The 37 indicators for performance evaluation of public sewage management agencies are divided into four major categories (agency manpower management ability, wastewater treatment plant operation and management, sludge and water reuse, service quality) in the first stage, and the necessity and score acquisition for the detailed indicators by each major category in the second stages. Priority was investigated through the Analytic Hierarchy Process (AHP) analysis technique for ease and relevance of company efforts. Also, based on the results of this analysis, integrated type weighting and relative importance were analyzed. As a result of the analysis, the weight and relative importance of the first stage classification were in the order of wastewater treatment plant operation and maintenance, operation agency manpower management ability, sludge and water reuse, and service quality. As a result of analyzing the weights and priorities of the detailed performance indicators in the second stage, it was found that operator’s career years, the percentage of certification holding rate in operators, compliance with the effluent water quality standards, training times for operators, and efforts to manage hazardous chemicals were important. Some of the indicators of operation agency performance evaluation may include indicators in which the performance of the company's efforts is underestimated or overestimated. In order to improve this, it is necessary to give weights in consideration of the necessity of the indicator, the relevance of the company's efforts, and the ease of obtaining scores.

PURPOSES: The purpose of this study is to analyze the characteristics of the weight values of evaluation items by traffic safety project type. METHODS: In general, a large-scale investment in projects such as the traffic safety project requires economic analyses to be performed in advance. However, there is an argument for considering special characteristics of the traffic safety project. Therefore, this study conducted characteristic analysis of the weight values of evaluation items. The analysis consisted of two steps. The first step was hypothesis verification using analysis of variance (ANOVA). In this process, the authors examined whether the weight of evaluation items is the same regardless of the traffic safety project type. Based on the first step's results, the authors proceeded to the second step. The objective of this step was to analyze how different the weight values are by traffic safety project type using an analytic hierarchy process. RESULTS: According to the ANOVA test results, the benefit to cost ratios have different weight values based on traffic safety project type at the 0.01 significance level. The policy evaluation items, such as the plans connection, resident opinion, and regional equity, also showed the same results except that the result for the related plans connection was statistically significant at the 0.05 level. Based on the first step's result, the AHP analysis in the second step showed that the traffic safety projects for vulnerable users and pedestrians have very low weight values in economic evaluation factors compared with other safety project types. The weight values for vulnerable users and pedestrians were 0.29 and 0.26, respectively, in economic evaluation items. On the other hand, the weight values for other safety project types were around 0.6. Among the policy evaluation items, resident opinion showed a higher weight value than other factors, such as connection and regional equity items. CONCLUSIONS: The social and economic impact of a traffic safety project varies by project type and project characteristics. Although the economic approach is overarching and a reasonable methodology is applied for large-scale projects, it should be noted that the safety issue, especially for transportation of vulnerable uses, requires a non-economical approach. Based on the analysis results, this study suggests that the priority of the projects should be determined by separating them into independent assessment groups depending on their characteristics.

Two key challenges in statistical relational learning are uncertainty and complexity. Standard frameworks for handling uncertainty are probability and first-order logic respectively. A Markov logic network (MLN) is a first-order knowledge base with weights attached to each formula and is suitable for classification of dataset which have variables correlated with each other. But we need domain knowledge to construct first-order logics and a computational complexity problem arises when calculating weights of first-order logics. To overcome these problems we suggest a method to generate first-order logics and learn weights using association analysis in this study.

Last 2003, the CRM mayor was not lively glaringly. At beginning of the year, it may be said that gained result fewer than half of that is forecasted. Enterprises are seen that there are a lot of occasions that did not carry CRM project that planned very first time in practice or put off investment program until 2004 altogether. This can see that it is thing which CRM's accuracy of data analysis process drops up to now and investment of enterprises is unprepared. In this paper, It consolidates the necessity on a LTV (Life Time Value) and analyzes data which is concerned of Customer Value. Under the these environments, defines the LTV rule that can improve the customer value. And then, Scheduling plays an important role in shop floor planning. Therefore, this study tries to proposed that Scheduling by customer needs group for minimizing the problem.

Today's environment of enterprise is changing, They have to face customer' demands with the right product, the right service and supply them at the right time. And also cut down logistics and inventory cost and bring up the profit as much as they can. This means the change of putting enterprise first in importance to putting customer first importance. therefore to correspond to customer's demand, shorting lead time is becoming a essential condition. The answer to this changes of environment is supply chain management. In this paper, It consolidates the necessity on a LTV(Life Time Value) and analyzes data which is concerned of Customer Value. Under the these environments, defines the LTV(Life Time Value) rule that can improve the customer value. We solved this problems using AHP(Analytic Hierarchy Process) for consistency at relationship matrix, AHP(Analytic Hierarchy Process) is based on Saaty's consistency rate. If consistency rate is under 0.1 point, preference rate's weights are acceptable. This study develop a program for AHP weights and support Satty's consistency rate.

본 연구는 다기준 의사결정 문제에서 항상 발생하는 가중치와 대안들의 평가치에 대한 불확실성을 최소화하기 위해 민감도 분석을 수행하는 절차를 제시하였다. 제기되는 가중치에 대한 불확실성을 극복하기 위해 일반적으로 순위가 뒤바뀔 수 있는 가장 민감한 평가기준의 결정과 대안의 효과 측정자료의 결정이 있다. 본 연구는 유량확보와 수질개선을 위한 수자원 계획수립을 위해 가중합계법을 이용한 문제에 두 경우의 민감도 분석을 모두 수행하였다. 이 과정에서 결정계수와 민감도 계수를 산정하여 이용하였다. 본 연구에서 제시한 민감도 분석 과정은 향후 수자원 계획 수립에 폭넓게 활용될 수 있다.