University of Macau

About: University of Macau is a education organization based out in Macao, Macau, China. It is known for research contribution in the topics: Population & Control theory. The organization has 6636 authors who have published 18324 publications receiving 327384 citations. The organization is also known as: UM & UMAC.

A model of emotional intelligence and conflict management strategies: a study in seven countries

Abstract: The study investigated the relationships of the five dimensions of emotional intelligence: self‐awareness, self‐regulation, motivation, empathy, and social skills of supervisors to subordinates' strategies of handling conflict: problem solving and bargaining. Data (N = 1,395) for this study were collected with questionnaires from MBA students in seven countries (U.S., Greece, China, Bangladesh, Hong Kong and Macau, South Africa, and Portugal). Psychometric properties of the measures were tested and improved with exploratory and confirmatory factor analysis and analysis of indicator and internal consistency reliabilities, and the hypotheses were tested with a structural equations model for each country. Results in the U.S. and in the combined sample provided support for the model which suggests that self‐awareness is positively associated with self‐regulation, empathy, and social skills; self regulation is positively associated with empathy and social skills; empathy and social skills are positively associated with motivation; which in turn, is positively associated with problem solving strategy and negatively associated with bargaining strategy. Differences among countries in these relationships are noted and implications for organizations discussed.

Short-selling, margin-trading, and price efficiency: Evidence from the Chinese market

Abstract: China launched a pilot scheme in March 2010 to lift the ban on short-selling and margin-trading for stocks on a designated list. We find that stocks experience negative returns when added to the list. After the ban is lifted, price efficiency increases while stock return volatility decreases. Panel data regressions reveal that intensified short-selling activities are associated with improved price efficiency. Short-sellers trade to eliminate overpricing by selling stocks with higher contemporaneous returns following a downward trend, and their trades predict future returns. In contrast, we find intensified margin-trading activities for stocks with lower contemporaneous returns, and these trades have no return predictive power.

Ultra-high electrocatalytic activity of VS2 nanoflowers for efficient hydrogen evolution reaction

Abstract: It is a great challenge to explore cheap, abundant and eco-friendly electrocatalysts for hydrogen evolution reaction (HER). Here, we report the fabrication of VS2 nanoflowers with 1T phase by a simple hydrothermal method and their electrocatalytic performance in the HER. We find that the VS2 nanoflowers show comparable HER performance to Pt in acids, including an ultra-low onset potential of 32 mV, a Tafel slope of 34 mV dec−1 which resembles that of Pt, and a small overpotential of 58 mV (54 mV for Pt) at a current density of 10 mA cm−2. High stability and almost 100% faradaic efficiency indicate the practical application of VS2 nanoflowers in the HER. Our first-principles calculations reveal that the thermoneutral Gibbs free energy of hydrogen adsorption on both the basal and edge sites of the 1T-VS2 monolayer can be achieved under certain hydrogen coverage and the monolayer shows good conductivity, which contribute to the impressive catalytic performance of VS2 nanoflowers. We expect that the VS2 nanostructures may be applicable in electrocatalysis with high efficiency.

New Flexure Parallel-Kinematic Micropositioning System With Large Workspace

Abstract: Flexure-based micropositioning systems with a large workspace are attractive for a variety of precision engineering applications. In this paper, a new idea of multistage compound parallelogram flexure is proposed for the mechanism design of a novel parallel-kinematic XY micropositioning system, which has a motion range larger than 10 mm along with a compact structure. The established quantitative models and the stage performances are validated by conducting finite-element analysis (FEA) and experimental studies. Moreover, an enhanced model-predictive control (EMPC) is presented for positioning control of the system, which has a nonminimum-phase plant. It is shown that the EMPC is capable of producing a low magnitude of output tracking error by imposing an appropriate suppression on the control effort. Simulation and experimental studies reveal that the EMPC scheme outperforms the conventional proportional-integral-derivative (PID) and MPC methods in terms of transient response speed and steady-state accuracy. The idea that is presented in this paper is extendable to design and control of other micro-/nanopositioning systems with either minimum- or nonminimum-phase plants.

Extreme Learning Machine With Composite Kernels for Hyperspectral Image Classification

Abstract: Due to its simple, fast, and good generalization ability, extreme learning machine (ELM) has recently drawn increasing attention in the pattern recognition and machine learning fields. To investigate the performance of ELM on the hyperspectral images (HSIs), this paper proposes two spatial–spectral composite kernel (CK) ELM classification methods. In the proposed CK framework, the single spatial or spectral kernel consists of activation–function-based kernel and general Gaussian kernel, respectively. The proposed methods inherit the advantages of ELM and have an analytic solution to directly implement the multiclass classification. Experimental results on three benchmark hyperspectral datasets demonstrate that the proposed ELM with CK methods outperform the general ELM, SVM, and SVM with CK methods.