The present thesis provides a model to monetarily aggregate procurement risks to support decision makers. A material flow oriented view forms the fundament of the model. The model is designed to aggregate delay, quality and cost related procurement risks considering their uncertainty. Procurement risks are aggregated to form a monetary risk distribution. Decision-makers can select procurement strategies that are adequate for their risk situation, depending on their affinity for risk to mitigate procurement risks.
The present thesis provides a model to monetarily aggregate procurement risks to support decision makers. A material flow oriented view forms the fundament of the model. The model is designed to aggregate delay, quality and cost related procurement risks considering their uncertainty. Procurement risks are aggregated to form a monetary risk distribution. Decision-makers can select procurement strategies that are adequate for their risk situation, depending on their affinity for risk to mitigate procurement risks.
Skepticism Films: Knowing and Doubting the World in Contemporary Cinema introduces skepticism films as updated configurations of skepticist thought experiments which exemplify the pervasiveness of philosophical ideas in popular culture. Philipp Schmerheim defends a pluralistic film-philosophical position according to which films can be, but need not be, expressions of philosophical thought in their own right. It critically investigates the influence of ideas of skepticism on film-philosophical theories and develops a typology of skepticism films by analyzing The Truman Show, Inception, The Matrix, Vanilla Sky, The Thirteenth Floor, Moon and other contemporary skepticism films. With its focus on skepticism as one of the most significant philosophical problems, Skepticism Films provides a better understanding of the dynamic interplay between film, theories of film and philosophy.
This thesis investigates the fracture of nearly incompressible hyperelastic media. It covers the different characteristics of bulk material failure under dilatational or distortional loads and develops a unified description of the corresponding failure surface. It proposes a coupled strain and energy failure criterion for the assessment of notch-induced crack nucleation and presents a weak-interface-model that allows for efficient stress, strain and failure analyses of hyperelastic adhesive lap joints. Theoretical concepts for the measurement of fracture properties of nonlinear elastic materials are provided. The methodology is developed using two exemplary hyperelastic silicones, DOWSIL 993 Structural Glazing Sealant and DOWSIL Transparent Structural Silicone Adhesive, and is validated using large sets of experiments of different loading conditions.
From ancient soothsayers and astrologists to today’s pollsters and economists, probability theory has long been used to predict the future on the basis of past and present knowledge. Mathematical Models of Information and Stochastic Systems shows that the amount of knowledge about a system plays an important role in the mathematical models used to foretell the future of the system. It explains how this known quantity of information is used to derive a system’s probabilistic properties. After an introduction, the book presents several basic principles that are employed in the remainder of the text to develop useful examples of probability theory. It examines both discrete and continuous distribution functions and random variables, followed by a chapter on the average values, correlations, and covariances of functions of variables as well as the probabilistic mathematical model of quantum mechanics. The author then explores the concepts of randomness and entropy and derives various discrete probabilities and continuous probability density functions from what is known about a particular stochastic system. The final chapters discuss information of discrete and continuous systems, time-dependent stochastic processes, data analysis, and chaotic systems and fractals. By building a range of probability distributions based on prior knowledge of the problem, this classroom-tested text illustrates how to predict the behavior of diverse systems. A solutions manual is available for qualifying instructors.
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