Abstract The 21st century globalization and liberalization pose distinctive human resource management challenges to businesses especially those operating across national boundaries as multinational or global enterprises (Huselid, 1995). According to Huselid (1995), strategic human resource management primary should be emphasized to ensure that managers and employees are adjusting and accepting their organizational human resource practices in their daily work, thus, the human resource management practices appear to be more essential. The study attempted to gain a better understanding of the human resource management practices in hairdressing salon service industry in Taiwan by analyzing the relationships between employee¡¦s technical skill and organizational commitment on work performance. The data was collected by the researcher using mailing and delivering questionnaires. The sample size included 500 hair stylists from north, central, and south of Taiwan. There were 307 questionnaires and the return rate was 61.4%. The data was analyzed by descriptive statistics, Pearson correction analysis, and Structure equation modeling. The results of this study were as follows: 1. The perception of hair stylists on the human resource management practices showed high in employment security, then in decrease status distinction, training, contingent and compensation. 2. The organizational commitment and technical ability showed positive corrections on human resource system. In addition, the influence on the organizational commitment is greater than on the technical ability. 3. There was a negative relationship between organizational commitment and turnover intention. 4. There was a positive relationship between technical skill and work performance. 5. The work performance could be improved by using the intermediary result of technical ability from the human resource management practices. 6. There was a negative relationship between turnover intention and human resource management practices.

There are two purposes in this research, one is the development of the new method which can be used for detection and quantification of triarylmethanes in fish tissues. The other is that we confirmed validation and utility of triarylmethanes by the method that is according to Commission Decision 2002/657/EC. Homogenized fish tissues were extracted twice with acetonitrile and defatted with n-hexane. HPLC separation was conducted with the RP-18 column. The mobile phases consisted of 0.5 mM ammonium acetate buffer (pH 3.8, adjusted with acetic acid)¡V ACN (contained 0.1% formic acid) solution. Triarylmethane was determined by LC-ESI-MS/MS in positive mode. The correlation coefficients of calibration curves with triarylmethane in fish tissues were 0.998 ~ 0.999. The decision limits (CC£\) were 0.16 ¡Ó 0.07 £gg/kg(MG), 0.15 ¡Ó 0.04 £gg/kg(LMG), 0.20 ¡Ó 0.13 £gg/kg(CV) and 0.23 ¡Ó 0.12 £gg/kg(LCV), and detection capabilities (CC£]) were 0.20 ¡Ó 0.09 £gg/kg(MG), 0.18 ¡Ó 0.05 £gg/kg(LMG), 0.24 ¡Ó 0.16 £ggkg-1(CV) and 0.29 ¡Ó 0.15 £gg/kg(LCV).

Sustaining high performance demand has led to the development of manycore processors. These manycore processors have thermal properties which are different from conventional processors. In order to understand the thermal characteristics of such manycore processors, we have developed a modeling environment with a rich set of features which can be used to used to model different scenarios in manycore processors. Using this modeling framework, we have developed a thermal management policy called 'Weight based management policy'. We have also developed a GUI based modeling tool which can be integrated into the computer architecture curriculum so as to enable students to understand the importance of thermal limitations right during the design phase.

This thesis describes the efficient design of a future many-core processor that can provide higher performance under the limited chip power budget. To achieve such a goal, this thesis first develops an analytical framework within which computer architects can estimate achievable performance improvement of different many-core architectures given the same power budget. From this study, this thesis found that a future many-core processor needs (1) energy-efficient parallel cores and (2) a high-performance sequential core. Based on these observations, this thesis proposes an energy-efficient broad-purpose acceleration layer that can be snapped on top of a conventional general-purpose processor. In addition to such an energy-efficient parallel cores, this thesis also proposes different architectural techniques to further boost the performance of sequential computation while those parallel cores are idle. In particular, this thesis develops low-cost architectural techniques to enhance the memory performance of a host core by utilizing those idle parallel cores. This idea is evaluated in two different system architectures: one with the aforementioned acceleration layer and the other with an emerging integrated CPU and GPU chip.

The thesis explores the sources of energy inefficiency in asymmetric multi- core architectures where energy efficiency is measured by the energy-delay squared product. The insights gathered from this study drive the development of optimized thread scheduling and coordinated cache management strategies in an important class of asymmetric shared memory architectures. The proposed techniques are founded on well known mathematical optimization techniques yet are lightweight enough to be implemented in practical systems.

Achieving a high degree of efficiency is non-trivial when managing the performance of large web-facing applications such as e-commerce websites and social networks. While computing clouds have been touted as a good solution for elastic applications, many significant technological challenges still have to be addressed in order to leverage the full potential of this new computing paradigm. In this dissertation I argue that the automation of elastic n-tier application performance management in computing clouds presents novel challenges to classical system performance management methodology that can be successfully addressed through a systematic empirical approach. I present strong evidence in support of my thesis in a framework of three incremental building blocks: Experimental Analysis of Elastic System Scalability and Consolidation, Modeling and Detection of Non-trivial Performance Phenomena in Elastic Systems, and Automated Control and Configuration Planning of Elastic Systems. More concretely, I first provide a proof of concept for the feasibility of large-scale experimental database system performance analyses, and illustrate several complex performance phenomena based on the gathered scalability and consolidation data. Second, I extend these initial results to a proof of concept for automating bottleneck detection based on statistical analysis and an abstract definition of multi-bottlenecks. Third, I build a performance control system that manages elastic n-tier applications efficiently with respect to complex performance phenomena such as multi-bottlenecks. This control system provides a proof of concept for automated online performance management based on empirical data.

Thesis (M.S.)--Eastern Illinois University, 2009. / Includes bibliographical references (leaves [117]-125).

Thesis (M.S.)--Mississippi State University. Department of Electrical and Computer Engineering. / Title from title screen. Includes bibliographical references.

Thesis (M.S.)--Mississippi State University. Department of Computational Engineering. / Title from title screen. Includes bibliographical references.

Thesis (M.S.)--Mississippi State University. Department of Electrical and Computer Engineering. / Title from title screen. Includes bibliographical references.