• Korean Journal of Agricultural and Forest Meteorology
• /
• v.25 no.4
• /
• pp.446-454
• /
• 2023

The impact of climate change on agriculture is substantial, especially as global warming is projected to lead to varying temperature and humidity patterns in the future. These changes pose a higher risk for both crops and livestock, exposing them to environmental stressors under altered climatic conditions. Specifically, as temperatures are expected to rise, the risk of heat stress is assessable through the Temperature-Humidity Index (THI), derived from temperature and relative humidity data. This study involved the comparison of THI collected from 10 Korea Meteorological Administration ASOS stations spanning a 60-year period from 1961 to 2020. Moreover, high-resolution temperature and humidity distribution data from 1981 to 2020 were employed to generate high-resolution TH I distributions, analyzing temporal changes. Additionally, the number of days characterized by heat stress, derived from TH I, was compared over different time periods. Generally, TH I showed an upward trend over the past, albeit with varying rates across different locations. As TH I increased, the frequency of heat stress days also rose, indicating potential future cost increases in the livestock industry due to heat-related challenges. The findings emphasize the feasibility of evaluating heat stress risk in livestock using THI and underscore the need for research analyzing THI under future climate change scenarios.

• Journal of Korean Society of Water and Wastewater
• /
• v.37 no.5
• /
• pp.261-269
• /
• 2023

In light of recent social concerns related to issues such as water supply pipe deterioration leading to problems like leaks and degraded water quality, the significance of maintenance efforts to enhance water source quality and ensure a stable water supply has grown substantially. In this study, scan statistic was applied to analyze water quality complaints and water leakage accidents from 2015 to 2021 to present a reasonable method to identify areas requiring improvement in water management. SaTScan, a spatio-temporal statistical analysis program, and ArcGIS were used for spatial information analysis, and clusters with high relative risk (RR) were determined using the maximum log-likelihood ratio, relative risk, and Monte Carlo hypothesis test for I city, the target area. Specifically, in the case of water quality complaints, the analysis results were compared by distinguishing cases occurring before and after the onset of "red water." The period between 2015 and 2019 revealed that preceding the occurrence of red water, the leak cluster at location L2 posed a significantly higher risk (RR: 2.45) than other regions. As for water quality complaints, cluster C2 exhibited a notably elevated RR (RR: 2.21) and appeared concentrated in areas D and S, respectively. On the other hand, post-red water incidents of water quality complaints were predominantly concentrated in area S. The analysis found that the locations of complaint clusters were similar to those of red water incidents. Of these, cluster C7 exhibited a substantial RR of 4.58, signifying more than a twofold increase compared to pre-incident levels. A kernel density map analysis was performed using GIS to identify priority areas for waterworks management based on the central location of clusters and complaint cluster RR data.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.10 no.4
• /
• pp.121-131
• /
• 2008

This study was conducted to delineate temporal and spatial patterns of potential risk of cold injury by combining the short-term cold hardiness of Campbell Early grapevine and the IPCC projected climate winter season minimum temperature at a landscape scale. Gridded data sets of daily maximum and minimum temperature with a 270m cell spacing ("High Definition Digital Temperature Map", HD-DTM) were prepared for the current climatological normal year (1971-2000) based on observations at the 56 Korea Meteorological Administration (KMA) stations using a geospatial interpolation scheme for correcting land surface effects (e.g., land use, topography, and elevation). The same procedure was applied to the official temperature projection dataset covering South Korea (under the auspices of the IPCC-SRES A2 and A1B scenarios) for 2071-2100. The dormancy depth model was run with the gridded datasets to estimate the geographical pattern of any changes in the short-term cold hardiness of Campbell Early across South Korea for the current and future normal years (1971-2000 and 2071-2100). We combined this result with the projected mean annual minimum temperature for each period to obtain the potential risk of cold injury. Results showed that both the land areas with the normal cold-hardiness (-150 and below for dormancy depth) and those with the sub-threshold temperature for freezing damage ($-15^{\circ}C$ and below) will decrease in 2071-2100, reducing the freezing risk. Although more land area will encounter less risk in the future, the land area with higher risk (>70%) will expand from 14% at the current normal year to 23 (A1B) ${\sim}5%$ (A2) in the future. Our method can be applied to other deciduous fruit trees for delineating geographical shift of cold-hardiness zone under the projected climate change in the future, thereby providing valuable information for adaptation strategy in fruit industry.

