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.

Regional flood frequency techniques are commonly used to estimate flood quantiles when flood data are unavailable or the record length at an individual gauging station is insufficient for reliable analyses. These methods compensate for limited or unavailable data by pooling data from nearby gauged sites. This requires the delineation of hydrologically homogeneous regions in which the flood regime is sufficiently similar to allow the spatial transfer of information. Therefore, several Regional Flood Frequency Analysis (RFFA) methods are applied to the Ceyhan Basin. Dalyrmple (1960) Method is applied as a common RFFA method used in Turkey. Multivariate statistical techniques which are Stepwise and Nonlinear Regression Analysis are also applied to flood statistics and basin characteristics for gauging stations. Rainfall, Perimeter, Length of Main River, Circularity, Relative Relief, Basin Relief, Hmax, Hmin, Hmean and H&Delta / are the simple additional basin characteristics. Moreover, before the analysis started, stations are clustered according to their basin characteristics by using the combination of Ward&rsquo / s and k-means clustering techniques. At the end of the study, the results are compared considering the Root Mean Squared Errors, Nash-Sutcliffe Efficiency Index and % difference of results. Using additional basin characteristics and making an analysis with multivariate statistical techniques have positive effect for getting accurate results compared to Dalyrmple (1960) Method in Ceyhan Basin. Clustered region data give more accurate results than non-clustered region data. Comparison between clustered region and non-clustered region Q100/Q2.33 reduced variate values for whole region is 3.53, for cluster-2 it is 3.43 and for cluster-3 it is 3.65. This show that clustering has positive effect in the results. Nonlinear Regression Analysis with three clusters give less errors which are 29.54 RMSE and 0.735 Nash-Sutcliffe Index, when compared to other methods in Ceyhan Basin.

In order to achieve global carbon reduction targets, buildings must be designed to be energy efficient. Building performance simulation methods, together with sensitivity analysis and evolutionary optimization methods, can be used to generate design solution and performance information that can be used in identifying energy and cost efficient design solutions. Sensitivity analysis is used to identify the design variables that have the greatest impacts on the design objectives and constraints. Multi-objective evolutionary optimization is used to find a Pareto set of design solutions that optimize the conflicting design objectives while satisfying the design constraints; building design being an inherently multi-objective process. For instance, there is commonly a desire to minimise both the building energy demand and capital cost while maintaining thermal comfort. Sensitivity analysis has previously been coupled with a model-based optimization in order to reduce the computational effort of running a robust optimization and in order to provide an insight into the solution sensitivities in the neighbourhood of each optimum solution. However, there has been little research conducted to explore the extent to which the solutions found from a building design optimization can be used for a global or local sensitivity analysis, or the extent to which the local sensitivities differ from the global sensitivities. It has also been common for the sensitivity analysis to be conducted using continuous variables, whereas building optimization problems are more typically formulated using a mixture of discretized-continuous variables (with physical meaning) and categorical variables (without physical meaning). This thesis investigates three main questions; the form of global sensitivity analysis most appropriate for use with problems having mixed discretised-continuous and categorical variables; the extent to which samples taken from an optimization run can be used in a global sensitivity analysis, the optimization process causing these solutions to be biased; and the extent to which global and local sensitivities are different. The experiments conducted in this research are based on the mid-floor of a commercial office building having 5 zones, and which is located in Birmingham, UK. The optimization and sensitivity analysis problems are formulated with 16 design variables, including orientation, heating and cooling setpoints, window-to-wall ratios, start and stop time, and construction types. The design objectives are the minimisation of both energy demand and capital cost, with solution infeasibility being a function of occupant thermal comfort. It is concluded that a robust global sensitivity analysis can be achieved using stepwise regression with the use of bidirectional elimination, rank transformation of the variables and BIC (Bayesian information criterion). It is concluded that, when the optimization is based on a genetic algorithm, that solutions taken from the start of the optimization process can be reliably used in a global sensitivity analysis, and therefore, there is no need to generate a separate set of random samples for use in the sensitivity analysis. The extent to which the convergence of the variables during the optimization can be used as a proxy for the variable sensitivities has also been investigated. It is concluded that it is not possible to identify the relative importance of variables through the optimization, even though the most important variable exhibited fast and stable convergence. Finally, it is concluded that differences exist in the variable rankings resulting from the global and local sensitivity methods, although the top-ranked solutions from each approach tend to be the same. It also concluded that the sensitivity of the objectives and constraints to all variables is obtainable through a local sensitivity analysis, but that a global sensitivity analysis is only likely to identify the most important variables. The repeatability of these conclusions has been investigated and confirmed by applying the methods to the example design problem with the building being located in four different climates (Birmingham, UK; San Francisco, US; and Chicago, US).

