Refine
Has Fulltext
- yes (378)
Year of publication
Document Type
- Doctoral Thesis (165)
- Journal article (147)
- Working Paper (40)
- Conference Proceeding (11)
- Master Thesis (6)
- Report (5)
- Bachelor Thesis (2)
- Book (1)
- Study Thesis (term paper) (1)
Language
- English (341)
- German (36)
- Multiple languages (1)
Keywords
- Leistungsbewertung (29)
- virtual reality (19)
- Datennetz (14)
- Quality of Experience (12)
- Netzwerk (10)
- Robotik (10)
- machine learning (9)
- Modellierung (8)
- Simulation (8)
- Autonomer Roboter (7)
Institute
- Institut für Informatik (378) (remove)
Schriftenreihe
Sonstige beteiligte Institutionen
- Cologne Game Lab (3)
- Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Raumfahrtsysteme (2)
- Open University of the Netherlands (2)
- Siemens AG (2)
- Zentrum für Telematik e.V. (2)
- Airbus Defence and Space GmbH (1)
- Beuth Hochschule für Technik Berlin (1)
- Birmingham City University (1)
- California Institute of Technology (1)
- DLR (1)
This paper demonstrates an innovative and simple solution for obstacle detection and collision avoidance of unmanned aerial vehicles (UAVs) optimized for and evaluated with quadrotors. The sensors exploited in this paper are low-cost ultrasonic and infrared range finders, which are much cheaper though noisier than more expensive sensors such as laser scanners. This needs to be taken into consideration for the design, implementation, and parametrization of the signal processing and control algorithm for such a system, which is the topic of this paper. For improved data fusion, inertial and optical flow sensors are used as a distance derivative for reference. As a result, a UAV is capable of distance controlled collision avoidance, which is more complex and powerful than comparable simple solutions. At the same time, the solution remains simple with a low computational burden. Thus, memory and time-consuming simultaneous localization and mapping is not required for collision avoidance.
Background
Information extraction techniques that get structured representations out of unstructured data make a large amount of clinically relevant information about patients accessible for semantic applications. These methods typically rely on standardized terminologies that guide this process. Many languages and clinical domains, however, lack appropriate resources and tools, as well as evaluations of their applications, especially if detailed conceptualizations of the domain are required. For instance, German transthoracic echocardiography reports have not been targeted sufficiently before, despite of their importance for clinical trials. This work therefore aimed at development and evaluation of an information extraction component with a fine-grained terminology that enables to recognize almost all relevant information stated in German transthoracic echocardiography reports at the University Hospital of Würzburg.
Methods
A domain expert validated and iteratively refined an automatically inferred base terminology. The terminology was used by an ontology-driven information extraction system that outputs attribute value pairs. The final component has been mapped to the central elements of a standardized terminology, and it has been evaluated according to documents with different layouts.
Results
The final system achieved state-of-the-art precision (micro average.996) and recall (micro average.961) on 100 test documents that represent more than 90 % of all reports. In particular, principal aspects as defined in a standardized external terminology were recognized with f 1=.989 (micro average) and f 1=.963 (macro average). As a result of keyword matching and restraint concept extraction, the system obtained high precision also on unstructured or exceptionally short documents, and documents with uncommon layout.
Conclusions
The developed terminology and the proposed information extraction system allow to extract fine-grained information from German semi-structured transthoracic echocardiography reports with very high precision and high recall on the majority of documents at the University Hospital of Würzburg. Extracted results populate a clinical data warehouse which supports clinical research.
In unserem Alltag kommen wir heute ständig mit Systemen der Informations- und Kommunikationstechnik in Kontakt. Diese bestehen häufig aus mehreren interagierenden und kommunizierenden Komponenten, wie zum Beispiel nebenläufige Software zur effizienten Nutzung von Mehrkernprozessoren oder Sensornetzwerke. Systeme, die aus mehreren interagierenden und kommunizierenden Komponenten bestehen sind häufig komplex und dadurch sehr fehleranfällig. Daher ist es wichtig zuverlässige Methoden, die helfen die korrekte Funktionsweise solcher Systeme sicherzustellen, zu besitzen.
