• Korean Chemical Engineering Research
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• v.57 no.5
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• pp.637-651
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• 2019

In the event of a major accident such as an explosion in a refinery or a petrochemical plant, it has caused a serious loss of life and property and has had a great impact on the insurance market. In the case of catastrophic incidents occurring in process industries such as refinery and petrochemical plants, only the proximate causes of loss have been drawn and studied from inspectors or claims adjustors responsible for claims of property insurers, incident cause investigators, and national forensic service workers. However, it has not been done well for conducting root cause analysis (RCA) and identifying the factors that contributed to the failure and establishing preventive measures before leading to chemical plant's catastrophic incidents. In this study, the criteria of warning signs on CCPS catastrophic incident waning sign self-assessment tool which was derived through the RCA method and the contribution factor analysis method using the swiss cheese model principle has been reviewed first. Secondly, in order to determine the major incident warning signs in an actual chemical plant, 614 recommendations which have been issued during last the 17 years by loss control engineers of global reinsurers were analyzed. Finally, in order to facilitate the assessment index for catastrophic incident warning signs, the criteria for the catastrophic incident warning sign index at chemical plants were grouped by type and classified into upper category and lower category. Then, a catastrophic incident warning sign index for a chemical plant was developed using the weighted values of each category derived by applying the analytic hierarchy process (pairwise comparison method) through a questionnaire answered by relevant experts of the chemical plant. It is expected that the final 'assessment index for catastrophic incident warning signs' can be utilized by the refinery and petrochemical plant's internal as well as external auditors to assess vulnerability levels related to incident warning signs, and identify the elements of incident warning signs that need to be tracked and managed to prevent the occurrence of serious incidents in the future.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1723-1735
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• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.

• Journal of Soil and Groundwater Environment
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• v.13 no.4
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• pp.40-53
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• 2008

Groundwater pollution prediction methods have been developed to plan the sustainable groundwater usage and protection from potential pollution in many countries. DRASTIC established by US EPA is the most widely used groundwater vulnerability mapping method. However, the DRASTIC showed limitation in predicting the groundwater contamination because the DRASTIC method is designed to embrace only hydrogeologic factors. Therefore, in this study, three different methods were applied to improve a groundwater pollution prediction method: US EPA DRASTIC, Modified-DRASTIC suggested by Panagopoulos et al. (2006), and LSDG (Land use, Soil drainage, Depth to water, Geology) proposed by Rupert (1999). The Modified-DRASTIC is the modified version of the DRASTIC in terms of the rating scales and the weighting coefficients. The rating scales of each factor were calculated by the statistical comparison of nitrate concentrations in each class using the Wilcoxon rank-sum test; while the weighting coefficients were modified by the statistical correlation of each parameter to nitrate concentrations using the Spearman's rho test. The LSDG is a simple rating method using four factors such as Land use, Soil drainage, Depth to water, and Geology. Classes in each factor are compared by the Wilcoxon rank-sum test which gives a different rating to each class if the nitrate concentration in the class is significantly different. A database of nitrate concentrations in groundwaters from 149 wells was built in Keumsan area. Application of three different methods for assessing the groundwater pollution potential resulted that the prediction which was represented by a correlation (r) between each index and nitrate was improved from the EPA DRASTIC (r = 0.058) to the modified rating (r = 0.245), to the modified rating and weights (r = 0.400), and to the LSDG (r = 0.415), respectively. The LSDG seemed appropriate to predict the groundwater pollution in that it contained land use as a factor of the groundwater pollution sources and the rating of each class was defined by a real pollution nitrate concentration.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.242-252
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• 2016

A process-based ecosystem model, BIOME-BGC, was applied to simulate seasonal and inter-annual dynamics of carbon and water processes for potential evergreen needleleaf forest (ENF) biome in Korea. Two simulation sites, Milyang and Unljin, were selected to reflect warm-and-dry and cool-and-wet climate regimes, where massive diebacks of pines including Pinus densiflora, P. koraiensis and P thunbergii, were observed in 2009 and 2014, respectively. Standard Precipitation Index (SPI) showed periodic drought occurrence at every 5 years or so for both sites. Since mid-2000s, droughts occurred with hotter climate condition. Among many model variables, Cpool (i.e., a temporary carbon pool reserving photosynthetic compounds before allocations for new tissue production) was identified as a useful proxy variable of tree carbon starvation caused by reduction of gross primary production (GPP) and/or increase of maintenance respiration (Rm). Temporal Cpool variation agreed well with timings of pine tree diebacks for both sites. Though water stress was important, winter- and spring-time warmer temperature also played critical roles in reduction of Cpool, especially for the cool-and-wet Uljin. Shallow soil depth intensified the drought effect, which was, however, marginal for soil depth shallower than 0.5 m. Our modeling analysis implicates seasonal drought and warmer climate can intensify vulnerability of ENF dieback in Korea, especially for shallower soils, in which multi-year continued stress is of concern more than short-term episodic stress.

