Author: Stuart Hamilton
Publisher: IWA Publishing
ISBN: 1780404700
Category : Science
Languages : en
Pages : 106
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Book Description
Ageing infrastructure and declining water resources are major concerns with a growing global population. Controlling water loss has therefore become a priority for water utilities around the world. In order to improve efficiencies, water utilities need to apply good practices in leak detection. Leak Detection: Technology and Implementation assists water utilities with the development and implementation of leak detection programs. Leak detection and repair is one of the components of controlling water loss. In addition, techniques are discussed within this book and relevant case studies are presented. This book provides useful and practical information on leakage issues.
Author: Amit Kumar
Publisher: Springer Nature
ISBN: 981157961X
Category : Technology & Engineering
Languages : en
Pages : 1561
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Book Description
This book is a collection of research papers and articles presented at the 3rd International Conference on Communications and Cyber-Physical Engineering (ICCCE 2020), held on 1-2 February 2020 at CMR Engineering College, Hyderabad, Telangana, India. Discussing the latest developments in voice and data communication engineering, cyber-physical systems, network science, communication software, image and multimedia processing research and applications, as well as communication technologies and other related technologies, it includes contributions from both academia and industry. This book is a valuable resource for scientists, research scholars and PG students working to formulate their research ideas and find the future directions in these areas. Further, it may serve as a reference work to understand the latest engineering and technologies used by practicing engineers in the field of communication engineering.
Author: Hemachandran K
Publisher: CRC Press
ISBN: 1000569586
Category : Business & Economics
Languages : en
Pages : 147
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Book Description
This book introduces Bayesian reasoning and Gaussian processes into machine learning applications. Bayesian methods are applied in many areas, such as game development, decision making, and drug discovery. It is very effective for machine learning algorithms in handling missing data and extracting information from small datasets. Bayesian Reasoning and Gaussian Processes for Machine Learning Applications uses a statistical background to understand continuous distributions and how learning can be viewed from a probabilistic framework. The chapters progress into such machine learning topics as belief network and Bayesian reinforcement learning, which is followed by Gaussian process introduction, classification, regression, covariance, and performance analysis of Gaussian processes with other models. FEATURES Contains recent advancements in machine learning Highlights applications of machine learning algorithms Offers both quantitative and qualitative research Includes numerous case studies This book is aimed at graduates, researchers, and professionals in the field of data science and machine learning.
Author: J. N. Reddy
Publisher: Springer Nature
ISBN: 9811933030
Category : Architecture
Languages : en
Pages : 1023
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Book Description
This book presents articles from the Second International Conference on Sustainable Civil Engineering and Architecture, held on 30 October 2021 in Ho Chi Minh City, Vietnam. The conference brings together international experts from both academia and industry to share their knowledge, expertise, to facilitate collaboration and improve cooperation in the field. The book highlights the latest advances in sustainable architecture and civil engineering, covering topics such as offshore structures, structural engineering, construction materials, and architecture.
Author: Panagiotis Tsakalides
Publisher: CRC Press
ISBN: 1351986171
Category : Technology & Engineering
Languages : en
Pages : 348
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Book Description
The effects of climate change, rapid urbanization, and aging infrastructure challenge water policymakers to confront a radical paradigm shift in water resources utilization. Recent advances in sensing, networking, processing, and control have provided the means for sustainable solutions in water management, and their implementation in water infrastructures is collectively referred to as "smart water grids." Smart water grids depend upon cyber-physical system principles to effectively respond to issues regarding the scalability and reliability of dynamic and inaccessible environments. As such, unique smart water grid issues associated with front-end signal processing, communication, control, and data analysis must be jointly addressed, while sophisticated techniques for data analytics must be introduced into cyber-physical systems research. This book provides a thorough description of the best practices for designing and implementing cyber-physical systems that are tailored to different aspects of smart water grids. It is organized into three distinct, yet complementary areas, namely: the theory behind water-oriented cyber-physical systems with an emphasis on front-end sensing and processing, communication technologies, and learning techniques over water data; the applications and emerging topics of cyber-physical systems for water urban infrastructures, including real-life deployments, modern control tools, and economic aspects for smart water grids; and the applications and emerging topics across natural environments, emphasizing the evolution of fresh water resources. The structured discussion yields a rich, comprehensive body of knowledge on this emerging topic of research and engineering. As water issues intensify on a global scale, this book offers an algorithmic and practical toolkit for intermediate and advanced readers as well as professionals and researchers who are active in, or interested in, learning more about smart water grids. Key Features: Emphasizes the multidisciplinary nature of this emerging topic, covering both theoretical and practical aspects of this area while providing insights on existing deployments, which can serve as design examples for new applications. Explores how modern signal processing and machine learning techniques can contribute and enrich the potential of smart water grids, well beyond conventional closed-loop control techniques. Highlights complementary aspects that will help shape the future of smart water grids, such as consumption awareness, economic aspects, and control tools in industrial water treatment as well as the impact of climate change on fresh water resources. Enables the reader to better understand this emerging topic, investing in current state-of-the-art and future technological roadmaps for smart water grids.
