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After more than twenty years of research, the molecular events of apoptotic cell death can be succinctly stated; different pathways, activated by diverse signals, increase the activity of proteases called caspases that rapidly and irreversibly dismantle condemned cell by cleaving specific substrates. In this time the ideas that apoptosis protects us from tumourigenesis and that cancer chemotherapy works by inducing apoptosis also emerged. Currently, apoptosis research is shifting away from the intracellular events within the dying cell to focus on the effect of apoptotic cells on surrounding tissues. This is producing counterintuitive data showing that our understanding of the role of apoptosis in tumourigenesis and cancer therapy is too simple, with some interesting and provocative implications. Here, we will consider evidence supporting the idea that dying cells signal their presence to the surrounding tissue and, in doing so, elicit repair and regeneration that compensates for any loss of function caused by cell death. We will discuss evidence suggesting that cancer cell proliferation may be driven by inappropriate or corrupted tissue-repair programmes that are initiated by signals from apoptotic cells and show how this may dramatically modify how we view the role of apoptosis in both tumourigenesis and cancer therapy.
This article concerns with the accessibility of Business process modelling tools (BPMo tools) and business process modelling languages (BPMo languages). Therefore the reader will be introduced to business process management and the authors' motivation behind this inquiry. Afterwards, the paper will reflect problems when applying inaccessible BPMo tools. To illustrate these problems the authors distinguish between two different categories of issues and provide practical examples. Finally the article will present three approaches to improve the accessibility of BPMo tools and BPMo languages.
The work presented in this paper focuses on the comparison of well-known and new fault-diagnosis algorithms in the robot domain. The main challenge for fault diagnosis is to allow the robot to effectively cope not only with internal hardware and software faults but with external disturbances and errors from dynamic and complex environments as well. Based on a study of literature covering fault-diagnosis algorithms, I selected four of these methods based on both linear and non-linear models, analysed and implemented them in a mathematical robot-model, representing a four-wheels-OMNI robot. In experiments I tested the ability of the algorithms to detect and identify abnormal behaviour and to optimize the model parameters for the given training data. The final goal was to point out the strengths of each algorithm and to figure out which method would best suit the demands of fault diagnosis for a particular robot.
The ability of detecting people has become a crucial subtask, especially in robotic systems which aim an application in public or domestic environments. Robots already provide their services e.g. in real home improvement markets and guide people to a desired product. In such a scenario many robot internal tasks would benefit from the knowledge of knowing the number and positions of people in the vicinity. The navigation for example could treat them as dynamical moving objects and also predict their next motion directions in order to compute a much safer path. Or the robot could specifically approach customers and offer its services. This requires to detect a person or even a group of people in a reasonable range in front of the robot. Challenges of such a real-world task are e.g. changing lightning conditions, a dynamic environment and different people shapes. In this thesis a 3D people detection approach based on point cloud data provided by the Microsoft Kinect is implemented and integrated on mobile service robot. A Top-Down/Bottom-Up segmentation is applied to increase the systems flexibility and provided the capability to the detect people even if they are partially occluded. A feature set is proposed to detect people in various pose configurations and motions using a machine learning technique. The system can detect people up to a distance of 5 meters. The experimental evaluation compared different machine learning techniques and showed that standing people can be detected with a rate of 87.29% and sitting people with 74.94% using a Random Forest classifier. Certain objects caused several false detections. To elimante those a verification is proposed which further evaluates the persons shape in the 2D space. The detection component has been implemented as s sequential (frame rate of 10 Hz) and a parallel application (frame rate of 16 Hz). Finally, the component has been embedded into complete people search task which explorates the environment, find all people and approach each detected person.
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.
