Since Taiwan and Vietnam established economic and commercial link in November 1992, the two countries¡¦ relationship has been getting closer and closer. Up to now, Taiwan is the second big investor in Vietnam. The similar customs and weather of the two countries and Vietnamese characteristics such as moderate, diligent, patient and studious became the considerable factors that urged Taiwan Government signed an Agreement with Vietnam in May 6, 1999 to import Vietnamese labors. Because the history of importing Vietnamese labors is not long, organizations may face some managerial problems with Vietnamese labors, so how to select and train Vietnamese labors in order to improve their job performance should be a research topic. This research uses sampling by self-determining from companies that import ten Vietnamese labors and upward. In addition, in order to understand if labors¡¦ performance is also affected by their value or not, this research selects four companies from the above group to probe Vietnamese, Taiwanese and Philipino labors¡¦ value. There are 88 questionnaires for companies¡¦ Human Resource departments, in which 32 retrieves are valid and 280 questionnaires for labors, in which 248 retrieves are valid. The research discovers companies that send officials to Vietnam to select labors can recruit better labors, especially labors¡¦ physical workload are obviously excellent. The longer Vietnamese labors stay in Taiwan, the better their performance is, especially technical skill, language ability, problem resolve ability and physical workload. When select Vietnamese labors, if companies pay more attention to language ability, adaptability and technical skills, their labors¡¦ performance will be better. In addition, if companies pay more attention to training, their labors¡¦ performance will be better. Especially if companies place much importance on training about organizations¡¦ rules, their labors¡¦ working attitude will be much better. This improves the importance of training for Vietnamese labors.

none

The purpose of this study was to explore the issues that are typically encountered when using personality instruments for personnel selection. Cattell's Sixteen Personality Factor Questionnaire (16PF) was used in the study to predict job performance in a small team-based manufacturing organization. Issues including the utility of the 16PF in this setting, the bandwidth fidelity argument (to use narrow or broad traits), and whether job-specific versus company-wide profiles provide better prediction success were addressed. The usefulness of the organization's current selection process of using the 16PF to generate interview questions was also investigated. Results indicate that the 16PF can be a useful tool for personnel selection in this setting and that the 16PF was able to correctly classify if an applicant was going to be successful over 86% of the time. Evidence for using narrow factors instead of broad factors was also presented, and the benefits of using job specific profiles were discussed. The limitations of this study were addressed, which included conducting this type of research with relatively small sample sizes. Additionally, this study provides suggestions for additional research in the future.

To detect dependence among variables is an essential task in many scientific investigations. In this study we propose a new measure of association, the coefficient of intrinsic dependence (CID), which takes value in [0,1] and faithfully reflects the full range of dependence for two random variables. The CID is free of distributional and functional assumptions. It can be easily implemented and extended to multivariate situations. Traditionally, the correlation coefficient is the preferred measure of association. However, it's effectiveness is considerably compromised when the random variables are not normally distributed. Besides, the interpretation of the correlation coefficient is difficult when the data are categorical. By contrast, the CID is free of these problems. In our simulation studies, we find that the ability of the CID in differentiating different levels of dependence remains robust across different data types (categorical or continuous) and model features (linear or curvilinear). Also, the CID is particularly effective when the dependence is strong, making it a powerful tool for variable selection. As an illustration, the CID is applied to variable selection in two aspects: classification and prediction. The analysis of actual data from a study of breast cancer gene expression is included. For the classification problem, we identify a pair of genes that best classify a patient's prognosis signature, and for the prediction problem, we identify a pair of genes that best relates to the expression of a specific gene.

High-throughput technologies for rapid measurement of vast numbers of biolog- ical variables offer the potential for highly discriminatory diagnosis and prognosis; however, high dimensionality together with small samples creates the need for fea- ture selection, while at the same time making feature-selection algorithms less reliable. Feature selection is required to avoid overfitting, and the combinatorial nature of the problem demands a suboptimal feature-selection algorithm. In this dissertation, we have found that feature selection is problematic in small- sample settings via three different approaches. First we examined the feature-ranking performance of several kinds of error estimators for different classification rules, by considering all feature subsets and using 2 measures of performance. The results show that their ranking is strongly affected by inaccurate error estimation. Secondly, since enumerating all feature subsets is computationally impossible in practice, a suboptimal feature-selection algorithm is often employed to find from a large set of potential features a small subset with which to classify the samples. If error estimation is required for a feature-selection algorithm, then the impact of error estimation can be greater than the choice of algorithm. Lastly, we took a regression approach by comparing the classification errors for the optimal feature sets and the errors for the feature sets found by feature-selection algorithms. Our study shows that it is unlikely that feature selection will yield a feature set whose error is close to that of the optimal feature set, and the inability to find a good feature set should not lead to the conclusion that good feature sets do not exist.

Nowadays, web services have been widely utilized on the Internet. The communication of organizations becomes much easier; thanks to the advances of computer and communication technologies and the inexpensive cost, and the integration of applications within and across business organizations is a trend. In general, there are two approaches in composing web services inside or outside an organization: orchestration and choreography. Previous work in the web service selection is usually based on orchestration model and focuses on the interest of a single party. However, in many application scenarios, business goals are achieved by pair-wise interactions among a set of WSs, and there is no single entity that is in charge of selecting web service for each task. Each web service can autonomously perform web service selection. By autonomy, we maintain that each WS is aware of only its partner web services. In such a choreographic environment, we study the kind of information that each web service should provide to its partner web services and how each web service should perform web service selection so as to maximize the chance of successfully accomplish a business goal. The proposed approach is evaluated by simulating 10,000 execution sequences of the target WS and assumed a fixed operation reliability for each delegation. The experimental results show that our proposed method is close to centralized method and better than other two selection methods, namely random and view-based-propagation-free.

Thesis (M.S.)--University of Wyoming, 2008. / Title from PDF title page (viewed on Nov. 19, 2009). Includes bibliographical references.

Thesis (Ph. D.)--Swedish University of Agricultural Sciences, 2001. / Thesis statement in Swedish and English abstract inserted. Includes bibliographical references.

Thesis (Ph. D.)--University of Chicago, Committee of Genetics, 2002. / Includes bibliographical references. Also available on the Internet.

Thesis (doctoral)--Universität, Kiel, 2000.