Im Rahmen dieser Doktorarbeit wurden neue Methoden zur Verbesserung der Verifizierbarkeit von asynchronen nebenläufigen Systemen durch Anwendung der symbolischen Modellprüfung mit binären Entscheidungsdiagrammen (BDDs) entwickelt. Ein asynchrones nebenläufiges System besteht aus mehreren Komponenten, von denen zu einem Zeitpunkt jeweils nur eine Komponente Transitionen ausführen kann. Die Modellprüfung ist eine Technik zur formalen Verifikation, bei der die Gültigkeit einer Menge von zu prüfenden Eigenschaften für eine gegebene Systembeschreibung automatisch durch Softwarewerkzeuge, die Modellprüfer genannt werden, entschieden wird. Das Hauptproblem der symbolischen Modellprüfung ist das Problem der Zustandsraumexplosion und es sind weitere Verbesserungen notwendig, um die symbolische Modellprüfung häufiger erfolgreich durchführen zu können.
Bei der BDD-basierten symbolischen Modellprüfung werden Mengen von Systemzuständen und Mengen von Transitionen jeweils durch BDDs repräsentiert. Zentrale Operationen bei ihr sind die Berechnung von Nachfolger- und Vorgängerzuständen von gegebenen Zustandsmengen, welche Bildberechnungen genannt werden. Um die Gültigkeit von Eigenschaften für eine gegebene Systembeschreibung zu überprüfen, werden wiederholt Bildberechnungen durchgeführt. Daher ist ihre effiziente Berechnung entscheidend für eine geringe Laufzeit und einen niedrigen Speicherbedarf der Modellprüfung. In einer Bildberechnung werden ein BDD zur Repräsentation einer Menge von Transitionen und ein BDD für eine Menge von Zuständen kombiniert, um eine Menge von Nachfolger- oder Vorgängerzuständen zu berechnen. Oft ist auch die Größe von BDDs zur Repräsentation der Transitionsrelation von Systemen entscheidend für die erfolgreiche Anwendbarkeit der Modellprüfung.
In der vorliegenden Arbeit werden neue Datenstrukturen zur Repräsentation der Transitionsrelation von asynchronen nebenläufigen Systemen bei der BDD-basierten symbolischen Modellprüfung vorgestellt. Zusätzlich werden neue Algorithmen zur Durchführung von Bildberechnungen präsentiert. Beides kann zu großen Reduktionen der Laufzeit und des Speicherbedarfs führen. Asynchrone nebenläufige Systeme besitzen häufig Symmetrien. Eine Technik zur Reduktion des Problems der Zustandsraumexplosion ist die Symmetriereduktion. In dieser Arbeit wird ebenfalls ein neuer effizienter Algorithmus zur Symmetriereduktion bei der symbolischen Modellprüfung mit BDDs aufgeführt.
Diese Forschungsarbeit beschreibt alle Aspekte der Entwicklung eines neuartigen, autonomen Quadrokopters, genannt AQopterI8, zur Innenraumerkundung. Dank seiner einzigartigen modularen Komposition von Soft- und Hardware ist der AQopterI8 in der Lage auch unter widrigen Umweltbedingungen autonom zu agieren und unterschiedliche Anforderungen zu erfüllen. Die Arbeit behandelt sowohl theoretische Fragestellungen unter dem Schwerpunkt der einfachen Realisierbarkeit als auch Aspekte der praktischen Umsetzung, womit sie Themen aus den Gebieten Signalverarbeitung, Regelungstechnik, Elektrotechnik, Modellbau, Robotik und Informatik behandelt. Kernaspekt der Arbeit sind Lösungen zur Autonomie, Hinderniserkennung und Kollisionsvermeidung.
Das System verwendet IMUs (Inertial Measurement Unit, inertiale Messeinheit) zur Orientierungsbestimmung und Lageregelung und kann unterschiedliche Sensormodelle automatisch detektieren. Ultraschall-, Infrarot- und Luftdrucksensoren in Kombination mit der IMU werden zur Höhenbestimmung und Höhenregelung eingesetzt. Darüber hinaus werden bildgebende Sensoren (Videokamera, PMD), ein Laser-Scanner sowie Ultraschall- und Infrarotsensoren zur Hindernis-erkennung und Kollisionsvermeidung (Abstandsregelung) verwendet. Mit Hilfe optischer Sensoren kann der Quadrokopter basierend auf Prinzipien der Bildverarbeitung Objekte erkennen sowie seine Position im Raum bestimmen. Die genannten Subsysteme im Zusammenspiel erlauben es dem AQopterI8 ein Objekt in einem unbekannten Raum autonom, d.h. völlig ohne jedes externe Hilfsmittel, zu suchen und dessen Position auf einer Karte anzugeben. Das System kann Kollisionen mit Wänden vermeiden und Personen autonom ausweichen. Dabei verwendet der AQopterI8 Hardware, die deutlich günstiger und Dank der Redundanz gleichzeitig erheblich verlässlicher ist als vergleichbare Mono-Sensor-Systeme (z.B. Kamera- oder Laser-Scanner-basierte Systeme).
