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Leadership in Music Technology Education: Philosophy, Praxis, and Pedagogy
by Daniel WalzerLeadership in Music Technology Education examines the pedagogical, sociocultural, and philosophical issues that affect curriculum, research, and decision-making in music technology in higher education. This book considers a range of cutting-edge topics, including the impact of the COVID-19 pandemic, professional development concepts, partnerships between higher education and the creative and cultural industries, and the effects technology has on sustainability. Drawing on Leadership theories, including Transformational, Situational, Servant, and Social Change Model Theory, the book puts forward a new model, Creative Industry Leadership, which considers the sociocultural aspects of Music Technology Education, and interrogates biased ideologies that limit opportunities for a broad range of learners and practitioners in education and beyond. Additionally, Leadership in Music Technology Education examines educators’ informal leadership capacities during the COVID-19 pandemic and how inclusive pedagogy expands the creative boundaries of teaching, learning, and music-making for all. Leadership in Music Technology Education is crucial reading for instructors teaching audio engineering and music technology, as well as researchers in education, music pedagogy and related fields. This is also a valuable read for anyone with an interest in music technology and its many potentialities.
Leading in Analytics: The Seven Critical Tasks for Executives to Master in the Age of Big Data (Wiley and SAS Business Series)
by Joseph A. CazierA step-by-step guide for business leaders who need to manage successful big data projects Leading in Analytics: The Critical Tasks for Executives to Master in the Age of Big Data takes you through the entire process of guiding an analytics initiative from inception to execution. You’ll learn which aspects of the project to pay attention to, the right questions to ask, and how to keep the project team focused on its mission to produce relevant and valuable project. As an executive, you can’t control every aspect of the process. But if you focus on high-impact factors that you can control, you can ensure an effective outcome. This book describes those factors and offers practical insight on how to get them right. Drawn from best-practice research in the field of analytics, the Manageable Tasks described in this book are specific to the goal of implementing big data tools at an enterprise level. A dream team of analytics and business experts have contributed their knowledge to show you how to choose the right business problem to address, put together the right team, gather the right data, select the right tools, and execute your strategic plan to produce an actionable result. Become an analytics-savvy executive with this valuable book. Ensure the success of analytics initiatives, maximize ROI, and draw value from big data Learn to define success and failure in analytics and big data projects Set your organization up for analytics success by identifying problems that have big data solutions Bring together the people, the tools, and the strategies that are right for the jobBy learning to pay attention to critical tasks in every analytics project, non-technical executives and strategic planners can guide their organizations to measurable results.
Leading in Analytics: The Seven Critical Tasks for Executives to Master in the Age of Big Data (Wiley and SAS Business Series)
by Joseph A. CazierA step-by-step guide for business leaders who need to manage successful big data projects Leading in Analytics: The Critical Tasks for Executives to Master in the Age of Big Data takes you through the entire process of guiding an analytics initiative from inception to execution. You’ll learn which aspects of the project to pay attention to, the right questions to ask, and how to keep the project team focused on its mission to produce relevant and valuable project. As an executive, you can’t control every aspect of the process. But if you focus on high-impact factors that you can control, you can ensure an effective outcome. This book describes those factors and offers practical insight on how to get them right. Drawn from best-practice research in the field of analytics, the Manageable Tasks described in this book are specific to the goal of implementing big data tools at an enterprise level. A dream team of analytics and business experts have contributed their knowledge to show you how to choose the right business problem to address, put together the right team, gather the right data, select the right tools, and execute your strategic plan to produce an actionable result. Become an analytics-savvy executive with this valuable book. Ensure the success of analytics initiatives, maximize ROI, and draw value from big data Learn to define success and failure in analytics and big data projects Set your organization up for analytics success by identifying problems that have big data solutions Bring together the people, the tools, and the strategies that are right for the jobBy learning to pay attention to critical tasks in every analytics project, non-technical executives and strategic planners can guide their organizations to measurable results.
