• Journal of Environmental Science International
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• v.23 no.1
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• pp.129-142
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• 2014

To treat chromaticity contained in effluents of dyeing wastewater efficiently, potent dye-degrading microorganisms were isolated from influent water, aeration- tank sludge, recycle water and settling-tank sludge located in leather and dyeing treatment plant. Six potent strains were finally isolated and identified as Comamonas testosteroni, Methylobacteriaceae bacterium, Stenotrophomonas sp., Kluyveromyces fragilis, Ascomycetes sp. and Basidiomycetes sp. When Basidiomycetes sp. was inoculated into ME medium containing basal mixed-dyes, 93% of color was removed after 8 days incubation. In the same experiment, the 1:1 mixed culture of Basidiomycetes sp. and photosynthetic bacterium exhibited 88% of color removal; however, it showed better color removal for single-color dyes. The aeration-tank and settling-tank samples revealed higher color removal (95-96%) for black dyes. The settling-tank sample also revealed higher color removal on basal mixed-dyes, which resulted in 90% color removal after 6-h incubation. From the above results, it is expected to achieve a higher color removal using the mixed microorganisms that were isolated from aeration-tank and settling-tank samples.

• Fisheries and Aquatic Sciences
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• v.27 no.9
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• pp.588-599
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• 2024

Tank color is an important environmental factor influencing aquaculture performance, but it remains poorly understood for juvenile giant trevally (Caranx ignobilis) under laboratory conditions. This study evaluated the effects of five different tank colors (white, blue, red, yellow, and dark grey) on growth performance, survival, feed utilization efficiency, body coloration, and biochemical composition of juvenile giant trevally. In a 28-day experiment, juvenile giant trevally with an initial mean length of 1.91 ± 0.03 cm and an initial weight of 0.24 ± 0.04 g were reared in tanks with different colors at a density of 1 fish/L, and each treatment was replicated three times. Results showed that fish reared in yellow tanks had higher growth rate, higher survival, and lower feed conversion ratio compared to those reared in white and blue tanks (p < 0.05). Fish reared in yellow and red tanks had significantly darker yellow body coloration and accumulated more carotenoids than those reared in white and dark grey tanks. Additionally, fish reared in yellow and red tanks had higher body protein content, whereas fish reared in white tanks had higher body moisture content (p < 0.05). These findings indicate that tank color could be an important factor in improving the rearing performance and skin pigmentation of juvenile giant trevally. Yellow tank color is suggested as a potential strategy to optimize juvenile giant trevally seed production in aquaculture.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.17 no.1
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• pp.7-11
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• 1981

The author carried out an experiment to find out the responsing patterns of filefish, Stepha nolepis cirrhifer (Temminck et Schlegel) to the color lights. The experimental tank (360LX50WX55H cm) was set up in a dark room. Six Longitudinal sections each being 60 em intervals are marked in the tank to observe the location of the fish. Water depth in the tank was kept 50 em level. Light bulbs of 20W were placed at the both ends of the tank to be projected the light horizontally into the tank. Two different colored filters were selected in combination from four' colors-red, blue, yellow, and white, and were placed in front of the light bulbs to make\ulcorner different light of color. Light intensity were controlled by use of auxiliary filters intercepted between the bulb and the filter. The fish were acclimatized in the dark for 40 minutes prior to employ in the experiment. Upon turning on the light, the number of fish in each section was counted 40 times in every 30 seconds, and the mean of the number of fish in each section was given as the gathering rate of the fish. The results obtained are as follows: 1. Color of light, to which the fish gathered abundantly was found in the named order of blue, white, green, and red. 2. The differences of gathering rate upon arbitary combined two color lights were shown significant, and the differences increased remarkably in accordance with the lapse of illuminating period.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.21 no.1
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• pp.35-40
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• 1985

