Research Report 2010 – 2013, Human-Computer Interaction, FernUniversität in Hagen

Research at the Chair of Human-Computer Interaction (HCI group) at FernUniversität in Hagen is focused on the investigation and development of interactive and intelligent systems. Cooperating with researchers around the world, the group is active in basic as well as applied research. The underlying motivation on the part of basic research is the big question of the nature of consciousness. Here the group is interested in the investigation of intelligent biological systems by means of theory building as well as simulations on computers and robotical systems. More concrete, the HCI group aims at gaining deeper insight into particular aspects of human or animal cognition, such as vision or spatial cognition. The main goal on the part of applied research is the development of intelligent computer systems that interact with humans in an intuitive and multimodal way

A generalized computational model for modeling and simulation of complex systems

The use of computer models and simulation is a widely adopted approach to study complex systems. To this end a diverse set of computational models like Cellular Automata, Artificial Neural Networks, or Agent-based simulation is being used. As a common denominator virtually all of these approaches favor different variations of complex systems and are tailored to support the description of systems that fit the corresponding variation well. Although this form of specialization has its benefits like ease of modeling with respect to the particular subset of complex systems, the drawbacks of this specialization are a lack of comparability between structurally different systems and a diminished expressiveness with respect to systems that do not fit any particular subset of complex systems favored by existing, specialized models. In this paper a generalized computational model for complex systems is proposed which allows for the description of most types of systems with a single model. Furthermore, the proposed model provides a high degree of encapsulation and reduces the amount of shared knowledge needed among the constituents of the system. The paper closes with a set of example applications of the proposed model to further illustrate the involved concepts and to provide an intuition on how this model may be used

The XDEM Multi-physics and Multi-scale Simulation Technology: Review on DEM-CFD Coupling, Methodology and Engineering Applications

The XDEM multi-physics and multi-scale simulation platform roots in the Ex- tended Discrete Element Method (XDEM) and is being developed at the In- stitute of Computational Engineering at the University of Luxembourg. The platform is an advanced multi- physics simulation technology that combines flexibility and versatility to establish the next generation of multi-physics and multi-scale simulation tools. For this purpose the simulation framework relies on coupling various predictive tools based on both an Eulerian and Lagrangian approach. Eulerian approaches represent the wide field of continuum models while the Lagrange approach is perfectly suited to characterise discrete phases. Thus, continuum models include classical simulation tools such as Computa- tional Fluid Dynamics (CFD) or Finite Element Analysis (FEA) while an ex- tended configuration of the classical Discrete Element Method (DEM) addresses the discrete e.g. particulate phase. Apart from predicting the trajectories of individual particles, XDEM extends the application to estimating the thermo- dynamic state of each particle by advanced and optimised algorithms. The thermodynamic state may include temperature and species distributions due to chemical reaction and external heat sources. Hence, coupling these extended features with either CFD or FEA opens up a wide range of applications as diverse as pharmaceutical industry e.g. drug production, agriculture food and processing industry, mining, construction and agricultural machinery, metals manufacturing, energy production and systems biology

Forschungsbericht 2010 – 2013, Lehrgebiet Mensch-Computer-Interaktion, FernUniversität in Hagen

Das Lehrgebiet Mensch-Computer-Interaktion (MCI) der FernUniversität in Hagen befasst sich mit der Untersuchung und Entwicklung Interaktiver und Intelligenter Systeme. Das Lehrgebiet ist sowohl in der Grundlagen- als auch angewandten Forschung aktiv und kooperiert mit internationalen Forschungsgruppen. Aufseiten der Grundlagenforschung besteht die zugrunde liegende Motivation in der großen Frage nach der Natur des Bewusstseins. Hier ist das Lehrgebiet an der Untersuchung intelligenter, biologischer Systeme mit Hilfe von Simulationen auf Computern und Robotersystemen sowie Theoriebildung interessiert. Konkreter ausgedrückt besteht ein Ziel darin, Einsichten in bestimmte Aspekte menschlicher oder tierischer kognitiver Fähigkeiten wie das Sehen oder die Raumkognition zu gewinnen. Das Hauptziel im Bereich der angewandten Forschung besteht in der Entwicklung intelligenter Computersysteme, die in der Lage sind, mit Menschen auf eine intuitive und multimodale Weise zu interagieren

A co-located partitions strategy for parallel CFD-DEM couplings

In this work, a new partition-collocation strategy for the parallel execution of CFD--DEM couplings is investigated. Having a good parallel performance is a key issue for an Eulerian-Lagrangian software that aims to be applied to solve industrially significant problems, as the computational cost of these couplings is one of their main drawback. The approach presented here consists in co-locating the overlapping parts of the simulation domain of each software on the same MPI process, in order to reduce the cost of the data exchanges. It is shown how this strategy allows reducing memory consumption and inter-process communication between CFD and DEM to a minimum and therefore to overcome an important parallelization bottleneck identified in the literature. Three benchmarks are proposed to assess the consistency and scalability of this approach. A coupled execution on 280 cores shows that less than 0.1% of the time is used to perform inter-physics data exchange

In vitro bioconversion of polyphenols from black tea and red wine/grape juice by human intestinal microbiota displays strong interindividual variability

Dietary polyphenols in tea and wine have been associated with beneficial health effects. After ingestion, most polyphenols are metabolized by the colonic microbiota. The current study aimed at exploring the interindividual variation of gut microbial polyphenol bioconversion from 10 healthy human subjects. In vitro fecal batch fermentations simulating conditions in the distal colon were performed using polyphenols from black tea and a mixture of red wine and grape juice. Microbial bioconversion was monitored by NMR- and GC-MS-based profiling of diverse metabolites and phenolics. The complex polyphenol mixtures were degraded to a limited number of key metabolites. Each subject displayed a specific metabolite profile differing in composition and time courses as well as levels of these metabolites. Moreover, clear differences depending on the polyphenol sources were observed. In conclusion, varying metabolite pathways among individuals result in different metabolome profiles and therefore related health effects are hypothesized to differ between subjects