Hong Kong University of Science and Technology

About: Hong Kong University of Science and Technology is a education organization based out in Hong Kong, Hong Kong, China. It is known for research contribution in the topics: Computer science & Catalysis. The organization has 20126 authors who have published 52428 publications receiving 1965915 citations. The organization is also known as: HKUST & The Hong Kong University of Science and Technology.

The 2018 GaN power electronics roadmap

Abstract: Gallium nitride (GaN) is a compound semiconductor that has tremendous potential to facilitate economic growth in a semiconductor industry that is silicon-based and currently faced with diminishing returns of performance versus cost of investment. At a material level, its high electric field strength and electron mobility have already shown tremendous potential for high frequency communications and photonic applications. Advances in growth on commercially viable large area substrates are now at the point where power conversion applications of GaN are at the cusp of commercialisation. The future for building on the work described here in ways driven by specific challenges emerging from entirely new markets and applications is very exciting. This collection of GaN technology developments is therefore not itself a road map but a valuable collection of global state-of-the-art GaN research that will inform the next phase of the technology as market driven requirements evolve. First generation production devices are igniting large new markets and applications that can only be achieved using the advantages of higher speed, low specific resistivity and low saturation switching transistors. Major investments are being made by industrial companies in a wide variety of markets exploring the use of the technology in new circuit topologies, packaging solutions and system architectures that are required to achieve and optimise the system advantages offered by GaN transistors. It is this momentum that will drive priorities for the next stages of device research gathered here.

Dominant Local Binary Patterns for Texture Classification

Abstract: This paper proposes a novel approach to extract image features for texture classification. The proposed features are robust to image rotation, less sensitive to histogram equalization and noise. It comprises of two sets of features: dominant local binary patterns (DLBP) in a texture image and the supplementary features extracted by using the circularly symmetric Gabor filter responses. The dominant local binary pattern method makes use of the most frequently occurred patterns to capture descriptive textural information, while the Gabor-based features aim at supplying additional global textural information to the DLBP features. Through experiments, the proposed approach has been intensively evaluated by applying a large number of classification tests to histogram-equalized, randomly rotated and noise corrupted images in Outex, Brodatz, Meastex, and CUReT texture image databases. Our method has also been compared with six published texture features in the experiments. It is experimentally demonstrated that the proposed method achieves the highest classification accuracy in various texture databases and image conditions.

Fluorescent bio/chemosensors based on silole and tetraphenylethene luminogens with aggregation-induced emission feature

Abstract: New fluorescent sensors have been developed, utilizing the aggregation-induced emission (AIE) attribute of silole and tetraphenylethene luminogens. In this feature article, we briefly summarize recent progress in the development of AIE-based bio/chemosensors for assays of nuclease and AChE activities, screening of inhibitors, and detection of various analytes including charged biopolymers, ionic species, volatile and explosive organic compounds.

How Does Industry Affect Firm Financial Structure

Abstract: We examine the importance of industry to firm-level financial and real decisions. We find that in addition to standard industry fixed effects, financial structure also depends on a firm's position within its industry. In competitive industries, a firm's financial leverage depends on its natural hedge (its proximity to the median industry capital--labor ratio), the actions of other firms in the industry, and its status as entrant, incumbent, or exiting firm. Financial leverage is higher and less dispersed in concentrated industries, where strategic debt interactions are also stronger, but a firm's natural hedge is not significant. Our results show that financial structure, technology, and risk are jointly determined within industries. These findings are consistent with recent industry equilibrium models of financial structure. Copyright 2005, Oxford University Press.