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Is Optimal Still Good Enough? Time Traps in Supply Chains

Supply Chain Management (SCM) is the process of planning, implementing, and controlling the operations of a supply chain in an efficient way. Supply Chain Planning – as an important subtask of SCM – is the process of allocating resources over a network of interrelated locations with the goal to satisfy customer requirements. Operations Researchers support by developing adequate mathematical optimization models and providing suitable solution procedures. In this paper we discuss what adequate could mean. Therefore, we may ask several questions concerning “optimality” in Supply Chain Planning under causal and temporal uncertainty: What is an optimal solution? When is it optimal? For how long is it optimal? How should the design of a supply chain be changed when conditions and requirements ask for new structures?

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Home-based system for physical activity monitoring in patients with multiple sclerosis

Limitations in physical activity are considered as a key problem in patients with multiple sclerosis (PwMS). Contemporary methods to assess the level of physical activity in PwMS are regular clinical observation. However, these methods either rely on high recall and accurate reporting from the patients (e.g. self-report questionnaires), or they are conducted during a particular clinical assessment with predefined activities. Therefore, the main aim of this pilot study was to develop an objective method to gather information about the real type and intensity of daily activities performed by PwMS in every-day living situations using an accelerometer. Furthermore, the accelerometer-derived measures are investigated regarding their potential for discriminating between different MS groups.

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Particle Filter Map Matching and Trajectory Prediction Using a Spline Based Intersection Model

For Advanced Driver Assistence Systems and Autonomous Driving it is of major advantage to know future trajectories of traffic participants. These are influenced by many factors in the environment. One important factor is the geometry of the intersection a vehicle is approaching. In this work, we describe how we can extract a spline based intersection model from low detail map data like OpenStreetMap that can be adjusted over time. A particle filter based map matching algorithm is used to localize the ego vehicle relative to the intersection model. Additionally objects detected from the ego vehicle’s sensors are matched onto the intersection model in order to predict the future trajectories of the ego vehicle and other traffic participants using the intersection model.

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GPU based Voxel-Collision-Detection for Robot Motion Planning

Begleitender Foliensatz zum Tutorial von Andreas Hermann am 15. Juli 2014 auf der International Conference on Intelligent Autonomous Systems in Padova.

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Abschlussbericht zum Forschungsvorhaben „Geschäftsmodelle und IKT-basierte Dienstleistungen für Elektromobilität“

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Kurzbericht zum Forschungsvorhaben „Geschäftsmodelle und IKT-basierte Dienstleistungen für Elektromobilität“

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Gegenmaßnahmen zu bestehenden Bring Your Own Device Risiken

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