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Cluster metrics and temporal coherency in pixel based matrices

Description

In this thesis, the application of pixel-based vertical axes used within parallel coordinate plots is explored in an attempt to improve how existing tools can explain complex multivariate interactions across temporal data. Several promising visualization techniques are combined, such as:

In this thesis, the application of pixel-based vertical axes used within parallel coordinate plots is explored in an attempt to improve how existing tools can explain complex multivariate interactions across temporal data. Several promising visualization techniques are combined, such as: visual boosting to allow for quicker consumption of large data sets, the bond energy algorithm to find finer patterns and anomalies through contrast, multi-dimensional scaling, flow lines, user guided clustering, and row-column ordering. User input is applied on precomputed data sets to provide for real time interaction. General applicability of the techniques are tested against industrial trade, social networking, financial, and sparse data sets of varying dimensionality.

Contributors

Agent

Created

Date Created
2014

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Visual analytics for spatiotemporal cluster analysis

Description

Traditionally, visualization is one of the most important and commonly used methods of generating insight into large scale data. Particularly for spatiotemporal data, the translation of such data into a visual form allows users to quickly see patterns, explore summaries

Traditionally, visualization is one of the most important and commonly used methods of generating insight into large scale data. Particularly for spatiotemporal data, the translation of such data into a visual form allows users to quickly see patterns, explore summaries and relate domain knowledge about underlying geographical phenomena that would not be apparent in tabular form. However, several critical challenges arise when visualizing and exploring these large spatiotemporal datasets. While, the underlying geographical component of the data lends itself well to univariate visualization in the form of traditional cartographic representations (e.g., choropleth, isopleth, dasymetric maps), as the data becomes multivariate, cartographic representations become more complex. To simplify the visual representations, analytical methods such as clustering and feature extraction are often applied as part of the classification phase. The automatic classification can then be rendered onto a map; however, one common issue in data classification is that items near a classification boundary are often mislabeled.

This thesis explores methods to augment the automated spatial classification by utilizing interactive machine learning as part of the cluster creation step. First, this thesis explores the design space for spatiotemporal analysis through the development of a comprehensive data wrangling and exploratory data analysis platform. Second, this system is augmented with a novel method for evaluating the visual impact of edge cases for multivariate geographic projections. Finally, system features and functionality are demonstrated through a series of case studies, with key features including similarity analysis, multivariate clustering, and novel visual support for cluster comparison.

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Agent

Created

Date Created
2016

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Students' understanding of weathering and erosion

Description

Conceptual change has been a large part of science education research for several decades due to the fact that it allows teachers to think about what students' preconceptions are and how to change these to the correct scientific conceptions. To

Conceptual change has been a large part of science education research for several decades due to the fact that it allows teachers to think about what students' preconceptions are and how to change these to the correct scientific conceptions. To have students change their preconceptions teachers need to allow students to confront what they think they know in the presence of the phenomena. Students then collect and analyze evidence pertaining to the phenomena. The goal in the end is for students to reorganize their concepts and change or correct their preconceptions, so that they hold more accurate scientific conceptions. The purpose of this study was to investigate how students' conceptions of the Earth's surface, specifically weathering and erosion, change using the conceptual change framework to guide the instructional decisions. The subjects of the study were a class of 25 seventh grade students. This class received a three-week unit on weathering and erosion that was structured using the conceptual change framework set by Posner, Strike, Hewson, and Gertzog (1982). This framework starts by looking at students' misconceptions, then uses scientific data that students collect to confront their misconceptions. The changes in students' conceptions were measured by a pre concept sketch and post concept sketch. The results of this study showed that the conceptual change framework can modify students' preconceptions of weathering and erosion to correct scientific conceptions. There was statistical significant difference between students' pre concept sketches and post concept sketches scores. After examining the concept sketches, differences were found in how students' concepts had changed from pre to post concept sketch. Further research needs to be done with conceptual change and the geosciences to see if conceptual change is an effective method to use to teach students about the geosciences.

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Agent

Created

Date Created
2011

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Experience in data quality assessment on archived historical freeway traffic data

Description

Concern regarding the quality of traffic data exists among engineers and planners tasked with obtaining and using the data for various transportation applications. While data quality issues are often understood by analysts doing the hands on work, rarely are the

Concern regarding the quality of traffic data exists among engineers and planners tasked with obtaining and using the data for various transportation applications. While data quality issues are often understood by analysts doing the hands on work, rarely are the quality characteristics of the data effectively communicated beyond the analyst. This research is an exercise in measuring and reporting data quality. The assessment was conducted to support the performance measurement program at the Maricopa Association of Governments in Phoenix, Arizona, and investigates the traffic data from 228 continuous monitoring freeway sensors in the metropolitan region. Results of the assessment provide an example of describing the quality of the traffic data with each of six data quality measures suggested in the literature, which are accuracy, completeness, validity, timeliness, coverage and accessibility. An important contribution is made in the use of data quality visualization tools. These visualization tools are used in evaluating the validity of the traffic data beyond pass/fail criteria commonly used. More significantly, they serve to educate an intuitive sense or understanding of the underlying characteristics of the data considered valid. Recommendations from the experience gained in this assessment include that data quality visualization tools be developed and used in the processing and quality control of traffic data, and that these visualization tools, along with other information on the quality control effort, be stored as metadata with the processed data.

