• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.38 no.3
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• pp.1-10
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• 2020

The purpose of this study is to identify whether the cranes had been bred in the palace of the Joseon Dynasty period and to consider the related cases. The temporal range of this study is in the Joseon Dynasty period, and the spatial range is throughout the entire palace, including the naejeon(內殿) and oijeon(外殿), and government offices inside(闕內各司) and government offices outside(闕外各司). The reference materials for this study were partly extracted and translated from the original documents to consider, and a Korean version of documents was used in the database of the Institute for the Translation of Korean Classics. The results of this study are summarized as follows. First, the cranes were bred from the early Joseon Dynasty Era in Uijeongbu, the highest government office in the Joseon Dynasty period. After the Japanese Invasion of Korea in 1592, crane breeding in Uijeongbu(議政府) seems to have been suspended due to the damage to the government building and the change in the status of the government office. Second, crane breeding in Hongmungwan(弘文館), which was responsible for the classics colloquium(經筵) and public opinions and assisted the king by the side, continued from the early Joseon Dynasty period(Jungjong's Era) to the late Joseon Dynasty period(Jeongjo's Era) after the Japanese Invasion of Korea in 1592. Third, in the Jeongjo's Era, the cranes were also bred in Gyujanggak(奎章閣), which was newly established as the central institution of learning to strengthen the royal authority. At that time, it seems that several cranes were bred in Gyujanggak. Fourth, it is judged that 'Crane breeding' in the core government offices of Joseon, such as Uijeongbu, Hongmungwan, and Gyujanggak, was meaningful as a symbol of identities, such as the status and character of the institution. Fifth, it seems that the cranes bred in the palace, including Hongmungwan, were conventionally brought by the Baecheon County of Hwanghae-do. This convention caused minor conflicts between the central and local government offices during the Yeongjo's Era, but it seems to have continued throughout the Jeongjo's Era. In this study, there is a limit that most of the studies were conducted based on local data. If further data discovery and translation outcomes are accumulated in the future, more abundant cases will be identified. The deepened follow-up studies are also needed, other than the cases of rearing cranes in the local government offices and temples.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.561-568
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• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.29-39
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• 1999

An earlier study of the effect of rain found that the capacity of freeway systems was reduced, but did not address the effects of rain on the nature of traffic flows. Indeed, the substantial variation due to the intensity of adverse weather conditions is entirely rational so that its effects must be considered in freeway facility design. However, all of the data in Highway Capacity Manual(HCM) have come from ideal conditions. The primary objective of this study is to investigate the effect of rain on urban freeway traffic flows in Seoul. To do so, the relations between three key traffic variables(flow rates, speed, occupancy), their threshold values between congested and uncontested traffic flow regimes, and speed distribution were investigated. The traffic data from Olympic Expressway in Seoul were obtained from Imagine Detection System (Autoscope) with 30 seconds and 1 minute time periods. The slope of the regression line relating flow to occupancy in the uncongested regime decreases when it is raining. In essence, this result indicates that the average service flow rate (it may be interpreted as a capacity of freeway) is reduced as weather conditions deteriorate. The reduction is in the range between 10 and 20%, which agrees with the range proposed by 1994 US HCM. It is noteworthy that the service flow rates of inner lanes are relatively higher than those of other lanes. The average speed is also reduced in rainy day, but the flow-speed relationship and the threshold values of speed and occupancy (these are called critical speed and critical occupancy) are not very sensitive to the weather conditions.

• Korean Journal of Remote Sensing
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• v.20 no.2
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• pp.77-89
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• 2004

The spatial and temporal variations of aerosol optical depth (AOD) over Northeast Asia regions have special importance in the aerosol research for estimation of aerosol radiative forcing parameters and climate change. Aerosol optical and physical properties (AOD and ${\AA}$ngstrom parameter) have been investigated by using Moderate Resolution Imaging Spectroradiometer (MODIS) and Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) to estimate aerosol characteristics over the study region during 2001. Additionally, aerosol characteristics over the Korean peninsular during Aerosol Characteristic Experiment in Asia (ACE-Asia) Intensive Observation Period (IOP) have been investigated by using satellite observations. The results showed that the daily-observed aerosol data indicate seasonal variations with relatively higher aerosol loading in the spring and very low during the winter. The typical Asian dust case showed higher AOD (>0.7) with lower Angstrom exponent (<0.5) and higher AI (>0.5) that is mainly due to the composition of coarse particles in the springtime. Mean AOD for 2001 at 4 different places showed 0.65$\pm$0.37 at Beijing, 0.31$\pm$0.19 at Gosan, 0.54$\pm$0.26 at Seoul, and 0.38$\pm$0.19 at Kwangju, respectively. An interesting result was found in the present study that polluted aerosol events with small size dominated-aerosol loading around the Korean peninsular are sometimes observed. The origin of these polluted aerosols was thought to East China. Aerosol distribution from satellite images and trajectory results shows the proof of aerosol transport. Therefore, aerosol monitoring using satellite data is very useful.

