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nexusstc/Social Knowledge Creation in the Humanities: Volume 1 (Volume 7) (New Technologies in Medieval and Renaissance Studies)/8b7015d8096c4269695ddf0519b45331.pdf

Social Knowledge Creation in the Humanities: Volume 1 (Volume 7) (New Technologies in Medieval and Renaissance Studies) Alyssa Arbuckle (editor), Aaron Mauro (editor), Daniel Powell (editor) Iter Press, 1, 2017

The ubiquity of social media has transformed the scope and scale of scholarly communication in the arts and humanities. The consequences of this new participatory and collaborative environment for humanities research has allowed for fresh approaches to communicating research. Social Knowledge Creation takes up the norms and customs of online life to reorient, redistribute, and oftentimes flatten traditional academic hierarchies. This book discusses the implications of how humanists communicate with the world and looks to how social media shapes research methods. This volume addresses peer-review, open access publishing, tenure and promotion, mentorship, teaching, collaboration, and interdisciplinarity as a comprehensive introduction to these rapidly changing trends in scholarly communication, digital pedagogy, and educational technology. Collaborative structures are rapidly augmenting disciplinary focus of humanities curriculum and the public impact of humanities research teams with new organizational and disciplinary thinking. Social Knowledge Creation represents a particularly dynamic and growing field in which the humanities seeks to find new ways to communicate the legacy and traditions of humanities based inquiry in a 21st century context. New Technologies in Medieval and Renaissance Studies Volume 7. Edited by Alyssa Arbuckle, Aaron Mauro, and Daniel Powell

英语 [en] · PDF · 9.5MB · 2017 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc · Save

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lgli/V:\comics\_0DAY2\Alpha Folders 0-9 - D\D\Doc Savage\Doc Savage Novel Collection complete\095 The Devil's Playground.pdf

095 The Devil's Playground.pdf

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upload/imslp/Diz, Ezequiel/IMSLP830431-PMLP4182-Pantomina.pdf

PMLUS03115-2cc2-Falla_-_El_Amor_Brujo_(orch._score).pdf Profesor-31

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nexusstc/The Past is a Future Country (Societas)/f81fe063dc31a846260703ff54e52397.epub

The Past is a Future Country , the coming Conservative Demographic Revolution Edward Dutton; J. O. A. Rayner-Hilles Andrews UK Limited 2022, Societas (Imprint Academic (Firm)), Exeter, 2022

Since the 1960s, the West has moved ever-leftwards. 'Equality' and 'feelings' are central to the New Religion that rejects all traditional values. Yet beneath the institutionally dominant 'Left' stews a growing and restless 'Right'. How has this fractured situation come about? What will the future hold?In The Past is a Future Country, the authors trace it back to the Industrial Revolution. Darwinian selection massively weakened, meaning that, for the first time in history, the selfish, sick and stupid could survive and reproduce, undermining our religious, group-oriented culture. Now the West is scourged by an epidemic of narcissists, competing to signal their individuality and moral superiority. But their 'fight for equality' is really a fight for self-promotion. Reflecting this runaway individualism, Westerners increasingly don't have children, save for those who are genetically resistant to this onslaught — the staunchly conservative and religious: the eventual inheritors of the earth.But there is a dark storm brewing in the demographic data that the authors have analysed. There is a burgeoning growth in the population of exceptionally unintelligent and antisocial people that social welfare systems cannot sustain for much longer. The developed world will pass away, and the global population that depends on it will crash, in the greatest Malthusian Collapse of all time. Yet all is not lost. The authors show how a resistant class of intelligent, religious conservatives will band together to preserve enclaves of civilization that may survive most of the coming apocalypse, and from its ashes rebuild a new world: A Neo-Byzantium.

