Ming Chuan University

About: Ming Chuan University is a education organization based out in Taoyuan District, Taiwan. It is known for research contribution in the topics: Tourism & Service quality. The organization has 2206 authors who have published 3205 publications receiving 52602 citations. The organization is also known as: MCU.

Teacher self-efficacy and teaching practices in the health and physical education curriculum in Taiwan

Abstract: The purpose in this study was to confirm the relationship between teacher self-efficacy and teaching practices in the health and physical education (HPE) curriculum in Taiwan. We used stratified random sampling and cluster sampling methods to select 842 HPE teachers from elementary schools in Taiwan. They completed the Teacher Self-Efficacy Scale in HPE and the Teaching Practice Scale in HPE (Pan, 2006, 2007). Structural equation modeling was used to analyze the suitability of the hypothetical model. Results indicated that the model had acceptable goodness-of-fit and it was concluded that teachers’ self-efficacy has a positive effect on teaching practices in HPE.

Revisiting Early Warning Signals of Corporate Credit Default Using Linguistic Analysis

Abstract: We apply computational linguistic text mining (TM) analysis to extract and quantify relevant Chinese financial news in an attempt to further develop the classical early warning models of financial distress. Extending the work of Demers and Vega (2011), we propose a measure of the degree of credit default, referred to in this study as the ‘distress intensity of default-corpus’ (DIDC), and investigate the predictive power of this measure on default probability by incorporating it into the signaling model, along with the classical financial performance variables (the liquidity, debt, activity and profitability ratios). We also apply the ‘naive probability of the Merton distance to default’ model (Bharath and Shumway, 2008) for our robustness analysis. A logistic regression (LR) model is constructed to better integrate the DIDC and financial performance variables into a more effective early warning signal model, with the incorporation of DIDC into the LR model revealing a significant reduction in Type I errors and an apparent increase in classification accuracy. This provides proof of the effectiveness of the additional information from TM on the financial corpus, whilst also confirming the predictive power of TM on credit default. The major contribution of this study stems from our potential refinement of early warning models of financial distress through the incorporation of information provided by related media reports.

Utility-Aware Charging Scheduling for Multiple Mobile Chargers in Large-Scale Wireless Rechargeable Sensor Networks

Abstract: Mobile charging can provide stable and reliable energy replenishment for wireless rechargeable sensor network (WRSN) However, relatively low charging utility exists in existing solutions In this paper, we present a utility-based collaborative charging (UBCC) strategy to maximize the charging utility of mobile chargers (MCs) in large-scale WRSNs Charging MCs and server MCs are employed to jointly achieve our goal by three aspects First, a path merging scheme is designed to save the traveling paths of MCs Unlike existing studies with entirely diverse movement trajectories of MCs, the same traveling path is assigned to both the departure charging MCs and the return MCs, which serve different charging areas Second, an idle-difference alleviating scheme is devised to improve the utilization rate of MCs Different from current solutions with a large difference of working hours of MCs, each charging MC is assigned the equal charging tasks, resulting in synchronous charging and simultaneous energy replenishment of MCs Third, an energy-waste averting scheme is designed to maximize the energy utilization of MCs The energy of each MC is just exhausted until the MC completes its charging tasks and traveling roles Extensive simulation results demonstrate the advantages of UBCC in the charging cost and charging utility

A profile of information systems research published in expert systems with applications from 1995 to 2008

Abstract: Expert systems with applications (ESWA) has been regarded as one of the highly qualified journals in the information system. This paper profiles research published in ESWA from 1995 to 2008. Based on the multidimensional analysis, we identified the most productive author and universities, research paper numbers per geographic region, and the most employed issues and methodologies used by the most highly published authors. Our results indicate that (1) ESWA is clearly an internationalized journal, (2) the most employed methodologies are fuzzy ESs and knowledge-based systems, and (3) the leading highly published authors always have diverse methodologies and applications. Furthermore, the implications for researchers, journal editors, universities, and research institution are presented.