Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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Description
Depression, anxiety, and suicidal thoughts or actions are on the rise in adolescents (National Institute of Mental Health, 2015; Bridge, Asti, & Horowitz, 2015). Parents, school administrators, and therapists are searching for resiliency factors with in at-risk groups to aid students in need. In previous work, Luthar and Zigler (1992) reported that intelligent youth are more resilient than less intelligent youth under low stress conditions but they lose their advantage under high stress conditions. This study examined whether intelligence (reflected in grade point average; GPA) and maladaptive (internalizing and externalizing symptoms) behaviors are negatively related in adolescents, and tested whether level of stress, reflected in emotion regulation and friendship quality, moderated that association. It also probed whether the relationships differ by gender. Sixth-graders (N=506) were recruited with active parental consent from three middle schools. Adolescents completed self-report questionnaires Regarding demo graphics, maladaptive behaviors, emotion regulation, and friendship quality, and GPA data were collected from the school. Regression analyses found that GPA was negatively related to externalizing symptoms. Girls with poor friendship communication report significantly higher maladaptive behaviors. This relation was more pronounced for girls with high GPAs, as predicted. Results support the theory that intelligent female adolescents are more reactive under adverse circumstances. Future efforts should follow students through middle school into high school to evaluate whether friendships remain important to adjustment, hold for boys as well as girls, and have implications for relationship interventions.
ContributorsGonzales, Ashlyn Carol (Author) / Luthar, Suniya (Thesis director) / Davis, Mary (Committee member) / Infurna, Frank (Committee member) / Department of Psychology (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Constant false alarm rate is one of the essential algorithms in a RADAR detection system. It allows the RADAR system to dynamically set thresholds based on the data power level to distinguish targets with interfering noise and clutters.
To have a better acknowledgment of constant false alarm rate approaches performance, three clutter models, Gamma, Weibull, and Log-normal, have been introduced to evaluate the detection's capability of each constant false alarm rate algorithm.
The order statistical constant false alarm rate approach outperforms other conventional constant false alarm rate methods, especially in clutter evolved environments. However, this method requires high power consumption due to repeat sorting.
In the automotive RADAR system, the computational complexity of algorithms is essential because this system is in real-time. Therefore, the algorithms must be fast and efficient to ensure low power consumption and processing time.
The reduced computational complexity implementations of cell-averaging and order statistic constant false alarm rate were explored. Their big O and processing time has been reduced.
To have a better acknowledgment of constant false alarm rate approaches performance, three clutter models, Gamma, Weibull, and Log-normal, have been introduced to evaluate the detection's capability of each constant false alarm rate algorithm.
The order statistical constant false alarm rate approach outperforms other conventional constant false alarm rate methods, especially in clutter evolved environments. However, this method requires high power consumption due to repeat sorting.
In the automotive RADAR system, the computational complexity of algorithms is essential because this system is in real-time. Therefore, the algorithms must be fast and efficient to ensure low power consumption and processing time.
The reduced computational complexity implementations of cell-averaging and order statistic constant false alarm rate were explored. Their big O and processing time has been reduced.
ContributorsChu, Huiwen (Author) / Bliss, Daniel W. (Thesis advisor) / Alkhateeb, Ahmed (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2020