Contributions in Merlin

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Many companies react to competitors’ acquisition sprees refl exively, by launching bids of their own. Smart managers should consider other moves.

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The control of compliant robots is, due to their often nonlinear and complex dynamics, inherently difficult. The vision of morphological computation proposes to view these aspects not only as problems, but rather also as parts of the solution. Non-rigid body parts are not seen anymore as imperfect realizations of rigid body parts, but rather as potential computational resources. The applicability of this vision has already been demonstrated for a variety of complex robot control problems. Nevertheless, a theoretical basis for understanding the capabilities and limitations of morphological computation has been missing so far. We present a model for morphological computation with compliant bodies, where a precise mathematical characterization of the potential computational contribution of a complex physical body is feasible. The theory suggests that complexity and nonlinearity, typically unwanted properties of robots, are desired features in order to provide computational power. We demonstrate that simple generic models of physical bodies, based on mass-spring systems, can be used to implement complex nonlinear operators. By adding a simple readout (which is static and linear) to the morphology such devices are able to emulate complex mappings of input to output streams in continuous time. Hence, by outsourcing parts of the computation to the physical body, the difficult problem of learning to control a complex body, could be reduced to a simple and perspicuous learning task, which can not get stuck in local minima of an error function.

During the last three decades, scholars from communication studies, political science, sociology, cultural anthropology and management science have studied the characteristics and dynamics of meetings from different perspectives. This has resulted in a large, though very fragmented, body of knowledge about meetings and their different functions in the organization. So far, however, this knowledge has not been systematically related to the strategy process. The purpose of this review is to organize the different literatures by identifying the meeting functions (coordination, cognitive, political, symbolic and social) as well as the meeting practices (initiation, conduct and termination practices) and by outlining the impact of meetings on the strategy process. This results in an integrative framework which synthesizes the literature and which serves as a guide for future research.

The purpose of this paper is to develop tracing of lineage and provenance techniques for temporal databases. Using the snapshot reducibility property of temporal databases we will define a pointwise lineage traceability for temporal databases. Merging time points with the same lineage in the result of temporal operators allows an interval-based model by still allowing lineage traceability. On examples we show the algebra and it lineage. To trace lineage we need to materialize intermediate results. Moreover, lineage tells us only about the tuples that contribute and not how they contribute to the result query. That is why we further define relations annotated with provenance semirings. To be able to to perform queries on such relations we generalize the algebra to operate on them, so that query execution propagates provenance information. Finally, we define positive relational algebra, which propagates how-provenance.

Direct volume visualization has become an important tool in many domains for visualizing and examining volumetric datasets. The tremendous increase in computing power of the hardware over the past years makes it possible to immediately visualize volumetric datasets obtained from scanning devices at fully interactive frame rates. However, despite this change of paradigm compared to the slow offline methods of the past, direct volume visualization suffers from disadvantages constricting an immediate, reliable analysis of volumetric datasets.This thesis begins with an overview of different methods for direct volume visualization followed by an in-depth review of the theoretical foundation including inherent challenges. Subsequently selected state-of-the-art techniques used in this thesis are explained in detail. One challenge that all techniques have in common is the dependency on good transfer functions. Only good transfer functions allow for the right insight into the dataset permitting a reliable analysis. These transfer functions are often constructed manually in a time consuming and cumbersome trial-and-error process. We propose an automated general purpose approach for generating a set of best transfer functions based on information theory. Our algorithm appraises the information content of the images generated by a particular transfer function when rotating the dataset, as it is the case in interactive sessions. Quantifying the quality of a transfer function in this way enables a directed search for the set of best transfer functions in a feedback loop employing a combination of two different optimization algorithms. This set of best, distinct transfer functions helps the user to gain an immediate overview of each facet of a dataset.When visualizing volumetric datasets, it is of major importance that domain experts are able to recognize small features, to distinguish the relationship and connectivity between them and to get the right perception. For this the applied illumination and shading model plays an important part. Sophisticated models including realistic looking directional shadows, ambient occlusion and color bleeding effects can greatly enhance the perception. Unfortunately common models exhibiting these effects are expensive to compute and not suitable for interactive applications. We present a method showing how these effects can be applied to GPU volume ray-casting while fully maintaining interactivity based on the original, exponential extinction coefficient of the volume rendering integral. Exploiting the fact that the original, exponential extinction coefficient is summable, our framework is built on top of a 3D summed area table that allows for quick lookups of extinction queries.Technically volumetric datasets consist of discrete scalar or sometimes vector data. As the resolution of this data hardly ever fits the resolution of the output device, the data needs to be interpolated or reconstructed. Volume visualization methods based on 3D textures can profit from fast built-in trilinear interpolation of the hardware. However, trilinear interpolation is not the first choice when it comes to image quality. Volume splatting on the other hand is a volume visualization technique that makes it easy to integrate arbitrary interpolation schemes. The performance of volume splatting is directly related to the applied interpolation scheme and the resulting interpolation kernel respectively. In this thesis we introduce an algorithm for volume splatting that greatly enhances the performance by reducing the required amount of splatting operations from interpolation kernel slices. Further, we show how the image quality of volume visualization can be enhanced by using the original, exponential extinction coefficient of the volume rendering integral instead of common alpha-blending simplifications.