• Journal of the Korea Organic Resources Recycling Association
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• v.24 no.3
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• pp.5-13
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• 2016

This study investigated the environmental and economical assessment for sewage sludge treatment options including biogasification, incineration, carbonization, drying, and solidification. For the economical feasibility the 30 plants with anaerobic digestion treatment and the 17 plants without anaerobic digestion treatment were investigated. In regarding to the environmental assessment, the air emission pollutants (SOx, NOx, etc) from incineration and carbonization plants were assessed and 1~34 % of emission limits was emitted. Drying and solidification plants emitted about 30 % of odour limits. And the rest of the pollutants were emitted either at not-detectable level or at below the limits. When the by-products from the solidification treatment was used as landfill cover materials, the unconfined compression strength could be below the limit and it could cause an unsafe condition for those passing vehicles and the possibility of the ground subsidence. There has been a maintenance difficulty due to frequent blockage and operational failure. The result of the comparison of sewage sludge treatment options showed that anaerobic digestion+incineration was the most economically feasible considering incineration and drying. For smaller treatment capacity, solidification was the most economically feasible considering carbonization and solidification and anaerobic digestion+carbonization was the most economically feasible considering carbonization and solidification.

• Journal of Ginseng Research
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• v.41 no.1
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• pp.23-30
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• 2017

Background: Ginsenoside Rg1 is a class of steroid glycoside and triterpene saponin in Panax ginseng. Many studies suggest that Rg1 suppresses adipocyte differentiation in 3T3-L1. However, the detail molecular mechanism of Rg1 on adipogenesis in 3T3-L1 is still not fully understood. Methods: 3T3-L1 preadipocyte was used to evaluate the effect of Rg1 on adipocyte development in the differentiation in a stage-dependent manner in vitro. Oil Red O staining and Nile red staining were conducted to measure intracellular lipid accumulation and superoxide production, respectively. We analyzed the protein expression using Western blot in vitro. The zebrafish model was used to investigate whether Rg1 suppresses the early stage of fat accumulation in vivo. Results: Rg1 decreased lipid accumulation in early-stage differentiation of 3T3-L1 compared with intermediate and later stages of adipocyte differentiation. Rg1 dramatically increased CAAT/enhancer binding protein (C/EBP) homologous protein-10 (CHOP10) and subsequently reduced the $C/EBP{\beta}$ transcriptional activity that prohibited the initiation of adipogenic marker expression as well as triglyceride synthase. Rg1 decreased the expression of extracellular signal-regulated kinase 1/2 and glycogen synthase kinase $3{\beta}$, which are also essential for stimulating the expression of $CEBP{\beta}$. Rg1 also reduced reactive oxygen species production because of the downregulated protein level of nicotinamide adenine dinucleotide phosphate hydrogen (NADPH) oxidase 4 (NOX4). While Rg1 increased the endogenous antioxidant enzymes, it also dramatically decreased the accumulation of lipid and triglyceride in high fat diet-induced obese zebrafish. Conclusion: We demonstrated that Rg1 suppresses early-stage differentiation via the activation of CHOP10 and attenuates fat accumulation in vivo. These results indicate that Rg1 might have the potential to reduce body fat accumulation in the early stage of obesity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Journal of Korea Port Economic Association
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• v.38 no.3
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• pp.29-51
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• 2022

The International Maritime Organization (IMO) designated the Emission Control Area (ECA) in Northern Europe to reduce the NOx and SOx emissions from ships in the coastal areas. This study used Network slack-based measure (SBM) Data Envelopment Model (DEM) and Bootstrop Truncated Regression (BTR) model to analyze the ECA's impact on ferry companies' financial performances based on the financial data from eight ferry carriers in Northern Europe, the Mediterranean and North America from 2004 to 2017. To alleviate the problem of arbitrary variable selection in DEA, the variable selection criteria proposed by Dyson et al. (2001) were applied; the size of the company was considered through the Network SBM DEA model; and the company's profit-generating process was divided into stages to measure financial performance in more detail. In addition, the BTR model was applied to derive results that minimize the bias of the data. The study found that ECA regulations did not always negatively affect the shipping companies' financial performance. Rather, a steady increase in efficiency was observed for Northern European ferry companies which were subject to the strongest regulations. For North American ferry companies, government subsidies were found to have a significant impact on efficiency, and relatively small impact on efficiency due to the ECA and oil prices. For the Mediterranean ferry companies, efficiency values have decreased since the implementation of ECA regulation despite the lowest level of regulation in the region.

