Faculty of Computing
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Publication Open Access A Framework for Macroeconomic Stress Testing on Credit Risk Management in Banking Sector(researchgate.net, 2017-08) Kandawala, D. S. A; Jayakody, J. A. D. C. A- In Sri Lanka the financial System composes the leading financial institutions which are associated with increased growth of an economy and contributes to the nation’s growth as well. Hence Financial system stability has become an integral part which safeguards financial system which is able to hold off external and internal shocks. This Process implements a healthy environment for investors and encourages financial markets and institutes for the efficient and effective functioning. The maintenance of financial system stability leads to analyze and emphasize potential vulnerabilities and risks to the financial system. Among the potential vulnerabilities and risks, Credit risk can be introduced as the dominant and leading macroeconomic risk factor in many banking sectors which has been introduced as the problem towards the financial system stability. Therefore Credit risks must be managed from financial crisis to enhance the performance, sustainable growth and consistent profitability for the betterment of financial system stability. The purpose of this research project is to propose a framework to investigate the relationship between credit risk management and its impact on performance of the Sri Lankan Banking Sector.Publication Open Access Experimental study on an efficient dengue disease management system: Planning and optimizing hospital staff allocation(The Science and Information (SAI) Organization, 2018-01) Jayasuriya, M. M. C; Galappaththi, G. K. K. T; Sampath, M. A. D; Nipunika, H. N; Rankothge, WDengue has become a serious health hazard in Sri Lanka with the increasing cases and loss of human lives. It is necessary to develop an efficient dengue disease management system which could predict the dengue outbreaks, plan the countermeasures accordingly and allocate resources for the countermeasures. We have proposed a platform for Dengue disease management with following modules: (1) a prediction module to predict the dengue outbreak and (2) an optimization algorithm module to optimize hospital staff according to the predictions made on future dengue patient counts. This paper focuses on the optimization algorithm module. It has been developed based on two approaches: (1) Genetic Algorithm (GA) and (2) Iterated Local Search (ILS). We are presenting the performances of our optimization algorithm module with a comparison of the two approaches. Our results show that the GA approach is much more efficient and faster than the ILS approach.Publication Open Access Hashtag Generator and Content Authenticator(researchgate.net, 2018-01) Yapa Abeywardena, K; Ginige, A. R; Herath, N; Somarathne, H; Thennakoon, T. M. N. SIn the recent past, Online Marketing applications have been a focus of research. But still there are enormous challenges on the accuracy and authenticity of the content posted through social media. And if the social media business platforms are considered, majority of the users who try to add a market value to their own product face the problem of not getting enough attention from their target audience. The purpose of this research is to develop a safe and efficient trending hashtag generating application solution for social media business users which generates trending and relevant hashtags for user content in order to get a broad reach of target audience, automatically generates a meaningful caption to their relevant posts and guarantees the authenticity of the product at the same time. The user content is analyzed and filters the important keywords, generates a meaningful caption, suggest related trending keywords and generates trending hashtags to get the required reach for online marketers. Additionally, the marketing products’ content authentication is ensured. The application uses Natural Language Processing, Machine Learning, API technologies, Java and Python technologies. A unique database is assigned to users which contains rankings for each user. The target audience who engages in buying products get to know about the status of the sellers with respect to authenticity of the content. It is believed that the application provides a promising solution to existing audience reach problems of online marketers and buyers. The significance of this system is to help marketers and buyers to engage in online buying and selling with much effective, reliable and safer ways. This mitigate the vulnerability of bad social media marketing influences and helps to establish a safe and reliable online marketing practice to make both sellers and buyers happy. This paper provides a brief description on how to perform