Institut für Informatik und Computational Science
Refine
Year of publication
- 2013 (58) (remove)
Document Type
- Article (37)
- Doctoral Thesis (15)
- Monograph/Edited Volume (2)
- Conference Proceeding (2)
- Master's Thesis (1)
- Preprint (1)
Keywords
- Theory (2)
- 3D Computer Grafik (1)
- 3D Computer Graphics (1)
- Active evaluation (1)
- Anisotroper Kuwahara Filter (1)
- Answer Set Programming (1)
- Answer set programming (1)
- Aspect-Oriented Programming (1)
- Aspektorientierte Programmierung (1)
- Berührungseingaben (1)
- Cloud Computing (1)
- Cloud computing (1)
- Cluster computing (1)
- Clusteranalyse (1)
- Continuous Testing (1)
- Continuous Versioning (1)
- Data Privacy (1)
- Datenschutz (1)
- Deal of the Day (1)
- Debugging (1)
- Design (1)
- Differenz von Gauss Filtern (1)
- E-Learning (1)
- Eingabegenauigkeit (1)
- Evolution (1)
- Experimentation (1)
- Explore-first Programming (1)
- Fault Localization (1)
- Flussgesteuerter Bilateraler Filter (1)
- Focus+Context Visualization (1)
- Fokus-&-Kontext Visualisierung (1)
- Green computing (1)
- Grounded theory (1)
- HCI (1)
- Human Factors (1)
- Image and video stylization (1)
- Information federation (1)
- Information retrieval (1)
- Information security (1)
- Interactive Rendering (1)
- Interaktives Rendering (1)
- Internet applications (1)
- Internetanwendungen (1)
- Java Security Framework (1)
- Landmark visibility (1)
- Learning Analytics (1)
- Leistungsfähigkeit (1)
- Life-Long Learning (1)
- Liguistisch (1)
- Loyalty (1)
- Mischmodelle (1)
- Mobilgeräte (1)
- Modell (1)
- Nicht-photorealistisches Rendering (1)
- Owner-Retained Access Control (ORAC) (1)
- Pedestrian navigation (1)
- Performance (1)
- Policy Languages (1)
- Policy Sprachen (1)
- Prototyping (1)
- Ranking (1)
- Relevanz (1)
- Scalability (1)
- Selektion (1)
- Semantic web (1)
- Service orientation (1)
- Skalierbarkeit (1)
- Structural equation modeling (1)
- Theorembeweisen (1)
- Unifikation (1)
- Usability testing (1)
- User-centred design (1)
- Vorhersage (1)
- Web of Data (1)
- anisotropic Kuwahara filter (1)
- answer set programming (1)
- artistic rendering (1)
- belief merging (1)
- belief revision (1)
- clustering (1)
- coherence-enhancing filtering (1)
- controlled vocabularies (1)
- course timetabling (1)
- difference of Gaussians (1)
- educational timetabling (1)
- entity alignment (1)
- flow-based bilateral filter (1)
- graph clustering (1)
- input accuracy (1)
- lebenslanges Lernen (1)
- linguistic (1)
- machine learning (1)
- map/reduce (1)
- maschinelles Lernen (1)
- metadata (1)
- mixture models (1)
- mobile devices (1)
- model (1)
- non-photorealistic rendering (1)
- nonphotorealistic rendering (NPR) (1)
- prediction (1)
- program encodings (1)
- proof complexity (1)
- proving (1)
- relevance (1)
- selection (1)
- semantic web (1)
- strong equivalence (1)
- tableau calculi (1)
- theorem (1)
- topics (1)
- touch input (1)
Im Bachelor-Studiengang (B. Sc.) IT Security an der Fachhochschule St. Pölten wurde im Wintersemester 2011/12 versuchsweise die Lehrorganisation im ersten Fachsemester verändert: Die Module bzw. Teilmodule wurden nicht mehr alle parallel zueinander unterrichtet, sondern jedes Modul wurde exklusiv über einige Wochen abgehalten. Im Beitrag werden die Auswirkungen und bisherigen Erfahrungen mit dieser Reorganisation der Lehre geschildert: So haben sich die Noten im Mittel um etwa eine Note verbessert, die Zahl derjenigen Studierenden, die durch Prüfungen durchfallen, ist drastisch gesunken. Die Zufriedenheit der Studierenden und Lehrenden ist so groß, dass diese Form der Lehrorganisation im gesamten Bachelor- und auch im Masterstudiengang übernommen wird.
