<p>Contemporary algorithms employed for reconstruction of 3D volumes from helical cone beam projections are so called non-exact algorithms. This means that the reconstructed volumes contain artifacts irrespective of the detector resolution and number of projection angles employed in the process. In this thesis, three iterative schemes for suppression of these so called cone artifacts are investigated.</p><p>The first scheme, iterative weighted filtered backprojection (IWFBP), is based on iterative application of a non-exact algorithm. For this method, artifact reduction, as well as spatial resolution and noise properties are measured. During the first five iterations, cone artifacts are clearly reduced. As a side effect, spatial resolution and noise are increased. To avoid this side effect and improve the convergence properties, a regularization procedure is proposed and evaluated.</p><p>In order to reduce the cost of the IWBP scheme, a second scheme is created by combining IWFBP with the so called ordered subsets technique, which we call OSIWFBP. This method divides the projection data set into subsets, and operates sequentially on each of these in a certain order, hence the name “ordered subsets”. We investigate two different ordering schemes and number of subsets, as well as the possibility to accelerate cone artifact suppression. The main conclusion is that the ordered subsets technique indeed reduces the number of iterations needed, but that it suffers from the drawback of noise amplification.</p><p>The third scheme starts by dividing input data into high- and low-frequency data, followed by non-iterative reconstruction of the high-frequency part and IWFBP reconstruction of the low-frequency part. This could open for acceleration by reduction of data in the iterative part. The results show that a suppression of artifacts similar to that of the IWFBP method can be obtained, even if a significant part of high-frequency data is non-iteratively reconstructed.</p>

This thesis consists of two parts: a synthesis of the theory of categories enriched in a quantaloid; and a weakening of this theory for it to include semicategories describing ordered sheaves on a quantaloid. A synthesis of, and supplements to, results in the literature concerning the theory of categories enriched in a quantaloid Q (as particular case of categories enriched in a bicategory) is contained in the first chapters. This theory is built with Q-categories, functors and distributors, and contains such notions as, for example, adjoint functors, weighted colimits, presheaves, Kan extensions, Cauchy completions and Morita equivalence, and so on. The literature does not provide an overview of these matters, so it was necessary to provide one here. Then the necessary theory is developed to arrive at an elementary description of ``ordered sheaves on a quantaloid Q', henceforth referred to as Q-orders. As there is no ``topos of sheaves on a quantaloid', Q-orders cannot be defined as ordered objects in such a topos. Instead a description of Q-orders as categorical structures enriched in the quantaloid Q is proposed. The well-known ordered sheaves on a locale L (i.e.~ordered objects in the topos of sheaves on L) should of course be a particular example of the general theory, taking Q to be the (one-object suspension of) L. Then it turns out that the theory of Q-categories has to be weakened to include ``categories without units', i.e. Q-semicategories. But for Q-semicategories to admit a convenient distributor calculus, a ``regularity' condition has to be imposed. And for those regular Q-semicategories to admit a reasonable theory of Cauchy completions and Morita equivalence, the even stronger condition of ``total regularity' has to be imposed. The former notion has been studied before for semicategories enriched in a symmetric monoidal closed category; the latter notion is new, and is introduced via the intuitively clear idea of ``stability of objects'. The point is then that precisely the Cauchy complete totally regular Q-semicategories are the Q-orders; for a locale L they are indeed the ordered objects in the topos of sheaves on L. A (bi)equivalent description of those Q-orders can be given in terms of categories enriched in the split-idempotent completion of the quantaloid Q: a totally regular semicategory enriched in Q corresponds in a precise sense to a category enriched in the split-idempotent completion of Q. Applying this once more to a locale L instead of a quantaloid Q, these results thus deepen the work of the Louvain-la-Neuve school, and reconcile it with that of the Sydney school, on the description of (ordered) sheaves on a locale as enriched categorical structures. The extended introduction gives a compact yet intuitive presentation of the developments contained in the thesis.

Contemporary algorithms employed for reconstruction of 3D volumes from helical cone beam projections are so called non-exact algorithms. This means that the reconstructed volumes contain artifacts irrespective of the detector resolution and number of projection angles employed in the process. In this thesis, three iterative schemes for suppression of these so called cone artifacts are investigated. The first scheme, iterative weighted filtered backprojection (IWFBP), is based on iterative application of a non-exact algorithm. For this method, artifact reduction, as well as spatial resolution and noise properties are measured. During the first five iterations, cone artifacts are clearly reduced. As a side effect, spatial resolution and noise are increased. To avoid this side effect and improve the convergence properties, a regularization procedure is proposed and evaluated. In order to reduce the cost of the IWBP scheme, a second scheme is created by combining IWFBP with the so called ordered subsets technique, which we call OSIWFBP. This method divides the projection data set into subsets, and operates sequentially on each of these in a certain order, hence the name “ordered subsets”. We investigate two different ordering schemes and number of subsets, as well as the possibility to accelerate cone artifact suppression. The main conclusion is that the ordered subsets technique indeed reduces the number of iterations needed, but that it suffers from the drawback of noise amplification. The third scheme starts by dividing input data into high- and low-frequency data, followed by non-iterative reconstruction of the high-frequency part and IWFBP reconstruction of the low-frequency part. This could open for acceleration by reduction of data in the iterative part. The results show that a suppression of artifacts similar to that of the IWFBP method can be obtained, even if a significant part of high-frequency data is non-iteratively reconstructed.

