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Random-access memory (RAM) testing to detect unrestricted pattern-sensitive faults (PSFs) is impractical due to the size of the memory checking sequence required. A formal model for restricted PSFs in RAMs called adjacent-pattern interference faults (APIFs) is presented. A test algorithm capable of detecting APIFs in RAMs requiring a minimum number of memory operations is then developed.

The continuous improvement in the speed of digital components in conjunction with reduction of size has brought about a revolutionary age of microprocessors. Mathematical functions, which at one time could only be implemented by complex analog circuitry, can now be easily implemented via microprocessors and high density digital components. Principles of random number generation must be understood in order to implement pseudo-random algorithms in a digital random frequency generator (DRFG) design. Chapter 1 is a discussion of several types of random number algorithms which have been used in the past and outlines the deficiencies and advantages associated with each individual algorithm. In particular, problems such a cycling and maximum period deficiency are discussed. The discussions in Chapter 1 lead to the selection of a random number algorithm which can be used in a DRFG design. There are other characteristics which should be observed in the evaluation of acceptable random number algorithms. In Chapter 2 three tests are described which can be applied in order to test the algorithm for the well-known uniformity and independence criteria. These tests are implemented in a Fortran program which is used to evaluated the algorithm selected in Chapter 1. The random number generator evaluation program (RNGEP) listing is presented in Appendix B. The results of the tests applied to the DRFG random number algorithm are presented in Appendix C.

The purpose of this study was to examine the policies and practices of school districts with random drug testing policies in Pennsylvania. Specifically, this study intended to help administrators understand the phenomenon of drug testing as one available means of substance use prevention. In response to the rising drug use in our schools, random drug testing has increasingly become one of the many possible solutions being used to prevent student drug use. Currently, drug testing programs have been examined in the workplace and in intercollegiate athletics. However, very little evaluative research has been conducted on whether school districts are satisfied with their random drug testing policies and practices. The researcher anticipates making a significant contribution for school administrators as they strive to generate drug-free schools. The literature review presented in this research study examined the historical perspective of drug use in our nation and the events and perceptions that led up to the job-related drug testing that began in the military and workplace. The role values play in the policymaking process is discussed as well as any conflicts that arise due to diversity in those values. The costs and benefits of a random drug testing policy are also presented. For this study, random drug testing was examined in the context of a range of school districts within Pennsylvania that have implemented similar policies. Statistical data was utilized in order to collect and analyze superintendents' perspectives and satisfaction with random drug testing programs in order to increase the overall understanding of drug testing as a strategy for prevention. Parents, teachers, coaches, administrators and communities may benefit from this detailed study by way of the recommendations that will be provided for future school leaders and various stakeholders considering the adoption of a random drug testing policy. / Educational Administration

<p> Entropy of mixing for random mass defects is examined and equations for the phonon contribution are developed. The Green's function method used gives the entropy change due to the phonons at all temperatures, but for experimental comparison the high temperature region is used. There simple formulae obtain, but the mass defect is not sufficient to account for the observed entropy changes. This suggests that further work is necessary. </p> / Thesis / Master of Science (MSc)

Meta-analysis has been widely used in clinical research because it provides a useful tool for combining results from a series of trials addressing the same question. Two major approaches for study-to-study variation can be used in a meta-analysis: the fixed effects model which assumes that each study has the same true effect size, and the random effects model which assumes that the true effect size is a random variable that varies between studies. When there are covariates arising from the study, regression models can be used to explain the effects of these covariates on the between study variation in effect size. The purpose of this project is to draw some general conclusions about the statistical methods used in meta-analyses by re-examining several clinical examples which presented some problems. Four illustrative examples of recent meta-analyses were selected and re-examined. Both fixed effects and random effects models were used. In addition, regression models were used in two examples. Some general conclusions were made about the statistical aspects of meta-analysis from this project. The overall estimate of the fixed effects model tends to be overly influenced by large trials and may results in contradictory conclusions when extreme trials (small vs. large samples) are combined. Therefore, it is advocated that the weights allocated to each trial in any meta-analysis should be explicitly calculated and displayed. The random effects model takes a more balanced account of all studies and considers other unknown factors which may affect the effect size. Therefore, the random effects model and random effects regression model are more appropriate for these clinical data meta-analyses. / Thesis / Master of Science (MS)

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