Author: S. Smys
Publisher: Springer Nature
ISBN: 9811637288
Category : Technology & Engineering
Languages : en
Pages : 889
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Book Description
This book is a collection of peer-reviewed best-selected research papers presented at 4th International Conference on Computer Networks and Inventive Communication Technologies (ICCNCT 2021). The book covers new results in theory, methodology, and applications of computer networks and data communications. It includes original papers on computer networks, network protocols and wireless networks, data communication technologies, and network security. The proceedings of this conference are a valuable resource, dealing with both the important core and the specialized issues in the areas of next-generation wireless network design, control, and management, as well as in the areas of protection, assurance, and trust in information security practice. It is a reference for researchers, instructors, students, scientists, engineers, managers, and industry practitioners for advanced work in the area.
Author: Allam Hamdan
Publisher: Springer Nature
ISBN: 3031621069
Category :
Languages : en
Pages : 1112
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Book Description
Author: M. Farley
Publisher: IWA Publishing
ISBN: 1900222116
Category : Science
Languages : en
Pages : 297
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Book Description
This is a best practice manual for addressing water losses in water distribution networks worldwide. Systems and methodologies are presented for improving water loss and leakage management in a range of networks, from systems with a well-developed infrastructure to those in developing countries where the network may need to be upgraded. The key feature of the manual is a diagnostic approach to develop a water loss strategy - using the appropriate tools to find the right solutions - which can be applied to any network. The methods of assessing the scale and volume of water loss are outlined, together with the procedures for setting up leakage monitoring and detection systems. As well as real losses (leakage) procedures for addressing apparent losses, by introducing regulatory and customer metering policies are explained. Suggestions are made for demand management and water conservation programmes, to complement the water loss strategy. Recommendations are made for training workshops and operation and maintenance programmes to ensure skills transfer and sustainability. The manual is illustrated throughout with case studies. Losses in Water Distribution Networks will appeal to a wide range of practitioners responsible for designing and managing a water loss strategy. These include consultants, operations managers, engineers, technicians and operational staff. It will also be a valuable reference for senior managers and decision makers, who may require an overview of the principles and procedures for controlling losses. The book will also be suitable as a source document for courses in Water Engineering, Resource Management and Environmental Management.
Author: Francois Chollet
Publisher: Simon and Schuster
ISBN: 1638352046
Category : Computers
Languages : en
Pages : 597
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Book Description
Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance
Author: N. Subhashini
Publisher: Springer Nature
ISBN: 9811983380
Category : Technology & Engineering
Languages : en
Pages : 589
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Book Description
This book presents select proceedings of the Virtual International Conference on Futuristic Communication and Network Technologies (VICFCNT 2021). It covers various domains in communication engineering and networking technologies. This volume comprises recent research in areas like cyber-physical systems, acoustics, speech & video signal processing, and IoT. This book is a collated work of academicians, researchers, and industry personnel from the international arena. This book will be useful for researchers, professionals, and engineers working in the core areas of electronics and communication.
