<p>This thesis examines usage of English colour terms in context, based on an extensive computerised text corpus, the Bank of English. It describes the ways in which English colour terms may be used to refer to nuances outside their normal area of designation and to attributes outside the colour domain. Usage patterns are analysed on three different levels: with regard to the overall frequency of occurrences, nominal domains and individual tokens, respectively. </p><p>Cognitive linguistics supplies the theoretical framework employed in the analyses of the observed patterns. The study identifies three types of usage where colour terms refer to peripheral colour nuances or to concepts outside the colour domain: classifying, figurative and marked usage. </p><p>When a colour term has a classifying function, it can be used outside the normal area of designation. This usage is analysed as a type of reference-point construction where a term referring to a salient point in the colour domain is used to subcategorise an entity whose actual colour may be only a peripheral member of the category named by the colour term. An analysis of the OED and the Bank of English shows that this type of usage is primarily restricted to a few of the most salient basic terms. </p><p>This study points to the close affinities between classifying and figurative usage. Figurative expressions of colour terms frequently have a classifying function. I argue that figurative meanings are derived through two types of metonymy: +SALIENT ATTRIBUTE FOR OBJECT+ and +SALIENT CONCRETE ATTRIBUTE FOR SALIENT ABSTRACT ATTRIBUTE+. </p><p>Marked usage arises when specific colour terms are used in nominal domains where the specificity is not expected. This phenomenon is consequently confined to non-basic colour terms. </p><p>On the basis of the established patterns of usage and the frequency of occurrences, this thesis suggests that the colour category may be analysed as a radial category, with the basic colour terms forming the centre. </p>

This thesis examines usage of English colour terms in context, based on an extensive computerised text corpus, the Bank of English. It describes the ways in which English colour terms may be used to refer to nuances outside their normal area of designation and to attributes outside the colour domain. Usage patterns are analysed on three different levels: with regard to the overall frequency of occurrences, nominal domains and individual tokens, respectively. Cognitive linguistics supplies the theoretical framework employed in the analyses of the observed patterns. The study identifies three types of usage where colour terms refer to peripheral colour nuances or to concepts outside the colour domain: classifying, figurative and marked usage. When a colour term has a classifying function, it can be used outside the normal area of designation. This usage is analysed as a type of reference-point construction where a term referring to a salient point in the colour domain is used to subcategorise an entity whose actual colour may be only a peripheral member of the category named by the colour term. An analysis of the OED and the Bank of English shows that this type of usage is primarily restricted to a few of the most salient basic terms. This study points to the close affinities between classifying and figurative usage. Figurative expressions of colour terms frequently have a classifying function. I argue that figurative meanings are derived through two types of metonymy: +SALIENT ATTRIBUTE FOR OBJECT+ and +SALIENT CONCRETE ATTRIBUTE FOR SALIENT ABSTRACT ATTRIBUTE+. Marked usage arises when specific colour terms are used in nominal domains where the specificity is not expected. This phenomenon is consequently confined to non-basic colour terms. On the basis of the established patterns of usage and the frequency of occurrences, this thesis suggests that the colour category may be analysed as a radial category, with the basic colour terms forming the centre.

