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All Journal Journal of Moeslim Research Technik Journal of Selvicoltura Asean Journal of Tecnologia Quantica Journal of Loomingulisus ja Innovatsioon Techno Agriculturae Studium of Research Research of Scientia Naturalis Journal of Social Entrepreneurship and Creative Technology Journal of Multidisciplinary Sustainability Asean
Yang Xiang
Beijing Normal University
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Physics Other

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Performance Analysis of Cloud Computing Systems in Collaborative Software Development Environments Zhang Li; Yang Xiang; Arnes Yuli Vandika
Journal of Moeslim Research Technik Vol. 1 No. 6 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v1i6.1562

Abstract

The rise of cloud computing has transformed software development, enabling collaborative environments that enhance productivity and efficiency. However, the performance of cloud computing systems in supporting collaborative software development remains an area of active research, with various factors influencing effectiveness. This study aims to analyze the performance of cloud computing systems in collaborative software development environments. The focus is on identifying key performance metrics and their impact on team productivity and project outcomes. A mixed-methods approach was employed, combining quantitative performance metrics and qualitative surveys from development teams using cloud-based tools. Key metrics analyzed included system uptime, response time, and resource utilization. Surveys gathered insights on user satisfaction and perceived efficiency improvements. The findings reveal that cloud computing systems significantly enhance collaboration among software development teams. Metrics indicated an average system uptime of 99.5%, with response times averaging under 200 milliseconds. Survey results showed that 85% of participants reported increased productivity when using cloud-based tools compared to traditional methods. The research concludes that cloud computing systems provide substantial performance advantages in collaborative software development environments. These systems facilitate better communication, resource sharing, and project management, ultimately leading to improved project outcomes. Future research should explore the long-term effects of cloud computing on software development practices and its implications for team dynamics.
AUTOMATED DETECTION OF ROAD SURFACE DEFECTS USING UAVS AND CONVOLUTIONAL NEURAL NETWORKS Roya Zahir; Jamil Khan; Yang Xiang; Siti Shofiah
Journal of Moeslim Research Technik Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v2i3.2349

Abstract

This study presents a novel approach to the automated detection of road surface defects using Unmanned Aerial Vehicles (UAVs) and advanced image processing. The research background highlights the critical need for efficient and safe road infrastructure maintenance. Traditional methods, which rely on manual visual inspections, are often time-consuming, expensive, and expose inspectors to traffic risks. The primary objective is to design and validate an automated system for identifying and classifying various road surface defects, such as potholes, cracks, and rutting. The system aims to leverage aerial imagery captured by UAVs and process it with a Convolutional Neural Network (CNN). The research seeks to demonstrate a solution that is faster, more accurate, and safer than manual inspection methods, paving the way for proactive road maintenance. The research methodology involves three key stages: data acquisition, model development, and validation. High-resolution images of various road defects are captured using a UAV. These images are then used to train a custom-designed CNN model. The model is trained to recognize and classify different types of defects with high precision. The results indicate that the combination of UAVs and CNNs is a robust and effective solution for road monitoring. The conclusion is that this automated system provides a scalable, safe, and highly accurate method for road surface defect detection.  
Balancing Conservation and Development: A Policy Framework for Sustainable Forest Management Sun Wei; Yang Xiang; Zhang Li
Journal of Selvicoltura Asean Vol. 1 No. 4 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsa.v1i4.1665

Abstract

The interplay between conservation and development poses significant challenges in forest management. Unsustainable practices often lead to biodiversity loss and environmental degradation, highlighting the urgent need for effective policy frameworks that balance these competing interests. Sustainable forest management is essential for preserving ecosystems while supporting economic growth. This research aims to develop a comprehensive policy framework that harmonizes conservation and development goals in forest management. The study seeks to identify strategies that promote sustainable practices, enhance biodiversity, and support local communities' livelihoods. A mixed-methods approach was employed, combining qualitative and quantitative data collection. Case studies from various regions were analyzed to understand existing policies and their impacts on forest management. Stakeholder interviews and surveys were conducted to gather insights on the challenges and opportunities in balancing conservation with development. The findings indicate that successful policy frameworks incorporate multi-stakeholder participation, adaptive management strategies, and comprehensive monitoring systems. The analysis revealed that integrating local knowledge and addressing socio-economic factors are crucial for effective implementation. Case studies demonstrated that successful balance results in improved ecological outcomes and enhanced community well-being. The research underscores the importance of a holistic approach to forest management that aligns conservation and development objectives. By implementing the proposed policy framework, stakeholders can foster sustainable practices that benefit both ecosystems and local communities, ensuring long-term viability and resilience of forest resources.
Development of Quantum Noise-Based Quantum Random Number Generator (QRNG) Yang Xiang; Wang Jing; Sun Wei
Journal of Tecnologia Quantica Vol. 1 No. 4 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v1i4.1682

