Browsing by Author "Ranawaka, R. A. C. S."

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Feasibility of the use of Wavelet theory for the analysis of climate changes
(4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Ranawaka, R. A. C. S.
Climate is the most important component that affects the environment, with direct and indirect influences of human activities. Generally, climate is the average weather prevailing over an area. The climate is dynamic in many ways, for example, changes in time and space, and the changes occur over fairly long time. Climate change is the change of patterns of climate factors of a region in the particular time period. The purpose of this study is to apply the Wavelet techniques for analyzing the climate changes of two districts of Sri Lanka. The two districts representing two different provinces were chosen for the study, which are Ratnapura and Hambantota. Ratnapura district has a wet climate zone whereas Hambantota represents dry zone of the country. The analysis was carried out through monthly secondary data of last twenty-four years (1990-2013) which were collected from the Department of Meteorology, Sri Lanka. Although there are several climatic factors affect the climate change; this study examines climate factors such as diurnal variation of temperature, maximum and minimum humidity and rainfall. This paper shows the application of the Wavelet transform for each climate factor other than the time series. Further, cross wavelet analysis is also conducted. The Wavelet analysis is frequently used as a tool to study the periodicity in climate time series since that is a method to decompose a time series-frequency space. According to the result of periodic patterns, it is possible to predict the future climate of regional and global. Wavelet can be introduced as the next level with a Fourier series. When Wavelet transform localizes both time and frequency, the Fourier transforms localize only the frequency. The collected data were analyzed to obtain Box plots, Time Series and Scatter Plots with the MINITAB software and Power Spectrums with the R Software. The box plot analysis demonstrates the dispersion of monthly data of each factor. The results concluded that the highest rainfall occurred in October and November for both districts. Furthermore, in both districts, the maximum the Diurnal variations of temperature and maximum relative humidity occurred in February and November respectively. Periodicities (monthly/annually band) of each factor for both districts were identified by the Wavelet Analysis. For the diurnal variation of temperature, there is a dominant constant annual oscillation in Ratnapura for the whole 24 years. Hambantota also has an annual periodicity for the whole 24 years, except years between 999 - 2003. It shows that 4 - 8 and 8 - 16 monthly band periodicities have occurred in both Ratnapura and Hambantota before 1998 for the maximum relative humidity. Similarly, the results can be interpreted for all factors. As future work, this can be applied to the whole country with the improved mathematical program through modern mathematical tools.
Learning analytics intervention and evaluation of factors associated with student academic performance in SLTC education study programs
(4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Ranawaka, R. A. C. S.; Perera, W. A. S. N.
The value of education and its significance is important for human beings as it helps in the personal, social and economic development of the nation. The performance of students plays a vital role in order to develop quality graduates from higher educational institutions and it will eventually lead to increased employment. It is imperative either that diagnostic methodology should be implemented to identify and examine the major factors, which affect the suboptimal academic performance of students. The purpose of this this research is to explore the qualitative and quantitative factors that are associated towards the academic performance of students. Sri Lanka Technological Campus (SLTC) has been offering approved Engineering Degree Program since 2016. Batch 3, 4, 5 and 6 undergraduates from the school of Engineering, were selected as the target population of this study and sample was selected by simple random sampling technique. A questionnaire was distributed among the respective respondents to collect data to identify the qualitative and quantitative factors that affect on student academic performance. The collected data from the questionnaire were analyzed with the Statistical Package Minitab 2017. We collected the data related to learning, teaching, attendance, involvement of extracurricular activities and non-academic activities, course assessment, peer influence and family issues, to identify socially, emotionally or academically unprepared students. Chi-square test, Correlation analysis and multiple regression were used analyze the data. A multiple regression model was fitted to identify the strength of each factor, which affected the academic performance of students using quantitative and qualitative data with the model validation. Furthermore, the fitted model was significant by the P-test. There is a high correlation among the dependent and independent variables as academic performance of student in SLTC, attendance, language of delivering the course and the delivery method, class size of students and non-academic activities. It is recommended that study background and family back ground are highly affected to the student performances. Early identification of factors that affect on student academic performance help to overcome the major problem of higher education, which is the right balance of enrolled and graduated students