Due to the financial turmoil in recent years, risk management has become an important issue, investors would like to be fully-prepared to cope with financial crisis before it happen. This research uses the Fama and French three-factor and the U.S. Dollar Index (USDX) as an exchange rate variations indicator to capture the international relations. It constitutes a four-factor model to analyze the S&P100 stock returns changes, and we introduce the skewed-t distribution to simulate the distribution of stock returns and capture the characteristics of skewness and kurtosis. We use cluster analysis to cluster the sample companies by their risk characteristics. And then we observe the explanatory power of each risk factor. The study shows that the S&P100 stocks are subjected to the market premium, and the scale effect is smaller than others. ¡@¡@ At last, in accordance with the GARCH-Skewed-t model to simulate the average, variance, skewness and kurtosis of each cluster. We track the long-term performance of each parameter which are used to observe the unusual changes before financial crisis. The empirical results show that the skewness parameter has perfect warning for financial turmoil. The cluster with warning ability is affected by B/M ratio effect and exchange rate changes. Among the case, the cluster has the best early warning effect when it's influenced by the exchange rate indicator. It displays that by adding an exchange rate risk indicator into the multi-factor model, we will have a better clustering result. It means that the skewness parameter of cluster with influence of exchange rate indicator can be used to observe financial turmoil, which can in turns, be used as an early warning system to determine the occurrence of extreme events.

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Two drilled cores were collected from the Jhuoshuei River delta for this study, which is focused on the analyses of sedimentological, statistical analysis, AMS C14 dating and paleoenvironment interpretation based on the benthic foraminiferal fossils. Foraminiferal shell do not exist between 30000 and 12000 yr B.P., indicating the environment of this sections might be terrestrial. Between 12000 and 8000 yr B.P., the southern core do not have traces of foraminifera, suggesting the deposition site was terrestrial. The northern core contains the benthic foraminiferal shell between 12000 and 9000 yr B.P. The foraminiferal assemblage indicates the sedimentation might be a inner shelf like enviroment. An estuarine like environment was suggested between 9000 and 8000 yr B.P.. Between 8000 and 6000 yr B.P., foraminiferal cluster analysis indicates a middle to inner shelf environment at the southern core site; a inner shelf at the northern core. From 6000 to 3000 yr B.P., foraminiferal cluster analysis indicates a inner shelf at the south core while northern core foraminifera became fewer and the environment gradually changing to terrestrial facies. From 3000 yr B.P. upwards, foraminiferal cluster analysis indicates a shallower inner shelf at the southern core. From 2000 yr B.P. to today, the southern core changed to terrestrial.

Program Trading has gotten more popular recent years. According to thestatistics, there was about 53.6% of daily volume in the United States, and increased to 73% in 2009. With the universal of program trading, more people have begun to research program trading. The purpose of this paper is constructing a developed platform of program trading for researching or developing. In addition to developed platform, we provide the run-time environment, and three main functions: 1. The job scheduler 2. The high scalability 3. The developed platform In this paper, we use SLURM to implement an economical computing service for program trading. SLURM is a resource management software for some large clusters. However it lacked for an easy interface to the ended users. We modify Xinetd as the external interface for SLURM, and implement the program trading development platform for researching or developing. According to the result, using our scheduler and the external interface that modify from Xinetd can be effective in controlling the server resource and increase the availability.

If nodes got failed in a distributed application service, it will not only pay more cost to handle with these results missing, but also make scheduler cause additional loadings. For whole results don¡¦t recalculated cause by fault occurs, it will be recalculated data of fault nodes in backup machines. Therefore, this paper uses three methods: N + N nodes, N + 1 nodes, and N + 1 nodes with probability to experiment and analyze their pros and cons, the third way gives jobs weight before assigning them, and converts weight into probability and nice value(defined by SLURM[1]) to influence scheduler¡¦s decision of jobs¡¦ order. When fault occurs, calculating in normal nodes¡¦ results will back to control node, and then the fault node¡¦s jobs are going to be reassigned or not be reassigned to backup machine for getting complete results. Finally, we will analyze these three ways good and bad.