• The Korea Journal of Herbology
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• v.37 no.1
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• pp.19-29
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• 2022

Objectives : Although the pharmacological effects of anti-inflammatory and antioxidant action of Atractylodes macrocephala Koidzumi water extract (AM) have been proven from many studies, reports on the antioxidant effect of AM on ulcerative colitis (UC) are scarce. Therefore, we aimed at evaluating the anti-oxidant effect of AM on the DSS-induced UC model. Methods : To induce ulcerative colitis, 8-week-old male Balb/c mice received 5% DSS in drinking water for 1 week. After 1 week of adaptation, mice were divided into four groups (n=8 each) for use as normal (Normal), DSS Control (Control), DSS + AM 100 mg/kg (AM100)-treatment, DSS + AM 200 mg/kg (AM200)-treatment. After 1 week of the experiment, the animals were sacrificed, and the extracted colon tissue was analyzed for protein through western blot. Results : As a result of confirming the macroscopic changes in colon tissues to confirm the therapeutic effects of AM, the decrease in colon length was suppressed in the AM treatment group compared to the control group. In addition, as a result of biochemical analysis, AM administration significantly reduced serum glutamic oxalacetic transaminase, glutamic pyruvate transaminase levels and tissue malondialdehyde levels. As a result of confirming the protein expression level through western blot, AM administration significantly decreased the expression of NADPH-related proteins such as NOX2, p22^phox, and iNOS, but significantly increased the expression of SOD, catalase, and GPx-1/2. Conclusions : AM may improve DSS-induced UC in mice by modulating NADPH and antioxidant-related proteins. In conclusion, AM showed an antioxidant effect through the improvement of oxidative stress on UC.

• Journal of Industrial Convergence
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• v.21 no.7
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• pp.19-27
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• 2023

As the secondary battery market expands, the process of producing laterite ore using the rotary kiln and electric furnace method is expanding worldwide. As ESG management expands, the management of air pollutants such as nitrogen oxides in exhaust gases is strengthened. The rotary kiln, one of the main facilities of the pyrometallurgy process, is a facility for drying and preliminary reduction of ore, and it generate nitrogen oxides, thus prediction of nitrogen oxide is important. In this study, LSTM for regression prediction and LightGBM for classification prediction were used to predict and then model optimization was performed using AutoML. When applying LSTM, the predicted value after 5 minutes was 0.86, MAE 5.13ppm, and after 40 minutes, the predicted value was 0.38 and MAE 10.84ppm. As a result of applying LightGBM for classification prediction, the test accuracy rose from 0.75 after 5 minutes to 0.61 after 40 minutes, to a level that can be used for actual operation, and as a result of model optimization through AutoML, the accuracy of the prediction after 5 minutes improved from 0.75 to 0.80 and from 0.61 to 0.70. Through this study, nitrogen oxide prediction values can be applied to actual operations to contribute to compliance with air pollutant emission regulations and ESG management.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.48-59
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• 2023

Ground-level ozone affects human health and plant growth. Ozone is produced by chemical reactions between oxides of nitrogen (NOx) and volatile organic compounds (VOCs) from anthropogenic and biogenic sources. In this study, two different land cover and emission factor datasets were input to the MEGAN v2.1 emission model to examine how these parameters contribute to the biogenic emissions and ozone production. Four input sensitivity scenarios (A, B, C and D) were generated from land cover and vegetation emission factors combination. The effects of BVOCs emissions by scenario were also investigated. From air quality modeling result using CAMx, maximum 1 hour ozone concentrations were estimated 62 ppb, 60 ppb, 68 ppb, 65 ppb, 55 ppb for scenarios A, B, C, D and E, respectively. For maximum 8 hour ozone concentration, 57 ppb, 56 ppb, 63 ppb, 60 ppb, and 53 ppb were estimated by scenario. The minimum difference by land cover was up to 25 ppb and by emission factor that was up to 35 ppb. From the modeling performance evaluation using ground ozone measurement over the six regions (East Seoul, West Seoul, Incheon, Namyangju, Wonju, and Daegu), the model performed well in terms of the correlation coefficient (0.6 to 0.82). For the 4 urban regions (East Seoul, West Seoul, Incheon, and Namyangju), ozone simulations were not quite sensitive to the change of BVOC emissions. For rural regions (Wonju and Daegu) , however, BVOC emission affected ozone concentration much more than previously mentioned regions, especially in case of scenario C. This implies the importance of biogenic emissions on ozone production over the sub-urban to rural regions.