Perceptions regarding intercollegiate alliance among administrators of Taiwanese technological higher education institutions

This study explored Taiwanese technological higher education administrators' perceptions about the motivation and capability of their institutions to form intercollegiate alliance, their preferred areas of collaboration, and their preferred partner attributes. Possible differences in perceptions of administrators from public and private institutions were also explored. ^ The study targeted six chief administrators in each of 88 technological and vocational higher education institutions in Taiwan. A mix of quantitative and qualitative research designs was used to collect and analyze data. Quantitative data were collected from 328 administrators through a questionnaire and analyzed using univariate and multivariate statistical techniques. In addition, to obtain a deeper understanding of the process of alliance formation, qualitative data were collected through interviews with 13 administrators and content analyzed using emergent themes analysis. ^ Findings revealed that Taiwanese technological education administrators were not strongly confident in the competitive positions of their institutions. They perceived themselves as non-competitive in faculty research performance, in getting financial support, and having easy-access locations. Administrators believed that forming an alliance would help them obtain more external resources, achieve academic enhancement, provide better services, have a stronger voice, and obtain promotion to a higher institutional level. Cost cutting was not believed to be an attainable goal. ^ Strong interest was expressed for an alliance in the sharing of technology, information networks, and library resources; cross-registration; admissions and recruitment practices; school-industry endeavors; and international academic exchanges. Sharing of administrators and staff, joint bidding and purchasing, and cooperative fundraising were considered of less interest. ^ Administrators favored partners who have excellent academic programs, who have complementary skills, who are willing to share resources, and who are enthusiastic leaders. They also wanted partners to match their institutions in performance and prestige and to be geographically close to them. ^ Multivariate analysis of variance did not reveal significant differences between the perceptions of the administrators from public and private institutions. It was concluded that despite governmental encouragement and the institutions' eagerness for forming an alliance, the administrators had little confidence that a sustainable alliance could be arranged. ^

Women Hospitality Managers: Perceptions of Gender-Related Career Challenges

In spite of increases in the number of women who are both academically pre- pared and interested in pursuing hospitality management careers, women appear to be leaving the industry at a much higher rate than their male counter- parts. Although women are better represented in lower and middle management than ever before, there has been no corresponding increase in the number of women in top level management positions. The author explores women managers' perceptions of the career-related challenges they confront in hospitality environments and suggests that inadequate access to informal information networks, lack of women mentors, and the impact of unique job characteristics are their most significant concerns.

Mitigating congestion by integrating time forecasting and realtime information aggregation in cellular networks

An iterative travel time forecasting scheme, named the Advanced Multilane Prediction based Real-time Fastest Path (AMPRFP) algorithm, is presented in this dissertation. This scheme is derived from the conventional kernel estimator based prediction model by the association of real-time nonlinear impacts that caused by neighboring arcs’ traffic patterns with the historical traffic behaviors. The AMPRFP algorithm is evaluated by prediction of the travel time of congested arcs in the urban area of Jacksonville City. Experiment results illustrate that the proposed scheme is able to significantly reduce both the relative mean error (RME) and the root-mean-squared error (RMSE) of the predicted travel time. To obtain high quality real-time traffic information, which is essential to the performance of the AMPRFP algorithm, a data clean scheme enhanced empirical learning (DCSEEL) algorithm is also introduced. This novel method investigates the correlation between distance and direction in the geometrical map, which is not considered in existing fingerprint localization methods. Specifically, empirical learning methods are applied to minimize the error that exists in the estimated distance. A direction filter is developed to clean joints that have negative influence to the localization accuracy. Synthetic experiments in urban, suburban and rural environments are designed to evaluate the performance of DCSEEL algorithm in determining the cellular probe’s position. The results show that the cellular probe’s localization accuracy can be notably improved by the DCSEEL algorithm. Additionally, a new fast correlation technique for overcoming the time efficiency problem of the existing correlation algorithm based floating car data (FCD) technique is developed. The matching process is transformed into a 1-dimensional (1-D) curve matching problem and the Fast Normalized Cross-Correlation (FNCC) algorithm is introduced to supersede the Pearson product Moment Correlation Co-efficient (PMCC) algorithm in order to achieve the real-time requirement of the FCD method. The fast correlation technique shows a significant improvement in reducing the computational cost without affecting the accuracy of the matching process.