• Journal of the Korean Society of Safety
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• v.35 no.5
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• pp.15-21
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• 2020

Quantitative risk assessment (QRA) is used as a legal or voluntary safety management tool for the hazardous material industry and the utilization of the method is gradually increasing. Therefore, a leak frequency analysis based on reliable generic data is a critical element in the evolution of QRA and safety technologies. The aim of this paper is to derive the leak frequency function that can be applied more flexibly in QRA based on OGP report with high reliability and global utilization. For the purpose, we first reviewed the data on the 16 equipments included in the OGP report and selected the predictors. And then we found good equations to fit the OGP data using non-linear regression analysis. The various expectation functions were applied to search for suitable parameter to serve as a meaningful reference in the future. The results of this analysis show that the best fitting parameter is found in the form of DNV function and connection function in natural logarithm. In conclusion, the average percentage error between the fitted and the original value is very small as 3 %, so the derived prediction function can be applicable in the quantitative frequency analysis. This study is to contribute to expand the applicability of QRA and advance safety engineering as providing the generic equations for practical leak frequency analysis.

• Journal of Korean Library and Information Science Society
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• v.52 no.3
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• pp.157-175
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• 2021

The purpose of this study is to investigate the service quality of special libraries using Importance-Performance Analysis (IPA) method. This study also applied the working year factor to IPA model for establishing more improved library service strategies. A total 127 library users who work in governmental policy or research institutions in South Korea participated in this study. This study conducted regression analysis to compare with the results of IPA. The results of survey revealed that special library users had high expectation for library services, but they perceived the performance of the library service as insufficient. Special library users assessed that the information services of libraries were well provided but required additional efforts in services related with space and provided by librarian. Interestingly, when the library services were measured by working years, special library users who have worked for more than eight years were generally satisfied with library services with no "possible overkill" services, but users with less than three years working experience particularly expressed dissatisfaction with the service provided by librarians. The results of regression analysis supported the results of IPA. Finally, this study provides several important suggestions for better special library service.

• Journal of the Korean Society of Propulsion Engineers
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• v.23 no.4
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• pp.81-91
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• 2019

The 3-dimensional grain burn-back analysis is performed using the face offsetting method for calculating the solid rocket motor performance. The grain burning configuration analysis is a moving surface problem that calculates the regression of the burning surface. In the previous study, various moving interface analysis methods were applied for the grain burn-back analysis, but the results were imperfect. In this study, a 3-dimensional grain burn-back analysis module is developed using the face offsetting method, which combines the advantages of the existing moving interface analysis methods to increase the accuracy and robustness. As a result, the face offsetting method is proved to be efficient for the grain burn-back analysis.

• Journal of the Korea Concrete Institute
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• v.16 no.2 s.80
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• pp.195-204
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• 2004

Poisson's ratio due to multiaxial creep of concrete reported by existing experimental works was controversial. Poisson's ratio calculated from measured strain is very sensitive to small experimental error. This sensitivity make it difficult to find out whether the Poisson's ratio varies with time or remain constant, and whether the Poisson's ratio has different value with stress states or not. A new approach method is needed to resolve the discrepancy and obtain reliable results. This paper presents analytical study on multiaxial creep test results. Microplane model as a new approach method is applied to optimally fitting the test data extracted from experimental studies on multiaxial creep of concrete. Double-power law is used as a model to present volumetric and deviatoric creep evolutions on a microplane. Six parameters representing the volumetric and deviatoric compliance functions are determined from regression analysis and the optimum fits accurately describe the test data. Poisson's ratio is calculated from the optimum fits and its value varies with time. Regression analysis is also performed assuming that Poisson's ratio remains constant with time. Four parameters are determined for this condition, and the error between the optimum fits and the test data is slightly larger than that for six parameter regression results. The constant Poisson's ratio with time is obtained from four parameter analysis results and the constant value can be used in practice without serious error.

• Journal of Trauma and Injury
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• v.25 no.4
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• pp.139-144
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• 2012

Purpose: Hypovolemic shock is the leading cause of death in multiple trauma patients with pelvic bone fracures. The purpose of this study was to develop a simple prediction method for injury severity and amount of hemorrhage via an analysis of the correlation between the site of pelvic bone fracture and the amount of transfusion and to verify the usefulness of the such a simple scoring system. Methods: We analyzed retrospectively the medical records and radiologic examination of 102 patients who had been diagnosed as having a pelvic bone fracture and who had visited the Emergency Department between January 2007 and December 2011. Fracture sites in the pelvis were confirmed and re-classified anatomically as pubis, ilium or sacrum. A multiple linear regression analysis was performed on the amount of transfusion, and a simplified scoring system was developed. The predictive value of the amount of transfusion for the scoring system as verified by using the receiver operating characteristics (ROC). The area under the curve of the ROC was compared with the injury severity score (ISS). Results: From among the 102 patients, 97 patients (M:F=68:29, mean $age=46.7{\pm}16.6years$) were enrolled for analysis. The average ISS of the patients was $16.2{\pm}7.9$, and the average amount of packed RBC transfusion for 24 hr was $3.9{\pm}4.6units$. The regression equation resulting from the multiple linear regression analysis was 'packed RBC units=1.40${\times}$(sacrum fracture)+1.72${\times}$(pubis fracture)+1.67${\times}$(ilium fracture)+0.36' and was found to be suitable (p=0.005). We simplified the regression equation to 'Pelvic Bleeding Score=sacrum+pubis+ilium.' Each fractured site was scored as 0(no fracture) point, 1(right or left) point, or 2(both) points. Sacrum had only 0 or 1 point. The score ranged from 0 to 5. The area under the curve (AUC) of the ROC was 0.718 (95% CI: 0.588-0.848, p=0.009). For an upper Pelvis Bleeding Score of 3 points, the sensitivity of the prediction for a massive transfusion was 71.4%, and the specificity was 69.9%. Conclusion: We developed a simplified scoring system for the anatomical fracture sites in the pelvis to predict the requirement for a transfusion (Pelvis Bleeding Score (PBS)). The PBS, compared with the ISS, is considered a useful predictor of the need for a transfusion during initial management.

