Search Results (7)

Accurate river flow velocity estimation is critical for flood risk management and sediment transport modeling. This study proposes an artificial intelligence (AI)-based framework that integrates optical flow analysis and deep learning to estimate flow velocity from charge-coupled device (CCD) camera videos. The approach was tested on a field dataset from Yufeng No. 2 stream (torrent), consisting of 3263 ten min 4 K videos recorded over two months, paired with Doppler radar measurements as the ground truth. Video preprocessing included frame resizing to 224 × 224 pixels, day/night classification, and exclusion of sequences with missing frames. Two deep learning architectures—a convolutional neural network combined with long short-term memory (CNN+LSTM) and a three-dimensional convolutional neural network (3D CNN)—were evaluated under different input configurations: red–green–blue (RGB) frames, optical flow, and combined RGB with optical flow. Performance was assessed using Nash–Sutcliffe Efficiency (NSE) and the index of agreement (d statistic). Results show that optical flow combined with a 3D CNN achieved the best accuracy (NSE > 0.5), outperforming CNN+LSTM and RGB-based inputs. Increasing the training set beyond approximately 100 videos provided no significant improvement, while nighttime videos degraded performance due to poor image quality and frame loss. These findings highlight the potential of combining optical flow and deep learning for cost-effective and scalable flow monitoring in small rivers. Future work will address nighttime video enhancement, broader velocity ranges, and real-time implementation. By improving the timeliness and accuracy of river flow monitoring, the proposed approach supports early warning systems, flood risk reduction, and sustainable water resource management. When integrated with turbidity measurements, it enables more accurate estimation of sediment loads transported into downstream reservoirs, helping to predict siltation rates and safeguard long-term water supply capacity. These outcomes contribute to the Sustainable Development Goals, particularly SDG 6 (Clean Water and Sanitation), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action), by enhancing disaster preparedness, protecting communities, and promoting climate-resilient water management practices. Full article

With the increasing demand for sustainable and cost-effective alternatives in the construction industry, polymer composites have emerged as a promising solution. This study focuses on the development of innovative composite tiles using Linear Low-Density Polyethylene (LLDPE) powder blended with epoxy resin and a hardener as a green substitute for conventional ceramic and cement tiles. LLDPE is recognized for its flexibility, durability, and chemical resistance, making it an effective filler within the epoxy matrix. To optimize its material properties, composite samples were fabricated using three different LLDPE-to-epoxy ratios: 30:70, 40:60, and 50:50. Flexural strength testing revealed that while the 50:50 blend achieved the highest maximum value (29.887 MPa), it also exhibited significant variability, reducing its reliability for practical applications. In contrast, the 40:60 ratio demonstrated more consistent and repeatable flexural strength, ranging from 16 to 20 MPa, which is ideal for flooring applications where mechanical performance under repeated loading is critical. Scanning Electron Microscopy (SEM) images confirmed uniform filler dispersion in the 40:60 mix, further supporting its mechanical consistency. The 30:70 composition showed irregular and erratic behaviour, with values ranging from 11.596 to 25.765 MPa, indicating poor dispersion and increased brittleness. To complement the development of the materials, deep learning techniques were employed for real-time defect detection in the manufactured tiles. Utilizing the YOLOv8 (You Only Look Once version 8) algorithm, this study implemented an automated, vision-based surface monitoring system capable of identifying surface deterioration and defects. A dataset comprising over 100 annotated images was prepared, featuring various surface defects such as cracks, craters, glaze detachment, and tile lacunae, alongside defect-free samples. The integration of machine learning not only enhances quality control in the production process but also offers a scalable solution for defect detection in large-scale manufacturing environments. This research demonstrates a dual approach to material innovation and intelligent defect detection to improve the performance and quality assurance of composite tiles, contributing to sustainable construction practices. Full article

With expanding urban sprawl and the characterization of Australian housing as little more than glorified tents, there is a clear need for expert-informed tools—such as the Green Building Council of Australia’s Communities ratings. But what lessons can be learned from the ratings of recent housing developments? A review of existing cases and supporting materials found low rates of engagement for some criteria and few projects meeting the criteria, with the most direct links being with sustainability. The patterns of scores obtained and criteria addressed appear to reflect many developers placing emphasis on compliance with the minimum standards rather than best practice in sustainability. Notable areas with poor performance include greenhouse gas mitigation strategies, the use of environmentally friendly materials and the sustainability of buildings. Strong, comprehensive education campaigns regarding up-front costs relative to long-term benefits, perhaps more heavily focused on end consumers, may help address some of the hesitancy developers have in engaging with key criteria. However, current rating frameworks fail to account for the pressing need for infill development to address the ‘missing middle’. Perhaps an evolution is needed in sustainability-oriented ratings, such as a mandatory sustainability assessment, that would crystallize the green premium of sustainable housing, thereby harnessing the demand from consumers’ for better quality. Full article

In high-tech electronics manufacturing, non-quality costs significantly impact organizational profitability and competitiveness. This case study introduces a novel Quality Deterioration Index (QDI) to systematically identify and prioritize root causes of non-quality costs within a leading electronics manufacturer. The primary objective is to integrate sustainable quality management practices that align with green sustainability objectives, such as reducing electronic waste, improving energy efficiency, and minimizing hazardous materials usage. Our comprehensive methodology encompasses a literature review, interviews, document analysis, and statistical analysis of survey data to uncover the influence of procedural, cultural, and environmental factors on quality deviations. The key findings reveal critical areas for improvement, particularly in supply chain inefficiencies, workforce challenges, and procedural gaps. By employing the QDI, we provide a structured framework that enhances both operational efficiency and environmental performance. The novelty of this research lies in its dual approach to simultaneously address economic and environmental performance, offering actionable insights for manufacturers aiming to integrate robust quality management systems with sustainability objectives. This study contributes to the ongoing dialogue on sustainable manufacturing strategies, underscoring the pivotal role of quality management in achieving both economic viability and environmental stewardship. Future research should expand this approach across various industries and global contexts to validate and refine the integration of quality management and sustainability. Full article

