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A Sliding Window Based Voting Classifier for Activity Sensor Based User Identification
Get PDFIdentification is the core of any authentication protocol design as the purpose of the authentication is to verify the user’s identity. The efficient establishment and verification of identity remain a big challenge. Recently, biometrics-based identification algorithms gained popularity as a means of identifying individuals using their unique biological characteristics. In this thesis, we propose a novel and efficient identification framework, ActID, which can identify a user based on his/her hand motion while walking. ActID not only selects a set of high-quality features based on Optimal Feature Evaluation and Selection and Correlation-based Feature Selection algorithms but also includes a novel sliding window based voting classifier. Therefore, it achieves several important design goals for gait authentication based on resource-constrained devices, including lightweight and real-time classification, high identification accuracy, a minimum number of sensors, and a minimum amount of data collected. Performance evaluation shows that ActID is cost-effective and easily deployable, selects only a minimum number of 10 high-quality features, uses only accelerometer sensor and increases the cost efficiency of user identification, collects only a small amount of 10 seconds of activity data, satisfies real-time requirements, and achieves a high identification accuracy of 100% when applied to a 30 user dataset
An examination of the impact Career and Technical Education (CTE) programs have on high school graduation rates
No full textThe purpose of this study focuses on the effects of enrollment in Career and Technical Education (CTE) courses on high school graduation rates. The study utilized archival data from 16,953 high school students from the Drowsy Willow Independent School District (DWISD), a large suburban school district in southeast Texas. Archived transcript and demographic data were collected of each high school student enrolled in DWISD between 2010-2016. Chi-square Tests of Independence and Logistic Regression were used to evaluate the relationship between the students’ enrollment in CTE coursework and their probability for graduating high school. Additionally, 12 CTE educators were interviewed to determine their perceptions of how CTE coursework influence and affect students at-risk of dropping out of school.
The results of this study reveal that a significant relation exists between CTE enrollment and student dropout behavior. These findings offer new insight regarding the extent to which students should enroll in CTE coursework and as to how CTE educators can engage students at-risk of dropping ou
Factors that Impede the Enrollment of Black Students in Dual Credit Programs
No full textThe number of students enrolled in Dual Credit programs in the state of Texas continues to grow, however, there are disparities in Black student enrollment rates. The purpose of this study was to identify factors that impeded the enrollment of Black students in Dual Credit programs. This sequential mixed method study consisted of a quantitative survey that was administered to over 1000 Black students. In addition, nine Black students were individually interviewed to provided qualitative context. All survey participants were Black, high school graduates, 18 years or older, and currently enrolled in a Texas community college or university. The nine Black students interviewed were self-identified and indicated no participation in Dual Credit while in high school. According to the quantitative date, there were no significant findings between Black students who participated in Dual Credit and those who did not. The qualitative data captured the voices of Black students and identified factors that impeded the enrollment of Black students in Dual Credit
Classification of Positive and Negative Stimuli Using EEG Data Functional Connectivity and Machine Learning
Get PDFElectroencephalography (EEG) provides electrical measures of brain activity by monitoring voltage fluctuations of the collective neural activity in different parts on the cortex of the brain. Recently, there have been numerous applications of machine learning techniques to classify events or participants based on EEG data in the biomedical field. EEG data are rich in the sense that one can extract many features from the data. This makes feature selection and reduction an important step in EEG based classification. Feature selection and correlations between features for classification of EEG data typically depend on time-frequency characteristics of the EEG channels, which represent data from different parts of the brain cortex.
