@inproceedings{55429, abstract = {{A detailed understanding of the cognitive process underlying diagnostic reasoning in medical experts is currently lacking. While high-level theories like hypothetico-deductive reasoning were proposed long ago, the inner workings of the step-by-step dynamics within the mind remain unknown. We present a fully automated approach to elicit, monitor, and record diagnostic reasoning processes at a fine-grained level. A web-based user interface enables physicians to carry out a full diagnosis process on a simulated patient, given as a pre-defined clinical vignette. By collecting the physician’s information queries and hypothesis revisions, highly detailed diagnostic reasoning trajectories are captured leading to a diagnosis and its justification. Four expert epileptologists with a mean experience of 19 years were recruited to evaluate the system and share their impressions in semi-structured interviews. We find that the recorded trajectories validate proposed theories on broader diagnostic reasoning, while also providing valuable additional details extending previous findings.}}, author = {{Battefeld, Dominik and Mues, Sigrid and Wehner, Tim and House, Patrick and Kellinghaus, Christoph and Wellmer, Jörg and Kopp, Stefan}}, booktitle = {{Proceedings of the 46th Annual Conference of the Cognitive Science Society}}, keywords = {{Differential Diagnosis, Diagnostic Reasoning, Reasoning Process Analysis, Seizure, Epilepsy}}, location = {{Rotterdam, NL}}, title = {{{Revealing the Dynamics of Medical Diagnostic Reasoning as Step-by-Step Cognitive Process Trajectories}}}, year = {{2024}}, } @inproceedings{47522, abstract = {{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.}}, author = {{Prager, Raphael Patrick and Dietrich, Konstantin and Schneider, Lennart and Schäpermeier, Lennart and Bischl, Bernd and Kerschke, Pascal and Trautmann, Heike and Mersmann, Olaf}}, booktitle = {{Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms}}, isbn = {{9798400702020}}, keywords = {{Benchmarking, Instance Generator, Black-Box Continuous Optimization, Exploratory Landscape Analysis, Neural Networks}}, pages = {{129–139}}, publisher = {{Association for Computing Machinery}}, title = {{{Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features}}}, doi = {{10.1145/3594805.3607136}}, year = {{2023}}, } @inproceedings{48872, abstract = {{Quality diversity (QD) is a branch of evolutionary computation that gained increasing interest in recent years. The Map-Elites QD approach defines a feature space, i.e., a partition of the search space, and stores the best solution for each cell of this space. We study a simple QD algorithm in the context of pseudo-Boolean optimisation on the "number of ones" feature space, where the ith cell stores the best solution amongst those with a number of ones in [(i - 1)k, ik - 1]. Here k is a granularity parameter 1 {$\leq$} k {$\leq$} n+1. We give a tight bound on the expected time until all cells are covered for arbitrary fitness functions and for all k and analyse the expected optimisation time of QD on OneMax and other problems whose structure aligns favourably with the feature space. On combinatorial problems we show that QD finds a (1 - 1/e)-approximation when maximising any monotone sub-modular function with a single uniform cardinality constraint efficiently. Defining the feature space as the number of connected components of a connected graph, we show that QD finds a minimum spanning tree in expected polynomial time.}}, author = {{Bossek, Jakob and Sudholt, Dirk}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference}}, isbn = {{9798400701191}}, keywords = {{quality diversity, runtime analysis}}, pages = {{1546–1554}}, publisher = {{Association for Computing Machinery}}, title = {{{Runtime Analysis of Quality Diversity Algorithms}}}, doi = {{10.1145/3583131.3590383}}, year = {{2023}}, } @inproceedings{48886, abstract = {{Generating new instances via evolutionary methods is commonly used to create new benchmarking data-sets, with a focus on attempting to cover an instance-space as completely as possible. Recent approaches have exploited Quality-Diversity methods to evolve sets of instances that are both diverse and discriminatory with respect to a portfolio of solvers, but these methods can be challenging when attempting to find diversity in a high-dimensional feature-space. We address this issue by training a model based on Principal Component Analysis on existing instances to create a low-dimension projection of the high-dimension feature-vectors, and then apply Novelty Search directly in the new low-dimension space. We conduct experiments to evolve diverse and discriminatory instances of Knapsack Problems, comparing the use of Novelty Search in the original feature-space to using Novelty Search in a low-dimensional projection, and repeat over a given set of dimensions. We find that the methods are complementary: if treated as an ensemble, they collectively provide increased coverage of the space. Specifically, searching for novelty in a low-dimension space contributes 56% of the filled regions of the space, while searching directly in the feature-space covers the remaining 44%.