Department of Computer Science and Software Engineering-Scopes

Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/2177

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Aspect Based Sentiment Analysis for Evaluating Movies and TV series Publisher: IEEE Cite This PDF
(2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Cooray, T.; Perera, G.; Chandrasena, D.; Alosius, J.; Kugathasan, A.
Aspect-based sentiment analysis (ABSA) is used in different fields for analyzing customer reviews to project an overall customer opinion on certain products. With the expansion of the internet, people are provided with an inexpensive and time-saving method to express their opinion to a larger audience, while various industries are handed with the opportunity to gather free information from it to obtain market value. The implementation of machine learning methods for the evaluation of aspects related to movies and television series has not been commenced, and it could be a new development for the industry. This study focuses on conducting an ABSA on a movie or a television series based on genre, story as well as cast and crew aspects. The data collected from social media through web scraping is processed to produce adequate results to get a broad understanding on how the popularity of the movie or the television series related to above mentioned aspects. Then, each aspect is further analyzed to gather precise information belonging to each aspect. The accuracy of the results of the proposed system has been achieved over 79%. The results proved that the solution is highly successful than the former works with high business value.
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Assisting Wheelchair: Assist W
(IEEE, 2021-12-07) Ranaweera, D; Athalage, C; Sri Virajamana, M; Kaveesha, C; De Silva, D. I; De Silva, H
Traditional wheelchairs used by disabled people are required to be controlled manually. Hence, continuous monitoring and assistance of a caretaker is a mandatory requirement. This paper introduces an autonomous assisting wheelchair - Assist W, which would facilitate disabled people to do their day-to-day activities independently in a very safe manner, thereby managing their mental and physical health. Assist W can scan the location and design a 2D map of the house using SLAM algorithm and LIDAR sensor. After generating the map, Assist W is able to move automatically according to the commands (Voice and touch) given by the user, with the help of the map data. There is an AR (Augmented Reality) chat-bot that acts as a good companion to manage the mental health of the disabled person. Assist W is also able to manage the security and physical health of the disabled person by providing a fall detection system and automatic lifting system, and sending emergency alerts to the caretakers. This system was tested using simulation.
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Consumer and Farmer Centric Subscription Based Organic Vegetable/Fruit Delivery System
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Karunarathna, T.M.N.P.; Kumari, M.M.A.; Kulasinghe, W.D.K.A.; Liyanage, T.L.P.; Kodagoda, N.; Suriyanwsa, K.; Kumari, D.
For centuries, the economy of Sri Lanka has been backed by the agricultural sector. Even though it has contributed to the development of the nation on a large scale, the economies and living standards of the farmers have not been improved much. Most of the farmers remain poor mainly due to not knowing the market demand and the low buying prices of the middleman. Meanwhile, the consumers in Sri Lanka are buying non-organic vegetables and fruits which are highly contaminated with dangerous chemicals which in turn has contributed to the rapidly increasing non-communicable disease rates in both consumers and farmers. The proposed system is an attempt to solve these problems faced by both farmers and consumers by reducing the farmers-consumer knowledge gap and providing consumers a trustworthy and personalized subscription for organic vegetables/fruits with a donation platform.
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E-Learn Detector: Smart Behaviour MonitoringSystem to Analyze Student Behaviours DuringOnline Educational Activities
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Bamunuge, H.K.T.; Perera, H.M.; Kumarage, S.; Savindri, P.A.P.; Kasthurirathna, D.; Kugathasan, A.
With the rise of online education more attention is being paid to the deficiencies in online learning platforms. Online Learning environments aim to deliver efficacious instructions, but rarely take providing a conventional classroom experience to the students into consideration. Efficient detection of students’ learning situations can provide information to teachers to help them identify students having trouble in real-time. This idea has been exploited several times for Intelligent Tutoring Systems, but not yet in other types of learning environments that are less structured. “E-Learn Detector is a web application solution to these existing issues in online learning which consists of unique features such as verifying the user during logging procedure and throughout an examination, detecting suspicious behaviors and presence of multiple users during online examinations and detecting low engagement levels of students during online lectures. “E-Learn Detector” is developed with the aim to provide guidance to students to improve their academic performance and behavior during classroom activities and to induce the best out of the educational activities.
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E-Learning Platform for Hearing Impaired Students
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Krishnamoorthy, N.; Raveendran, A.; Vadiveswaran, P.; Arulraj, S.R.; Manathunga, K.; Siriwardana, S.
With the Spread of global pandemic Covid-19, the traditional education was transformed to online from traditional learning drastically. Hence the use of e-Learning platforms was increased. But this idea has issues with certain communities of people around the world. The hearing-impaired people have many issues with eLearning platforms because of their deficiency in hearing sound. Therefore, through this paper authors are introducing a learning platform for hearing impaired communities to aid in learning effectively. The proposed platform uses sign language to facilitate communication among students and tutors while providing sign language learning materials, practicing opportunities and Q&A sessions. The system has a low light enhancement module to enhance the videos uploaded by the tutor, module to convert the uploaded videos to American Sign Language and it also converts the questions asked via sign language to text.
