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- Title
- ASSOCIATIONS BETWEEN PRE-PREGNANCY WEIGHT STATUS AND/OR GESTATIONAL WEIGHT GAIN AND OBESITY IN OLDER CHILDREN.
- Creator
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Hammond, Marisa P, Quelly, Susan, University of Central Florida
- Abstract / Description
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Childhood obesity is a global health concern that puts children at risk for developing serious health complications. With increasing rates worldwide, it is important to determine how to decrease its prevalence and promote prevention in future generations. Emerging evidence indicating that pre-pregnancy weight status and/or gestational weight gain (GWG) may be linked with overweight/obesity in children. Much of this body of research focused on weight status of offspring at birth and at...
Show moreChildhood obesity is a global health concern that puts children at risk for developing serious health complications. With increasing rates worldwide, it is important to determine how to decrease its prevalence and promote prevention in future generations. Emerging evidence indicating that pre-pregnancy weight status and/or gestational weight gain (GWG) may be linked with overweight/obesity in children. Much of this body of research focused on weight status of offspring at birth and at preschool age. The purpose of this study is to: (1) analyze the research findings regarding obesity in children 5 to 18 years and their mother's pre-pregnancy weight status and/or GWG, and (2) make recommendations for prevention based on a review of current research. A database search of CINAHL, Medline, ERIC and PsycInfo was conducted. A total of 14 articles were identified based on their relevance to key search terms and meeting criteria. This literature review indicated support for associations between an underweight/overweight/obese pre-pregnancy weight status combined with greater than recommended total GWG and higher overweight/obesity in older children and adolescent offspring. Findings also supported the associations between pre-pregnancy weight status with high GWG during early pregnancy and increased offspring overweight/obesity. Pre-pregnancy overweight/obese weight status of mothers was the single factor consistently found to be strongly associated with risk for overweight and obesity in children 5 to 18 years of age. Results of this review support the need for further education, interventions, and policies aimed at healthy nutrition for women during and prior to pregnancy to prevent childhood obesity.
Show less - Date Issued
- 2017
- Identifier
- CFH2000160, ucf:46019
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH2000160
- Title
- THE EFFECT OF DIETARY INTERVENTIONS ON FETAL BIRTH WEIGHTS IN PREGNANT ADOLESCENTS: A SYSTEMATIC REVIEW.
- Creator
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Nath, Seeta, D'Amato-Kubiet, Leslee, University of Central Florida
- Abstract / Description
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Nutrition status during adolescent pregnancy and childbearing is a complex, multifaceted condition that can impact the health status of the teen mother and her baby. Adolescent mothers are at higher risk for low birth weight infants because of the unique dietary requirements needed to accommodate for both the growth needs of the adolescent mother and her unborn child. The purpose of this research was to examine dietary interventions that have the greatest effect on fetal birth weight outcomes...
Show moreNutrition status during adolescent pregnancy and childbearing is a complex, multifaceted condition that can impact the health status of the teen mother and her baby. Adolescent mothers are at higher risk for low birth weight infants because of the unique dietary requirements needed to accommodate for both the growth needs of the adolescent mother and her unborn child. The purpose of this research was to examine dietary interventions that have the greatest effect on fetal birth weight outcomes in adolescent mothers. Secondly, this study explored dietary nutrients effective in reducing the likelihood of complications commonly associated with low birth weight infants in adolescent pregnancy. A systematic literature review was conducted from the following online databases: Cumulative Index to Nursing and Allied Health Literature (CINAHL), Medical Literature On-line (MEDLINE), Education Resources Information Center (ERIC), and PsycInfo. Initial search terms included 'adolescent', 'nutrition', 'diet', and 'prenatal'. Further search items included 'weight' and 'outcome'. Selected articles included those published between 2000-2013, written in English, and peer-reviewed. Significant evidence supported positive birth weight outcomes for dietary supplementation with zinc and calcium, and BMI-specific weight gains for adolescent pregnancy. No significant evidence was provided on the effect of iron and fatty acid composition on birth weight outcomes. Results for other dietary interventions and their effects on fetal birth weight were either inconclusive or absent. Discovering dietary interventions that work best in prenatal care of adolescent populations will allow for more individually-tailored, dietary specific interventions to be developed to combat the prevalence of low fetal birth weight infants in adolescent pregnancy.
Show less - Date Issued
- 2014
- Identifier
- CFH0004646, ucf:45278
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH0004646
- Title
- NUTRITIONAL INTAKE AND WEIGHT GAIN IN INFANTS WITH NEONATAL ABSTINENCE SYNDROME: A LITERATURE REVIEW.
- Creator
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Kubisch, Kailey A, D'Amato-Kubiet, Leslee, University of Central Florida
- Abstract / Description
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Neonatal abstinence syndrome (NAS) in infants presents unique challenges in feeding and weight gain. The unpredictable clinical manifestations associated with the newborns withdrawal from exposure to drugs in utero can lead to costly delays in transition of the infant out of the Neonatal Intensive Care Unit (NICU).The purpose of this review of literature was to explore feeding positions and nutritional intake with the greatest impact on weight gain in infants with neonatal abstinence syndrome...