• Journal of Korean Society of Disaster and Security
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• v.13 no.4
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• pp.37-46
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• 2020

Although the importance of resilience is emerging around the world, the single definition of resilience related to natural disasters is not clear. The reason for this is that there is no specific definition of how the definition of resilience relates to similar terms such as vulnerability, recovery, adaptability, and sustainability. In addition, it is because each country and region have different geographic and geological characteristics, and each measurement index is different, just as typhoons, droughts, and earthquakes have different types of disasters. Therefore, in this study, the definition of resilience is reflected in the spatial characteristics of this study as the ability to recover from'complex disasters (concentrated heavy rain, landslides, earth and stone flows) occurring on local roads or on local roads adjacent to people or facilities. Defined. And it was divided into DRR: Disaster Resilience focusing on the Road. In addition, domestic and foreign literature surveys were conducted to derive road-centered disaster resilience factors, and a hierarchical structure was established and AHP survey was conducted to establish a DRR evaluation system. As a result of the analysis of the AHP survey, the weight of direct road disaster influencing factors (drainage facilities, protection facilities, etc.) located inside local roads was 0.742, and the weight of indirect road disaster influencing factors (population, property, etc.) located near local roads. Was found to be 0.258, indicating that the direct impact factor of road disaster was relatively higher than that of the indirect impact factor.

• Korean Journal of Psychosomatic Medicine
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• v.32 no.1
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• pp.1-9
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• 2024

Frailty is a clinical syndrome as an increased vulnerability to stressors, leading to a decrease in physiologic reserves and a decline in the ability to maintain a good homeostasis. This condition leads to an increased risk of hospitalization, disability and mortality. Frailty occurs due to various causes and requires a multidimensional approach. It is also important to detect and manage it early. Frailty is also deeply related to neuropsychiatric problems such as pain and depression. In evaluating frailty, it is desirable to comprehensively consider not only physical areas such as disease, nutrition, movement, and sensory functions, but also psychosocial areas, and representative scales include Fried's physical frailty phenotype and Rockwood's frailty index. Physical activity and appropriate protein intake are important for frailty management, and inappropriate drug use should be reduced and oral care, cognitive function, and falls should also be noted. Frailty and pain can affect each other, and pain can promote frailty. Evidence has been published that hormone and protein abnormalities, immune system activity and inflammatory response, and epigenetic mechanisms work in common in the field of frailty and pain. More extensive and high-quality research should be conducted in the future, and the quality of life will be improved if the results are applied to the suppression and treatment of old age and pain.

• Journal of Oriental Neuropsychiatry
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• v.31 no.1
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• pp.1-12
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• 2020

Objectives: The purpose of this study was to evaluate the reliability and validity of the instrument on pattern identification for insomnia (PIT-Insomnia) and verify the correlation between PIT-Insomnia and psychological tests. Methods: Two evaluators examined the pattern identification of the participants who met insomnia disorder diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorder, Fifth Edition (DSM-5) and took the Insomnia Severity Index (ISI) score over 15 once manually and twice using the PIT-Insomnia to measure the inter-rater and test-retest reliability. We also conducted the following surveys: the Pittsburgh Sleep Quality Index (PSQI), the Korean version of Beck's depression inventory (K-BDI), the Korean version of the State-Trait Anxiety Inventory (STAI-K), the Korean Symptom checklist-95 (KSCL-95), and the EuroQol-5 dimension (EQ-5D), to measure concurrent validity and correlation between the PTI-Insomnia and psychological tests. Results: 1. The test-retest reliability analysis of the pattern identification results showed moderate agreement, and test-retest reliability analysis of each pattern identification score showed agreements from poor to moderate. 2. The inter-rater reliability analysis of the pattern identification results via manual showed slight agreement, when analysis was performed with calibration, the inter-rater reliability analysis of the pattern identification results via manual showed fair agreement. 3. The concordance analysis between results via manual and the PIT-Insomnia showed poor agreement, when the analysis was performed with calibration, concordance analysis showed fair agreement. 4. The concordance analysis between the PIT-Insomnia and the PSQI showed positive linear correlation. 5. The concordance analysis between the PIT-Insomnia and the PSQI, K-BDI, STAI-K, KSCL-95, and EQ-5D showed that non-interaction between the heart and kidney have positive linear correlation with the K-BDI, anxiety item of KSCL-95, dual deficiency of the heart-spleen have positive linear correlation with somatization item of KSCL-95, paranoia item of KSCL-95, heart deficiency with timidity have positive linear correlation with stress vulnerability item of KSCL-95, parania item of KSCL-95, phlegm-fire harassing the heart have positive linear correlation with K-BDI, paranoia item of KSCL-95, depressed liver qi transforming into fire have positive linear correlation with the anxiety item of KSCL-95, parania item of KSCL-95, all pattern identification have negative linear correlation with EQ-5D. Conclusions: The PIT-Insomnia has moderate agreement of reliability and reflects the severity of insomnia since it has some concurrent validity with the PSQI. There are some correlations between the PTI-Insomnia with specific psychological tests, so we could suggest it can be used appropriately in the clinical situation.

