• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1965-1974
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• 2021

Satellite remote sensing approach can be actively used for forest monitoring. Especially, it is much meaningful to utilize Korea multi-purpose satellites, an independently operated satellite in Korea, for forest monitoring of Korea, Recently, several studies have been performed to exploit meaningful information from satellite remote sensed data via machine learning approaches. The forest information produced through machine learning approaches can be used to support the efficiency of traditional forest monitoring methods, such as in-situ survey or qualitative analysis of aerial image. The performance of machine learning approaches is greatly depending on the characteristics of study area and data. Thus, it is very important to survey the best model among the various machine learning models. In this study, the performance of deep neural network to classify artificial or natural forests was analyzed in Samcheok, Korea. As a result, the pixel accuracy was about 0.857. F1 scores for natural and artificial forests were about 0.917 and 0.433 respectively. The F1 score of artificial forest was low. However, we can find that the artificial and natural forest classification performance improvement of about 0.06 and 0.10 in F1 scores, compared to the results from single layered sigmoid artificial neural network. Based on these results, it is necessary to find a more appropriate model for the forest type classification by applying additional models based on a convolutional neural network.

• Journal of the Korean earth science society
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• v.40 no.2
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• pp.109-118
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• 2019

Cloud-aerosol interactions are considered to be one of the most important forcing mechanisms in the climate system. However, there is considerable disagreement on the magnitude and even on the sign of how aerosol perturbations affect cloud fraction and lifetime. Furthermore, aerosol effects on clouds and precipitation are not readily separable from the effects of meteorology. This review paper summarizes the study of precipitation susceptibility $S_o$, which qualifies how aerosol perturbations alter the magnitude of the precipitation rate (R) while minimizing the effects of macrophysical factors such as cloud depth (H) and liquid water path (LWP). The analysis shows that the precipitation susceptibility $S_o$ for the warm marine boundary layer clouds is insensitive to aerosol perturbations at low LWP (equivalently low H). However, R decreases as aerosols increase at intermediate LWP. This is because aerosols act as cloud seed and produce numerous small-sized particles, which impede the collision and coalescence process that leads to precipitation. At high LWP, $S_o$ decreases with increasing LWP as there are enough water contents in the clouds. The LWP or H dependent $S_o$ behavior differs depending on the predominant cloud physics processes in the clouds.

• Land and Housing Review
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• v.14 no.2
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• pp.125-135
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• 2023

Drones are used in various fields, including land survey, transportation, forestry/agriculture, marine, environment, disaster prevention, water resources, cultural assets, and construction, as their industrial importance and market size have increased. In this study, image data for deep learning was collected using a mavic3 drone capturing images at a shooting altitude was 20 m with ×7 magnification. Swin Transformer and UperNet were employed as the backbone and architecture of the deep learning model. About 800 sheets of labeled data were augmented to increase the amount of data. The learning process encompassed three rounds. The Cross-Entropy loss function was used in the first and second learning; the Tversky loss function was used in the third learning. In the future, when the crack detection model is advanced through convergence with the Internet of Things (IoT) through additional research, it will be possible to detect patching or potholes. In addition, it is expected that real-time detection tasks of drones can quickly secure the detection of pavement maintenance sections.

• Journal of the Korean Society for Marine Environment & Energy
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• v.17 no.4
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• pp.306-317
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• 2014

