@article{45782, abstract = {{The development of automotive components with reduced greenhouse gas (GHG) emissions is needed to reduce overall vehicle emissions. Life Cycle Engineering (LCE) based on Life Cycle Assessment (LCA) supports this by providing holistic information and improvement potentials regarding eco-efficient products. Key factors influencing LCAs of automotive components, such as material production, will change in the future. First approaches for integrating future scenarios for these key factors into LCE already exist, but they only consider a limited number of parameters and scenarios. This work aims to develop a method that can be practically applied in the industry for integrating prospective LCAs (pLCA) into the LCE of automotive components, considering relevant parameters and consistent scenarios. Therefore, pLCA methods are further developed to investigate the influence of future scenarios on the GHG emissions of automotive components. The practical application is demonstrated for a vehicle component with different design options. This paper shows that different development paths of the foreground and background system can shift the ecological optimum of design alternatives. Therefore, future pathways of relevant parameters must be considered comprehensively to reduce GHG emissions of future vehicles. This work contributes to the methodological and practical integration of pLCA into automotive development processes and provides quantitative results.}}, author = {{Grenz, Julian and Ostermann, Moritz and Käsewieter, Karoline and Cerdas, Felipe and Marten, Thorsten and Herrmann, Christoph and Tröster, Thomas}}, issn = {{2071-1050}}, journal = {{Sustainability}}, keywords = {{prospective LCA, life cycle engineering (LCE), lightweight design, automotive components, body parts, circular economy, steel, aluminum, hybrid materials, fiber metal laminates}}, number = {{13}}, publisher = {{MDPI AG}}, title = {{{Integrating Prospective LCA in the Development of Automotive Components}}}, doi = {{10.3390/su151310041}}, volume = {{15}}, year = {{2023}}, } @inproceedings{45793, abstract = {{The global megatrends of digitization and sustainability lead to new challenges for the design and management of technical products in industrial companies. Product management - as the bridge between market and company - has the task to absorb and combine the manifold requirements and make the right product-related decisions. In the process, product management is confronted with heterogeneous information, rapidly changing portfolio components, as well as increasing product, and organizational complexity. Combining and utilizing data from different sources, e.g., product usage data and social media data leads to promising potentials to improve the quality of product-related decisions. In this paper, we reinforce the need for data-driven product management as an interdisciplinary field of action. The state of data-driven product management in practice was analyzed by conducting workshops with six manufacturing companies and hosting a focus group meeting with experts from different industries. We investigate the expectations and derive requirements leading us to open research questions, a vision for data-driven product management, and a research agenda to shape future research efforts.}}, author = {{Grigoryan, Khoren and Fichtler, Timm and Schreiner, Nick and Rabe, Martin and Panzner, Melina and Kühn, Arno and Dumitrescu, Roman and Koldewey, Christian}}, booktitle = {{Procedia CIRP 33}}, keywords = {{Product Management, Data Analytics, Data-Driven Design, Product-related data, Lifecycle Data, Tool-support}}, location = {{Sydney}}, title = {{{Data-Driven Product Management: A Practitioner-Driven Research Agenda}}}, year = {{2023}}, } @inproceedings{46500, abstract = {{The security of Industrial Control Systems is relevant both for reliable production system operations and for high-quality throughput in terms of manufactured products. Security measures are designed, operated and maintained by different roles along product and production system lifecycles. Defense-in-Depth as a paradigm builds upon the assumption that breaches are unavoidable. The paper at hand provides an analysis of roles, corresponding Human Factors and their relevance for data theft and sabotage attacks. The resulting taxonomy is reflected by an example related to Additive Manufacturing. The results assist in both designing and redesigning Industrial Control System as part of an entire production system so that Defense-in-Depth with regard to Human Factors is built in by design.