• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.1
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• pp.127-136
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• 2002

This papers presents a practical damage detection algorithm based on damage index method that accurately assesses both the location and severity of the localized detriment in a bridge structure using only limited mode shapes. In the algorithm, the ratio of the modal vector sensitivity of an undamaged structure to that of a damaged structure is used as an indicator of damage. However, a difficulty arises when the damaged element is located at a node of mode where the amplitude of medal vector is close to zero, leading the singularity of the ratio (i.e., division-by-zero). This singularity problem is overcome by introducing a parameter denoted a sensitivity filter, a function of mode shape of the structure, in modal vector sensitivity. Using this concept, an improvement can be considerably achieved in the estimation of both degree of severity and location of damage. To verify the proposed algorithm, its numerical implementations are conducted for a simply supported beam and a 2-span continuous beam.

• Korean Journal of Environment and Ecology
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• v.20 no.2
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• pp.267-273
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• 2006

The biomass of Pinus densiflora stands burnt out by the 2005 Yangyang forest fire was estimated based on the grades of fire severity; light, moderate and heavy. In order to measure the post-fire ground biomass in kg/ha, the ground fuels including shrub layer were collected and weighted and the crown biomass was estimated using allometric regressions and leaf area index for dry weight of P. densiflora. The pre-fire biomass was assumed to be equal to that of non-damaged P. densiflora stands having the same characteristics. The results indicated that the forest fire burnt out fuels of stands; 3,693 kg/ha in the light-damaged, 8,724 kg/ha in the moderately-damaged, and 17,451 kg/ha in the heavily-damaged forest stands.

• Journal of the Korean Society of Safety
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• v.36 no.4
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• pp.80-87
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• 2021

Risk assessment techniques are processes used to evaluate hazardous risk factors in construction sites, facilities, raw materials, machinery, and equipment, and to estimate the size of risk that could lead to injury or disease, and establish countermeasures. The most important thing in assessing risk is calculating the size of the risk. If the size of the risk cannot be calculated objectively and quantitatively, all members who participated in the evaluation would passively engage in establishing and implementing appropriate measures. Therefore, this study focused on predicting accidents that are expected to occur in the future based on past occupational accident statistics, and quantifying the size of the risk in an overview. The technique employed in this study differs from other risk assessment techniques in that the subjective elements of evaluators were excluded as much as possible by utilizing past occupational accident statistics. This study aims to calculate the size of the risk, regardless of evaluators, such as a manager, supervisor, safety manager, or employee. The size of the risk is the combination of the likelihood and severity of an accident. In this study, the likelihood of an accident was evaluated using the theory of Bud Accident Chainability, and the severity of an accident was calculated using the occupational accident statistics over the past five years according to the accident classification by the International Labor Organization.

• Journal of Forest and Environmental Science
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• v.40 no.1
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• pp.1-8
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• 2024

Recently, intensive research has been conducted to develop innovative methods for diagnosing plant diseases based on hyperspectral technologies. Hyperspectral analysis is a new subject that combines optical spectroscopy and image analysis methods, which makes it possible to simultaneously evaluate both physiological and morphological parameters. Among the physiological and morphological parameters are classifying healthy and diseased plants, assessing the severity of the disease, differentiating the types of pathogens, and identifying the symptoms of biotic stresses at early stages, including during the incubation period, when the symptoms are not visible to the human eye. Plant diseases cause significant economic losses in agriculture around the world as the symptoms of diseases usually appear when the plants are infected severely. Early detection, quantification, and identification of plant diseases are crucial for the targeted application of plant protection measures in crop production. Hence, this can be done by possible applications of hyperspectral sensors and platforms on different scales for disease diagnosis. Further, the main areas of application of hyperspectral sensors in the diagnosis of plant diseases are considered, such as detection, differentiation, and identification of diseases, estimation of disease severity, and phenotyping of disease resistance of genotypes. This review provides a deeper understanding, of basic principles and implementation of hyperspectral sensors that can measure pathogen-induced changes in plant physiology. Hence, it brings together critically assessed reports and evaluations of researchers who have adopted the use of this application. This review concluded with an overview that hyperspectral sensors, as a non-invasive system of measurement can be adopted in early detection, identification, and possible solutions to farmers as it would empower prior intervention to help moderate against decrease in yield and/or total crop loss.

