Browsing by Author "Weerasinghe, N"

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Embargo
Conquerors of poverty – a case study of Colombo slum dwellers
(Emerald Publishing, 2025-02-07) Nanayakkara Wasam Mudage, K; Weerasinghe, N; Madusanka, M; Saliya, C.A; Lokeshwara, A. A; Jayatissa, C. D
Purpose: While extensive research has explored poverty in various dimensions, there remains a notable dearth of studies focusing on success stories of slum dwellers overcoming adversity. This research seeks to address this gap by investigating the strategies employed by individuals to transcend poverty. Moreover, it evaluates the practicality and effectiveness of existing theories in real-world contexts through careful interpretation. Design/methodology/approach: Data were gathered from two distinct cases through comprehensive, in-depth interviews. These narratives were subjected to scrutiny employing the Description Analysis Interpretation method. Subsequent interpretation and theoretical exploration were guided by Bourdieu’s class theory. The overarching goal was to shed light on the remarkable journeys of specific slum residents who surpassed the constraints of poverty. This endeavor not only highlighted the practical efficacy of these theories but also underscored their relevance in illuminating real-world scenarios through interpretation. Findings: The findings underscore the capacity of slum dwellers to rise above poverty, thereby emphasizing the practical utility of specific theories aimed at poverty alleviation in elucidating their experiences. Notably, social capital, a cornerstone of Bourdieu’s class theory, emerges as equally pivotal as economic capital in shaping individuals' trajectories. Research limitations/implications: The study’s scope is confined to narratives within the Colombo slums, offering a platform for future researchers to extend their investigations beyond this context. By employing alternative methodologies and exploring diverse geographical regions, scholars can broaden their understanding of poverty alleviation strategies and their applicability across varied socioeconomic landscapes. This calls for wider research for comprehensive exploration and comprehension of poverty dynamics beyond singular locales. Practical implications: The study provides invaluable insights for policymakers, governmental bodies and nongovernmental organizations, urging them to reconsider and reformulate policies, educational strategies and community development programs tailored to the needs of slum dwellers and their children. These insights offer a pathway toward more effective interventions aimed at fostering sustainable upliftment within these marginalized communities. Originality/value: This research fills a critical gap in poverty literature by exploring success stories of slum dwellers overcoming adversity, an area often overlooked. It uniquely investigates the strategies these individuals employ to transcend poverty, offering fresh insights into the practical application of poverty alleviation theories. Utilizing Bourdieu’s class theory, the study highlights the importance of both social and economic capital in these success narratives. By focusing on real-life experiences, it underscores the relevance and utility of these theories in real-world contexts, enriching the theoretical discourse and providing valuable perspectives for policymakers and practitioners.Poverty
Open Access
Efficient Hotspot Detection in Solar Panels via Computer Vision and Machine Learning
(Multidisciplinary Digital Publishing Institute (MDPI), 2025-07-15) Fernando, N; Seneviratne, L; Weerasinghe, N; Rathnayake, N; Hoshino, Y
Solar power generation is rapidly emerging within renewable energy due to its cost-effectiveness and ease of deployment. However, improper inspection and maintenance lead to significant damage from unnoticed solar hotspots. Even with inspections, factors like shadows, dust, and shading cause localized heat, mimicking hotspot behavior. This study emphasizes interpretability and efficiency, identifying key predictive features through feature-level and What-if Analysis. It evaluates model training and inference times to assess effectiveness in resource-limited environments, aiming to balance accuracy, generalization, and efficiency. Using Unmanned Aerial Vehicle (UAV)-acquired thermal images from five datasets, the study compares five Machine Learning (ML) models and five Deep Learning (DL) models. Explainable AI (XAI) techniques guide the analysis, with a particular focus on MPEG (Moving Picture Experts Group)-7 features for hotspot discrimination, supported by statistical validation. Medium Gaussian SVM achieved the best trade-off, with 99.3% accuracy and 18 s inference time. Feature analysis revealed blue chrominance as a strong early indicator of hotspot detection. Statistical validation across datasets confirmed the discriminative strength of MPEG-7 features. This study revisits the assumption that DL models are inherently superior, presenting an interpretable alternative for hotspot detection; highlighting the potential impact of domain mismatch. Model-level insight shows that both absolute and relative temperature variations are important in solar panel inspections. The relative decrease in “blueness” provides a crucial early indication of faults, especially in low-contrast thermal images where distinguishing normal warm areas from actual hotspot is difficult. Feature-level insight highlights how subtle changes in color composition, particularly reductions in blue components, serve as early indicators of developing anomalies.