Where girls the role of boys in CS - attitudes of CS students in a female-dominated environment
(2013)
A survey has been carried out in the Computer Science (CS) department at the University of Baghdad to investigate the attitudes of CS students in a female dominant environment, showing the differences between male and female students in different academic years. We also compare the attitudes of the freshman students of two different cultures (University of Baghdad, Iraq, and the University of Potsdam).
Viele Hochschulen nutzen SAP ERP in der Lehre, um den Studierenden einen Einblick in die Funktionsweise und den Aufbau von integrierter Standardsoftware zu ermöglichen. Im Rahmen solcher Schulungen bilden die Studierenden eine Meinung und Bewertung der Software. In diesem Artikel wird untersucht, wie sich klassische Modelle der Nutzungswahrnehmung auf die spezielle Situation von SAP ERP in der Lehre übertragen lassen und welchen Einfluss bestimmte Faktoren haben. Dazu wurden vier Vorher-Nachher-Studien durchgeführt. Die Ergebnisse zeigen, dass die Funktionalität im Laufe der Schulung positiver und die Benutzungsfreundlichkeit als negativer bewertet wird.
Scientific writing is an important skill for computer science and computer engineering professionals. In this paper we present a writing concept across the curriculum program directed towards scientific writing. The program is built around a hierarchy of learning outcomes. The hierarchy is constructed through analyzing the learning outcomes in relation to competencies that are needed to fulfill them.
This document presents a formula selection system for classical first order theorem proving based on the relevance of formulae for the proof of a conjecture. It is based on unifiability of predicates and is also able to use a linguistic approach for the selection. The scope of the technique is the reduction of the set of formulae and the increase of the amount of provable conjectures in a given time. Since the technique generates a subset of the formula set, it can be used as a preprocessor for automated theorem proving. The document contains the conception, implementation and evaluation of both selection concepts. While the one concept generates a search graph over the negation normal forms or Skolem normal forms of the given formulae, the linguistic concept analyses the formulae and determines frequencies of lexemes and uses a tf-idf weighting algorithm to determine the relevance of the formulae. Though the concept is built for first order logic, it is not limited to it. The concept can be used for higher order and modal logik, too, with minimal adoptions. The system was also evaluated at the world championship of automated theorem provers (CADE ATP Systems Competition, CASC-24) in combination with the leanCoP theorem prover and the evaluation of the results of the CASC and the benchmarks with the problems of the CASC of the year 2012 (CASC-J6) show that the concept of the system has positive impact to the performance of automated theorem provers. Also, the benchmarks with two different theorem provers which use different calculi have shown that the selection is independent from the calculus. Moreover, the concept of TEMPLAR has shown to be competitive to some extent with the concept of SinE and even helped one of the theorem provers to solve problems that were not (or slower) solved with SinE selection in the CASC. Finally, the evaluation implies that the combination of the unification based and linguistic selection yields more improved results though no optimisation was done for the problems.
