Several statistical results under multinomial distribution with infinite categories

This dissertation discusses several statistical results under multinomial distribution with infinite categories. Firstly, the discussion focuses on Simpson’s diversity index and Turing’s formula. We established an unbiased estimate for the newly proposed Generalized Simpson’s indices and the associated asymptotic properties and showed that the parameters of a multinomial distribution may be re-parameterized as a set of Generalized Simpson’s di- versity indices. Secondly, two-dimensional asymptotic normality of a non-parametric sample coverage estimate based on Turing’s formulae was derived under a fixed underlying probabil- ity distribution {pk ; k = 1, 2, · · · } where all pk > 0. Thirdly, the dissertation also establishes a previously unknown sufficient condition for the second order Turing’s formula. The newly derived asymptotic results based on Turing’s formula paves a possible way to establish a new estimating approach for Hill’s tail probability model

Marital hostility, adolescents’ responses to marital conflict, and adolescents’ adjustment: the moderating role of cooperative marital conflict

Marital hostility is a salient risk factor for adolescents’ well-being, academic performance, and social functioning. In contrast to the substantial body of research focusing on the effects of marital hostility on adolescents’ development, few studies have examined a positive conflict process (i.e., cooperative marital conflict) and how it operates in conjunction with marital hostility to shape youth adjustment during early adolescence. Furthermore, the generative mechanisms through which cooperative marital conflict and marital hostility are associated with youth adjustment are not well understood. To fill this gap, the present study examined the longitudinal associations between marital hostility, cooperative marital conflict, and increases in early adolescents’ adjustment problems based on three annual waves of data from a community-based sample of 366 two-parent families residing in a Southeastern state within the US. In particular, cognitive-contextual theory, emotion security theory, and a risk and resilience perspective were used to deduce the potential mechanisms through which marital hostility interacted with cooperative marital conflict in the prediction of youth responses to marital conflict over time and increases in youth adjustment problems. Gender differences also were examined. Several important findings emerged. Cooperative marital conflict and the sub-dimensions of cooperative marital conflict (i.e., constructive problem solving, marital warmth, and effective conflict resolution) did not moderate the association between marital hostility and increases in youth internalizing and externalizing problems over time. Cooperative marital conflict, in general, and marital warmth and effective conflict resolution, in particular, buffered the negative impact of marital hostility on adolescent girls’ lower cognitive representations of the family. Unexpectedly, marital hostility was associated with boys’ self-blame only when their parents demonstrated higher levels of cooperative marital conflict and constructive problem solving. These findings highlight the importance of examining adolescents’ responses to marital conflict in the context of cooperative marital conflict processes. Results also emphasize the importance of examining proximal cognitive, emotional, and behavioral reactions to marital conflict in relation to marital hostility and cooperative marital conflict than is more distal problem behavior. Results suggest that the positive emotional atmosphere and the resolution state cues might imply to youth positive, sympathetic, and harmonious representations of the marital and family relationships, which ultimately could help reduce the weakening, disrupted representations constructed from hostile marital interactions. That significant buffering effects of marital warmth and effective conflict resolution are relevant for girls supported the communal hypothesis. Girls are more likely to emphasize communal goals or interpersonal connectedness and therefore girls might be more likely to detect the positive cues during the conflict processes and are able to reduce negative representations as a result. Results also contribute to theory development by providing evidence for the distinctness of cooperative marital conflict and marital hostility and their interactive effects on youth responses to marital conflict. Given the prominent pathological effects of marital hostility on a wide range of youth adjustment outcomes, future studies should continue to examine the buffering effects of cooperative marital conflict in the presence of marital hostility for other aspects of youth development and across different groups of families and youth

Exploration of factors associated with tea culture and tea tourism in United States, China, and Taiwan

The purpose of this study was to explore how demographic and motivational factors influence tea-drinking behaviors, tea cultural perceptions, and expectations on tea tourism. Few research studies on tea tourism have been published in English literatures. This study reviewed related literatures in both English and Chinese, to integrate the body of knowledge of tea culture and tourism, contribute to understanding and transmission of tea cultures, and promote communications between English and Chinese tea tourism studies. The researcher surveyed a total of 246 university faculty in U.S, China and Taiwan, using convenience sampling methods. The survey contained questions in four categories: tea drinking behaviors, tea cultural perceptions, attitudes, motivations and expectations of tea tourism, and demographics including country of residence, age, gender, education, annual income, and self-reported cultural backgrounds. Data collection procedure was conducted through an online surveying tool, Qualtrics, using web-based surveying methodology. Data were analyzed through Statistical Package for the Social Sciences© version 18.0. This study had five major findings in: (a) tea drinking behavioral profile, (b) the relation between demographic factors and tea drinking behaviors, (c) the relationship between tea drinking behaviors and tea culture, (d) the influence of cultural backgrounds on tea cultural perceptions, and (e) the factors influencing tea tourism expectations. Based on the conclusions, recommendations were made for future research and tea related practical sectors

