• Korean Journal of Environmental Biology
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• v.25 no.2
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• pp.168-177
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• 2007

By using DEM and digital actual vegetation map with MGE GIS software program, topographic features (altitude, slope, latitude, etc.) quantitatively were analysed and their data integrated as the index of climatic conditions (WI, CI, air temperature, etc.) in South Korea. Warmth Index (WI) decreases $5.27^{\circ}C{\cdot}month$ with latitudinal $1^{\circ} degree, and $3.41^{\circ}C{\cdot}month$ with attitudinal 100 m increase. The relationship between CI and WI values is expressed as a linear regression, $WI=116.01+0.96{\times}CI,\;R^2=0.996$. The distributional peaks of different plant communities along Warmth Index gradient showed the sequence of Abies nephrolepis, Taxus cuspidata, Abies koreana, Quercus mongolica, Carpinus laxiflora, Q. dentata, C. tschonoskii, Q. serrate, Pinus densiflora, Q. aliena, Q. variabilis, Q. acutissima, P. thunbergii, Q. acute, Castanopsis cuspidata var. sieboldii, Camellia japonica, Machilus thunbergii community from lower to higher values. The Quercus mongolica forest occurred frequently on E-NW and SE slope aspect within WI $70{\sim}80^{\circ}C{\cdot}month$ optimal range at mesic sites, NW and SE slope than xeric sites S and SW slope. The Q. serrata forest showed the most distributional frequency in NW and W slope aspect within WI $90{\sim}100^{\circ}C{\cdot}month$ range, Q. variabilis and Q. acutissima forest showed the high frequency of distribution in SE slope in WI $95{\sim}100^{\circ}C{\cdot}month$ range. By the slope gradient analysis, five groups were found: 1. Abies nephrolepis, Machilus thunbergii, 2. Taxus cuspidata, Abies koreana, Quercus mongolica, Q. dentata, Q. serrata, Q. variabilis, Castanopsis cuspidata var. sieboldii 3. Pinus densiflora, Q. aliena, Q. acutissima, P. thunbergii, Q. acuta 4. Carpinus laxiflora, Camellia japonica 5. C. tschonoskii from steep slope to gentle slope sequence.

• Analytical Science and Technology
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• v.25 no.2
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• pp.121-126
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• 2012

It is essential to evaluate the quality of Hanji record paper without damaging the record paper by previous destructive methods. The samples were Hanji record paper produced in the 1900s. Near-infrared (NIR) spectrometer was used as a non destructive method for evaluating the quality of record papers. Fourier transform (FT) spectrometer was used with 12,500 to 4,000 $cm^{-1}$ wavenumber range for quantitative analysis and it has high accuracy and good signal-to-noise ratio. The acidity and moisture content of Hanji record paper were measured by integrating sphere as diffuse reflectance type. The acidity (pH) of chemical factors as a quality evaluated factor of Hanji was correlated to NIR spectrum. The NIR spectrum was pretreated to obtain the coefficients of optimum correlation. Multiplicative scatter correction (MSC) and First derivative of Savitzky-Golay were used as pretreated methods. The coefficients of optimum correlation were calculated by PLSR (partial least square regression). The correlation coefficients ($R^2$) of acidity had 0.92 on NIR spectra without pretreatment. Also the standard error of prediction (SEP) of pH was 0.24. And then the NIR spectra with pretreatment would have better correlation coefficient ($R^2$ = 0.98) and 0.19 as SEP on pH. For moisture contents, the linearity correlation without pretreatment was higher than the case with pretreatment (MSC, $1^{st}$ derivative). As the best result, the $R^2$ was 0.99 and SEP was 0.45. This indicates that it is highly proper to evaluate the quality of Hanji record papers speedily with integrated sphere and FT NIR analyzer as a non-destructive method.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.4
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• pp.61-75
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• 2018