Neben dem Zweck als Forschungsarbeit (Dissertation) dient die vorliegende Arbeit auch als Dokumentation des Gesamtprojektes AQopterI8, dessen Ziel die Erforschung und Entwicklung neuartiger autonomer Quadrokopter zur Innenraumerkundung ist. Darüber hinaus wird das System zum Zweck der Lehre und Forschung an der Universität Würzburg, der Fachhochschule Brandenburg sowie der Fachhochschule Würzburg-Schweinfurt eingesetzt. Darunter fallen Laborübungen und 31 vom Autor dieser Arbeit betreute studentische Bachelor- und Masterarbeiten.
Das Projekt wurde ausgezeichnet vom Universitätsbund und der IHK Würzburg-Mainfranken mit dem Universitätsförderpreis der Mainfränkischen Wirtschaft und wird gefördert unter den Bezeichnungen „Lebensretter mit Propellern“ und „Rettungshelfer mit Propellern“. Außerdem wurde die Arbeit für den Gips-Schüle-Preis nominiert. Absicht dieser Projekte ist die Entwicklung einer Rettungsdrohne. In den Medien Zeitung, Fernsehen und Radio wurde über den AQopterI8 schon mehrfach berichtet.
Die Evaluierung zeigt, dass das System in der Lage ist, voll autonom in Innenräumen zu fliegen, Kollisionen mit Objekten zu vermeiden (Abstandsregelung), eine Suche durchzuführen, Objekte zu erkennen, zu lokalisieren und zu zählen. Da nur wenige Forschungsarbeiten diesen Grad an Autonomie erreichen, gleichzeitig aber keine Arbeit die gestellten Anforderungen vergleichbar erfüllt, erweitert die Arbeit den Stand der Forschung.
Within this thesis a new philosophy in monitoring spacecrafts is presented: the
unification of the various kinds of monitoring techniques used during the
different lifecylce phases of a spacecraft.
The challenging requirements being set for this monitoring framework are:
- "separation of concerns" as a design principle (dividing the steps of logging
from registered sources, sending to connected sinks and displaying of
information),
- usage during all mission phases,
- usage by all actors (EGSE engineers, groundstation operators, etc.),
- configurable at runtime, especially regarding the level of detail of logging
information, and
- very low resource consumption.
First a prototype of the monitoring framework was developed as a support library
for the real-time operating system
RODOS. This prototype was tested on dedicated hardware platforms relevant for
space, and also on a satellite demonstrator used for educational purposes.
As a second step, the results and lessons learned from the development and usage
of this prototype were transfered to a real space mission: the first satellite
of the DLR compact satellite series - a space based platform for DLR's own
research activities. Within this project, the software of the avionic subsystem
was supplemented by a powerful logging component, which enhances the traditional
housekeeping capabilities and offers extensive filtering and debugging
techniques for monitoring and FDIR needs. This logging component is the major
part of the flight version of the monitoring framework. It is completed by
counterparts running on the development computers and as well as the EGSE
hardware in the integration room, making it most valuable already in the
earliest stages of traditional spacecraft development.
Future plans in terms of adding support from the groundstation as well will lead
to a seamless integration of the monitoring framework not only into to the
spacecraft itself, but into the whole space system.
A simple test setup has been developed at Institute of Aerospace Information Technology, University of Würzburg, Germany to realize basic functionalities for formation flight of quadrocopters. The test environment is planned to be utilized for developing and validating the algorithms for formation flying capability in real environment as well as for education purpose. An already existing test bed for single quadrocopter was extended with necessary inter-communication and distributed control mechanism to test the algorithms for formation flights in 2 degrees of freedom (roll / pitch). This study encompasses the domain of communication, control engineering and embedded systems programming. Bluetooth protocol has been used for inter-communication between two quadrocopters. A simple approach of PID control in combination with Kalman filter has been exploited. MATLAB Instrument Control Toolbox has been used for data display, plotting and analysis. Plots can be drawn in real-time and received information can also be stored in the form of files for later use and analysis. The test setup has been developed indigenously and at considerably low cost. Emphasis has been placed on simplicity to facilitate students learning process. Several lessons have been learnt during the course of development of this setup. Proposed setup is quite flexible that can be modified as per changing requirements.
