Дисертації: "Rank analysis"

1

Busse, Ludwig M. Orbanz Peter Buhmann Joachim M. Buhmann Joachim M. Buhmann Joachim M. "Cluster analysis of heterogeneous rank data." Zurich : ETH Department of Computer Science, Institute of Computational Sciences, 2007. http://e-collection.ethbib.ethz.ch/show?type=dipl&nr=350.

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2

Cerny, C. M. "On higher rank Cuntz-Pimsner algebras." Thesis, University of Nottingham, 2012. http://eprints.nottingham.ac.uk/13243/.

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3

Chan, Yip-cheung, and 陳葉祥. "Minimal rank of abelian group matrices." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B29797512.

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4

Chan, Yip-cheung. "Minimal rank of abelian group matrices /." Hong Kong : University of Hong Kong, 1996. http://sunzi.lib.hku.hk/hkuto/record.jsp?B1759215X.

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5

Hatefi, Armin. "Mixture model analysis with rank-based samples." Statistica Sinica, 2013. http://hdl.handle.net/1993/23849.

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Анотація:

Simple random sampling (SRS) is the most commonly used sampling design in data collection. In many applications (e.g., in fisheries and medical research) quantification of the variable of interest is either time-consuming or expensive but ranking a number of sampling units, without actual measurement on them, can be done relatively easy and at low cost. In these situations, one may use rank-based sampling (RBS) designs to obtain more representative samples from the underlying population and improve the efficiency of the statistical inference. In this thesis, we study the theory and application of the finite mixture models (FMMs) under RBS designs. In Chapter 2, we study the problems of Maximum Likelihood (ML) estimation and classification in a general class of FMMs under different ranked set sampling (RSS) designs. In Chapter 3, deriving Fisher information (FI) content of different RSS data structures including complete and incomplete RSS data, we show that the FI contained in each variation of the RSS data about different features of FMMs is larger than the FI contained in their SRS counterparts. There are situations where it is difficult to rank all the sampling units in a set with high confidence. Forcing rankers to assign unique ranks to the units (as RSS) can lead to substantial ranking error and consequently to poor statistical inference. We hence focus on the partially rank-ordered set (PROS) sampling design, which is aimed at reducing the ranking error and the burden on rankers by allowing them to declare ties (partially ordered subsets) among the sampling units. Studying the information and uncertainty structures of the PROS data in a general class of distributions, in Chapter 4, we show the superiority of the PROS design in data analysis over RSS and SRS schemes. In Chapter 5, we also investigate the ML estimation and classification problems of FMMs under the PROS design. Finally, we apply our results to estimate the age structure of a short-lived fish species based on the length frequency data, using SRS, RSS and PROS designs.

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6

Subramanian, Nandita. "Analysis of Rank Distance for Malware Classification." University of Cincinnati / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479823187035784.

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7

Ziegler, Caleb. "On Factors of Rank One Subshifts." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1157623/.

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Rank one subshifts are dynamical systems generated by a regular combinatorial process based on sequences of positive integers called the cut and spacer parameters. Despite the simple process that generates them, rank one subshifts comprise a generic set and are the source of many counterexamples. As a result, measure theoretic rank one subshifts, called rank one transformations, have been extensively studied and investigations into rank one subshifts been the basis of much recent work. We will answer several open problems about rank one subshifts. We completely classify the maximal equicontinuous factor for rank one subshifts, so that this factor can be computed from the parameters. We use these methods to classify when large classes of rank one subshifts have mixing properties. Also, we completely classify the situation when a rank one subshift can be a factor of another rank one subshift.

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8

Kang, Zhao. "LOW RANK AND SPARSE MODELING FOR DATA ANALYSIS." OpenSIUC, 2017. https://opensiuc.lib.siu.edu/dissertations/1366.

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Nowadays, many real-world problems must deal with collections of high-dimensional data. High dimensional data usually have intrinsic low-dimensional representations, which are suited for subsequent analysis or processing. Therefore, finding low-dimensional representations is an essential step in many machine learning and data mining tasks. Low-rank and sparse modeling are emerging mathematical tools dealing with uncertainties of real-world data. Leveraging on the underlying structure of data, low-rank and sparse modeling approaches have achieved impressive performance in many data analysis tasks. Since the general rank minimization problem is computationally NP-hard, the convex relaxation of original problem is often solved. One popular heuristic method is to use the nuclear norm to approximate the rank of a matrix. Despite the success of nuclear norm minimization in capturing the low intrinsic-dimensionality of data, the nuclear norm minimizes not only the rank, but also the variance of matrix and may not be a good approximation to the rank function in practical problems. To mitigate above issue, this thesis proposes several nonconvex functions to approximate the rank function. However, It is often difficult to solve nonconvex problem. In this thesis, an optimization framework for nonconvex problem is further developed. The effectiveness of this approach is examined on several important applications, including matrix completion, robust principle component analysis, clustering, and recommender systems. Another issue associated with current clustering methods is that they work in two separate steps including similarity matrix computation and subsequent spectral clustering. The learned similarity matrix may not be optimal for subsequent clustering. Therefore, a unified algorithm framework is developed in this thesis. To capture the nonlinear relations among data points, we formulate this method in kernel space. Furthermore, the obtained continuous spectral solutions could severely deviate from the true discrete cluster labels, a discrete transformation is further incorporated in our model. Finally, our framework can simultaneously learn similarity matrix, kernel, and discrete cluster labels. The performance of the proposed algorithms is established through extensive experiments. This framework can be easily extended to semi-supervised classification.

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9

Zhang, Kai. "Kernel-based clustering and low rank approximation /." View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?CSED%202008%20ZHANG.

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10

Kudela, László [Verfasser], Ernst [Akademischer Betreuer] Rank, Zohar [Gutachter] Yosibash, Ernst [Gutachter] Rank, and Uwe [Gutachter] Stilla. "Image-based finite element analysis / László Kudela ; Gutachter: Zohar Yosibash, Ernst Rank, Uwe Stilla ; Betreuer: Ernst Rank." München : Universitätsbibliothek der TU München, 2020. http://d-nb.info/1222161648/34.

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11

Cronin, Blaise, and Lokman I. Meho. "Using the H-index to Rank Influential Information Scientists." Wiley, 2006. http://hdl.handle.net/10150/105439.

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We apply a new bibliometric measure, the h-index (Hirsch, 2005), to the literature of information science. Faculty rankings based on raw citation counts are compared with those based on h-counts. There is a strong positive correlation between the two sets of rankings. We show how the h-index can be used to express the broad impact of a scholarâ s research output over time in more nuanced fashion than straight citation counts.

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12

Zhou, Ke. "Extending low-rank matrix factorizations for emerging applications." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50230.

