@article{15414, author = {{Schryen, Guido}}, journal = {{Communications of the ACM}}, number = {{9}}, pages = {{35 -- 37}}, title = {{{Integrating Management Science into the HPC Research Ecosystem}}}, volume = {{63}}, year = {{2020}}, } @inproceedings{15490, author = {{Claes, Leander and Baumhögger, Elmar and Rüther, Torben and Gierse, Jan and Tröster, Thomas and Henning, Bernd}}, booktitle = {{Fortschritte der Akustik - DAGA 2020}}, pages = {{1077--1080}}, title = {{{Reduction of systematic measurement deviation in acoustic absorption measurement systems}}}, year = {{2020}}, } @article{15513, abstract = {{This interview is part of the special issue (01/2020) on “High Performance Business Computing” to be published in the journal Business & Information Systems Engineering. The interviewee Utz-Uwe Haus is Senior Research Engineer @ CRAY European Research Lab (CERL)). A bio of him is included at the end of the interview.}}, author = {{Schryen, Guido and Kliewer, Natalia and Fink, Andreas}}, journal = {{Business & Information Systems Engineering}}, number = {{01/2020}}, pages = {{21 -- 23}}, title = {{{Interview with Utz-Uwe Haus on “High Performance Computing in Economic Environments: Opportunities and Challenges"}}}, volume = {{62}}, year = {{2020}}, } @article{15022, author = {{Schryen, Guido}}, journal = {{European Journal of Operational Research}}, number = {{1}}, pages = {{1 -- 18}}, publisher = {{Elsevier}}, title = {{{Parallel computational optimization in operations research: A new integrative framework, literature review and research directions}}}, volume = {{287}}, year = {{2020}}, } @article{16197, abstract = {{Nonlinear Pancharatnam–Berry phase metasurfaces facilitate the nontrivial phase modulation for frequency conversion processes by leveraging photon‐spin dependent nonlinear geometric‐phases. However, plasmonic metasurfaces show some severe limitation for nonlinear frequency conversion due to the intrinsic high ohmic loss and low damage threshold of plasmonic nanostructures. Here, the nonlinear geometric‐phases associated with the third‐harmonic generation process occurring in all‐dielectric metasurfaces is studied systematically, which are composed of silicon nanofins with different in‐plane rotational symmetries. It is found that the wave coupling among different field components of the resonant fundamental field gives rise to the appearance of different nonlinear geometric‐phases of the generated third‐harmonic signals. The experimental observations of the nonlinear beam steering and nonlinear holography realized in this work by all‐dielectric geometric‐phase metasurfaces are well explained with the developed theory. This work offers a new physical picture to understand the nonlinear optical process occurring at nanoscale dielectric resonators and will help in the design of nonlinear metasurfaces with tailored phase properties.}}, author = {{Liu, Bingyi and Sain, Basudeb and Reineke, Bernhard and Zhao, Ruizhe and Meier, Cedrik and Huang, Lingling and Jiang, Yongyuan and Zentgraf, Thomas}}, issn = {{2195-1071}}, journal = {{Advanced Optical Materials}}, number = {{9}}, publisher = {{Wiley}}, title = {{{Nonlinear Wavefront Control by Geometric-Phase Dielectric Metasurfaces: Influence of Mode Field and Rotational Symmetry}}}, doi = {{10.1002/adom.201902050}}, volume = {{8}}, year = {{2020}}, } @inproceedings{16219, abstract = {{Network function virtualization (NFV) proposes to replace physical middleboxes with more flexible virtual network functions (VNFs). To dynamically adjust to everchanging traffic demands, VNFs have to be instantiated and their allocated resources have to be adjusted on demand. Deciding the amount of allocated resources is non-trivial. Existing optimization approaches often assume fixed resource requirements for each VNF instance. However, this can easily lead to either waste of resources or bad service quality if too many or too few resources are allocated. To solve this problem, we train machine learning models on real VNF data, containing measurements of performance and resource requirements. For each VNF, the trained models can then accurately predict the required resources to handle a certain traffic load. We integrate these machine learning models into an algorithm for joint VNF scaling and placement and evaluate their impact on resulting VNF placements. Our evaluation based on real-world data shows that using suitable machine learning models effectively avoids over- and underallocation of resources, leading to up to 12 times lower resource consumption and better service quality with up to 4.5 times lower total delay than using standard fixed resource allocation.