Browsing by Author "Attanayake, A. M. C. H."

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Factors associated with severity of road accidents in Gampaha police division in Sri Lanka
(Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Madhubhashini, M. G. A. K.; Attanayake, A. M. C. H.; Sooriyaarachchi, D. J. C.
Road accidents are main social problem in Sri Lanka, which causes immense damages and injuries unintentionally and unexpectedly. There are numerous factors, which contribute road accidents such as time of the day, road surface, weather, light condition, location, traffic density, traffic control availability, vehicle type, vehicle age, driver’s gender, driver’s age, license availability, usage of alcohol and etc. This study aims to identify the factors that mainly contribute to road accident severity in Gampaha Police Division through formulating an effective model. Altogether, 1375 data were collected from 2015 to 2017 from Police report of the Gampaha Police Division and the above mentioned 13 factors were considered. In this research 25% of the data were used for the validate the model and remain 75% of the data were used for build the model. Severity of accidents were categorized as fatal, grievous, damage only and non-grievous accidents. Chi-square test of independence has detected that road surface, light condition, location, traffic density, traffic control availability, vehicle type, driver’s age and usage of alcohol are the significant factors. The Location variable removed due to multicollinearity and remain significant factors used for Multinomial logistic model to model the severity of road accidents. The area under the ROC value was 59.2% for model building data and the area under the ROC value was 58.4% for model validation data. That means the developed model more accurately predicts the severity of accidents than the prediction in baseline model. Based on the results, it is discovered that traffic control availability increases the effect on the probability of a fatal accidents and fail of alcohol test, road surface and vehicle type decreases the effect on the probability of a fatal accidents. Moreover, traffic control availability and traffic density increase the effect on the probability of grievous category and alcohol test, vehicle type have negative impact on the probability of damage only accidents. Traffic density have positive impact on damage only accidents. The analysis shows different factors contribute a significant impact on the severity of road accidents. The result of this research is useful for police to understand factors affect on severity of road accidents and decrease the number of road accidents in future.
Forecasting COVID-19 Cases Using Alpha-Sutte Indicator: A Comparison with Autoregressive Integrated Moving Average (ARIMA) Method
(Department of Statistics & Computer Science, Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Attanayake, A. M. C. H.; Perera, S. S. N.
COVID-19 is a pandemic which has spread to more than 200 countries. Its high transmission rate makes it difficult to control. To date, no specific treatment has been found as a cure for the disease. Therefore, prediction of COVID-19 cases provides a useful insight to mitigate the disease. This study aims to model and predict COVID-19 cases. Eight countries: Italy, New Zealand, the USA, Brazil, India, Pakistan, Spain, and South Africa which are in different phases of COVID-19 distribution as well as in different socioeconomic and geographical characteristics were selected as test cases. The Alpha-Sutte Indicator approach was utilized as the modelling strategy. The capability of the approach in modelling COVID-19 cases over the ARIMA method was tested in the study. Data consist of accumulated COVID-19 cases present in the selected countries from the first day of the presence of cases to September 26, 2020. Ten percent of the data were used to validate the modelling approach. The analysis disclosed that the Alpha-Sutte modelling approach is appropriate in modelling cumulative COVID-19 cases over ARIMA by reporting 0.11%, 0.33%, 0.08%, 0.72%, 0.12%, 0.03%, 1.28%, and 0.08% of the mean absolute percentage error (MAPE) for the USA, Brazil, Italy, India, New Zealand, Pakistan, Spain, and South Africa, respectively. Differences between forecasted and real cases of COVID-19 in the validation set were tested using the paired t-test. The differences were not statistically significant, revealing the effectiveness of the modelling approach. Thus, predictions were generated using the Alpha-Sutte approach for each country. Therefore, the Alpha-Sutte method can be recommended for short-term forecasting of cumulative COVID-19 incidences. The authorities in the health care sector and other administrators may use the predictions to control and manage the COVID-19 cases
Fuzzy linear regression approach for modelling dengue disease transmission in Colombo
(Faculty of Science, University of Kelaniya Sri Lanka, 2023) Fernando, W. S. R.; Attanayake, A. M. C. H.
Dengue fever is caused by the dengue virus and is primarily transmitted through the bites of Aedes mosquitoes. Dengue fever is a significant public health concern in Colombo, Sri Lanka, with recurring outbreaks affecting a large number of individuals. Understanding the factors influencing dengue transmission is crucial for effective disease control and prevention. This study aims to explore a fuzzy regression approach for modelling dengue disease transmission in Colombo. As fuzzy linear regression incorporates uncertainty and imprecision into the modelling process, it has an advantage over conventional regression techniques. A fuzzy linear regression model was developed using various climate predictors, such as rainfall, relative humidity, wind speed, and temperature. Among these Climate variables, relative humidity and rainfall, are found to play a crucial role in mosquito breeding and the subsequent spread of the dengue virus. The fuzzy linear regression model is used to assess the relationships between these predictors and dengue transmission rates in Colombo. The suggested fuzzy linear regression model's evaluation criteria were done using R2 , Root Mean Squared Error, and Mean Absolute Error values. This study provides insights into the relationship between climatic factors and dengue transmission in Colombo by utilizing the above regression model. Climate variables, such as relative humidity and rainfall, are found to play a crucial role in mosquito breeding and the subsequent spread of the dengue virus. The findings highlight the importance of considering climatic predictors when developing dengue prevention strategies, particularly in urban environments like Colombo.