The author carried out experiments to find out the response of rock bream, Oplegnathus fasciatus (TEMMINCK et SCHLEGEL) and sea bass, Epinephelus septemfasciatus (THUNBERG) to the color nettings. The experimental water tank(180L$\times$50W$\times$55Hcm) was set up n a dark room and water level was maintained 50cm high from the bottom. The tank was devided three longitudinal sections marking 60 cm interval. The illumination systems, consisted of 20 watt fluorescent lamps and filter, were suspended adove the tank. Two different color nettings selected from five colors (red, yellow, green, blue, black) were placed in each end section of the tank. Ten fish were used in each experiment and the fish were acclimatized in the dark for 60 minutes before experiment. After the light on, the number of fish in each section of the tank was counted in every 30 seconds interval for 30 minutes. The results obtained are as follows: 1. The rock bream selected the color nettings in the order of yellow, black, blue, green and red. 2. The sea bass selected the color nettings in the order of green, black, red, blue and yellow.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.16 no.1
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• pp.37-42
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• 1980

The purpose of the present study is to find the color induced maximum gathering rate and to observed'the trend of the - gathering rate by using two species of commercial fishes: rock bream, Oplegnathus fasciatus (Temminet et Schlegel) and 'grass puffer, Fugu niphobles (Jordan et Snyder). An experimental tank($360L{\times}50W{\times}55H cm$) was set up in a dark room. An illumination system was attached to the two end of tank to fix horizontal light intensity by co~bination c' one light bulb(20W) and four filters (red, blue, yellow, white) and the five regulating filters in order to fix light intensity. During the experiment water depth was maintained 50 cm lever in the tank. The tank was marked into six longitudinal sections each being 60 em long to observe the distribution of fish. The fish were acclimatized in dark condition for 40 minutes prior to the main experiment. Upon turning on the light, the number of fish in each section was counted 40 times every 30 seconds, and the gathering rates ,were obtain from the average number of fish in each secion. The color induced maximum gathering rate of rock bream appeared to be red, blue yellow and white color orderly.However, that of grass puffer appeared to be blue, white, yellow and red color orderly. Trend of the gathering rate in illumination time showed the remarkable fluctuation in the rock bream and little difference at the two color light sources. However, trend of the gathering rate in illumination time showed the little fluctuation in grass puffer and much difference at the two color light sources.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.510-513
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• 2016

Detecting of the object in image processing is substantial but it depends on the object itself and the environment. An object can be detected either by its shape or color. Color is an essential for pattern recognition and computer vision. It is an attractive feature because of its simplicity and its robustness to scale changes and to detect the positions of the object. Generally, color of an object depends on its characteristics of the perceiving eye and brain. Physically, objects can be said to have color because of the light leaving their surfaces. Here, we conducted experiment in the aquarium fish tank. Different color of fish robots are mimic the natural swim of fish. Unfortunately, in the underwater medium, the colors are modified by attenuation and difficult to identify the color for moving objects. We consider the fish motion as a moving object and coordinates are found at every instinct of the aquarium to detect the position of the fish robot using OpenCV color detection. In this paper, we proposed to identify the position of the fish robot by their color and use the position data to control the fish robot gathering in one point in the fish tank through serial communication using RF module. It was verified by the performance test of detecting the position of the fish robot.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2010.05a
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• pp.77-81
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• 2010

This study deals with the analysis of color-difference and physical property of anti-corrosion coatings using at inside of concrete tank for drinking water. Because anti-corrosion coatings are effected by chemical attack, color and physical property are changed. So in this study when epoxy resin coatings of 3 types were received chemical attack by Cl- and NaOH, we present the co-relationship between color-difference and bond strength. For this study, we used the colorimetry, which can measure the degree of color difference on surface of materials. As the results, in case of Cl-, color change is appeared, bond strength also is decreased. From this experiment, we could know that color change due to chemical aging has the deep relationship with physical performance(bond strength) materials. further researches are needed.