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Low-rank matrix factorizations have become increasingly popular to project high dimensional data into latent spaces with small dimensions in order to obtain better understandings of the data and thus more accurate predictions. In particular, they have been widely applied to important applications such as collaborative filtering and social network analysis. In this thesis, I investigate the applications and extensions of the ideas of the low-rank matrix factorization to solve several practically important problems arise from collaborative filtering and social network analysis. A key challenge in recommendation system research is how to effectively profile new users, a problem generally known as \emph{cold-start} recommendation. In the first part of this work, we extend the low-rank matrix factorization by allowing the latent factors to have more complex structures --- decision trees to solve the problem of cold-start recommendations. In particular, we present \emph{functional matrix factorization} (fMF), a novel cold-start recommendation method that solves the problem of adaptive interview construction based on low-rank matrix factorizations. The second part of this work considers the efficiency problem of making recommendations in the context of large user and item spaces. Specifically, we address the problem through learning binary codes for collaborative filtering, which can be viewed as restricting the latent factors in low-rank matrix factorizations to be binary vectors that represent the binary codes for both users and items. In the third part of this work, we investigate the applications of low-rank matrix factorizations in the context of social network analysis. Specifically, we propose a convex optimization approach to discover the hidden network of social influence with low-rank and sparse structure by modeling the recurrent events at different individuals as multi-dimensional Hawkes processes, emphasizing the mutual-excitation nature of the dynamics of event occurrences. The proposed framework combines the estimation of mutually exciting process and the low-rank matrix factorization in a principled manner. In the fourth part of this work, we estimate the triggering kernels for the Hawkes process. In particular, we focus on estimating the triggering kernels from an infinite dimensional functional space with the Euler Lagrange equation, which can be viewed as applying the idea of low-rank factorizations in the functional space.

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13

Mahata, Kaushik. "Estimation Using Low Rank Signal Models." Doctoral thesis, Uppsala University, Department of Information Technology, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-3844.

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Designing estimators based on low rank signal models is a common practice in signal processing. Some of these estimators are designed to use a single low rank snapshot vector, while others employ multiple snapshots. This dissertation deals with both these cases in different contexts.

Separable nonlinear least squares is a popular tool to extract parameter estimates from a single snapshot vector. Asymptotic statistical properties of the separable non-linear least squares estimates are explored in the first part of the thesis. The assumptions imposed on the noise process and the data model are general. Therefore, the results are useful in a wide range of applications. Sufficient conditions are established for consistency, asymptotic normality and statistical efficiency of the estimates. An expression for the asymptotic covariance matrix is derived and it is shown that the estimates are circular. The analysis is extended also to the constrained separable nonlinear least squares problems.

Nonparametric estimation of the material functions from wave propagation experiments is the topic of the second part. This is a typical application where a single snapshot vector is employed. Numerical and statistical properties of the least squares algorithm are explored in this context. Boundary conditions in the experiments are used to achieve superior estimation performance. Subsequently, a subspace based estimation algorithm is proposed. The subspace algorithm is not only computationally efficient, but is also equivalent to the least squares method in accuracy.

Estimation of the frequencies of multiple real valued sine waves is the topic in the third part, where multiple snapshots are employed. A new low rank signal model is introduced. Subsequently, an ESPRIT like method named R-Esprit and a weighted subspace fitting approach are developed based on the proposed model. When compared to ESPRIT, R-Esprit is not only computationally more economical but is also equivalent in performance. The weighted subspace fitting approach shows significant improvement in the resolution threshold. It is also robust to additive noise.

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14

Siegert, Stefan. "Rank statistics of forecast ensembles." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-102152.

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Ensembles are today routinely applied to estimate uncertainty in numerical predictions of complex systems such as the weather. Instead of initializing a single numerical forecast, using only the best guess of the present state as initial conditions, a collection (an ensemble) of forecasts whose members start from slightly different initial conditions is calculated. By varying the initial conditions within their error bars, the sensitivity of the resulting forecasts to these measurement errors can be accounted for. The ensemble approach can also be applied to estimate forecast errors that are due to insufficiently known model parameters by varying these parameters between ensemble members. An important (and difficult) question in ensemble weather forecasting is how well does an ensemble of forecasts reproduce the actual forecast uncertainty. A widely used criterion to assess the quality of forecast ensembles is statistical consistency which demands that the ensemble members and the corresponding measurement (the ``verification\'\') behave like random independent draws from the same underlying probability distribution. Since this forecast distribution is generally unknown, such an analysis is nontrivial. An established criterion to assess statistical consistency of a historical archive of scalar ensembles and verifications is uniformity of the verification rank: If the verification falls between the (k-1)-st and k-th largest ensemble member it is said to have rank k. Statistical consistency implies that the average frequency of occurrence should be the same for each rank. A central result of the present thesis is that, in a statistically consistent K-member ensemble, the (K+1)-dimensional vector of rank probabilities is a random vector that is uniformly distributed on the K-dimensional probability simplex. This behavior is universal for all possible forecast distributions. It thus provides a way to describe forecast ensembles in a nonparametric way, without making any assumptions about the statistical behavior of the ensemble data. The physical details of the forecast model are eliminated, and the notion of statistical consistency is captured in an elementary way. Two applications of this result to ensemble analysis are presented. Ensemble stratification, the partitioning of an archive of ensemble forecasts into subsets using a discriminating criterion, is considered in the light of the above result. It is shown that certain stratification criteria can make the individual subsets of ensembles appear statistically inconsistent, even though the unstratified ensemble is statistically consistent. This effect is explained by considering statistical fluctuations of rank probabilities. A new hypothesis test is developed to assess statistical consistency of stratified ensembles while taking these potentially misleading stratification effects into account. The distribution of rank probabilities is further used to study the predictability of outliers, which are defined as events where the verification falls outside the range of the ensemble, being either smaller than the smallest, or larger than the largest ensemble member. It is shown that these events are better predictable than by a naive benchmark prediction, which unconditionally issues the average outlier frequency of 2/(K+1) as a forecast. Predictability of outlier events, quantified in terms of probabilistic skill scores and receiver operating characteristics (ROC), is shown to be universal in a hypothetical forecast ensemble. An empirical study shows that in an operational temperature forecast ensemble, outliers are likewise predictable, and that the corresponding predictability measures agree with the analytically calculated ones.

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15

Papaioannou, Iason [Verfasser], Ernst Akademischer Betreuer] Rank, Daniel [Akademischer Betreuer] Straub, and Manolis [Akademischer Betreuer] [Papadrakakis. "Non-intrusive finite element reliability analysis methods / Iason Papaioannou. Gutachter: Daniel Straub ; Ernst Rank ; Manolis Papadrakakis. Betreuer: Ernst Rank." München : Universitätsbibliothek der TU München, 2012. http://d-nb.info/1024161439/34.

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16

CHEN, ZHAOREN. "ANALYSIS OF EQUITY MARKETS: A SPEARMAN RANK CORRELATION COEFFICIENT APPROACH." Thesis, The University of Arizona, 2016. http://hdl.handle.net/10150/612636.

