City University of Hong Kong

About: City University of Hong Kong is a education organization based out in Hong Kong, China. It is known for research contribution in the topics: Computer science & Nonlinear system. The organization has 19778 authors who have published 60149 publications receiving 1738681 citations. The organization is also known as: CityU.

Bulk metallic glasses

Abstract: Amorphous alloys were first developed over 40 years ago and found applications as magnetic core or reinforcement added to other materials. The scope of applications is limited due to the small thickness in the region of only tens of microns. The research effort in the past two decades, mainly pioneered by a Japanese- and a US-group of scientists, has substantially relaxed this size constrain. Some bulk metallic glasses can have tensile strength up to 3000 MPa with good corrosion resistance, reasonable toughness, low internal friction and good processability. Bulk metallic glasses are now being used in consumer electronic industries, sporting goods industries, etc. In this paper, the authors reviewed the recent development of new alloy systems of bulk metallic glasses. The properties and processing technologies relevant to the industrial applications of these alloys are also discussed here. The behaviors of bulk metallic glasses under extreme conditions such as high pressure and low temperature are especially addressed in this review. In order that the scope of applications can be broadened, the understanding of the glass-forming criteria is important for the design of new alloy systems and also the processing techniques.

Surface modification of titanium, titanium alloys, and related materials for biomedical applications

Abstract: Titanium and titanium alloys are widely used in biomedical devices and components, especially as hard tissue replacements as well as in cardiac and cardiovascular applications, because of their desirable properties, such as relatively low modulus, good fatigue strength, formability, machinability, corrosion resistance, and biocompatibility. However, titanium and its alloys cannot meet all of the clinical requirements. Therefore, in order to improve the biological, chemical, and mechanical properties, surface modification is often performed. This article reviews the various surface modification technologies pertaining to titanium and titanium alloys including mechanical treatment, thermal spraying, sol–gel, chemical and electrochemical treatment, and ion implantation from the perspective of biomedical engineering. Recent work has shown that the wear resistance, corrosion resistance, and biological properties of titanium and titanium alloys can be improved selectively using the appropriate surface treatment techniques while the desirable bulk attributes of the materials are retained. The proper surface treatment expands the use of titanium and titanium alloys in the biomedical fields. Some of the recent applications are also discussed in this paper.

Least Squares Generative Adversarial Networks

Abstract: Unsupervised learning with generative adversarial networks (GANs) has proven hugely successful. Regular GANs hypothesize the discriminator as a classifier with the sigmoid cross entropy loss function. However, we found that this loss function may lead to the vanishing gradients problem during the learning process. To overcome such a problem, we propose in this paper the Least Squares Generative Adversarial Networks (LSGANs) which adopt the least squares loss function for the discriminator. We show that minimizing the objective function of LSGAN yields minimizing the Pearson $\chi^2$ divergence. There are two benefits of LSGANs over regular GANs. First, LSGANs are able to generate higher quality images than regular GANs. Second, LSGANs perform more stable during the learning process. We evaluate LSGANs on five scene datasets and the experimental results show that the images generated by LSGANs are of better quality than the ones generated by regular GANs. We also conduct two comparison experiments between LSGANs and regular GANs to illustrate the stability of LSGANs.

Contributing knowledge to electronic knowledge repositories: an empirical investigation

Abstract: Organizations are attempting to leverage their knowledge resources by employing knowledge management (KM) systems, a key form of which are electronic knowledge repositories (EKRs). A large number of KM initiatives fail due to the reluctance of employees to share knowledge through these systems. Motivated by such concerns, this study formulates and tests a theoretical model to explain EKR usage by knowledge contributors. The model employs social exchange theory to identify cost and benefit factors affecting EKR usage, and social capital theory to account for the moderating influence of contextual factors. The model is validated through a large-scale survey of public sector organizations. The results reveal that knowledge self-efficacy and enjoyment in helping others significantly impact EKR usage by knowledge contributors. Contextual factors (generalized trust, pro-sharing norms, and identification) moderate the impact of codification effort, reciprocity, and organizational reward on EKR usage, respectively. It can be seen that extrinsic benefits (reciprocity and organizational reward) impact EKR usage contingent on particular contextual factors whereas the effects of intrinsic benefits (knowledge self-efficacy and enjoyment in helping others) on EKR usage are not moderated by contextual factors. The loss of knowledge power and image do not appear to impact EKR usage by knowledge contributors. Besides contributing to theory building in KM, the results of this study inform KM practice.

Tropical cyclones and climate change

Abstract: Whether the characteristics of tropical cyclones have altered, or will alter, in a changing climate has been subject of considerable debate. An overview of recent research indicates that greenhouse warming will cause stronger storms, on average, but a decrease in the frequency of tropical cyclones. Whether the characteristics of tropical cyclones have changed or will change in a warming climate — and if so, how — has been the subject of considerable investigation, often with conflicting results. Large amplitude fluctuations in the frequency and intensity of tropical cyclones greatly complicate both the detection of long-term trends and their attribution to rising levels of atmospheric greenhouse gases. Trend detection is further impeded by substantial limitations in the availability and quality of global historical records of tropical cyclones. Therefore, it remains uncertain whether past changes in tropical cyclone activity have exceeded the variability expected from natural causes. However, future projections based on theory and high-resolution dynamical models consistently indicate that greenhouse warming will cause the globally averaged intensity of tropical cyclones to shift towards stronger storms, with intensity increases of 2–11% by 2100. Existing modelling studies also consistently project decreases in the globally averaged frequency of tropical cyclones, by 6–34%. Balanced against this, higher resolution modelling studies typically project substantial increases in the frequency of the most intense cyclones, and increases of the order of 20% in the precipitation rate within 100 km of the storm centre. For all cyclone parameters, projected changes for individual basins show large variations between different modelling studies.