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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.
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).
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)
Microcontroller-based sensor systems offer great opportunities for the implementation of safety features for potentially dangerous machinery. However, in general they are difficult to assess with regard to their reliability and failure rate. This paper describes the safety assessment of hardware and software of a new and innovative sensor system. The hardware is assessed by standardized methods according to norm EN ISO 13849-1, while the use of model checking is presented as an approach to solve the problem of validating the software.
A robot (e.g. mobile manipulator) that interacts with its environment to perform its tasks, often faces situations in which it is unable to achieve its goals despite perfect functioning of its sensors and actuators. These situations occur when the behavior of the object(s) manipulated by the robot deviates from its expected course because of unforeseeable ircumstances. These deviations are experienced by the robot as unknown external faults. In this work we present an approach that increases reliability of mobile manipulators against the unknown external faults. This approach focuses on the actions of manipulators which involve releasing of an object. The proposed approach, which is triggered after detection of a fault, is formulated as a three-step scheme that takes a definition of a planning operator and an example simulation as its inputs. The planning operator corresponds to the action that fails because of the fault occurrence, whereas the example simulation shows the desired/expected behavior of the objects for the same action. In its first step, the scheme finds a description of the expected behavior of the objects in terms of logical atoms (i.e. description vocabulary). The description of the simulation is used by the second step to find limits of the parameters of the manipulated object. These parameters are the variables that define the releasing state of the object.
Using randomly chosen values of the parameters within these limits, this step creates different examples of the releasing state of the object. Each one of these examples is labelled as desired or undesired according to the behavior exhibited by the object (in the simulation), when the object is released in the state corresponded by the example. The description vocabulary is also used in labeling the examples autonomously. In the third step, an algorithm (i.e. N-Bins) uses the labelled examples to suggest the state for the object in which releasing it avoids the occurrence of unknown external faults.
The proposed N-Bins algorithm can also be used for binary classification problems. Therefore, in our experiments with the proposed approach we also test its prediction ability along with the analysis of the results of our approach. The results show that under the circumstances peculiar to our approach, N-Bins algorithm shows reasonable prediction accuracy where other state of the art classification algorithms fail to do so. Thus, N-Bins also extends the ability of a robot to predict the behavior of the object to avoid unknown external faults. In this work we use simulation environment OPENRave that uses physics engine ODE to simulate the dynamics of rigid bodies.
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.
Die Jahresberichte der Hochschule Bonn-Rhein-Sieg haben jedes Mal ein anderes Schwerpunktthema. Für den Jahresbericht 2012 lautet das Thema "Verantwortlich handeln und Vorbild sein: Die Hochschule in der Gesellschaft".
Den Anfang bildet ein Gespräch zwischen dem Intendanten der Deutschen Welle, Erik Bettermann, und Hochschulpräsident Hartmut Ihne über Verantwortung in der Ausbildung und das Engagement in der Entwicklungszusammenarbeit. In den Kapiteln Studium & Lehre, Forschung, Campus, Region und Internationales findet sich ein vielfältiges Themenspektrum, wobei die Übergänge fließend sind, denn viele Themen ließen sich auch durchaus anderen Kapiteln zuordnen.
Sonderseiten sind in der neuen Ausgabe der "Pause" gewidmet: Forschungssemestern und Sabbatjahr, die Pause im wissenschaftlichen Fokus oder die ganz normale Kaffeepause. Pausen müssen sein.
The Report starts with an interview between Eric Bettermann, Director of the German radio station Deutsche Welle, and University President Hartmut Ihne, which deals with responsibility in education and our University’s activities in the area of development cooperation. The chapters “Studies & Research”, “Research”, “Campus” , “The Region and International Issues” cover a wide spectrum of topics that are not rigidly defined because many topics might just as readily be assigned to other chapters.
In the latest edition, some special pages have been dedicated to the topic of “Taking a break”, i.e. to research semesters and sabbaticals, to breaks as a scientific focal point or to absolutely normal coffee breaks. Breaks are an essential part of our lives.
