Global ETD Search

11	Optimization of surge irrigation Ortel, Terry William. January 1986 (has links) Call number: LD2668 .T4 1986 O77 / Master of Science / Biological and Agricultural Engineering Masters theses
12	Preliminary investigation into estimating eye disease incidence rate from age specific prevalence data Majeke, Lunga January 2011 (has links) This study presents the methodology for estimating the incidence rate from the age specific prevalence data of three different eye diseases. We consider both situations where the mortality may differ from one person to another, with and without the disease. The method used was developed by Marvin J. Podgor for estimating incidence rate from prevalence data. It delves into the application of logistic regression to obtain the smoothed prevalence rates that helps in obtaining incidence rate. The study concluded that the use of logistic regression can produce a meaningful model, and the incidence rates of these diseases were not affected by the assumption of differential mortality. Eye -- Diseases -- Statistics Incidence functions Regression analysis -- Data processing Medical statistics
13	A Selective Polarity DC-DC Converter with Virtually Infinite Voltage Levels Liu, Kaiyang 29 July 2016 (has links) Indiana University-Purdue University Indianapolis (IUPUI) / This research introduces a new design of a converter modified from SEPIC converter (Single end primary inductive converter), capable of generating desired voltage levels and polarities. The new switching converter topology allows for boost and buck of the input voltage theoretically achieving infinite positive and negative voltage levels. The proposed topology utilizes single high frequency switch to perform the power conversion which simplifies the design of the gate driver, but meanwhile, it still retains the ability to provide a wide range of output voltage. Mathematical modeling of the converter and computer simulations are validated by experimental data. To verify its performance a prototype was designed and built. It is experimentally proven that the circuit can generate a desired voltage in the range of voltages up to ±170 V, delivering 480 Watts of power to a resistive load. High voltages -- Measurement Electric switchgear -- Research Power electronics
14	Model selection Hildebrand, Annelize 11 1900 (has links) In developing an understanding of real-world problems, researchers develop mathematical and statistical models. Various model selection methods exist which can be used to obtain a mathematical model that best describes the real-world situation in some or other sense. These methods aim to assess the merits of competing models by concentrating on a particular criterion. Each selection method is associated with its own criterion and is named accordingly. The better known ones include Akaike's Information Criterion, Mallows' Cp and cross-validation, to name a few. The value of the criterion is calculated for each model and the model corresponding to the minimum value of the criterion is then selected as the "best" model. / Mathematical Sciences / M. Sc. (Statistics) Model selection Discrepancy measures Criteria Akaike Information Criterion Mallows' Cp Cross-validation R-square Adjusted R-square Mean Square Error 519.5 Mallows' Cp Akaike Information Criterion Mathematical models -- Evaluation
15	Model selection Hildebrand, Annelize 11 1900 (has links) In developing an understanding of real-world problems, researchers develop mathematical and statistical models. Various model selection methods exist which can be used to obtain a mathematical model that best describes the real-world situation in some or other sense. These methods aim to assess the merits of competing models by concentrating on a particular criterion. Each selection method is associated with its own criterion and is named accordingly. The better known ones include Akaike's Information Criterion, Mallows' Cp and cross-validation, to name a few. The value of the criterion is calculated for each model and the model corresponding to the minimum value of the criterion is then selected as the "best" model. / Mathematical Sciences / M. Sc. (Statistics) Model selection Discrepancy measures Criteria Akaike Information Criterion Mallows' Cp Cross-validation R-square Adjusted R-square Mean Square Error 519.5 Mallows' Cp Akaike Information Criterion Mathematical models -- Evaluation
