• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.701-705
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• 2011

The paper reviews Cronbaha's coefficient to measure a single source of error. On the contrary to classical measurement theory, the generalizability study can be used in the social survey design to calculate Generalizability Index (GI) and Dependability Index (DI) for measuring multiple sources of errors of behavior evaluation. The study proposes application guidelines to implement R:($A{\times}B$) mixed models that are composed of random factor and fixed factor.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10b
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• pp.1273-1278
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• 2000

Bridge load rating calculations provide a basis for determining the safe load capacity of bridge. Load rating requires engineering judgement in determining a rating value that is applicable to maintaining the safe use of the bridge and arriving at posting and permit decisions. Load testing is an effective means in calculating the rating value of bridge. In Korea, load carrying capacity of bridge is modified by stress modification factor that is determined from comparisons of measured values and analysis results The stress modification factor may be corrupted by vehicle location error that is defined as the gap of test vehicle location between load testing and analysis. In this study, the effects of vehicle location error to structural response and stress modification factor are investigated, and a new method for evaluating stress modification factor is proposed. The random data analysis shows that the proposed method is less sensitive to vehicle location error than the present method.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.2
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• pp.75-84
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• 2019

In this study, the random forest approach was used to predict the national mean rice yield of South Korea by using mean climatic factors at a national scale. A random forest model that used monthly climate variable and year as an important predictor in predicting crop yield. Annual yield change would be affected by technical improvement for crop management as well as climate. Year as prediction factor represent technical improvement. Thus, it is likely that the variables of importance identified for the random forest model could result in a large error in prediction of rice yield in practice. It was also found that elimination of the trend of yield data resulted in reasonable accuracy in prediction of yield using the random forest model. For example, yield prediction using the training set (data obtained from 1991 to 2005) had a relatively high degree of agreement statistics. Although the degree of agreement statistics for yield prediction for the test set (2006-2015) was not as good as those for the training set, the value of relative root mean square error (RRMSE) was less than 5%. In the variable importance plot, significant difference was noted in the importance of climate factors between the training and test sets. This difference could be attributed to the shifting of the transplanting date, which might have affected the growing season. This suggested that acceptable yield prediction could be achieved using random forest, when the data set included consistent planting or transplanting dates in the predicted area.

• Korean Journal of Logic
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• v.5 no.2
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• pp.115-131
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• 2002

The problem of disjunctive causal factors is generalized as follows. Suppose that there are no factors of the kind considered so far that need to be held fixed in background contexts. Nevertheless, it is still possible that within the background contexts, each disjunct of a disjunctive causal factor X v W confers a different probability on an effect factor in Question. So a problem arises of how we identify a single causally significant probability of the effect factor in the presence of the disjunctive causal factor, assuming that each disjunct of the disjunctive causal factor confers a different probability on the effect factor. In this paper, I first introduce an experiment in which disjunctive causal factors seem to pose a problem for the theory of probabilistic causation. Second, I show how Eells' solution to the problem of disjunctive causal factors meets the problem that arises in the experiment. Third, I examine Hitchcock's arguments against Eells' solution, arguing that Hitchcock misconstrues Eells' solution, and disregards the feature of the theory of probabilistic causation such that a factor is a causal factor for another factor relative to a population P of a population type Q.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.4
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• pp.91-99
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• 2022

By applying METHOD 514.8 of the US military standard MIL-STD-810H, vibration analysis of the winding core automatic feeding device was performed during vehicle transportation. The contact point between the LM guide and main support frame was weak in the vertical axis, transverse axis, and longitudinal axis during the transportation of the automatic winding core feeder vehicle, and the maximum equivalent stress was 236.31 MPa in the longitudinal axis. When random vibration was applied, the safety margin in the longitudinal direction was 0.26, indicating low safety. The safety margin was changed by increasing the damage factor to 0.1. Finally, the safety margin was improved to 3.48 to secure safety. Resonance occurred with a Q factor of 9.34 in the harmonic response to which the RMS value of the ASD data was input, and the vertical axis safety margin was derived as 0.16. When the damping factor was 0.15, the Q factor was 3.37, and resonance was avoided with a safety margin of 6.62.

