Over the last decade there has been a worldwide increase in the use of retractable roofs for stadia. This increase has been based on the flexibility and better economic performance offered by venues featuring retractable roofs compared to those with traditional fixed roofs. With this increased interest an evolution in retractable roof systems has followed. This dissertation is concerned with the development of concepts for retractable roof systems. A review is carried out to establish the current state-of-the-art of retractable roof design. A second review of deployable structures is used to identify a suitable retractable structure for further development. The structure chosen is formed by a two-dimensional ring of pantographic bar elements interconnected through simple revolute hinges. A concept for retractable roofs is then proposed by covering the bar elements with rigid cover plates. To prevent the cover plates from inhibiting the motion of the structure a theorem governing the shape of these plate elements is developed through a geometrical study of the retractable mechanism. Applying the theorem it is found that retractable structures of any plan shape can be formed from plate elements only. To prove the concept a 1.3 meter diameter model is designed and built. To increase the structural efficiency of the proposed retractable roof concept it is investigated if the original plan shape can be adapted to a spherical surface. The investigation reveals that it is not possible to adapt the mechanism but the shape of the rigid cover plates can be adapted to a spherical surface. Three novel retractable mechanisms are then developed to allow opening and closing of a structure formed by such spherical plate elements. Two mechanisms are based on a spherical motion for the plate elements. It is shown that the spherical structure can be opened and closed by simply rotating the individual plates about fixed points. Hence a simple structure is proposed where each plate is rotated individually in a synchronous motion. To eliminate the need for mechanical synchronisation of the motion, a mechanism based on a reciprocal arrangement of the plates is developed. The plate elements are interconnected through sliding connections allowing them mutually to support each other, hence forming a self-supporting structure in which the motion of all plates is synchronised. To simplify the structure further, an investigation into whether the plate elements can be interconnected solely through simple revolute joints is carried out. This is not found to be possible for a spherical motion. However, a spatial mechanism is developed in which the plate elements are interconnected through bars and spherical joints. Geometrical optimisation of the motion path and connection points is used to eliminate the internal strains that occur in the initial design of this structure so a single degree-of-freedom mechanism is obtained. The research presented in this dissertation has hence led to the development of a series of novel concepts for retractable roof systems.

Polynomial continuation, a branch of numerical continuation, has been applied to several primary problems in kinematic geometry. The objective of the research presented in this document was to explore the possible extensions of the application of polynomial continuation, especially in the field of deployable structure design. The power of polynomial continuation as a design tool lies in its ability to find all solutions of a system of polynomial equations (even positive dimensional solution sets). A linkage design problem posed in polynomial form can be made to yield every possible feasible outcome, many of which may never otherwise have been found. Methods of polynomial continuation based design are illustrated here by way of various examples. In particular, the types of deployable structures which form planar rings, or frames, in their deployed configurations are used as design cases. Polynomial continuation is shown to be a powerful component of an equation-based design process. A polyhedral homotopy method, particularly suited to solving problems in kinematics, was synthesised from several researchers' published continuation techniques, and augmented with modern, freely available mathematical computing algorithms. Special adaptations were made in the areas of level-k subface identification, lifting value balancing, and path-following. Techniques of forming closure/compatibility equations by direct use of symmetry, or by use of transfer matrices to enforce loop closure, were developed as appropriate for each example. The geometry of a plane symmetric (rectangular) 6R foldable frame was examined and classified in terms of Denavit-Hartenberg Parameters. Its design parameters were then grouped into feasible and non-feasible regions, before continuation was used as a design tool; generating the design parameters required to build a foldable frame which meets certain configurational specifications. Two further deployable ring/frame classes were then used as design cases: (a) rings which form (planar) regular polygons when deployed, and (b) rings which are doubly plane symmetric and planar when deployed. The governing equations used in the continuation design process are based on symmetry compatibility and transfer matrices respectively. Finally, the 6, 7 and 8-link versions of N-loops were subjected to a witness set analysis, illustrating the way in which continuation can reveal the nature of the mobility of an unknown linkage. Key features of the results are that polynomial continuation was able to provide complete sets of feasible options to a number of practical design problems, and also to reveal the nature of the mobility of a real overconstrained linkage.

