• Korean Journal of Environment and Ecology
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• v.29 no.5
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• pp.710-717
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• 2015

This study was conducted investigate population size and habitat use for the conservation and management of the endangered long-tailed goral in the Seoraksan National Park using feces and camera trap during 2010 to 2014 (track survey, camera trap). As a result of feces tracking and camera trap, its population size was estimated as 160 (camera trap)~251 (feces) individuals in the Seoraksan National Park. The goral prefer $35^{\circ}{\sim}60^{\circ}$ (slope), 600~700m (elevation), NE (aspect), 0~50m (distance to stream), 300~600m (distance to road) and bread-leaved forest (forest type) according to field tracking of fecal. Based on field camera trap, we estimated the age classes of goral populations and activity of gorals during day-time (07-18 time, 56.5%) and night-time (18-07 time, 43.5%). Such analyses of population size and habitat use of the goral could be applied as important fundamental data for conservation of gorals and management of their habitats.

• Journal of Forest and Environmental Science
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• v.33 no.3
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• pp.239-242
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• 2017

Although camera traps have been widely used to understand the abundance of wildlife in recent decades, the effort has been restricted to small sub-set of wildlife which can mark-and-recapture. The Random Encounter Model shows an alternative approach to estimate the absolute abundance from camera trap detection rate for any animals without the need for individual recognition. Our study aims to examine the feasibility and validity of the Random Encounter Model for the density estimation of endangered leopard cats (Prionailurus bengalensis) in Maekdo riparian park, Busan, South Korea. According to the model, the estimated leopard cat density was $1.76km^{-2}$ (CI 95%, 0.74-3.49), which indicated 2.46 leopard cats in $1.4km^2$ of our study area. This estimate was not statistically different from the previous leopard cat population count ($2.33{\pm}0.58$) in the same area. As follows, our research demonstrated the application and usefulness of the Random Encounter Model in density estimation of unmarked wildlife which helps to manage and protect the target species with a better understanding of their status.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.42 no.1
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• pp.11-18
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• 2006

The behavior patterns of common octopus, Octopus minor to a cylindric trap were examined in the water tank using a video camera in order to know entering mechanism to the trap and to improve it. Fishing efficiency by 2 kinds of traps(A: 3 entrances, B: 2 entrances) was investigated in the coastal area of Deugryang Bay from May to July, 2005. Common octopus tends to approach by swimming more than walking towards trap. When they approached to the trap, they showed much more behaviors that sate at the around than upper part of it. Approaching behaviors of common octopus was more vigorous at nighttime than daytime on the trap, they showed the most vigorous action between 2 am and 4 am of the day. The rate of staying 30 seconds over around the trap was 41.5% in the nighttime. CPUE(g/trap) of common octopus caught by A type trap was 21.4% higher than the B type trap but there was no difference on the significance level of 5% by the ANOVA. Catch rate of common octopus and by-catch species caught by the A type trap were 97.2%, three and 98.7%, two for B type trap, respectively.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.2
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• pp.72-78
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• 2023

The leopard (Panthera pardus) is one of the most widespread felids worldwide. Despite their wide distribution, reliable data on leopard population densities are still inadequate for conservation and management strategies in different landscapes. In the present study, we estimated leopard density using camera traps in the Ranthambhore Tiger Reserve (RTR), Rajasthan, India, between December 2010 and February 2011, where leopards coexist alongside a high density of tigers (Panthera tigris), a larger predator (RTR). A sampling effort of 4,450 trap days was made from 178 camera trapping stations over 75 days, resulting in 46 suitable photo captures (25 right flanks and 21 left flanks). In total, 18 individuals (7 males, 8 females, and 3 unknown sexes) were identified using the right flanks, and the estimated leopard density was 8.8 (standard error=2.8) individuals/100 km². Leopard density appeared to respond to small prey (<50 kg weight) richness. As this is the first systematic study to provide baseline information on leopard density in RTR, it could form a baseline for comparison in future investigations.

