• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.671-680
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• 2003

The accuracy of inflow into tunnel estimates depends largely on how well permeability is characterized. But, the average of the packer test results will always underestimate the upper end of the permeability range, and therefore underestimate the inflow. Taking an average of the test results always underestimates inflow because the average permeability does not really exist. The distribution of packer-test data may not accurately reflect permeability, however, due to the limits of the test method and the luck of the field investigation. These discrepancies may be overcome by using Raymer(2001)'s log-normal plots and Heuer(1995)'s histograms of the data to develop a permeability model that will be used in lieu of the data to calculate inflow. Furthermore, the influence on the inflow is examined by the geological characteristics based upon the hundred times of packer test OO tunnel project.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.139-148
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• 2022

We attempted to determine how adolescents' general characteristics, appearance stress, and anxiety affect adolescents' body image distortion using data from the 16th Korea Youth Risk Behavior Survey. We confirmed Body image distortion in 38.2% of the subjects, and the results of underestimated body image in 19.9% and overestimation in 18.3%. Appearance stress and anxiety were found to have an effect in both underestimate and overestimate groups. We confirmed that demographic characteristics such as gender, economic level, and academic level influence different aspects in the underestimation and overestimation groups. Therefore, we suggested that comprehensive evaluation by subdividing the subjective perception of adolescents' weight into cases of overestimation and underestimation will be an important factor in determining mental health and weight control behavior in the future.

• Genomics & Informatics
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• v.20 no.1
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• pp.9.1-9.6
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• 2022

Mendelian randomization (MR) uses genetic variation as a natural experiment to investigate the causal effects of modifiable risk factors (exposures) on outcomes. Two-sample Mendelian randomization (2SMR) is widely used to measure causal effects between exposures and outcomes via genome-wide association studies. 2SMR can increase statistical power by utilizing summary statistics from large consortia such as the UK Biobank. However, the first-order term approximation of standard error is commonly used when applying 2SMR. This approximation can underestimate the variance of causal effects in MR, which can lead to an increased false-positive rate. An alternative is to use the second-order approximation of the standard error, which can considerably correct for the deviation of the first-order approximation. In this study, we simulated MR to show the degree to which the first-order approximation underestimates the variance. We show that depending on the specific situation, the first-order approximation can underestimate the variance almost by half when compared to the true variance, whereas the second-order approximation is robust and accurate.

• Journal of Trauma and Injury
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• v.35 no.4
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• pp.232-239
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• 2022

Purpose: The recent increase in electric scooter (e-scooter) use has been accompanied by an increase in injuries from e-scooter-related accidents. Studies have reported that most such injuries are minor, and physicians may therefore underestimate the severity of such injuries. This study investigated the types and severity of injuries caused by isolated e-scooter accidents (i.e., those that did not involve colliding with other cars or falling from heights). Methods: This prospective observational study was conducted from May to December 2021 at Dankook University Hospital tertiary medical center. The demographic data of patients injured in isolated e-scooter-related accidents were collected. All injuries were categorized by body part. Results: Fifty eligible patients visited our emergency department during the study period. Of these, 76% were categorized as nonemergency, and 62% were discharged after initial evaluation and treatment at the emergency department. Another 10% were admitted to the intensive care unit (ICU) and 18% to the ward, with nine patients receiving at least one operation. The average hospital stays were 2.4 days in the ICU and 9 days in the ward. One death occurred due to traumatic brain injury (overall mortality rate, 2%). Multiple fractures of the left third through ninth ribs combined with lung laceration and fractures of T12 and L4 were noted. Conclusions: Various types and severities of injuries can occur in isolated e-scooter accidents. While most such injuries are minor, some will require ICU admission or surgery, and deaths can occur. Physicians should not underestimate the severity of such injuries.

• Imaging Science in Dentistry
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• v.46 no.4
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• pp.297-297
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• 2016

• Computational Structural Engineering
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• v.5 no.3
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• pp.139-146
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• 1992

Vibrational behaviors of highway girder bridges due to heavy traffics are discussed, and empirical formulae for impact factors are suggested in this paper. Appropriate vehicle model for vibration analysis is found and impact factors are calculated with different surface roughnesses, vehicle speeds and span lengths. It is shown that the present codes tend to underestimate impact factors.

• Wind and Structures
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• v.19 no.3
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• pp.271-294
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• 2014

The impact of artefacts in archived wind observations on the design wind speed obtained by extreme value analysis is demonstrated using case studies. A signpost protocol for detecting candidate artefacts is described and its performance assessed by comparing results against previously validated data. The protocol targets artefacts by exploiting the serial correlation between observations. Additional "sieve" algorithms are proposed to identify types of correctable artefact from their "signature" in the data. In extreme value analysis, artefacts displace valid observations only when they are larger, hence always increase the design wind speed. Care must be taken not identify large valid values as artefacts, since their removal will tend to underestimate the design wind speed.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.383-395
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• 1999

This study is concerned with the evaluation of predictive ability of classification models with ordered multiple categories. If categories can be ordered or ranked the spread of misclassification should be considered to evaluate the performance of the classification models using loss rate since the apparent error rate can not measure the spread of misclassification. Since loss rate is known to underestimate the true loss rate the bootstrap method were used to estimate the true loss rate. thus this study suggests the method to evaluate the predictive power of the classification models using loss rate and the bootstrap estimate of the true loss rate.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.11a
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• pp.234-237
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• 2003

Previous researches about headed reinforcement have not been concerned about bond failure which is quite important is some cases. In this paper, failure mechanism including bond failure was presented in order to define the contribution of bond stress at the time failure occurs. Examined with design codes and test results, it is proved to be rational to consider the contribution of bond stress in determining the ultimate pull-out capacity of headed reinforcement. Direct adaptation of design code for anchor bolt without modification for the contribution of bond stress will lead to underestimate the capacity of headed reinforcement.

• Computational Structural Engineering
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• v.5 no.2
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• pp.87-91
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• 1992

Vibrational behaviors of highway girder bridges due to heavy traffics are discussed, and empirical formulae for impact factors are suggested in this paper. Appropriate vehicle model for vibration analysis is found and impact factors are calculated with different surface roughnesses, vehicle speeds and span lengths. It is shown that the present codes tend to underestimate impact factors.