• Korean Journal of Construction Engineering and Management
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• v.16 no.2
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• pp.38-45
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• 2015

The risk analysis phase of construction risk management process is subdivided into the qualitative risk analysis that plays a major role, and the quantitative risk analysis acting as a supportive role. The traditional calculation method for quantifying a risk value that has been applied so far is an equation to multiply a probability by an impact simply, but its result shows the low risk value biased distribution. Although another equation that shows the high risk biased distribution as an alternative of traditional method was proposed, both of the low or high risk biased equations do not match with the statistical general knowledge that most natural phenomenons are close to the normal distribution. This study proposes a new risk value calculation method that is concentrated to the moderate risk value. Because the risk value distribution by a new method shows a normal shape similar to natural phenomenon, it helps to choose a middle level not biased to the low or high levels when choosing the level of risk response. Furthermore, it could contribute to improve the flexibility and rationality of risk analysis method by providing additional options for the risk value calculation.

• Journal of Korean Biological Nursing Science
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• v.16 no.2
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• pp.113-122
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• 2014

Purpose: This study was to identify predictors of drug dosage calculation error risk in newly graduated nurses. Methods: A total of 115 newly graduated nurses who passed their employment examination, but didn't work for hospital yet, were recruited from a university hospital. The data were analyzed by descriptive statistics, $X^2$-test, t-test, ANOVA, Pearson correlation coefficients, and stepwise multiple regression using the SPSS 18.0 program. Results: The mean score of 'drug dosage calculation ability' was $0.81{\pm}0.16$ and the mean score of 'certainty of calculation' was $2.95{\pm}0.60$ out of a 5 point scale. The error risk of drug dosage calculation was positively related to anxiety for drug dosage calculations (r=.388, p<.001), but negatively related to interest and confidence in mathematics (r=-.468, p<.001), confidence related to dosage calculations (r=-.426, p<.001). The main predictors of error risk related drug calculations in newly graduated nurses were identified as interest and confidence in mathematics (${\beta}$=-.468, p<.001). This factor explained about 21.9% of the variance in error risk of drug dosage calculation. Conclusion: The strategies used to decrease the error risk related drug dosage calculation such as improving interest and confidence in mathematics should be developed and implemented.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.636-647
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• 2004

The objective of this paper is to provide an improved reorder decision policy for general multi-echelon distribution systems utilizing the shared stock information. It has been known that traditional reorder policies sometimes show poor performance in distribution systems. Thus, in our previous research we introduced the order risk policy which utilizes the shared stock information more accurately for the 2-echelon distribution system and proved the optimality. However, since the real world supply chain is generally composed with more than 2 echelons, we extend the order risk policy for the general multi-echelon systems. Since the calculation of the exact order risk value for general multi-echelon systems is very complex, we provide two approximation methods for the real-time calculation. Through the computational experiment comparing the order risk policy with the existing policies under various conditions, we show the performance of the order risk policy and analyze the value of the shared stock information varying with the characteristics of the supply chain.

• IE interfaces
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• v.17 no.3
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• pp.359-374
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• 2004

The objective of this paper is to provide an improved reorder decision policy for general multi-echelon distribution systems utilizing the shared stock information. It has been known that traditional reorder policies sometimes show poor performance in distribution systems. Thus, in our previous research we introduced the order risk policy which utilizes the shared stock information more accurately for the 2- echelon distribution system and proved the optimality. However, since the real world supply chain is generally composed with more than 2 echelons, we extend the order risk policy for the general multi-echelon systems. Since the calculation of the exact order risk value for general multi-echelon systems is very complex, we provide two approximation methods for the real-time calculation. Through the computational experiment comparing the order risk policy with the existing policies under various conditions, we show the performance of the order risk policy and analyze the value of the shared stock information varying with the characteristics of the supply chain.

• Journal of Preventive Medicine and Public Health
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• v.43 no.6
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• pp.543-548
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• 2010

Objectives: The objective of this study was to calculate sample size and power in an ongoing cohort, Korea radiation effect and epidemiology cohort (KREEC). Method: Sample size calculation was performed using PASS 2002 based on Cox regression and Poisson regression models. Person-year was calculated by using data from '1993-1997 Total cancer incidence by sex and age, Seoul' and Korean statistical informative service. Results: With the assumption of relative risk=1.3, exposure:non-exposure=1:2 and power=0.8, sample size calculation was 405 events based on a Cox regression model. When the relative risk was assumed to be 1.5 then number of events was 170. Based on a Poisson regression model, relative risk=1.3, exposure:non-exposure=1:2 and power=0.8 rendered 385 events. Relative risk of 1.5 resulted in a total of 157 events. We calculated person-years (PY) with event numbers and cancer incidence rate in the nonexposure group. Based on a Cox regression model, with relative risk=1.3, exposure:non-exposure=1:2 and power=0.8, 136 245PY was needed to secure the power. In a Poisson regression model, with relative risk=1.3, exposure:non-exposure=1:2 and power=0.8, person-year needed was 129517PY. A total of 1939 cases were identified in KREEC until December 2007. Conclusions: A retrospective power calculation in an ongoing study might be biased by the data. Prospective power calculation should be carried out based on various assumptions prior to the study.

