Classical propositional logic (CPL) captures our basic understanding of the linguistic connectives “and”, “or” and “not”. It also provides a very good basis for digital circuits. But it does not account for more sophisticated linguistic notions such as “always”, “possibly”, “believed” or “knows”. Philosophers therefore invented many different non-classical logics which extend CPL with further operators for these notions.
Honours and Masters project
Displaying 91 - 100 of 260 honours projects.
Predicting User Engagement
Is the user paying attention? Is the content engaging enough?
The degree of concentration, enthusiasm, optimism, and passion displayed by individual(s) while interacting with a machine is referred to as ‘user engagement’. Engagement is a positive psychological state characterized by active behavioral participation, positive emotional experiences, and intense cognitive focus. Being able to detect engagement and/or attention has wide applications in consumer commerce, smart cars, augmented reality etc.
Predicting User Engagement
Is the user paying attention? Is the content engaging enough?
The degree of concentration, enthusiasm, optimism, and passion displayed by individual(s) while interacting with a machine is referred to as ‘user engagement’. Engagement is a positive psychological state characterized by active behavioral participation, positive emotional experiences, and intense cognitive focus. Being able to detect engagement and/or attention has wide applications in consumer commerce, smart cars, augmented reality etc.
Deepfakes Detection in Images/Video/Audio
Deepfakes detection deals with machine learning methods, which detect if an image/video/audio sample is manipulated with a generative AI software. In recent years, deepfakes have been increasingly used for malicious purposes, including financial fraud, misinformation campaigns, identity theft, and cyber harassment. The ability to generate highly realistic synthetic content poses a serious threat to digital security, privacy, and trust in media. This project will develop methods for detecting deepfakes.
AI (Deep Reinforcement Learning) for Strategic Bidding in Energy Markets
The world’s energy markets are transforming, and more renewable energy is integrated into the electric energy market. The intermittent renewable supply leads to unexpected demand-supply mismatches and results in highly fluctuating energy prices. Energy arbitrage aims to strategically operate energy devices to leverage the temporal price spread to smooth out the price differences in the market, which also generates some revenue.
Game Design
Project Description: The project is focused on developing game-based learning environments where the users’ trace or interaction data could be collected. The game-based environment needs to be designed to allow the users to navigate and explore at their own pace. Using the environment, the participants can practice their technical/professional skills from various options.
Citation Analysis and Social Network Analysis
Project description
This research project aims to explore how researchers are investigating various epistemic emotions that arise within educational contexts. Through a combination of literature review, citation and bibliometric analysis, this project will uncover trends in the field and may guide future directions. The outcome of this research is expected to be a peer-reviewed publication that may provide a valuable addition to your CV.
AI-Enhanced Mental Health Support for Vulnerable Populations [Minor Thesis]
Mental health challenges disproportionately affect vulnerable populations, often due to limited access to traditional healthcare services. The rise of Generative AI offers a groundbreaking opportunity to bridge this gap by providing personalized, scalable, and accessible mental health support. This project, led out of Action Lab, aims to harness the potential of Generative AI to develop innovative technologies tailored for mental health interventions.
Mind Reading: Translating Brain Activity into Textual Language
Our groundbreaking research explores the intricate relationship between natural language processing (NLP) and electroencephalography (EEG) brain signals [1]. By leveraging advanced machine learning techniques, we aim to decode the neural patterns associated with language comprehension and production, ultimately enabling seamless communication between humans and machines. Our innovative approach has the potential to revolutionize brain-computer interfaces,speech recognition technologies, and assistive devices for individuals with communication impairments.
Social media epidemic intelligence and surveillance for chronic conditions and their associated risk factors
Collecting and analysing social media content (e.g., Reddit), along with using Google Trends, presents a great opportunity to develop social media epidemic intelligence. This approach can enhance the understanding of chronic conditions such as arthritis, back pain, and knee pain, as well as track associated areas such as treatments and risk factors, including obesity, diet, physical activity, and exercise. This approach can be also used to understand the community attitudes about these conditions, and see if there are changes over time as there as new public campaigns.