Model-based Product Configuration in Augmented Reality Applications - Gottschalk, Sebastian; Yigitbas, Enes; Schmidt, Eugen; Engels, Gregor (Human-Centered Software Engineering. HCSE 2020)
Augmented Reality (AR) has recently found high attention in mobile shopping apps such as in domains like furniture or decoration. Here, the developers of the apps focus on the positioning of atomic 3D objects in the physical environment. With this focus, they neglect the conﬁguration of multi-faceted 3D object composition according to the user needs and environmental constraints. To tackle these challenges, we present a model-based approach to support AR-assisted product con-ﬁguration based on the concept of Dynamic Software Product Lines. Our approach splits products (e.g. table) into parts (e.g. tabletop, ta-ble legs, funnier) with their 3D objects and additional information (e.g. name, price). The possible products, which can be conﬁgured out of these parts, are stored in a feature model. At runtime, this feature model can be used to conﬁgure 3D object compositions out of the product parts and adapt to user needs and environmental constraints. The beneﬁts of this approach are demonstrated by a case study of conﬁguring modular kitchens with the help of a prototypical mobile-based implementation.
Keywords: Product Configuration; Augmented Reality; Runtime Adaptation; Dynamic Software Product Lines

A Group Signature Scheme from Flexible Public Key Signatures and Structure-Preserving Signatures on Equivalence Classes - Schürmann, Patrick

Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator - Klus, Stefan; Nüske, Feliks; Hamzi, Boumediene (Entropy)
Many dimensionality and model reduction techniques rely on estimating dominant eigenfunctions of associated dynamical operators from data. Important examples include the Koopman operator and its generator, but also the Schrödinger operator. We propose a kernel-based method for the approximation of differential operators in reproducing kernel Hilbert spaces and show how eigenfunctions can be estimated by solving auxiliary matrix eigenvalue problems. The resulting algorithms are applied to molecular dynamics and quantum chemistry examples. Furthermore, we exploit that, under certain conditions, the Schrödinger operator can be transformed into a Kolmogorov backward operator corresponding to a drift-diffusion process and vice versa. This allows us to apply methods developed for the analysis of high-dimensional stochastic differential equations to quantum mechanical systems.

Privacy-Preserving Incentive Systems with Highly Efficient Point-Collection - Bobolz, Jan; Eidens, Fabian; Krenn, Stephan; Slamanig, Daniel; Striecks, Christoph (Proceedings of the 15th ACM Asia Conference on Computer and Communications Security (ASIA CCS ’20),)

Metasurfaces help lasers to mode-lock - Sain, Basudeb; Zentgraf, Thomas (Light: Science & Applications)

Polarization-Encrypted Orbital Angular Momentum Multiplexed Metasurface Holography - Zhou, Hongqiang; Sain, Basudeb; Wang, Yongtian; Schlickriede, Christian; Zhao, Ruizhe; Zhang, Xue; Wei, Qunshuo; Li, Xiaowei; Huang, Lingling; Zentgraf, Thomas (ACS Nano)

Hypothesis-driven Adaptation of Business Models based on Product Line Engineering - Gottschalk, Sebastian; Rittmeier, Florian; Engels, Gregor (Proceedings of the 22nd IEEE International Conference on Business Informatics)
The continuous innovation of its business models is an important task for a company to stay competitive. During this process, the company has to validate various hypotheses about its business models by adapting to uncertain and changing customer needs effectively and efficiently. This adaptation, in turn, can be supported by the concept of Software Product Lines (SPLs). SPLs reduce the time to market by deriving products for customers with changing requirements using a common set of features, structured as a feature model. Analogously, we support the process of business model adaptation by applying the engineering process of SPLs to the structure of the Business Model Canvas (BMC). We call this concept a Business Model Decision Line (BMDL). The BMDL matches business domain knowledge in the form of a feature model with customer needs to derive hypotheses about the business model together with experiments for validation. Our approach is effective by providing a comprehensive overview of possible business model adaptations and efficient by reusing experiments for different hypotheses. We implement our approach in a tool and illustrate the usefulness with an example of developing business models for a mobile application.
Keywords: Business Model Decision Line; Business Model Adaptation; Hypothesis-driven Adaptation; Software Product Line; Feature Model

Model-based Hypothesis Engineering for Supporting Adaptation to Uncertain Customer Needs - Gottschalk, Sebastian; Yigitbas, Enes; Engels, Gregor (Business Modeling and Software Design)
To build successful products, the developers have to adapt their product features and business models to uncertain customer needs. This adaptation is part of the research discipline of Hypotheses Engineering (HE) where customer needs can be seen as hypotheses that need to be tested iteratively by conducting experiments together with the customer. So far, modeling support and associated traceability of this iterative process are missing. Both, in turn, are important to document the adaptation to the customer needs and identify experiments that provide most evidence to the customer needs. To target this issue, we introduce a model-based HE approach with a twofold contribution: First, we develop a modeling language that models hypotheses and experiments as interrelated hierarchies together with a mapping between them. While the hypotheses are labeled with a score level of their current evidence, the experiments are labeled with a score level of maximum evidence that can be achieved during conduction. Second, we provide an iterative process to determine experiments that offer the most evidence improvement to the modeled hypotheses. We illustrate the usefulness of the approach with an example of testing the business model of a mobile application.
Keywords: Hypothesis Engineering; Model-based; Customer Need Adaptation; Business Model; Product Features

A Holistic Approach to Optimization-Based Design of Hybrid Materials - Triebus, Marcel; Tröster, Thomas (Proceedings 4th International Conference Hybrid Materials & Structures)

Distinguishing Knowledge Impact from Citation Impact: A Methodology for Analysing Knowledge Impact for the Literature Review Genre - Schryen, Guido; Wagner, Gerit; Benlian, Alexander
The scientific impact of research papers is multi-dimensional and can be determined quantitatively by means of citation analysis and qualitatively by means of content analysis. Accounting for the widely acknowledged limitations of pure citation analysis, we adopt a knowledge-based perspective on scientific impact to develop a methodology for content-based citation analysis which allows determining how papers have enabled knowledge development in subsequent research (knowledge impact). As knowledge development differs between research genres, we develop a new knowledgebased citation analysis methodology for the genre of standalone literature reviews (LRs). We apply the suggested methodology to the IS business value domain by manually coding 22 LRs and 1,228 citing papers (CPs) and show that the results challenge the assumption that citations indicate knowledge impact. We derive implications for distinguishing knowledge impact from citation impact in the LR genre. Finally, we develop recommendations for authors of LRs, scientific evaluation committees and editorial boards of journals how to apply and benefit from the suggested methodology, and we discuss its efficiency and automatization.
Keywords: Scientific impact; knowledge impact; content-based citation analysis; methodology