We introduce formal proof systems based on tableau methods for analyzing computations in Answer Set Programming (ASP). Our approach furnishes fine-grained instruments for characterizing operations as well as strategies of ASP solvers. The granularity is detailed enough to capture a variety of propagation and choice methods of algorithms used for ASP solving, also incorporating SAT-based and conflict-driven learning approaches to some extent. This provides us with a uniform setting for identifying and comparing fundamental properties of ASP solving approaches. In particular, we investigate their proof complexities and show that the run-times of best-case computations can vary exponentially between different existing ASP solvers. Apart from providing a framework for comparing ASP solving approaches, our characterizations also contribute to their understanding by pinning down the constitutive atomic operations. Furthermore, our framework is flexible enough to integrate new inference patterns, and so to study their relation to existing ones. To this end, we generalize our approach and provide an extensible basis aiming at a modular incorporation of additional language constructs. This is exemplified by augmenting our basic tableau methods with cardinality constraints and disjunctions.
Der vorliegende Beitrag beschäftigt sich mit der Frage, wie der eLearning-Support in großen Institutionen effizient gestaltet werden kann. Vorgestellt wird ein experimentelles Beratungsprojekt, das Lehrende bei der Gestaltung von eLearning-Maßnahmen mithilfe der Lernplattform ILIAS1 unterstützt. Neben der Zielsetzung des Projekts werden dessen Aufbau und erste Praxiserfahrungen erörtert. Außerdem werden Potenziale des Beratungsformats, die insbesondere mit der individuellen Vor-Ort-Beratung der Lehrenden durch hochschuldidaktisch geschulte Studierende einhergehen, erläutert. Abschließend werden Grenzen und Weiterentwicklungsperspektiven des Projekts dargestellt. Am Beispiel der ILIAS-Beratung soll gezeigt werden, dass es sich einer nachhaltigen Organisationsentwicklung als zuträglich erweist, Kooperationen erschiedenartiger Organisationseinheiten zu fördern und die entstehenden Synergieeffekte zu nutzen.
In the early days of computer graphics, research was mainly driven by the goal to create realistic synthetic imagery. By contrast, non-photorealistic computer graphics, established as its own branch of computer graphics in the early 1990s, is mainly motivated by concepts and principles found in traditional art forms, such as painting, illustration, and graphic design, and it investigates concepts and techniques that abstract from reality using expressive, stylized, or illustrative rendering techniques. This thesis focuses on the artistic stylization of two-dimensional content and presents several novel automatic techniques for the creation of simplified stylistic illustrations from color images, video, and 3D renderings. Primary innovation of these novel techniques is that they utilize the smooth structure tensor as a simple and efficient way to obtain information about the local structure of an image. More specifically, this thesis contributes to knowledge in this field in the following ways. First, a comprehensive review of the structure tensor is provided. In particular, different methods for integrating the minor eigenvector field of the smoothed structure tensor are developed, and the superiority of the smoothed structure tensor over the popular edge tangent flow is demonstrated. Second, separable implementations of the popular bilateral and difference of Gaussians filters that adapt to the local structure are presented. These filters avoid artifacts while being computationally highly efficient. Taken together, both provide an effective way to create a cartoon-style effect. Third, a generalization of the Kuwahara filter is presented that avoids artifacts by adapting the shape, scale, and orientation of the filter to the local structure. This causes directional image features to be better preserved and emphasized, resulting in overall sharper edges and a more feature-abiding painterly effect. In addition to the single-scale variant, a multi-scale variant is presented, which is capable of performing a highly aggressive abstraction. Fourth, a technique that builds upon the idea of combining flow-guided smoothing with shock filtering is presented, allowing for an aggressive exaggeration and an emphasis of directional image features. All presented techniques are suitable for temporally coherent per-frame filtering of video or dynamic 3D renderings, without requiring expensive extra processing, such as optical flow. Moreover, they can be efficiently implemented to process content in real-time on a GPU.
This paper surveys the field of nonphotorealistic rendering (NPR), focusing on techniques for transforming 2D input (images and video) into artistically stylized renderings. We first present a taxonomy of the 2D NPR algorithms developed over the past two decades, structured according to the design characteristics and behavior of each technique. We then describe a chronology of development from the semiautomatic paint systems of the early nineties, through to the automated painterly rendering systems of the late nineties driven by image gradient analysis. Two complementary trends in the NPR literature are then addressed, with reference to our taxonomy. First, the fusion of higher level computer vision and NPR, illustrating the trends toward scene analysis to drive artistic abstraction and diversity of style. Second, the evolution of local processing approaches toward edge-aware filtering for real-time stylization of images and video. The survey then concludes with a discussion of open challenges for 2D NPR identified in recent NPR symposia, including topics such as user and aesthetic evaluation.