• Journal of the Korean Geotechnical Society
• /
• v.36 no.2
• /
• pp.5-15
• /
• 2020

The liquefaction phenomenon that occurred during the Pohang earthquake (M_L=5.4) brought new awareness to the people about the risk of liquefaction caused by the earthquake. Liquefaction hazard maps with 2 km grid made in 2014 used more than 100,000 borehole data for the whole country, and regions without soil investigation data were produced using interpolation. In the mapping of macro liquefaction hazard for the whole country, the site amplification effect and the ground water level 0 m were considered. Recently, the Ministry of Public Administration and Security (2018) published a new site classification method and amplification coefficient of the common standard for seismic design. Therefore, it is necessary to rewrite the liquefaction hazard map reflecting the revised amplification coefficient. In this study, the results of site classification according to the average shear wave velocity in soils before and after revision were compared in the whole country. Also, liquefaction assessment results were compared in Gangseo-gu, Busan. At this time, two ground accelerations corresponding to the 500 and 1,000 years of return period and two ground water table, 5 m for the average condition and 0 m the extreme condition were applied. In the drawing of liquefaction hazard map, a 500 m grid was applied to secure a resolution higher than the previous 2 km grid. As a result, the ground conditions that were classified as S_C and S_D grounds based on the existing site classification standard were reclassified as S₂, S₃, and S₄ through the revised site classification standard. Also, the result of the Liquefaction assessments with a return period of 500 years and 1,000 years resulted in a relatively overestimation of the LPI applied with the ground amplification factor before revision. And the results of this study have a great influence on the liquefaction assessment, which is the basis of the creation of the regional liquefaction hazard map using the amplification factor.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.65-82
• /
• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of radiological science and technology
• /
• v.37 no.4
• /
• pp.287-294
• /
• 2014

Gallstone is the most common disease of the biliary system. Korean has experienced an increase in the percentage of cholesterol gallstones. The major risk factors associated with cholesterol gallstones are age, gender as well as obesity. This study was designed to determine the prevalence of gallstones in the last three years and evaluate the associated risk factors in the population who underwent health screening. The study population consisted of 2,484 males and 2,212 females who visited the health promotion center in Dalseogu, Daegu in Korea from January 2011 to December 2013. Each participant in the study had their biliary system gallbladder examined using ultrasonography. Classified as underweight, normal weight or overweight using the population of obese according to the body mass index, and classified according to mood diagnosis of diabetes presented by the American Diabetes Association. Fasting blood glucose and number of liver function, the divided the control group by referring to the normal liver function values used herein. The geological map, I was classified as NCEP APT III. A showed of total 148 people were found to have gallstones. The prevalence of sex among 148 patients (3.15%) 84 men (1.79%) and 64 women 1.36%) which shows significantly there is little difference. 1.84% 40 years and below, 3.38% 40's showed age prevalence was 4.66% in 50's and above. In addition, Total-cholesterol was at the most in 52 people, LDL-cholesterol in 398 people, Triglyceride in 36 people, HDL-cholesterol in 19 people. The abnormal group, was created from the total-cholesterol categories from a physical examination of a subject that has been found to be gallstones in the gallbladder. A result of conducting the univariate analysis shows the prevalence of gallstones, a correlation that is meaningful. The logistic regression analysis of multiple ages was chosen to show risk factors age independent cholelithiasis. In spite of the conclusion, gallstones are not displayed in relation to the metabolic syndrome but in order to clarify this, not only the subject of a health examination is needed but, a further study of the general public when possible.

