Finite element modeling concepts and linear analyses of 3D regular open cell structures

Various Finite Element modeling concepts and linear analyses of 3D regular cellular solids (lattice structures) with relative densities ranging from 10% to 20% are presented. Continuum element based models and beam element based models are employed, the latter with and without an adaptation of stiffness in the vicinity of the vertices. Space filling unit cell models are used for a constitutive characterization of four different structures in terms of density and directional dependence of their Young's moduli. Finite structure models of different size are simulated for investigating the influence of free surfaces and being compared to results of uniaxial compression tests of samples fabricated by two different Rapid Prototyping techniques.     

Ecological performance of electrical consumer products: the influence of automation and information-based measures

Being concerned with the environmental impact of electrical consumer products, this article examines possibilities of influencing ecological user performance through design features. Furthermore, it looks at the relationship of user characteristics and ecological performance. The impact of level of automation and type of control labelling on ecological user performance was examined in a lab-based experimental scenario with 36 users. In addition to performance indicators, a range of user variables (e.g., self-reported domestic behaviour, environmental knowledge and attitude) was measured to assess their influence on user behaviour. The results showed that low-level automation improved ecological performance whereas no such positive effect was observed for enhanced display-control labelling. Furthermore, the results suggested that the user's mental model of ecological performance was rather limited. No relationship was found between environmental knowledge, attitude and performance. The findings pointed at the strong prevalence of habits in the domestic domain. The implications of the results for designers of consumer products are discussed.     

Europeanist-programme roadmap for optical communications generated by theoptimist thematic network

On the basis of Europeanist project results in the field of photonics, theoptimist thematic network has produced a roadmap for optical communications. This work is described in the present article which provides scenarios for the evolution of the optical network in the coming 10 years. Predictable developments in optical components, sub-systems and systems and their consequences on the architecture and performances of the networks are analysed. Specific interest is focused on the various parts of the network structure namely the access, the metropolitan area, the wide area and the global networks. Technical documents elaborated by theoptimist consortium and minutes fromist workshops can be found on the website http://www.ist-optimist.org/.[1]. They constitute a main source for further information.     

Coupled Action Recognition and Pose Estimation from Multiple Views

Action recognition and pose estimation are two closely related topics in understanding human body movements; information from one task can be leveraged to assist the other, yet the two are often treated separately. We present here a framework for coupled action recognition and pose estimation by formulating pose estimation as an optimization over a set of action-specific manifolds. The framework allows for integration of a 2D appearance-based action recognition system as a prior for 3D pose estimation and for refinement of the action labels using relational pose features based on the extracted 3D poses. Our experiments show that our pose estimation system is able to estimate body poses with high degrees of freedom using very few particles and can achieve state-of-the-art results on the HumanEva-II benchmark. We also thoroughly investigate the impact of pose estimation and action recognition accuracy on each other on the challenging TUM kitchen dataset. We demonstrate not only the feasibility of using extracted 3D poses for action recognition, but also improved performance in comparison to action recognition using low-level appearance features.     

The influence of product aesthetics and usability over the course of time: a longitudinal field experiment

A longitudinal field experiment was carried out over a period of 2 weeks to examine the influence of product aesthetics and inherent product usability. A 2 × 2 × 3 mixed design was used in the study, with product aesthetics (high/low) and usability (high/low) being manipulated as between-subjects variables and exposure time as a repeated-measures variable (three levels). A sample of 60 mobile phone users was tested during a multiple-session usability test. A range of outcome variables was measured, including performance, perceived usability, perceived aesthetics and emotion. A major finding was that the positive effect of an aesthetically appealing product on perceived usability, reported in many previous studies, began to wane with increasing exposure time. The data provided similar evidence for emotion, which also showed changes as a function of exposure time. The study has methodological implications for the future design of usability tests, notably suggesting the need for longitudinal approaches in usability research. PRACTITIONER SUMMARY: This study indicates that product aesthetics influences perceived usability considerably in one-off usability tests but this influence wanes over time. When completing a usability test it is therefore advisable to adopt a longitudinal multiple-session approach to reduce the possibly undesirable influence of aesthetics on usability ratings.     