This study has been executed to understand the additional and removal processes of nutrients in the Saemangeum Salt-water Lake, and discussed with other monthly-collected environmental parameters such as water temperature, salinity, dissolved oxygen, suspended solids, and Chl-a from 2008 to 2010. $NO_3$-N, TP, $PO_4$-P, and DISi showed the removal processes along with the salinity gradients at the surface water of the lake, whereas $NO_2$-N, $NH_4$-N, and Chl-a showed addition trend. In the bottom water all water quality parameters except $NO_3$-N appeared addition processes indicating evidence of continuous nutrients suppliance into the bottom layer. The mixing modelling approach revealed that the biogeochemical processes in the lake consume $NO_3$-N and consequently added $NH_4$-N and $PO_4$-P to the bottom water during the summer seasons. The $NH_4$-N and $PO_4$-P appeared strong increase at the bottom water of the river-side of the lake and strong concentration gradient difference of dissolved oxygen also appeared in the same time. DISi exhibited continuous seasonal supply from spring to summer. Internal addition of $NH_4$-N and $PO_4$-P in the river-side of the lake were much higher than the dike-side, while the increase of DISi showed similar level both the dike and river sides. The temporal distribution of benthic flux for DISi indicates that addition of nutrients in the bottom water was strongly affected by other sources, for example, submarine ground-water discharge (SGD) through bottom sediment.

• Journal of Navigation and Port Research
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• v.28 no.10 s.96
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• pp.899-908
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• 2004

The rise of income and introduction of 5 day a week working system give korean people opportunities to enjoy their leisure time. And many korean people have much interest in oceanic sports such as yachting and also oceanic leisure equipments. With the popularization and development of the equipments, the scope of oceanic activities has been expanding in Korea just as in the advanced oceanic countries. However, The current conditions for the sports in Korea are not advanced and even worse than underdeveloped countries. In order to develop the underdeveloped resources of Korean marina, we need to customize the marina models of advanced nations to serve the specific needs and circumstances of Korea As such we have carried out a comparative analysis of how Austrailia, Newzealand, Singapore, japan and Malaysia operate their marina, reaching the following conclusions. Firstly, in marina operations, in order to protect personal property rights and to preserve the environment, we must operate membership and non-membership, profit and non-profit schemes separately, yet without regulating the dress code entering or leaving the club house. Secondly, in order to accumulate greater value added, new sporting events should be hosted each year. There is also the need for an active use of volunteers, the generation of greater interest in yacht tourism, and the simplification of CIQ procedures for foreign yachts as well as the provision of language services. Thirdly, a permanent yacht school should be established, and classes should be taught by qualified instructors. Beginners, intermediary, and advanced learner classes should be managed separately with special emphasis on the dinghy yacht program for children. Fourthly, arrival and departure at the moorings must be regulated autonomically, and there must be systematic measures for the marina to be able, in part, to compensate for loss and damages to equipment, security and surveillance after usage fees have been paid for. Fifthly, marine safety personnel must be formed in accordance with Korea's current circumstances from civilian organizations in order to be used actively in benchmarking, rescue operations, and oceanic searches at times of disaster at sea.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.3
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• pp.165-173
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• 2010

A cloud detection method is introduced to improve the reliability of NOAA/AVHRR Sea Surface Temperature (SST) data processed during the daytime and nighttime in the TeraScan System. In daytime, the channels 2 and 4 are used to detect a cloud using the three tests, which are spatial uniformity tests of brightness temperature (infrared channel 4) and channel 2 albedo, and reflectivity threshold test for visible channel 2. Meanwhile, the nighttime cloud detection tests are performed by using the channels 3 and 4, because the channel 2 data are not available in nighttime. This process include the dual channel brightness temperature difference (ch3 - ch4) and infrared channel brightness temperature threshold tests. For a comparison of daytime and nighttime SST images, two data used here are obtained at 0:28 (UTC) and 21:00 (UTC) on May 13, 2009. 6 parameters was tested to understand the factors that affect a cloud masking in and around Korean Peninsula. In daytime, the thresholds for ch2_max cover a range 3 through 8, and ch4_delta and ch2_delta are fixed on 5 and 2, respectively. In nighttime, the threshold range of ch3_minus_ch4 is from -1 to 0, and ch4_delta and min_ch4_temp have the fixed thresholds with 3.5 and 0, respectively. It is acceptable that the resulted images represent a reliability of SST according to the change of cloud masking area by each level. In the future, the accuracy of SST will be verified, and an assimilation method for SST data should be tested for a reliability improvement considering an atmospheric characteristic of research area around Korean Peninsula.

