Technische Universität Darmstadt

About: Technische Universität Darmstadt is a education organization based out in Darmstadt, Germany. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 17316 authors who have published 40619 publications receiving 937916 citations. The organization is also known as: Darmstadt University of Technology & University of Darmstadt.

Scalable recognition of daily activities with wearable sensors

Abstract: High-level and longer-term activity recognition has great potentials in areas such as medical diagnosis and human behavior modeling. So far however, activity recognition research has mostly focused on lowlevel and short-term activities. This paper therefore makes a first step towards recognition of high-level activities as they occur in daily life. For this we record a realistic 10h data set and analyze the performance of four different algorithms for the recognition of both low- and high-level activities. Here we focus on simple features and computationally efficient algorithms as this facilitates the embedding and deployment of the approach in real-world scenarios. While preliminary, the experimental results suggest that the recognition of high-level activities can be achieved with the same algorithms as the recognition of low-level activities.

Highly accurate surface and volume integration on implicit domains by means of moment‐fitting

Abstract: We introduce a new method for the numerical integration over curved surfaces and volumes defined by a level set function. The method is based on the solution of a small linear system based on a simplified variant of the moment-fitting equations. Numerical experiments suggest that the accuracy of the resulting quadrature rules exceeds the accuracy of traditional methods by orders of magnitude. Using moments up to an order of p, the measured experimental orders of convergence exceed hp. Consequently, their construction is very efficient because only coarse computational grids are required. The conceptual simplicity allows for the application on very general grid types, which is demonstrated by numerical experiments on quadrilateral, triangular and hexahedral grids.

Evaluating the Engagement with Social Robots

Abstract: To interact and cooperate with humans in their daily-life activities, robots should exhibit human-like " intelligence ". This skill will substantially emerge from the interconnection of all the algorithms used to ensure cognitive and interaction capabilities. While new robotics technologies allow us to extend such abilities, their evaluation for social interaction is still challenging. The quality of a human-robot interaction can not be reduced to the evaluation of the employed algorithms: we should integrate the engagement information that naturally arises during interaction in response to the robot's behaviors. In this paper we want to show a practical approach to evaluate the engagement aroused during interactions between humans and social robots. We will introduce a set of metrics useful in direct, face to face scenarios, based on the behaviors analysis of the human partners. We will show how such metrics are useS. M. Anzalone · M. Chetouani Sorbonne Universites , ful to assess how the robot is perceived by humans and how this perception changes according to the behaviors shown by the social robot. We discuss experimental results obtained in two human-interaction studies, with the robots Nao and iCub respectively.

Commissioning and early experiments of the PHELIX facility

Abstract: At the Helmholtz center GSI, PHELIX (Petawatt High Energy Laser for heavy Ion eXperiments) has been commissioned for operation in stand-alone mode and, in combination with ions accelerated up to an energy of 13 MeV/u by the heavy ion accelerator UNILAC The combination of PHELIX with the heavy-ion beams available at GSI enables a large variety of unique experiments Novel research opportunities are spanning from the study of ion–matter interaction, through challenging new experiments in atomic physics, nuclear physics, and astrophysics, into the field of relativistic plasma physics

Fatty acids of fungi and nematodes—possible biomarkers in the soil food chain?

Abstract: The fatty acid composition of 16 different soil fungi (ascomycetes, basidiomycetes, mitosporic fungi) and a fungal-feeding nematode Aphelenchoides sp. reared on seven fungal species was investigated. Additionally, fatty acid profiles of Aphelenchoides sp. and A. saprophilus grown on the same fungal food source,Agrocybe gibberosa, were compared. Thirteen predominant fatty acids were detected in the fungi. Most of them occurred in each of the 16 species, but relative quantities of individual fatty acids differed, in particular those of unsaturated ones. Most fungal species could be differentiated from each other on this basis. Our study revealed convergence, but also, differences, in the fatty acid composition of systematically related fungi, i.e. a taxonomic or phylogenetic relationship was not necessarily accompanied by similarity in fatty acid profiles. Nematodes comprised a wider fatty acid spectrum than fungi, with 17 predominant fatty acids, and a higher amount of long-chain, polyunsaturated acids than their fungal diet. Fungal host tissue may have supplied palmitic, oleic and linoleic acid present, whereas most of the long-chain unsaturated fatty acids were synthesized by the nematodes. Unsaturated fatty acids mainly belonged to the ω6 and 9 family, indicating a carboxyl-directed desaturation as a major metabolic pathway. The fungal host significantly affected the fatty acid profile of the nematodes. However, we could not assign individual fatty acids as biomarkers reflecting the dietary source, likely due to the considerable convergence within tested fungal species. Of the basidiomycetes analyzed Laccaria laccata, was distinctly separated from the others and this difference could also be detected in the nematodes showing the influence of food type. We conclude that the lipid composition of nematodes is controlled by both the nematode and its diet and that monitoring fatty acid patterns of soil animals may therefore provide a way to detect trophic interactions in belowground food webs.