臺灣和日本都面臨嚴重的高齡化問題，對於高齡化所導致的勞動力減少，最好的因應方式便是提升高齡者的勞動參與率，而日本的高齡者具有世界最高的勞動參與率，本研究藉由比較日本與臺灣的高齡者就業的影響因素，提出促進高齡者就業的方法，發現影響高齡者就業的因素可分為個人特質、經濟因素及家庭因素等。而日本樣本中本人外家庭收入和工作與否有顯著的正相關，而與子女同住及子女親族的奉養金則對高齡者就業的影響不顯著，相對於日本，子女對於臺灣高齡者就業有著顯著的影響，有子女奉養金的高齡者，就業的機會顯著的降低，若想提高高齡者就業，可以完善老人年金制度，讓臺灣的高齡者較不需依靠子女奉養，然而這卻也有可能因為財富效果反而造成就業率降低，最好的方法，無非是宣導高齡者就業的必要，改善社會對高齡者就業的偏見，並提供適宜高齡者就業的環境，如彈性的工時，輕鬆的工作等，並消除企業對年齡的歧視，如此才能活用高齡者的知識經驗，提高高齡者的就業率。

This thesis investigates the associations between crash outcomes, the existence and type of driver distraction as well as driver’s age. The crash outcomes considered in this thesis consist of the type of crash as well as the injury severity sustained by occupants involved in the crash. An ordered logit model was built to predict the likelihood of severe injuries and a multinomial model was developed to predict the likelihood that a driver will be involved in one of three common crash types: singular, angular, and rearend. In these models, various factors (e.g., weather, driver’s gender, and speeding) have been statistically controlled for, but the main focus was on the interaction of driver’s age and distraction type. The findings of this thesis have implications for policy making and prioritizing capabilities of distraction-related safety systems.

This thesis investigates the associations between crash outcomes, the existence and type of driver distraction as well as driver’s age. The crash outcomes considered in this thesis consist of the type of crash as well as the injury severity sustained by occupants involved in the crash. An ordered logit model was built to predict the likelihood of severe injuries and a multinomial model was developed to predict the likelihood that a driver will be involved in one of three common crash types: singular, angular, and rearend. In these models, various factors (e.g., weather, driver’s gender, and speeding) have been statistically controlled for, but the main focus was on the interaction of driver’s age and distraction type. The findings of this thesis have implications for policy making and prioritizing capabilities of distraction-related safety systems.

Semantic query optimization is an important issue in many contexts of databases including information integration, view maintenance and data warehousing and can substantially improve performance, especially in today's database systems which contain gigabytes of data. A crucial issue in semantic query optimization is query containment. Several papers have dealt with the problem of conjunctive query containment. In particular, some of the literature admits SQL like query languages with aggregate operations such as sum/count. Moreover, since real SQL requires a richer semantics than set semantics, there has been work on bag-semantics for SQL, essentially by introducing an interpreted column. One important technique for reasoning about query containment in the context of bag semantics is to translate the queries to alternatives using aggregate functions and assuming set semantics. Furthermore, in SQL, order by is the operator by which the results are sorted based on certain attributes and, clearly, ordering is an important issue in query optimization. As such, there has been work done in support of ordering based on the application of the domain. However, a final step is required in order to introduce a rich semantics in support. In this work, we integrate set and bag semantics to be able to reason about real SQL queries. We demonstrate an ordered bag semantics for SQL using a relational algebra with aggregates. We define a set algebra with various expressions of interest, then define syntax and semantics for bag algebra, and finally extend these definitions to ordered bags. This is done by adding a pair of additional interpreted columns to computed relations in which the first column is used in the standard fashion to capture duplicate tuples in query results, and the second adds an ordering priority to the output. We show that the relational algebra with aggregates can be used to compute these interpreted columns with sufficient flexibility to work as a semantics for standard SQL queries, which are allowed to include order by and duplicate preserving select clauses. The reduction of a workable ordered bag semantics for SQL to the relational algebra with aggregates - as we have developed it - can enable existing query containment theory to be applied in practical query containment.