FUZZY LINEAR REGRESSION: AN APPLICATION TO HEART DISEASE
(Department of Statistics and Computer Science, University of Kelaniya Sri Lanka, 2021) Attanayake, A. M. C. H.
Disorders in heart condition refer to heart disease. Several risk factors are associated with causing the heart disease. Physical inactivity and smoking are leading risk factors among other risk factors. The aim of this study is to investigate the relationship of heart disease with physical activity and smoking. Regression analysis is one of the key areas that can be utilized in finding the relationship of variables. By considering heart disease as the output variable (dependent variable) and correlated other factors as input variables, one can model the relationship through multiple linear regression. Fuzzy regression is an application of fuzzy platform for conventional regression analysis. Fuzzy regression analysis gives a fuzzy relationship between dependent and independent variables which represents vagueness in the data. The input data may be crisp values or fuzzy numbers whereas the conventional ordinary least squares regression can handle only crisp measures. The model output is in the form of fuzzy representative which has lower and upper approximation models to represent the fuzziness of the output. Fuzzy models are especially suitable in modelling and predicting heart disease as the disease
Instrument to Measure Safety Climate: An Application to a Tyre Manufacturing Plant
(Department of Statistics & Computer Science, Faculty of Science, University of Kelaniya, Dalugama, Kelaniya (SRI LANKA);, 2021) Madurangee, L. H. L. S.; Attanayake, A. M. C. H.; Jayasundara, D. D. M.
ABSTRACT Occupational health and safety is a key feature in good governance. It depends on the safety culture of each and every person relevant to a work place. Culture means people think or act according to their opinions and beliefs by themselves without any external force. Positive safety culture gives benefits to both employee and employer. Therefore, measure the current status of safety culture is important to identify the areas which already improved and areas need to be improved. Safety climate is a descriptive measure that implies the status of the safety culture. Safety climate in a work place can be measured through the employees’ attitudes regarding the work place. A selfadministrative questionnaire can be used to collect the data as a productive method. The objective of the study was to develop a questionnaire as an instrument to measure safety climate in a work place through employees’ attitudes and validate the theoretical structure of safety climate with five dimensions. The questionnaire was designed based on literature survey under five dimensions. 30 Likert item questions were used to measure the 5 dimensions and Likert scaling technique was used to measure those five dimensions. Data were collected based on a tire manufacturing plant. Since these dimensions are highly correlated a pilot survey was conducted to identify ambiguities and difficult questions. A representative sample was selected using stratified sampling technique. The reliability of the questionnaire was measured using Chonbach’s Alpha statistic and Split –half Test. Confirmatory factor analysis was used to validate the theoretical structure. According to its results common factor was explained more than 80% of variance in each variables and model diagnostic tests showed that errors were satisfied the assumptions. The goodness of fit statistics showed that fitted model was acceptable. It can be concluded that the theoretically assumed structure to measure the safety climate with five dimensions is acceptable. This study provides a complete guidance on how to measure safety climate through a questionnaire and any interested parties may able to make their own measuring system based on the study.
Perceived value analysis of motorcycles in Sri Lanka
(Faculty of Science, University of Kelaniya, Sri Lanka., 2021) Chanika, P. A. L.; Attanayake, A. M. C. H.; Gunaratne, M. D. N.
The motorcycle is the vehicle with highest demand in Sri Lanka. Motorcycle usage in Sri Lanka is expanding rapidly over the years primarily due to its affordable price range. Customer perception refers to the customer's opinion of the service/product and evaluates through perceived value analysis. It is important to know the relationship between the price of motorcycles and customer perceived value of motorcycles for decision-makers in the automotive industry. The objectives of this study are to identify the attributes which are most important in formulating the customer perception towards motorcycle prices, identify the relationship between the price and customer perception of the motorcycles and calculate the perceived value for each motorcycle model under consideration. A total of 1117 customers were used to generate data with respect to 21 motorcycle models. Non- probability sampling techniques were appliedin the market survey, that gathered data on customer opinion on attributes such as brand, appearance, features, fuel efficiency, resale value, after-sale services, and suitability for road. were identified as the important attributes in formulating the customer perception towards motorcycle prices. Perceived value for each Commuter Standard, Commuter Deluxe, Sports Classic and Sports Premium motorcycle models were calculated by using the weightage of each attribute and rank of motorcycles. According to the Pearson correlation coefficient, there is a positive relationship between the actual price and the perceived value of motorcycles. Therefore, this analysis helps to understand purchasing decisions of customers and industry players can use this information for adjusting their pricing strategies against the market competition.
