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Titlebook: Making of a Satellite Centre; The Genesis of ISRO‘ Prem Shanker Goel Book 2022 Indian National Academy of Engineering 2022 Satellite Centre

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发表于 2025-3-21 16:38:21 | 显示全部楼层 |阅读模式
书目名称Making of a Satellite Centre
副标题The Genesis of ISRO‘
编辑Prem Shanker Goel
视频video
概述Takes the reader through the journey of Indian Space Research Organisation (ISRO) over five decades.Provides the evolution of Satellite Centre in India as an evolution of a culture and values that are
图书封面Titlebook: Making of a Satellite Centre; The Genesis of ISRO‘ Prem Shanker Goel Book 2022 Indian National Academy of Engineering 2022 Satellite Centre
描述This book tells the story of the evolution of the Satellite Center which started from a small Satellite Systems Division in 1967 with a handful of engineers to a vibrant R&D center which is playing the lead role in the Indian Satellite Program. India‘s space program is unique as it is driven by societal applications. The Indian Space Research Organisation (ISRO) has centers dedicated to various space applications. The ISRO Satellite Centre, now known as the UR Rao Satellite Centre (URSC), has evolved as lead center for Satellite Technology over five decades and has developed state-of-the-art satellites for applications such as remote sensing, satellite communication and space science. Through the story of URSC, the book describes the challenges of putting together new research and development centers and programs and conveys the importance of leadership and project management skills required to undertake such a task. This book is of interest to researchers, professionals, and administrators involved in the development of new R&D facilities and also to space scientists and space enthusiasts across the world.
出版日期Book 2022
关键词Satellite Centre; Indian Space; Indian satellite centre; Satellite Technology; Indian Satellite Program
版次1
doihttps://doi.org/10.1007/978-981-16-3480-2
isbn_softcover978-981-16-3482-6
isbn_ebook978-981-16-3480-2
copyrightIndian National Academy of Engineering 2022
The information of publication is updating

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Prem Shanker Goelfollowing advantages: it is almost similar to the highly accurate combined model, as a single solution it requires much fewer memory resources, no additional validation test must be reserved to do this procedure and, more importantly, the resulting model is expressed as a single classifier in terms
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Prem Shanker Goel to clusters of .-.. In addition, the clusters were analyzed by a wine expert. The clusters represented different types of Red wine quality. The success and the accuracy of the imputation were validated using another two datasets: White wine and Page blocks (from the UCI). The results were consisten
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Prem Shanker Goelctal EEG signal maximally. We learn a one-step forecast operator restricted to just these features, using autoregression (AR(1)). We improve this in a novel way by cross-learning common knowledge across patients and recordings using ., and devise a novel transformation to increase the efficiency of
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