an organized online marketing discipline via the Trending Hashtag Generator & Image Authenticator application.Publication Embargo Quantification of machine effectiveness in building and construction industry(IEEE, 2018-02-08) Weerasinghe, H. M; De Silva, D. HBuilding and Construction industry highly depends on different kinds of heavy machines and machinery vehicles when it comes to performing different construction tasks. Since the current industry is not heavily concerned about measuring the effectiveness of machines, a considerable amount of budget is wasted due to the misuse of machines. Hence, there should be a proper method to monitor their effectiveness and to eradicate their misuse. Effectiveness can be achieved by analyzing the matrices, Availability, Performance, and Quality. Availability measurements can be acquired by analyzing the machine's on/off times and also the idle times, and by introducing a GPS and sensor equipped tracking device, the availability of machines can be tracked. The device is capable of acquiring the geographical location and the on/off state of the machine. Performance can be acquired by analyzing the task and the details of the machine. Excavating, Digging, Scraping, Spreading, and Loading are some of the construction activities and different machines are used for different purposes. This paper reports on a reliable way of calculating the performance by using specially designed algorithms for each type of machine. The algorithm uses a data driven questionnaire for each and every machinery vehicle to evaluate the quality factor. Each question has a weightage value where questions can be rated based on the value. By analyzing and calculating the outputs of availability, performance and quality factors, the system is able to calculate the effectiveness of the machine.Publication Embargo Learning platform for visually impaired children through artificial intelligence and computer vision(IEEE, 2018-02-19) Balasuriya, B. K; Lokuhettiarachchi, N. P; Ranasinghe, A. R. M. D. N; Shiwantha, K. D. C; Jayawardena, CThe topic Visual Disabilities and Computer Vision are the most researched topics of recent years. Researchers have been trying to combine two topics to create most usable systems to the visually disabled to aid them in their day to day tasks. In this research, we are trying to create an application which is targeting children between the age of 6-14 who suffers from visual disabilities to aid them in their primary learning task of learning to identify objects without a supervision of a third-party. We are trying to achieve this task by combining latest advancements of Computer Vision and Artificial Intelligence technologies by using Deep Region Based Convolutional Networks (R-CNN), Recurrent Neural Networks (RNN) and Speech models to provide an interactive learning experience to such individuals. The paper discusses.Publication Embargo Social media based personalized advertisement engine(IEEE, 2018-02-19) De Silva, H; Jayasinghe, P; Perera, A; Pramudith, S; Kasthurirathna, DOnline advertising has become a global phenomenon that affects the retail market substantially. Advertisements engines are an effective solution to the mobile application market to push advertisements. This paper reports evidence that AdSeeker, User Preference Based Advertisement Engine Based on Social Media is an effective solution to improve the business value of the marketing and advertising. Since the internet is used by vast number of people, it essentially needs a comprehensive method to push personalized advertisements to the right people. Adseeker is a system built using ontological mapping and social media content based semantic analysis to direct personalized. Identifying personal relationship hierarchy, and ontological approach for advertisement classification helps to identify the most appropriate advertisement for each user. AdSeeker uses the tweets posted by users to capture the preference of each and every user. Each user pushed advertisements based on their individual preferences. Based on the social experiments done using Adseeker, we could demonstrate that the social media profile based advertising is effective in providing highly relevant advertisements.Publication Embargo TreeSpirit: Illegal logging detection and alerting system using audio identification over an IoT network(IEEE, 2018-02-19) Kalhara, P. G; Jayasinghearachchi, V. D; Dias, A. H. A. T; Ratnayake, V. C; Jayawardena, C; Kuruwitaarachchi, NIllegal logging has been identified as a major problem in the world, which may be minimized through effective monitoring of forest covered areas. In this paper, we propose and describe the initial steps to build a new three-tier architecture for Forest Monitoring based on Wireless Sensor Network and Chainsaw Noise Identification using a Neural