This project will apply feature selection techniques for identifying features that can effectively predict the Logistics Performance Index (LPI), building upon our previously published work [1].
Honours and Minor Thesis projects
Displaying 71 - 80 of 216 honours projects.
Primary supervisor: Wai Peng Wong
Primary supervisor: Wai Peng Wong
This project aims to analyse the comments of Twitter on non-communicable diseases. Students are expected to carry out Aspects Detection to identify the specific aspects discussed in the tweets e.g., causes, transmission and symptoms. Subsequently, students are expected to conduct sentiment analysis utilizing tools like TextBlob or VADER, while also taking into account the importance of considering emojis to enhance classification accuracy.
Primary supervisor: Buser Say
SCIPPlan is a mathematical optimisation based automated planner for domains with i) mixed (i.e., real and/or discrete valued) state and action spaces, ii) nonlinear state transitions that are functions of time, and iii) general reward functions. SCIPPlan iteratively i) finds violated constraints (i.e., zero-crossings) by simulating the state transitions, and ii) adds the violated constraints back to its underlying optimization model, until a valid plan is found. The purpose of this project is to improve the performance of SCIPPlan.
Primary supervisor: Raphaël C.-W. Phan
Cybersecurity researchers are contemplating how to best use the currently trending AI techniques to aid cybersecurity, beyond just for classification.
The aim of this Honours project is to get the student to work with the supervisors on the latest AI techniques to adapt them over for cybersecurity, building first on baseline approaches for which code is available.
Primary supervisor: Ron Steinfeld
Cryptographic applications require a careful implementation to avoid side-channel attacks that reveal secret information to an attacker (e.g. via run-time measurements). In particular, for floating point arithmetic it is known that the timing of some basic arithmetic operations and functions on some CPUs depends on the input values [1], and thus the timing may leak secret information when the input contains secret values. Constant-time implementation tries to mitigate such run-time timing leakage on typical devices.
Primary supervisor: Ong Huey Fang
Following the success of the Human Genome Project, the entire scientific community witnessed a large data explosion in genomics, which was also aided by advances in molecular biology technologies such as next-generation sequencing. These high-throughput technologies enable comprehensive molecular profiling of cancer cell lines, including gene expression. Regardless of the use of gene-based assays, they provide abundant genomic information for identifying participating genes (biomarkers) that contribute to the chemoresistance process in cancer cells.…
Primary supervisor: Yasmeen George
The need: Early detection and diagnosis of eye conditions is critically important as many diseases, including diabetic retinopathy, glaucoma, and age-related macular degeneration, often show minimal or even no symptoms. Glaucoma is called the "silent thief of sight" since it progressively damages the eyes without any noticeable signs.
Primary supervisor: Helen Purchase
This project relates to the visualisation of the source of data used in scientific experiments, and their results. The visualisation focus is graphs.
Trust in the results of scientific experiments and scientific modelling relies on knowing how they have been derived – that is, the ‘scientific workflow’ that led to their production. Being able to reproduce the scientific workflow that led to such results is critical in ensuring trust, confidence and transparency [2].
Primary supervisor: Wai Peng Wong
In our current day and age, there is an exponential growth in multimodal data, especially the transition of social media from text-based communications to video formats which can be observed with the rise of TikTok, Youtube, and Instagram Reels. This shift requires a shift in how we analyze multimodal data as we will have to move away from traditional text sentiment analysis such as TextCNN.
Primary supervisor: Raveendran A/L Paramesran
The application of AI in sports is widely researched as both coaches and players realise the significance of quantitative analysis that can be extracted from video matches. Detecting and segmenting in-play scenes in sport video
sequences is necessary in various applications such as quantitative game and performance analysis. In studies on video-based game and performance analysis of racket sports, much research efforts have been made to explore the relationships between predefined parameters and sports performance, and the methodologies for effective coaching.