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All Journal Journal of Computer Science Advancements Journal of Moeslim Research Technik Journal of Selvicoltura Asean Journal of Biomedical and Techno Nanomaterials Journal of Multidisciplinary Sustainability Asean
Ava Lee
Nanyang Technological University
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Other

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 1 
Decoupling Economic Growth from Ecological Impact: A Socio-Ecological Modeling of Small-Scale Fisheries in the Post-Pandemic Era Anna Dara; Lucas Wong; Ava Lee; Ziad Khalil
Journal of Multidisciplinary Sustainability Asean Vol. 3 No. 2 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijmsa.v3i2.3790

Abstract

Background Small-scale fisheries are vital for coastal communities but face increasing challenges from overfishing, degradation, and economic instability, all of which were exacerbated by the COVID-19 pandemic. Purpose This research aims to decouple economic growth from ecological impact in small-scale fisheries by creating a socio-ecological model that integrates both economic and ecological variables for sustainable management. Method The study employs a mixed-methods approach, combining socio-economic surveys, interviews with key stakeholders, and ecological data collection to build the integrated framework. Results Regions adopting sustainable practices demonstrated resilience in both ecological and economic recovery post-pandemic, while regions relying on unsustainable practices continued to face decline. Conclusion Long-term sustainability requires a balanced approach that combines financial incentives, sustainable practices, community engagement, and integrated policies supporting both economic recovery and environmental conservation.
ELECTROMECHANICAL SYNERGY: ADVANCED MODELING OF COUPLED ELECTRICAL–MECHANICAL ENERGY SYSTEMS Rusman Rusman; Ava Lee; Sarah Williams
Journal of Moeslim Research Technik Vol. 3 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v3i1.3375

Abstract

Electromechanical energy systems increasingly underpin modern transportation, industrial automation, and renewable power technologies, yet their behavior is often modeled through simplified decoupled approaches that overlook dynamic interaction between electrical and mechanical domains. This study aims to develop and evaluate an advanced modeling framework that explicitly represents electromechanical synergy as a bidirectional and nonlinear energy exchange process. The research employs a quantitative, model-driven methodology integrating electromagnetic equations, mechanical dynamics, and coupling coefficients within a unified simulation environment. Representative electromechanical systems are analyzed under steady-state and transient operating conditions to assess model accuracy and system behavior. The results demonstrate that coupled modeling significantly improves predictive accuracy for torque response, angular velocity, vibration behavior, and system stability compared to conventional decoupled models. The findings also reveal that coupling effects intensify during transient excitation and load variation, confirming the central role of interaction dynamics in system performance. The study concludes that electromechanical systems should be treated as integrated energy structures rather than isolated subsystems. Advanced coupled modeling provides a robust analytical foundation for design optimization, control development, and reliability assessment in complex energy systems. These contributions support future interdisciplinary research and facilitate practical implementation across emerging electromechanical applications worldwide in diverse industrial academic settings.
COMMUNITY-BASED FOREST GOVERNANCE MODELS IN SOUTHEAST ASIA: BETWEEN LOCAL WISDOM AND STATE POLICY Ethan Tan; Ava Lee; Lucas Wong
Journal of Selvicoltura Asean Vol. 3 No. 2 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsa.v3i2.3757

Abstract

Southeast Asia’s forests are critical to both global biodiversity and local livelihoods. Yet, these ecosystems are under significant threat from deforestation, climate change, and unsustainable resource extraction. The governance of forest resources in the region remains a complex issue, as it involves the interaction between local communities’ traditional knowledge and practices, and state policies aimed at forest conservation and management. Understanding the dynamics of community-based forest governance models, which integrate local wisdom with state regulations, is crucial for achieving sustainable forest management. This study aims to examine the role of community-based forest governance models in Southeast Asia, with a particular focus on how local wisdom and state policy intersect. The research seeks to explore the challenges and opportunities in aligning indigenous governance practices with formal state policies for effective forest management. A qualitative approach was employed, utilizing case studies from various Southeast Asian countries, including Indonesia, Thailand, and the Philippines. Data were gathered through interviews with community leaders, government officials, and forest managers, as well as field observations. The findings highlight that while local communities possess valuable ecological knowledge, there are often conflicts with state policies that prioritize top-down forest management. However, successful models exist where collaboration between communities and state actors leads to more sustainable outcomes. The study underscores the importance of integrating local wisdom with state policies to create more effective and inclusive forest governance frameworks.
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.
PRECLINICAL EVALUATION OF NANOMATERIAL-BASED THERAPEUTICS FOR TRANSLATIONAL MEDICINE Ryan Teo; Ethan Tan; Ava Lee
Journal of Biomedical and Techno Nanomaterials Vol. 3 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jbtn.v3i1.3561

Abstract

Nanomaterial-based therapeutics have shown immense promise in translational medicine, offering innovative solutions for targeted drug delivery, cancer therapy, and regenerative medicine. The unique properties of nanomaterials, including their high surface area, biocompatibility, and ability to be engineered for specific functions, make them ideal candidates for improving the precision and efficacy of medical treatments. However, the preclinical evaluation of these nanomaterials is critical to ensuring their safety, efficacy, and clinical applicability. This study aims to evaluate the preclinical performance of nanomaterial-based therapeutics in the context of translational medicine. The research focuses on assessing the pharmacokinetics, biocompatibility, and therapeutic efficacy of nanomaterials in animal models to determine their potential for clinical translation. A series of preclinical tests were conducted using animal models to assess the pharmacokinetics, biodistribution, and toxicity of various nanomaterials. Therapeutic efficacy was evaluated through specific disease models, including cancer and wound healing, using both in vitro and in vivo techniques. The study demonstrated that nanomaterial-based therapeutics exhibited promising pharmacokinetics and high therapeutic efficacy, with minimal toxicity. Nanomaterials showed targeted drug delivery and enhanced therapeutic outcomes in preclinical models, particularly in cancer therapy. Nanomaterial-based therapeutics hold significant potential for advancing translational medicine. Preclinical evaluations confirm their promise for targeted therapy, though further research on long-term safety and clinical translation is needed.
Co-Authors Anna Dara Ethan Tan Lucas Wong Rusman Rusman Ryan Teo Sarah Williams Sofia Lim Ziad Khalil