Research Publications Authored by SLIIT Staff
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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.
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Publication Embargo An Analysis on Different Distance Measures in KNN with PCA for Android Malware Detection(IEEE, 2022-11-30) Dissanayake, S; Gunathunga, S; Jayanetti, D; Perera, K; Liyanapathirana, C; Rupasinghe, LAs Majority of the market is presently occupied by Android consumers, Android operating system is a prominent target for intruders. This research shows a dynamic Android malware detection approach that classifies dangerous and trustworthy applications using system call monitoring. While the applications were in the execution phase, dynamic system call analysis was conducted on legitimate and malicious applications. Majority of relevant machine learning-based studies on detecting android malware frequently employ baseline classifier settings and concentrate on selecting either the best attributes or classifier. This study examines the performance of K Nearest Neighbor (KNN), factoring its many hyper-parameters with a focus on various distance metrics and this paper shows performance of KNN before and after performing Principal Component Analysis (PCA). The findings demonstrate that the classification performance may be significantly improved by using the adequate distance metric. KNN algorithm shows decent accuracy and improvement of efficiency such as decreasing the training time After PCA.Publication Embargo Supply and Demand Planning of Electricity Power: A Comprehensive Solution(IEEE, 2019-12-06) Perera, S; Dissanayake, S; Fernando, D; De Silva, S; Rankothge, WElectrical energy is one of the fastest growing energy demands in the world. Uncertainty in supplying the demand can threaten the social economic aspects of a country. The biggest driver of electrical demand is weather. Climatic changes not only affect the demand but also renewable energy supply. Wind and Solar are two alternative energy sources with less pollution. We have proposed a platform which helps energy providers, energy traders with services related to electricity supply and demand planning, with following modules. (1) Forecasting electricity consumption patterns (2) Forecasting wind power generation (3) Optimizing Load Shedding. Our platform has been implemented using statistical and machine learning techniques: Multi-Linear Regression for consumption prediction, Random forest regression for wind power forecast, and genetic algorithm to optimize load shedding. Our results show that, using our proposed module, we can minimize the imbalance between the supply and demand of electricity by predicting the consumption patterns of consumers, predicting the wind power generation and by selecting the best feeder to be selected for load shedding under given constraints.Publication Open Access Restraint usage characteristics and other factors associated with safety of children involved in motor vehicle crashes(David Publishing, 2016) Dissanayake, S; Amarasingha, NInvolvement in road traffic crashes as vehicle occupants is a leading cause of death and serious injury among children. The objective of this study was to investigate crash severity factors and child safety restraint use characteristics in order to identify effective countermeasures to increase children’s highway safety. Characteristics and percentages of restraint use among child passengers aged 4~13 years were examined using highway crash data from Kansas. The association between restraint use, injury severity and characteristics of children involved in crashes were investigated using OR (odds ratios) and a logistic regression model, which was used to identify risk factors. Results showed that children, who were unrestrained, were seated in the front seat, traveling with drunk drivers and on rural roads, and traveling during nighttime was more vulnerable to severe injury in the case of motor vehicle crashes. The most frequent contributing causes related to crashes involving children included driver’s inattention while driving, failure to yield right-of-way, driving too fast, wet roads and animals in the road. Based on identified critical factors, general countermeasure ideas to improve children’s traffic safety were suggested, including age-appropriate and size-appropriate seat belt restraints and having children seated in the rear seat. Parents and children must gain better education regarding these safety measures in order to increase child safety on the road.Publication Open Access Household travel survey method for vehicle kilometers travel estimations: A case study in a developing country.