In this study, DLC thin films were electrodeposited at low DC potential using a mixture of acetic acid and DI water with different ratio. The parameters of DLC thin film deposition include the DC potential, deposition temperature, concentration of electrolyte solution, were correlated to the growth mechanism. The amount of nitrogen incorporated into DLC thin films were varied with the deposited temperature. The characteristics of DLC films by various measurements such as : the I-t curves of DLC film growth, SEM, AFM, FTIR, XPS, Raman and N&K spectroscopy, were investigated in detail. Experimental results showed that the surface roughness decreased, and sp3/sp2+sp3 value of DLC increased with the deposition temperature and deposition time. Optical properties showed that the refractive index, optical energy gap increased with the deposition temperature. For SEM cross-section measurement, it showed that the thickness of DLC films decreased due to the erosion process. However, the N-DLC films become graphitization. According to our study, we find that the surface morphology of the N-DLC films are homogeneous and compact. However, with the increase of the deposition temperature, the ratio of sp3-C-N bonds increase and the ratio of sp2-C-C bonds decrease, and these lead to the increase of refractive index and optical energy gap.

This thesis is an investment strategy that seeks to profit from increases in market volatility. There have been several boom and bust cycles during the past fifteen years and volatility is projected to continue forward as a result of global asset misallocation and challenges stemming from debt liquidity. Volatility is measured by the Chicago Board of Options Exchange VIX volatility index. A proposed mean reversion strategy uses the VIX as a contrarian indicator of hope and fear to time decisions at extreme levels that have been determined through statistical analysis. This thesis found through back testing that market timing is possible at extreme levels of fear but is less reliable during extreme levels of hope and complacency. This strategy that utilizes measures of sentiment does however outperform the general market despite being active only five months on average per year. By synthesizing a broad range of fundamental, technical, and behavioral research, this thesis develops a unique contribution and practical set of market trading guidelines. The significance of these findings will help the individual investor to make better decisions during times of increased volatility.

The dissertation studies the relationship among durable goods, price indexes and monetary policy in two sticky-price models with durable goods. One is a one-sector model with only durable goods and the other is a two-sector model with durable and non-durable goods. In the models with durable goods, the COLI (Cost of Living Index) and the PPI (Producer Price Index) identical to the CPI (Consumer Price Index) measured by the acquisitions approach are distinguished, and the COLI/PPI ratio plays an important rule in monetary policy transmission. The welfare function based on the household utility can be represented by a quadratic function of the quasi-differenced durables-stock gaps and the PPI inflation rates. In the one-sector model, the optimal policy maximizing welfare is to keep the (acquisition) price and the output gap at a constant rate which does not depend on the durability of consumption goods. In the two-sector model with sticky prices, the central bank has only one policy instrument, so it cannot cope with distortions in both sectors. Simulation results show that the PPI is an adequate price index for monetary policy and that a policy of targeting core inflation constructed by putting more weight on prices in the sector producing more durable goods is near optimal.

Since its introduction in the year 2000 by Ahlswede et al., the network coding paradigm has revolutionized the way we understand information flows in networks. Traditionally, information transmitted in a communication network was treated as a commodity in a transportation network, much like cars on highways or fluids in pipes. This approach, however, fails to capture the very nature of information, which in contrast to material goods, can be coded and decoded. The network coding techniques take full advantage of the inherent properties of information, and allow the nodes in a network, not only to store and forward, but also to "mix", i.e., encode, their received data. This approach was shown to result in a substantial throughput gain over the traditional routing and tree packing techniques. In this dissertation, we study applications of network coding for guarantying reliable and secure information transmission in networks with compromised edges. First, we investigate the construction of robust network codes for achieving network resilience against link failures. We focus on the practical important case of unicast networks with non-uniform edge capacities where a single link can fail at a time. We demonstrate that these networks exhibit unique structural properties when they are minimal, i.e., when they do not contain redundant edges. Based on this structure, we prove that robust linear network codes exist for these networks over GF(2), and devise an efficient algorithm to construct them. Second, we consider the problem of securing a multicast network against an eavesdropper that can intercept the packets on a limited number of network links. We recast this problem as a network generalization of the classical wiretap channel of Type II introduced by Ozarow and Wyner in 1984. In particular, we demonstrate that perfect secrecy can be achieved by using the Ozarow-Wyner scheme of coset coding at the source, on top of the implemented network code. Consequently, we transparently recover important results available in the literature on secure network coding. We also derive new bounds on the required secure code alphabet size and an algorithm for code construction. In the last part of this dissertation, we study the connection between index coding, network coding, and matroid linear representation. We devise a reduction from the index coding problem to the network coding problem, implying that in the linear case these two problems are equivalent. We also present a second reduction from the matroid linear representability problem to index coding, and therefore, to network coding. The latter reduction establishes a strong connection between matroid theory and network coding theory. These two reductions are then used to construct special instances of the index coding problem where vector linear codes outperform scalar linear ones, and where non-linear encoding is needed to achieve the optimal number of transmission. Thereby, we provide a counterexample to a related conjecture in the literature and demonstrate the benefits of vector linear codes.

SAS has become an increasingly important public-health problem in recent years. It can abversely affect neurocognitive, cardiovascular, respiratory diseases and can also cause behavior disorder. Moreover, up to 90¢H of these cases are obstructive sleep apnea (OSA). Therefore, it is important that how to diagnose, detect and treat OSA. The respiratory disturbance index is one parameter of estimating OSA. Polysomnography can monitor the OSA with relatively fewer invasive techniques. However, polysomnography-based sleep studies are expensive and time-consuming because they require overnight evaluation in sleep laboratories with dedicated systems and attending personnel. Based on the digital oximetry, this work introduces the estimating respiratory disturbance index. In particular, via signal processing, feature parameters and artificial intelligence, this thesis describes an off-line SpO2-based RDI estimating system.

