• Structural Engineering and Mechanics
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• v.22 no.6
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• pp.665-683
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• 2006

The strength behaviors of Fiber Reinforced Plastics (FRP) Composites can be greatly influenced by the properties of constitutive materials, the laminate structures, and load conditions etc, accompanied by many uncertainty factors. So the reliability study on FRP is an important subject of research. Many achievements have been made in reliability studies based on the probability theory, but little has been done on the roles played by fuzzy variables. In this paper, a fuzzy reliability model for FRP laminates is established first, in which the loads are considered as random variables and the strengths as fuzzy variables. Then a numerical model is developed to assess the fuzzy reliability. The Monte Carlo simulation method is utilized to compute the reliability of laminas under the maximum stress criterion. In the second part of this paper, a generalized fuzzy reliability model (GFRM) is proposed. By virtue of the fact that there may exist a series of states between the failure state and the function state, a fuzzy assumption for the structure state together with the probabilistic assumption for strength parameters is adopted to construct the GFRM of composite materials. By defining a generalized limit state function, the problem is converted to the conventional reliability formula that enables the first-order reliability method (FORM) applicable in calculating the reliability index. Several examples are worked out to show the validity of the models and the efficiency of the methods proposed in this paper. The parameter sensitivity analysis shows that some of the mean values of the strength parameters have great influence on the laminated composites' reliability. The differences resulting from the application of different failure criteria and different fuzzy assumptions are also discussed. It is concluded that the GFRM is feasible to use, and can provide an effective and synthetic method to evaluate the reliability of a system with different types of uncertainty factors.

• Journal of Korea Water Resources Association
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• v.48 no.9
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• pp.757-768
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• 2015

Recently, climate change has affected short time concentrated local rainfall and unexpected heavy rain which is increasingly causing life and property damage. In this research, arithmetic average analysis, weighted average analysis, and principal component analysis are used for predicting flood risk. This research is foundation for application of predicting flood risk based on annals of disaster and status of urban planning. Results obtained by arithmetic average analysis, weighted average analysis, and principal component analysis using many factors affect on flood are compared. In case of arithmetic average analysis, each factor has same weights though it is simple method. In case of weighted average analysis, correlation factors are complex by many variables and multicollinearty problem happen though it has different weights. For solving these problems, principal component analysis (PCA) is used because each factor has different weights and the number of variables is smaller than other methods by combining variables. Finally, flood risk assessment considering flood control ability and urban environment risk in former research is predicted.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.201-206
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• 2020

Diversification of project delivery methods (PDM) under ever-changing construction business environment has significantly changed the role of project participants. Active efforts to effectively sharing the roles and responsibilities have been observed in the project management offices (PMOs) among owner/operator organizations as well as engineering, procurement, construction and maintenance (EPCM) firms. In order for being effective in a holistic way throughout the project life-cycle, a PMO needs to have 'adequate management skills' as well as 'essential technical capabilities' in cooperating with many different participants. One of the well-known examples of the PMO's tool to support these skills and capabilities is the effective 'work packaging (WP)' that serves as a common basis integrating all relevant information in a structured manner. In an attempt to enhance the construction productivity, the concept of 'advanced work packing (AWP)' has been introduced by Construction Industry Institute (CII). The AWP enables productivity to be improved by early planning of construction packages in the design phase "with the end in mind". The purpose of this study is to identify and evaluate the 'variables' of advanced work packing (AWP) for life-cycle information integration. Firstly, an extended concept of advanced WP based on the CII AWP was defined in order to comprehend many different issues of business functions (e.g. cost, schedule, quality, etc.). A structured list of major components and variables of AWP were then identified and examined for practical viability with real-world examples. Strategic fits and managerial effectiveness were stressed throughout the analyses. Findings, implications and lessons learned are briefly discussed as well.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.132-139
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• 2009

Yield is a very important measure that can expresses simply for productivity and performance of company. So, yield is used widely in many industries nowadays. With the development of the information technology and online based real-time process monitoring technology, many industries operate the production lines that are developed into automation system. In these production lines, the product structures are very complexity and variety. So, there are many multi-variate processes that need to be monitored with many quality characteristics and associated process variables at the same time. These situations have made it possible to obtain super-large manufacturing process data sets. However, there are many difficulties with finding the cause of process variation or useful information in the high capacity database. In order to solve this problem, neural networks technique is a favorite technique that predicts the yield of process for process control. This paper uses a neural networks technique for improvement and maintenance of yield in manufacturing process. The purpose of this paper is to model the prediction of a sub process that has much effect to improve yields in total manufacturing process and the prediction of adjustment values of this sub process. These informations feedback into the process and the process is adjusted. Also, we show that the proposed model is useful to the manufacturing process through the case study.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.257-263
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• 2019