給定聯合分配，可以容易地導出對應的條件分配。反之，給定條件分配的資訊，是否能導出對應的聯合分配呢？例如根據O. Paul et al.（1963，1968）對造成心血管疾病因素之追蹤研究，可得出咖啡量、吸菸量及是否有心血管疾病三者間的條件機率模型資料，是否能找到對應的聯合機率模型，以便可以更深入地研究三者之關係，是一個重要的議題。在選定參考點下，Chen（2010）提出以勝算比法找條件密度函數相容的充要條件，以及在相容性成立時，如何求得聯合分配。在二維中，當兩正值條件機率矩陣不相容時，郭俊佑（2013）以幾何平均法修正勝算比矩陣，並導出近似聯合分配，同時利用幾何平均法之特性，提出最佳參考點之選擇法則。本研究以二維的勝算比法為基礎，探討三維離散的相容性問題，獲得下列幾項結果：一、證明了三個三維條件機率矩陣相容的充要條件就是兩兩相容。二、當三維條件機率矩陣不相容時，利用幾何平均法導出近似聯合分配。三、利用兩兩相容的充要條件，導出三維條件機率矩陣相容的充要條件，並證明該充要條件與Chen的結果一致。四、在幾何平均法下，提出最少點法，有效率地找出最佳參考點，以產生總誤差最小的近似聯合分配。五、設計出程式檢驗三維條件機率矩陣是否相容，並找出最佳參考點，同時比較最少點法與窮舉法之間效率的差異。 / Given a joint distribution, we can easily derive the corresponding fully conditional distributions. Conversely, given fully conditional distributions, can we find out the corresponding joint distribution? For example, according to a longitudinal study of coronary heart disease risk factors by O. Paul et al. (1963, 1968), we obtain conditional probability model data among coffee intake, the number of cigarettes smoked and whether he/she has coronary heart disease or not. Whether we can find out the corresponding joint distribution is an important issue as the joint distribution may be used to do further analyses. Chen (2010) used odds ratio method to find a necessary and sufficient condition for their compatibility and also gave the corresponding joint distribution for compatible situations. When two positive discrete conditional distributions in two dimensions are incompatible, Kuo (2013) used a geometric mean method to modify odds ratio matrices and derived an approximate joint distribution. Kuo also provided a rule to find the best reference point when the geometric mean method is used. In this research, based on odds ratio method in two dimensions, we discuss their compatibility problems and obtain the following results on three-dimensional discrete cases. Firstly, we prove that a necessary and sufficient condition for the compatibility of three conditional probability matrices in three dimensions is pairwise compatible. Secondly, we extend Kuo’s method on two-dimensional cases to derive three-dimensional approximate joint distributions for incompatible situations. Thirdly, we derive a necessary and sufficient condition for the compatibility of three conditional probability matrices in three dimensions in terms of pairwise compatibility and also prove that this condition is consistent with Chen’s results. Fourthly, we provide a minimum-points method to efficiently find the best reference point and yield an approximate joint distribution such that total error is the smallest. Fifthly, we design a computer program to run three-dimensional discrete conditional probability matrices problems for compatibility and also compare the efficiency between minimum-points method and exhausting method.

Es wurde eine programmunterstützte Methode für die Umsetzung des Toleranzmanagements entwickelt, welche die Bereiche Entwicklung, Technologie und Qualität in gemeinsame Verantwortung bringt. Dabei galt es, den Iterationsprozess der Lösungsfindung in verschiedenen Detaillierungsstufen mit wenigen Schleifen und im Streben nach kurzen Entwicklungszeiten, geringen Toleranzkosten, Qualitätsverlusten und Blindleistungen zu durchlaufen. Ein stimmiges Toleranzkonzept überzeugt durch toleranzgerechte Aufbaufolgen, robuste und funktionsnahe Referenzierungen, kompensatorische Verfahren sowie toleranzunempfindliche Beeinträchtigungen und Auswirkungen. Die Auslegung aller toleranzrelevanten Produktanforderungen und Prozessgegebenheiten wird in Form von Toleranzketten und Maßkatalogen automatisiert dokumentiert und mündet schließlich in bestätigten Kunden-Lieferanten-Vereinbarungen.