}}, author = {{Schneider, Stefan Balthasar and Satheeschandran, Narayanan Puthenpurayil and Peuster, Manuel and Karl, Holger}}, booktitle = {{IEEE Conference on Network Softwarization (NetSoft)}}, location = {{Ghent, Belgium}}, publisher = {{IEEE}}, title = {{{Machine Learning for Dynamic Resource Allocation in Network Function Virtualization}}}, year = {{2020}}, } @article{16249, abstract = {{Timing plays a crucial role in the context of information security investments. We regard timing in two dimensions, namely the time of announcement in relation to the time of investment and the time of announcement in relation to the time of a fundamental security incident. The financial value of information security investments is assessed by examining the relationship between the investment announcements and their stock market reaction focusing on the two time dimensions. Using an event study methodology, we found that both dimensions influence the stock market return of the investing organization. Our results indicate that (1) after fundamental security incidents in a given industry, the stock price will react more positively to a firm’s announcement of actual information security investments than to announcements of the intention to invest; (2) the stock price will react more positively to a firm’s announcements of the intention to invest after the fundamental security incident compared to before; and (3) the stock price will react more positively to a firm’s announcements of actual information security investments after the fundamental security incident compared to before. Overall, the lowest abnormal return can be expected when the intention to invest is announced before a fundamental information security incident and the highest return when actual investing after a fundamental information security incident in the respective industry.}}, author = {{Szubartowicz, Eva and Schryen, Guido}}, journal = {{Journal of Information System Security}}, keywords = {{Event Study, Information Security, Investment Announcements, Stock Price Reaction, Value of Information Security Investments}}, number = {{1}}, pages = {{3 -- 31}}, publisher = {{Information Institute Publishing, Washington DC, USA}}, title = {{{Timing in Information Security: An Event Study on the Impact of Information Security Investment Announcements}}}, volume = {{16}}, year = {{2020}}, } @inproceedings{16285, abstract = {{To decide in which part of town to open stores, high street retailers consult statistical data on customers and cities, but they cannot analyze their customers’ shopping behavior and geospatial features of a city due to missing data. While previous research has proposed recommendation systems and decision aids that address this type of decision problem – including factory location and assortment planning – there currently is no design knowledge available to prescribe the design of city center area recommendation systems (CCARS). We set out to design a software prototype considering local customers’ shopping interests and geospatial data on their shopping trips for retail site selection. With real data on 500 customers and 1,100 shopping trips, we demonstrate and evaluate our IT artifact. Our results illustrate how retailers and public town center managers can use CCARS for spatial location selection, growing retailers’ profits and a city center’s attractiveness for its citizens.