• Journal of The Korean Association For Science Education
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• v.32 no.1
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• pp.160-181
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• 2012

The purpose of this study is to understand raters' errors in rating performance assessments of science inquiry. For this, 60 middle school students performed scientific inquiry about sound propagation and 4 trained raters rated their activity sheets. Variance components estimation for the result of the generalizability analysis for the person, task, rater design, the variance components for rater, rater by person and rater by task are about 25%. Among 4 raters, 2 raters' severity is higher than the other two raters and their severities were stabilized. Four raters' rating agreed with each other in 51 cases among the 240 cases. Through the raters' conferences, the rater error types for 189 disagreed cases were identified as one of three types; different salience, severity, and overlooking. The error type 1, different salience, showed 38% of the disagreed cases. Salient task and salient assessment components are different among the raters. The error type 2, severity, showed 25% and the error type 3, overlooking showed 31%. The error type 2 seemed to have happened when the students responses were on the borders of two levels. Error type 3 seemed to have happened when raters overlooked some important part of students' responses because she or he immersed her or himself in one's own salience. To reduce the above rater errors, raters' conference in salience of task and assesment components are needed before performing the holistic scoring of complex tasks. Also raters need to recognize her/his severity and efforts to keep one's own severity. Multiple raters are needed to prevent the errors from being overlooked. The further studies in raters' tendencies and sources of different interpretations on the rubric are suggested.

• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.108-117
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• 2023

Objectives : Somatic symptom disorder (SSD) is characterized by the manifestation of a variety of physical symptoms, but little is known about differences in autonomic nervous system activity according to symptom severity, especially within patient groups. In this study, we examined differences in heart rate variability (HRV) across symptom severity in a group of SSD patients to analyze a representative marker of autonomic nervous system changes by symptoms severity. Methods : Medical records were retrospectively reviewed for patients who were diagnosed with SSD based on DSM-5 from September 18, 2020 to October 29, 2021. We applied inverse probability of treatment weighting (IPTW) methods to generate more homogeneous comparisons in HRV parameters by correcting for selection biases due to sociodemographic and clinical characteristic differences between groups. Results : There were statistically significant correlations between the somatic symptom severity and LF (nu), HF (nu), LF/HF, as well as SD1/SD2 and Alpha1/Alpha2. After IPTW estimation, the mild to moderate group was corrected to 27 (53.0%) and the severe group to 24 (47.0%), and homogeneity was achieved as the differences in demographic and clinical characteristics were not significant. The analysis of inverse probability weighted regression adjustment model showed that the severe group was associated with significantly lower RMSSD (β=-0.70, p=0.003) and pNN20 (β=-1.04, p=0.019) in the time domain and higher LF (nu) (β=0.29, p<0.001), lower HF (nu) (β=-0.29, p<0.001), higher LF/HF (β=1.41, p=0.001), and in the nonlinear domain, significant differences were tested for SampEn15 (β=-0.35, p=0.014), SD1/SD2 (β=-0.68, p<0.001), and Alpha1/Alpha2 (ß=0.43, p=0.001). Conclusions : These results suggest that differences in HRV parameters by SSD severity were showed in the time, frequency and nonlinear domains, specific parameters demonstrating significantly higher sympathetic nerve activity and reduced ability of the parasympathetic nervous system in SSD patients with severe symptoms.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.54-67
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• 2014

