Under the mechanism of natural selection, creatures are forced to evolve naturally in order to survive. Keen-sighted jumping spiders have long been considered as the main predation pressure of terrestrial arthropod. Many species benefit from mimicking the appearance of jumping spider. In this study according to the experimental data from Wang (2009b), a data analysis is undertaken concerning male Ptocasius strupifer¡¦s behavior to different subject groups, namely, male Ptocasius strupifer, female Ptocasius strupifer, male Plexippus paykulli, female Plexippus paykulli, Cataclysta angulata and Eugauria albidentata, so as to investigate the jumping spider mimicry of Eugauria albidentata. In this work, our interest is to compare the behavior of male Ptocasius strupifer on Eugauria albidentata with there of the other five groups mentioned above, and identify which one is the most similar to there of Eugauria albidentata . We use different statistical methods, i.e. likelihood ratio test, factor analysis and cluster analysis to evaluate the closeness of the behavior between different groups. According to the analysis result, it shows that the behavior of Ptocasius strupifer towards Eugauria albidentata is more similar to those of both female Ptocasius strupifer and female Plexippus paykulli. Moreover there is a wide discrepancy between Eugauria albidentata and Cataclysta angulata, although both of them belong to Musotiminae.

Prior to 1960, most countries over the world used traditional economic indicators to represent their social status. Economists mostly used Gross National Product, GNP, as a measurement of the social welfare standard of a country or a society. However, with the progress of the development, the traditional economic indicators were unable to follow the progress of social welfares. Therefore, it made economists hard to measure the status of social welfares. Sen (1977) thought that the development of human beings is not restricted to the increase of average disposable incomes only. He thought that people should use the indicators with more information to measure the distinctive diversity of welfares. Bauer (1966) first stated the social indicators as a measurement of social status and trends. Then, the so-called ¡§Social Indicators Movement¡¨ was aroused by Bauer¡¦s theory. As a result, to measure the development of a society entirely, people could determine the development from the medicine, health, economy, environment, and welfare aspects. In the researches about social developments, there were many discussions in building indicators of social welfare, quality of living, basic fulfillment, and development of welfare. The research is trying to establish a system of social indicators to measure the development from every aspect and selecting the social indicator index with representative indicators as a measurement of society development. Moreover, this research would analyze the systems of social indicators in Taiwan from 1982 to 2002 to see if the government made an appropriate allocation of resources in the executions of related policies. The research refers to 20 related indicator systems in Taiwan and overseas as their times of quotes and principles of selecting indicators to sum up 9 probable indicators. Then, the Principal Component Analysis method and the Varian method are adopted as research methods to abstract factors. Moreover, there are two abstracted factors. One is economic and environment factor and another one is medical welfare and unemployment factor. The research uses weighted method to find out the synthetic indicators in Taiwan from 1982 to 2002. The weighted multiple gained from factor analysis for the two factors is 0.8353 and 0.1647. Based on the data mining and analysis from second information, three scores were acquired, economic and environment factor, medical welfare and unemployment factor, and entirely performance. Each of these three scores shows the trend and the change year by year. The last, according the result from this analysis, the policy and recommendation was brought up.

Although e-enterprise has been a main stream, there are many stories about the resistance of employees. On the other hand, by the times of knowledge economy age and the popularity of e-learning, a lot of people join the online classes or traditional classes with the support of e-learning system after their office hours. Actually, e-learning system is one kind of e-enterprise systems. If the e-learning experience can let the students be more knowledgeable to the e-enterprise, it will be very helpful to proceed e-enterprise project. The purpose of this research is to probe whether the experience of e-learning would impact the cognition of e-enterprises development. This research adopted quantitative method to explore the relationship between e-learning experience and e-enterprise cognition. A questionnaire survey has been sent to the students who have used the e-learning systems in online courses or traditional courses. According to statistic analyses, the major conclusions are as follows: 1. The e-learning experiences have significant impact on e-enterprise cognition. 2. The impact of the experience of using discussion tools of e-learning systems on e-enterprise cognition will not be interfered by student¡¦s studying attitude. 3. However, The impact of the experience of using supplementary tools of e-learning systems on e-enterprise cognition will be interfered by student¡¦s studying attitude.

