The emergence of closed-loop Brayton cycle power plants, such as the PBMR, resulted in the need to simulate start-up transients for industrial multi-stage axial flow compressors operating at subsonic conditions. This implies that the delivery pressure and power requirements must be predicted for different mass flow rates and rotational speeds while operating in the first and fourth quadrants on the compressor performance charts. Therefore, an analytical performance prediction model for subsonic multi-stage axial flow compressors had to be developed that can be integrated into a generic network analysis software code such as Flownex. For this purpose, performance calculations based on one-dimensional mean-line analysis demonstrated good accuracy, provided that the correct models for losses, incidence and deviation are used. Such a model is therefore the focus of this study. A preliminary analytical performance prediction code, with the capability of interchanging between different deviation and loss models is presented. Reasonably complex loss models are integrated in association with the correct incidence and deviation models in a software package called "Engineering Equation Solver" (EES). The total pressure loss calculations are based on a superposition of theoretically separable loss components that include the following: blade profile losses, secondary losses and annulus losses. The fundamental conservation equations for mass, momentum and energy for compressible "rotating pipe" flow were implemented into the performance prediction code. Performance prediction models were validated against experimental data and evaluated according to their ease of implementation. Verification was done by comparing simulation results with experimental work done by Von Backstrom. This includes a calculation to determine the uncertainty in the experimental results. Furthermore, since the conventional definition of isentropic efficiency breaks down at the boundaries of quadrants on the performance charts, a new non-dimensional power formulation is presented that allows for the calculation of the compressor power in all of the relevant quadrants. Good comparison was found between simulation results and measurements in the first and fourth quadrant of operation. / Thesis (M.Ing. (Nuclear Engineering))--North-West University, Potchefstroom Campus, 2007.

Graduation date: 2004

My dissertation is focused on developing a better understanding of the technology and innovation strategies of corporations and their impacts on firm performance. I am particularly interested in corporate venture capital (CVC), which serves as a strategy for accessing external technology for corporate investors and as an alternative source of financing and complementary assets for start-ups. I have investigated the conditions under which corporate investors and start-ups achieve the strategic goals by establishing CVC ties, and on estimating the technological and financial gains created by the CVC ties. Specifically, I have concentrated on when and where CVC ties are established in order to maximize economic value. The former relates to a timing issue, whereas the latter is a space issue of CVC investments. In the first essay, I examine corporate investors' decisions to establish CVC ties and their subsequent strategic actions. Consistent with the real options perspective on CVC investments, I find that CVC investments can help corporate investors effectively search for and select future acquisition or licensing partners by reducing asymmetric information and uncertainty that may characterize markets for technology. Specifically, CVC investments facilitate the external acquisition of technology by substituting for a corporate investor's absorptive capacity, as reflected by its upstream research capabilities. CVC investments instead complement the portfolio of internally generated new products, since they allow highly productive corporate investors to shift their focus onto exploratory initiatives with the objective of selecting future technology and partners. Finally, CVC investments facilitate exploratory investments in distant technological areas that are subsequently integrated through licensing or acquisitions. These findings contribute to emerging research on the organization and financing patterns of external R&D activities. In the second essay, I investigate the nature of the relationship between technological spillovers and capital gains created by CVC investments for corporate investors. Using a simple equilibrium model and data from the global bio-pharmaceutical industry between 1986 and 2007, I find that these technological spillovers and capital gains are complements. This complementarity is enhanced when CVC investments are made in post-IPO and technologically diversified start-ups. Beyond providing a broad benchmark for heterogeneous returns on CVC investments, this study has important implications for corporate investors and start-ups. In particular, to the extent that capital gain is greatly determined by changes in the market values of start-ups, it implies that CVC investments can create value for start-ups as well as corporate investors. These mutual benefits can be greatly determined by when (e.g., post-IPO start-ups) and where (e.g., technologically diversified start-ups) CVC investments are made. In the third essay, I analyze the contextual factors that impact the probability of start-ups' obtaining financing through independent venture capitalists and corporate investors. The systematic empirical evidence based on a three-stage game theoretic model suggests that start-ups that possess better evaluated technology tend to be financed through independent venture capitalists, rather than corporate investors. In contrast, start-ups tend to be financed through corporate investors, rather than independent venture capitalists, when their intellectual properties are effectively protected and their research pipelines contain multiple products. These findings provide a theoretical basis to explain why several types of investors co-exist in the entrepreneurial financing market. Moreover, the existence of such determinants indicates that, although investors traditionally have been viewed as the powerful partner that dominates the investment decision, start-ups are also active decision makers in investment ties.

