This thesis introduces a new effective method in statistical modeling and probabilistic decision making problems. The method is based on maximizing the Shannon Logarithmic Entropy Function for information, subject to the given prior information to serve as constraints, to generate a probability distribution. The method is known as the Maximum Entropy Principle or "Jaynes Principle". Tribus used it earlier, but in a limited case, without general application to either statistical modeling or probablistic decision making. In this thesis, a new method which generalizes the above principle is introduced. This permits practical applications, some of which are illustrated. / Thesis / Master of Engineering (ME)

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<p>The number of speed-limiting paths in modern digital integrated circuits (ICs) is in the range of millions. Due to un-modelled electrical effects and process variations in advanced fabrication technologies, it is difficult for pre-silicon timing analysis tools to provide accurate delay estimates. Hence, programmable delay elements are commonly inserted in high-performance circuits in order to provide a tuning mechanism at the post-silicon phase. Due to the large number of such tuning elements, finding the appropriate configuration bits for each element mandates an automated approach.</p> <p>In this thesis we present three contributions to the field of digital IC design automation that leverage the presence of programmable delay tuning elements. These new automated approaches are geared toward three distinct objectives. The first one is to maximize the circuit performance using a scalable algorithmic framework. The second objective is to combat the lifetime performance degradation caused by circuit aging. The final objective is to improve the timing of the scan enable signal during the at-speed testing of digital ICs.</p> <p>As the programmable delay tuning elements will become prevalent in the future generations of digital ICs, the contributions from this thesis will help improve the design methodologies that are expected to evolve in order to address at runtime the timing problems introduced by the increased fabrication process variability.</p> / Doctor of Philosophy (PhD)

In clinical research, it is sometimes desirable to dichotomize a continuous variable so that the information expressed using a dichotomous variable is more straightforward for clinicians to interpret and communicate. The distribution of a continuous variable can differ between two populations defined by the case status. Under such a scenario, the dichotomization process can be based on distributions of the continuous variable in two distinct populations. The resulting dichotomous variable can be used as an endpoint in future studies. Even though dichotomization has not been extensively studied, dichotomization has been commonly carried out in clinical trials. We developed a methodology on dichotomization based on maximizing the correlation between the two populations and the dichotomous variable. We have investigated several commonly assumed distributions (e.g., normal, log-normal and gamma distribution) of the continuous variable for the two populations and developed a numerical algorithm for the proposed method to determine the optimal cutoff point. The two populations can differ in form and/or parameters. The proposed method of finding the optimal cutoff was also extended to adjust for covariates. In real world scenarios where the two samples from the two populations are not completely identified, we recommended using the EM method to first estimate the parameters associated with the two populations before applying the proposed method to find the optimal cutoff point. The performance of the proposed method with the numerical algorithm and the EM method has been studied for several theoretical distributions and using simulated data. These methods were also applied to a varicella vaccine example. / Statistics

Die vorliegende Arbeit untersucht den Zusammenhang zwischen Meditation und der Neigung zur Gewinnmaximierung. Sie baut auf Modellen auf, die Meditation mit Achtsamkeit und moralischem Verhalten in Verbindung bringen. In zwei getrennten Laborexperimenten mit 109 sowie 450 Teilnehmern und unterschiedlichen Forschungsdesigns ließ sie eine Managemententscheidung mit ethischer Dimension treffen. Die Teilnehmer meditierten und entschieden danach, wie viele Mitarbeiter sie in einer Krisensituation entlassen, um kurzfristig den Gewinn zu maximieren. Die Einschätzungen der Meditierenden wurden mit denen der Kontrollgruppen verglichen. Die Ergebnisse des ersten Experiments legen nahe, dass Teilnehmer, die sich für Meditation interessieren, bereits vor der Meditation eine geringere Neigung zur Gewinnmaximierung haben als die Teilnehmer der Kontrollgruppe. Die Ergebnisse des zweiten Experiments deuten auf ein Mediationsmodell mit einem Wirkmechanismus zwischen Meditation, Achtsamkeit und Gewinnmaximierung hin. Die statistische Auswertung legt nahe, dass die Meditationsübung signifikant die Neigung zur Gewinnmaximierung minderte, indem sie die Achtsamkeit der Teilnehmer erhöhte. Achtsamkeit war ein partieller Mediator. Damit scheint Meditation sowohl den Zustand der Achtsamkeit als auch das tatsächliche Entscheidungsverhalten zu beeinflussen. Interessanterweise trat dieser Effekt bereits nach einer Meditation von 13 Minuten ein. Ein achtsamer Umgang mit den eigenen Mitarbeitern und den Entscheidungen im Unternehmen könnte insgesamt wünschenswert sein.