This study was performed to estimate Greenhouse gases(GHGs) emissions from biomass burning at large forest fire(Ulju, Pohang and Bonghwa) in 2013. The extended methodology to estimate GHGs adopted the IPCC(Intergovermental Panel on Climate Change) Guidelines(2006) equation. For classifying fire damaged area and analyzing burn severity of total three large-fire area damaged, this study used post-fire imagery from Rapideye imagery to compute the Maximum Likelihood Classifiction (MLC). The result of accuracy assessment on burn severity from imagery showed that average overall accuracy was 75.93% and Kapp coefficient was 0.67 Finally, GHGs emissions from biomass burning in the three large-fire area 2013 were estimated as follows: Ulju $CO_2$ 63,260, CO 5.207, $CH_4$ 360, $N_2O$ 28.0 and $NO_x$ $4.4g/kg^{-1}{\cdot}ha^{-1}$, Pohang $CO_2$ 28,675, CO 2.359, $CH_4$ 163, $N_2O$ 12.7 and $NO_x$ $1.9g/kg^{-1}{\cdot}ha^{-1}$ and Bonghwa $CO_2$ 53,086, CO 1,655, $CH_4$ 114, $N_2O$ 23.5 and $NO_x$ $3.6g/kg^{-1}{\cdot}ha^{-1}$.

• Journal of Korea Water Resources Association
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• v.49 no.4
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• pp.275-282
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• 2016

The objective of this study is to propose a new method to determine the drought event and the design drought severity. In order to define a drought event from precipitation data, theory of run was applied with the cumulative rainfall deficit. When we have a large amount of rainfall over the threshold level, in this study, we compare with the previous cumulative rainfall deficit to determine whether the drought is relieved or not. The recurrence characteristics of the drought severity on the specific duration was analyzed by the conditional bivariate copula function and confidence intervals were estimated to quantify uncertainties. The methodology was applied to Seoul station with the historical dataset (1909~2015). It was observed that the past droughts considered as extreme hydrological events had from 10 to 50 years of return period. On the other hand, the current on-going drought event started from 2013 showed the significantly higher return period. It is expected that the result of this study may be utilized as the reliable criteria based on the concept of return period for the drought contingency plan.

• Journal of Korea Water Resources Association
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• v.46 no.4
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• pp.425-437
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• 2013

This study performed the bivariate drought frequency analysis for duration and severity of drought, using copula functions which allow considering the correlation structure of joint features of drought. We suggested the confidence intervals of duration-severity-frequency (DSF) curves for the given drought duration using stochastic scheme of monthly rainfall generation for 57 sites in Korea. This study also investigated drought risk via illustrating the largest drought events on record over 50 and 100 consecutive years. It appears that drought risks are much higher in some parts of the Nakdong River basin, southern and east coastal areas. However, such analyses are not always reliable, especially when the frequency analysis is performed based on the data observed over relatively short period of time. To quantify the uncertainty of drought frequency curves, the droughts were filtered by different durations. The 5%, 25%, 50%, 75%, and 95% confidence intervals of the drought severity for a given duration were estimated based on the simulated rainfall time series. Finally, it is shown that the growing uncertainties is revealed in the estimation of the joint probability using the two marginal distributions since the correlation coefficient of two variables is relatively low.

• Journal of Korea Water Resources Association
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• v.52 no.6
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• pp.381-395
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• 2019

The purpose of this study is to predict agricultural reservoir storage rate (RSR) in a month. This algorithm was developed by multiple linear regression model (MLRM) which included the past 3 months RSRs data and the future climate change scenarios. In order to improve use of predicted RSR, this study need the severe criteria in terms of drought. So, the predicted RSR was indexed as the 3 months reservoir drought index (RDI3) and then it was disaggregated into drought duration, severity, and intensity. For the future RSR estimation by climate change scenarios, the 6 RCP 8.5 scenarios of HadGEM2-ES, CESM1-BGC, MPI-ESM-MR, INM-CM4, FGOALS-s2, and HadGEM3-RA were used in three future evaluation periods (S1: 2011~2040, S2: 2041~2070, S3: 2071~2099). The future S3 period of HadGEM2-ES scenario which has the biggest increase in precipitation and temperature showed the largest decrease to 60.2% among the 6 scenarios compared to the historical RSR (1976~2005) 77.3%. In contrast, INM-CM4 scenario which has smallest changes in precipitation and temperature in S3 period showed the smallest decrease to 72.8%. For the CESM1-BGC and MPI-ESM-MR, FGOALS-s2, and HadGEM3-RA, the S3 period RSR showed 72.6%, 72.6%, 67.4%, and 64.5% decrease respectively. The future severe drought condition of RDI3 below -0.25 showed the increase trend for the number and severity up to -2.0 during S3 period.