• Journal of Korea Water Resources Association
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• v.47 no.12
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• pp.1107-1119
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• 2014

Interesting in abnormal climate is currently growing because of climate change. With this, an increasing number of people continue to show concern over the negative effects of such changes. In Korea, the annual average rainfall amount increased to about 19% from 1,155 mm in the 1910s to 1,375 mm in the 2000s. By the end of the 21st century, it has been projected that rainfall will further increase to about 17%. In particular, the 10-year frequency of localized heavy rain of more than 100-mm rainfall per day reached 385 days in the last 10 years. As such, it increased 1.7 times from 222 in the 1970s-80s. The extreme events caused by climate change is thus reported as having exacerbated over the years. Gangwon-province will suffer more from climate change than any other region in Korea because of its mostly mountainous terrain. It is a special region with both mountainous and oceanic climates divided alongside the eastern and western regions of the Taebaek Mountain Range. As such, this paper try to quantify using ETCCDI (Expert Team on Climate Change Detection and Indices) the recent climate changes in this region.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.617-625
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• 1999

Global warming has begun since the industrial revolution and it is getting worse recently. Even though the increase of greenhouse gases such as $CO_2$ is thought to be the main cause for global warming, its impact on global climate has not been revealed clearly in rather quantitative manners. However, researches using General Circulation Models(GCMs) has shown the accumulation of greenhouse gases increases the global mean temperature, which in turn impacts on the global water circulation pattern. This changes in global water circulation pattern result in abnormal and more frequent meteorological events such as severe floods and droughts, generally more severe than the normal ones, which are now common around the world and is referred as a indirect proof of global warming. Korean peninsula also cannot be an exception and have had several extremes recently. The main objective of this research is to analyze the impact of global warming on the change of flood and drought frequency. Based on the assumption that now is a point in a continuously changing climate due to global warming, we analyzed the observed daily rainfall data to find out how the increase of annual rainfall amount affects the distribution of daily rainfall. Obviously, the more the annual rainfall depth, the more frequency of much daily rainfall, and vice versa. However, the analysis of the 17 points data of Keum river basin in Korea shows that especially the number of days of under 10mm or over 50mm daily rainfall depth is highly correlated with the amount of annual rainfall depth, not the number of dry days with their correlation coefficients quite high around 0.8 to 0.9.

• Journal of Wetlands Research
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• v.12 no.2
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• pp.13-23
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• 2010

According to recent researches on climate change, the global warming is obvious to increase rainfall intensity. Damage caused by extreme hydrologic events due to global change is steadily getting bigger and bigger. Recently, frequently occurring heavy rainfalls surely affect the trend of rainfall observations. Probability precipitation estimation method used in designing and planning hydrological resources assumes that rainfall data is stationary. The stationary probability precipitation estimation method could be very weak to abnormal rainfalls occurred by climate change, because stationary probability precipitation estimation method cannot reflect increasing trend of rainfall intensity. This study analyzed temporal variation of trend in rainfall time series at 51 stations which are not significant for statistical trend tests. After modeling rainfall time series with maintaining observed statistical characteristics, this study also estimated whether rainfall data is significant for the statistical trend test in near future. It was found that 13 stations among sample stations will have trend within 10 years. The results indicate that non-stationary probability precipitation estimation method must be applied to sufficiently consider increase trend of rainfall.

• Land and Housing Review
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• v.12 no.3
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• pp.109-119
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• 2021

Global warming caused by greenhouse gas emissions has rapidly increased abnormal climate events and geotechnical engineering hazards in terms of their size and frequency accordingly. Biopolymer-based soil treatment (BPST) in geotechnical engineering has been implemented in recent years as an alternative to reducing carbon footprint. Furthermore, thermo-gelating biopolymers, including agar gum, gellan gum, and xanthan gum, are known to strengthen soils noticeably. However, an explicitly detailed evaluation of the correlation between the factors, that have a significant influence on the strengthening behavior of BPST, has not been explored yet. In this study, machine learning regression analysis was performed using the UCS (unconfined compressive strength) data for BPST tested in the laboratory to evaluate the factors influencing the strengthening behavior of gellan gum-treated soil mixtures. General linear regression, Ridge, and Lasso were used as linear regression methods; the key factors influencing the behavior of BPST were determined by RMSE (root mean squared error) and regression coefficient values. The results of the analysis showed that the concentration of biopolymer and the content of clay have the most significant influence on the strength of BPST.

