Flooding is one of the fatal natural hazards frequently generating serious impact to infrastructures. As yet, its characteristics are expected to be changing with the changing of global climate. This paper identifies the spatio-temporal correlation patterns of disruptions by flooding hazards at the county-level for the Deep South in the United States, particularly the state of Arkansas. The frequency of each flooding disruption calculated as time series, is generated from flooding records within research period of 1998-2013. A set of quality control procedures including duplicated data check, spatial outliers check, and homogeneity test is applied prior to the regression analysis. The spatial characteristic of those disruptions is identified by mapping them, while their temporal characteristic is assessed using correlation coefficient defined in this paper. Accordingly, greater correlation of disruptions by flooding is found with the decreasing of the distance between for most pairs of the locations throughout the study period.

Selenium, the essential trace element, is well known as its antioxidant function, antiviral properties, and its anti-inflammatory function to human health. The relationships between selenium status and diabetes mellitus have been widely studied, but the consistency of results is lacking. This study used diagnosed diabetes incidence from year 2004 to 2012 and soil selenium content by counties within 48 contiguous states in the U.S. with Generalized Linear Mixed Model- R-Side as the major statistical method to determine whether there is a significant correlation or not. Results showed that the diagnosed diabetes population had been increased from 2004 to 2012 for all 48 states. The South region showed the highest increased rate whereas the Northeast region showed the least. Also, Kentucky, Louisiana, Maryland, and Massachusetts are the four states showed the significant correlation between soil selenium content and diabetes incidence. However, improved analytical methods and data are needed for further research.

Single nucleotide polymorphisms (SNPs) have been involved in describing the risk a person is at for developing diseases. Simulating a collection of d correlated autosomal biallelic SNPs is useful to acquire empirical results for statistical tests in settings such as having a low sample size. A collection of d correlated autosomal biallelic SNPs can be modeled as a random vector X = (X1,...,Xd) where Xi ∼ binomial(2, pi) and pi is the minor allele frequency for the ith SNP. The pairwise correlations between components of X can be specified by a d ×d symmetric positive definite correlation matrix having all diagonal entries equal to one. Two versions of a novel method to simulate X are developed in this thesis; one version is based on generating correlated binomials directly and the other is based on generating correlated Bernoulli random vectors and summing them component wise. Two existing methods to simulate X are also discussed and implemented. In particular, a method involving the multivariate normal by Madsen and Birkes (2013) is compared to our novel methods for d ≥ 3. Our novel binomial method has a different variance for the Fisher transformed sample correlation than the other two methods. Overall, if the target pairwise correlations are smaller than the lowest upper bound possible and the number of SNPs is low, then our novel Bernoulli method works the best since it is faster than the Madsen and Birkes method and has comparable variability and bias for sample correlation. / Thesis / Master of Science (MSc)

<p> The (α,n) reaction on natural chromium has been used to study levels in 55Fe up to 2.5 MeV excitation. Intensities and angular distributions of the decay gamma rays were measured, yielding branching and E2/M1 mixing ratios. In a magnetized target of the alloy Cr20Fe80, the rotation of the angular distributions was observed. Using recently determined lifetimes and the average internal field of 277 kOe measured in the target material by Mössbauer absorption, the following g-factors are obtained: - 931 keV, 5/2- -: +1.2 ±0.5 1316 keV, 7/2- -: +0.5 ± 0.5 1408 keV, 7/2- -: -0.77 ± 0.16 </p> / Thesis / Master of Science (MSc)

Soil chemical and physical properties are important to farm productivity, and they vary within fields, so farmers are interested in managing inputs like fertilizer according to local soil conditions within fields. Thus, they must have knowledge of soil conditions of interest, which have historically been measured at a few locations with tedious soil sampling and laboratory analyses. Advantageous to farmers would be a measurement method that provided more geographically detailed information at similar or lower cost. Remote and ground-based optical sensing are possibilities for gathering detailed soil information rapidly and inexpensively. This study considers the possibility of optically measuring soil characteristics. The first objective was to determine relationships between spectral reflectance in the 250- to 2500-nm range and the following soil constituents: clay, sand, Ca, K, Mg, Na, P, Zn, and acidity (pH). The second objective was to find wavebands for estimating certain soil properties, with the goal of sensor development. Physical, chemical, and spectral-reflectance measurements were made on 969 soil samples collected from two Mississippi fields over two years. Reflectances were averaged over 50-nm wavebands and analyzed with simple- and multiple-linear regression and canonical correlation in relation to soil properties. No single waveband was highly correlated to any soil property in this study, but waveband groups exhibited strong correlations with some soil properties. Clay was the only property consistently strongly correlated (R2 ¡Ý 0.50) to waveband groups over different fields and years. In general, waveband groups that were most highly correlated with a specific soil property in one field in one year were not similar to waveband groups most highly correlated with that property in a different field or year. Thus, it was difficult to select a waveband group for sensor development regarding a specific soil property. However, a group of nine promising wavebands was considered for estimating clay, and results for data in this study indicated the feasibility of grossly estimating clay content with spectral reflectance. Canonical correlation analysis demonstrated strong correlations among certain groups of soil-properties and wavebands. Clay appeared as the most promising property for sensor development from this portion of the study also.