英语 [en] · EPUB · 2.1MB · 2022 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/zlib · Save

upload/duxiu_main/x/djvu/16046757_清华副刊_清华大学周刊社.djvu

清华副刊清华大学周刊社 1933

中文 [zh] · DJVU · 3.5MB · 1933 · 📗 未知类型的图书 · 🚀/upload · Save

magzdb/Super Street/2009/6/624696744df80e1443047f477c7b95d8.pdf

Super Street 2009 No 6 Super Street, #6, #6, 13, 2009

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英语 [en] · PDF · 80.3MB · 2009 · 📰 杂志 · 🚀/lgli/magzdb/upload · Save

scihub/10.1007/978-981-4585-60-6.pdf

[Advances in Industrial Control] Practical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation || Danwei Wang, Yongqiang Ye, Bin Zhang (auth.) Springer Nature Singapore, 10.1007/97, 2014

This book is on the iterative learning control (ILC) with focus on the design and implementation. We approach the ILC design based on the frequency domain analysis and address the ILC implementation based on the sampled data methods. This is the first book of ILC from frequency domain and sampled data methodologies. The frequency domain design methods offer ILC users insights to the convergence performance which is of practical benefits. This book presents a comprehensive framework with various methodologies to ensure the learnable bandwidth in the ILC system to be set with a balance between learning performance and learning stability. The sampled data implementation ensures effective execution of ILC in practical dynamic systems. The presented sampled data ILC methods also ensure the balance of performance and stability of learning process. Furthermore, the presented theories and methodologies are tested with an ILC controlled robotic system. The experimental results show that the machines can work in much higher accuracy than a feedback control alone can offer. With the proposed ILC algorithms, it is possible that machines can work to their hardware design limits set by sensors and actuators. The target audience for this book includes scientists, engineers and practitioners involved in any systems with repetitive operations.

英语 [en] · PDF · 8.4MB · 2014 · 📘 非小说类图书 · 🚀/lgli/scihub/zlib · Save

upload/newsarch_ebooks/2020/03/07/9814585599.epub

Practical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation (Advances in Industrial Control) Danwei Wang, Yongqiang Ye and Bin Zhang Springer Singapore, Singapore, Springer Nature, Heidleberg, 2014

This book is on the iterative learning control (ILC) with focus on the design and implementation. We approach the ILC design based on the frequency domain analysis and address the ILC implementation based on the sampled data methods. This is the first book of ILC from frequency domain and sampled data methodologies. The frequency domain design methods offer ILC users insights to the convergence performance which is of practical benefits. This book presents a comprehensive framework with various methodologies to ensure the learnable bandwidth in the ILC system to be set with a balance between learning performance and learning stability. The sampled data implementation ensures effective execution of ILC in practical dynamic systems. The presented sampled data ILC methods also ensure the balance of performance and stability of learning process. Furthermore, the presented theories and methodologies are tested with an ILC controlled robotic system. The experimental results show that the machines can work in much higher accuracy than a feedback control alone can offer. With the proposed ILC algorithms, it is possible that machines can work to their hardware design limits set by sensors and actuators. The target audience for this book includes scientists, engineers and practitioners involved in any systems with repetitive operations.

英语 [en] · EPUB · 5.5MB · 2014 · 📗 未知类型的图书 · 🚀/upload/zlib · Save

lgli/G:\1\springer_new\bok%3A978-981-4585-60-6.pdf

Practical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation (Advances in Industrial Control) Danwei Wang, Yongqiang Ye, Bin Zhang (auth.) Springer-Verlag Singapur, Advances in Industrial Control, Advances in Industrial Control, 1, 2014

This book is on the iterative learning control (ILC) with focus on the design and implementation. We approach the ILC design based on the frequency domain analysis and address the ILC implementation based on the sampled data methods. This is the first book of ILC from frequency domain and sampled data methodologies. The frequency domain design methods offer ILC users insights to the convergence performance which is of practical benefits. This book presents a comprehensive framework with various methodologies to ensure the learnable bandwidth in the ILC system to be set with a balance between learning performance and learning stability. The sampled data implementation ensures effective execution of ILC in practical dynamic systems. The presented sampled data ILC methods also ensure the balance of performance and stability of learning process. Furthermore, the presented theories and methodologies are tested with an ILC controlled robotic system. The experimental results show that the machines can work in much higher accuracy than a feedback control alone can offer. With the proposed ILC algorithms, it is possible that machines can work to their hardware design limits set by sensors and actuators. The target audience for this book includes scientists, engineers and practitioners involved in any systems with repetitive operations. Erscheinungsdatum: 08.07.2014

英语 [en] · PDF · 8.4MB · 2014 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/scihub/zlib · Save