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Item Open Access Visual prediction of quantitative information using social media data(2017) Fatehi Ebrahimzadeh, HamedIn recent years, the availability of a vast amount of user-generated data via social media, has given an opportunity to researchers for analyzing these data sources and discovering meaningful information. However, processing and understanding this immense amount of data is challenging and calls for automated approaches, and involvement of field experts to use their field knowledge and experience to enhance the data analysis. So far, existing approaches only enable the detection of indicative information from the data such as the occurrence of critical incidents, relevant situation reports etc. Consequently, the next step would be to better relate the user provided information to the real-world quantities. In this work, a predictive visual analytics approach is developed that offers semi-automated methods to estimate quantitative information (e.g. number of people who participate in a public event). At first, the approach provides interactive visual tools to explore social media data in time and space and select features required as input for training and prediction interactively. Next, a suitable model can be trained based on these feature sets and applied for prediction. Finally, the approach also allows to visually explore prediction results and measure quality of predictions with respect to the ground truth information obtained from past observations. The result of this work is a generic visual analytics approach, that provides expert user with visual tools for a constant interaction between human and machine, for producing quantitative predictions based on social media data. The results of predictions are promising, especially in cases that the location, time and other related information to public events are considered together with the content of user-generated data.Item Open Access Integration of IoT devices via a blockchain-based decentralized application(2017) Ahmad, AfzaalBlockchains are shared, immutable ledgers for recording the history of transactions. They foster a new generation of transactional applications that establish trust, accountability, and transparency. It enables contract partners to secure a deal without involving a trusted third party. Initially, the focus was on financial industry for digital assets trading like Bitcoin, but with the emergence of Smart Contracts, blockchain becomes a complete programmable platform. Many research and commercial organization start diving into blockchain world, bringing new ideas of its application in different sectors like supply chain, Health, and autonomous shopping. This thesis presents an idea to integrate Internet of Things (IoT) devices via a blockchain based decentralize application based on Ethereum. The application consists of front-end application which can be deployed to any web server, and a smart contract which will be deployed on a private blockchain network comprises of Peer-to-Peer (P2P) connected IoT devices acting as full Ethereum node. The application emulates the digital transport ticketing system where the asset is a ticket which can be purchased and paid by the user using ether in their Ethereum account on the blockchain. Once the purchase transaction is mined, it is propagated to all the peers. Ticket can now be accessed locally without requesting any centralized system, which makes the system easily accessible and safe because of the security, data integrity and decentralization of the blockchain-based systems.Item Open Access A MATLAB toolbox for the Scintrex CG-5 gravimeter at GIS(2017) Gu, SiyunThis thesis is about a MATLAB toolbox for the Scintrex CG-5 gravimeter. The aim of this toolbox is to offer a basic data process for gravity measurement, which is compatible for most applications in geodesy. In particular, the toolbox covers: 1. data selection, 2. adjustment, 3. gravity gradient computation, 4. gravity visualization, 5. calibration factor estimation. A graphical user interface enables users without deeper programming knowledge to operate this toolbox and obtain the results like adjusted values or figures.Item Open Access Erweiterung und Evaluation einer lupenbasierten Technik zur Exploration von Textsammlungen(2017) Assenov, IvanIn recent years there has been a sharp increase in the amount of text publicly accessible in digital form. The primary cause for this is widespread access to the Internet, the popularity of e-mail and social networking websites and collaborative efforts to preserve and share knowledge. These developments have inspired the creation of a wide variety of information visualization techniques that focus on large-scale text data and facilitate its exploration and analysis. One popular approach represents individual documents as glyphs on a 2D surface, with pairwise distances corresponding to semantic similarities. The metaphor of a moveable lens that summarizes the contents of texts underneath it has been proposed as a method of interaction targeted at free exploration tasks. The main goal of this master’s thesis project is to extend the basic technique by adding labels to the visualization that guide its users towards regions of interest more quickly without negatively impacting the lens’ usefulness. Also, an automatic framework that determines the tool’s effectiveness under different parameter settings is developed. Finally, the proposed improvements and the overall technique are evaluated by means of a think-aloud user study.Item Open Access Crawling hardware for OpenTOSCA(2017) Choudhury, PushpamHeterogeneity is the essence of the IoT paradigm. There is heterogeneity in communication and transport protocols, in network infrastructure, and even among the interacting devices themselves. Managing discovery of the different devices in such a paradigm is an extremely complex task. The typical solutions include an abstraction layer, commonly known as the middleware layer, that handles this complexity for the devices, thereby, allowing