Show moreNeonatal abstinence syndrome (NAS) in infants presents unique challenges in feeding and weight gain. The unpredictable clinical manifestations associated with the newborns withdrawal from exposure to drugs in utero can lead to costly delays in transition of the infant out of the Neonatal Intensive Care Unit (NICU).The purpose of this review of literature was to explore feeding positions and nutritional intake with the greatest impact on weight gain in infants with neonatal abstinence syndrome (NAS) following delivery. The secondary purpose was to compare the clinical manifestations of infants with NAS that influence nutritional intake and their relationship to length of time and cost of stay in the NICU. A review of literature was performed using multiple databases. Articles focusing on feeding position and nutrition intake were identified for interventions to effectively promote weight gain, while reducing clinical manifestations common in infants with NAS. Articles exploring improved feeding and weight gain in infants with NAS and reduced length of stay in the NICU were also synthesized for cost reductions to the facility. Results from 12 studies comparing various feeding positions that optimized nutrition, and reduced negative clinical manifestations in infants with NAS were synthesized for content relevant to the research questions. Results suggest a relationship between placing infants in the c-position, and side-lying position to reduce sensory stimulation, with reducing clinical manifestations for infants actively experiencing withdrawal symptoms from NAS. Providing chin and cheek support as needed, decreasing eye contact during feeding periods, and providing darker quiet environments all play an important role in allowing infants with NAS to optimize their weight gain. As previously stated, to manage nutritional intake and optimize weight gain, reduction of clinical manifestations through pharmacological and non-pharmacological interventions must be actively incorporated into the infants' plan of care.
Show less - Date Issued
- 2019
- Identifier
- CFH2000561, ucf:45675
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH2000561
- Title
- Factors Influencing Nurse Practitioners' Weight Management Practices in Primary Care.
- Creator
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Hyer, Suzanne, Edwards, Joellen, Quelly, Susan, Upvall, Michele, Pasarica, Magdalena, University of Central Florida
- Abstract / Description
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More American adults are overweight or obese than ever before. Nurse practitioners (NPs) play a critical and expanding role in primary care, which is an ideal setting for the assessment and management of weight loss. NPs can make a significant contribution to tackling the obesity crisis. The study presented here seeks to close the gap in data related to how NPs approach weight management with their primary care patients. This study focused on a comprehensive examination of the current...
Show moreMore American adults are overweight or obese than ever before. Nurse practitioners (NPs) play a critical and expanding role in primary care, which is an ideal setting for the assessment and management of weight loss. NPs can make a significant contribution to tackling the obesity crisis. The study presented here seeks to close the gap in data related to how NPs approach weight management with their primary care patients. This study focused on a comprehensive examination of the current practice patterns of NPs related to weight management, a theoretical concept analysis of weight bias among healthcare providers, along with the results of a cross-sectional survey that investigated primary care NPs' weight management practice patterns and the relationship among attitudes, perceived barriers, self-efficacy, perceived skill, and demographic characteristics. The results from this study may be applied to provider training and education for obesity and weight management that ultimately improves patients' health outcomes.
Show less - Date Issued
- 2019
- Identifier
- CFE0007658, ucf:52498
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007658
- Title
- EXPLORING WOMEN'S LIFE COURSE EXPERIENCES WITH WEIGHT USING STORY THEORY.
- Creator
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Edmonds Poff, Allison, Bushy, Angeline, University of Central Florida
- Abstract / Description
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This qualitative study included women who had gone through the menopausal transition and had experienced obesity, and it focused on their weight histories and experiences across the life course. The goal of this research was to add to the body of knowledge concerning weight gain by applying a novel middle range theory (story theory). Story theory was used to collect and interpret from women's life course stories the critical themes and patterns of their weight gain. Oral accounts were...
Show moreThis qualitative study included women who had gone through the menopausal transition and had experienced obesity, and it focused on their weight histories and experiences across the life course. The goal of this research was to add to the body of knowledge concerning weight gain by applying a novel middle range theory (story theory). Story theory was used to collect and interpret from women's life course stories the critical themes and patterns of their weight gain. Oral accounts were elicited during personal interviews from a convenience sample of ten women recruited from a weight loss and exercise program in Central Florida. Literature focusing on the prevalence of obesity, contributing factors and associated complications, as well as treatment approaches is extensive. A variety of approaches have been proposed to identify factors that contribute to the development of obesity across the lifespan. Ultimately, the goal of these studies is to understand risk factors for weight gain along with corresponding prevention and management strategies. A particular life course approach focuses on critical periods across the life span that may be associated with risk for the development of obesity. For women, puberty, pregnancy and menopause are noted to be critical for weight change in the life course as they are associated with hormonal changes and changes in body composition including fat mass. Story theory was chosen to conceptualize and guide participants through a personal interview in order to share their weight experiences along their life course. Content analysis procedures were used to analyze the data in order to identify themes and corresponding verbatim exemplars. A re-constructed composite story was developed that included excerpts from the participants' stories in order to reveal contextualized results. Themes that were identified relative to participants' experiences with their weight included: changes associated with emotional and physical health; eating patterns associated with multiple and/or changing roles/relationships; and, changes in the environment. An interpretation of the predominant pattern of weight gain included: changes in eating and physical activity that occur during multiple and simultaneous transitional life experiences, primarily in adulthood. The findings suggest that transitional experiences in women's lives - physiological, developmental, relational or environmental - were critical in that they presented risk for behavior changes related to eating and physical activity. The results of this study and the use of story theory have implications for providing individualized, patient-centered lifestyle recommendations for the prevention of unhealthy weight gain.
Show less - Date Issued
- 2011
- Identifier
- CFE0003974, ucf:48663
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003974
- Title
- ANATOMICAL AND FUNCTIONAL ASSESSMENT OF PNMT+ NEURONS IN THE MOUSE HYPOTHALAMUS AND CEREBELLUM: POTENTIAL ROLES IN ENERGY METABOLISM AND MOTOR CONTROL.
- Creator
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Lindo, Lake A, Ebert, Steven, University of Central Florida
- Abstract / Description
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Phenylethanolamine N-methyltransferase (Pnmt) is the enzyme in the catecholamine pathway responsible for converting norepinephrine to epinephrine. Pnmt is present in numerous areas; however, the scope of its expression in the mouse brain is not fully understood. A genetic mouse model was generated by the Ebert lab that exhibited the selective destruction of all Pnmt+ cells through the induction of apoptosis by Diphtheria Toxin A. Unexpected phenotypic defects arose that are characterized by...