• Korean Journal of Labor Studies
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• v.24 no.2
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• pp.321-365
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• 2018

Though the British shipbuilding industry dominated the world market in the 19th century, it could not avoid the repetitive rise and fall of the unemployment following after the cyclical fluctuations. Without challenging the employers' rights to fire at will, the boilermakers maintained their own unemployment insurance in order to escape from the new poverty law system. In the beginning the craft union could continue their own unemployment insurance under the National Insurance Act of 1911, but it went into bankruptcy under the massive unemployment of the 1920s and the attacks of shipyard employers. The Act of 1911 was a step towards social solidarity in that it spread the risks beyond the occupational boundaries, applying unemployment insurance to unskilled and non-union workers, and the employer and the government also paid the premium. In the Great Depression, the shipyard trade unions demanded that the government should intervene in the shipbuilding market to provide jobs, but it was not accepted by the government. The government responded only to the another demand of the union for the maintenance, which could be achieved partially through the abnormal operation of the insurance system, abandoning the insurance principle. After all, unemployment in the shipbuilding industry was resolved only by the expansion of rearmaments and the outbreak of World War II. From the 19th century to the World War II, the craft unions did not challenge the employers' right to fire at will and did not attempt to regulate dismissal procedures or make any demands on dismissal compensations. During interwar periods rules and practices related with weak employment protection - one of the main features of the liberal employment adjustment institution - were prevalent in Britain. The principle of 'employment at will' could survive through the historical events such as the World War I, II as the operation of the unemployment insurance became the focus of the social conflicts.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.1
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• pp.15-25
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• 2019

The development of reliable and objective definitions as well as automated processes for the detection of health care-associated infections (HAIs) is crucial; however, transformation to an automated surveillance system remains a challenge. Early outbreak identification usually requires clinicians who can recognize abnormal events as well as ongoing disease surveillance to determine the baseline rate of cases. The system screens the laboratory information system (LIS) data daily to detect candidates for health care-associated bloodstream infection (HABSI) according to well-defined detection rules. The system detects and reserves professional autonomy by requiring further confirmation. In addition, web-based HABSI surveillance and classification systems use discrete data elements obtained from the LIS, and the LIS-provided data correlates strongly with the conventional infection-control personnel surveillance system. The system was timely, acceptable, useful, and sensitive according to the prevention guidelines. The surveillance system is useful because it can help health care professionals better understand when and where the transmission of a wide range of potential pathogens may be occurring in a hospital. A national plan is needed to strengthen the main structures in HAI prevention, Healthcare Associated Prevention and Control Committee (HAIPCC), sterilization service (SS), microbiology laboratories, and hand hygiene resources, considering their impact on HAI prevention.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.41-51
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• 2018

Recently, in the field of video surveillance, deep learning based learning method is applied to intelligent video surveillance system, and various events such as crime, fire, and abnormal phenomenon can be robustly detected. However, since occlusion occurs due to the loss of 3d information generated by projecting the 3d real-world in 2d image, it is need to consider the occlusion problem in order to accurately detect the object and to estimate the pose. Therefore, in this paper, we detect moving objects by solving the occlusion problem of object detection process by adding depth information to existing RGB information. Then, using the convolution neural network in the detected region, the positions of the 14 keypoints of the human joint region can be predicted. Finally, in order to solve the self-occlusion problem occurring in the pose estimation process, the method for 3d human pose estimation is described by extending the range of estimation to the 3d space using the predicted result of 2d keypoint and the deep neural network. In the future, the result of 2d and 3d pose estimation of this research can be used as easy data for future human behavior recognition and contribute to the development of industrial technology.

