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Das Kopplungsverbot verbietet, die Nutzung einer Dienstleistung von der Erteilung einer nicht für die Leistungserbringung erforderlichen Einwilligung abhängig zu machen. Personalisierte Werbung wird hierdurch erheblich erschwert. Anbieter können jedoch durch Bereitstellung eines alternativen, einwilligungsfreien Zugangs zu derselben Leistung ihren Dienst datenschutzkonform anbieten. Ein solcher Zugang muss nicht zwingend in Form eines fixen Entgelts gestaltet sein. Vielmehr ist es datenschutzrechtlich in gewissem Umfang zulässig, Preise unter Einbeziehung personenbezogener Daten dynamisch zu gestalten.
Kurz vor der parlamentarischen Sommerpause hat der Bundestag am 28.6.2019 das 2. Datenschutz-Anpassungs- und Umsetzungsgesetz EU (2. DSAnpUG-EU) beschlossen, der Bundesrat hat diesem Gesetz am 20.9.2019 zugestimmt. Das Artikelgesetz, welches im sog. Omnibusverfahren zahlreiche Gesetze auf Bundesebene ändert, soll zur Vereinheitlichung und Anpassung des Bundesrechts an die seit Mai 2018 geltende Datenschutz-Grundverordnung (DSGVO) beitragen.
Das „Recht auf Vergessenwerden“ unter Geltung der DSGVO: Anwendungsbereich und Rechtmäßigkeit
(2019)
Das „Recht auf Vergessenwerden“ unter Geltung der DSGVO: Rechtmäßigkeit der Anzeige sensibler Daten
(2019)
The paper industry is the industry with the third highest energy consumption in the European Union. Using recycled paper instead of fresh fibers for papermaking is less energy consuming and saves resources. However, adhesive contaminants in recycled paper are particularly problematic since they reduce the quality of the resulting paper-product. To remove as many contaminants and at the same time obtain as many valuable fibres as possible, fine screening systems, consisting of multiple interconnected pressure screens, are used. Choosing the best configuration is a non-trivial task: The screens can be interconnected in several ways, and suitable screen designs as well as operational parameters have to be selected. Additionally, one has to face conflicting objectives. In this paper, we present an approach for the multi-criteria optimization of pressure screen systems based on Mixed-Integer Nonlinear Programming. We specifically focus on a clear representation of the trade-off between different objectives.
Water suppliers are faced with the great challenge of achieving high-quality and, at the same time, low-cost water supply. In practice, the focus is set on the most beneficial maintenance measures and/or capacity adaptations of existing water distribution systems (WDS). Since climatic and demographic influences will pose further challenges in the future, the resilience enhancement of WDS, i.e. the enhancement of their capability to withstand and recover from disturbances, has been in particular focus recently. To assess the resilience of WDS, metrics based on graph theory have been proposed. In this study, a promising approach is applied to assess the resilience of the WDS for a district in a major German City. The conducted analysis provides insight into the process of actively influencing the
resilience of WDS
In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead.