• 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.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.3
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• pp.209-214
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• 2001

Physiological responses of rice to the flooding time of different water turbidity (clear water, sub-muddy water, muddy water) were analyzed as photosynthesis, chlorophyll fluorescence, transpiration, and physiological recovery. Photosynthetic rate was higher as turbidity increased and decreased as flooding time was extended. Floodings of 36 hrs and 42 hrs were resulted in 25% and 50% decrease of photosynthetic rate, respectively. Transpiration rate was higher in high turbidity (increased 30%, 25%, and 20% in clear, sub-muddy, and muddy water, respectively) and in increased floodings. Fv/Fm decreased as increased turbidity and flooding time. About 20% decrease of Fv/Fm was recorded in 48 hrs and 36 hrs after flooding with clear water and sub-muddy water(including muddy water), respectively. Total nitrogen was decreased with flooding treatment. Significant decrease of total nitrogen was occurred 36 hrs after flooding with muddy water, Dry weight measured 2 weeks after flooding treatment as an indication of recovery of flooding stress didn't show significant difference with turbidity, but significantly decreased as flooding time was prolonged. About 25% and 50% decreases were found in 24 hrs and 42 hrs flooding time, respectively. furthermore, 48 hrs of flooding with sub-muddy and muddy water resulted in no physiological recovery. Photosynthetic rate was decreased 15% and 10% with clear water and muddy water(including sub-muddy water), respectively. The rate was dramatically decreased 42 hrs after flooding. Transpiration rate increased about 20% regardless of turbidity and flooding time. We found transitory decrease of photosynthetic and transpiration rate at the point of 24 hrs after flooding and right after do-flooding.

• Korean Journal of Ecology and Environment
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• v.41 no.3
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• pp.360-366
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• 2008

The spatial and temporal variations of the high turbid water by a single event of heavy rain (total 299.1 mm and daily maximum 99.4 mm) were studied in Andong Reservoir, which has hypolimnetic discharges. Turbid water entered into the reservoir, was isolated from the bottom at the midreservoir and then passed through the metalimnion as an interflow current in the lacustrine zone. Maximum turbidity was 290 NTU at 16 m depth of the midreservoir, but the initial turbidity showed about 10 NTU in the reservoir before the rainfall. Turbid water in the reservoir affected to increase the withdrawal turbidity from the 3rd day after the rainfall, the maximum turbidity was 129 NTU at 5th day after the rainfall. Turbid water that flew towards the downreservoir distributed within 5 m above the outlet gate of the intake tower, showing the maximum turbidity, and that was decreased in its thickness and concentration by discharging through the intake tower. It has taken 38 days until the turbidity in the withdrawal reduced to 30 NTU, and 87 days to reduce the turbidity to the way when it was before the rainfall, with the correlation coefficient of 0.96 and 0.97, respectively. Turbid water was withdrawn from the reservoir by entraining into the intake tower as a form of the interflow, and not be settled down to the bottom of the reservoir. Therefore, we assessed that the depth of the withdrawal was appropriately positioned in Andong Reservoir, so as to withdraw the turbid water effectively from the reservoir.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.2
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• pp.87-95
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• 2016

Turbidity is a key indicator to the user that the 'Discolored Water' phenomenon known to be caused by corrosion of the pipeline in the water supply system. 'Discolored Water' is defined as a state with a turbidity of the degree to which the user visually be able to recognize water. Therefore, this study used data mining techniques in order to estimate turbidity changes in water supply system. Decision tree analysis was applied in data mining techniques to develop estimation models for turbidity changes in the water supply system. The pH and residual chlorine dataset was used as variables of the turbidity estimation model. As a result, the case of applying both variables(pH and residual chlorine) were shown more reasonable estimation results than models only using each variable. However, the estimation model developed in this study were shown to have underestimated predictions for the peak observed values. To overcome this disadvantage, a high-pass filter method was introduced as a pretreatment of estimation model. Modified model using high-pass filter method showed more exactly predictions for the peak observed values as well as improved prediction performance than the conventional model.