}}, author = {{Marrero, Alejandro and Segredo, Eduardo and Hart, Emma and Bossek, Jakob and Neumann, Aneta}}, booktitle = {{Proceedings of the Genetic} and Evolutionary Computation Conference}}, isbn = {{9798400701191}}, keywords = {{evolutionary computation, instance generation, instance-space analysis, knapsack problem, novelty search}}, pages = {{312–320}}, publisher = {{Association for Computing Machinery}}, title = {{{Generating Diverse and Discriminatory Knapsack Instances by Searching for Novelty in Variable Dimensions of Feature-Space}}}, doi = {{10.1145/3583131.3590504}}, year = {{2023}}, } @article{48871, abstract = {{Most runtime analyses of randomised search heuristics focus on the expected number of function evaluations to find a unique global optimum. We ask a fundamental question: if additional search points are declared optimal, or declared as desirable target points, do these additional optima speed up evolutionary algorithms? More formally, we analyse the expected hitting time of a target set OPT{$\cup$}S where S is a set of non-optimal search points and OPT is the set of optima and compare it to the expected hitting time of OPT. We show that the answer to our question depends on the number and placement of search points in S. For all black-box algorithms and all fitness functions with polynomial expected optimisation times we show that, if additional optima are placed randomly, even an exponential number of optima has a negligible effect on the expected optimisation time. Considering Hamming balls around all global optima gives an easier target for some algorithms and functions and can shift the phase transition with respect to offspring population sizes in the (1,{$\lambda$}) EA on OneMax. However, for the one-dimensional Ising model the time to reach Hamming balls of radius (1/2-{$ϵ$})n around optima does not reduce the asymptotic expected optimisation time in the worst case. Finally, on functions where search trajectories typically join in a single search point, turning one search point into an optimum drastically reduces the expected optimisation time.}}, author = {{Bossek, Jakob and Sudholt, Dirk}}, issn = {{0304-3975}}, journal = {{Theoretical Computer Science}}, keywords = {{Evolutionary algorithms, pseudo-Boolean functions, runtime analysis}}, pages = {{113757}}, title = {{{Do Additional Target Points Speed Up Evolutionary Algorithms?}}}, doi = {{10.1016/j.tcs.2023.113757}}, year = {{2023}}, } @inproceedings{37058, abstract = {{Digital technologies have made the line of visibility more transparent, enabling customers to get deeper insights into an organization’s core operations than ever before. This creates new challenges for organizations trying to consistently deliver high-quality customer experiences. In this paper we conduct an empirical analysis of customers’ preferences and their willingness-to-pay for different degrees of process transparency, using the example of digitally-enabled business-to-customer delivery services. Applying conjoint analysis, we quantify customers’ preferences and willingness-to-pay for different service attributes and levels. Our contributions are two-fold: For research, we provide empirical measurements of customers’ preferences and their willingness-to-pay for process transparency, suggesting that more is not always better. Additionally, we provide a blueprint of how conjoint analysis can be applied to study design decisions regarding changing an organization’s digital line of visibility. For practice, our findings enable service managers to make decisions about process transparency and establishing different levels of service quality. }}, author = {{Brennig, Katharina and Müller, Oliver}}, booktitle = {{Hawaii International Conference on System Sciences}}, keywords = {{Digital Services, Line of Visibility, Process Transparency, Customer Preferences, Conjoint Analysis}}, location = {{Lāhainā}}, title = {{{More Isn’t Always Better – Measuring Customers’ Preferences for Digital Process Transparency}}}, year = {{2023}}, } @inbook{52662, abstract = {{Static analysis tools support developers in detecting potential coding issues, such as bugs or vulnerabilities. Research emphasizes technical challenges of such tools but also mentions severe