This paper is a study on mathematical aspects that can be basic for understanding and applying the contents of machine learning. If you are familiar with mathematics in the field of computer science, you can create algorithms that can diversify researches and implement them faster, so you can implement many real-life ideas. There is no curriculum standard for mathematics in the field of machine learning, and there are many absolutely lacking mathematical contents that are taught in the curriculum presented at existing universities. Machine learning now includes speech recognition systems, search engines, automatic driving systems, process automation, object recognition, and more. Many applications that you want to implement combine a large amount of data with many variables into the components that the programmer generates. In this course, the mathematical areas required for computer engineer (CS) practitioners and computer engineering educators have become diverse and complex. It is important to analyze the mathematical content required by engineers and educators and the mathematics required in the field. This paper attempts to present an effective range design for the essential processes from the basic education content to the deepening education content for the development of many researches.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.9
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• pp.1333-1342
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• 2013

New & renewable energy becomes a crucial subject to solve the problems inherent in the current energy resources, which results in the fast development of the new & renewable energy industry worldwide. However, not only its base is still weak but the high initial investment for technology development and certain scale of an energy market are required in many cases. For this reason, many countries in the world, including Korea, run the energy policies to foster the new & renewable energy industry such as RSP and FIT. In general, a policy should be established to take various, intertwined interests as well as a number of variables related to economic, social, environmental, and international matters into comprehensive consideration. For new & renewable energy industry, there are many variables to be considered and indexes necessary for evaluation but it is hard to take all of them into account. Even though they were considered, no criteria are available for use in a consistent manner. Therefore, this study plans to develop an evaluation model for the Korean new & renewable energy policy.

• Journal of Korea Water Resources Association
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• v.40 no.4
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• pp.299-311
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• 2007

Climatic abnormal phenomena involving El Nino and La Nina have been frequently reported in recent decades. The interannual climate variability represented by El Nino-Southern Oscillation (ENSO) is sometimes investigated to account for the climatic abnormal phenomena around the world. Although many hydroclimatologists have studied the impact of ENSO on regional precipitation and streamflow, however, there are still many difficulties in finding the dominant causal relationship between them. This relationship is very useful in making hydrological forecasting models for water resources management. In this study, the seasonal relationships between ENSO and hydrologic variables were investigated in Korea. As an ENSO indicator, Southern Oscillation Index (SOI) was used. Monthly precipitation, monthly mean temperature, and monthly dam inflow data were used after being transformed to the standardized normal index. Seasonal relationships between ENSO and hydrologic variables were investigated based on the exceedance probability and distribution of hydrologic variables conditioned on the ENSO episode. The results from the analysis of this study showed that the warm ENSO episode affects increases in precipitation and temperature, and the cold ENSO episode is related with decreases in precipitation and temperature in Korea. However, in some regions, the local relationships do not correspond with the general seasonal relationship.

• Management & Information Systems Review
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• v.38 no.3
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• pp.187-210
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• 2019

Companies shall hold social responsibility as a member of the social community. Corporate social responsibility uses corporate resources, yet it plays important roles in reducing social imbalance. Their responsibilities are highly associated with the corporate sustainability. Many earlier studies on the association between corporate social responsibility and corporate sustainability have been attempted. Yet it should be mentioned that they do not show a variety of realities as linearity between dependent variables and independent variables were assumed. Thus, this study aims to analyze Markov blanket, a node of minimum descriptive variables that relieve a rigid assumption among variables and affect corporate sustainability by using Bayesian network. Sensitivity analysis was used to elicit how other variables affect by reflecting the complex reality when real factors are changed. As an important result of this study, the firm's future earnings sustainability is naturally related to operating earnings, and as the corporate governance structure is sound, the firm is able to steadily fulfill its social responsibility. However, the fact that the size of a company is large does not mean that it is in good compliance with corporate laws. This would not be unrelated to the fact that many of today's companies are not complying with the law and are suffering social condemnation. Results from this study will serve as a useful analytic tool when investors and creditors showing interests in corporate sustainability for assessing the value of companies and making investment decisions. Moreover, they can be used as references for relevant agency supervising capital markets to establish or improve appropriate institutions aimed at improving corporate sustainability.

• Asia Marketing Journal
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• v.14 no.1
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• pp.1-24
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• 2012