• Journal of Environmental Health Sciences
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• v.27 no.4
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• pp.15-24
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• 2001

The objective of this study it to evaluate the microbial safety in rapid sand filters adapted in most drinking water treatment plants. The potential pathogens to cause water quality problems Are presumed to be Giardia and Gryptosporidium. They look like particles in view of their size. It has been reported that if the number of particles (larger than 2 ${\mu}{\textrm}{m}$ in water) is less than 100 per mL and its turbidity is below 0.1 NTU, it is considered as a safe water in terms of pathogens. In order to achieve such a good water quality. filter-aids (chemicals) were added to the inlet-channel of filter and their effectiveness was evaluated on the basis of water quality factors such as turbidity and particle counting. This study was conducted in she three steps of experiment: jar test. pilot plant test and real water treatment plant test (P plant in seoul). The experiment reult of the P water treatment showed that cationic polyamine was the most effective in the removal of particles and turbidity at the does of 0.25 mg/L. The turbidity without filer-aids showed in the range of 0.12 ~0.17 NTU during filtration and 0.14 NTU on the average. However. with addition of polyamine, the turbidity represented below(or less than) 0.1 NTU after 20 min in the start of filtration and kept 0.08 NTU on the average. On the other hand, as for number of particles, while no filter-aids led to the range of 111 ~270 per mL and 190 on the average, addition of polydmine led to 113 per mL on talc average, and kept below100 per mL after 20 min in the start of filtration.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.1
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• pp.83-91
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• 2021

The increased turbidity in rivers during flood events has various effects on water environmental management, including drinking water supply systems. Thus, prediction of turbid water is essential for water environmental management. Recently, various advanced machine learning algorithms have been increasingly used in water environmental management. Ensemble machine learning algorithms such as random forest (RF) and gradient boosting decision tree (GBDT) are some of the most popular machine learning algorithms used for water environmental management, along with deep learning algorithms such as recurrent neural networks. In this study GBDT, an ensemble machine learning algorithm, and gated recurrent unit (GRU), a recurrent neural networks algorithm, are used for model development to predict turbidity in a river. The observation frequencies of input data used for the model were 2, 4, 8, 24, 48, 120 and 168 h. The root-mean-square error-observations standard deviation ratio (RSR) of GRU and GBDT ranges between 0.182~0.766 and 0.400~0.683, respectively. Both models show similar prediction accuracy with RSR of 0.682 for GRU and 0.683 for GBDT. The GRU shows better prediction accuracy when the observation frequency is relatively short (i.e., 2, 4, and 8 h) where GBDT shows better prediction accuracy when the observation frequency is relatively long (i.e. 48, 120, 160 h). The results suggest that the characteristics of input data should be considered to develop an appropriate model to predict turbidity.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.148-149
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• 2005

In this study, among the precision decline main causes of sounding, I suggested the characteristics of sounding data acquired by echo sounder with increasing of turbidity For this, I acquired sounding data by inputting turbidity inducer artificially in artificial water tank. And then achieved regression analysis. Conclusion are as following : Sounding Capabilities can be divided into three ranges according to the turbidity : normal range, critical range and the range where data can not be obtained by an echo sounder

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.41 no.5
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• pp.44-49
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• 2009

Old newspaper was deinked using commercial cellulolytic enzymes and a surfactant complex at low alkalinity. The properties of the deinked pulp(DIP) were evaluated and the suspended solids content, cationic demand, turbidity, and chemical oxygen demand(COD) of the process water were measured. The results can summarized as follows, 1. The brightness and yield of the DIP were improved using enzymatic surfactant complex deinking. 2. The amount of foaming during deinking with the enzyme surfactant complex was higher than that with synthetic surfactant deinking. However, it was not sufficient to cause process problem. 3. The pH and turbidity of the white water from deinking with the enzyme surfactant complex were similar to those of the white water from surfactant deinking. 4. The suspended solids content, cationic demand, and COD of the white water from deinking with the enzyme surfactant complex were improved compared to those of the white water from surfactant deinking.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.888-890
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• 2009

This study presented a lab-scale apparatus for turbidity control in the lakes or reservoirs. Overall, the filamentous mat had a capture efficiency of 70~90% compared with the control group. Generally, the capture efficiency decreased with improved input turbidity flux. However, the attachment and sedimentation were thought to be the main processes for turbidity water retention and removal. Thus, the increase of hydraulic detention time in the mat zone is very important to improve the capture efficiency of the turbidity water.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.1312-1316
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• 2005

Due to the Typhoon MAEMI on Sep. of 12 in 2003, the turbidity value of IMHA Dam was recorded more than 213NTU until now. The natural zeolite located in the east coast of Korean peninsula was applied to reduce turbidity with ion exchange Process. The result of this technique, the value of turbidity was reduced less than 1NTU. Also the value of pH showed stable state compare to before and after.