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Aufhebungsvertrag (II A 100)
(2005)
Arbeitsentgelt (IIA 70)
(2005)
Arbeitszeit (II A 90)
(2005)
Case Management
(2014)
With regard to performance well established SW-only design methodologies proceed by making the initial specification run first, then by enhancing its functionality and finally by optimizing it. When designing Embedded Systems (EbS) this approach is not viable since decisive design decisions like e.g. the estimation of required processing power or the identification of those parts of the specification which need to be delegated to dedicated HW depend on the fastness and fairness of the initial specification. We here propose a sequence of optimization steps embedded into the design flow, which enables a structured way to accelerate a given working EbS specification at different layers. This sequence of accelerations comprises algorithm selection, algorithm transformation, data transformation, implementation optimization and finally HW acceleration. It is analyzed how all acceleration steps are influenced by the specific attributes of the underlying EbS. The overall acceleration procedure is explained and quantified at hand of a real-life industrial example.
Open Innovation
(2018)
Open Innovation
(2020)
Gegen unveröffentlichte – nur wenigen Personen bekannte – Sicherheitslücken (Less-than-Zero-Day Vulnerabilities) und diese ausnutzende Angriffsprogramme (Exploits) können IT-Systeme nicht geschützt werden. In der Vergangenheit wurden Sicherheitslücken meist dem Hersteller gemeldet; dieser stellte (allerdings nicht in allen Fällen) eine Fehlerkorrektur zur Verfügung. In jüngerer Zeit werden Sicherheitslücken systematisch (Tool-gestützt) gesucht und an Behörden, Unternehmen und an die organisierte Kriminalität verkauft – und nicht oder nicht sofort dem Hersteller gemeldet. Durch Ausnutzung dieser unveröffentlichten Sicherheitslücken ist Wirtschaftsspionage und Computersabotage (auch der Steuerungsrechner des Internet) unerkannt möglich [GI 2007]. Praktizierte Anwendungen sind – u.a. auch als Titan Rain – dokumentiert [BfDI 2007, Keizer 2006, NSTAC 2007, Pohl 2007, Rath 2007].
Poland
(2018)
Poland belongs to the first wave of pension reformers in Central and Eastern Europe. The Polish pension reform of the late 1990s can serve as a case study for the challenges faced when implementing a radical paradigmatic pension reform towards a privatized DC scheme. This report analyses the background of the original reform, discusses its political, social and economic impact and explains the reasons for later reform reversals. The report stresses that the two re-reform waves, which took place in 2011 and 2013, were mainly driven by fiscal considerations. Since the current system maintains the DC scheme applied to both public and private tiers, the recent reversal of privatization will not improve benefit levels.
Die Welt war es in den letzten drei Jahrzehnten gewöhnt, dass größere ökonomische Krisen von den Entwicklungsländern ausgehen. Dies traf zu im Falle Mexikos (1995), Thailands (1997) als Auslöser der sich ausbreitenden Asienkrise) sowie der tiefen ökonomischen Verwerfungen in Argentinien (2001). Umso größer war die mentale Schockwelle, als die jüngste – und vor allem erstmals seit achtzig Jahren globale – Wirtschaftskrise von den USA ausging.
Wirtschaft und Entwicklung: Die Bedeutung der Privatwirtschaft in der Entwicklungszusammenarbeit
(2013)
Die sozialen Herausforderungen der Zukunft und die gesellschaftspolitische Rolle von Unternehmen
(2012)
In Artificial Intelligence, numerous learning paradigms have been developed over the past decades. In most cases of embodied and situated agents, the learning goal for the artificial agent is to „map“ or classify the environment and the objects therein [1, 2], in order to improve navigation or the execution of some other domain-specific task. Dynamic environments and changing tasks still pose a major challenge for robotic learning in real-world domains. In order to intelligently adapt its task strategies, the agent needs cognitive abilities to more deeply understand its environment and the effects of its actions. In order to approach this challenge within an open-ended learning loop, the XPERO project (http://www.xpero.org) explores the paradigm of Learning by Experimentation to increase the robot's conceptual world knowledge autonomously. In this setting, tasks which are selected by an actionselection mechanism are interrupted by a learning loop in those cases where the robot identifies learning as necessary for solving a task or for explaining observations. It is important to note that our approach targets unsupervised learning, since there is no oracle available to the agent, nor does it have access to a reward function providing direct feedback on the quality of its learned model, as e.g. in reinforcement learning approaches. In the following sections we present our framework for integrating autonomous robotic experimentation into such a learning loop. In section 1 we explain the different modules for stimulation and design of experiments and their interaction. In section 2 we describe our implementation of these modules and how we applied them to a real world scenario to gather target-oriented data for learning conceptual knowledge. There we also indicate how the goaloriented data generation enables machine learning algorithms to revise the failed prediction model.
Domestic Robotics
(2008)
Domestic Robotics
(2016)