them to interact with one another. One major limitation of the existing middleware solutions is in their ability to allow for an easily configurable approach required to handle the tremendous scale of heterogeneous components in the IoT. The objective of this thesis is to develop such a highly configurable discovery middleware approach. The proposed approach aims to discover a variety of heterogeneous devices and services depending on a multi-level plugin layer, consisting of independent plugins that interact with each other based on the pipes and filters architectural pattern. To allow for the dynamic configuration of the middleware, a discovery configuration is developed. The output from the middleware includes a list of devices and their capabilities and is accessible via a web interface which can interact with a range of different clients. The proposed approach is validated on a scenario in a real-life environment.Item Open Access Individual characteristics of successful coding challengers(2017) Wyrich, MarvinAssessing a software engineer's problem-solving ability to algorithmic programming tasks has been an essential part of technical interviews at some of the most successful technology companies for several years now. Despite the adoption of coding challenges among these companies, we do not know what influences the performance of different software engineers in solving such coding challenges. We conducted an exploratory study with software engineering students to find hypothesis on what individual characteristics make a good coding challenge solver. Our findings show that the better coding challengers have also better exam grades and more programming experience. Furthermore, conscientious as well as sad software engineers performed worse in our study.Item Open Access Progressive sparse coding for in situ volume visualization(2017) Berian, GratianNowadays High-Performance Computing (HPC) suffer from an ever-growing gap between computational power, I/O bandwidth and storage capacity. Typical runs of HPC simulations produce Terabytes of data every day. This poses a serious problem when it comes to storing and manipulating such high amount of data. In this thesis I will present a method for compressing time-dependent volume data using an overcomplete dictionary learned from the input data. The proposed method comprises of two steps. In the first step the dictionary is learned over a number of training examples extracted from the volume that we want to compress. This process is an iterative one and at each step the dictionary is updated to better sparsely represent the training data. The second step expresses each block of the volume as a sparse linear combination of the dictionary atoms that were trained over that volume. In order to establish the performance of the proposed method different aspects were tested such as: training speed vs sparsifying speed, compression ratio vs reconstruction error, dictionary reusabilty for multiple time steps and how does a dictionary perform when it is used on a different volume than the one it was trained on. Finally we compare the quality of the reconstructed volume to the original volume and other lossy compression techniques in order to have a visual understanding about the quality of the reconstruction.Item Open Access Modell mit Mastergleichung zur Beschreibung der Exziton-Phonon-Wechselwirkung in Cu2O(2017) Rommel, PatricExzitonen in äußeren Feldern sind ein wertvolles Modellsystem, um theoretische Vorhersagen über eine Vielzahl verschiedener Effekte experimentell zugänglich zu machen und zu überprüfen. Wichtig ist hier in erster Linie der Einfluss der Bandstruktur, durch welchen sich wichtige Korrekturen im Vergleich zum wasserstoffartigen Modell ergeben. Sie bildet unter anderem die reduzierte Symmetrie im Kristallgitter ab. Andererseits gibt es im Festkörper neben den Exzitonen auch andere Quasiteilchen deren Effekte zu beachten sind. In dieser Arbeit soll es dabei um die Exziton-Phonon-Wechselwirkung und ihren Einfluss auf das Eigenwertspektrum der Exzitonen gehen.Item Open Access Automated root cause isolation in performance regression testing(2017) Vogel, SebastianTesting of software is an important aspect of software development. There exist multiple kinds of tests, like unit tests and integration tests. The tests this thesis will focus on will be load tests, which are used to observe a system’s behavior under load. The presented approach will use these load tests in order to observe and analyze the performance of a system, like e.g. the response times of methods. Next these observations are compared with those made on other versions of the system, in order to detect performance regressions, deteriorations in performance, between versions. Another goal of the approach will be to identify the root cause of the regressions, which is the source code change responsible for introducing them. By doing this, the task of fixing this problem will be made easier for the software engineer, since he has an entry point for the problem.Item Open Access Visual analytics of big data from distributed systems(2017) Kutzleb, AndréDistributed Systems are challenging to debug because the temporal order of events and distributed states are hard to track. The high complexity of distributed systems make fully automatic reasoning difficult to apply. Domain experts are often required to reason about the behavior of a system based on log files from various sources. This situation presents a good opportunity for visual analytics. Data from multiple sources can be preprocessed and visualized, and then domain experts can conduct exploratory analysis to accelerate the identification of issues. The goal of this master thesis was to create such a visual analytics tool to help domain experts explore data collected from distributed systems more efficiently and assist in identifying bugs and anomalies. The system was used by domain experts and helped to identify issues in a distributed system, showing that visual analytics can be a useful tool to assist domain experts in their daily work.