Institut für Informatik und Computational Science
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- Doctoral Thesis (206) (remove)
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With the rise of electronic integration between organizations, the need for a precise specification of interaction behavior increases. Information systems, replacing interaction previously carried out by humans via phone, faxes and emails, require a precise specification for handling all possible situations. Such interaction behavior is described in process choreographies. Choreographies enumerate the roles involved, the allowed interactions, the message contents and the behavioral dependencies between interactions. Choreographies serve as interaction contract and are the starting point for adapting existing business processes and systems or for implementing new software components. As a thorough analysis and comparison of choreography modeling languages is missing in the literature, this thesis introduces a requirements framework for choreography languages and uses it for comparing current choreography languages. Language proposals for overcoming the limitations are given for choreography modeling on the conceptual and on the technical level. Using an interconnection modeling style, behavioral dependencies are defined on a per-role basis and different roles are interconnected using message flow. This thesis reveals a number of modeling "anti-patterns" for interconnection modeling, motivating further investigations on choreography languages following the interaction modeling style. Here, interactions are seen as atomic building blocks and the behavioral dependencies between them are defined globally. Two novel language proposals are put forward for this modeling style which have already influenced industrial standardization initiatives. While avoiding many of the pitfalls of interconnection modeling, new anomalies can arise in interaction models. A choreography might not be realizable, i.e. there does not exist a set of interacting roles that collectively realize the specified behavior. This thesis investigates different dimensions of realizability.
One of the main problems in machine learning is to train a predictive model from training data and to make predictions on test data. Most predictive models are constructed under the assumption that the training data is governed by the exact same distribution which the model will later be exposed to. In practice, control over the data collection process is often imperfect. A typical scenario is when labels are collected by questionnaires and one does not have access to the test population. For example, parts of the test population are underrepresented in the survey, out of reach, or do not return the questionnaire. In many applications training data from the test distribution are scarce because they are difficult to obtain or very expensive. Data from auxiliary sources drawn from similar distributions are often cheaply available. This thesis centers around learning under differing training and test distributions and covers several problem settings with different assumptions on the relationship between training and test distributions-including multi-task learning and learning under covariate shift and sample selection bias. Several new models are derived that directly characterize the divergence between training and test distributions, without the intermediate step of estimating training and test distributions separately. The integral part of these models are rescaling weights that match the rescaled or resampled training distribution to the test distribution. Integrated models are studied where only one optimization problem needs to be solved for learning under differing distributions. With a two-step approximation to the integrated models almost any supervised learning algorithm can be adopted to biased training data. In case studies on spam filtering, HIV therapy screening, targeted advertising, and other applications the performance of the new models is compared to state-of-the-art reference methods.
Although educational content in electronic form is increasing dramatically, its usage in an educational environment is poor, mainly due to the fact that there is too much of (unreliable) redundant, and not relevant information. Finding appropriate answers is a rather difficult task being reliant on the user filtering of the pertinent information from the noise. Turning knowledge bases like the online tele-TASK archive into useful educational resources requires identifying correct, reliable, and "machine-understandable" information, as well as developing simple but efficient search tools with the ability to reason over this information. Our vision is to create an E-Librarian Service, which is able to retrieve multimedia resources from a knowledge base in a more efficient way than by browsing through an index, or by using a simple keyword search. In our E-Librarian Service, the user can enter his question in a very simple and human way; in natural language (NL). Our premise is that more pertinent results would be retrieved if the search engine understood the sense of the user's query. The returned results are then logical consequences of an inference rather than of keyword matchings. Our E-Librarian Service does not return the answer to the user's question, but it retrieves the most pertinent document(s), in which the user finds the answer to his/her question. Among all the documents that have some common information with the user query, our E-Librarian Service identifies the most pertinent match(es), keeping in mind that the user expects an exhaustive answer while preferring a concise answer with only little or no information overhead. Also, our E-Librarian Service always proposes a solution to the user, even if the system concludes that there is no exhaustive answer. Our E-Librarian Service was implemented prototypically in three different educational tools. A first prototype is CHESt (Computer History Expert System); it has a knowledge base with 300 multimedia clips that cover the main events in computer history. A second prototype is MatES (Mathematics Expert System); it has a knowledge base with 115 clips that cover the topic of fractions in mathematics for secondary school w.r.t. the official school programme. All clips were recorded mainly by pupils. The third and most advanced prototype is the "Lecture Butler's E-Librarain Service"; it has a Web service interface to respect a service oriented architecture (SOA), and was developed in the context of the Web-University project at the Hasso-Plattner-Institute (HPI). Two major experiments in an educational environment - at the Lycée Technique Esch/Alzette in Luxembourg - were made to test the pertinence and reliability of our E-Librarian Service as a complement to traditional courses. The first experiment (in 2005) was made with CHESt in different classes, and covered a single lesson. The second experiment (in 2006) covered a period of 6 weeks of intensive use of MatES in one class. There was no classical mathematics lesson where the teacher gave explanations, but the students had to learn in an autonomous and exploratory way. They had to ask questions to the E-Librarian Service just the way they would if there was a human teacher.
