Sabaragamuwa University Journal最新文献

{"title":"Examining the Influence of Rural Road Network Development on Livelihood - A Case Study on Kilinochchi District","authors":"Nirubikaa Ravikumar, K. Banujan, A. Aginthini","doi":"10.4038/suslj.v19i2.7790","DOIUrl":"https://doi.org/10.4038/suslj.v19i2.7790","url":null,"abstract":"TThe population of Sri Lanka, an island country in the Asian zone, is projected to be about 22 million in mid-2030. In Sri Lanka, the transportation economy plays a significant role. Roads provide the benefits to enhance the socio-economic conditions of communities. Roads are linked to locations, individuals, and social and economic activities. Better road conditions promote better connections between rural and social and economic activities. While rural road investment is widely believed to reduce poverty, there has been little systematic analysis or evidence on whether rural roads affect people experiencing poverty or the impact. After the war ended in 2008, the government carried out some road projects nationwide. Kilinochchi district is also not exceptional. This study focused only on rural roads and how they relate to livelihood. A questionnaire survey was conducted, covering four dimensions; impact on (i) Transportation Services, (ii) Traveling Patterns, (iii) Village Profile, and (iv) Income and Welfare before and after the road projects in Kilinochchi District. One hundred twenty-two families were selected for the research. For the change in the aesthetic value of the village after the road development, none of the respondents rated it as reduced or reduced dramatically. Around 100 respondents accepted that school connectivity has significantly improved after road development. The study proves that road development positively impacts people’s social and economic practices.","PeriodicalId":363402,"journal":{"name":"Sabaragamuwa University Journal","volume":" 36","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139139118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Career Perception on Banking Industry among Management Undergraduates","authors":"M.W.F Zamma, B. L. and Galhena","doi":"10.4038/suslj.v19i2.7746","DOIUrl":"https://doi.org/10.4038/suslj.v19i2.7746","url":null,"abstract":"Career perception especially among management graduates is a vital phenomenon that is under exploration among academics. However, no previous research has been done on exploring this phenomenon in Sri Lankan context. Thus, addressing the knowledge gap in the literature, the main purpose of this study is to identify the significant factors determining career perception on banking industry among state university management undergraduates in Sri Lanka. Based on the extant literature four independent variables namely social status, physical working conditions, financial benefits, career growth were identified to address the research question of the study. The sample was derived from 152 third and final year management students from university of Ruhuna. Self-administered questionnaires were used to collect the necessary data. Multiple regression analysis was used to test the hypotheses. The study found that social status, physical working conditions, and financial benefits are significant factors explain the career perception on banking industry among respondents. These findings particularly would be beneficial to undergraduates and career counseling institutions as well as for the society at large.","PeriodicalId":363402,"journal":{"name":"Sabaragamuwa University Journal","volume":" 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139137707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Breast Cancer Detection using Image Processing and Machine Learning: A Comprehensive Review and Improved Segmentation Approach","authors":"D.D.H. Erandika, U. P. Ishanka","doi":"10.4038/suslj.v19i2.7791","DOIUrl":"https://doi.org/10.4038/suslj.v19i2.7791","url":null,"abstract":"Breast cancer stands as one of the most prevalent health concerns for women. Early detection of breast cancer can significantly improve the chances of survival. In developed countries, more than 19.9% of women will die per year due to breast cancer. Regular breast cancer screening is an important way to detect cancer early. Image processing techniques are highly used for different types of cancer detection applications with medical screening. Segmentation of the breast tumor region is a critical step in image processing related to this manner. Lots of research work can be found on developing ways for detecting breast cancers. However still, there is a need for a standard and robust cancer region segmentation method. Right cancer region segmentation is significant for better feature extraction and better classification. This study presents a comprehensive literature review about technologies used with image enhancement and tumor segmentation. Further, the study proposes a robust approach to image