The general map-labeling problem is as follows: given a set of geometric objects to be labeled, or features, in the plane, and for each feature a set of label positions, maximize the number of placed labels such that there is at most one label per feature and no two labels overlap. There are three types of features in a map: point, line, and area features. Unfortunately, one cannot expect to find efficient algorithms that solve the labeling problem optimally.
Interactive maps are digital maps that only show a small part of the entire map whereas the user can manipulate the shown part, the view, by continuously panning, zooming, rotating, and tilting (that is, changing the perspective between a top and a bird view). An example for the application of interactive maps is in navigational devices. Interactive maps are challenging in that the labeling must be updated whenever labels leave the view and, while zooming, the label size must be constant on the screen (which either makes space for further labels or makes labels overlap when zooming in or out, respectively). These updates must be computed in real time, that is, the computation must be so fast that the user does not notice that we spend time on the computation. Additionally, labels must not jump or flicker, that is, labels must not suddenly change their positions or, while zooming out, a vanished label must not appear again.
In this thesis, we present efficient algorithms that dynamically label point and line features in interactive maps. We try to label as many features as possible while we prohibit labels that overlap, jump, and flicker. We have implemented all our approaches and tested them on real-world data. We conclude that our algorithms are indeed real-time capable.
At the center of the Internet’s protocol stack stands the Internet Protocol (IP) as a common denominator that enables all communication. To make routing efficient, resilient, and scalable, several aspects must be considered. Care must be taken that traffic is well balanced to make efficient use of the existing network resources, both in failure free operation and in failure scenarios.
Finding the optimal routing in a network is an NP-complete problem. Therefore, routing optimization is usually performed using heuristics. This dissertation shows that a routing optimized with one objective function is often not good when looking at other objective functions. It can even be worse than unoptimized routing with respect to that objective function. After looking at failure-free routing and traffic distribution in different failure scenarios, the analysis is extended to include the loop-free alternate (LFA) IP fast reroute mechanism. Different application scenarios of LFAs are examined and a special focus is set on the fact that LFAs usually cannot protect all traffic in a network even against single link failures. Thus, the routing optimization for LFAs is targeted on both link utilization and failure coverage. Finally, the pre-congestion notification mechanism PCN for network admission control and overload protection is analyzed and optimized. Different design options for implementing the protocol are compared, before algorithms are developed for the calculation and optimization of protocol parameters and PCN-based routing.
The second part of the thesis tackles a routing problem that can only be resolved on a global scale. The scalability of the Internet is at risk since a major and intensifying growth of the interdomain routing tables has been observed. Several protocols and architectures are analyzed that can be used to make interdomain routing more scalable. The most promising approach is the locator/identifier (Loc/ID) split architecture which separates routing from host identification. This way, changes in connectivity, mobility of end hosts, or traffic-engineering activities are hidden from the routing in the core of the Internet and the routing tables can be kept much smaller. All of the currently proposed Loc/ID split approaches have their downsides. In particular, the fact that most architectures use the ID for routing outside the Internet’s core is a poor design, which inhibits many of the possible features of a new routing architecture. To better understand the problems and to provide a solution for a scalable routing design that implements a true Loc/ID split, the new GLI-Split protocol is developed in this thesis, which provides separation of global and local routing and uses an ID that is independent from any routing decisions.
Besides GLI-Split, several other new routing architectures implementing Loc/ID split have been proposed for the Internet. Most of them assume that a mapping system is queried for EID-to-RLOC mappings by an intermediate node at the border of an edge network. When the mapping system is queried by an intermediate node, packets are already on their way towards their destination, and therefore, the mapping system must be fast, scalable, secure, resilient, and should be able to relay packets without locators to nodes that can forward them to the correct destination. The dissertation develops a classification for all proposed mapping system architectures and shows their similarities and differences. Finally, the fast two-level mapping system FIRMS is developed. It includes security and resilience features as well as a relay service for initial packets of a flow when intermediate nodes encounter a cache miss for the EID-to-RLOC mapping.
Context-specific Consistencies in Information Extraction: Rule-based and Probabilistic Approaches
(2015)
Large amounts of communication, documentation as well as knowledge and information are stored in textual documents. Most often, these texts like webpages, books, tweets or reports are only available in an unstructured representation since they are created and interpreted by humans. In order to take advantage of this huge amount of concealed information and to include it in analytic processes, it needs to be transformed into a structured representation. Information extraction considers exactly this task. It tries to identify well-defined entities and relations in unstructured data and especially in textual documents.
