Abstract The purpose of this study is to investigate and compare the development of knowledge-based economy and related policies in Taiwan, China and Hong Kong. Furthermore, a cross-country analysis of knowledge-based economy is conducted. The meaning and content of knowledge-based economy are firstly analyzed in the light of innovation theory and human capital theory. A cross-country empirical study is then conducted. The data source is 2001 World Development Indicators CD-Rom published by the World Bank. Utilizing the method of factor analysis, we extract two important factors characterizing knowledge-based economy. The first is the efficiency of communication and exchanging information, which represents the efficiency of delivering knowledge, and the level of human capital, which represents the stock of knowledge. The regression method is used to analyze the relationships between the two factors and productivity. It is found that both factors have strong positive effects on GDP per capita, agriculture value added per worker, and research and development expenditure. Individual indicators in the two factors are used to evaluate and compare the performance of Taiwan, China, and Hong Kong. It is found that Taiwan¡¦s level of knowledge-based economy is similar to the average level of APEC memberships, but better than that of East Asia, of Pacific countries, and of upper-middle income countries. China¡¦s level of knowledge-based economy is obviously not able to catch up with the average level of APEC memberships, that of East Asia, that of Pacific countries, and that of low-middle income countries. The performance of knowledge-based economy of Hong Kong is much better and equal to that of OECD and of G8 memberships. Our findings imply that the performance of knowledge-based economy of Taiwan is better than that of China, but inferior to that of Hong Kong and that of Japan, Singapore, and Korea. The reason might be that Taiwan¡¦s implementation of related national policies falls behind these countries. We suggest that the government should put more emphasis on implementing information and communication infrastructure in order to enhance the efficiency of delivering, stirring up, and diffusing of knowledge.

The coming of knowledge-based economy age leads to the competitive advantage of high-technology industries strongly depend on human capital and intellectual capital. In order to rise the capacity of self-innovation and obtain new technologies, for high-technology industries, in-house research and development is necessary, but acquiring technology from outside, especially from academe, becomes more and more important. The phenomena of cluster, high-technology industries build factories near by universities, is the beginning of the interaction between industries and universities¡]1951 Silicon Valley¡^. Until the 1980¡¦s, the United States government didn¡¦t start to draft the policy about promoting industry-university collaboration and technology transfer, and in Taiwan, it started at 1991. Good interaction between industries and universities can arrange the resources and make a win-win situation. By reviewing the literatures on the development of scientific parks and mechanism of industry-university collaboration of Taiwan and other advanced countries¡]the United States ,Japan, and German¡^, especially focus on technology transfer, patent management, related laws, national innovation system, etc., I found some problems and defects and have some suggestions that may help.

The embryo of higher education starts from medieval era. Along with the Renaissance, and Enlightenment, the domain knowledge in higher education comprises theology, philosophy and science. It is the most distinguish character in contemporary capitalism States that science and technology gradually becomes the leading productivity engine. The core competence of science and technology exists in the research and development (R&D) capability. Once the higher education involves in the development of science and technology, the State naturally regards it as one of key production elements. This essay is based on the theory of production relationship, studying the interaction between economy (infrastructure) and ideology (politics and education), and taking the evolution of higher education in Post-war Taiwan as an example. Here we called higher education in Taiwan in the period of 1954 to 1980 as Dominant State Apparatus. During this period the State practiced nationalism through elite politics and technocratic. In 50s and 60s, the State emphasized the political stability, so the ideology was one of the standards for selecting freshmen into higher education. In 60s to 80s, leaded by Council for Economic Planning and Development, the State adjusted the rate of higher education attainment and adjusted the proportion of different colleges/ departments in higher education according to the rational economic value. A report of manpower development by Council for Economic Planning and Development is encouraging a steady rise in the area of science, medicine, agriculture, and engineering, so called natural science in higher education. And the neglect of social science, Liberal Arts is resulted. From 80s, the higher education in Taiwan remains instrumentality, which is called Latent State Apparatus here. The higher education follows the State¡¦s strategic industry and technology policy accordingly. The State enforces higher education to develop some particular research areas by giving subsidiary. In this knowledge-based economy era, knowledge commercialized and education industrialized is going to be main trends. It is predictable that higher education would allocate its major resources in research areas, which can yield most economic value. At that moment, Higher Education would become not only the State Apparatus, but also Market Apparatus.

