• Journal of fish pathology
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• v.35 no.2
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• pp.205-214
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• 2022

In recent years, there have been many studies investigating changes in animal behavior using video tracking technology to track motion. However, there have been very few studies and results on changes in the behavior of fish infected with a pathogen. Therefore, the present study attempted to analyze the behavior of angelfish (Pterophyllum scalare) infected with bacterial pathogens using video tracking. Two cameras were placed in front of the water tank to obtain behavior data, and tracking was performed for three days until the day of death. Data such as average speed, changes in speed, the locations of the fish in the tank, and fractal dimension were statistically analyzed based on the fish speed and location in the tank of the fish. For bacterial infection, an individual angelfish was intraperitoneally injected with approximately 10⁶ CFU ml^-1 of Aeromonas hydrophila or Edwardsiella piscicida. The experiment was carried out five times for each group. Fish infected with the bacterial pathogens showed a tendency to increase in speed and to spend more time in the upper part of the tank one or two days before death. On the day the fish died, the average speed, changes in speed, and the fractal dimension value were significantly lower than the corresponding values in the control group, and the fish also remained in the lower part of the tank. Our results indicated that behavioral changes in fish could be successfully detected earlier than death using video tracking technology, and that this method presents potential for disease monitoring in aquaculture.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.375-382
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• 2016

This paper realizes control of the motion of a swimming robot fish in order to implement an underwater robot fish aquarium. And it implements positional control of a two-axis trajectory path of the robot fish in the aquarium. The performance of the robot was verified though certified field tests. It provided excellent performance in driving force, durability, and water resistance in experimental results. It can control robot motion, that is, it recognizes an object by using an optical flow object-detecting algorithm, which uses a video camera rather than image-detecting sensors inside the robot fish. It is possible to find the robot's position and control the motion of the robot fish using a radio frequency (RF) modem controlled via personal computer. This paper proposes realization of robot fish motion-tracking control using the optical flow object-detecting algorithm. It was verified via performance tests of lead-lag action control of robot fish in the aquarium.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.870-875
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• 2008

The main objective of this paper is to control a trajectory tracking of the fish-mimetic robot by CPG (Central Pattern Generator), which is biological approach. CPG is biological neural networks that generate rhythmic movements for locomotion of animals, such as walking, running, swimming and flying. Animals show marvelous ability of autonomous dynamic adaptation for an unsteady fluid dynamic environment or various environments. So, we propose the 3-DOF CPG controller to track the trajectory of the fish robot in plane motion. The conformity of the proposed control algorithm is validated by simulation for a fish robot model, which is made by a commercial dynamic package.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.46 no.3
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• pp.273-281
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• 2013

The movement patterns of fish aggregations swimming freely near artificial reefs on August 24, 2006, at Suyeong Man, Busan, Korea, were acoustically investigated and analyzed. Acoustic surveys were conducted using a 70kHz split-beam echo sounder, 330 kHz side-scan sonar and a 310 kHz imaging sonar. Algorithms for tracking the movement of fish aggregations swimming in response to artificial reefs were developed. The travel direction and the swimming speed for two aggregations of fish were estimated from the trajectory orientations of echo responses recorded by the imaging sonar.The first group was floating just above the reef structure, while remaining in the midwater column, and the second group was swimming through and around artificial reefs near the seabed. The mean swimming speed was estimated to be 0.40 m/s for the midwater fish aggregation and 0.17 m/s for the bottom aggregation close to artificial reefs. These results suggest that the swimming behavior of fish aggregations passing close to artificial reefs near the seabed displayed a slower moving pattern than fish floating just above the reef structure in the midwater column.

• Fisheries and Aquatic Sciences
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• v.14 no.3
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• pp.218-225
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• 2011

Dual frequency identification sonar (DIDSON) is an imaging sonar that has been used for numerous fisheries investigations in a diverse range of freshwater and marine environments. The main purpose of DIDSON is fish counting, fish sizing, and fish behavioral studies. DIDSON records video-quality data, so processing power for handling the vast amount of data with high speed is a priority. Therefore, a semiautomated analysis of DIDSON data for fish counting, sizing, and fish behavior in Echoview (fisheries acoustic data analysis software) was accomplished using testing data collected on the Rakaia River, New Zealand. Using this data, the methods and algorithms for background noise subtraction, image smoothing, target (fish) detection, and conversion to single targets were precisely illustrated. Verification by visualization identified the resulting targets. As a result, not only fish counts but also fish sizing information such as length, thickness, perimeter, compactness, and orientation were obtained. The alpha-beta fish tracking algorithm was employed to extract the speed, change in depth, and the distributed depth relating to fish behavior. Tail-beat pattern was depicted using the maximum intensity of all beams. This methodology can be used as a template and applied to data from BlueView two-dimensional imaging sonar.

