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Poincaré gauge theory of gravity: Friedman cosmology with even and odd parity modes: Analytic part
(2011)
The ISO 27000 is a well-established series of information security standards. The scope for applying these standards can be an organisation as a whole, single business processes or even an IT application or IT infrastructure. The context establishment and the asset identification are among the first steps to be performed. The quality of the results produced when performing these steps has a crucial influence on the subsequent steps such as identifying loss, vulnerabilities, possible attacks and defining countermeasures. Thus, a context analysis to gather all necessary information in the initial steps is important, but is not offered in the standard. In this paper, we focus on the scope of cloud computing systems and present a way to support the context establishment and the asset identification described in ISO 27005. A cloud system analysis pattern and different kinds of stakeholder templates serve to understand and describe a given cloud development problem, i.e. the envisaged IT systems and the relevant parts of the operational environment. We illustrate our support using an online banking cloud scenario.
Seit den ersten nationalen, strategischen Papieren zu Datenmanagement-Fragen in der Wissenschaft in den USA (NSF, 2005), Großbritannien (Lyon, 2007; Swan & Brown, 2008), der EU (Atkinson et al. 2008; OGF22-ET CG, 2008) und vor allem seit den Guidelines der OECD (2007) wird international intensiv über die Erfordernisse der Ausbildung von „Datenspezialisten“ diskutiert. Grundlegende Überlegungen, die einen gewissen internationalen Konsens gefunden haben, wurden im Auftrag von JISC von Swan und Brown (2008, S. 1) entwickelt (vgl. Hank & Davidson, 2009). Sie schlagen vier Rollen im Forschungsdatenmanagement vor. Neben dem Data Creator (datenproduzierender Forscher), dem Data Scientist (Wissenschaftler der bspw. bei der Datenanalyse unterstützt) und dem Data Manager (verantwortlich für alle technischen Aspekte: Lagerung, Zugriff, Aufbewahrung) wurde auch der Data Librarian benannt. Im Weiteren wird, auch unter Beachtung der Tätigkeiten die im Data Curation Lifecycle Model (s. Beitrag von Rümpel. Kap. 1.2) aufgeführt sind, neben dem Data Manager und dem Data Curator insbesondere auf den Data Librarian eingegangen.
This paper presents a tracking of parts of a human body in a virtual TV studio environment. The tracking is based on a depth camera and a HD studio camera and aims at a realistic interaction between the actor and the computer generated environment. Stereo calibration methods are used to match corresponding pixels of both cameras (HD color and depth image). Hence the images were rectified and column aligned. The disparity is used to correct the depth image pixel by pixel. This image registration results in row and column aligned images where ghost regions are in the depth image resulting from occlusion. Both images are used to generate foreground masks with chroma and depth keying. The color image is taken for skin color segmentation to determine and distinguish the actor’s hands and face. In the depth image the flesh colored regions were used to determine their spatial position. The extracted positions were augmented by virtual objects. The scene is rendered correctly with virtual camera parameters which were calculated from the camera calibration parameters. Generated computer graphics with alpha value are combined with the HD color images. This compositing shows interaction with augmented objects for verification. The additional depth information results in changing the size of objects next to the hands when the actor moves around.