Automated model generation for performance engineering of building automation networks

Large technical systems need to be designed both reliable and efficient. Specialized design tools offer therefore a simplified, abstract design and extend details autonomously in the background. Analytic and simulation based models could improve the quality by testing and dimensioning the design before implementation, but setting up the necessary models is time-consuming and expensive. Therefore many developers ask for analysis tools which are able to create their models from the available information in the design tools. This paper presents such an automated modeling approach basing on an existing design database at the example of a network analysis for building automation fieldbuses. The process of automated modeling is unfolded, and the potentials and limitations are discussed.     

Vapor- and liquid-phase adsorption of alcohol and water in silicalite-1 synthesized in fluoride media

In this work, batch-adsorption experiments and molecular simulations are employed to probe the adsorption of binary mixtures containing ethanol or a linear alkane-1,n-diol solvated in water or ethanol onto silicalite-1. Since the batch-adsorption experiments require an additional relationship to determine the amount of solute (and solvent) adsorbed, as only the bulk liquid reservoir can be probed directly, molecular simulations are used to provide a relationship between solute and solvent adsorption for input to the experimental bulk measurements. The combination of bulk experimental measurements and simulated solute–solvent relationship yields solvent and solute loadings that are self-consistent with simulation alone, and allow for an assessment of the various assumptions made in the literature. At low solution concentrations, the solute loading calculated is independent of the assumption made. At high concentrations, a negligent choice of assumption can lead to systematic overestimation or underestimation of calculated solute loading.     

Synthesis and in vitro evaluation of alpha-GalCer epimers

alpha-GalCer (also known as KRN7000) is an immunomodulatory glycolipid that is known to potently activate invariant natural killer T (NKT) cells upon CD1d-mediated stimulation. Because Th1 and Th2 cytokines, which are released after alpha-GalCer presentation, antagonize each other's effects, alpha-GalCer analogues that induce a biased Th1/Th2 response are highly awaited. In this context, we report the synthesis and in vitro evaluation of alpha-Gal-D-xylo-Cer and two alpha-Gal-L-lyxo-Cer analogues, one with the natural acyl chain, the other with a truncated chain.     

New Challenges for Integrated Circuit Solutions

Integrated circuit solutions have been one of the enabling technologies, contributing to the success of wireless communications. As the focus of the new generation is moving towards higher bandwidths and new services and applications, challenges for the integrated circuit solutions are ever growing. Development focus has shifted from component design and optimization towards significant system oriented content captured both in the hardware platform and supporting software. This integrated approach challenges existing development models, and affects other disciplines related to wireless system development. This paper explores major challenges for integrated circuit solutions emerging from the system-oriented approach.     

Adaptive and economic data representation in control architectures of autonomous real-world robots

Learning algorithms for autonomous robots in complex, real-world environments usually have to deal with many degrees of freedom and continuous state spaces. Reinforcement learning is a promising concept for unsupervised learning, but common algorithms suffer from huge storage and calculation requirements if they are used to construct an internal model by estimating a value-function for every action in every possible state. In our attempt to approximate this function at the lowest cost, we introduce a flexible method that focuses on the states of greatest interest, and interpolates between them with a fast and easy-to-implement algorithm. In order to provide the highest accuracy to any predefined limit, we enhanced this algorithm by a fast converging multilayer error approximator. This work was presented in part at the Sixth International Symposium on Artificial Life and Robotics, Tokyo, January 15–17, 2001