usability shortcomings. These shortcomings hinder the adoption of static analysis tools, and user dissatisfaction may even lead to tool abandonment. To comprehensively assess the state of the art, we present the first systematic usability evaluation of a wide range of static analysis tools. We derived a set of 36 relevant criteria from the literature and used them to evaluate a total of 46 static analysis tools complying with our inclusion and exclusion criteria - a representative set of mainly non-proprietary tools. The evaluation against the usability criteria in a multiple-raters approach shows that two thirds of the considered tools off er poor warning messages, while about three-quarters provide hardly any fix support. Furthermore, the integration of user knowledge is strongly neglected, which could be used for instance, to improve handling of false positives. Finally, issues regarding workflow integration and specialized user interfaces are revealed. These findings should prove useful in guiding and focusing further research and development in user experience for static code analyses.}}, author = {{Nachtigall, Marcus and Schlichtig, Michael and Bodden, Eric}}, booktitle = {{Software Engineering 2023}}, isbn = {{978-3-88579-726-5}}, keywords = {{Automated static analysis, Software usability}}, pages = {{95–96}}, publisher = {{Gesellschaft für Informatik e.V.}}, title = {{{Evaluation of Usability Criteria Addressed by Static Analysis Tools on a Large Scale}}}, year = {{2023}}, } @inbook{52660, abstract = {{Application Programming Interfaces (APIs) are the primary mechanism developers use to obtain access to third-party algorithms and services. Unfortunately, APIs can be misused, which can have catastrophic consequences, especially if the APIs provide security-critical functionalities like cryptography. Understanding what API misuses are, and how they are caused, is important to prevent them, eg, with API misuse detectors. However, definitions for API misuses and related terms in literature vary. This paper presents a systematic literature review to clarify these terms and introduces FUM, a novel Framework for API Usage constraint and Misuse classification. The literature review revealed that API misuses are violations of API usage constraints. To address this, we provide unified definitions and use them to derive FUM. To assess the extent to which FUM aids in determining and guiding the improvement of an API misuses detector’s capabilities, we performed a case study on the state-of the-art misuse detection tool CogniCrypt. The study showed that FUM can be used to properly assess CogniCrypt’s capabilities, identify weaknesses and assist in deriving mitigations and improvements.}}, author = {{Schlichtig, Michael and Sassalla, Steffen and Narasimhan, Krishna and Bodden, Eric}}, booktitle = {{Software Engineering 2023}}, isbn = {{978-3-88579-726-5}}, keywords = {{API misuses API usage constraints, classification framework, API misuse detection, static analysis}}, pages = {{105–106}}, publisher = {{Gesellschaft für Informatik e.V.}}, title = {{{Introducing FUM: A Framework for API Usage Constraint and Misuse Classification}}}, year = {{2023}}, } @article{53320, author = {{Winkler, Michael}}, issn = {{0294-1449}}, journal = {{Annales de l'Institut Henri Poincaré C, Analyse non linéaire}}, keywords = {{Mathematical Physics, Analysis, Applied Mathematics}}, publisher = {{European Mathematical Society - EMS - Publishing House GmbH}}, title = {{{A quantitative strong parabolic maximum principle and application to a taxis-type migration–consumption model involving signal-dependent degenerate diffusion}}}, doi = {{10.4171/aihpc/73}}, year = {{2023}}, } @article{53318, author = {{Li, Genglin and Winkler, Michael}}, issn = {{0003-6811}}, journal = {{Applicable Analysis}}, keywords = {{Applied Mathematics, Analysis}}, number = {{1}}, pages = {{45--64}}, publisher = {{Informa UK Limited}}, title = {{{Refined regularity analysis for a Keller-Segel-consumption system involving signal-dependent motilities}}}, doi = {{10.1080/00036811.2023.2173183}}, volume = {{103}}, year = {{2023}}, } @article{53324, author = {{Ahn, Jaewook and Winkler, Michael}}, issn = {{0944-2669}}, journal = {{Calculus of Variations and Partial Differential Equations}}, keywords = {{Applied Mathematics, Analysis}}, number = {{6}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{A critical exponent for blow-up in a two-dimensional chemotaxis-consumption system}}}, doi = {{10.1007/s00526-023-02523-5}}, volume = {{62}}, year = {{2023}}, } @article{53329, author = {{Tao, Youshan and Winkler, Michael}}, issn = {{1468-1218}}, journal = {{Nonlinear Analysis: Real World Applications}}, keywords = {{Applied