UTSA Student Works
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Browsing UTSA Student Works by Department "Electrical and Computer Engineering"
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Item Advancing and Securing Human-Machine Chatbot Interactive Systems(2021-04-08) Nadim, MohammadItem Are eRNA functional?(2021-04-08) Paniagua, KarlaItem Best Practices to Foster Pre-service Teachers’ Science Content Knowledge(UTSA Office of Undergraduate Research, 2022-12) Salinas, PaulinaUnderstanding the science instruction approaches to pre-service teacher preparation is important to identify the effective features of these experiences and apply them to the design of new learning experiences. The main idea is that teachers often feel not prepared to teach science, and there are several research reports that teachers need opportunities to continue learning science as they prepare to teach it. Thus, it is important to identify the best practices and science learning experiences that can inform the preparation of teachers. Additionally, it is possible to understand the factors that include usefulness and perceived ease of technology as a special case in teacher preparation. Moreover, the focus of the literature review and revision of research work is to understand the affordances and limitations of different learning environments to support and provide a positive science learning experience to teachers with the intersection of science and technology as a particular case.Item CenTex FIRST Tech Challenge Conference 2023 Digest(2023-08-19)The CenTex FTC Conference, held at the University of Texas at San Antonio on August 19, 2023, was a vibrant gathering focused on igniting interest in robotics among high school students in central Texas. The conference was organized by the FTC team 16458, TechnoWizards, and centered on the innovative application of the FIRST Tech Challenge (FTC) program to inspire and engage young minds. Eight FTC teams hailing from Austin, University, San Antonio, and Laredo showcased their experiences and insights gained from participating in the 2022-2023 Power Play competition. Through a series of 14 presentations, attendees gained valuable knowledge and perspectives on robotics, enhancing their understanding and enthusiasm for STEM education.Item Fusion of Biometrics for Recognizing People(2021-04-08) Atapattu, TharinduItem Graphene Supercapacitors (People's Choice Award)(2021-04-08) Gopalakrishnan, PratheekItem Identifying Gamma Radiation Anomaly Signals Using Quantum Computation Methods(2022-07-28) Foate, Joshua; Valdez, Luis; Alamaniotis, MiltosCollected data using a radiation detector to identify anomalies in the presence of naturally occurring radioactive material. Samples of the anomaly signals were put into a Hopfield neural network to train the network to identify whether data from the detector was an anomaly or background radiation. Converting our data into a 3SAT (3- Satisfiability) problem and use Grover's algorithm to find the solutions for Hopfield Artificial Neural Network memoryItem Intelligent Anomaly Identification In Inverter-Based Cyber-Physical Systems(2021-04-08) Khan, Asad AliItem Inverse Reinforcement Learning(2021-04-08) Tao, FengItem Quantum Classification in Large Genomics Dataset (People's Choice Winner)(2023-10-18) Passo, SthefanieItem Role of AI in the Security of EV Charging Systems(2021-04-08) Nolan, ReithItem SSL4EO-L: Datasets and Foundation Models for Landsat Imagery(UTSA Graduate School, 2024-04-02) Stewart, Adam J.; Lehmann, Nils; Corley, Isaac A.; Wang, Yi; Ait Ali Braham, Nassim; Sehgal, Shradha; Robinson, Caleb; Banerjee, ArindamLandsat: Science, Petabytes, and SSL: [Figure] • Landsat's scientific significance and extended coverage • Petabytes of accessible Landsat imagery • Challenge: diverse sensors, varied wavelengths, and the lack of pre-trained models • Problem: scarcity of large labeled datasets • Solution: self-supervised learning (SSL)Item ZRG: A Dataset for Multimodal 3D Residential Rooftop Understanding(UTSA Graduate School, 2024-04-02) Corley, Isaac; Lwowski, Jonathan; Najafirad, PeymanRooftop Understanding: [Figure] The anatomy of a residential roof is complex. The understanding of rooftop geometry and structure has important real world applications including: ● Roof Damage Inspection & Detection ● Residential Solar Rooftop Potential ● 3D Modeling and Digital Twins Cities Dataset Acquisition: [Figure] ● Data acquired from over 20k residential roof inspections from across the United States using DJI drones ● Diverse: includes single and multi family homes (e.g. apartment complexes) from rural and urban locations ● Overhead and oblique imagery acquired for analyzing inspecting rooftops as well as performing multiview reconstruction to estimate rooftop structure and height