• Korean Journal of Environment and Ecology
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• v.33 no.5
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• pp.605-619
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• 2019

The objective of this study was to analyze eutrophication characteristics, empirical model analysis, and variation of water quality according to monsoon intensity in Hapcheon Reservoir for 16 years from 2002 to 2017. Long-term annual water quality analysis showed that Hapcheon Reservoir was in a meso-nutrition to eutrophic condition, and the eutrophic state intensified after the summer monsoon. Annual rainfall volume (high vs. low rainfall) and the seasonal intensity in each year were the key factors that regulate the long-term water quality variation provided that there is no significant change of the point- and non-point source in the watershed. Dry years and wet years showed significant differences in the concentrations of TP, TN, BOD, and conductivity, indicating that precipitation had the most direct influence on nutrients and organic matter dynamics. Nutrient indicators (TP, TN), organic pollution indicators (BOD, COD), total suspended solids, and chlorophyll-a (Chl-a), which was an estimator of primary productivity, had significant positive relations (p<0.05) with precipitation. The Chl-a concentration, which is an indicator of green algae, was highly correlated with TP, TN, and BOD, which differed from other lakes that showed the lower Chl-a concentration when nutrients increased excessively. Empirical model analysis of log-transformed TN, TP, and Chl-a indicated that the Chl-a concentration was linearly regulated by phosphorus concentration, but not by nitrogen concentration. Spatial regression analysis of the riverine, transition, and lacustrine zones of $log_{10}TN$, $log_{10}TP$, and $log_{10}CHL$ showed that TN and Chl-a had significant relations (p<0.005) while TN and Chl-a had p > 0.05, indicating that phosphorus had a key role in the algal growth. Moreover, the higher correlation of both $log_{10}TP$ and $log_{10}TN$ to $log_{10}CHL$ in the riverine zone than the lacustrine zone indicated that there was little impact of inorganic suspended solids on the light limitation in the riverine zone.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.968-974
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• 2010

We assessed the feasibility of discrete wavelet transform (DWT) applied for the spectral processing to enhance the estimation performance quality of soil organic matters using visible-near infrared spectra and mapped their distribution via block Kriging model. Continuum-removal and $1^{st}$ derivative transform as well as Haar and Daubechies DWT were used to enhance spectral variation in terms of soil organic matter contents and those spectra were put into the PLSR (Partial Least Squares Regression) model. Estimation results using raw reflectance and transformed spectra showed similar quality with $R^2$ > 0.6 and RPD> 1.5. These values mean the approximation prediction on soil organic matter contents. The poor performance of estimation using DWT spectra might be caused by coarser approximation of DWT which not enough to express spectral variation based on soil organic matter contents. The distribution maps of soil organic matter were drawn via a spatial information model, Kriging. Organic contents of soil samples made Gaussian distribution centered at around 20 g $kg^{-1}$ and the values in the map were distributed with similar patterns. The estimated organic matter contents had similar distribution to the measured values even though some parts of estimated value map showed slightly higher. If the estimation quality is improved more, estimation model and mapping using spectroscopy may be applied in global soil mapping, soil classification, and remote sensing data analysis as a rapid and cost-effective method.

• Journal of The Korean Association For Science Education
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• v.41 no.5
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• pp.371-390
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• 2021

The purpose of this study is to develop a neuropsychological model for the spatial ability factor and to divide the brain active area involved in the light & shadow problem solving process into the domain-general ability and the domain-specific ability based on the neuropsychological model. Twenty-four male college students participated in the study to measure the synchronized eye movement and electroencephalograms (EEG) while they performed the spatial ability test and the light & shadow tasks. Neuropsychological model for the spatial ability factor and light & shadow problem solving process was developed by integrating the measurements of the participants' eye movements, brain activity areas, and the interview findings regarding their thoughts and strategies. The results of this study are as follows; first, the spatial visualization and mental rotation factors mainly required activation of the parietal lobe, and the spatial orientation factor required activation of the frontal lobe. Second, in the light & shadow problem solving process, participants use both their spatial ability as a domain-general thought, and the application of scientific principles as a domain-specific thought. The brain activity patterns resulting from a participants' inferring the shadow by parallel light source and inferring the shadow when the direction of the light changed were similar to the neuropsychological model for the spatial visualization factor. The brain activity pattern from inferring an object from its shadow by light from multiple directions was similar to the neuropsychological model for the spatial orientation factor. The brain activity pattern from inferring a shadow with a point source of light was similar to the neuropsychological model for the spatial visualization factor. In addition, when solving the light & shadow tasks, the brain's middle temporal gyrus, precentral gyrus, inferior frontal gyrus, middle frontal gyrus were additionally activated, which are responsible for deductive reasoning, working memory, and planning for action.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1475-1490
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• 2021

