Erweiterung des epistemologischen Verständnisses durch Konfrontation mit anomalen Daten. - Pollmeier, Pascal; Fechner, Sabine (Naturwissenschaftlicher Unterricht und Lehrerbildung im Umbruch?)

Guaranteeing Properties of Reconfigurable Hardware Circuits with Proof-Carrying Hardware - Wiersema, Tobias
Previous research in proof-carrying hardware has established the feasibility and utility of the approach, and provided a concrete solution for employing it for the certification of functional equivalence checking against a specification, but fell short in connecting it to state-of-the-art formal verification insights, methods and tools. Due to the immense complexity of modern circuits, and verification challenges such as the state explosion problem for sequential circuits, this restriction of readily-available verification solutions severely limited the applicability of the approach in wider contexts. This thesis closes the gap between the PCH approach and current advances in formal hardware verification, provides methods and tools to express and certify a wide range of circuit properties, both functional and non-functional, and presents for the first time prototypes in which circuits that are implemented on actual reconfigurable hardware are verified with PCH methods. Using these results, designers can now apply PCH to establish trust in more complex circuits, by using more diverse properties which they can express using modern, efficient property specification techniques.
Keywords: Proof-Carrying Hardware; Formal Verification; Sequential Circuits; Non-Functional Properties; Functional Properties

Examination of hazardous situations in industrial closed-loop processes using dynamic simulations - Bothe, Mike; Lutters, Nicole; Kenig, Eugeny (Chemical Engineering Transactions)

Option Implied Tax Rate Expectations - Eberbach, Jelena; Sureth-Sloane, Caren; Uhrig-Homburg, Marliese

TaintBench: Automatic real-world malware benchmarking of Android taint analyses - Luo, Linghui; Pauck, Felix; Piskachev, Goran; Benz, Manuel; Pashchenko, Ivan; Mory, Martin; Bodden, Eric; Hermann, Ben; Massacci, Fabio (Empirical Software Engineering)
Due to the lack of established real-world benchmark suites for static taint analyses of Android applications, evaluations of these analyses are often restricted and hard to compare. Even in evaluations that do use real-world apps, details about the ground truth in those apps are rarely documented, which makes it difficult to compare and reproduce the results. To push Android taint analysis research forward, this paper thus recommends criteria for constructing real-world benchmark suites for this specific domain, and presents TaintBench, the first real-world malware benchmark suite with documented taint flows. TaintBench benchmark apps include taint flows with complex structures, and addresses static challenges that are commonly agreed on by the community. Together with the TaintBench suite, we introduce the TaintBench framework, whose goal is to simplify real-world benchmarking of Android taint analyses. First, a usability test shows that the framework improves experts’ performance and perceived usability when documenting and inspecting taint flows. Second, experiments using TaintBench reveal new insights for the taint analysis tools Amandroid and FlowDroid: (i) They are less effective on real-world malware apps than on synthetic benchmark apps. (ii) Predefined lists of sources and sinks heavily impact the tools’ accuracy. (iii) Surprisingly, up-to-date versions of both tools are less accurate than their predecessors.

К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН - Lugovtsova, Yevgeniya; Zeipert, Henning; Johannesmann, Sarah; Nicolai, Marcel; Prager, Jens; Henning, Bernd (МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская школа-конференция)

Entwicklung von Praxiskompetenz durch Kooperationsprozesse von Lehrkräften - Bloh, Thiemo (Zeitschrift für Bildungsforschung)
Zusammenfassung Lehrkräftekooperation wird generell eine positive Bedeutung in Bezug auf Schul- und Unterrichtsentwicklung zugeschrieben. Dabei sind empirische Belege für eine positive Wirksamkeit nach wie vor kaum vorhanden, es gibt sogar Befunde zu ‚negativen‘ Konsequenzen von Lehrkräftekooperation. Um diese Widersprüchlichkeit zu klären, wurde in der vorliegenden Arbeit Kooperation nicht als Instrument bzw. als Technik betrachtet, sondern als soziale Praxis verstanden, in der eigenlogisches, kollektiv-implizites Wissen (re)produziert wird (Community of Practice). Parallel dazu wurde ein praxeologisches Kompetenzverständnis (Praxiskompetenz) eingeführt, das wesentlich auf die Praxeologie Pierre Bourdieus zurückgeht und den Zusammenhang zwischen Lehrkräftekooperation als Community of Practice und kollektiv strukturierter, individueller Kompetenz theoretisch verdeutlicht. Die empirischen Befunde, welche mittels der Dokumentarischen Methode generiert wurden, verweisen auf die Bedeutung unterschiedlicher Relationslogiken (Nicht-Passung, Entfaltung, Herausforderung) für das ‚Lernen‘ von oder innerhalb von Praxiskompetenz(en) und damit auch auf die Wichtigkeit einer grundlegend kollektiv gerahmten Perspektive auf Lehrkräftekooperation. Vor diesem Hintergrund ist ein allzu positiver Blick auf Lehrkräftekooperationsprozesse kritisch zu betrachten.

Far-Field Automatic Speech Recognition - Haeb-Umbach, Reinhold; Heymann, Jahn; Drude, Lukas; Watanabe, Shinji; Delcroix, Marc; Nakatani, Tomohiro (Proceedings of the IEEE)
The machine recognition of speech spoken at a distance from the microphones, known as far-field automatic speech recognition (ASR), has received a significant increase of attention in science and industry, which caused or was caused by an equally significant improvement in recognition accuracy. Meanwhile it has entered the consumer market with digital home assistants with a spoken language interface being its most prominent application. Speech recorded at a distance is affected by various acoustic distortions and, consequently, quite different processing pipelines have emerged compared to ASR for close-talk speech. A signal enhancement front-end for dereverberation, source separation and acoustic beamforming is employed to clean up the speech, and the back-end ASR engine is robustified by multi-condition training and adaptation. We will also describe the so-called end-to-end approach to ASR, which is a new promising architecture that has recently been extended to the far-field scenario. This tutorial article gives an account of the algorithms used to enable accurate speech recognition from a distance, and it will be seen that, although deep learning has a significant share in the technological breakthroughs, a clever combination with traditional signal processing can lead to surprisingly effective solutions.

A Comparison of Multi-View Learning Strategies for Satellite Image-based Real Estate Appraisal - Kucklick, Jan-Peter; Müller, Oliver (The AAAI-21 Workshop on Knowledge Discovery from Unstructured Data in Financial Services)

Derivative-Free Multiobjective Trust Region Descent Method Using Radial Basis Function Surrogate Models - Berkemeier, Manuel Bastian; Peitz, Sebastian (Mathematical and Computational Applications)
We present a flexible trust region descend algorithm for unconstrained and convexly constrained multiobjective optimization problems. It is targeted at heterogeneous and expensive problems, i.e., problems that have at least one objective function that is computationally expensive. The method is derivative-free in the sense that neither need derivative information be available for the expensive objectives nor are gradients approximated using repeated function evaluations as is the case in finite-difference methods. Instead, a multiobjective trust region approach is used that works similarly to its well-known scalar pendants. Local surrogate models constructed from evaluation data of the true objective functions are employed to compute possible descent directions. In contrast to existing multiobjective trust region algorithms, these surrogates are not polynomial but carefully constructed radial basis function networks. This has the important advantage that the number of data points scales linearly with the parameter space dimension. The local models qualify as fully linear and the corresponding general scalar framework is adapted for problems with multiple objectives. Convergence to Pareto critical points is proven and numerical examples illustrate our findings.