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MNet-Sim: A Multi-layered Semantic Similarity Network to Evaluate Sentence Similarity
(2021-11) Kasthurirathna, D; Jeyaraj, M. N
Similarity is a comparative - subjective measure that varies with the domain within which it is considered. In several NLP applications such as document classification, pattern recognition, chatbot questionanswering, sentiment analysis, etc., identifying an accurate similarity score for sentence pairs has become a crucial area of research. In the existing models that assess similarity, the limitation of effectively computing this similarity based on contextual comparisons, the localization due to the centering theory, and the lack of non-semantic textual comparisons have proven to be drawbacks. Hence, this paper presents a multi-layered semantic similarity network model built upon multiple similarity measures that render an overall sentence similarity score based on the principles of Network Science, neighboring weighted relational edges, and a proposed extended node similarity computation formula. The proposed multi-layered network model was evaluated and tested against established state-of-the-art models and is shown to have demonstrated better performance scores in assessing sentence similarity
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Mobile Based Solution to Weight Loss Planning for Children (with Obesity) in Sri Lanka
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Rajapakse, R.M.M.P.K.; Mudalige, J.M.A.I.; Perera, L.A.D.Y.S.; Warakagoda, R.N.A.M.S.C.B.; Siriwardana, S.
Obesity is a condition where there is excess fat in the body, and it is one of the world's most extreme and dangerous dietary diseases. Genetic factors, lack of physical activity, unhealthy eating patterns, or a combination of these factors are the most common causes of obesity. This is important because it influences every part of a child's life. More, in particular, this disorder leads to poor health and negative social standing with perceptions. Nowadays, children are paying keen interest in technology and related devices. Therefore, in this research, we are planning to give a mobile-based solution with a smart band that is used to monitor the child. In this solution, we are mainly focusing on Sri Lankan children with obesity who are aged between 5-10. In our solution, there are four main sections which are, monitoring child activities, recognizing the activities, and getting relevant data, then based on those data and previous activity completion levels, this solution will suggest activities for losing weight, provide specific diet plans for each child considering the health conditions and predict the probability of having main obesity-
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SmartCoach: Comprehensive Tutor Recommender and Student Attentiveness Measuring Platform
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Samarasekara, H. D. K.; Hansaka, H. M. P.; Rajapaksha, S. D. D.; Tharaka, W. A. D. G.; Manathunga, K.; Sriyarathna, D.C.
With the pandemic, coaching or tutoring classes became to halt as the underlying system wasn’t facilitating to adapt to emergency teaching mechanisms due to sparse of relevant technologies and tutor unawareness. SmartCoach is an integrated platform that allows students to find suitable tutors based on recommendations and other parameters like proximity, previous track record etc. using sentiment analysis and natural language processing. For tutors, SmartCoach allows publishing learning materials, automatic quiz creation, tracking attendance and, attentiveness during classes using OpenCV library. Moreover tutors get a dashboard featuring critical aspects about their classes and, personal income. This research is aimed to introduce a comprehensive distance learning platform with novel technological approaches that connect both potential students and tutors to a common platform.
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VOYAGER – Smart Travel Guidance Cross Platform Mobile Application
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Wijesinghe, W.A.K.D.; Amarasinghe, A.G.L.D.P.; Bandara, T.M.U.A.; Gamage, A.I.; Ganegoda, D.
The tourism industry is one of the largest industries that contribute to the worldwide economy. Also, it is one of the best income sources in Sri Lanka. It makes a considerable amount of money directly and indirectly through contributing to the government budget, job market and foreign exchange earnings. Same as foreign visitors, a significant amount of domestic travelers contributes to the economy in Sri Lanka. Hence, the tourism industry is popular in Sri Lanka; this research aims to enhance travelers’ travelling experience. When considering today’s travel communities, there are a set of unanswered questions that travelers tend to find answers manually from forums and social media because of the lack of features in the current apps. This paper discusses the development of the “Voyager – Smart travel guidance mobile application” to fulfil the gap between current apps and user requirements. The mobile application mainly focuses on the following features; smart travel plan within the desired travel period, shortest and scenic path options, automatic review categorizing and rating system, place tagging and place feature extracting system, fuel data analyzer, and one-tap emergency guidance feature. Despite the previous mentioned features, the final mobile application includes a friends system between app users, group travel planning, and an in-app chat system. As a result of the research project, this user-friendly mobile application will provide a better user experience when travelling, and it will help to develop the tourism culture in Sri Lanka.
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WoKnack – A Professional Social Media Platform for Women Using Machine Learning Approach
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Shanmugarajah, S.; Praisoody, A.; Rakib Uddin, M.D.
Today’s generation is heavily influenced by social media. However, most users decline to post their abilities on these platforms for a variety of reasons, including security, a lack of basic skills, and a lack of knowledge about the various skill sets. It's understandable that women face many security risks on these platforms. WoKnack is a professional social networking platform dedicated to women. This opens opportunities for women to demonstrate their abilities and teach other women. This paper targets onfunctionalities like registration limited to female users, skill categorization, post verification and privacy preservation. Facial image, identification document and Voice related gender verification done using machine learning approaches to identify thegender before registration. Accuracy of 91% gained during the process. Skills have been categorized using Natural language processing and post verification done based on these categories. Usage of the best accurate algorithm gives an accuracy of 94% during this process. In order to preserve the privacy of users Data anonymization, skill and location clustering have been added to the system.