With widespread use of the Internet, data is often shared between organizations in B2B health care networks. Integrating data across all sources in a health care network would be useful to public health surveillance and provide a complete view of how the overall network is performing. Because of the lack of standardization for a common data model across organizations, matching identities between different locations in order to link and aggregate records is difficult. Moreover, privacy legislation controls the use of personal information, and health care data is very sensitive in nature so the protection of data privacy and prevention of personal health information leaks is more important than ever. Throughout the process of integrating data sets from different organizations, consent (explicitly or implicitly) and/or permission to use must be in place, data sets must be de-identified, and identity must be protected. Furthermore, one must ensure that combining data sets from different data sources into a single consolidated data set does not create data that may be potentially re-identified even when only summary data records are created. In this thesis, we propose new privacy preserving data integration protocols for public health surveillance, identify a set of privacy preserving data integration patterns, and propose a supporting framework that combines a methodology and architecture with which to implement these protocols in practice. Our work is validated with two real world case studies that were developed in partnership with two different public health surveillance organizations.

Electronic data has become the standard method of storing information in our modern age. Evolving from paper-based data to electronic data creates opportunities to share information between organizations in record speeds, especially when handling large data sets. However, sharing sensitive information creates requirements for electronic data exchange: privacy requires that the original data will not be revealed to unauthorized parties. In the healthcare sector in particular, there are two important use cases that require exchanging information in a privacy-preserving way. 1. Contract research organizations (CROs) need to verify the eligibility of a participant in a phase 1 clinical trial. One criterion is checking that an individual is not concurrently enrolled in a trial at another CRO. However, privacy laws and the maintenance of a private list of participants for competitive purposes prevent CROs from checking against that criterion. 2. A patient’s medical record is usually distributed amongst several healthcare organizations. To improve healthcare services, it is important to have a patient’s complete medical history: either to help diagnose an illness or to gather statistics for better disease control. However, patient medical files need to be confidential. Two healthcare organizations cannot link their large patient databases by disclosing identity revealing details (e.g., names or health card numbers). This thesis presents the development and evaluation of protocols capable of querying and linking datasets in a privacy-preserving manner: TRACK for checking concurrent enrolment in phase 1 clinical trials, and SHARE for linking two large datasets in terms of millions of (patient medical) records. These protocols are better than existing approaches in terms of the privacy protection level they offer (e.g., against dictionary and frequency attacks), of the reliance on trusted third parties, and of performance when performing blocking. These protocols were extensively validated in simulated scenarios similar to their real-world counterparts. The thesis presents novel identity representation schemes that offer strong privacy measures while being efficient for very large databases. These schemes may be used by other researchers to represent identity in different use cases. CROs may implement the protocols (and especially TRACK) in systems to check if an individual exists in another CRO’s dataset without revealing the identity of that individual. Two healthcare organizations may use a system based on this research (and especially the SHARE protocol) to discover their common patients while protecting the identities of the other patients.

