Hosted by CityU’s Center for Cybersecurity Innovation and School of Technology and Computing (STC), the Applied Research Symposium is open to faculty, professionals, and students from any discipline, university, or professional organization. At the end of each quarter, any students who would like to share their projects including capstone courses will present their outcomes. This symposium will provide opportunities for students, researchers, and practitioners to discuss the influence and impact of the applied computing on the future of our planet and our society
Manual work increases the time complexity without providing the proper structure so that the data can live in one place and be accessed anytime conveniently. Currently, the university processes new and revised courses manually. A new application, “Curriculum Committee submission Management Tool,” will be built inside the PowerApps, where all the stakeholders will enter the data at the frontend web application. Later, it can be retrieved anytime from the data set “CC_Request” at SharePoint. It will also introduce a systematic and more organized way of handling data while maintaining the data integrity at the backend in SharePoint.
A system for recognizing traffic signs has indeed been developed to ensure autonomous vehicles in adhering to speed limits while also improving security and safety. The major purpose is to make it easier for autonomous driving cars to maintain their attention on the road and avoid accidents in everyday scenarios. Along with the advancement of deep learning, it is now feasible to utilize a deep learning model to detect and recognize traffic lights. In recent years, many high-accuracy computer vision and machine learning models have performed admirably on traffic sign recognition classification problems. However, these models have a restriction in that they can only identify huge objects and their detection speed is slower. This research focuses on using a convolutional neural network (CNN) to train the dataset to create a deep learning model to improve its recognition speed and accuracy. This model improves accuracy and works well during the object recognition process.
OneUI kitchen remodeling website is going to provide the seamless experience to personalize their kitchen with many benefits for customers. And Through project mainly concentrate the developing the web application using serverless framework architecture and deployed an AWS cloud service.
This project aims to help unvaccinated people socially distance by giving them the necessary tools. One of the things most unvaccinated people will do is get vaccinated. So, giving them the capability to remotely schedule/view/edit/cancel vaccine appointments will allow them to socially distance more.
4:30 – 4:35 PM
Greeting & Announcement
Advisor: Ali Khamesipour
Chair: Nhi Dang
Teams link: Main
4:35 – 4:55 PM
4:55 – 5:15 PM
5:15 – 5:35 PM
Hunardeep Kaur – M.S. Computer Science
Topic: Curriculum Committee Submission Management Tool
Preethi Balasubramaniam – M.S. Computer Science
Topic: Traffic sign recognition Using Convolutional Neural Network
Sravya Karnati – M.S. Computer Science
Topic: OneUI kitchen Remodeling Project (Web application)
Chair: Yang Ren
Teams link: Session 01