}}, author = {{Pottebaum, Jens and Rossel, Jost and Somorovsky, Juraj and Acar, Yasemin and Fahr, René and Arias Cabarcos, Patricia and Bodden, Eric and Gräßler, Iris}}, booktitle = {{2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)}}, keywords = {{Defense-in-Depth, Human Factors, Production Engineering, Product Design, Systems Engineering}}, location = {{Delft, Netherlands}}, pages = {{379--385}}, publisher = {{IEEE}}, title = {{{Re-Envisioning Industrial Control Systems Security by Considering Human Factors as a Core Element of Defense-in-Depth}}}, doi = {{10.1109/eurospw59978.2023.00048}}, year = {{2023}}, } @inproceedings{48894, abstract = {{Recently different evolutionary computation approaches have been developed that generate sets of high quality diverse solutions for a given optimisation problem. Many studies have considered diversity 1) as a mean to explore niches in behavioural space (quality diversity) or 2) to increase the structural differences of solutions (evolutionary diversity optimisation). In this study, we introduce a co-evolutionary algorithm to simultaneously explore the two spaces for the multi-component traveling thief problem. The results show the capability of the co-evolutionary algorithm to achieve significantly higher diversity compared to the baseline evolutionary diversity algorithms from the literature.}}, author = {{Nikfarjam, Adel and Neumann, Aneta and Bossek, Jakob and Neumann, Frank}}, booktitle = {{Parallel Problem Solving from Nature (PPSN XVII)}}, editor = {{Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tu\v sar, Tea}}, isbn = {{978-3-031-14714-2}}, keywords = {{Co-evolutionary algorithms, Evolutionary diversity optimisation, Quality diversity, Traveling thief problem}}, pages = {{237–249}}, publisher = {{Springer International Publishing}}, title = {{{Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem}}}, doi = {{10.1007/978-3-031-14714-2_17}}, year = {{2022}}, } @article{35732, abstract = {{While the Information Systems (IS) discipline has researched digital platforms extensively, the body of knowledge appertaining to platforms still appears fragmented and lacking conceptual consistency. Based on automated text mining and unsupervised machine learning, we collect, analyze, and interpret the IS discipline’s comprehensive research on platforms—comprising 11,049 papers spanning 44 years of research activity. From a cluster analysis concerning platform concepts’ semantically most similar words, we identify six research streams on platforms, each with their own platform terms. Based on interpreting the identified concepts vis-à-vis the extant research and considering a temporal perspective on the concepts’ application, we present a lexicon of platform concepts, to guide further research on platforms in the IS discipline. Researchers and managers can build on our results to position their work appropriately, applying a specific theoretical perspective on platforms in isolation or combining multiple perspectives to study platform phenomena at a more abstract level.}}, author = {{Bartelheimer, Christian and zur Heiden, Philipp and Lüttenberg, Hedda and Beverungen, Daniel}}, issn = {{1019-6781}}, journal = {{Electronic Markets}}, keywords = {{Platform, Text mining, Machine learning, Data communications, Interpretive research, Systems design and implementation}}, pages = {{375--396}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Systematizing the lexicon of platforms in information systems: a data-driven study}}}, doi = {{10.1007/s12525-022-00530-6}}, volume = {{32}}, year = {{2022}}, } @inproceedings{36866, abstract = {{Die additive Fertigung bietet die Möglichkeit, digitale Prototypen dank der Besonderheit der werkzeuglosen Fertigung schnellstmöglich in reale Strukturen umzusetzen. Dieses Verfahren kann jedoch nur dann mit optimaler Geschwindigkeit genutzt werden, wenn Engpässe wirksam vermieden werden können. Einer dieser Engpässe ist der Konstruktionsprozess. Gerade im Bereich der additiven Fertigung