Network. In addition to detection of chainsaw noises, we also propose methodologies to localize the origin of the chainsaw noise.Publication Open Access Recommending a Model to Forecast Sri Lanka Wholesale Price Index Using Big Data Analytics(IEEE, 2018-02-22) Thakshila, P. M. C; Asanka, P. P. G. DThe Whole Sale Price Index (WPI) is a main index, which is used to measure price variance before a product or service release to a consumer. WPI represents the basket of wholesale goods and services on market basket. Sri Lanka WPI is accumulated using Laspeyre's formula considering based year as 1974 and up till now not seasonally adjusted. Data collection, compilation, and Dissemination of WPI are done by Prices, Wedges, and Employment division of the Statistics Department of Central bank of Sri Lanka (CBSL) and releasing to public every month. Forecasting of WPI is necessary to understand the aid primary level economic impact of the country. Big data analysis and Data mining are using for data where it is hard to handle using traditional tools and techniques. Decision makers able to gain valuable insights analyzing that varied and rapidly changing data. Time series analysis compromise method for analyzing time series data in order to extract meaningful statistics and other characteristics of data. This review discusses the way to utilize big data analysis technology to systematically analyze time series based WPI data in Sri Lanka. The time series based forecast technologies ARIMA, ANN, VAR, Moving Average, AFARIMA etc. are reviewed based on previous findings. Based on the result will present the effective model to forecast WPIs in Sri Lanka and will critically evaluate selected WPIs. That selection will coordinate based on the weight and relationship to all items based WPI. WPI will compare with existing Sri Lankan Price Indices based on the relational factors.Publication Embargo Impact Analysis of US Dollar Index Volatility on Imports and Import Categories of Sri Lanka(IEEE, 2018-07-31) Sahabandu, R. V; Asanka, P. P. G. DThe economic liberation in 1977 resulted in drastic changes in many aspects of Sri Lanka. Considering about 1978-2015, the country yearly import demand represents over 30% share of the gross domestic product (GDP) except 1984, 2009, 2010, 2013-2015. Investigations and the studies on a countries' imports are surprisingly overlooked as there are several studies being carried out focusing only the aggregated export volume concerning the exchange rate volatility. The monthly data of Sri Lanka imports, import categories and monthly US Dollar (USD) volatility from January 2007-December 2016 were used for the analysis. This study tries to learn the impact of US Dollar Index (USDX) volatility on import demand of Sri Lanka. The Autoregressive Distributed Lag (ARDL) Approach is employed to learn long-term and short-term cointegration among the underlying variables. There exists a 95% statistically significant short-run relationship and it is identified that the import categories, Consumer Goods (CG), Intermediate Goods (IG), Investment Goods (INV), Unclassified Items (UI), None-Oil Imports (NO) have a speed of adjustment to the equilibrium (SAE) in the long-run of 17%, 36%, 23%, 23%, 25% respectively. The total imports reveal that the disequilibrium conditions will be resolved by 27% within a period of one month that is shocked due to the USDX volatility. Knowledge of the relationship between USDX fluctuation, exchange rate volatility and import volume will support to pursuit for a beneficial trade and prevent or be prepared for a much more stable situation within Sri Lanka.Publication Embargo Towards a Smart City: Application of Optimization for a Smart Transportation Management System(IEEE, 2018-12) Thiranjaya, C; Rushan, R; Udayanga, P; Kaushalya, U; Rankothge, WIntelligent traffic planning, the efficiency of public transport and the improved connectivity of all road users in a city, comprise the mobility characteristics of a smart city. In the era of smart cities, efficient and well managed public transportation systems play a crucial role. The planning and allocation of public transportation systems, especially the public bus scheduling is one of the major resource allocation problems where the optimal resource allocation increases the passenger's as well as bus owner's satisfaction. In this research, we have proposed a platform for public transportation management, especially for optimal planning and scheduling of buses. We have used two approaches for our algorithms: Iterated Local Search (ILS) and Genetic Algorithm (GA). In this paper, we are presenting our optimization algorithms and their performances. Our results show that, using our algorithms, we can decide the optimal allocations of buses and plan the bus schedules dynamically in the order of seconds.