• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.199-207
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• 2016

This study was conducted to develop a forest fire occurrence model using meteorological characteristics for practical forecasting of forest fire danger rate by reflecting the climate change for the time period of 2000yrs. Forest fire in South Korea is highly influenced by humidity, wind speed, temperature, and precipitation. To effectively forecast forest fire occurrence, we developed a forest fire danger rating model using weather factors associated with forest fire in 2000yrs. Forest fire occurrence patterns were investigated statistically to develop a forest fire danger rating index using times series weather data sets collected from 76 meteorological observation centers. The data sets were used for 11 years from 2000 to 2010. Development of the national forest fire occurrence probability model used a logistic regression analysis with forest fire occurrence data and meteorological variables. Nine probability models for individual nine provinces including Jeju Island have been developed. The results of the statistical analysis show that the logistic models (p<0.05) strongly depends on the effective and relative humidity, temperature, wind speed, and rainfall. The results of verification showed that the probability of randomly selected fires ranges from 0.687 to 0.981, which represent a relatively high accuracy of the developed model. These findings may be beneficial to the policy makers in South Korea for the prevention of forest fires.

• Journal of Preventive Medicine and Public Health
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• v.29 no.4 s.55
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• pp.801-814
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• 1996

Background: Korean people could abuse healthy foods as well as medications, which might cause serious side effects. The aim of this study was elucidating liver dysfunction due to the self-medications of hepatotonics, healthy foods and herb medications by nested case-control study. Methods: Study subjects were drawn from male members of Seoul Cohort Study who were recruited by self-administered structured questionnaire survey through mailing to the healthy men between the age of 40 and 59 years through the program of biennial health check-up offered by Korea Medical Insurance Corporation(KMIC). The liver dysfunction was defined as the level of serum AST and ALT above 40 IU/L and increased in more than one hunderd per-cent during the 2 year follow-up period. To estimate the odds ratio between self-medication and liver dysfunction after controlling for potential confounders, logistic regression was performed. Results: During the follow-up period, 30 members were identified to fit into case criteria and 2,625 members were selected as control. In logistic regression analyses, history of healthy foods intake, age under 45 years, obesity, and habit of regular exercise were significantly associated with liver dysfunction. The following factors exhibited no statistical significance: intake of hepatotonics, of herb medicine; history of disease in family, of operation, and of radiologic examination; smoking habits and drinking amounts. Conclusion: The significant association between the intake of healthy foods and the liver dysfunction illustrates that chronically optional overuse of healthy foods might bring to hazards to health. As the increasing trend of the size of purchasing healthy foods in Korea, pharmacoepidemiologic studies evaluating the safety and efficacy of the widely used healthy foods should be performed in the near future.

• Journal of dental hygiene science
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• v.16 no.2
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• pp.142-149
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• 2016

The number of male dental hygienists has been continuously increasing in dental services. The purpose of this study aimed to identify the relationship between job stress, job satisfaction, and turnover intention in male dental hygienists and to provide basic data to improve their job satisfaction. The study population was 110 Korean male dental hygienists working for dental clinics or hospitals. The data were collected from November 10 to December 7, 2015. After an explanation about the objective of the study, 110 questionnaires were distributed via email, and 97 responses were analyzed using SPSS. Overall averages of job stress, job satisfaction and turnover intention in male dental hygienists were 3.05, 2.92, and 3.47 out of 5, respectively. Some sub-factors of job stress, including interpersonal relationships at the workplace and future prospects of dental clinics, were proven to have statistically significant negative influence on job satisfaction (p<0.001). Regression analysis was performed with job stress and job satisfaction as independent variables and turnover intention as a dependent variable. Results showed that job stress had a positive effect on turnover intention (p<0.01) while job satisfaction had a negative effect on turnover intention (p<0.001). Job satisfaction was revealed to have statistically significant negative influence on turnover intention (p<0.001). Some of sub-factors of job stress, including work environment and future prospects of dental clinics and professional position, had a positive effect on turnover intention (p<0.05). The study showed that higher job stress led to higher turnover intention, and higher job satisfaction led to lower turnover intention. Accordingly, job stress and job satisfaction are critical factors for turnover intention in male dental hygienists.

