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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

Visualizing incomplete data in multidimensional databases

Peterson, Nina Marie. January 2006 (has links) (PDF)
Thesis (M.S.)--Washington State University, May 2006. / Includes bibliographical references (p. 81-83).

Educational issues in introductory tertiary biology /

Buntting, Catherine Michelle Nicole. January 2006 (has links)
Thesis (Ph.D.)--University of Waikato, 2006. / Includes bibliographical references (leaves 257-278)

Modeling and visualization of flexible protein-protein interactions

Siddavanahalli, Vinay Kiranshankar, January 1900 (has links) (PDF)
Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

GPU Based Methods for Interactive Information Visualization of Big Data

Mi, Peng 19 January 2016 (has links)
Interactive visual analysis has been a key component of gaining insights in information visualization area. However, the amount of data has increased exponentially in the past few years. Existing information visualization techniques lack scalability to deal with big data, such as graphs with millions of nodes, or millions of multidimensional data records. Recently, the remarkable development of Graphics Processing Unit (GPU) makes GPU useful for general-purpose computation. Researchers have proposed GPU based solutions for visualizing big data in graphics and scientific visualization areas. However, GPU based big data solutions in information visualization area are not well investigated. In this thesis, I concentrate on the visualization of big data in information visualization area. More specifically, I focus on visual exploration of large graphs and multidimensional datasets based on the GPU technology. My work demonstrates that GPU based methods are useful for sensemaking of big data in information visualization area. / Master of Science

Countering network level denial of information attacks using information visualization

Conti, Gregory John 27 March 2006 (has links)
We are besieged with information every day, our inboxes overflow with spam and our search queries return a great deal of irrelevant information. In most cases there is no malicious intent, just simply too much information. However, if we consider active malicious entities, the picture darkens. Denial of information (DoI) attacks assail the human through their computer system and manifest themselves as attacks that target the human's perceptual, cognitive and motor capabilities. By exploiting these capabilities, attackers reduce our ability to acquire and act upon desired information. Even if a traditional denial of service attack against a machine is not possible, the human utilizing the machine may still succumb to DoI attack. When successful, DoI attacks actively alter our decision making, often without our knowledge. In this dissertation, we address the problem of countering DoI attacks. We begin by presenting a taxonomy and framework of DoI attacks and countermeasures to add structure to the problem space. We then closely examine the use of information visualization as a countermeasure. Information visualization is a powerful technique that taps into the high bandwidth visual recognition capability of the human and is well suited to resist DoI attack. Unfortunately, most information visualization systems are designed without a clear emphasis on protecting the human from malicious activity. To address this issue we present a general framework for information visualization system security analysis. We then delve deeply into countering DoI in the network security domain using carefully crafted information visualization techniques to build a DoI attack resistant security visualization system. By creating such a system, we raise the bar on adversaries who now must cope with visualization enhanced humans in addition to traditional automated intrusion detection systems and text-based analysis tools. We conclude with a human-centric evaluation to demonstrate our systems effectiveness.

Display Techniques in Information-Rich Virtual Environments

Polys, Nicholas Fearing 31 July 2006 (has links)
Across domains, researchers, engineers, and designers are faced with large volumes of data that are heterogeneous in nature - including spatial, abstract, and temporal information. There are numerous design and technical challenges when considering the unification, management, and presentation of these information types. Most research and applications have focused on display techniques for each of the information types individually, but much less in known about how to represent the relationships between information types. This research explores the perceptual and usability impacts of data representations and layout algorithms for the next-generation of integrated information spaces. We propose Information-Rich Virtual Environments (IRVEs) as a solution to challenges of integrated information spaces. In this presentation, we will demonstrate the application requirements and foundational technology of IRVEs and articulate crucial tradeoffs in IRVE information design. We will present a design space and evaluation methodology to explore the usability effects of these tradeoffs. Experimental results will be presented for a series of empirical usability evaluations that increase our understanding of how these tradeoffs can be resolved to improve user performance. Finally, we interpret the results though the models of Information Theory and Human Information Processing to derive new conclusions regarding the role of perceptual cues in determining user performance in IRVEs. These lessons are posed as a set of design guidelines to aid developers of new IRVE interfaces and specifications. / Ph. D.

