• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.652-658
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• 1997

Coagulant feeding control is very important in the water treatment process. Coagulant feeding is related to the raw water quality such as turbidity, alkalinity, water temperature, pH and so on. However, since the process of chemical reaction has not been clarified so far, coagulant dosing rate has been decided by jar-test. In order to overcome the difficulty mentioned above, Fuzzy Neural Network to fuse fuzzy logic and neural network was proposed, and the scheme was applied to the automatic determination of coagulant dosing rate. This algorithm can automatically identify the if-then rules, tune the membership functions by utilizing expert's experimental data. The proposed scheme is evaluated by computer simulation and interfaced with coagulant feeder operated by magnetic flowmeter, control valve and PLC. It is shown that coagulant feeding according to real time sensing of water quality is very effective.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.1
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• pp.92-97
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• 2005

This research is to investigate the effect of the dual coagulant using inorganic coagulants($AICl3{\cdot}6H2O$) and polymer on the coagulant process. Jar-test was conducted by using Kaolin injected raw water. PDA(Photometric Dispersion Analyzer) equipment in order to analyze the size of the particles and the characteristics of the shapes. The change in the rate of sample ores' residual deposited after coagulants were also compared. According to the result derived from this experiment, the concentration of inorganic coagulant reduced 50% and the residual was lower by using dual coagulants compared to using single coagulant. However the dual coagulant required sufficient mixing time, and affected particle characteristics, with the effect of the injection order of coagulants, the simultaneous injection of inorganic coagulant and polymer showed the most effective in the particle removal.

• Fisheries and Aquatic Sciences
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• v.12 no.3
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• pp.194-202
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• 2009

Sulfated fucans are known to have both anti-thrombotic and anti-coagulant activities. In this study, the variation in platelet aggregation and anti-coagulant activities was investigated in vitro with regard to administered dose, molecular weight distribution, sulfate content, and sugar composition in two algal fucoidans from Eisenia bicyclis and Undaria pinnatifida sporophylls (Mekabu). The anti-coagulant activity largely correlated with sulfate content and with molecular weight distribution in a dose-dependent manner. However, both fucoidans demonstrated inhibitory responses to ADP-induced platelet aggregation in dose- and structure-dependent manners that contrasted with the anti-coagulant activity. Neither molecular weight distribution nor sulfate content greatly affected platelet-aggregation inhibition (PA-inhibition) by the fucoidan fractions, whereas anti-coagulant activity was sensitive to these structural factors. Interestingly, an E. bicyclis fucoidan fraction exhibited almost complete PA-inhibition at a treatment dose of 500 mg/mL while retaining weak anti-coagulant activity. In conclusion, these observations suggest that fucoidan may be a useful anti-thrombotic or anti-platelet agent in various arterial thrombotic disorders, including post-vascular intervention with controlled bleeding complications, due to its anti-coagulant modulating activity.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.3139-3143
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• 2007

The objective of this paper was to investigate the mixing characteristics of an three-stage inline coagulant mixing system experimentally. Wastewater samples of pH 8.5 and initial turbidity 1,000NTU were taken from a site of tunneling work. At the constant dosage, 0.36mL/L, of polymer as coagulant aids, the coagulation efficiency with the dosage of PAC as coagulant was about 4${\sim}$6% at 10 minutes after sampling. In the case of 2 different velocity gradient conditions, the efficiency of turbidity removal was increased about 6.5${\sim}$8% with increasing the dosage of coagulant while, the efficiency was increased about 20${\sim}$21.5% with increasing the dosage of coagulant aids. The efficiency of turbidity removal with the settling time after sampling was about 90% after 1 minute, and the efficiency was about 95% after 5 minutes.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.1
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• pp.101-107
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• 1997

Recently, as the raw water quality becomes to be polluted and the seasonal and local variation of water quality becomes to be severe, an exact control of coagulant dosing have been required in the water treat- ment plant. The amounts of coagulant is related to the raw water quality such as turbidity, alkalinity, water temperature, pH and edectrical conductivity. However the process of chemical reaction has not been clarified so far, so the dosing rate has been decided by jar-test, which is taken one or two hours. For the sake of this coagulant dosing control, fuzzy neural network to fuse fuzzy logic and neural network was proposed, and the scheme was applied to automatic determination of coagulant dosing rate. This controller can automatically identify the if-then rules and tune the membership functions by utilizing expert's cintrol data. It is shown that determination of coagulant dosing rate according to real time sensing of water quality is very effect.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.6
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• pp.724-730
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• 2015

The aim of this study was to produce Aminotosan$^{(R)}$ fertilizer using optimized chitosan coagulant from waste livestock blood. Amino-acid fertilizer was produced by pretreated livestock blood. Chitosan coagulant was aggregated with amino-acid fertilizer to produce Aminotosan$^{(R)}$. Optimized coagulation conditions were set using chitosan coagulant such as 10% citric acid and 500 ppm chitosan coagulant by analysis of CST and TTF. The efficiency of coagulation by chitosan coagulant under the optimal conditions was better than chemical coagulants. After solid/liquid separation for coagulated amino-acid fertilizer, Aminotosan$^{(R)}$ fertilizer which added eco-friendly and aesthetic functions was produced.