• Fisheries and Aquatic Sciences
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• v.26 no.12
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• pp.698-707
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• 2023

Fish are an essential resource in human society, and while ecological research on them is challenging, it is absolutely necessary. Recent technologies enabled researchers to monitor underwater fish behavior. Acoustic signals, satellite-mediated location estimation, and light-based geolocation are powerful tools for tracking fish movements from freshwater to deep-sea habitats. These tools allow us to track various fish species and elucidate their ecology. Furthermore, based on these technologies, we can develop fisheries management plans and enhance aquaculture productivity. In this review, we also discuss challenges in improving current technologies and provide future recommendations for fish bio-logging studies.

• Environmental Analysis Health and Toxicology
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• v.14 no.4
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• pp.217-222
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• 1999

Changes in certain fish behaviors are known to be very sensitive indicators of sublethal exposure to environmental contaminants. Therefore, behavioral toxicity tests, if properly designed, can be very useful to assess the influence of hazardous chemicals on fish. However, quantitative analysis of xenobiotic-mediated changes in locomotor behavior in fishes are rare, due mainly to the methodological difficulties. In general, fish movement has been known to be hypertrophic or hypotrophic according to the chemicals. As a study of fish behavioral toxicities, we qualified the swimming movement of Oryzias latipes using computer-automated video tracking system. Oryzias latipes was exposed to cadmium of 128 mg/L for 1 hour in a limited aquaria, then the total swimming distance, the average swimming velocity, the histogram of turning angles, and the turning frequency were analyzed. Fish treated with cadmium showed decreased swimming activities, decreased velocity, and decreased turning frequency, which means hypotrophic activity. From these results, the computer-automated video tracking system of this study seems to be a good tool for the evaluation of the potential ecotoxicological studies.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.6
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• pp.965-973
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• 2021

The behavior of angelfish Pterophyllum scalare exposed to low and high temperatures was monitored by video tracking, and information such as the initial speed, changes in speed, and locations of the fish in the tank were analyzed. The water temperature was raised from 26℃ to 36℃ or lowered from 26℃ to 16℃ for 4 h. The control group was maintained at 26℃ for 8 h. The experiment was repeated five times for each group. Machine learning analysis comprising a long short-term memory model was used to train and test the behavioral data (80 s) after pre-processing. Results showed that when the water temperature changed to 36℃ or 16℃, the average speed, changes in speed and fractal dimension value were significantly lower than those in the control group. Machine learning analysis revealed that the accuracy of 80-s video footage data was 87.4%. The machine learning used in this study could distinguish between the optimal temperature group and changing temperature groups with specificity and sensitivity percentages of 86.9% and 87.4%, respectively. Therefore, video tracking technology can be used to effectively analyze fish behavior. In addition, it can be used as an early warning system for fish health in aquariums and fish farms.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.25 no.2
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• pp.54-60
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• 1989

This paper described on the tracking of an individual fish at the fishing ground of set net by use of a small ultrasonic fish tag. The apparatuses used were composed with a tag, three receivers and two time-interval counter oscilloscope. A pulsed ultrasonic transmitter tag fitted to back of a dorsal fin of a yellowtail specimen, Seriola quinqueradidta TEMMINCK et SCHLEGEL is tracked by measuring differences in the time of arrival of the acoustic pulses at an arrangement of three receivers in the freeding tank. The successive positions of the fish were calculated from the differences in the received time of the signals. A fish carying the tag was tracked in the fishing ground of set net by use of the hydrophone and Loran-C. The results of the tests showed that this method gave good positional information to track the movement of an individual fish in the fishing ground of set net.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.906-912
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• 2014

The study of fish robot is a main subject that are related with the propulsive force comparison using a varying amplitude and frequency for body and tail motion trajectory, and the quick turn using a proper trajectory function. In this study, when a fish robot thrusts forward, feedback control is difficult to apply for a fish robot, because body and tail joints as a sine wave are rolled. Therefore, we detect the virtual position based on the path of the fish robot, define the angle errors using the detected position and the look-ahead point on the given path, and design a controller to track given path. We have found that the proposed method is useful through the computer simulations.