Open Access
Institutional Best Practices Amidst and Beyond the COVID-19: The Case of Higher Educational Institutes in Sri Lanka
(SLIIT Business School, 2023-12-24) Rathnayake, N; Weerasinghe, A; Weerasinghe, N; Kumarasinghe, J
COVID-19 is a blessing for the higher education industry in developing nations since it has accelerated the digitization of higher education. Education is essential to transforming people into human capital. The COVID-19 restrictions on physically entering educational institutions gave boost to the biggest educational disaster in the world. The objective of this study is to investigate the best practices employed by the Higher Education Institutions (HEIs) in Sri Lanka to enhance university academic role both amid and beyond the pandemic. The technique of nonprobability purposive sampling was employed, and the results were then analyzed thematically. Best practices in academic research and knowledge dissemination fields, and teaching have been recognized by the study from the viewpoint of the HEIs. Beyond the pandemic, virtual laboratories, concurrent delivery, and hybrid deliveries are still in use, while academic research and knowledge dissemination are being digitalized and exposed to a global audience. The shift from traditional classrooms to the distance learning environment in developing nations has accelerated the process of meeting the sustainable development objective of high-quality education by 2030. As a result, policymakers in these nations can emphasize digitally enabling the higher education sector.
Embargo
Mixed Reality Supermarket: A Modern Approach into Day - to - Day Grocery Shopping
(IEEE, 2020-11-04) Weerasinghe, N; Jayawardena, S; Mahawatta, D; Navaratne, H; Sriyaratna, D; Gamage, I
In the modern world where there are massive trends in development and implementation of new technologies, combination of Virtual Reality and Augmented Reality is one which has key potential in an everyday developing world. The main concept behind Virtual Reality is simply immersing the user in a virtual environment at the comfort of their own place. This is done by creating a computer-generated 3D environment with hand gestured navigation system combined with concepts of voice recognition, image processing and machine learning that explores intense human interactions. As we are in the 21st century, where technological transformations are most certainly creating blurry lines between fiction and reality, more and more people have the need to fulfill their daily requirements easily without wasting their valuable time. Buying day to day needs from a supermarket is one of the main activities that each one of us struggle to go through during the day. Targeting the above simple daily activities, we are making an effort to apply VR Technology to this area through this research and thus trying to provide a rather new technological experience for purchasing items from a supermarket. This can be beneficial to the consumers to minimize their valuable time wasted, and also, they will be able to get the real experience of shopping while getting exposure to marketing.
Open Access
Sustainability practices and organizational performance during the COVID-19 pandemic and economic crisis: A case of apparel and textile industry in Sri Lanka
(NLM (Medline), 2023-07-04) Weerasinghe, N; Weerasinghe, A; Perera, Y; Tennakoon, S; Rathnayake, N; Jayasinghe, P
The apparel and textile industry is the backbone of the Sri Lankan economy, contributing significantly to the country's gross domestic product (GDP). The coronavirus (COVID-19) pandemic, which also triggered the ongoing economic crisis in Sri Lanka, has a profound effect on the organizational performance of apparel sector firms in Sri Lanka. In this context, the study examines the impact of multi-dimensional corporate sustainability practices on organizational performance in the said sector. The study employed the partial least squares structural equation modelling (PLS-SEM) technique for analysing and testing the hypothesis of the study while using Smart PLS 4.0 software as the analysis tool. Relevant data were collected through a questionnaire from 300 apparel firms registered with the Board of Investment of Sri Lanka (BOI). The study results indicated that "economic vigour," "ethical practices," and "social equity" have a significant impact on organizational performance, while "corporate governance" and "environmental performance" have an insignificant impact. Unique discoveries from this study would be useful to prosper organizational performance and formulate novel sustainable future strategies not limited to the garment industry even during harsh economic conditions. Copyright: © 2023 Weerasinghe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.