Abstract

The background of this research focuses on the development of a quantum noise-based Quantum Random Number Generator (QRNG) to generate random numbers that are safer and more efficient compared to conventional methods. Quantum fluctuation-based QRNG has the potential to generate more unpredictable numbers, improving security in cryptographic and simulation applications. The purpose of this research is to develop a QRNG system that can generate high-quality random numbers with various experimental settings and conditions. The method used is an experiment measuring quantum fluctuations through a photon detector to generate a random number based on quantum noise, followed by statistical testing to test the quality of the randomness. The results show that quantum noise-based QRNG is able to generate random numbers with better quality than conventional random number generators, with p-values that indicate very high random uncertainty. In addition, these QRNGs can operate at various photon intensities without compromising the random quality produced. The conclusion of this study is that quantum noise-based QRNG offers a safer and more efficient solution in generating random numbers for applications that require high randomness. Further research is needed to improve efficiency and overcome implementation obstacles in the real world.
The Influence of Organizational Culture on the Level of Innovation in Manufacturing Companies Zhang Li; Yang Xiang; Sun Wei
Journal of Loomingulisus ja Innovatsioon Vol. 1 No. 5 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/innovatsioon.v1i5.1710

Abstract

This study examines the influence of organizational culture on the level of innovation in manufacturing companies. Organizational culture plays a crucial role in shaping the behavior of employees and influencing how companies adapt to changes and foster innovation. Despite the growing importance of innovation in maintaining competitiveness in the manufacturing sector, the relationship between organizational culture and innovation has not been fully explored in this context. This research aims to investigate how different dimensions of organizational culture—such as support for risk-taking, communication practices, and employee involvement—affect innovation outcomes in manufacturing firms. A quantitative research design was employed, using surveys distributed to employees in various manufacturing companies across different regions. The survey data were analyzed using statistical methods, including regression analysis, to determine the correlation between organizational culture and innovation levels. The findings indicate that a strong, innovation-supportive organizational culture significantly enhances the innovation capacity of manufacturing companies. Specifically, companies with cultures that promote open communication and risk-taking showed higher levels of innovative output. The study concludes that fostering a culture that values creativity, risk-taking, and collaboration can significantly improve innovation outcomes in manufacturing companies. Future research should further explore the role of leadership in shaping organizational culture and driving innovation within this sector.  
GREENHOUSE TECHNOLOGY INNOVATIONS FOR SUSTAINABLE AGRICULTURE IN THE UNITED KINGDOM Zhang Li; Yang Xiang; Liu Yang; Ardi Azhar Nampira
Techno Agriculturae Studium of Research Vol. 2 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/agriculturae.v2i1.1993

Abstract

Greenhouse technology is an important innovation in facing the challenges of sustainable agriculture in the UK, especially in the face of climate change and increasing food needs. This research aims to explore the application of advanced technologies in greenhouses, such as automation sensors, hydroponics, aquaponics, and renewable energy, as well as their impact on agricultural productivity and sustainability. Descriptive-qualitative research methods are used to gain insights from farmers and experts in the field of agricultural technology, through interviews and direct observations. The results showed a significant improvement in resource use efficiency, with a reduction in water use of up to 50% and an increase in crop yields of up to 30%. The adoption of renewable energy in greenhouses also plays a role in reducing carbon emissions and operational costs. In conclusion, greenhouse technology innovation has the potential to be an important solution to achieving sustainable agriculture in the UK, but more research is needed to evaluate the long-term impact on the environment.
INNOVATIONS IN BIOREMEDIATION: HARNESSING MICROBIAL POWER TO CLEAN UP POLLUTION Yang Xiang; Sun Wei; Elvis Ewane
Research of Scientia Naturalis Vol. 2 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v2i2.2008

Abstract

Pollution poses a significant threat to ecosystems and human health, prompting the need for effective remediation strategies. Bioremediation, which utilizes microorganisms to degrade environmental pollutants, has emerged as a promising approach to address this challenge. This study aims to explore recent advancements in bioremediation technologies, focusing on the role of specific microbial communities in the degradation of various pollutants, including heavy metals, hydrocarbons, and pesticides. The research seeks to identify effective microbial strategies and their applications in real-world scenarios. A comprehensive literature review was conducted, analyzing recent studies on microbial bioremediation techniques. Laboratory experiments were performed to evaluate the degradation rates of selected pollutants by specific microbial strains. Case studies of successful bioremediation projects were also included to illustrate practical applications. Findings indicate that innovative microbial techniques, such as genetically engineered strains and bioaugmentation, significantly enhance the degradation of pollutants. Successful case studies demonstrated substantial reductions in pollutant concentrations, showcasing the efficacy of microbial bioremediation in various environments. This research highlights the potential of harnessing microbial power for effective pollution cleanup.
BEYOND SPECIES RICHNESS: QUANTIFYING FUNCTIONAL BIODIVERSITY THROUGH MATHEMATICAL ECOLOGY Yang Xiang; Kaito Tanaka; Lena Hoffmann
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.v3i1.3540