GEOMETRIC ANALYSIS TOOLS FOR MESH SEGMENTATION

Surface segmentation, a process which divides a surface into parts, is the basis for many surface manipulation applications which include model metamorphosis, model simplifica- tion, model retrieval, model alignment and texture mapping. This dissertation discusses novel methods for geometric surface analysis and segmentation and applications for these methods. Novel work within this dissertation includes a new 3D mesh segmentation algo- rithm which is referred to as the ridge-walking algorithm. The main benefit of this algo- rithm is that it can dynamically change the criteria it uses to identify surface parts which allows the algorithm to be adjusted to suit different types of surfaces and different segmen- tation goals. The dynamic segmentation behavior allows users to extract three different types of surface regions: (1) regions delineated by convex ridges, (2) regions delineated by concave valleys, and (3) regions delineated by both concave and convex curves. The ridge walking algorithm is quantitatively evaluated by comparing it with competing algo- rithms and human-generated segmentations. The evaluation is accompanied with a detailed geometrical analysis of a select subset of segmentation results to facilitate a better under- standing of the strengths and weaknesses of this algorithm. The ridge walking algorithm is applied to three domain-specific segmentation prob- lems. The first application uses this algorithm to partition bone fragment surfaces into three semantic parts: (1) the fracture surface, (2) the periosteal surface and (3) the articular surface. Segmentation of bone fragments is an important computational step necessary in developing quantitative methods for bone fracture analysis and for creating computational tools for virtual fracture reconstruction. The second application modifies the 3D ridge walking algorithm so that it can be applied to 2D images. In this case, the 2D image is modeled as a Monge patch and principal curvatures of the intensity surface are computed iv for each image pixel. These principal curvatures are then used by ridge walking algorithm to segment the image into meaningful parts. The third application uses the ridge walking algorithm to facilitate analysis of virtual 3D terrain models. Specifically, the algorithm is integrated as a part of a larger software system designed to enable users to browse, visualize and analyze 3D geometric data generated by NASA’s Mars Exploratory Rovers Spirit and Opportunity. In this context, the ridge walking algorithm is used to identify surface features such as rocks in the terrain models

A study of conjugate addition of curcumin and chalcone derivatives

Curcumin is one of the promising herbal-based drugs. It has been shown to have antioxidant,antibacterial, anti-angiogenic and other activities. As curcumin's derivative, chalcone shares similar functions. Both of these two compounds have alpha,beta-unsaturated carbonyl structures(enone), which is a typical 1,4-conjugate addition (Michael addition) acceptor. Glutathione is an endogenous tripeptide, whose sulfhydral group is a typical nucleophilic agent. In this case, the derivatives of curcumin and chalcone may be reduced by glutathione and their pharmacological functions would be changed. The study focused on how to use quantum chemistry tools and transition state theory to access to the conjugate addition of alpha,beta-unsaturated carbonyl compounds. Besides, the reductions of the derivatives of chalcone were also studied. The characteristics of the reactions were obtained by analyzing geometries and energy profiles of the simplified reactions, as well as the influence of functional groups on derivatives in this type of reaction. This study may be generally useful for the scientific community for two fundamental reasons: (a) to provide general strategies to enhance or retard drugs from reacting with glutathione, and (b) to provide insight into computational methods that are able to help design potential lead candidates

HIERARCHICAL LEARNING OF DISCRIMINATIVE FEATURES AND CLASSIFIERS FOR LARGE-SCALE VISUAL RECOGNITION

Enabling computers to recognize objects present in images has been a long standing but tremendously challenging problem in the field of computer vision for decades. Beyond the difficulties resulting from huge appearance variations, large-scale visual recognition poses unprecedented challenges when the number of visual categories being considered becomes thousands, and the amount of images increases to millions. This dissertation contributes to addressing a number of the challenging issues in large-scale visual recognition. First, we develop an automatic image-text alignment method to collect massive amounts of labeled images from the Web for training visual concept classifiers. Specif- ically, we first crawl a large number of cross-media Web pages containing Web images and their auxiliary texts, and then segment them into a collection of image-text pairs. We then show that near-duplicate image clustering according to visual similarity can significantly reduce the uncertainty on the relatedness of Web images’ semantics to their auxiliary text terms or phrases. Finally, we empirically demonstrate that ran- dom walk over a newly proposed phrase correlation network can help to achieve more precise image-text alignment by refining the relevance scores between Web images and their auxiliary text terms. Second, we propose a visual tree model to reduce the computational complexity of a large-scale visual recognition system by hierarchically organizing and learning the classifiers for a large number of visual categories in a tree structure. Compared to previous tree models, such as the label tree, our visual tree model does not require training a huge amount of classifiers in advance which is computationally expensive. However, we experimentally show that the proposed visual tree achieves results that are comparable or even better to other tree models in terms of recognition accuracy and efficiency. Third, we present a joint dictionary learning (JDL) algorithm which exploits the inter-category visual correlations to learn more discriminative dictionaries for image content representation. Given a group of visually correlated categories, JDL simul- taneously learns one common dictionary and multiple category-specific dictionaries to explicitly separate the shared visual atoms from the category-specific ones. We accordingly develop three classification schemes to make full use of the dictionaries learned by JDL for visual content representation in the task of image categoriza- tion. Experiments on two image data sets which respectively contain 17 and 1,000 categories demonstrate the effectiveness of the proposed algorithm. In the last part of the dissertation, we develop a novel data-driven algorithm to quantitatively characterize the semantic gaps of different visual concepts for learning complexity estimation and inference model selection. The semantic gaps are estimated directly in the visual feature space since the visual feature space is the common space for concept classifier training and automatic concept detection. We show that the quantitative characterization of the semantic gaps helps to automatically select more effective inference models for classifier training, which further improves the recognition accuracy rates

