Doctor of Philosophy

dissertationDisease-specific ontologies, designed to structure and represent the medical knowledge about disease etiology, diagnosis, treatment, and prognosis, are essential for many advanced applications, such as predictive modeling, cohort identification, and clinical decision support. However, manually building disease-specific ontologies is very labor-intensive, especially in the process of knowledge acquisition. On the other hand, medical knowledge has been documented in a variety of biomedical knowledge resources, such as textbook, clinical guidelines, research articles, and clinical data repositories, which offers a great opportunity for an automated knowledge acquisition. In this dissertation, we aim to facilitate the large-scale development of disease-specific ontologies through automated extraction of disease-specific vocabularies from existing biomedical knowledge resources. Three separate studies presented in this dissertation explored both manual and automated vocabulary extraction. The first study addresses the question of whether disease-specific reference vocabularies derived from manual concept acquisition can achieve a near-saturated coverage (or near the greatest possible amount of disease-pertinent concepts) by using a small number of literature sources. Using a general-purpose, manual acquisition approach we developed, this study concludes that a small number of expert-curated biomedical literature resources can prove sufficient for acquiring near-saturated disease-specific vocabularies. The second and third studies introduce automated techniques for extracting disease-specific vocabularies from both MEDLINE citations (title and abstract) and a clinical data repository. In the second study, we developed and assessed a pipeline-based system which extracts disease-specific treatments from PubMed citations. The system has achieved a mean precision of 0.8 for the top 100 extracted treatment concepts. In the third study, we applied classification models to reduce irrelevant disease-concepts associations extracted from MEDLINE citations and electronic medical records. This study suggested the combination of measures of relevance from disparate sources to improve the identification of true-relevant concepts through classification and also demonstrated the generalizability of the studied classification model to new diseases. With the studies, we concluded that existing biomedical knowledge resources are valuable sources for extracting disease-concept associations, from which classification based on statistical measures of relevance could assist a semi-automated generation of disease-specific vocabularies

China’s shifting role and motives in East Asian economic integration : a Chinese perspective on China-ASEAN economic cooperation in the 1990s and 2000s

East Asian regionalism substantially intensified after the 1997-8 Asian Financial Crisis (AFC), which was a significant case and an increasingly emerging issue of new regionalism after the Cold War ended in the early 1990s. In contrast with business-led regionalization, government-led regionalism was the key way leading to East Asian economic integration, of which bilateral governmental economic cooperation between China and ASEAN was the substance. The thesis explores China’s shifting role in economic cooperation with ASEAN before and after its WTO accession in 2001 within a theoretical framework of complex interdependence. In the bilateral interdependent economic relations, China became a mutual complementary partner of ASEAN from a natural competitor; and became a foreign direct investment (FDI) source of ASEAN from a net recipient after the WTO accession. This laid a sound basis for China to be well placed as the leader in East Asian economic integration. The thesis investigates the motives that prompted China to shift its attitude towards economic cooperation with ASEAN (clearly illustrated by China’s initiative of the China-ASEAN Free Trade Area (CAFTA) proposal in 2001) from a Chinese perspective. China’s grand strategy, which highlighted the neighbours’ stability and prosperity in political sense and exploration of regional markets in neighbour countries in economic sense, was the radical motives. In addition, Beijing desired to diminish the two domestic problems: the disparity between East and West China and the gap between the urban and rural areas by enhancing economic cooperation with ASEAN. This, as the key motive, induced China’s shifting attitude towards economic cooperation with ASEAN and towards economic integration in East Asia. This thesis contributed to the second wave of regionalism studies after the 1997-8 AFC by examining the implications of China’s domestic politics on regionalism in East Asian case from a Chinese inward-looking perspective

Growth of Thin Oxidation-Resistive Crystalline Si Nanostructures on Graphene

We report the growth of Si nanostructures, either as thin films or nanoparticles, on graphene substrates. The Si nanostructures are shown to be single crystalline, air stable and oxidation resistive, as indicated by the observation of a single crystalline Si Raman mode at around 520 cm-1, a STM image of an ordered surface structure under ambient condition, and a Schottky junction with graphite. Ultra-thin silicon regions exhibit silicene-like behavior, including a Raman mode at around 550 cm-1, a triangular lattice structure in STM that has distinctly different lattice spacing from that of either graphene or thicker Si, and metallic conductivity of up to 500 times higher than that of graphite. This work suggests a bottom-up approach to forming a Si nanostructure array on a large scale patterned graphene substrate for fabricating nanoscale Si electronic devices

Impact of Channel Aging on Massive MIMO Vehicular Networks in Non-isotropic Scattering Scenarios

Massive multiple-input multiple-output (MIMO) relies on accurate channel estimation for precoding and receiving to achieve its claimed performance advantages. When serving vehicular users, the rapid channel aging effect greatly hinders its advantages, and a careful system design is required to ensure an efficient use of wireless resources. In this paper, we investigate this problem for the first time in a non-isotropic scattering scenario. The von Mises distribution is adopted for the angle of arrival (AoA), resulting in a tunable channel temporal correlation coefficient (TCC) model, which can adapt to different AoA spread conditions through the k parameter and incorporates the isotropic Jakes-Clarke model as a special case. The simulated results in a Manhattan grid-type multi-cell network clearly demonstrate the impact of channel aging on the uplink spectral efficiency (SE) performance and moreover, in order to maximize the area average SE, the size of the transmission block should be optimally selected according to some linear equations of k