The topic of National Innovation System (NIS) is gradually emphasized. The NIS includes four compositions. They are government, industry, university and public research organization. The knowledge flow is transmitted among the four compositions through innovation policy. Thus, many countries have begun to develop NIS. The NIS will raise the economic growth rate, and promote the competitiveness of industry. Consequently, the study of NIS becomes very popular. OECD (Organization for Economic Cooperation and Development) build particular NIS structures to explain the difference between members, and try to find the key successful way to achieve national innovative goals. In the Asia, the Taiwan, China, Japan and South Korea show high relationship in the politics and economics. Japan and South are high-developing countries, and their innovation activities are very successful in the world, especially in those of technology industry. Additionally, China has abundant natural resources to help them develop technology industries. For above reasons, we elect these countries to be studied, and we try to find the essential factors of successful NIS. This study includes two research issues. We first collect the secondary data to explain different NIS structure among four countries. Then, we use Stepwise Regression Analysis to evaluate the performance of innovation. Finally we use the Pearson Correlation Analysis to analyze relationship between NIS performance and semiconductor industry development. The results of this study include: (1) R&D expenditure is the most important factor to influence the performance of national innovation; (2) Expenditure on basic research is an important factor to influence the output of innovation; (3) national innovation and industry development shows high relationship; and (4) the ranking of national innovation performance is not totally the same as that of industry development. Based on these findings, we will provide some important policy suggestions for innovation activities in Taiwan.

Reproduction de : Thèse de doctorat : Traitement de l'image et mathématiques appliquées : Toulouse, INPT : 2007. / Titre provenant de l'écran-titre. Bibliogr. 115 réf.

The effect of a single genetic mutation can vary greatly between different types of cells. The mutated gene may not be expressed in one tissue but may cause a devastating loss of function in another. To learn about disease mechanisms and generate novel therapies, genetic disorders must be studied in the types of cells where the mutations are most deleterious. Recently, scientists have begun manipulating cellular identity to create the cell types most affected by various genetic diseases. This dissertation describes the experience of generating reprogramming models for three genetic disorders: Ring 14 syndrome, Pearson syndrome, and Fanconi anemia.

No description available.

No description available.

No description available.

Ellis and Bheki, the KwaZulu-Natal theatre duo of Ellis Pearson and Bheki Mkhwane (hereafter Mkhwane and Pearson), define their theatre as 'Theatre of the Imagination,' a hybrid (Hauptfleisch 1997: 49) of African and European performance styles. / Thesis (M.A.)-University of KwaZulu-Natal, Pietermaritzburg, 2008.

This thesis uses archetypal theory as explained by Carol Pearson in The Hero Within: Six Archetypes We Live By to illustrate the heroic journey undertaken by the protagonist in Edna St. Vincent Millay's poem "Renascence." Feminist archetypal theory is a useful lens for gaining the reader access to the underlying paradigms of struggle experienced by the female literary character because it exposes the parallels that exist in separate female experiences. By applying Pearson's theory to Millay's work, readers are able to elucidate more clearly the methods used by the poet to create commonality and continuity with her female audience. Throughout the poem, the protagonist hero recursively circles through the Innocent, Orphan, Martyr, Wanderer, Warrior, and Magician phases. This essay utilizes a close reading strategy to illustrate its argument and provide evidence to its conclusions.

We consider the problem of extracting a specific feature from a noisy signal generated by a multi-channels Remote Field Eddy Current Sensor. The sensor is installed on a mobile robot whose mission is the detection of anomalous regions in metal pipelines. Given the presence of noise that characterizes the data series, anomaly signals could be masked by noise and therefore difficult to identify in some instances. In order to enhance signal peaks that potentially identify anomalies we consider an entropy filter built on a-posteriori probability density functions associated with data series. Thresholds based on the Neyman-Pearson criterion for hypothesis testing are derived. The algorithmic tool is applied to the analysis of data from a portion of pipeline with a set of anomalies introduced at predetermined locations. Critical areas identifying anomalies capture the set of damaged locations, demonstrating the effectiveness of the filter in detection with Remote Field Eddy Current Sensor.

Thesis (Ph.D.)--University of Tulsa, 1993. / Includes bibliographical references (leaves 120-129).