Symposia & Conferences
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Item 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.Item Economic determinants of suicides in Sri Lanka over the period 1975 – 2015.(International Research Symposium on Pure and Applied Sciences, 2017 Faculty of Science, University of Kelaniya, Sri Lanka., 2017) Devindi, R. P. D. C. S.; Kulatunga, D. D. S.Suicide is a major public health problem in the world. According to the World Health Organization, every 40 seconds, a person commits suicide somewhere in the world. In Sri Lanka a steady increase of suicides has been reported and it stands in the fourth place among the countries with high occurrences of suicides in 2015. Further suicide is one of the major causes of death in Sri Lanka. There are many studies done in Sri Lanka to investigate the variations in suicide rates in relation to age, gender, method and reason specific trends and geographical distributions. But there are no previous studies done to identify the economic determinants using a dynamic econometric model of suicides on the basis of time series data. This study investigates the association of economic conditions with the suicide rates among male, female and general population in Sri Lanka over the period 1975-2015.The data for suicides from 1975 to 2015 was taken from the Registrar General Department and Police Department of Sri Lanka. The effective suicide rates were computed as the number of suicides per 100,000 population. The unemployment rate, GDP growth rate, inflation and fertility rates for 1975-2015 were taken from the Department of Census and Statistics. In our analysis, overall suicide rate, male suicide rate and female suicide rate are taken as dependent variables, and unemployment rate, GDP growth rate, inflation and fertility rate as independent variables in each case. Because of the time series nature of the variables, Autoregressive Distributed Lag (ARDL) regression model is employed to identify the long run relationship between the dependent variable and explanatory variables. The analysis reveals that, for the general population the incidence and rate of suicide increase with the increase in unemployment rate and inflation. Further, the male suicide rate increases with the increase in unemployment and inflation. The positive coefficient of the unemployment rate supports the increase in female suicides. In general, the ARDL models reveal the association between suicide and three economic variables; inflation, unemployment and GDP growth. The inflation and unemployment enhance the incidence of overall suicides and male suicides, while only inflation supports the incidence of female suicides in the long run in Sri Lanka. There are some limitations in the analysis due to the unavailability of information of several economic factors. The results obtained in this analysis would be helpful for a comprehensive work on economic determinants of suicides in Sri Lanka.