enhancement and cancer region segmentation for breast cancer detection using image processing techniques and machine learning. In this work, mammograms are enhanced using Contrast Limited Adaptive Histogram Equalization and denoised using the Median blurring filter. This study enables an effective image segmentation approach with two stages: removing the background using thresholding, tumor region segmentation using a combination of thresholding, and Canny edge detection. Segmented tumor region’s features are extracted using the Gabor filter. Here the accuracy of the approach is compared with three main machine learning classifiers: Decision Tree, Random Forest, Multinomial Logistic Regression and mammograms are classified into three classes (malignant, benign and normal). Finally, an ensemble approach is proposed using the hard voting mechanism to improve the accuracy. With the dataset of mini-MIAS this proposed approach achieved 78.89% accuracy. Results demonstrated that the proposed breast cancer detection approach improves the performance of segmentation breast tumor regions.","PeriodicalId":363402,"journal":{"name":"Sabaragamuwa University Journal","volume":" 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139141167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Insights from Japanese Community-Supported Agriculture (CSA) for Building Resilient Local Food Systems in Sri Lanka","authors":"M. Esham","doi":"10.4038/suslj.v19i2.7785","DOIUrl":"https://doi.org/10.4038/suslj.v19i2.7785","url":null,"abstract":"No abstract available","PeriodicalId":363402,"journal":{"name":"Sabaragamuwa University Journal","volume":" 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139141412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards a More Intuitive Sinhala Chatbot: Leveraging NLU for Enhanced Intent Identification and Entity Extraction","authors":"Pasan Avishka, Nirubikaa Ravikumar, K. Banujan, Hansi Gunasinghe","doi":"10.4038/suslj.v19i2.7792","DOIUrl":"https://doi.org/10.4038/suslj.v19i2.7792","url":null,"abstract":"In the fast-paced and ever-changing world of conversational AI, chatbots have become essential interfaces for user interactions in various domains, especially when supporting different languages. This study delves into the development of chatbots and their ability to understand language, explicitly focusing on the Sinhala language. The effectiveness of two platforms, Rasa NLU and Microsoft LUIS, were compared in identifying and extracting intents. Both platforms showed proficiency, but Rasa stood out for its flexibility, cost-effectiveness and accurate intent recognition. A case study in the restaurant domain was conducted to demonstrate the system’s capabilities. An architecture was created that can interpret Sinhala expressions and analyze intents using the NLU engine. The study defined four intents: Food Ordering, Get In Touch, About Restaurant and None. The findings highlight how this architecture has the potential to accurately interpret intents during chatbot development regardless of the conversational language used. This research aims to contribute insights to developers, linguists and AI enthusiasts involved in language-specific chatbot development by emphasizing its promises and challenges.","PeriodicalId":363402,"journal":{"name":"Sabaragamuwa University Journal","volume":" 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139138425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards a research agenda for building business resilience to climate change in the SME sector of Sri Lanka","authors":"M. Esham","doi":"10.4038/suslj.v19i1.7768","DOIUrl":"https://doi.org/10.4038/suslj.v19i1.7768","url":null,"abstract":"","PeriodicalId":363402,"journal":{"name":"Sabaragamuwa University Journal","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114189340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Morphological and Qualitative Phytochemical Comparison of Selected Salacia Species in Lowland Wet Zone of Sri Lanka","authors":"S. M. Amarathunge, D. Pushpakumara","doi":"10.4038/suslj.v19i1.7771","DOIUrl":"https://doi.org/10.4038/suslj.v19i1.7771","url":null,"abstract":"","PeriodicalId":363402,"journal":{"name":"Sabaragamuwa University Journal","volume":"06 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127194065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Impact of Fiscal and Monetary Policy Changes on Investors' Investment Performance: Empirical Evidence from Investors in the Colombo Stock Exchange in Sri Lanka","authors":"L. Menike","doi":"10.4038/SUSLJ.V18I1.7751","DOIUrl":"https://doi.org/10.4038/SUSLJ.V18I1.7751","url":null,"abstract":"The effect of fiscal and monetary policy is transmitted in several ways by investor choice and the performance of investments. This study investigates how individual investors perceive government fiscal and monetary policy decisions and how they respond to such policy changes to make profitable