This thesis presents the characterization and calibration of the MOPITT-A instrument which uses the technique of correlation spectroscopy to ensure carbon monoxide in the atmosphere. A theoretical model is developed for the instrument and compared to MOPITT-A measurements collected under controlled laboratory conditions, which were designed to emulate atmospheric signals. It is shown that the model and measurements are in very good agreement with each other and that the MOPITT-A instrument behaves as expected. It was found that the gain of the instrument varies with time. The cause of the gain variation is not known but it is suggested that frosting inside the detector nest would be consistent with the observed nature of the variation.

Deploying a large number of information security (INFOSEC) systems can provide in-depth protection for systems and networks. However, the sheer number of security alerts output by security sensors can overwhelm security analysts from performing effective analysis and taking timely response. Therefore, alert correlation is the core component in a security management system. Most of existing alert correlation techniques depend on a priori and hard-coded domain knowledge that lead to their limited capabilities of detecting new attack strategies. These approaches also focus more on the aggregation and analysis of raw security alerts, and build basic or low-level attack scenarios. This thesis focuses on discovering novel attack strategies with analysis of security alerts. Our framework helps security administrator aggregate redundant alerts, intelligently correlate security alerts, analyze attack strategies, and take appropriate actions against forthcoming attacks. In alert correlation, we have developed an integrated correlation system with three complementary correlation mechanisms. We have developed a probabilistic-based correlation engine that incorporates domain knowledge to correlate alerts that have direct causal relationship. We have developed a statistical analysis-based and a temporal analysis-based correlation engines to discover attack transition patterns in which attack steps do not have direct causal relationship in terms of security and performance measure but exhibit statistical and temporal patterns. We construct attack scenarios and conduct attack path analysis based on the correlation results. Security analysts are presented with aggregated information on attack strategies from the integrated correlation system. In attack plan recognition, we address the challenges of identifying attacker's high-level strategies and intentions as well as predicting upcoming attacks. We apply graph-based techniques to correlating isolated attack scenarios derived from low-level alert correlation based on their relationship in attack plans. We conduct probabilistic inference to evaluate the likelihood of attack goal(s) and predict potential upcoming attacks based on observed attack activities. We evaluate our algorithms using DARPA's Grand Challenge Problem (GCP) data sets and live traffic data collected from our backbone network. The results show that our approach can effectively discover novel attack strategies, provide a quantitative analysis of attack scenarios and identify attack plans.

In this thesis work, the background of atmospheric turbulence degradation in imaging was reviewed and two aspects are highlighted: blurring and geometric distortion. The turbulence burring parameter is determined by the atmospheric turbulence condition that is often unknown; therefore, a blur identification technique was developed that is based on a higher order statistics (HOS). It was observed that the kurtosis generally increases as an image becomes blurred (smoothed). Such an observation was interpreted in the frequency domain in terms of phase correlation. Kurtosis minimization based blur identification is built upon this observation. It was shown that kurtosis minimization is effective in identifying the blurring parameter directly from the degraded image. Kurtosis minimization is a general method for blur identification. It has been tested on a variety of blurs such as Gaussian blur, out of focus blur as well as motion blur. To compensate for the geometric distortion, earlier work on the turbulent motion compensation was extended to deal with situations in which there is camera/object motion. Trajectory smoothing is used to suppress the turbulent motion while preserving the real motion. Though the scintillation effect of atmospheric turbulence is not considered separately, it can be handled the same way as multiple frame denoising while motion trajectories are built.

Cooperative communications is an emerging technique that has spatial diversity inherent in wireless multiuser communication systems without multiple antennas at each node. Most studies in the literature assume that users acting as the relays are normally operated and trustworthy, which, however, may not always be true in practice. This thesis considers the design of robust cooperative communication in physical layer for combating relay misbehaviors. This thesis considers both models in which the cooperative communications is with direct path (WDP) and without direct path (WODP). Two signal-correlation-detection rules for both WDP and WODP are proposed, respectively. Utilizing the proposed signal-correlation-detection mechanism, the destination identifies the misbehaving relays within the cooperative communication network and then excludes their transmitting messages when performing the diversity combining to infer the symbols of interest sent by the source. The proposed signal-correlation-detection rules are optimally designed in accordance with either the criterion of the minimization of the probability of misbehavior misidentification or the criterion of the maximum generalized likelihood detector. In addition, this thesis also provides the BER analysis of the cooperative communications employing the proposed misbehaving relay detectors. The simulation result demonstrates that the proposed schemes have excellent robust performance when the relay misbehavior is present in the cooperative communication networks.

