004 Datenverarbeitung; Informatik
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Replikation einer Multi-Agenten-Simulationsumgebung zur Überprüfung auf Integrität und Konsistenz
(2012)
In dieser Master -Arbeit möchte ich zunächst eine Simulation vorstellen, mit der das Verhalten von Agenten untersucht wird, die in einer generierten Welt versuchen zu über leben und dazu einige Handlungsmöglichkeiten zur Auswahl haben. Anschließend werde ich kurz die theoretischen Aspekte beleuchten, welche hier zu Grunde liegen. Der Hauptteil meiner Arbeit ist meine Replikation einer Simulation, die von Andreas König im Jahr 2000 in Java angefertigt worden ist [Kö2000] . Ich werde hier seine Arbeit in stark verkürzter Form darstellen und anschließend auf meine eigene Entwicklung eingehen.
Im Schlussteil der Arbeit werde ich die Ergebnisse meiner Simulation mit denen von Andreas König vergleichen und die verwendeten Werkzeuge (Java und NetLogo) besprechen. Zum Abschluss werde ich in einem Fazit mein Vorhaben kurz zusammenfassen und berichten was sich umsetzen ließ, was nicht funktioniert hat und warum.
Remote rendering services offer the possibility to stream high quality images to lower powered devices. Due to the transmission of data the interactivity of applications is afflicted with a delay. A method to reduce delay of the camera manipulation on the client is called 3d-warping. This method causes artifacts. In this thesis different approaches of remote rendering setups will be shown. The artifacts and improvements of the warping method will be described. Methods to reduce the artifacts will be implemented and analyzed.
The thesis develops and evaluates a hypothetical model of the factors that influence user acceptance of weblog technology. Previous acceptance studies are reviewed, and the various models employed are discussed. The eventual model is based on the technology acceptance model (TAM) by Davis et al. It conceptualizes and operationalizes a quantitative survey conducted by means of an online questionnaire, strictly from a user perspective. Finally, it is tested and validated by applying methods of data analysis.
The annotation of digital media is no new area of research, instead it is widely investigated. There are many innovative ideas for creating the process of annotation. The most extensive segment of related work is about semi automatic annotation. One characteristic is common in the related work: None of them put the user in focus. If you want to build an interface, which is supporting and satsfying the user, you will have to do a user evaluation first. Whithin this thesis we want to analyze, which features an interface should or should not have to meet these requirements of support, user satisfaction and beeing intuitive. After collecting many ideas and arguing with a team of experts, we determined only a few of them. Different combination of these determined variables form the interfaces, we have to investigate in our usability study. The results of the usability leads to the assumption, that autocompletion and suggestion features supports the user. Furthermore coloring tags for grouping them into categories is not disturbing to the user, but has a tendency of being supportive. Same tendencies emerge for an interface consisting of two user interface elements. There is also an example given for the definition differences of being intuitive. This thesis leads to the concolusion that for reasons of user satisfaction and support it is allowed to differ from classical annotation interface features and to implement further usability studies in the section of annotation interfaces.
Problems in the analysis of requirements often lead to failures when developing software systems. This problem is nowadays being faced by requirements engineering. The early involvement of all kinds of stakeholders in the development of such a system and a structured process to elicitate and analyse requirements have made it a crucial factor as a first step in software development. The increasing complexity of modern softwaresystems though leads to a rising amount of information which has to be dealt with during analysis. Without the support of appropriate tools this would be almost impossible to do. Especially in bigger projects, which tend to be spatially distributed, an effective requirements engineering could not be implemented without this kind of support. Today there is a wide range of tools dealing with this matter. They have been in use since some time now and, in their most recent versions, realize the most important aspects of requirements engineering. Within the scope of this thesis some of these tools will be analysed, focussing on both the major functionalities concerning the management of requirements and the repository of these tools. The results of this analyis will be integrated into a reference model.