Die studie vergelyk die prestasie van 'n koop-en-hou-strategie met die van 'n tydsberekeningstrategie binne die raamwerk van die arbitrasie-prysbepalingsteorie (APT) op die nywerheidsindeks van die Johannesburgse Aandelebeurs (JA). Die periode van die studie is oor twee tydperke, naamlik Januarie 1970 tot September 1987 en Januarie 1989 tot Junie 1997. Die langtermyntendens van die nywerheidsindeks en APT-faktore is bepaal deur die beste nie-reglynige model vir elke tydreeks te vind. Reglynige meervoudige stapsgewyse regressie-ontleding is gebruik om die bewegings van die nywerheidsindeks rondom die langtermyntendens te voorspel. Die sloeringsreekse van die langtermyntendensresidutelling van die APT-faktore en die sloeringsreekse van die eerste-ordeverskiltelling van die langtermyntendensresidutelling is as moontlike voorspellers gebruik. Gegrond hierop is beslissingslyne ontwik:kel wat gebruik is vir die implementering van 'n tydsberekeningstrategie. Die resultate van die studie is die volgende: • Waar die sloeringsreekse van die langtermyntendensresidutelling van die APTfaktore as moontlike voorspellers gebruik is, is die risiko-aangepaste opbrengskoers van 'n tydsberekeningstrategie 6, 41 persent en 0, 71 persent b6 die van 'n koop-en-hou-strategie vir tydperk een en twee onderskeidelik. • Waar die sloeringsreekse van die eerste-ordeverskiltelling van die langtermyntendensresidutelling van die APT-faktore as moontlike voorspellers gebruik is, is die risiko-aangepaste opbrengskoers van 'n tydsberekeningstrategie 10,40 persent en 1,04 persent b6 die van 'n koop-enhou- strategie vir tydperk een en twee onderskeidelik. Die belangrikste gevolgtrekking van die studie is dat die APT en 'n tydsberekeningstrategie teoreties en prakties versoenbaar is op die JA. Aanbevelings vir toekomstige navorsing is die volgende: ( 1) sistematiese risikofaktore, anders as makro-ekonomiese faktore, behoort identifiseer te word wat die voorspellingswaarde van die faktore in die tweede tydperk van die studie kan verhoog; (2) elke stap van die model wat ontwikkel is, behoort op elke indeks van die JA toegepas te word om die risiko-aangepaste opbrengskoers van 'n tydsberekeningstrategie toegepas op elkeen van die indekse met die van 'n koop-en-hou-strategie te vergelyk; en (3) die invloed van transaksiekoste en dividende op die potensiele voordele van tydsberekening moet bepaal word. / The study compares the performance of a buy-and-hold strategy with that of a markettiming strategy in the framework of the arbitrage pricing theory (APT) applied to the industrial index of the Johannesburg Stock Exchange (JSE). The study period is divided into two parts, namely January 1970 to September 1987 and January 1989 to June 1997. The long-term trend of the industrial index and every APT factor is determined by finding the best nonlinear model for each time series. Linear multiple stepwise regression analysis, with the lagged time series of the long-term trend error terms of the APT factors, is used to forecast the movement of the industrial index around its long-term trend. Decision lines were developed to implement a market-timing strategy. The results of the study are as follows: • Where the lagged time series of the long-term trend error terms of the APT factors were used as possible predictors, the risk-adjusted return of a markettiming strategy was 6, 41 percent and 0, 71 percent higher than that of a buyand- hold strategy for periods one and two respectively. • Where the lagged time series of the first-order difference of the long-term trend error term of the APT factors were used as possible predictors, the riskadjusted return of the market-timing strategy was 10,40 percent and 1,04 percent higher than that of a buy-and-hold strategy for periods one and two respectively. The main conclusion of the study is that the APT and a market-timing strategy are theoretically and practically reconcilable on the JSE. The main recommendations of the study are the following: (1) systematic risk factors, other than macroeconomic factors, should be identified in order to increase the forecasting value of these factors in the second period of the study; (2) each step of the model developed in this study should be repeated on every index of the JSE; and (3) the influence of transaction costs and dividends on the potential benefits of a market-timing strategy should be determined. / Business Management / DCom (Sakebestuur)