Kaohsiung is a densely populated harbor city, in which the density of motor vehicles is also high. Since the temperature and sunlight is also relatively high in Southern Taiwan, tending to transform ambient volatile organic compounds to ozone thus causes high ozone events. This study measured the concentrations of 63 hydrocarbon (HC) species from C2 to C15 simultaneously at the Nan-Chie and Hsiung-Kong sites in Kaohsiung city during the morning (07-10), the afternoon (13-16), and the evening (18-21) periods on three successive days in winter 2004. Results show that the most abundant species of Kaohsiung¡¦s air is toluene (43.01-60.95 £gg/m3), followed by i-pentane, 1,2,4-trimethylbenzene, benzene, n-butane, propane, and acetylene, in the range 9.55-16.93 £gg/m3, while the concentrations of halocarbons is 0.17-4.12 £gg/m3. Alkanes (44.7-45.9%) represent the largest proportion of the total HC, followed by aromatics (35.4-36.8%), alkenes (10.5-10.9%) and halocarbons (3.6-3.9 %). The OFP (ozone formation potential) of HC species were evaluated based on the MIR (maximum incremental reactivity). Results show that aromatics (45.9-54.3%) represent the largest proportion of the OFP, followed by alkenes (17.7-37.5%), and alkanes (16.5-23.6%). The results from the factor analyses show the major sources of ambient HC in Kaohsiung city are the vehicle exhausts, industrial processes, solvent evaporations, combustion exhausts, and petrochemical processes.

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Because of the economic development of Taiwan, population gathering and the habit of people using transports, these considerations have made vehicle grow up fast. Vehicles emitted a large amount of pollutant that has caused many air pollution occasions. The motive of this study is to understand the motorcycle driving cycle, amount of pollutant and emission factor in four areas ¡VTaipei, Taichung, Kaoshiung and Pingtung. But it is very poor on concerning study in Taiwan. It is necessary to go on the concerning investigation and to establish the driving cycle and the actual emission factor of mobile source of Taiwan. The experiment includes two parts: one is regional driving pattern that is selected by factor analysis from samples; the other is to get the concentration of the pollutant and to calculate emission factors of the one by using Dynamometer. The pollutants are carbon monoxide (CO), total hydrocarbon (THC) and nitrogen oxides (NOX). In this study, the emission factors of motorcycles of the four areas are ¡§Taipei: CO 8.24 g/km, THC 2.53 g/km, NOX 0.12 g/km, CO2 55.98 g/km, Taichung: CO 7.81 g/km, THC 2.28 g/km, NOX 0.12 g/km, CO2 54.31 g/km, Kaoshiung: CO 6.53 g/km, THC 1.62 g/km, NOX 0.13 g/km, CO2 54.03 g/km, and Pingtung: CO 6.79 g/km, THC 1.63 g/km, NOX 0.13 g/km, CO2 41.42 g/km.

This dissertation consists of three essays. Chapter II uses the method of structural factor analysis to study the effects of monetary policy on key macroeconomic variables in a data rich environment. I propose two structural factor models. One is the structural factor augmented vector autoregressive (SFAVAR) model and the other is the structural factor vector autoregressive (SFVAR) model. Compared to the traditional vector autogression (VAR) model, both models incorporate far more information from hundreds of data series, series that can be and are monitored by the Central Bank. Moreover, the factors used are structurally meaningful, a feature that adds to the understanding of the “black box” of the monetary transmission mechanism. Both models generate qualitatively reasonable impulse response functions. Using the SFVAR model, both the “price puzzle” and the “liquidity puzzle” are eliminated. Chapter III employs the method of structural factor analysis to conduct a forecasting exercise in a data rich environment. I simulate out-of-sample real time forecasting using a structural dynamic factor forecasting model and its variations. I use several structural factors to summarize the information from a large set of candidate explanatory variables. Compared to Stock and Watson (2002)’s models, the models proposed in this chapter can further allow me to select the factors structurally for each variable to be forecasted. I find advantages to using the structural dynamic factor forecasting models compared to alternatives that include univariate autoregression (AR) model, the VAR model and Stock and Watson’s (2002) models, especially when forecasting real variables. In chapter IV, we measure U.S. technology shocks by implementing a dual approach, which is based on more reliable price data instead of aggregate quantity data. By doing so, we find the relative volatility of technology shocks and the correlation between output fluctuation and technology shocks to be much smaller than those revealed in most real-business-cycle (RBC) studies. Our results support the findings of Burnside, Eichenbaum and Rebelo (1996), who showed that the correlation between technology shocks and output is exaggerated in the RBC literature. This suggests that one should examine other sources of fluctuations for a better understanding of the business cycle phenomena.