sind in letzter Zeit immer leistungsfähigere Softwarelösungen erschienen, die das Design für die additive Fertigung, einschließlich der meisten Computer-Aided-Design (CAD)-Aufgaben, beschleunigen. In vielen Bereichen wird daher bereits versucht, so viele Schritte wie möglich zu automatisieren, nicht selten unter Verwendung neuronaler Netze und künstlicher Intelligenz. Dieser Beitrag zeigt am Beispiel einer automatisierten Strukturoptimierung eines Stuhls, warum das Nutzen neuronaler Netze im Konstruktionsprozess sinnvoll ist, um die Bereiche der konventionellen Topologieoptimierung und des Generative Design weiter zu verknüpfen und somit die Produktentwicklungszeit zu reduzieren.}}, author = {{Ott, Manuel and Meihöfener, Niclas and Koch, Rainer}}, booktitle = {{Bericht 407 - 7. Tagung des DVM-Arbeitskreises Additiv gefertigte Bauteile und Strukturen}}, keywords = {{Künstliche Intelligenz, Neuronale Netze, 3D-Druck, Design for Additive Manufacturing}}, location = {{Berlin}}, pages = {{91--106}}, title = {{{Neuronale Netze in der Konstruktion zur Ausschöpfung der Potentiale additiver Fertigungstechnologien}}}, doi = {{10.48447/ADD-2022-014}}, volume = {{7}}, year = {{2022}}, } @inproceedings{32309, abstract = {{Due to the increasing influences of a VUCA world, design thinking workshops have been established as a standard technique to build solutions according to uncertain customer needs. Concerning the ongoing pandemic and rising development of solutions across organizations, more and more workshops were conducted online with software support. However, existing software tools insufficiently address the different workshop situations in terms of the process (i.e., fixed tasks to conduct), the place (e.g., static online whiteboards), and people (i.e., synchronous working of all stakeholders). Therefore, we propose a design science study to develop a situation-specific software support that can be configured with flexible development processes, different places, and task-related people. Based on practical experience in existing research projects, we derive the initial design requirements and map them to a set of design principles. Out of that, we design a concept with its implementation as a software tool and point out open challenges. }}, author = {{Gottschalk, Sebastian and Yigitbas, Enes and Nowosad, Alexander and Engels, Gregor}}, booktitle = {{Proceedings of the 5th International Workshop on Software-intensive Business (IWSiB'22) }}, keywords = {{design thinking, situation-specific, cross-organizational, software support}}, publisher = {{ACM}}, title = {{{Towards Situation-specific Software Support for Cross-organizational Design Thinking Processes}}}, year = {{2022}}, } @article{31691, abstract = {{Sustainable product engineering is becoming increasingly important. This includes the development of environmentally friendly products and the design for recycling. In this paper a holistic method for the assessment of solution alternatives is presented, in which the stakeholder perspectives along the generic product lifecycle are taken into account. Finally, a new visualization is presented. By visualizing the results in the integrated sustainability triangle, decision-makers in product development can holistically assess the sustainability of the solution alternatives.}}, author = {{Gräßler, Iris and Hesse, Philipp}}, issn = {{2732-527X}}, journal = {{Proceedings of the Design Society}}, keywords = {{sustainability, decision making, generic product lifecycle, design analysis, ecodesign}}, pages = {{1001--1010}}, publisher = {{Cambridge University Press (CUP)}}, title = {{{Approach to Sustainability-Based Assessment of Solution Alternatives in Early Stages of Product Engineering}}}, doi = {{10.1017/pds.2022.102}}, volume = {{2}}, year = {{2022}}, } @article{33684, author = {{Schade, Robert and Kenter, Tobias and Elgabarty, Hossam and Lass, Michael and Schütt, Ole and Lazzaro, Alfio and Pabst, Hans and Mohr, Stephan and Hutter, Jürg and Kühne, Thomas and Plessl, Christian}}, issn = {{0167-8191}}, journal = {{Parallel Computing}}, keywords = {{Artificial Intelligence, Computer Graphics and Computer-Aided Design, Computer Networks and Communications, Hardware and Architecture, Theoretical Computer Science, Software}}, publisher = {{Elsevier BV}}, title = {{{Towards electronic structure-based ab-initio molecular dynamics simulations with hundreds of millions of atoms}}}, doi = {{10.1016/j.parco.2022.102920}}, volume = {{111}}, year = {{2022}}, } @inproceedings{29803, abstract = {{Ultrasonic wire bonding is a solid-state joining process used to form electrical interconnections in micro and power electronics and batteries. A high frequency oscillation causes a metallurgical bond deformation in the contact area. Due to the numerous physical influencing factors, it is very difficult to accurately capture this process in a model. Therefore, our goal is to determine a suitable feed-forward control strategy for the bonding process even without detailed model knowledge. We propose the use of batch constrained Bayesian optimization for the control design. Hence, Bayesian optimization is precisely adapted to the application of bonding: the constraint is used to check one quality feature of the process and the use of batches leads to more efficient experiments. Our approach is suitable to determine a feed-forward control for the bonding process that provides very high quality bonds without using a physical model. We also show that the quality of the Bayesian optimization based control outperforms random search as well as manual search by a user. Using a simple prior knowledge model derived from data further improves the quality of the connection. The Bayesian optimization approach offers the possibility to perform a sensitivity analysis of the control parameters, which allows to evaluate the influence of each control parameter on the bond quality. In summary, Bayesian optimization applied to the bonding process provides an excellent opportunity to develop a feedforward control without full modeling of the underlying physical processes.}}, author = {{Hesse, Michael and Hunstig, Matthias and Timmermann, Julia and Trächtler, Ansgar}}, booktitle = {{Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM)}}, isbn = {{978-989-758-549-4}}, keywords = {{Bayesian optimization, Wire bonding, Feed-forward control, model-free design}}, location = {{Online}}, pages = {{383--394}}, title = {{{Batch Constrained Bayesian Optimization for UltrasonicWire Bonding Feed-forward Control Design}}}, year = {{2022}}, } @inproceedings{22309, abstract = {{Approximate computing (AC) has acquired significant maturity in recent years as a promising approach to obtain energy and area-efficient hardware. Automated approximate accelerator synthesis involves a great deal of complexity on the size of design space which exponentially grows with the number of possible approximations. Design space exploration of approximate accelerator synthesis is usually targeted via heuristic-based search methods. The majority of existing frameworks prune a large part of the design space using a greedy-based approach to keep the problem tractable. Therefore, they result in inferior solutions since many potential solutions are neglected in the pruning process without the possibility of backtracking of removed approximate instances. In this paper, we address the aforementioned issue by adopting Monte Carlo Tree Search (MCTS), as an efficient stochastic learning-based search algorithm, in the context of automated synthesis of approximate accelerators. This enables the synthesis frameworks to deeply subsamples the design space of approximate accelerator synthesis toward most promising approximate instances based on the required performance goals, i.e., power consumption, area, or/and delay. We investigated the challenges of providing an efficient open-source framework that benefits analytical and search-based approximation techniques simultaneously to both speed up the synthesis runtime and improve the quality of obtained results. Besides, we studied the utilization of machine learning algorithms to improve the performance of several critical steps, i.e., accelerator quality testing, in the synthesis framework. The proposed framework can help the community to rapidly generate efficient approximate accelerators in a reasonable runtime.