Process Mining Data Canvas: A method to identify data and process knowledge for data collection and preparation in process mining projects - Brock, Jonathan; von Enzberg, Sebastian; Kühn, Arno; Dumitrescu, Roman (Procedia CIRP)
Keywords: General Medicine

Targeted-oriented selection of engineering methods - Wilke, Daria; Schierbaum, Anja; Anacker, Harald; Dumitrescu, Roman (Procedia CIRP)
Keywords: General Medicine

On the Membership and Correctness Problem for State Serializability and Value Opacity - König, Jürgen

XCS for Self-awareness in Autonomous Computing Systems - Hansmeier, Tim

Improved Hardness Results for the Guided Local Hamiltonian Problem - Gharibian, Sevag; Hayakawa, Ryu; Gall, François Le; Morimae, Tomoyuki (Proceedings of the 50th EATCS International Colloquium on Automata, Languages and Programming (ICALP))
Estimating the ground state energy of a local Hamiltonian is a central problem in quantum chemistry. In order to further investigate its complexity and the potential of quantum algorithms for quantum chemistry, Gharibian and Le Gall (STOC 2022) recently introduced the guided local Hamiltonian problem (GLH), which is a variant of the local Hamiltonian problem where an approximation of a ground state is given as an additional input. Gharibian and Le Gall showed quantum advantage (more precisely, BQP-completeness) for GLH with $6$-local Hamiltonians when the guiding vector has overlap (inverse-polynomially) close to 1/2 with a ground state. In this paper, we optimally improve both the locality and the overlap parameters: we show that this quantum advantage (BQP-completeness) persists even with 2-local Hamiltonians, and even when the guiding vector has overlap (inverse-polynomially) close to 1 with a ground state. Moreover, we show that the quantum advantage also holds for 2-local physically motivated Hamiltonians on a 2D square lattice. This makes a further step towards establishing practical quantum advantage in quantum chemistry.

Stakeholder-oriented Elaboration of Artificial Intelligence use cases using the example of Special-Purpose engineering - Humpert, Lynn; Wäschle, Moritz; Horstmeyer, Sarah; Anacker, Harald; Dumitrescu, Roman; Albers, Albert (Procedia CIRP)
Keywords: General Medicine

Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features - Prager, Raphael Patrick; Dietrich, Konstantin; Schneider, Lennart; Schäpermeier, Lennart; Bischl, Bernd; Kerschke, Pascal; Trautmann, Heike; Mersmann, Olaf (Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms)
Artificial benchmark functions are commonly used in optimization research because of their ability to rapidly evaluate potential solutions, making them a preferred substitute for real-world problems. However, these benchmark functions have faced criticism for their limited resemblance to real-world problems. In response, recent research has focused on automatically generating new benchmark functions for areas where established test suites are inadequate. These approaches have limitations, such as the difficulty of generating new benchmark functions that exhibit exploratory landscape analysis (ELA) features beyond those of existing benchmarks.The objective of this work is to develop a method for generating benchmark functions for single-objective continuous optimization with user-specified structural properties. Specifically, we aim to demonstrate a proof of concept for a method that uses an ELA feature vector to specify these properties in advance. To achieve this, we begin by generating a random sample of decision space variables and objective values. We then adjust the objective values using CMA-ES until the corresponding features of our new problem match the predefined ELA features within a specified threshold. By iteratively transforming the landscape in this way, we ensure that the resulting function exhibits the desired properties. To create the final function, we use the resulting point cloud as training data for a simple neural network that produces a function exhibiting the target ELA features. We demonstrate the effectiveness of this approach by replicating the existing functions of the well-known BBOB suite and creating new functions with ELA feature values that are not present in BBOB.
Keywords: Benchmarking; Instance Generator; Black-Box Continuous Optimization; Exploratory Landscape Analysis; Neural Networks

Nullifying the Inherent Bias of Non-invariant Exploratory Landscape Analysis Features - Prager, Raphael Patrick; Trautmann, Heike (Applications of Evolutionary Computation)
Exploratory landscape analysis (ELA) in single-objective black-box optimization relies on a comprehensive and large set of numerical features characterizing problem instances. Those foster problem understanding and serve as basis for constructing automated algorithm selection models choosing the best suited algorithm for a problem at hand based on the aforementioned features computed prior to optimization. This work specifically points to the sensitivity of a substantial proportion of these features to absolute objective values, i.e., we observe a lack of shift and scale invariance. We show that this unfortunately induces bias within automated algorithm selection models, an overfitting to specific benchmark problem sets used for training and thereby hinders generalization capabilities to unseen problems. We tackle these issues by presenting an appropriate objective normalization to be used prior to ELA feature computation and empirically illustrate the respective effectiveness focusing on the BBOB benchmark set.

Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets - Schäpermeier, Lennart; Kerschke, Pascal; Grimme, Christian; Trautmann, Heike (Evolutionary Multi-Criterion Optimization)
The design and choice of benchmark suites are ongoing topics of discussion in the multi-objective optimization community. Some suites provide a good understanding of their Pareto sets and fronts, such as the well-known DTLZ and ZDT problems. However, they lack diversity in their landscape properties and do not provide a mechanism for creating multiple distinct problem instances. Other suites, like bi-objective BBOB, possess diverse and challenging landscape properties, but their optima are not well understood and can only be approximated empirically without any guarantees.

Pflacco: Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems in Python - Prager, Raphael Patrick; Trautmann, Heike (Evolutionary Computation)
The herein proposed Python package pflacco provides a set of numerical features to characterize single-objective continuous and constrained optimization problems. Thereby, pflacco addresses two major challenges in the area optimization. Firstly, it provides the means to develop an understanding of a given problem instance, which is crucial for designing, selecting, or configuring optimization algorithms in general. Secondly, these numerical features can be utilized in the research streams of automated algorithm selection and configuration. While the majority of these landscape features is already available in the R package flacco, our Python implementation offers these tools to an even wider audience and thereby promotes research interests and novel avenues in the area of optimization.

Privacy-Preserving Natural Language Processing - Habernal, Ivan; Mireshghallah, Fatemehsadat; Thaine, Patricia; Ghanavati, Sepideh; Feyisetan, Oluwaseyi (Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Tutorial Abstracts)

Trade-Offs Between Fairness and Privacy in Language Modeling - Matzken, Cleo; Eger, Steffen; Habernal, Ivan (Findings of the Association for Computational Linguistics: ACL 2023)

Crowdsourcing on Sensitive Data with Privacy-Preserving Text Rewriting - Mouhammad, Nina; Daxenberger, Johannes; Schiller, Benjamin; Habernal, Ivan (Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII))

Privacy-Preserving Models for Legal Natural Language Processing - Yin, Ying; Habernal, Ivan (Proceedings of the Natural Legal Language Processing Workshop 2022)

Zuweisung verteilter Speicher unter Maximierung der minimalen gewichteten Bandbreite - Decking, Leo
Bei dem betrachteten Speicherproblem werden Daten mit verschiedenen Zugriffswahrscheinlichkeiten auf Speicher mit verschiedenen Bandbreiten und Kapazitäten aufgeteilt, dabei sind Replikate erlaubt. Es wird die nach Zugriffswahrscheinlichkeit gewichtete kleinste Bandbreite der Daten maximiert. Wir zeigen, dass sowohl das diskrete Speicherproblem, bei dem die Bandbreite der Speicher jeweils gleichmäßig auf die dort abgelegten Daten aufgeteilt wird, als auch das kontinuierliche Speicherproblem, bei dem die Bandbreite der Speicher beliebig auf abgelegte Daten verteilt werden darf, NP-schwer ist. Es können also, wenn P ̸ = NP, keine effizienten Algorithmen für eine optimale Lösung existieren. Stattdessen zeigen wir jeweils einen 1/2-Approximationsalgorithmus.

Digitizing Processes in Manufacturing Companies via Low-Code Software (to appear) - Weidmann, Nils; Kirchhoff, Jonas; Sauer, Stefan
Low-code development platforms (LCDPs) recently sparked interest in both academia and industry, promising to speed up software development and make it accessible to users with little or no programming experience. Thus, the mass-development of software applications that are custom-made to the tasks, skills, and preferences of end users is potentially enabled. Although different LCDPs have been analysed with respect to their functionality and applied to exemplary case studies in recent work, there is a shortage of experience reports in which LCDPs are used to digitize business processes in small and medium manufacturing enterprises. In this paper, we therefore summarize our experience from supporting industry partners to identify business processes that are suitable for being implemented with low-code technologies and to select an LCDP that meets the requirements of the business process while aligning with the overall digitization strategy of the respective company. We also present the opportunities and challenges of the low-code approach as perceived by industry partners. In summary, the low-code approach should be seen as an essential factor for the digitization of business processes in small and medium manufacturing companies.

