• Journal of the Korea Organic Resources Recycling Association
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• v.31 no.1
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• pp.69-84
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• 2023

Despite the continuous installation and regular inspection of waste treatment facilities, complaints about excessive incineration and illegal dumping stench continue to occur at on-site treatment facilities. In addition, field surveys were conducted on the waste treatment facilities currently in operation (6 type) to understand the waste treatment process for each field, to grasp the main operating factors applied to the inspection. In addition, we calculated the material·energy balance for each main process and confirmed the proper operation of the waste disposal facility. As a result of the site survey, in the case of heat treatment facilities such as incineration, cement kilns, and incineration heat recovery facilities, the main factors are maintenance of the temperature of the incinerator required for incineration and treatment of the generated air pollutants, and in the case of landfill facilities Retaining wall stability, closed landfill leachate and emission control emerged as major factors. In the case of sterilization and crushing facilities, the most important factor is whether or not sterilization is possible (apobacterium inspection).In the case of food distribution waste treatment facilities, retention time and odor control during fermentation (digestion, decomposed) are major factors. Calculation results of material balance and energy resin for each waste treatment facility In the case of incineration facilities, it was confirmed that the amount of flooring materials generated is about 14 % and the amount of scattering materials is about 3 % of the amount of waste input, and that the facility is being operated properly. In addition, among foodwaste facilities, in the case of an anaerobic digestion facility, the amount of biogas generated relative to the amount of inflow is about 17 %, and the biogas conversion efficiency is about 81 %, in the case of composting facility, about 11 % composting of the inflow waste was produced, and it was comfirmend that all were properly operated. As a result, in order to improve the inspection method for waste treatment facilities, it is necessary not only to accumulate quantitative standards for detailed inspection methods, but also to collect operational data for one year at the time of regular inspections of each facility, Grasping the flow and judging whether or not the treatment facility is properly operated. It is then determined that the operation and management efficiency of the treatment facility will increase.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.2
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• pp.317-324
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• 2012

To reduce non-point source pollutants in Juam Lake eco-wetlands, purification efficiencies of pollutants were investigated at three different systems. The constructed wetlands (CWs) consisted of A system, B system and C system. A system consisted of $1^{st}$ free water surface (FWS) CW, $2^{nd}$ FWS CW, $3^{rd}$ FWS CW, $4^{th}$ subsurface flow (SSF) CW and $5^{th}$ SSF CW. B system consisted of $1^{st}$ FWS CW, $2^{nd}$ FWS CW, $3^{rd}$ FWS CW, $4^{th}$ FWS CW and $5^{th}$ SSF CW. C system consisted of $1^{st}$ FWS CW, $2^{nd}$ FWS CW, $3^{rd}$ FWS CW, $4^{th}$ FWS CW and $5^{th}$ SSF CW. The concentrations of BOD, COD, SS, T-N and T-P in inflow ranged 0.20 ~ 0.91, 1.24 ~ 8.00, 0.60 ~ 8.60, 0.04 ~ 2.50 and $0.001{\sim}0.685mg\;L^{-1}$ from March to October in 2011, respectively. Removal rates of BOD, SS, T-N and T-P were high in Autumn, Spring, Spring and Summer, respectively. In A system, $1^{st}$ FWS CW, $2^{nd}$ FWS CW and $3^{rd}$ FWS CW were dominated by Leersia oryzoides. In B system, $1^{st}$ FWS CW, $3^{rd}$ FWS CW and $4^{th}$ FWS CW were dominated by Leersia oryzoides. In C system, $2^{nd}$ FWS CW and $3^{rd}$ FWS CW were dominated by Nymphaea teragona.