In preference-based Evolutionary Multi-objective Optimization (EMO), the decision maker is looking for a diverse, but locally focused non-dominated front in a preferred area of the objective space, as close as possible to the true Pareto-front. Since solutions found outside the area of interest are considered less important or even irrelevant, the optimization can focus its efforts on the preferred area and find the solutions that the decision maker is looking for more quickly, i.e., with fewer simulation runs. This is particularly important if the available time for optimization is limited, as is the case in many real-world applications. Although previous studies in using this kind of guided-search with preference information, for example, withthe R-NSGA-II algorithm, have shown positive results, only very few of them considered the stochastic outputs of simulated systems. In the literature, this phenomenon of stochastic evaluation functions is sometimes called noisy optimization. If an EMO algorithm is run without any countermeasure to noisy evaluation functions, the performance will deteriorate, compared to the case if the true mean objective values are known. While, in general, static resampling of solutions to reduce the uncertainty of all evaluated design solutions can allow EMO algorithms to avoid this problem, it will significantly increase the required simulation time/budget, as many samples will be wasted on candidate solutions which are inferior. In comparison, a Dynamic Resampling (DR) strategy can allow the exploration and exploitation trade-off to be optimized, since the required accuracy about objective values varies between solutions. In a dense, converged population, itis important to know the accurate objective values, whereas noisy objective values are less harmful when an algorithm is exploring the objective space, especially early in the optimization process. Therefore, a well-designed Dynamic Resampling strategy which resamples the solution carefully, according to the resampling need, can help an EMO algorithm achieve better results than a static resampling allocation. While there are abundant studies in Simulation-based Optimization that considered Dynamic Resampling, the survey done in this study has found that there is no related work that considered how combinations of Dynamic Resampling and preference-based guided search can further enhance the performance of EMO algorithms, especially if the problems under study involve computationally expensive evaluations, like production systems simulation. The aim of this thesis is therefore to study, design and then to compare new combinations of preference-based EMO algorithms with various DR strategies, in order to improve the solution quality found by simulation-based multi-objective optimization with stochastic outputs, under a limited function evaluation or simulation budget. Specifically, based on the advantages and flexibility offered by interactive, reference point-based approaches, studies of the performance enhancements of R-NSGA-II when augmented with various DR strategies, with increasing degrees of statistical sophistication, as well as several adaptive features in terms of optimization parameters, have been made. The research results have clearly shown that optimization results can be improved, if a hybrid DR strategy is used and adaptive algorithm parameters are chosen according to the noise level and problem complexity. In the case of a limited simulation budget, the results allow the conclusions that both decision maker preferences and DR should be used at the same time to achieve the best results in simulation-based multi-objective optimization. / Vid preferensbaserad evolutionär flermålsoptimering försöker beslutsfattaren hitta lösningar som är fokuserade kring ett valt preferensområde i målrymden och som ligger så nära den optimala Pareto-fronten som möjligt. Eftersom lösningar utanför preferensområdet anses som mindre intressanta, eller till och med oviktiga, kan optimeringen fokusera på den intressanta delen av målrymden och hitta relevanta lösningar snabbare, vilket betyder att färre lösningar behöver utvärderas. Detta är en stor fördel vid simuleringsbaserad flermålsoptimering med långa simuleringstider eftersom antalet olika konfigurationer som kan simuleras och utvärderas är mycket begränsat. Även tidigare studier som använt fokuserad flermålsoptimering styrd av användarpreferenser, t.ex. med algoritmen R-NSGA-II, har visat positiva resultat men enbart få av dessa har tagit hänsyn till det stokastiska beteendet hos de simulerade systemen. I litteraturen kallas optimering med stokastiska utvärderingsfunktioner ibland "noisy optimization". Om en optimeringsalgoritm inte tar hänsyn till att de utvärderade målvärdena är stokastiska kommer prestandan vara