}}, author = {{zur Heiden, Philipp and Berendes, Carsten Ingo and Beverungen, Daniel}}, booktitle = {{Proceedings of the 15th International Conference on Wirtschaftsinformatik}}, keywords = {{Town Center Management, High Street Retail, Recommender Systems, Geospatial Recommendations, Design Science Research}}, location = {{Potsdam}}, title = {{{Designing City Center Area Recommendation Systems }}}, doi = {{doi.org/10.30844/wi_2020_e1-heiden}}, year = {{2020}}, } @article{16290, abstract = {{The control of complex systems is of critical importance in many branches of science, engineering, and industry, many of which are governed by nonlinear partial differential equations. Controlling an unsteady fluid flow is particularly important, as flow control is a key enabler for technologies in energy (e.g., wind, tidal, and combustion), transportation (e.g., planes, trains, and automobiles), security (e.g., tracking airborne contamination), and health (e.g., artificial hearts and artificial respiration). However, the high-dimensional, nonlinear, and multi-scale dynamics make real-time feedback control infeasible. Fortunately, these high- dimensional systems exhibit dominant, low-dimensional patterns of activity that can be exploited for effective control in the sense that knowledge of the entire state of a system is not required. Advances in machine learning have the potential to revolutionize flow control given its ability to extract principled, low-rank feature spaces characterizing such complex systems.We present a novel deep learning modelpredictive control framework that exploits low-rank features of the flow in order to achieve considerable improvements to control performance. Instead of predicting the entire fluid state, we use a recurrent neural network (RNN) to accurately predict the control relevant quantities of the system, which are then embedded into an MPC framework to construct a feedback loop. In order to lower the data requirements and to improve the prediction accuracy and thus the control performance, incoming sensor data are used to update the RNN online. The results are validated using varying fluid flow examples of increasing complexity.}}, author = {{Bieker, Katharina and Peitz, Sebastian and Brunton, Steven L. and Kutz, J. Nathan and Dellnitz, Michael}}, issn = {{0935-4964}}, journal = {{Theoretical and Computational Fluid Dynamics}}, pages = {{577–591}}, title = {{{Deep model predictive flow control with limited sensor data and online learning}}}, doi = {{10.1007/s00162-020-00520-4}}, volume = {{34}}, year = {{2020}}, } @techreport{23568, abstract = {{We study the structure of power networks in consideration of local protests against certain power lines (’not-in-my-backyard’). An application of a network formation game is used to determine whether or not such protests arise. We examine the existence of stable networks and their characteristics, when no player wants to make an alteration. Stability within this game is only reached if each player is sufficiently connected to a power source but is not linked to more players than necessary. In addition we introduce an algorithm that creates a stable network.}}, author = {{Block, Lukas}}, keywords = {{Network formation, NIMBY, Power networks, Nash stability}}, title = {{{Network formation with NIMBY constraints}}}, year = {{2020}}, } @misc{30180, author = {{Ficara, Elena and d'Agostini, Franca }}, booktitle = {{La Stampa}}, title = {{{Perché celebrare Hegel? La sua dialettica è un brand, il suo pensiero una febbre benefica}}}, year = {{2020}}, } @article{20143, author = {{Otroshi, Mortaza and Rossel, Moritz and Meschut, Gerson}}, journal = {{Journal of Advanced Joining Processes}}, keywords = {{Self-pierce riveting, Ductile fracture, Damage modeling, GISSMO damage model}}, publisher = {{Elsevier}}, title = {{{Stress state dependent damage modeling of self-pierce riveting process simulation using GISSMO damage model}}}, doi = {{10.1016/j.jajp.2020.100015}}, volume = {{1}}, year = {{2020}}, } @article{11946, abstract = {{Literature reviews (LRs) play an important role in the development of domain knowledge in all fields. Yet, we observe a lack of insights into the activities with which LRs actually develop knowledge. To address this important gap, we (1) derive knowledge building activities from the extant literature