Simultaneous testing of multiple null hypotheses has now become an integral part of statistical analysis of data arising from modern scientific investigations. Often the test statistics in such multiple testing problem are correlated. The research in this dissertation is motivated by the scope of improving or extending existing methods to incorporate correlation in the data. Sarkar (2008) proposes controlling the pairwise false discovery rate (Pairwise-FDR), which inherently takes into account the dependence among the p-values, thereby making it a more robust, less conservative and more powerful under dependence than the usual notion of FDR. In this dissertation, we further investigate the performance of Pairwise-FDR under a dependent mixture model. In particular, we consider a step-up method to control the Pairwise-FDR under this model assuming that the correlation between any two p-values is the same (exchangeable). We also suggest improving this method by incorporating an estimate of the number of pairs of true null hypotheses developed under this model. Efron (2007, Journal of the American Statistical Association 102, 93-103) proposed a novel approach to incorporate dependence among the null p-values into a multiple testing method controlling false discoveries. In this dissertation, we try to investigate the scope of utilizing this approach by proposing alternative versions of adaptive Bonferroni and BH methods which estimates the number of true null hypotheses from the empirical null distribution introduced by Efron. These newer adaptive procedures have been numerically shown to perform better than existing adaptive Bonferroni or BH methods within a wider range of dependence. A gene expression microarray data set has been used to highlight the difference in results obtained upon applying the proposed and other adaptive BH methods. Another approach to address the presence of correlation is motivated by the scope of utilizing the dependence structure of the data towards further improving some multiple testing methods while maintaining control of some error rate. The dependence structure of the data is incorporated using pairwise weights. In this dissertation we propose a weighted version of the pairwise FDR (Sarkar, 2008) using pairwise weights and a method controlling the weighted pairwise- FDR. We give a discussion on the application of such weighted procedure and suggest some weighting schemes that generates pairwise weights. / Statistics

The Direct-Video-Broadcast Satellite (DVB-S) standard is used to provide video and radio to millions of users worldwide. It is designed to provide quasi-error free satellite communications. This thesis discusses some of the limitations of the DVB-S standard, describes some attempts in related work to address these concerns, and purposes a new modification to enhance the performance and reliability of the Direct-Video-Broadcast Satellite (DVB-S) standard by using a correlator in a DVB-S receiver. In many existing receive chains, synchronization speed is slightly delayed because phase ambiguity cannot be determined and corrected until after Viterbi decoding. Using correlation against known symbols before demodulation, the phase ambiguity can be corrected prior to Viterbi decoding, thus reducing the amount of time required to synchronize the received signal. To enhance the correlator's ability to detect the DVB-S synchronization bytes, a two byte, rather than single byte, known sync word is proposed as a modification to the standard. The motivation behind a longer sync word is to improve the standard in high noise environments. A two byte sync word provides more known information for correlation. The resulting correlation peaks are double that of when a single byte is used; this corresponds to about a 3 dB increase in SNR to provide fast signal acquisition and signal tracking in a noisy environment. / Master of Science

No / The conventional summation generator (SG) has been broken in the past using a number of different methods. Recently, a modified SG was proposed by Lee and Moon to increase the resistance of such generators against these attacks. However, this paper shows that even the modified generator is still vulnerable to correlation attacks.

Most American universities and colleges require students to provide faculty evaluation at end of each academic term, as a way of measuring faculty teaching performance. Although some analysts think that this kind of evaluation does not necessarily provide a good measurement of teaching effectiveness, there is a growing agreement in the academic world about its reliability. This study attempts to find any strong statistical evidence supporting faculty evaluation by students as a measure of faculty teaching effectiveness. Emphasis will be on analyzing relationships between instructor ratings by students and corresponding students’ grades. Various statistical methods are applied to analyze a sample of real data and derive conclusions. Methods considered include multivariate statistical analysis, principal component analysis, Pearson's correlation coefficient, Spearman's and Kendall’s rank correlation coefficients, linear and logistic regression analysis.

Cross-correlation is often used as the primary technique to compare two biological signals. The cross-correlation technique is an effective means to measure the synchronization of two signals if the relative phases at all frequencies are distributed linearly, that is, there is a group delay. The group delay assumption of cross-correlation analysis imposes an unfavourable restriction on signals with relative phase correlation which varies at different frequencies. Traditional Fourier analysis applied to a short data segments, namely the Short Time Fourier Transform (STFT), provides phase information for each frequency component, but it is not suitable for biological signals with non-stationary statistics for which the ideal segment length is unknown. The application of a wavelet based phase analysis technique is discussed in this study. The frequency decomposition and temporally localized nature of the wavelet transform provides localized phase-frequency information for two signals. A wavelet frequency temporal relative phase pattern (WFT-RPP) technique to extract relative phase information at specific frequencies over the time course of a time-varying signal was developed. The technique was tested on simulated data and surface electromyographic (sEMG) data recorded from upper limb muscles in human subjects as they performed a series of dynamic push and pull tasks. Selected sEMG channel pairs are compared against each other using the WFT-RPP technique to extract the relative phase information and repetitive relative phase patterns for certain muscle pairs were observed. The properties of the WFT-RPP and the merits and weaknesses of using the technique for determining intermuscular sEMG synchronization is discussed. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2011-09-13 11:58:16.014