}}, author = {{Awais, Muhammad and Platzner, Marco}}, booktitle = {{Proceedings of IEEE Computer Society Annual Symposium on VLSI}}, keywords = {{Approximate computing, Design space exploration, Accelerator synthesis}}, location = {{Tampa, Florida USA (Virtual)}}, pages = {{384--389}}, publisher = {{IEEE}}, title = {{{MCTS-Based Synthesis Towards Efficient Approximate Accelerators}}}, year = {{2021}}, } @inproceedings{21727, abstract = {{Platform-based business models underlie the success of many of today’s largest, fastest-growing, and most disruptive companies. Despite the success of prominent examples, such as Uber and Airbnb, creating a profitable platform ecosystem presents a key challenge for many companies across all industries. Although research provides knowledge about platforms’ different value drivers (e.g., network effects), companies that seek to transform their current business model into a platform-based one lack an artifact to reduce knowledge boundaries, collaborate effectively, and cope with the complexities and dynamics of platform ecosystems. We address this challenge by developing two artifacts and combining research from variability modeling, business model dependencies, and system dynamics. This paper presents a design science research approach to develop the platform ecosystem modeling language and the platform ecosystem development tool that support researcher and practitioner by visualizing and simulating platform ecosystems. }}, author = {{Vorbohle, Christian and Gottschalk, Sebastian}}, booktitle = {{Proceedings of the 29th European Conference on Information Systems (ECIS)}}, keywords = {{Platform Ecosystems, Platform Ecosystem Modeling Language, Platform Ecosystem Development Tool, Business Models, Design Science}}, location = {{Virtual Conference/Workshop}}, publisher = {{AIS}}, title = {{{Towards Visualizing and Simulating Business Models in Dynamic Platform Ecosystems }}}, year = {{2021}}, } @phdthesis{28683, abstract = {{In den letzten Jahren haben sich Software-Ökosysteme als neue, erfolgreiche Geschäftsform etabliert. Unternehmen agieren hierbei als Anbieter von Software-Plattformen, auf denen Drittanbieter Softwarelösungen für den Markt anbieten können. Etablierte Beispiele sind hierbei sogenannte App-Stores, die z.B. von Google oder Apple angeboten werden. Beim Aufbau von Software-Ökosystemen müssen vom Plattformanbieter viele architektonische Entwurfsentscheidungen getroffen werden. Bisher gibt es keine Architekturrichtlinien und -werkzeuge, die den Entwurf einer Ökosystemarchitektur unterstützen. Dadurch fehlt hier systematisches, wiederverwendbares Wissen. Plattformanbieter müssen auf ad-hoc Entscheidungen zurückgreifen. Dies kann dann zu Problemen im Betrieb der Software-Plattformen führen, zu erhöhten Ausfallrisiken und Mehrkosten. Der Mangel an Architekturwissen manifestiert sich konkret in zwei Gruppen von Herausforderungen: Erstens fehlt eine Wissensbasis zu Architekturalternativen und zweitens fehlt es an methodischem Wissen zu Entwicklung und Betrieb von Software-Ökosystemen. Eine Architekturwissensbasis würde Orientierungshilfen zu den Bestandteilen von Software-Ökosystemen und deren Abhängigkeiten geben, während methodisches Wissen die Erstellung dieser Systeme erleichtern würde. In der Dissertation werden diese Herausforderungen durch die Entwicklung des Frameworks SecoArc für die Modellierung von Software-Ökosystemen angegangen. Der Beitrag der Dissertation ist zweifach: 1. Das SecoArc-Framework umfasst eine Architekturwissensbasis, die wiederverwendbare Architekturentwurfsentscheidungen von Software-Ökosystemen enthält. Die Wissensbasis wurde entwickelt, indem das Architekturwissen bestehender Ökosysteme sowie aus existierender Fachliteratur ermittelt wurde und in einer Produktlinie für Software-Ökosysteme konsolidiert wurde. Die Produktlinie umfasst architektonische Gemeinsamkeiten und Variabilitäten von Software-Ökosystemen. 2. Das SecoArc-Framework liefert methodisches Wissen, um die Ökosystemarchitektur in Modellen zu entwerfen und zu analysieren. Dieses Wissen wurde entwickelt, indem drei Architekturmuster identifiziert wurden. Jedes Muster erfasst unterschiedliche Beziehungen zwischen architektonischen Entwurfsentscheidungen zu den Qualitätsmerkmalen einer Ökosystemgesundheit und der Erreichung von Geschäftszielen. Die Architekturmuster und die Produktlinie wurden dazu genutzt, ein Modellierungsframework zu entwickeln und in Form eines Prototypen umzusetzen, welches einen Entwurfsprozess, eine Modellierungssprache und eine Architekturanalysetechnik umfasst. Es erleichtert das Modellieren, Analysieren und Vergleichen von Ökosystemarchitekturen. Die Ergebnisse der Dissertation wurden im Rahmen von zwei Studien evaluiert. In der ersten Validierungsstudie wurden das Framework sowie der Prototyp verwendet, um zwei alternative Ökosystemarchitekturen zu entwerfen und zu analysieren. In der zweiten Studie wurde eine Analyse von existierenden Ökosystemen basierend auf den architektonischen Variabilitäten des Frameworks durchgeführt.