Interdisciplinary Programs Office Division of Emerging Interdisciplinary Areas 218 Machine Learning on Wearable Devices Supervisor: HUI Pan / EMIA Student: LAM Sing Yu / CS Course: UROP1100, Fall This research study focuses on the various techniques used to detect emotions on wearable devices that are making increasing use of EXtended Reality (XR) technologies such as Augmented and Virtual Reality. The primary purpose of XR technologies is to connect the virtual world to the physical world. Detecting emotions plays a key role in streamlining said connectivity. In this work, we aim to evaluate the state-of-the-art techniques used to detect emotions in XR environments or that can be used in such scenarios. A De-polarization System for Social Media Supervisor: HUI Pan / EMIA Student: LAU Ching Ming Samuel / COMP Course: UROP1100, Spring Nowadays, the social media algorithms are designed in a way that enforce personalisation and hence there is a tendency for the echo chambers to be built(Liu et al., 2021). This situation could be manifested in political news, as people only trust and agree with the stance of the media that they tend to watch. To prevent this situation, a tool is proposed to de-polarize news article by recommending news with similar content but different stance and bias. News with various stances will be recommended instead of all opposite stances to attract users to use this tool. In this report, the entire flow of the tool will be discussed, as well as the results and future work. A De-polarization System for Social Media Supervisor: HUI Pan / EMIA Student: NGAMMANKONGTANGKIT Suttinai / CPEG Course: UROP1100, Spring With the current Ukraine-Russia war, it affected the social media widely. As we are in a digital world, people tend to receive their information through Internet which raises to the misinformation via social media. This is to discredit the other side and position themselves as the right side. This report aims to present the research on Ukraine-Russia misinformation starting from searching for rumor through official sources, organizing gathered information in the excel sheet, identifying keywords for each rumor, and finally group them into different categories. Finally, the report analyzed the information collected and provided conclusions for this research.
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