Thesis (Ph. D.)--West Virginia University, 2009. / Title from document title page. Document formatted into pages; contains xii, 196 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 141-146).

Thesis (M.S.)--West Virginia University, 2010. / Title from document title page. Document formatted into pages; contains vii, 55 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 53-54).

Purpose: Substance use and weapon carrying among adolescents is a growing concern. The objective of this study is to investigate the association between adolescent substance use and weapon carrying using the 2013 Youth Risk Behavior Survey (YRBS). Methods: Analyses were conducted using the 2013 YRBS, a nationally representative dataset sampling public and private high school students throughout the United States (US). Data from a total of 148,282 US adolescents were used in the present study. Results: Two outcomes were assessed: weapon carrying within the past 30 days and weapon carrying on school property within the past 30 days. Among adolescents who carried a weapon, 77.3% were male, 62.7% were white, 28.5%% were in 9th grade, 33.8% used a tobacco product and 57.4% drank alcohol within the past 30 days, while 22.8% used a Schedule 1 drug and 14.0% used a Schedule 2 drug during their lifetime. Among adolescents who carried a weapon on school property, 74.4% were male, 55.1% were white, 26.5% were in 11th grade, 40.1% used a tobacco product and 61.9% drank alcohol within the past 30 days, while 32.1% used a Schedule 1 drug and 26.9% used a Schedule 2 drug during their lifetime. For the multivariable model predicting adolescent weapon carrying, tobacco use (adjusted odds ratio (AOR) = 2.31, 95% CI: 2.06, 2.59), alcohol use (AOR = 2.04, 95% CI: 1.81, 2.29), and Schedule 2 drug use (AOR = 2.27, 95% CI: 1.83, 2.80) were significantly associated with increased risk of carrying a weapon, adjusting for all covariates in the model simultaneously. For the multivariable model predicting adolescent weapon carrying on school property, tobacco use (AOR = 2.33, 95% CI: 1.89, 2.86), alcohol use (AOR = 2.53, 95% CI: 2.02, 3.18), and Schedule 2 drug use (AOR = 2.58, 95% CI: 1.94, 3.43) were significantly associated with increased risk of carrying a weapon on school property, adjusting for all covariates in the model. Raw counts and weighted frequencies are reported. Conclusions: Statistically significant associations between adolescent substance use and weapon carrying were found, suggesting that adolescent substance use is associated with increased weapon carrying behavior, both off and on school property. Future weapon carrying prevention efforts should target not only adolescents who are high risk for weapon carrying, but also those who are at risk for misusing substances.

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Thesis (M. Phil.)--University of Hong Kong, 2007. / Title proper from title frame. Also available in printed format.

Proof-carrying code is an application of software verification techniques to the problem of ensuring the safety of mobile code. However, previous proof-carrying code systems have assumed that mobile code will faithfully execute the instructions of the program. Realistic implementations of computing systems are susceptible to probabilistic behaviours that can alter the execution of a program in ways that can result in corruption or security breaches. We investigate the use of a probabilistic bytecode language to model deterministic programs that are executed on probabilistic computing systems. To model probabilistic safety properties, a probabilistic logic is adapted to out bytecode instruction language, and soundness is proven. A sketch of a completeness proof of the logic is also shown.

Proof-carrying code is an application of software verification techniques to the problem of ensuring the safety of mobile code. However, previous proof-carrying code systems have assumed that mobile code will faithfully execute the instructions of the program. Realistic implementations of computing systems are susceptible to probabilistic behaviours that can alter the execution of a program in ways that can result in corruption or security breaches. We investigate the use of a probabilistic bytecode language to model deterministic programs that are executed on probabilistic computing systems. To model probabilistic safety properties, a probabilistic logic is adapted to out bytecode instruction language, and soundness is proven. A sketch of a completeness proof of the logic is also shown.

Thesis (MHSc--Health Science) -- AUT University, 2008. / Includes bibliographical references. Also held in print (185 leaves : ill. ; 30 cm.) in the Archive at the City Campus (T 615.8515 MCK)

Thesis, PlanB (M.S.)--University of Wisconsin--Stout, 2006. / Includes bibliographical references.