16	Single-index regression models Wu, Jingwei 05 1900 (has links) Indiana University-Purdue University Indianapolis (IUPUI) / Useful medical indices pose important roles in predicting medical outcomes. Medical indices, such as the well-known Body Mass Index (BMI), Charleson Comorbidity Index, etc., have been used extensively in research and clinical practice, for the quantification of risks in individual patients. However, the development of these indices is challenged; and primarily based on heuristic arguments. Statistically, most medical indices can be expressed as a function of a linear combination of individual variables and fitted by single-index model. Single-index model represents a way to retain latent nonlinear features of the data without the usual complications that come with increased dimensionality. In my dissertation, I propose a single-index model approach to analytically derive indices from observed data; the resulted index inherently correlates with specific health outcomes of interest. The first part of this dissertation discusses the derivation of an index function for the prediction of one outcome using longitudinal data. A cubic-spline estimation scheme for partially linear single-index mixed effect model is proposed to incorporate the within-subject correlations among outcome measures contributed by the same subject. A recursive algorithm based on the optimization of penalized least square estimation equation is derived and is shown to work well in both simulated data and derivation of a new body mass measure for the assessment of hypertension risk in children. The second part of this dissertation extends the single-index model to a multivariate setting. Specifically, a multivariate version of single-index model for longitudinal data is presented. An important feature of the proposed model is the accommodation of both correlations among multivariate outcomes and among the repeated measurements from the same subject via random effects that link the outcomes in a unified modeling structure. A new body mass index measure that simultaneously predicts systolic and diastolic blood pressure in children is illustrated. The final part of this dissertation shows existence, root-n strong consistency and asymptotic normality of the estimators in multivariate single-index model under suitable conditions. These asymptotic results are assessed in finite sample simulation and permit joint inference for all parameters. Asymptotics Longitudinal data analysis Mixed effect model Multivariate outcomes P-spline Errors-in-variables models Parameter estimation Mathematical statistics Biometry Multivariate analysis Diagnosis
17	Nitrous oxide emission from riparian buffers in agricultural landscapes of Indiana Fisher, Katelin Rose 25 February 2014 (has links) Indiana University-Purdue University Indianapolis (IUPUI) / Riparian buffers have well documented capacity to remove nitrate (NO3-) from runoff and subsurface flow paths, but information on field-scale N2O emission from these buffers is lacking. This study monitored N2O fluxes at two agricultural riparian buffers in the White River watershed (Indiana) from December 2009 to May 2011 to assess the impact of landscape and hydrogeomorphologic factors on emission. Soil chemical and biochemical properties were measured and environmental variables (soil temperature and moisture) were monitored in an attempt to identify key drivers of N2O emission. The study sites included a mature riparian forest (WR) and a riparian grass buffer (LWD); adjacent corn fields were also monitored for land-use comparison. With the exception of net N mineralization, most soil properties (particle size, bulk density, pH, denitrification potential, organic carbon, C:N) showed little correlation with N2O emission. Analysis of variance (ANOVA) identified season, land-use (riparian buffer vs. crop field), and site geomorphology as major drivers of N2O emission. At both study sites, N2O emission showed strong seasonal variability; the largest emission peaks in the riparian buffers (up to 1,300 % increase) and crop fields (up to 3,500 % increase) occurred in late spring/early summer as a result of flooding, elevated soil moisture and N-fertilization. Nitrous oxide emission was found to be significantly higher in crop fields than in riparian buffers at both LWD (mean: 1.72 and 0.18 mg N2O-N m-2 d-1) and WR (mean: 0.72 and 1.26 mg N2O-N m-2 d-1, respectively). Significant difference (p=0.02) in N2O emission between the riparian buffers was detected, and this effect was attributed to site geomorphology and the greater potential for flooding at the WR site (no flooding occurred at LWD). More than previously expected, the study results demonstrate that N2O emission in riparian buffers is largely driven by landscape geomorphology and land-stream connection (flood potential). Denitrification -- Research Biomineralization Analysis of variance -- Research