Nowadays, customer satisfaction has been one of company's major objectives, and the index to measure and communicate customer satisfaction has been generally accepted among business practices. The major issues of CSI(customer satisfaction index) are three questions, as follows: (a)what level of customer satisfaction is tolerable, (b)whether customer satisfaction and company performance has positive causality, and (c)what to do to improve customer satisfaction. Among these, the second issue is recently attracting academic research in several perspectives. On this study, the second issue will be addressed. Many researchers including Anderson have regarded customer satisfaction as core competencies, such as brand equity, customer equity. They want to verify following causality "customer satisfaction → market performance(market share, sales growth rate) → financial performance(operating margin, profitability) → corporate value performance(stock price, credit ratings)" based on the process model of marketing performance. On the other hand, Insoo Jeon and Aeju Jeong(2009) verified sequential causality based on the process model by the domestic data. According to the rejection of several hypotheses, they suggested the balance model of marketing performance as an alternative. The objective of this study, based on the existing process model, is to examine the causal relationship between customer satisfaction and corporate value performance. Anderson and Mansi(2009) proved the relationship between ACSI(American Customer Satisfaction Index) and credit ratings using 2,574 samples from 1994 to 2004 on the assumption that credit rating could be an indicator of a corporate value performance. The similar study(Sangwoon Yoon, 2010) was processed in Korean data, but it didn't confirm the relationship between KCSI(Korean CSI) and credit ratings, unlike the results of Anderson and Mansi(2009). The summary of these studies is in the Table 1. Two studies analyzing the relationship between customer satisfaction and credit ratings weren't consistent results. So, in this study we are to test the conflicting results of the relationship between customer satisfaction and credit ratings based on the research model considering Korean credit ratings. To prove the hypothesis, we suggest the research model as follows. Two important features of this model are the inclusion of important variables in the existing Korean credit rating system and government support. To control their influences on credit ratings, we included three important variables of Korean credit rating system and government support, in case of financial institutions including banks. ROA, ER, TA, these three variables are chosen among various kinds of financial indicators since they are the most frequent variables in many previous studies. The results of the research model are relatively favorable : R², F-value and p-value is .631, 233.15 and .000 respectively. Thus, the explanatory power of the research model as a whole is good and the model is statistically significant. The research model has good explanatory power, the regression coefficients of the KCSI is .096 as positive(+) and t-value and p-value is 2.220 and .0135 respectively. As a results, we can say the hypothesis is supported. Meanwhile, all other explanatory variables including ROA, ER, log(TA), GS_DV are identified as significant and each variables has a positive(+) relationship with CRS. In particular, the t-value of log(TA) is 23.557 and log(TA) as an explanatory variables of the corporate credit ratings shows very high level of statistical significance. Considering interrelationship between financial indicators such as ROA, ER which include total asset in their formula, we can expect multicollinearity problem. But indicators like VIF and tolerance limits that shows whether multicollinearity exists or not, say that there is no statistically significant multicollinearity in all the explanatory variables. KCSI, the main subject of this study, is a statistically significant level even though the standardized regression coefficients and t-value of KCSI is .055 and 2.220 respectively and a relatively low level among explanatory variables. Considering that we chose other explanatory variables based on the level of explanatory power out of many indicators in the previous studies, KCSI is validated as one of the most significant explanatory variables for credit rating score. And this result can provide new insights on the determinants of credit ratings. However, KCSI has relatively lower impact than main financial indicators like log(TA), ER. Therefore, KCSI is one of the determinants of credit ratings, but don't have an exceedingly significant influence. In addition, this study found that customer satisfaction had more meaningful impact on corporations of small asset size than those of big asset size, and on service companies than manufacturers. The findings of this study is consistent with Anderson and Mansi(2009), but different from Sangwoon Yoon(2010). Although research model of this study is a bit different from Anderson and Mansi(2009), we can conclude that customer satisfaction has a significant influence on company's credit ratings either Korea or the United State. In addition, this paper found that customer satisfaction had more meaningful impact on corporations of small asset size than those of big asset size and on service companies than manufacturers. Until now there are a few of researches about the relationship between customer satisfaction and various business performance, some of which were supported, some weren't. The contribution of this study is that credit rating is applied as a corporate value performance in addition to stock price. It is somewhat important, because credit ratings determine the cost of debt. But so far it doesn't get attention of marketing researches. Based on this study, we can say that customer satisfaction is partially related to all indicators of corporate business performances. Practical meanings for customer satisfaction department are that it needs to actively invest in the customer satisfaction, because active investment also contributes to higher credit ratings and other business performances. A suggestion for credit evaluators is that they need to design new credit rating model which reflect qualitative customer satisfaction as well as existing variables like ROA, ER, TA.

• Health Policy and Management
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• v.24 no.2
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• pp.191-202
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• 2014

Background: The organizational citizenship behavior is generally known as the important factor relevant to the organizational effectiveness. This research examined the mediating effect of the organizational citizenship behavior of hospital employees on the organizational effectiveness. Methods: Data were collected from 1,112 employees located in city of Seoul, Kyunggi and Chungnam province through self-administered questionnaires. Collected data were analyzed using IBM SPSS ver. 20.0, frequency analysis, t-test, analysis of variance, regression analysis, and path analysis. The main findings of the study are as follows. Results: First, it was found that many characteristics variables of personality, job, and relationship together affected organizational citizenship behavior of hospital employees. Especially, the following variables of negative affectivity, desire for growth, job value, job significance, and job security were found to have significant effect on the organizational citizenship behavior of hospital employees. Second, the results of path analysis showed that, through the mediating effect of organizational citizenship behavior, personality variables of positive and negative affectivity, and desire for growth, job characteristics variables of job value, job significance, and job security, and relationship variables of organizational support and task interdependence, had significant total effects on the level of job satisfaction of hospital employees. Conclusion: As a result, the organizational citizenship behavior seems to have both direct and indirect effects on the organizational effectiveness of hospital employees. Based on above findings, some theoretical and practical implications were discussed.