Faculty of Computing
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Publication Embargo CodeJr: Comprehensive Programming Application for Children(IEEE, 2022-12-09) Muthuthanthirige, M.D.C. J; Illangasinghe, U.P; Illangasinghe, D.N; Halgaswatta, I.; Samarakoon, U; Amarasena, NSince the beginning of the millennium, computer technology has been the key area of concern and developing essential programming knowledge and intellectual skills from the young age have proven that they will gain more success in their careers. The ideology behind this research is, the problem with absence of a complete multi-disciplinary and interactive programming application for children between the age of 10 - 15 years, to learn programming concepts with a well-established text-based programming language. There are 4 major approaches in this research. Gamification approach focuses on expressing knowledge about Python programming via a game while concentrating on low perfumers. Collaborative approach aims to deliver a brand-new experience for children by aggregating cooperative methodologies and Artificial Intelligence with learning to enforce mutual learning. This component is based on collaborative sessions which allow a group of students with similar interest to join to learn python programming. Drag-drop approach enables children to learn Python language through videos and will be given basic practice questions after finishing the course. Story telling approach guides children to learn programming concepts step by step using story telling. Focused on storytelling approach and interactivity via voice conversation to learn programming language for children.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 Embargo Comprehensive Forensic Data Extraction and Representation System for Windows Registry(IEEE, 2019-12-05) W. De Alwis, C; Rupasinghe, LComputer forensics is the process of methodically examining computer media (hard disks, diskettes, tapes, etc.) for evidence. When considering computer forensics, registry forensics plays a vital role because it helps identifying system configurations, application details, user configurations and helps in finding registry malware. Therefore, it is significant to extract this registry information to simplify the investigations for forensic professionals. At present, tools are limited to few commonly used registry information and there is a much border area to cover. Investigators have to manually search for the registries for required artifacts. But the nature and complexity of the registry file structure limits most of the investigators using these registries. Limiting this registry analysis only to the physical registry files and not considering the ability of extraction of registry information from Volatile Memory is another significant issue in registry forensics. Because these tools are only rely on the physical registry files and cannot extract registry artifacts from Volatile Memory. In order to cater to this problem, this research provide a comprehensive solution to registry analysis. This system is capable of extracting registry information from both physical registry files and Volatile Memory.