}}, author = {{Schwichtenberg, Bahar}}, keywords = {{Enterprise Architecture, Architectural Design Decisions, Open Platforms}}, title = {{{Modeling and Analyzing Software Ecosystems}}}, doi = {{10.17619/UNIPB/1-1270 }}, year = {{2021}}, } @article{21436, abstract = {{Ultrasonic wire bonding is a solid-state joining process, used in the electronics industry to form electrical connections, e.g. to connect electrical terminals within semiconductor modules. Many process parameters affect the bond strength, such like the bond normal force, ultrasonic power, wire material and bonding frequency. Today, process design, development, and optimization is most likely based on the knowledge of process engineers and is mainly performed by experimental testing. In this contribution, a newly developed simulation tool is presented, to reduce time and costs and efficiently determine optimized process parameter. Based on a co-simulation of MATLAB and ANSYS, the different physical phenomena of the wire bonding process are considered using finite element simulation for the complex plastic deformation of the wire and reduced order models for the transient dynamics of the transducer, wire, substrate and bond formation. The model parameters such as the coefficients of friction between bond tool and wire and between wire and substrate were determined for aluminium and copper wire in experiments with a test rig specially developed for the requirements of heavy wire bonding. To reduce simulation time, for the finite element simulation a restart analysis and high performance computing is utilized. Detailed analysis of the bond formation showed, that the normal pressure distribution in the contact between wire and substrate has high impact on bond formation and distribution of welded areas in the contact area.}}, author = {{Schemmel, Reinhard and Krieger, Viktor and Hemsel, Tobias and Sextro, Walter}}, issn = {{0026-2714}}, journal = {{Microelectronics Reliability}}, keywords = {{Ultrasonic heavy wire bonding, Co-simulation, ANSYS, MATLAB, Process optimization, Friction coefficient, Copper-copper, Aluminium-copper}}, pages = {{114077}}, title = {{{Co-simulation of MATLAB and ANSYS for ultrasonic wire bonding process optimization}}}, doi = {{https://doi.org/10.1016/j.microrel.2021.114077}}, volume = {{119}}, year = {{2021}}, } @inbook{22930, abstract = {{Self-piercing riveting is an established technique for joining multi-material structures in car body manufacturing. Rivets for self-piercing riveting differ in their geometry, the material used, the condition of the material and their surface condition. To shorten the manufacturing process by omitting the heat treatment and the coating process, the authors have elaborated a concept for the use of stainless steel with high strain hardening as a rivet material. The focus of the present investigation is on the evaluation of the influences of the rivet’s geometry and material on its deformation behaviour. Conventional rivets of types P and HD2, a rivet with an improved geometry made of treatable steel 38B2, and rivets made of the stainless steels 1.3815 and 1.4541 are examined. The analysis is conducted by means of multi-step joining tests for two material combinations comprising high-strength steel HCT70X and aluminium EN AW-5083. The joints are cut to provide a cross-section and the deformation behaviour of the different rivets is analysed on the basis of the measured changes in geometry and hardness. In parallel, an examination of the force-stroke curves provides further insights. It can be demonstrated that, besides the geometry, the material strength, in particular, has a significant influence on the deformation behaviour of the rivet. The strength of steel 1.4541 is seen to be too low for the joining task, while the strength of steel 1.3815 is sufficient, and hence the investigation confirms the capability of rivets made of 1.3815 for joining even challenging material combinations.