• The Journal of Engineering Geology
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• v.21 no.4
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• pp.361-367
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• 2011

The uniaxial compressive strength (UCS) is an important factor in the design and construction of surface and underground structures. However, the method employed to measure UCS is time consuming and expensive to apply in the field. Therefore, we developed a model to estimate UCS based on a few properties using linear regression analysis, which is a statistical method. To develop the model, valid factors from the test results were selected from a correlation analysis using a statistical program, and the model was formulated by linear regression based on the relationships among factors. UCS estimates derived from the model were compared with the results of UCS tests, to assess the reliability of the model. The relationship between rock properties and UCS indicates that the factors with the greatest influence on UCS are point load strength and shape facto r. The UCS values obtained using the model are in good agreement with the results of the UCS test. Therefore, the developed model may be used to estimate the UCS of rocks in regions with similar conditions to those of the present study area.

• The Journal of the Korea Contents Association
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• v.12 no.1
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• pp.508-515
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• 2012

The purpose of this study was to examine if factors of baseball stadium environment which people have spectating satisfaction of professional baseball. The respondents of the study 614 who were spectators at D city professional baseball event. The stratified cluster random sampling method has been used in this study. The material collection device was the brochure named [A Influence of Factors of Baseball Stadium Environment on Spectating Satisfaction of Professional Baseball]. The result of reliability check up was here below; stadium factors ${\alpha}$=.966~.890, spectating costs ${\alpha}$=.922~.988, spectating promotion ${\alpha}$=.894~.789. To analyze materials, the "correlation analysis" and "regression analysis" were used as statistic analysis techniques. The conclusion based on above study method and the result of material analysis are here below. 1. The stadium factors influence spectating satisfaction of professional baseball. 2. The spectating cost factors influence spectating satisfaction of professional baseball. 3. The spectating promotion factors influence spectating satisfaction of professional baseball.

• Journal of Biosystems Engineering
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• v.40 no.3
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• pp.289-295
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• 2015

Purpose: From the perspective of biomechanics, joint moments quantitatively show a subject's ability to perform actions. In this study, the effect of normalization in the fast and asymmetric motions of a golf swing was investigated by applying three different normalization methods to the raw joint moment. Methods: The study included 13 subjects with no previous history of musculoskeletal diseases. Golf swing analyses were performed with six infrared cameras and two force plates. The majority of the raw peak joint moments showed a significant correlation at p < 0.05. Additionally, the resulting effects after applying body weight (BW), body weight multiplied by height (BWH), and body weight multiplied by leg length (BWL) normalization methods were analyzed through correlation and regression analysis. Results: The BW, BWH, and BWL normalization methods normalized 8, 10, and 11 peak joint moments out of 18, respectively. The best method for normalizing the golf swing was found to be the BWL method, which showed significant statistical differences. Several raw peak joint moments showed no significant correlation with measured anthropometrics, which was considered to be related to the muscle coordination that occurs in the swing of skilled professional golfers. Conclusions: The results of this study show that the BWL normalization method can effectively remove differences due to physical characteristics in the golf swing analysis.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.721-731
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• 2017

In this study, principal component analysis methods using Lasso penalty are introduced. There are two popular methods that apply Lasso penalty to principal component analysis. The first method is to find an optimal vector of linear combination as the regression coefficient vector of regressing for each principal component on the original data matrix with Lasso penalty (elastic net penalty in general). The second method is to find an optimal vector of linear combination by minimizing the residual matrix obtained from approximating the original matrix by the singular value decomposition with Lasso penalty. In this study, we have reviewed two methods of principal components using Lasso penalty in detail, and shown that these methods have an advantage especially in applying to data sets that have more variables than cases. Also, these methods are compared in an application to a real data set using R program. More specifically, these methods are applied to the crime data in Ahamad (1967), which has more variables than cases.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.104-114
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• 2022

The purpose of using coolant in machining is both to increase a tool life and also to prevent product deformation and thus, stabilize the surface quality by lubricating and cooling the tool and the machining surface. However, a very small amount of cutting mist should be used because chlorine-based extreme pressure additives are used to generate environmental pollutants in the production process and cause occupational diseases of workers. In this study, medical titanium alloy (Ti-6Al-7Nb) was subjected to a processing experiment by selecting factors and levels affecting cutting power in the processing of the Aerosol Dry Lubrication (ADL) method using vegetable oil. The machining shape was a slot to sufficiently reflect the effect of the cutting depth. As for the measurement of cutting force, the trend of cutting characteristics was identified through complete factor analysis. The factors affecting the cutting force of ADL slot processing were identified using the reaction surface analysis method, and the characteristics of the cutting force according to the change in factor level were analyzed. As the cutting speed increased, the cutting force decreased and then increased again. The cutting force continued to increase as the feed speed increased. The increase in the cutting depth increased the cutting force more significantly than the increase in the cutting speed and the feed speed. Through the reaction surface analysis method, the regression equation for predicting cutting force was identified, and the optimal processing conditions were proposed. The cutting force was predicted from the secondary regression equation and compared with the experimental value.