Non-profit organizations (NPOs) support economically disadvantaged communities by improving housing conditions and building homes, despite limited resources. With rising housing costs and poverty causing homelessness and poor housing quality, NPOs’ efforts are crucial. However, operating constraints (such as financial, policy, and others), often lead NPOs to prioritize initial costs over sustainability and environmental impacts. Therefore, this research investigated the adoption, implementation, and routinization patterns for sustainability and green efforts in Mississippi (US) by a leading NPO. The research used a two-phased combined design methodology, with the first phase involving explorative design that involved the identification of criteria that led to selecting the affiliates of Habitat for Humanity (HFH) as the unit of analysis. The selected NPO (HFH) had 38 affiliates across Mississippi, US, at the time of the study. The second phase involved a cross-sectional design, with data collected by utilizing a structured telephone survey. All collected data were subjected to descriptive and inferential statistics, and thematic analysis. Twenty-five affiliates (66% response rate) participated in the study, and the results indicate that a small proportion of affiliates were actively adopting sustainability practices for projects constructed, and most were located in the southern part of the state. The research identified factors that lead to the routinization of sustainability practices, the most commonly used third-party benchmarking tools, and perceptions of NPOs towards such tools to evaluate the greenness of residential projects. Some crucial implications were identifying uneven project completion within HFH, limited adoption of green strategies, and perception of green certification as non-vital. Full article

Ηuman sustainability in dental enterprises, as in every workplace, is connected to air and water quality, eco-friendly and naturally designed working spaces, and the culture of the 4Rs. The purpose of this study was to assess pro-environmental behavior, as well as knowledge of preferences for circular economies and green building construction, among a sample of dental students and dentists in Greece. We further assessed the factors influencing their choices. Students (N1 = 93) and dentists (N2 = 126) filled in e-questionnaires from April to December 2022. The data revealed that both students and dentists lack knowledge about the circular economy (N1 = 67.74%, N2 = 68.25%), EU regulations on amalgam disposal (N1 = 64.51%, N2 = 58.73%), and plastic recycling (N1 = 76.34%, N2 = 76.98%); meanwhile, they do recycle at home (N1 = 80.64%, N2 = 82.54%) and have participated in voluntary environmental initiatives (N1 = 58.06%, N2 = 66.66%). Gender influences the importance of factors related to green dental practices, with women students being more likely to agree that increased costs for network changes (p = 0.02) and poor wastewater management (p = 0.01) are significant. Students from urban areas are more likely to give positive answers to questions related to the lack of state financial support (p = 0.02), low levels of green design in buildings (p = 0.03), the negligible direct financial benefits of green dental offices (p = 0.04), the negligible reputational benefits of green dental offices (p = 0.02), and the lack of continuing education training seminars on green dentistry (p = 0.05). For dentists, no significant relationships were observed, except for a weak positive relationship for the increases in costs due to changes related to utility networks (p = 0.08), while increases in waste energy (p = 0.12) and the waste of dental materials (p = 0.19) seemed significant only for dentists in urban areas. Women dentists were more likely to answer positively regarding wasting energy (p = 0.024) and the use of unapproved disinfection products (p = 0.036). The findings contribute ideas and solutions for green dental practice buildings and sustainable behaviors through educational activities and regarding the social aspects of factors such as age, experience in dentistry, gender, and urbanism. This study also provides a basis for future multi-disciplinary research on dental quality assurance, the psychology of environmentalism, economics, and behavioral science in dentistry. Full article

High prevalence of poor mental health is a major public health problem. Natural environments may contribute to mitigating stress and enhancing health. However, there is little evidence on whether community-level interventions intended to increase exposure to natural environments can improve mental health and related behaviours. In the first study of its kind, we evaluated whether the implementation of a programme designed to improve the quality of, and access to, local woodlands in deprived communities in Scotland, UK, was associated with lower perceived stress or other health-related outcomes, using a controlled, repeat cross-sectional design with a nested prospective cohort. Interventions included physical changes to the woodlands and community engagement activities within the woodlands, with data collected at baseline (2013) and post-intervention (2014 and 2015). The interventions were, unexpectedly, associated with increased perceived stress compared to control sites. However, we observed significantly greater increases in stress for those living >500 m from intervention sites. Visits to nearby nature (woods and other green space) increased overall, and moderate physical activity levels also increased. In the intervention communities, those who visited natural environments showed smaller increases in stress than those who did not; there was also some evidence of increased nature connectedness and social cohesion. The intervention costs were modest but there were no significant changes in quality of life on which to base cost-effectiveness. Findings suggest factors not captured in the study may have contributed to the perceived stress patterns found. Wider community engagement and longer post-intervention follow-up may be needed to achieve significant health benefits from woodland interventions such as those described here. The study points to the challenges in evidencing the effectiveness of green space and forestry interventions to enhance health in urban environments, but also to potential benefits from more integrated approaches across health and landscape planning and management practice. Full article