Detecting oil spill area using statistical characteristics of SAR images has limitations in that classification algorithm is complicated and is greatly affected by outliers. To overcome these limitations, studies using neural networks to classify oil spills are recently investigated. However, the studies to evaluate whether the performance of model shows a consistent detection performance for various oil spill cases were insufficient. Therefore, in this study, two CNNs (Convolutional Neural Networks) with basic structures(Simple CNN and U-net) were used to discover whether there is a difference in detection performance according to the structure of CNN and distribution characteristics of oil spill. As a result, through the method proposed in this study, the Simple CNN with contracting path only detected oil spill with an F1 score of 86.24% and U-net, which has both contracting and expansive path showed an F1 score of 91.44%. Both models successfully detected oil spills, but detection performance of the U-net was higher than Simple CNN. Additionally, in order to compare the accuracy of models according to various oil spill cases, the cases were classified into four different categories according to the spatial distribution characteristics of the oil spill (presence of land near the oil spill area) and the clarity of border between oil and seawater. The Simple CNN had F1 score values of 85.71%, 87.43%, 86.50%, and 85.86% for each category, showing the maximum difference of 1.71%. In the case of U-net, the values for each category were 89.77%, 92.27%, 92.59%, and 92.66%, with the maximum difference of 2.90%. Such results indicate that neither model showed significant differences in detection performance by the characteristics of oil spill distribution. However, the difference in detection tendency was caused by the difference in the model structure and the oil spill distribution characteristics. In all four oil spill categories, the Simple CNN showed a tendency to overestimate the oil spill area and the U-net showed a tendency to underestimate it. These tendencies were emphasized when the border between oil and seawater was unclear.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.959-974
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• 2021

Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the possibility as a new water quality index which simultaneously contains optical information of water quality parameters has been suggested. In thisstudy, Ocean Colour-Climate Change Initiative (OC-CCI) based 4 km FUI was spatially downscaled to the resolution of 500 m using the Geostationary Ocean Color Imager (GOCI) data and Random Forest (RF) machine learning. Then, the RF-derived FUI was examined in terms of its correlation with various water quality parameters measured in coastal areas and its spatial distribution and seasonal characteristics. The results showed that the RF-derived FUI resulted in higher accuracy (Coefficient of Determination (R²)=0.81, Root Mean Square Error (RMSE)=0.7784) than GOCI-derived FUI estimated by Pitarch's OC-CCI FUI algorithm (R²=0.72, RMSE=0.9708). RF-derived FUI showed a high correlation with five water quality parameters including Total Nitrogen, Total Phosphorus, Chlorophyll-a, Total Suspended Solids, Transparency with the correlation coefficients of 0.87, 0.88, 0.97, 0.65, and -0.98, respectively. The temporal pattern of the RF-derived FUI well reflected the physical relationship with various water quality parameters with a strong seasonality. The research findingssuggested the potential of the high resolution FUI in coastal water quality management in the Korean Peninsula.

• Korean Journal of Environment and Ecology
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• v.35 no.5
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• pp.480-489
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• 2021

Climate change poses great threats to wildlife populations by decreasing their number and destroying their habitats, jeopardizing biodiversity conservation. Asiatic salamander (Hynobiidae) species are particularly vulnerable to climate change due to their small home range and limited dispersal ability. Thus, this study used one salamander species, the Korean clawed salamander (Onychodactylus koreanus), as a model species and examined their habitat characteristics and current distribution in South Korea to predict its spatial distribution under climate change. As a result, we found that altitude was the most important environmental factor for their spatial distribution and that they showed a dense distribution in high-altitude forest regions such as Gangwon and Gyeongsanbuk provinces. The spatial distribution range and habitat characteristics predicted in the species distribution models were sufficiently in accordance with previous studies on the species. By modeling their distribution changes under two different climate change scenarios, we predicted that the distribution range of the Korean clawed salamander population would decrease by 62.96% under the RCP4.5 scenario and by 98.52% under the RCP8.5 scenario, indicating a sharp reduction due to climate change. The model's AUC value was the highest in the present (0.837), followed by RCP4.5 (0.832) and RCP8.5 (0.807). Our study provides a basic reference for implementing conservation plans for amphibians under climate change. Additional research using various analysis techniques reflecting habitat characteristics and minute habitat factors for the whole life cycle of Korean-tailed salamanders help identify major environmental factors that affect species reduction.