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In this honors thesis, I attempted to develop an investment strategy to analyze the U.S. stock market by studying the correlations between nine sectors defined by the Select Sector Standard & Poor’s Depository Receipts (SPDR). These funds are a group of exchange-traded funds (ETFs) which are traded worldwide and can adequately represent the performance of the sectors. Through my method, I hope to identify the sector trends in the future by evaluating the sector ETF’s most recent short-term period data. This analysis will provide an alternate investment method for investors to avoid short-term investment risk as well as explanations of why I think the approach may not be valid.

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17

David, Thomson 1961. "A system dynamics based analysis of "rank and fire" management policy." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/91738.

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18

Strazzullo, Francesco. "Symmetry Analysis of General Rank-3 Pfaffian Systems in Five Variables." DigitalCommons@USU, 2009. https://digitalcommons.usu.edu/etd/449.

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In this dissertation we applied geometric methods to study underdetermined second order scalar ordinary differential equations (called general Monge equations), nonlinear involutive systems of two scalar partial differential equations in two independent variables and one unknown and non-Monge-Ampere Goursat parabolic scalar PDE in the plane. These particular kinds of differential equations are related to general rank-3 Pfaffian systems in five variables. Cartan studied these objects in his 1910 paper. In this work Cartan provided normal forms only for some general rank-3 Pfaffian systems with 14-, 7-, and 6-dimensional symmetry algebra. We applied our normal forms to [i] sharpen Cartan's integration method of nonlinear involutive systems, [ii] classify all general Monge equations with a freely acting transverse 3-dimensional symmetry algebra, of which many new examples are presented, and [iii] provide a broad classification of non-Monge-Ampere Darboux integrable hyperbolic PDE in the plane. We developed a computer software, called FiveVariables, that classifies general rank-3 Pfaffian systems. FiveVariables runs in the environment DifferentialGeometry of Maple, version 11 and later.

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19

Rovi, Ana. "Analysis of 2 x 2 x 2 Tensors." Thesis, Linköping University, Department of Mathematics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-56762.

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The question about how to determine the rank of a tensor has been widely studied in the literature. However the analytical methods to compute the decomposition of tensors have not been so much developed even for low-rank tensors.

In this report we present analytical methods for finding real and complex PARAFAC decompositions of 2 x 2 x 2 tensors before computing the actual rank of the tensor.

These methods are also implemented in MATLAB.

We also consider the question of how best lower-rank approximation gives rise to problems of degeneracy, and give some analytical explanations for these issues.

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20

Treece, Kelly S. "Personality and Promotion: An Analysis of the Structured Rank of Female Officers." ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/3236.

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Female law enforcement officers remain an underrepresented population in ranking positions within police organizations in the United States. Current research focuses on systemic factors that inhibit female law enforcement officers within the United States from achieving positions of rank. Grounded in Costa and McCrae's five factor model of personality, this study examined female law enforcement officers' personality traits and their relation to achieved rank. This quantitative study used multiple regression analysis of survey data to determine whether the personality traits of openness, conscientiousness, extraversion, agreeableness, and/or neuroticism alone or in combination predict rank. American female law enforcement officers in both ranking and nonranking positions were sampled from the social media site LEO-ONLY. Data collection included the personality index NEO Five Factor Inventory - 3 survey (a self-report inventory that measured the five domains of personality) and a research-developed demographic questionnaire. Data were collected electronically through the Survey Monkey website. Findings of the study indicated that a statistically significant relationship between the five factor model personality traits alone or in combination with one another and rank of female law enforcement officers was not found. Although the results of the study were not statistically significant, the study results determined that the personality traits of both ranking and nonranking female officers were similar. The results of this study will influence social change by providing a different perspective on influencing factors in rank advancement of female law enforcement officers.

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21

Xia, Tian. "Learning to Rank Algorithms and Their Application in Machine Translation." Wright State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=wright1451610555.

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22

Biradar, Rakesh. "Analysis and Prediction of Community Structure Using Unsupervised Learning." Digital WPI, 2016. https://digitalcommons.wpi.edu/etd-theses/138.

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In this thesis, we perform analysis and prediction for community structures in graphs using unsupervised learning. The methods we use require the data matrices to be of low rank, and such matrices appear quite often in real world problems across a broad range of domains. Such a modelling assumption is widely considered by classical algorithms such as principal component analysis (PCA), and the same assumption is often used to achieve dimensionality reduction. Dimension reduction, which is a classic method in unsupervised learning, can be leveraged in a wide array of problems, including prediction of strength of connection between communities from unlabeled or partially labeled data. Accordingly, a low rank assumption addresses many real world problems, and a low rank assumption has been used in this thesis to predict the strength of connection between communities in Amazon product data. In particular, we have analyzed real world data across retail and cyber domains, with the focus being on the retail domain. Herein, our focus is on analyzing the strength of connection between the communities in Amazon product data, where each community represents a group of products, and we are given the strength of connection between the individual products but not between the product communities. We call the strength of connection between individual products first order data and the strength of connection between communities second order data. This usage is inspired by [1] where first order time series are used to compute second order covariance matrices where such covariance matrices encode the strength of connection between the time series. In order to find the strength of connection between the communities, we define various metrics to measure this strength, and one of the goals of this thesis is to choose a good metric, which supports effective predictions. However, the main objective is to predict the strength of connection between most of the communities, given measurements of the strength of connection between only a few communities. To address this challenge, we use modern extensions of PCA such as eRPCA that can provide better predictions and can be computationally efficient for large problems. However, the current theory of eRPCA algorithms is not designed to treat problems where the initial data (such as the second order matrix of communities strength) is both low rank and sparse. Therefore, we analyze the performance of eRPCA algorithm on such data and modify our approaches for the particular structure of Amazon product communities to perform the necessary predictions.

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23

Twagirumukiza, Etienne. "Analysis of Faculty Evaluation by Students as a Reliable Measure of Faculty Teaching Performance." Digital Archive @ GSU, 2011. http://digitalarchive.gsu.edu/math_theses/105.

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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.

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24

Wang, Hao, and 王皓. "Advanced rank-aware queries and recommendation with novel types of data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/206672.

