• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.27 no.2
• /
• pp.55-65
• /
• 2024

This study aimed to figure out diel activity patterns of water deer and wild boar, whose habitat is disturbed by human activity in a suburban area. Photographic data of water deer and wild boar collected by 18 camera traps from January 2021 to November 2022 was categorized into four diel periods (dawn, day, dusk, and night), and converted into frequencies per 100 CTD (Camera Trap-Days) for seasonal and spatial diel activity pattern analysis. Water deer exhibited intense nocturnality in fall, and wild boar did in fall and winter. During the fall, water deer's night-time capture rate was the highest (61.9%), and day-time photographic rate was the lowest (13.9%) among other seasons. During the fall and winter, wild boar's night-time photographic rate was relatively high (77.6%, 78.0%, respectively), and day-time photographic rate was relatively low (0.7%, 1.8%) in comparison with other seasons. In spatial diel activity analysis, both water deer and wild boar showed a tendency to avoid humans, especially near trails during day-time hours. The day-time photographic rate of water deer in trail-near group was 12.1% and trail-far group was 24.6%. The day-time photographic rate of wild boar was 3.4%, 5.7%, respectively. Because the diel activity patterns of wildlife reflect human disturbance, this study provides useful ecological information for developing appropriate management plans for the coexistence of water deer and wild boar in suburban areas.

• Information Systems Review
• /
• v.21 no.3
• /
• pp.111-129
• /
• 2019

Recently, artificial intelligence (AI)-enabled products and services such as smartphones, smart speakers, chatbots are being released due to advances in AI technology. Thus researchers making effort to reveal that consumers' intention to adopt AI-enabled products. Yet, little is known about the intended adoption of AI-enabled products. Because most of studies has been not consideredthe perceived utility value of consumers for each attribute by classified based on the characteristics of AI-enabled products. Therefore, the purpose of this study is to investigate the difference in importance between attributes that affect the intention to adopt of AI-enabled products. For this, first, identified and classified the attributes of AI-enabled products based on IS Success Model of DeLone and McLean. Second, measured the utility value of each attribute on the adoption of AI-enabled products through conjoint analysis. And we employed construal level theory to see whether there are differences in the relative importance of AI-enabled products attributes depending on the temporal distance. Third, we segmented the market based on the utility value of each respondent through cluster analysis and tried to understand the characteristics and needs of consumers in each segment market. We expect to provide theoretical implications for conceptually structured attributes and factors of AI-enabled products and practical implications for how development efforts of AI-enabled products are needed to reach consumers need for each segment.

• Journal of the Korean Geotechnical Society
• /
• v.40 no.4
• /
• pp.49-60
• /
• 2024

Ground-penetrating radar (GPR) enables rapid data acquisition over extensive areas, but interpreting the obtained data requires specialized knowledge. Numerous studies have utilized numerical analysis methods to examine GPR signal characteristics under various conditions. To develop more realistic numerical models, the heterogeneous nature of the ground, which causes clutter, must be considered. Clutter refers to signals reflected by objects other than the target. The Peplinski material model and fractal techniques can simulate these heterogeneous characteristics, yet there is a shortage of research on the necessary input parameters. Moreover, methods for quantitatively evaluating the similarity between field and analytical data are not well established. In this study, we calculated the autocorrelation coefficient of field data and determined the correlation length using the autocorrelation function. The correlation length represented the temporal or spatial distance over which data exhibited similarity. By comparing the correlation length of field data with that of the numerical model incorporating fractal weights, we quantitatively evaluated a numerical model for heterogeneous ground. Consequently, the results of this study demonstrated a numerical modeling technique that reflected the clutter characteristics of the field through correlation length.

• Journal of Korean Society of Environmental Engineers
• /
• v.39 no.5
• /
• pp.255-264
• /
• 2017

To evaluate the water quality changes in agricultural reservoir covered with floating photovoltaic solar-tracking systems, the water quality variations with time and depth were monitored on both six sites for light blocking zones and four sites for light penetration zones after the installation of floating photovoltaic solar-tracking systems in Geumgwang reservoir at Anseong-si, Kyeonggi province. For one year with 16 monitoring events, water quality parameters [i.e., water temperature, pH, dissolved oxygen (DO), chlorophyll-a (Chl-a), and blue-green algae (BGA)] were monitored at depths of 0.3 m, 1 m, 3 m, and 5 m, while chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) were monitored at depths of 0.3 m. Statistically, the difference in all water quality parameters was not significantly different (p > 0.05) at the level of significance of 0.05. Based on these results, the water quality data from light blocking zones (site 1~6) and light penetration zones (site 7~10) were clustered, and were compared with time and depth. As a result, the difference in water temperature, pH, DO, COD, TN, TP, Chl-a, and BGA between light blocking zones and light penetration zones was not significant (p > 0.05) with different time and depth. For Chl-a and BGA, some data from light blocking zones greater than light penetration zones were temporary observed due to the severe drought, low water storage rate, and over growth of periphyton. However, this temporal phenomenon did not impact the water quality. Considering the small water surface area (${\leq}0.5%$) covered by floating photovoltaic solar-tracking systems, the mixing effect of whole Geumgwang reservoir caused by Ekman current and continuous discharge were more dominant than the effect of reduced solar irradiance. Further study is warranted to monitor the changes in water quality and aquatic ecosystems with greater water surface area covered by floating photovoltaic solar-tracking systems for a long time.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.19 no.3
• /
• pp.169-179
• /
• 2014