Show morePhenylethanolamine N-methyltransferase (Pnmt) is the enzyme in the catecholamine pathway responsible for converting norepinephrine to epinephrine. Pnmt is present in numerous areas; however, the scope of its expression in the mouse brain is not fully understood. A genetic mouse model was generated by the Ebert lab that exhibited the selective destruction of all Pnmt+ cells through the induction of apoptosis by Diphtheria Toxin A. Unexpected phenotypic defects arose that are characterized by metabolic weight deficits and motor ataxia. The distribution of Pnmt+ neurons was examined throughout the hypothalamus and cerebellum to generate an anatomical map of current and historical Pnmt expression using various histochemical methods. Historical Pnmt expression appears more extensive than current expression levels at the adult stage, indicating that certain cells in the mouse brain may have experienced transient Pnmt expression. The presence of Pnmt in these regions suggests that the destruction of these neurons may play a role in the phenotypic defects observed in the ablation mouse model. Gaining a more comprehensive understanding of the potential role of Pnmt in these areas may elucidate new drug targets or novel methods to treat obesity and motor control disorders such as ataxia.
Show less - Date Issued
- 2018
- Identifier
- CFH2000547, ucf:45689
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH2000547
- Title
- FOOD FOR THOUGHT: THE RELATIONSHIP BETWEEN THOUGHT SUPPRESSION AND WEIGHT CONTROL.
- Creator
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Peterson, Rachel, Tantleff Dunn, Stacey, University of Central Florida
- Abstract / Description
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The current study assessed the relationship between individuals' tendency to suppress thoughts, particularly related to food and body weight/shape, and outcomes such as weight loss maintenance and diet sabotaging experiences (e.g., binge eating). Community and university individuals (N = 347) who are or previously were overweight completed self-report measures of thought suppression, weight history, and eating behaviors. Suppression of specific thoughts about food/weight/shape was related...
Show moreThe current study assessed the relationship between individuals' tendency to suppress thoughts, particularly related to food and body weight/shape, and outcomes such as weight loss maintenance and diet sabotaging experiences (e.g., binge eating). Community and university individuals (N = 347) who are or previously were overweight completed self-report measures of thought suppression, weight history, and eating behaviors. Suppression of specific thoughts about food/weight/shape was related to weight cycling, binge eating, and food cravings. Participants who believed thoughts of food lead to eating were more likely to attempt suppression of food-related thoughts. Results have implications for improving weight loss maintenance and support further exploration of third wave interventions, such as Acceptance and Commitment Therapy and Mindfulness, in the treatment of obesity.
Show less - Date Issued
- 2008
- Identifier
- CFE0002231, ucf:47906
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002231
- Title
- Modeling Autocorrelation and Sample Weights in Panel Data: A Monte Carlo Simulation Study.
- Creator
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Acharya, Parul, Sivo, Stephen, Hahs-Vaughn, Debbie, Witta, Eleanor, Butler, Malcolm, University of Central Florida
- Abstract / Description
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This dissertation investigates the interactive or joint influence of autocorrelative processes (autoregressive-AR, moving average-MA, and autoregressive moving average-ARMA) and sample weights present in a longitudinal panel data set. Specifically, to what extent are the sample estimates influenced when autocorrelation (which is usually present in a panel data having correlated observations and errors) and sample weights (complex sample design feature used in longitudinal data having multi...
Show moreThis dissertation investigates the interactive or joint influence of autocorrelative processes (autoregressive-AR, moving average-MA, and autoregressive moving average-ARMA) and sample weights present in a longitudinal panel data set. Specifically, to what extent are the sample estimates influenced when autocorrelation (which is usually present in a panel data having correlated observations and errors) and sample weights (complex sample design feature used in longitudinal data having multi-stage sampling design) are modeled versus when they are not modeled or either one of them is taken into account. The current study utilized a Monte Carlo simulation design to vary the type and magnitude of autocorrelative processes and sample weights as factors incorporated in growth or latent curve models to evaluate the effect on sample latent curve estimates (mean intercept, mean slope, intercept variance, slope variance, and intercept slope correlation). Various latent curve models with weights or without weights were specified with an autocorrelative process and then fitted to data sets having either the AR, MA or ARMA process. The relevance and practical importance of the simulation results were ascertained by testing the joint influence of autocorrelation and weights on the Early Childhood Longitudinal Study for Kindergartens (ECLS-K) data set which is a panel data set having complex sample design features. The results indicate that autocorrelative processes and weights interact with each other as sources of error to a statistically significant degree. Accounting for just the autocorrelative process without weights or utilizing weights while ignoring the autocorrelative process may lead to bias in the sample estimates particularly in large-scale datasets in which these two sources of error are inherently embedded. The mean intercept and mean slope of latent curve models without weights was consistently underestimated when fitted to data sets having AR, MA or ARMA process. On the other hand, the intercept variance, intercept slope, and intercept slope correlation were overestimated for latent curve models with weights. However, these three estimates were not accurate as the standard errors associated with them were high. In addition, fit indices, AR and MA estimates, parsimony of the model, behavior of sample latent curve estimates, and interaction effects between autocorrelative processes and sample weights should be assessed for all the models before a particular model is deemed as most appropriate. If the AR estimate is high and MA estimate is low for a LCAR model than the other models that are fitted to a data set having sample weights and the fit indices are in the acceptable cut-off range, then the data set has a higher likelihood of having an AR process between the observations. If the MA estimate is high and AR estimate is low for a LCMA model than the other models that are fitted to a data set having sample weights and the fit indices are in the acceptable cut-off range, then the data set has a higher likelihood of having an MA process between the observations. If both AR and MA estimates are high for a LCARMA model than the other models that are fitted to a data set having sample weights and the fit indices are in the acceptable cut-off range, then the data set has a higher likelihood of having an ARMA process between the observations. The results from the current study recommends that biases from both autocorrelation and sample weights needs to be simultaneously modeled to obtain accurate estimates. The type of autocorrelation (AR, MA or ARMA), magnitude of autocorrelation, and sample weights influences the behavior of estimates and all the three facets should be carefully considered to correctly interpret the estimates especially in the context of measuring growth or change in the variable(s) of interest over time in large-scale longitudinal panel data sets.
