Geförderte OA-Publikationen

Changes in organizational structure affect the intra-organizational communication network. However, despite an increasing relevance of less hierarchical and less bureaucratic forms of organizing, the question of how self-managing forms of organization influence employees’ communication behavior has received only scant attention yet. In our study, we analyze the case of a medium-sized firm that experiences organizational change from rigid bureaucratic structures to a more self-managing organization model and question how employees’ centrality in the communication network is affected by this reorganization. Following an explorative research approach informed by prior research on self-managing forms of organizations and communication networks, our findings show that after the change process communication generally is less dependent on formal hierarchy. However, while employees who held a higher rank before the change process loose in centrality, their centrality at the end of the change process is still higher than that of other employees. Moreover, employees who experience a promotion become more central in the communication network while demotions do not have an effect. By discussing these findings in the context of organizational change and the persistence of organizational structures, we contribute to a more comprehensive understanding of the implementation process of self-managing organizations.

Many speech processing systems struggle in conditions with low signal-to-noise ratios and in changing acoustic environments. Adaptation at the transduction level with integrated signal processing could help to address this; in human hearing, transduction and signal processing are integrated and can be adaptively tuned for noisy conditions. Here we report a microelectromechanical cochlea as a bio-inspired acoustic sensor with integrated signal processing functionality. Real-time feedback is used to tune the sensing and processing properties, and dynamic switching between linear and nonlinear characteristics improves the detection of signals in noisy conditions, increases the sensor dynamic range and enables adaptation to changing acoustic environments. The transition to nonlinear behaviour is attributed to a Hopf bifurcation and we experimentally validate its dependence on sensor and feedback parameters. We also show that output-signal coupling between two coupled sensors can increase the frequency coverage.

Reactive aluminum-nickel multilayer system shows exothermic energetic materials which act as a heat source for packaging and bonding of microsystems. The main challenge is controlling the self-propagation reaction velocity and temperature generated by thermal management through different thermal conductive substrate materials. The current work investigates the heat distribution of Al/Ni multilayer foils from different thermal conductive substrates which act as heat sink materials during the self-propagating reaction. A two-dimensional numerical model was developed to study thermal conductive heat loss and substrate thermal properties on the self-propagating reaction in Al/Ni multilayer foils. The self-propagating reaction was introduced on the surface of the foils by an electrical spark. Here we investigate the minimum critical thickness of Al/Ni multilayer foils which shows the self-propagation reaction on different substrates and verified from the two-dimensional numerical model. The outcomes of this investigation will facilitate the integration of Al/Ni multilayer foils on different substrates as intrinsic heat sources for different applications of micro/nanodevices.

In many research fields, human-annotated data plays an important role as it is used to accomplish a multitude of tasks. One such example is in the field of multimedia quality assessment where subjective annotations can be used to train or evaluate quality prediction models. Lab-based tests could be one approach to get such quality annotations. They are usually performed in well-defined and controlled environments to ensure high reliability. However, this high reliability comes at a cost of higher time consumption and costs incurred. To mitigate this, crowd or online tests could be used. Usually, online tests cover a wider range of end devices, environmental conditions, or participants, which may have an impact on the ratings. To verify whether such online tests can be used for visual quality assessment, we designed three online tests. These online tests are based on previously conducted lab tests as this enables comparison of the results of both test paradigms. Our focus is on the quality assessment of high-resolution images and videos. The online tests use AVrate Voyager, which is a publicly accessible framework for online tests. To transform the lab tests into online tests, dedicated adaptations in the test methodologies are required. The considered modifications are, for example, a patch-based or centre cropping of the images and videos, or a randomly sub-sampling of the to-be-rated stimuli. Based on the analysis of the test results in terms of correlation and SOS analysis it is shown that online tests can be used as a reliable replacement for lab tests albeit with some limitations. These limitations relate to, e.g., lack of appropriate display devices, limitation of web technologies, and modern browsers considering support for different video codecs and formats.

AI-generated images have gained in popularity in recent years due to improvements and developments in the field of artificial intelligence. This has led to several new AI generators, which may produce realistic, funny, and impressive images using a simple text prompt. DALL-E-2, Midjourney, and Craiyon are a few examples of the mentioned approaches. In general, it can be seen that the quality, realism, and appeal of the images vary depending on the used approach. Therefore, in this paper, we analyze to what extent such AI-generated images are realistic or of high appeal from a more photographic point of view and how users perceive them. To evaluate the appeal of several state-of-the-art AI generators, we develop a dataset consisting of 27 different text prompts, with some of them being based on the DrawBench prompts. Using these prompts we generated a total of 135 images with five different AI-Text-To-Image generators. These images in combination with real photos form the basis of our evaluation. The evaluation is based on an online subjective study and the results are compared with state-of-the-art image quality models and features. The results indicate that some of the included generators are able to produce realistic and highly appealing images. However, this depends on the approach and text prompt to a large extent. The dataset and evaluation of this paper are made publicly available for reproducibility, following an Open Science approach.