• Journal of Forest and Environmental Science
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• v.34 no.1
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• pp.71-76
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• 2018

The long-tailed goral (Naemorhedus caudatus) has slowly recolonized habitats in South Korea. Because it is necessary to know the status of groups in recolonized areas, we determined detection frequencies and group sizes using camera trapping, a non-invasive monitoring method. In Uljin, a far southern goral habitat in South Korea, we used a Moultrie 5.0 camera and mineral block as bait during the breeding season in BaekAm Mountain (148 days, 18 May to 11 October) and Geumjong Mountain (63 days, 18 May to 18 July) in 2010. Totally, 155 images were captured in BaekAm Mountain, whereas four images were captured in Geumjong Mountain. The species was most frequently detected at sunrise (05:00-08:00) and sunset (18:00-20:00). Through population structure evaluation, we identified at least 11 individuals, including one solitary mature male, four females, four kids, and two solitary subadults in BaekAm Mountain. However, in Geumjong Mountain, we identified only two individuals (female with kid). Monitoring efficiency in the recolonized area differed depending on population density and habitat conditions. Because we could evaluate the population structure, and behavioral patterns in the study sites, monitoring using camera traps could be applied for the recolonized habitats in South Korea.

• Journal of Ecology and Environment
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• v.45 no.2
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• pp.88-96
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• 2021

Background: Sika deer, Cervus nippon, were originally introduced to South Korea from Japan and Taiwan for commercial farming purposes. Unfortunately, they were released into the wild during religious events and have since begun to impact the native ecosystem and species endemic to South Korea. The study of activity patterns can improve our understanding of the environmental impact of non-native species and their association with sympatric species. Using camera traps, we studied the diel and seasonal activity patterns of non-native sika deer and quantified the temporal overlap with sympatric mammalian species in the Muljangori-oreum wetlands of Hallasan National Park, South Korea. Results: A total of 970 trap events were recorded for five mammalian species from nine locations during the camera-trap survey. Siberian roe deer (Capreolus pygargus tianschanicus) had the highest number of recorded events (72.0%), followed by sika deer (Cervus nippon) (16.2%), wild boar (Sus scrofa) (5.0%), Asian badger (Meles leucurus) (4.5%), and the Jeju weasel (Mustela sibirica quelpartis) (2.0%). Sika deer had bimodal activity patterns throughout the year, with peaks throughout the spring-autumn twilight, and day and night time throughout the winter. Relating the daily activity of sika deer with other mammalian species, roe deer expressed the highest degree of overlap (Δ₄ = 0.80) while the Asian badger demonstrated the lowest overlap (Δ₄ = 0.37). Conclusions: Our data show that sika deer are a crepuscular species with seasonal variations in daily activity patterns. Additionally, we identified the temporal differences in activity peaks between different mammals in the Muljangori-oreum wetlands and found higher degree of overlap between sika deer and roe deer during twilight hours.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.211-218
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• 2023

Background: Traditional wildlife monitoring has often relied on invasive techniques posing risks to species and demanding substantial resources. To address this, camera traps emerged as non-invasive alternatives, albeit primarily tailored for larger mammals, posing limitations for small mammal research. Thus, the Mostela, an innovative tool designed to overcome these challenges, was introduced to monitor small mammals in South Korea. Results: The Mostela was deployed at two study sites in South Korea, yielding compelling evidence of its efficiency in capturing small mammal species. By analyzing the collected data, we calculated the relative abundance of each species and elucidated their activity patterns. Conclusions: In summary, the Mostela system demonstrates substantial potential for advancing small mammal monitoring, offering valuable insights into diversity, community dynamics, activity patterns, and habitat preferences. Its application extends to the detection of endangered and rare species, further contributing to wildlife conservation efforts in South Korea. Consequently, the Mostela system stands as a valuable addition to the toolkit of conservationists and researchers, fostering ethical and non-invasive research practices while advancing our understanding of small mammal populations and ecosystems.