• Journal of the Korea Organic Resources Recycling Association
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• v.16 no.2
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• pp.74-80
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• 2008

Removal of nitrogen compound under nitrification related with denitrification by biofilm which developed on the porous media was investigated. With the investigation of $NH_4-N$ nitrification and autotrophic denitrification supplied with sulfur media as electron donor, conclusions were retrieved as follows. When $F/M_N$ ratio of $NH_4-N$ was increased from $0.0062-0.034gNH_4-N/g\;MLVSS{\cdot}day$ by the change of influent concentration and HRT the nitrification rate decreased as the increase of loading rate. Also under the same conditions of $F/M_N$ ratio, the alkalinity consumption rate of operation was higher at 8 hours of HRT than at 6 hours of HRT. Accordingly the influent loading rate variation by detention time with influent flow influenced more on the nitrification efficiency than the influent loading rate variation by the influent concentration did. Denitrification rate with various EBCT(Empty Bed Contact Time) showed average 25% at 8.4hrs of EBCT but sharply decreased average 5% at 4.6hrs of EBCT, so the operation would be more effective at above 8.4hrs of EBCT. Also denitrification rate was known to be adversely increased as $NO_3-N$ loading rate per unit volume of sulfur-media was decreased within the range of $0.5{\sim}2.0kgNO_3-N/m^3{\cdot}day$.

• Clean Technology
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• v.12 no.2
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• pp.67-77
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• 2006

A simple dual sludge process, called as $KNR^{(R)}$ (Kwon's Nutrient Removal) system, was developed for small sewage treatment. It is a hybrid system that consists of an UMBR (Upflow multi-layer bioreactor) as anaerobic and anoxic reactor with suspended denitrifier and a post aerobic biofilm reactor, filled with pellet-like media, with attached nitrifier. To evaluate the stability and performance of this system for small sewage treatment, the pilot-scale $KNR^{(R)}$ plant with a treatment capacity of $50m^3/d$ was practically applied to the actual sewage treatment plant, which was under retrofit construction during pilot plant operation, with a capacity of $50m^3/d$ in a small rural community. The HRTs of a UMBR and a post aerobic biofilm reactor were about 4.7 h and 7.2 h, respectively. The temperature in the reactor varied from $18.1^{\circ}C$ to $28.1^{\circ}C$. The pilot plant showed stable performance even though the pilot plant had been the severe fluctuation of influent flow rate and BOD/N ratio. During a whole period of this study, average concentrations of $COD_{cr}$, $COD_{Mn}$, $BOD_5$, TN, and TP in the final effluent obtained from this system were 11.0 mg/L, 8.8 mg/L, 4.2 mg/L, 3.5 mg/L, 9.8 mg/L, and 0.87/0.17 mg/L (with/without poly aluminium chloride(PAC)), which corresponded to a removal efficiency of 95.3%, 87.6%, 96.3%, 96.5%, 68.2%, and 55.4/90.3%, respectively. Excess sludge production rates were $0.026kg-DS/m^3$-sewage and 0.220 kg-DS/kg-BOD lower 1.9 to 3.8 times than those in activated sludge based system such as $A_2O$ and Bardenpho.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.1
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• pp.26-46
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• 2020

An irrigated-maize agroecosystem is viewed as an open thermodynamic system upon which solar radiation impresses a large gradient that moves the system away from equilibrium. Following the imperative of the second law of thermodynamics, such agroecosystem resists and reduces the externally applied gradient by using all means of this nature-human coupled system acting together as a nonequilibrium dissipative process. The ultimate purpose of our study is to test this hypothesis by examining the energetics of agroecosystem growth and development. As a first step toward this test, we employed the eddy covariance flux data from 2003 to 2014 at the AmeriFlux NE1 irrigated-maize site at Mead, Nebraska, USA, and analyzed the energetics of this agroecosystem by scrutinizing its radiation, energy and entropy exchange. Our results showed: (1) more energy capture during growing season than non-growing season, and increasing energy capture through growing season until senescence; (2) more energy flow activity within and through the system, providing greater potential for degradation; (3) higher efficiency in terms of carbon uptake and water use through growing season until senescence; and (4) the resulting energy degradation occurred at the expense of increasing net entropy accumulation within the system as well as net entropy transfer out to the surrounding environment. Under the drought conditions in 2012, the increased entropy production within the system was accompanied by the enhanced entropy transfer out of the system, resulting in insignificant net entropy change. Drought mitigation with more frequent irrigation shifted the main route of entropy transfer from sensible to latent heat fluxes, yielding the production and carbon uptake exceeding the 12-year mean values at the cost of less efficient use of water and light.