This paper studies the dependence structure between the real estate and financial markets in the United States from roughly 1975 to 2010, including the stock, bond and foreign exchange markets. This analysis uses dynamic copulas, including the Gaussian, Gumbel and Clayton copula. The Gumbel and Clayton copulas are used to separately capture the tail dependence of data. The dependence between the property indices (HPI and NCREIF) and the three financial markets is analyzed using the parameters of the copula. The property indices are divided in two different ways: by different regions and by different types of real estate. Although we study the dependence between the real estate and the financial markets in the U.S., the main objective of this paper is to analyze the change in the dependence structure when financial disasters occur. This study indicates that the real estate and the stock markets were positively related during this time period, and this dependence drove extreme movement when financial crises occurred. This dependence differed depending on the type of financial crisis, such as the Internet bubble crisis or the financial crisis in 2008. The dependence between the real estate and bond markets was also positively related, and extreme movement also occurred during financial crises. As for the dependence between the real estate and foreign exchange markets, although the results shows that dependence decreased when financial crises occurred, this is because the value of U.S. dollars are opposite to those of the index, and the left tail dependence exists as previous result. When looking at different regions or types of property, the differences in dependence structure were not obvious, although they were positively related. Both right and left tail dependences existed for most regions and property types, although some regions or types showed either right or left tail dependences alone. Therefore, investors should focus on the relationship between different markets, not on the region or type of real estate.

This paper refers to Ma and Hung(2004) using the amount of the institutional investors to measure the competitions of trading and the order flows of the institutional investors to measure correlations of information. We filter the data on daily basis and divide the data into four groups: high competition and high correlation, high competition and low correlation, low competition and high correlation, and low competition and low correlation. From the measurements of the informed traders¡¦ intraday behavior, we find that in the sample of high competitions of trading, the informed traders trade aggressively to exploit the common private information in the early period; In the middle period, since the common private information has been revealed to the market, the informed traders trade passively to avoid other informed traders knowing his private information; In the later period, the informed trader trade aggressively again to consume their private information before the market close. So, when trading these stocks, uninformed individual investors should avoid entering the market in the early and the later periods because of the high adverse selection cost. Besides, when prior return increases (decreases), the informed traders tend to place buy (sell) orders, indicating the informed traders are momentum traders. Last but not least, we observe in the sample of low competition and low correlation, the foreign investors behave differently in intraday strategy. Given the increasing of prior return, the buy (sell) orders of the foreign investors become passive (aggressive) in the early period, but in the later period, the buy (sell) orders of the foreign investors turn to be more aggressive (passive) with the increasing of prior return. The result may relate to the strategy of proprietary traders. For this reason, when trading these stocks, uninformed individual investors should avoid following the large orders and the momentum strategy in the early period.

This study investigated the significant differences and correlations on college students' quality of life and their occupational selections. A total of 870 college students were stratified randomly selected from 15 Taiwanese colleges. All participants completed "quality of life" and "occupational selections" scales. In addition, 4 target students with either the highest total scores on quality of life or with the highest total scores on occupational selections were recruited for individual follow-up interview. Independent t-test, one-way ANOVA, and canonical correlation assessed the similarities and differences between groups. The initial findings were as follows: 1. College students¡¦ quality of life and occupational selections appear to have upper middle satisfaction and identification. 2. Female college students' mean score on the dimension of "domestic factor' was significantly higher than their male counterparts. 3. The first birth born college students' total mean on the "quality of life' and the dimension of "mental health' were significantly higher than the last birth born college students. 4. College students with high educational expectation had significantly higher mean scores on the "occupational selections", dimensions of "domestic factor' and "occupational / social factor' than these low educational expectation participants. 5. College students from mothers with high educational levels presented significantly higher means on "quality of life ' and the dimension of "occupational / social factor" than their counterparts. 6. College students from mothers with high educational levels presented significantly higher means on "quality of life', "occupational selections' and the dimension of "occupational /social factor' than their counterparts. 7. Students come from private technology colleges presented significantly higher mean scores on "quality of life', "occupational selections', and dimensions of "physical health' ,"individual factor' and "domestic factor' than their counterparts. 8. High academic achievement college students' mean scores on the "quality of life', and the dimensions of "social health' and "individual factor' were significantly higher than these low academic college students. 9. College students from high income families presented significantly higher means on the dimensions of "mental health' and "social health' than these low income families¡¦ college students. 10. There were significant canonical correlations between college students' quality of life and occupational selections. Based on these results, some educational implications and suggestions are discussed.