Interesting entities are often consistently structured within a certain context, especially in semi-structured texts. However, their actual composition varies and is possibly inconsistent among different contexts. Information extraction models stay behind their potential and return inferior results if they do not consider these consistencies during processing. This work presents a selection of practical and novel approaches for exploiting these context-specific consistencies in information extraction tasks. The approaches direct their attention not only to one technique, but are based on handcrafted rules as well as probabilistic models.
A new rule-based system called UIMA Ruta has been developed in order to provide optimal conditions for rule engineers. This system consists of a compact rule language with a high expressiveness and strong development support. Both elements facilitate rapid development of information extraction applications and improve the general engineering experience, which reduces the necessary efforts and costs when specifying rules.
The advantages and applicability of UIMA Ruta for exploiting context-specific consistencies are illustrated in three case studies. They utilize different engineering approaches for including the consistencies in the information extraction task. Either the recall is increased by finding additional entities with similar composition, or the precision is improved by filtering inconsistent entities. Furthermore, another case study highlights how transformation-based approaches are able to correct preliminary entities using the knowledge about the occurring consistencies.
The approaches of this work based on machine learning rely on Conditional Random Fields, popular probabilistic graphical models for sequence labeling. They take advantage of a consistency model, which is automatically induced during processing the document. The approach based on stacked graphical models utilizes the learnt descriptions as feature functions that have a static meaning for the model, but change their actual function for each document. The other two models extend the graph structure with additional factors dependent on the learnt model of consistency. They include feature functions for consistent and inconsistent entities as well as for additional positions that fulfill the consistencies.
The presented approaches are evaluated in three real-world domains: segmentation of scientific references, template extraction in curricula vitae, and identification and categorization of sections in clinical discharge letters. They are able to achieve remarkable results and provide an error reduction of up to 30% compared to usually applied techniques.
Knowledge-based systems (KBS) face an ever-increasing interest in various disciplines and contexts. Yet, the former aim to construct the ’perfect intelligent software’ continuously shifts to user-centered, participative solutions. Such systems enable users to contribute their personal knowledge to the problem solving process for increased efficiency and an ameliorated user experience. More precisely, we define non-functional key requirements of participative KBS as: Transparency (encompassing KBS status mediation), configurability (user adaptability, degree of user control/exploration), quality of the KB and UI, and evolvability (enabling the KBS to grow mature with their users). Many of those requirements depend on the respective target users, thus calling for a more user-centered development. Often, also highly expertise domains are targeted — inducing highly complex KBs — which requires a more careful and considerate UI/interaction design. Still, current KBS engineering (KBSE) approaches mostly focus on knowledge acquisition (KA) This often leads to non-optimal, little reusable, and non/little evaluated KBS front-end solutions.
In this thesis we propose a more encompassing KBSE approach. Due to the strong mutual influences between KB and UI, we suggest a novel form of intertwined UI and KB development. We base the approach on three core components for encompassing KBSE:
(1) Extensible prototyping, a tailored form of evolutionary prototyping; this builds on mature UI prototypes and offers two extension steps for the anytime creation of core KBS prototypes (KB + core UI) and fully productive KBS (core KBS prototype + common framing functionality). (2) KBS UI patterns, that define reusable solutions for the core KBS UI/interaction; we provide a basic collection of such patterns in this work. (3) Suitable usability instruments for the assessment of the KBS artifacts. Therewith, we do not strive for ’yet another’ self-contained KBS engineering methodology. Rather, we motivate to extend existing approaches by the proposed key components. We demonstrate this based on an agile KBSE model.
For practical support, we introduce the tailored KBSE tool ProKEt. ProKEt offers a basic selection of KBS core UI patterns and corresponding configuration options out of the box; their further adaption/extension is possible on various levels of expertise. For practical usability support, ProKEt offers facilities for quantitative and qualitative data collection. ProKEt explicitly fosters the suggested, intertwined development of UI and KB. For seamlessly integrating KA activities, it provides extension points for two selected external KA tools: For KnowOF, a standard office based KA environment. And for KnowWE, a semantic wiki for collaborative KA. Therewith, ProKEt offers powerful support for encompassing, user-centered KBSE.
Finally, based on the approach and the tool, we also developed a novel KBS type: Clarification KBS as a mashup of consultation and justification KBS modules. Those denote a specifically suitable realization for participative KBS in highly expertise contexts and consequently require a specific design. In this thesis, apart from more common UI solutions, we particularly also introduce KBS UI patterns especially tailored towards Clarification KBS.