Lean Game Development: Apply Lean Frameworks to the Process of Game Development
by Julia Naomi Rosenfield BoeiraMaster Lean UX and Lean Startup techniques to improve your agile game development experience beyond Scrum. This updated version of the book focuses on applying lean and agile methodologies to the game development process and features improved examples, applied techniques, and a whole new section explaining how to test a game in Unity with CI. You'll see how to define a minimum viable product (MVP) for games with Lean Canvas, allowing customers to iterate over it and collect feedback for improvement at every cycle. All of these are achieved while still using standard Agile techniques. The first part of the book explains the ideation process of a game and how lean methodologies allow developers, especially small studios, to avoid scope creep. Next, it it provides guidance on creating MVPs and using player feedback to iterate and improve games. The book then discusses continual improvement (CI) methods. A crucial part of CI is generation of Lean Canvas. Lean Game Development, Second Edition shows you how to iterate until you develop a game that satisfies developers, gamers, and your studio's financial goals.What You'll LearnStudy lean and agile methodologies to enhance the game development process Find out how to improve the way game productions define value and iterate over itApply development strategies to enrich the game development processWho This Book Is ForPeople from all sectors of the gaming industry will find the book useful in planning their project in a more iterative way, unloading the management burden on the development process and collecting feedback to improve the game content as early as possible.
Learn Programming with C: An Easy Step-by-Step Self-Practice Book for Learning C
by Sazzad M.S. Imran Md Atiqur AhadAuthored by two standout professors in the field of Computer Science and Technology with extensive experience in instructing, Learn Programming with C: An Easy Step-by Step Self-Practice Book for Learning C is a comprehensive and accessible guide to programming with one of the most popular languages. Meticulously illustrated with figures and examples, this book is a comprehensive guide to writing, editing, and executing C programs on different operating systems and platforms, as well as how to embed C programs into other applications and how to create one’s own library. A variety of questions and exercises are included in each chapter to test the readers’ knowledge. Written for the novice C programmer, especially undergraduate and graduate students, this book’s line-by-line explanation of code and succinct writing style makes it an excellent companion for classroom teaching, learning, and programming labs.
Learn Programming with C: An Easy Step-by-Step Self-Practice Book for Learning C
by Sazzad M.S. Imran Md Atiqur AhadAuthored by two standout professors in the field of Computer Science and Technology with extensive experience in instructing, Learn Programming with C: An Easy Step-by Step Self-Practice Book for Learning C is a comprehensive and accessible guide to programming with one of the most popular languages. Meticulously illustrated with figures and examples, this book is a comprehensive guide to writing, editing, and executing C programs on different operating systems and platforms, as well as how to embed C programs into other applications and how to create one’s own library. A variety of questions and exercises are included in each chapter to test the readers’ knowledge. Written for the novice C programmer, especially undergraduate and graduate students, this book’s line-by-line explanation of code and succinct writing style makes it an excellent companion for classroom teaching, learning, and programming labs.