This study investigated the significant differences and correlations on college students¡¦ reading motivation and their internet literacy. A total of 950 college students were stratified randomly selected from 17 Taiwanese colleges. All participants completed ¡§Reading motivation¡¨ and ¡§Internet literacy¡¨ scales. In addition, 5 target students with highest scores on internet literacy were recruited for standardized test and follow-up interview. Independent t-test, one-way ANOVA, and canonical correlation assessed the similarities and differences between groups. The initial findings were as follows: 1.College students¡¦ reading motivation and internet literacy appear to have moderate performance. 2.Female college students¡¦ mean score on ¡§reading motivation¡¨ was significantly higher than their male counterparts. 3.High academic achievement college students¡¦ mean score on ¡§internet literacy¡¨ was significantly higher than low academic college students. 4.College students who major in engineering, manufacturing domain¡¦s mean score on ¡§internet literacy¡¨, dimensions of ¡§information accessing¡¨, ¡§information sharing¡¨ were significantly higher than social sciences, business management domain¡¦s college students. And college students who major in liberal arts domain¡¦s mean score on dimensions of ¡§information creating¡¨ were significantly higher than agronomy major¡¦s college students. 5.College students with higher reading frequency¡¦s mean score on ¡§reading motivation¡¨ and ¡§internet literacy¡¨ were significantly higher than low reading frequency college students. 6.College students with higher book-borrowing frequency¡¦s mean score on ¡§reading motivation¡¨, dimensions of ¡§information creating¡¨ were significantly higher than low book-borrowing frequency college students. 7.College students consume more time on reading¡¦s mean score on ¡§reading motivation¡¨, dimensions of ¡§information creating¡¨ were significantly higher than these consuming less time on reading¡¦s participants. 8. College students with longer internet seniority¡¦s mean score on ¡§internet literacy¡¨, dimensions of ¡§information accessing¡¨, ¡§information evaluating¡¨ and ¡§information integrating¡¨ were significantly higher than less internet seniority¡¦s college students. 9.College students with higher educational expectation had significantly higher mean scores on ¡§reading motivation¡¨ and ¡§internet literacy¡¨ than these low educational expectation participants. 10.Canonical correlations between college students¡¦ ¡§reading motivation¡¨ and ¡§internet literacy¡¨ were found in this study.

The Leadership in Energy and Environmental Design (LEED) Green Building Rating System provides third-party verification for environmentally sustainable construction. LEED certified buildings often provide healthier work and living environments, however, it does not provide any direct economic incentives to the owners and developers. An early research suggested that there was a significant correlation between appraised unit value of a parcel and LEED sustainable site criteria for public transportation access. Moreover, the regression model for predicting appraised unit value of a parcel suggested that the coefficient of Number of Light Rail Stations was positive, while the coefficient of Number of Bus Stops was negative. This result contradicted our original expectation that both number of bus stops and light rail stations could have a positive effect on the appraised unit value. Hence it becomes important to conduct further research to explain this phenomenon. In this research, Pearson correlation was examined to determine whether there is a significant correlation between median household income and the number of bus stops and light rail stations for a given parcel that meet LEED sustainable site criteria for public transportation access. After confirming no significant correlation exists, multiple regression analysis was applied to establish a regression model for predicting unit value of a given parcel using number of bus stops and light rail stations for a given parcel that meet LEED sustainable site criteria for public transportation access, median household income and parcel area as the independent variables. Result of Pearson correlation indicated that there was no significant correlation exists between median household income and the number of bus stops and light rail stations for a given parcel which met LEED sustainable site criteria for public transportation access. Findings of multiple regression analysis suggested that all independent variables were significant predictors for unit value of a parcel. Besides, this regression model had a higher adjusted R- square value than that of the model which was established by Bhagyashri Joshi. It means that this regression model could better predict appraised unit value of an unimproved parcel.

This thesis mainly focuses on the integration of Space-Time Block Coding (STBC) and Complementary Code based CDMA system. Our proposed integration systems have not only the merit of complementary code but also the extra advantage of diversity gain from STBC. Especially, when the different frequency channel gain has strong correlation, the complementary code will cancel most of interference.