Show less - Date Issued
- 2015
- Identifier
- CFE0005914, ucf:50850
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005914
- Title
- Weighted Low-Rank Approximation of Matrices:Some Analytical and Numerical Aspects.
- Creator
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Dutta, Aritra, Li, Xin, Sun, Qiyu, Mohapatra, Ram, Nashed, M, Shah, Mubarak, University of Central Florida
- Abstract / Description
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This dissertation addresses some analytical and numerical aspects of a problem of weighted low-rank approximation of matrices. We propose and solve two different versions of weighted low-rank approximation problems. We demonstrate, in addition, how these formulations can be efficiently used to solve some classic problems in computer vision. We also present the superior performance of our algorithms over the existing state-of-the-art unweighted and weighted low-rank approximation algorithms...
Show moreThis dissertation addresses some analytical and numerical aspects of a problem of weighted low-rank approximation of matrices. We propose and solve two different versions of weighted low-rank approximation problems. We demonstrate, in addition, how these formulations can be efficiently used to solve some classic problems in computer vision. We also present the superior performance of our algorithms over the existing state-of-the-art unweighted and weighted low-rank approximation algorithms.Classical principal component analysis (PCA) is constrained to have equal weighting on the elements of the matrix, which might lead to a degraded design in some problems. To address this fundamental flaw in PCA, Golub, Hoffman, and Stewart proposed and solved a problem of constrained low-rank approximation of matrices: For a given matrix $A = (A_1\;A_2)$, find a low rank matrix $X = (A_1\;X_2)$ such that ${\rm rank}(X)$ is less than $r$, a prescribed bound, and $\|A-X\|$ is small.~Motivated by the above formulation, we propose a weighted low-rank approximation problem that generalizes the constrained low-rank approximation problem of Golub, Hoffman and Stewart.~We study a general framework obtained by pointwise multiplication with the weight matrix and consider the following problem:~For a given matrix $A\in\mathbb{R}^{m\times n}$ solve:\begin{eqnarray*}\label{weighted problem}\min_{\substack{X}}\|\left(A-X\right)\odot W\|_F^2~{\rm subject~to~}{\rm rank}(X)\le r,\end{eqnarray*}where $\odot$ denotes the pointwise multiplication and $\|\cdot\|_F$ is the Frobenius norm of matrices.In the first part, we study a special version of the above general weighted low-rank approximation problem.~Instead of using pointwise multiplication with the weight matrix, we use the regular matrix multiplication and replace the rank constraint by its convex surrogate, the nuclear norm, and consider the following problem:\begin{eqnarray*}\label{weighted problem 1}\hat{X} (&)=(&) \arg \min_X \{\frac{1}{2}\|(A-X)W\|_F^2 +\tau\|X\|_\ast\},\end{eqnarray*}where $\|\cdot\|_*$ denotes the nuclear norm of $X$.~Considering its resemblance with the classic singular value thresholding problem we call it the weighted singular value thresholding~(WSVT)~problem.~As expected,~the WSVT problem has no closed form analytical solution in general,~and a numerical procedure is needed to solve it.~We introduce auxiliary variables and apply simple and fast alternating direction method to solve WSVT numerically.~Moreover, we present a convergence analysis of the algorithm and propose a mechanism for estimating the weight from the data.~We demonstrate the performance of WSVT on two computer vision applications:~background estimation from video sequences~and facial shadow removal.~In both cases,~WSVT shows superior performance to all other models traditionally used. In the second part, we study the general framework of the proposed problem.~For the special case of weight, we study the limiting behavior of the solution to our problem,~both analytically and numerically.~In the limiting case of weights,~as $(W_1)_{ij}\to\infty, W_2=\mathbbm{1}$, a matrix of 1,~we show the solutions to our weighted problem converge, and the limit is the solution to the constrained low-rank approximation problem of Golub et. al. Additionally, by asymptotic analysis of the solution to our problem,~we propose a rate of convergence.~By doing this, we make explicit connections between a vast genre of weighted and unweighted low-rank approximation problems.~In addition to these, we devise a novel and efficient numerical algorithm based on the alternating direction method for the special case of weight and present a detailed convergence analysis.~Our approach improves substantially over the existing weighted low-rank approximation algorithms proposed in the literature.~Finally, we explore the use of our algorithm to real-world problems in a variety of domains, such as computer vision and machine learning. Finally, for a special family of weights, we demonstrate an interesting property of the solution to the general weighted low-rank approximation problem. Additionally, we devise two accelerated algorithms by using this property and present their effectiveness compared to the algorithm proposed in Chapter 4.
Show less - Date Issued
- 2016
- Identifier
- CFE0006833, ucf:51789
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006833
- Title
- THE EFFECTS OF WEARABLE FITNESS DEVICES ON PEDIATRIC OBESITY: AN INTEGRATIVE LITERATURE REVIEW.
- Creator
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Sabina, Kevin, Decker, Jonathan, Hill, Peggy, University of Central Florida
- Abstract / Description
-
Childhood obesity is a foremost concern throughout the health care community. Approximately 17.6% of the pediatric population meet the criteria for obesity, which can lead to health disparities later in life, such as hypertension, type 2 diabetes mellitus, and metabolic syndrome. Emerging mobile and wearable lifestyle tracking devices can be a viable solution to the challenging problem of childhood obesity through behavior changes, feasibility, and adherence. The purpose of this literature...
