Geförderte OA-Publikationen

Artificial intelligence (AI) has become a part of the mainstream public discourse beyond expert communities about its risks, benefits, and need for regulation. In particular, since 2014, the news media have intensified their coverage of this emerging technology and its potential impact on most domains of society. Although many studies have analyzed traditional media coverage of AI, analyses of social media, especially video-sharing platforms, are rare. In addition, research from a risk communication perspective remains scarce, despite the widely recognized potential threats to society from many AI applications. This study aims to detect recurring patterns of societal threat/efficacy in YouTube videos, analyze their main sources, and compare detected frames in terms of reach and response. Using a theoretical framework combining framing and risk communication, the study analyzed the societal threat/efficacy attributed to AI in easily accessible YouTube videos published in a year when public attention to AI temporarily peaked (2018). Four dominant AI frames were identified: the balanced frame, the high-efficacy frame, the high-threat frame, and the no-threat frame. The balanced and no-threat frames were the most prevalent, with predominantly positive and neutral AI narratives that neither adequately address the risks nor the necessary societal response from a normative risk communication perspective. The results revealed the specific risks and benefits of AI that are most frequently addressed. Video views and user engagement with AI videos were analyzed. Recommendations for effective AI risk communication and implications for risk governance were derived from the results.

Understanding turbulent thermal convection is essential for modeling many natural phenomena. This study investigates the spatiotemporal dynamics of the vortical structures in the mid-plane of turbulent Rayleigh-Bénard convection in SF6 via experiments. For this, a Rayleigh-Bénard cell of aspect ratio 10 is placed inside a pressure vessel and pressurized up to 1, 1.5, and 2.5 bar in order to reach Rayleigh numbers of Ra = 9.4 × 10^5, 2.0 × 10^6, and 5.5 × 10^6, respectively. For all three cases, the Prandtl number is Pr = 0.79 and Δ T ≈ 7 K. Then, stereoscopic particle image velocimetry is conducted to measure the three velocity components in the horizontal-mid-plane for 5.78 × 10^3 free fall times. For the given aspect ratio, the flow is no longer dominated by the side walls of the cell and turbulent superstructures that show a two-dimensional repetitive organization form. These superstructures show diverse shapes with faster dissipation rates as Ra increases. Out-of-plane vortices are the main feature of the flow. As Ra increases, the number of these vortices also increases, and their size shrinks. However, their total number is almost constant for each Ra through the measurement period. Furthermore, their occurrence is random and does not depend on whether the flow is upward-heated, downward-cooled, or horizontally directed. Vortex tracking was applied to measure lifetime, displacement, and traveled distance of these structures. The relation between lifetime and traveled distance is rather linear. Interestingly, in the vortex centers, the out-of-plane momentum transport is larger in comparison to the bulk flow. Therefore, these vortices will play a major role in the heat transport in such flows.

The tuning of the self-propagating reaction is studied theoretically by introducing a non-reactive material between two reactive material elements. For the study, the Ni/Al bilayer system was chosen. The Ni/Al elements were placed on a silicon wafer covered with a 1-µm-thick silicon dioxide. The spaces between the multilayer reactive material elements were filled with different non-reactive materials covering a wide range of thermal properties. On top of this heterogeneous layer, a 1-µm-thick sealing layer was placed consisting of the filler material. The carried out two-dimensional simulations demonstrated that embedding material allows to scale the ignition transfer time and the heat propagation velocity. For example, for a transfer length of 1 µm, the ignition time can be tuned from nano- to microseconds. Consequently, in contrast to previous results embedding materials allow scaling the properties of the self-propagating reaction in heterogeneous reactive material systems.

Evolving software is a highly complex and creative problem in which a number of different strategies are used to solve the tasks at hand. These strategies and reoccurring coding patterns can offer insights into the process. However, they can be highly project or even task-specific. We aim to identify code change patterns in order to draw conclusions about the software development process. For this, we propose a novel way to calculate high-level file overarching diffs, and a novel way to parallelize pattern mining. In a study of 1000 Java projects, we mined and analyzed a total of 45,000 patterns. We present 13 patterns, showing extreme points of the 7 pattern categories we identified. We found that a large number of high-level change patterns exist and occur frequently. The majority of mined patterns were associated with a specific project and contributor, where and by whom it was more likely to be used. While a large number of different code change patterns are used, only a few, mostly unsurprising ones, are common under all circumstances. The majority of code change patterns are highly specific to different context factors that we further explore.

The paper presents the comparison of two different continuous-time adaptive control strategies applied to the temperature stabilization of molten glass during conditioning. Both control methods include on-line linear continuous-time model parameter identification using a nonstandard procedure based on the modulating functions method. The related control task is of great practical importance because it directly affects the quality of manufactured glass containers. The molten glass temperature must be stabilized with accuracy of about 1C˚ which can be very difficult. At the core of this work, the synthesis of a nonstandard adaptive control procedure is described that consists of a linear quadratic regulator (LQR) being fed with process parameters and state estimates. These new state estimates are generated with a special transform and reconstructed by a special type of modulating function state observer consisting of two modulating function based soft-sensors which rely on a continuous-time model. However, an equally important issue of this investigation is the efficiency and accuracy of the algorithm. To this end, the described stabilization method will be compared with a standard continuous-time model predictive control (MPC) approach that was used in the authors’ previous research on the continuous molten glass temperature stabilization in a single glass forehearth zone. Simulation results based on experimental calibration data are presented and compared for these two approaches. It turns out that the first method with LQR is simpler than the MPC approach while maintaining the same level of accuracy and quality of control.