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.
Ubiquitous in today's consumer-driven society, embedded systems use microprocessors that are hidden in our everyday products and designed to perform specific tasks. Effective use of these embedded systems requires engineers to be proficient in all phases of this effort, from planning, design, and analysis to manufacturing and marketing.Taking a sys
Reinforcement Learning for Cyber-Physical Systems: with Cybersecurity Case Studies was inspired by recent developments in the fields of reinforcement learning (RL) and cyber-physical systems (CPSs). Rooted in behavioral psychology, RL is one of the primary strands of machine learning. Different from other machine learning algorithms, such as supervised learning and unsupervised learning, the key feature of RL is its unique learning paradigm, i.e., trial-and-error. Combined with the deep neural networks, deep RL become so powerful that many complicated systems can be automatically managed by AI agents at a superhuman level. On the other hand, CPSs are envisioned to revolutionize our society in the near future. Such examples include the emerging smart buildings, intelligent transportation, and electric grids. However, the conventional hand-programming controller in CPSs could neither handle the increasing complexity of the system, nor automatically adapt itself to new situations that it has never encountered before. The problem of how to apply the existing deep RL algorithms, or develop new RL algorithms to enable the real-time adaptive CPSs, remains open. This book aims to establish a linkage between the two domains by systematically introducing RL foundations and algorithms, each supported by one or a few state-of-the-art CPS examples to help readers understand the intuition and usefulness of RL techniques. Features Introduces reinforcement learning, including advanced topics in RL Applies reinforcement learning to cyber-physical systems and cybersecurity Contains state-of-the-art examples and exercises in each chapter Provides two cybersecurity case studies Reinforcement Learning for Cyber-Physical Systems with Cybersecurity Case Studies is an ideal text for graduate students or junior/senior undergraduates in the fields of science, engineering, computer science, or applied mathematics. It would also prove useful to researchers and engineers interested in cybersecurity, RL, and CPS. The only background knowledge required to appreciate the book is a basic knowledge of calculus and probability theory.
Mobile Cloud Computing: Models, Implementation, and Security provides a comprehensive introduction to mobile cloud computing, including key concepts, models, and relevant applications. The book focuses on novel and advanced algorithms, as well as mobile app development. The book begins with an overview of mobile cloud computing concepts, models, and service deployments, as well as specific cloud service models. It continues with the basic mechanisms and principles of mobile computing, as well as virtualization techniques. The book also introduces mobile cloud computing architecture, design, key techniques, and challenges. The second part of the book covers optimizations of data processing and storage in mobile clouds, including performance and green clouds. The crucial optimization algorithm in mobile cloud computing is also explored, along with big data and service computing. Security issues in mobile cloud computing are covered in-depth, including a brief introduction to security and privacy issues and threats, as well as privacy protection techniques in mobile systems. The last part of the book features the integration of service-oriented architecture with mobile cloud computing. It discusses web service specifications related to implementations of mobile cloud computing. The book not only presents critical concepts in mobile cloud systems, but also drives readers to deeper research, through open discussion questions. Practical case studies are also included. Suitable for graduate students and professionals, this book provides a detailed and timely overview of mobile cloud computing for a broad range of readers.
Many high-performance DSP processors employ multi-bank on-chip memory to improve performance and energy consumption. This architectural feature supports higher memory bandwidth by allowing multiple data memory accesses to be executed in parallel. However, making effective use of multi-bank memory remains difficult, considering the combined effect of performance and energy requirement. In this project, our focus is to study the assignment and scheduling problem that minimizes the total energy while satisfying performance requirements. Our approach has several major contributions: First, we study the combined effects of energy-saving and performance of memory in a systematic approach. Second, we exploit the energy saving of memory with memory type assignment. Third, data locality has been improved by using variable partition.