The content aggregator platform Reddit has established itself as one of the most popular websites in the world. However, scientific research on Reddit is hindered as Reddit allows (and even encourages) user anonymity, i.e., user profiles do not contain personal information such as the gender. Inferring the gender of users in large-scale could enable the analysis of gender-specific areas of interest, reactions to events, and behavioral patterns. In this direction, this thesis suggests a machine learning approach of estimating the gender of Reddit users. By exploiting specific conventions in parts of the website, we obtain a ground truth for more than 190 million comments of labeled users. This data is then used to train machine learning classifiers to use them to gain insights about the gender balance of particular subreddits and the platform in general. By comparing a variety of different approaches for classification algorithm, we find that character-level convolutional neural network achieves performance with an 82.3% F1 score on a task of predicting a gender of a user based on his/her comments. The score surpasses 85% mark for frequent users with more than 50 comments. Furthermore, we discover that female users are less active on Reddit platform, they write fewer comments and post in fewer subreddits on average, when compared to male users.
Opinion Mining : Using Twitter as a source of opinion for the prediction of stock market prices
(2012)
Neben den theoretischen Grundkonzepten der automatisierten Fließtextanalyse, die das Fundament dieser Arbeit bilden, soll ein Überblick in den derzeitigen Forschungsstand bei der Analyse von Twitter-Nachrichten gegeben werden. Hierzu werden verschiedene Forschungsergebnisse der, derzeit verfügbaren wissenschaftlichen Literatur erläutert, miteinander verglichen und kritisch hinterfragt. Deren Ergebnisse und Vorgehensweisen sollen in unsere eigene Forschung mit eingehen, soweit sie sinnvoll erscheinen. Ziel ist es hierbei, den derzeitigen Forschungsstand möglichst gut zu nutzen.
Ein weiteres Ziel ist es, dem Leser einen Überblick über verschiedene maschinelle Datenanalysemethoden zur Erkennung von Meinungen zu geben. Dies ist notwendig, um die Bedeutung der im späteren Verlauf der Arbeit eingesetzten Analysemethoden in ihrem wissenschaftlichen Kontext besser verstehen zu können. Da diese Methoden auf verschiedene Arten durchgeführt werden können, werden verschiedene Analysemethoden vorgestellt und miteinander verglichen. Hierdurch soll die Machbarkeit der folgenden Meinungsauswertung bewiesen werden. Um eine hinreichende Genauigkeit bei der folgenden Untersuchung zu gewährleisten, wird auf ein bereits bestehendes und evaluiertes Framework zurückgegriffen. Dieses ist als API 1 verfügbar und wird daher zusätzlich behandelt. Der Kern Inhalt dieser Arbeit wird sich der Analyse von Twitternachrichten mit den Methoden des Opinion Mining widmen.
Es soll untersucht werden, ob sich Korrelationen zwischen der Meinungsausprägung von Twitternachrichten und dem Börsenkurs eines Unternehmens finden lassen. Es soll dabei die Stimmungslage der Firma Google Inc. über einen Zeitraum von einem Monat untersucht und die dadurch gefunden Erkenntnisse mit dem Börsenkurs des Unternehmens verglichen werden. Ziel ist es, die Erkenntnisse von (Sprenger & Welpe, 2010) und (Taytal & Komaragiri, 2009) auf diesem Gebiet zu überprüfen und weitere Fragestellungen zu beantworten.
Today you can find smartphones everywhere. This situation created a hype for Augmented Reality and AR Apps. The big question is: Do these applications provide a real added value? To make AR pratically it is important to add the computational power of a computer to the advantages of AR. An easy and fast way of interaction is essential.
A Poker-Assistance-Software is an ideal test area for an AR Application with real added value. The estimation of the winning probability and a fast automated tracking of the playing cards is the perfect field of investigation.
In this discussion it is interesting to evaluate the added value of AR Applications in common.
Particle swarm optimization is an optimization technique based on simulation of the social behavior of swarms.
The goal of this thesis is to solve 6DOF local pose estimation using a modified particle swarm technique introduced by Khan et al. in 2010. Local pose estimation is achieved by using continuous depth and color data from a RGB-D sensor. Datasets are aquired from different camera poses and registered into a common model. Accuracy and computation time of the implementation is compared to state of the art algorithms and evaluated in different configurations.