• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.15 no.2
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• pp.51-61
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• 2010

Surface particulate organic carbon (POC) concentration was measured in the Northeastern Gulf of Mexico on 9 cruises from November 1997 to August 2000 to investigate the seasonal and spatial variability related to synchronous remote sensing data (Sea-viewing Wide Field-of-view Sensor (SeaWiFS), sea surface temperature (SST), sea surface height anomaly (SSHA), and sea surface wind (SSW)) and recorded river discharge data. Surface POC concentrations have higher values (>100 $mg/m^3$) on the inner shelf and near the Mississippi Delta, and decrease across the shelf and slope. The inter-annual variations of surface POC concentrations are relatively higher during 1997 and 1998 (El Nino) than during 1999 and 2000 (La Nina) in the study area. This phenomenon is directly related to the output of Mississippi River and other major rivers, which associated with global climate change such as ENSO events. Although highest river runoff into the northern Gulf of Mexico Coast occurs in early spring and lowest flow in late summer and fall, wide-range POC plumes are observed during the summer cruises and lower concentrations and narrow dispersion of POC during the spring and fall cruises. During the summer seasons, the river discharge remarkably decreases compared to the spring, but increasing temperature causes strong stratification of the water column and increasing buoyancy in near-surface waters. Low-density plumes containing higher POC concentrations extend out over the shelf and slope with spatial patterns and controlled by the Loop Current and eddies, which dominate offshore circulation. Although river discharge is normal or abnormal during the spring and fall seasons, increasing wind stress and decreasing temperature cause vertical mixing, with higher surface POC concentrations confined to the inner shelf.

• Journal of Sericultural and Entomological Science
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• v.28 no.1
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• pp.43-53
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• 1986

Among many microbial pesticides, Bacillus thuringiensis is one of the most hopeful pesticide and some commercial products have been appearing on the market. Because these commercial products contain living spores and toxins of the organism, there is a danger that living spores of B. thuringiensis may be scattered by wind and cause a great damage in the sericulture areas. In order to avoide these risks it is desirable to select the strain which has low pathogenicity to the silkworm, and at the sometime being highly pathogenic to the pest insects. Thus this study has been carried out to acquire some basic informations about the procedure of desicable strain selection. Three strains of B. thuringiensis var. kurstaki, var. dendrolimus and var. aizawai were used for the pathogenicity test on the silkworm, Bombux mori and the fall webwarm, Hyphantria cunea. Those strains were investigated by the agarose gel electrophoresis patterns of plasmid DNA determine whether mutation had occured. Pathogenicity tests were carried out of using isolated crystal proteins and spore-crystal protein to mixtures of each strain, seperatively. In case of using spore-crystal protein mixture, the order of pathogenicity in varities of B. thuringiensis against B.mopri and H.cunea were kurstaki, aizawai, dendrolimus and kurstaki, dendrolimus, aizawai, respectively. But using isolated crystal proteins, dendrolimus had the highest toxicity to H. cunea and the lowest toxicity to B. mori among tested three strains. From the above results, dendrolimus was presumed the most desirable straing for using microbial pesticide.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.531-548
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• 2015

Atmospheric Motion Vector (AMV) from satellite images have shown Slow Speed Bias (SSB) in comparison with rawinsonde. The causes of SSB are originated from tracking, selection, and height assignment error, which is known to be the leading error. However, recent works have shown that height assignment error cannot be fully explained the cause of SSB. This paper attempts a new approach to examine the possibility of SSB reduction of COMS AMV by using a new target tracking algorithm. Tracking error can be caused by averaging of various wind patterns within a target and changing of cloud shape in searching process over time. To overcome this problem, Gaussian Mixture Model (GMM) has been adopted to extract the coldest cluster as target since the shape of such target is less subject to transformation. Then, an image filtering scheme is applied to weigh more on the selected coldest pixels than the other, which makes it easy to track the target. When AMV derived from our algorithm with sum of squared distance method and current COMS are compared with rawindsonde, our products show noticeable improvement over COMS products in mean wind speed by an increase of $2.7ms^{-1}$ and SSB reduction by 29%. However, the statistics regarding the bias show negative impact for mid/low level with our algorithm, and the number of vectors are reduced by 40% relative to COMS. Therefore, further study is required to improve accuracy for mid/low level winds and increase the number of AMV vectors.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.525-532
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• 2021