• Korean Journal of Environment and Ecology
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• v.36 no.5
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• pp.535-549
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• 2022

Damage to forests, such as broken or falling trees, has increased due to the increased intensity and frequency of abnormal climate events, such as strong winds and heavy rains. However, it is difficult to respond to them in advance based on prediction since structural defects such as cavities and bumps inside trees are difficult to identify with a visual inspection. Non-invasive sonic tomography (SoT) is a method of estimating internal defects while minimizing physical damage to trees. Although SoT is effective in diagnosing internal defects, its accuracy varies depending on the species. Therefore, it is necessary to analyze the reliability of its measurement results before applying it in the field. In this study, we measured internal defects in wood by cross-applying destructive resistance micro drilling on old Pinus densifloraSiebold & Zucc. and Ginkgo bilobaL., which are representative tree species in Korea, to verify the reliability of SoT and compared the evaluation results. The t-test for the mean values of the defect measurement between the two groups showed no statistically significant difference in pine trees and some difference in ginkgo trees. Linear regression analysis results showed a positive correlation with an increase in defects in SoT images when the defects in the drill resistance graph increased in both species.

• Journal of Life Science
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• v.33 no.1
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• pp.102-113
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• 2023

This review discusses the cellular and molecular mechanisms by which the endometrial estrogen and progesterone receptors regulate local estrogen production, expression of the specific estrogen receptors, progesterone resistance, inflammatory responses and the differentiation and survival of endometriotic cells in endometrial inflammation. The epigenetic aberrations of endometrial stromal cells play an important role in the pathogenesis and progression of endometriosis. In particular, differential methylation of the estrogen receptor genes changes in the stromal cells the dominancy of estrogen receptor from ERα into ERβ, and results in the abnormal estrogen responses including inflammation, progesterone resistance and the disturbance of retinoid synthesis. These stromal cells also stimulate local estrogen production in response to PGE2 and the SF-1 mediated induction of steroidogenic enzyme expression, and the increased estradiol then feeds back into the ERβ to repeat the vicious inflammatory cycle through the activation of COX-2. In addition, high levels of ERβ expression may also change the chromatin structure of endometrial mesenchymal stem cells, and together with the repeated menstrual cycles can induce formation of the endometriotic tissue. The cascade of these serial events then leads to cell adhesion, angiogenesis and survival of the differentiation-disregulated stromal cells through the action of inflammatory factors such as ERβ-mediated estrogen, TNF-α and TGF-β1. Therefore, understanding of the dynamic hormonal changes during the menstrual cycle and the corresponding signal transduction mechanisms of the related nuclear receptors in endometrium would provide new insights for treating inflammatory diseases such as the endometriosis.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1211-1222
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• 2022

Abnormal condition inevitably occurs during operation of water distribution system (WDS) and requires the isolation of certain areas using isolation valves. In general, the determination of the optimal location of isolation valves considered minimization of hydraulic failures as isolation of certain areas causes a change in hydraulic states (e.g., flow direction, velocity, pressure, etc.). Water quality failure can also be induced by changes in hydraulics, which have not been considered for isolation valve system design. Therefore, this study proposes a new isolation valve system design methodology to prevent unexpected water quality failure events. The new methodology considers flow direction change ratio (FDCR), which accounts for flow direction changes after isolation of the area, as a constraint while reliability is used as the objective function. The optimal design model has been applied to a synthetic grid network and the results are compared with the traditional design approach. Results show that considering FDCR can eliminate flow direction changes while average pressure and coefficient of variation of pressure, velocity, and hydraulic geodesic index (HGI) outperform compared to the traditional design approach. The proposed methodology is expected to be a useful approach to minimizing unexpected consequences by traditional design approaches.