• Microbiology and Biotechnology Letters
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• v.51 no.1
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• pp.69-82
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• 2023

Nitrilases are a hydrolase group of enzymes that catalyzes nitrile compounds and produce industrially important organic acids. The current objective is to optimize nitrilase production using statistical methods assisted with artificial intelligence (AI) tool from novel nitrile degrading isolate. A nitrile hydrolyzing bacteria Bacillus subtilis AGAB-2 (GenBank Ascension number- MW857547) was isolated from industrial effluent waste through an enrichment culture technique. The culture conditions were optimized by creating an orthogonal design with 7 variables to investigate the effect of the significant factors on nitrilase activity. On the basis of obtained data, an AI-driven support vector machine was used for the fitted regression, which yielded new sets of predicted responses with zero mean error and reduced root mean square error. The results of the above global optimization were regarded as the theoretical optimal function conditions. Nitrilase activity of 9832 ± 15.3 U/ml was obtained under optimized conditions, which is a 5.3-fold increase in compared to unoptimized (1822 ± 18.42 U/ml). The statistical optimization method involving Plackett Burman Design and Response surface methodology in combination with an AI tool created a better response prediction model with a significant improvement in enzyme production.

• Journal of the Korean Society of Marine Environment & Safety
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• v.15 no.2
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• pp.91-98
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• 2009

The long-term water-quality change of Asan Bay by the influx of polluted disposal water was predicted through a simulation with an Eco-hydrodynamic model. Eco-hydrodynamic model is composed of a multi-level hydrodynamic model to simulate the water flow and an ecosystem model to simulate water quality. The water quality simulation revealed that the COD(Chemical Oxygen Demand), dissolved inorganic nitrogen(DIN) and dissolved inorganic phosphorus(DIP) are increased at 5 stations for the subsequent 6 months after the influx of the effluent. COD, DIN and DIP showed gradual decreases in concentration during the period of one to two years after the increase of last 6 months and reached steady state for next three to ten years. Concentration levels of COD, DIN, and DIP showed the increase by the ranges of $11{\sim}67%$, $10{\sim}67%$, and $0.5{\sim}7%$, respectively, which represents that the COD and DIN are the most prevalent pollutants among substances in the effluent through the sewage treatment plant. The current water quality of Asan Bay based on the observed COD, TN and TP concentrations ranks into the class II of the Korean standards for marine water quality but the water quality would deteriorate into class III in case that the disposal water by the sewage plant is discharged into the Bay.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.53-59
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• 2020

Initial response is important in marine oil spills, such as the Hebei Spirit oil spill, but it is very difficult to predict the movement of oil out of the ocean, where there are many variables. In order to solve this problem, the forecasting of oil spill has been carried out by expanding the particle prediction, which is an existing study that studies the movement of floats on the sea using the data of the float. In the ocean data format HDF5, the current and wind velocity data at a specific location were extracted using bilinear interpolation, and then the movement of numerous points was predicted by particles and the results were visualized using polygons and heat maps. In addition, we propose a spill oil particle matching algorithm to compensate for the lack of data and the difference between the spilled oil and movement. The spilled oil particle matching algorithm is an algorithm that tracks the movement of particles by granulating the appearance of surface oil spilled oil. The problem was segmented using principal component analysis and matched using genetic algorithm to the point where the variance of travel distance of effluent oil is minimized. As a result of verifying the effluent oil visualization data, it was confirmed that the particle matching algorithm using principal component analysis and genetic algorithm showed the best performance, and the mean data error was 3.2%.

• Fire Science and Engineering
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• v.29 no.2
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• pp.73-78
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• 2015

Fire in the risk management subject belongs to high risk disaster which accompanies personnel and materiel loss. So, management of disaster and safety is required to include fire prevention activities, fire risk prediction and investment of safety management expense. Combustion toxicity is required by gas toxicity test (KS F 2271), to minimize human damage. In this study, gas toxicity test were experimented with regard to urethane sample (Depth 5~25 mm) to obtain basic data. Fire effluent exposing to experimental animal were analyzed by FT-IR (Fourier transform infrared spectroscopy). Combustion toxicity index Lethal Fractional Effective Dose ($L_{FED}$) of ISO 13344 was calculated. According to the result of calculating Lethal Concentration 50% ($LC_{50}$) based on $L_{FED}$, $LC_{50}$ of urethane sample containing certain level of fire load is confirmed as $118{\sim}129g/m^3$. Through this study, applicability of this method was confirmed for fire risk assessment. This method can provide information to predict human damage by toxicity combustion gas for securing safety.