In the ocean, it is difficult to separate the effects of one cause due to the multiple causes, but the self-organizing map can be analyzed by adding other factors to the cluster result. Therefore, in this study, the results of the clustering of sea level data were applied to sea surface temperature. Sea level data was clustered into a total of 6 nodes. The difference between sea surface temperature and sea level height has a one-month delay, which applied sea surface temperature data a month ago to the clustered results. As a result of comparing the mean of sea surface temperature of 140 to 150°E, where the sea surface temperature was variously distributed, in the case of nodes 1, 3, and 5, it was possible to find a meandering sea surface temperature distribution that is clearly distinguished from the sea level data. While nodes 2, 4 and 6, the sea surface temperature distribution was smooth. In this study, sea surface temperature data were applied to the clustered results of sea level data, but later it is necessary to apply wind or geostrophic velocity data to compare.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.77-88
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• 2021

Duck industry had a rapid growth in recent years. Nevertheless, researches to improve duck house environment are still not sufficient enough. Moisture generation of duck house litter is an important factor because it may cause severe illness and low productivity. However, the measuring process is difficult because it could be disturbed with animal excrements and other factors. Therefore, it has to be calculated according to the environmental data around the duck house litter. To cut through all these procedures, we built several machine learning regression model forecasting moisture generation of litter by measured environment data (air temperature, relative humidity, wind velocity and water contents). 5 models (Multi Linear Regression, k-Nearest Neighbors, Support Vector Regression, Random Forest and Deep Neural Network). have been selected for regression. By using R-Square, RMSE and MAE as evaluation metrics, the best accurate model was estimated according to the variables for each machine learning model. In addition, to address the small amount of data acquired through lab experiments, bootstrapping method, a technique utilized in statistics, was used. As a result, the most accurate model selected was Random Forest, with parameters of n-estimator 200 by bootstrapping the original data nine times.

• Geophysics and Geophysical Exploration
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• v.26 no.1
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• pp.8-17
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• 2023

Various sources, such as wind, waves, ships, and gas leaks from the seafloor, forms bubbles in the ocean. Underwater bubbles cause signal scattering, considerably affecting acoustic measurements. This characteristic of bubbles is used to block underwater noise by attenuating the intensity of the propagated signal. Recently, researchers have been studying the large-scale release of methane gas as bubble plumes from the seabed. Understanding the physical properties and distribution of bubble plumes is crucial for studying the relation between leaked methane gas and climate change. Therefore, a water tank experiment was conducted to estimate the distribution of bubble plumes using seismic imaging techniques and acoustic signals obtained from artificially generated bubbles using a bubble generator. Reverse time migration was applied to image the bubble plumes while the acquired acoustic envelope signal was used to effectively estimate bubble distribution. Imaging results were compared with optical camera images to verify the estimated bubble distribution. The water tank experiment confirmed that the proposed system could successfully image the distribution of bubble plumes using reverse time migration and the envelope signal. The experiment showed that the scattering signal of artificial bubble plumes can be used for seismic imaging.