Clustering schemes can reduce energy consumption, prolong network lifetime and improve scalability in wireless sensor networks (WSNs). In a typical cluster-based WSN, sensor nodes are organized into clusters. Each cluster elects a cluster head (CH) node. The CH is responsible for collecting the sensed data from cluster members, aggregating data and transmitting data to the sink node via a multi-hop path through intermediate CHs. Thus, the use of cluster techniques not only shortens the transmission distances for sensor nodes but also reduces energy consumption; however, each cluster imposes a larger load on the CH. Under this situation, CHs closer to the sink node tend to use up their batteries faster than those farther away from the sink node due to imbalanced traffics among CHs. To overcome this problem, we contribute to the energy balancing issues in WSNs from two aspects. In the first work, we first analyze the corona model. Based on analysis results, we found that nearly balanced energy consumption of WSNs can be achieved with the additional help of arranging different initial conditions. We then propose the Energy-balanced Node Deployment with Balanced Energy (END-BE) scheme and Energy-balanced Node Deployment with Maximum Life-Time (END-MLT) scheme, which determine the cluster density for each corona according to the energy consumption of each CH. Simulation results show that energy consumption is nearly balanced by implementing END-BE, and the network lifetime is greatly improved by adopting END-MLT. In the second work, we development a novel cluster-based routing protocol for corona-structured wireless sensor networks in order to balance the energy consumption among CHs. Based on the relaying traffic of each CH conveys, adequate radius for each corona can be determined through nearly balanced energy depletion analysis, which leads to balanced energy consumption among CHs. Simulation results demonstrate that our clustering approach effectively improves the network lifetime, residual energy and reduces the number of CH rotations in comparison with the Multi-Layer Clustering Routing Algorithm (MLCRA).

The chemical characterization of individual nanoparticles (NPs) </= 100 nm in diameter is one of the current frontiers in analytical chemistry. We present here, a methodology for the characterization of individual NPs by obtaining molecular information from single massive cluster impacts. The clusters used in this secondary ion mass spectrometry (SIMS) technique are Au4004+ and C60+. The ionized ejecta from each impact are recorded individually which allows to identify ions emitted from a surface volume of ~10 nm in diameter and 5-10 nm in depth. The mode of analyzing ejecta individually from each single cluster impact gives insight into surface homogeneity, in our case NPs and their immediate surroundings. We show that when the NPs (50 nm Al) are larger than the size of the volume perturbed by the projectile, the secondary ion emission (SI) resembles that of a bulk surface. However, when the NP (5 nm Ag) is of the size range of the volume perturbed by projectile the SI emission is different from that of a bulk surface. As part of this sub-assay volume study, the influence of neighboring NP on the SI emission was examined by using a mixture of different types of NPs (5 nm Au and 5 nm Ag). The methodology of using cluster SIMS via a sequence of stochastic single impacts yield information on the surface coverage of the NPs, as well as the influence of the chemical environment on the type of SI emission. We also present a case of soft landing NPs for laser desorption ionization mass spectrometry. NPs enhance the SI emission in a manner that maintains the integrity of the spatial distribution of molecular species. The results indicate that the application can be extended to imaging mass spectrometry.

A "peer advisory group" essentially melds a business advisory board with a peer group. Peer advisory groups consist of business managers who meet together for the purpose of mutual self-improvement and learning through the sharing of experiences. The entire peer advisory group concept encompasses many variations and this research focuses on groups consisting of farm managers. Unfortunately, some farm managers who wish to participate have expressed frustration with group formation: they find it difficult to identify suitable individuals to participate in a peer advisory group with. Peer advisory groups can take many forms, and experts have suggested an individual should specifically seek out people interested in the same type of group. For example, an individual who wants to strictly focus discussion on production issues should seek out other individuals who also seek to focus on production discussions. Some individuals have suggested that some type of "clearinghouse" organizations could be beneficial in assisting individuals with the peer advisory group formation problem. Such an organization would likely need to adapt some sort of method for identifying individuals who have interest in a similar type of group. Although this could be approached from several different angles, one possible approach involves the practice of cluster analysis?a wide set of procedures intended to break down a set of objects into "clusters" of individuals with similar attributes. Cluster analysis comes with several attractive benefits; however, literature includes countless variations in the methods and criticisms of certain aspects of the methodology. This thesis focuses on using cluster analysis to assist with peer advisory group formation. More specifically, this thesis seeks to answer the following question: how could a clearinghouse organization apply cluster analysis methods to a pool of candidates to effectively create peer advisory groups congruent to the individuals' needs and wants? An approach was proposed which differs slightly from traditional cluster analysis methods, and this was applied to a hypothetical pool of candidates, along with several control methods. The proposed approach was found to most effectively create peer advisory groups which fulfilled the desires of the individuals.

