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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

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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.
ADAPTIVE COMPLEXITY IN LIVING SYSTEMS: INTEGRATING ECOLOGICAL DYNAMICS WITH NONLINEAR MATHEMATICAL MODELING Aarav Sharma; Sofia Lim; Daniel Schmidt
Research of Scientia Naturalis Vol. 3 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v3i1.3541

Abstract

Adaptive complexity is a defining feature of living systems, where nonlinear interactions, feedback mechanisms, and environmental variability shape dynamic behaviors that cannot be adequately explained through linear models. Ecological research increasingly recognizes the limitations of equilibrium-based approaches, yet a coherent integration of ecological dynamics with nonlinear mathematical modeling remains underdeveloped. This study aims to develop an integrative framework that captures adaptive complexity by combining empirical ecological data with nonlinear dynamical systems analysis. The research employs a mixed-methods design, incorporating secondary ecological datasets, computational modeling, and techniques such as bifurcation and sensitivity analysis to examine system behavior under varying conditions. Results demonstrate that ecological systems exhibit multi-stability, threshold effects, and chaotic dynamics, with environmental variability and interaction intensity significantly influencing system transitions. Nonlinear models successfully capture emergent behaviors and reveal critical tipping points that are not identifiable through linear approaches. These findings highlight that adaptive complexity operates as an organizing principle rather than a peripheral characteristic of living systems. The study concludes that integrating ecological dynamics with nonlinear mathematical modeling enhances both theoretical understanding and practical predictive capacity, offering a robust framework for analyzing resilience and transformation in ecological systems.
VR FOR GOOD: A SOCIO-PRENEURSHIP MODEL UTILIZING VIRTUAL REALITY EXPOSURE THERAPY (VRET) FOR AFFORDABLE MENTAL HEALTH SERVICES Ethan Thompson; Sofia Lim; Ingrid Olsson
Journal of Social Entrepreneurship and Creative Technology Vol. 2 No. 6 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jseact.v2i6.2988

Abstract

The global mental health crisis continues to escalate, with millions of individuals facing barriers to accessing affordable care. Traditional mental health services, while effective, are often inaccessible due to high costs, geographic barriers, and limited availability. This research proposes a socio-preneurship model that leverages Virtual Reality Exposure Therapy (VRET) as a scalable, cost-effective solution to address these challenges. The study aims to explore the feasibility and effectiveness of utilizing VRET within a socio-preneurship framework to provide affordable mental health services to underserved populations. A mixed-methods approach was employed, combining quantitative measures of anxiety and stress reduction with qualitative interviews to assess user satisfaction and engagement. Participants were divided into a VR therapy group and a control group receiving traditional therapy. The results demonstrated significant improvements in anxiety and stress levels for the VR therapy group compared to the control group, alongside higher levels of user engagement and satisfaction. The study concludes that VRET, when integrated into a socio-preneurship model, offers a viable, accessible, and effective solution to providing mental health services in underserved communities. This approach not only improves mental health outcomes but also creates sustainable, scalable systems for addressing mental health disparities.
GAMIFYING SOCIAL INNOVATION: ENTREPRENEURIAL DESIGN THINKING FOR SUSTAINABLE SOCIETIES Sofia Lim; Sakura Suzuki; Emma Brown; Dodi Setiawan Riatmaja
Journal of Social Entrepreneurship and Creative Technology Vol. 3 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jseact.v3i1.3296

Abstract

The increasing complexity of social and environmental challenges has exposed the limitations of conventional, top-down innovation models in achieving sustainable societal change. Social innovation therefore requires participatory, adaptive, and engaging approaches capable of mobilizing collective creativity and long-term commitment. This study aims to examine how gamification can be strategically integrated into entrepreneurial design thinking to strengthen social innovation processes for sustainable societies. A qualitative and exploratory research design was employed, drawing on secondary data from peer-reviewed literature, policy reports, and documented social innovation initiatives that apply design thinking and gamified mechanisms. Data were analyzed through thematic interpretation to identify patterns of engagement, collaboration, and learning. The results indicate that gamification functions as a structural enabler rather than a superficial motivational tool, enhancing stakeholder engagement, sustaining participation, and supporting collaborative problem-solving throughout iterative design thinking stages. Gamified design thinking was found to foster experiential learning, shared ownership, and adaptability, which are critical for addressing complex sustainability challenges. The study concludes that effective social innovation depends not only on innovative solutions but also on well-designed participatory processes. Integrating gamification within entrepreneurial design thinking offers a promising framework for aligning innovation practices with sustainability goals across diverse social contexts and long-term societal impact.
SCALING SOCIAL VALUE THROUGH CREATIVE TECHNOLOGIES: STRATEGIC CHALLENGES IN DIGITAL ENTREPRENEURSHIP Sofia Lim; Jaden Tan; James Scott; Ma'rifani Fitri Arisa
Journal of Social Entrepreneurship and Creative Technology Vol. 3 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jseact.v3i1.3475

Abstract

The rapid expansion of creative technologies has transformed digital entrepreneurship into a critical driver of social innovation and inclusive growth. Platform ecosystems, artificial intelligence, and data-driven infrastructures enable ventures to scale rapidly, yet strategic tensions emerge between technological acceleration and sustained social mission integrity. This study aims to develop and empirically validate a strategic framework explaining how digital entrepreneurs scale social value while navigating governance, stakeholder, and measurement challenges. A mixed-methods explanatory sequential design was employed, combining survey data from 214 digital social ventures with in-depth case studies of selected firms operating in technology-intensive sectors. Multiple regression and structural equation modeling were used to test relationships among technological capability, strategic agility, stakeholder integration, impact measurement sophistication, and scaling performance. Findings indicate that technological capability significantly predicts scaling performance (? = 0.41, p < 0.001), with strategic agility acting as a mediating variable. Hybrid ventures balancing innovation with governance and ecosystem collaboration achieved superior scaling outcomes. The study concludes that sustainable scaling of social value requires multidimensional capability alignment rather than technology-driven expansion alone. Integrative strategic management of creative technologies is essential for maintaining legitimacy, adaptability, and measurable social impact in digital entrepreneurship.
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