Aufgrund eines nahezu gleichlautenden Beschlusses des Kreistages im Rhein-Sieg-Kreis (RSK) und des Hauptausschusses der Stadt Bonn im Jahr 2011 wurden die jeweiligen Verwaltungen beauftragt, gemeinsam mit den Energieversorgern der Region ein Starthilfekonzept Elektromobilität zu entwickeln. In Folge dieses Beschlusses konstituierte sich Ende 2011 ein Arbeitskreis, der aus den Verwaltungen des Rhein-Sieg-Kreises und der Stadt Bonn, den Energieversorgern SWB Energie und Wasser, der Rhenag, den Stadtwerken Troisdorf, der Rheinenergie und den RWE besteht. Die inhaltlichen Schwerpunkte, die inzwischen in drei Arbeitskreisen behandelt werden, umfassen den Ausbau der Ladeinfrastruktur, die Öffentlichkeitsarbeit und die Bereitstellung von Strom aus regenerativen Quellen durch den Zubau entsprechender Anlagen in der Region. Während Maßnahmen zur Öffentlichkeitsarbeit und die Bereitstellung Grünen Stroms aus den Arbeitskreisen direkt bearbeitet und bewegt werden, ist dies aufgrund der Komplexität des Themas und der zahlreichen Einflussgrößen beim Ausbau der Ladeinfrastruktur nicht möglich. Daraus entstand die Überlegung einer Kooperation mit der Hochschule Bonn-Rhein-Sieg.
With the increasing average age of the population in many developed countries, afflictions like cardiovascular diseases have also increased. Exercising has a proven therapeutic effect on the cardiovascular system and can counteract this development. To avoid overstrain, determining an optimal training dose is crucial. In previous research, heart rate has been shown to be a good measure for cardiovascular behavior. Hence, prediction of the heart rate from work load information is an essential part in models used for training control. Most heart-rate-based models are described in the context of specific scenarios, and have been evaluated on unique datasets only. In this paper, we conduct a joint evaluation of existing approaches to model the cardiovascular system under a certain strain, and compare their predictive performance. For this purpose, we investigated some analytical models as well as some machine learning approaches in two scenarios: prediction over a certain time horizon into the future, and estimation of the relation between work load and heart rate over a whole training session.
Ohne Zweifel kein Wissen und keine Innovation, dies gilt für die Forschung im Allgemeinen und natürlich auch an unserer Hochschule. Gerade in der Wissenschaft ist der methodische Zweifel oft der Ausgangspunkt einer spezifischen Untersuchung. Er soll dabei behilflich sein, Klarheit zu erlangen. Frei nach dem Philosophen Rene Descartes: Was kann ich eigentlich mit Sicherheit wissen? Nur wer ab und an zweifelt, der schaut um die Ecke, stellt sich, andere und seine Umwelt in Frage, sucht nach neuen Wegen, Antworten und strebt nach Veränderung. Und auch dort, wo Wissenschaft vermittelt wird, also im Seminar, in einer Übung oder Vorlesung, muss Platz sein für eine selbstreflexive Grundhaltung. An der H-BRS ist Zweifeln also nicht nur erlaubt, sondern erwünscht.
Doubting - Path to Science
(2016)
Förderpreise 2016
(2016)
During exercise, heart rate has proven to be a good measure in planning workouts. It is not only simple to measure but also well understood and has been used for many years for workout planning. To use heart rate to control physical exercise, a model which predicts future heart rate dependent on a given strain can be utilized. In this paper, we present a mathematical model based on convolution for predicting the heart rate response to strain with four physiologically explainable parameters. This model is based on the general idea of the Fitness-Fatigue model for performance analysis, but is revised here for heart rate analysis. Comparisons show that the Convolution model can compete with other known heart rate models. Furthermore, this new model can be improved by reducing the number of parameters. The remaining parameter seems to be a promising indicator of the actual subject’s fitness.