Learn R: As a Language (Chapman & Hall/CRC The R Series)
by Pedro J. AphaloLearning a computer language like R can be either frustrating, fun or boring. Having fun requires challenges that wake up the learner’s curiosity but also provide an emotional reward for overcoming them. The book is designed so that it includes smaller and bigger challenges, in what I call playgrounds, in the hope that all readers will enjoy their path to R fluency. Fluency in the use of a language is a skill that is acquired through practice and exploration. For students and professionals in the biological sciences, humanities and many applied fields, recognizing the parallels between R and natural languages should help them feel at home with R. The approach I use is similar to that of a travel guide, encouraging exploration and describing the available alternatives and how to reach them. The intention is to guide the reader through the R landscape of 2024 and beyond.What is new in the second edition? Text expanded by more than 25% to include additional R features and gentler and more detailed explanations Contains 24 new diagrams and flowcharts, seven new tables, and revised text and code examples for clarity All three indexes were expanded, and answers to 28 frequently asked questions added What will you find in this book? Programming concepts explained as they apply to current R Emphasis on the role of abstractions in programming Few prescriptive rules—mostly the author’s preferences together with alternatives Presentation of the R language emphasizing the “R way of doing things” Tutoring for “programming in the small” using scripts for data analysis Explanation of the differences between R proper and extensions for data wrangling The grammar of graphics is described as a language for the construction of data visualisations Examples of data exchange between R and the foreign world using common file formats Coaching to become an independent R user, capable of writing original scripts and solving future challenges
Learn R: As a Language (Chapman & Hall/CRC The R Series)
by Pedro J. AphaloLearning a computer language like R can be either frustrating, fun or boring. Having fun requires challenges that wake up the learner’s curiosity but also provide an emotional reward for overcoming them. The book is designed so that it includes smaller and bigger challenges, in what I call playgrounds, in the hope that all readers will enjoy their path to R fluency. Fluency in the use of a language is a skill that is acquired through practice and exploration. For students and professionals in the biological sciences, humanities and many applied fields, recognizing the parallels between R and natural languages should help them feel at home with R. The approach I use is similar to that of a travel guide, encouraging exploration and describing the available alternatives and how to reach them. The intention is to guide the reader through the R landscape of 2024 and beyond.What is new in the second edition? Text expanded by more than 25% to include additional R features and gentler and more detailed explanations Contains 24 new diagrams and flowcharts, seven new tables, and revised text and code examples for clarity All three indexes were expanded, and answers to 28 frequently asked questions added What will you find in this book? Programming concepts explained as they apply to current R Emphasis on the role of abstractions in programming Few prescriptive rules—mostly the author’s preferences together with alternatives Presentation of the R language emphasizing the “R way of doing things” Tutoring for “programming in the small” using scripts for data analysis Explanation of the differences between R proper and extensions for data wrangling The grammar of graphics is described as a language for the construction of data visualisations Examples of data exchange between R and the foreign world using common file formats Coaching to become an independent R user, capable of writing original scripts and solving future challenges
Learning Advanced Python by Studying Open Source Projects (Chapman & Hall/CRC The Python Series)
by Rongpeng LiThis book is one of its own kind. It is not an encyclopedia or a hands-on tutorial that traps readers in the tutorial hell. It is a distillation of just one common Python user’s learning experience. The experience is packaged with exceptional teaching techniques, careful dependence unraveling and, most importantly, passion. Learning Advanced Python by Studying Open Source Projects helps readers overcome the difficulty in their day-to-day tasks and seek insights from solutions in famous open source projects. Different from a technical manual, this book mixes the technical knowledge, real-world applications and more theoretical content, providing readers with a practical and engaging approach to learning Python. Throughout this book, readers will learn how to write Python code that is efficient, readable and maintainable, covering key topics such as data structures, algorithms, object-oriented programming and more. The author’s passion for Python shines through in this book, making it an enjoyable and inspiring read for both beginners and experienced programmers.
Learning Advanced Python by Studying Open Source Projects (Chapman & Hall/CRC The Python Series)
by Rongpeng LiThis book is one of its own kind. It is not an encyclopedia or a hands-on tutorial that traps readers in the tutorial hell. It is a distillation of just one common Python user’s learning experience. The experience is packaged with exceptional teaching techniques, careful dependence unraveling and, most importantly, passion. Learning Advanced Python by Studying Open Source Projects helps readers overcome the difficulty in their day-to-day tasks and seek insights from solutions in famous open source projects. Different from a technical manual, this book mixes the technical knowledge, real-world applications and more theoretical content, providing readers with a practical and engaging approach to learning Python. Throughout this book, readers will learn how to write Python code that is efficient, readable and maintainable, covering key topics such as data structures, algorithms, object-oriented programming and more. The author’s passion for Python shines through in this book, making it an enjoyable and inspiring read for both beginners and experienced programmers.
