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Due to an increasing demand from decision makers for proper economic evaluations of health care services, cost-effectiveness analyses are becoming increasingly frequent. The statistic of interest in cost-effectiveness analysis is the incremental cost effectiveness ratio (ICER). When patient-specific data on costs and effects of alternative interventions is available, it can be used to quantify the uncertainty in the estimate of the ICER. Expressing this uncertainty by using confidence intervals has been recommended. However, because the statistic of interest is a ratio of two correlated random variables, its variance cannot be estimated exactly. Furthermore, the distribution of the ratio is unknown. Recently, several approximate methods have been proposed for calculating confidence intervals for the incremental cost-effectiveness ratio. These include two parametric methods: one which relies on a Taylor's Series approximation of the variance, and one based on Fieller's theorem; as well as a number of methods which rely on bootstrapping methodology. In this manuscript, these methods were applied to data obtained from a randomized clinical trial in which both health resources consumed and health outcomes were observed. Furthermore, several variations of the bootstrapping methods were proposed and applied to the same data set. Probabilities of the true ICER being in given ranges were also estimated using a bootstrapping approach. Finally, issues of sample size and power were briefly considered. The relative advantages and disadvantages of the different approaches were discussed. / Thesis / Master of Science (MS)

A vertex υ in a set S is said to be cost effective if it is adjacent to at least as many vertices in V\S as it is in S and is very cost effective if it is adjacent to more vertices in V\S than to vertices in S. A dominating set S is (very) cost effective if every vertex in S is (very) cost effective. The minimum cardinality of a (very) cost effective dominating set of G is the (very) cost effective domination number of G. Our main results include a quadratic upper bound on the very cost effective domination number of a graph in terms of its domination number. The proof of this result gives a linear upper bound for hereditarily sparse graphs which include trees. We show that no such linear bound exists for graphs in general, even when restricted to bipartite graphs. Further, we characterize the extremal trees attaining the bound. Noting that the very cost effective domination number is bounded below by the domination number, we show that every value of the very cost effective domination number between these lower and upper bounds for trees is realizable. Similar results are given for the cost effective domination number.

For a graph G=(V, E) and a set of vertices S⊆ V, a vertex v∈S is said to be very cost effective if it is adjacent to more vertices in V{set minus}. S than in S. A bipartition π= {S, V{set minus}. S} is called very cost effective if both S and V{set minus}. S are very cost effective sets. Not all graphs have a very cost effective bipartition, for example, the complete graphs of odd order do not. We characterize the cactus graphs having a very cost effective bipartition. Also, we show that if a graph G or H has a very cost effective bipartition, then so does the Cartesian product G□ H.

As WWW service grow up rapidly and becomes the most popular information system on the internet, web site owner invest heavily to improve the performance of web server. And, because of the 'Server Farm' architecture comes real, web server performance breaks the limit of single server, which directly cause server performance improvement. All these factors raise the cost of website performance measurement program to catch up server performance. Besides, because of dynamic webpage and database linkage are applied widely in production environment. HTTP requests (for example, sessions) with state and identifications increase rapidly. Traditional Web Benchmarking methods are out of date and not supporting these new transaction models. Also, traditional benchmarking methodologies only provide the max/average values for overview, which can not properly describe the performance of the websites with massive dynamic webpages. All these problems shows the traditional benchmarking methodologies are not sufficient for today's technologies. In this paper, we have designed and implemented a configurable and cost-effective website performance measurement program against these problems. We introduced the concept of 'workload', and pre-design detailed HTTP request table, where time, contains, and HTTP commands to use can be assigned. Also we use configurable and replaceable design of open modules and divide the major modules into workload generator, load generator and report generator. These modules can be even separated into three independent programs, which makes this benchmark program become more flexible and adaptive to fit new technologies without adjusting the kernel. We also introduced the concept of 'Virtual User' to describe a real user behavior. We could keep the HTTP state and identification by automatic reply via cookie and assigning user identification in the same process. To increase the efficiency, each load generator can do self-diagnostics and quantify the measurements, and properly reassign the workloads by the value returned by the system. These makes every load generator do everything it could, and not been halted by the low-speed machine. And we can also prevent the mis-measurement by overloading. From the result of the experience, our design can describe the web server performance and load changes by time. We can also compare it to request category and URL, to show the root of causes and time basis to administrator. Overall, our web benchmarking methodology shows the strength to traditional web benchmarking methods.

For any integer k≥0, a set of vertices S of a graph G=(V,E) is k-cost-effective if for every v∈S,|N(v)∩(V∖S)|≥|N(v)∩S|+k. In this paper we study the minimum cardinality of a maximal k-cost-effective set and the maximum cardinality of a k-cost-effective set. We obtain Gallai-type results involving the k-cost-effective and global k-offensive alliance parameters, and we provide bounds on the maximum k-cost-effective number. Finally, we consider k-cost-effective sets that are also dominating. We show that computing the k-cost-effective domination number is NP-complete for bipartite graphs. Moreover, we note that not all trees have a k-cost-effective dominating set and give a constructive characterization of those that do.

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In this paper, we present how to optimize our ARM7TDMI instruction set compatible microprocessor. The ARM7TDMI is a 32-bit microprocessor developed by ARM Ldt. It used in embedded application such as mobile phones, pager and PDAs. The ARM7 family owes its success to the combination of low power, low cost and high performance. However, as applications become more complex and integrate more and more functionality, the processor is required to provide more and more performance. We tune the hardware simply, no use complex hardware, to complete performance optimization. We use synthesis tool to synthesize our RTL design and analyze timing to fund the critical path of our microprocessor. We will describe how to optimize the critical path to increase performance.