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.

The purpose of this thesis is to develop a system for folding an origami model using computer generated, or virtual, paper. This research is detailed according to both the creative and technical aspects of that process, with particular attention given to formulating a solution for animating the paper in a way that is physically realistic. The project is executed in Autodesk Maya, a 3D computer graphics program, and rendered with mental ray, a production quality rendering software. The final results are illustrated via excerpts from When Pigs Fly…, an original 3D short which uses the developed methodology to give life to an origami-based narrative. The techniques employed in this thesis can provide a valuable framework for other artists embarking on similar productions and supply a foundation for more advanced problems related to folding and computer graphics.

Influenced by synesthesia, the creators of such ‘visual musics’ as abstract art, color organs, abstract film, and most recently visualizers, have attempted to illustrate correspondences between the senses. This thesis attempts to develop a framework for music visualization founded on emotional analogues between visual art and music. The framework implements audio signal spectrum analysis, mood modeling, and color theory to produce pertinent data for use in visualizations. The research is manifest as a computer program that creates a simple visualizer. Built in Max/MSP/Jitter, a programming environment especially for musical and multimedia processing, it analyzes data and produces images in real-time. The program employs spectrum analysis to extract musical data such as loudness, brightness, and note attacks from the audio signals of AIFF song files. These musical features are used to calculate the Energy and Stress of the song, which determine the general mood of the music. The mood can fall into one of the four general categories of Exuberance, Contentment, Depression, and Anxious/Frantic. This method of automatic mood classification resulted in an eighty-five percent accuracy rate. Applying color expression theory yields a color palette that reflects the musical mood. The color palette and the musical features are then supplied to four different animation schemes to produce visuals. The visualizer generates shapes and forms in a three-dimensional environment and animates them in response to the real-time musical data. The visualizer allows user input to actively direct the creation of a variety of different visualizations. This personalization of the synesthetic effects of the visualizer invites the viewer to actively consider his or her own unique associations and facilitates understanding of the phenomenon of synesthesia and sensory fusion.

The goals of this research include developing and identifying software technologies, which facilitate the use of buildings described in Building Information Modeling (BIM) tools in both a simulation and visualization. The study focused on the development of a tool to fulfill the visualization needs of a Visual Energy Use System. To accomplish this, the study identified an open BIM file standard, the Industry Foundation Classes (IFC). The study also identified a video game based 3D virtual environment, the Doom 3 Engine. A tool developed during the study, IFCtoMAP, converts IFC data into the .MAP file format understood by the Doom 3 Engine. Finally, the study identified the IFCtoIDF utility, which translates IFC data into a format understood by the building energy simulation program EnergyPlus. Data from the Building Information Modeling tool Revit Building exports to the .IFC file format, which in turn drives the two conversion utilities IFCtoMAP and IFCtoIDF. The output of the IFCtoIDF tool consists of an .IDF file that EnergyPlus uses to perform an energy simulation. The output of the IFCtoMAP tool consists of a .MAP file, which the Doom 3 game engine uses to display three dimensional first person perspective visualization. The result of the study was the successful creation of an automated tool that converts building geometry found in .IFC files into the .MAP file format understood by Doom 3 game engine. This document details the methods employed by the IFCtoMAP software along with a brief discussion of the IFCtoIDF conversion utility.

In visualization problems, surface shape is often a piece of data that must be shown effectively. One factor that strongly affects shape perception is texture. For example, patterns of texture on a surface can show the surface orientation from foreshortening or compression of the texture marks, and surface depth through size variation from perspective projection. However, texture is generally under-used in the scientific visualization community. The benefits of using texture on single surfaces also apply to layered surfaces. Layering of multiple surfaces in a single viewpoint allows direct comparison of surface shape. The studies presented in this dissertation aim to find optimal methods for texturing of both single and layered surfaces. This line of research starts with open, many-parameter experiments using human subjects to find what factors are important for optimal texturing of layered surfaces. These experiments showed that texture shape parameters are very important, and that texture brightness is critical so that shading cues are available. Also, the optimal textures seem to be task dependent; a feature finding task needed relatively little texture information, but more shape-dependent tasks needed stronger texture cues. In visualization problems, surface shape is often a piece of data that must be shown effectively. One factor that strongly affects shape perception is texture. For example, patterns of texture on a surface can show the surface orientation from foreshortening or compression of the texture marks, and surface depth through size variation from perspective projection. However, texture is generally under-used in the scientific visualization community. The benefits of using texture on single surfaces also apply to layered surfaces. Layering of multiple surfaces in a single viewpoint allows direct comparison of surface shape. The studies presented in this dissertation aim to find optimal methods for texturing of both single and layered surfaces. This line of research starts with open, many-parameter experiments using human subjects to find what factors are important for optimal texturing of layered surfaces. These experiments showed that texture shape parameters are very important, and that texture brightness is critical so that shading cues are available. Also, the optimal textures seem to be task dependent; a feature finding task needed relatively little texture information, but more shape-dependent tasks needed stronger texture cues.