Intuitive Modelle der Informatik sind gedankliche Vorstellungen über informatische Konzepte, die mit subjektiver Gewissheit verbunden sind. Menschen verwenden sie, wenn sie die Arbeitsweise von Computerprogrammen nachvollziehen oder anderen erklären, die logische Korrektheit eines Programms prüfen oder in einem kreativen Prozess selbst Programme entwickeln. Intuitive Modelle können auf verschiedene Weise repräsentiert und kommuniziert werden, etwa verbal-abstrakt, durch ablauf- oder strukturorientierte Abbildungen und Filme oder konkrete Beispiele. Diskutiert werden in dieser Arbeit grundlegende intuitive Modelle für folgende inhaltliche Aspekte einer Programmausführung: Allokation von Aktivität bei einer Programmausführung, Benennung von Entitäten, Daten, Funktionen, Verarbeitung, Kontrollstrukturen zur Steuerung von Programmläufen, Rekursion, Klassen und Objekte. Mit Hilfe eines Systems von Online-Spielen, der Python Visual Sandbox, werden die psychische Realität verschiedener intuitiver Modelle bei Programmieranfängern nachgewiesen und fehlerhafte Anwendungen (Fehlvorstellungen) identifiziert.
This work introduces novel internal and external memory algorithms for computing voxel skeletons of massive voxel objects with complex network-like architecture and for converting these voxel skeletons to piecewise linear geometry, that is triangle meshes and piecewise straight lines. The presented techniques help to tackle the challenge of visualizing and analyzing 3d images of increasing size and complexity, which are becoming more and more important in, for example, biological and medical research. Section 2.3.1 contributes to the theoretical foundations of thinning algorithms with a discussion of homotopic thinning in the grid cell model. The grid cell model explicitly represents a cell complex built of faces, edges, and vertices shared between voxels. A characterization of pairs of cells to be deleted is much simpler than characterizations of simple voxels were before. The grid cell model resolves topologically unclear voxel configurations at junctions and locked voxel configurations causing, for example, interior voxels in sets of non-simple voxels. A general conclusion is that the grid cell model is superior to indecomposable voxels for algorithms that need detailed control of topology. Section 2.3.2 introduces a noise-insensitive measure based on the geodesic distance along the boundary to compute two-dimensional skeletons. The measure is able to retain thin object structures if they are geometrically important while ignoring noise on the object's boundary. This combination of properties is not known of other measures. The measure is also used to guide erosion in a thinning process from the boundary towards lines centered within plate-like structures. Geodesic distance based quantities seem to be well suited to robustly identify one- and two-dimensional skeletons. Chapter 6 applies the method to visualization of bone micro-architecture. Chapter 3 describes a novel geometry generation scheme for representing voxel skeletons, which retracts voxel skeletons to piecewise linear geometry per dual cube. The generated triangle meshes and graphs provide a link to geometry processing and efficient rendering of voxel skeletons. The scheme creates non-closed surfaces with boundaries, which contain fewer triangles than a representation of voxel skeletons using closed surfaces like small cubes or iso-surfaces. A conclusion is that thinking specifically about voxel skeleton configurations instead of generic voxel configurations helps to deal with the topological implications. The geometry generation is one foundation of the applications presented in Chapter 6. Chapter 5 presents a novel external memory algorithm for distance ordered homotopic thinning. The presented method extends known algorithms for computing chamfer distance transformations and thinning to execute I/O-efficiently when input is larger than the available main memory. The applied block-wise decomposition schemes are quite simple. Yet it was necessary to carefully analyze effects of block boundaries to devise globally correct external memory variants of known algorithms. In general, doing so is superior to naive block-wise processing ignoring boundary effects. Chapter 6 applies the algorithms in a novel method based on confocal microscopy for quantitative study of micro-vascular networks in the field of microcirculation.