There is an increasing need for three-dimensional description for various applications such as the development of catchment areas, forest fire control and restoration. Three-dimensional information plays an indispensable role; therefore acquisition of the digital elevation models (DEMs) is the first step in these applications. LiDAR is a recent development in remote sensing with great potential for providing high resolution and accurate three-dimensional point clouds for describing terrain surface. The acquired LiDAR data represents the surface where the laser pulse is reflected from the height of the terrain and object above ground. These objects should be removed to derive the DEMs. Many LiDAR data-filtering studies are based on surface, block, and slope algorithms. These methods have been developed to filter out most features above the terrain; however, in certain situations they have proved unsatisfactory. The different algorithm based on different point of view to describe the terrain surface. The appropriate adoption of the advantages from these algorithms will develop a more complete way to derive DEMs. Knowledge-based system is developed to solve some specific problems according to the given appropriate domain knowledge. Huang (2007) proposed a Knowledge-based classification system in urban feature classification using LiDAR data and high resolution aerial imagery with 93% classification accuracy. This research proposed a knowledge-based LiDAR filtering (KBLF) as a follow-up study of Huang¡¦s study. KBLF integrates various knowledge rules derived from experts in the area of ground feature extraction using LiDAR data to increase the capability of describing terrain and ground feature classification. The filtering capability of KBLF is enhanced as expected to get better quality of referenced ground points to recover terrain height and DEMs using Inverse Distance Weighting (IDW) and Nearest Neighbor (NN) methods.

This thesis report presents the work of analysing current challenges in Multidisciplinary Analysis systems. Exemplary the system of an aerospace supplier, GKN Aerospace Sweden AB, is examined and several suggestions for improve- ment are implemented. The Multidisciplinary Analysis system, with company internal name Engineering Workbench, employs a set-based approach in exploring the design-space for jet engine components. A number of design cases with varied geometrical and environmental parameters is generated using Design of Experiment sampling methods. Each design case is then subjected to a set of analyses. Using the analyses results, a surrogate model of the parts behaviour in relation to the input parameters is created. This enables the product developer to get a general view of the model’s behaviour and also to react to changes in product requirements. Design research methodology is applied to further develop the Engineering Workbench into a versatile design support system and expand the functionality to include producibility assessment. In its original state, the execution of a study requires explicit domain knowledge and programming skills in several disciplines. The execution of a study is often halted by minor process errors. Several methods to improve this status are suggested and tested. Among those are the introduction of an interface to improve the usability and expand the range of possible users. Further the integration of a four level system architecture supporting a modular structure. Producibility assessment is enabled by developing an expert system where geometrical and simulation results can be caught, analysed and evaluated to produce producibility metrics. Evaluation of the implemented solutions indicate a step in the right direction. Further development towards Multidisciplinary Optimisation, involving experts in information technologies as well as case- based reasoning techniques is suggested and discussed.

This research extends the knowledge-based view of the firm as it relates to organizational structure. In particular, this research provides evidence that fundamental classifications of knowledge are measurable, in relative terms, as factors of production. It then relates differences in relative quantities of these classifications of knowledge to the presence or absence of inter-firm boundaries. Finally, this study provides evidence that financial performance may be related to the alignment of organizational structure with knowledge-based factors of production. This study contributes to strategic management theory by offering a potential solution to the difficulties of measuring knowledge as a factor of production. The research was motivated by the belief that it is the cost and value of knowledge that determines economic efficiency (Simon, 1999). By surveying professionals in the mutual fund industry for their relative reliance on three classifications of knowledge, this study suggests a set of measures of knowledge-based factors of production. These measures in turn support the testing of hypotheses related to the vertical integration (or de-integration) of adjacent stages of production. Researchers have typically categorized organizational knowledge as either tacit or explicit. This research develops the concept of encapsulated knowledge as a fundamental classification of knowledge. Encapsulated knowledge is neither tacit nor explicit, because it is externalized and implicit. Progress in measuring knowledge is made by distinguishing between knowledge that resides in human minds (tacit), knowledge that is codified as information (codified), and knowledge that is embodied in the design and functionality of physical artefacts (encapsulated). Relative reliance on the fundamentally different knowledge-based factors of production was found to vary between adjacent stages of production, despite the essential overlap of jointly held substantive knowledge. Portfolio managers are generally less (more) reliant on tacit (encapsulated) knowledge than other investment management professionals in the mutual fund complex. In addition, portfolio managers whose firms are de-integrated from the mutual fund management firms were found to be more (less) reliant on tacit (encapsulated) knowledge than their integrated counterparts. Finally, alignment between mutual fund structure and reliance on knowledge-based factors of production was found to affect performance of mutual funds.

