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Publication Embargo The digital bridge: how digital transformation mediates the innovative culture-resilience nexus in IT firms(Emerald Publishing, 2025) Kodithuwakku, T; Samaraweera, I; Mathew, M; Samarakkody, T; Thelijjagoda, S; Gamage, SPurpose – This study aims to identify the impact of innovative culture on organizational resilience in the Sri Lankan information technology (IT) sector, with a specific focus on the mediation role of digital transformation. Design/methodology/approach – Using a quantitative approach, data were collected from over 274 participants who were managerial or above-level employees in the IT industry via surveys. Partial least squares structural equation modeling was used to analyze the data and test the hypothesized relationships between variables. Findings – The findings of this study revealed that innovative culture has a significant positive impact on the adoption of digital transformation, as the innovative mindset that is ingrained encourages continuous growth, creativity and risk-taking, thereby strengthening digital transformation initiatives. Both innovative culture and digital transformation have a significant positive impact on organizational resilience. Digital transformation significantly mediates the effect of innovative culture on organizational resilience. Practical implications – The findings offer valuable guidance to industry leaders and policymakers for the strategic utilization of technology and the design of appropriate business models. Originality/value – This study emphasizes the importance of developing innovative culture and digital transformation in the IT industry to ensure sustainable business processes.Publication Open Access Framework to create opportunities to maximize the contribution of differently abled employees in the Sri Lankan garment industry(Springer Science and Business Media, 2025-04) Gurudasa, P; Lokeshwara, A; Weerarathna, R; Thelijjagoda, S; Weerasinghe, C; Fonseka, S; Dananjaya, SThe primary focus of this study was on Differently Abled Employees’ (DAEs) work performance within Sri Lanka’s garment industry. Prior research revealed inadequate awareness among organizations regarding the provision of employment opportunities for DAEs. Notably, DAEs constitute a substantial portion of the economically inactive working-age population in Sri Lanka. In this setting, the study aimed to identify the crucial factors influencing the contribution of DAEs in the Sri Lankan garment industry. In this setting, the study sought to measure their impact and develop a framework that supports both DAEs and the garment industry, fostering a mutually beneficial work environment. Utilizing a mixed approach, the study encompassed a sample population of 270 DAEs. Data collection involved semi-structured interviews and a Likert scale questionnaire. Convenience sampling was deployed to interview 14 DAEs, while a sample of 159 DAEs was selected through simple random sampling for the distribution of the questionnaire. Thematic analysis and multiple linear regression analysis were employed to analyze qualitative and quantitative data. The results underscored the significance of the examined factors affecting DAEs’ contributions. Based on regression analysis results, the researchers developed a framework, which underwent further refinement through reviews and discussions. The findings proposed supportive strategies to achieve the overarching objective of the study to maximize DAEs’ contributions in the workplace.Publication Embargo Personal well-being index as a measure of quality of life of diverse groups of people with visual impairment and blindness(Springer Science and Business Media B.V., 2023-07-12) Jayathilaka, R; Dunuwila, V; Attale, D; De Seram, H; Sudusinghe, D; Abeyrathna, I; Suraweera, T; Thelijjagoda, SToday, the world adopts various assessment tools and indices to measure quality of life (QoL) of different persons. The Personal Well-being Index (PWI) is a popular and validated tool used by developed countries to assess the QoL of their citizens. The PWI consists of seven major domains that define people’s QoL. Thus, the main purpose of this study is to explore the application of PWI in measuring the QoL of the visually impaired and blind (VI and B) persons in Sri Lanka, and to identify how QoL varies with their demographic characteristics. Primary data revealed among 64 VI&B, 34 blind and 30 visually impaired people from Hambanthota, was analysed based on vision level, age, gender, marital status, and the level of education. Results indicated that visually impaired (VI) respondents had a higher PWI value than that of the blind. Accordingly, the age group of 40–59 contributes to a higher PWI value than that of others; while the results signify that the PWI values basically depend on the levels of education the participants received. It is significant that the blind and the partially sighted people are concerned about their future security to a greater extent compared to the other domains in the PWI. Also, QoL was perceived to deteriorate with age. Thus, it is evident that efforts to improve QoL of people with visual disabilities requires priority to secure a fruitful and secure future for them.Publication Open Access Can visual impairment impact your income potential?