Proactive Dengue Management System Synergize by an Exponential Smoothing Model
(Research & Development Centre for Mathematical Modelling,Department of Mathematics, University of Colombo,Sri Lanka, Department of Statistics & Computer Science,Faculty of Science, University of Kelaniya, Kelaniya, Sri Lanka., 2021) Wetthasinghe, W. A. U. K.; Attanayake, A. M. C. H.; Liyanage, U. P.; Perera, S. S. N.
In a critical area like health sector centralized computer system helps to improve the efficiency of the health system. In particular, controlling an epidemic is usually difficult in developing countries. In this study we introduce a multi-platform, centralized proactive management system to manage dengue controlling activities in Sri Lanka. The system make common platform (ProDMS) for all sectors who contribute their services for mitigating dengue [1]. We mainly focused to the special feature of the system which enhance the centralized property. Cross platform environment was developed under this feature as a bridge to connect researches and general public. ProDMS is a internet base web application and researches can plug their dengue forecasting models to the system and publish their outputs as graphs through the web system. The ProDMS web application, which consisting of plug and play system architecture concepts, fully support for any statistical or mathematical model to publish its results online. In this work we use one of the univariate time series modelling approaches; namely exponential smoothing to plug with the system. This research helps to enhance efficiency of Dengue controlling process and support to generalize centralization.
Study on the selection of mobile service providers: Special reference to the students at Faculty of Science, University of Kelaniya.
(International Research Symposium on Pure and Applied Sciences, 2017 Faculty of Science, University of Kelaniya, Sri Lanka., 2017) Dassanayake, D. A. R. C.; Wijayawardhana, H. N. A. M.; Premathilaka, L. M.; Senarath, S. A. K. B.; Weerasekara, W. M. D. D.; Thilakarathne, K. H. K. D. S.; Goonetilleke, H. R.; Sandaruwan, B. H. S.; Winisinghe, W. T. D.; Kumara, J. L. S. M.; Attanayake, A. M. C. H.
Mobile service providers are important in the rapid development of telecommunication and information technology. Major mobile service providers in Sri Lanka are Dialog, Mobitel, Airtel, Etisalat and Hutch. The aim of this study is to understand the selection of mobile service providers in Sri Lanka by students of the Faculty of Science. The objectives are to identify the most popular mobile service provider among the students of the Faculty of Science and reason for it, categorize the most popular mobile service provider by gender, year of study and relationship type of students and measure the satisfaction on available facilities of service providers. A survey was conducted during the period of September – December 2016. Among the 1670 students registered in the Faculty of Science, 181 respondents were randomly selected using simple random sampling method (without replacement). An appropriate questionnaire was developed in order to gather data and achieve the objectives. After the initial pilot survey was conducted, a questionnaire was administered in person and online (for unavailable students) while personal interviews were also conducted to improve the response rate from students who had not responsed due to their heavy workload. The analysis reveals that the majority of students (67%) of the Faculty of Science preferred to use Mobitel, whereas 21% of the students preferred Dialog and only 5% of the students, used Airtel. Most of the female students (55%) preferred to use Mobitel as their mobile phone provider whereas 74% of male students preferred to use the same network. The main reason for their selection was cited as the providers’ wider coverage. The results remained the same for majority of students studying in the first, second, and third year. The results remained the same irrespective of the stuts, i.e. single, in a relationship or married category. When considering individual service providers, only Hutch users were 100% satisfied with their service. In conclusion, this survey discloses important findings about the selection of mobile service providers by students of the Faculty of Science.
TREND ANALYSIS OF FINANCIAL PERFORMANCE OF THE BANK OF CEYLON, SRI LANKA
(Department of Statistics and Computer Science University of Kelaniya Sri Lanka, 2021) Attanayake, A. M. C. H.; Liyanage, N.
Trend analysis is important in banking to analyze and predict their financial statements. The aim of this study is to analyze the trend of key financial performance indicators; profit, advances and deposits of the Bank of Ceylon, Sri Lanka. Non-parametric loess analysis, Sen’s slope, linear/quadratic trend modeling, growth curve fitting and change point analysis were implemented to understand the trend pattern of the data. Results revealed that quadratic trend model was suited for advances and growth curves for both deposits and profits. The loess analysis detected upward trends for both advances and deposits but it was nearly horizontal for profit. The estimated slopes of the trends were significant in the Sen’s slope of three financial indicators. Potential significant changing points were detected in all