Abstract

Biodiversity has traditionally been assessed through species richness, yet this approach often fails to capture the functional roles that determine ecosystem processes and resilience. Increasing ecological evidence indicates that ecosystems with similar species counts may differ substantially in functional composition, leading to divergent ecological outcomes. This study aims to develop a mathematical ecology framework that quantifies functional biodiversity by integrating trait-based analysis with nonlinear modeling. The research employs a quantitative design combining secondary ecological datasets, multidimensional trait space construction, and computational modeling to evaluate relationships between functional diversity and ecosystem performance. Results demonstrate that functional richness, evenness, and divergence significantly predict ecosystem productivity and stability, while species richness shows limited explanatory power. Nonlinear analysis reveals threshold effects and complex interactions, indicating that functional trait composition governs ecosystem responses to environmental change. Functional diversity also shapes network structure, enhancing system resilience through redundancy and complementarity among traits. The study concludes that functional biodiversity provides a more comprehensive and predictive measure of ecological complexity than species richness alone. Integration of mathematical ecology with trait-based approaches offers a robust analytical framework for advancing biodiversity research and informing conservation strategies.
BEYOND IMMERSION: THE EFFICACY OF VIRTUAL REALITY (VR) SIMULATIONS IN DEVELOPING TECHNICAL SKILLS FOR VOCATIONAL EDUCATION Fauzi Erwis; Yang Xiang; Jari Koskinen
Journal of Social Entrepreneurship and Creative Technology Vol. 2 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jseact.v2i4.2677

Abstract

Traditional vocational education (VET) for complex psychomotor skills is costly, risky, and difficult to scale. While Virtual Reality (VR) is a potential solution, research has focused on “immersion,” not empirical “efficacy.” The critical gap is the unverified “transfer-of-training” from virtual simulations to real-world, physical tasks. This study aimed to empirically evaluate the efficacy of VR-only training versus traditional hands-on methods. It specifically sought to measure (1) “virtual-to-real” skill transfer, (2) long-term skill retention, and (3) training efficiency. An experimental pre-test/post-test/retention-test design was used. 80 (N=80) novice welding trainees were randomized to a VR-Only (n=40) or Traditional (n=40) group. Psychomotor skill was measured on physical equipment at baseline (T1), post-intervention (T2), and 4-week retention (T3) using an expert-validated rubric (PAR), analyzed with ANCOVA. The VR-Only group demonstrated statistically superior skill transfer on the physical post-test (T2) (p < .001, \eta_p^2 = .710). This superiority was durable, with significantly higher skill retention at the T3 follow-up (p < .001). The VR group also achieved competency 27% faster (6.4 vs 8.8 hours) and at zero consumable material cost. -fidelity VR, driven by instantaneous data-driven feedback, is a more effective, efficient, and cost-effective training modality than the traditional “gold standard” for novice psychomotor skill acquisition. This study provides robust validation for the “virtual-to-real” transfer-of-training.
Public Health Policy in the Age of Climate Change: Developing Sustainable Healthcare Systems for Future Generations Trisnawati Trisnawati; Chen Mei; Yang Xiang
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.v3i2.3493

Abstract

Background. Public health systems worldwide are increasingly challenged by the accelerating impacts of climate change, including extreme weather events, shifting disease patterns, and growing health inequities. These challenges expose structural vulnerabilities in existing healthcare systems and highlight the urgent need for policy frameworks that integrate sustainability, resilience, and long-term population health considerations. Purpose. This study aims to examine how public health policy can be reoriented to support the development of sustainable healthcare systems capable of protecting future generations in the context of climate change. Method. The research employed a qualitative–analytical approach based on a systematic review of international policy documents, peer-reviewed journal articles, and reports from global health and environmental organizations published between 2015 and 2024. The analysis focused on policy strategies linking climate adaptation, health system strengthening, and sustainability principles. Results. The findings indicate that effective public health policies increasingly emphasize cross-sector collaboration, climate-resilient health infrastructure, low-carbon healthcare delivery, and preventive, community-based interventions. Countries that integrate environmental considerations into health governance demonstrate greater capacity to manage climate-related health risks and reduce long-term system costs. Conclusion. The study concludes that sustainable healthcare systems require transformative public health policies that move beyond short-term crisis responses toward integrated, forward-looking strategies. Embedding climate resilience and sustainability into public health policy is essential for safeguarding health equity and ensuring the viability of healthcare systems for future generations.
Co-Authors Ardi Azhar Nampira Arnes Yuli Vandika Chen Mei Elvis Ewane Fauzi Erwis Jamil Khan Jari Koskinen Kaito Tanaka Lena Hoffmann Liu Yang Roya Zahir Siti Shofiah Sun Wei Trisnawati Trisnawati Wang Jing Zhang Li