Category: Publications

Automatic Scatterplot Design Optimization For Clustering Identification

Posted on October 1, 2022April 16, 2024 by paul.a.rosen

In this paper, we propose an automatic tool to optimize the design factors of scatterplots to reveal the most salient cluster structure. Our approach leverages the merge tree data structure to identify the clusters and optimize the choice of subsampling algorithm, sampling rate, marker size, and marker opacity used to generate a scatterplot image.

AffectiveTDA: Using Topological Data Analysis to Improve Analysis and Explainability in Affective Computing

Posted on October 15, 2021April 16, 2024 by paul.a.rosen

We present an approach utilizing Topological Data Analysis to study the structure of face poses used in affective computing, i.e., the process of recognizing human emotion. The approach uses a conditional comparison of different emotions, both respective and irrespective of time, with multiple topological distance metrics, dimension reduction techniques, and face subsections (e.g., eyes, nose, mouth, etc.). Continue reading

CleanAirNowKC: Building Community Power by Improving Data Accessibility

Posted on October 12, 2021April 16, 2024 by paul.a.rosen

In this paper, we have implemented an interactive map that can help CleanAirNowKC community members to monitor air quality efficiently. The system also allows for reporting and tracking industrial emissions or toxic releases, which will further help identify major contributors to pollution. These resources can serve an important role as evidence that will assist in advocating for community-driven just policies to improve the air quality regulation in Kansas City. Continue reading

Through The Looking Glass: Insights Into Visualization Pedagogy Through Sentiment Analysis Of Peer Review Text

Posted on September 2, 2021April 16, 2024 by paul.a.rosen

We discuss the construction and application of peer review in two visualization courses from different colleges at the University of South Florida. We then analyze student projects and peer review text via sentiment analysis to infer insights for visualization educators, including the focus of course content, engagement across student groups, student mastery of concepts, course trends over time, and expert intervention effectiveness. Continue reading

Polarity In The Classroom: An Application Leveraging Peer Sentiment Towards Scalable Assessment

Posted on September 2, 2021April 16, 2024 by paul.a.rosen

In this work, we detail the process by which we create our domain-dependent lexicon and aspect-informed review form as well as our entire sentiment analysis algorithm which provides a fine-grained sentiment score from text alone. We analyze the validity from our corpus of over 6800 peer reviews from nine courses to understand the viability of sentiment in the classroom for increasing the information from and reliability of grading open-ended assignments in large courses. Continue reading

A Survey Of Perception-Based Visualization Studies By Task

Posted on August 16, 2021April 16, 2024 by paul.a.rosen

In this report, we provide a systematic and comprehensive review of research studies on perception related to visualization. This survey reviews perception-focused visualization studies since 1980 and summarizes their research developments focusing on low-level tasks, further breaking techniques down by visual encoding and visualization type. Continue reading

Inferring Quality In Point Cloud-Based Three-Dimensional Objects Using Topographical Data Analysis

Posted on April 10, 2021April 16, 2024 by paul.a.rosen

This patent describes a technique for assessing the quality of point-cloud datasets for 3D printing using Topological Data Anaylsis.

Fast And Scalable Complex Network Descriptor Using Pagerank And Persistent Homology

Posted on December 1, 2020April 16, 2024 by paul.a.rosen

In this article we use the PageRank function along with persistent homology to obtain a scalable graph descriptor and utilize it to compare the similarities between graphs. Continue reading

Parallel Mapper

Posted on November 1, 2020April 16, 2024 by paul.a.rosen

In this paper, we study the parallel analysis of the construction of Mapper. We give a provably correct parallel algorithm to execute Mapper on a multiple processors. Our algorithm relies on a divide and conquer strategy for the codomain cover which gets pulled back to the domain cover.

An Efficient Data Retrieval Parallel Reeb Graph Algorithm

Posted on October 15, 2020April 16, 2024 by paul.a.rosen

We propose a parallel augmented Reeb graph algorithm on triangulated meshes with and without a boundary. That is, in addition to our parallel algorithm for computing a Reeb graph, we describe a method for extracting the original manifold data from the Reeb graph structure.