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EDPB: Europäische Aufsichtsbehörden mit neuen Guidelines zur datenschutzkonformen Einwilligung
(2020)
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.
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.
The established Hoeffding-Blum-Kiefer-Rosenblatt independence test statistic is investigated for partly not identically distributed data. Surprisingly, it turns out that the statistic has the well-known distribution-free limiting null distribution of the classical criterion under standard regularity conditions. An application is testing goodness-of-fit for the regression function in a non parametric random effects meta-regression model, where the consistency is obtained as well. Simulations investigate size and power of the approach for small and moderate sample sizes. A real data example based on clinical trials illustrates how the test can be used in applications.
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.
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.
The maintenance of wind turbines is of growing importance considering the transition to renewable energy. This paper presents a multi-robot-approach for automated wind turbine maintenance including a novel climbing robot. Currently, wind turbine maintenance remains a manual task, which is monotonous, dangerous, and also physically demanding due to the large scale of wind turbines. Technical climbers are required to work at significant heights, even in bad weather conditions. Furthermore, a skilled labor force with sufficient knowledge in repairing fiber composite material is rare. Autonomous mobile systems enable the digitization of the maintenance process. They can be designed for weather-independent operations. This work contributes to the development and experimental validation of a maintenance system consisting of multiple robotic platforms for a variety of tasks, such as wind turbine tower and rotor blade service. In this work, multicopters with vision and LiDAR sensors for global inspection are used to guide slower climbing robots. Light-weight magnetic climbers with surface contact were used to analyze structure parts with non-destructive inspection methods and to locally repair smaller defects. Localization was enabled by adapting odometry for conical-shaped surfaces considering additional navigation sensors. Magnets were suitable for steel towers to clamp onto the surface. A friction-based climbing ring robot (SMART— Scanning, Monitoring, Analyzing, Repair and Transportation) completed the set-up for higher payload. The maintenance period could be extended by using weather-proofed maintenance robots. The multi-robot-system was running the Robot Operating System (ROS). Additionally, first steps towards machine learning would enable maintenance staff to use pattern classification for fault diagnosis in order to operate safely from the ground in the future.
Räumliche Transformation
(2020)
Sekundäre galvanische Zelle
(2020)
Die vorliegende Erfindung betrifft eine sekundäre galvanische Zelle, umfassend eine Kathode, eine Anode und einen Separator, der zwischen der Kathode und der Anode angeordnet ist, wobei die Kathode ein erstes elastomeres Polymer umfasst, welches mit einem ersten Füllstoff als Kathodenmaterial gefüllt ist, wobei die Anode ein zweites elastomeres Polymer umfasst, welches mit einem zweiten Füllstoff als Anodenmaterial gefüllt ist, wobei der Separator ein drittes elastomeres Polymer umfasst, wobei das erste elastomere Polymer, das zweite elastomere Polymer und das dritte elastomere Polymer unabhängig voneinander aus vernetzungsfähigen Dienkautschuken ausgewählt sind, und wobei zumindest eines von dem ersten elastomeren Polymer, dem zweiten elastomeren Polymer und dem dritten elastomeren Polymer eine ionische Flüssigkeit und/oder ein elektrisch leitfähiges Polymer enthält. Die vorliegende Erfindung betrifft ferner eine wiederaufladbare Batterie, umfassend die erfindungsgemäße sekundäre galvanische Zelle, ein Verfahren zur Herstellung einer sekundären galvanischen Zelle sowie die Verwendung der erfindungsgemäßen sekundären galvanischen Zelle sowie der erfindungsgemäßen wiederaufladbaren Batterie.