Analyzing training performance in sport is usually based on standardized test protocols and needs laboratory equipment, e.g., for measuring blood lactate concentration or other physiological body parameters. Avoiding special equipment and standardized test protocols, we show that it is possible to reach a quality of performance simulation comparable to the results of laboratory studies using training models with nothing but training data. For this purpose, we introduce a fitting concept for a performance model that takes the peculiarities of using training data for the task of performance diagnostics into account. With a specific way of data preprocessing, accuracy of laboratory studies can be achieved for about 50% of the tested subjects, while lower correlation of the other 50% can be explained.
The Fitness-Fatigue model (Calvert et al. 1976) is widely used for performance analysis. This antagonistic model is based on a fitness-term, a fatigue-term, and an initial basic level of performance. Instead of generic parameter values, individualizing the model needs a fitting of parameters. With fitted parameters, the model adapts to account for individual responses to strain. Even though in most cases fitting of recorded training data shows useful results, without modification the model cannot be simply used for prediction.
Forschung@H-BRS
(2017)
Die Hochschule präsentiert mit ihrer neuen Broschüre "Forschung@H-BRS" ausgewählte Projekte von Wissenschaftlerinnen und Wissenschaftlern aus den Instituten und Fachbereichen in einem ansprechenden Format. Hochschulpräsident Harmtut Ihne blickt zu Anfang der Broschüre auf den Stand der anwendungsorientierten Forschung an der Hochschule und in Deutschland.
Neuroevolution methods evolve the weights of a neural network, and in some cases the topology, but little work has been done to analyze the effect of evolving the activation functions of individual nodes on network size, an important factor when training networks with a small number of samples. In this work we extend the neuroevolution algorithm NEAT to evolve the activation function of neurons in addition to the topology and weights of the network. The size and performance of networks produced using NEAT with uniform activation in all nodes, or homogenous networks, is compared to networks which contain a mixture of activation functions, or heterogenous networks. For a number of regression and classification benchmarks it is shown that, (1) qualitatively different activation functions lead to different results in homogeneous networks, (2) the heterogeneous version of NEAT is able to select well performing activation functions, (3) the produced heterogeneous networks are significantly smaller than homogeneous networks.
The MAP-Elites algorithm produces a set of high-performing solutions that vary according to features defined by the user. This technique has the potential to be a powerful tool for design space exploration, but is limited by the need for numerous evaluations. The Surrogate-Assisted Illumination algorithm (SAIL), introduced here, integrates approximative models and intelligent sampling of the objective function to minimize the number of evaluations required by MAP-Elites.
The ability of SAIL to efficiently produce both accurate models and diverse high performing solutions is illustrated on a 2D airfoil design problem. The search space is divided into bins, each holding a design with a different combination of features. In each bin SAIL produces a better performing solution than MAP-Elites, and requires several orders of magnitude fewer evaluations. The CMA-ES algorithm was used to produce an optimal design in each bin: with the same number of evaluations required by CMA-ES to find a near-optimal solution in a single bin, SAIL finds solutions of similar quality in every bin.
A new method for design space exploration and optimization, Surrogate-Assisted Illumination (SAIL), is presented. Inspired by robotics techniques designed to produce diverse repertoires of behaviors for use in damage recovery, SAIL produces diverse designs that vary according to features specified by the designer. By producing high-performing designs with varied combinations of user-defined features a map of the design space is created. This map illuminates the relationship between the chosen features and performance, and can aid designers in identifying promising design concepts. SAIL is designed for use with compu-tationally expensive design problems, such as fluid or structural dynamics, and integrates approximative models and intelligent sampling of the objective function to minimize the number of function evaluations required. On a 2D airfoil optimization problem SAIL is shown to produce hundreds of diverse designs which perform competitively with those found by state-of-the-art black box optimization. Its capabilities are further illustrated in a more expensive 3D aerodynamic optimization task.
The MAP-Elites algorithm produces a set of high-performing solutions that vary according to features defined by the user. This technique to 'illuminate' the problem space through the lens of chosen features has the potential to be a powerful tool for exploring design spaces, but is limited by the need for numerous evaluations. The Surrogate-Assisted Illumination (SAIL) algorithm, introduced here, integrates approximative models and intelligent sampling of the objective function to minimize the number of evaluations required by MAP-Elites.