• Microbiology and Biotechnology Letters
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• v.39 no.4
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• pp.317-323
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• 2011

Strain A-3, an amylase-producing bacteria, was isolated from coastal seawater near Daecheon in the Republic of Korea. It was seen to possess a single polar flagella and grow well, on ASW-YP agar plates, at temperatures of between $20-37^{\circ}C$. However, it grew more slowly at the temperatures of $15^{\circ}C$ and $40^{\circ}C$. Similarly, it was observed to grow abundantly, in an Artificial Sea Water-Yeast extract-Peptone (ASW-YP) liquid medium, in a pH range of 6-9, but not grow at pHs of 4-5 and a pH of 10. Strain A-3 was noted as being close to Pseudoalteromonas phenolica O-$BC30^T$, Pseudoalteromonas luteoviolacea $NCIMB1893^T$, Pseudoalteromonas rubra $ATCC29570^T$, and Pseudoalteromonas byunsanensis $FR1199^T$, with 98.30%, 97.86%, 97.78%, and 97.25% similarities respectively, in its 16S rRNA sequence. A phylogenetic tree revealed that strain A-3 and P. phenolica O-$BC30^T$ belong to a clade. However, strain A-3 differed from P. phenolica O-$BC30^T$ in relation to a number of physiological characteristics. Strain A-3 exhibited no growth above 5% NaCl concentrations, no utilization of D-glucose, D-mannose, D-maltose, or D-melibose, and no lipase (C-14) activity. All of these properties strongly indicate that strain A-3 is distant from P. phenolica O-$BC30^T$ and thus led us to name it Pseudoalteromonas sp. A-3. Pseudoalteromonas sp. A-3 produces ${\alpha}$-amylase throughout growth. Maximal amylase activities of 144.48 U/mL and 149.20 U/mL were seen at pH 7.0 and $37^{\circ}C$, respectively. Pseudoalteromonas sp. A-3's high, stable production of ${\alpha}$-amylase in addition to its biochemical features, such as alkalitolerance, suggest that it is a good candidate for industrial applications.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.20 no.1
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• pp.1-15
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• 2015

Impacts of Sea Surface Temperature (SST) assimilation to the prediction of upper ocean temperature is investigated by using a regional ocean forecasting system, in which 3-dimensional optimal interpolation is applied. In the present study, Sea Surface Temperature and Sea Ice Analysis (OSTIA) dataset is adopted for the daily SST assimilation. This study mainly compares two experimental results with (Exp. DA) and without data assimilation (Exp. NoDA). When comparing both results with OSTIA SST data during Sept. 2011, Exp. NoDA shows Root Mean Square Error (RMSE) of about $1.5^{\circ}C$ at 24, 48, 72 forecast hour. On the other hand, Exp. DA yields the relatively lower RMSE of below $0.8^{\circ}C$ at all forecast hour. In particular, RMSE from Exp. DA reaches $0.57^{\circ}C$ at 24 forecast hour, indicating that the assimilation of daily SST (i.e., OSTIA) improves the performance in the early SST prediction. Furthermore, reduction ratio of RMSE in the Exp. DA reaches over 60% in the Yellow and East seas. In order to examine impacts in the shallow costal region, the SST measured by eight moored buoys around Korean peninsula is compared with both experiments. Exp. DA reveals reduction ratio of RMSE over 70% in all season except for summer, showing the contribution of OSTIA assimilation to the short-range prediction in the coastal region. In addition, the effect of SST assimilation in the upper ocean temperature is examined by the comparison with Argo data in the East Sea. The comparison shows that RMSE from Exp. DA is reduced by $1.5^{\circ}C$ up to 100 m depth in winter where vertical mixing is strong. Thus, SST assimilation is found to be efficient also in the upper ocean prediction. However, the temperature below the mixed layer in winter reveals larger difference in Exp. DA, implying that SST assimilation has still a limitation to the prediction of ocean interior.