Die studie vergelyk die prestasie van 'n koop-en-hou-strategie met die van 'n tydsberekeningstrategie binne die raamwerk van die arbitrasie-prysbepalingsteorie (APT) op die nywerheidsindeks van die Johannesburgse Aandelebeurs (JA). Die periode van die studie is oor twee tydperke, naamlik Januarie 1970 tot September 1987 en Januarie 1989 tot Junie 1997. Die langtermyntendens van die nywerheidsindeks en APT-faktore is bepaal deur die beste nie-reglynige model vir elke tydreeks te vind. Reglynige meervoudige stapsgewyse regressie-ontleding is gebruik om die bewegings van die nywerheidsindeks rondom die langtermyntendens te voorspel. Die sloeringsreekse van die langtermyntendensresidutelling van die APT-faktore en die sloeringsreekse van die eerste-ordeverskiltelling van die langtermyntendensresidutelling is as moontlike voorspellers gebruik. Gegrond hierop is beslissingslyne ontwik:kel wat gebruik is vir die implementering van 'n tydsberekeningstrategie. Die resultate van die studie is die volgende: • Waar die sloeringsreekse van die langtermyntendensresidutelling van die APTfaktore as moontlike voorspellers gebruik is, is die risiko-aangepaste opbrengskoers van 'n tydsberekeningstrategie 6, 41 persent en 0, 71 persent b6 die van 'n koop-en-hou-strategie vir tydperk een en twee onderskeidelik. • Waar die sloeringsreekse van die eerste-ordeverskiltelling van die langtermyntendensresidutelling van die APT-faktore as moontlike voorspellers gebruik is, is die risiko-aangepaste opbrengskoers van 'n tydsberekeningstrategie 10,40 persent en 1,04 persent b6 die van 'n koop-enhou- strategie vir tydperk een en twee onderskeidelik. Die belangrikste gevolgtrekking van die studie is dat die APT en 'n tydsberekeningstrategie teoreties en prakties versoenbaar is op die JA. Aanbevelings vir toekomstige navorsing is die volgende: ( 1) sistematiese risikofaktore, anders as makro-ekonomiese faktore, behoort identifiseer te word wat die voorspellingswaarde van die faktore in die tweede tydperk van die studie kan verhoog; (2) elke stap van die model wat ontwikkel is, behoort op elke indeks van die JA toegepas te word om die risiko-aangepaste opbrengskoers van 'n tydsberekeningstrategie toegepas op elkeen van die indekse met die van 'n koop-en-hou-strategie te vergelyk; en (3) die invloed van transaksiekoste en dividende op die potensiele voordele van tydsberekening moet bepaal word. / The study compares the performance of a buy-and-hold strategy with that of a markettiming strategy in the framework of the arbitrage pricing theory (APT) applied to the industrial index of the Johannesburg Stock Exchange (JSE). The study period is divided into two parts, namely January 1970 to September 1987 and January 1989 to June 1997. The long-term trend of the industrial index and every APT factor is determined by finding the best nonlinear model for each time series. Linear multiple stepwise regression analysis, with the lagged time series of the long-term trend error terms of the APT factors, is used to forecast the movement of the industrial index around its long-term trend. Decision lines were developed to implement a market-timing strategy. The results of the study are as follows: • Where the lagged time series of the long-term trend error terms of the APT factors were used as possible predictors, the risk-adjusted return of a markettiming strategy was 6, 41 percent and 0, 71 percent higher than that of a buyand- hold strategy for periods one and two respectively. • Where the lagged time series of the first-order difference of the long-term trend error term of the APT factors were used as possible predictors, the riskadjusted return of the market-timing strategy was 10,40 percent and 1,04 percent higher than that of a buy-and-hold strategy for periods one and two respectively. The main conclusion of the study is that the APT and a market-timing strategy are theoretically and practically reconcilable on the JSE. The main recommendations of the study are the following: (1) systematic risk factors, other than macroeconomic factors, should be identified in order to increase the forecasting value of these factors in the second period of the study; (2) each step of the model developed in this study should be repeated on every index of the JSE; and (3) the influence of transaction costs and dividends on the potential benefits of a market-timing strategy should be determined. / Business Management / DCom (Sakebestuur)