Research Publications

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Subject: search.filters.subject.Sri Lankan

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Now showing 1 - 9 of 9
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    ItemOpen Access
    Lean integrated circular economy in the Sri Lankan construction industry: a qualitative Delphi study
    (Ceylon Institute of Builders, 2025) Vijayakumar, H; Ranadewa K.A.T.O; Weerakoon, P; Weerakoon, P; Jayanetti J.K.D.D.T
    The construction industry is known for its significant environmental impact and waste generation. To address this issue, the concept of Circular Economy (CE) has emerged, aiming to minimise waste and maximise resource utilisation. However, there are several barriers which impede the implementation of the CE concept in the construction industry. Therefore, this research aims to incorporate the lean concept to overcome the barriers of CE implementation in the construction industry. Therefore, this research develops a framework for a lean-enabled CE in the construction industry. The qualitative approach is used for this paper, and the Delphi technique was adopted. Purposive sampling was used to select the experts for the study, and data were analysed through manual content analysis. The findings revealed 10 benefits from CE and 12 benefits from Lean were identified, along with 8 benefits of CE and Lean integration. Furthermore, 19 barriers were identified towards this integration, and 12 strategies were identified to overcome these barriers. This study also provides a comprehensive mapping between CE and Lean implementation benefits, their integration benefits and barriers, and strategies. In addition, integrating lean and CE for the construction industry can lead to many significant benefits, such as cost savings, improved environmental performance, and enhanced stakeholder engagement.
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    Impact of Pandemic on Finances of SMEs in Sri Lankan Construction Industry
    (SLIIT, Faculty of Engineering, 2024-10) Abeysiria, O; Allis, C; Lokuge, A
    This study focuses on the impact of the pandemic on the financial aspects of Sri Lankan construction SMEs. The pandemic has significantly affected economies globally. Sri Lanka, a country whose economy mainly consists of SMEs, has faced adverse effects due to the preventive measures implemented to control the spread of the disease. Nearly 90% of registered construction firms in Sri Lanka belong to the SME category. Financial challenges or difficulties were encountered by construction SMEs even before the pandemic impacted Sri Lanka. Currently, most of the Sri Lankan construction SMEs are on the brink of bankruptcy, mainly due to the financial challenges brought about by the pandemic. This study comprises primary data produced from semi-structured interviews and secondary sources of data from the literature review. It has identified the financial challenges undergone by construction SMEs in usual manners, including limited access to bank credit facilities, lack of capital of the contractor, and lack of cash flow due to delayed payments, among others. Principally, there were several financial challenges created due to the pandemic, including barriers in obtaining credit facilities from suppliers, and the challenges that were usually present have intensified with the effects of the ongoing pandemic. In the latter part of this study, strategies that Sri Lankan construction SMEs have executed to survive in the industry are pointed out. Most SME contractors in Sri Lanka do not have positive perspectives on staying in the industry for the long term, given the financial challenges they have encountered with the current pandemic.
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    A Machine Learning Approach to Predict Default Lease Cases in Sri Lankan Financial Institutions
    (IEEE, 2022-12-26) Perera, V. A. S.; Kavirathne, G. P. R. A.; Karunathunge, L. C. R.; Dewapura, B. N.; Karunasena, A.; Pemadasa, M. G. N. M.
    The economic growth of a country can be aided by a strong financial services industry. Therefore, financial companies play a vital role in today’s society. However, by providing credit facilities, they expose themselves to a significant amount of risks, since most of them lack a proper strategy to identify whether the customer is reliable and capable of paying back on time. Hence, it is widely acknowledged that having a proper strategy in place to manage and lessen the credit risks that these companies face is more beneficial, rather than relying on traditional manual techniques. This study is intended to propose a machine learning-based solution to predict possible financial lease defaults beforehand. The dataset used in this work was obtained from a leading finance company in Sri Lanka, where the data were related to leasing contracts and their equipment. According to the final results of this study, a deep learning model implemented using an Artificial Neural Network, which was compared against several other machine learning models, is the best to predict default lease cases in Sri Lankan financial institutions. The finalized model provides 93.93% of classification accuracy, 85.49% of F-measure, 87.69% of AUROC score, and 80.41% of Kappa score.
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    Rapid Risk Assessment of Sri Lankan School Buildings against Tsunamis
    (IEEE, 2022-10-04) Nawanandana, C; Dias, P
    Rapid assessment of building vulnerability and risk is very useful, especially if based on sound engineering principles as opposed to expert opinion alone. A tsunami relative risk index (TRRI) has recently been proposed for hospital buildings based on such an approach. This study extends the concept to reinforced concrete school buildings. Two typical plan forms of school buildings were explored, each of two and three storey height. The criterion for overall structural failure was the shear capacity of columns; for scour, the number of footings undermined; and for debris impact, the shear capacity of corner columns. Of the parameters explored, the inundation depth and flow velocity were found to have the greatest influence on TRRI, while building type, building height and flow direction had much smaller influence. Debris impact was the governing risk at low inundation depths (around 1m), with scour at medium depths (around 3m) and overall structural shear failure at higher depths (around 5m).
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    Ontology Based Question Answering System for Sri Lankan Online School Education
    (IEEE, 2022-10-04) Jayabahu, J.M.G.R.; Rajapaksha, U.U.S.