on LRs, (2) suggest a knowledge-based typology of LRs that complements existing typologies, and (3) apply the suggested typology in an empirical study that explores how LRs with different goals and methodologies have contributed to knowledge development. The analysis of 240 LRs published in 40 renowned IS journals between 2000 and 2014 allows us to draw a detailed picture of knowledge development achieved by one of the most important genres in the IS field. An overarching contribution of our work is to unify extant conceptualizations of LRs by clarifying and illustrating how LRs apply different methodologies in a range of knowledge building activities to achieve their goals with respect to theory.}}, author = {{Schryen, Guido and Wagner, Gerit and Benlian, Alexander and Paré, Guy}}, issn = {{ 1529-3181}}, journal = {{Communications of the AIS}}, keywords = {{Literature review, knowledge development, knowledge building activities, knowledge-based typology, information systems research}}, pages = {{134--186}}, title = {{{A Knowledge Development Perspective on Literature Reviews: Validation of a New Typology in the IS Field}}}, doi = {{10.17705/1CAIS.04607}}, volume = {{46}}, year = {{2020}}, } @article{14985, author = {{Schryen, Guido and Kliewer, Natalia and Fink, Andreas}}, journal = {{Business & Information Systems Engineering}}, number = {{1}}, pages = {{1--3}}, title = {{{High Performance Business Computing}}}, doi = {{10.1007/s12599-019-00622-2}}, volume = {{62}}, year = {{2020}}, } @book{32425, author = {{Tönsing, Johanna}}, title = {{{Animalische Epistemologie: Tierwahrheiten bei Franz Kafka am Beispiel von "Ein Bericht für eine Akademie"}}}, year = {{2020}}, } @misc{21294, author = {{Hagengruber, Ruth}}, booktitle = {{H-France Net}}, issn = {{ISSN 1553-9172}}, title = {{{Review Hagengruber Le Ru Émilie Du Châtelet Philosophe }}}, volume = {{158}}, year = {{2020}}, } @article{17598, author = {{Nakatani, Tomohiro and Boeddeker, Christoph and Kinoshita, Keisuke and Ikeshita, Rintaro and Delcroix, Marc and Haeb-Umbach, Reinhold}}, journal = {{IEEE/ACM Transactions on Audio, Speech, and Language Processing}}, pages = {{1--1}}, title = {{{Jointly optimal denoising, dereverberation, and source separation}}}, doi = {{10.1109/TASLP.2020.3013118}}, year = {{2020}}, } @article{27394, abstract = {{Der systematischen Reflexion von Praxiserfahrungen anhand von Theorie wird in der Lehrerinnenbildung ein besonders hoher Stellenwert zugeschrieben. Auf Makroebene wurde durch die Einführung des Praxissemesters in NRW auf der einen Seite ein wichtiger Schritt zur stärkeren Verknüpfung von Schulpraxis und universitärer Ausbildung getan. Auf der anderen Seite bestehen auf der Mirkoebene immer noch Herausforderungen in der Relationierung von Theorie und Praxis für Lehramtsstudierende. Hier heißt es für Dozierende, die Lehramtsstudierende während dieses Langzeitpraktikums in universitären Veranstaltungen begleiten, tragfähige Seminarkonzepte zu entwickeln. Der vorliegende Beitrag stellt eine Methode, die Theoriebasierte Fallreflexion (TFR), mit zwei Umsetzungsvarianten vor. Damit wird eine konkrete Möglichkeit dargelegt, wie in Begleitveranstaltungen zum Praxissemester zum einen eine systematische theoretische Analyse und zum anderen die Generierung individueller Handlungsmöglichkeiten für die konkrete Schulpraxis angeleitet werden kann. Des Weiteren werden insgesamt 410 verschiedene Rückmeldungen zur Methode von insgesamt N = 93 Studierenden, welche die TFR im Rahmen einer halbtägigen Blockveranstaltung durchführten, mittels der qualitativen Inhaltsanalyse nach Mayring (2015) kategorisiert. Die Studierenden betonten in ihren Rückmeldungen besonders das Potential der TFR im Hinblick auf ein tieferes Verständnis von theoretischen Inhalten sowie hinsichtlich der Möglichkeiten zum intensiven Austausch mit Kommilitonen*innen sowie zur individuellen Reflexion schulpraktischer Situationen.