In this proposed work, we calculated functional connectivity (FC) between different EEG channels as our features for classification and applied it for classification of positive and negative visual stimuli. Previously, EEG data were collected from 12 participants (6 females and 6 males) while they were observing positive and negative images in a random order and the data were completely de-identified. After filtering of the noise in the data, we extracted FC features. From these FC features for each of the stimuli, we reduced the number of features using techniques which included correlation-based and principal components based methods. Once the features were selected, we implemented classification of positive vs. negative stimuli using classification techniques support vector machines, decision trees, random forests, k nearest neighbors, Gaussian process, Adaboost, quadratic discriminant analysis and logistic regression. We compared the classification accuracy results Support vector machine and Logistic regression provided the highest classification accuracy of whether a participant was seeing a positive or negative image, with accuracies of up to 71.9% and 71.4% for each of the participant, respectively
The Effects of Pimavanserin on Corticosterone Levels in a Rodent Model of Posttraumatic Stress Disorder
Get PDFPTSD can affect individuals that have experienced or witnessed a traumatic event, resulting in numerous physical and psychiatric symptoms. Selective serotonin reuptake inhibitors (SSRIs) and behavior therapy are often applied to treat PTSD symptoms. Although they are rarely administered, atypical antipsychotic medication has beneficial outcomes in those suffering from severe PTSD symptoms. This study aims to investigate the effects of the antipsychotic drug, pimavanserin, on corticosterone in a rodent model of post-traumatic stress disorder. This study also aims to provide further validity to an existing rodent model of PTSD and the procedures commonly utilized to induce stress. The current model of PTSD is a result of social isolation and a repeated stress exposure procedure, which subjected the rodents to predator odor while restrained. Forty-eight female Lewis rats were included in this blinded study. Rodents were randomized to one of four equally sized groups: control group (sham-stress), pimavanserin high dose stressed group, pimavanserin low dose stressed group, or no treatment stressed group. The effects of isolation and two stress inducing events were measured by comparing corticosterone levels between the control group and stressed groups, independent of treatment. Additionally, the influence of pimavanserin on corticosterone levels and potential dose-dependent effects were measured. It was hypothesized that corticosterone levels would increase after rodents were subjected to single housing. Additionally, it was predicted that a decrease in stress hormone levels in the blood samples collected following the stress exposure for all groups, except for the non-stressed control group, would be observed. It was also hypothesized that higher levels of corticosterone would be measured among subjects treated with the antipsychotic drug, pimavanserin. Finally, results revealing dose dependent effects were predicted. It was hypothesized that a higher level of corticosterone would be observed in those treated with a higher dose of pimavanserin. Significant differences were also observed within subjects in the corticosterone concentrations collected on Day 8, Day 21, and Day 47. Specifically, stress hormone levels collected on Day 21 differed significantly from levels obtained on Day 8 and Day 47. These findings suggest a temporary effect of social isolation on stress response. Significant differences were observed between groups in corticosterone concentrations in the blood samples collected on Day 55, 24 days after stress exposure. These findings indicate a dose-dependent effect, as subjects that received the higher dose of pimavanserin produced the lowest corticosterone levels.
Outcomes of this study will expand existing literature regarding the use of antipsychotics to treat PTSD symptoms and measures commonly utilized to induce stress in rodents
Second-generation immigrant graduate students' persistence toward graduation: Factors affecting their ability to complete a program of study
No full textThe demand for more knowledgeable employees has created a renewed focus in the United States to produce more postgraduate degreed individuals. Researchers have noted that a master’s degree could become the new bachelor’s degree as employers are requiring more advanced skills and abilities (Wendler et al., 2010). While there are several researchers (Collie et al., 2017; Deming & Dynarski, 2009; Lee et al., 2013) who have studied the persistence of undergraduate students, few researchers (e.g., Harde & Hackett, 2015) have completed a systematic research of graduate student supports. Graduate students have encountered numerous obstacles that have impeded their ability to complete their degree programs, less is known about additional obstacles immigrant students have faced when pursuing a graduate degree. Terrazas-Carrillo et al., (2017) found that “graduate student attrition has been referred to as the hidden crisis in higher education” (p. 61). Some of the issues that graduate students faced included lack of employer support (Wyland et al., 2015), lack of family support (Strom & Savage, 2014), and lack of university personnel supports (Okahana et al., 2018; O’Keeffe, 2013). The Completion and Attrition in STEM Master’s Programs: Pilot Study Findings survey (Council of Graduate Schools, 2017) was used and adapted for the purposes of this research
The Role of Remorse and Gender in Juror Decision Making for Capital Punishment
