• Journal of the Korean Society of Hazard Mitigation
• /
• v.9 no.1
• /
• pp.135-144
• /
• 2009

The objective of this study is to examine the effect of hydrological factors on critical durations, and to analyze the relationship between the watershed characteristics and the critical duration of design rainfall in the medium sized catchments. Hydrological factors are used to return period, probable intensity formula, hydrograph method, effective rainfall and temporal pattern of design rainfall. Hydrologic analysis has done over the 44 medium sized catchments with $50{\sim}5,000{\beta}{\yen}$. Watershed characteristics such as catchment area, channel length, channel slope, catchment slope, time to peak, concentration of time and curve number were used to simulate correlation analysis. All of hydrological factors except return period influence to the critical duration of design rainfall. Also, it is revealed that critical duration is influenced by the watershed characteristics such as area, channel length, channel slope and catchment slope. Multiple regression analysis using watershed characteristics is carried out for the estimation of relationship among these. And the 7 type equations are proposed by the multiple regression using watershed characteristics and critical duration of design rainfall. The determination coefficient of multiple regression equations shows $0.96{\sim}0.97$.

• Architectural research
• /
• v.16 no.2
• /
• pp.75-80
• /
• 2014

Risks, uncertainties, and associated cost overruns are critical problems for construction projects. Cost contingency is an important funding source for these unforeseen events and is included in the base estimate to help perform financially successful projects. In order to predict more accurate contingency, many empirical models using regression analysis and artificial neural network method have been proposed and showed its viability to minimize prediction errors. However, categorical factors on contingency cannot have been treated and thus considered in these empirical models since those models are able to treat only numerical factors. This paper identified potential factors on contingency in transportation construction projects and evaluated categorical factors using the one-way ANOVA statistical method. Among factors including project work type, delivery method type, contract agreement type, bid award type, letting type, and geographical location, two factors of project work type and contract agreement type were found to be statistically important on allocating cost contingency.

• Journal of the Korean Data and Information Science Society
• /
• v.18 no.1
• /
• pp.185-194
• /
• 2007

The information of covariates are available to do fully efficient fractional imputation(FEFI). The new method, FEFI with logistic regression is proposed to construct complete contingency tables. Jackknife method is used to get a standard errors of log-odds ratio from the completed table by the new method. Simulation results, when covariates have more information about categorical variables, reveal that the new method provides more efficient estimates of log-odds ratio than either multiple imputation(MI) based on data augmentation or complete case analysis.

• Transactions of Materials Processing
• /
• v.13 no.7
• /
• pp.594-599
• /
• 2004

In the sheet metal forming operations, the strain measurement of sheet panel is an essential work which provides the formability information needed in die design, process design, and product inspection. To measure efficiently complex geometry strains, the 3-dimensional automative strain measurement system, which theoretically has a high accuracy but practically has about 3～5％ strain error, is often used. For eliminating the strain error resulted in measuring the strains of formed panels using an automated strain measurement system, the position error calibration method is suggested, which computes accurate strains using the grids with accurate nodal coordinates. The accurate nodal coordinates are calculated by adding the nodal coordinates measured by the measurement system and the position error found using the multiple regression method as a function of the main error parameters obtained from the analysis of strain error in a standard cube. For the verification, the strain distributions of square and dome cups obtained from the position error calibration method are compared with those provided by the finite element analysis and ASAME.

• Journal of Korean Academy of Nursing Administration
• /
• v.10 no.1
• /
• pp.141-159
• /
• 2004

Purpose: The purpose of this study was to investigate the degree of information technology application, and to identify the effect of information technology application en knowledge management process in clinical nurses. Method: Participants were 629 regular clinical nurses who had worked for over 1 year in general units of 9 tertiary medical hospitals including 2 national university hospitals, 5 university hospitals, and 2 hospitals founded by business enterprises. Data were collected from March to May 2003 through questionnaires. Thee structured instruments were used to collect the data: Information Technology Application scale, Knowledge Management Process Scale(Jeong, Lee, Lee, & Kim, 2003), and one for general characteristics. The data were analyzed using reliability analysis, descriptive analysis, one-way ANOVA, $Scheff{\acute{e}$ test, correlation analysis, partial correlation analysis, and multiple regression analysis with the SPSS for Windows 10,0 program. Result: 1) The HIS application degree, IT application ability, and IT application frequency were significantly correlated with the degree of knowledge management process activation and 4 elements of knowledge management process, Knowledge Creation, Knowledge Storage, Knowledge Sharing, and Knowledge Utilization(p=.000). 2) The 3 variables, HIS application degree, IT application ability, and IT application frequency explained 47.2% of the total variance of the degree of knowledge management process activation, and 352% of me total variance of Knowledge Storage. And 2 variables, HIS application degree and IT application frequency explained 17.6% of the total variance of Knowledge Creation, 39.9% of the total variance of Knowledge sharing, and 33.8% of the total variance of Knowledge utilization(p=.000). 3) As a result of multiple regression analysis, the key determinant of the degree of knowledge management process activation for nurses was HIS application degree The HIS application degree, IT application frequency, position, IT application ability, and continuous total numbers of years working at the present hospital explained 51.1% of the total variance of the degree of knowledge management process activation(p=.000). Conclusions: These results suggest that the information technology application positively affects the nurses' knowledge management process. From the above findings, information technology application is empirically verified as a useful and effective method to activate knowledge management process, and knowledge management.

