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Profile: Interdisziplinäre Beiträge

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Book Series: Digital Cultures ISBN: 9783957961013 Year: Pages: 150 DOI: 10.14619/021 Language: German
Publisher: meson press
Subject: Media and communication
Added to DOAB on : 2019-11-15 13:41:44
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Profile haben Konjunktur. Seit der Verbreitung von Social Networking Sites sind sie alltäglicher Ort der Selbstdarstellung. Doch die Praktiken und Techniken der Profilierung sind keineswegs neu. Schon lange beschreiben Profile potentielle StraftäterInnen. Nun bestimmen sie auch die potentielle Kreditwürdigkeit. Im Spannungsfeld zwischen Profil und Profilierung nehmen die Beiträge aus Medienwissenschaft, Soziologie, Geschichtswissenschaft und Informatik die vielschichtigen Dimensionen dieses zentralen Phänomens der digitalen Medienkultur in den Blick: Wie verändern sich Bedeutung und Bewertung des Profil-Begriffs? Wie stehen Profile in Zusammenhang mit Subjektivierung und Machtkonstellationen? Welche Wechselwirkungen zwischen Profilen und Privatheit sind gegenwärtig relevant?

Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA)

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ISBN: 9783731506959 Year: Pages: V, 259 p. DOI: 10.5445/KSP/1000071931 Language: ENGLISH
Publisher: KIT Scientific Publishing
Subject: Computer Science
Added to DOAB on : 2019-07-30 20:02:00
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The Helmholtz Association funded the ""Large-Scale Data Management and Analysis"" portfolio theme from 2012-2016. Four Helmholtz centres, six universities and another research institution in Germany joined to enable data-intensive science by optimising data life cycles in selected scientific communities. In our Data Life cycle Labs, data experts performed joint R&D together with scientific communities. The Data Services Integration Team focused on generic solutions applied by several communities.

Realtime Analysis of Large-Scale Data

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ISBN: 9783731505525 Year: Pages: XIII, 98 p. DOI: 10.5445/KSP/1000056498 Language: ENGLISH
Publisher: KIT Scientific Publishing
Subject: Computer Science
Added to DOAB on : 2019-07-30 20:02:00
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In photon science more and more data are taken. It is not possible anymore to store and process all data offline. In this book, we explore strategies for handling this large amount of data. A neural network as well as techniques from image processing are used to efficiently categorize and select useful data. We also indicate why many sophisticated algorithms cannot be used in this context. In addition, a prototype for data selection is presented, discussed, and benchmarked.

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2017 (3)