In the dynamic era, knowledge management is an important means that enterprises show one's talent and maintain the advantage of the competition. If enterprises can manage knowledge well, it can grasp and win the first chance of strength. And in order to maximize the knowledge management effectively, enterprises need to utilize the performance index to weigh the effect, and then improve it. In enterprises, the goal of organizational learning is creating knowledge and using knowledge to solve problems. So organizational learning closely linked with knowledge management. This study attempts to investigate the impact on KM performance based on the organizational learning perspective. As enterprises want to improve the performance index of knowledge management, they only need to find out key factors to the performance index, and then improve it. Furthermore, different KM strategies can help to find out influences on KM performance. When the KM performances of enterprises are not satisfactory, enterprises need to inspect the KM strategy to adopt suitably and adjust the KM strategy accordingly. This study also investigates how organizational learning enabler impacts organizational learning. This study used questionnaire investigation to prove the research model is fit or not, and used ANOVA and regression analysis to test all hypotheses. The result of the study shows that organizational learning has influence on knowledge management performance. Organization position and task complexity will enable organizational learning, and through different KM strategies, the impacts of KM performance based on organizational learning are different.

This research studies the degree of publicity made by Kaoshiung City Government and the anti-corruption condition caused by the degree of administrative transparency. This study also provides further understanding about present Kaoshiung City Government immediate online services, including people¡¦s requests and claims to Mayor¡¦s inbox and the anti-corruption advocated by the Department of Civil Service and Ethics: To explore how fast and how responses are made to citizens through Internet, and also to become the basis of anti-corruption index. To understand the expectations of civilians towards the overall government¡¦s publicity system. To establish a anti-corruption documentation system to provide sources of subsequent denotation of policy and knowledge transformation To design and suggest Kaoshiung¡¦s future anti-corruption policy, improve present file management and increase degree of publicity in order to achieve the goal of high quality and high efficiency To interview officials or others who involve with the administrative procedure, and provide concrete suggestions based on the content from the interview

Objective: To explore correclational relationship between the risk factors and medical resources consumption in cardiovascular disease patients. Methods: A database containing 44940 cardiovascular disease patients in a southern Taiwan Medical center from year 2003 to 2005 was chosen as studying sample. By applying Charlson Comorbidity Index as one of the major risk factors to these cardiovascular disease patients, then using liner regression to analyze the data for their relationship with medical resources consumption. Results: Medical resources consumption increases as the cardiovascular disease patients become older. The higher the comorbidity index weight with the patient, the more the patient consumes medical resources. A patient¡¦s comorbidity index weight has great influence to the length of hospital stay of the patient and the frequency of clinic visit of the patient. The higher the comorbidity index weight a patient he or she, is likely to stay in hospital longer or to see doctors more often. The variance inflation factor (VIF) of each independent variable is ranged between 1 and 1.343, which means there are no high correlations between independent variables in the modes. In other words, there is no correlative influence effect that would invalidate the assumption. Conclusion: The findings of this study can be a good reference to hospital disease management. In addition, they can be applied to predicting the risk factor in medical resources consumption. Also they can be adapted into medical insurance payment system, thereby improving medical resource distribution.

none

In recent years, many people use the World Wide Web and Internet to find information that they want. HTML is a document markup language for publishing hypertext on the WWW. HTML has been the target format for content developers around the world. Basically, HTML tags serve the primary purpose of describing how to display a data item. Therefore, HTML documents are difficult to find some useful information. That is because, HTML documents are mixed content with display tags. On the other hand, XML is the another data format for data exchange inter-enterprise applications on the Internet. In order to facilitate data exchange, industry groups define public Document Type Definitions (DTD) that specify the format of the XML documents to be exchanged between their applications. Moreover, WWW/EDI or Electric Commerce is very popular and a lot of business data uses XML to exchange information on the World Wide Web. Basically, XML tags describe the data itself. The contents (meaning) of the XML documents and the display format is separated. It could be easily to find meaningful information of the XML documents and analyze the information. Moreover, when a large volume of business data (XML documents) exists, one way to support the management of the XML documents is to apply the relational databases. For such an approach, we must transform the XML documents to the relational databases. In this thesis, we design and implement the indexing strategies to efficiently access XML documents. XML document is fundamentally different from relational data. XML is a hierarchical and nested document, it is very similar to the semistructured data model. The characteristic of semistructured data is that it may not have a fixed schema and it may be irregular or incomplete. Though, the semistructured data model is flexible in data modeling, it requires a large search space in query processing since there is no schema fixed in advance. Indexing is the way of how to improve query performance efficiently. However, due to the special properties of semistructued data, there are up to five types of queries: (1) complete single path, (2) specified leaf only, (3) specified intrapath, (4) specified attribute/element(value), and (5) multiple paths with the same level. In this thesis, we classify all possible queries into those five query types. Next, we create different indexes for different query types. Moreover, we design and implement the query transformation from XML query statements to SQL statements. Also, we create a user-friendly interface for users to input XML query statements. The whole system is implemented in JAVA and SQL Server 2000. From our experiences, we show that our indexing strategies can improve the XML query processing performance very well.