Prof. Dr. Alexander Asteroth
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Departments, institutes and facilities
- Fachbereich Informatik (43)
- Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE) (41)
- Fachbereich Ingenieurwissenschaften und Kommunikation (7)
- Internationales Zentrum für Nachhaltige Entwicklung (IZNE) (3)
- Institut für KI und Autonome Systeme (A2S) (1)
- Institut für Sicherheitsforschung (ISF) (1)
- Institute of Visual Computing (IVC) (1)
Document Type
- Conference Object (39)
- Article (11)
- Report (4)
- Book (monograph, edited volume) (1)
- Part of a Book (1)
- Diploma Thesis (1)
- Doctoral Thesis (1)
- Preprint (1)
Year of publication
Keywords
- Quality diversity (4)
- MAP-Elites (3)
- Quality Diversity (3)
- Aerodynamics (2)
- Bayesian optimization (2)
- Evolutionary computation (2)
- Heart Rate Prediction (2)
- Neuroevolution (2)
- Surrogate Modeling (2)
- UAV (2)
In der vorliegenden Arbeit werden Verfahren vorgestellt, die geeignet sind, Modelle des menschlichen kardiovaskulären Systems an individuelle Kreislaufreaktionen anzupassen. Allgemeine Kreislaufmodelle des menschlichen kardiovaskulären Systems sind in der Regel nichtlineare Differentialgleichungssysteme, für die es keine effizienten Optimierungsverfahren gibt. Durch die Einschränkung auf relevante Aspekte (bzgl. der Individualisierungsaufgabe) wird ein solches Modell auf Modelle einfacherer Struktur projiziert, die eine Approximation durch Funktionsapproximatoren erlauben, für welche wiederum effiziente Optimierungsalgorithmen existieren. In Abhängigkeit von der Struktur der Individualisierungsaufgabe kommt zusätzlich ein modifiziertes BFGS-Verfahren zum Einsatz, das Approximationen solcher Modellaspekte verwendet um die Konvergenz der Modellindividualisierung zu verbessern.
Theoretische Informatik
(2002)
Eine anschauliche Einführung in die klassischen Themenbereiche der Theoretischen Informatik für Studierende der Informatik im Haupt- und Nebenfach. Die Autoren wählen einen Ansatz, der durch zahlreiche ausgearbeitete Beispiele auch LeserInnen mit nur elementaren Mathematikkenntnissen den Zugang zu Berechenbarkeit, Komplexitätstheorie und formalen Sprachen ermöglicht. Die mathematischen Konzepte werden sowohl formal eingeführt als auch informell erläutert und durch grafische Darstellungen veranschaulicht. Das Buch umfasst den Lehrstoff einführender Vorlesungen in die Theoretische Informatik und bietet zahlreiche Übungsaufgaben zu jedem Kapitel an. (Verlagsangaben)
We present a model checking algorithm for ∀CTL (and full CTL) which uses an iterative abstraction refinement strategy.
It terminates at least for all transition systems M that have a finite simulation or bisimulation quotient. In contrast to other abstraction refinement algorithms, we always work with abstract models whose sizes depend only on the length of the formula θ (but not on the size of the system, which might be infinite).
AErOmAt Abschlussbericht
(2020)
Das Projekt AErOmAt hatte zum Ziel, neue Methoden zu entwickeln, um einen erheblichen Teil aerodynamischer Simulationen bei rechenaufwändigen Optimierungsdomänen einzusparen. Die Hochschule Bonn-Rhein-Sieg (H-BRS) hat auf diesem Weg einen gesellschaftlich relevanten und gleichzeitig wirtschaftlich verwertbaren Beitrag zur Energieeffizienzforschung geleistet. Das Projekt führte außerdem zu einer schnelleren Integration der neuberufenen Antragsteller in die vorhandenen Forschungsstrukturen.
This paper describes the development of a Pedelec controller whose performance level (PL) conforms to European standard on safety of machinery [9] and whose soft- ware is verified to conform to EPAC standard [6] by means of a software verification technique called model checking. In compliance with the standard [9] the hardware needs to implement the required properties corresponding to categories “C” and “D”. The latter is used if the breaks are not able to bring the velomobile with a broken motor controller to a full stop. Therefore the controller needs to implement a test unit, which verifies the functionality of the components and, in case of an emergency, shuts the whole hardware down to prevent injuries of the cyclist. The MTTFd can be measured through a failure graph, which is the result of a FMEA analysis, and can be used to proof that the Pedelec controller meets the regulations of the system specification. The analysis of the system in compliance with [9] usually treats the software as a black box thus ignoring its inner workings and validating its correctness by means of testing. In this paper we present a temporal logic specification according to [6], based on which the software for the Pedelec controller is implemented, and verify instead of only testing its functionality. By means of model checking [1] we proof that the software fulfills all requirements which are regulated by its specification.
This work addresses the issue of finding an optimal flight zone for a side-by-side tracking and following Unmanned Aerial Vehicle(UAV) adhering to space-restricting factors brought upon by a dynamic Vector Field Extraction (VFE) algorithm. The VFE algorithm demands a relatively perpendicular field of view of the UAV to the tracked vehicle, thereby enforcing the space-restricting factors which are distance, angle and altitude. The objective of the UAV is to perform side-by-side tracking and following of a lightweight ground vehicle while acquiring high quality video of tufts attached to the side of the tracked vehicle. The recorded video is supplied to the VFE algorithm that produces the positions and deformations of the tufts over time as they interact with the surrounding air, resulting in an airflow model of the tracked vehicle. The present limitations of wind tunnel tests and computational fluid dynamics simulation suggest the use of a UAV for real world evaluation of the aerodynamic properties of the vehicle’s exterior. The novelty of the proposed approach is alluded to defining the specific flight zone restricting factors while adhering to the VFE algorithm, where as a result we were capable of formalizing a locally-static and a globally-dynamic geofence attached to the tracked vehicle and enclosing the UAV.
Design optimization techniques are often used at the beginning of the design process to explore the space of possible designs. In these domains illumination algorithms, such as MAP-Elites, are promising alternatives to classic optimization algorithms because they produce diverse, high-quality solutions in a single run, instead of only a single near-optimal solution. Unfortunately, these algorithms currently require a large number of function evaluations, limiting their applicability. In this article we introduce a new illumination algorithm, Surrogate-Assisted Illumination (SAIL), that leverages surrogate modeling techniques to create a map of the design space according to user-defined features while minimizing the number of fitness evaluations. On a two-dimensional airfoil optimization problem SAIL produces hundreds of diverse but high-performing designs with several orders of magnitude fewer evaluations than MAP-Elites or CMA-ES. We demonstrate that SAIL is also capable of producing maps of high-performing designs in realistic three-dimensional aerodynamic tasks with an accurate flow simulation. Data-efficient design exploration with SAIL can help designers understand what is possible, beyond what is optimal, by considering more than pure objective-based optimization.