With the advent of e-commerce, users are presented with numerous alternatives to satisfy their everyday needs. Choosing from the available options generally entails the consideration of multiple, often conflicting aspects, the tradeoff among which is assessed differently by different users.
This project proposes PERFLEXO, a new methodology for multi-objective querying centred around three hard requirements, i.e., personalization, flexibility in the preference input, and output-size control. Past approaches have considered these requirements individually, but no existing work satisfies all three of them. On the technical side, the main contributions of the project will centre on PERFLEXO’s ability to process large option-sets (i.e., scalability) and produce shortlists in reasonable time (i.e., responsiveness).
This research project aims to improve understanding of Singapore consumers’ perception of alternative protein and subsequently, foster their acceptance of this novel food technology. The term “alternative proteins” refers to animal-free protein alternatives that can be organised into three distinct categories: “plant-based proteins, edible insects, and a group referred to as ‘cellular agriculture’. This latter group encompasses products commonly referred to as ‘cultured’ or ‘clean’ meat, milk and other animal products, created either through culturing stem cells outside (in vitro) animal bodies, or through the genetic modification and fermentation of yeast cells. More specifically, this study aims to answer the following research questions:
- What are Singapore consumers’ perception of alternative proteins?
- What message frames are most effective in fostering consumers’ acceptance of alternative proteins?
- Which type/s of social media influencers (SMI) are most effective in influencing consumer acceptance of alternative proteins?
- What are the effects of the message frames on Singapore consumers’ attitudes and behavioural intentions (or behavior) in relation to alternative proteins?
AI models trained offline rely on the accessibility of all classes in training data. When they are updated online to learn new incoming data, they often bias to the patterns of new classes, and thus forget old ones. The problem is known as catastrophic forgetting. This project aims to tackle this issue by task-specific data augmentation. The augmentation for old classes is achieved by distilling from new or open-set data that contain the knowledge of old classes, e.g., shared contexts and sub-parts.
The increasingly widespread use of digital tokens around the world has meant that businesses have been seeking clarity with respect to their tax liabilities from transactions involving digital tokens. However, as such transactions are relatively new, there is considerable uncertainty as to the appropriate tax treatment in what can be a rather messy field. Singapore has provided comprehensive guidance on the taxation of digital tokens in the form of e-tax guides. However, quite understandably, a good number of open questions still remain. This project aims to add to the available knowledge on the taxation of digital tokens in Singapore by providing a single comprehensive guide that can be easily referenced by businesses seeking clarity on their tax obligations. In particular, it will add value by looking at four areas that are not currently covered by the existing guidance and literature: 1) a clear theoretical map of the area; 2) the application of existing law (case law and statutes) to these new transactions; 3) a comparative approach, to determine how the tax treatment in Singapore differs from that of other leading jurisdictions; and 4) the stamp duty implications of transactions involving digital tokens. In addition, the project will cover the three most relevant taxes in this area: 1) income tax; 2) goods and services tax; and 3) stamp duties.
(This is a 6-month extension of the research collaboration with Fujitsu Ltd.) Under the Fujitsu-SMU Urban Computing and Engineering (UNiCEN) Corp Lab, SMU has undertaken the Digital Platform Experimentation (DigiPlex) project with Fujitsu. The project was carried out using the Digital Annealer (DA), a quantum inspired-technology inspired by Fujitsu. Through the DigiPlex project, certain challenges in solving constrained optimization problems using such technology, and promising methods on tuning of the underlying model parameters to improve run time performance, have been identified. This project aims at developing hyper parameter tuning methodology, machine learning techniques, operations research algorithms, and software tools to enhance quantum-inspired techniques for solving large scale real-world combinatorial optimization problems.
This project aims to develop a practical method for certifying real-world AI-based systems based on a novel combination of static and dynamic verification, targeting systems with a certification requirement similar to that of EAL 6-7 for traditional software systems. We accomplish this by developing a completely new set of algorithms, which are designed to battle the scalability limitation of static verification techniques and connect static and dynamic verification, and use the partial verification engine developed to solve the verification problem systematically.
The world is experiencing a rapid transition towards a digital society. Although huge number of Internet of Things (IoT) devices are being deployed to provide accurate and real-time sensing and observation of the environment, security and privacy concerns are becoming one of the major barriers for large scale adoption and deployment of IoT. To that end, this project aims to provide IoT devices with privacy-aware authentication and flexible authorisation capabilities to build trust in IoT.
With the widespread adoption of drones in civilian, business, and government applications nowadays, concerns for breaches of safety, security, and privacy by exploiting drone systems are also rising to the highest national level. Malicious entities have used drones to conduct physical and cyber-attacks such as unauthorized surveillance, drug smuggling, armed use, etc. In this project, the research team aims to develop methods and tools for analysing a list of drones to audit drones for detecting anomalies such as malware, data leak, software bugs that could be exploited to conduct criminal/malicious drone activities. The research team will analyse at least five different drone-related criminal/malicious activities from their collaborator and demonstrate how ADrone can assist Drone forensic analysts with the detection of the root causes of activities.
The first objective of this programme evaluation endeavour is to produce a ‘Roadmap Report’ that will aid Alzheimer’s Disease Association (ADA)’s efforts to improve subsequent iterations of the Voice for Hope (VFH) programme. The second objective of this research study is to co-create an ‘Amplification Article’ with collaborators at ADA, with the goal of sharing valuable insights from the VFH programme in Singapore with the larger ecosystem in Asia and beyond. This effort will allow for the curation of further evidence-based programmes that benefit persons with dementia and their caregivers in the future.
This project focuses on the interaction among individuals that occurs within the framework of an institution. For an institution to deliver socially desirable outcomes, the design of the institution has to provide the individuals with the right incentives. Implementation theory is considered a natural framework for us to ensure the correct incentive structure in the design of institutions. The objective of this project is to design effective, that is, simple and practically usable institutions, by imposing various robustness requirements on the class of institutions to be considered. The project thus aims to generate critical insights on the robust design of institutions, which would in turn significantly enhance our ability to design effective institutions for economic, political, and social situations.