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 English | 2022 | ISBN: 1107040663 | 657 pages | PDF | 33.35 MB Get up to speed with the fundamentals of electronic sensor design with this comprehensive guide, and discover powerful techniques to reduce the overall design timeline for your specific applications. Includes a step-by-step introduction to a generalized information-centric approach for designing electronic sensors, demonstrating universally applicable practical approaches to speed up the design process. Features detailed coverage of all the tools necessary for effective characterization and organization of the design process, improving overall process efficiency. Provides a coherent and rigorous theoretical framework for understanding the fundamentals of sensor design, to encourage an intuitive understanding of sensor design requirements. Emphasising an integrated interdisciplinary approach throughout, this is an essential tool for professional engineers and graduate students keen to improve their understanding of cutting-edge electronic sensor design.  English | 2022 | ISBN: 9781098117405 | 69 pages | PDF,EPUB | 14.94 MB Make deep learning models more efficient by using fewer resources to deliver better quality. With this book, you'll examine algorithms and techniques used by researchers and engineers at Google, Facebook, and other AI labs to train and deploy models on devices ranging from server-side machines to tiny microcontrollers.  English | 2020 | ISBN: 0134832213 | 656 Pages | PDF | 925.2 MB is written to show how information and ideas drawn from research in educational psychology can be applied to solve the everyday problems of teaching. The seventh Canadian edition maintains the lucid writing style for which the book is renowned. The text provides accurate, up-to-date coverage of the foundational areas within educational psychology: learning, development, motivation, teaching, and assessment, combined with intelligent examination of emerging trends in the field and society that affect student learning, such as student diversity, inclusion of students with special learning needs, education and neuroscience, and technology.  English | 2022 | ISBN: 1108832377 | 231 pages | PDF | 9.4 MB Discover this multi-disciplinary and insightful work, which integrates machine learning, edge computing, and big data. Presents the basics of training machine learning models, key challenges and issues, as well as comprehensive techniques including edge learning algorithms, and system design issues. Describes architectures, frameworks, and key technologies for learning performance, security, and privacy, as well as incentive issues in training/inference at the network edge. Intended to stimulate fruitful discussions, inspire further research ideas, and inform readers from both academia and industry backgrounds. Essential reading for experienced researchers and developers, or for those who are just entering the field.  English | 2020 | ISBN: 0750324309 | 299 pages | True (PDF,EPUB,MOB) | 56.45 MB This book focuses on use-inspired basic science by connecting theoretical methods and mathematical developments in ecology with practical real-world problems, either in production or conservation. The text aims to increase the reader's confidence to rely on partial aspects and relations of systems to which we only have an incomplete understanding. By abstracting and simplifying problems, Ecological Modelling and Ecophysics seeks to expand the reader's understanding and ability to solve practical issues with rigorous quantitative methods.  English | 2021 | ISBN: 0128236981 | 486 pages | True pdf, epub | 38.44 MB Discrete Networked Dynamic Systems: Analysis and Performanceprovides a high-level treatment of a general class of linear discrete-time dynamic systems interconnected over an information network, exchanging relative state measurements or output measurements. It presents a systematic analysis of the material and providesan account to the math development in a unified way.  English | 2019 | ISBN: 978-0323547581 | 218 pages | True pdf | 13.26 MB Written with the radiography student in mind,Digital Radiography and PACS, 3rd Editionaddresses today's digital imaging systems, including computed radiography (CR), digital radiography (DR), and picture archiving and communications systems (PACS). This new edition incorporates the latest technical terminology and has been updated to reflect the 2017 ASRT Core Curriculum guidelines. It includes tips on acquiring, processing, and producing clear radiographic images, performing advanced image processing and manipulation functions on CR/DR workstations, storing images with PACS workstations, and a guide to quality control and management. Coauthored by radiography educators Christi Carter and Beth Veale, this text is designed to help you produce clear radiographic images and learn to provide safe archiving solutions.  English | 2021 | ISBN: 1538141353 | 189 pages | True PDF EPUB | 8.69 MB More and more individuals today are "digital natives." They are comfortable with all of the advances in technology, using it every day. However, while they may be able to access the digital world easily does not translate into being able to successfully navigate it. Regardless of age and experience, young adults must be mindful of their digital presence in the expanding digital world. This book provides a guide for librarians, educators, counselors, and administrators to guide secondary and higher education students in successfully practicing responsible citizenship and civics in the digital world. In our world where our social credit is held increasing value, digital civics and citizenship are powerful tools, especially for students just venturing into this expansive realm.  English | 2022 | ISBN: 0750333537, 978-0-7503-3355-9 | 241 pages | True PDF EPUB MOBI | 62.14 MB This book focuses on major trends and challenges in the detection of lung cancer, presenting work aimed at identifying new techniques and their use in biomedical analysis. This volume covers recent advancements in lung cancer and imaging detection and classification, examining the main applications of computer aided diagnosis relating to lung cancer: lung nodule segmentation, lung nodule classification, and Big Data in lung cancer. Ideal for academics working in lung cancer, data-mining, machine learning, deep learning and reinforcement learning, as well as industry professionals working in the areas of healthcare, lung cancer imaging, machine learning, deep learning and reinforcement learning, this edited collection comprises an essential reference for researchers at the forefront of the field, and provides a high-level entry point for more advanced students.  English | 2020 | ISBN: 0750331410 | 186 pages | True (PDF,EPUB,MOB) | 37.41 MB essential part of our view of the world. Our world is measured and calibrated, |
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