This study aims to verify the effect of green buffers, built as urban planning facilities on the reduction of ultra-fine particulate($PM_{2.5}$) and analyze changes in ultra-fine particles by structure, green volume and planting types of wayside green buffers, thus drawing the factors that can be used when green buffers are built to reduce ultra-fine particulate based on the results. This study selected Songpa-gu, and investigated 16 sites on 5 green buffers adjacent to two of Songpa-gu's main roads, 'Yangjaedaero' and 'Songpadaero'. This study divided all the green spaces into three different types-slope type, plain type and mounding type, and analyzed the mean green volume. As a result of measuring the concentration of $PM_{2.5}$, this study found that it was $55.5{\mu}g/m^3$ on average in winter, which was a harmful level according to the integrated environmental index provided by Seoul City, saying that levels above $50{\mu}g/m^3$ may have a harmful effect on sensitive groups of people. Particularly, the concentration of $PM_{2.5}$ was $38.6{\mu}g/m^3$ on average in spring, which exceeded the mean concentration of $PM_{2.5}$ in Seoul City in 2015. The mean concentrations of $PM_{2.5}$ in every investigation spot were $46.6{\mu}g/m^3$ for sidewalks, $45.5{\mu}g/m^3$ for green spaces and $42.9{\mu}g/m^3$ for residential areas, all of which were lower than $53.2{\mu}g/m^3$ for roads, regardless of the season. The concentration of $PM_{2.5}$ for residential areas was the lowest. In the stage of confirming the effect of green buffers, this study analyzed the correlation between the green volume of vegetation and the fluctuated rate of ultra-fine particles. As a result, it was found that the green coverage rate of trees and shrubs was related to the crown volume in every investigation spot but were mutually and complexly affected by each other. Therefore, this study judged that the greater the number of layers of shrubs that are made, the more effective it is in reducing the concentration of $PM_{2.5}$. As for seasonal characteristics, this study analyzed the correlation between the concentration of $PM_{2.5}$ for residential areas in winter and the green coverage rate of each green space type. As a result, this study found that there was a negative correlation showing that the higher the shrub green coverage rate is, the lower the concentration value becomes in all the slope-type, plain-type and mounding-type green spaces. This study confirmed that the number of tree rows and the number of shrub layers have negative correlations with the fluctuated concentration rate of $PM_{2.5}$. Especially, it was judged that the shrub green volume has greater effect than any other factor, and each green space type shows a negative correlation with the shrub coverage rate in winter.

• Korean Security Journal
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• no.43
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• pp.67-97
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• 2015

In Korea, a single emergency number, such as 911 of the USA and 999 of the UK, does not exist. This issue became highly controversial, when the Sewol Ferry Sinking disaster occurred last year. So, the Korean government has planned to adopt a single emergency number, integrating 112 of the Police, 119 of the Fire and Ambulance, 122 of the Korean Coast Guard, and many other emergency numbers. However, the integration plan recently proposed by the Ministry of Public Safety Security seems to be, what is called, a "partial integration model" which repeals the 122 number, but still maintains 112, 119, and 110 respectively. In this context, the study looks into USA's (diverse) 911 operating system, and subsequently tries to draw general features or characteristics. Further, the research attempts to derive policy implication from the general features. If the proposed partial integration model reflects the policy implications, the model can virtually operate like the 911 system -i.e. a single emergency number system - creating inter-operability between responding agencies such as police, fire, and ambulance, even though it is not a perfect integration model. The features drawn are (1) integration of emergency call-taking, (2) functional separation of call-taking and dispatching, (3) integration of physical facilities for call-taking and dispatching, and (4) professional call-takers and dispatchers. Moreover, the policy implications derived from the characteristics are (1) a user-friendly system - fast but accurate responses, (2) integrated responses to accidents, (3) professional call-taking and dispatching & objective and comprehensive risk assessment, and finally (4) active organizational learning in emergency call centers. Considering the policy implications, the following suggestions need to be applied to the current proposed plan: 1. Emergency services' systems should be tightly linked and connected in a systemic way so that they can communicate and exchange intelligence with one another. 2. Public safety answering points (call centers) of each emergency service should share their education and training modules, manuals, etc. Common training and manuals are also needed for inter-operability. 3. Personal management to enable-long term service in public safety answering points (call centers) should be established as one of the ways to promote professionalism.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.31 no.1
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• pp.45-55
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• 1998

