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Sabbatical semester report
(2020)
Schreiben im Studium
(2020)
Sollte das wissenschaftliche Schreiben als allgemeine Wissenschaftssprache vermittelt werden oder sollten die sprachlichen Anforderungen in den jeweiligen Disziplinen berücksichtigt werden? Die Antwort auf diese Frage hängt auch davon ab, wie stark sich die Wissenschaftssprachen unterscheiden. In der vorliegenden Studie wurden wissenschaftssprachliche Besonderheiten anhand zweier Korpora untersucht, die deutschsprachige Dissertationen der Fächer Betriebswirtschaftslehre (BWL) bzw. Maschinenbau (MB) umfassten und in denen der Gebrauch von Mehrworteinheiten (z.B. im vergleich zu den) verglichen wurde. Die Untersuchung verdeutlicht den unterschiedlichen Gebrauch der Mehrworteinheiten zwischen den Disziplinen: Nur vierzehn der 50 häufigsten Mehrworteinheiten wurden in beiden Korpora genutzt. Die Ergebnisse werden mit Blick auf die Vermittlung des wissenschaftlichen Schreibens erörtert. Es werden Überlegungen zur Weiterentwicklung der Methode angestellt und es wird diskutiert, wie die Korpuslinguistik die Schreibvermittlung im Studium unterstützen könnte.
Seamless-Learning-Plattform
(2020)
This paper presents the goals, service design approach, and the results of the project “Accessible Tourism around Lake Constance”, which is currently run by different universities, industrial partners and selected hotels in Switzerland, Germany and Austria. In the 1st phase, interviews with different persons with disabilities and elderly persons have been conducted to identify the barriers and pains faced by tourists who want to spend their holidays in the region of Lake Constance as well as possible assistive technologies that help to overcome these barriers. The analysis of the interviews shows that one third of the pains and barriers are due to missing, insufficient, wrong or inaccessible information about the
accessibility of the accommodation, surroundings, and points of interests during the planning phase of the holidays. Digital assistive technologies hence play a
major role in bridging this information gap. In the 2nd phase so-called Hotel-Living-Labs (HLL) have been established where the identified assistive technologies
can be evaluated. Based on these HLLs an overall service for accessible holidays has been designed and developed. In the last phase, this service has been implemented
based on the HLLs as well as the identified assistive technologies and is currently field tested with tourists with disabilities from the three participated countries.
Shared Field, Divided Field
(2020)
Side Channel Attack Resistance of the Elliptic Curve Point Multiplication using Eisenstein Integers
(2020)
Asymmetric cryptography empowers secure key exchange and digital signatures for message authentication. Nevertheless, consumer electronics and embedded systems often rely on symmetric cryptosystems because asymmetric cryptosystems are computationally intensive. Besides, implementations of cryptosystems are prone to side-channel attacks (SCA). Consequently, the secure and efficient implementation of asymmetric cryptography on resource-constrained systems is demanding. In this work, elliptic curve cryptography is considered. A new concept for an SCA resistant calculation of the elliptic curve point multiplication over Eisenstein integers is presented and an efficient arithmetic over Eisenstein integers is proposed. Representing the key by Eisenstein integer expansions is beneficial to reduce the computational complexity and the memory requirements of an SCA protected implementation.
Side Channel Attack Resistance of the Elliptic Curve Point Multiplication using Gaussian Integers
(2020)
Elliptic curve cryptography is a cornerstone of embedded security. However, hardware implementations of the elliptic curve point multiplication are prone to side channel attacks. In this work, we present a new key expansion algorithm which improves the resistance against timing and simple power analysis attacks. Furthermore, we consider a new concept for calculating the point multiplication, where the points of the curve are represented as Gaussian integers. Gaussian integers are subset of the complex numbers, such that the real and imaginary parts are integers. Since Gaussian integer fields are isomorphic to prime fields, this concept is suitable for many elliptic curves. Representing the key by a Gaussian integer expansion is beneficial to reduce the computational complexity and the memory requirements of a secure hardware implementation.
Deep neural networks (DNNs) are known for their high prediction performance, especially in perceptual tasks such as object recognition or autonomous driving. Still, DNNs are prone to yield unreliable predictions when encountering completely new situations without indicating their uncertainty. Bayesian variants of DNNs (BDNNs), such as MC dropout BDNNs, do provide uncertainty measures. However, BDNNs are slow during test time because they rely on a sampling approach. Here we present a single shot MC dropout approximation that preserves the advantages of BDNNs without being slower than a DNN. Our approach is to analytically approximate for each layer in a fully connected network the expected value and the variance of the MC dropout signal. We evaluate our approach on different benchmark datasets and a simulated toy example. We demonstrate that our single shot MC dropout approximation resembles the point estimate and the uncertainty estimate of the predictive distribution that is achieved with an MC approach, while being fast enough for real-time deployments of BDNNs.