The Chinese University of Hong Kong

About: The Chinese University of Hong Kong is a education organization based out in Hong Kong, China. It is known for research contribution in the topics: Population & Computer science. The organization has 43411 authors who have published 93672 publications receiving 3066651 citations.

A Distributed Control Approach to A Robust Output Regulation Problem for Multi-Agent Linear Systems

Abstract: In this note, the robust output regulation problem of a multi-agent system is considered. An internal model based distributed control scheme is adopted to achieve the objectives of asymptotic tracking and disturbance rejection in an uncertain multi-agent system where both the reference inputs and disturbances are generated by an exosystem.

A sequence variant in ZFHX3 on 16q22 associates with atrial fibrillation and ischemic stroke.

Abstract: Daniel Gudbjartsson and colleagues report a genome-wide association study for atrial fibrillation, a condition associated with increased risk of stroke. They report a variant in ZFHX3 associated with atrial fibrillation as well as ischemic stroke. We expanded our genome-wide association study on atrial fibrillation (AF) in Iceland, which previously identified risk variants on 4q25, and tested the most significant associations in samples from Iceland, Norway and the United States. A variant in the ZFHX3 gene on chromosome 16q22, rs7193343-T, associated significantly with AF (odds ratio OR = 1.21, P = 1.4 × 10−10). This variant also associated with ischemic stroke (OR = 1.11, P = 0.00054) and cardioembolic stroke (OR = 1.22, P = 0.00021) in a combined analysis of five stroke samples.

Ice‐Templated Assembly Strategy to Construct 3D Boron Nitride Nanosheet Networks in Polymer Composites for Thermal Conductivity Improvement

Abstract: Owing to the growing heat removal issue of modern electronic devices, polymer composites with high thermal conductivity have drawn much attention in the past few years. However, a traditional method to enhance the thermal conductivity of the polymers by addition of inorganic fillers usually creates composite with not only limited thermal conductivity but also other detrimental effects due to large amount of fillers required. Here, novel polymer composites are reported by first constructing 3D boron nitride nanosheets (3D-BNNS) network using ice-templated approach and then infiltrating them with epoxy matrix. The obtained polymer composites exhibit a high thermal conductivity (2.85 W m(-1) K(-1)), a low thermal expansion coefficient (24-32 ppm K(-1)), and an increased glass transition temperature (T(g)) at relatively low BNNSs loading (9.29 vol%). These results demonstrate that this approach opens a new avenue for design and preparation of polymer composites with high thermal conductivity. The polymer composites are potentially useful in advanced electronic packaging techniques, namely, thermal interface materials, underfill materials, molding compounds, and organic substrates.

Dual-space linear discriminant analysis for face recognition

Abstract: Linear discriminant analysis (LDA) is a popular feature extraction technique for face recognition. However, it often suffers from the small sample size problem when dealing with the high dimensional face data. Some approaches have been proposed to overcome this problem, but they are often unstable and have to discard some discriminative information. In this paper, a dual-space LDA approach for face recognition is proposed to take full advantage of the discriminative information in the face space. Based on a probabilistic visual model, the eigenvalue spectrum in the null space of within-class scatter matrix is estimated, and discriminant analysis is simultaneously applied in the principal and null subspaces of the within-class scatter matrix. The two sets of discriminative features are then combined for recognition. It outperforms existing LDA approaches.