18	Advanced Modeling of Longitudinal Spectroscopy Data Kundu, Madan Gopal January 2014 (has links) Indiana University-Purdue University Indianapolis (IUPUI) / Magnetic resonance (MR) spectroscopy is a neuroimaging technique. It is widely used to quantify the concentration of important metabolites in a brain tissue. Imbalance in concentration of brain metabolites has been found to be associated with development of neurological impairment. There has been increasing trend of using MR spectroscopy as a diagnosis tool for neurological disorders. We established statistical methodology to analyze data obtained from the MR spectroscopy in the context of the HIV associated neurological disorder. First, we have developed novel methodology to study the association of marker of neurological disorder with MR spectrum from brain and how this association evolves with time. The entire problem fits into the framework of scalar-on-function regression model with individual spectrum being the functional predictor. We have extended one of the existing cross-sectional scalar-on-function regression techniques to longitudinal set-up. Advantage of proposed method includes: 1) ability to model flexible time-varying association between response and functional predictor and (2) ability to incorporate prior information. Second part of research attempts to study the influence of the clinical and demographic factors on the progression of brain metabolites over time. In order to understand the influence of these factors in fully non-parametric way, we proposed LongCART algorithm to construct regression tree with longitudinal data. Such a regression tree helps to identify smaller subpopulations (characterized by baseline factors) with differential longitudinal profile and hence helps us to identify influence of baseline factors. Advantage of LongCART algorithm includes: (1) it maintains of type-I error in determining best split, (2) substantially reduces computation time and (2) applicable even observations are taken at subject-specific time-points. Finally, we carried out an in-depth analysis of longitudinal changes in the brain metabolite concentrations in three brain regions, namely, white matter, gray matter and basal ganglia in chronically infected HIV patients enrolled in HIV Neuroimaging Consortium study. We studied the influence of important baseline factors (clinical and demographic) on these longitudinal profiles of brain metabolites using LongCART algorithm in order to identify subgroup of patients at higher risk of neurological impairment. / Partial research support was provided by the National Institutes of Health grants U01-MH083545, R01-CA126205 and U01-CA086368 Spectroscopy Functional Data Analysis Longitudinal Functional Data Analysis Brownian Bridge Longitudinal CART Longitudinal Regression Tree HIV Brain metabolites HIV neuroimaging consortium LongPEER PEER Decomposition based penalty NAA Creatine Myo-inositol Choline Glutamine and Glutamate White matter Gray matter Basal ganglia LongCART neurological disorder Global deficit score GSVD General Singular Value Decomposition Microbial metabolites -- Research HIV infections -- Complications Myelinated neurofibrils Research -- Methodology Trees (Graph theory) -- Research Biometry -- Research -- Methodology Cerebral cortex Central nervous system -- Abnormalities Spectrum analysis -- Research HIV (Viruses) -- Research -- Analysis Creatine Choline Glutamine
19	Spatio-temporal analyses of the distribution of alcohol outlets in California Li, Li January 2014 (has links) Indiana University-Purdue University Indianapolis (IUPUI) / The objective of this research is to examine the development of the California alcohol outlets over time and the relationship between neighborhood characteristics and densities of the alcohol outlets. Two types of advanced analyses were done after the usual preliminary description of data. Firstly, fixed and random effects linear regression were used for the county panel data across time (1945-2010) with a dummy variable added to capture the change in law regarding limitations on alcohol outlets density. Secondly, a Bayesian spatio-temporal Poisson regression of the census tract panel data was conducted to capture recent availability of population characteristics affecting outlet density. The spatial Conditional Autoregressive model was embedded in the Poisson regression to detect spatial dependency of unexplained variance of alcohol outlet density. The results show that the alcohol outlets density reduced under the limitation law over time. However, it was no more effective in reducing the growth of alcohol outlets after the limitation was modified to be more restrictive. Poorer, higher vacancy rate and lower percentage of Black neighborhoods tend to have higher alcohol outlet density (numbers of alcohol outlets to population ratio) for both on-sale general and off-sale general. Other characteristics like percentage of Hispanics, percentage of Asians, percentage of younger population and median income of adjacency neighbors were associated with densities of on-sale general and off sale general alcohol outlets. Some regions like the San Francisco Bay area and the Greater Los Angeles area have more alcohol outlets than the predictions of neighborhood characteristics included in the model. Liquor stores -- Location -- California Alcoholism and crime -- California Youth -- Alcohol use -- California

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