• Journal of the Korea Institute of Building Construction
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• v.19 no.6
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• pp.529-538
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• 2019

Typhoons can cause significant financial damage worldwide. For this reason, states, local governments and insurance companies attempt to quantify and mitigate the financial risks related to these natural disasters by developing a typhoon risk assessment model. As such, the importance of typhoon risk assessment models is increasing, and it is also important to reflect local vulnerabilities to enable sophisticated assessments. Although a practical study of economic losses associated with natural disasters has identified essential risk indicators, comprehensive studies covering the correlation between vulnerability and economic loss are still needed. The purpose of this study is to identify typhoon damage indicators and to develop evaluation indicators for typhoon damage prediction functions, utilizing the loses from Typhoon Maemi as data. This study analyzes actual loss records of Typhoon Maemi provided by local insurance companies to prepare for a scenario of maximum losses. To create a vulnerability function, the authors used the wind speed and distance from the coast and the total value of property, construction type, floors, and underground floor indicators. The results and metrics of this study provide practical guidelines for government agencies and insurance companies in developing vulnerability functions that reflect the actual financial losses and regional vulnerabilities of buildings.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.118-127
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• 2021

Recently, the public's interest in the air environment has increased, and public health is threatened by fine particulate matter. Furthermore, the government continues efforts to improve air quality by expanding the monitoring of air pollutants and reinforcing environmental standards. Since air quality differs depending on the region in the Korean Peninsula, it is currently necessary to identify the cause and search for influencing factors. In this study, the atmospheric environment and regional differences in cities located in the Chungnam Province were observed. As a research method, regression analysis was performed for weather conditions, such as temperature, wind speed, precipitation, and season and targeted at air pollutants, such as SO₂, NO₂, CO, O₃, PM₁₀, and PM_2.5, as well as heavy metals contained in particulate matter, such as Pb, Cd, Cr, Cu, Ni, As, Mn, Fe, Al, Ca, and Mg. In the case of PM₁₀, the concentrations of Mn(0.4884) in Cheonan, CO(0.3329) in Dangjin, and Mg(0.5691) in Seosan were highest. In the case of PM_2.5, Cheonan NO₂(0.4759), Dangjin CO(0.4128), and Seosan NO₂(0.3715) were significantly affected. In summary, the influencing factors vary according to the region in Chungnam province in terms of air quality, and there is a difference in the degree of contribution. Therefore, it is considered that the Korean government's management of air quality is required for each region.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.346-352
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• 2022

Mountain meteorology in South Korea that is covered mountains with complex terrain is important for understanding and managing the forest disaster and forest ecosystems. In particular, recent changes in dryness and/or rainfall intensity due to climate change may cause an increase in the possibility of forest disasters. Therefore, accurate monitoring of mountain meteorology is needed for efficient forest management. Korea Forest Service (KFS) is establishing the Automatic Mountain Meteorology Observation Stations (AMOS) in the mountain regions since 2012. 464 AMOSs are observing various meteorological variables such as air temperature, relative humidity, wind speed and direction, precipitation, soil temperature, and air pressure for every minute, which is conducted the quality control (QC) to retain data reliability. QC process includes the physical limit test, step test, internal consistency test, persistence test, climate range test, and median filter test. All of AMOS observations are open to use, which can be found from the Korean Mountain Meteorology Information System (KoMIS, http://mtweather.nifos.go.kr/) of the National Institute of Forest Science and the Public Data Portal (https://public.go.kr/). AMOS observations with guaranteed quality can be used in various forest fields including the public safety, forest recreation, forest leisure activities, etc., and can contribute to the advancement of forest science and technology. In this paper, a series of processes are introduced to collect and use the AMOS dataset in the mountain region in South Korea.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.6
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• pp.731-736
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• 2021

Oil fences effectively prevent the spread of oil spilled in the sea, thereby reducing the damage to the marine environment. However, the fence is damaged by oil and structures at the accident site and is discarded. When incinerated disposal method for discarded fences, fine dust, and harmful materials are generated. Moreover, as a part of the damaged fence is dumped into the sea, it may cause secondary environmental pollution, such as microplastics. Therefore, in this study, durability was measured using the most common solid foam type oil fences. As a result, the reduction rate of after five days of contact was 13 % in seawater and 3 % in oil, affected by temperature changes. Thus, the durability of the fence should be improved because it is exposed to seawater and oil and affected by wind, light, and waves depending on the weather conditions. Therefore, we suggest a method to improve the oil fence inspection to strengthen the durability of the fence's fabric part.