• Journal of agriculture & life science
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• v.46 no.6
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• pp.51-57
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• 2012

This study was carried out to analyze chemical compositions of the fog water of a forest area, Jinju and to provide basic information for establishing measures on the acid fog water of forest area. The results are as follows: The pH of fog water was 4.3 in 2010, whereas the pH in 2011 was 4.0. The electrical conductivity of the fog water was $477.2{\mu}s$ in 2010, and $562.7{\mu}s$ in 2011. Among the anions, the concentration of $NO^{3-}$ was the highest, which recorded 267.1 mg/L in spring season and 279.1 mg/L in summer season, followed by $SO{_4}^{2-}$ at the concentration of 177.2 mg/L in spring season and 198.6mg/L in summer season. In autumn and winter, the concentration of $NO^{3-}$ was highest as 217.7 mg/L and 237.9 mg/L, respectively and followed by $SO{_4}^{2-}$, which concentration was 164.2 mg/L in autumn season and 190.1 mg/L in winter season (p<0.05). Among the cations, the concentration of $Ca^{2+}$ was 221.3 mg/L in spring and 233.7mg/L in summer, followed by $Na^+$ at 125.1 mg/L in spring season and 131.7 mg/L in summer In autumn and winter, the concentration of $Ca^{2+}$ was highest at 196.8 mg/L and 198.8 mg/L, followed by $Na^+$ at the concentration of 97.1 mg/L in autumn and 117.2 mg/L in winter (p<0.05). The pH of the fog rain that causes acid mist showed the correlation with $Ca^{++}$ (1% of level), $EC(r=-0.9861^{**})$, $NO^{3-}$ ($r=-0.9677^{**}$), and $SO{_4}^{2-}$ ($r=-0.9510^{**}$). The regression equation on the factors affecting the generation of acidic fog rain was estimated to be a $Y(pH)=6.4627+0.9723X_2(EC)+0.9364X_4(NO_3{^-})+0.9044X_5(SO{_4}^{2-})+0.8049X_{10}(Ca^{2+})+0.6709X_8(K^+)\;(r^2=0.8787)$.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.31 no.4 s.54
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• pp.337-342
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• 2005

The aim of this study was to evaluate the influence of different skin care ingredient concentrations on the effect of polyols and oils on the human skin moisturization and skin surface roughness. Polyols and oils were essential ingredients to make a skin care formulation. But these were still not understood how much concentration(s) were tested on human skin in the aspect of efficacy and sensory. We studied to examine various concentrations of ingredient by cosmetic companies using noninvasive methods. Polyols were composed of glycerol and butylene glycol (BG) as 1:1 ratio, and oils were hydrogenated polydecene, cetyl ethylhexanoate and pentaerythrityl tetraethylhexanoate (PTO(R), Stearinerie Dubois Fils Co., France) as 1:1:1 ratio. All compounds were tested $0{\sim}27%dml$ Polyols and $0{\sim}35%dml$ oils in O/W emulsions. We investigated the effect of water contents and the effect of stratum corneum roughness in forearm skin after application of compounds. Water contents of the skin measured by skin capacitance and skin surface roughness measured visual scoring of skin surface biopsy through the scanning electron microscopy. Water contents of the skin were highly related to amount of polyols (to 20%) and oils (to 12%). Correlation coefficients were 0.971 and 0.985 respectively (p<0.01), 2 h after application. Skin surface roughness was positively correlated with polyol contents in concentration dependent manner, and depend on oils up to 6%. The ratio of coefficient was 2.5 to 1 (polyol to oils) by regression analysis. Further studies will be conducted with other ingredients such as surfactants, lipids and aqueous materials, and with ether methods for noninvasive measurement.

• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.589-600
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• 2020

Effective conservation and management of protected areas require monitoring the settlement of invasive alien species and reducing their dispersion capacity. We simulated the potential distribution of invasive alien plant species (IAPS) using three representative species distribution models (Bioclim, GLM, and MaxEnt) based on the IAPS distribution in the forest genetic resource reserve (2,274ha) in Uljin-gun, Korea. We then selected the realistic and suitable species distribution model that reflects the local region and ecological management characteristics based on the simulation results. The simulation predicted the tendency of the IAPS distributed along the linear landscape elements, such as roads, and including some forest harvested area. The statistical comparison of the prediction and accuracy of each model tested in this study showed that the GLM and MaxEnt models generally had high performance and accuracy compared to the Bioclim model. The Bioclim model calculated the largest potential distribution area, followed by GLM and MaxEnt in that order. The Phenomenological review of the simulation results showed that the sample size more significantly affected the GLM and Bioclim models, while the MaxEnt model was the most consistent regardless of the sample size. The optimal model overall for predicting the distribution of IAPS among the three models was the MaxEnt model. The model selection approach based on detailed flora distribution data presented in this study is expected to be useful for efficiently managing the conservation areas and identifying the realistic and precise species distribution model reflecting local characteristics.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.127-146
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• 2022