Learning Analytics Enhanced Online Learning Support
by Shuang LiOffering the latest developments in online education in the era of big data, this book explores theories, technologies, and practices in the field of data-driven online learning support services using learning analytics. This book is divided into five chapters. Chapter 1 reflects and reconstructs the connotation of learning support against the backdrop of education reform, the rise of learning analytics, and the upgrading of the demand for learning services in the new era. Chapter 2 presents a P-K-DSE-E model of online learner characteristics and discusses measurement and data representation methods for learner characteristics based on it. Chapters 3–5 focus on the three types of learning support that are closely related to learning performance and satisfaction, including the promotion of social learning, electronic learning assessment based on the learning process, and personalized tutoring and support. This book innovatively develops the concept, theory, and practical methods of student support services in distance education traditional practices in the new era and provides valuable exploration of data-driven personalized learning service methods and technologies in the era of artificial intelligence through rich examples. This book will be essential reading for students and scholars of distance and online education, educational technology, and audiovisual education.
Learning Analytics Enhanced Online Learning Support
by Shuang LiOffering the latest developments in online education in the era of big data, this book explores theories, technologies, and practices in the field of data-driven online learning support services using learning analytics. This book is divided into five chapters. Chapter 1 reflects and reconstructs the connotation of learning support against the backdrop of education reform, the rise of learning analytics, and the upgrading of the demand for learning services in the new era. Chapter 2 presents a P-K-DSE-E model of online learner characteristics and discusses measurement and data representation methods for learner characteristics based on it. Chapters 3–5 focus on the three types of learning support that are closely related to learning performance and satisfaction, including the promotion of social learning, electronic learning assessment based on the learning process, and personalized tutoring and support. This book innovatively develops the concept, theory, and practical methods of student support services in distance education traditional practices in the new era and provides valuable exploration of data-driven personalized learning service methods and technologies in the era of artificial intelligence through rich examples. This book will be essential reading for students and scholars of distance and online education, educational technology, and audiovisual education.
Learning and Relearning Equipment Complexity: Achieving Safety in Engineering Complex Systems (Developments in Quality and Safety)
by Sasho AndonovWith industrial systems becoming ever more mechanized and reliant on advanced technology, the complexity of equipment, especially in risky industries, is increasing on a daily basis. A thorough understanding of operations and providing safety for these complex systems has become a firm requirement for many. This book offers the knowledge required by safety professionals to provide and maintain the safety of engineering complex systems. Through a scientific and engineering approach to designing, implementing, operating, and maintaining complex systems, Learning and Relearning Equipment Complexity: Achieving Safety in Engineering Complex Systems details the need for more engineering and scientific knowledge to understand and maintain their safety. It gives clear explanations of reasons for a system’s complexity, based on control systems and non-linear dynamics. In addition, the book addresses the necessary changes in the approach and the procedures for the safety assessment of engineering complex systems. The reader will develop a thorough understanding of what complex systems are, why they are complex, and how they are utilized. This book will appeal to any safety professional tasked with complex systems. This extends to professionals in risky industries such as aviation, nuclear power, chemicals, railway and transport, and pharmaceuticals.
Learning and Relearning Equipment Complexity: Achieving Safety in Engineering Complex Systems (Developments in Quality and Safety)
by Sasho AndonovWith industrial systems becoming ever more mechanized and reliant on advanced technology, the complexity of equipment, especially in risky industries, is increasing on a daily basis. A thorough understanding of operations and providing safety for these complex systems has become a firm requirement for many. This book offers the knowledge required by safety professionals to provide and maintain the safety of engineering complex systems. Through a scientific and engineering approach to designing, implementing, operating, and maintaining complex systems, Learning and Relearning Equipment Complexity: Achieving Safety in Engineering Complex Systems details the need for more engineering and scientific knowledge to understand and maintain their safety. It gives clear explanations of reasons for a system’s complexity, based on control systems and non-linear dynamics. In addition, the book addresses the necessary changes in the approach and the procedures for the safety assessment of engineering complex systems. The reader will develop a thorough understanding of what complex systems are, why they are complex, and how they are utilized. This book will appeal to any safety professional tasked with complex systems. This extends to professionals in risky industries such as aviation, nuclear power, chemicals, railway and transport, and pharmaceuticals.
