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Publication Open Access CHALLENGES & PROSPECTS FOR ECONOMIC EMPOWERMENT OF PERSONS WITH VISUAL IMPAIRMENT & BLINDNESS ENGAGED IN SELFEMPLOYED VENTURES(y Sri Lanka Forum of University Economists (SLFUE) Uva Wellassa University of Sri Lanka, 2021-01-21) Dunuwila, V. R; Suraweera, T; Jayathilaka, R; Thelijjagoda, SPeople with disabilities experience numerous barriers with regard to securing employment, thus, they are more likely to work for low wages, informally and precariously. Besides, some of them are entitled for a disability benefit which is often inadequate to cover their daily expenses (Global Disability Summit, 2018). Economic empowerment can be defined as a way of ensuring income security for people with disabilities to achieve income security, advance economically, enrich themselves through empowerment and autonomy to make economic decisions within and outside the home (Global Disability Summit, 2018). Self-employment is perceived as a viable option for empowering disabled individuals that facilitates achieving a balance between disability status and work life (Kitching, 2014; Pagán, 2009; Adams, et al., 2019). Pagán (2009) indicated the presence of a strong relationship between disability status and self-employment; thus, selfemployment rates were higher among people with disabilities compared to those who report no limitation in daily activities (Kitching, 2014; Pagán, 2009; Adams, et al., 2019). The Global Disability Summit (2018) indicates that obstacles to economic empowerment experienced by people with disabilities can vary depending on the nature of an individual’s impairment, their gender, socioeconomic status and the context in which they live. Adams, et al., (2019) further indicate that the decision to enter into self-employment for most disabled individuals were influenced by the ‘push’ factors such as lack of alternative employment opportunities, rather than the ‘pull’ factors such as passion or interest in a particular field, or the desire to work for themselves (Kitching, 2014; Adams, et al., 2019). Past research reveals that the disabled self-employed face significant problems in sustaining the business due to reasons such as consumer discrimination, inadequate training, poor access to information, absence of appropriate business support and challenges in accessing finance (Adams, et al., 2019; Kitching, 2014; Pagán, 2009; Vaziri, Schreiber, Wieching, & Wulf, 2014)Publication Open Access IN A QUEST FOR ‘WHAT THEY VALUE THE MOST’: PERSONS WITH VISUAL IMPAIRMENT AND BLINDNESS IN A CLUSTERED COMMUNITY IN SRI LANKA(y Sri Lanka Forum of University Economists (SLFUE) Uva Wellassa University of Sri Lanka, 2021-01-21) Attale, D.S.C; Sudusinghe, D. R; Abeyrathna, H. A. P. I; De Seram, S. S. H; Jayathilaka, R; Suraweera, T; Thelijjagoda, SThe community engagement and the resource requirements of a community would vary on the nature of the community. If one would broadly recognize persons with visual impairment and blindness (VI&B) as community per se, it is expected that their needs, resource requirements and the activities they engagedin would differ from the rest of the population in general. This research aims to explore the nature of resource requirements and the activities commonly engaged-in by a ‘community’ of persons with VI&B, in a ‘clustered village’ in Southern Sri Lanka. Though sociologists interpret the term community in various ways, this study adopts the definition of Sylvia Dale, (1990); “Community is a body of people living in the same locality…Alternatively, a sense of identity and belonging shared among people living in the same locality, Also, the set of social relations found in a particular bounded area” (Dale, 1990, p. 562). Accordingly, the ‘Siyanethugama’ 55th model village was developed by the National Housing Authority in 2018, where 27 families having at least one person in each with VI&B, would very well be embraced as a “community”. Each family is allocated a 10 perch land with a basic one-bedroom house. Visual impairment or vision impairment, is the degree of reduced vision level from low vision to total blindness that impedes a person’s ability to function at certain or many tasks. As at 2018, among the Sri Lankan population of 21 million (worldometer, 2020), considerably 1.7% of individuals carry a visual impairment (Devapriya, 2020). A study is yet be performed in the Sri Lankan context based on the theme “Resources and activities that VI&B people value the most in their lives”. The preference of an individual’s resources and activities may vary according to their demographic characteristics. This empirical study focuses on deriving what types of resources and activities the VI&B people ascertain the most in their lives, and how the demographic characteristics affect their lives based on their visual impairment type. This study contributes to draw attention from the government towards the VI&B people and types of actions the government can take, to improve the lifestyle of VI&B people in Sri Lanka.Publication Open Access Effects of Seven Domains of Personal Well-being on Quality of Life of Persons with Visual Impairment and Blindness in Sri Lanka(researchgate.net, 2021-08) Dunuwila, V. R; Jayathilaka, R; Attale, D; De