Show moreChildhood obesity is a foremost concern throughout the health care community. Approximately 17.6% of the pediatric population meet the criteria for obesity, which can lead to health disparities later in life, such as hypertension, type 2 diabetes mellitus, and metabolic syndrome. Emerging mobile and wearable lifestyle tracking devices can be a viable solution to the challenging problem of childhood obesity through behavior changes, feasibility, and adherence. The purpose of this literature review was to determine the effect that mobile and wearable activity tracking devices have on the obese pediatric population. A centralized review of the literature was conducted using various data basesand resulted in 19 articles. 5 articles were chosen to review in more detail. 13 other articles were hand searched through credible resource citations, rendering 14 articles that met all criteria. The three general themes found in this literature review suggest that wearable activity tracking devices can be designed and effectively used by the pediatric population. Also, wearable activity tracking devices are accurate in conveying information on physical activity, calories, and heart rate. Lastly, wearable activity tracking devices can initiate behavioral changes in children leading to an increase in physical activity, resulting in the prevention and treatment of pediatric obesity.While in a majority of the studies analyzed trails were short. The research suggests wearable activity tracking devices will produce the desired results of increased activity in pediatric populations when they are worn correctly, are adequately engaging, and when they are designed in a feasible manner that is appealing to children.
Show less - Date Issued
- 2018
- Identifier
- CFH2000375, ucf:45824
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH2000375
- Title
- INFORMATION RETRIEVAL PERFORMANCE ENHANCEMENT USING THE AVERAGE STANDARD ESTIMATOR AND THE MULTI-CRITERIA DECISION WEIGHTED SET OF PERFORMANCE MEASURES.
- Creator
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AHRAM, TAREQ, McCauley-Bush, Pamela, University of Central Florida
- Abstract / Description
-
Information retrieval is much more challenging than traditional small document collection retrieval. The main difference is the importance of correlations between related concepts in complex data structures. These structures have been studied by several information retrieval systems. This research began by performing a comprehensive review and comparison of several techniques of matrix dimensionality estimation and their respective effects on enhancing retrieval performance using singular...
Show moreInformation retrieval is much more challenging than traditional small document collection retrieval. The main difference is the importance of correlations between related concepts in complex data structures. These structures have been studied by several information retrieval systems. This research began by performing a comprehensive review and comparison of several techniques of matrix dimensionality estimation and their respective effects on enhancing retrieval performance using singular value decomposition and latent semantic analysis. Two novel techniques have been introduced in this research to enhance intrinsic dimensionality estimation, the Multi-criteria Decision Weighted model to estimate matrix intrinsic dimensionality for large document collections and the Average Standard Estimator (ASE) for estimating data intrinsic dimensionality based on the singular value decomposition (SVD). ASE estimates the level of significance for singular values resulting from the singular value decomposition. ASE assumes that those variables with deep relations have sufficient correlation and that only those relationships with high singular values are significant and should be maintained. Experimental results over all possible dimensions indicated that ASE improved matrix intrinsic dimensionality estimation by including the effect of both singular values magnitude of decrease and random noise distracters. Analysis based on selected performance measures indicates that for each document collection there is a region of lower dimensionalities associated with improved retrieval performance. However, there was clear disagreement between the various performance measures on the model associated with best performance. The introduction of the multi-weighted model and Analytical Hierarchy Processing (AHP) analysis helped in ranking dimensionality estimation techniques and facilitates satisfying overall model goals by leveraging contradicting constrains and satisfying information retrieval priorities. ASE provided the best estimate for MEDLINE intrinsic dimensionality among all other dimensionality estimation techniques, and further, ASE improved precision and relative relevance by 10.2% and 7.4% respectively. AHP analysis indicates that ASE and the weighted model ranked the best among other methods with 30.3% and 20.3% in satisfying overall model goals in MEDLINE and 22.6% and 25.1% for CRANFIELD. The weighted model improved MEDLINE relative relevance by 4.4%, while the scree plot, weighted model, and ASE provided better estimation of data intrinsic dimensionality for CRANFIELD collection than Kaiser-Guttman and Percentage of variance. ASE dimensionality estimation technique provided a better estimation of CISI intrinsic dimensionality than all other tested methods since all methods except ASE tend to underestimate CISI document collection intrinsic dimensionality. ASE improved CISI average relative relevance and average search length by 28.4% and 22.0% respectively. This research provided evidence supporting a system using a weighted multi-criteria performance evaluation technique resulting in better overall performance than a single criteria ranking model. Thus, the weighted multi-criteria model with dimensionality reduction provides a more efficient implementation for information retrieval than using a full rank model.
Show less - Date Issued
- 2008
- Identifier
- CFE0002426, ucf:47747
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002426
- Title
- Weierstrass vertices and divisor theory of graphs.
- Creator
-
De Vas Gunasekara, Ajani Ruwandhika, Brennan, Joseph, Song, Zixia, Martin, Heath, University of Central Florida
- Abstract / Description
-
Chip-firing games and divisor theory on finite, connected, undirected and unweighted graphs have been studied as analogs of divisor theory on Riemann Surfaces. As part of this theory, a version of the one-dimensional Riemann-Roch theorem was introduced for graphs by Matt Baker in 2007. Properties of algebraic curves that have been studied can be applied to study graphs by means of the divisor theory of graphs.In this research, we investigate the property of a vertex of a graph having the...
Show moreChip-firing games and divisor theory on finite, connected, undirected and unweighted graphs have been studied as analogs of divisor theory on Riemann Surfaces. As part of this theory, a version of the one-dimensional Riemann-Roch theorem was introduced for graphs by Matt Baker in 2007. Properties of algebraic curves that have been studied can be applied to study graphs by means of the divisor theory of graphs.In this research, we investigate the property of a vertex of a graph having the Weierstrass property in analogy to the theory of Weierstrass points on algebraic curves. The weight of the Weierstrass vertices is then calculated in a manner analogous to the algebraic curve case. Although there are many graphs for which all vertices are Weierstrass vertices, there are bounds on the total weight of the Weierstrass vertices as a function of the arithmetic genus.For complete graphs, all of the vertices are Weierstrass when the number of vertices (n) is greater than or equals to $4$ and no vertex is Weierstrass for $n$ strictly less than 4. We study the complete graphs on 4, 5 and 6 vertices and reveal a pattern in the gap sequence for higher cases of n.Furthermore, we introduce a formula to calculate the Weierstrass weight of a vertex of the complete graph on n vertices. Additionally, we prove that Weierstrass semigroup of complete graphs is 2 - generated. Moreover, we show that there are no graphs of genus 2 and 6 vertices with all the vertices being normal Weierstrass vertices and generalize this result to any graph with genus g.