No full textWhile defendants are expected to show remorse for committing a crime (Sundby, 1998) and remorse is particularly important during the sentencing phase of a trial (Zhong et al., 2014), there is little systematic evidence to understand how jurors evaluate a defendant’s remorsefulness. Previous research on capital cases has focused almost exclusively on male defendants despite the fact that these crimes are committed by females as well. In the present study, level of remorse and defendant gender are examined in the sentencing phase of a capital murder trial. Participants read trial scenarios with defendant gender and remorse manipulated and then responded to a questionnaire designed to identify what role remorse played in their sentencing decision. Participants were more likely to assign a life sentence than the death penalty to defendants who demonstrated sincere remorse. The study also examined interactions between juror and defendant gender. There was a significant three-way effect of remorse level, sentencing, and participant gender, but these effects were only present for women participants. Additional effects of participant gender and remorse level were found for perceptions of the defendant. The present study supports the importance of defendant remorsefulness and a consideration of juror gender on the perceptions of defendants and sentencing decisions
Exploratory Analysis of Delay Discounting and Cognitive-Affective Regulation Measures in Cocaine Users
Get PDFResearch investigating addiction across populations suggests that identifying high-risk behavioral factors within a population may help identify key areas to target during treatment. Delay discounting, the measure of the preference for smaller, sooner rewards over larger rewards after a longer delay, has been shown to be a robust predictor of relapse risk, treatment compliance, and abstinence duration in addicted populations. Previous work suggests that individuals exhibiting higher rates of delayed reward discounting are more likely to develop a substance use disorder, and that the continual abuse of substances perpetuates an increase in impulsive decision-making over time, contributing to the cyclic nature of chronic substance use. In addition to behavioral measures, self-report measures assessing high-risk cognitive-affective factors (e.g., distress tolerance, emotion regulation) have also proven to be robust predictors of treatment outcomes. Given the observed correspondence between heightened impulsivity, cognitive-affective regulation, and substance abuse, understanding variables that may interact with impulsive behavior is a promising path towards more effective treatment outcomes. This project had three aims: to compare delay discounting modelling techniques (AUC, Mazur’s k, AUClog, and log-k) in a cocaine-abusing sample, to analyze three cognitive-affective regulation measures (AIS, DERS, and DTS) for potential latent factors, and to assess the relationships between these cognitive-affective measures and delay discounting models. Results of the delay discounting modelling comparing AUC, AUClog, Mazur’s k, and log-k methods to AIS, DTS, and DERS scores yielded no significant relationships, though non-significant trends were consistent with previous literature. An exploratory factor analysis yielded a final three factor solution, with factors corresponding to the DTS, the DERS, and the AIS, respectively. Though delay discounting models and cognitive-affective regulation have been linked to similar treatment outcomes, an exploratory analysis investigating the relationship between these variables suggests no direct relationship between delay discounting and emotion regulation, distress tolerance, or psychological avoidance/inflexibility
Using Behavioral Skills Training to Train Police Officers to Respond to Individuals with Autism
Get PDFResearch indicates that individuals with autism may be more likely to encounter law enforcement due to the various unusual behaviors associated with autism (e.g., stereotypy) (Osborn, 2008). Although individuals with autism are more likely to encounter law enforcement, little research has been conducted on teaching police officers strategies to gain compliance during these encounters. Additionally, no study has evaluated police officers' performance during these situations. This study addressed these gaps in the literature by assessing the effectiveness of a brief, hands-on training for teaching officers how to gain compliance when encountering individuals with autism. In Experiment 1, behavioral skill training (BST) was used to train three police officers how to deliver prompts and reinforcement for compliance and how to respond to problem behavior. In Experiment 2, two training models, lecture only and brief BST, were evaluated with twenty-four police cadets. BST increased correct responding for all participants. These results suggest that BST is an efficient and effective model for training law enforcement in these methods
Instructional Leader Practices: Are They Related to Student Achievement
Get PDFThe purpose of this sequential mixed method study was to examine the relationship between the four core leadership principles and student achievement in schools in a small region in Texas. This study included a review of data collected from the School Leadership Survey from a purposeful sample of school principals from schools serviced in the Region V Service Center Area. A purposeful sample of principals from elementary, middle and high schools were also interviewed in an attempt to provide a more in-depth understanding of the potential influence of principal behaviors on student achievement. Quantitative data were analyzed using frequencies, percentages, and Pearson's product-moment correlations (r), while and inductive coding process was used to analyze the collected qualitative data. Quantitative analysis demonstrated that there was not a statistical mean difference between the four core principles and student achievement, except with managing the instructional program. The qualitative analysis supported the evidence from current research related to the notion that a positive relationship exist between the two constructs