Seram, H; Sudusinghe, D; Abeyrathna, I; Suraweera, T; Thelijjagoda, SThe quality of life (QoL) of people with disabilities is of interest to social researchers in most parts of the World. However, this is an area somewhat overlooked by society in general. It is obvious that the lifestyle of a person with visual disabilities may differ significantly compared to those who see the World with their own eyes. Additionally, persons with visual disabilities are known to experience specific challenges, unlike people who are sighted. Hence, the main objective of this study is to examine the extent to which the seven domains of the Personal Wellbeing Index (PWI), namely, the standard of living, achievements in life, community connectedness, close relationships, health, safety, and future security, impact the QoL of people with visual impairment and blindness. The sample of 64 participants, 34 blind and 30 visually impaired individuals, were obtained via purposive sampling from one among 25 districts, Hambanthota, in Southern Sri Lanka. Data collection was carried out through a tailored questionnaire, employed as a telephone survey, and through face-to-face interviews. The relationship between the seven domains of PWI and QoL was analyzed through standard statistical methods using SPSS. Further, demographic factors such as age and gender were also examined in the analysis. Results show that the majority of persons with visual impairment and blindness, in particular those in the age group 40-59, are satisfied with the seven domains of PWI. However, the PWI domain of ‘future of security is of significant concern to this community. The results also assert that the ‘community connectedness’ and ‘achievements in life’ are two areas that need to be looked into by the policymakers for sustained QoL among persons with visual impairment and blindness. Authors acknowledge contribution of the World Bank assisted AHEAD Research project of SLIIT Business School for support extended in relation to data collection and guidance.Publication Embargo Road Navigation System Using Automatic Speech Recognition (ASR) And Natural Language Processing (NLP)(IEEE, 2019-01-31) Withanage, P; Liyanage, T; Deeyakaduwe, N; Dias, E; Thelijjagoda, SIn a highly evolving technical era, Voice-based Navigation Systems play a major role to bridge the gap between human and machine. To overcome the difficulty in taking and understanding user's voice commands, simulating the natural language, process the route with user's turn by turn directions while mentioning key entities like street names, landmarks, point of interests, junctions and map the route in an interactive interface, we propose a user-centric roadmap navigation mobile application called “Direct Me”. The approach of generating the user preferred route, system will first convert the audio streams into text through Automatic Speech Recognizer (ASR) using Pocket Sphinx Library, followed by Natural Language Processing (NLP) by utilizing Stanford CoreNLP Framework to retrieve the navigation-associated information and process the route in the Map using Google Map API upon the user request. This system is used to provide an efficient approach to translate natural language directions to a machine-understandable format and will benefit the development of voice-based navigation-oriented humanmachine interface.Publication Embargo Sentiment classification of Sinhala content in social media(IEEE, 2020-09-24) Jayasuriya, P; Ekanayake, S; Munasinghe, R; Munasinghe, B; Weerasinghe, I; Thelijjagoda, SIn this study, we focus on the classification of Sinhala social media sentiments into positive and negative classes for a particular domain (sports). We have employed machine learning algorithms and lexicon-based sentiment classification methods. We also consider a hybrid approach by constructing an ensemble classifier in which we combine Machine Learning and Lexicon based methods. For individual methods, machine learning algorithms performed best in terms of accuracy. The ensemble classifier was able to improve performance further.Publication Embargo Product Recommendation and Context Validation Based E-Commerce System With Currency Free Economy(IEEE, 2021-12-09) Siriwardana, D. T; Ulpathakumbura, U; Wanniarachchi, T; Thelijjagoda, SDue to the covid-9 situation, online shopping shows rapid growth among Sri Lanka and other countries. Meanwhile, with the visible downward trend of the Sri Lankan economy, people have been suffering due to inflation, leading to higher expenses of goods and services. A web-based solution called ‘Ceylon Barter Bay’ was developed as an e-bartering platform for Sri Lankans to get bartering experience and develop one-to-one trading. This paper comes with an appropriate business model for ‘Ceylon Barter Bay’ as a novice entrepreneur idea. This website was developed with enhanced abuse detectors and a related product recommendation system. Natural language processing and machine learning techniques are used in the process to get a better solution. Since the developed system is mainly based on advertising, a random forest algorithm-based machine learning model with 99% accuracy detects the context offensiveness. To detect violent behavior in feedback/comments, the logistic regression algorithm-based machine