Durch den bundesweiten Rückgang der Schülerzahlen und einer steigenden Zahl von Bildungsangeboten geraten Universitäten und Hochschulen in den nächsten Jahren weiter in eine Wettbewerbssituation, weshalb sie effektive Marketingmaßnahmen entwickeln müssen, um Schülerinnen und Schüler möglichst frühzeitig für das jeweilige Angebot (z. B. Informatik- und informatiknahe Studiengänge) zu interessieren. Ein Medium, über das sich potenziell sehr viele Jugendliche erreichen lassen, sind dabei soziale Netzwerke. Diese Arbeit präsentiert Ergebnisse einer Studie unter Informatikstudienanfängerinnen und -anfängern zum Nutzungsverhalten sozialer Netzwerke und zieht Schlussfolgerungen zu deren Eignung als Werbe- und Informationskanal für die Zielgruppe der Informatikinteressierten.
Simplicity is a mindset, a way of looking at solutions, an extremely wide-ranging philosophical stance on the world, and thus a deeply rooted cultural paradigm. The culture of "less" can be profoundly disruptive, cutting out existing "standard" elements from products and business models, thereby revolutionizing entire markets.
fundamental challenge for product-lifecycle management in collaborative value networks is to utilize the vast amount of product information available from heterogeneous sources in order to improve business analytics, decision support, and processes. This becomes even more challenging if those sources are distributed across multiple organizations. Federations of semantic information services, combining service-orientation and semantic technologies, provide a promising solution for this problem. However, without proper measures to establish information security, companies will be reluctant to join an information federation, which could lead to serious adoption barriers.
Following the design science paradigm, this paper presents general objectives and a process for designing a secure federation of semantic information services. Furthermore, new as well as established security measures are discussed. Here, our contributions include an access-control enforcement system for semantic information services and a process for modeling access-control policies across organizations. In addition, a comprehensive security architecture is presented. An implementation of the architecture in the context of an application scenario and several performance experiments demonstrate the practical viability of our approach.
Die vorliegende Arbeit erörtert die Frage, wie Nachwuchs für das Informatikstudium nachhaltig gesichert werden kann. Dazu werden Befragungen unter Schülerinnen und Schülern (13-16 Jahre), sowie aktuelle Informatik-Schnupperangebote für Schülerinnen und Schüler an deutschsprachigen Hochschulen vorgestellt und untersucht. Diese Gegenüberstellung zeigt deutlich, dass die Angebote nur bedingt eine breite Zielgruppe ansprechen und dass weitere Formate und Inhalte notwendig sind, um Schülerinnen und Schüler frühzeitig und in voller Breite zu erreichen und für das Informatikstudium zu begeistern. Daraus wird abgeleitet, dass Missverständnisse und Probleme mit der Informatik im Schulkontext aufgegriffen werden müssen. Das vorgestellte Programm Schulbotschafter Informatik stellt einen möglichen Weg dar, um dies zu erreichen und übliche Schnupperangebote zu ergänzen.