• The Korean Journal of Pharmacology
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• v.32 no.3
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• pp.335-345
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• 1996

A critical role of oxygen-derived free radicals has been implicated in ischemia/reperfusion (I/R)-induced brain damage. In this study, we have produced experimental I/R to the brains of Mongolian gerbil (Meriones unguiculatus) by a transient occlusion and release of the common carotid arteries. We have attempted to determine whether the oxidative stress is generated upon I/R and whether this oxidative stress is linked to the cell damage. Since hippocampus has been suggested as one of the most vulnerable regions of the brain to the oxidative stress, we analyzed samples from hippocampus in comparison with those from cortex. In addition, we have examined the expression of heat shock protein 70kD species (HSP70) in these regions in order to evaluate a possible role of this protein in I/R-induced brain damage. To determine whether the oxidative stress is produced upon I/R, we measured the glutathione oxidation, GSSG/ (GSH + 2xGSSG), as an index of oxidative stress. We found an increase of the glutathione oxidation primarily in hippocampus upon I/R. To determine whether this oxidative stress is linked to the cell damage, we measured the degree of lipid peroxidation upon I/R. We found an increase of lipid peroxidation in both regions. However, the magnitude of increases was greater in hippocampus than in cortex. In addition, we found that changes in both the magnitude and the temporal patterns of glutathione oxidation closely correlated with those of lipid peroxidation. Our study provides biochemical evidences that the oxidative stress is generated upon I/R and this oxidative stress is linked to the oxidative cell damage. Our study also provides evidences that the degree of oxidative stress as well as oxidative cell damage is greater in hippocampus than in cortex. We could not find difference in the basal level of HSP70 expression between hippocampus and cortex, indicating that the intrinsic vulnerability of hippocampus cannot be explained by the lower level of HSP70 expression. We did find, however, that the induction of HSP70 expression upon I/R was impaired in the hippocampus. This impairment appeared to be at the transcriptional level. These results suggest that the measurement of HSP70 induction may be employed as a useful predictor of differential cellular susceptibilities to the I/R-induced brain damage.

• Journal of Practical Agriculture & Fisheries Research
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• v.20 no.1
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• pp.107-123
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• 2018

The global impact of climate change on agriculture is now increasing. The purpose of this study was to investigate the effect of climate change on livestock productivity. The variables that have the greatest influence on climate change factors were examined through previous studies and expert surveys. We also used the actual productivity data of livestock farmers to investigate the relationship with climate change. In order to evaluate the climate for changes in livestock productivity, national representative data (such as bullocks, dairy, pigs, laying hens, and broilers) were surveyed in Korea. Also, to select and classify evaluation indexes, we selected climate change factor variables as prior studies and studied the weighting factor of climate variable factors. In this study, the researchers of industry, academia, and farmers in the livestock sector conducted questionnaires on the indicators of vulnerability to climate change using experts, and then weighed the selected indicators using the hierarchical analysis process (AHP). In order to verify the validity of the evaluation index, was examined using domestic climate data (temperature, precipitation, humidity, etc.). Correlation and regression analysis were performed. The empirical relationship between climate change and livestock productivity was examined through this study. As a result, we used data with high reliability of statistical analysis and found that there are significant variables.