Introduction to the Minitrack on Data-driven Services in Manufacturing: Innovation, Engineering, Transformation, and Management - Koldewey, Christian; Martin, Rabe; Dumitrescu, Roman; Winter, Johannes (Proceedings of the 56th Hawaii International Conference on System Sciences)

Datengestützte Produktplanung
Unter dem Einfluss der Digitalisierung wandeln sich mechatronische Produkte zunehmend in cyber-physische Systeme (CPS). Diese sind in der Lage, umfangreiche Daten während ihres Betriebs zu sammeln und über digitale Netzinfrastrukturen zur Verfügung zu stellen. Gemeinsam mit weiteren Daten aus der Betriebsphase versprechen sie wertvolle Erkenntnisse über das Produkt und dessen Nutzer, welche für die Hersteller der CPS insbesondere für die Planung zukünftiger Produktgenerationenrelevant sind. Die zielgerichtete Nutzung von Betriebsdaten in der strategischen Produktplanung stellt produzierende Unternehmen jedoch noch vor zahlreiche Herausforderungen, z. B. hinsichtlich der Identifizierung Erfolg versprechender Use Cases. Das vorliegende Buch greift diese Herausforderungen auf und stellt ein Instrumentarium vor, das produzierende Unternehmen zur datengestützten Produktplanung befähigt. Neben der Vorstellung praxiserprobter Methoden und Werkzeuge werden Einblicke in vier Pilotprojekte gegeben. Das Instrumentarium entstand im Forschungsprojekt „DizRuPt“, das vom Bundesministerium für Bildung und Forschung (BMBF) gefördert wurde.

"Always Contribute Back": A Qualitative Study on Security Challenges of the Open Source Supply Chain - Wermke, Dominik; Klemmer, Jan H.; Wöhler, Noah; Schmüser, Juliane; Sri Ramulu, Harshini; Acar, Yasemin; Fahl, Sascha (44th IEEE Symposium on Security and Privacy, SP 2023, San Francisco, CA, USA, May 21-25, 2023)

Pushed by Accident: A Mixed-Methods Study on Strategies of Handling Secret Information in Source Code Repositories - Krause, Alexander; Klemmer, Jan H.; Huaman, Nicolas; Wermke, Dominik; Acar, Yasemin; Fahl, Sascha (32nd USENIX Security Symposium, USENIX Security 2023, Anaheim, CA, USA, August 9-11, 2023)

It’s like flossing your teeth: On the Importance and Challenges of Reproducible Builds for Software Supply Chain Security - Fourné, Marcel; Wermke, Dominik; Enck, William; Fahl, Sascha; Acar, Yasemin (44th IEEE Symposium on Security and Privacy, SP 2023, San Francisco, CA, USA, May 21-25, 2023)

"In Eighty Percent of the Cases, I Select the Password for Them": Security and Privacy Challenges, Advice, and Opportunities at Cybercafes in Kenya - Munyendo, Collins W.; Acar, Yasemin; Aviv, Adam J. (44th IEEE Symposium on Security and Privacy, SP 2023, San Francisco, CA, USA, May 21-25, 2023)

Ethical Frameworks and Computer Security Trolley Problems: Foundations for Conversations - Kohno, Tadayoshi; Acar, Yasemin; Loh, Wulf (CoRR)

A World Full of Privacy and Security (Mis)conceptions? Findings of a Representative Survey in 12 Countries - Herbert, Franziska; Becker, Steffen; Schaewitz, Leonie; Hielscher, Jonas; Kowalewski, Marvin; Sasse, M. Angela; Acar, Yasemin; Dürmuth, Markus (Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, CHI 2023, Hamburg, Germany, April 23-28, 2023)

"We are a startup to the core": A qualitative interview study on the security and privacy development practices in Turkish software startups - Keküllüoglu, Dilara; Acar, Yasemin (44th IEEE Symposium on Security and Privacy, SP 2023, San Francisco, CA, USA, May 21-25, 2023)

"Oh yes! over-preparing for meetings is my jam :)": The Gendered Experiences of System Administrators - Kaur, Mannat; Sri Ramulu, Harshini; Acar, Yasemin; Fiebig, Tobias (Proc. ACM Hum. Comput. Interact.)

