling.

This book highlights selected papers presented at the 2nd International Symposium on Artificial Intelligence and Robotics 2017 (ISAIR2017), held in Nakamura Centenary Memorial Hall, Kitakyushu, Japan on November 25-26, 2017. Today, the integration of artificial intelligence and robotic technologies has become a topic of growing interest for both researchers and developers from academic fields and industries worldwide, and artificial intelligence is poised to become the main approach pursued in next-generation robotics research. The rapidly growing number of artificial intelligence algorithms and big data solutions has significantly extended the number of potential applications for robotic technologies. However, it also poses new challenges for the artificial intelligence community. The aim of this symposium is to provide a platform for young researchers to share the latest scientific achievements in this field, which are discussed in these proceedings.

• Identification of the Conjugate Pair to Estimating Object Distance: An Application of the Ant Colony Algorithm.-Design of Palm Acupuncture Points Indicator.- Low-rank Representation and Locality-constrained Regression for Robust Low-Resolution Face Recognition.- Face Recognition Benchmark with ID Photos.- Scene Relighting using a Single Reference Image through Material Constrained Layer Decomposition.- Applying Adaptive Actor-critic Learning to Human Upper Lime Lifting Motion.- A Demand-based Allocation Mechanism for Virtual Machine.- A Joint Hierarchy Model for Action Recognition Using Kinect.- QoS-Based Medical Program Evolution.- An Improved 3D Surface Reconstruction Method based on Three Wavelength Phase Shift Profilometry.- The Research on the Lung Tumor Imaging based on the Electrical Impedance Tomography.- Combining CNN and MRF for Road Detection.- The Increasing of Discrimination Accuracy of Waxed Apples based on Hyperspectral Imaging Optimized by Spectral Correlation Analysis.- A Diffeomorphic Demons Approach to Statistical Shape Modeling.
• (source: Nielsen Book Data)

This book highlights selected papers presented at the 2nd International Symposium on Artificial Intelligence and Robotics 2017 (ISAIR2017), held in Nakamura Centenary Memorial Hall, Kitakyushu, Japan on November 25-26, 2017. Today, the integration of artificial intelligence and robotic technologies has become a topic of growing interest for both researchers and developers from academic fields and industries worldwide, and artificial intelligence is poised to become the main approach pursued in next-generation robotics research. The rapidly growing number of artificial intelligence algorithms and big data solutions has significantly extended the number of potential applications for robotic technologies. However, it also poses new challenges for the artificial intelligence community. The aim of this symposium is to provide a platform for young researchers to share the latest scientific achievements in this field, which are discussed in these proceedings.
(source: Nielsen Book Data)

• Introduction to Science and Engineering Principles for the Development of Bioinspired Materials / Muhammad Wajid Ullah, Zhijun Shi, Sehrish Manan, Guang Yang
• Biofabrication. Biotemplating Principles / Cordt Zollfrank, Daniel Opdenbosch
• Tubular Tissue Engineering Based on Microfluidics / Lixue Tang, Wenfu Zheng, Xingyu Jiang
• Construction of Three-Dimensional Tissues with Capillary Networks by Coating of Nanometer- or Micrometer-Sized Film on Cell Surfaces / Michiya Matsusaki, Akihiro Nishiguchi, Chun-Yen Liu, Mitsuru Akashi
• Three-dimensional Biofabrication on Nematic Ordered Cellulose Templates / Tetsuo Kondo
• Preparation and Application of Biomimetic Materials Inspired by Mussel Adhesive Proteins / Heng Shen, Zhenchao Qian, Ning Zhao, Jian Xu
• Self-assembly of Polylactic Acid-based Amphiphilic Block Copolymers and Their Application in the Biomedical Field / Lin Xiao, Lixia Huang, Li Liu, Guang Yang
• Biomacromolecules. Electroconductive Bioscaffolds for 2D and 3D Cell Culture / Zhijun Shi, Lin Mao, Muhammad Wajid Ullah, Sixiang Li, Li Wang, Sanming Hu, Guang Yang
• Starch and Plant Storage Polysaccharides / Francisco Vilaplana, Wei Zou, Robert G Gilbert
• Conformational Properties of Polysaccharide Derivatives / Ken Terao, Takahiro Sato
• Silk Proteins / Lallepak Lamboni, Tiatou Souho, Amarachi Rosemary Osi, Guang Yang
• Polypeptides Synthesized by Ring-opening Polymerization of N-Carboxyanhydrides / Yuan Yao, Yongfeng Zhou, Deyue Yan
• Preparation of Gradient Polymeric Structures and Their Biological Applications / Tao Du, Feng Zhou, Shutao Wang
• Biomaterials. Bioinspired Materials and Structures / Tom Masselter, Georg Bold, Marc Thielen, Olga Speck, Thomas Speck
• Thermal- and Photo-deformable Liquid Crystal Polymers and Bioinspired Movements / Yuyun Liu, Jiu-an Lv, Yanlei Yu
• Tuning Mechanical Properties of Protein Hydrogels / Xiao-Wei Wang, Dong Liu, Guang-Zhong Yin, Wen-Bin Zhang
• Dendritic Polymer Micelles for Drug Delivery / Mosa Alsehli, Mario Gauthier
• Bone-inspired Biomaterials / Frank A Müller
• Research Progress in Biomimetic Materials for Human Dental Caries Restoration / Yazi Wang, Fengwei Liu, Eric Habib, Ruili Wang, Xiaoze Jiang, XX Zhu, Meifang Zhu
• Index
• Supplemental Images.

