DCU Expo 2023 Final Year Projects

27 3. PalTime This project was created as a unique web chatting application targeted towards teens and young adults. It provides an enhanced chatting experience by detecting common trends in one-on-one chats and picking up on the type of person you are/what you enjoy to do. Furthermore, the application provides daily friendshipmatches that refresh after a certain time period. These matches are based on a user’s 3 foundation pastimes chosen upon registration, Myers-Briggs Type Indicator (MBTI) personality type compatibility and the new pastimes that PalTime picks up by analyzing chat trends using Natural Language Processing (NLP). Class Computer Applications Project Area Databases, Instant Messaging, Natural Language Processing, Social Networking, Web Application, User Interface (UI)/User Experience (UX) Design Project Technology CSS, HTML5, JavaScript, MySQL, Nodejs, SQL, React.js Student Name(s) Aleena Naseem  |  John Hsian Yuen Naik Email aleena.naseem3@mail.dcu.ie  |  john.naik2@mail.dcu.ie Supervisor Dr Hyowon Lee 4. Decarbonisation of Dwellings: Cost Analysis of Methods and Technologies of Domestic Heating Systems in Irish Households A cost analysis of methods and technologies of lowering non-renewable energy sources usage in Irish dwellings. To do this an investigation of solar energy was undertaken and the results are shown in the excel format. Class Mechanical andManufacturing Engineering (Year 4) Project Area Energy Conservation Project Technology Excel/VB Student Name(s) Julianne Daly Email julianne.daly47@mail.dcu.ie Supervisor Dr James Carton 5. Size and Fit Prediction in Fashion E-Commerce The leading cause of product returns is poor size and fit (S&F). The objective of this project was to automate and improve S&F recommendations at the time of purchase. This “what if” project combines real-world e-commerce order and returns datawith synthesized customer data to build a recommendation system for size and fit. It shows the potential to reduce size-related product returns which is not only beneficial for customers but also can increase profit margins for fashion e-commerce businesses and reduce these businesses’ carbon footprint. Class Data Science Project Area Artificial Intelligence, Data Analytics, E-Commerce Project Technology Python, Machine Learning Student Name(s) Louise Anderson Email louise.anderson23@mail.dcu.ie Supervisor Prof Alan Smeaton