Kwang-Man Ko, Department of Computer Engineering, Sangji University,83 Sangjidae-gil, Wonju-si, Gangwon-do, Republic of Korea
This study proposes a traceable method for converting multi-jurisdictional cybersecurity and software-quality requirements into two quantitative compliance indicators for digital medical devices and evaluates its methodological validity through simulation. Requirements from the Korean MFDS, the U.S.FDA, the EU MDR and MDCG guidance, IMDRF guidance, and relevant IEC, ISO, and AAMI standards are consolidated into traceable verification items. A compensatory Weighted-Sum indicator summarizes overall development progress, whereas a Jurisdiction-Bottleneck indicator identifies the lowest jurisdictionspecific level of compliance. A simulation-based evaluation using a ten-item insulin-pump scenario examines the calculation procedure and decision-making behavior of the proposed indicators. The simulation yields Weighted-Sum and Jurisdiction-Bottleneck scores of 69.0% and 60.0%, respectively. Sensitivity analysis using alternative enforceability encodings confirms the stability of the identified bottleneck, while counterfactual analysis distinguishes item-level improvement effects from denominator effects. These results demonstrate the computational consistency, interpretability, and complementary decision behavior of the proposed indicators. However, the simulation does not establish industrial effectiveness, inter-rater agreement, or the ability to predict actual regulatory approval outcomes.
Digital Medical Devices, Medical Software, Standard Compliance Evaluation, Quantitative Evaluation Index
Haowei Sun1, Bobby Nguyen2, 1TVT Community Day School, 5 Federation Way, Irvine, CA 92603, 2University of California, Riverside, 900 University Ave, Riverside, CA 92521
Deaf and hard-of-hearing individuals can face barriers when accessing spoken information and important environmental sounds. hearassist addresses this problem through an AI-powered mobile system combining live transcription, conversation summaries, environmental sound detection, and customizable vibration alerts through a wearable band [1]. The system uses speech recognition, natural language processing, and audio classification while prioritizing on-device processing for privacy and low latency. Development involved challenges integrating these components and debugging code as new features were added [2]. Two experiments tested the system under realistic conditions. Sound detection reached 90% accuracy in quiet conditions but decreased to 60% with conversation noise.Transcription achieved a 6% word error rate for clear speech but reached 35% when fast, accented speech and background noise were combined. These results highlight areas for continued improvement while demonstrating hearassist’s potential to combine multiple accessibility functions into one system for everyday communication and environmental awareness.
Assistance, Hearing, Accessibility, Convenience
Haoyi Wang, Armando Contreras, 1St Margaret’s Episcopal School, 31641 La Novia Avenue, San Juan Capistrano, CA 92675, 2University of California, Irvine, Irvine, CA 92697
Video game stores have become really crowded since platforms like Steam let people find, buy, and talk about games all in one place (Valve Corporation, n.d.). My project, Uptrend, tries to make finding new games easier and less confusing. Uptrend shows popular games, trends, data, ratings, comments, and also has a watchlist. I built the website using HTML, CSS, JavaScript, Firebase Authentication, Firestore, and game data links (Google, 2026a; Google, 2026b) [13]. While making it, I had problems with spacing, old game visuals, and Firebase permissions. I fixed these by cleaning up the layout, updating the game data, and changing how the login and watchlist syncing worked. When I tested Uptrend, users were able to find game pages faster than with a normal search, and the watchlist saved games quickly before syncing them online [1]. Overall, Uptrend makes finding and keeping track of games faster, simpler, and easier to understand.
Video games, Tracking, Discovery, Marketplace, HTML, CSS, JavaScript, Friebase, Data
Elvin Qihuo Liao1, Bobby Nguyen2, 1Sage Hill High School, Newport Coast Drive, Newport Beach, CA, 2University of California, Riverside, 900 University Ave, Riverside, CA 92521
This paper presents Flow State, a mobile application designed to help tennis players find compatible partners and organize sessions. The project addresses the difficulty beginners and independent players experience when searching for opponents with suitable skill levels, locations, schedules, and playing preferences. The application combines three major components: user authentication and profile management, a compatibility-based matchmaking system, and session booking and scheduling. Flutter and Dart provide the application interface and logic, while Firebase Authentication, Cloud Firestore, and Firebase Storage manage accounts and data [4]. Match recommendations use weighted profile, session, history, and recent-activity information, including filtering for inactive profiles. Booking features check capacity, duplicate reservations, and schedule conflicts. Experiments using simulated player profiles and scheduling cases tested recommendation alignment and booking reliability. Results indicated that the system could produce personalized matches and reject invalid bookings. Future improvements include larger real-use testing, skill verification, calendar integration, and stronger privacy and safety features.
Sports Matchmaking, Tennis, Compatibility-Based Recommendation, Mobile Application Development
Jinxi Sha1, Moddwyn Andaya2, 1Sage Hill School, 20402 Newport Coast Drive, Newport Coast, CA 92657, 2California State University, Sacramento, 6000 Jed Smith Dr, Sacramento, CA 95819
Virus VS Vaccine is a Unity-based strategy simulation in which a player manages a spreading virus across a network of connected locations by allocating a limited weekly budget of Efficiency Points toward vaccination and shutdown interventions. The project responds to the ongoing real-world need for tools that make networked, resource- constrained public health trade-offs tangible rather than abstract. We describe the three linked systems that make this possible: a location-and-connection network, a shutdown intervention state machine, and an Efficiency Point economy, and walk through a representative code sample from each. An experiment comparing network-severing interventions against vaccination found vaccination consistently more effective at limiting total infections, a result consistent with published findings on the limited effectiveness of travel restrictions alone. We compare our approach against three existing methodologies, three compartmental modeling, cellular-automata simulation, and branching-scenario games, and outline the calibration and state-management improvements that further development would prioritize.
Epidemic simulation, Game-based learning, Compartmental modeling, Public health intervention
Lanqi Li1, Rodrigo Onate2, 1Eleanor Roosevelt High School, 7447 Scholar way, Eastvale, CA 92880, 2California State University, Fullerton, 800 N State College Blvd, Fullerton, CA 92831
Everyday life skills are rarely taught with the same individualisation that academic subjects increasingly receive, and existing children’s apps either present identical content to every user or expose general-purpose chatbots without age-appropriate guardrails. This paper presents Common Matters, an adaptive Flutter application that uses GPT-5.2 to generate ten-paragraph life-skills lessons whose vocabulary, narrative form, and assessment shape are all conditioned on the child’s saved reading level and one of six learning styles, with illustrations served from a SHA-1 keyed Firebase Storage cache and fill-in-the-blank answers graded by the model itself. Two evaluations on the live system found that generated stories were valid and on topic in over 94% of 300 trials, and that the LLM grader agreed with human raters above 91% on every legitimately correct answer variation while strict matching fell below 20%. Common Matters offers a low-cost, inclusive alternative to static educational apps.
Large Language Models, Educational Technology, Adaptive Learning, Learning Styles, Flutter, Firebase, Children’ s Education, Personalized Content Generation, AI-Graded Assessment, Mobile Learning