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Agent

Created

Date Created
2011

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A visualization dashboard for Muslim social movements

Description

Muslim radicalism is recognized as one of the greatest security threats for the United States and the rest of the world. Use of force to eliminate specific radical entities is ineffective in containing radicalism as a whole. There is a

Muslim radicalism is recognized as one of the greatest security threats for the United States and the rest of the world. Use of force to eliminate specific radical entities is ineffective in containing radicalism as a whole. There is a need to understand the origin, ideologies and behavior of Radical and Counter-Radical organizations and how they shape up over a period of time. Recognizing and supporting counter-radical organizations is one of the most important steps towards impeding radical organizations. A lot of research has already been done to categorize and recognize organizations, to understand their behavior, their interactions with other organizations, their target demographics and the area of influence. We have a huge amount of information which is a result of the research done over these topics. This thesis provides a powerful and interactive way to navigate through all this information, using a Visualization Dashboard. The dashboard makes it easier for Social Scientists, Policy Analysts, Military and other personnel to visualize an organization's propensity towards violence and radicalism. It also tracks the peaking religious, political and socio-economic markers, their target demographics and locations. A powerful search interface with parametric search helps in narrowing down to specific scenarios and view the corresponding information related to the organizations. This tool helps to identify moderate Counter-Radical organizations and also has the potential of predicting the orientation of various organizations based on the current information.

Contributors

Agent

Created

Date Created
2012

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Designing tools to increase group awareness in the work place

Description

This thesis investigates the role of activity visualization tools in increasing group awareness at the workspace. Today, electronic calendaring tools are widely used in the workplace. The primary function is to enable each person maintain a work schedule. They also

This thesis investigates the role of activity visualization tools in increasing group awareness at the workspace. Today, electronic calendaring tools are widely used in the workplace. The primary function is to enable each person maintain a work schedule. They also are used to schedule meetings and share work details when appropriate. However, a key limitation of current tools is that they do not enable people in the workplace to understand the activity of the group as a whole. A tool that increases group awareness would promote reflection; it would enable thoughtful engagement with one's co-workers. I have developed two tools: the first tool enables the worker to examine detailed task information of one's own tasks, within the context of his/her peers' anonymized task data. The second tool is a public display to promote group reflection. I have used an iterative design methodology to refine the tools. I developed ActivityStream desktop tool that enables users to examine the detailed information of their own activities and the aggregate information of other peers' activities. ActivityStream uses a client-server architecture. The server collected activity data from each user by parsing RSS feeds associated with their preferred online calendaring and task management tool, on a daily basis. The client software displays personalized aggregate data and user specific tasks, including task types. The client display visualizes the activity data at multiple time scales. The activity data for each user is represented though discrete blocks; interacting with the block will reveal task details. The activity of the rest of the group is anonymized and aggregated. ActivityStream visualizes the aggregated data via Bezier curves. I developed ActivityStream public display that shows a group people's activity levels change over time to promote group reflection. In particular, the public display shows the anonymized task activity data, over the course of one year. The public display visualizes data for each user using a Bezier curve. The display shows data from all users simultaneously. This representation enables users to reflect on the relationships across the group members, over the course of one year. The survey results revealed that users are more aware of their peers' activities in the workspace.

Contributors

Agent

Created

Date Created
2010

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A comparison of the effects of imagery and action observation on baseball batting performance

Description

This study investigated the effect of two different preparation methods on hitting performance in a high&ndashfidelity; baseball batting simulation. Novice and expert players participated in one of three conditions: observation (viewing a video of the goal action), visualization (hearing a

This study investigated the effect of two different preparation methods on hitting performance in a high&ndashfidelity; baseball batting simulation. Novice and expert players participated in one of three conditions: observation (viewing a video of the goal action), visualization (hearing a script of the goal action), or a no&ndashpreparation; control group. Each participant completed three different hitting tasks: pull hit, opposite&ndashfield; hit, and sacrifice fly. Experts had more successful hits, overall, than novices. The number of successful hits was significantly higher for both the observation and visualization conditions than for the control. In most cases, performance was best in the observation condition. Experts demonstrated greater effects from the mental preparation techniques compared to novices. However, these effects were mediated by task difficulty. The difference between experts and novices, as well as the difference between the observation and visualization conditions was greater for the more difficult hitting task (opposite&ndashfield; hitting) than for the easier hitting task (sacrifice fly). These effects of mental preparation were associated with significant changes in batting kinematics (e.g., changes in point of bat/ball contact and swing direction). The results indicate that mental preparation can improve directional hitting ability in baseball with the optimal preparation methods depending on skill&ndashlevel; and task difficulty.

