• Journal of Ocean Engineering and Technology
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• v.23 no.6
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• pp.39-43
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• 2009

A flow and low temperature of deep seawater the biofouling properties in a seawater environment of different materials, such as a steel pipe, polyethylene pipe, and nylon net, used for ocean industries. Experiments in a real sea environment were performed to grasp the quantitative and qualitative biofouling from diatoms attached to materials by measuring the Chlorophyll-a density. Experimental samples were placed under five types of ocean environmental conditions and analyzed every month for five months. It is shown that the biofouling by diatoms was strongly affected by the seawater temperature for all of the experimental samples. It was found that diatoms mainly adhered to the nylon net, while crustaceans prefer polyethylene, under a high temperature condition. It is believed that the biofouling properties are strongly related to the surface roughness of a material. The biofouling under the low temperature condition of deep seawater was rare and stable for the experimental periods. The inside of a pipe conveying deep seawater can be presumed to remain clear without biofouling on the condition of a flow and low temperature of deep seawater.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.301-301
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• 2022

본 연구는 운영 조건이 달라짐에 따라 회전수가 변하는 기기의 정상적 가동 여부와 고장 종류를 판별하기 위한 인공지능 알고리즘의 적용을 다루고 있다. 회전수가 변하는 장비로부터 계측된 상태 모니터링 센서의 신호는 비정상(non-stationary)적 특성이 있으므로, 상태 신호의 한계치가 고장 판별의 기준이 되기 어렵다는 점을 해결하고자 하였다. 정상 가동 여부는 이상 감지에 효율적인 오토인코더 및 기계학습 알고리즘을 적용하였으며, 고장 종류 판별에는 기계학습법과 합성곱 기반의 심층학습 방법을 적용하였다. 변하는 회전수와 연계된 주파수의 비정상적 시계열도 적절한 고장 특징 (Feature)로 대변될 수 있도록 시간 및 주파수 영역에서 특징 벡터를 구성할 수 있음을 예제로 설명하였다. 차원 축소 및 카이 제곱 기법을 적용하여 최적의 특징 벡터를 추출하여 기계학습의 분류 알고리즘이 비정상적 회전 신호를 가진 장비의 고장 예측에 활용될 수 있음을 보였다. 이 과정에서 k-NN(k-Nearest Neighbor), SVM(Support Vector Machine), Random Forest의 기계학습 알고리즘을 적용하였다. 또한 시계열 기반의 오토인코더 및 CNN (Convolution Neural Network) 적용하여 이상 감지와 고장진단을 수행한 결과를 비교하여 제시하였다.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.1
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• pp.49-61
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• 2021

The repeated shipboard measurements that have been conducted by the National Institute of Fisheries Science (NIFS) for more than a half century, provide the valuable long-term hydrographic data with high spatial-temporal resolution. However, this unprecedent dataset has been rarely used for oceanic climate sciences because of its reliability issue. In this study, temporal variability of salinity error in the NIFS data was quantified by means of extremely small variability of salinity in the deep layer of the south-western East Sea, in order to contribute to studies on long-term variability of the East Sea. The NIFS salinity errors estimated on the isothermal surfaces of 1℃ have a remarkable temporal variation, such as ~0.160 g/kg in the year of 1961~1980, ~0.060 g/kg in 1981~1994,~0.020 g/kg in 1995~2002, and ~0.010 g/kg in 2003~2014 on average, which basically represent bias error. In the recent years, even though the quality of salinity has been improved, there still remain relatively large bias errors in salinity data presumably due to failure of salinity sensor managements, especially in 2011, 2013, and 2014. On the contrary, the salinity in the year of 2012 was very accurate and stable, whose error was estimated as about 0.001 g/kg comparable to the salinity sensor accuracy. Thus, as long as developing proper data quality control procedures and sensor management systems, I expect that the NIFS shipboard hydrographic data could have good enough quality to support various studies on ocean response to climate variabilities. Additionally, a few points to improve the current NIFS shipboard measurements were suggested in the discussion section.

• Journal of the Korean Society for Marine Environment & Energy
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• v.9 no.4
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• pp.243-252
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• 2006

Influence of the increasing carbon dioxide concentration in seawater on various marine organisms is assessed in this article with regard to the impacts of anthropogenic $CO_2$ introduced into surface or deep oceans. Recent proposals to sequester $CO_2$ in deep oceans arouse the concerns of adverse effects of increased $CO_2$ concentration on deep-sea organisms. Atmospheric introduction of $CO_2$ into the ocean can also acidify the surface water, thereby the population of some sensitive organisms including coral reefs, cocolithophorids and sea urchins will be reduced considerably in near future (e.g. in 2100 unless the increasing trend of $CO_2$ emission is actively regulated). We exposed bioluminescent bacteria and benthic amphipods to varying concentrations of $CO_2$ and also pH for a short period. The ${\sim}l.5$ unit decrease of pH adversely affected test organisms. However, amphipods were not influenced by decreasing pH when HCl was used for the seawater acidification. In this article, we reviewed the biological adverse effects of $CO_2$ on various marine organisms studied so for. Theses results will be useful to predict the potential risks of the increase of $CO_2$ concentrations in seawater due to the increase of atmospheric $CO_2$ emission and/or sequestration of $CO_2$ in deep oceans.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.49-54
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• 2017

