DCU Expo 2023 Final Year Projects

87 183. Assessing the Accuracy of Time-Series ForecastingModels onMeteorological Datasets This project assesses the accuracy of various time-series forecastingmodels on meteorological datasets with gaps, where gaps refer tomissing data points. The data includes parameters such as temperature, precipitation, and humidity and is split into training and testing sets. Various forecastingmodels, including ARIMA, SARIMA, LSTM, and others, are trained on the training set using different predictive variables and validation methods. The accuracy of each model is evaluated usingMAE, RMSE, andMAPE on the testing set. The project aims to identify the best models andmethods for meteorological datasets where gaps are present to improve weather forecasting, which has practical significance for various industries today. Class Computer Applications Project Area Data Analytics, Web Application Project Technology CSS, HTML5, JavaScript, MySQL, Python, Machine Learning Student Name(s) Kevin Patrick Boyle  | Mark Reid Email kevin.boyle42@mail.dcu.ie   | mark.reid28@mail.dcu.ie Supervisor Prof Mark Roantree 184. Simulated Investigation of FlexibleMembranes in Fluid This project involves the gathering of benchmark data for the behavior of material in and out of fluid/water. Class Mechanical andManufacturing Engineering (Year 5) Project Area Simulation Project Technology ANSYSWorkbench Student Name(s) David Langan Email david.langan4@mail.dcu.ie Supervisor Dr Yan Delauré 185. Note Taker The project has two parts – a listening device and a Django based web application. The device has passive and triggered listeningmodes. The web app receives data from either the user’s device or the listening device, and after processing the recording, converts it to text to be used when creating notes. The app is hosted on the user’s phone or computer, and the user accesses their recordings through their account on multiple devices. Class Enterprise Computing Project Area Wearable Technology, Web Application Project Technology CSS, HTML5, JavaScript, MySQL, Python Student Name(s) Oluwayomi Amodu  |  Leonardo Shehu Email oluwayomi.amodu2@mail.dcu.ie   |  leonardo.shehu2@mail.dcu.ie Supervisor Dr Cathal Gurrin