• Clinical and Experimental Emergency Medicine
• /
• v.5 no.4
• /
• pp.230-239
• /
• 2018

Objective The suicide rate in South Korea is very high and is expected to increase in coming years. Intoxication is the most common suicide attempt method as well as one of the common reason for presenting to an emergency medical center. We used decision tree modeling analysis to identify predictors of risk for suicide by intentional intoxication. Methods A single-center, retrospective study was conducted at our hospital using a 4-year registry of the institute from January 1, 2013 to December 31, 2016. Demographic factors, such as sex, age, intentionality, therapeutic adherence, alcohol consumption, smoking status, physical disease, cancer, psychiatric disease, and toxicological factors, such as type of intoxicant and poisoning severity score were collected. Candidate risk factors based on the decision tree were used to select variables for multiple logistic regression analysis. Results In total, 4,023 patients with intoxication were enrolled as study participants, with 2,247 (55.9%) identified as cases of intentional intoxication. Reported annual percentages of intentional intoxication among patients were 628/937 (67.0%), 608/1,082 (56.2%), 536/1,017 (52.7), 475/987 (48.1%) from 2013 to 2016. Significant predictors identified based on decision tree analysis were alcohol consumption, old age, psychiatric disease, smoking, and male sex; those identified based on multiple regression analysis were alcohol consumption, smoking, male sex, psychiatric disease, old age, poor therapeutic adherence, and physical disease. Conclusion We identified important predictors of suicide risk by intentional intoxication. A specific and realistic approach to analysis using the decision tree modeling technique is an effective method to determine those groups at risk of suicide by intentional intoxication.

• Journal of the Korean housing association
• /
• v.6 no.1
• /
• pp.31-37
• /
• 1995

The purpose of this study is to analyse the distribution of thermal sensation response and thermal environment condition in convective heating space. The contents of this study are as follows: 1)the spatial distributions of thermal conditions are measured 2)the thermal sensation vote of residents is taken in order to investigate the relation between thermal condition and human thermal sensation in sedentary condition 3)to analyse the distribution of subject's thermal sensation vote and thermal environment condition by two methods-regression method and graph method.

• Communications for Statistical Applications and Methods
• /
• v.3 no.3
• /
• pp.31-37
• /
• 1996

A hierarchical loglinear model comparison method is developed which is based on the well kmown partitioned likelihood ratio statistiss. For any paels, we can regard the difference of the geedness of fit statistics as the variation explained by a full model, and develop a partial test to compare a full model with a reduced model in that hierarchy. Note that this has similar arguments as that of the regression analysis.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2000.04a
• /
• pp.26-29
• /
• 2000

drawbead expert models are developed for calculating drawbead restraining force and drawbead-exit thinnings which are boundary conditions in FEM stamping simulation employing the linear multiple regression method by which the deviation of drawing characteristics between drawing test and mathematical model is minimized. In order to show the efficiency and accuracy of an expert drawbead model a finite element simulation of auto-body panel stamping is carried out. The finite element simulation shows that the expert drawbead model provides the accurate solution guarantees the stable convergence and the merit in the computation time.

• Journal of the Korean Data and Information Science Society
• /
• v.15 no.2
• /
• pp.331-337
• /
• 2004

In the analysis of massive volume data, a neural network model is a useful tool. To implement the Neural network model, it is important to select initial value. Since the initial values are generally used as random value in the neural network, the convergent performance and the prediction rate of model are not stable. To overcome the drawback a possible method use samples randomly selected from the whole data set. That is, coefficients estimated by logistic regression based on the samples are the initial values.