• Membrane and Water Treatment
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• v.9 no.6
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• pp.455-462
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• 2018

The measurement and monitoring of the biochemical oxygen demand (BOD) play an important role in the planning and operation of wastewater treatment plants. The most basic method for determining biochemical oxygen demand is direct measurement. However, this method is both expensive and takes a long time. A five-day period is required to determine the biochemical oxygen demand. This study has been carried out in a wastewater treatment plant in Turkey (Hurma WWTP) in order to estimate the biochemical oxygen demand a shorter time and with a lower cost. Estimation was performed using artificial neural network (ANN) method. There are three different methods in the training of artificial neural networks, respectively, multi-layered (ML-ANN), teaching learning based algorithm (TLBO-ANN) and artificial bee colony algorithm (ABC-ANN). The input flow (Q), wastewater temperature (t), pH, chemical oxygen demand (COD), suspended sediment (SS), total phosphorus (tP), total nitrogen (tN), and electrical conductivity of wastewater (EC) are used as the input parameters to estimate the BOD. The root mean squared error (RMSE) and the mean absolute error (MAE) values were used in evaluating performance criteria for each model. As a result of the general evaluation, the ML-ANN method provided the best estimation results both training and test series with 0.8924 and 0.8442 determination coefficient, respectively.

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.4
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• pp.77-84
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• 1998

Adsorption and leaching characteristics of the artificial soils produced from water and wastewater treatment sludges were examined. The batch adsorption test and TCLP leaching test were used, and constituents of interest were heavy metals and nutrients. As, Cr, Cu, Pb, and Cd were analyzed for metals, and nitrogen and phosphorus were analyzed for nutrients. All the artificial soils showed strong adsorption and low leaching for the heavy metals, which implies that the artificial soils may not be hazardous to the environment due to heavy metals and even they can be utilized effectively to remove metals in solution like mine and industrial wastewaters. This is quite promising result because in most case heavy metals are the most concern in the application of sludge product to the farmland. For the nutrients, generally, artificial soils showed high adsorption and low leaching except artificial soil from wastewater sludge produced by low temperature firing. The artificial soils produced from water treatment sludge were active in adsorbing nutrients and showed low leaching that they can be practically used to remove nutrients in advanced treatment process of the wastewater. The artificial soils produced from wastewater treatment sludge were less active in adsorbing nutrients and showed high teaching. However, they could be used usefully if applied properly to the plant growing because of their fertilizing effect. Based on the test results, overall, the artificial soils were thought to be not hazardous to the environment and they could be more useful if applied properly.

• Journal of Animal Environmental Science
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• v.6 no.2
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• pp.65-72
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• 2000

This study was conducted to investigate the effects of artificial filaments equipped in the aeration tank of aerobic·fermentation system on the removal efficiency of swine wastes which were fermented an aerobically and thus containing high nitrogen. Two aerobic fermentation system each consist4s of 4 tanks ; storage tank, 1st and 2nd aeration tank and settling tank were run before and one or three weeks after equipment of artificial filament in the aeration tanks. Total solids concentration tended to increase by aerobic fermentation in all running periods. However, decreased(P<0.05) total nitrogen concentration was shown three weeks after the equipment of artificial filament. Ammonia nitrogen concentration also largely decreased(p<0.05) in both running periods of one and three weeks after equipment of artificial filaments. These results suggest that the artificial filaments may improve the removal efficiency of nitrogen in swine wastewater containing high nitrogen during aerobic fermentation.

• Korean Journal of Environmental Agriculture
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• v.21 no.2
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• pp.122-129
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• 2002

The removal rate of heavy metals from the wastewater, the accumulation and translocation of heavy metals in plants after transplanting, and the responses of water celery growth with different wastewater treatments were investigated to determine the potential ability of green-remediation with hydroponic culture of water celery. The removal rate and translocation of Cd, Cu, Ni and Pb from different wastewater to plants were compared with cultivation periods after transplanting. The removal rate of heavy metals from wastewater was different with each treatment but increased with growing periods of water celery plants. The removal rate of Cd, Cu, Ni and Pb in Artificial solution, Artificial solution+EDTA, Munmark industrical wastewater, Jungsun minewater is ranged from 22 to 73%, from 28 to 100%, from 13 to 92% and from 41 to 100% at 6 days after transplanting, respectively. The translocations of Cd, Cu, Ni and Pb from roots to shoots in Artificial solution, Artificial solution+EDTA, Munmark industrical wastewater, Jungsun minewater are ranged from 14 to 28%. 8 to 30%. from 28 to 45% and from 2 to 15% at 12 days after transplanting, respectively. In plant growth responses, it appears to be inhibited the plant growth over all treatments excepts for Munmark industrial wastewater in these glowing periods. Therefore the water celery might play a useful role in phytoremediation to clean up wastewater contaminated with Cd, Cu, Ni or Pb.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.2
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• pp.161-173
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• 2002