• Journal of the Korea Safety Management & Science
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• v.15 no.3
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• pp.113-125
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• 2013

According to 2012 OECD environmental report, Korea was ranked as the first country of water stress. Water footprint is a method to calculate water usage during the life cycle of a product from material procurement through production to disposal to recycle and to quantify the load to water resources. In water footprint calculation, water consumption unit is used. Agricultural water use is over 48% so it is urgent to mange that area Korea needs to spread the discussion about water footprint as quickly as possible, for the study to prevent social and environmental problems due to water shortage. This paper, through water footprint calculation and comparison in Chungju and Geochang areas, looks to counter measures for water risk, targeting domestically-produced apple.

• Journal of the Korea Institute of Building Construction
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• v.18 no.3
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• pp.295-303
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• 2018

In the DBB delivery system, the design stage and the construction stage are separated. Because of this, design changes frequently occur, and problems such as construction cost overrun, schedule delay, and quality deterioration happen as well. Recently, in the construction industry CM at Risk(CM@R) delivery system, which can systematically solve the above-mentioned problems of DBB delivery system, meet various demands of clients, and overcome the limited cost and period. In the CM@R delivery system, the contractor negotiates for a maximum guaranteed price(GMP) with the client at the design stage, and the CM performer carries out the construction within the GMP. However, uncertainties are inherent in the GMP calculation because the calculation is based on unfinished drawings and documents. In this study, a Probabilistic Earlier GMP Calculation Method by combining a probabilistic tool of Monte Carlo simulation with a case based reasoning is proposed so that the uncertainty in GMP calculation is reflected. After the earlier GMP is calculated, a process to calculate the $2^{nd}$ GMP at the time of around 80 % of detailed deign and to negotiate with the client to fix the final GMP is proposed. The Probabilistic Earlier GMP Calculation Method is verified through the case study. In this study, researchers set the range of GMP through the proposed probabilistic GMP calculation and tried to reduce the risk through negotiation between the client and the CM performer. The proposed method and process would contribute to the successful introduction of CM@R in Korea.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.9
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• pp.487-493
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• 2004

The electric power industry throughout the world is undergoing considerable changes from the vertically integrated utility structure to the deregulated market. However, the deregulated electricity market is operated with respect to theory of economical efficiency, and therefore, the system operator requires data with fast contingency ranking for security of the bulk power system. This paper compares the weather dependant probabilistic risk index(PRI) with the system performance index for power flow in the IEEE-RTS. The system performance index for power flow presents the power system stability. This paper presents fast calculation method for determining contingency ranking using the weather dependant probabilistic risk index(PRI). The probabilistic risk index can be classified into the case of normal and adverse weather. This paper proposes calculation method using the probabilistic risk index in determining contingency ranking required for security under the deregulated electricity market.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.65-72
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• 2001

With the recent rising project complexities and competitive environments in the construction projects, a risk management is recognized as more important management tool than the others. However, as most risk management techniques applied to the construction projects are centered around their initial phases and risk analyses, they are not developed into general project management technique such as time management, cost management and quality management, etc., that are usually applied in the process of construction. Thus, this paper proposes a response process to construction project risks based on the risk threshold and its calculation methodology applying a concept of VaR to establish risk management as general management technique in the construction projects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.959-981
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• 2017

Existing Android malware detection approaches mostly have concentrated on superficial features such as requested or used permissions, which can't reflect the essential differences between benign apps and malware. In this paper, we propose a quantitative calculation model of application risks based on the key observation that the essential differences between benign apps and malware actually lie in the way how permissions are used, or rather the way how their corresponding permission methods are used. Specifically, we employ a fine-grained analysis on Android application risks. We firstly classify application risks into five specific categories and then introduce comprehensive risk, which is computed based on the former five, to describe the overall risk of an application. Given that users' risk preference and risk-bearing ability are naturally fuzzy, we design and implement a fuzzy logic system to calculate the comprehensive risk. On the basis of the quantitative calculation model, we propose a risk classification based approach for Android malware detection. The experiments show that our approach can achieve high accuracy with a low false positive rate using the RandomForest algorithm.