• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.33-37
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• 2008

The interaction between artificial fish and aquatic surroundings and the fish's realistic locomotion are very important elements to construct virtual aquariums. In general, the artificial fish in virtual aquariums used to be created by 3D modeling tools, and was repeatedly showing the simple and constant form of swimming. This paper will analyze the sorts of biological forms of fish-swimming and the propelling and turning characteristics. Then, we propose a method of the basic swimming and turning of artificial fish to generate various and natural-looking locomotion. It is possible to make a explorable virtual aquarium more immersive by using interactive interfaces together.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.59.1-59.1
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• 2005

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1936-1937
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• 2011

본 논문에서는 수중 로봇의 추진에 대한 연구를 수행하였다. 특히, 물고기 꼬리 형태의 추진기에 대한 연구를 수행하였으며, 지느러미의 형태에 따라 발생하는 추진력의 특성에 대해서 실험을 통하여 살펴보았다. 실험 결과, 같은 동력이 가해지더라도, 추진체의 형상이 달라지면 발생하는 추력에도 차이가 남을 알 수 있었다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.421-422
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• 2013

• Journal of computational fluids engineering
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• v.16 no.2
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• pp.24-29
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• 2011

Immersed boundary lattice Boltzmann method has been applied to analyze the characteristics of the self-propelled fish motion swimming robot. The airfoil NACA0012 with caudal fin stroke model was considered to examine the characteristics. The foil in steady forward motion and a combination of steady-state harmonic deformation produces thrust through the formation of a flow downstream from the trailing edge. The harmonic motion of the foil causes unsteady shedding of vorticity from the trailing edge, while forming the vortices at the leading edge as well. The resultant thrust is developed by the pressure difference formed on the upper and lower surface of the airfoil. and the time averaged thrust coefficient increases as Re increase in the region of $Re{\leqq}700$. The suggested numerical method is suitable to develop the fish-motion model to control the swimming robot, however It would need to extend in 3D analysis to examine the higher Re and to determine the more detail mechanism of thrust production.

• Journal of Wetlands Research
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• v.20 no.2
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• pp.161-172
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• 2018

A mixed farming system that includes organic rice production and freshwater fish farming is being called into attention in Korean agricultural industry and rural areas in order to improve farm management and environmental conservation. This study was conducted to evaluate the environmental and ecological value of such mixed farming practices. Expert assessment and rapid assessment method (RAM) of wetland evaluation were employed for this study. Experts have responded that biodiversity conservation including amphibian and reptile habitat (2.39), aquatic insect habitat (2.36), Fishery habitat (2.34), vegetation diversity (2.13), avian habitat (2.05), and experience and education were the most important function of mixed farming. The wetland function evaluation conducted using modified RAM indicated that rice-fish mixed system showed improvements in most of the evaluated functions, compared to the conventional rice paddies. The overall wetland function of rice paddies in rice-fish mixed system was greatly improved as compared with the conventional rice paddies. Rice paddies are known to play an important role in biodiversity maintenance, and provide ecosystem services such as climate modulation and carbon reduction. Rice-fish mixed system of farming may not only improve various ecosystem services of rice paddies, but may increase farm income through value added fish farming, as well as promotion of social services such as education and maintenance of tradition. Additional research is needed for quantitative analysis of the values gained from the most improved wetland function when mixed farming system is actually put into practice, and to utilize the results in advertising of the organic rice, and in various sectors such as food, education and direct payment policy.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.552-560
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• 2021

Currently, the domestic aquaculture industry is pursuing smartization, but it is still proceeding with human subjective judgment in many processes in the aquaculture stage. The prerequisite for the smart aquaculture industry is to effectively grasp the condition of fish in the farm. If real-time monitoring is possible by identifying the number of fish populations, size, pathways, and speed of movement, various forms of automation such as automatic feed supply and disease determination can be carried out. In this study, we proposed an algorithm to identify the state of fish in real time using underwater video data. The fish detection performance was compared and evaluated by applying the latest deep learning-based object detection models, and an algorithm was proposed to measure fish object identification, path tracking, and moving speed in continuous image frames in the video using the fish detection results. The proposed algorithm showed 92% object detection performance (based on F1-score), and it was confirmed that it effectively tracks a large number of fish objects in real time on the actual test video. It is expected that the algorithm proposed in this paper can be effectively used in various smart farming technologies such as automatic feed feeding and fish disease prediction in the future.