Contributions in Merlin

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This Master Thesis deals with the search for new patterns to enhance the discovery of fraudulent activities within the jurisdiction of a financial institution. Therefore transactional data from a database is analyzed, scored and processed for the later usage by an internal anti-money laundering specialist. The findings are again stored in a database and processed by TV - the Transaction Visualizer, an existing and already commercially used tool. As a result of this thesis, the software module TMatch and the graphical user interface TMatchViz were developed. The interaction of these two tools was tested and evaluated using synthetically created datasets. Furthermore, the approximations made and their impact on the specification of the algorithms will be addressed in his report.

This thesis addresses the refinement of adaptation rules in a web-based to-do management system named MOCCA. MOCCA is an adaptive system, which adapts the user interface using the cultural background information of each user. To achieve the goal of this thesis, a recommender system was developed, which clusters similar users into groups. In order to create new adaptation rules for similar users, the system calculates recommendations, which are assigned to the groups. The recommender system uses techniques such as collaborative filtering, k-Means and the statistical X2 goodness-of-fit test. The system was designed in a modular fashion and divided into two parts. One part of the recommender system gathers similar users and groups them accordingly. The other part uses the generated groups and calculates recommendations. For each part two concrete components were created. Those components are interchangeable, so that the recommender system can be composed as desired. All possible compositions were evaluated with a set of test users. It could be shown, that the developed recommender system generates a more accurate user interface than the initially given adaptation rules.

In this thesis we implement a 3D visualization for software systems. We use a 3D city metaphor and display the source code entities as city objects. This allows users to intuitively understand what they see. The tool can be used for the analysis of complex software systems. Our prototype of the tool helps in understanding, maintenance and reverse engineering of large systems. One of our main goals is to outperform currently available software visualizations in performance and usability. We use the powerful jMonkeyEngine for the rendering of the 3D view. Our tool is written in Java. The current architecture of our tool was developed keeping extensibility in mind. Test persons evaluate our tool. The results show that the testers are pleased with the 3D visualization. The strengths of our tool lie in its abilities to give an overview of a software system and that it allows to find code smells easily. The use of a game engine results in a smooth 3D view.

The ECCEROBOT project is an effort to build and control an anthropomimetic robot which contains a muscule-tendon like actuator system embedded in a skeleton. This diploma thesis has been written in the context of the ECCEROBOT project and its goal was to simulate the working of a muscle as accurately as possible. To build the simulation, the first step was to select a suitable simulation tool. A survey of the available physics based simulation tools was undertaken to select the most suitable open-source tool with respect to accuracy, stability and speed of calculation for simulations of the robot. Finally, JBullet, the Java version of the Bullet physics engine, was selected in combination with OpenGL to simulate an arm of the robot. The simulation of the arm muscle was done based on the Hill model. Various combinations of parameters were investigated for the control of the muscle and also what actions the muscle could perform most effectively in simulation. The report contains the findings related with the accuracy of the simulated arm and its performance in interaction with other objects.

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Today, modelers must rely on their instinct and experience to decide how much detail of a system is worth being modeled. This ad-hoc modeling may result in models that are either too abstract or too detailed for their intended use. We propose to investigate objective measurement of a model’s abstractness and systematic guidance to attain the right level of abstraction. Such a contribution has the potential to improve the quality of models and reduce the amount of time needed for modeling activities.

Prediction of software defects works well within projects as long as there is a sufficient amount of data available to train any models. However, this is rarely the case for new software projects and for many companies. So far, only a few have studies focused on transferring prediction models from one project to another. In this paper, we study cross-project defect prediction models on a large scale. For 12 real-world applications, we ran 622 cross-project predictions. Our results indicate that cross-project prediction is a serious challenge, i.e., simply using models from projects in the same domain or with the same process does not lead to accurate predictions. To help software engineers choose models wisely, we identified factors that do influence the success of cross-project predictions. We also derived decision trees that can provide early estimates for precision, recall, and accuracy before a prediction is attempted.

Hedonic aspects are increasingly considered as an important factor in user acceptance of information systems, especially for activities with high self-fulfilling value for the users. In this paper we report on the results of an experiment investigating the hedonic qualities of an interactive large-display workspace for collocated collaboration in sales-oriented travel advisory. The results show a higher hedonic stimulation quality of a touch-based large-display travel advisory workspace than that of a traditional workspace with catalogues. Together with the feedback of both customers and travel agents this suggests the adequacy of using touch-based large-displays with visual workspaces for supporting the hedonic stimulation of user experience in collocated collaboration settings. The relation of high perception of hedonic quality to positive emotional attitudes towards the use of a large-display workspace indicates that even in utilitarian activities (e.g. reaching sales goals for travel agents) hedonic aspects can play an important role. This calls for reconsidering the traditional divide of hedonic vs. utilitarian systems in current literature, to a more balanced view towards systems which provide both utilitarian and hedonic sources of value to the user.

In this study, we examine the rationale that informed traders use in choosing various financial instruments in order to speculate on the volatility of the underlying asset, here a common stock. Using a continuous-time trading model, we demonstrate that the quality of the private information regarding the volatility parameter together with the relative transaction costs observed in the various segments of the cash and derivatives markets will determine informed agents' trading habitats. We further show that in the presence of imprecise volatility signals, only the "most sophisticated" traders (those with highly precise volatility signals) will engage in pure volatility bets. Traders with less precise signals will choose a naked option strategy, while traders at the low spectrum of the precision scale will invest in the underlying stock. Thus, the low volume of pure volatility trades observed by Lakonishok et al. (2007) does not necessarily imply that only fringe traders have chosen to speculate on volatility. Rather, it may suggest that the majority of informed traders do not have precise volatility signals.