Phytoplankton community and primary productivity have been investigated in a fall season in the southern coastal waters of the last Sea, Korea. A strong thermocline formed at the 20\~60\;m$ layer and a cold water mass also existed in the bottom around Yong-il Bay. The offshore of the surveyed area was likely to be influenced by relatively warmer water, whereas the inshore represented Higher primary productivity with lower water temperature and lower salinity. A total of 133 species of phytoplankton occurred, representing 107 spp. of diatom, 23 spp. of dinoflagellate 3 spp. of silicoflagellate. Skeletonema costatum and Asterionellepsis glacialis were most predominant with more than $30\%$ dominance ratio, while Leptocylindrus danicus was also dominant at all transect lines. Standing crops of phytoplankton ranged from $2.7{\times}10^3\;to\;141.6{\times}10^3\;cell^{\ell-1}$. Chlorophyll a concentration varied with stations and layers, but the $30\~50$ m layer showed maximun with about $1.18{\mu}g{\ell}^{-1}$ rather than at the surface layer. It is believed that the maximun in standing crops and chlorophyll of phytoplankton formed at the $20\~50$ m layer above the thermocline during the survey. Phytoplankton primary productivity ranged from 0.32 to 3.04 mgC $m^{-3}\;hr^{-1}$, showing higher at the inshore than at the offshore. The range of integrated primary productivity was $263.3\~1085.5 mgC\;m^{-2}\;day^{-1}$ for the euphotic layer. Photosysthesis rates varied with the range from 0.76 to 8.04 mgC mgChl $\alpha^{-1}\;hr^{-1}$. Phytoplankton photosynthesis at the inshore was saturated at lower irradiance ($15\~35\%$ of surface) and showed higher efficiency, Thus, it revealed that the phytoplankton community probably adapted to the middle of euphotic layer because the depth of mixing layer became thinner due to the formation of thermocline.

• Korean Public Health Research
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• v.44 no.4
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• pp.87-97
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• 2018

Background: Recently, the prevalence of obesity (body mass index [BMI] ${\geq}25kg/m^2$) has been increasing rapidly worldwide over a short period. In Korea, the prevalence of obesity has also increased rapidly due to the rapid socio-economic development and lifestyle changes, with differing patterns according to gender. This study aimed to compare the change in obesity prevalence according to gender among the adult population in Korea using representative data, the National Health Check-up Database (NHCD), to follow-up individuals who had undergone checkups during both years in Korea (2011~2013). Methods: To analyze the changes in obesity prevalence in the recent two years, data regarding men and women who had undergone health check-ups in both two years (2011, 2013) were extracted. The final study population comprised 144,934 persons: 83,604 (58%) males and 61,330 (42%) females. Chi-square test within a univariate analysis, and the level of factor difference was verified with t-test, one-way ANOVA and multiple comparison. Results: In 2011, one out of three participants was obese (BMI ${\geq}25kg/m^2$; male, 37.7%; female, 27.3%) and more than half of the subjects were overweight (BMI ${\geq}23kg/m^2$; male, 65.6%; female, 50.4%) requiring obesity management. For the two years, the BMI of the participants significantly increased (p < .0001) and the prevalence of obesity increased among both males and females. The prevalence of obesity was higher among both genders with a longer duration of smoking, more smoking, family history of hypertension, and family history of diabetes. However, residence, income level, drinking status, psychiatric disorder, disability status and severity of disability were the opposite gender. Conclusion: In the analysis of data, the prevalence of obesity among both men and women was increasing. The degree of change in the prevalence of obesity among men and women was different in each variable. Thus, it will need to consider gender in developing health policies for obesity mediation and to provide integrated healthcare and management for those people.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.