• Clean Technology
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• v.2 no.2
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• pp.100-125
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• 1996

After recycle of spent materials has been optimised, there remains a proportion of waste which must be dealt with in the most environmentally friendly manner available. For materials such as municipal waste, clinical waste, toxic waste and special wastes such as tyres, incineration is often the most appropriate technology. The study of incineration must take a process system approach covering the following aspects: ${\bullet}$ Collection and blending of waste, ${\bullet}$ The two stage combustion process, ${\bullet}$ Quenching, scrubbing and polishing of the flue gases, ${\bullet}$ Dispersion of the flue gases and disposal of any solid or liquid effluent. The design of furnaces for the burning of a bed of material is being hampered by lack of an accurate mathematical model of the process and some semi-empirical correlations have to be used at present. The prediction of the incinerator gas phase flow is in a more advanced stage of development using computational fluid dynamics (CFD) analysis, although further validation data is still required. Unfortunately, it is not possible to scale down many aspects of waste incineration and tests on full scale incinerators are essencial. Thanks to a close relationship between SUWIC and Sheffield Heat&Power Ltd., an extended research programme has been carried out ar the Bernard Road Incinerator plant in Sheffield. This plant consists of two Municipal(35 MW) and two Clinical (5MW) Waste Incinerators which provide district heating for a large part of city. The heat is distributed as hot water to commercial, domestic ( >5000 dwelling) and industrial buildings through 30km of 14" pipes plus a smaller pipe distribution system. To improve the economics, a 6 MW generator is now being added to the system.

• Journal of Korean Society of Water and Wastewater
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• v.21 no.4
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• pp.429-437
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• 2007

This study aims to develop a sulfur-using denitrification process which is possible a renovation to advanced treatment plant submerging a simple module in activated sludge aeration tank. At first, the impact factor of sulfur-using denitrification was appreciated by the batch test. Secondly, reflecting a dissolved oxygen effect of sulfur-using denitrification that was confirmed by the batch test, in a continuous nitrification/sulfur-using denitrification, high-rate nitrogen removal reaction was induced at optimum condition controlling DO concentration according to phases. Also, inside and outside of sulfur-using denitrification module was covered with microfilter and the module was considered as an alternative of clarifier. Result of batch test for sulfur-using denitrification, $NO_2{^-}N$ was lower for consumption of alkalinity and sulfur than that of $NO_3{^-}-N$. These results revealed the accordance of theoretical prediction. In continuous nitrification/sulfur-using denitrification experiment, actual wastewater was used as a influent, and influent nitrogen loading rates were increased 0.04, 0.07, 0.11, $0.14kg\;N/m^3-day$ by changing hydraulic retention times. At this time, nitrogen loading rates of packed sulfur were increased 0.23, 0.46, 0.69, $0.93kg\;N/m^3-day$. As a result, nitrification efficiency was about 100% and denitrification efficiency was 93, 81, 79, 72%. Accordingly, nitrogen removal was a high-rate. Also the module of sulfur-using denitrification covered with microfilter did not make a fouling phenomena according to increased flux. And the module was achieved effluent suspended solids of below 10 mg/L without a clarifier. In conclusion, it is possible a renovation to advanced treatment plant submerging a simple module packed sulfur in activated sludge aeration tank of traditional facilities. And the plant used the module packed sulfur is expected as a effective facilities of high-rate and the smallest.

• Journal of Environmental Impact Assessment
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• v.22 no.6
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• pp.581-589
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• 2013

Generally, Sewage Treatment Plants(STPs) are complexes systems in which a range of physical, chemical and biological processes occur. However, their performance strongly depends on the know-how acquired by the field-engineer. Recently, in order to solve this situations, various operation and management technologies based on the Instrumentation, Control and Automation(ICA) have been developed. As a economies-environmental affect point of view, this study was for the performance evaluation and assessment of results from the Smart Operation System(SOS) in full-scale STP. The SOS in STP consisted of the process monitoring module, including real-time influent prediction and effluent simulation, and the Smart Air Control(SAC) module. According to the results from field test for 2 years, the results of economical evaluation, amount of benefits and cost saving by the SOS have shown to be much higher than that of traditional operation. Nevertheless, the removal load(kg/yr) of BOD 13.3 %, COD 28.2 %, TN 44.4 % and TP 20.8 % were increased, respectively. Remarkable improvement of removal load could be achieved after the SOS was adapted. It was concerned that the SOS offer a user friendly functionalities and cost saving needed by the field-engineers. In addition, it was expected that the results of this study would supply helpful information for design and cost saving for the SOS in full-scale STP.