(PLoS ONE, 2023-04-20) Wickramaarachchi, C; Jayathilaka, R; Suraweera, T; Thelijjagoda, S; Kollure, LPeople’s quality of life (QOL) has been disrupted globally in the wake of the pandemic in recent times. This was mainly due to global economic crises fuelled by the coronavirus (COVID– 19) and other related factors. Sri Lanka, too, was facing major social and economic constraints in the period 2021–2022. Thus, all communities islandwide have been economically disturbed. Among others, people with Visual Impairment and Blindness (VIB) have been pushed to severely disadvantageous positions, financially and otherwise. A sample from three geographical locations in Sri Lanka; and eleven individuals representing diverse cadres in Sri Lankan society were purposively selected for the study based on the existence of the majority of the visually impaired community using a mixed approach. Descriptive statistics were utilised to analyse the identified socio-economic characteristics. Ordered probit regression was employed to determine the mediating effect of socio-economic status on income levels. Word Cloud illustrates the factors affecting the QOL. Most severely impaired individuals are more likely to earn a lower rate of income. This situation has degraded their lives and poor QOL. Participants’ responses elucidate that facilities, resources, education, opportunities, income, employment, and government activities would enhance their QOL. The study adds value to society by recognising VIB people, helping them gain financial independence and strengthening them without marginalising the impaired community. The proposed policies in this study would be valuable for these social groups to address their wealth concerns.Publication Embargo MiMi: Sinhala Language Speech Assistive Learning Bot to Support Children with Stuttering(IEEE, 2022-12-13) Vithana, K.C.D; Weerarathne, D.N.N; Krishan, H.A.S; Wijesiri, M.R.M; Thelijjagoda, S; Jayawickrama, J. A. D. T.This research paper presents “MiMi”, a Sinhala Language voice assistive gamified solution that is designed to address stuttering in children aged between three and fourteen. Speech disorders occur when the regular flow of communication is disrupted. Stuttering, Lisps, Dysarthria, and Apraxia are some variations of speech impairments. Stuttering can be caused by a variety of factors including physical weaknesses, inherited diseases, Autism, and accidents. The risk of continuing to stutter into adulthood is highest in children between the ages of three to fourteen. It is recognized that stuttering therapy activities were less effective in managing stuttering after this age. Stuttering treatments comprise speech therapy with speech-language therapists, which requires in-person sessions that can be challenging and expensive in some circumstances. A parent’s financial ability, their busy schedules, the state of the economy in the nation, and the feasibility of physically seeing therapists and enduring treatments are all factors that might encourage or demotivate participation in therapy sessions. The development in technology and technical approaches have revolutionized the medical field and several studies have been conducted regarding communication disorders in recent years. The application can be used to practice a child’s needed speech therapy virtually and can also be used to aid speech therapy sessions done by speech therapists. The main aim of the system is to provide a customized, engaging, and innovative therapeutic strategy for children to manage stuttering.Publication Embargo Impact of Critical Success Factors in Oracle EBS Enterprise Resource Planning Post Go Live Implementation:A Case Study on SriLankan Airlines(Institute of Electrical and Electronics Engineers, 2022-01-08) Dissanayake, I; Thelijjagoda, SIn today's business world, ERP does everything from recording transaction data, managing workflows, analyzing data to provide insights to decision makers for effective decision making. Selection of a right ERP, proper testing and post go live could be a major scale system implementation for any organization. Thus, it is extremely beneficial to evaluate and test the Critical Success Factors (CSFs) in order to ensure a successful ERP post go live implementation. The primary goal of this study is to determine the impact of Critical Success Factors that influence for a successful post go live ERP implementation in the context of the national airline of Sri Lanka which is SriLankan Airlines. Three critical success factors were identified through this study. This study aims on Adequate end user training, Business Process Management (BPM) and Top Management Support as CSFs. The findings have verified that the ERP implementation success is influenced by the Top Management Support, Business Process Management and adequate end user trainings. Out of the identified three CSFs, it is statistically proven that the adequate end user training takes a significantly prominent place for a successful post go live implementation while BPM and Top Management Support also equally contribute to drive an ERP implementation project with expected outcomes. This study could be a guidance for enterprises, be beneficial to ERP clienteles, ERP consultants and service providers, be added to the existing body of knowledge.Publication Embargo AppGuider: Feature Comparison System using Neural Network with FastText and Aspect-based Sentiment Analysis on Play Store User Reviews(Institute of Electrical and Electronics Engineers, 2022-10-22) Thelijjagoda, S; Oshadi, D.M.KNowadays, there's a rapid growth in the number of apps downloaded from the app stores. People nowadays use apps for even the most simple daily tasks. In this situation, people always tend to search for new apps for the new tasks they come across in daily life. User reviews have a high impact on the app downloads. When analysing user reviews, it's important to consider the aspect that has been discussed in reviews. In mobile app reviews, the discussed aspect is mostly a functionality or feature of the mobile app. Therefore, it's crucial to make use of this important data in a way that helps app seekers to easily find the best-suited app for their requirements and also helps app developers to identify their weak features that need to be improved. This research was conducted to provide a strategy that visualizes user review summaries in a form that is relevant to the end user with the intention of achieving a model that is not only lightweight but also highly accurate and effective in terms of its performance. The AppGuider system was implemented, mainly with two models for sentiment analysis and aspect extraction. The sentiment classification model was developed with a