I argue for the Expanded Cluster Account of art (ECA) by first inquiring as to whether “art” is best described by a cluster account and where ECA fits into the current landscape of theories of concepts. Second, I explicate the relevant aspects of Boyd’s theory of natural kinds and argue that his concepts of “disciplinary matrices” and “homeostatic property clusters” (roughly analogous to Gaut’s criterial properties for characterizing art, particularized for each individual kind) have relevant roles in a proper cluster account of art, thus explicating and expanding Gaut’s account in the process. Third, I defend the thesis that Boyd’s concept of “disciplinary matrix,” when applied to “art,” is fulfilled by George Dickie’s notion of “the Artworld.” Lastly, I consider objections to ECA and positively explain its heuristic and explanatory efficacy above and beyond other contemporary “anti-definitional” accounts.

This project examines the theoretical basis for linking industrial clustering to the strategic management of firms. Specifically, a recently deployed theory building framework defined three perspectives on clustering, the competitiveness perspective, the externalities perspective and the territorial perspective, but stopped short of explaining when, where and to whom these perspectives are relevant. This thesis proposes that firms are the central recipient of cluster effects and that the product-based, resource-based and knowledge-based approaches to management provide the theoretical base from which the operational contexts of each cluster perspective can be defined. Three cluster-management relationships are modelled and beta-tested on a sample of cluster-based firms. The empirical analysis is designed to provide feedback to the theory building process and not to prove or disprove the theory itself.<p> The analysis yielded little if any evidence that the proposed cluster-management relationships are present in the sample that was studied. This result was a surprise as the exuberance with which clusters and their benefits are often promoted suggests that in a cluster there should be a pronounced correlation between firm performance and cluster attributes. The statistical limitations of this analysis mean the results can not be inferred to the general population and that the theoretical propositions are not actually disproved. Nonetheless, the muted observations do cast attention on the need for better modelling and measurement instruments in the field of cluster research. In addition, this project initiates a deductive process by which subsequent research can focus on the causal pathways that comprise the phenomenon of industrial clustering; including the pathway that links clusters to firms and then to economic performance.

Overweight and obesity in Canada has significantly increased during the last three decades, paralleled by increased intake of fat and sugar particularly sugary beverages leading to higher level of energy intake, as well as reduction in physical activity. Canadian Community Health Survey, Cycle 2.2, 2004 (CCHS 2.2), provides the opportunity to evaluate beverage intakes of Canadians in relation to overweight and obesity using Body Mass Index (BMI).<p> To examine the association between sugar-sweetened beverages and BMI in Canadian adults, we used data from CCHS 2.2 (n=14,304, aged >18 year and <65 year) in which dietary intake was assessed using 24-h recall. In various steps, data on beverage consumption were identified, coded and classified. Using descriptive statistics, we determined total gram intake and the contribution of each beverage to total energy intake among age/sex groups. To determine the most suitable patterns of beverage consumptions among Canadian adults, a cluster analysis K-means method was applied. Males and females were classified into distinct clusters based on the dominant pattern of beverage intakes. Finally, step-wise logistic regression models were used to determine associations between sugar-sweetened beverages and BMI, controlling for age, marital status, income, education, physical activity, total energy intake, immigration status, smoking habits and ethnicity. To account for complex survey design, all data were weighted and bootstrapped.<p> BMI in women with predominant fruit drink pattern (791.1±32.9 g) was significantly higher than those with no dominant pattern in beverage consumption (28.3±1 vs. 26.8±0.3 respectively, P<0.001). In women, high intake of fruit drinks was a significant predictor of overweight (OR=1.84, 95% C.I:1.06-3.20), obesity (OR=2.55, 95% C.I:1.46-4.47) and overweight/obesity (OR=2.05, 95% C.I:1.29-3.25). In men, mean BMI was not different among beverage consumption clusters and none of the beverages was a predictor for overweight and obesity. For the first time, in a nationally representative data, we report association of sugar-sweetened beverages and overweight and obesity in Canadian women.