This research extends the knowledge-based view of the firm as it relates to organizational structure. In particular, this research provides evidence that fundamental classifications of knowledge are measurable, in relative terms, as factors of production. It then relates differences in relative quantities of these classifications of knowledge to the presence or absence of inter-firm boundaries. Finally, this study provides evidence that financial performance may be related to the alignment of organizational structure with knowledge-based factors of production. This study contributes to strategic management theory by offering a potential solution to the difficulties of measuring knowledge as a factor of production. The research was motivated by the belief that it is the cost and value of knowledge that determines economic efficiency (Simon, 1999). By surveying professionals in the mutual fund industry for their relative reliance on three classifications of knowledge, this study suggests a set of measures of knowledge-based factors of production. These measures in turn support the testing of hypotheses related to the vertical integration (or de-integration) of adjacent stages of production. Researchers have typically categorized organizational knowledge as either tacit or explicit. This research develops the concept of encapsulated knowledge as a fundamental classification of knowledge. Encapsulated knowledge is neither tacit nor explicit, because it is externalized and implicit. Progress in measuring knowledge is made by distinguishing between knowledge that resides in human minds (tacit), knowledge that is codified as information (codified), and knowledge that is embodied in the design and functionality of physical artefacts (encapsulated). Relative reliance on the fundamentally different knowledge-based factors of production was found to vary between adjacent stages of production, despite the essential overlap of jointly held substantive knowledge. Portfolio managers are generally less (more) reliant on tacit (encapsulated) knowledge than other investment management professionals in the mutual fund complex. In addition, portfolio managers whose firms are de-integrated from the mutual fund management firms were found to be more (less) reliant on tacit (encapsulated) knowledge than their integrated counterparts. Finally, alignment between mutual fund structure and reliance on knowledge-based factors of production was found to affect performance of mutual funds.

Šiuolaikiniai IS inžinerijos metodai yra nuolat vystomi ir tobulinami, tačiau iš esmės jie yra grindžiami empiriniais procesais. Empiriškai išgautų žinių kokybė gali būti nepakankama sėkmingam projekto įgyvendinimui, nes netikslus vartotojo reikalavimų specifikavimas neigiamai įtakoja visus programinės įrangos kūrimo etapus, o tai didina projekto įgyvendinimo riziką. Disertacinis darbas skirtas sukurti IS inžinerijos metodą, kuris įgalintų empiriniais būdais surinktas dalykinės srities žinias patikrinti formalių kriterijų atžvilgiu. Metodui sukurti buvo apjungti žiniomis grindžiamos ir modeliais grindžiamos IS inžinerijos principai. Šiuo tikslu klasikinis MDA procesas buvo papildytas pagrindiniu žiniomis grindžiamos IS inžinerijos komponentu – veiklos modeliu. Darbo metu buvo sukurtas žiniomis grindžiamo MDA metodo dalykinės programos prototipas, kuris iš dalies automatizuoja siūlomo metodo procesą. Žiniomis grindžiamo MDA metodo efektyvumas buvo patikrintas jį taikant eksperimentinio tyrimo atlikimui, kurio metu buvo sukurta pašto siuntų stebėjimo programėlė. Tyrimo metu nustatyta, kad tikslinga taikyti žiniomis grindžiamą MDA metodą PĮ kūrime nes: 1) detaliau dokumentuojami vartotojo reikalavimai (tikrinami formalių kriterijų atžvilgiu); 2) sumažinama loginių trūkių atsiradimo galimybė (tarp programinės įrangos kūrimo dalyvių); 3) daugiaplatforminiuose sprendimuose sumažinamos projekto įgyvendinimo laiko sąnaudos (dėka automatinio kodo generavimo iš patikrintų modelių). / Although new methods of information systems engineering are being researched and developed, they are empirical in nature. The problem domain knowledge acquisition process relies heavily on the system analyst and user; therefore it is not clear whether the knowledge of the problem domain is comprehensive. This may lead to occurrence of logical gaps, misinterpretation of system requirements, thus causing issues for project. The research work is meant to develop new IS engineering method that will allow validation of the problem domain knowledge against formal criteria. In order to create such method basic principles of Knowledge Based ISE and Model Driven ISE were combined. By combining the two approaches Knowledge Based MDA method was created that extends traditional MDA with Enterprise Model. During the research Knowledge Based MDA tool’s prototype, that is capable of partly automating Knowledge Based MDA process, was created. The efficiency of Knowledge Based MDA method was validated by creating real life application for mobile devices. During the empirical research it was established that by using developed method software requirements quality is improved and comprehensive documentation is created (due to Enterprise Model based validation), occurrence of logical gaps between software development stakeholders is reduced, time consumption needed for creation of application for multiplatform systems is reduced (due to automated code generation and shorter testing stage).

