• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.127-134
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• 2021

This study aims to determine the role of innovative capabilities as a mediator in analyzing entrepreneurial marketing's effect on sustainable competitive advantage in food and beverage micro-, small-, and medium- enterprises (MSMEs). Data was obtained from a food and beverage store manager in Tangerang City, comprising 119 samples. Furthermore, the G⁎Power, a tool used to calculate statistical power analysis for various t-tests, F tests, χ2 tests, z tests, and several exact tests, was used to determine the number of research samples, the α error probability of 5%, and 3 variables. The data collection method used questionnaires with Likert Scale 1-5 to indicate strongly disagree to strongly agree. To analyze data, we used Path Analysis supported by SmartPLS statistics software. Path analysis is a form of multiple regression statistical analysis that is used to evaluate causal models by examining the relationships between a dependent variable and two or more independent variables. It aims to provide estimates of the magnitude and significance of hypothesized causal connections between sets of variables. The data processing process took place in two stages, namely the estimation model testing with validity and reliability, and the structural model testing to decide the impact or correlation between variables utilizing the t-test. The result showed a positive and significant effect of entrepreneurial marketing to innovative capability and competitive advantage through the innovative capability of MSMEs.

• Steel and Composite Structures
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• v.21 no.5
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• pp.1031-1043
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• 2016

Optimization of the construction scheme of the cable-strut tensile structure based on error sensitivity analysis is studied in this paper. First, the element length was extracted as a fundamental variable, and the relationship between element length change and element internal force was established. By setting all pre-stresses in active cables to zero, the equation between the pre-stress deviation in the passive cables and the element length error was obtained to analyze and evaluate the error effects under different construction schemes. Afterwards, based on the probability statistics theory, the mathematical model of element length error is set up. The statistical features of the pre-stress deviation were achieved. Finally, a cable-strut tensile structure model with a diameter of 5.0 m was fabricated. The element length errors are simulated by adjusting the element length, and each member in one symmetrical unit was elongated by 3 mm to explore the error sensitivity of each type of element. The numerical analysis of error sensitivity was also carried out by the FEA model in ANSYS software, where the element length change was simulated by implementing appropriate temperature changes. The theoretical analysis and experimental results both indicated that different elements had different error sensitivities. Likewise, different construction schemes had different construction precisions, and the optimal construction scheme should be chosen for the real construction projects to achieve lower error effects, lower cost and greater convenience.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.4
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• pp.57-68
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• 2001

It is matter of common knowledge to give impetus to the water resources development to cope with increasing demand and supply for the water utilization project including agricultural living and industrial water owing to the economic and civilization development in recent years. Regional design rainfall is necessary or the design of the dam reservoir levee and drainage facilities for the development of various kinds of essential waters including agricultural water. For the estimation of the regional design rainfall classification of the climatologically an geographically homogeneous regions should be preceded preferentially This study was mainly conducted to derive the optimal regionalization of the precipitation data which can be classified by the climatologically and geographically homogeneous regions all over the regions except Cheju and Wulreung islands in Korea. A total of 65 rain gauges were used to regional analysis of precipitation. Annual maximum series for the consecutive durations of 1, 3, 6, 12, 24, 36, 48 and 72hr were used for various statistical analysis. Both K-means clustering and mean annual precipitation methods are used to identify homogeneous regions all over the regions. Nine and five homogeneous regions for the precipitation were classified by the K-means clustering and mean annual methods, respectively. Finally, Five homogeneous regions were established by the trial and error method with homogeneity test using statistics of $\chi$$^2$ distribution.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.3
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• pp.107-117
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• 2022