Mathematics, Computational Mathematics, General Economics, Econometrics and Finance, General Engineering, General Medicine, Analysis}}, publisher = {{Elsevier BV}}, title = {{{Analysis of a chemotaxis-SIS epidemic model with unbounded infection force}}}, doi = {{10.1016/j.nonrwa.2022.103820}}, volume = {{71}}, year = {{2023}}, } @article{53341, abstract = {{AbstractThe Cauchy problem in $$\mathbb {R}^n$$ R n is considered for the Keller–Segel system $$\begin{aligned} \left\{ \begin{array}{l}u_t = \Delta u - \nabla \cdot (u\nabla v), \\ 0 = \Delta v + u, \end{array} \right. \qquad \qquad (\star ) \end{aligned}$$ u t = Δ u - ∇ · ( u ∇ v ) , 0 = Δ v + u , ( ⋆ ) with a focus on a detailed description of behavior in the presence of nonnegative radially symmetric initial data $$u_0$$ u 0 with non-integrable behavior at spatial infinity. It is shown that if $$u_0$$ u 0 is continuous and bounded, then ($$\star $$ ⋆ ) admits a local-in-time classical solution, whereas if $$u_0(x)\rightarrow +\infty $$ u 0 ( x ) → + ∞ as $$|x|\rightarrow \infty $$ | x | → ∞ , then no such solution can be found. Furthermore, a collection of three sufficient criteria for either global existence or global nonexistence indicates that with respect to the occurrence of finite-time blow-up, spatial decay properties of an explicit singular steady state plays a critical role. In particular, this underlines that explosions in ($$\star $$ ⋆ ) need not be enforced by initially high concentrations near finite points, but can be exclusively due to large tails.}}, author = {{Winkler, Michael}}, issn = {{2296-9020}}, journal = {{Journal of Elliptic and Parabolic Equations}}, keywords = {{Applied Mathematics, Numerical Analysis, Analysis}}, number = {{2}}, pages = {{919--959}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Solutions to the Keller–Segel system with non-integrable behavior at spatial infinity}}}, doi = {{10.1007/s41808-023-00230-y}}, volume = {{9}}, year = {{2023}}, } @article{53342, author = {{Winkler, Michael and Yokota, Tomomi}}, issn = {{0022-0396}}, journal = {{Journal of Differential Equations}}, keywords = {{Analysis, Applied Mathematics}}, pages = {{1--28}}, publisher = {{Elsevier BV}}, title = {{{Avoiding critical mass phenomena by arbitrarily mild saturation of cross-diffusive fluxes in two-dimensional Keller-Segel-Navier-Stokes systems}}}, doi = {{10.1016/j.jde.2023.07.029}}, volume = {{374}}, year = {{2023}}, } @article{53346, author = {{Winkler, Michael}}, issn = {{1079-9389}}, journal = {{Advances in Differential Equations}}, keywords = {{Applied Mathematics, Analysis}}, number = {{11/12}}, publisher = {{Khayyam Publishing, Inc}}, title = {{{Absence of collapse into persistent Dirac-type singularities in a Keller-Segel-Navier-Stokes system involving local sensing}}}, doi = {{10.57262/ade028-1112-921}}, volume = {{28}}, year = {{2023}}, } @article{53540, abstract = {{AbstractThis note is concerned with two families of operators related to the fractional Laplacian, the first arising from the Caffarelli-Silvestre extension problem and the second from the fractional heat equation. They both include the Poisson semigroup. We show that on a complete, connected, and non-compact Riemannian manifold of non-negative Ricci curvature, in both cases, the solution with $$L^1$$ L 1 initial data behaves asymptotically as the mass times the fundamental solution. Similar long-time convergence results remain valid on more general manifolds satisfying the Li-Yau two-sided estimate of the heat kernel. The situation changes drastically on hyperbolic space, and more generally on rank one non-compact symmetric spaces: we show that for the Poisson semigroup, the convergence to the Poisson kernel fails -but remains true under the additional assumption of radial initial data.}}, author = {{Papageorgiou, Efthymia}}, issn = {{0926-2601}}, journal = {{Potential Analysis}}, keywords = {{Analysis}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Large-Time Behavior of Two Families of Operators Related to the Fractional Laplacian on Certain Riemannian Manifolds}}}, doi = {{10.1007/s11118-023-10109-1}}, year = {{2023}}, } @article{53539, abstract = {{AbstractThe infinite Brownian loop on a Riemannian manifold is the limit in distribution of the Brownian bridge of length T around a fixed origin when $$T \rightarrow +\infty $$ T → + ∞ . The aim of this note is to study its long-time asymptotics on Riemannian symmetric spaces G/K of noncompact type and of general rank. This amounts to the behavior of solutions to the heat equation subject to the Doob transform induced by the ground spherical function. Unlike the standard Brownian motion, we observe in this case phenomena which are similar to the Euclidean setting, namely $$L^1$$ L 1 asymptotic convergence without requiring bi-K-invariance for initial data, and strong $$L^{\infty }$$ L ∞ convergence.