An authoritative introduction to the science and engineering of bioinspired materials Bioinspired Materials Science and Engineering offers a comprehensive view of the science and engineering of bioinspired materials and includes a discussion of biofabrication approaches and applications of bioinspired materials as they are fed back to nature in the guise of biomaterials. The authors also review some biological compounds and shows how they can be useful in the engineering of bioinspired materials. With contributions from noted experts in the field, this comprehensive resource considers biofabrication, biomacromolecules, and biomaterials. The authors illustrate the bioinspiration process from materials design and conception to application of bioinspired materials. In addition, the text presents the multidisciplinary aspect of the concept, and contains a typical example of how knowledge is acquired from nature, and how in turn this information contributes to biological sciences, with an accent on biomedical applications. This important resource: Offers an introduction to the science and engineering principles for the development of bioinspired materials Includes a summary of recent developments on biotemplated formation of inorganic materials using natural templates Illustrates the fabrication of 3D-tumor invasion models and their potential application in drug assessments Explores electroactive hydrogels based on natural polymers Contains information on turning mechanical properties of protein hydrogels for biomedical applications Written for chemists, biologists, physicists, and engineers, Bioinspired Materials Science and Engineering contains an indispensible resource for an understanding of bioinspired materials science and engineering. .
(source: Nielsen Book Data)

• Introduction to Science and Engineering Principles for the Development of Bioinspired Materials / Muhammad Wajid Ullah, Zhijun Shi, Sehrish Manan, Guang Yang
• Biofabrication. Biotemplating Principles / Cordt Zollfrank, Daniel Opdenbosch
• Tubular Tissue Engineering Based on Microfluidics / Lixue Tang, Wenfu Zheng, Xingyu Jiang
• Construction of Three-Dimensional Tissues with Capillary Networks by Coating of Nanometer- or Micrometer-Sized Film on Cell Surfaces / Michiya Matsusaki, Akihiro Nishiguchi, Chun-Yen Liu, Mitsuru Akashi
• Three-dimensional Biofabrication on Nematic Ordered Cellulose Templates / Tetsuo Kondo
• Preparation and Application of Biomimetic Materials Inspired by Mussel Adhesive Proteins / Heng Shen, Zhenchao Qian, Ning Zhao, Jian Xu
• Self-assembly of Polylactic Acid-based Amphiphilic Block Copolymers and Their Application in the Biomedical Field / Lin Xiao, Lixia Huang, Li Liu, Guang Yang
• Biomacromolecules. Electroconductive Bioscaffolds for 2D and 3D Cell Culture / Zhijun Shi, Lin Mao, Muhammad Wajid Ullah, Sixiang Li, Li Wang, Sanming Hu, Guang Yang
• Starch and Plant Storage Polysaccharides / Francisco Vilaplana, Wei Zou, Robert G Gilbert
• Conformational Properties of Polysaccharide Derivatives / Ken Terao, Takahiro Sato
• Silk Proteins / Lallepak Lamboni, Tiatou Souho, Amarachi Rosemary Osi, Guang Yang
• Polypeptides Synthesized by Ring-opening Polymerization of N-Carboxyanhydrides / Yuan Yao, Yongfeng Zhou, Deyue Yan
• Preparation of Gradient Polymeric Structures and Their Biological Applications / Tao Du, Feng Zhou, Shutao Wang
• Biomaterials. Bioinspired Materials and Structures / Tom Masselter, Georg Bold, Marc Thielen, Olga Speck, Thomas Speck
• Thermal- and Photo-deformable Liquid Crystal Polymers and Bioinspired Movements / Yuyun Liu, Jiu-an Lv, Yanlei Yu
• Tuning Mechanical Properties of Protein Hydrogels / Xiao-Wei Wang, Dong Liu, Guang-Zhong Yin, Wen-Bin Zhang
• Dendritic Polymer Micelles for Drug Delivery / Mosa Alsehli, Mario Gauthier
• Bone-inspired Biomaterials / Frank A Müller
• Research Progress in Biomimetic Materials for Human Dental Caries Restoration / Yazi Wang, Fengwei Liu, Eric Habib, Ruili Wang, Xiaoze Jiang, XX Zhu, Meifang Zhu
• Index
• Supplemental Images.