learning model was used with 88% accuracy. ‘Ceylon Barter Bay’ will recommend related items. Both collaborative and content-based recommendations have been performed using linear regression, respectively. In Sri Lanka, this has been recognized as an acceptable solution to break the monopoly of money via a web-based applicationPublication Embargo Expert Prediction System for Spice Plants Grown in Sri Lanka: An Incentive for Planters(IEEE, 2021-12-09) Gunasekara, R; Withanage, H; Wimalachandra, N; Hettiarachchi, L; Attanayaka, B; Thelijjagoda, SSpice is an element that brings unique identification to Sri Lanka. The taste that is inherent in Sri Lankan spices is the main reason for this unique identification. The demand for Sri Lankan spices is growing day by day in local markets as well as in markets overseas. The plantation of spice crops needs to be planned carefully as those add a significant contribution not only to the domestic consumption but also to Sri Lanka’s export income. Hence, the cultivation of spices should be done systematically to provide a supply that meets the demand. In most cases, large scale and small scale of these crop plantations are not successful. Therefore, assisting these spice planters to identify the most suitable location for crop growth has become a critical requirement in the agriculture sector of Sri Lanka. As there are no applications developed yet in Sri Lanka to support this requirement, researchers try to give a reasonable solution to fill this gap. ‘Mr. Masala’ mobile application was developed with aim of encouraging planters to cultivate spices successfully. This mobile application can be used to identify whether a selected location by a planter is suitable to grow the spice plant they expect to grow. This is done by measuring environmental conditions such as temperature, rainfall, humidity, sunlight and soil pH. Also, users would be able to get an approximate amount of crop productivity, production costs & income for the size of their land, measure the amount of fertilizers needed for soil preparation & maintenance, and amount of pesticides needed to control pests and diseases. Furthermore, spice planters can measure factors required for the growth of spices regularly, helping them obtain expected yields and profits.Publication Embargo Sentiment Classification of Sinhala Content in Social Media: An Ensemble Approach(IEEE, 2021-12-09) Jayasuriya, P; Munasinghe, R; Thelijjagoda, SWe focus on the binary classification of Sinhala social media content in the sports domain using machine learning algorithms. In particular, we improve upon the accuracy achieved in a previous study of ours that utilized word and character N-grams. We use the base learners from that study to implement a probability-based stacking ensemble approach. This is done by creating a base learner library of 1066 base learners, using 13 different algorithms and different N-gram feature extraction methods. Different base learner combinations from the library are then stacked together to find the best stacking ensemble model. The best stacking ensemble model achieves an accuracy of 83.8% which is an improvement of over 1.5% of our previous study.Publication Embargo Sentiment Classification of Sinhala Content in Social Media: A Comparison between Stemmers and N-gram Features(IEEE, 2021-12-09) Jayasuriya, P; Munasinghe, R; Thelijjagoda, SSentiment classification for non-English languages has gained significant attention from researchers in the past few years with the increasing use of non-English scripts and Romanized scripts for expressing sentiments over social media. In this study, we begin by classifying Sinhala sentiments on social media into positive and negative polarity classes using N-gram feature extraction. N-grams are a contiguous sequence of words or characters of a text. Then we focus on improving the classification accuracy by employing different stemming methods. Stemming is generally used to reduce the dimensionality of the feature set - something which needs to be carried out with great care as over reducing feature dimensionality causes the classification accuracy to decrease. Finally, we compare the accuracy and efficiency of N-gram feature extraction and stemming based sentiment analysis models.Publication Open Access Implications for Utilizing YouTube based Community Interactions for Destination Marketing(arXiv preprint arXiv:1305.5019, 2013-05-22) Sambhanthan, A; Thelijjagoda, S; Tan, JIn recent time, YouTube has evolved into a powerful medium for social interaction. Utilizing YouTube for enhancing marketing endeavors is a strategy practiced by marketing professionals across several industries. This paper rationalizes on the different ways and means of leveraging YouTube-based platforms for effective destination marketing by the hospitality industry (hotels). More specifically, the typology of virtual communities is adapted to evaluate the YouTube platform for effective destination marketing. Comments made by YouTube users have been subjected to a content analysis and the results are reported here under the five broad clusters of virtual communities. Implications for utilizing YouTube-based community interactions for destination marketing are also highlighted as part of the outcome of this research.