High strength lightweight steel can effectively save energy and cut emissions of vehicles, although it is more brittle than traditional low strength steel, which causes safety issue. This project tailors the coating structure of high strength lightweight steel to make this steel more ductile and ensure the safety.
Professor Komura’s research focuses on creating diverse human movements for computer animation, games, and virtual environments. His research team designed a new type of neural network called the Periodic Autoencoder that can identify repeating patterns in large sets of motion data without any additional information. This allows us to create unique movements in various styles, such as dance motions synchronized to music or dribbling movements in soccer. Additionally, the system can help find similar motions in large database, produce natural movements between a small number of key frame poses and estimate human movements even when the body is partially obscured in videos.
“HKU PERfECT” is the first wearable platform that can simultaneously acquire the following three merits.
1. Highly sensitive: By combing electrochemical technology with microelectronic technology, the highest sensitivity is reached.
2. Smallest and lightest: By using the smallest possible electronic units and marrying emerging stretchable bioelectronic technologies, coin-sized and light (0.5 grams) PERfECT wearables have been used for diagnosis and treatment of various diseases, and rehabilitation.
3. Energy efficient: By using interdisciplinary research strategies spanning analytical chemistry, low-power microelectronics, and low-power wireless communication, PERfECT achieves the highest accuracy with the lowest power consumption, ideal for long-term using.
This is a large-scale simulation platform for managing and controlling Hong Kong taxis. The simulator platform can be used to simulate the movements and trajectories of taxis for idle cruising, picking up passengers, and delivering passengers on a large-scale transportation network. The simulation platform is calibrated by a real dataset of Hong Kong taxis to ensure that the simulation well approximates the reality. This simulator is jointly developed by the teams of Dr. Jintao Ke at HKU and Prof. Hai Yang at HKUST. The simulation platform will be open for public use in the near future.
Professor Choy’s team invented silver nanowire (NW) based flexible transparent electrodes (FTEs) and silver nanoparticle (NP) electrodes. They both have attractive electrical and optical properties, and low-cost. By intergrating both inventions (that is disposing a layer of nanoparticle on the NW FTEs), it can be used as flexible organic photovoltaics.
This project aims to study the behaviour of MTR passengers during COVID-19 based on a large set (>325GB) of MTR trip records collected in 2019-2020. An efficient and secure online platform has been built to enable researchers to perform analyses and generate visualizations.
Counterfeiting threatens the global economy and security. According the report issued by the United States Patent and Trademark Office (USPTO) in 2020 “the value of global counterfeiting and pirated products is estimated US $ 4.5 trillion a year.” Despite enormous efforts, conventional anti-counterfeiting approaches such as QR codes can be easily fabricated due to limited data encryption capacity on a 2D in-plane space.
How can we increase the encryption density in a limited space?
Clean water and energy are vital for human activity and socio-economic development. This project focuses on developing more effective reverse osmosis (RO) and nanofiltration (NF) membranes and processes. Professor Tang’s team has pioneered the development of nano-foaming theory and interlayer structure to regulate membranes with excellent performance.
An immersive virtual reality-based exercise system was developed to support poststroke upper limb exercises. In a 2-week randomized controlled trial, fifty patients used the system for exercises (intervention) or a sham entertainment program (control). The findings demonstrate that the system can improve shoulder joint motion and is safe and acceptable.
To address challenges and future developments in structural engineering, Dr. Wang has developed a deep-learning-based platform, which contains (1) physics-informed neural networks (EPINN) for structural simulation and (2) state-of-the-art neural operator (VINO) for structural health monitoring.