• Proceedings of the Korea Concrete Institute Conference
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• 1998.10b
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• pp.656-661
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• 1998

This paper presents a method of statistical analysis and sensitivity analysis of creep and shrinkage effects in PSC box girder bridges. The statistical and sensitivity analyses are performed by using the numerical simulation of Latin Hypercube sampling. For each sample, the time-dependent structural analysis is performed to produce response data, which are then statistically analyzed. The probabilistic prediction of the confidence limits on long-term effects of creep and shrinkage is then expressed. Three measures are examined to quantify the sensitivity of the outputs to each of the input variables. These are rank correlation coefficient(RCC), partial rank correlation coefficient(PRCC) and standardized rank regression coefficient(SRRC) computed on the ranks of the observations. Probability band widens with time, which indicates an increase of prediction uncertainty with time. The creep model uncertainty factor and the relative humidity appear as the most dominant factors with regard to the model output uncertainty.

• Science of Emotion and Sensibility
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• v.9 no.spc3
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• pp.277-286
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• 2006

This study evaluates how much D/H and enclosed effects are closely related with each other centering around the spaces of cities in Japan. The partial ranks of the degree of angle in D/H and of the enclosure of the real spaces which the experimenter feels are measured through the method of partial rank correlation analysis on the sane objects. The result shows that all 42 samples(0.49), 25 interior space samples(0.63), and 17 exterior samples(0.59) are analysed to be less correlated. Seen above, there is limit to explaining modern spaces with the degree of angle in D/H. The result reveals that the space structure of modem cities consists of a lot more complex elements, so it is not suitable to evaluate the spaces of cities with the past theories of D/H and enclosed effect. Therefore, to evaluate the enclosed effect, a new evaluation model and a study of influential elements of city spaces and enclosed effect should be developed.

• Clinical and Experimental Reproductive Medicine
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• v.50 no.3
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• pp.206-212
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• 2023

Objective: The aim of the present study was to evaluate the associations between hematologic parameters related to systemic inflammation and insulin resistance-associated metabolic parameters in women with polycystic ovary syndrome (PCOS). Methods: Eighty-two women between the ages of 18 and 35 years who were diagnosed with PCOS were included in this study. A 2-hour 75-g oral glucose tolerance test (OGTT) was administered to all study participants; fasting and postprandial glucose and insulin levels were measured simultaneously during the 2-hour OGTT. Hematologic parameters were derived from a standard complete blood count and a differential count of fasting-state blood samples. The correlations between hematologic parameters and insulin resistance-associated clinical and metabolic parameters were evaluated using the Spearman rank correlation and partial correlation coefficients. Hematologic parameters related to systemic inflammation were compared between the two groups, categorized by the presence or absence of insulin resistance. Results: Significant differences in the absolute neutrophil count, absolute monocyte count, platelet count, and neutrophil-lymphocyte ratio were found between the insulin-resistant group and insulin-nonresistant group. Correlation analysis found that all hematological parameters, except for the platelet-lymphocyte ratio, were associated with at least one insulin resistance-associated metabolic parameter. However, these significant correlations between hematological and metabolic parameters were attenuated after controlling for the effects of other covariates using partial correlation analysis. Conclusion: The association between hematologic parameters indicative of systemic inflammation and insulin resistance-associated metabolic parameters seems to be strongly influenced by other anthropometric covariates in women with PCOS.

• Journal of Korean Society for Quality Management
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• v.39 no.2
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• pp.244-255
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• 2011

In this study, we try to evaluate the efficiency of the photonics industry using a data envelopment analysis(DEA) model. We first develope four stage procedures for selecting proper input and output variables which consist of selecting the first candidate variables from literature survey, selecting the second candidate variables through experts' discussion, measuring the partial efficiency of the selected variables based on Tofallis' profiling, and clustering some variables through the rank correlation analysis of partial efficiency proposed by Min and Kim(l998). With this procedure, we select 4 input variables(capital, number of employee, R&D cost, operating cost) and 2 output variables(sales, growth of sales) and then utilize CCR and BCC model to measure efficiencies of 26 photonics companies in Gwangju. Moreover, we perform the reference group analysis to figure out what causes inefficiencies and to provide the desirable values for input and output variables at which inefficient photonics companies become efficient. Finally, we classify 26 photonics companies into three groups such as optical communications, optical applications, and optical sources, and perform the Kruskal-Wallis test to check if there exist some differences between efficiencies of three groups.

• Journal of Radiation Protection and Research
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• v.25 no.4
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• pp.233-239
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• 2000

The sensitivity analysis of input parameters was Performed fer an ingestion dose assessment model (U. S. NRC's Regulatory Guide 1.109 model) from routine releases of radionuclides. In this study, three kinds of typical Korean foodstuffs (rice, leaff vegetables, milk) and two kinds of radionuclides $(^{l37}Cs,\;^{131}I)$ were considered. The values of input parameters were sampled using a Latin hypercube sampling technique based on Monte Carlo approach. Sensitivity indices, which represent the influence or the importance of input parameters for predictive results, were quantitatively expressed by the partial rank correlation coefficients. As the results, the ratio of the interception fraction to the yield of agricultural plants and the human consumption rate were sensitive input parameters for the considered foodstuffs and radionuclides. Additionally, in case of milk, the transfer factor of radionuclides from animal intake to milk and the daily intake rate of feedstuffs were sensitive input parameters. The weathering removal half-life and the delay time from food production to human consumption were relatively sensitive for $^{137}Cs$ and $^{131}I$ depositions, respectively.

