This dissertation: (a) investigated the degree to which the squared canonical correlation coefficient is biased in multivariate nonnormal distributions and (b) identified formulae that adjust the squared canonical correlation coefficient (Rc2) such that it most closely approximates the true population effect under normal and nonnormal data conditions. Five conditions were manipulated in a fully-crossed design to determine the degree of bias associated with Rc2: distribution shape, variable sets, sample size to variable ratios, and within- and between-set correlations. Very few of the condition combinations produced acceptable amounts of bias in Rc2, but those that did were all found with first function results. The sample size to variable ratio (n:v)was determined to have the greatest impact on the bias associated with the Rc2 for the first, second, and third functions. The variable set condition also affected the accuracy of Rc2, but for the second and third functions only. The kurtosis levels of the marginal distributions (b2), and the between- and within-set correlations demonstrated little or no impact on the bias associated with Rc2. Therefore, it is recommended that researchers use n:v ratios of at least 10:1 in canonical analyses, although greater n:v ratios have the potential to produce even less bias. Furthermore,because it was determined that b2 did not impact the accuracy of Rc2, one can be somewhat confident that, with marginal distributions possessing homogenous kurtosis levels ranging anywhere from -1 to 8, Rc2 will likely be as accurate as that resulting from a normal distribution. Because the majority of Rc2 estimates were extremely biased, it is recommended that all Rc2 effects, regardless of which function from which they result, be adjusted using an appropriate adjustment formula. If no rationale exists for the use of another formula, the Rozeboom-2 would likely be a safe choice given that it produced the greatest number of unbiased Rc2 estimates for the greatest number of condition combinations in this study.

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The engineered barrier system is a basic element in the design of repository to isolate high level radioactive waste (HLW). In this system, the clay barrier plays a prominent role in dispersing the heat generated from the waste, reduce the flow of pore water from the host rock, and maintaining the structural stability of the waste canister. The compacted expansive clay (generally bentonite blocks) is initially in unsaturated state. During the life time of the repository, the barrier will undergo different coupled thermal, hydrological and mechanical (THM) phenomena due to heating (from the heat-emitting nuclear waste) and hydration (from the saturated host rock). The design of nuclear waste disposal requires the prediction of the long term barrier behavior (i.e. hundred or thousand years), so numerical modeling is a basic component of the repository design. The numerical analyses are performed using mathematical THM formulation and the associated numerical code. Constitutive models are an essential part of the numerical simulations. Those constitutive models represent the intrinsic behavior of the material for the individual physical phenomenon (i.e. thermal, hydraulic and mechanical). Deterministic analyses have shown the potential of such mathematical formulations to describe the physical behavior of the engineered barrier system. However, the effect of the inherent uncertainties associated with the different constitutive models on the global behavior of the isolation system has not been explored yet. The first part of this thesis is related to application of recent probabilistic methods to understand and assess the impact of uncertainties on the global THM model response. Experimental data associated with the FEBEX project has been adopted for the case study presented in this thesis. CODE_BRIGHT, a fully coupled THM finite element program, is used to perform the numerical THM analysis. The second part of this thesis focuses on the complex mechanical behavior observed in a barrier material subjected (during 5 years) to heating and hydration under actual repository conditions The studied experiment is the (ongoing) full scale in-situ FEBEX test at Grimsel test site, Switzerland. A partial dismantling of this experiment has allowed the inspection of the barrier material subjected to varying stresses due to hydration and heating. The clay underwent both elastic and plastic volumetric deformations at different suction and temperature levels with changes in the pre-consolidation pressure and voids ratio that are difficult to explain with conventional models. In this thesis a double structure elasto plastic model is proposed to study the mechanical behavior of this barrier material. The numerical modeling was performed with CODE_BRIGHT. The study shows that the double structure model explains satisfactorily the observed changes in the mechanical behavior of the clay material.

In this thesis, an analysis of Bitcoin, Monero price and volatility is conducted with respect to S&P500 and the VIX index. Moreover using Python, we computed correlation coefficients of nine cryptocurrencies with two different approaches: Pearson and Spearman from July 2016 -July 2018. Moreover the Pearson correlation coefficient was computed for each year from July2016 - July 2017 - July 2018. It has been concluded that in 2016 the correlation between the selected cryptocurrencies was very weak - almost none, but in 2017 the correlation increased and became moderate positive. In 2018, almost all of the cryptocurrencies were highly correlated. For example, from January until July of 2018, the Bitcoin - Monero correlation was 0.86 and Bitcoin - Ethereum was 0.82.

