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University of Houston

Academic institutionnorthamerica · us
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Research library446linked papers
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Selected work

Representative Papers

Assessing Cybersecurity Risks and Traffic Impact in Connected Autonomous Vehicles

Jun 13, 2024International Conference on Transportation and Development 2024

This study addresses the traffic efficiency and safety risks posed by cyberattacks that inject false information into connected and autonomous vehicles. To mitigate these threats, the authors propose a novel intelligent car-following model that enhances both safety and throughput by continuously monitoring the leading vehicle’s state and dynamically optimizing acceleration and deceleration decisions. Leveraging a high-fidelity simulation platform, the research constructs a realistic vehicular communication environment and representative cybersecurity attack scenarios to systematically evaluate the disruptive effects of falsified data on traffic flow. Experimental results demonstrate that the proposed approach significantly suppresses the propagation of malicious information, thereby effectively improving the robustness and stability of the overall traffic system.

4 citationsRead paper

Evaluating the Impact of COVID-19 on Transportation Infrastructure Funding in the United States

Aug 31, 2022International Conference on Transportation and Development 2022

This study addresses the significant decline in motor fuel consumption during the COVID-19 pandemic and its adverse impact on U.S. state-level transportation infrastructure funding, which heavily relies on fuel tax revenues. For the first time, the research integrates pandemic dynamics, fuel consumption patterns, and demographic data into a machine learning framework to quantify the long-term fiscal effects on state transportation budgets and forecast future trends. The proposed model demonstrates exceptional predictive performance at the state level (R² > 95%), accurately capturing fluctuations in fuel usage. Projections indicate that fuel tax revenues in several states are expected to remain 10%–15% below pre-pandemic levels for one to two years, providing policymakers with a data-driven foundation for strategic planning and fiscal adaptation.

2 citationsRead paper

Simulations of MRI Guided and Powered Ferric Applicators for Tetherless Delivery of Therapeutic Interventions

Jan 07, 2022International Conference Bioscience, Biochemistry and Bioinformatics

This work addresses the challenge of safely and precisely delivering untethered ferromagnetic therapeutic devices through vascular networks under MRI guidance by developing a real-time simulation platform that integrates vascular geometry, hemodynamics, and MRI physical constraints. Leveraging preoperative MRI data, the platform automatically reconstructs patient-specific vascular structures and introduces a novel virtual fixture mechanism to enforce safety boundaries, thereby preventing vessel damage. It incorporates user-defined blood flow models and accounts for MRI gradient field limitations to enable high-fidelity device navigation simulation. The system supports multithreaded real-time control, evaluates path feasibility, and generates gradient field commands compliant with MRI safety standards, offering reliable preoperative validation and operational guidance for subsequent in vivo experiments.

2 citationsRead paper

Two Deep Learning Approaches for Automated Segmentation of Left Ventricle in Cine Cardiac MRI

Jan 07, 2022International Conference Bioscience, Biochemistry and Bioinformatics

Accurate and robust automatic segmentation of the left ventricle in cardiac MRI is crucial for clinical diagnosis, yet existing methods still face challenges in precision and generalizability. This work proposes two novel U-Net variants, LNU-Net and IBU-Net, which incorporate layer normalization (LN) and instance-batch normalization (IBN), respectively, to enhance model stability and performance. To further improve generalization, the training pipeline integrates data augmentation through affine transformations and elastic deformations. Evaluated on a dataset comprising 45 patients and 805 short-axis cine MRI slices, the proposed methods consistently outperform current state-of-the-art approaches in key metrics, including the Dice coefficient and mean perpendicular distance, demonstrating their effectiveness and technical innovation in left ventricular segmentation.

2 citationsRead paper

Can Platform Design Encourage Curiosity? Evidence from an Independent Social Media Experiment

Jan 22, 2026

Social media platforms are often criticized for amplifying antisocial behaviors and lacking effective mechanisms to foster prosocial tendencies such as curiosity. This study addresses this gap by constructing an independent experimental platform and conducting a randomized controlled trial with 2,282 U.S. adults in a highly controlled environment. Using AI-driven virtual users to simulate authentic social interactions, the research systematically manipulated platform social norms and interface design. Findings demonstrate that curiosity-inducing interventions significantly increased users’ question-asking frequency and textual markers of curiosity while reducing toxic language. Although these interventions decreased generalized engagement metrics—such as likes and comments—they did not adversely affect subjective user experience or time spent creating content. The study thus provides causal evidence and a practical design pathway for promoting prosocial behavior on digital platforms.

1 citationsRead paper
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