Learning Automata and Their Applications to Intelligent Systems
by JunQi Zhang MengChu ZhouComprehensive guide on learning automata, introducing two variants to accelerate convergence and computational update speed Learning Automata and Their Applications to Intelligent Systems provides a comprehensive guide on learning automata from the perspective of principles, algorithms, improvement directions, and applications. The text introduces two variants to accelerate the convergence speed and computational update speed, respectively; these two examples demonstrate how to design new learning automata for a specific field from the aspect of algorithm design to give full play to the advantage of learning automata. As noisy optimization problems exist widely in various intelligent systems, this book elaborates on how to employ learning automata to solve noisy optimization problems from the perspective of algorithm design and application. The existing and most representative applications of learning automata include classification, clustering, game, knapsack, network, optimization, ranking, and scheduling. They are well-discussed. Future research directions to promote an intelligent system are suggested. Written by two highly qualified academics with significant experience in the field, Learning Automata and Their Applications to Intelligent Systems covers such topics as: Mathematical analysis of the behavior of learning automata, along with suitable learning algorithms Two application-oriented learning automata: one to discover and track spatiotemporal event patterns, and the other to solve stochastic searching on a line Demonstrations of two pioneering variants of Optimal Computing Budge Allocation (OCBA) methods and how to combine learning automata with ordinal optimization How to achieve significantly faster convergence and higher accuracy than classical pursuit schemes via lower computational complexity of updating the state probabilityA timely text in a rapidly developing field, Learning Automata and Their Applications to Intelligent Systems is an essential resource for researchers in machine learning, engineering, operation, and management. The book is also highly suitable for graduate level courses on machine learning, soft computing, reinforcement learning and stochastic optimization.
Learning Automata and Their Applications to Intelligent Systems
by JunQi Zhang MengChu ZhouComprehensive guide on learning automata, introducing two variants to accelerate convergence and computational update speed Learning Automata and Their Applications to Intelligent Systems provides a comprehensive guide on learning automata from the perspective of principles, algorithms, improvement directions, and applications. The text introduces two variants to accelerate the convergence speed and computational update speed, respectively; these two examples demonstrate how to design new learning automata for a specific field from the aspect of algorithm design to give full play to the advantage of learning automata. As noisy optimization problems exist widely in various intelligent systems, this book elaborates on how to employ learning automata to solve noisy optimization problems from the perspective of algorithm design and application. The existing and most representative applications of learning automata include classification, clustering, game, knapsack, network, optimization, ranking, and scheduling. They are well-discussed. Future research directions to promote an intelligent system are suggested. Written by two highly qualified academics with significant experience in the field, Learning Automata and Their Applications to Intelligent Systems covers such topics as: Mathematical analysis of the behavior of learning automata, along with suitable learning algorithms Two application-oriented learning automata: one to discover and track spatiotemporal event patterns, and the other to solve stochastic searching on a line Demonstrations of two pioneering variants of Optimal Computing Budge Allocation (OCBA) methods and how to combine learning automata with ordinal optimization How to achieve significantly faster convergence and higher accuracy than classical pursuit schemes via lower computational complexity of updating the state probabilityA timely text in a rapidly developing field, Learning Automata and Their Applications to Intelligent Systems is an essential resource for researchers in machine learning, engineering, operation, and management. The book is also highly suitable for graduate level courses on machine learning, soft computing, reinforcement learning and stochastic optimization.
