Purpose: To evaluate the factors affecting hospital utilization for respiratory diseases by ecological study design and GIS tool. To raise the social concern for respiratory disease by the result. Methods: Hospital admission data supported by national health insurance cooperation were transformed to spread sheet data format and combined with air monitoring dataset. Air pollution data were collected from the annual report of air monitoring published by Korea Ministry of Environment. Socioeconomic statistics including population density, age distribution, forest ratio etc.. were filed using Korea National Statistical Office database. Multiple linear regression analysis was performed to evaluate the factors affecting hospital utilization for respiratory diseases. Analytical unit was 52 cities. Results: The factors affecting hospital utilization for respiratory diseases were the proportion of population 60 years and over, seaside city, $O_3$ level, smoking rate. Conclusions: However, outdoor pollutants monitoring data and smoking rate have weakness in reflecting individual exposure. Further research is required to propose more illustrative means to evaluate causal relationship between air pollution and respiratory health effect factors.
A class imbalance problem arises when one class outnumbers the other class by a large proportion in binary data. Studies such as transforming the learning data have been conducted to solve this imbalance problem. In this study, we compared resampling methods among methods to deal with an imbalance in the classification problem. We sought to find a way to more effectively detect the minority class in the data. Through simulation, a total of 20 methods of over-sampling, under-sampling, and combined method of over- and under-sampling were compared. The logistic regression, support vector machine, and random forest models, which are commonly used in classification problems, were used as classifiers. The simulation results showed that the random under sampling (RUS) method had the highest sensitivity with an accuracy over 0.5. The next most sensitive method was an over-sampling adaptive synthetic sampling approach. This revealed that the RUS method was suitable for finding minority class values. The results of applying to some real data sets were similar to those of the simulation.
The choice of business method is a necessary decision at the last moment of life, and to this end, we use several criteria. Our funeral methods were dominated by ancestral worship culture and religion, not nature. It is only recently that nature was used as a means from a human perspective, but natural field methods such as consideration for nature and symbiosis with nature have emerged. The recent high public preference for natural fields is today's strong zeitgeist and nature-friendly values. Based on statistics in 2021, Korea's national cremation rate exceeded 92%, and compared to less than 20% of the cremation rate just 20 years ago, our business method has changed rapidly. As the cremation promotion movement and government policies, which began in the early 90s, were systematically developed, the enshrinement facility was established next to us. However, while this was also subject to criticism of national damage, the Jang Act called natural field was introduced into the system in 2008, and about 15 years have passed, but the revitalization of natural field is slower than expected. One of the reasons for the stagnation of development is to forget the basic spirit of the natural field (once you return to the forest), and to think like a graveyard grave. Accordingly, this study aims to identify the background of the introduction and current operation of natural fields and present development measures to improve memorial services to make natural fields loved by the people.
Background: Surgical resection is the standard treatment for early-stage lung cancer. Since postoperative lung function is related to mortality, predicted postoperative lung function is used to determine the treatment modality. The aim of this study was to evaluate the predictive performance of linear regression and machine learning models. Methods: We extracted data from the Clinical Data Warehouse and developed three sets: set I, the linear regression model; set II, machine learning models omitting the missing data: and set III, machine learning models imputing the missing data. Six machine learning models, the least absolute shrinkage and selection operator (LASSO), Ridge regression, ElasticNet, Random Forest, eXtreme gradient boosting (XGBoost), and the light gradient boosting machine (LightGBM) were implemented. The forced expiratory volume in 1 second measured 6 months after surgery was defined as the outcome. Five-fold cross-validation was performed for hyperparameter tuning of the machine learning models. The dataset was split into training and test datasets at a 70:30 ratio. Implementation was done after dataset splitting in set III. Predictive performance was evaluated by R2 and mean squared error (MSE) in the three sets. Results: A total of 1,487 patients were included in sets I and III and 896 patients were included in set II. In set I, the R2 value was 0.27 and in set II, LightGBM was the best model with the highest R2 value of 0.5 and the lowest MSE of 154.95. In set III, LightGBM was the best model with the highest R2 value of 0.56 and the lowest MSE of 174.07. Conclusion: The LightGBM model showed the best performance in predicting postoperative lung function.