• Korean Journal of Environmental Agriculture
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• v.36 no.3
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• pp.193-200
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• 2017

BACKGROUND: Plant growth under smart greenhouse (that is plant factory system) conditions of an artificial light type is significantly depending on the artificial light sources such as a fluorescent lamps or Light-Emitting Diodes (LEDs) with specific spectral wavelengths regardless of the outside environmental changes. In this experiment, characteristics on the growth and compound synthesis of kale seedlings affected by light qualities and intensities provided by LEDs were mentioned. METHODS AND RESULTS: The kale seedlings which developed 3~4 true leaves were exposed by fluorescent lamps or LEDs lights of red (R), blue+white (BW), blue+red (BR) with 50 (L) or $100(H){\mu}mol/m^2/s^1$ photosynthetic photon flux (PPF) under hydroponic culture system of deep flow technique for 50 days. Shoot fresh weight increased under the RH, BWH, and BRH treatments with higher PPF. Shoot elongation of the seedlings decreased, and polyphenol synthesis promoted by the higher light intensity conditions. Sugar synthesis in the leaves was above 2 times greater under the RH treatment of monochromic red light quality with $100{\mu}mol/m^2/s^1\;PPF$ than $50{\mu}mol/m^2/s^1\;PPF$. CONCLUSION: The results show that the control of light quality and intensity in the smart greenhouse conditions with artificial lights significantly affects the growth and compound synthesis in the fresh kale leaves with higher culture efficiency compared to the conventional soil culture under greenhouse or field conditions. Researches on the optimum light intensities of the LEDs with special spectral wavelengths are necessary for maximum growth and metabolism in the seedlings.

• Journal of the Korean Society of Radiology
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• v.11 no.5
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• pp.297-302
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• 2017

Recently, building materials and air purification filters with eco-friendly charcoal are actively studying to reduce the concentration of radon gas in indoor air. In this study, radon reduction performance was assessed by designing and producing new panel-type activated carbon filter that can be handled more efficiently than conventional charcoal filters, which can reduce radon gas. For the fabrication of our panel-type activated carbon filter, first the pressed molding product after mixing activated carbon powder and polyurethane. Then, through diamond cutting, the activated carbon filter of 2 mm, 4 mm and 6 mm thickness were fabricated. To investigate the physical characteristics of the fabricated activated carbon filter, a surface area and flexural strength measurement was performed. In addition, to evaluate the reduction performance of radon gas in indoor, the radon concentration of before and after the filter passes from a constant amount of air flow using three acrylic chambers was measured, respectively. As a result, the surface area of the fabricated activated carbon was approximately $1,008m^2/g$ showing similar value to conventional products. Also, the flexural load was found to have three times higher value than the gypsum board with 435 N. Finally, the radon reduction efficiency from indoor gas improved as the thickness of the activated carbon increases, resulting in an excellent radon removal rate of more than 90 % in the 6 mm thick filter. From the experimental results, the panel-type activated carbon is considered to be available as an eco-friendly building material to reduce radon gas in an enclosed indoor environment.