Recently, absorbent biofilters, which are inexpensive and easy to manacle, have been supplied to the rural areas, but have limitations in removing the nutrients effectively. Accordingly, as an alternative plan. natural zeolites were arranged in front or at the rear of the absorbent biofilters, and their removal efficiency for nitrogen and, ultimately, their applicability to the on-site wastewater treatment system were studied. Furthermore, the same experiments were carried out on artificial zeolites, made from coal ashes at National Honam Agricultural Experiment Station, to compare natural zeolites with artificial ones. Treated wastewater through the Absorbent Biofilter showed 22.6% nitrogen removal efficiency, while 64.6% was attained when natural Zeolites were placed in front of the absorbent biofilters (Zeolite-Aerobic process). As an addition, phosphorus was also efficiently removed. On the other hand, Aerobic-Zeolite process, which arranged natural zeolites at the rear of the biofilters, did not have significantly higher nitrogen removal as compared to the treatment using only the absorbent biofilters. Furthermore, upon regeneration of the natural zeolite, the ion exchange rate was fecund to increase over 10% as compared to before regeneration. Our results show that natural zeolites, applied to the on-site wastewater treatment system through the Zeolite-Aerobic process, not only increase the removal efficiency of nutrients, but, by choosing the appropriate regeneration time, can also be cast-effective. Artificial zeolites, on the other hand, though more efficient in removing nutrients, cannot be regenerated and, therefore, are not cost-effective.

• Journal of Korean Society of Water and Wastewater
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• v.38 no.1
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• pp.1-15
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• 2024

Occurrence of process environment changes, such as influent load variances and process condition changes, can reduce treatment efficiency, increasing effluent water quality. In order to prevent exceeding effluent standards, it is necessary to manage effluent water quality based on process operation data including influent and process condition before exceeding occur. Accordingly, the development of the effluent water quality prediction system and the application of technology to wastewater treatment processes are getting attention. Therefore, in this study, through the multi-channel measuring instruments in the bio-reactor and smart multi-item water quality sensors (location in bio-reactor influent/effluent) were installed in The Seonam water recycling center #2 treatment plant series 3, it was collected water quality data centering around COD, T-N. Using the collected data, the artificial intelligence-based effluent quality prediction model was developed, and relative errors were compared with effluent TMS measurement data. Through relative error comparison, the applicability of the artificial intelligence-based effluent water quality prediction model in wastewater treatment process was reviewed.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.555-561
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• 2009

The established mathematical modeling methods have limitation to know the hydraulic characteristics at the wastewater treatment plant which are complex and nonlinear systems. So, an artificial neural network (ANN) model based on hydraulic characteristics is applied for modeling wastewater quality of a full-scale wastewater treatment plant using DNR (Daewoo nutrient removal) process. ANN was trained using data which are influents (TSS, BOD, COD, TN, TP) and effluents (COD, TN, TP) components in a year, and predicted the effluent results based on the training. To raise the efficiency of prediction, inputs of ANN are added the influent and effluent information that are in yesterday and the day before yesterday. The results of training data tend to have high accuracy between real value and predicted value, but test data tend to have lower accuracy. However, the more hydraulic characteristics are considered, the results become more accuracy.

• Journal of Korean Society of Water and Wastewater
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• v.31 no.4
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• pp.289-296
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• 2017

Pulp and paper industry produces large volumes of wastewater and residual sludge waste, resulting in many issues in relation to wastewater treatment and sludge disposal. Contaminants in pulp and paper wastewater include effluent solids, sediments, chemical oxygen demand (COD), and biological oxygen demand (BOD), which should be treated by wastewater treatment processes such as coagulation and biological treatment. However, few works have been attempted to predict the treatment efficiency of pulp and paper wastewater. Accordingly, this study presented empirical models based on experimental data in laboratory-scale coagulation tests and compared them with statistical models such as artificial neural network (ANN). Results showed that the water quality parameters such as turbidity, suspended solids, COD, and UVA can be predicted using either linear or expoential regression models. Nevertheless, the accuracies for turbidity and UVA predictions were relatively lower than those for SS and COD. On the other hand, ANN showed higher accuracies than the emprical models for all water parameters. However, it seems that two kinds of models should be used together to provide more accurate information on the treatment efficiency of pulp and paper wastewater.

• Korean Journal of Microbiology
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• v.48 no.3
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• pp.187-191
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• 2012

Two-component system (TCS)-based bacterial zinc and copper biosensors, in which green fluorescent protein (GFP) is expressed under the control of zraP and cusC promoter in ZraS/R and CusS/R TCS, were evaluated in artificial wastewater. Bacterial biosensors developed in this study efficiently expressed GFP by the recognition of $Zn^{2+}$ and $Cu^{2+}$ in artificial wastewater. Secondly, TCS-based zinc and copper removing bacteria with the peptide displayed on cell surface were examined in artificial wastewater. Zinc and copper removing bacteria expressed the peptide as a fusion protein such as OmpC-ZBP (zinc binding peptide) and OmpC-CBP (copper binding peptide) on the cell surface when sensing exogenous $Zn^{2+}$ and $Cu^{2+}$ through ZraS/R and CusS/R TCS. The recombinant cell expressing metal-adsorbing peptide could efficiently remove copper and zinc (15 and 18 mg/g dry cell weight, respectively) in artificial wastewater. Therefore, it was demonstrated that the TCS-based recombinant cell for the recognition or removal of heavy metal functions well in artificial wastewater environment.

• Resources Recycling
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• v.16 no.1 s.75
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• pp.68-72
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• 2007

The influences of reduction time, potential difference and ionic concentration flow rate have been investigated on the electrolytic recovery of silver from artificial photographic wastewater in continuous flow reactor system. As the initial concentration of silver ion and applied potential were increased, the amount of silver recovered was observed to be raised. Also, the electrolytically recovered material from artificial wastewater was proved to be pure silver based on the qualitative analyses by EPMA and XRD.