deep learning approach that included a two-layer neural network, while the aspect extraction model was built with an unsupervised machine learning approach using the LdaMulticore algorithm. FastApi was used for data visualization in Frontend. User reviews were vectorized with FastText prior to input into the model. The accuracy of the sentiment classification model is 91%, with an 85.97% f1 score, an 85.93% recall, and an 86.05% precision. The FastText model outperformed the Stanford CoreNLP library in the performance test. The integrated system was evaluated by 25 user reviews that were entered manually and sentiment classification model scored 92% while the aspect extraction model scored of 76% accuracy.Publication Embargo Healbot: NLP-based Health Care Assistant for Global Pandemics(IEEE, 2022-10-04) Anushka, S; Thelijjagoda, SSince it was detected, coronavirus (also known as COVID-19) has become a worldwide epidemic. The surge in patients has made it challenging for hospitals and medical professionals to keep up due to the increasing number of recorded incidents. When the pandemic starts, it is getting really hard to visit a medical specialist, even in more remote areas. According to the Johns Hopkins university’s Covid dashboard, approximately 220 million Covid cases were reported worldwide [2]. According to government hospital reports, 666,086 cases were found in Sri Lanka [3]. It’s a massive amount to handle for the health sector and the country. Consequently, there are many deaths reported every day as a result of the challenges in inpatient care. Because all patients are treated in their homes, this must be done efficiently. Only the most urgent cases are being treated in hospitals. Hospitals and quarantine centers are overcrowded. People in remote areas are also trying to treat the disease without knowing anything about it because they have limited access to information. This is because it needs a Chatbot to help with diagnosing Covid symptoms at home, and to assist patients in finding the right treatment options. An artificial intelligence (AI) Chatbot has been developed with the goal of diagnosing COVID-19 exposure and advising rapid remedies. As part of this analysis, relevant past research was reviewed to establish the best reliable approach for predicting COVID-19 in people. There was an integration of Logistic Regression, Decision Trees, and Random Forests to develop the model. The model was trained with the clinical data taken from the COVID-19 patients and machine learning models are evaluated to see how accurate they are. It was determined how accurate the algorithms were. The patients who were infected with COVID-19 were examined by using implemented prototype to predict the severity level and the trained model makes use of RASA Framework, FastAPI, and MongoDB for the pur...Publication Embargo Designing of a Voice-Based Programming IDE for Source Code Generation: A Machine Learning Approach(IEEE, 2022-10-04) Nizzad, A.R. M.; Thelijjagoda, SHumans are precise in recognizing natural languages and responding contextually unlike machines. However, speech recognition or Automatic speech recognition often refers to converting human speech or voice to textual information with the help of artificial intelligence algorithms. With the advancement of Artificial Intelligence technologies and extensive research being conducted in AI, speech recognition has received much attention and has emerged as a subset of Natural Language Processing where the advancement and accuracy in speech recognition will open many ways to provide a high standard of human-computer interaction. In this study, using the pre-trained transformer model with a transfer learning approach, the English to Python dataset was used to train the transformer model to produce syntactically correct source code in python. Additionally, the Word2Vec model was used to generate voice-to-text as input for the model. For the purpose of demonstration, a custom Python IDE is developed to generate source code from voice input. The results and findings suggest that in the transformer model, with the use of transfer learning, any dataset can be trained to produce syntactically correct source code. The model’s training loss and validation loss were below 5 and 2.1, respectively. Future research can focus on generating valid source code from any human spoken language without restricting it to English only.Publication Embargo Healthy Heart – Heart Risk Prediction System on Personalized Guidance for Heart Patients(IEEE, 2022-07-18) Bandara, K.R.C; Dureksha, D.D.T.D; Pinidiya, S.C; Amarasinghe, R.M.G.H; Thelijjagoda, S; Kishara, JHuman heart is the principal part of the human body. Change in human lifestyle, work related stress and unhealthy food habits contribute to the increase in rate of numerous heart related diseases. In accordance with several research, various heart diseases have been the key reason for deaths in Sri Lanka. According to the 2018 records, stroke affected 31%, coronary heart disease affected 23%, and ischemic heart disease affected 14%. Therefore, there is a need for an automated system which will enhance medical efficiency and to identify such diseases in time for proper treatment. The proposed system takes physical and medical datasets of heart patients as manual input parameters and predicts the patient’s risk of having a heart disease. Prediction process grants the patient a risk level according to the heart condition and proposes a personalized daily guidance for the patient to avoid risks associated with, along with a meal planner, exercise scheduler and a stress releaser as well as alert the patient well in advance. The system will present an efficient technique of predicting heart diseases using machine learning approaches to analyze huge complex medical data. Some of the used algorithms are Random Forest, Logistic regression, Decision tree classifier etc... The research mainly aims to prevent the escalation of heart diseases in patients and lead them to a healthy lifestyle.