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Verantwortlichkeit, Data Breach, das Ende von Fax & E-Mail: Aufsichtsbehörden mit streitbaren Thesen
(2020)
Textsammlung mit allen für den Datenschutz in Kirchen maßgeblichen Regelwerken: DSGVO, KDG, KDR-OG, DSG-EKD sowie begleitende Verordnungen (KDG-DVO, KDR-OG-DVO und ITSVO-EKD) und Verfahrensgesetze (KDSGO und KiGG.EKD). Die vorliegende Textsammlung enthält die für den Datenschutz der beiden großen Kirchen in Deutschland maßgeblichen Vorschriften: Dies sind, neben der Datenschutz-Grundverordnung, die Normen des kirchlichen Rechts, die neu erlassen bzw. geändert wurden. Weiter sind die verschiedenen Durchführungsverordnungen für die kirchlichen Datenschutzgesetze und die maßgeblichen Normen des kirchlichen Verfahrensrechts abgedruckt. Ergänzt wird das Werk durch Verweise auf maßgebliche Veröffentlichungen der weltlichen und kirchlichen Datenschutzaufsichtsbehörden und weitere Materialien.
Nach dem Scheitern des Privacy Shield hofft der Datenschutzberater Alexander Golland, dass die europäischen Behörden bald konkrete Maßnahmen für den Datentransfer in Drittländer vorschlagen. Auch kleine Unternehmen müssten die Herausforderung bewältigen – sonst wäre das Urteil nur Wasser auf die Mühlen jener, die ohnehin über den Datenschutz schimpfen.
Experience has shown that a priori created static resource allocation plans are vulnerable to runtime deviations and hence often become uneconomic or highly exceed a predefined soft deadline. The assumption of constant task execution times during allocation planning is even more unlikely in a cloud environment where virtualized resources vary in performance. Revising the initially created resource allocation plan at runtime allows the scheduler to react on deviations between planning and execution. Such an adaptive rescheduling of a many-task application workflow is only feasible, when the planning time can be handled efficiently at runtime. In this paper, we present the static low-complexity resource allocation planning algorithm (LCP) applicable to efficiently schedule many-task scientific application workflows on cloud resources of different capabilities. The benefits of the presented algorithm are benchmarked against alternative approaches. The benchmark results show that LCP is not only able to compete against higher complexity algorithms in terms of planned costs and planned makespan but also outperforms them significantly by magnitudes of 2 to 160 in terms of required planning time. Hence, LCP is superior in terms of practical usability where low planning time is essential such as in our targeted online rescheduling scenario.
This paper primarily presents an aerodynamic CFD analysis of a winged spaceplane geometry based on the Japanese Space Walker proposal. StarCCM was used to calculate aerodynamic coefficients for a typical space flight trajectory including super-, trans- and subsonic Mach numbers and two angles of attack. Since the solution of the RANS equations in such supersonic flight regimes is still computationally expensive, inviscid Euler simulations can principally lead to a significant reduction in computational effort. The impact on accuracy of aerodynamic properties is further analysed by comparing both methods for different flight regimes up to a Mach number of 4.
The Rothman–Woodroofe symmetry test statistic is revisited on the basis of independent but not necessarily identically distributed random variables. The distribution-freeness if the underlying distributions are all symmetric and continuous is obtained. The results are applied for testing symmetry in a meta-analysis random effects model. The consistency of the procedure is discussed in this situation as well. A comparison with an alternative proposal from the literature is conducted via simulations. Real data are analyzed to demonstrate how the new approach works in practice.
We discuss the testing problem of homogeneity of the marginal distributions of a continuous bivariate distribution based on a paired sample with possibly missing components (missing completely at random). Applying the well-known two-sample Crámer–von-Mises distance to the remaining data, we determine the limiting null distribution of our test statistic in this situation. It is seen that a new resampling approach is appropriate for the approximation of the unknown null distribution. We prove that the resulting test asymptotically reaches the significance level and is consistent. Properties of the test under local alternatives are pointed out as well. Simulations investigate the quality of the approximation and the power of the new approach in the finite sample case. As an illustration we apply the test to real data sets.