investments. The data were gathered from a diversified group of 364 individual investors in the Colombo Stock Exchange (CSE) by administering a structured questionnaire focusing on their opinions of fiscal and monetary policy changes. Factor analysis was carried out to identify the meaningful fiscal and monetary policy actions that determine individual investment decisions and performance. The results of multiple regression analysis show that the government’s choice of tax instruments has a significant influence on stock returns and all taxes jointly depress investor investment performance. Government expenditure as a fiscal policy variable has a positive impact on investor returns, implying that a continual increase in government expenditure will result in the enhancement of firm profits and returns to investors by allowing stock prices to go up. Thus, market participants might assume that expansionary fiscal policy signals an increase in future returns. Further, a decline in interest rates and an increase in money circulation under monetary policy impacts positively on investors’ investment performance. As expected, an increase in money circulation in the economy will persuade investors to invest more in stocks as extra funds are available. These results have important implications for both investors and stock market analysts in their effort to understand the impact of fiscal and monetary policies on the stock return expectations of individual investors, but they should consider both fiscal and monetary policy decisions and their interactions together rather than in isolation.","PeriodicalId":363402,"journal":{"name":"Sabaragamuwa University Journal","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131175204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial Arrangements on Growth and Yield of Cowpea (Vigna unguiculata L. Walp.) in Intercropping","authors":"A. Maduwanthi, B. Karunarathna","doi":"10.4038/SUSLJ.V18I1.7755","DOIUrl":"https://doi.org/10.4038/SUSLJ.V18I1.7755","url":null,"abstract":"This experiment was conducted at the Crop Farm of Eastern University, Sri Lanka to evaluate the effect of different spatial arrangements on growth and yield of cowpea (Vigna unguiculata L. Walp) under okra (Abelmoschus esculentus L.) cowpea intercropping in sandy regosol. The experiment was laid out in a Randomized Complete Block Design (RCBD) having monocropping and different intercropping patterns. The results revealed that there was a significant difference (P 0.05) with different plating patterns. The study concluded that 60 cm between two rows with 150 cm between two pairs of rows of okra with three rows of cowpea in between paired rows would be the most suitable planting system to get maximum growth and yield of cowpea.","PeriodicalId":363402,"journal":{"name":"Sabaragamuwa University Journal","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123276743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Students’ Performance in Microeconomics: Evidence from Vavuniya Campus, Sri Lanka","authors":"A. Thayaparan, G. Gunathilaka","doi":"10.4038/SUSLJ.V18I1.7756","DOIUrl":"https://doi.org/10.4038/SUSLJ.V18I1.7756","url":null,"abstract":"This study examined the factors affecting the performance of undergraduate students in microeconomics at Vavuniya campus, Sri Lanka. For this purpose, a survey is conducted to collect the data using a sample of 85 students, who enrolled in microeconomics during their first year first semester in the academic year 2015/2016. The data on students’ performance in microeconomics measured in terms of their grades they obtained for the subject, demographic characters with family background and educational factors gathered from the questionnaire. The collected data was analyzed using frequency, chi- square test, ordered probit regression and marginal effects in the study. Frequency of the students’ grades revealed that, nearly 59% of them got grade B while 9.4% of them received grade A and 4.7%of the students received grade D. Chi - square test found that family stress and frequency of the study habits significantly associates with the students’ grades in the subject while the grade obtained in general English in G.C.E (A/L) and the usage of library facilities were less associated in the study. Results of ordinal probit model suggested that among the variables related to demographic characteristics with family background, gender and family stress are the good predictors of student performance in microeconomics whereas among educational factors allocation of time, economics as a subject taken by the students in G.C.E (A/L), mathematics knowledge and the usage of library facilities are the other best predictors in students’ performance in the subject.","PeriodicalId":363402,"journal":{"name":"Sabaragamuwa University Journal","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131924662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}