Förderpreise 2013
(2013)
Als Basis für Simulationen innerhalb virtueller Umgebungen werden meist unterliegende Semantiken benötigt. Im Fall von Verkehrssimulationen werden in der Regel definierte Verkehrsnetzwerke genutzt. Die Erstellung dieser Netzwerke wird meist per Hand durchgeführt, wodurch sie fehleranfällig ist und viel Zeit erfordert. Dieses Projekt wurde im Rahmen des AVeSi Projektes durchgeführt, in dem an der Entwicklung einer realistischen Verkehrssimulation für virtuelle Umgebung geforscht wird. Der im Projekt angestrebte Simulationsansatz basiert auf der Nutzung von zwei Komplexitätsebenen – einer mikroskopischen und einer mesoskopischen. Um einen Übergang zwischen den Simulationsebenen zu realisieren ist eine Verknüpfung der Verkehrsnetzwerke notwendig, was ebenfalls mit einem hohen Zeitaufwand verbunden ist. In diesem Bericht werden Modelle für Verkehrsnetzwerke beider Ebenen vorgestellt. Anschließend wird ein Ansatz beschrieben, der eine automatische Generierung und Verknüpfung von Verkehrsnetzwerken beider Modelle ermöglicht. Als Grundlage für die Generierung der Netzwerke dienen Daten im OpenDRIVE®-Format. Zur Evaluierung wurden wirklichkeitsgetreue OpenStreetMap-Daten, durch Verwendung einer Drittanbietersoftware, in OpenDRIVE®-Datensätze überführt. Es konnte nachgewiesen werden, dass es durch den Ansatz möglich ist, innerhalb weniger Minuten, große Verkehrsnetzwerke zu erzeugen, auf denen unmittelbar Simulationen ausgeführt werden können. Die Qualität der zur Evaluierung generierten Netzwerke reicht jedoch für Umgebungen, in denen ein hoher Realitätsgrad gefordert wird, nicht aus, was einen zusätzlichen Bearbeitungsschritt notwendig macht. Die Qualitätsprobleme konnten darauf zurückgeführt werden, dass der Detailgrad, der den Evaluierungsdaten zu Grunde liegenden OpenStreetMap-Daten, nicht hoch genug und der Überführungsprozess nicht ausreichend transparent ist.
Annual Report 2011 - 2012
(2013)
Molecular modeling is an important subdomain in the field of computational modeling, regarding both scientific and industrial applications. This is because computer simulations on a molecular level are a virtuous instrument to study the impact of microscopic on macroscopic phenomena. Accurate molecular models are indispensable for such simulations in order to predict physical target observables, like density, pressure, diffusion coefficients or energetic properties, quantitatively over a wide range of temperatures. Thereby, molecular interactions are described mathematically by force fields. The mathematical description includes parameters for both intramolecular and intermolecular interactions. While intramolecular force field parameters can be determined by quantum mechanics, the parameterization of the intermolecular part is often tedious. Recently, an empirical procedure, based on the minimization of a loss function between simulated and experimental physical properties, was published by the authors. Thereby, efficient gradient-based numerical optimization algorithms were used. However, empirical force field optimization is inhibited by the two following central issues appearing in molecular simulations: firstly, they are extremely time-consuming, even on modern and high-performance computer clusters, and secondly, simulation data is affected by statistical noise. The latter provokes the fact that an accurate computation of gradients or Hessians is nearly impossible close to a local or global minimum, mainly because the loss function is flat. Therefore, the question arises of whether to apply a derivative-free method approximating the loss function by an appropriate model function. In this paper, a new Sparse Grid-based Optimization Workflow (SpaGrOW) is presented, which accomplishes this task robustly and, at the same time, keeps the number of time-consuming simulations relatively small. This is achieved by an efficient sampling procedure for the approximation based on sparse grids, which is described in full detail: in order to counteract the fact that sparse grids are fully occupied on their boundaries, a mathematical transformation is applied to generate homogeneous Dirichlet boundary conditions. As the main drawback of sparse grids methods is the assumption that the function to be modeled exhibits certain smoothness properties, it has to be approximated by smooth functions first. Radial basis functions turned out to be very suitable to solve this task. The smoothing procedure and the subsequent interpolation on sparse grids are performed within sufficiently large compact trust regions of the parameter space. It is shown and explained how the combination of the three ingredients leads to a new efficient derivative-free algorithm, which has the additional advantage that it is capable of reducing the overall number of simulations by a factor of about two in comparison to gradient-based optimization methods. At the same time, the robustness with respect to statistical noise is maintained. This assertion is proven by both theoretical considerations and practical evaluations for molecular simulations on chemical example substances.
Realism and plausibility of computer controlled entities in entertainment software have been enhanced by adding both static personalities and dynamic emotions. Here a generic model is introduced which allows the transfer of findings from real-life personality studies to a computational model. This information is used for decision making. The introduction of dynamic event-based emotions enables adaptive behavior patterns. The advantages of this new model have been validated with a four-way crossroad in a traffic simulation. Driving agents using the introduced model enhanced by dynamics were compared to agents based on static personality profiles and simple rule-based behavior. It has been shown that adding an adaptive dynamic factor to agents improves perceivable plausibility and realism. It also supports coping with extreme situations in a fair and understandable way.