}}, author = {{Papageorgiou, Efthymia}}, issn = {{2296-9020}}, journal = {{Journal of Elliptic and Parabolic Equations}}, keywords = {{Applied Mathematics, Numerical Analysis, Analysis}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Asymptotics for the infinite Brownian loop on noncompact symmetric spaces}}}, doi = {{10.1007/s41808-023-00250-8}}, year = {{2023}}, } @article{43105, author = {{Black, Tobias and Fuest, Mario and Lankeit, Johannes and Mizukami, Masaaki}}, issn = {{1468-1218}}, journal = {{Nonlinear Analysis: Real World Applications}}, keywords = {{Applied Mathematics, Computational Mathematics, General Economics, Econometrics and Finance, General Engineering, General Medicine, Analysis}}, publisher = {{Elsevier BV}}, title = {{{Possible points of blow-up in chemotaxis systems with spatially heterogeneous logistic source}}}, doi = {{10.1016/j.nonrwa.2023.103868}}, volume = {{73}}, year = {{2023}}, } @inproceedings{44390, abstract = {{The development of autonomous vehicles and their introduction in urban traffic offer many opportunities for traffic improvements. In this paper, an approach for a future traffic control system for mixed autonomy traffic environments is presented. Furthermore, a simulation framework based on the city of Paderborn is introduced to enable the development and examination of such a system. This encompasses multiple elements including the road network itself, traffic lights, sensors as well as methods to analyse the topology of the network. Furthermore, a procedure for traffic demand generation and routing is presented based on statistical data of the city and traffic data obtained by measurements. The resulting model can receive and apply the generated control inputs and in turn generates simulated sensor data for the control system based on the current system state.}}, author = {{Link, Christopher and Malena, Kevin and Gausemeier, Sandra and Trächtler, Ansgar}}, booktitle = {{Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems}}, isbn = {{978-989-758-652-1}}, keywords = {{Traffic Simulation, Traffic Control, Car2X, Mixed Autonomy, Autonomous Vehicles, SUMO, Sensor Simulation, Traffic Demand Generation, Routing, Traffic Lights, Graph Analysis, Traffic Observer}}, location = {{Prague, Czech Republic}}, publisher = {{SCITEPRESS - Science and Technology Publications}}, title = {{{Simulation Environment for Traffic Control Systems Targeting Mixed Autonomy Traffic Scenarios}}}, doi = {{10.5220/0011987600003479}}, year = {{2023}}, } @article{29240, abstract = {{The principle of least action is one of the most fundamental physical principle. It says that among all possible motions connecting two points in a phase space, the system will exhibit those motions which extremise an action functional. Many qualitative features of dynamical systems, such as the presence of conservation laws and energy balance equations, are related to the existence of an action functional. Incorporating variational structure into learning algorithms for dynamical systems is, therefore, crucial in order to make sure that the learned model shares important features with the exact physical system. In this paper we show how to incorporate variational principles into trajectory predictions of learned dynamical systems. The novelty of this work is that (1) our technique relies only on discrete position data of observed trajectories. Velocities or conjugate momenta do not need to be observed or approximated and no prior knowledge about the form of the variational principle is assumed. Instead, they are recovered using backward error analysis. (2) Moreover, our technique compensates discretisation errors when trajectories are computed from the learned system. This is important when moderate to large step-sizes are used and high accuracy is required. For this, we introduce and rigorously analyse the concept of inverse modified Lagrangians by developing an inverse version of variational backward error analysis. (3) Finally, we introduce a method to perform system identification from position observations only, based on variational backward error analysis.}}, author = {{Ober-Blöbaum, Sina and Offen, Christian}}, issn = {{0377-0427}}, journal = {{Journal of Computational and Applied Mathematics}}, keywords = {{Lagrangian learning, variational backward error analysis, modified Lagrangian, variational integrators, physics informed learning}}, pages = {{114780}}, publisher = {{Elsevier}}, title = {{{Variational Learning of Euler–Lagrange Dynamics from Data}}}, doi = {{10.1016/j.cam.2022.114780}}, volume = {{421}}, year = {{2023}}, }