The amount of knowledge increases rapidly due to the increasing number of available data sources. However, the autonomy of data sources and the resulting heterogeneity prevent comprehensive data analysis and applications. Data integration aims to overcome heterogeneity by unifying different data sources and enriching unstructured data. The enrichment of data consists of different subtasks, amongst other the annotation process. The annotation process links document phrases to terms of a standardized vocabulary. Annotated documents enable effective retrieval methods, comparability of different documents, and comprehensive data analysis, such as finding adversarial drug effects based on patient data. A vocabulary allows the comparability using standardized terms. An ontology can also represent a vocabulary, whereas concepts, relationships, and logical constraints additionally define an ontology. The annotation process is applicable in different domains. Nevertheless, there is a difference between generic and specialized domains according to the annotation process. This thesis emphasizes the differences between the domains and addresses the identified challenges. The majority of annotation approaches focuses on the evaluation of general domains, such as Wikipedia. This thesis evaluates the developed annotation approaches with case report forms that are medical documents for examining clinical trials. The natural language provides different challenges, such as similar meanings using different phrases. The proposed annotation method, AnnoMap, considers the fuzziness of natural language. A further challenge is the reuse of verified annotations. Existing annotations represent knowledge that can be reused for further annotation processes. AnnoMap consists of a reuse strategy that utilizes verified annotations to link new documents to appropriate concepts. Due to the broad spectrum of areas in the biomedical domain, different tools exist. The tools perform differently regarding a particular domain. This thesis proposes a combination approach to unify results from different tools. The method utilizes existing tool results to build a classification model that can classify new annotations as correct or incorrect. The results show that the reuse and the machine learning-based combination improve the annotation quality compared to existing approaches focussing on the biomedical domain. A further part of data integration is entity resolution to build unified knowledge bases from different data sources. A data source consists of a set of records characterized by attributes. The goal of entity resolution is to identify records representing the same real-world entity. Many methods focus on linking data sources consisting of records being characterized by attributes. Nevertheless, only a few methods can handle graph-structured knowledge bases or consider temporal aspects. The temporal aspects are essential to identify the same entities over different time intervals since these aspects underlie certain conditions. Moreover, records can be related to other records so that a small graph structure exists for each record. These small graphs can be linked to each other if they represent the same. This thesis proposes an entity resolution approach for census data consisting of person records for different time intervals. The approach also considers the graph structure of persons given by family relationships. For achieving qualitative results, current methods apply machine-learning techniques to classify record pairs as the same entity. The classification task used a model that is generated by training data. In this case, the training data is a set of record pairs that are labeled as a duplicate or not. Nevertheless, the generation of training data is a time-consuming task so that active learning techniques are relevant for reducing the number of training examples. The entity resolution method for temporal graph-structured data shows an improvement compared to previous collective entity resolution approaches. The developed active learning approach achieves comparable results to supervised learning methods and outperforms other limited budget active learning methods. Besides the entity resolution approach, the thesis introduces the concept of evolution operators for communities. These operators can express the dynamics of communities and individuals. For instance, we can formulate that two communities merged or split over time. Moreover, the operators allow observing the history of individuals. Overall, the presented annotation approaches generate qualitative annotations for medical forms. The annotations enable comprehensive analysis across different data sources as well as accurate queries. The proposed entity resolution approaches improve existing ones so that they contribute to the generation of qualitative knowledge graphs and data analysis tasks.

In an inquiry into national behavior, students of international relations treat national data as independent variables. Students of comparative politics treat them as dependent variables in an attempt to compute foreign policy outputs. There is reason to believe that international and comparative studies can be incorporated into a system of linkage politics. This study employs the framework of "linkage politics" of James N. Rosenau in an attempt to investigate the North Korean confrontation policy from 1953 to 1970. The basic assumption upon which this research operates is that the foreign policy of the North Korea has been a function of "fused linkages" between the nation's international environment and national conditions. "Fused linkage" is defined as a phenomenon by which certain national outputs and environmental inputs reciprocate in a continuous cycle. Thus the fused linkage case for North Korea's confrontation is defined as "circular confrontation." Based on Rosenau's proposed linkage framework, this study presents its own analytical framework. The major linkage groups are conceived of "exogenous" and "endogenous" conditions. Both of these conditions are divided into "constants" and "variables" and are treated as such. Each of these conditions was in turn analyzed with reference to relevant referents. Throughout the study particular attention is given to linkage processes between the two conditions.

京都大学 / 0048 / 新制・課程博士 / 博士(エネルギー科学) / 甲第22709号 / エネ博第406号 / 新制||エネ||78(附属図書館) / 京都大学大学院エネルギー科学研究科エネルギー基礎科学専攻 / (主査)教授 坂口 浩司, 教授 松田 一成, 教授 野平 俊之 / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DFAM