Cloud computing is a model for enabling on-demand access to a shared pool of computing resources. With virtually limitless on-demand resources, a cloud environment enables the hosted Internet application to quickly cope when there is an increase in the workload. However, the overhead of provisioning resources exposes the Internet application to periods of under-provisioning and performance degradation. Moreover, the performance interference, due to the consolidation in the cloud environment, complicates the performance management of the Internet applications. In this dissertation, we propose two approaches to mitigate the impact of the resources provisioning overhead. The first approach employs control theory to scale resources vertically and cope fast with workload. This approach assumes that the provider has knowledge and control over the platform running in the virtual machines (VMs), which limits it to Platform as a Service (PaaS) and Software as a Service (SaaS) providers. The second approach is a customer-side one that deals with the horizontal scalability in an Infrastructure as a Service (IaaS) model. It addresses the trade-off problem between cost and performance with a multi-goal optimization solution. This approach finds the scale thresholds that achieve the highest performance with the lowest increase in the cost. Moreover, the second approach employs a proposed time series forecasting algorithm to scale the application proactively and avoid under-utilization periods. Furthermore, to mitigate the interference impact on the Internet application performance, we developed a system which finds and eliminates the VMs suffering from performance interference. The developed system is a light-weight solution which does not imply provider involvement. To evaluate our approaches and the designed algorithms at large-scale level, we developed a simulator called (ScaleSim). In the simulator, we implemented scalability components acting as the scalability components of Amazon EC2. The current scalability implementation in Amazon EC2 is used as a reference point for evaluating the improvement in the scalable application performance. ScaleSim is fed with realistic models of the RUBiS benchmark extracted from the real environment. The workload is generated from the access logs of the 1998 world cup website. The results show that optimizing the scalability thresholds and adopting proactive scalability can mitigate 88% of the resources provisioning overhead impact with only a 9% increase in the cost.
In einigen Bereichen der Informatiklehre ist es möglich, die persönlichen Erfahrungen der Studierenden im Umgang mit Informationstechnik aufzugreifen und vor dem Hintergrund theoretischer Konzepte aus der Literatur gemeinsam mit ihnen zu reflektieren. Das hier vorgestellte Lehrkonzept des Reflexionsdialogs erstreckt sich über drei Seminartermine und vorbereitende Selbstlernphasen. Unterstützt wird das Konzept durch DialogueMaps, eine Software zur Visualisierung komplexer Sachverhalte und zur Unterstützung interaktiver Dialoge. Dieser Beitrag beschreibt die Hintergründe des Lehrkonzeptes, das Lehrkonzept selbst sowie die inhaltliche Ausgestaltung im Rahmen eines Mastermoduls „Computergestützte Kooperation“.
This thesis proposes a privacy protection framework for the controlled distribution and use of personal private data. The framework is based on the idea that privacy policies can be set directly by the data owner and can be automatically enforced against the data user. Data privacy continues to be a very important topic, as our dependency on electronic communication maintains its current growth, and private data is shared between multiple devices, users and locations. The growing amount and the ubiquitous availability of personal private data increases the likelihood of data misuse. Early privacy protection techniques, such as anonymous email and payment systems have focused on data avoidance and anonymous use of services. They did not take into account that data sharing cannot be avoided when people participate in electronic communication scenarios that involve social interactions. This leads to a situation where data is shared widely and uncontrollably and in most cases the data owner has no control over further distribution and use of personal private data. Previous efforts to integrate privacy awareness into data processing workflows have focused on the extension of existing access control frameworks with privacy aware functions or have analysed specific individual problems such as the expressiveness of policy languages. So far, very few implementations of integrated privacy protection mechanisms exist and can be studied to prove their effectiveness for privacy protection. Second level issues that stem from practical application of the implemented mechanisms, such as usability, life-time data management and changes in trustworthiness have received very little attention so far, mainly because they require actual implementations to be studied. Most existing privacy protection schemes silently assume that it is the privilege of the data user to define the contract under which personal private data is released. Such an approach simplifies policy management and policy enforcement for the data user, but leaves the data owner with a binary decision to submit or withhold his or her personal data based on the provided policy. We wanted to empower the data owner to express his or her privacy preferences through privacy policies that follow the so-called Owner-Retained Access Control (ORAC) model. ORAC has been proposed by McCollum, et al. as an alternate access control mechanism that leaves the authority