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Nowadays we are living in an era of rich data, not only in the sense of the amount of data, but also in the sense of various sources and content of data. Efficient search, management, and exploitation of data have, over decades, been a major direction of database research. In this thesis, three challenging problems are proposed and studied, targeting (i) time series data, (ii) user preference data, and (iii) location-based social network data, respectively, providing efficient solutions to corresponding real-life applications. First, durability queries are studied in historical time series databases, which identify objects that have durable quality over time. For example, a sociologist may be interested in the top 10 web search terms during the period of some historical events; the police may seek for vehicles that move close to a suspect 70% of the time during a certain time, etc. Such durable top-k (DTop-k) and durable k-nearest neighbor (DkNN) queries can be viewed as natural extensions of the standard snapshot top-k and NN queries to timestamped sequences of values or locations. Although their snapshot counterparts have been studied extensively, there is little prior work that addresses this new class of durability queries. Efficient and scalable algorithms are proposed based on novel indexing techniques. Next, an efficient solution to k-nearest neighbor search over top-m lists is investigated. A top-m list is a ranking of m items, typically representing some user’s preference over these items. For example, a user may have a list of her 10 most favourite books; the result from a search engine is typically a list of webpages ranked according to their relevance to some keywords. The search problem aims at extracting k top-m lists from the database that are the “closest” to some query list where the closeness is evaluated using commonly used measures such as the Fagin’s intersection metric, Spearman’s footrule, Kendall’s tau, etc. Despite of the importance of such queries, there’s little prior work suggesting any efficient solution. In this thesis, a unified framework is proposed to answer such queries efficiently. Finally, the problem of top-N venue recommendation in location-based social networks (LBSNs) is studied, which recommends new venues to users. As an increasingly larger number of users partake in LBSNs, the recommendation problem in this setting has attracted significant attention in research and in practical applications. The detailed information about past user behavior that is traced by the LBSN differentiates the problem significantly from its traditional settings. The spatial nature in the past user behavior and also the information about the user social interaction with other users, provide a richer background to build a more accurate and expressive recommendation model. Although there have been extensive studies on recommender systems working with user-item ratings, GPS trajectories, and other types of data, there are very few approaches that exploit the unique properties of the LBSN user check-in data. In this thesis, effective and efficient algorithms that create recommendations are proposed based on such properties.
published_or_final_version
Computer Science
Doctoral
Doctor of Philosophy

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25

Bakshi, Vivek. "Application of Inter-Die Rank Statistics in Defect Detection." PDXScholar, 2012. https://pdxscholar.library.pdx.edu/open_access_etds/90.

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This thesis presents a statistical method to identify the test escapes. Test often acquires parametric measurements as a function of logical state of a chip. The usual method of classifying chips as pass or fail is to compare each state measurement to a test limit. Subtle manufacturing defects are escaping the test limits due to process variations in deep sub-micron technologies which results in mixing of healthy and faulty parametric test measurements. This thesis identifies the chips with subtle defects by using rank order of the parametric measurements. A hypothesis is developed that a defect is likely to disturb the defect-free ranking, whereas a shift caused by process variations will not affect the rank. The hypothesis does not depend on a-priori knowledge of a defect-free ranking of parametric measurements. This thesis introduces a modified Estimation Maximization (EM) algorithm to separate the healthy and faulty tau components calculated from parametric responses of die pairs on a wafer. The modified EM uses generalized beta distributions to model the two components of tau mixture distribution. The modified EM estimates the faulty probability of each die on a wafer. The sensitivity of the modified EM is evaluated using Monte Carlo simulations. The modified EM is applied on production product A. An average 30% reduction in DPPM (defective parts per million) is observed in Product A across all lots.

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26

Schwind, David A. "A qualitative analysis of selection to flag rank in the United States Navy." Thesis, access online version, 2004. http://theses.nps.navy.mil/04Jun%5FSchwind.pdf.

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27

Almeida-Silva, Lina Maria. "Cladistic analysis of Macrobunidae Petrunkevitch, 1928 new rank and revision of Macrobuninae (Araneae)." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/41/41133/tde-20032014-094350/.