• Journal of Bio-Environment Control
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• v.31 no.1
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• pp.67-76
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• 2022

This study aimed to determine the photosynthesis and growth characteristics of Peucedanum japonicum T. grown under aquaponics in a plant factory (AP) by comparing those grown under hydroponic cultivation system (HP). The AP system raised 30 fishes at a density of 10.6 kg·m^-3 in a 367.5 L tank, and at HP, nutrient solution was controlled with EC 1.3 dS·m^-1 and pH 6.5. The pH level ranged from 4.0 to 7.1 for the AP system and 4.0 to 7.4 for the HP system. The pH level in the AP began to decrease with an increase in nitrate nitrogen (NO₃-N) and lasted bellower than pH 5.5 for 15-67 DAT. It was found that ammonium nitrogen (NH₄-N) continued to increase even under low pH conditions. EC was maintained at 1.3 to 1.5 dS·m^-1 in both systems. The concentration of major mineral elements in the fish tank was higher than that of the hydroponics, except for K and Mg. There was no significant difference in the photosynthesis characteristics, but the PIABS parameters were 30.4% lower in the AP compared to the HP at the 34DAT and 12.0% lower at the 74DAT. There was no significant difference in the growth characteristics, but the petiole length was 56% longer in the leaf grown under the AP system. While there was no significant difference in the fresh and dry weights of leaf and root, the leaf area ratio was 36.43% higher in the AP system. All the integrated results suggest that aquaponics is a highly-sustainable farming to safely produce food by recycling agricultural by-products, and to produce Peucedanum japonicum as much as hydroponics under a proper fish density and pH level.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.2
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• pp.87-102
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• 2022

To clarify the spatial distribution pattern of macrozoobenthos in Korean coastal waters in the summer season and investigate the relationship between community structure and benthic environmental factors, field surveys on community structure and benthic environmental factors were conducted at 117 stations in August 2017. A total of 613 macrobenthic species were identified, with the mean density of 1,228 ind./m² and the mean biomass (wet weight) of 110.9 g WW/m². Rich biodiversity was found at stations near Wando and along the coast of the East Sea, and there is a trend that stations with greater biodiversity also showed higher mean density as well. The dominant species in all the coastal areas in Korea was Heteromastus filiformis, which were found at most of the stations during the survey. The relatively deep areas in the East Sea were dominated by Magelona johnsoni and Maldane cristata, which were the third and ninth dominant species in the study areas, respectively. Pseudopolydora kempi and Rhynchospio sp. were observed only at the station located in the Nakdong River estuary. From the cluster analysis the stations could be clustered into three station groups with more similar faunal composition. Group A was located in the eastern coast, characterized with deep water depth and low levels of sand contents, while Group B was located in the southern coast, characterized by shallow depth of water and high content of mud and organic matter. Lastly, Group C was in the western coast, demonstrating low levels of mud content and organic matters. The biodiversity of macrobenthic species in the study area showed high positive correlation coefficients with benthic environmental factors such as sorting, clay, silt, and contents of organic matter in sediments, but negatively correlated with the sand contents. Major dominant species, Theora lata and Eriopisella sechellensis, both showed negative correlation coefficients with the sand contents, but a relatively high positive correlation with the levels of organic contents.It can be concluded that the spatial distribution patterns of macrobenthic organisms in Korean coastal waters are affected by depth, sediment type, and contents of organic matters.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.191-203
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• 2022

In this paper, we developed a system that intelligently identifies skin image data from big data collected from social media Instagram and extracts standardized skin sample data for skin condition diagnosis and management. The system proposed in this paper consists of big data collection and analysis stage, skin image analysis stage, training data preparation stage, artificial neural network training stage, and skin image identification stage. In the big data collection and analysis stage, big data is collected from Instagram and image information for skin condition diagnosis and management is stored as an analysis result. In the skin image analysis stage, the evaluation and analysis results of the skin image are obtained using a traditional image processing technique. In the training data preparation stage, the training data were prepared by extracting the skin sample data from the skin image analysis result. And in the artificial neural network training stage, an artificial neural network AnnSampleSkin that intelligently predicts the skin image type using this training data was built up, and the model was completed through training. In the skin image identification step, skin samples are extracted from images collected from social media, and the image type prediction results of the trained artificial neural network AnnSampleSkin are integrated to intelligently identify the final skin image type. The skin image identification method proposed in this paper shows explain high skin image identification accuracy of about 92% or more, and can provide standardized skin sample image big data. The extracted skin sample set is expected to be used as standardized skin image data that is very efficient and useful for diagnosing and managing skin conditions.