Show less - Date Issued
- 2018
- Identifier
- CFE0007397, ucf:52072
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007397
- Title
- SOCIAL CAPITAL INFLUENCES IN WOMEN AT RISK FOR POOR PREGNANCY OUTCOMES.
- Creator
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James-Mesloh, Jennifer, Wan, Thomas, University of Central Florida
- Abstract / Description
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Poor pregnancy outcomes such as prematurity, low birth weight and infant mortality are societal indicators of a nationÃÂÂ...
Show morePoor pregnancy outcomes such as prematurity, low birth weight and infant mortality are societal indicators of a nationÂÂÂÂÂÂÂÂ's health status. These indicators have remained at exceptionally high rates in the United States despite the levels of resources and technology. In the quest to understand that discrepancy, among the ranges of theories and models for explaining poor pregnancy outcomes an emerging concept is coming to attention: social capital. In order to test whether maternal social capital has an impact on pregnancy outcome, women in a Healthy Start program were surveyed over a 13-month period to assess their social capital levels and then their pregnancy outcomes. What emerged was that maternal social capital can predict up to 47% of the variance in pregnancy outcome. That is a powerful research result considering that previously there has been no literature tracing a link between maternal social capital and pregnancy outcome. In this study, maternal risk factors adversely affect up to 30% of the variance in pregnancy outcomes. Previous research has focused on maternal risk factors as the primary reason for high rates of preterm delivery, low birth weight, and infant mortality in the United States. However, this research found that in the sample of women at risk for adverse pregnancy outcomes, maternal risk factors had a very strong influence on maternal social capital (R-square=65%) while their effects on pregnancy outcomes were about half of their effects on social capital. This result suggests that social capital mediates the effects of maternal risk factors on pregnancy outcomes. It appears that one of the reasons that the high rates of adverse pregnancy outcomes in the United States have remained a mystery is that maternal social capital has not been taken into account.
Show less - Date Issued
- 2010
- Identifier
- CFE0003123, ucf:48639
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003123
- Title
- TAILORING THE PROPERTIES OF POLYELECTROLYTE COATED CERIUM OXIDE NANOPARTICLES AS A FUNCTION OF MOLECULAR WEIGHT.
- Creator
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Saraf, Shashank, Seal, Sudipta, Cho, Hyoung, Zhai, Lei, Heinrich, Helge, Harper, James, University of Central Florida
- Abstract / Description
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The application of Cerium oxide nanoparticles (CNPs) for therapeutic purposes requires a stable dispersion of nanoparticles in biological environment. The objective of this study is to tailor the properties of polyelectrolyte coated CNPs as a function of molecular weight to achieve a stable and catalytic active dispersion. This was achieved by coating CNPs with polyacrylic acid (PAA)which increased the dispersion stability of CNPs and enhanced the catalytic ability. The stability of PAA...
Show moreThe application of Cerium oxide nanoparticles (CNPs) for therapeutic purposes requires a stable dispersion of nanoparticles in biological environment. The objective of this study is to tailor the properties of polyelectrolyte coated CNPs as a function of molecular weight to achieve a stable and catalytic active dispersion. This was achieved by coating CNPs with polyacrylic acid (PAA)which increased the dispersion stability of CNPs and enhanced the catalytic ability. The stability of PAA coating was analysed using the change in the Gibbs free energy computed by Langmuir adsorption model. The adsorption isotherms were determined using soft particle electrokinetics which overcomes the challenges presented by other techniques. The Gibbs free energy was highest for PAA coated CNPs by 250 kg/mole indicating the most stable coating. The free energy for PAA 100 kg/mole coated CNPs is 85% lower than the PAA250 coated CNPs. This significant difference is caused by the strong adsorption of PAA100 on CNPs. Catalytic activity of PAA-CNPs is accessed by the catalase enzymatic activity of nanoparticles. The catalase activity was higher for PAA coated CNPs as compared to bare CNPs which indicated preferential adsorption of hydrogen peroxide induced by coating. Apart from PAA coating the catalase activity is also affected by the structure of the coating layer.
Show less - Date Issued
- 2013
- Identifier
- CFE0005410, ucf:50410
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005410
- Title
- LEARNING, DETECTION, REPRESENTATION, INDEXING AND RETRIEVAL OF MULTI-AGENT EVENTS IN VIDEOS.
- Creator
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Hakeem, Asaad, Shah, Mubarak, University of Central Florida
- Abstract / Description
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The world that we live in is a complex network of agents and their interactions which are termed as events. An instance of an event is composed of directly measurable low-level actions (which I term sub-events) having a temporal order. Also, the agents can act independently (e.g. voting) as well as collectively (e.g. scoring a touch-down in a football game) to perform an event. With the dawn of the new millennium, the low-level vision tasks such as segmentation, object classification, and...