Within the area under consideration there are two great series of strata. The lower one is known as the Purcell-Belt Series and is divided into two main groups. A widespread unconformity separates the Purcell Series from the younger and overlying Windermere Series. The Lower Purcell-Belt group consists of the Aldridge-Prichard, Creston-Ravalli, Kitchener-Wallace, and Siyeh-Striped Peak. They were deposited under marine conditions from the erosion of a western Precambrian Cascadia. The Upper Purcell-Belt group consists of the Dutch Creek, Mount Nelson and their equivalents in Canada and the Missoula Group of Montana and possibly the Priest River group of Washington. This group is separated from the Lower Purcell by a period of diastrophism marked by the intrusion of Purcell sills and the extrusion of Purcell lavas. The Upper Purcell-Belt sediments were derived from the positive areas as a result of the preceding crusted disturbance. The Purcell-Belt times were closed by large scale orogeny called the "Purcell Uplift". The north-south trending belt of Purcell mountains formed a landmass which greatly affected lower Palaeozoic stratigraphy. This positive area is commonly referred to as the "Montana Island". The Precambrian portion of the Windermere Series includes the Toby-Shedroof conglomerate, Irene Deola volcanics and the Horsethief Creek-Monk formations. The clastic formations were derived from the Purcell Mountains and deposited on their western flank. Marine conditions arose during Horsethief Creek times. The Cambrian portion of the Windermere Series was deposited in a north-south trending geosynclinal trough which extended from the Metaline quadrangle to the Field-Golden area of the Rocky Mountains and probably beyond. It includes the lower quartzitic Hamill Group and the overlying limy and argillaceous Lardeau group. They were deposited as the shoreline transgressed south and east over the "Montana Island" and reduced it from one of high relief to one of low relief. Stages of emergence and resumed sedimentation are indicated, by upper formations of the Lardeau group. / Science, Faculty of / Earth, Ocean and Atmospheric Sciences, Department of / Graduate

Correlation tests were run on yearly snowfall and tornado activity data collected between water-years 1965/66 and 2010/11. Snowfall activity was evaluated using two separate measurements, which included snowfall days and daily snow depth. Tornado activity was measured through tornado days and total yearly tornado occurrences. Tornado days were defined as a 24-h period (0600–0600 UTC) during which either one or more tornadoes occurred within a chosen southern region boundary. Correlation tests revealed an absence of any mutual relationship between the snowfall and tornado activity. Three prominent teleconnections (ENSO, NAO, & AO), 6-month (Oct-Dec and Feb-Apr) and 3-month means (Oct-May) were also analyzed to reveal possible correlations with the tornado and snowfall activity. Significant negative correlations were found between ONI × tornado days; ONI × tornado totals; NAOI × snowfall days; NAOI × snow depth; AOI × snowfall days; and AOI × snow depth

ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada / Thermocouple measurements require “cold junction” compensation in order to obtain a correct reading. This compensation has traditionally been done with custom circuitry. In flight test applications where volume and power are at a premium (e.g. weapons flight test) it is desirable to have a more flexible solution that uses standard analog data acquisition channels already available as part of the encoder circuitry and performs compensation with remote software. This can be done via digital compensation, but certain measures must be taken to maintain accuracy and minimize noise. This paper describes some of these techniques and their performance tradeoffs.

International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / This paper proposes a problem that the error tolerance property of spread spectrum sequence influences the performance of spread spectrum system. Then the relation is analyzed between the error tolerance property and the correlation property of binary sequence when correlation detection is proceeded, and the theoretical limitation of error tolerance is given. Finally, we investigate the relationship between the determination of the output decision threshold of correlation, the probability of correlation peak detection and the error tolerance of the spread spectrum sequence.

Ovarian cancer results from the dysregulation, in normal ovarian epithelial cells, of genes responsible for the control of critical biological processes. Since their discovery 20 years ago, microRNAs have increasingly been implicated in that dysregulation due to their role mediating gene expression; changes in microRNA expression levels in cancer have been linked with tumor growth, proliferation and metastasis. Their imputed involvement in cancer has led to the possibility of their use as biomarkers and to their potential clinical use. Using mRNA and microRNA microarray analysis to compare human gene expression in normal ovarian surface epithelial (OSE) cells and epithelial ovarian cancer (EOC) cells, we explored the interactions between microRNAs and genes. First, we validated in silico predictions of microRNA targets by comparing them with in vitro evidence after exogenous microRNA transfection. We found that pairs of microRNAs with identical 7-nt (nucleotide) seed regions shared 88% of their predicted targets and 55% of their in vitro targets, confirming the importance of the seed as a targeting mechanism. But more importantly, we found that even a single nucleotide change in the seed region can result in a significant shift in the set of targeted genes, implying strong functional conservation of the seeds and their corresponding binding sites. Next, we discovered a 3-element network motif which explains the upregulation of nearly 800 genes in ovarian cancer which, as predicted microRNA targets, might be expected to be down- regulated. This model shows that, under certain circumstances, repressor genes which are down- regulated in cancer can apparently override the repressive effects of microRNAs, resulting in the upregulation of predicted microRNA targets. Finally, we developed a phenomenological network model, based on the Pearson correlation of microarray gene expression data, to identify subnetworks dysregulated in cell cycle and apoptosis. While our methodology reported many genes previously associated with ovarian cancer, it significantly suggested potentially oncogenic genes for further investigation. This network model can easily be extended to identify dysregulated genes in other cancers.

International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California / The emergence of encrypted PCM as a standard within DOD makes possible the correction of time skews between diverse data sources. Time alignment of data streams can be accomplished before decryption and so is independent of specific format. Data quality assessment in order to do a best-source selection remains problematic, but workable.