How mold inserts influence the replication of metallic microparts produced by electroplating into two-component templates

Multi-component injection molding combined with electroplating, the so-called MSG process, represents a promising process chain to replicate metallic microstructures. MSG is the German acronym of ‘Mehrkomponenten-Spritzgießen und Galvanoformung’, in English ‘Multi-component Injection Molding and Electroplating’. The process is based on the highly accurate reproduction of surface details through injection molding to build a microstructure into a two-component template and electrodeposition of e.g. nickel into this cavity. This electroplated micropart is the replication of the former structure. To study the influence of the mold insert on the accuracy of the molded part and the produced microparts, a test specimen was fabricated and analyzed using a milled mold insert. On the mold insert, three microcoil parts, the components of a microgripper, were micromilled. The effect of the individual process steps on the surface quality and dimensional changes of the final microcoil will be presented. It will also be shown how the quality of the injection molding insert influences the dimensional accuracy of the produced microparts. Finally, potential process improvements will be outlined.     

Where do machine learning and human-computer interaction meet?

Implementation of machine learning (ML) in human-computer interaction (HCI) work is not trivial. This article reports on a survey of 112 professionals and academicians specializing in HCI, who were asked to state level of ML use in HCI work. Responses were captured via a structured questionnaire. Analysis showed that about one-third of those who participated in the survey had used ML in conjunction with a variety of different HCI tasks. However, statistically significant differences could not be identified between those who have and those who have not used ML. Using statistics, contingency analysis, and clustering, we modeled interaction between representative HCI tasks and ML paradigms. We discovered that neural networks, rule induction, and statistical learning emerged as the most popular ML paradigms across HCI workers, although intensive learning, such as inductive logic programming, are gaining popularity among application developers. We also discovered that the leading causes for declining use of ML in HCI work are (1) misperceptions about ML, (2) lack of awareness of ML's potential, and (3) scarcity of concrete case studies demonstrating the application of ML in HCI.     

Mapping reactive flow patterns in monolithic nanoporous catalysts

The development of high-efficiency porous catalyst membranes critically depends on our understanding of where the majority of the chemical conversions occur within the porous structure. This requires mapping of chemical reactions and mass transport inside the complex nanoscale architecture of porous catalyst membranes which is a multiscale problem in both the temporal and spatial domains. To address this problem, we developed a multiscale mass transport computational framework based on the lattice Boltzmann method that allows us to account for catalytic reactions at the gas–solid interface by introducing a new boundary condition. In good agreement with experiments, the simulations reveal that most catalytic reactions occur near the gas-flow facing side of the catalyst membrane if chemical reactions are fast compared to mass transport within the porous catalyst membrane.     

Live modeling in the context of state machine models and code generation

Software and Systems Modeling - Live modeling has been recognized as an important technique to edit behavioral models while being executed and helps in better understanding the impact of a design...     

Hough forests for object detection, tracking, and action recognition

Abstract—The paper introduces Hough forests, which are random forests adapted to perform a generalized Hough transform in an efficient way. Compared to previous Hough-based systems such as implicit shape models, Hough forests improve the performance of the generalized Hough transform for object detection on a categorical level. At the same time, their flexibility permits extensions of the Hough transform to new domains such as object tracking and action recognition. Hough forests can be regarded as task-adapted codebooks of local appearance that allow fast supervised training and fast matching at test time. They achieve high detection accuracy since the entries of such codebooks are optimized to cast Hough votes with small variance and since their efficiency permits dense sampling of local image patches or video cuboids during detection. The efficacy of Hough forests for a set of computer vision tasks is validated through experiments on a large set of publicly available benchmark data sets and comparisons with the state-of-the-art.