Recently, as word embedding has shown excellent performance in various tasks of deep learning-based natural language processing, researches on the advancement and application of word, sentence, and document embedding are being actively conducted. Among them, cross-language transfer, which enables semantic exchange between different languages, is growing simultaneously with the development of embedding models. Academia's interests in vector alignment are growing with the expectation that it can be applied to various embedding-based analysis. In particular, vector alignment is expected to be applied to mapping between specialized domains and generalized domains. In other words, it is expected that it will be possible to map the vocabulary of specialized fields such as R&D, medicine, and law into the space of the pre-trained language model learned with huge volume of general-purpose documents, or provide a clue for mapping vocabulary between mutually different specialized fields. However, since linear-based vector alignment which has been mainly studied in academia basically assumes statistical linearity, it tends to simplify the vector space. This essentially assumes that different types of vector spaces are geometrically similar, which yields a limitation that it causes inevitable distortion in the alignment process. To overcome this limitation, we propose a deep learning-based vector alignment methodology that effectively learns the nonlinearity of data. The proposed methodology consists of sequential learning of a skip-connected autoencoder and a regression model to align the specialized word embedding expressed in each space to the general embedding space. Finally, through the inference of the two trained models, the specialized vocabulary can be aligned in the general space. To verify the performance of the proposed methodology, an experiment was performed on a total of 77,578 documents in the field of 'health care' among national R&D tasks performed from 2011 to 2020. As a result, it was confirmed that the proposed methodology showed superior performance in terms of cosine similarity compared to the existing linear vector alignment.

• Journal of Korean Society of Forest Science
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• v.111 no.3
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• pp.365-373
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• 2022

We compared carbon stocks in tree biomass and soils of Quercus acutissima, Q. mongolica, Q. serrata, and Q. variabilis stands. A total of 531 plots (Q. acutissima: 110 plots, Q. mongolica: 177 plots, Q. serrata: 96 plots, Q. variabilis: 148 plots) were examined between 2016 and 2021 to determine the tree biomass and soil carbon stocks throughout the country. The carbon stocks of tree biomass were significantly higher in Q. mongolica (mean stand age, 57 years, 144.9 Mg C ha^-1) than in Q. variabilis (mean stand age, 43 years, 123.7 Mg C ha^-1), Q. serrata (mean stand age, 43 years, 120.1 Mg C ha^-1), and Q. acutissima (mean stand age, 36 years, 113.2 Mg C ha^-1) stands. The soil carbon concentration was significantly higher in Q. mongolica (A: 43.1 mg C g-1) than in Q. serrata (31.0 mg C g-1), Q. variabilis (25.31 mg C g-1), and Q. acutissima (24.4 mg C g-1) stands. The soil carbon stocks were significantly higher in Q. mongolica (116.8 Mg C ha^-1) than in Q. acutissima (49.3 Mg C ha^-1) stands. Total carbon stocks of tree biomass and soil were highest in Q. mongolica (262 Mg C ha^-1), followed by Q. serrata (218 Mg C ha^-1), Q. variabilis (211 Mg C ha^-1), and Q. acutissima (163 Mg C ha^-1) stands. Multiple linear regressions were performed to estimate the total carbon stocks of the four Quercus spp., and results showed that total carbon stocks increased with increasing elevation, mean diameter at breast height, and basal areas. Basal area and elevation of Quercus spp. stands were important explanatory variables based on multiple linear regressions for estimating carbon stocks.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.133-149
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• 2022

Existing domestic studies on estimating rice yield were mainly implemented at the level of cities and counties in the entire nation using MODIS satellite images with low spatial resolution. Unlike previous studies, this study tried to estimate rice yield at the level of eup-myon-dong in Gimje-si, Jeollabuk-do using Sentinel-2 satellite images with medium spatial resolution, rainfall and soil data, and then to evaluate its accuracy. Five vegetation indices such as NDVI, LAI, EVI2, MCARI1 and MCARI2 derived from Sentinel-2 images of August 1, 2018 for Gimje-si, Jeollabuk-do, rainfall and paddy soil-type data were aggregated by the level of eup-myon-dong and then rice yield was estimated with gamma generalized linear model, an expanded variant of multi-variate regression analysis to solve the non-normality problem of dependent variable. In the rice yield model finally developed, EVI2, rainfall days in September, and saline soils ratio were used as significant independent variables. The coefficient of determination representing the model fit was 0.68 and the RMSE for showing the model accuracy was 62.29kg/10a. This model estimated the total rice production in Gimje-si in 2018 to be 96,914.6M/T, which was very close to 94,470.3M/T the actual amount specified in the Statistical Yearbook with an error of 0.46%. Also, the rice production per unit area of Gimje-si was amounted to 552kg/10a, which was almost consistent with 550kg/10a of the statistical data. This result is similar to that of the previous studies and it demonstrated that the rice yield can be estimated using Sentinel-2 satellite images at the level of cities and counties or smaller districts in Korea.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.