The Wechsler Intelligence Scale for Children – Third Edition (WISC-III; Wechsler, 1991) and the Children’s Memory Scale (CMS; Cohen, 1997) are frequently used measures of children’s cognitive ability and memory, respectively. They are often used together to assess a child’s strengths and weaknesses to individualize recommendations for assisting them in the educational setting. However, research suggests that there may be some overlap in the abilities assessed by these instruments, making complete administration of both somewhat redundant. Furthermore, previous studies have been equivocal with regard to the assessment of children with Attention- Deficit/ Hyperactivity Disorder (ADHD) on the WISC-III. Support for the applicability of the four-factor structure of the WISC-III has been questioned, particularly in terms of its utility in the diagnosis of ADHD based on the Freedom from Distractibility Index (FFD). A combined confirmatory factor analysis was conducted on the WISC-III and CMS to determine whether a combination of their subtests could be used in lieu of complete administration of each test. The combined WISC-III/ CMS standardization sample was obtained from the Psychological Corporation for use in the confirmatory factor analyses. One-, six-, and seven-factor models were initially proposed for the analyses. Results of the combined confirmatory factor analyses indicated that all three models failed to fit the data as well as a new five-factor model that was created during modification of the six-factor model. Once the five-factor model was specified as the most appropriate model, a clinical sample from a research study was analyzed on the model to find out whether there were age and gender performance differences and also to determine how accurately the new factors differentiated between clinical and nonclinical subsamples. Results indicated that males and females performed significantly differently on the Processing Speed factor but there were no age differences. There were significant differences between the ADHD and no diagnosis groups on three factors: Verbal Comprehension, Working Memory, and Processing Speed; there were no differences on the factors between ADHD subtypes. Together, the five factors were able to correctly classify 66% of children with ADHD. Implications of these results are discussed and suggestions for future research are provided.

The trend in personal finance and retirement planning has changed, more and more investors have focused on the popular issue of wealth allocation across asset classes and specific investments. As a result, mutual fund investment companies have become an increasingly effective conduit for current income generation, capital appreciation, and the benefits derived through diversification. As time goes by, the amount of offshore funds introduced in Taiwan is increasing. We investors always want to ask which one could perform well and bring the investors a good return based on the past performance information. Thus the purpose of this paper is to give an overview and performance persistence of the largely unexploited Taiwan offshore and international American, European, Japanese, and Global equity mutual funds compared to Taiwan equity mutual funds and the Information Technology equity mutual funds. To do this, we evaluate fund performance applied for the Composite Index to cooperate the highly cooperate the colinearity problem of the performance indices which is introduced from Lee (2007) and Chou (2007). We focus on 6 biggest off-shore mutual fund market in Taiwan which are American, European, Global, Taiwan, Japan and Information Technology. All the performance information and fund characteristic are from Lipper. We restrict our sample to pure equity funds with at least 36 months of data. Performance details and specific fund characteristics are collected by the end of 2006. We develop the Composite Index component weights by factor analysis from January 2003 through December 2004 and rank the funds by the Composite Index score to exam the performance persistence through January 2005 through 2006. All returns are almost in local currency. We have the conclusion which all the difference in performance of the top 10% and the bottom 10% in each market is significant from zero except for the Information Technology industry. We find the effect of the Composite Index would depend on the maturity, variety, and the characteristic of the market. The more mature the market is, the less significant the performance between top deciles and bottom deciles, American mutual fund is the best supportive evidence. All the return-based indices are not adding value to select funds. Though the performance of the Composite Index is better than the other index, the raw annual return is not so high to be applied. As to the variety, the different categories and the range of the distribution of monthly return in the market have the effect to the significance of the difference in performance between the top 10% and the bottom 10%, markets of European, Global, Japan, and Taiwan are the best explanations. Finally, the higher the risk is the better the fund perform is the one special rule selecting fund in the market of Information Technology.

Thesis (M.A.)--University of Notre Dame, 2008. / Thesis directed by Ke-Hai Yuan for the Department of Psychology. "December 2008." Includes bibliographical references (leaves 105-106).