Reinforcement Learning for Cyber-Physical Systems: with Cybersecurity Case Studies was inspired by recent developments in the fields of reinforcement learning (RL) and cyber-physical systems (CPSs). Rooted in behavioral psychology, RL is one of the primary strands of machine learning. Different from other machine learning algorithms, such as supervised learning and unsupervised learning, the key feature of RL is its unique learning paradigm, i.e., trial-and-error. Combined with the deep neural networks, deep RL become so powerful that many complicated systems can be automatically managed by AI agents at a superhuman level. On the other hand, CPSs are envisioned to revolutionize our society in the near future. Such examples include the emerging smart buildings, intelligent transportation, and electric grids. However, the conventional hand-programming controller in CPSs could neither handle the increasing complexity of the system, nor automatically adapt itself to new situations that it has never encountered before. The problem of how to apply the existing deep RL algorithms, or develop new RL algorithms to enable the real-time adaptive CPSs, remains open. This book aims to establish a linkage between the two domains by systematically introducing RL foundations and algorithms, each supported by one or a few state-of-the-art CPS examples to help readers understand the intuition and usefulness of RL techniques. Features Introduces reinforcement learning, including advanced topics in RL Applies reinforcement learning to cyber-physical systems and cybersecurity Contains state-of-the-art examples and exercises in each chapter Provides two cybersecurity case studies Reinforcement Learning for Cyber-Physical Systems with Cybersecurity Case Studies is an ideal text for graduate students or junior/senior undergraduates in the fields of science, engineering, computer science, or applied mathematics. It would also prove useful to researchers and engineers interested in cybersecurity, RL, and CPS. The only background knowledge required to appreciate the book is a basic knowledge of calculus and probability theory.
Mobile Cloud Computing: Models, Implementation, and Security provides a comprehensive introduction to mobile cloud computing, including key concepts, models, and relevant applications. The book focuses on novel and advanced algorithms, as well as mobile app development. The book begins with an overview of mobile cloud computing concepts, models, and service deployments, as well as specific cloud service models. It continues with the basic mechanisms and principles of mobile computing, as well as virtualization techniques. The book also introduces mobile cloud computing architecture, design, key techniques, and challenges. The second part of the book covers optimizations of data processing and storage in mobile clouds, including performance and green clouds. The crucial optimization algorithm in mobile cloud computing is also explored, along with big data and service computing. Security issues in mobile cloud computing are covered in-depth, including a brief introduction to security and privacy issues and threats, as well as privacy protection techniques in mobile systems. The last part of the book features the integration of service-oriented architecture with mobile cloud computing. It discusses web service specifications related to implementations of mobile cloud computing. The book not only presents critical concepts in mobile cloud systems, but also drives readers to deeper research, through open discussion questions. Practical case studies are also included. Suitable for graduate students and professionals, this book provides a detailed and timely overview of mobile cloud computing for a broad range of readers.
Ubiquitous in today's consumer-driven society, embedded systems use microprocessors that are hidden in our everyday products and designed to perform specific tasks. Effective use of these embedded systems requires engineers to be proficient in all phases of this effort, from planning, design, and analysis to manufacturing and marketing.Taking a sys
Mobile Applications Development with Android: Technologies and Algorithms presents advanced techniques for mobile app development, and addresses recent developments in mobile technologies and wireless networks. The book covers advanced algorithms, embedded systems, novel mobile app architecture, and mobile cloud computing paradigms. Divided into three sections, the book explores three major dimensions in the current mobile app development domain. The first section describes mobile app design and development skills, including a quick start on using Java to run an Android application on a real phone. It also introduces 2D graphics and UI design, as well as multimedia in Android mobile apps. The second part of the book delves into advanced mobile app optimization, including an overview of mobile embedded systems and architecture. Data storage in Android, mobile optimization by dynamic programming, and mobile optimization by loop scheduling are also covered. The last section of the book looks at emerging technologies, including mobile cloud computing, advanced techniques using Big Data, and mobile Big Data storage. About the Authors Meikang Qiu is an Associate Professor of Computer Science at Pace University, and an adjunct professor at Columbia University. He is an IEEE/ACM Senior Member, as well as Chair of the IEEE STC (Special Technical Community) on Smart Computing. He is an Associate Editor of a dozen of journals including IEEE Transactions on Computers and IEEE Transactions on Cloud Computing. He has published 320+ peer-reviewed journal/conference papers and won 10+ Best Paper Awards. Wenyun Dai is pursuing his PhD at Pace University. His research interests include high performance computing, mobile data privacy, resource management optimization, cloud computing, and mobile networking. His paper about mobile app privacy has been published in IEEE Transactions on Computers. Keke Gai is pursuing his PhD at Pace University. He has published over 60 peer-reviewed journal or conference papers, and has received three IEEE Best Paper Awards. His research interests include cloud computing, cyber security, combinatorial optimization, business process modeling, enterprise architecture, and Internet computing. .
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.
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.