lägre jämfört med om optimeringsalgoritmen har tillgång till de verkliga målvärdena. Statisk upprepad utvärdering av lösningar med syftet att reducera osäkerheten hos alla evaluerade lösningar hjälper optimeringsalgoritmer att undvika problemet, men leder samtidigt till en betydande ökning av antalet nödvändiga simuleringar och därigenom en ökning av optimeringstiden. Detta är problematiskt eftersom det innebär att många simuleringar utförs i onödan på undermåliga lösningar, där exakta målvärden inte bidrar till att förbättra optimeringens resultat. Upprepad utvärdering reducerar ovissheten och hjälper till att förbättra optimeringen, men har också ett pris. Om flera simuleringar används för varje lösning så minskar antalet olika lösningar som kan simuleras och sökrymden kan inte utforskas lika mycket, givet att det totala antalet simuleringar är begränsat. Dynamisk upprepad utvärdering kan däremot effektivisera flermålsoptimeringens avvägning mellan utforskning och exploatering av sökrymden baserat på det faktum att den nödvändiga precisionen i målvärdena varierar mellan de olika lösningarna i målrymden. I en tät och konvergerad population av lösningar är det viktigt att känna till de exakta målvärdena, medan osäkra målvärden är mindre skadliga i ett tidigt stadium i optimeringsprocessen när algoritmen utforskar målrymden. En dynamisk strategi för upprepad utvärdering med en noggrann allokering av utvärderingarna kan därför uppnå bättre resultat än en allokering som är statisk. Trots att finns ett rikligt antal studier inom simuleringsbaserad optimering som använder sig av dynamisk upprepad utvärdering så har inga relaterade studier hittats som undersöker hur kombinationer av dynamisk upprepad utvärdering och preferensbaserad styrning kan förbättra prestandan hos algoritmer för flermålsoptimering ytterligare. Speciell avsaknad finns det av studier om optimering av problem med långa simuleringstider, som t.ex. simulering av produktionssystem. Avhandlingens mål är därför att studera, konstruera och jämföra nya kombinationer av preferensbaserade optimeringsalgoritmer och dynamiska strategier för upprepad utvärdering. Syftet är att förbättra resultatet av simuleringsbaserad flermålsoptimering som har stokastiska målvärden när antalet utvärderingar eller optimeringstiden är begränsade. Avhandlingen har speciellt fokuserat på att undersöka prestandahöjande åtgärder hos algoritmen R-NSGA-II i kombination med dynamisk upprepad utvärdering, baserad på fördelarna och flexibiliteten som interaktiva referenspunktbaserade algoritmer erbjuder. Exempel på förbättringsåtgärder är dynamiska algoritmer för upprepad utvärdering med förbättrad statistisk osäkerhetshantering och adaptiva optimeringsparametrar. Resultaten från avhandlingen visar tydligt att optimeringsresultaten kan förbättras om hybrida dynamiska algoritmer för upprepad utvärdering används och adaptiva optimeringsparametrar väljs beroende på osäkerhetsnivån och komplexiteten i optimeringsproblemet. För de fall där simuleringstiden är begränsad är slutsatsen från avhandlingen att både användarpreferenser och dynamisk upprepad utvärdering bör användas samtidigt för att uppnå de bästa resultaten i simuleringsbaserad flermålsoptimering.

Indiana University-Purdue University Indianapolis (IUPUI) / Osteogenesis imperfecta is a rare congenital disease commonly characterized by brittle bones caused by mutations in the genes encoding Type I collagen, the single most abundant protein produced by the body. The murine model (oim) exists as a natural mutation of this protein, converting its heterotrimeric structure of two Col1a1 molecules and a single Col1a2 molecule into homotrimers composed of only the former. This defect impacts bone mechanical integrity, greatly weakening their structure. Femurs from male wild type (WT), heterozygous (oim/+), and homozygous (oim/oim) mice, all at 12 weeks of age, were assessed using assays at multiple length scales with minimal sample processing to ensure a near-physiological state. Atomic force microscopy (AFM) demonstrated detectable differences in the organization of collagen at the nanometer scale that may partially attribute to alterations in material and structural behavior obtained through mechanical testing and reference point indentation (RPI). Changes in geometric and chemical structure through the use of µ-Computed Tomography and Raman spectroscopy respectively indicate a smaller, brittle phenotype caused by oim. Changes within the periodic D-spacing of collagen point towards a reduced mineral nucleation site, supported by reduced mineral crystallinity, resulting in altered material and structural behavior in oim/oim mice. Multi-scale analyses of this nature offer much in assessing how molecular changes can compound to create a degraded, brittle phenotype.