}}, author = {{Uhe, Benedikt and Kuball, Clara-Maria and Merklein, Marion and Meschut, Gerson}}, booktitle = {{Forming the Future - Proceedings of the 13th International Conference on the Technology of Plasticity. The Minerals, Metals & Materials Series.}}, editor = {{Daehn, Glenn and Cao, Jian and Kinsey, Brad and Tekkaya, Erman and Vivek, Anupam and Yoshida, Yoshinori}}, keywords = {{Self-piercing riveting, Lightweight design, Deformation behaviour, Stainless steel, High nitrogen steel}}, pages = {{1495--1506}}, publisher = {{Springer}}, title = {{{Self-Piercing Riveting Using Rivets Made of Stainless Steel with High Strain Hardening}}}, doi = {{10.1007/978-3-030-75381-8_124}}, year = {{2021}}, } @inbook{21542, abstract = {{Using near-field (NF) scan data to predict the far-field (FF) behaviour of radiating electronic systems represents a novel method to accompany the whole RF design process. This approach involves so-called Huygens' box as an efficient radiation model inside an electromagnetic (EM) simulation tool and then transforms the scanned NF measured data into the FF. For this, the basic idea of the Huygens'box principle and the NF-to-FF transformation are briefly presented. The NF is measured on the Huygens' box around a device under test using anNF scanner, recording the magnitude and phase of the site-related magnetic and electric components. A comparison between a fullwave simulation and the measurement results shows a good similarity in both the NF and the simulated and transformed FF.Thus, this method is applicable to predict the FF behaviour of any electronic system by measuring the NF. With this knowledge, the RF design can be improved due to allowing a significant reduction of EM compatibility failure at the end of the development flow. In addition, the very efficient FF radiation model can be used for detailed investigations in various environments and the impact of such an equivalent radiation source on other electronic systems can be assessed.}}, author = {{Schröder, Dominik and Lange, Sven and Hangmann, Christian and Hedayat, Christian}}, booktitle = {{Tensorial Analysis of Networks (TAN) Modelling for PCB Signal Integrity and EMC Analysis}}, isbn = {{9781839530494}}, keywords = {{Huygens' box, NF-to-FF transformation, efficient FF radiation model, FF behaviour, EMI assessment, PCB, near-field measurements, efficient radiation model, far-field behaviour, RF design process, far-field prediction, Huygens'box principle, fullwave simulation, electronic system radiation, equivalent radiation source, electromagnetic simulation tool, near-field scan data, EM compatibility failure reduction}}, pages = {{315--346 (32)}}, publisher = {{ The Institution of Engineering and Technology (IET)}}, title = {{{Far-field prediction combining simulations with near-field measurements for EMI assessment of PCBs}}}, doi = {{10.1049/pbcs072e_ch14}}, year = {{2020}}, } @inproceedings{17055, abstract = {{Understanding a new literature corpus can be a grueling experience for junior scholars. Nevertheless, corresponding guidelines have not been updated for decades. We contend that the traditional strategy of skimming all papers and reading selected papers afterwards needs to be revised. Therefore, we design a new strategy that guides the overall exploratory process by prioritizing influential papers for initial reading, followed by skimming the remaining papers. Consistent with schemata theory, starting with in-depth reading allows readers to acquire more substantial prior content schemata, which are representa-tive for the literature corpus and useful in the following skimming process. To this end, we develop a prototype that identifies the influential papers from a set of PDFs, which is illustrated in a case study in the IT business value domain. With the new strategy, we envision a more efficient process of exploring unknown literature corpora.