    Today, distance education is one of the world’s most popular forms of education, and there are several opportunities for students to receive education online. Here, ontology can be considered one of the leading knowledge representation ways in e-learning systems. This research addressed students’ learning difficulties in Sri Lankan online education during the past two years. Students had to learn from home via online video conferences or audio series taught by teachers. However, students could not learn by asking questions or referring to the library materials to improve their self-studying knowledge. To overcome this issue, this research developed an ontology for school children in Sri Lanka, focusing on their IT syllabus and improving their self-education knowledge. This aims to provide personalized content while improving information searching. Students can ask questions from UI, and questions are taken as an input parameter and generate a query while cleansing for matching processes. Answers are generated by connecting to the index database and ontology repository, and the end output is displayed in the user interface. In the evaluation, it was targeted to categorize the questions according to relevant components, and the research shows the questions that are categorized into relevant categories while enhancing the performance.
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    Techno-economic Feasibility of Implementing Carbon Capture and Storage Technology in Sri Lankan Power Sector
    (IEEE, 2021-09-24) Damayanthi, R. M. H; Guruvita, K. M
    Earth is consistently getting hotter with the highest recorded global temperature was in 2020, surpassing the previous record in 2016. Global warming is the principle explanation behind the temperature increase on the planet. As one of the maj or greenhouse gases, carbon dioxide has a strong influence on the global warming. Fossil fuel-based power generation is one of the primary source that release carbon dioxide to the environment. Carbon Capture and Storage (CCS) is an emerging global technology to reduce the carbon dioxide emissions from fossil fuel power generation plants. However, this technology is highly capital and resource intensive and those vary from country to country as well. Therefore, it is essential to estimate the economic feasibility and the impacts on the environmental resources beforehand. This study is an effort to estimate the technical and economic feasibility of implementing CCS technology in the Sri Lankan fossil fuel power plants.
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    EasyTalk: A Translator for Sri Lankan Sign Language using Machine Learning and Artificial Intelligence
    (IEEE, 2020-12-10) Manoj Kumar, D; Bavanraj, k; Thavananthan, S; Bastiansz, G. M. A. S; Harshanath, S. M. B; Alosious, J
    Sign language is used by the hearing-impaired and inarticulate community to communicate with each other. But not all Sri Lankans are aware of the sign language or verbal languages and a translation is required. The Sri Lankan Sign Language is tightly bound to the hearing-impaired and inarticulate. The paper presents EasyTalk, a sign language translator which can translate Sri Lankan Sign Language into text and audio formats as well as translate verbal language into Sri Lankan Sign Language which would benefit them to express their ideas. This is handled in four separate components. The first component, Hand Gesture Detector captures hand signs using pre-trained models. Image Classifier component classifies and translates the detected hand signs. The Text and Voice Generator component produces a text or an audio formatted output for identified hand signs. Finally, Text to Sign Converter works on converting an entered English text back into the sign language based animated images. By using these techniques, EasyTalk can detect, translate and produce relevant outputs with superior accuracy. This can result in effective and efficient communication between the community with differently-abled people and the community with normal people.
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    Improve the Efficiency and Security by Digitalizing the Sri Lankan Police Department
    (IEEE, 2021-12-09) Senaratne, A. N; Abeywardana, K. Y; Pathirathna, R. P. D.T. D; Priyamantha, Y. P. C. N; Dias, W. D. S; Katukithulgala, B
    Police, as the main law enforcement organization in Sri Lanka, play a major role in preserving the public order, preventing criminal, terrorist activities, and enforcing the law. As a developing nation, Sri Lanka Police Department is moving forward with emerging technologies to effectively manage operations and rapidly respond to opportunities and challenges. Compared to developed countries, Police Department is still far more behind when working with modern technologies. Lack of coordination between departments, duplication of data, delay of services, unauthorized data modification, absence of data analysis and prediction systems, lack of transparency, and corruption were identified as the main issues that exist in the police department. In this paper, we propose 4 main improvements which help to overcome those issues and challenges. Improving the existing police clearance certificate system to issue digital certificates capable of verifying the authenticity, integrity of the document and providing efficient delivery and great user experience to the applicants. Implementing a Blockchain network to store confidential data securely by providing transparency and integrity. Developing a machine learning model to predict crimes geographically and predict fight crime action based on data gathered from a real-time camera system (CCTV).
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    Analysis on the Risk and the Categorization on Test Automation in Sri Lankan Software Industry
    (IEEE, 2021-12-09) Sundaralingam, S; Rajapaksha, S. K
    Delivering quality software to customer is the key objective of software industry. One of the essential fragment of life cycle of software is software testing. In software testing test automation is playing a major role. If test automation cannot be practiced in proper way the delivery of the software quality would impact directly and leads to loss of customer, which is a failure of business. Test automation has several problems which needs to address in each stage. Test automation cause several issues when execute test automation in a company. All these issues need to be handled by different people, therefore initially issues need to be identified and classified and then solve properly. This research is to identify the improvements to categorize the problems automatically and find the solution for the problem in test automation process and hence to practice the test automation in healthier way in order to achieve better software quality. Test automation issue are analyzed and the solutions are proposed. On which stage, the test automation is causing problems and how to solve them are recommend in this research, Test automation issues are categorized and under relevant category therefore issues can be solved speedily. The issues are passed as sentence and they are categorized under the relevant category to fix them quickly. The sentences are preprocessed and conducted feature selection using filter methods and predict under appropriate category. The issue has been cleaned in preprocess stage. Implemented LSTM base algorithm using filter method to categorize the issues. In this research an implementation to categorize test automation problems are formed. Recommendation and solutions are proposed on test automation which would aid to practice test automation in better way and that would leads to better software quality delivery.