Under the mechanism of natural selection, creatures are forced to evolve naturally in order to survive. Keen-sighted jumping spiders have long been considered as the main predation pressure of terrestrial arthropod. Many species benefit from mimicking the appearance of jumping spider. In this study according to the experimental data from Wang (2009b), a data analysis is undertaken concerning male Ptocasius strupifer¡¦s behavior to different subject groups, namely, male Ptocasius strupifer, female Ptocasius strupifer, male Plexippus paykulli, female Plexippus paykulli, Cataclysta angulata and Eugauria albidentata, so as to investigate the jumping spider mimicry of Eugauria albidentata. In this work, our interest is to compare the behavior of male Ptocasius strupifer on Eugauria albidentata with there of the other five groups mentioned above, and identify which one is the most similar to there of Eugauria albidentata . We use different statistical methods, i.e. likelihood ratio test, factor analysis and cluster analysis to evaluate the closeness of the behavior between different groups. According to the analysis result, it shows that the behavior of Ptocasius strupifer towards Eugauria albidentata is more similar to those of both female Ptocasius strupifer and female Plexippus paykulli. Moreover there is a wide discrepancy between Eugauria albidentata and Cataclysta angulata, although both of them belong to Musotiminae.

Taiwan's online game industry from July 1999 Lager technology company launched its first self-made online game, "King of Kings" in Taiwan can have the strength of online game development. Love justice from 2000 Japanese JSS International also represents the company's "Stone Age", and also South Korean Deputy Gamania NCsoft's "Lineage", Taiwan began to develop the online game industry. This study discusses the Asian online game industry in the development of major countries such as Japan, Korea and mainland China through Michael Porter's Diamond Model. Diamond Model proposed by the factors of production, demand factors, related and supporting industries and firm strategy, structure and competition, etc. There are four options the Government and the chance to face the two surfaces as a study aid purchase theoretical basis for online games in Taiwan market for research and analysis, which found that Taiwan's online game industry is facing a critical stage of development, the Government has been too slow, so the domestic company already own alliance to the government for help, hoping to help Taiwan game company to reduce the access to Chinese market barriers, but also hope the Government can set up the digital content industry park, providing preferential tax rates in order to promote the development of industrial cluster competitive environment.

In this paper, I'll introduce the applications of Mathematica 7th and 8th edition in probability and statistics. The major contents are statistical data and charts, basis statistics, probability distributions, hypothesis testing, distribution fitting, regression analysis, cluster analysis and so on. Except introducing variously related commands, this paper will provides corresponding examples, so it can be regarded as a toolbook for people interested in the probabilities and statistical parts of this software.

Micromagnetic modeling numerically solves magnetization evolution equation to process magnetic domain analysis, which helps to understand the macroscopic magnetic properties of ferromagnets. To apply this method in simulation of magnetostrictive ferromagnets, there exist two main challenges: the complicated microelasticity due to the magnetostrictive strain, and very expensive computation mainly caused by the calculation of long-range magnetostatic and elastic interactions. A parallel computing for phase field model based on computer cluster is then developed as a promising tool for domain analysis in magnetostrictive ferromagnetic materials. We have successfully built an 8-node Apple workgroup cluster, deploying the hardware system and configuring the software environment, as a platform for parallel computation of phase field model of magnetic materials. Several testing programs have been implemented to evaluate the performance of the cluster system, especially for the application of parallel computation using MPI. The results show the cluster system can simultaneously support up to 32 processes for MPI program with high performance of interprocess communication. The parallel computations of phase field model of magnetic materials implemented by a MPI program have been performed on the developed cluster system. The simulated results of a single domain rotation in Terfenol-D crystals agree well with the theoretical prediction. A further simulation including magnetic and elastic interaction among multiple domains shows that we need take into account the interaction effects in order to accurately characterize the magnetization processes in Terfenol-D. These simulation examples suggest that the paralleling computation of the phase field model of magnetic materials based on a powerful cluster system is a promising technology that meets the need of domain analysis.