Monthly mean surface heat fluxes in the southeastern Yellow Sea are calculated using directly observed airsea variables from an ocean buoy station including short- and longwave radiations, and COARE 3.0 bulk flux algorithm. The calculated monthly mean heat fluxes are then compared with previous estimates of climatological monthly mean surface heat fluxes near the buoy location. Sea surface receives heat through net shortwave radiation ($Q_i$) and loses heat as net longwave radiation ($Q_b$), sensible heat flux ($Q_h$), and latent heat flux ($Q_e$). $Q_e$ is the largest contribution to the total heat loss of about 51 %, and $Q_b$ and $Q_h$ account for 34% and 15% of the total heat loss, respectively. Net heat flux ($Q_n$) shows maximum in May ($191.4W/m^2$) when $Q_i$ shows its annual maximum, and minimum in December ($-264.9W/m^2$) when the heat loss terms show their annual minimum values. Annual mean $Q_n$ is estimated to be $1.9W/m^2$, which is negligibly small considering instrument errors (maximum of ${\pm}19.7W/m^2$). In the previous estimates, summertime incoming radiations ($Q_i$) are underestimated by about $10{\sim}40W/m^2$, and wintertime heat losses due to $Q_e$ and $Q_h$ are overestimated by about $50W/m^2$ and $30{\sim}70W/m^2$, respectively. Consequently, as compared to $Q_n$ from the present study, the amount of net heat gain during the period of net oceanic heat gain between April and August is underestimated, while the ocean's net heat loss in winter is overestimated in other studies. The difference in $Q_n$ is as large as $70{\sim}130W/m^2$ in December and January. Analysis of long-term reanalysis product (MERRA) indicates that the difference in the monthly mean heat fluxes between the present and previous studies is not due to the temporal variability of fluxes but due to inaccurate data used for the calculation of the heat fluxes. This study suggests that caution should be exercised in using the climatological monthly mean surface heat fluxes documented previously for various research and numerical modeling purposes.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.29 no.1
• /
• pp.84-91
• /
• 1996

Heat flux of the East China Sea was estimated with the bulk method, the East China mount based on the marine meteorological data and cloud amount data observed by a satellite. Solar radiation is maximum in May and minimum in December. Its amount decreases gradually southward during the winter half year (from October to March), and increases northward during the summer half year (from April to September) due to the influence of Changma (Baiu) front. The spatial difference of long-wave radiation is relatively small, but its temporal difference is quite large, i.e., the value in February is about two times greater than that in July. The spatial patterns of sensible and latent heat fluxes reflect well the effect of current distribution in this region. The heat loss from the ocean surface is more than $830Wm^{-2}$ in winter, which is five times greater than the net radiation amount during the same period, The annual net heat flux is negative, which means heat loss from the sea surface, in the whole region over the East China Sea. The region with the largest loss of more than $400Wm^{-2}$ in January is observed over the southwestern Kyushu. The annual mean value of solar radiation, long-wave radiation, sensible and latent heat fluxes are estimated $187Wm^{-2},\;-52Wm^{-2},\;-30Wm^{-2}\;and\;-137Wm^{-2}$, respectively, consequently the East China Sea losses the energy of $32Wm^{-2}(2.48\times10^{13}W)$. Through the heat exchange between the air and the sea, the heat energy of $0.4\times10^{13}W$ is supplied from the air to the sea in A region (the Yellow Sea), $2.1\times10^{13}W$ in B region (the East China Sea) and $1.7\times10^{13}W$ in C region (the Kuroshio part), respectively.

• Korean Journal of Remote Sensing
• /
• v.27 no.4
• /
• pp.467-480
• /
• 2011

Spatial and temporal variabilities of NPP(Net Primary Production) retrieved from two satellite instruments, AVHRR(Advanced Very High Resolution Radiometer, 1981-2000) and MODIS(MODerate-resolution Imaging Spectroradiometer, 2000-2006), were investigated. The range of mean NPP from A VHRR and MODIS were estimated to be 894-1068 $g{\cdot}C/m^2$/yr and 610-694.90 $g{\cdot}C/m^2$/yr, respectively. The discrepancy of NPP between the two instruments is about 325 $g{\cdot}C/m^2$/yr, and MODIS product is generally closer to the ground measurement than AVHRR despite the limitation in direct comparison such as spatial resolution and vegetation classification. The higher NPP values over South Korea are related to the regions with higher biomass (e.g., mountains) and higher annual temperature. The interannual NPP trends from the two satellite products were computed, and both mean annual trends show continuous NPP increase; 2.14 $g{\cdot}C/m^2$/yr from AVHRR(1981-2000) and 6.08 $g{\cdot}C/m^2$/yr from MODIS (2000-2006) over South Korea. Specifically, the higher increasing trends over the Southwestern region are likely due to the increasing productivity of crop fields from sufficient irrigation and fertilizer use. The retrieved NPP shows a closer relationship between monthly temperature and precipitation, which results in maximum correlation during summer monsoons. The difference in the detection wavelength and model schemes during the retrieval can make a significant difference in the satellite products, and a better accuracy in the meterological and land use data and modeling applications will be necessary to improve the satellite-based NPP data.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.9 no.6
• /
• pp.31-39
• /
• 2009