S3C2 Summit 2202-09: Industry Secure Suppy Chain Summit - Tran, Mindy; Acar, Yasemin; Cucker, Michel; Enck, William; Kapravelos, Alexandros; Kästner, Christian; Williams, Laurie A. (CoRR)

S3C2 Summit 2023-02: Industry Secure Supply Chain Summit - Dunlap, Trevor; Acar, Yasemin; Cucker, Michel; Enck, William; Kapravelos, Alexandros; Kästner, Christian; Williams, Laurie A. (CoRR)

S3C2 Summit 2023-06: Government Secure Supply Chain Summit - Enck, William; Acar, Yasemin; Cukier, Michel; Kapravelos, Alexandros; Kästner, Christian; Williams, Laurie A. (CoRR)

"Security is not my field, I’m a stats guy": A Qualitative Root Cause Analysis of Barriers to Adversarial Machine Learning Defenses in Industry - Mink, Jaron; Kaur, Harjot; Schmüser, Juliane; Fahl, Sascha; Acar, Yasemin (32nd USENIX Security Symposium, USENIX Security 2023, Anaheim, CA, USA, August 9-11, 2023)

Lost and not Found: An Investigation of Recovery Methods for Multi-Factor Authentication - Amft, Sabrina; Höltervennhoff, Sandra; Huaman, Nicolas; Krause, Alexander; Simko, Lucy; Acar, Yasemin; Fahl, Sascha (CoRR)

Nachhaltigkeit durch Daten im MBSE: Einblick in die Entwicklung eines Modell-Empfehlungssystems - Tissen, Denis; Tschirner, Christian; Koldewey, Christian; Dumitrescu, Roman (Tag des Systems Engineering)

A process-model for tailoring prototyping of cyber-physical systems - Tissen, Denis; Koldewey, Christian; Dumitrescu, Roman

Private Set Intersection using Third Generation FHE - Anonymous, A.

Rational Models in Cryptography Applied to Matching - Anonymous, A.

Platform Approach for Modularising Battery Electric fast Ferries - Seidenberg, Tobias; Disselkamp, Jan-Philipp; Jürgenhake, Christoph; Anacker, Harald; Dumitrescu, Roman; Papanikolaou, Apostolos (Proceedings of the Design Society)
Abstract The transportation sector is responsible for a relevant share of the total emissions and offers great potentials. It is necessary to implement as many zero-emission mobility systems as possible in the shortest time. For fast ferries, which are a relevant transport manner for a large share of the global population, technical issues could be solved and the successful operation was demonstrated. Up to today high-speed ships have been fully individually designed because physical effects demand for an individual optimisation for each use-case. Specifically for battery electric ships the overall efficiency is crucial to ensure not only an ecological but also economical operation. With today's methods the design and production of such an individual designed ferry does take too long. To cover the rising demand, new approaches for mass production need to be established. In this paper we describe a method for designing a platform for ships with the example of a battery electric fast ferry. The focus is on the actual modularisation, as other aspects like requirements or results of our example case are published elsewhere and are therefore just included briefly. The method is validated on the world's first battery powered high-speed ferry.

A systematic literature review on the Digital Twin of the factory in the context of the product and factory lifecycle - Cieply, Jonas; Disselkamp, Jan-Philipp; Dyck, Florian; Alturk, Waddah; Kühn, Arno; Dumitrescu, Roman (Procedia CIRP)
Keywords: General Medicine

Development of a modular architecture for complex mechatronic systems - Seidenberg, Tobias; Disselkamp, Jan-Philipp; Jürgenhake, Christoph; Grobbel, Daniel; Dumitrescu, Roman; Papanikolaou, Apostolos (Procedia CIRP)
Keywords: General Medicine

Integrated product and production development - a systematic literature review - Disselkamp, Jan-Philipp; Cieply, Jonas; Dyck, Florian; Grothe, Robin; Anacker, Harald; Dumitrescu, Roman (Procedia CIRP)
Keywords: General Medicine

Systems Engineering Potentials and Use Cases for the Offer Phase in Special Purpose Machinery - Wilke, Daria; Humpert, Lynn; Mansheim, Johanna; Anacker, Harald; Dumitrescu, Roman (DS 125: Proceedings of the 34th Symposium Design for X (DFX2023))