Proceedings of the Korean Society of Crop Science Conference
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2022.10a
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pp.90-90
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2022
Nicaragua is located in Central America, climatic conditions are considered tropical dry forest. Statistics reflex that in Nicaragua exits 24,000 rice farmers. National rice production only covers 73% of the national consumption. It exists two sowing system: irrigation and rainfed. Varieties used in both systems are mid-late maturity (120-135 days), there are 14 released varieties for irrigation, eight for rainfed, and eight landraces used in rainfed. The current breeding system (introduction of lines from Colombia) has increased the national production, however, has some limitation due to the lack of enough variability, reducing the proability of finding good genotypes and therefore the possibility of satisfying 100% of the demand. The purpose of this study was to analyze the problems that must be resolved in the short and long term to improve rice productivity in Nicaragua. In this paper we explain some proposal for an improvement plan. The selection of varieties with high adaptability to various cultivation environmental conditions it is necessary, also to thoroughly manage seed purity to supply certified seeds. In rice cultivation technology, it needs to improve seedling standing and weeding effect by improving soil leveling and water-saving cultivation technology. Also, proper fertilization and planting density must be established in irrigated and rain-fed areas. Furthermore, capacity must be strengthened by collecting and training with the most recent agricultural technology information, as well as by revitalizing the union rather than the individual farmer. It is necessary to develop varieties highly adaptable to the Nicaraguan cultivation environment, as well as to expand irrigation facilities and cultivation technology suitable for weather conditions in rain-fed areas. Last, it is necessary to maintain the consistency of agricultural policy for continuous and stable rice production in response to climate change events such as drought or intermittent heavy rain.
Korean Journal of Agricultural and Forest Meteorology
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v.1
no.1
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pp.41-51
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1999
This study was conducted to investigate the effects of local climatic conditions on the annual increment of Korean white pine planted in Gapyung and Yaungdong. For this, stand variables such as mean DBH, mean height, basal area per hectare, and volume per hectare by stand age were measured and summarized for each locality. Based on these statistics, annual increments for 8 years from stand age 10 to 18 were calculated for each of stand variables. A topoclimatological technique which makes use of empirical relationships between the topography and the weather in study sites was applied to produce normal estimates of monthly mean, maximum, minimum temperatures, relative humidity, precipitation, and hours of sunshine. Then, the yearly climatic variables from 1990 to 1997 for each study site were derived from the spatial interpolation procedures based on inverse- distance weighting of the observed deviation from the climatic normals at the nearest 11 standard weather stations. From these estimates, 17 weather variables such as warmth index, coldness index, index of aridity etc., which affect the tree growth, were computed on yearly base for each locality. The deviations of measured annual increments from the expected annual increments for 8 years based on yield table of Korean white pine were then correlated with and regressed on the yearly weather variables to examine effects of local climatic conditions on the growth. Gapyung area provides better conditions for the growth of Korean white pine in the early stage than Youngdong area. This indicates that the conditions such as low temperature, high relative humidity, and large amount of precipitation provide favor environment for the early growth of Korean white pine. A ccording to the correlation and regression an analysis using local climatic conditions and annual increments, the growth pattern of Gapyung area corresponds to this tendency. However, it was found that the relationship between annual increments and local climatic conditions in Youngdong area shows different tendency from Gapyung. These results mean that the yearly growth pattern could not sufficiently be explained by climatic conditions with high variance in yearly weather variables. In addition, the poor growth in Youngdong area might not only be affected by climatic conditions, but also by other environmental factors such as site quality.
Korean Journal of Agricultural and Forest Meteorology
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v.26
no.1
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pp.31-52
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2024
Considering the significant relationship between a tree's branch structure and physiology, understanding the detailed branch structure is crucial for fields such as species classification, and 3D tree modelling. Recently, terrestrial laser scanning (TLS) and quantitative structure model (QSM) have enhanced the understanding of branch structures by capturing the radius, length, and branching angle of branches. Previous studies examining branch structure with TL S and QSM often relied on mean or median of branch structure parameters, such as the radius ratio and length ratio in parent-child relationships, as representative values. Additionally, these studies have typically focused on the relationship between trunk and the first order branches. This study aims to explore the distribution of branch structure parameters up to the third order in Aesculus hippocastanum, Ginkgo biloba, and Prunus yedoensis. The gamma distribution best represented the distributions of branch structure parameters, as evidenced by the average of Kolmogorov-Smirnov statistics (radius = 0.048; length = 0.061; angle = 0.050). Comparisons of the mode, mean, and median were conducted to determine the most representative measure indicating the central tendency of branch structure parameters. The estimated distributions showed differences between the mode and mean (average of normalized differences for radius ratio = 11.2%; length ratio = 17.0%; branching angle = 8.2%), and between the mode and median (radius ratio = 7.5%; length ratio = 11.5%; branching angle = 5.5%). Comparisons of the estimated distributions across branch orders and species were conducted, showing variations across branch orders and species. This study suggests that examining the estimated distribution of the branch structure parameter offers a more detailed description of branch structure, capturing the central tendencies of branch structure parameters. We also emphasize the importance of examining higher branch orders to gain a comprehensive understanding of branch structure, highlighting the differences across branch orders.