• Journal of the Korean Geotechnical Society
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• v.39 no.6
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• pp.5-12
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• 2023

Proactive assessment of landslide susceptibility is necessary for minimizing casualties. This study proposes a methodology for classifying the landslide safety factor using a classification algorithm based on machine learning techniques. The high-risk area model is adopted to perform the classification and eight geotechnical parameters are adopted as inputs. Four classification algorithms-namely decision tree, k-nearest neighbor, logistic regression, and random forest-are employed for comparing classification accuracy for the safety factors ranging between 1.2 and 2.0. Notably, a high accuracy is demonstrated in the safety factor range of 1.2~1.7, but a relatively low accuracy is obtained in the range of 1.8~2.0. To overcome this issue, the synthetic minority over-sampling technique (SMOTE) is adopted to generate additional data. The application of SMOTE improves the average accuracy by ~250% in the safety factor range of 1.8~2.0. The results demonstrate that SMOTE algorithm improves the accuracy of classification algorithms when applied to geotechnical data.

• Tribology and Lubricants
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• v.16 no.6
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• pp.448-454
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• 2000

The roughness effects are very important due to the presence of interacting asperities in partial lubrication regime. An average Reynolds equation using flow factors is very useful to determine the effects of surface roughness on mixed lubrication. In this paper, the pressure flow factors for surfaces having Gaussian and non-Gaussian distribution of roughness height are evaluated in terms of various kurtosis. The effect of kurtosis on pressure flow factors is investigated using random rough surface generated numerically. The pressure flow factor increases with increasing kurtosis in mixed lubrication regime (h/$\sigma$<3). As h/$\sigma$ increases, the pressure flow factors approach to 1 asymptotically regardless of kurtosis.

• Journal of the Korean housing association
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• v.16 no.2
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• pp.99-105
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• 2005

Due to the vast increase in the elderly population and the changes in traditional filial duties, the importance of the elderly living arrangement is being greatly emphasized. The purpose of this study was to analyse the determinant factor of intention to move into senior congregate housing. The survey was conducted among middle-aged people in their fifties, who lived in Seoul, using the systematic random sampling method. The final sample included 498 respondents. The results were as follows. 1) It was revealed that many respondents thought positively about senior congregate housing. Both of having children and income were proved as an important variables which had an impact factor to move into senior congregate housing. 2) It was found that residential environment was the more important factor than housing level itself or personal social environment.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1103-1111
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• 2000

The hyper-geometric distribution software reliability growth model (HGDM) usually assumes that all the software faults detected are perfectly removed without introducing new faults. However, since new faults can be introduced during the test-and-debug phase, the perfect debugging assumption should be relaxed. In this context, Hou, Kuo and Chang [7] developed a modified HGDM for imperfect debugging environment, assuming tat the learning factor is constant. In this paper we extend the existing imperfect debugging HGDM for tow respects: introduction of random sensitivity factor and allowance of variable learning factor. Then the statistical characteristics of he suggested model are studied and its applications to two real data sets are demonstrated.

• Structural Engineering and Mechanics
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• v.22 no.4
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• pp.469-481
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• 2006

A new method called fuzzy factor method for the stationary stochastic response analysis of fuzzy truss with global fuzzy structural parameters is presented in this paper. Considering the fuzziness of the structural physical parameters and geometric dimensions simultaneously, the fuzzy correlation function matrix of structural displacement response in time domain is derived by using the fuzzy factor method and the optimization method, the fuzzy mean square values of the structural displacement and stress response in the frequency domain are then developed with the fuzzy factor method. The influences of the fuzziness of structural parameters on the fuzziness of mean square values of the displacement and stress response are inspected via an example and some important conclusions are obtained. Finally, the example is simulated by Monte-Carlo method and the results of the two methods are close, which verified the feasibility of the method given in this paper.