We collected and reared Theragra chalcogramma walleye pollock brood-stock for use in natural spawning tests and undertook to obtain domestic pollock via fertilized egg capture, development of fertilized eggs, and absorption of yolk sac after hatching. Whole pollock were caught with trammel and set nets and immediately placed in a deep-sea water tank. Adults were the most common pollock age group (43.0%; n = 86) among the 254 pollock captured in March 2014 with 57.9% (n = 147) being captured off Southern Gosung, Korea. The main spawning period of pollock is February (spawning phase of 91% of pollock). From the deep-sea tank, we collected 1640 mL of naturally fertilized eggs (~820,000 eggs) from 12 spawning events occurring between February 4 and 22 2015. The floating/ live eggs were maintained in deep-sea water tanks at $5.5{\pm}0.2^{\circ}C$. Egg size was $1.5{\pm}0.03mm$. Six hours after fertilization the eggs were at the 2 cell stage, and the eggs hatched approximately 340 hours after collection. At hatching, larval length and yolk sac area were $5.2{\pm}0.25mm$ and $9.5{\pm}1.00mm^2$ (100%), respectively. Four days after hatching, the yolk sac area was $2.2{\pm}0.53mm^2$ ($23.1{\pm}5.55%$). This is the first report of collection of naturally fertilized eggs from pollock and their subsequent hatching while held in an indoor deep-sea water tank. The results suggest that such collection could assist in the recovery of pollock resources and the possibility of domestic rearing of cultivated larvae.

• 한국해양학회지
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• v.27 no.4
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• pp.324-331
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• 1992

Water masses and circulations around Korean peninsula are briefly described based on recent studies. The results of theses studies are discussed from the physical point of view. Oceanic conditions in this region are largely due to the roles played by the Tsushima Warm Current, an onshore extension of the Kuroshio, and local conditions such as wind, surface heat flux and fresh water input etc. To the south and west of Korea, the northern/western border of the Tsushima Warm Current Water is roughly the line joining Taiwan and Cheju island. In summer, it is affected by large amount of fresh water discharged from the Changjiang and in winter, an intrusion of this water into the Yellow Sea is induced by the prevailing northwesterly monsoon wind. To the east of Korea, the Tsushima Warm Current Water presents roughly south of the line joining the wast coast of Korea near 37-38$^{\circ}$N and Tsugaru-Soya Straits in the northern Japan. But this situation, together with those in deeper layers, may greatly be changed by winter atmospheric conditions (wind and surface heat flux). The seas around Korea are not yet physically well understood and many problems wait physical explanations. Some problems, along with personal views of them, are mentioned.

• 한국해양학회지
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• v.26 no.3
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• pp.278-290
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• 1991

A synoptic survey of chemical properties was carried out at 21 stations in the Ulleung Basin in May 1988 on board T/V HANBADA. Vertical structures of typical profiles are: surface mixedlayer waters in the upper 30∼40 m with depleted nutrients concentrations, thermocline waters with rapid variations in all physical and chemical properties. and deep Waters below 200 m which are nearly homogeneous. Along the northern section at 37$^{\circ}$12'N. The salinity minimum layer was observed at about 190m. which characterize the East Sea Intermediate Water (ESIW). The dissolved oxygen concentration in this layer was about 230∼ 275uM, lower than 290uM (6.5ml/l) which is the previously known characteristics of the ESIW. However, apparent oxygen utilization (AOU), nitrate, phosphate and silicate show systematically low concentration in the salinity-minimum layer. The low values of AOU and all the nutrients associated with the salinity-minimum, may be useful to identify the ESIW and serve as a new tracer in the East Sea.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1209-1216
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• 2020

In this study, we propose a method for detecting coastal surface wastes using an UAV(Unmanned Aerial Vehicle) remote sensing method and an object detection algorithm based on deep learning. An object detection algorithm based on deep neural networks was proposed to detect coastal debris in aerial images. A deep neural network model was trained with image datasets of three classes: PET, Styrofoam, and plastics. And the detection accuracy of each class was compared with Darknet-53. Through this, it was possible to monitor the wastes landing on the shore by type through unmanned aerial vehicles. In the future, if the method proposed in this study is applied, a complete enumeration of the whole beach will be possible. It is believed that it can contribute to increase the efficiency of the marine environment monitoring field.

• Journal of Environmental Science International
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• v.20 no.7
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• pp.919-927
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• 2011

A ecosystem model was applied for understanding of circulation process of state variables in marine ecosystem. A mass balance was conducted by calculating the physical process. The sensitivity analysis was conducted to know which coefficient is the most effective factor to the state variables in the model. The results of the mass balance indicate that the primary production was 58.6 ton C/day in the case of mass flux. DIN and DIP in nutrient ingestion of phytoplankton were each 7.9 ton N/day, 1.1 ton P/day. POC and DOC in mineralization of organic matter were each 10.8 ton C/day, 40.6 ton C/day. The results of sensitivity analysis showed that the maximum growth rate of phytoplankton was the most important factor for overall state variables. In the case of nutrients, Half saturation constant of DIN, and mineralization rate of DOM for COD were important factor.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.63-70
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• 2021

Generating a super-resolution meteological data by using a high-resolution deep neural network can provide precise research and useful real-life services. We propose a new technique of generating improved training data for super-resolution deep neural networks. To generate high-resolution meteorological data with domain specific knowledge, Lambert conformal conic projection and objective analysis were applied based on observation data and ERA5 reanalysis field data of specialized institutions. As a result, temperature and humidity analysis data based on domain specific knowledge showed improved RMSE by up to 42% and 46%, respectively. Next, a super-resolution generative adversarial network (SRGAN) which is one of the aritifial intelligence techniques was used to automate the manual data generation technique using damain specific techniques as described above. Experiments were conducted to generate high-resolution data with 1 km resolution from global model data with 10 km resolution. Finally, the results generated with SRGAN have a higher resoltuion than the global model input data, and showed a similar analysis pattern to the manually generated high-resolution analysis data, but also showed a smooth boundary.