Distributed information service architecture for overlapping multiaccess networks

Multimedia delivery in mobile multiaccess network environments has emerged as a key area within the future Internet research domain. When network heterogeneity is coupled with the proliferation of multiaccess capabilities in mobile handheld devices, one can expect many new avenues for developing novel services and applications. New mechanisms for audio/video delivery over multiaccess networks will define the next generation of major distribution technologies, but will require significantly more information to operate according to their best potential. In this paper we present and evaluate a distributed information service, which can enhance media delivery over such multiaccess networks. We describe the proposed information service, which is built upon the new distributed control and management framework (DCMF) and the mobility management triggering functionality (TRG). We use a testbed which includes 3G/HSPA, WLAN and WiMAX network accesses to evaluate our proposed architecture and present results that demonstrate its value in enhancing video delivery and minimizing service disruption in an involved scenario.     

Information-based adaptive fast-forward for visual surveillance

Automated video analysis lacks reliability when searching for unknown events in video data. The practical approach is to watch all the recorded video data, if applicable in fast-forward mode. In this paper we present a method to adapt the playback velocity of the video to the temporal information density, so that the users can explore the video under controlled cognitive load. The proposed approach can cope with static changes and is robust to video noise. First, we formulate temporal information as symmetrized Rényi divergence, deriving this measure from signal coding theory. Further, we discuss the animated visualization of accelerated video sequences and propose a physiologically motivated blending approach to cope with arbitrary playback velocities. Finally, we compare the proposed method with the current approaches in this field by experiments and a qualitative user study, and show its advantages over motion-based measures.     

Compressed Word Problems in HNN-extensions and?Amalgamated Products

It is shown that the compressed word problem for an HNN-extension ??H,t?Ot ^?1 at=?(a) (a??A)?? with A finite is polynomial time Turing-reducible to the compressed word problem for the base group H. An analogous result for amalgamated free products is shown as well.     

Interactive High‐Quality Visualization of Higher‐Order Finite Elements

Higher‐order finite element methods have emerged as an important discretization scheme for simulation. They are increasingly used in contemporary numerical solvers, generating a new class of data that must be analyzed by scientists and engineers. Currently available visualization tools for this type of data are either batch oriented or limited to certain cell types and polynomial degrees. Other approaches approximate higher‐order data by resampling resulting in trade‐offs in interactivity and quality. To overcome these limitations, we have developed a distributed visualization system which allows for interactive exploration of non‐conforming unstructured grids, resulting from space‐time discontinuous Galerkin simulations, in which each cell has its own higher‐order polynomial solution. Our system employs GPU‐based raycasting for direct volume rendering of complex grids which feature non‐convex, curvilinear cells with varying polynomial degree. Frequency‐based adaptive sampling accounts for the high variations along rays. For distribution across a GPU cluster, the initial object‐space partitioning is determined by cell characteristics like the polynomial degree and is adapted at runtime by a load balancing mechanism. The performance and utility of our system is evaluated for different aeroacoustic simulations involving the propagation of shock fronts.     

Maximum likelihood analysis of algorithms and data structures

We present a new approach for an average-case analysis of algorithms and data structures that supports a non-uniform distribution of the inputs and is based on the maximum likelihood training of stochastic grammars. The approach is exemplified by an analysis of the expected size of binary tries as well as by three sorting algorithms and it is compared to the known results that were obtained by traditional techniques. Investigating traditional settings like the random permutation model, we rediscover well-known results formerly derived by pure analytic methods; changing to biased data yields original results. All but one step of our analysis can be automated on top of a computer-algebra system. Thus our new approach can reduce the effort required for an average-case analysis, allowing for the consideration of realistic input distributions with unknown distribution functions at the same time. As a by-product, our approach yields an easy way to generate random combinatorial objects according to various probability distributions.     

From Images to Shape Models for Object Detection

We present an object class detection approach which fully integrates the complementary strengths offered by shape matchers. Like an object detector, it can learn class models directly from images, and can localize novel instances in the presence of intra-class variations, clutter, and scale changes. Like a shape matcher, it finds the boundaries of objects, rather than just their bounding-boxes. This is achieved by a novel technique for learning a shape model of an object class given images of example instances. Furthermore, we also integrate Hough-style voting with a non-rigid point matching algorithm to localize the model in cluttered images. As demonstrated by an extensive evaluation, our method can localize object boundaries accurately and does not need segmented examples for training (only bounding-boxes).     

Ceramic micro parts produced by micro injection molding: latest developments

Powder injection molding is a preferred technology for the production of micro parts or microstructured parts. Derived from the well known thermoplastic injection molding technique it is suitable for a large-scale production of ceramic and metallic parts without final machining. To achieve good surface quality and control the part size and distortions is an important goal to allow mass production. This means that all process steps like part design adjusted for MIM/CIM-technology, appropriate choice of powder and binder components and injection molding simulation to design the sprue are required. Concerning the injection molding itself high quality mold inserts, high-precision injection molding with suitable molding machines like Battenfeld Microsystem50 or standard machine with special equipment like variotherm or evacuation of the molding tool and an adjusted debinding and sintering process have to be available. Results of producing micro parts by powder injection molding of ceramic feedstock will be presented.     

Estimation of Detection Thresholds for Redirected Walking Techniques

In immersive virtual environments (IVEs), users can control their virtual viewpoint by moving their tracked head and walking through the real world. Usually, movements in the real world are mapped one-to-one to virtual camera motions. With redirection techniques, the virtual camera is manipulated by applying gains to user motion so that the virtual world moves differently than the real world. Thus, users can walk through large-scale IVEs while physically remaining in a reasonably small workspace. In psychophysical experiments with a two-alternative forced-choice task, we have quantified how much humans can unknowingly be redirected on physical paths that are different from the visually perceived paths. We tested 12 subjects in three different experiments: (E1) discrimination between virtual and physical rotations, (E2) discrimination between virtual and physical straightforward movements, and (E3) discrimination of path curvature. In experiment E1, subjects performed rotations with different gains, and then had to choose whether the visually perceived rotation was smaller or greater than the physical rotation. In experiment E2, subjects chose whether the physical walk was shorter or longer than the visually perceived scaled travel distance. In experiment E3, subjects estimate the path curvature when walking a curved path in the real world while the visual display shows a straight path in the virtual world. Our results show that users can be turned physically about 49 percent more or 20 percent less than the perceived virtual rotation, distances can be downscaled by 14 percent and upscaled by 26 percent, and users can be redirected on a circular arc with a radius greater than 22 m while they believe that they are walking straight.     

Integrated cost/weight optimization of aircraft structures

A methodology for a combined cost/weight optimization of aircraft components is proposed. The objective function is formed by a simplified form of direct operating cost, i.e. by a weighted sum of the manufacturing cost and the component weight. Hence, the structural engineer can perform the evaluation of a design solution based on economical values rather than pure cost or weight targets. The parameter that governs the balance between manufacturing cost and weight is called weight penalty and incorporates the effect of fuel burn, environmental impact or contractual penalties due to overweight. Unlike previous work, the analytical cost model and structural models are replaced by commercially available software packages that allow a more realistic model of the manufacturing costs; further, arbitrary constraints for the structural analysis can be implemented. By means of parametric studies it is shown that the design solution strongly depends on the magnitude of the weight penalty.