(2021-05-01) Gunathilaka, S; Amarasingha, N; Dissanayake, S; Lakmali, MVehicle Kilometers Travelled (VKT) represents number of kilometers travelled by vehicles during a specific period of time in a specific area of concern. Transportation planners, policy makers, urban planners, and estimators of vehicle emission, energy consumption and fuelprice encourage the calculation of VKT for various analytical purposes. However, in most of the developing countries VKT is not estimated due to data challenges. This study aimed at proposing a household travel survey method for estimating VKT in developing countries where timely VKT data are not available. Also, estimating Personal Kilometers Travelled (PKT) seems important in developing countries, since the majority is using public and non-motorized transport modes rather than personal vehicles in those countries. This proposed method allows to collect data that are needed for estimating both VKT and PKT together with socio demographic information. A case study was conducted in three different regions; Northern, Eastern and Southern areas of Sri Lanka, which is a developing country. Questions were asked regarding to trips in a typical week, trips in holidays, special seasons or vacations, number of passengers travelled, travel modes and, socio demography of the respondent. Pilot surveys were conducted prior to the actual surveys to verify the efficiency of developed questionnaire. Samples were taken satisfying all the selected socio demographic categories within the community. Collected data through surveys were aggregated to annual level and, weighted using relevant census and population data. Weighted VKT and PKT estimates were obtained under each selected socio demographic category. Also, VKT estimates were statistically compared for studying the travel behavior of people across different regions. ANOVA and Post Hoc tests were employed for statistical comparisons. These findings can efficiently be used for transport planning, policy making activities, emission calculations, energy consumption estimations etc. by transport and environmental agencies of the country. The case study revealed the experience of utilizing the household travel survey method in Sri Lanka, making it possible to be replicated in other developing countries as well.Publication Embargo Gender differences of young drivers on injury severity outcome of highway crashes(Pergamon, 2014-06-01) Amarasingha, N; Dissanayake, SProblem: Gender differences of young drivers involved in crashes and the associated differences in risk factors have not been fully explored in the United States (U.S.). Accordingly, this study investigated the topic, where the odds ratios (ORs) were used to identify differences in crash involvements between male and female young drivers. Method: Logistic regression models for injury severity of young male drivers and young female drivers were developed. Different driver, environmental, vehicle, and road related factors that have affected young fe- male drivers' and young male drivers' crash involvements were identified using the models. Results: Results in- dicated that some variables are significantly related to female drivers' injury risk but not male drivers' injury risk and vice versa. Variables such as driving with valid licenses, driving on weekends, avoidance or slow maneu- vers at time of crash, non-collision and overturn crashes, and collision with a pedestrian were significant vari- ables in female driver injury severity model but not in young male driver severity model. Travel on graded roadways, concrete surfaces, and wet road surfaces, collision with another vehicle, and rear-end collisions were variables that were significant in male-driver severity model but not in female-driver severity model. Summary: Factors which increase young female drivers' injury severity and young male drivers' injury severity were identified. This study adds detailed information about gender differences and similarities in injury severity risk of young drivers. Practical applications: It is important to note that the findings of this study show that gender differences do exists among young drivers. This sends a message to the industry that the transportation profes- sionals and researchers, who are developing countermeasures to increase the traffic safety, may need to pay attention to the differences. This might be particularly true when developing education materials for driver train- ing for young/inexperienced driversPublication Embargo Intelligent Digitalization of the Sinhala Form Templates(IEEE, 2021-12-07) Gomez, K; Jinadasa, M; Dantanarayana, V; Dissanayake, S; Kodagoda, N; Kuruppu, TIn Sri Lanka, most of the population uses the Sinhala Language as their first language to communicate and for documentation in most government departments. It is evident that the digitalization of the Sinhala Language is essential in a country like Sri Lanka. The specialty of Sinhalese characters is that they have very tiny differences in feature, and the number of different characters formed from the letters of the Sinhala alphabet and its elements is relatively high, leading to the classification among the Sinhala letters becoming quite a complex task. Previous proposed research case studies involved machine learning based feature detections related to rule-based theories and geometry features that had average accuracy rates, which indicate that further improvement is required with new features. Consequently, in this research paper, a Deep Learning Character Classification method for Sinhala OCR is proposed, which is for both Printed and Handwritten Sinhala texts as well as an Intelligent Sinhala Form Automation technique to read both answers and questions in an application to convert them into e-texts. The converted e-texts will be sharpened and fixed through a Sinhala Spelling & Grammar checking feature that is developed in the system more intelligently. In this research work, it was a success to obtain an overall accuracy level of more than 90% considering all components.