An increasing number of applications requires user interfaces that facilitate the handling of large geodata sets. Using virtual 3D city models, complex geospatial information can be communicated visually in an intuitive way. Therefore, real-time visualization of virtual 3D city models represents a key functionality for interactive exploration, presentation, analysis, and manipulation of geospatial data. This thesis concentrates on the development and implementation of concepts and techniques for real-time city model visualization. It discusses rendering algorithms as well as complementary modeling concepts and interaction techniques. Particularly, the work introduces a new real-time rendering technique to handle city models of high complexity concerning texture size and number of textures. Such models are difficult to handle by current technology, primarily due to two problems: - Limited texture memory: The amount of simultaneously usable texture data is limited by the memory of the graphics hardware. - Limited number of textures: Using several thousand different textures simultaneously causes significant performance problems due to texture switch operations during rendering. The multiresolution texture atlases approach, introduced in this thesis, overcomes both problems. During rendering, it permanently maintains a small set of textures that are sufficient for the current view and the screen resolution available. The efficiency of multiresolution texture atlases is evaluated in performance tests. To summarize, the results demonstrate that the following goals have been achieved: - Real-time rendering becomes possible for 3D scenes whose amount of texture data exceeds the main memory capacity. - Overhead due to texture switches is kept permanently low, so that the number of different textures has no significant effect on the rendering frame rate. Furthermore, this thesis introduces two new approaches for real-time city model visualization that use textures as core visualization elements: - An approach for visualization of thematic information. - An approach for illustrative visualization of 3D city models. Both techniques demonstrate that multiresolution texture atlases provide a basic functionality for the development of new applications and systems in the domain of city model visualization.
The innovation of information techniques has changed many aspects of our life. In health care field, we can obtain, manage and communicate high-quality large volumetric image data by computer integrated devices, to support medical care. In this dissertation I propose several promising methods that could assist physicians in processing, observing and communicating the image data. They are included in my three research aspects: telemedicine integration, medical image visualization and image segmentation. And these methods are also demonstrated by the demo software that I developed. One of my research point focuses on medical information storage standard in telemedicine, for example DICOM, which is the predominant standard for the storage and communication of medical images. I propose a novel 3D image data storage method, which was lacking in current DICOM standard. I also created a mechanism to make use of the non-standard or private DICOM files. In this thesis I present several rendering techniques on medical image visualization to offer different display manners, both 2D and 3D, for example, cut through data volume in arbitrary degree, rendering the surface shell of the data, and rendering the semi-transparent volume of the data. A hybrid segmentation approach, designed for semi-automated segmentation of radiological image, such as CT, MRI, etc, is proposed in this thesis to get the organ or interested area from the image. This approach takes advantage of the region-based method and boundary-based methods. Three steps compose the hybrid approach: the first step gets coarse segmentation by fuzzy affinity and generates homogeneity operator; the second step divides the image by Voronoi Diagram and reclassifies the regions by the operator to refine segmentation from the previous step; the third step handles vague boundary by level set model. Topics for future research are mentioned in the end, including new supplement for DICOM standard for segmentation information storage, visualization of multimodal image information, and improvement of the segmentation approach to higher dimension.
Answer Set Programming (ASP) emerged in the late 1990s as a new logic programming paradigm, having its roots in nonmonotonic reasoning, deductive databases, and logic programming with negation as failure. The basic idea of ASP is to represent a computational problem as a logic program whose answer sets correspond to solutions, and then to use an answer set solver for finding answer sets of the program. ASP is particularly suited for solving NP-complete search problems. Among these, we find applications to product configuration, diagnosis, and graph-theoretical problems, e.g. finding Hamiltonian cycles. On different lines of ASP research, many extensions of the basic formalism have been proposed. The most intensively studied one is the modelling of preferences in ASP. They constitute a natural and effective way of selecting preferred solutions among a plethora of solutions for a problem. For example, preferences have been successfully used for timetabling, auctioning, and product configuration. In this thesis, we concentrate on preferences within answer set programming. Among several formalisms and semantics for preference handling in ASP, we concentrate on ordered logic programs with the underlying D-, W-, and B-semantics. In this setting, preferences are defined among rules of a logic program. They select preferred answer sets among (standard) answer sets of the underlying logic program. Up to now, those preferred answer sets have been computed either via a compilation method or by meta-interpretation. Hence, the question comes up, whether and how preferences can be integrated into an existing ASP solver. To solve this question, we develop an operational graph-based framework for the computation of answer sets of logic programs. Then, we integrate preferences into this operational approach. We empirically observe that our integrative approach performs in most cases better than the compilation method or meta-interpretation. Another research issue in ASP are optimization methods that remove redundancies, as also found in database query optimizers. For these purposes, the rather recently suggested notion of strong equivalence for ASP can be used. If a program is strongly equivalent to a subprogram of itself, then one can always use the subprogram instead of the original program, a technique which serves as an effective optimization method. Up to now, strong equivalence has not been considered for logic programs with preferences. In this thesis, we tackle this issue and generalize the notion of strong equivalence to ordered logic programs. We give necessary and sufficient conditions for the strong equivalence of two ordered logic programs. Furthermore, we provide program transformations for ordered logic programs and show in how far preferences can be simplified. Finally, we present two new applications for preferences within answer set programming. First, we define new procedures for group decision making, which we apply to the problem of scheduling a group meeting. As a second new application, we reconstruct a linguistic problem appearing in German dialects within ASP. Regarding linguistic studies, there is an ongoing debate about how unique the rule systems of language are in human cognition. The reconstruction of grammatical regularities with tools from computer science has consequences for this debate: if grammars can be modelled this way, then they share core properties with other non-linguistic rule systems.