A new technique, called the polymerization algorithm, is described for the hierarchical segmentation of polymerized volume data sets (PVDS) using the Lblock data structure. The Lblock data structure is defined as a 3dimensional isorectangular block of enhanced vertex information. Segmentation of the PVDS is attained by intersecting and merging Lblock coverings of the enhanced volumetric data. The data structure allows for easy compression, storage, segmentation, and reconstruction of volumetric data obtained from scanning a mammalian brain at submicron resolution, using threedimensional light microscopy (knifeedge scanning microscopy (KESM), confocal microscopy (CFM), and multiphoton microscopy (MPM)). A hybrid technique using the polymerization algorithm and an existing vectorbased tracing algorithm is developed. Both the polymerized and the hybrid algorithm have been tested and their analyzed results are presented.

Past educational studies reveal that students have difficulty making the connection between the mathematical and analytical models used to describe building behavior and the behavior itself. This thesis examines the development and use of visual simulation software as a tool to help students create connections between abstract mathematical models and the real world. A framework for the software was designed and implemented, enabling students to interactively construct, analyze, and evaluate models within a single environment. The software was tested by students in an undergraduate dynamics course to assess its effectiveness as a learning tool. Results are presented through scenarios that demonstrate the extensibility and flexibility of the framework and an analysis of student responses from the Student Assessment of Learning Gains instrument.

Advancement in high-throughput microscopy technology such as the Knife-Edge Scanning Microscopy (KESM) is enabling the production of massive amounts of high-resolution and high-quality volumetric data of biological microstructures. To fully utilize these data, they should be efficiently distributed to the scientific research community through the Internet and should be easily visualized, annotated, and analyzed. Given the volumetric nature of the data, visualizing them in 3D is important. However, since we cannot assume that every end user has high-end hardware, an approach that has minimal hardware and software requirements will be necessary, such as a standard web browser running on a typical personal computer. There are several web applications that facilitate the viewing of large collections of images. Google Maps and Google Maps-like interfaces such as Brainmaps.org allow users to pan and zoom 2D images efficiently. However, they do not yet support the rendering of volumetric data in their standard web interface. The goal of this thesis is to develop a light-weight volumetric image viewer using existing web technologies such as HTML, CSS and JavaScript while exploiting the properties of stereo vision to facilitate the viewing and annotations of volumetric data. The choice of stereogram over other techniques was made since it allows the usage of raw image stacks produced by the 3D microscope without any extra computation on the data at all. Operations to generate stereo images using 2D image stacks include distance attenuation and binocular disparity. By using HTML and JavaScript that are computationally cheap, we can accomplish both tasks dynamically in a standard web browser, by overlaying the images with intervening semi-opaque layers. The annotation framework has also been implemented and tested. In order for annotation to work in this environment, it should also be in the form of stereogram and should aid the merging of stereo pairs. The current technique allows users to place a mark (dot) on one image stack, and its projected position onto the other image stack is calculated dynamically on the client side. Other extra metadata such as textual descriptions can be entered by the user as well. To cope with the occlusion problem caused by changes in the z direction, the structure traced by the user will be displayed on the side, together with the data stacks. Using the same stereo-gram creation techniques, the traces made by the user is dynamically generated and shown as stereogram. We expect the approach presented in this thesis to be applicable to a broader scientific domain, including geology and meteorology.

<p>OpenModelica is a complete environment for developing and simulatingModelica models based on free software. It is promoted and developed bythe OpenModelica Consortium. This thesis details a method for describingand consequently displaying visualizations of Modelica models in OMNote-book, an application in the OpenModelica suite where models can be writtenand simulated in a document mixed with text, images and plots. Two dif-ferent approaches are discussed; one based on Modelica annotations and onebased on creating a simple object hierarchy which can be connected to exist-ing models. Trial implementations are done which make it possible to discardthe annotation approach, and show that an object based solution is the onebest suited for a complete implementation. It is expanded into a working 3Dvisualization solution, embedded in OMNotebook.</p>

Thesis (M.S.)--West Virginia University, 2002. / Title from document title page. Document formatted into pages; contains iii, 72 p. Includes abstract. Includes bibliographical references.