• Journal of Forest and Environmental Science
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• v.34 no.1
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• pp.46-49
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• 2018

This study aims to explore the knowledge structure of the leopard cat (Prionailurus bengalensis) research during the period of 1952-2017. Data was collected from Google Scholar and Research Information Service System (RISS), and a total of 482 author keywords from 125 papers from peer-reviewed scholarly journals were retrieved. Co-word analysis was applied to examine patterns and trends in the leopard cat research by measuring the association strengths of the author keywords along with the descriptive analysis of the keywords. The result shows that the most commonly used keywords in leopard cat research were Felidae, Iriomte cat, and camera trap except for its English and scientific name, and camera traps became a frequent keyword since 2005. Co-word analysis also reveals that leopard cat research has been actively conducted in Southeast Asia in conjugation with studying other carnivores using the camera traps. Through the understanding of the patterns and trends, the finding of this study could provide an opportunity for the exploration of neglected areas in the leopard cat research and conservation.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.4
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• pp.17-34
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• 2023

Camera trapping has been used as a non-invasive survey method that minimizes anthropogenic disturbance to ecosystems. Nevertheless, it is labor-intensive and time-consuming, requiring researchers to quantify species and populations. In this study, we aimed to improve the preprocessing of camera trapping data by utilizing an object detection algorithm. Wildlife monitoring using unmanned sensor cameras was conducted in a forested urban forest and a green space on a university campus in Cheonan City, Chungcheongnam-do, Korea. The collected camera trapping data were classified by a researcher to identify the occurrence of species. The data was then used to test the performance of the YOLO-X object detection algorithm for wildlife detection. The camera trapping resulted in 10,500 images of the urban forest and 51,974 images of green spaces on campus. Out of the total 62,474 images, 52,993 images (84.82%) were found to be false positives, while 9,481 images (15.18%) were found to contain wildlife. As a result of wildlife monitoring, 19 species of birds, 5 species of mammals, and 1 species of reptile were observed within the study area. In addition, there were statistically significant differences in the frequency of occurrence of the following species according to the type of urban greenery: Parus varius(t = -3.035, p < 0.01), Parus major(t = 2.112, p < 0.05), Passer montanus(t = 2.112, p < 0.05), Paradoxornis webbianus(t = 2.112, p < 0.05), Turdus hortulorum(t = -4.026, p < 0.001), and Sitta europaea(t = -2.189, p < 0.05). The detection performance of the YOLO-X model for wildlife occurrence was analyzed, and it successfully classified 94.2% of the camera trapping data. In particular, the number of true positive predictions was 7,809 images and the number of false negative predictions was 51,044 images. In this study, the object detection algorithm YOLO-X model was used to detect the presence of wildlife in the camera trapping data. In this study, the YOLO-X model was used with a filter activated to detect 10 specific animal taxa out of the 80 classes trained on the COCO dataset, without any additional training. In future studies, it is necessary to create and apply training data for key occurrence species to make the model suitable for wildlife monitoring.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 2006.05a
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• pp.262-262
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• 2006

The characteristics of Brown gas was experimentally studied in view of efficiency and flame propagation. For this study, the Brown gas stack with 7 cells was manufactured following the Brown gas related patents and reports. All measuring equipments were re-tested and calibrated by Korea Laboratory Accreditation Scheme (KOLAS) certified laboratories. Since the amount of produced gas is most crucial in determining the efficiency, we adopted two gas collecting methods such as bottle trap method and wet gas meter method. The energy efficiency of our own fabricated stack was measured to be 75%, which is comparable to general alkaline water electrolysis efficiency. In order to analyze the flame propagation characteristics of Brown gas, we measured the flame propagation pressure, velocity, and shape by using strain type pressure sensor, optical sensor, and high speed camera in conjunction with Schliren system, respectively. From the experimental results, it was found that the flame propagation behavior of Brown gas was almost the same as that of hydrogen and oxygen mixture gas in 2:1 molar ratio. Moreover, from the high speed camera analysis, we concluded that Brown gas flame exhibits explosion behavior as does mixture gas ($H_{2}:O_{2}=2:1$).