Although new methods of information systems engineering are being researched and developed, they are empirical in nature. The problem domain knowledge acquisition process relies heavily on the system analyst and user; therefore it is not clear whether the knowledge of the problem domain is comprehensive. This may lead to occurrence of logical gaps, misinterpretation of system requirements, thus causing issues for project. The research work is meant to develop new IS engineering method that will allow validation of the problem domain knowledge against formal criteria. In order to create such method basic principles of Knowledge Based ISE and Model Driven ISE were combined. By combining the two approaches Knowledge Based MDA method was created that extends traditional MDA with Enterprise Model. During the research Knowledge Based MDA tool’s prototype, that is capable of partly automating Knowledge Based MDA process, was created. The efficiency of Knowledge Based MDA method was validated by creating real life application for mobile devices. During the empirical research it was established that by using developed method software requirements quality is improved and comprehensive documentation is created (due to Enterprise Model based validation), occurrence of logical gaps between software development stakeholders is reduced, time consumption needed for creation of application for multiplatform systems is reduced (due to automated code generation and shorter testing stage). / Šiuolaikiniai IS inžinerijos metodai yra nuolat vystomi ir tobulinami, tačiau iš esmės jie yra grindžiami empiriniais procesais. Empiriškai išgautų žinių kokybė gali būti nepakankama sėkmingam projekto įgyvendinimui, nes netikslus vartotojo reikalavimų specifikavimas neigiamai įtakoja visus programinės įrangos kūrimo etapus, o tai didina projekto įgyvendinimo riziką. Disertacinis darbas skirtas sukurti IS inžinerijos metodą, kuris įgalintų empiriniais būdais surinktas dalykinės srities žinias patikrinti formalių kriterijų atžvilgiu. Metodui sukurti buvo apjungti žiniomis grindžiamos ir modeliais grindžiamos IS inžinerijos principai. Šiuo tikslu klasikinis MDA procesas buvo papildytas pagrindiniu žiniomis grindžiamos IS inžinerijos komponentu – veiklos modeliu. Darbo metu buvo sukurtas žiniomis grindžiamo MDA metodo dalykinės programos prototipas, kuris iš dalies automatizuoja siūlomo metodo procesą. Žiniomis grindžiamo MDA metodo efektyvumas buvo patikrintas jį taikant eksperimentinio tyrimo atlikimui, kurio metu buvo sukurta pašto siuntų stebėjimo programėlė. Tyrimo metu nustatyta, kad tikslinga taikyti žiniomis grindžiamą MDA metodą PĮ kūrime nes: 1) detaliau dokumentuojami vartotojo reikalavimai (tikrinami formalių kriterijų atžvilgiu); 2) sumažinama loginių trūkių atsiradimo galimybė (tarp programinės įrangos kūrimo dalyvių); 3) daugiaplatforminiuose sprendimuose sumažinamos projekto įgyvendinimo laiko sąnaudos (dėka automatinio kodo generavimo iš patikrintų modelių).