This research aims at identifying the goshawk's possible and replaceable breeding ground by using the MaxEnt prediction model which has so far been insufficiently used in Korea, and providing evidence to expand possible protection areas for the goshawk's breeding for the future. The field research identified 10 goshawk's nests, and 23 appearance points confirmed during the 3rd round of environmental research were used for analysis. 4 geomorphic, 3 environmental, 7 distance, and 9 weather factors were used as model variables. The final environmental variables were selected through non-parametric verification between appearance and non-appearance coordinates identified by random sampling. The final predictive model (MaxEnt) was structured using 10 factors related to breeding ground and 7 factors related to appearance area selected by statistics verification. According to the results of the study, the factor that affected breeding point structure model the most was temperature seasonality, followed by distance from mixforest, density-class on the forest map and relief energy. The factor that affected appearance point structure model the most was temperature seasonality, followed by distance from rivers and ponds, distance from agricultural land and gradient. The nature of the goshawk's breeding environment and habit to breed inside forests were reflected in this modeling that targets breeding points. The northern central area which is about $189.5 km^2$(2.55 %) is expected to be suitable breeding ground. Large cities such as Cheongju and Chungju are located in the southern part of Chungcheongbuk-do whereas the northern part of Chungcheongbuk-do has evenly distributed forests and farmlands, which helps goshawks have a scope of influence and food source to breed. Appearance point modeling predicted an area of $3,071 km^2$(41.38 %) showing a wider ranging habitat than that of the breeding point modeling due to some limitations such as limited moving observation and non-consideration of seasonal changes. When targeting the breeding points, a specific predictive area can be deduced but it is difficult to check the points of nests and it is impossible to reflect the goshawk's behavioral area. On the other hand, when targeting appearance points, a wider ranging area can be covered but it is less accurate compared to predictive breeding point since simple movements and constant use status are not reflected. However, with these results, the goshawk's habitat can be predicted with reasonable accuracy. In particular, it is necessary to apply precise predictive breeding area data based on habitat modeling results when enforcing an environmental evaluation or establishing a development plan.
Journal of the Korean Institute of Landscape Architecture
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v.43
no.2
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pp.13-22
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2015
The study discovers mood state and enhancement effect of users by scenery of location targeting Seonyudo Park; where is widely recognized as the representative recycling environmental park as well as theme experience space and scenery admiration in Korea. Also, the influence level of park and thematic space upon wellness was researched for future park design and its base data. As a result of semantic differential(SD), the most items showed low point in positive way when people admiring the scenery in Seonyudo. Also, a subject experienced differently depending on each inside scenery element of the park. As a result of profile of mood states(POMS), a tension and anxiety points were shown in order of Urban (7.78) > Water Purification Basin(3.33) > Gardens of Water Plants(2.11) > Garden of Green Pillar(2.00) > Garden of Time (0.89). The depression points were shown in order of Urban(4.94) > Water Purification Basin(3.50) > Garden of Green Pillar(2.94) > Garden of Time(1.61) > Gardens of Water Plants(1.38). The anger and hostility points were shown in order of Urban(4.22) > Water Purification Basin(3.33) > Garden of Green Pillar(2.22) > Garden of Time(1.39) > Gardens of Water Plants(1.11). The fatigue points were shown in order of Urban(6.5) > Water Purification Basin(3.39) > Garden of Green Pillar(2.78) > Garden of Time(2.28) > Gardens of Water Plants (2.06). The vigor points were shown in order of Gardens of Water Plants(11.39) > Garden of Time(11.00) > Garden of Green Pillar(8.39) > Water Purification Basin(7.77) > Urban(5.28). Also, as a result of statistics analysis, difference value of scenery type is significant. The result of total emotional disturbance(TED) was analyzed in order of Urban(24.5) > Water Purification Basin(9.5) > Garden of Green Pillar(4.67) > Garden of Time(-1.39) > Gardens of Water Plants(-1.22).
Chang-Hoi Ho;Byung-Gon Kim;Baek-Min Kim;Doo-Sun R. Park;Chang-Kyun Park;Seok-Woo Son;Jee-Hoon Jeong;Dong-Hyun Cha
Atmosphere
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v.33
no.2
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pp.223-246
/
2023
This paper summarized the research papers on weather extremes that occurred in the Republic of Korea, which were published in the domestic and foreign journals during 1963~2022. Weather extreme is defined as a weather phenomenon that causes serious casualty and property loss; here, it includes typhoon, heavy rain, drought, heat wave, cold surge, heavy snow, and strong gust. Based on the 2011~2020 statistics in Korea, above 80% of property loss due to all natural disasters were caused by typhoons and heavy rainfalls. However, the impact of the other weather extremes can be underestimated rather than we have actually experienced; the property loss caused by the other extremes is hard to be quantitatively counted. Particularly, as global warming becomes serious, the influence of drought and heat wave has been increasing. The damages caused by cold surges, heavy snow, and strong gust occurred over relatively local areas on short-term time scales compared to other weather hazards. In particularly, strong gust accompanied with drought may result in severe forest fires over mountainous regions. We hope that the present review paper may remind us of the importance of weather extremes that directly affect our lives.
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