Theses and Dissertations from UMD
Permanent URI for this communityhttp://hdl.handle.net/1903/2
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
More information is available at Theses and Dissertations at University of Maryland Libraries.
Browse
2 results
Search Results
Item Towards Visual Analytics in Virtual Environments(2018) Krokos, Eric; Varshney, Amitabh; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Virtual reality (VR) is poised to become the new medium through which we engage, view, and consume content. In contrast to traditional 2D desktop displays, which restrict our interaction space onto an arbitrary 2D-plane with unnatural interaction mechanisms, VR expands the visualization and interaction space into our 3D domain, enabling natural observations and interactions with information. With the rise of Big Data, processing and visualizing such enormous datasets is of utmost importance and remains a difficult challenge. Machine learning, specifically deep learning, is rising to meet this challenge. In this work, we present several studies: (a) demonstrating the effectiveness of immersive environments over traditional desktops for memory recall, (b) quantifying cybersickness in virtual environments, (c) enabling human analysts and deep learning to support, refine, and enhance each other through visualization, and (d) visualizing root-DNS information, enabling analysts to find new and interesting anomalies and patterns. In our first work, we conduct a user study where participants memorize and recall a series of spatially-distributed faces on both a desktop and head-mounted display (HMD). We found that the use of virtual memory palaces in the HMD condition improves recall accuracy when compared to the traditional desktop condition. This improvement was statistically significant. Next, we present our work on quantifying cybersickness through EEG analysis. We found statistically significant correlations with increases in delta, theta, and alpha brain waves with self-reported sickness levels, enabling future virtual reality developers to design countermeasures. Third, we present our work on enabling domain experts to discover hidden labels and communities within unlabeled (or coarsely labeled) high-dimensional datasets using deep learning with visualization. Lastly, we present a 3D visualization of root-DNS traffic, revealing characteristics of a DDOS attack and changes in the distribution of queries received over time. Together, this work takes the first steps in bringing together machine learning, visual analytics, and virtual reality.Item TOWARD SYMBIOTIC HUMAN-AI INTERACTION FOCUSING ON PROGRAMMING BY EXAMPLE(2017) Lee, Tak Yeon; Bederson, Benjamin B; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Programming has become a new literacy, but is still inaccessible to ordinary people. Programming-by-example (PBE) is an alternative approach that allows people to teach computers repetitive tasks by demonstrating couple input and output examples of the tasks. While the advancements of PBE have been mainly driven by algorithmic improvements, a growing community of researchers started realizing the importance of issues on the human side of PBE. For instance, inexperienced users often find it hard to provide complete and consistent examples, which is crucial for computers to learn the correct programs. Unfortunately, most PBE systems have limited ways to communicate with users about what it can or cannot do, and how to handle unsuccessful situations. The lack of symbiotic interaction between human users and PBE engines remain as a major hurdle against a widespread adoption of PBE techniques. To address the issues on the human side of PBE, this dissertation has four research threads. First, we began with two formative studies to establish a better understanding of inexperienced users' needs and mental models. Second, based on the findings of the formative studies, we developed a Visual Environment for Symbiotic Programming, called VESPY. VESPY interleaves visual programming and PBE techniques, enabling users (1) to decompose complex tasks into small modules on its 2-d grid, and (2) to complete each module by providing input and output examples. Four sample programs demonstrate VESPY's remarkable versatility. However, we also noticed that VESPY still had a number of usability issues. Third, to better understand the usability issues and how to help users out from common mistakes, we conducted an online user study that observed how inexperience users perform program decomposition and disambiguation, which are the two core activities of PBE. We identified seven types of mistakes, and reaffirmed that informative feedback on those mistakes is crucial for designing usable systems. Finally, we explored the design space of feedback components, in order to understand their impact on user's experience. My dissertation contributes to the AI and HCI communities with: (i) identification of unmet needs of end-users of the Web; (ii) characterization of non-programmers’ mental model; (iii) design process of interleaving visual programming and PBE; (iv) identification of mistakes people make while using PBE; and (v) design and assessment of feedback components for PBE users.