over access decisions by the originator of the data. The data owner is given control over the release policy for his or her personal data, and he or she can set permissions or restrictions according to individually perceived trust values. Such a policy needs to be expressed in a coherent way and must allow the deterministic policy evaluation by different entities. The privacy policy also needs to be communicated from the data owner to the data user, so that it can be enforced. Data and policy are stored together as a Protected Data Object that follows the Sticky Policy paradigm as defined by Mont, et al. and others. We developed a unique policy combination approach that takes usability aspects for the creation and maintenance of policies into consideration. Our privacy policy consists of three parts: A Default Policy provides basic privacy protection if no specific rules have been entered by the data owner. An Owner Policy part allows the customisation of the default policy by the data owner. And a so-called Safety Policy guarantees that the data owner cannot specify disadvantageous policies, which, for example, exclude him or her from further access to the private data. The combined evaluation of these three policy-parts yields the necessary access decision. The automatic enforcement of privacy policies in our protection framework is supported by a reference monitor implementation. We started our work with the development of a client-side protection mechanism that allows the enforcement of data-use restrictions after private data has been released to the data user. The client-side enforcement component for data-use policies is based on a modified Java Security Framework. Privacy policies are translated into corresponding Java permissions that can be automatically enforced by the Java Security Manager. When we later extended our work to implement server-side protection mechanisms, we found several drawbacks for the privacy enforcement through the Java Security Framework. We solved this problem by extending our reference monitor design to use Aspect-Oriented Programming (AOP) and the Java Reflection API to intercept data accesses in existing applications and provide a way to enforce data owner-defined privacy policies for business applications.
Learning a model for the relationship between the attributes and the annotated labels of data examples serves two purposes. Firstly, it enables the prediction of the label for examples without annotation. Secondly, the parameters of the model can provide useful insights into the structure of the data. If the data has an inherent partitioned structure, it is natural to mirror this structure in the model. Such mixture models predict by combining the individual predictions generated by the mixture components which correspond to the partitions in the data. Often the partitioned structure is latent, and has to be inferred when learning the mixture model. Directly evaluating the accuracy of the inferred partition structure is, in many cases, impossible because the ground truth cannot be obtained for comparison. However it can be assessed indirectly by measuring the prediction accuracy of the mixture model that arises from it. This thesis addresses the interplay between the improvement of predictive accuracy by uncovering latent cluster structure in data, and further addresses the validation of the estimated structure by measuring the accuracy of the resulting predictive model. In the application of filtering unsolicited emails, the emails in the training set are latently clustered into advertisement campaigns. Uncovering this latent structure allows filtering of future emails with very low false positive rates. In order to model the cluster structure, a Bayesian clustering model for dependent binary features is developed in this thesis. Knowing the clustering of emails into campaigns can also aid in uncovering which emails have been sent on behalf of the same network of captured hosts, so-called botnets. This association of emails to networks is another layer of latent clustering. Uncovering this latent structure allows service providers to further increase the accuracy of email filtering and to effectively defend against distributed denial-of-service attacks. To this end, a discriminative clustering model is derived in this thesis that is based on the graph of observed emails. The partitionings inferred using this model are evaluated through their capacity to predict the campaigns of new emails. Furthermore, when classifying the content of emails, statistical information about the sending server can be valuable. Learning a model that is able to make use of it requires training data that includes server statistics. In order to also use training data where the server statistics are missing, a model that is a mixture over potentially all substitutions thereof is developed. Another application is to predict the navigation behavior of the users of a website. Here, there is no a priori partitioning of the users into clusters, but to understand different usage scenarios and design different layouts for them, imposing a partitioning is necessary. The presented approach simultaneously optimizes the discriminative as well as the predictive power of the clusters. Each model is evaluated on real-world data and compared to baseline methods. The results show that explicitly modeling the assumptions about the latent cluster structure leads to improved predictions compared to the baselines. It is beneficial to incorporate a small number of hyperparameters that can be tuned to yield the best predictions in cases where the prediction accuracy can not be optimized directly.