Article Per Year (5 Year)
p-Index From 2021 - 2026
1.197
P-Index
This Author published in this journals
All Journal Journal of Computer Science Advancements Research of Scientia Naturalis Journal of Social Entrepreneurship and Creative Technology
Sofia Lim
Singapore University of Technology and Design
Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Physics

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : journal of computer science advancements

 1 
CODING REVOLUTION: HOW AI AGENTS ARE TAKING OVER SOFTWARE REPOSITORY MAINTENANCE Ryan Teo; Ava Lee; Sofia Lim
Journal of Computer Science Advancements Vol. 3 No. 6 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v3i6.3322

Abstract

The rapid expansion of global software infrastructure has created a critical bottleneck, as human developers struggle to manage escalating technical debt and complex repository maintenance. This research explores the transformative shift toward “Autonomous Repository Management” (ARM), where AI agents transition from passive assistants to independent maintainers. The primary objective is to evaluate the efficacy of agentic architectures in performing end-to-end maintenance tasks across diverse software ecosystems. Employing a longitudinal experimental design, this study utilized a purposive sample of 50 open-source repositories, applying a custom “RepoHealth-Bench” framework to measure performance. Findings indicate that AI agents reduced technical debt by 31.5% in legacy systems and achieved a 96.5% patch success rate in standardized libraries, significantly outperforming human-centric benchmarks in speed and security remediation. Inferential analysis reveals a strong correlation between repository documentation quality and agent reliability, suggesting a “compounding health” effect through iterative machine-led refactoring. The study concludes that the “Coding Revolution” effectively reverses software entropy, shifting the developer's role from manual execution to high-level orchestration. These results provide a foundational blueprint for integrating autonomous digital workforces into the modern software development lifecycle, marking the end of the manual maintenance era.
IMAGE PROCESSING AND COMPUTER VISION TECHNIQUES FOR AUTOMATED SMART SURVEILLANCE SYSTEMS Zainal Syahlan; Sofia Lim; Lucas Wong
Journal of Computer Science Advancements Vol. 3 No. 6 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v3i6.3323

Abstract

The rapid development of urbanization and security concerns has prompted the integration of automated smart surveillance systems to enhance public safety and operational efficiency. Traditional surveillance methods often rely on human monitoring, which is prone to errors and inefficiencies. Image processing and computer vision techniques provide a solution by automating object detection, tracking, and anomaly recognition. This study aims to investigate advanced image processing and computer vision techniques for improving the performance of automated smart surveillance systems. A hybrid approach combining convolutional neural networks (CNNs), attention mechanisms, and edge computing is proposed to enhance both detection accuracy and real-time processing speed. The research employed experimental design, utilizing a dataset of 12,000 annotated image frames and 85 hours of video footage from diverse environmental conditions. Performance metrics such as precision, recall, mean average precision (mAP), and processing speed were measured. Results demonstrate that the proposed model outperforms traditional CNN models, achieving higher detection accuracy and faster processing speed. The study concludes that integrating edge computing with adaptive image processing and attention-based neural networks significantly improves automated surveillance system performance in real-world settings. These findings offer valuable insights for the development of scalable and efficient smart surveillance technologies.
EMBEDDED SYSTEMS DESIGN FOR SMART PRODUCTS IN INDUSTRY FOUR POINT ZERO MANUFACTURING Nana Sujana; Jaden Tan; Sofia Lim
Journal of Computer Science Advancements Vol. 4 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v4i1.3391

Abstract

Industry Four Point Zero manufacturing has transformed conventional production systems into intelligent, interconnected environments in which smart products play a central role. These smart products rely heavily on embedded systems to enable sensing, real-time control, communication, and autonomous decision-making under strict industrial constraints. This study aims to examine how embedded systems design influences the performance of smart products in Industry Four Point Zero manufacturing contexts, with particular attention to design attributes that support efficiency, adaptability, and reliability. A mixed-methods research design was employed, combining quantitative analysis of survey data collected from industrial practitioners with qualitative insights derived from case-based observations in manufacturing settings. The instruments focused on key embedded system design dimensions, including modularity, real-time responsiveness, communication efficiency, and system reliability, as well as corresponding smart product performance indicators. The results reveal that embedded systems design has a significant and positive effect on smart product performance, with communication efficiency and system reliability emerging as the strongest predictors of operational efficiency and fault tolerance. The findings demonstrate that smart manufacturing effectiveness is strongly determined by device-level design decisions rather than by higher-level digital infrastructures alone. In conclusion, the study highlights embedded systems design as a strategic foundation for smart products and underscores its critical role in achieving sustainable and resilient Industry Four Point Zero manufacturing.
Co-Authors Aarav Sharma Ava Lee Daniel Schmidt Dodi Setiawan Riatmaja Emma Brown Ethan Thompson Ingrid Olsson Jaden Tan James Scott Lucas Wong Ma'rifani Fitri Arisa Nana Sujana Ryan Teo Sakura Suzuki Zainal Syahlan