Computer Science Focus on Research
When: Monday, October 07, 2019
Where: PGH 563
Time: 11:00 AM
Focus on Research (FoR) is an opportunity for any COSC PhD student to discuss a research project (with or without preliminary results), a conference dry run, or any research topic of interest to present to an audience of peers and faculty. It is a great avenue for PhD students to practice presentation skills in front of a larger and broader audience.
SMACK: Subjective Measure of Applied Contextual Knowledge
Mohammed Alshair, Ph.D. Student
Abstract:
We developed an augmented reality [AR] application in Microsoft’s HoloLens platform to investigate if an AR-based assessment tool better assesses a student’s real-world knowledge and skill compared to a traditional, pen-and-paper-based assessment. The AR-based assessment focused on applying knowledge to contextually subjective problems while the traditional assessment required recalling knowledge in unchanging, deterministic problems.
Under our AR-based simulated construction scene, participants, 18 students enrolled in a Construction Management Safety course, were required to visually inspect the scene, correctly identify unsafe conditions, and justify their selections in a multiple-choice setting. After their AR-based assessment, they were required to complete a post-survey and a debrief. Also, they were required to complete the traditional assessment and presurvey before the AR-based assessment. Our study demonstrated that the participants preferred the AR-based assessment over the traditional assessment. However, they had higher performance ratings in the traditional assessment than the AR-based assessment.Bio:
Mohammed Alshair is a Ph.D. student at the University of Houston. His advisors are Dr. Chang Yun and Dr. Jaspal Subhlok. He finds it beneficial to use innovative technologies such as augmented and virtual realities in all sectors, for example, medicine, education, engineering, etc. Moreover, that is why his main interest is solving problems using these different realities regarding training, treatment, assisting, and education, to name a few.
Unsteady Flow Visualization via Physics Based Pathline Exploration
Duong Nguyen, Ph.D. Student
Abstract:
Most existing unsteady flow visualization techniques concentrate on the depiction of geometric patterns in flow, assuming the geometry information provides sufficient representation of the underlying physical characteristics, which is not always the case. To address this challenge, this work proposes to analyze the time-dependent characteristics of the physical attributes measured along pathlines which can be represented as a series of time activity curves (TAC). We demonstrate that the temporal trends of these TACs can convey the relation between pathlines and certain well-known flow features (e.g., vortices and shearing layers), which enables us to select pathlines that can effectively represent the physical characteristics of interest and their temporal behavior in the unsteady flow. Inspired by this observation, a new TAC-based unsteady flow visualization and analysis framework is proposed.
The center of this framework is a new event-based distance metric (EDM) that compares the similarity of two TACs, from which a new spatio-temporal, hierarchical clustering that classifies pathlines based on their physical attributes and a TAC-based pathline exploration and selection strategy are proposed. A visual analytic system incorporating the TAC-based pathline clustering and exploration is developed, which also provides new visualizations to support the user exploration of unsteady flow using TACs. The new system successfully reveals the detailed structure of vortices, the relation between shear layer and vortex formation, and vortex breakdown, which are difficult to convey with conventional methods.
Bio:
Duong Nguyen is a 4th-year Ph.D. student of Computer Science at the University of Houston. He is working with Professor Guoning Chen on the large-scale scientific data analysis and visualization. He received his Bachelor’s degree in Computer Science from Vietnam National University, Ha Noi.
Impact of Hex-Mesh Structure on Simulation Quality - A First Study
Muhammad Naeem Akram, Ph.D. student
Abstract:
It has been shown that the element quality of a hexahedral mesh has direct impact on the quality of simulations performed on it. However, there is little study about how the structure of a hex-mesh impacts the quality of simulations. In our research study, we aim to access how the structures of different hex-meshes of same volume will affect the same simulation performed on them. For this purpose, we generate hex-meshes with different structures and evaluate them based on two types of simulations ran on them: elliptic PDEs and stress tensor simulations.
Bio:
Muhammad Naeem Akram is a 2nd year Ph.D. student in Computer Science at University of Houston. His research is supervised by Dr. Guoning Chen and his research interest focuses on the generation and optimization of hexahedral meshes.