CALIBRATING SLOPE-DEPENDENT ERRORS IN PROFILOMETRY

Optical profilometers, such as scanning white light interferometers and confocal microscopes, provide high resolution measurements and are widely utilized in many fields for measuring surface topography. The techniques are capable of high-speed surface measurements with nanometer-scale repeatability, and are used in industries such as data storage, automotive, MEMS, electronics, micro-optics, and bio-medical, to name a few. The instrument works best on flat, stepped structures, and slope-dependent systematic errors can be present in the measurement of steep sloped regions. These errors can be the same order of magnitude as features on the surface to be measured. Researchers have carried out many studies of these errors from first principle analyses; however the errors depend on proprietary details of the optical design and cannot be exactly calculated from first principles. The problem is further complicated by a lack of calibration artifacts to measure the errors directly. We propose a self-calibration technique, the random ball test, for calibrating slope-dependent errors of such instruments. A simulation study validates the approach and shows that the random ball test is effective in practical limits. We demonstrate the calibration on a 50x confocal microscope and a 50x white light interferometer with a specific chosen algorithm, find a surface slope- dependent bias that increases monotonically with the magnitude of the surface slope. The uncertainty of the calibration is smaller than the observed measurement bias and is dominated by residual random noise. Effects such as distortion, drift and ball radius uncertainty were investigated to understand their contribution to the calibration uncertainty

Real-time lattice boltzmann shallow waters method for breaking wave simulations

We present a new approach for the simulation of surfacebased fluids based in a hybrid formulation of Lattice Boltzmann Method for Shallow Waters and particle systems. The modified LBM can handle arbitrary underlying terrain conditions and arbitrary fluid depth. It also introduces a novel method for tracking dry-wet regions and moving boundaries. Dynamic rigid bodies are also included in our simulations using a two-way coupling. Certain features of the simulation that the LBM can not handle because of its heightfield nature, as breaking waves, are detected and automatically turned into splash particles. Here we use a ballistic particle system, but our hybrid method can handle more complex systems as SPH. Both the LBM and particle systems are implemented in CUDA, although dynamic rigid bodies are simulated in CPU. We show the effectiveness of our method with various examples which achieve real-time on consumer-level hardware.Peer ReviewedPostprint (author's final draft

Low total harmonic distortion (THD) resonant converter for cooker magnetron power supply

The traditional cooker magnetron power supply consists industrial frequency transformer, whichis bulky, inefficient and with high harmonics distortion. There are numerous researchers whoinvestigates magnetron power supply design with soft switching converter, in order to reduceweight and improve efficiency [7–10]. However, no investigation currently exists on harmonicdistortion of traditionalmagnetron power supply, and very little research or analysis is done onharmonic distortion of new type of magnetron power supply. This project aims to investigateharmonic distortion of traditional magnetron power supply in the first phase. In the secondphase, a novel design of high frequency and low harmonic distortion magnetron power supply istargeted

Interparental conflict and infants’ behavior problems: The mediating role of maternal sensitivity

Although the negative effect of interparental conflict on child behavior problems has been well established, few studies have examined this association during infancy. This study examined the associations between mother-reported interparental conflict and young children’s behavior problems over the first 2 years of their lives in a sample of 212 mothers and infants. Two aspects of maternal sensitivity, sensitivity during distressing and nondistressing contexts, were examined as possible mediators between interparental conflict and infants’ behavior problems. Results indicated that interparental conflict was associated directly with infants’ externalizing problems over time but was associated indirectly with infants’ internalizing problems over time via compromised maternal sensitivity within distressing contexts but not through maternal sensitivity within nondistressing contexts. No significant child gender differences were found. Such findings add to a limited body of research suggesting that the early interparental relationship context is relevant for infant adjustment. The salient mediating role of maternal sensitivity within distressing contexts provides important theoretical and practical insights for future studies