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Macrobuninae Petrunkevitch is revised and submitted to a cladistic analysis. Macrobuninae, once considered the biggest Amaurobiidae Thorell subfamily is now proved to be not even closely related to Amaurobiinae, the \"true amaurobiids\". Our matrix, composed by 82 terminal taxa and 107 characters, includes representatives of all Macrobuninae genera and new taxa we believed to be part of Macrobuninae. As out-groups, we included representatives of the families Agelenidae Koch, Amaurobiidae, Amphinectidae Forster & Wilton, Chummidae Jocqué, Desidae Pocock, Dictynidae O. P.-Cambridge, Phyxelididae Lehtinen, Stiphidiidae Dalmas, Tengellidae Dahl, Titanoecidae Lehtinen, Zorocratidae Dahl and Zoropsidae Bertkau, which were suggested as related to Macrobuninae by previous studies. Our main results confirm Macrobuninae as not forming a monophyletic group with Amaurobiidae and shows the need to erect Macrobunidae Petrunkevitch, 1928 new rank to include Macrobuninae and relatives. Three other subfamilies are proposed here: Retirinae subfam. nov., Pakehinae subfam. nov., and Zanomyinae Ubick, 2005 new rank. Chummidae, currently composed by one genus and two species, is considered a junior-synonym with Macrobunidae. Amaurobiidae appears as sister group of the \"Oval Calamistrum Clade\" and the \"Fused Paracribellar clade\". The subfamily Macrobuninae is revised at the generic-level and redelimited to include a total of 26 genera. Of those, thirteen are newly described: Siyabonga gen. nov., Peckmaria gen. nov., Ijoubetumsam gen. nov., Imbumbulu gen. nov., Ibhulashi gen. nov., Umunwe gen. nov., Pigozzoi gen. nov., Samadhia gen. nov., Naynay gen. nov., Segoko gen. nov., Deusemais gen. nov., Madiba gen. nov. and Ushaka gen nov.. The remaining known genera are redescribed including their type-species, except the ones with recent, up to date descriptions. Seventeen new species are described: Emmenomma joshuabelli sp. nov., Macrobunus alejandrosanzi, sp. nov., Macrobunus eniomattosi sp. nov., Yupanquia lenktaitisi sp. nov., Ijoubetumsam frizzellae sp. nov., Deusemais viximaria sp. nov., Naynay meikleae sp. nov., Pigozzoi pifozonho sp. nov., Samadhia kellyfujiharae sp. nov., Siyabonga kakhulu sp. nov., Imbumbulu westhuizenis sp. nov., Madiba haddadi sp. nov., Ushaka umsila sp. nov., Ushaka philai sp. nov., Ibhulashi lakeside sp. nov., Umunwe ndabae sp. nov. and Segoko chueneorum sp. nov. Eight genera removed from Macrobuninae are assigned to other subfamilies and/or families. All taxonomic changes are justified by the phylogenetic analysis. For the first time the male specimens of Hicanodon Tullgren, Yupanquia Lehtinen and Chresiona Simon are described; Anisacate fuegianum bransfield Usher is raised to the species level, A. bransfield Usher new rank; Emmenomma beauchenicum Usher is considered junior synonym of E. oculatum Simon; Emmenomma oculatum obscurum Simon is removed from the synonym with E. oculatum and raised to the species level, Emmenomma obscurum Simon new rank. The type specimens of Macrobunus backhauseni (Simon) are considered non co-specifics and a new species Macrobunus alejandrosanzi sp. nov. is described based on the female. The true female of M. backhauseni is described for the first time. Other taxonomic changes include: removal of Notolathys Mello-Leitão from synonymy with Auximella Strand and placement as a junior synonym of Retiro Mello-Leitão; to consider Urepus Roth a junior synonym of Auximella; and Tymbira Mello-Leitão a junior synonym of Metaltella Mello-Leitão
Macrobuninae é alvo de uma revisão e análise cladística. Esta subfamília, que já foi considerada a maior de Amaurobiidae, mostra-se pouco relacionada aos Amaurobiinae ou \"amaurobiideos verdadeiros\". A matriz deste estudo, composta por 82 taxa terminais e 107 caracteres inclui representantes de todos os gêneros de Macrobuninae e novos taxa desta subfamília. Como grupo-externo, foram utilizados representantes de: Agelenidae Koch, Amaurobiidae, Amphinectidae Forster & Wilton, Chummidae Jocqué, Desidae Pocock, Dictynidae O. P.-Cambridge, Phyxelididae Lehtinen, Stiphidiidae Dalmas, Tengellidae Dahl, Titanoecidae Lehtinen, Zorocratidae Dahl e Zoropsidae Bertkau, uma vez que estas famílias foram relacionadas a Macrobuninae em outros estudos. Os resultados principais confirmam que Macrobuninae não está intimamente relacionada a Amaurobiidae e confirma a necessidade de elevar Macrobuninae à categoria de família, Macrobunidae Petrunckevitch, 1928 status nov. a fim de incluir os Macrobuninae e generos relacionados. Três subfamílias aqui descritas: Retirinae subfam. nov., Pakehinae subfam. nov., and Zanomyinae Ubick, 2005 status nov.. Chummidae Jocqué, atualmente composta por um gênero e duas espécies, passa a ser considerada sinônimo-junior de Macrobunidae. Amaurobiidae aparece como grupo-irmão dos clados \"paracribellares fundidas\" e calamistro oval. A subfamília Macrobuninae é revisada em nível genérico e redelimitada a fim de incluir um total de 26 gêneros. Destes, treze gêneros novos são descritos: Siyabonga gen . nov., Peckmaria gen. nov., Ijoubetumsam gen. nov., Imbumbulu gen. nov., Ibhulashi gen. nov., Umunwe gen. nov., Pigozzoi gen. nov., Samadhia gen. nov., Naynay gen. nov., Segoko gen. nov., Deusemais gen. nov., Madiba gen. nov. and Ushaka gen nov.. Dos treze gêneros conhecidos, apenas os que possuem descriçoões recentes e atualizadas não tiveram suas espécies-tipo redescritas. Dezessete espécies novas são descritas: Emmenomma joshuabelli sp. nov., Macrobunus alejandrosanzi, sp. nov., Macrobunus eniomattosi sp. nov., Yupanquia lenktaitisi sp. nov., Ijoubetumsam frizzellae sp. nov., Deusemais viximaria sp. nov., Naynay meikleae sp. nov., Pigozzoi pifozonho sp. nov., Samadhia kellyfujiharae sp. nov., Siyabonga kakhulu sp. nov., Imbumbulu westhuizenis sp. nov., Madiba haddadi sp. nov., Ushaka umsila sp. nov., Ushaka philai sp. nov., Ibhulashi lakeside sp. nov., Umunwe ndabae sp. nov. e Segoko chueneorum sp. nov.. Oito gêneros são removidos de Macrobuninae e transferidos para outras subfamílias e/ou famílias. As mudanças taxonômicas apresentadas são corroboradas pela análise cladística. São apresentadas as primeiras descrições de machos de espécies de Hicanodon Tullgren, Yupanquia Lehtinen e Chresiona Simon. Anisacate fuegianum bransfield Usher é elevada a categoria de espécie, A. bransfield Usher stat. nov.. Emmenomma beauchenicum Usher é considerada sinônimo junior de E. oculatum. Emmenomma oculatum obscurum Simon é removida da sinonímia e elevada a categoria de espécie, Emmenomma obscurum Simon stat. nov.. Os espécimes-tipo de M. backhauseni são aqui considerados duas espécies diferentes e com base na fêmea uma espécie nova M. alejandrosanzi sp. nov. é descrita. A verdadeira fêmea de M. backhauseni (Simon) é descrita pela primeira vez. Outras mudanças taxonômicas proveniente do estudo dos espécimes-tipo incluem remover Notolathys Mello-Leitão da sinonímia com Auximella Strand e transferir Notolathys para sinônimo-junior de Retiro Mello-Leitão; sinonimizar Urepus Roth e Auximella; considerar Tymbira Mello-Leitão sinônimo-junior de Metaltella Mello-Leitão

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28

Cai, Jinlu. "Coex-rank: an approach for microarray combined analysis - applications to PPARγ related datasets". Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/649.

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Microarrays have been widely used to study differential gene expression at the genomic level. They can also provide genome-wide co-expression information. Robust approaches are needed for integration and validation of independently-collected datasets which may contribute to a common hypothesis. Previously, attempts at meta-analysis have contributed to solutions to this problem. As an alternative, for microarray data from multiple highly similar biological experimental designs, a more direct combined approach is possible. In this thesis, a novel approach is described for microarray combined analysis, including gene-level unification into a virtual platform followed by normalization and a method for ranking candidate genes based on co-expression information - called Coex-Rank. We applied this approach to our Sppar (a PPARγ mutant) dataset, which illustrated an improvement in statistical power and a complementary advantage of the Coex-Rank method from a biological perspective. We also performed analysis to other PPARγ-related microarray datasets. From the perspective of gene sets, we observed that up-regulated genes from mice treated with the PPARγ ligand rosiglitazone were significantly down-regulated in mice with a global knock-in dominant-negative mutation of PPARγ. Integrated with publicly available PPRE (PPAR Response Element) datasets, we found that the genes which were most up-regulated by rosiglitazone treatment and which were also down-regulated by the global knock-in mutation of PPARγ were robustly enriched in PPREs near transcription start sites. In addition, we identified several potential PPARγ targets in the aorta and mesenteric artery for further experimental validation, such as Rhobtb1 and Rgs5.

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29

Gao, Xin. "Rank tests for interaction in two-way layouts with application in genetic analysis." Thesis, University of Ottawa (Canada), 2003. http://hdl.handle.net/10393/29015.

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To fully dissect complex traits, it is desirable to have methods able to test gene-gene interaction for human genetic data. This thesis provides a framework to process human quantitative trait data such that the problem becomes a hypothesis test of interaction for a two-way layout design with unequal replicates. Three new nonparametric rank tests are proposed. Their limiting distributions under Pitman alternatives and asymptotic relative efficiencies are studied. The tests are extended to unbalanced designs. We also introduce the notion of composite linear rank statistics and prove asymptotic normality under mild conditions. Consistent estimators are provided for the limiting variance-covariance matrix of arbitrary linear rank statistics.

