http://dlib.iit.ac.lk/xmlui/handle/123456789/1261 2026-04-08T13:02:08Z http://dlib.iit.ac.lk/xmlui/handle/123456789/1326 Conseils - Importance of identifying your personality type for choosing a better degree program that suits you Atapattu, Lehindu "Sri Lankan students follow the British or the Local curriculum to be eligible for their first degree. Based on the results, few get a chance in a state university. Therefore, the rest will have to go to a private university. Most students find it challenging to find an enjoyable and expectation-matching degree. They rarely use their personality type to choose a satisfactory degree. The project “Conseils” aims to design, develop and evaluate a website for the students to help them analyse their personality type to find a better degree and, ultimately, a career path. A pilot study was conducted to identify the problem in-depth. Additionally, a stratified random sampling was used as a probabilistic sampling technique containing a random sample of 10 students and a Consultant family physician and psychological counsellor. With the help of the information gathered from the interviews and questionnaire, a literature review was done. The method used to identify the personality type is Myers–Briggs Type Indicator. A personality type is a psychological classification used to identify individuals’ differences. By answering some questions, students can figure out their type, which they can use to know more about themselves. After thorough research on the development, a mathematical approach was used to analyse the user input data in the quiz used to find the personality type. The mathematical approach used averages generated from a dataset with a 29000+ data sample. " 2022-01-01T00:00:00Z http://dlib.iit.ac.lk/xmlui/handle/123456789/1320 FruitLK-A fruit quality detection application Abdullah, Mashoor "Fruit Consumers and Sellers are finding it difficult to determine the overall quality of the fruit due to its sub factors which affect the quality in different methods hence this affects the purchase decision of consumers and stock management of sellers due to the unawareness of fruit diseases, inability to determine shelf-life and complications related to ripeness thus the consumers do not have a knowledge of the fruit nutrients that are available therefore a solution is in need to assist in identifying the best quality fruit and to educate the sellers and consumers regarding the factors which affect fruit quality and how to overcome them. The factors which affect fruit quality are colour and ripeness, maturity, appearance, shelf-life and disease details hence these factors need to be monitored to ensure the best quality fruit remains. The research is focused on these factors and how to overcome them while developing a solution to give assistance to fruit sellers and consumers where they can utilise the solution to choose the best quality fruit. Iterative and incremental methodology have been followed so that the project will be developed which allows to make changes in the development process. The requirements were gathered from fruit sellers and consumers regarding the problem domain which allowed to gather the requirements and begin modelling user requirements. the questionnaire provided the necessary requirements from a larger number of stakeholder while separate questionnaires were used for seller and consumer. The mobile solution is based only in Sri Lanka and scope is towards the fruit Mango whereas the research proved that this is a timely solution and provides the desired solution to the identified problems thus it incorporates cutting edge technology to this concept while the evaluations were considered by domain experts, tech experts to prove that the aims of this project is achieved." 2022-01-01T00:00:00Z http://dlib.iit.ac.lk/xmlui/handle/123456789/1319 Predicting chronic kidney disease using machine learning Rerukaana, Navin "Chronic kidney disease (CKD) is a long-term disease that causes the kidneys to not work as they should. This disease can affect anyone, but it is more common for people who are older and for people who are from South Asia. Kidney disease affects 10% of the human population. CKD slowly and progressively loses the functions of the kidney over time, and eventually the person who has CKD may develop kidney failure. The main reason for implementing a system like this is to prevent CKD patients from getting into End Stage Renal Disease (ESRD), which means the person's kidneys stop working permanently, needing either a kidney transplant or a regular course of long-term treatment to stay alive. The main reasons for a patient getting ESRD is by failing to detect the disease at an early stage, not following proper diet plans even after identifying the disease, getting advice from inexperienced doctors, and not having proper follow up care. This system will help patients regularly get CKD predictions while they are at home, receive diet recommendations based on their level of disease to control or prevent getting the disease, and recommend specialized doctors (Neurologist) to get guidance from. With the use of machine learning techniques with the highest accuracy, this system will help people identify the disease before or at an earlier stage, which will help the patient prevent or slow down the progression of CKD. When implementing the machine learning model, 10 different models were created to pick the model with the most accuracy. A dataset with more than 400 records was used when implementing the model. To test the model, 40% of the dataset was used, and the rest, 60%, was used to train the model. Out of the 10 models created, the author has chosen the Random Forest classifier as the prediction model with an accuracy of 99.38%. The primary goal of this research is to create a system that will assist patients in detecting CKD in its early stages, receiving the appropriate treatment to manage it without developing end-stage renal disease (ESRD), and living a healthy life. " 2022-01-01T00:00:00Z http://dlib.iit.ac.lk/xmlui/handle/123456789/1318 Airplate - A Platform To Reduce International Catering Waste in Airlines Through Data, Insight and Action Perera, Tehara "The catering and in-flight services domain of the aviation industry generates a large amount of food waste particularly originating from deplaned waste and terminal waste. As a result of the increasing amounts of food wastage and the poor methods of disposal, key stakeholders of the industry incur large costs, deplete limited natural resources, affect the sustainability credibility of the airline industry and cause a significant enviornmental impact in contributing to the generation of greenhouse gases. Despite the rigorous regulations governing the industry and other causal factors that contribute to this problem, key stakeholders such as airlines, catering companies and authoritative bodies are making significant efforts to reduce waste generation and introduce innovative methods of waste management. However, a holistic approach that supports all key stakeholders of the industry is not currently available. This research intends to design, develop, test and evaluate a holistic system for passengers and cabin crew to identify key key areas of food wastage, minimise the impact to the business and environment and enhance customer experience by providing a personalised experience for the passengers. Airplate was developed to bridge the existent market gap by incorporating the information gathered during this research period. An agile-waterfall method was used as the key project methodology to develop Airplate and thorough research was conducted by using suitable requirement elicitation methods. The collected information was then used to build an initial prototype and feedback was obtained from relevant stakeholders of the application and the industry and refinements were made accordingly. All feedback obtained from the stakeholders were approving and enthusiastic of both the problem idea and the solution and any additional comments will be used to improve the solution in the future." 2022-01-01T00:00:00Z