• Journal of Venture Innovation
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• v.2 no.2
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• pp.95-115
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• 2019

In the context of today's business environment, not only is the nation or company's credit rating considered very important in our recent society, but it is also becoming important in international transactions. Likewise, at this point of time when the importance and reliability of credit evaluation are becoming important at home and abroad, this study analyzes financial ratios related to corporate profitability, safety, activity, financial growth, and profit growth to study the impact of financial indicators on enterprise value and corporate taxes on credit evaluation. To proceed with this, the financial ratio of 465 companies of KOSPI securities listed in 2017 was calculated and the impact of enterprise value and corporate taxes on credit evaluation was analyzed. Especially, this further study tried to derive a reliable and consistent conclusion by analyzing the financial data of KOSPI securities listed companies for eight years from 2011, which is the first year of K-IFRS introduction, to 2018. Research has shown that the significance levels among variables that show the profitability, safety, activity, financial growth, and profit growth of each financial ratio were significant at the 99% level, except for the profit growth. Validation of the research hypothesis found that while the profitability of KOSPI-listed companies significantly affects corporate value and income tax, indicators such as safety ratio and growth ratio do not significantly affect corporate value and income tax. Activity ratio resulted in significant effects on the value of enterprise value but not significant impacts on income taxes. In addition, it was found that the enterprise value has a significant effect on the company's credit and corporate income taxes, and that corporate income taxes also have a significant effect on the corporate credit evaluation, and this also shows that there is a mediating function of corporate tax. And as a result of further study, when looking at the financial ratio for eight years from 2011 to 2018, it was found that two variables, KARA and LTAX, are significant at a 1% significant level to KISC, whereas LEVE variables is not significant to KISC. The limitation of this study is that credit rating score and financial score cannot be said to be reliable indicators that investors in the capital market can normally obtain, compared to ranking criteria for corporate bonds or corporate bills directly related to capital procurement costs of enterprise. Above all, it is necessary to develop credit rating score and financial score reflecting financial indicators such as business cash flow or net assets market value and non-financial indicators such as industry growth potential or production efficiency.

• Journal of Korean Society of Forest Science
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• v.90 no.2
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• pp.197-209
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• 2001

TOPMODEL, semi-distributed hydrological model, is frequently applied to predict the amount of discharge, main flow pathways and water quality in a forested catchment, especially in a spatial dimension. TOPMODEL is a kind of conceptual model, not physical one. The main concept of TOPMODEL is constituted by the topographic index and soil transmissivity. Two components can be used for predicting the surface and subsurface contributing area. This study is conducted for the validation of applicability of TOPMODEL at small forested catchments in Korea. The experimental area is located at Gwangneung forest operated by Korea Forest Research Institute, Gyeonggi-do near Seoul metropolitan. Two study catchments in this area have been working since 1979 ; one is the natural mature deciduous forest(22.0 ha) about 80 years old and the other is the planted young coniferous forest(13.6 ha) about 22 years old. The data collected during the two events in July 1995 and June 2000 at the mature deciduous forest and the three events in July 1995 and 1999, August 2000 at the young coniferous forest were used as the observed data set, respectively. The topographic index was calculated using $10m{\times}10m$ resolution raster digital elevation map(DEM). The distribution of the topographic index ranged from 2.6 to 11.1 at the deciduous and 2.7 to 16.0 at the coniferous catchment. The result of the optimization using the forecasting efficiency as the objective function showed that the model parameter, m and the mean catchment value of surface saturated transmissivity, $lnT_0$ had a high sensitivity. The values of the optimized parameters for m and InT_0 were 0.034 and 0.038; 8.672 and 9.475 at the deciduous and 0.031, 0.032 and 0.033; 5.969, 7.129 and 7.575 at the coniferous catchment, respectively. The forecasting efficiencies resulted from the simulation using the optimized parameter were comparatively high ; 0.958 and 0.909 at the deciduous and 0.825, 0.922 and 0.961 at the coniferous catchment. The observed and simulated hyeto-hydrograph shoed that the time of lag to peak coincided well. Though the total runoff and peakflow of some events showed a discrepancy between the observed and simulated output, TOPMODEL could overall predict a hydrologic output at the estimation error less than 10 %. Therefore, TOPMODEL is useful tool for the prediction of runoff at an ungaged forested catchment in Korea.