The explosive growth of the World-Wide-Web and the emergence of ecommerce are the major two factors that have led to the development of recommender systems (Resnick and Varian, 1997). The main task of recommender systems is to learn from users and recommend items (e.g. information, products or books) that match the users’ personal preferences. Recommender systems have been an active research area for more than a decade. Many different techniques and systems with distinct strengths have been developed to generate better quality recommendations. One of the main factors that affect recommenders’ recommendation quality is the amount of information resources that are available to the recommenders. The main feature of the recommender systems is their ability to make personalised recommendations for different individuals. However, for many ecommerce sites, it is difficult for them to obtain sufficient knowledge about their users. Hence, the recommendations they provided to their users are often poor and not personalised. This information insufficiency problem is commonly referred to as the cold-start problem. Most existing research on recommender systems focus on developing techniques to better utilise the available information resources to achieve better recommendation quality. However, while the amount of available data and information remains insufficient, these techniques can only provide limited improvements to the overall recommendation quality. In this thesis, a novel and intuitive approach towards improving recommendation quality and alleviating the cold-start problem is attempted. This approach is enriching the information resources. It can be easily observed that when there is sufficient information and knowledge base to support recommendation making, even the simplest recommender systems can outperform the sophisticated ones with limited information resources. Two possible strategies are suggested in this thesis to achieve the proposed information enrichment for recommenders: • The first strategy suggests that information resources can be enriched by considering other information or data facets. Specifically, a taxonomy-based recommender, Hybrid Taxonomy Recommender (HTR), is presented in this thesis. HTR exploits the relationship between users’ taxonomic preferences and item preferences from the combination of the widely available product taxonomic information and the existing user rating data, and it then utilises this taxonomic preference to item preference relation to generate high quality recommendations. • The second strategy suggests that information resources can be enriched simply by obtaining information resources from other parties. In this thesis, a distributed recommender framework, Ecommerce-oriented Distributed Recommender System (EDRS), is proposed. The proposed EDRS allows multiple recommenders from different parties (i.e. organisations or ecommerce sites) to share recommendations and information resources with each other in order to improve their recommendation quality. Based on the results obtained from the experiments conducted in this thesis, the proposed systems and techniques have achieved great improvement in both making quality recommendations and alleviating the cold-start problem.

Most small new firms face problems in surviving the gestation process and achieving a viable performance thereafter because of the very fact of their smallness and newness. Due to a lack of internal resources, entrepreneurs of small new firms find it necessary to seek resources from outside the firm through their external social network. The theory of social capital that prescribes valuable resources are embedded in social relations is, thus, particularly relevant to the small business start-up situation. The embedded resources within an external network are hypothesized to have a positive impact on the business performance of these new firms. The main objective of the present study is to empirically investigate the impact of external networks, and in particular the initial social network of entrepreneurs, to the success of small firm start-up in Hong Kong. The second objective is to determine whether there is any interaction effect of the entrepreneur’s networking capability with the external network structure on the start-up success of small Hong Kong firms. / To carry out the research, this study offers a conceptual model linking initial network start-up success to initial network structure of start-up, and including an interaction effect from the entrepreneur’s networking capability. The study operationalizes social capital in four types of network constructs: network size, trustworthiness, network support and network diversity. A series of hypotheses relating to these four dimensions asserting external network determinants of the start-up success of small firms is posited. Other hypotheses which assert the interaction effect between an entrepreneur’s networking capability and the initial network structure on the success of small firm start-up, are also posited. A field survey, administered to 1,000 small Hong Kong firms of various industries, is used to gather the data. The questionnaire survey was developed in two languages – Chinese and English – to ensure a good level of understanding in the bilingual business environment of Hong Kong. Of the 1,000 questionnaires dispatched, a final sample of 89 small firms was used to empirically test the hypotheses using multiple regression analysis and multiple hierarchical regression analysis. Control variables such as entrepreneurs’ experiences and education prior to the firm start-up are included. / Empirical results indicate that the verification of social capital theory’s prescription for start-up success cannot be supported unequivocally. The results suggest that some initial network conditions such as initial size of strong tie network, network support and network diversity are positively associated with some measures of start-up success, but trustworthiness of network ties and the size of weak tie network do not figure among them. No evidence is found to support that entrepreneurs’ networking capability can positively enhance the effect of the initial network structure on start-up success. Overall, the study raises some questions on the positive linear relationship of certain operationalized constructs such as network size and trustworthiness of social capital with start-up success. Following the findings of this research, future studies may choose to further investigate social capital theory on small start-up success by refining the operationalization of social capital, and verify other interaction effects of entrepreneurs’ networking capabilities.

Master of Engineering / This thesis presents an innovative human promoter recognition model HPR-PCA. Principal component analysis (PCA) is applied on context feature selection DNA sequences and the prediction network is built with the artificial neural network (ANN). A thorough literature review of all the relevant topics in the promoter prediction field is also provided. As the main technique of HPR-PCA, the application of PCA on feature selection is firstly developed. In order to find informative and discriminative features for effective classification, PCA is applied on the different n-mer promoter and exon combined frequency matrices, and principal components (PCs) of each matrix are generated to construct the new feature space. ANN built classifiers are used to test the discriminability of each feature space. Finally, the 3 and 5-mer feature matrix is selected as the context feature in this model. Two proposed schemes of HPR-PCA model are discussed and the implementations of sub-modules in each scheme are introduced. The context features selected by PCA are III used to build three promoter and non-promoter classifiers. CpG-island modules are embedded into models in different ways. In the comparison, Scheme I obtains better prediction results on two test sets so it is adopted as the model for HPR-PCA for further evaluation. Three existing promoter prediction systems are used to compare to HPR-PCA on three test sets including the chromosome 22 sequence. The performance of HPR-PCA is outstanding compared to the other four systems.

Universiẗat, Diss.--Mannheim, 2007.

Thesis (Ph. D.)--University of Washington, 2008. / Vita. Includes bibliographical references (leaves 153-163).

Thesis (M.A.)--West Virginia University, 2004. / Title from document title page. Document formatted into pages; contains iv, 106 p. : ill. Includes abstract. Includes bibliographical references (p. 53-61).

Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xiii, 126 p.; also includes graphics Includes bibliographical references (p. 107-116). Available online via OhioLINK's ETD Center