With globalization and knowledge economy, although distance between spaces and obstacles to social and economic activities are reduced, does variation of space not exist in regional space anymore? Has effect of regional space on economic development changed? Many economic activities, especially research and development, still rely on face-to-face communication, but geographical link is still beneficial to technology sharing and decrease in cost. It¡¦s observed that research and development that knowledge economy relies on still emphasizes geographical link, localization of learning networks, and face-to-face communication, so clustering of high-tech industry is still popular in the world. In order to solve the abovementioned questions, this research reviews and discusses the theory and research of clustering economy, and analyzes the relationship between clustering of high-tech industry and innovation on the basis of Taiwan¡¦s cities or counties with last twenty¡¦s survey of industrial, business, and service industries. This research discusses effect on clustering of technology industry and its innovative variants. In addition, it¡¦s hypothesized that clustering level of technology industry and innovation of industry are interfacing with each other, in other words, it¡¦s hypothesized that variants as Taiwan¡¦s technology industry and innovation are interfacing with each other instead of being independent. The relationship between clustering of Taiwan¡¦s technology industry and innovation is investigated by 2SLS. The result shows that clustering of technology industry and innovative production have positive correlation, that is to say, clustering of technology industry is beneficial, and it¡¦s also beneficial to innovation of industry, so clustering of industry speeds up. Results of this research show that technology industry on this island has notable MAR professional dynamic external economics, implying that the more professional clustered one region¡¦s technology industry is, the more beneficial to one region¡¦s professional growth of technology industry is. The more noticeable Porter regional competitive dynamic external economic effect on technology industry is, the more competitive a technology industry is, and the more prevalent one region¡¦s technology is. Technology industry has noticeable human resource dynamic external economics, showing that the better educational background of one region¡¦s population is, the more growth of one region¡¦s technology industry will be. Clustering industry of agglomeration economy is the primary reason of formation of cities or space centering of economic activities, and it motivates innovation of an industry and development of a city. This research suggests that government should take advantage of clustering knowledge capital of space to multiply effect of clustering and knowledge capital to do space management in terms of future urban space management.

The original of industrial cluster analysis is to distinguish what is cluster. It is developing to overview industrial district and to conclude the potential industry. In the light of these defects, we cloud improve them for industrial development. This industrial cluster analysis of variables by literatures, including of Industrial Concentration Factor, Cluster Dependency Factor, Economic Prosperity Factor, and four strategic resources that influence development of cluster, including of High Quality Human Resource, Technology and Knowledge Resource, Infrastructure, Capital. Using the questionnaire and interview with members in the cluster. The results of research: (1)There is a orientation of TFT-LCD industrial cluster in the Southern Science Park and show a vertical industrial cluster than horizontal cluster. (2)Material and Key part of equipment is complete and available, but there is only one application firm that produces large TFT-LCD. (3) TFT-LCD industry is important in the district and creating economic development. (4)It is difficult to find many talents about TFT-LCD industry and High Quality Human Resource is positive effect to this cluster.(5)As a result of TFT-LCD industry is at initial stage, they have less demand of Technology and Knowledge Resource, but it is increasing in the future.(6)The films are satisfied of water and electricity system, but they think that the staff cloud not get better quality of life in the district.(7) As a result of using capital without borders and Taiwan¡¦s government take TFT-LCD industry seriously, the films get capital smoothly. Key words¡GSouthern Science Park ¡BThin-Film Transistor Liquid-Crystal Display ,TFT-LCD¡BIndustrial Cluster¡BLocation Quotient.