An authoritative introduction to the science and engineering of bioinspired materials Bioinspired Materials Science and Engineering offers a comprehensive view of the science and engineering of bioinspired materials and includes a discussion of biofabrication approaches and applications of bioinspired materials as they are fed back to nature in the guise of biomaterials. The authors also review some biological compounds and shows how they can be useful in the engineering of bioinspired materials. With contributions from noted experts in the field, this comprehensive resource considers biofabrication, biomacromolecules, and biomaterials. The authors illustrate the bioinspiration process from materials design and conception to application of bioinspired materials. In addition, the text presents the multidisciplinary aspect of the concept, and contains a typical example of how knowledge is acquired from nature, and how in turn this information contributes to biological sciences, with an accent on biomedical applications. This important resource: Offers an introduction to the science and engineering principles for the development of bioinspired materials Includes a summary of recent developments on biotemplated formation of inorganic materials using natural templates Illustrates the fabrication of 3D-tumor invasion models and their potential application in drug assessments Explores electroactive hydrogels based on natural polymers Contains information on turning mechanical properties of protein hydrogels for biomedical applications Written for chemists, biologists, physicists, and engineers, Bioinspired Materials Science and Engineering contains an indispensible resource for an understanding of bioinspired materials science and engineering. .
(source: Nielsen Book Data)

• Foreword
• Preface
• About the authors
• About our approach
• Connections to standards
• What is STEM?
• What constitutes a STEM program of study?
• It's about the question : matching the how to the why
• Is integration enough?
• Teaching StEMT through inquiry and the 5E instructional model
• Correlation to a framework for K-12 science education
• Earth and space sciences StEMT lessons. To infinity and beyond ; Oh, how the garden grows ; Separation anxiety ; The human factor
• Life sciences StEMT lessons. Cell-fie ; Itsy, bitsy spiders ; Gobble, gobble, toil and trouble ; Designing the super explore ; It's a what?
• Physical sciences StEMT lessons. Is it air or wind? ; Aircraft catapult ; Keepin' it cool! ; The pitch in the wave ; Mirror, mirror, on the wall
• Conclusion
• Appendix A: Claims, evidence, reasoning rubric
• Appendix B: Constellations
• Appendix C: Moon phases model sheet.

Sure, there are lots of cool STEM activities you can use in class. But do they really help your students learn science? This book shows you how to take lessons you're already familiar with and, through small changes, do what the title says: Design STEM lessons that are actually meaningful for teaching and learning science. You can also make sure your STEM lessons contain the content students need to learn. The book's foundation is a conceptual framework that keeps science front and center, showing you how to embed engineering, technology, and science applications in your lessons-similar to how you would embed literacy skills in your classwork. To make it easy to use this conceptual framework, Designing Meaningful STEM Lessons provides 13 ready-to-use lessons in physical science, life science, and Earth and space science. True to the authors' promise to be both relevant and exciting, the lessons have titles such as "Cell-fie" and "Aircraft Catapult." All correlate with A Framework for K-12 Science Education, take a constructivist approach, and operate within the 5E instructional model. By presenting STEM as a "process and not a thing, " Designing Meaningful STEM Lessons helps you bring STEM learning to life in your classroom, easily and effectively.
(source: Nielsen Book Data)