A Comparison of Plaintiff and Defense Expert Witness H-Index Scores in Mild Traumatic Brain Injury Civil Litigation (open access)

A Comparison of Plaintiff and Defense Expert Witness H-Index Scores in Mild Traumatic Brain Injury Civil Litigation

This study examines the background and qualifications of plaintiff and defense experts using the H-Index score as quantification of expert background and qualifications. The goal is to better understand the similarities and differences among the professionals offering paid expert witness testimony in mild traumatic brain injury (mTBI) civil litigation. In this quantitative study, descriptive statistics include the mean and standard deviation scores for the data to support examining measures of central tendency and variance, respectively. The study includes the use of logistic regression and the Wilcoxon signed-rank test, and their statistical assumptions were tested to determine whether they would be used or if it was more appropriate to use a non-parametric test. The study included two research questions: How do the qualifications of plaintiff and defense expert witnesses in mild traumatic brain injury civil litigation compare? and to what extent does a higher h-index correlate with a favorable litigation outcome in a mild traumatic brain injury case? The findings for the hypothesis tests associated with the research questions led to the acceptance of the null hypothesis in each test. There was a lack of asymptotic significance in Hypothesis 1 and a lack of significance in Hypothesis 2. The findings from …
Date: August 2022
Creator: Victor, Elise C
System: The UNT Digital Library
Understanding the Relationship between Critical Literacy, Cultural Literacy, and Religious Literacy for Second-Generation Immigrants (open access)

Understanding the Relationship between Critical Literacy, Cultural Literacy, and Religious Literacy for Second-Generation Immigrants

This study explores information seeking behavior of second-generation Muslim immigrants utilizing factors such as critical, cultural, and religious literacy skills. The study examined the second-generation immigrants' ability to balance their parents' and grandparents' native culture and traditions with the culture and traditions of their country. The interview questions were designed using the cognitive authority theory and the figured worlds theory that provides an explanation for the mentality of those who are in environments influenced by culture or religion. An interesting main finding of the study is that participants sought more religious-based rather than culturally-based information. Participants seek information from their parents, communities, and religious leaders, but are particular with who they consider credible and reliable; if the person providing the information follows a similar lifestyle to the participants, they are more likely to hold cognitive authority. Four different themes emerged from the study. The first is "religious focus" where many participants stated that religion is rather static whereas culture can evolve and change with time, location, and events. The second theme emerged is the reliance on family members for religious literacy given the close upbringing of Muslim extended family system. The third theme indicated that although information seeking behavior relied …
Date: August 2022
Creator: Khader, Malak M
System: The UNT Digital Library

Weight Initialization for Convolutional Neural Networks Using Unsupervised Machine Learning

The goal of this work is to improve the robustness and generalization of deep learning models, using a similar approach to the unsupervised "innate learning" strategy in visual development. A series of research studies are presented to demonstrate how an unsupervised machine learning efficient coding approach can create filters similar to the receptive fields of the primary visual cortex (V1) in the brain, and these filters are capable of pretraining convolutional neural networks (CNNs) to enable faster training times and higher accuracy with less dependency on the source data. Independent component analysis (ICA) is used for unsupervised feature extraction as it has shown success in both applied machine learning and modeling biological neural receptive fields. This pretraining applies equally well to various forms of visual input, including natural color images, black and white, binocular, and video to drive the V1-like Gabor filters in the brain. For efficient processing of typical visual scenes, the filters that ICA produces are developed by encoding natural images. These filters are then used to initialize the kernels in the first layer of a CNN to train on the CIFAR-10 dataset to perform image classification. Results show that the ICA initialization for a custom made CNN …
Date: August 2022
Creator: Behpour, Sahar
System: The UNT Digital Library