• Economic and Environmental Geology
• /
• v.52 no.6
• /
• pp.637-645
• /
• 2019

Due to the transformation to the intelligent information society, the rapid change of our life and environment is expected. The Ministry of Science and ICT (MSIT) and the National Research Council of Science and Technology (NST) introduced a five-year government supported research institution's planning and evaluation based on the mid-to long-term perspective. This study collects international benchmarking information including industry, academia, and research fields by collecting mid- and long-term strategy reports from public research institutes, surveys by experts from abroad universities and research institutes, and analyzing overseas market information reports. The British Geological Survey (BGS), the U.S. Geological Survey (USGS) and the japanese geological survey related institutes (AIST-GSJ) plans for three-dimensional national geological information, predictions of geological environmental disasters, and development of important metals and material in the low carbon economic transformation and in the era of the Fourth Industrial Revolution. The mid- and long-term program emphasizes basic and public research on geological information through abroad experts survey such as the IPGP-CNRS etc. The market analysis of the mining automation and digital map sectors has been able to derive the fields in which the role of public research institutes by the market is expected such as data collection on land and in the air, mobile or three-dimensional information production, smooth/fast/real-time maps, custom map design, mapping support to various platforms, geological environmental risk assessment and disaster management information and maps.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.13 no.1
• /
• pp.101-113
• /
• 2010

Recently actual rainfall pattern is decreasing rainy days and increasing in rainfall intensity and the frequency of flood occurrence is also increased. To consider recent situation, Engineers use deterministic methods like a PMP(Probable Maximum Precipitation). If design storm wouldn't occur, increasing of design criteria is extravagant. In addition, the biggest structure cause trouble with residents and environmental problem. And then it is necessary to study considering probability of rainfall parameter in each sub-basin for design of water structure. In this study, stochastic rainfall patterns are generated by using log-ratio method, Johnson system and multivariate Monte Carlo simulation. Using the stochastic rainfall patterns, hydrological analysis, hydraulic analysis and 2nd flooding analysis were performed based on GIS for their applicability. The results of simulations are similar to the actual damage area so the methodology of this study should be used about making a flood risk map or regidental shunting rout map against the region.

• Journal of the Korean Society of Radiology
• /
• v.13 no.7
• /
• pp.955-960
• /
• 2019

The Computed tomography (CT) scan can have high radiation in a few tests, and this risk is significant given that it is often repeated in one patient. In children, the incidence of radiation-induced cancer is reported because organs are growing, are more sensitive to radiation. 3D printing has recently been studied to be applied to various applications as a research field for 3D printing applications, research on fabrication of radiation shields and materials has been conducted. The purpose of the 3D printer is to replace the existing panel-type shields and to make customized designs according to the shape of the human body. Therefore, research on 3D information processing to be input to the 3D printer is also necessary. In this study, 3D data of the human body surface, which is the preliminary step of the manufacture of patient-specific eye shield using stereo vision depth map technology, was studied. This study aims to increase the possibility of three-dimensional output. As a result of experimenting with this method, which is relatively simple compared with other methods of 3D information processing, the minimum coordinates for 3D information are extracted. The results of this study provided the advantages and limitations of stereo images using natural light and will be the basic data for the manufacture of eye shields in the future.

• Spatial Information Research
• /
• v.14 no.4 s.39
• /
• pp.363-377
• /
• 2006

Mean annual soil loss was calculated and critical soil erosion areas were identified for the Congaree River Basin in South Carolina, USA using the Revised Universal Soil Loss Equation (RUSLE) model. In the RUSLE model, the mean annual soil loss (A) can be calculated by multiplying rainfall-runoff erosivity (R), soil erodibility (K), slope length and steepness (LS), crop-management (C), and support practice (P) factors. The critical soil erosion areas can be identified as the areas with soil loss amounts (A) greater than the soil loss tolerance (T) factor More than 10% of the total area was identified as a critical soil erosion area. Among seven subwatersheds within the Congaree River Basin, the urban areas of the Congaree Creek and the Gills Creek subwatersheds as well as the agricultural area of the Cedar Creek subwatershed appeared to be exposed to the risk of severe soil loss. As a prototype model for examining future effect of human and/or nature-induced changes on soil erosion, the RUSLE model customized for the area was embedded into ESRI ArcGIS ArcMap 9.0 using Visual Basic for Applications. Using the embedded model, users can modify C, LS, and P-factor values for each subwatershed by changing conditions such as land cover, canopy type, ground cover type, slope, type of agriculture, and agricultural practice types. The result mean annual soil loss and critical soil erosion areas can be compared to the ones with existing conditions and used for further soil loss management for the area.