DCU-Final-Year-Projects-Booklet-2025

45 39. Detection of Photosensitive Epileptic Triggers in Short-FormMedias This project aims to protect people with photosensitive epilepsy (PSE) from seizure-inducing content on short-formmedia platforms such as TikTok and YouTube Shorts. Amachine learningmodel has been developed to detect harmful visual patterns, such as flashing lights and high-contrast colours, using a customdataset. The systemalso analyses videos for trigger volatility and the presence of on-screen warnings to identify malicious intent in posts. This project improves upon traditional rule-basedmethods to create a safer andmore accessible digital space for PSE users and contributes to research in this underexplored area. Student Programme Data Science Project Area Computer Vision Project Technology Python, Machine Learning Student Name(s) JackMcGarrity  |  PadraicMcMahon Email jack.mcgarrity8@mail.dcu.ie  |  padraic.mcmahon24@mail.dcu.ie Supervisor Prof Suzanne Little 40. TimeTactix Timetable Generator TimeTactix is an automated scheduling system that takes user input to generate a personalised timetable. The application takes inputs such as student’s current timetable, project deadlines and personal commitments to generate the timetable. Doing this allows the user to have a personalised schedule that helps them to achieve their unique goals as well as maintain a balance in their personal lives. The project idea was inspired by the common problem students and others face, which is organising their time appropriately. For students, this struggle typically involves managing assignments, extracurricular activities, and exams, which in turn leads to decreased productivity. Student Programme Computer Science Project Area Databases, SMS, Web Application Project Technology HTML5, JQuery, JavaScript, Python, React.js, PostgreSQL Student Name(s) Ben Stephenson  |  Eamonn O’Leary Email ben.stephenson3@mail.dcu.ie   |  eamonn.oleary35@mail.dcu.ie Supervisor Dr David Sinclair 41. Measurement of Steel Cable Tension This report investigates alternative methods for measuring tension in steel cables, a critical factor in structural strength in engineering applications. Traditional methods, such as the Loos gauge, are commonly used but have limitations in accuracy. The approach for this project involves deriving equations frombeam theory and taut string theory to calculate tension based on frequency. This study addresses three boundary conditions: hinged-hinged, hinged-fixed and fixed-fixed. The experiment will be validated by the use of a tensile test machine, a Loos gauge, and frequency measurement equipment. This report plans to document the development of a frequency-based tension measurement technique for the enhancement of cable monitoring. Student Programme Mechanical andManufacturing Engineering (Year 5) Project Area Control Systems, Data Analytics, Mechanical Design andManufacture, Sensor Technology Project Technology Fast Fourier Transform, Oscilloscope Student Name(s) TomGleeson Email tom.gleeson22@mail.dcu.ie Supervisor Dr Harry Esmonde