Advances in biotechnologies rapidly increase the number of molecules of a cell which can be observed simultaneously. This includes expression levels of thousands or ten-thousands of genes as well as concentration levels of metabolites or proteins. Such Profile data, observed at different times or at different experimental conditions (e.g., heat or dry stress), show how the biological experiment is reflected on the molecular level. This information is helpful to understand the molecular behaviour and to identify molecules or combination of molecules that characterise specific biological condition (e.g., disease). This work shows the potentials of component extraction algorithms to identify the major factors which influenced the observed data. This can be the expected experimental factors such as the time or temperature as well as unexpected factors such as technical artefacts or even unknown biological behaviour. Extracting components means to reduce the very high-dimensional data to a small set of new variables termed components. Each component is a combination of all original variables. The classical approach for that purpose is the principal component analysis (PCA). It is shown that, in contrast to PCA which maximises the variance only, modern approaches such as independent component analysis (ICA) are more suitable for analysing molecular data. The condition of independence between components of ICA fits more naturally our assumption of individual (independent) factors which influence the data. This higher potential of ICA is demonstrated by a crossing experiment of the model plant Arabidopsis thaliana (Thale Cress). The experimental factors could be well identified and, in addition, ICA could even detect a technical artefact. However, in continuously observations such as in time experiments, the data show, in general, a nonlinear distribution. To analyse such nonlinear data, a nonlinear extension of PCA is used. This nonlinear PCA (NLPCA) is based on a neural network algorithm. The algorithm is adapted to be applicable to incomplete molecular data sets. Thus, it provides also the ability to estimate the missing data. The potential of nonlinear PCA to identify nonlinear factors is demonstrated by a cold stress experiment of Arabidopsis thaliana. The results of component analysis can be used to build a molecular network model. Since it includes functional dependencies it is termed functional network. Applied to the cold stress data, it is shown that functional networks are appropriate to visualise biological processes and thereby reveals molecular dynamics.
This thesis discusses challenges in IT security education, points out a gap between e-learning and practical education, and presents a work to fill the gap. E-learning is a flexible and personalized alternative to traditional education. Nonetheless, existing e-learning systems for IT security education have difficulties in delivering hands-on experience because of the lack of proximity. Laboratory environments and practical exercises are indispensable instruction tools to IT security education, but security education in conventional computer laboratories poses particular problems such as immobility as well as high creation and maintenance costs. Hence, there is a need to effectively transform security laboratories and practical exercises into e-learning forms. In this thesis, we introduce the Tele-Lab IT-Security architecture that allows students not only to learn IT security principles, but also to gain hands-on security experience by exercises in an online laboratory environment. In this architecture, virtual machines are used to provide safe user work environments instead of real computers. Thus, traditional laboratory environments can be cloned onto the Internet by software, which increases accessibility to laboratory resources and greatly reduces investment and maintenance costs. Under the Tele-Lab IT-Security framework, a set of technical solutions is also proposed to provide effective functionalities, reliability, security, and performance. The virtual machines with appropriate resource allocation, software installation, and system configurations are used to build lightweight security laboratories on a hosting computer. Reliability and availability of laboratory platforms are covered by a virtual machine management framework. This management framework provides necessary monitoring and administration services to detect and recover critical failures of virtual machines at run time. Considering the risk that virtual machines can be misused for compromising production networks, we present a security management solution to prevent the misuse of laboratory resources by security isolation at the system and network levels. This work is an attempt to bridge the gap between e-learning/tele-teaching and practical IT security education. It is not to substitute conventional teaching in laboratories but to add practical features to e-learning. This thesis demonstrates the possibility to implement hands-on security laboratories on the Internet reliably, securely, and economically.