Show moreThe world that we live in is a complex network of agents and their interactions which are termed as events. An instance of an event is composed of directly measurable low-level actions (which I term sub-events) having a temporal order. Also, the agents can act independently (e.g. voting) as well as collectively (e.g. scoring a touch-down in a football game) to perform an event. With the dawn of the new millennium, the low-level vision tasks such as segmentation, object classification, and tracking have become fairly robust. But a representational gap still exists between low-level measurements and high-level understanding of video sequences. This dissertation is an effort to bridge that gap where I propose novel learning, detection, representation, indexing and retrieval approaches for multi-agent events in videos. In order to achieve the goal of high-level understanding of videos, firstly, I apply statistical learning techniques to model the multiple agent events. For that purpose, I use the training videos to model the events by estimating the conditional dependencies between sub-events. Thus, given a video sequence, I track the people (heads and hand regions) and objects using a Meanshift tracker. An underlying rule-based system detects the sub-events using the tracked trajectories of the people and objects, based on their relative motion. Next, an event model is constructed by estimating the sub-event dependencies, that is, how frequently sub-event B occurs given that sub-event A has occurred. The advantages of such an event model are two-fold. First, I do not require prior knowledge of the number of agents involved in an event. Second, no assumptions are made about the length of an event. Secondly, after learning the event models, I detect events in a novel video by using graph clustering techniques. To that end, I construct a graph of temporally ordered sub-events occurring in the novel video. Next, using the learnt event model, I estimate a weight matrix of conditional dependencies between sub-events in the novel video. Further application of Normalized Cut (graph clustering technique) on the estimated weight matrix facilitate in detecting events in the novel video. The principal assumption made in this work is that the events are composed of highly correlated chains of sub-events that have high conditional dependency (association) within the cluster and relatively low conditional dependency (disassociation) between clusters. Thirdly, in order to represent the detected events, I propose an extension of CASE representation of natural languages. I extend CASE to allow the representation of temporal structure between sub-events. Also, in order to capture both multi-agent and multi-threaded events, I introduce a hierarchical CASE representation of events in terms of sub-events and case-lists. The essence of the proposition is that, based on the temporal relationships of the agent motions and a description of its state, it is possible to build a formal description of an event. Furthermore, I recognize the importance of representing the variations in the temporal order of sub-events, that may occur in an event, and encode the temporal probabilities directly into my event representation. The proposed extended representation with probabilistic temporal encoding is termed P-CASE that allows a plausible means of interface between users and the computer. Using the P-CASE representation I automatically encode the event ontology from training videos. This offers a significant advantage, since the domain experts do not have to go through the tedious task of determining the structure of events by browsing all the videos. Finally, I utilize the event representation for indexing and retrieval of events. Given the different instances of a particular event, I index the events using the P-CASE representation. Next, given a query in the P-CASE representation, event retrieval is performed using a two-level search. At the first level, a maximum likelihood estimate of the query event with the different indexed event models is computed. This provides the maximum matching event. At the second level, a matching score is obtained for all the event instances belonging to the maximum matched event model, using a weighted Jaccard similarity measure. Extensive experimentation was conducted for the detection, representation, indexing and retrieval of multiple agent events in videos of the meeting, surveillance, and railroad monitoring domains. To that end, the Semoran system was developed that takes in user inputs in any of the three forms for event retrieval: using predefined queries in P-CASE representation, using custom queries in P-CASE representation, or query by example video. The system then searches the entire database and returns the matched videos to the user. I used seven standard video datasets from the computer vision community as well as my own videos for testing the robustness of the proposed methods.
Show less - Date Issued
- 2007
- Identifier
- CFE0001620, ucf:47163
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0001620
- Title
- THE EFFECT OF WEIGHT AND SIZE ON MENTAL ROTATION.
- Creator
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Furtak, Luke, Sims, Valerie, University of Central Florida
- Abstract / Description
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Shepard and Metzler (1971) argued that mental rotation is analogous to the real world in that people imagine the rotation of an object as if it were being physically rotated. This study tested this assertion by exposing participants to physical shapes that increased in size and weight. Participants interacted with blocks designed after Shepard and Metzler mental rotation size that differed in size and weight then performed subsequent mental rotation. We found no difference in reaction time...
Show moreShepard and Metzler (1971) argued that mental rotation is analogous to the real world in that people imagine the rotation of an object as if it were being physically rotated. This study tested this assertion by exposing participants to physical shapes that increased in size and weight. Participants interacted with blocks designed after Shepard and Metzler mental rotation size that differed in size and weight then performed subsequent mental rotation. We found no difference in reaction time but found that increased size reduced accuracy. We discuss the implications of this study as they pertain to embodied cognition.
Show less - Date Issued
- 2014
- Identifier
- CFH0004711, ucf:45399
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH0004711
- Title
- INJECTION TECHNIQUES OF SUBCUTANEOUS ANTICOAGULANT THERAPIES.
- Creator
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Morissette, Leah, Desmarais, Paul, University of Central Florida
- Abstract / Description
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Subcutaneous anticoagulant medications like Heparin and Low-Molecular Weight Heparin are injections that readily cause bruising, pain, induration, and hematoma formation at the injection site. It is known that these adverse reactions can be correlated to the technique used to administer these medications; however, there is no established technique that reduces bruising, pain, induration, and hematoma formation at the site. Currently, the only protocol for subcutaneous Heparin and Low...
Show moreSubcutaneous anticoagulant medications like Heparin and Low-Molecular Weight Heparin are injections that readily cause bruising, pain, induration, and hematoma formation at the injection site. It is known that these adverse reactions can be correlated to the technique used to administer these medications; however, there is no established technique that reduces bruising, pain, induration, and hematoma formation at the site. Currently, the only protocol for subcutaneous Heparin and Low-Molecular Weight Heparin is that it is to be administered subcutaneously in the abdomen and when using a prefilled syringe, the air bubble should not be removed. The purpose of this study was to identify current nursing practice for the administration of these medications and to compare the results to researched techniques that resulted in less adverse site reactions. A total of 33 participants were recruited. The survey targeted six researched techniques found, after a comprehensive literature review, to have reduced site adverse effects associated with subcutaneous Heparin and Low-Molecular Weight Heparin. After completing the survey, it was found that current practice does not reflect techniques researched to reduce bruising, pain, induration, and hematoma formation at the site. In fact, very few completed one of the six research techniques that were questioned, which included: a two minute application of a cold compress/pack before and/or after the injection, an injection duration lasting 30 seconds, slow removal of the needle over five seconds, application of pressure after the injection for a minimum of 30 seconds, use of a hot pack/compress after the injection, and the use of a3 mL syringe. It was also found that there were inconsistencies in techniques that have been previously established as current protocol for these medications.