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Es wurde eine programmunterstützte Methode für die Umsetzung des Toleranzmanagements entwickelt, welche die Bereiche Entwicklung, Technologie und Qualität in gemeinsame Verantwortung bringt. Dabei galt es, den Iterationsprozess der Lösungsfindung in verschiedenen Detaillierungsstufen mit wenigen Schleifen und im Streben nach kurzen Entwicklungszeiten, geringen Toleranzkosten, Qualitätsverlusten und Blindleistungen zu durchlaufen. Ein stimmiges Toleranzkonzept überzeugt durch toleranzgerechte Aufbaufolgen, robuste und funktionsnahe Referenzierungen, kompensatorische Verfahren sowie toleranzunempfindliche Beeinträchtigungen und Auswirkungen. Die Auslegung aller toleranzrelevanten Produktanforderungen und Prozessgegebenheiten wird in Form von Toleranzketten und Maßkatalogen automatisiert dokumentiert und mündet schließlich in bestätigten Kunden-Lieferanten-Vereinbarungen.:1 Einleitung 2 Stand der Erkenntnisse 2.1 Grundlagen der Tolerierung 2.1.1 Anforderungen an Toleranzen 2.1.2 Tolerierung und Referenzierung 2.1.3 Modellierung von Abweichungen 2.1.4 Statistische Methoden und Kenngrößen 2.1.5 Toleranzkosten und Verlustfunktion 2.2 Toleranzmanagement 2.2.1 Teilgebiet des Qualitätsmanagements 2.2.2 Toleranzanalyse und -synthese 2.2.3 Erarbeitung des Toleranzkonzeptes 2.3 Produktgerechtes Toleranzmanagement 2.3.1 Produktqualität und Anforderungen 2.3.2 Modularität und Komplexität der Baugruppen 2.4 Entwicklungsintegriertes Toleranzmanagement 2.4.1 Phasen im Produktentstehungsprozess 2.4.2 Simultaneous Engineering 2.5 Fazit des Standes der Erkenntnisse 3 Toleranzmanagement im Automobilbau 3.1 Gliederung des Produkt- und Prozessmodells 3.2 Funktionsrelevante Anforderungen 3.2.1 Zielkatalog für die Außenhaut 3.2.2 Ermittlung der Akzeptanzgrenzen 3.3 Funktionsbeeinträchtigende Abweichungen 3.3.1 Abweichungen längs der Prozesskette 3.3.2 Abweichungen der Karosserie 3.3.3 Abweichungen der Anbauteile 3.3.4 Abweichungen in der Montage 3.3.5 Veränderungen vor Auslieferung 3.3.6 Veränderungen in der Nutzung 3.4 Potenziale für ein effektives Toleranzmanagement 4 Methoden des Toleranzmanagements 4.1 Der Problemlösungszyklus 4.2 Zielsetzung und Strukturierung 4.3 Funktionsbereiche und Qualitätsmerkmale 4.4 Baugruppen und Ausrichtkonzepte 4.5 Korrelation von Ursachen und Wirkungen 4.6 Toleranzketten und Produktstatus 4.7 Messpläne und Prozessstatus 4.8 Freigabe und Maßnahmen 4.9 Potenziale für ein effizientes Toleranzmanagement 5 Zielsetzung 6 Einsatz der Toleranz-Organisations-Matrix 6.1 Allgemeine Beschreibung 6.2 Bereiche und Detailierungsgrade 6.3 Bauteilkatalog und Zuständigkeiten 6.4 Konzepte und Anforderungen 6.5 Schnittlagenmodell und Referenzpunktsystem 6.6 Funktionsbeziehungen und Paarungselemente 6.7 Algorithmus der Toleranzanalyse und -synthese 6.8 Erzeugung von Maßkatalogen und Messplänen 6.9 Ermittlung der Abweichungen 6.10 Ergebnisse und Maßnahmen 6.11 Status und Historie 7 Nutzen der Toleranz-Organisations-Matrix 7.1 Gesamthaftes Toleranzmanagement 7.2 Effizientes Toleranzmanagement 7.3 Effektives Toleranzmanagement 7.4 Toleranzstrategien, -konzepte, -parameter 8 Entwicklungsintegriertes Toleranzmanagement 9 Kriterien für das Toleranzmanagement 10 Zusammenfassung und Ausblick