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Characterization, Properties and Applications of Novel Nanostructured Hydrogels.

Description: The characterization, properties and applications of the novel nanostructured microgel (nanoparticle network and microgel crystal) composed of poly-N-isopropylacrylanmide-co-allylamine (PNIPAM-co-allylamine) and PNIPAM-co-acrylic acid(AA) have been investigated. For the novel nanostructured hydrogels with the two levels of structure: the primary network inside each individual particle and the secondary network of the crosslinked nanoparticles, the new shear modulus, drug release law from hydrogel with heterogeneous structure have been studied. The successful method for calculating the volume fraction related the phase transition of colloid have been obtained. The kinetics of crystallization in an aqueous dispersion of PNIPAM particles has been explored using UV-visible transmission spectroscopy. This dissertation also includes the initial research on the melting behavior of colloidal crystals composed of PNIPAM microgels. Many new findings in this study area have never been reported before. The theoretical model for the columnar crystal growth from the top to bottom of PNIPAM microgel has been built, which explains the growth mechanism of the novel columnar hydrogel colloidal crystals. Since the unique structure of the novel nanostructured hydrogels, their properties are different with the conventional hydrogels and the hard-sphere-like system. The studies and results in this dissertation have the important significant for theoretical study and valuable application of these novel nanostructured hydrogels.
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Date: December 2006
Creator: Tang, Shijun
Partner: UNT Libraries

Investigation on Segmentation, Recognition and 3D Reconstruction of Objects Based on Lidar Data Or Mri

Description: Segmentation, recognition and 3D reconstruction of objects have been cutting-edge research topics, which have many applications ranging from environmental and medical to geographical applications as well as intelligent transportation. In this dissertation, I focus on the study of segmentation, recognition and 3D reconstruction of objects using LiDAR data/MRI. Three main works are that (I). Feature extraction algorithm based on sparse LiDAR data. A novel method has been proposed for feature extraction from sparse LiDAR data. The algorithm and the related principles have been described. Also, I have tested and discussed the choices and roles of parameters. By using correlation of neighboring points directly, statistic distribution of normal vectors at each point has been effectively used to determine the category of the selected point. (II). Segmentation and 3D reconstruction of objects based on LiDAR/MRI. The proposed method includes that the 3D LiDAR data are layered, that different categories are segmented, and that 3D canopy surfaces of individual tree crowns and clusters of trees are reconstructed from LiDAR point data based on a region active contour model. The proposed method allows for delineations of 3D forest canopy naturally from the contours of raw LiDAR point clouds. The proposed model is suitable not only for a series of ideal cone shapes, but also for other kinds of 3D shapes as well as other kinds dataset such as MRI. (III). Novel algorithms for recognition of objects based on LiDAR/MRI. Aimed to the sparse LiDAR data, the feature extraction algorithm has been proposed and applied to classify the building and trees. More importantly, the novel algorithms based on level set methods have been provided and employed to recognize not only the buildings and trees, the different trees (e.g. Oak trees and Douglas firs), but also the subthalamus nuclei (STNs). By using the novel algorithms based ...
Date: May 2015
Creator: Tang, Shijun
Partner: UNT Libraries