The purpose of this dissertation is to enhance the applicability and the accuracy of the Poisson cluster stochastic rainfall generators. Firstly, the 6 parameters of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) stochastic rainfall simulation model were regionalized across the contiguous United States. Each of the parameters of MBLRP model estimated at 3,444 National Climate Data Center (NCDC) rain gages was spatially interpolated based on the Ordinary Kriging technique to produce the parameter surface map for each of the 12 months of the year. Cross-validation was used to assess the validity of the parameter maps. The results indicate that the suggested maps reproduce well the statistics of the observed rainfall for different accumulation intervals, except for the lag-1 autocorrelation coefficient. The estimated parameter values were also used to produce the maps of storm and rain cell characteristics. Secondly, the relative importance of the rainfall statistics in the generation of watershed response characteristics was estimated based on regression analyses using the rainfall time series observed at 1099 NCDC rain gages. The result of the analyses was used to weigh the rainfall statistics differently in the parameter calibration process of MBLRP model. It was observed that synthetic rainfall time series generated weighing the precipitation statistics according to their relative importance outperformed those generated weighing all statistics equally in predicting watershed runoff depths and peak flows. When all statistics were given the same weight, runoff depths and peak flows were underestimated by 20 percent and 14 percent, respectively; while, when the statistics were weighed proportionally to their relative importance, the underestimation was reduced to 4 percent and 3 percent, which confirms the advantage of weighing the statistics differently. In general, the value of the weights depends on the hydrologic process being modeled. Lastly, a stochastic rainfall generation model that can integrate year-to-year variability of rainfall statistics is suggested. The new framework consists of two parts. The first part generates the short-term rainfall statistics based on the correlation between the observed rainfall statistics. The second part generates the rainfall time series using the modified Bartlett-Lewis rectangular pulse model based on the simulated rainfall statistics. The new approach was validated at 104 NCDC gages across the United States in its ability to reproduce rainfall and watershed response characteristics. The result indicates that the new framework outperformed the traditional approach in reproducing the distribution of monthly maximum rainfall depths, monthly runoff volumes and monthly peak flows.

Ferric ferrocyanide (Prussian blue) and its analogues are renowned for the variety of properties and applications associated with them. At the same time, however, they suffer from issues related to their variable composition and poor crystallinity. As a result, we are preparing discrete cyanide-bridged clusters both to mimic these materials and to search for properties unique to the molecule, such as single molecule magnetism. The work in this dissertation has focused on the expansion of series of trigonal bipyramidal (TBP) cyanide-bridged clusters, [M(tmphen)2]3[M′(CN)6]2, that exhibit a variety of properties including spin crossover, charge-transfer-induced spin transition, and photomagnetism. One goal of the work was focused on the preparation of new paramagnetic TBP clusters incorporating various 3d metal ion combinations. Nine new clusters were prepared and characterized, including several “model compounds” with only one type of paramagnetic metal ion. The magnetic properties of these model compounds were combined to better explain the coupling through the cyanide ligands in clusters with two paramagnetic metal centers. An additional two clusters were also prepared that were found to exhibit a thermally induced LS Fe^II -> HS Fe^II transition. The spin crossover event was confirmed by magnetic susceptibility and Mössbauer spectroscopy, and variable temperature X-ray crystallography revealed the transitions to be distinct for each FeII center and dependant on the interstitial solvent. Another major goal of the work was to investigate the TBP clusters for their potential to be used as building-blocks to prepare 1-D extended structures of linked clusters, such as a {[Co(tmphen)2]3[Fe(CN)6]2[Mn(MeOH)4]}∞(ClO4)3 chain. A final research goal was a search for photomagnetic behavior, the change in magnetic properties with irradiation, related to spin transitions in several key TBP clusters. The Fe3Fe2 and Fe3Co2 TBP clusters were found to exhibit a light-induced excited spin state trapping (the LIESST effect) similar to that observed in mononuclear FeII compounds, and the photo-induced charge transfer that has been observed in Co-Fe Prussian blue materials is mimicked by the Co3Fe2 TBP molecular analogue.

The Internet and web service have become the most popular platform and application of the Client-Server model due to the universality of the network recently years. Its growth is beyond the imagination, many traditional service have changed into web service stage by stage, and the load of the servers become more and more heavy. In the situation the server architecture must be adapted oppositely. The web cluster architecture that has the advantages of scalability, reliability and high performance requirement, is used extensively. In our lab developed and implemented a mechanism termed Content-aware Distributor, which is a software module for kernel-level extension, to effectively support content-based routing. Based on the achievement of the software-based Content-aware Distributor; we design and implementation a content management system for backend servers. The content management system provides a user friendly management console to allow a administrator to manage the whole cluster system. The content management system also monitors backend servers periodically, when server is awarded to be overloaded, the content management system will replicate popular content to other servers automatically. By this way cluster system can balance load of back end servers and increase system performance and throughput.