• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.2
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• pp.45-53
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• 1984

This study was conducted to investigate characteristics of nonpoint pollutant discharges and concentrations in runoff from the urban and agricultural areas in Korea. The analytical parameters used for this study were COD, BOD and SS. This study was conducted during the period from May to August 1981. Nonpoint pollutant mass loadings from the urban area were influenced by the rainfall intensity and the duration of rainfall, and etc. The concentrations of pollutants in the first flush was higher as the discharges increased. It was, however, found that the concentrations of pollutants in the heavy storm runoff were decreased due to the dilution effect. When other rainfall followed a peak rainfall, the concentrations of pollutants were lower than expected, because the first flush conveyed the most of pollutants deposited on the combined sewers. However the concentrations were increased in proportion to the increased flow when a rainfall of higher intensity than the first flush was continued. Yearly area yield rates in kg/ha were estimated to be 690.5(489.9~1,328) of COD, 319.7(226.8~614.8) of BOD, and 831.2(589.7~1,598) of SS. Pollutant sources in agricultural area were of the domestic waste water, manure composting stack, and agricultural solid wastes and etc. In the paddy field, yearly area yield rates in kg/ha were estimated to be 623.4(21.7~114) of COD, 18.65(9.53~34.5) of BOD, and 91.9(46.3~171.8) of SS. In the crop land, however, yearly rates in kg/ha were estimated to be 91.9(46.3~171.8) of COD, 23.09(11.7~42.5) of BOD, and 23.09(11.4~43.4) of SS. Pollutant sources in the feedlot area were originating from the feces of cattle, the cleaning water, the wastes spilled from manure composting stack during rain. Yearly area yield rate in kg/ha was estimated to be 3.804(2,489~6,658) of COD, 2.047(464~2,900) of BOD, and 1.149 (729~1,442) of SS. Pollutant discharges in the forest area were resulted from the organic layer like leaves and others deposited on the surface. Yearly area yield rate in kg/ha was estimated to be 9.86(5.45~18.56) of COD, 3.48(1.67~7.54) of BOD, and 4.64(9.74~10.35) of SS.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

• Tuberculosis and Respiratory Diseases
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• v.44 no.4
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• pp.822-835
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• 1997

Background : There have been many in vitro evidences that interleukin-4(IL-4) might be the most important cytokine inducing IgE synthesis from B-cells, and interferon-gamma(IFN-$\gamma$) might be a main cytokine antagonizing IL-4-mediated IgE synthesis. Recently some reports demonstrated that IFN-$\gamma$ might be used as a new therapeutic modality in some allergic diseases with high serum IgE level, such as atopic dermatitis or bronchial asthma. To evaluate the in vivo effect of IFN-$\gamma$ in bronchial asthma we tried a clinical study. Methods : Fifty bronchial asthmatics(serum IgE level over 200 IU/ml) who did not respond to inhaled or systemic corticosteroid treatment, and 17 healthy nonsmoking volunteers were included in this study. The CD 23 expressions of peripheral B-cells, the IL-4 activities of peripheral T-cells, the serum soluble CD23(sCD23) levels, and the superoxide anion(${O_2}^-$) generations by peripheral PMN were compared between bronchial asthmatics and normal subjects. The IL-4 activities of peripheral T-cells were analyzed by T-cell supernatant (T-sup)-induced CD23 expression from tonsil B-cells. In bronchial asthmatics the serum IgE levels and histamine $PC_{20}$ in addition to the above parameters were also compared before and after IFN-$\gamma$ treatment. IFN-$\gamma$ was administered subcutaneously with a weekly dose of 30,000 IU per kilogram of body weight for 4 weeks. Results : The ${O_2}^-$ generations by peripheral PMNs in bronchial asthmatics were higher than normal subjects($8.23{\pm}0.94$ vs $5.00{\pm}0.68\;nmol/1{\times}10^6$ cells, P<0.05), and significantly decreased after IFN-$\gamma$ treatment compared to initial values($3.69{\pm}0.88$ vs $8.61{\pm}1.53\;nmol/1{\times}10^6$ cells, P<0.05). CD23 expression of peripheral B-cells in bronchial asthmatics was higher than normal subjects($47.47{\pm}2.96%$, vs $31.62{\pm}1.92%$, P<0.05), but showed no significant change after IFN-$\gamma$ treatment. The serum sCD23 levels in bronchial asthmatics were slightly higher than normal subjects($191.04{\pm}23.3\;U/ml$ vs $162.85{\pm}4.85\;U/ml$), and 11(64.7%) of 17 patients showed a decreasing pattern in their serum sCD23 levels after IFN-$\gamma$ treatment. However the means of serum sCD23 levels were not different before and after IFN-$\gamma$ treatment. The IL-4 activities of peripheral T-cells in bronchial asthmatics were slightly higher than normal subjects($22.48{\pm}6.81%$ vs $18.90{\pm}2.43%$), and slightly increased after IFN-$\gamma$ treatment($27.90{\pm}2.56%$). Nine(60%) of 15 patients showed a decreasing pattern in their serum IgE levels after IFN-$\gamma$ treatment. And the levels of serum IgE were significantly decreased after IFN-$\gamma$ treatment compared to initial values ($658.67{\pm}120.84\;IU/ml$ vs $1394.32{\pm}314.42\;IU/ml$, P<0.05). Ten(83.3%) of 12 patients showed an improving pattern in bronchial hyperresponsiveness after IFN-$\gamma$ treatment, and the means of histamine $PC_{20}$ were significantly increased after IFN-$\gamma$ treatment compared to initial values ($1.22{\pm}0.29mg/ml$ vs $0.69{\pm}0.17mg/ml$, P<0.05). Conclusion : Our results suggest that IFN-$\gamma$ may be useful as well as safety in the treatment of bronchial asthmatics with high serum IgE level and that in vivo effects of IFN-$\gamma$ may be different from its in vitro effects on the regulations of IgE synthesis or the respiratory burst of PMN.