Contributors

Agent

Created

Date Created
2010

Designing a Digital Humanities Project Presentation

Description

Elizabeth Grumbach, the project manager of the Institute for Humanities Research's Digital Humanities Initiative, shares methodologies and best practices for designing a digital humanities project. The workshop will offer participants an introduction to digital humanities fundamentals, specifically tools and methodologies.

Elizabeth Grumbach, the project manager of the Institute for Humanities Research's Digital Humanities Initiative, shares methodologies and best practices for designing a digital humanities project. The workshop will offer participants an introduction to digital humanities fundamentals, specifically tools and methodologies. Participants explore technologies and platforms that allow scholars of all skills levels to engage with digital humanities methods. Participants will be introduced to a variety of tools (including mapping, visualization, data analytics, and multimedia digital publication platforms), and how and why to choose specific applications, platforms, and tools based on project needs.

Contributors

Agent

Created

Date Created
2018-09-26

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Firewall rule set analysis and visualization

Description

A firewall is a necessary component for network security and just like any regular equipment it requires maintenance. To keep up with changing cyber security trends and threats, firewall rules are modified frequently. Over time such modifications increase the complexity,

A firewall is a necessary component for network security and just like any regular equipment it requires maintenance. To keep up with changing cyber security trends and threats, firewall rules are modified frequently. Over time such modifications increase the complexity, size and verbosity of firewall rules. As the rule set grows in size, adding and modifying rule becomes a tedious task. This discourages network administrators to review the work done by previous administrators before and after applying any changes. As a result the quality and efficiency of the firewall goes down.

Modification and addition of rules without knowledge of previous rules creates anomalies like shadowing and rule redundancy. Anomalous rule sets not only limit the efficiency of the firewall but in some cases create a hole in the perimeter security. Detection of anomalies has been studied for a long time and some well established procedures have been implemented and tested. But they all have a common problem of visualizing the results. When it comes to visualization of firewall anomalies, the results do not fit in traditional matrix, tree or sunburst representations.

This research targets the anomaly detection and visualization problem. It analyzes and represents firewall rule anomalies in innovative ways such as hive plots and dynamic slices. Such graphical representations of rule anomalies are useful in understanding the state of a firewall. It also helps network administrators in finding and fixing the anomalous rules.

Contributors

Agent

Created

Date Created
2014

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Controversy analysis: clustering and ranking polarized networks with visualizations

Description

US Senate is the venue of political debates where the federal bills are formed and voted. Senators show their support/opposition along the bills with their votes. This information makes it possible to extract the polarity of the senators. Similarly, blogosphere

US Senate is the venue of political debates where the federal bills are formed and voted. Senators show their support/opposition along the bills with their votes. This information makes it possible to extract the polarity of the senators. Similarly, blogosphere plays an increasingly important role as a forum for public debate. Authors display sentiment toward issues, organizations or people using a natural language.

In this research, given a mixed set of senators/blogs debating on a set of political issues from opposing camps, I use signed bipartite graphs for modeling debates, and I propose an algorithm for partitioning both the opinion holders (senators or blogs) and the issues (bills or topics) comprising the debate into binary opposing camps. Simultaneously, my algorithm scales the entities on a univariate scale. Using this scale, a researcher can identify moderate and extreme senators/blogs within each camp, and polarizing versus unifying issues. Through performance evaluations I show that my proposed algorithm provides an effective solution to the problem, and performs much better than existing baseline algorithms adapted to solve this new problem. In my experiments, I used both real data from political blogosphere and US Congress records, as well as synthetic data which were obtained by varying polarization and degree distribution of the vertices of the graph to show the robustness of my algorithm.

I also applied my algorithm on all the terms of the US Senate to the date for longitudinal analysis and developed a web based interactive user interface www.PartisanScale.com to visualize the analysis.

US politics is most often polarized with respect to the left/right alignment of the entities. However, certain issues do not reflect the polarization due to political parties, but observe a split correlating to the demographics of the senators, or simply receive consensus. I propose a hierarchical clustering algorithm that identifies groups of bills that share the same polarization characteristics. I developed a web based interactive user interface www.ControversyAnalysis.com to visualize the clusters while providing a synopsis through distribution charts, word clouds, and heat maps.

Contributors

Agent

Created

Date Created
2015