Purpose : The purpose of this study was to establish a model of the predictive factors for success or failure of examinees undertaking the Korean physical therapist licensing examination (KPTLE). Additionally, we assessed the pass/fail cut-off point. Methods : We analyzed the results of 10,881 examinees who undertook the KPTLE, using data provided by the Korea Health Personnel Licensing Examination Institute. The target variable was the test result (pass or fail), and the input variables were: sex, age, test subject, and total score. Frequency analysis, chi-square test, descriptive statistics, independent t-test, correlation analysis, binary logistic regression, and receiver operating characteristic (ROC) curve analyses were performed on the data. Results : Sex and age were not significant predictors of attaining a pass (p>.05). The test subjects with the highest probability of passing were, in order, medical regulation (MR) (Odds ratio (OR)=2.91, p<.001), foundations of physical therapy (FPT) (OR=2.86, p<.001), diagnosis and evaluation for physical therapy (DEPT) (OR=2.74, p<.001), physical therapy intervention (PTI) (OR=2.66, p<.001), and practical examination (PE) (OR=1.24, p<.001). The cut-off points for each subject were: FPT, 32.50; DEPT, 29.50; PTI, 44.50; MR, 14.50; and PE, 50.50. The total score (TS) was 164.50. The sensitivity, specificity, and the classification accuracy of the prediction model was 99 %, 98 %, and 99 %, respectively, indicating high accuracy. Area under the curve (AUC) values for each subject were: FPT, .958; DEPT, .968; PTI, .984; MR, .885; PE, .962; and TS, .998, indicating a high degree of fit. Conclusion : In our study, the predictive factors for passing KPTLE were identified, and the optimal cut-off point was calculated for each subject. Logistic regression was adequate to explain the predictive model. These results will provide universities and examinees with useful information for predicting their success or failure in the KPTLE.

• Journal of Korean Society for Quality Management
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• v.46 no.2
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• pp.327-338
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• 2018

Purpose: A risk evaluation procedure is proposed for common failure causes in FMEA(Failure Mode and Effects Analysis). The conventional FMEA does not provide a proper means to compare common failure causes with other failure causes. This research aims to develop a risk evaluation procedure in FMEA where common failure causes and other failure causes exist together. Methods: For each common failure cause, the effect of each combination of its resulting failures is recommended to be reevaluated considering their interactive worsening effect. And the probability that each combination of failures is incurred by the same common cause is also considered. Based on these two factors, the severity of each common cause is determined. Other procedures are similar to the conventional method. Results: The proposed procedure enables to compare and prioritize every failure cause. Thus, the common causes, each of which incurring two or more failures, and other causes, each of which is corresponding to one failure, can be fairly compared. Conclusion: A fair and proper way of comparing the common failure causes and other causes is provided. The procedure is somewhat complicated and requires more works to do. But it is worth to do.

• Journal of Preventive Medicine and Public Health
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• v.31 no.4 s.63
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• pp.875-884
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• 1998

Missing observations are common in medical research and health survey research. Several statistical methods to handle the missing data problem have been proposed. The EM algorithm (Expectation-Maximization algorithm) is one of the ways of efficiently handling the missing data problem based on sufficient statistics. In this paper, we developed statistical models and methods for survey data with multivariate missing observations. Especially, we adopted the EM algorithm to handle the multivariate missing observations. We assume that the multivariate observations follow a multivariate normal distribution, where the mean vector and the covariance matrix are primarily of interest. We applied the proposed statistical method to analyze data from a health survey. The data set we used came from a physician survey on Resource-Based Relative Value Scale(RBRVS). In addition to the EM algorithm, we applied the complete case analysis, which uses only completely observed cases, and the available case analysis, which utilizes all available information. The residual and normal probability plots were evaluated to access the assumption of normality. We found that the residual sum of squares from the EM algorithm was smaller than those of the complete-case and the available-case analyses.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.2
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• pp.223-234
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• 2014

This paper describes the analysis results of channel characteristics in the operating area of satellite OTM(On-The-Move) terminal. The communication channel between the Koreasat-5 and OTM terminal on a test car is measured and recorded from Daejeon to Daecheon, using the downlink frequency of around 20 GHz. And the measurement data are divided into two classes ; highway environment and national road environment, and then are statistically analyzed. The statistical evaluation of satellite channel is conducted by using probability density function and Markov model and then presents average connection duration(ACD), average fade duration( AFD), and level crossing rate(LCR) of highway environment and national road environment. Finally the statistics data of the two environments are compared with each other.