This study has found that there is a reverse phase with interdecadal variation in temporal variations of tropical cyclone (TC) genesis frequency (TCGF) between Northwest sector and Southeast sector, based on climatological mean tropical cyclone genesis location over the western North Pacific. The TCGF in the Northwest sector has been increased since the mid 1980s (1986-2005), while TCGF in the Southeast sector was higher until the early 1970s (1951-1970). The analysis of a difference between 1986-2005 and 1951-1970 showed results as follows: i) Through the analysis of vertical wind shear (VWS) and sea surface temperature (SST), less VWS and higher SST in the former (latter) period was located in the Northwest (Southeast) sector. ii) In the analysis of TC passage frequency (TCPF), TCs occurred in the Northwest sector frequently passed from east sea of the Philippines, through East China Sea, to Korea and Japan in the latter period, while TCs in the former period frequently has a lot of influences on South China Sea (SCS). In the case of TCs occurred in the Southeast sector, TCs in the west (east), based on $150^{\circ}E$ had a high passage frequency in the latter (former) period. In particular, TCs during the latter period frequently moved toward from the east sea of the Philippines to SCS and southern China. iii) This difference of TCPF between the two periods was characterized by 500 hPa anomalous pressure pattern. Particularly, anomalous cyclonic circulation strengthened over the East Asian continent caused anomalous southerlies along the East Asian coast line from the east sea of the Philippines to be predominate. These anomalous winds served as steering flows that TC can easily move toward same regions.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.18 no.2
• /
• pp.101-114
• /
• 2012

The physico-chemical characteristics including water temperature, salinity, dissolved oxygen(DO), chemical oxygen demand (COD), chlorophyll-a(Chl. a), suspended particulate matter(SPM) and dissolved inorganic nutrients were investigated in the Garolim Bay, Yellow Sea, Korea in 2010 carried out six times per year at 11 fixed stations by Korea Fisheries Research & Development Institute. The water temperature, salinity, COD, dissolved inorganic nutrients, Chl. a and SPM showed significant difference between surface and bottom water but the other parameters didn't. There were not significant difference between stations. The water temperature showed typical change patterns of the temperate seawater. The annual average of salinity showed more than 31 so that there could not have occurred low saline water. The average of DO from June to August showed over than 3mg/L which showed higher than the below standard value of the hypoxic (oxygen-deficient) water. The average of Chl. a varied $1.68{\mu}g/L$ at surface, $2.38{\mu}g/L$ at bottom layer in June and $1.68{\mu}g/L$ at surface, $1.57{\mu}g/L$ at bottom layer at August. The dissolved inorganic nutrients showed high concentration in February and low concentration in August due to the limitation of the freshwater input in summer and phytoplankton used to the dissolved inorganic nutrients. The ratio of DIN/DIP showed 30.52 at surface and 37.89 at bottom layer in June which was higher than other month. The SPM was 44.15mg/L at bottom layer in February which was the highest value in this study due to the northwest monsoon. Because of the actively water change in the open sea without inflow of freshwater from land in Garolom Bay, there were not occurred low saline water and hypoxic water. thus, this Bay showed good water quality and required to be conserved continuously as important costal area for fisheries.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.35 no.4
• /
• pp.408-416
• /
• 2002

A 3D hydrodynamic-ecological coupled model was applied to estimate carrying capacity in Geoje-Hansan Bay where is one of the most important oyster culturing grounds in Korea. We considered the carrying capacity as the difference between food supply to the oysters and food demand, considering monthly difference of the actual growth. The food supply to the system was determined from the results of the model simulation (tidal exchange and chlorophyll $\alpha$) over the culturing period from September to May of the following year. The food demand was estimated from the food concentration (chlorophyll $\alpha$) multiple the filtration rate of oysters that is considered monthly different growth rate of oysters and food concentration. The values of carrying capacity for the system varied from 6.1 ton/ha (minimum carrying capacity) in february to 14.91 ton/ha (maximum carrying capacity) in April of marketable size oysters (>4 g wet-tissue weight) depending on temporal variations in the food supply. The oyster production calculated from present facilities was 9 ton/ha in wet-tissue weight in Geoje-Hansan Bay. This value corresponded to $60\%$ of maximum carrying capacity of the system. The optimal carrying capacity without negatively affecting on oyster production was 5.5 ton/ha when calculated from annual statistic data and 6.1 ton/ha when determined by this study. These results suggest that it must be reduced $32\%$~$39\%$ of oyster facilities in the system.