• Journal of Hydrogen and New Energy
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• v.23 no.6
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• pp.678-687
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• 2012

Concentration fields of solid powder in a liquid fuel were quantitatively measured by a visualization technique. The measurement system consists of a camcoder and three LCD monitors. The solid powder (glass powder) were filled in a head tank which was installed over a main mixing tank ($D{\times}H$, $310{\times}370mm$). The main mixing tank was filled with JetA1 fuel oil. With a sudden opening of the upper tank by pressurized nitrogen gas with 1.9 bar, the solid powder were poured into the JetA1 oil. An impeller type agitator was being rotated in the mixing with 700 rpm for the enhancements of mixing. Uniform visualization for the mixing flow field was made by the light from the three LCD monitors, and the visualized images were captured by the camcoder. The color images captured by the camcoder The color information of the captured images was decoded into three principle colors R, G, and B to get quantitattive relations between the concentrations of the solid powder and the colors. To get better fitting for the strong non-linearity between the concentration and the color, a neural network which has strong fitting performances was used. Analyses on the transient mixing of the solid powders were quantitatively made.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.30 no.2
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• pp.78-85
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• 1994

The author carried out an experiment to find out the response of Striped puffer. Fugu xanthoperus (Temminck et Schlegel) to the color lights. The experimental tank (300L$\times$50W$\times$50Hcm) was set up in a dark room. Six longitudinal sections with 60cm intervals are marked in the tank to observe the location of the fish. Water depth in the tank was kept 50cm level. Light bulbs of 20W at the both ends of the tank projected the light horizontally into the tank. Two different colored filters were selected from four colors of red, blue, yellow, and white, and the were placed in front of the light bulbs to make different colors of light. Light intensity was controlled by use of auxiliary filiters intercepted between the bulb and the filter. The fishes were acclimatized in the dark for 60 minutes before they were employed in the experiment. Upon turning on the light, the number of fish in each section was counted 40 times in 30 second intervals, and the mean of the number of fish in each section was counted 40 times in 30 second intervals, and the mean of the number of fish in each section was given as the gathering rate of the fish. The colors favourited by the fish was found in order of blue, yellow, white and red in the daytime, and blue, white, yellow and red at night. The difference of the average distribution on two different colors of light was 13.12%(4.10-26.55%), and the difference in the daytime(14.79%) was larger than at night (11.45%). Constantly the gathering rate of fish on illumination period was fluctuated with instability. As the gathering rate of fish on illumination period was fluctuated with instability. As the gathering rate on one color of light increased, the gathering rate on the other color of light decreased. The difference of the gathering rate on two different colors of light was comparatively distinct and the difference in the daytime was larger than at night.

• Journal of Hydrogen and New Energy
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• v.23 no.4
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• pp.364-372
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• 2012

Transient mixing states of two different fuel oils, dimethylformamide (DMF) oil and JetA1 oil, were investigated by using a color image processing and a neural network. A tank ($D{\times}H$, $310{\times}370mm$) was filled with JetA1 oil. The DMF oil was filled at a top tank, and was mixed with the JetA1 oil in the tank mixing tank via a sudden opening which was performed by nitrogen gas with 1.9 bar. An impeller was rotated with 700 rpm for mixing enhancements of the two fuel oils. To visualize the mixing state of the DMF oil with the JetA1 oil, the DMF oil was coated with Rhodamine B whose color was red. A LCD monitor was used for uniform illumination. The color changes of the DMF oil were captured by a camcoder and the images were transferred to a host computer for quantifying the information of color changes. The color images of two mixed oils were captured with the camcoder. The R, G, B color information of the captured images was used to quantify the concentration of the DMF oil. To quantify the concentration of the DMF oil in the JetA1 oil, a calibration of color-to-concentration was carried out before the main experiment was done. Transient mixing states of DMF oil with the JetA1 oil since after the sudden infiltration were quantified and characterized with the constructed visualization technique.