• Journal of the Korean Society of Safety
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• v.35 no.6
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• pp.25-31
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• 2020

Boiling Liquid Expanding Vapor Explosion(BLEVE) can cause not only economic damage to the plant but also serious casualties. LPG accidents account for 89.6 percent of all accidents caused by gas leaks in Korea over the past nine years, while casualties from accidents also account for 73 percent of all accidents, according to statistics from the Korea Gas Safety Corporation. In addition, a potential explosion and a fire accident from one LPG storage tank may affect the nearby storage tanks, causing secondary and tertiary damage (domino effect). The safety distance standards for LPG used by LPG workplaces, charging stations, and homes in Korea have become stricter following the explosion of LPG charging stations in Bucheon. The safety distance regulation is divided into regulations based on the distance damage and the risk including frequency. This study suggests two approaches to optimizing the safety distance based on the just consequence and risk including frequencies. Using the Phast 7.2 Risk Assessment software by DNV GL, the explosion overpressure and heat radiation were derived according to the distance caused by BLEVE in the worst-case scenario, and accident and damage probability were derived by considering the probit function and domino effect. In addition, the safety distance between LPG tanks or LPG charging stations was derived to minimize damage effects by utilizing these measures.

• Atmosphere
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• v.33 no.5
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• pp.531-548
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• 2023

We developed the Aviation Convective Index (ACI) for predicting deep convective area using the operational global Numerical Weather Prediction model of the Korea Meteorological Administration. Seasonally optimized ACI (ACI_SnOpt) was developed to consider seasonal variabilities on deep convections in Korea. Yearly optimized ACI (ACI_YrOpt) in Part 1 showed that seasonally averaged values of Area Under the ROC Curve (AUC) and True Skill Statistics (TSS) were decreased by 0.420% and 5.797%, respectively, due to the significant degradation in winter season. In Part 2, we developed new membership function (MF) and weight combination of input variables in the ACI algorithm, which were optimized in each season. Finally, the seasonally optimized ACI (ACI_SnOpt) showed better performance skills with the significant improvements in AUC and TSS by 0.983% and 25.641% respectively, compared with those from the ACI_YrOpt. To confirm the improvements in new algorithm, we also conducted two case studies in winter and spring with observed Convectively-Induced Turbulence (CIT) events from the aircraft data. In these cases, the ACI_SnOpt predicted a better spatial distribution and intensity of deep convection. Enhancements in the forecast fields from the ACI_YrOpt to ACI_SnOpt in the selected cases explained well the changes in overall performance skills of the probability of detection for both "yes" and "no" occurrences of deep convection during 1-yr period of the data. These results imply that the ACI forecast should be optimized seasonally to take into account the variabilities in the background conditions for deep convections in Korea.

• School Mathematics
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• v.9 no.2
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• pp.223-240
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• 2007

The purpose of this study was to investigate the degree to which the middle school mathematics curriculum matched the item difficulty levels of representative mathematics items. The items used in this study were developed for the National Assessment of Educational Achievement. Ranks for difficulty values of the 60 multiple-choice item were calculated via both Classical Test Theory and Item Response Theory and correlated with the rank order of the mathematics content and cognitive domains sequence. There are six content domains; number and operation, algebra, measurement, figure, pattern and function, and probability and statistics. The cognitive domains include computation, understanding, reasoning and problem-solving. Results suggest a congruence between cognitive domain's sequence and item difficulty levels of items based on that sequence. This finding indicates that the linear or hierarchical assumptions concerning the sequence appears to be reasonable. The characteristics of items that were exceptions to this trend were addressed.