Humankapital har ökat i betydelse då allt fler företag har blivit så kallade kunskapsföretag, vilka inriktar sig på att skapa värde genom att endast erbjuda personalens kunskap, kompetens och erfarenhet. Humankapitalet menar forskare, är en tillgång för företaget och borde därför också redovisas som en sådan, precis som företagets andra tillgångar. Dock får inte humankapital i dagens läge tas upp som en tillgång i den finansiella rapporten. Det redovisas därför ofta frivilligt av företagen i hållbarhetsredovisningar. Kunskapsföretagen borde enligt forskare vara de som redovisar absolut mest information om sitt humankapital, då det är företags viktigaste tillgång. Forskare menar också att företagens storlek är en faktor som påverkar hur mycket humankapital som redovisas. Är detta verkligheten? Syftet med denna uppsats är att undersöka om det finns några skillnader i hur kunskapsföretag och industriföretag redovisar sitt humankapital i sin årsredovisning samt om företagets storlek påverkar mängden humankapital som återfinns i företagens årsredovisningar. Metoden som används var en kvalitativ dokumentundersökning. I empiri och analys kapitlet finns företagssammanfattningar och vad Scoreboarden gav för resultat. Resultatet redovisas utefter Scoreboardens olika kategorier: anställda, anställdas utbildning, anställdas välmående och motivation, övrig kvalitativ information, styrelse och ledning. Resultatet analyseras också utefter kategori för att underlätta överskådligheten och analysen. Vi delar sedan upp Scoreboarden i två övergripande kategorier: ”Anställda” och ”Ledande befattningshavare”. En analys görs av dessa övergripande kategorier. ”Anställda” består av kategorierna: anställda, anställdas utbildning, anställdas välmående och motivation samt övrig kvalitativ information. ”Ledande befattningshavare” består av: styrelse och ledning. Sist analyseras skillnaden mellan företagens totala redovisning av humankapital. Slutsatser som kan dras utifrån undersökningen är att det finns en skillnad mellan kunskapsföretag och industriföretag om vi bryter ner informationen. Kunskapsföretagen redovisar mer information om ”Anställda”, medan industriföretagen redovisar mer om ”Ledande befattningshavare”. Studeras den totala bilden är skillnaderna mindre. Dock finner vi att industriföretagens redovisning av humankapital påverkas av företagets storlek, medan kunskapsföretaget inte uppvisar en sådan trend. / Human capital has become increasingly important as more companies have become so called knowledge-based enterprises, which focuses on creating value by offering their staff knowledge, skills and experience. The human capital is, according to scientists, an asset to the company and should therefore be recognized as such, just like the company's other assets. However, human capital cannot be recognized as an asset in the financial report. Firms therefore often report this information voluntarily in sustainability reports. According to researchers, the knowledge companies should be the one that presents the most information regarding its human capital, since it is such a company's most important asset. Researchers also believe that corporate size is a factor that affects how much human capital is reported. Is this reality? The purpose of this paper is to investigate whether there are any differences in how knowledge- and industry enterprises reports its human capital in its annual report, and if the company's size affects the amount of human capital that can be found in corporate annual reports. The method used was a qualitative document examination. In the empirical evidence and analysis chapter, the reader can find company summaries and the results the scoreboard gave us. The results are reported according to the Scoreboards different categories: employees, employee training, employee well-being and motivation, other qualitative information, the board and management. The results are also analyzed by category to facilitate transparency and the analysis. We then divided the scoreboard into two overall categories: "Employees" and "Senior Management". An analysis is made of these overall categories. "Employee" is composed of the categories: employees, employee training, employee well-being and motivation and other qualitative information. "Senior management" consists of: Board and management. Finally, the difference between a company's overall human capital reporting is analyzed. The conclusions that can be drawn from the survey are that there is a difference between knowledge- and industry enterprises when they are broken down by categories. Knowledge Enterprises presents more information about "Employees", while industrial companies report more about "Senior Management". Looking at the total picture, the differences are minor; however, we find that the industrial firms' reporting of human capital is influenced by firm size, while the knowledge company does not exhibit such a trend.