A Learning Community of Reflective Teachers: From Whispers to Resonance
by Neeraja RaghavanTeachers possess a wealth of untapped wisdom and valuable experience. Whether it’s in matter of educational policy, curriculum development or textbook selection, teachers carry a trove of information and insights to share. Traditionally, teacher development has been driven by administrators of schools, and it often takes the form of a ‘mentor’ teaching the staff of a school. But what happens when teachers across different locations collaborate and learn together? This volume documents such an initiative, sparked off by the Covid-19 pandemic, which brought people together online. It underscores the power of teachers debating, discussing, and learning from each other. Based on an Indian experience, the book addresses a range of issues teachers and educators face across the world — encompassing pedagogy, classroom management, school culture and teacher development. A unique story of community building and teacher education, this book also contains key outcomes and insights which take us through their action research projects and showcases a model of teacher development that can be adopted by interested readers. Above all, it brings out the crying need for a teacher’s voice to be heard — for far too long, teachers have been mere implementers of decisions taken by policy makers or managements of schools. By means of networking communities such as the one described in this book, the transformation of teachers going from whispers to resonance is greatly amplified. An important intervention in the domain of teacher development, this volume will be of great interest to students, researchers and practitioners of education, teacher education, and sociology of education. It will also be useful for teacher trainees, academicians, teacher educators, policymakers, schoolteachers, curriculum developers, teacher training institutes, and universities offering teacher education programs.
A Learning Community of Reflective Teachers: From Whispers to Resonance
by Neeraja RaghavanTeachers possess a wealth of untapped wisdom and valuable experience. Whether it’s in matter of educational policy, curriculum development or textbook selection, teachers carry a trove of information and insights to share. Traditionally, teacher development has been driven by administrators of schools, and it often takes the form of a ‘mentor’ teaching the staff of a school. But what happens when teachers across different locations collaborate and learn together? This volume documents such an initiative, sparked off by the Covid-19 pandemic, which brought people together online. It underscores the power of teachers debating, discussing, and learning from each other. Based on an Indian experience, the book addresses a range of issues teachers and educators face across the world — encompassing pedagogy, classroom management, school culture and teacher development. A unique story of community building and teacher education, this book also contains key outcomes and insights which take us through their action research projects and showcases a model of teacher development that can be adopted by interested readers. Above all, it brings out the crying need for a teacher’s voice to be heard — for far too long, teachers have been mere implementers of decisions taken by policy makers or managements of schools. By means of networking communities such as the one described in this book, the transformation of teachers going from whispers to resonance is greatly amplified. An important intervention in the domain of teacher development, this volume will be of great interest to students, researchers and practitioners of education, teacher education, and sociology of education. It will also be useful for teacher trainees, academicians, teacher educators, policymakers, schoolteachers, curriculum developers, teacher training institutes, and universities offering teacher education programs.