}}, author = {{Bonanati, Sabrina and Westphal, Petra and Wiethoff, Christoph}}, journal = {{HLZ - Herausforderungen Lehrer*innenbildung}}, keywords = {{TFR, Theoriebasierte Fallreflexion, Praxissemester, Begleitseminar, Theorie-Praxis-Verzahnung}}, number = {{1}}, pages = {{461–479}}, title = {{{Theoriebasierte Fallreflexion (TFR) im Praxissemester. Didaktische Umsetzung und Evaluation. }}}, doi = {{10.4119/HLZ-3142}}, volume = {{3}}, year = {{2020}}, } @inproceedings{29298, abstract = {{Die Themen „Big Data“, „Künstliche Intelligenz und „Data Science“ werden seit einiger Zeit nicht nur in der breiten Öffentlichkeit kontrovers diskutiert, sondern stellen für die Ausbildung in den IT- und IT-nahen Berufen schon heute neue Herausforderungen dar, die in Zukunft durch die gesellschaftliche und technologische Weiterentwicklung hin zu einer Datengesellschaft noch größer werden. An dieser Stelle stellt sich die Frage, welche Aspekte dieses großen Themenkomplexes für Schule und Ausbildung von Wichtigkeit sind und wie diese Themen sinnstiftend und gewinnbringend in die informatische Ausbildung in verschiedenen Bildungsgängen integriert werden können. Im Rahmen des von uns im Jahr 2017 organisierten Symposiums zum Thema „Data Science“ wurden für die Bildung relevante Aspekte erörtert, wodurch als Kernelemente für den Unterricht Algorithmen der Künstlichen Intelligenz und ihre Anwendung in Industrie und Gesellschaft, Explorationen von Big Data sowie der Umgang mit eigenen Daten in sozialen Netzwerken herausgearbeitet wurden. Ziel ist, aus diesen Themenbereichen sowohl ein umfassendes Curriculum als auch Module für verschiedene Unterrichtsszenarien zu entwickeln und zu erproben. Durch diese Materialien soll es Lehrkräften aus der Informatik, Mathematik oder Technik ermöglicht werden, diese Themen auf Basis des Curriculums und der erprobten Unterrichtskonzepte selbst zu unterrichten. Hierfür wurde im Rahmen des Projekts ProDaBi (Projekt Data Science und Big Data in der Schule, https://www.prodabi.de), initiiert von der Telekom Stiftung, ein experimenteller Projektkurs entwickelt, den wir mit Schüler:innen der Sekundarstufe II an der Universität Paderborn im Schuljahr 2018/19 durchführten. Dieser Kurs enthält neben einem Modul zur Exploration von Big Data und einem weiteren Modul zum Maschinellen Lernen als Teil der Künstlichen Intelligenz auch eine Projektphase, die es in Zusammenarbeit mit lokalen Unternehmen den Schüler:innen ermöglicht, das Erlernte in ein reales Data Science-Projekt einzubringen. Aus den Erfahrungen dieses Projektkurses sowie den parallel durchgeführten Erprobungen einzelner Bausteine auch mit beruflichen Schulen werden ab dem Schuljahr 2019/20 die hierfür verwendeten Materialien weiterentwickelt und weiteren Kooperationspartnern zur Erprobung zur Verfügung gestellt. Damit wurden zum Ende des Projekts nicht nur vollständige Unterrichtsmaterialien, sondern auch ein umfassendes Curriculum entwickelt.}}, author = {{Opel, Simone Anna and Schlichtig, Michael}}, booktitle = {{Sammelband der 27. Fachtagung der BAG Berufliche Bildung}}, editor = {{Vollmer, Thomas and Karges, Torben and Richter, Tim and Schlömer, Britta and Schütt-Sayed, Sören}}, keywords = {{Berufsbildung, vocational education, Ausbildung, training, berufliche Weiterbildung, advanced vocational education, Digitalisierung, digitalization, Unterricht, teaching, Lehrmethode, teaching method, Interdisziplinarität, interdisciplinarity, Fachdidaktik, subject didactics, Curriculum, curriculum, gewerblich-technischer Beruf, vocational/technical occupation, Fachkraft, specialist, Qualifikationsanforderungen, qualification requirements, Kompetenz, competence, Lehrerbildung, teacher training, Bundesrepublik Deutschland, Federal Republic of Germany}}, location = {{Siegen}}, pages = {{176--194}}, publisher = {{wbv Media GmbH & Co. KG}}, title = {{{Data Science und Big Data in der beruflichen Bildung – Konzeption und Erprobung eines Projektkurses für die Sekundarstufe II}}}, doi = {{https://doi.org/10.3278/6004722w}}, volume = {{55}}, year = {{2020}}, } @inproceedings{29546, author = {{Maslovskaya, Sofya and Caillau, Jean-Baptiste and Djema, Walid and Giraldi, Laetitia and Jean-Luc, Jean-Luc and Pomet, Jean-Baptiste}}, title = {{{The turnpike property in maximization of microbial metabolite production}}}, year = {{2020}}, }