Hepatitis C Virus (HCV) is an infection that can have grave consequences when left untreated. Hepatitis C can be easily eradicated with direct acting antiviral therapy. People who inject drugs (PWID) and inmates are among those with the highest incidence of HCV. However, cure rates among this population remains low. This is, in part, related to an interruption in the HCV care cascade such that only 30% of PWID are linked to care and only 8% of those receive treatment. Inadequate screening and failure to be linked to HCV care remain the largest impediments to treatment success. There is limited research on barriers and facilitators to primary care, where screening may take place, and linkage to HCV care among PWID. Few studies have evaluated vulnerable populations such as those living in rural communities or inmates. The purpose of this dissertation was to develop a broader understanding of barriers and facilitators to healthcare utilization among PWID at the primary care and specialist levels (linkage to care). Three manuscripts addressed important gaps in knowledge. The first was a review of the literature to describe the state of science on linkage to care among PWID. All but one reviewed study recruited from countries with universal healthcare, urban areas, and opioid substitution facilities. The review of the literature revealed that little is known about the barriers/facilitators to linkage to HCV care faced by rural-dwelling PWID from countries without universal healthcare. The second manuscript is a study to determine whether predictors of linkage to care identified in urban-dwelling PWID from countries with universal healthcare predicted seeking HCV care among PWID living in rural Appalachia. Data were obtained from a subsample of 63 HCV positive PWID who recently used opioids, were between the ages of 18-35 years, and lived in one of five rural counties in Kentucky. Logistic regression revealed that recent injection drug use was the only predictor of seeking HCV care. However, remote use of opioid substitution therapy and no transportation issues approached clinical significance. Although not evaluated in our second manuscript, seeing a primary care provider (PCP) is associated with an increased likelihood of being linked to care and higher rates of screening/diagnosis. Among rural dwelling PWID, there are subpopulations that may face unique barriers to linkage to care. One sub-population that may be particularly vulnerable are female PWID who are incarcerated. Therefore, the purpose of the third study was to determine predictors of primary care use using data from 302 female inmates from rural Appalachia with a history of injecting drugs. Age, insurance issues, and health problems that interfere with responsibilities were predictors of PCP use. In this dissertation, I have addressed important gaps in the literature by determining barriers and facilitators to seeking HCV care and primary care use among PWID from rural Kentucky. Additional studies are needed using a larger sample of rural PWID to confirm our findings. In addition, further studies should evaluate system and provider level barriers to linkage to care and PCP use among rural PWID.

To determine accurately the number of serious injuries at EU level and to compare serious injury rates between different countries it is essential to use a common definition. In January 2013, the High Level Group on Road Safety established the definition of serious injuries as patients with an injury level of MAIS3+(Maximum Abbreviated Injury Scale). Whatever the method used for estimating the number or serious injuries, at some point it is always necessary to use hospital records. The aim of this paper is to understand the implications for (1) in/exclusion criteria applied to case selection and (2) a methodological approach for converting ICD (International Classification of Diseases/Injuries) to MAIS codes, when estimating the number of road traffic serious injuries from hospital data. A descriptive analysis with hospital data from Spain and the Netherlands was carried out to examine the effect of certain choices concerning in- and exclusion criteria based on codes of the ICD9-CM and ICD10. The main parameters explored were: deaths before and after 30 days, readmissions, and external injury causes. Additionally, an analysis was done to explore the impact of using different conversion tools to derive MAIS3 + using data from Austria, Belgium, France, Germany, Netherlands, and Spain. Recommendations are given regarding the in/exclusion criteria and when there is incomplete data to ascertain a road injury, weighting factors could be used to correct data deviations and make more real estimations.

Living in the age of "Big Data" is both a blessing and a curse. On he one hand, the raw data can be analysed and then used for weather redictions, user recommendations, targeted advertising and more. On he other hand, when data is aggregated from multiple sources, there is no guarantee that each source has stored the data in a standardized or even compatible format to what is required by the application. So there is a need to parse the available data and convert it to the desired form. Here is where the problems start to arise: often the correspondences are not quite so straightforward between data instances that belong to the same domain, but come from different sources. For example, in the film industry, information about movies (cast, characters, ratings etc.) can be found on numerous websites such as IMDb or Rotten Tomatoes. Finding and matching all the data referring to the same movie is a challenge. The aim of this project is to select the most efficient algorithm to correlate movie related information gathered from various websites automatically. We have implemented a flexible application that allows us to make the performance comparison of multiple algorithms based on machine learning techniques. According to our experimental results, a well chosen set of rules is on par with the results from a neural network, these two proving to be the most effective classifiers for records with movie information as content.