• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.1
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• pp.19-24
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• 2023

In traditional fish farming way, the workers have to observe all of the pools every time and every day to feed at the right timing. This method causes tremendous stress on workers and wastes time. To solve this problem, we implemented an automatic detection system for feeding time using deep neural network. The detection system consists of two steps: classification of the presence or absence of feed and checking DO (Dissolved Oxygen) of the pool. For the classification, the pretrained ResNet18 model and transfer learning with custom dataset are used. DO is obtained from the DO sensor in the pool through HTTP in real time. For better accuracy, the next step, checking DO proceeds when the result of the classification is absence of feed several times in a row. DO is checked if it is higher than a DO reference value that is set by the workers. These actions are performed automatically in the UI programs developed with LabVIEW.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.5
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• pp.179-186
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• 2021

We need measures that can come up with alternative about fishery living zone and enhance local acceptance for responding to the increase in the proportion of renewable energy production and construction of 12GW Offshore wind power according to Korea's Renewable Energy 3020 initiative and Korean-version New Deal. In this study, We suggest that differentiation plans of co-location model in connection with offshore wind power generation suitable for the East Sea. The East Sea is an optimal site for building of a floating offshore wind power generation(FOWPG) field. It is expected that economic effects like energy production, aquatic resource development and tourism industrialization by farming bluefin tuna which is high valued fish and suitable for offshore aquaculture on public waters in FOWPG field. And we can confirm that budget reduction, smart management by sharing operation management technology and increase in fishermen income.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.56 no.1
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• pp.116-123
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• 2023

Flow-through aquaculture systems generate large amounts of wastewater containing compounds such as solids that can settle near aquafarms and cause eutrophication. The settled solids are often reintroduced into flow-through systems, and aquatic animals can be affected by the solids and pathogens associated with these solids. For a sustainable aquaculture operation, adequate wastewater treatment is required. Hydrocyclones are one of the most promising technologies for the removal of solids in aquaculture wastewater. In this study, a model for performance prediction of hydrocyclones was investigated under three different operating conditions: water temperature, solids concentration, and water inlet velocity. The synthetic solids solution was prepared using settled solids from abalone aquaculture farms. The daily solids removal rates of the tested hydrocyclones ranged from 0.18 to 26.0 g solids-m^-3-day^-1, and removal efficiency ranged from 5.1 to 34.4%. The inlet water velocity had the greatest effect on solids removal and hydrocyclone efficiencies. The following multiregression model equation was derived from the daily solids removal rate (g solids-m^-3-day^-1) results for water temperature (T, ℃), solids concentration (SS, mg-L^-1), and tangential inlet water velocity (TIV, m-sec^-1): daily solids removal rate: f(z)=4.465+0.809TIV-0.375T+0.217SS (r²=0.976).