Smooth Interactive Visualization

Reach, Andrew McCaleb 08 September 2017 (has links)
Information visualization is a powerful tool for understanding large datasets. However, many commonly-used techniques in information visualization are not C^1 smooth, i.e. when represented as a function, they are either discontinuous or have a discontinuous first derivative. For example, histograms are a non-smooth visualization of density. Not only are histograms non-smooth visually, but they are also non-smooth over their parameter space, as they change abruptly in response to smooth change of bin width or bin offset. For large data visualization, histograms are commonly used in place of smooth alternatives, such as kernel density plots, because histograms can be constructed from data cubes, allowing histograms to be constructed quickly for large datasets. Another example of a non-smooth technique in information visualization is the commonly-used transition approach to animation. Although transitions are designed to create smooth animations, the transition technique produces animations that have velocity discontinuities if the target is changed before the transition has finished. The smooth and efficient zooming and panning technique also shares this problem---the animations produced are smooth while in-flight, but they have velocity discontinuities at the beginning and end and of the animation as well as velocity discontinuities when interrupted. This dissertation applies ideas from signal processing to construct smooth alternatives to these non-smooth techniques. To visualize density for large datasets, we propose BLOCs, a smooth alternative to data cubes that allows kernel density plots to be constructed quickly for large datasets after an initial preprocessing step. To create animations that are smooth even when interrupted, we present LTI animation, a technique that uses LTI filters to create animations that are smooth, even when interrupted. To create zooming and panning animations that are smooth, even when interrupted, we generalize signal processing systems to Riemannian manifolds, resulting in smooth, efficient, and interruptible animations. / Ph. D.

Teachers’ Understanding and Usage of Scientific Data Visualizations for Teaching Topics in Earth and Space Science

Connolly, Rachel Berger January 2019 (has links)
Scientific data visualizations are the products, and increasingly a core practice, of modern computational science across all domains. With recent science education standards emphasizing student engagement in practices, these scientific visualizations will only increase in their availability and use for K-12 science instruction. But teacher practice is key to the successful learning outcomes for these, and any, educational technology. This study follows eleven science teachers from initial exposure in a PD program through classroom use of scientific data visualizations that address topics in Earth and Space science. The framework of technological pedagogical content knowledge (TPCK) is used to examine key dimensions of teacher knowledge that are activated as they seek to understand the data visualizations and the conceptual models that they represent, select and integrate them into their curriculum, and ultimately use them for instruction. Baseline measures of select dimensions of TPCK are measured for all teachers. Two representative case studies allow for a deep analysis of TPCK in action throughout their professional and instructional experience, and finally the impact on teachers’ knowledge from the experience is examined, with implications for educative curricular material and PD program design.

Geo-temporal visualization for tourism data using color curves

In Kwon Choi (6623771) 10 June 2019 (has links)
A study on using colors to represent the floating population of tourists and local residents on the map by each hour in each month. The resulting visualization can assist the decision-making in various areas by providing a vivid description of the movement of people in a day.

Visualização computacional de música com suporte à discriminação de elementos de teoria musical / Computer display music with support discrimination of music theory

Cantareira, Gabriel Dias 17 December 2014 (has links)
A visualização computacional de informação é um campo em expansão por oferecer meios de se interpretar e analisar vários tipos de dados em grande quantidade e/ou de grande complexidade, compreendendo diversas técnicas e ferramentas para fornecer a um usuário formas de interagir e explorar conjuntos de dados a fim de se obter informações úteis ou importantes. A música, por sua vez, é um domínio complexo e de difícil estudo sob o ponto de vista computacional devido à análise de seu conteúdo possuir caráter muitas vezes subjetivo e dependente da interpretação humana. Embora vários trabalhos tenham sido publicados a respeito do assunto nos últimos anos, a maior parte das aplicações de visualização de informação relativas a música tende a analisar conjuntos de composições musicais a fim de agrupar ou classificar dados de acordo com algum tipo de critério. Assim, a visualização das informações contidas em uma única peça musical por si só é uma área que ainda pode ser melhor explorada, sobretudo visando compreender a informação musical envolvida o conteúdo extraído por um músico a partir de partituras e tablaturas. Esta dissertação relata o desenvolvimento de uma abordagem para visualização de dados musicais referentes a melodias em guitarra, com a capacidade de exibir elementos como variações de harmonia, melodia e tempo, tendo como objetivo auxiliar um músico (ou aprendiz de músico) na tarefa de interpretar tais dados. / Information visualization is an expanding research field due to its offering of novel approaches to analyze data of great size or complexity, referring to many techniques and tools in order to offer ways to interact and explore data sets to find important or useful information. Music is a domain of high complexity and hard to study and analyze by computer due to its sometimes subjective features, dependant of human interpretation. Although many research initiatives have been published regarding this subject recently, most of the music-related information visualization applications tend to analyze datasets composed by many different musical pieces, aiming to classify or group the data according to certain criteria. Thus, visualization of the information contained in a single musical piece is an area that still could be better explored, especially regarding to the comprehension of the musical information involved information extracted by a musician by reading musical scores. This document reports the development of a novel approach to musical data visualization based on electric guitar melodies, capable of showing elements such as harmony, melody and timing variations, aiming to aid a musician in the task of understanding such data.

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