• Journal of Korean Society on Water Environment
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• v.28 no.6
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• pp.859-865
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• 2012

It is necessary to evaluate performances hitherto carried out in the management of Total Maximum Daily Loads (TMDLs) and to set up direction so that this system can be improved continuously in the future. This study was investigated load allocation achievement ratio, water quality goal achievement ratio and interrelation between water quality goal and load allocation for the first period (2004~2010). Load allocation achievement and BOD water quality goal achievement ratio were 50% and 73% in Guem River Basin, respectively. The main reason for excess of load allocation and shortfall of water quality goal were unfulfilled reduction plan and pollution sources increment. Therefore, it is necessary to develop enhanced pollution sources prediction method and make a list realizable reduction plan. 63% of the unit watershed was not interrelation between water quality goal and load allocation. The reason why water quality goal and load allocation had not correlation were water quality of upper unit watershed, increment of inflow quantity, effluent water quality of wastewater treatment plant affected the unit watershed, increment of inner productivity by algae, water quality deterioration during the specific period, river management flow, etc.

• Biotechnology and Bioprocess Engineering:BBE
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• v.5 no.5
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• pp.355-361
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• 2000

A recycling reactor system operated under sequential anoxic and oxic conditions for the treatment of swine wastewater has been developed, in which piggery slurry is fermentatively and aerobically treated and then part of the effluent is recycled to the pigsty. This system significantly removes offensive smells (at both the pigsty and the treatment plant), BOD and others, and may be cost effective for small-scale farms. The most dominant heterotrophic were, in order, Alcaligenes faecalis, Brevundimonas diminuta and Streptococcus sp., while lactic acid bacteria were dominantly observed in the anoxic tank. We propose a novel monitoring system for a recycling piggery slurry treatment system through the use of neural networks. In this study, we tried to model the treatment process for each tank in the system (influent, fermentation, aeration, first sedimentation and fourth sedimentation tanks) based upon the population densities of the heterotrophic and lactic acid bacteria. Principal component analysis(PCA) was first applied to identify a relationship between input and output. The input would be microbial densities and the treatment parameters, such as population densities of heterotrophic and lactic acid bacteria, suspended solids(SS), COD, NH$_4$(sup)+-N, ortho-phosphorus (o-P), and total-phosphorus (T-P). then multi-layer neural networks were employed to model the treatment process for each tank. PCA filtration of the input data as microbial densities was found to facilitate the modeling procedure for the system monitoring even with a relatively lower number of imput. Neural network independently trained for each treatment tank and their subsequent combined data analysis allowed a successful prediction of the treatment system for at least two days.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.56 no.1
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• pp.116-123
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• 2023

Flow-through aquaculture systems generate large amounts of wastewater containing compounds such as solids that can settle near aquafarms and cause eutrophication. The settled solids are often reintroduced into flow-through systems, and aquatic animals can be affected by the solids and pathogens associated with these solids. For a sustainable aquaculture operation, adequate wastewater treatment is required. Hydrocyclones are one of the most promising technologies for the removal of solids in aquaculture wastewater. In this study, a model for performance prediction of hydrocyclones was investigated under three different operating conditions: water temperature, solids concentration, and water inlet velocity. The synthetic solids solution was prepared using settled solids from abalone aquaculture farms. The daily solids removal rates of the tested hydrocyclones ranged from 0.18 to 26.0 g solids-m^-3-day^-1, and removal efficiency ranged from 5.1 to 34.4%. The inlet water velocity had the greatest effect on solids removal and hydrocyclone efficiencies. The following multiregression model equation was derived from the daily solids removal rate (g solids-m^-3-day^-1) results for water temperature (T, ℃), solids concentration (SS, mg-L^-1), and tangential inlet water velocity (TIV, m-sec^-1): daily solids removal rate: f(z)=4.465+0.809TIV-0.375T+0.217SS (r²=0.976).