The ability of SAIL to efficiently produce both accurate models and diverse high-performing solutions is illustrated on a 2D airfoil design problem. The search space is divided into bins, each holding a design with a different combination of features. In each bin SAIL produces a better performing solution than MAP-Elites, and requires several orders of magnitude fewer evaluations. The CMA-ES algorithm was used to produce an optimal design in each bin: with the same number of evaluations required by CMA-ES to find a near-optimal solution in a single bin, SAIL finds solutions of similar quality in every bin.
TREE Jahresbericht 2017
(2018)
Knapp fünf Jahre nach Gründung als Fachbereichsinstitut und zwei Jahre nach Verankerung als zentrale wissenschaftliche Einrichtung der Hochschule präsentieren wir - nicht ganz ohne Stolz - den ersten Jahresbericht des Instituts TREE. Er soll in seiner Breite als auch in seiner Tiefe die Stärken unserer gemeinschaftlichen Anstrengungen im Forschungsfeld der nachhaltigen Technologien aufzeigen: interdisziplinär, forschungsstark, nachwuchsfördernd und gesellschaftszugewandt. TREE ist weiterhin ein im Aufbruch begriffenes Institut, aber gerade das Jahr 2017 zeigt auch, dass wir uns schon in der Wissenschaftslandkarte einen Namen machen konnten: nach NaWETec konnte mit dem Themenkomplex "Effiziente Transportalternativen" ein zweiter Forschungsschwerpunkt drittmittelgefördert etabliert werden. Erste Promotionen im Rahmen des TREE konnten erfolgreich abgeschlossen und interessante Nachwuchswissenschaftler für "FHKarrierewege" gewonnen werden.
The use of wearable devices or “wearables” in the physical activity domain has been increasing in the last years. These devices are used as training tools providing the user with detailed information about individual physiological responses and feedback to the physical training process. Advantages in sensor technology, miniaturization, energy consumption and processing power increased the usability of these wearables. Furthermore, available sensor technologies must be reliable, valid, and usable. Considering the variety of the existing sensors not all of them are suitable to be integrated in wearables. The application and development of wearables has to consider the characteristics of the physical training process to improve the effectiveness and efficiency as training tools. During physical training, it is essential to elicit individual optimal strain to evoke the desired adjustments to training. One important goal is to neither overstrain nor under challenge the user. Many wearables use heart rate as indicator for this individual strain. However, due to a variety of internal and external influencing factors, heart rate kinetics are highly variable making it difficult to control the stress eliciting individually optimal strain. For optimal training control it is essential to model and predict individual responses and adapt the external stress if necessary. Basis for this modeling is the valid and reliable recording of these individual responses. Depending on the heart rate kinetics and the obtained physiological data, different models and techniques are available that can be used for strain or training control. Aim of this review is to give an overview of measurement, prediction, and control of individual heart rate responses. Therefore, available sensor technologies measuring the individual heart rate responses are analyzed and approaches to model and predict these individual responses discussed. Additionally, the feasibility for wearables is analyzed.
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.
Surrogate-assistance approaches have long been used in computationally expensive domains to improve the data-efficiency of optimization algorithms. Neuroevolution, however, has so far resisted the application of these techniques because it requires the surrogate model to make fitness predictions based on variable topologies, instead of a vector of parameters. Our main insight is that we can sidestep this problem by using kernel-based surrogate models, which require only the definition of a distance measure between individuals. Our second insight is that the well-established Neuroevolution of Augmenting Topologies (NEAT) algorithm provides a computationally efficient distance measure between dissimilar networks in the form of "compatibility distance", initially designed to maintain topological diversity. Combining these two ideas, we introduce a surrogate-assisted neuroevolution algorithm that combines NEAT and a surrogate model built using a compatibility distance kernel. We demonstrate the data-efficiency of this new algorithm on the low dimensional cart-pole swing-up problem, as well as the higher dimensional half-cheetah running task. In both tasks the surrogate-assisted variant achieves the same or better results with several times fewer function evaluations as the original NEAT.
Change - shaping reality
(2019)