Learning Continuous Integration with Jenkins: An end-to-end guide to creating operational, secure, resilient, and cost-effective CI/CD processes
by Nikhil PathaniaIntegrate Jenkins, Kubernetes, and more on cloud into a robust, GitOps-driven CI/CD system, leveraging JCasC, IaC, and AI for a streamlined software delivery processKey FeaturesFollow the construction of a Jenkins CI/CD pipeline start to finish through a real-world exampleConstruct a continuous deployment (CD) pipeline in Jenkins using GitOps principles and integration with Argo CDCraft and optimize your CI pipeline code with ChatGPT and GitHub CopilotPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThis updated edition of Learning Continuous Integration with Jenkins is your one-stop guide to implementing CI/CD with Jenkins, addressing crucial technologies such as cloud computing, containerization, Infrastructure as Code, and GitOps. Tailored to both beginners and seasoned developers, the book provides a practical path to mastering a production-grade, secure, resilient, and cost-effective CI/CD setup. Starting with a detailed introduction to the fundamental principles of CI, this book systematically takes you through setting up a CI environment using Jenkins and other pivotal DevOps tools within the CI/CD ecosystem. You’ll learn to write pipeline code with AI assistance and craft your own CI pipeline. With the help of hands-on tutorials, you’ll gain a profound understanding of the CI process and Jenkins’ robust capabilities. Additionally, the book teaches you how to expand your CI pipeline with automated testing and deployment, setting the stage for continuous deployment. To help you through the complete software delivery process, this book also covers methods to ensure that your CI/CD setup is maintainable across teams, secure, and performs optimally. By the end of the book, you’ll have become an expert in implementing and optimizing CI/CD setups across diverse teams.What you will learnUnderstand CI with the Golden Circle theoryDeploy Jenkins on the cloud using Helm charts and Jenkins Configuration as Code (JCasC)Implement optimal security practices to ensure Jenkins operates securelyExtend Jenkins for CI by integrating with SonarQube, GitHub, and ArtifactoryScale Jenkins using containers and the cloud for optimal performanceMaster Jenkins declarative syntax to enrich your pipeline coding vocabularyEnhance security and improve pipeline code within your CI/CD process using best practicesWho this book is forThis book is for a diverse audience, from university students studying Agile software development to seasoned developers, testers, release engineers, and project managers. If you’re already using Jenkins for CI, this book will assist you in elevating your projects to CD. Whether you’re new to the concepts of Agile, CI, and CD, or a DevOps engineer seeking advanced insights into JCasC, IaC, and Azure, this book will equip you with the tools to harness Jenkins for improved productivity and streamlined deliveries in the cloud.
Learning Professional Python: Volume 2: Advanced (Chapman & Hall/CRC The Python Series)
by Usharani Bhimavarapu Jude D. HemanthVolume 2 of Learning Professional Python is a resource for students who want to learn Python even if they don’t have any programming knowledge and for teachers who want a comprehensive introduction to Python to use with their students. This book helps the students achieve their dream job in the IT Industry and teaches the students in an easy, understandable manner while strengthening coding skills. Learning Professional Python: Volume 2 Objectives Become familiar with the features of Python programming language Introduce the object-oriented programming concepts Discover how to write Python code by following the object-oriented programming concepts Become comfortable with concepts such as classes, objects, inheritance, dynamic dispatch, interfaces, and packages Learn the Python generics and collections Develop exception handling and the multithreaded applications Design graphical user interface (GUI) applications
Learning Professional Python: Volume 1: The Basics (Chapman & Hall/CRC The Python Series)
by Usharani Bhimavarapu Jude D. HemanthVolume 1 of Learning Professional Python is a resource for students who want to learn Python even if they don’t have any programming knowledge and for teachers who want a comprehensive introduction to Python to use with their students. This book helps the students achieve their dream job in IT Industry and teaches the students in an easy, understandable manner while strengthening coding skills. Learning Professional Python: Volume 1 Objectives Become familiar with the features of Python programming language Introduce the object-oriented programming concepts Discover how to write Python code by following the object-oriented programming concepts Become comfortable with concepts such as classes, objects, inheritance, dynamic dispatch, interfaces, and packages Learn the Python generics and collections Develop exception handling and the multithreaded applications Design graphical user interface (GUI) applications
Learning Professional Python: Volume 1: The Basics (Chapman & Hall/CRC The Python Series)