• The Journal of Korean Academy of Prosthodontics
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• v.55 no.3
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• pp.272-278
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• 2017

Purpose: The aim of the present prospective clinical study was to assess the cumulative survival rate (CSR) of Neobiotech implants restored with fixed partial prosthesis in relation to its potential risk factors. Materials and methods: Thirty six partially edentulous patients received Neobiotech implants and implant supported fixed partial prosthesis at Korea University Guro Hospital Dental Center from November 2009 until November 2011. The observation period was set from the implant placement and the last clinical visit until December 2015. Implant survival rate was determined using the Kaplan-Meier method. The relationship between implant survival rate and the potential risk factors were analysed using the multi Cox proportional analysis (P<.05). Results: A total of 69 implants were placed in 36 patients after a mean observation period of 45.9 months. Two out of 69 implants failed before loading, yielding a 5-year cumulative survival rate of 97.1%. The maxillary implants have a lesser CSR than the mandibular implants based on log rank test analysis (maxilla=91.3%; mandible=100% P<.05). However, the multi Cox proportional analysis showed that implant location has no significant correlation with implant failure (P>.05). Conclusion: Neobiotech implants showed predictable results with a 5 year cumulative survival rate of 97.1%.

• Journal of Korean Clinical Nursing Research
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• v.18 no.2
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• pp.284-295
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• 2012

Purpose: This study was done to clarify effects of bispectral index monitoring sedative administration, compared to MOAA/S (Modified Observer's Assessment of Alertness and Sedation), on conscious sedation, physiological stability and recovery time for patients undergoing endoscopic submucosal dissection. Methods: Participants In this study were patients who underwent endoscopic submucosal dissection because of early gastric cancer. Participants were assigned randomly to an experimental group receiving sedatives based on bispectral index monitoring or to a control group with the MOAA/S instrument. Movements, belching, memory, pain, discomfort, physiological stability (MBP, PR, $SpO_2$), and recovery time were measured during the treatment and recovery. Data were analyzed using Spearman partial correlation coefficient analysis, Mixed model and Wilcoxon rank sum test to determine differences in the parameters. Results: There were no statistically significant differences between the two groups for conscious sedation(movement, belching, memory, pain, or discomfort), physiological stability and recovery time. Conclusion: The results of this study indicate that no differences were found between the two types of monitoring. Thus, use of a bispectral index monitor in clinical practice enabling medical staff to readily assess the conscious sedation of for these patients is expected to be increasingly used as an objective assessment tool for conscious sedation for patient safety.

• Journal of Korean Society of Forest Science
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• v.83 no.2
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• pp.175-190
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• 1994

In order to get fundamental information for prediction of landslide hazard, both forest and site factors affecting slope stability were investigated in many areas of active landslides. Twelve descriptors were identified and quantified to develop the prediction model by multivariate statistical analysis. The main results obtained could be summarized as follows : The main factors influencing a large scale of landslide were shown in order of precipitation, age group of forest trees, altitude, soil texture, slope gradient, position of slope, vegetation, stream order, vertical slope, bed rock, soil depth and aspect. According to partial correlation coefficient, it was shown in order of age group of forest trees, precipitation, soil texture, bed rock, slope gradient, position of slope, altitude, vertical slope, stream order, vegetation, soil depth and aspect. The main factors influencing a landslide occurrence were shown in order of age group of forest trees, altitude, soil texture, slope gradient, precipitation, vertical slope, stream order, bed rock and soil depth. Two prediction models were developed by magnitude and frequency of landslide. Particularly, a prediction method by magnitude of landslide was changed the score for the convenience of use. If the total store of the various factors mark over 9.1636, it is evaluated as a very dangerous area. The mean score of landslide and non-landslide group was 0.1977 and -0.1977, and variance was 0.1100 and 0.1250, respectively. The boundary value between the two groups related to slope stability was -0.02, and its predicted rate of discrimination was 73%. In the score range of the degree of landslide hazard based on the boundary value of discrimination, class A was 0.3132 over, class B was 0.3132 to -0.1050, class C was -0.1050 to -0.4196, class D was -0.4195 below. The rank of landslide hazard could be divided into classes A, B, C and D by the boundary value. In the number of slope, class A was 68, class B was 115, class C was 65, and class D was 52. The rate of landslide occurrence in class A and class B was shown at the hige prediction of 83%. Therefore, dangerous areas selected by the prediction method of landslide could be mapped for land-use planning and criterion of disaster district. And also, it could be applied to an administration index for disaster prevention.