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30

Dutra, Junior Elmário Gomes. "Um modelo de fusão de rankings baseado em análise de preferência." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2008. http://hdl.handle.net/10183/15890.

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O crescente volume de informações disponíveis na rede mundial de computadores, gera a necessidade do uso de ferramentas que sejam capazes de localizá-las e ordenálas, de forma cada vez mais precisa e que demandem cada vez menos recursos computacionais. Esta necessidade tem motivado pesquisadores a estudar e desenvolver modelos e técnicas que atendam esta demanda. Estudos recentes têm sinalizado que utilizar vários ordenamentos (rankings) previamente montados possibilita o retorno e ordenação de objetos de qualquer natureza com mais eficiência, principalmente pelo fato de haver uma redução no custo da busca pela informação. Este processo, conhecido como fusão de rankings, permite que se obtenha um ordenamento com base na opinião de diversos juízes (critérios), o que possibilita considerar um grande número de fontes, tanto geradas automaticamente como por especialistas. Entretanto os modelos propostos até então tem apresentado várias limitações na sua aplicação: desde a quantidade de rankings envolvidos até, principalmente, a utilização de rankings parciais. A proposta desta dissertação é apresentar um modelo de fusão de rankings que busca estabelecer um consenso entre as opiniões (rankings) dos diferentes juízes envolvidos, considerando distintos graus de relevância ou importância entre eles. A base desta proposta está na Análise de Preferência, um conjunto de técnicas que permite o tratamento da multidimensionalidade dos dados envolvidos. Ao ser testado em uma aplicação real, o modelo mostrou conseguir suprir algumas limitações apresentadas em outras abordagens, bem como apresentou resultados similares aos das aplicações originais. Esta pesquisa, ainda contribui, com a especificação de um sistema Web baseado em tecnologias open source, o qual permite que qualquer pessoa possa realizar a fusão de rankings.
The growing volume of available information on the web creates the need to use tools that are capable of retrieve and ordering this information, ever more precise and using less computer resources. This need has motivated researchers to study and develop models and techniques that solve this problem. Recent studies have indicated that use multiple rankings previously mounted makes possible the return and sorting of the objects of any kind with more efficiency, mainly because there is a reduction in the cost of searching for information. This process, called ranking fusion, provide a ranking based on the opinion of several judges (criteria), considering a large number of sources, both generated automatically and also by specialists. However the proposed models have shown severe limitations in its application: from the amount involved rankings to the use of partial rankings. The proposal of this dissertation is to show a model of ranking fusion that seeks to establish a consensus between the judgement (rankings) of the various judges involved, considering different degrees of relevance or importance among them. The baseline of this proposal is the Preference Analysis, a set of techniques that allows the treatment of multidimensional data handling. During tests in a real application, the model supplied some limitations presented by other approaches, and presented results similar to the original applications. Additionally, this research contributes with the specification of a web system based on open-sources technologies, enabling the realization of fusion rankings by anyone.

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31

Alsehaimi, Afnan Abdulrahman A. "Sentiment Analysis for E-book Reviews on Amazon to Determine E-book Impact Rank." University of Dayton / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1619109972210567.

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32

Öhman, Marie-Louise. "Aspects of analysis of small-sample right censored data using generalized Wilcoxon rank tests." Doctoral thesis, Umeå universitet, Statistiska institutionen, 1994. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-7313.

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The estimated bias and variance of commonly applied and jackknife variance estimators and observed significance level and power of standardised generalized Wilcoxon linear rank sum test statistics and tests, respectively, of Gehan and Prentice are compared in a Monte Carlo simulation study. The variance estimators are the permutational-, the conditional permutational- and the jackknife variance estimators of the test statistic of Gehan, and the asymptotic- and the jackknife variance estimators of the test statistic of Prentice. In unbalanced small sample size problems with right censoring, the commonly applied variance estimators for the generalized Wilcoxon rank test statistics of Gehan and Prentice may be biased. In the simulation study it appears that variance properties and observed level and power may be improved by using the jackknife variance estimator. To establish the sensitivity to gross errors and misclassifications for standardised generalized Wilcoxon linear rank sum statistics in small samples with right censoring, the sensitivity curves of Tukey are used. For a certain combined sample, which might contain gross errors, a relatively simple method is needed to establish the applicability of the inference drawn from the selected rank test. One way is to use the change of decision point, which in this thesis is defined as the smallest proportion of altered positions resulting in an opposite decision. When little is known about the shape of a distribution function, non-parametric estimates for the location parameter are found by making use of censored one-sample- and two-sample rank statistics. Methods for constructing censored small sample confidence intervals and asymptotic confidence intervals for a location parameter are also considered. Generalisations of the solutions from uncensored one-sample and two-sample rank tests are utilised. A Monte-Carlo simulation study indicates that rank estimators may have smaller absolute estimated bias and smaller estimated mean squared error than a location estimator derived from the Product-Limit estimator of the survival distribution function. The ideas described and discussed are illustrated with data from a clinical trial of Head and Neck cancer.
digitalisering@umu

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33

Öhman, Marie-Louise. "Aspects of analysis of small sample right censored data using generalized Wilcoxon rank tests /." Umeå : Univ, 1994. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=006873072&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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34

Arnroth, Lukas. "Speeding up PARAFAC : Approximation of tensor rank using the Tucker core." Thesis, Uppsala universitet, Statistiska institutionen, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-353287.

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In this paper, the approach of utilizing the core tensor from the Tucker decomposition, in place of theuncompressed tensor, for nding a valid tensor rank for the PARAFAC decomposition is considered.Validity of the proposed method is investigated in terms of error and time consumption. As thesolutions of the PARAFAC decomposition are unique, stability of the solutions through split-halfanalysis is investigated. Simulated and real data are considered. Although, no general validity ofthe method could be observed, the results for some datasets look promising with 10% compressionin all modes. It is also shown that increased compression does not necessarily imply less timeconsumption.

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35

Arnalds, Holmfridur Osk. "Correspondence between Multiple-Respondent Anecdotal Assessments and Functional Analysis: Analyses of Rank-Order, Magnitude-of-Difference, and Overall Outcomes." Thesis, University of North Texas, 2016. https://digital.library.unt.edu/ark:/67531/metadc849776/.

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We administered the Motivation Assessment Scale (MAS) and the Questions About Behavioral Function (QABF) to five raters and compared the results with functional analysis outcomes for 12 cases in which agreement was obtained for at least four out of five raters on either anecdotal assessment. The scores for functional categories on the MAS and QABF were ranked by averaging the scores for the raters who agreed on the primary maintaining variable. Functional analysis results were ranked by examining average responding across all conditions. A comparison showed correspondence between the highest category and the highest functional analysis condition for 10 out of 11 cases for the MAS and all 10 cases for the QABF. Correspondence for the category and condition ranked second was found for 2 out of 11 cases for the MAS and 2 out of 10 cases for the QABF. The magnitude of difference between categories on the MAS/QABF did not appear to predict the amount of difference in responding in the corresponding functional analyses.