by Usharani Bhimavarapu Jude D. HemanthVolume 1 of Learning Professional Python is a resource for students who want to learn Python even if they don’t have any programming knowledge and for teachers who want a comprehensive introduction to Python to use with their students. This book helps the students achieve their dream job in IT Industry and teaches the students in an easy, understandable manner while strengthening coding skills. Learning Professional Python: Volume 1 Objectives Become familiar with the features of Python programming language Introduce the object-oriented programming concepts Discover how to write Python code by following the object-oriented programming concepts Become comfortable with concepts such as classes, objects, inheritance, dynamic dispatch, interfaces, and packages Learn the Python generics and collections Develop exception handling and the multithreaded applications Design graphical user interface (GUI) applications
Learning Professional Python: Volume 2: Advanced (Chapman & Hall/CRC The Python Series)
by Usharani Bhimavarapu Jude D. HemanthVolume 2 of Learning Professional Python is a resource for students who want to learn Python even if they don’t have any programming knowledge and for teachers who want a comprehensive introduction to Python to use with their students. This book helps the students achieve their dream job in the IT Industry and teaches the students in an easy, understandable manner while strengthening coding skills. Learning Professional Python: Volume 2 Objectives Become familiar with the features of Python programming language Introduce the object-oriented programming concepts Discover how to write Python code by following the object-oriented programming concepts Become comfortable with concepts such as classes, objects, inheritance, dynamic dispatch, interfaces, and packages Learn the Python generics and collections Develop exception handling and the multithreaded applications Design graphical user interface (GUI) applications
Learning Techniques for the Internet of Things
by Praveen Kumar Donta Abhishek Hazra Lauri LovénThe book is structured into thirteen chapters; each comes with its own dedicated contributions and future research directions. Chapter 1 introduces IoT and the use of Edge computing, particularly cloud computing, and mobile edge computing. This chapter also mentions the use of edge computing in various real-time applications such as healthcare, manufacturing, agriculture, and transportation. Chapter 2 motivates mathematical modeling for federated learning systems with respect to IoT and its applications. Further Chapter 3 extends the discussion of federated learning for IoT, which has emerged as a privacy-preserving distributed machine learning approach. Chapter 4 provides various machine learning techniques in Industrial IoT to deliver rapid and accurate data analysis, essential for enhancing production quality, sustainability, and safety. Chapter discusses the potential role of data-driven technologies, such as Artificial Intelligence, Machine Learning, and Deep Learning, focuses on their integration with IoT communication technologies. Chapter 6 presents the requirements and challenges to realize IoT deployments in smart cities, including sensing infrastructure, Artificial Intelligence, computing platforms, and enabling communications technologies such as 5G networks. To highlight these challenges in practice, the chapter also presents a real-world case study of a city-scale deployment of IoT air quality monitoring within Helsinki city. Chapter 7 uses digital twins within smart cities to enhance economic progress and facilitate prompt decision-making regarding situational awareness. Chapter 8 provides insights into using Multi-Objective reinforcement learning in future IoT networks, especially for an efficient decision-making system. Chapter 9 offers a comprehensive review of intelligent inference approaches, with a specific emphasis on reducing inference time and minimizing transmitted bandwidth between IoT devices and the cloud. Chapter 10 summarizes the applications of deep learning models in various IoT fields. This chapter also presents an in-depth study of these techniques to examine new horizons of applications of deep learning models in different areas of IoT. Chapter 11 explores the integration of Quantum Key Distribution (QKD) into IoT systems. It delves into the potential benefits, challenges, and practical considerations of incorporating QKD into IoT networks. In chapter 12, a comprehensive overview regarding the current state of quantum IoT in the context of smart healthcare is presented, along with its applications, benefits, challenges, and prospects for the future. Chapter 13 proposes a blockchain-based architecture for securing and managing IoT data in intelligent transport systems, offering advantages like immutability, decentralization, and enhanced security.
Learning Technology for Education Challenges: 12th International Workshop, LTEC 2024, Kaohsiung, Taiwan, July 29 – August 1, 2024, Proceedings (Communications in Computer and Information Science #2082)
by Lorna Uden Dario LiberonaThis book constitutes the refereed proceedings of the 12th International Conference on Learning Technology for Education Challenges, LTEC 2024, held in Kaohsiung, Taiwan, during July 29–August 1, 2024. The 26 full papers included in this book were carefully reviewed and selected from 51 submissions. They were organized in topical sections as follows: serious games and virtual learning environments; learning practices and methodologies; learning technologies; learning processes and culture; e-learning and performance, and artificial intelligence and learning.