}}, author = {{Wagner, Gerit and Empl, Philipp and Schryen, Guido}}, booktitle = {{28th European Conference on Information Systems (ECIS 2020)}}, keywords = {{Reading and skimming, Exploring literature, Review methodology, Design science research, Schemata theory}}, location = {{Marrakesh, Morocco}}, title = {{{Designing a Novel Strategy for Exploring Literature Corpora}}}, 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{48366, abstract = {{The proportion of freshmen enrolled in dual study programmes has steadily increased in recent years. From the perspective of potential students, these programmes are highly attractive because they combine types of learning that used to be largely separate at an institutional level: vocational and academic learning. In training-integrated dual study programmes, different institutional contexts, governance regimes, teaching styles and learning environments make bridging these two worlds of learning a challenge for both educators and learners. However, these programmes also allow leeway for didactic innovation, through the cooperation of different types of educational institutions and through new ways of using available didactic methods, and for establishing a new relationship between higher education (HE) and vocational education and training (VET). This paper positions training-integrated dual study programmes as an object of design-based research (DBR). By developing and using an extended model for the pedagogic development of HEIs, “pädagogische Hochschulentwicklung” (Brahm, Jenert, & Euler, 2016a, p. 19; Euler, 2013, p. 360), the paper systematically identifies generic educational problems in these hybrids. Based on a literature review, this paper classifies and explains the design challenges at the level of the learning environment, the study programme and the organisation. The challenges revolve mainly around the cooperation and integration of HE and VET. The paper concludes with an outlook on future DBR projects designing dual studies.}}, author = {{Mordhorst, Lisa and Gössling, Bernd}}, issn = {{2511-0667}}, journal = {{EDeR. Educational Design Research}}, keywords = {{Dual study programmes, Design challenges, Pedagogic development of HEIs, Literature review, Study programme development, DBR cycle}}, number = {{1}}, publisher = {{Staats- und Universitatsbibliothek Hamburg Carl von Ossietzky}}, title = {{{Dual Study Programmes as a Design Challenge: Identifying Areas for Improvement as a Starting Point for Interventions}}}, doi = {{10.15460/eder.4.1.1482}}, volume = {{4}}, year = {{2020}}, } @inproceedings{48850, abstract = {{Sequential model-based optimization (SMBO) approaches are algorithms for solving problems that require computationally or otherwise expensive function evaluations. The key design principle of SMBO is a substitution of the true objective function by a surrogate, which is used to propose the point(s) to be evaluated next. SMBO algorithms are intrinsically modular, leaving the user with many important design choices. Significant research efforts go into understanding which settings perform best for which type of problems. Most works, however, focus on the choice of the model, the acquisition function, and the strategy used to optimize the latter. The choice of the initial sampling strategy, however, receives much less attention. Not surprisingly, quite diverging recommendations can be found in the literature. We analyze in this work how the size and the distribution of the initial sample influences the overall quality of the efficient global optimization (EGO) algorithm, a well-known SMBO approach. While, overall, small initial budgets using Halton sampling seem preferable, we also observe that the performance landscape is rather unstructured. We furthermore identify several situations in which EGO performs unfavorably against random sampling. Both observations indicate that an adaptive SMBO design could be beneficial, making SMBO an interesting test-bed for automated algorithm design.}}, author = {{Bossek, Jakob and Doerr, Carola and Kerschke, Pascal}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference}}, isbn = {{978-1-4503-7128-5}}, keywords = {{continuous black-box optimization, design of experiments, initial design, sequential model-based optimization}}, pages = {{778–786}}, publisher = {{Association for Computing Machinery}}, title = {{{Initial Design Strategies and Their Effects on Sequential Model-Based Optimization: An Exploratory Case Study Based on BBOB}}}, doi = {{10.1145/3377930.3390155}}, year = {{2020}}, }