7903 research outputs found
Sort by
Santa Clara Radio Astronomy Project IV: Data Acquisition
No full textSanta Clara Radio Astronomy Project (SCRAP) is a multi-year project that aims to make radio astronomy accessible to the Santa Clara University community. Previous iterations have focused on constructing and improving a parabolic radio telescope located on the balcony of the fourth floor at The Sobrato Campus for Discovery and Innovation at Santa Clara University. Until this year, the radio telescope has been stationary. As a consequence, the telescope is only capable of observing celestial objects directly above it, severely limiting the data capture area. This thesis describes the contributions of SCRAP IV Data Acquisition to the project: enabling 2D scanning through a rotational system. This thesis will describe the defined objectives, subsystems, integration and results of the addition of the rotation system. The addition of a rotational system greatly increases the opportunities of the telescope, allowing users to collect significantly more data as well as track specific celestial events
The GRD Companion
No full textThis project introduces the design and development of the GRD Companion. This gesture-controlled reminder device aims to support individuals with special needs in their daily routines, in the hope of them being more independent. The system we designed integrates a Raspberry Pi Zero 2 W, PAJ7620U2 gesture sensor, and audio playback components, all housed in a custom 3D-printed case. Some of our key design priorities included accessibility by relying only on gesture recognition to control the device, eliminating screens and buttons, as well as portability, enabling all users to carry the device anywhere. The device is paired with our WaveLink App, which allows teachers and caregivers to record personalized audio tasks for the user and send them to the device when paired via Bluetooth or WIFI hotspot. We chose to code using Python for gesture recognition and a scheduling logic to manage the hardware interactions within the device. The project emphasizes affordability, usability, and adaptability to help support teachers and caregivers in aiding individuals with special needs. Human subject testing was conducted to gain feedback to help guide improvements and confirmed the functionality and reliability of our device. Future iterations include expanding on customization features such as custom gesture recognition, a reward system, and real-time task completion
Vector Extension on a RISC-V CPU
No full textElectricians face significant health and safety hazards when inspecting drop ceilings, including exposure to dust, asbestos, and the risk of falls. To address these challenges, this project proposes a lightweight, autonomous robot capable of inspecting drop ceilings and assisting with wire tracing tasks—thereby distancing electricians from hazardous environments. The robot employs tread-based mobility to navigate fragile ceiling panels, integrated ultrasonic sensors and bumpers for obstacle avoidance, and an antenna system to detect and follow energized wire signals. Visual feedback is provided to the operator through a real-time video feed over a secure NoMachine interface, with manual and semi-autonomous operation modes supported. The system incorporates both hardware-based and digital signal filtering to isolate desired wire signals. Testing in a simulated drop ceiling environment demonstrated the robot’s ability to traverse obstacles, detect target signals, and operate effectively in low-light conditions. This solution has the potential to enhance workplace safety and efficiency for electricians performing drop ceiling inspections
Bilingual Buddy
No full textBilingual students often face challenges in mathematics not due to a lack of ability, but because of linguistic barriers that hinder their understanding of math-specific terminology and consequently their problem-solving language ability. This project addresses that issue through the development of a mobile application designed to support English language acquisition in the context of mathematics for Spanish-speaking students. Rather than teaching mathematical concepts directly, the app focuses on vocabulary, syntax, and contextual comprehension through scaffolded lessons, gamified elements, and an integrated AI chatbot.
Built using Flutter for cross-platform compatibility, the app prioritizes accessibility, simplicity, and engagement for young users. Ethical considerations such as data privacy and age-appropriate content are incorporated into the AI support system, which provides vocabulary hints and language feedback without evaluative functions. Evaluation with real users will inform future iterations and potential expansion to additional language pairs or subject domains. This project aims to fill a critical gap in educational technology by bridging math education and language learning, ultimately promoting equity and confidence among bilingual learners
Mapping Resilience and Community Through Transformed Green Spaces in Santa Clara
No full textThis study builds on existing research showing that green spaces are vital multifunctional solutions that promote both community well-being and climate adaptation. By integrating social and environmental vulnerability into the framework, the GsSVI offers a more holistic approach to resilience—one that centers justice, equity, diversity, and inclusion, while addressing exposure to extreme heat.
In alignment with item C-2-1 (Climate Resilient Land Use & Development) of the City of Santa Clara’s Climate Action Plan (CAP), this research analyzes the social, economic, and environmental vulnerabilities across Santa Clara through a Green Space Social Vulnerability Index (GsSVI), highlighting high-risk areas. The Priority Index categorizes these vulnerabilities from 1 (Most Vulnerable) to 5 (Least Vulnerable).
The findings support transforming high-vulnerability sites into green spaces and guide equity-centered planning decisions. These tools can empower communities to make informed, self-determined land use choices
Am I a Scientist? Using Pláticas to Understand Stem Identity Development Among High School Latinx Students in Advanced Science Classes
No full textThis qualitative study explores how Latinx students experience Advanced Placement (AP) and Honors science classes in high school, and how these experiences shape their STEM identity. Despite making up the largest demographic group at Solaris High School in Northern California, Latinx students are significantly underrepresented in advanced science courses. Using a pláticas methodology grounded in Critical Race Theory (CRT), Latinx Critical Race Theory (LatCrit), and Community Cultural Wealth (CCW), this study centers student voice to understand how systemic problems, such as tracking and deficit thinking, impact students’ access to and navigation of rigorous science classes. The study includes individual and communal pláticas with eight Latinx high school graduates who completed at least one AP or Honors science class.
Findings reveal that while students often enjoyed their science classes and received affirming support from some educators, students did not internalize a STEM identity due to lack of representation, microaggressions, and limited exposure to an inclusive definition of what it means to be a scientist. Educators’ actions played a pivotal role in shaping students’ selfperception as scientists. The study offers implications for practice, including more inclusive course recruitment and support structures that validate Latinx students’ experiences and aspirations. Ultimately, this research aims to inform policies and practices that create equitable access to advanced science education and foster enduring STEM identity among Latinx high school students