Show less - Date Issued
- 2015
- Identifier
- CFH0004733, ucf:45390
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH0004733
- Title
- Learning to Grasp Unknown Objects using Weighted Random Forest Algorithm from Selective Image and Point Cloud Feature.
- Creator
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Iqbal, Md Shahriar, Behal, Aman, Boloni, Ladislau, Haralambous, Michael, University of Central Florida
- Abstract / Description
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This method demonstrates an approach to determine the best grasping location on an unknown object using Weighted Random Forest Algorithm. It used RGB-D value of an object as input to find a suitable rectangular grasping region as the output. To accomplish this task, it uses a subspace of most important features from a very high dimensional extensive feature space that contains both image and point cloud features. Usage of most important features in the grasping algorithm has enabled the...
Show moreThis method demonstrates an approach to determine the best grasping location on an unknown object using Weighted Random Forest Algorithm. It used RGB-D value of an object as input to find a suitable rectangular grasping region as the output. To accomplish this task, it uses a subspace of most important features from a very high dimensional extensive feature space that contains both image and point cloud features. Usage of most important features in the grasping algorithm has enabled the system to be computationally very fast while preserving maximum information gain. In this approach, the Random Forest operates using optimum parameters e.g. Number of Trees, Number of Features at each node, Information Gain Criteria etc. ensures optimization in learning, with highest possible accuracy in minimum time in an advanced practical setting. The Weighted Random Forest chosen over Support Vector Machine (SVM), Decision Tree and Adaboost for implementation of the grasping system outperforms the stated machine learning algorithms both in training and testing accuracy and other performance estimates. The Grasping System utilizing learning from a score function detects the rectangular grasping region after selecting the top rectangle that has the largest score. The system is implemented and tested in a Baxter Research Robot with Parallel Plate Gripper in action.
Show less - Date Issued
- 2014
- Identifier
- CFE0005509, ucf:50358
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005509
- Title
- Cost-Sensitive Learning-based Methods for Imbalanced Classification Problems with Applications.
- Creator
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Razzaghi, Talayeh, Xanthopoulos, Petros, Karwowski, Waldemar, Pazour, Jennifer, Mikusinski, Piotr, University of Central Florida
- Abstract / Description
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Analysis and predictive modeling of massive datasets is an extremely significant problem that arises in many practical applications. The task of predictive modeling becomes even more challenging when data are imperfect or uncertain. The real data are frequently affected by outliers, uncertain labels, and uneven distribution of classes (imbalanced data). Such uncertainties createbias and make predictive modeling an even more difficult task. In the present work, we introduce a cost-sensitive...
Show moreAnalysis and predictive modeling of massive datasets is an extremely significant problem that arises in many practical applications. The task of predictive modeling becomes even more challenging when data are imperfect or uncertain. The real data are frequently affected by outliers, uncertain labels, and uneven distribution of classes (imbalanced data). Such uncertainties createbias and make predictive modeling an even more difficult task. In the present work, we introduce a cost-sensitive learning method (CSL) to deal with the classification of imperfect data. Typically, most traditional approaches for classification demonstrate poor performance in an environment with imperfect data. We propose the use of CSL with Support Vector Machine, which is a well-known data mining algorithm. The results reveal that the proposed algorithm produces more accurate classifiers and is more robust with respect to imperfect data. Furthermore, we explore the best performance measures to tackle imperfect data along with addressing real problems in quality control and business analytics.
Show less - Date Issued
- 2014
- Identifier
- CFE0005542, ucf:50298
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005542
- Title
- Designing Calorie Counter Smartphone Applications for Effective Weight Loss.
- Creator
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Milliard, Sharlin, Fanfarelli, Joseph, Bockelman, Patricia, Hartshorne, Richard, University of Central Florida
- Abstract / Description
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Poor dietary choices and lack of physical activity are two main contributing factors for the increasing prevalence of overweight and obesity in the United States. Overweight and obese individuals are at risk for developing major life-threatening diseases. Weight loss is an effective means for reversing these adverse health effects, and smartphone applications (apps) may be an effective means for supporting weight loss outside of formal clinical settings. This study involved identifying...
Show morePoor dietary choices and lack of physical activity are two main contributing factors for the increasing prevalence of overweight and obesity in the United States. Overweight and obese individuals are at risk for developing major life-threatening diseases. Weight loss is an effective means for reversing these adverse health effects, and smartphone applications (apps) may be an effective means for supporting weight loss outside of formal clinical settings. This study involved identifying factors that contribute to effective weight loss to compare with functionality commonly found in a sample of calorie counter apps. A content analysis was performed using a design framework that included a conceptual model describing the interaction of behaviors for effective weight loss and functional design requirements based upon behavior change and motivation to achieve weight loss. The requirements were used to analyze the presence of features in a sample of popular calorie counting apps, to infer their capability in supporting users' motivation to achieve weight loss. Results indicated that app features might not provide sufficient support to facilitate effective weight loss. Lack of supportive features affects perceived autonomy, relatedness, and competence, reducing motivation. This study provided guidelines to improve the design of calorie counter apps to include more features that support users as they engage in weight loss behaviors. The guidelines may become practical for use in mHealth apps used as part of formal and informal weight management strategies. Implications for future research involving wearable technologies and the use of gamified design strategies are discussed.
Show less - Date Issued
- 2019
- Identifier
- CFE0007838, ucf:52824
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007838