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36

Sanderson, Bryant. "Applying SERF Analysis to Rank Procurement Strategies for a North Dakota Green Field Pea Processor." Thesis, North Dakota State University, 2014. https://hdl.handle.net/10365/27424.

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There are many crops grown in North Dakota, but only a few have a futures market for prices and are grown readily throughout the country. The specialty crops in North Dakota display many of the same characteristics such as a lack of a futures market, high standards for grain quality, and concentrated production areas. These characteristics create unique procurement risks for specialty crop processors. This project ranks procurement strategies for a green field pea processor located in North Dakota using stochastic efficiency with respect to a function (SERF) analysis. Through SERF analysis, it was found that geographic diversification and forward contracting are useful tactics to include in a green field pea processors procurement strategies. The methodology and model can be applied to other specialty crops in North Dakota that display similar risk characteristics seen in green field peas such as lentils, dry edible beans, and malt barley.

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37

Grande, García Eduardo [Verfasser], Ernst [Akademischer Betreuer] Rank, and Rainer H. H. [Akademischer Betreuer] Burgkart. "Double Experimental Procedure for Model-Specific Finite Element Analysis of the Human Femur and Trabecular Bone / Eduardo Grande García. Gutachter: Ernst Rank ; Rainer H. H. Burgkart. Betreuer: Ernst Rank." München : Universitätsbibliothek der TU München, 2013. http://d-nb.info/1034420739/34.

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38

Alankus, Yasemin Begüm [Verfasser], and Heinrich [Akademischer Betreuer] Leonhardt. "Analysis of enforced RANK signaling in B cells in vivo / Yasemin Begüm Alankus ; Betreuer: Heinrich Leonhardt." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2017. http://d-nb.info/1191692213/34.

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39

Weld, Christopher. "Computational Graphics and Statistical Analysis: Mixed Type Random Variables, Confidence Regions, and Golden Quantile Rank Sets." W&M ScholarWorks, 2019. https://scholarworks.wm.edu/etd/1563898977.

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This dissertation has three principle areas of research: mixed type random variables, confidence regions, and golden quantile rank sets. While each offers a specific focus, some common themes persist; broadly stated, there are three. First, computational graphics play a critical role. Second, software development facilitates implementation and accessibility. Third, statistical analysis---often attributable to the aforementioned automation---provides valuable insights and applications. Each of the principle research areas are briefly summarized next. Mixed type random variables are a hybrid of continuous and discrete random variables, having components of both continuous probability density and discrete probability mass. This dissertation illustrates the challenges inherent in plotting mixed type distributions, and introduces an algorithm that addresses those issues. It considers sums and products of mixed type random variables, and supports its conclusions using Monte Carlo simulation experiments. Lastly, it introduces MixedAPPL, a computer algebra system software package designed for manipulating mixed type random variables. Confidence regions are a multi-dimensional version of a confidence interval. They are helpful to visualize and quantify uncertainty surrounding a point estimate. We begin by developing efficient plot algorithms for two-dimensional confidence regions. This research focuses specifically on likelihood-ratio based confidence regions for two-parameter univariate probability models, although the plot techniques are transferable to any two-dimensional setting. The R package 'conf' is introduced, which automates these confidence region plot algorithms for complete and right-censored data sets. Among its benefits, 'conf' provides access to Monte Carlo simulation experiments for confidence region coverage to an extent not possible previously. The corresponding coverage analysis results include reference tables for the Weibull, normal, and log-logistic distributions. These reference tables yield confidence region plots with exact coverage. The final topic is the introduction and analysis of a golden quantile rank set (GQRS). The term quantile rank set is used here to denote the population cumulative distribution function values corresponding to a sample. A GQRS can be thought of as "perfectly" representative of their population distribution because samples corresponding to a GQRS result in an estimator(s) matching the associated true population parameter(s). This unique characteristic is not applicable for all estimators and/or distributions, but when present, provides valuable insights and applications. Specifically, applications include an alternative (and at times computationally superior) method for parameter estimation and an exact actual coverage methodology for confidence regions (at times in which currently only estimates exist). Distributions with a GQRS associated with maximum likelihood estimation include the normal, exponential, Weibull, log logistic, and one-parameter exponential power distributions.

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40

Palzer, Wolfgang [Verfasser], Alexander [Akademischer Betreuer] Alldridge, and George [Akademischer Betreuer] Marinescu. "Fourier Analysis on Non-Compact Symmetric Superspaces of Rank One / Wolfgang Palzer. Gutachter: Alexander Alldridge ; George Marinescu." Köln : Universitäts- und Stadtbibliothek Köln, 2014. http://d-nb.info/1051088070/34.

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41

Bandeira, Luís Miguel Zorro. "Analysis of new situations for quasiconvexity versus rank-one convexity in 2 x 2 and other dimensions." Doctoral thesis, Universidade de Évora, 2008. http://hdl.handle.net/10174/11119.

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It is well-known that quasiconvexity is a fundamental concept for vector problems in the Calculus of Variations. Its main necessary condition is rankone convexity. Still today it is not known whether it is also sufficient or not, when the target space of deformations is m=2 (in the general case). We introduce a method to find, in a systematic way, rank-one convex polynomials. We show how it works in several examples. It can also be applied to convexity along general cones. An alternative proof is provided for the well-known quadratic case of quasiconvexity, which does not use the Plancherel formula. An application to the case of 4th degree homogeneous polynomials is shown. We also explore an attempt to disprove the implication, from rank-one convexity to quasiconvexity for 2x2 symmetric matrices, using the viewpoint of laminates and homogeneous gradient Young measures. /RESUMO - É bem conhecido que a quasiconvexidade é um conceito fundamental para problemas vectoriais do Cálculo das Variações. A sua principal condição necessária é a convexidade característica-l. Ainda hoje não é conhecido se é ou não suficiente, quando o espaço alvo das deformações é m=2 (no caso geral). Introduzimos um método para determinar, de uma forma sistemática, polinómios convexos característica-1. Mostramos como funciona em diversos exemplos. Pode também ser aplicado à convexidade ao longo de cones gerais. Providenciamos uma demonstração alternativa para o bem conhecido caso quadrático da quasiconvexidade, que não utiliza a fórmula de Plancherel. Apresentamos uma aplicação para o caso dos polinómios homogéneos de grau 4. Exploramos também uma tentativa para refutar a implicação da convex-idade característica-1 para a quasiconvexidade nas matrizes 2x2 simétricas, sob o ponto de vista dos laminados e das medidas de Young gradiente homogéneas.

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42

Vamvuka, Despina. "Thermogravimetric analysis studies of low rank coals and modelling of combustion and gasification processes in entrained systems." Thesis, University of Manchester, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.363216.