Venture Client Model: A systematic Literature Review - Haarmann, Lennard; Machon, Fabian; Rabe, Martin; Asmar, Laban; Dumitrescu, Roman (European Conference on Innovation and Entrepreneurship)
Established companies are increasingly opening their innovation systems to stay ahead of the competition. In this context, collaboration with innovative and agile start-ups are gaining continuously more importance. In the past established companies often used common corporate venturing methods such as incubators, accelerators, or corporate venture capital for collaboration. Compared to these methods the venture client model is relatively new and was invented by BMW employees in 2014. Using the venture client model, established companies become early clients of the start-ups even it is still a venture to do so. Together they carry out a pilot project to develop a proof of concept and validate it under real conditions. If successful, they enter a long-term collaboration to integrate the start-up’s solution into products, processes, or business models of the established company. The aim of this paper is to sum up the current literature and set a foundation for future research on this topic. Therefore, we conduct a systematic literature review. As a result, we provide a definition of the venture client model, describe characteristics, present advantages from the perspective of established companies and start-ups. In addition, we summarize the state of research regarding strategy, process, and organizational structure and for the venture client model. In terms of strategy, future research should elaborate defining elements of a strategy as well as ways to integrate the venture client model into the corporate innovation-ecosystem. Focusing on the process additional research is needed on a venture client reference process and its integration into the corporate’s core processes. Referring to the organizational structure a reference architecture for a venture client unit as well as its positioning within the organization (e.g., innovation management or corporate strategy) should be further investigated.

Framework for Dual Transformation: A Systematic Literature Review on the Interplays between Digitalization and Sustainability - Kürpick, Christian; Kühn, Arno; Olszewski, Luca; Dumitrescu, Roman (2023 IEEE Conference on Technologies for Sustainability (SusTech))

A Technology Foresight Maturity Model - Ellermann, Kai; Asmar, Laban; Dumitrescu, Roman (ISPIM Conference Proceedings)

A process mining maturity model: Enabling organizations to assess and improve their process mining activities - Brock, Jonathan; Löhr, Bernd; Brennig, Katharina; Seger, Thilo; Bartelheimer, Christian; von Enzberg, Sebastian; Kühn, Arno; Dumitrescu, Roman (ECIS 2023 Proceedings at AIS Electronic Library (AISeL).)

Systematics for an Integrative Modelling of Product and Production System - Schäfer, Louis; Günther, Matthias; Martin, Alex; Lüpfert, Mariella; Mandel, Constantin; Rapp, Simon; Lanza, Gisela; Anacker, Harald; Albers, Albert; Köchling, Daniel (Procedia CIRP)
Keywords: General Medicine

Virtual Assembly for Engineering – A Systematic Literature Review - Dyck, Florian; Anacker, Harald; Dumitrescu, Roman (Procedia CIRP)
Keywords: General Medicine

How Much User Context Do We Need? Privacy by Design in Mental Health NLP Applications - Sawhney, Ramit; Neerkaje, Atula; Habernal, Ivan; Flek, Lucie (Proceedings of the International AAAI Conference on Web and Social Media)
Clinical NLP tasks such as mental health assessment from text, must take social constraints into account - the performance maximization must be constrained by the utmost importance of guaranteeing privacy of user data. Consumer protection regulations, such as GDPR, generally handle privacy by restricting data availability, such as requiring to limit user data to 'what is necessary' for a given purpose. In this work, we reason that providing stricter formal privacy guarantees, while increasing the volume of user data in the model, in most cases increases benefit for all parties involved, especially for the user. We demonstrate our arguments on two existing suicide risk assessment datasets of Twitter and Reddit posts. We present the first analysis juxtaposing user history length and differential privacy budgets and elaborate how modeling additional user context enables utility preservation while maintaining acceptable user privacy guarantees.

One size does not fit all: Investigating strategies for differentially-private learning across NLP tasks - Senge, Manuel; Igamberdiev, Timour; Habernal, Ivan (Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing)

DP-BART for Privatized Text Rewriting under Local Differential Privacy - Igamberdiev, Timour; Habernal, Ivan (Findings of the Association for Computational Linguistics: ACL 2023)

The Legal Argument Reasoning Task in Civil Procedure - Bongard, Leonard; Held, Lena; Habernal, Ivan (Proceedings of the Natural Legal Language Processing Workshop 2022)