• Journal of the East Asian Society of Dietary Life
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• v.14 no.5
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• pp.449-456
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• 2004

Different types of coagulant and characteristics of its concentration added in the process of making milk curd were compared in this study. The pH of whey decreased when the amount of coagulant increased. The turbidity of whey was decreased when 5% of acetic acid and lemon juice were put into as coagulants. The texture of milk curd made with cow's milk and skim milk was measured the highest when acetic acid and lemon juice were added at 3, 5% of their concentration. The fracturability of milk curd made only with cow's milk decreased as the concentration of each coagulant increased. The cohesiveness was decreased as concentration of coagulant increased. The springiness was slightly changed depending on its coagulant but didn't show much of difference. The gummminess of milk curd made with cow's milk was increased when 3, 5% of coagulant was added. The result of sensory evaluation of milk curd showed that preference of milk curd wasn't depending on types of milk nor its coagulant. Also, flavor preference showed better when lemon juice was added. Preference in texture of milk curd was the highest made with cow's milk and skim milk. Preference in taste was high when 10% of lemon juice was added to skim milk and preference in its appearance showed higher when the alum was added as a coagulant to both cow's milk and skim milk than other coagulants.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.317-320
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• 1997

In the water purification plant, chemicals are injected for quick purification of raw water. It is clear that the amount of chemicals intrinsically depends on the water quality such as turbidity, temperature, pH and alkalinity etc. However, the process of chemical reaction to improve water quality by the chemicals is not yet fully clarified nor quantified. The feedback signal in the process of coagulant dosage, which should be measured (through the sensor of the plant) to compute the appropriate amount of chemicals, is also not available. Most traditional methods focus on judging the conditions of purifying reaction and determine the amounts of chemicals through manual operation of field experts or jar-test results. This paper presents the method of deriving the optimum dosing rate of coagulant, PAC(Polymerized Aluminium Chloride) for coagulant dosing process in water purification system. A neural network model is developed for coagulant dosing and purifying process. The optimum coagulant dosing rate can be derived the neural network model. Conventionally, four input variables (turbidity, temperature, pH, alkalinity of raw water) are known to be related to the process, while considering the relationships to the reaction of coagulation and flocculation. Also, the turbidity in flocculator is regarded as a new input variable. And the genetic algorithm is utilized to identify the neural network structure. The ability of the proposed scheme validated through the field test is proved to be of considerable practical value.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.282-285
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• 1996

In the water purification plant, the raw water is promptly purified by injecting chemicals. The amount of chemicals is directly related to water quality such as turbidity, temperature, pH and alkalinity. At present, however, the process of chemical reaction to the turbidity has not been clarified as yet. Since the process of coagulant dosage has no feedback signal, the amount of chemical can not be calculated from water quality data which were sensed from the plant. Accordingly, it has to be judged and determined by Jar-Test data which were made by skilled operators. In this paper, it is concerned to model and control the coagulant dosing process using jar-test results in order to predict optimum dosage of coagulant, PAC(Polymerized Aluminium Chloride). The considering relations to the reaction of coagulation and flocculation, the five independent variables(turbidity, temperature, pH, Alkalinity of the raw water, PAC feed rate) are selected out and they are put into calculation to develope a neural network model and a fuzzy model for coagulant dosing process in water purification system. These model are utilized to predict optimum coagulant dosage which can minimize the water turbidity in flocculator. The efficacy of the proposed control schemes was examined by the field test.

• Textile Coloration and Finishing
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• v.14 no.2
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• pp.40-50
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• 2002

In order to remove the pollutants effectively in the dye wastewater by chemical precipitation process, coagulation arid flocculation test were carried out using several coagulants on various reaction conditions. It was found that the Ferrous sulfate was the most effective coagulant for the removal of disperse dye(B79), and we could get the best result lot the removal of disperse dye(B56) in the aspects of TOC removal efficiency and sludge field. When the Ferrous sulfate dosage was $800mg/\ell$, the sludge settling velocity was very fast>, and the color was effectively removed in the disperse dye(B79) solution. Although the color removal was ineffective when the Alum was used as a coagulant, the sludge field was decreased in comparison with the Ferrous sulfate or the Ferric sulfate was used in the disperse dye(B56) solution. The general color removal effect for the disperse dye(B56 and B79) solutions, the Ferric sulfate was more proper coagulant than the Alum. It was showed that TOC removal was improved 5% and over by the addition of Calcium hydroxide, and $30mg/\ell$ of sludge yield was decreased(B79). When Alum or Ferric sulfate was used as a coagulant, pH condition for most effective color removal was 5 in B56 solution. In case of Ferrous sulfate as a coagulant, most effective pH condition for color removal was 9. When Ferric sulfate or Ferrous sulfate was used as a coagulant, pH condition for most effective color removal was 9 in B79 solution.