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Thermogravimetric analysis studies were performed on three low rank coals and a lignite (average size 41um), as well as the dense media separated fractions of these in nitrogen and air. All experiments were carried out at 20°C/min and over the temperature range of 25 to 850°C. Such studies have been used to examine the effect of the different minerology of the coals upon the devolatilization and combustion processes, to investigate the effect of mineral matter on coal reactivity, and to provide data for mathematical models of pulverized coal combustion and gasification in entrained systems. The first-order kinetic model, used to characterise the devolatilization and combustion processes, seemed to correlate the experimental data reasonably well. The activation energy values corresponding to devolatilization, and ranging from 22 to 38 KJ/mole, were similar for all coals, while those corresponding to combustion of the devolatilized coal varied between 41 and 96 KJ/mole and were significantly higher. The presence of the mineral matter slightly increased the reactivity of the coals in nitrogen, whereas it affected greatly the temperature sensitivity of the reaction in air, A mathematical model, incorporating thermogravimetric analysis data of Whitwick coal, was developed in order to predict the burning history of a single entrained coal particle, and to study the effect of ambient gas temperature and boundarylayer thickness on the final conversion, This model included a set of ordinary differential equations, describing the reaction rates and the mass and heat transport processes, as well as a partial differential equation, for computing the temperature profile within the particle. The system of equations was solved numerically, The location of the reaction zone on the solid surface, where gas-phase and heterogeneous combustion could occur simultaneously, appeared to describe successfully the combustion mechanism of the particle. The combustion process was chemical reaction rate controlled. The particle behaved essentially isothermally and its lifetime was estimated to be approximately 1.23s. A higher ambient gas temperature or boundary-layer thickness resulted in shorter burn-out times. Finally, a one-dimensional, steady-state model, for an entrained flow coal gasifier, was developed, by using combustion data from thermogravimetric analysis of Whitwick coal. The model was based on mass and energy balances, heterogeneous reaction rates and homogeneous gas-phase equilibrium. The resulting set of nonlinear mixed ordinary differential-implicit algebraic equations was solved numerically, by using modified Euler's method in conjunction with a nonlinear algebraic equation solver. Parametric studies were made, in order to provide a better understanding of the reactor performance, in terms of coal conversion, product gas composition and temperature profiles along the reactor, under various operating conditions, such as feed flow rates and gasifier pressure. High conversion of carbon could be predicted only if the devolatilization reaction proceeded in parallel with the heterogeneous reaction at the coal surface, with oxygen and steam. The model suggested that a two-stage gasification with precombustion, followed by reaction with steam would be possible. The critical parameters in gasification were the steam-to-coal and oxygen-to-coal feed ratios. Data is presented showing their effect on total conversion, synthesis gas composition and calorific value, as a function of reactor pressure. No experimental data for the verification of the simulation was performed, but comparison of the results with those of previous investigations showed consistency.

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43

Jiang, Boyi. "GIS-based Multi-criteriaAnalysis Used in Forest Fire Estimation: A Case Study of Northernmost Gävleborg County in Sweden." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-9626.

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Fire plays an important role in forest ecosystem management depending on the dual character of it. It should be managed and supervised effectively. In this particular study, the study area was located in the north part of Gävleborg County in Sweden, which is in a high- latitude region. Seven factors, divided into natural factors and human caused factors, were extracted from digital elevation model (DEM), classified land use map and feature shape files provided by National Land Survey of Sweden (Lantmäteriet). Two different weighting schemes for the factors were determined by the Analytic Hierarchy Process (AHP) method. With the help of ArcGIS 9.3 and Erdas 9.3, two classified result maps were obtained, where forest fire risk ranks were shown as five classes, very low, low, moderate, high and very high. The 43 fire incidents in the year 2007 and 2008 recorded by Global Fire Management System were used to evaluate the results. The results show that the higher rank the region is, the larger is the probability for forest fire risk and higher the risk to spread the fire. Furthermore, according to the occurrence time of the fire incidents, the period of time from end of May to beginning of June was generalized as a dangerous period for forest fire risk in this study area. After analyzing and discussing, even if there might be some uncertainties caused by variable selection, resolution problem and weighting schemes, the results were generally reliable.

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44

Bailey, Thomas M. "Analysis of firm desirability among Virginia's economic development directors." Thesis, This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-11182008-063259/.

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45

Ataman, Kaan. "Learning to rank by maximizing the AUC with linear programming for problems with binary output." Diss., University of Iowa, 2007. http://ir.uiowa.edu/etd/151.

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Johnson, Nikeisha Sewell. "A Phenomenological Analysis of Military Personnel's Experiences of Toxic Leadership." ScholarWorks, 2018. https://scholarworks.waldenu.edu/dissertations/5881.

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The existing quantitative literature on toxic leadership in the military has primarily explored negative outcomes, gendered military experience, and toxic leadership separately; however, relatively few studies have included all 3. The unidentified connection was critical in determining how toxic leadership varied and left a gap for further research to be conducted from a qualitative, phenomenological perspective. Therefore, this study addressed the manner in which encounters with toxic leadership differed across gender and military rank according to those experiencing it. Using a convenience sampling method, data were gathered through semi structured interviews with 12 Army veterans. Thematic analysis of the data revealed 63 meaningful statements and 3 emergent themes. Results affirmed that for both men and women, the higher the rank the more exposure to toxic leadership they encountered. Results also introduced race as a key factor for both genders because it was reported as the leading cause of participants' toxic encounters across rank and gender. The findings of this study also suggested that females were more susceptible to negative mental health outcomes after toxic leadership exposure versus their male counterparts. The results of this study contribute to positive social change by providing a thorough understanding of the qualities characteristic of experiences with toxic leadership to clarify the specific ways in which toxic leadership leads to negative outcomes. Results from this study will be useful for practitioners, military officials, and researchers seeking to better understand the leadership needs of contemporary military personnel.

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47

Shen, Chuen, and 沈川. "A survey analysis of working and shirking of the other rank members ofthe Hong Kong Fire Services Department." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B46776217.

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Schwedler, Michael Verfasser], Carsten [Akademischer Betreuer] [Könke, Ernst [Gutachter] Rank, and Karl [Gutachter] Beucke. "Integrated structural analysis using isogeometric finite element methods / Michael Schwedler ; Gutachter: Ernst Rank, Karl Beucke ; Betreuer: Carsten Könke." Weimar : Institut für Strukturmechanik, 2017. http://d-nb.info/1125372494/34.

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Schwedler, Michael [Verfasser], Carsten [Akademischer Betreuer] Könke, Ernst [Gutachter] Rank, and Karl [Gutachter] Beucke. "Integrated structural analysis using isogeometric finite element methods / Michael Schwedler ; Gutachter: Ernst Rank, Karl Beucke ; Betreuer: Carsten Könke." Weimar : Institut für Strukturmechanik, 2017. http://d-nb.info/1125372494/34.

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Sampath, Srinath. "Analysis of Agreement Between Two Long Ranked Lists." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1385415346.

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