Despite the recognized importance of the bond rating industry, little academic work has been done to investigate the determinants of the standards these firms employ to assign credit ratings to individual firms. There is an ongoing debate in the literature arguing whether the decline in the percentage of highly rated firms is because rating standards have become more stringent over time or whether the credit quality of firms in the economy has declined. We investigate this question in this dissertation. Our first contribution is to address several empirical problems in prior literature. This study uses a combination of structural models of default and econometric model of ratings to study the determinants of rating standards and, by doing so, overcome the earlier methodological shortcomings. Our second contribution is to test new theory which hypothesizes that the standards of a rating agency are conditional upon the distribution of default risk in the economy at the time. The results are robust no matter which structural models of default we employ. The evidence suggests the standards are relative to the default risk distribution and there has been a secular increase in the stringency in the assignment of ratings over time. A third way we extend the literature is by examining the accuracy of the assignment of ratings. Theoretical models suggest rating agencies have incentives to purposefully add noise to the assignment of ratings. We conduct an empirical analysis of the classification errors using receiver operating characteristic analysis. The results suggest that error rates have decreased at the extreme ends of the rating spectrum (AAA vs. AA and below; B and below vs. BB and above) over time while it has increased in the middle rating categories. This error rate is directly related to the distribution of default risk across firms at any point in time. These findings not only strengthen our result that standards are relative and time varying, but also suggest there is more noise in the assignment of ratings at exactly the time when there is more uncertainty regarding the credit risk of firms in the economy – i.e., during a credit crisis.

Semantic query optimization is an important issue in many contexts of databases including information integration, view maintenance and data warehousing and can substantially improve performance, especially in today's database systems which contain gigabytes of data. A crucial issue in semantic query optimization is query containment. Several papers have dealt with the problem of conjunctive query containment. In particular, some of the literature admits SQL like query languages with aggregate operations such as sum/count. Moreover, since real SQL requires a richer semantics than set semantics, there has been work on bag-semantics for SQL, essentially by introducing an interpreted column. One important technique for reasoning about query containment in the context of bag semantics is to translate the queries to alternatives using aggregate functions and assuming set semantics. Furthermore, in SQL, order by is the operator by which the results are sorted based on certain attributes and, clearly, ordering is an important issue in query optimization. As such, there has been work done in support of ordering based on the application of the domain. However, a final step is required in order to introduce a rich semantics in support. In this work, we integrate set and bag semantics to be able to reason about real SQL queries. We demonstrate an ordered bag semantics for SQL using a relational algebra with aggregates. We define a set algebra with various expressions of interest, then define syntax and semantics for bag algebra, and finally extend these definitions to ordered bags. This is done by adding a pair of additional interpreted columns to computed relations in which the first column is used in the standard fashion to capture duplicate tuples in query results, and the second adds an ordering priority to the output. We show that the relational algebra with aggregates can be used to compute these interpreted columns with sufficient flexibility to work as a semantics for standard SQL queries, which are allowed to include order by and duplicate preserving select clauses. The reduction of a workable ordered bag semantics for SQL to the relational algebra with aggregates - as we have developed it - can enable existing query containment theory to be applied in practical query containment.

The Printing Industry is undergoing a Digital Revolution . The importance of digital printing has been increasing substantially over the last decade. How has this development affected the paper selection of printing firms? Only paper suppliers who successfully anticipate the changing needs of the printing firms will be able to benefit from the industry trend. This paper employs a probability model to analyze a survey data set of 103 digital printing firms in the USA and Canada. The research idea is to link the firm s paper selection with the firm s characteristics in order to gain insights into the printing firm s paper purchase behavior and the overall industry structure. The first part of this work investigates the importance of certain paper aspects, such as price, runnability and print quality. Strikingly, a company s involvement in digital printing, measured by the percent of digital printers of the total number of printers in the firm, is a central determinant of the importance of all paper aspects analyzed. This finding underscores the tremendous importance of the printing firms transition to digital printing for the Paper Industry. Paper runnability is found to become more important the faster the firm grows and can be explained by the fact that more successful firms incur higher opportunity costs from downtime. Another key finding is that the importance of paper price is lower for firms who collaborate with their customer on the paper selection and are able to pass on cost increases in the paper price. The second part involves a more direct assessment of paper selection. Here, the firm s characteristics are utilized to explain the choice of coated versus uncoated paper for the printing job. The analysis shows that firms involved in sophisticated print services, such as Digital Asset Management or Variable Data Printing are more likely to use the high quality coated paper. Further it is found that the usage of coated paper increases with catalog printing whereas it decreases with book and manual printing.