Research Papers - Dept of Software Engineering

Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/1022

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Subject: search.filters.subject.Artificial Intelligence

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Now showing 1 - 5 of 5
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    Artificial Intelligence-Based Centralized Resource Management Application for Distributed Systems
    (IEEE, 2022-12-26) Hettiarachchi, L.S; Jayadeva, S. V; Bandara, R.A.V; Palliyaguruge, D
    Due to the decentralized nature and emergence of new practices, tools, and platforms, microservices have become one of the most widely spread software architectures in the modern software industry. Furthermore, the advancement of software packaging tools like Docker and orchestration platforms such as Kubernetes enable developers and operation engineers to deploy and manage microservice applications more effectively and efficiently. However, establishing and managing microservice applications are still cumbersome due to the infrastructure configuration and array of disjoint tools that fail to understand the application’s dynamic behavior. As a result, developers need to configure multiple tools and platforms to automate the deployment and monitoring process to provide the optimal deployment strategy for microservices. Even though many tools are available in the industry, the fully automated product which comprises deployment, monitoring, resiliency evaluation and optimization were not developed yet. In response to this issue, we propose an artificial intelligence (AI)-based centralized resource management tool, that provides an automated low latency container management, cluster metrics gathering, resiliency evaluation and optimal deployment strategy behave in dynamic nature.
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    GLIB: Ameliorated English Skills Development with Artificial Intelligence
    (IEEE, 2020-10) Srikanthan, P; Nizar, R; Ravikumar, A; Lalitharan, K; Harshanath, S. M. B; Alosius, J
    In language learning, most of the learners can learn the theory and memorize the sound of a language. However, the ability to speak and learn a language properly requires good practice, experience and good learning strategies. This research is an approach to innovate and improve the language learning strategies along with practices that help to improve the language skills for non-native learners and children who are in the early stage of learning. In this research, the English language will be used to experiment with our solution as the source due to its demand and familiarity in the world. This research is focused on four main skills such as conversation skills, pronunciation skills, listening skills and grammatical skills. This research is done by analyzing the difficulties in each of the skills mentioned above and also discusses and provides details about the solution implemented to improve learning English in an efficient way. The implementation of this research is done by using technologies like natural language processing, machine learning, and deep learning approaches to come up with components to train the learner. The application of this research is delivered by using a cross-platform application called GLIB. The name GLIB is inspired by a library in C language which represents fluency. This mobile application provides facilities to improve all the English language skills mentioned above along with guides, tips, practices, and feedback based on an evaluation to improve the English language.
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    Thuryalankara: Artificial Intelligence Based Audio Plugin For Sri Lankan Percussion Instruments
    (IEEE, 2021-12-01) Fernando, P. D. C; Fernando, B. A. N; Wanaguru, I. U; Perera, M. A. P. A; Buddhika, T; Kodagoda, N; Ganegoda, D
    Sri Lankan music is yet to prove its musical prowess by incorporating artificial intelligence tools, therefore, this research introduces a novel invention, an automated audio plugin for music producers, so the process of creating, mixing, mastering, and producing music is easier. To achieve this, the research introduces a Variational AutoEncoder (VAE) machine learning model to create and generate music, an artificial intelligence (AI) system that can automate the mastering process. This research also introduces an innovative component, a virtual instrumentation tool using MIDI technology for the Sri Lankan percussion instruments that allow users to play the instrument virtually using a MIDI keyboard, and alongside it, a preset beat generator that automatically maintain tempo consistency. Thuryalankara was able to receive a collective average of 80% accuracy rate exceeding the predicted accuracy rate of 65% from the software benchmarking test and the physical survey conducted with music producers. Finally, with the inclusion of powerful tools like this, the ultimate objective of this research is to take the Sri Lankan instruments to the international level where any producer from little to plenty experience is able to use this plugin to enhance their musical production.
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    A step towards a Natural Language Programming Tool (NLPT)
    (Researchget.net, 2014-06-13) Perera, K. J. A; Kuruppu, K. A. I; Gamage, M. P; Jayakody, J. A. P. B; Gunasekara, K. S. G. S; Kodagoda, N
    This research project is taking a step towards developing a tool that can facilitate Natural Language Programming (NLP). As a result Natural Language Programming Tool (NLPT) is designed that generates source codes in response to Natural Language (NL) instructions. The major issue that needs to be addressed is identifying the meaning of the user’s NL instruction. The research is aimed at solving the fundamental problems of symbolic NL understanding which is an evolving research area. As NL consists of a broad vocabulary Basic Mathematical Calculations and Basic Input/Output Operations are selected as the project domain. NLPT can be used as a programming tool to generate the relevant source code, plays as an interactive programming learning tool and serves as a brainstorming tool.
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    Virtual Dressing Room: Smart Approach to Select and Buy Clothes
    (2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Weerasinghe, S.W.P.N.M.; Rajapaksha, R.M.D.D.; Sathsara, L.G.I.; Gunasekara, H.S.D.N.; Wijendra, D.R.; De Silva, D.I.
    The clothing industry portrays a major part of a respective country`s economy. Due to the predilection for clothing items of the people have led to the increasing of physical and online clothing stores in all around the world. Most of the people are used to go to the physical shopping and purchase their desired clothing items. But, as a consequence of the current pandemic situation, most of the people are unable to step out from their homes. This application is intended to cater an opportunity to the customers, who are not able to reach the physical clothing stores due to a pandemic situation and mobility difficulties. In addition, this application diminishes the time wastage, clothing size mismatches and the lesser user satisfaction ratio inside a physical clothing store. A customized 3D model has featured in the application to cater the virtual fitting experience to the customer. And the AI chatbot assistant in the application interacts with the user while catering virtual assistance for a better cloth selection process. In addition to that, this application has concentrated on the clothing shop by providing a future sales prediction component utilizing the K-Nearest Neighbors algorithm to provide an aid to their business commitments.