• Journal of Korean Society of societal Security
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• v.4 no.2
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• pp.73-78
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• 2011

In order to resolve the problem of change in global climate which is worsening as days go by and to preemptively cope with strengthened restriction on carbon emission, the government enacted 'Framework Act on Low Carbon Green Growth' in 2010 and selected green technology and green industry as new national growth engines. For this reason, the necessity to use the un-utilized waste heat across the whole industrial system has become an issue, and studies on and applications of recycling in the agricultural and fishery fields such as cultivation of tropical crops and flatfishes by utilizing the waste heat and thermal effluent generated by large industrial complexes including power plants are being actively carried out. In this study, we looked into the domestic and overseas examples of having utilized waste heat abandoned in the form of power plant thermal effluent, and carried out economic efficiency evaluation of sturgeon aquaculture utilizing thermal effluent of Yeongwol LNG Combined Cycle Power Plant in Gangwon-do. In this analysis, we analyzed the economic efficiency of a model business plan divided into three steps, starting from a small scale in order to minimize the investment risk and financial burden, which is then gradually expanded. The business operation period was assumed to be 10 years (2012~2021), and the NVP (Net Present Value) and economic efficiency (B/C) for the operation period (10 years) were estimated for different loan size by dividing the size of external loan by stage into 80% and 40% based on the basic statistics secured through a site survey. Through the result of analysis, we can see that reducing the size of the external loan is an important factor in securing greater economic efficiency as, while the B/C is 1.79 in the case the external loan is 80% of the total investment, it is presumed to be improved to 1.81 when the loan is 40%. As the findings of this study showed that the economic efficiency of sturgeon aquaculture utilizing thermal effluent of power plant can be secured, it is presumed that regional development project items with high added value can be derived though this, and, in addition, this study will greatly contribute to reinforcement of the capability of local governments to cope with climate change.

• Journal of Life Science
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• v.26 no.2
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• pp.190-197
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• 2016

Aflatoxin M₁ can be produced in cow’s milk when cows eat contaminated produce. Milk is a major source of food for infants and for children who have a weak level of immunity, and the detection of Aflatoxin M₁ for risk assessment is necessary in order to reduce the amount of it in milk. In this study, the Aflatoxin M₁ level was monitored for one year in raw milk samples obtained from Chungnam Province, Korea. The milk samples were divided into three categories: 1. milk samples from a standard general farm, 2. milk samples from a HACCP controlled farm, and 3. milk samples from the supply of Aflatoxin M₁ reduced fodder. The average concentrations of Aflatoxin M₁ in milk were 0.023±0.005 ug/l for the standard general farm, 0.017±0.004 ug/l for the HACCP controlled farm, and 0.013±0.003 ug/l for the supply of Aflatoxin M₁ reduction fodder. Milk collected from the supply of Aflatoxin M₁ reduction fodder had the lowest level of Aflatoxin M₁. However, when efficiency and economic aspects are considered the most effective way of reducting Aflatoxin M₁, could be taking milk from the HACCP controlled farm and implementing good feed management. Institutional support from the government, careful management of dairy farming, and a strict farm sanitation program are required in order to lower the level of Aflatoxin M₁ in milk.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.127-137
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• 2019

Recidivism prediction has been a subject of constant research by experts since the early 1970s. But it has become more important as committed crimes by recidivist steadily increase. Especially, in the 1990s, after the US and Canada adopted the 'Recidivism Risk Assessment Report' as a decisive criterion during trial and parole screening, research on recidivism prediction became more active. And in the same period, empirical studies on 'Recidivism Factors' were started even at Korea. Even though most recidivism prediction studies have so far focused on factors of recidivism or the accuracy of recidivism prediction, it is important to minimize the prediction misclassification cost, because recidivism prediction has an asymmetric error cost structure. In general, the cost of misrecognizing people who do not cause recidivism to cause recidivism is lower than the cost of incorrectly classifying people who would cause recidivism. Because the former increases only the additional monitoring costs, while the latter increases the amount of social, and economic costs. Therefore, in this paper, we propose an XGBoost(eXtream Gradient Boosting; XGB) based recidivism prediction model considering asymmetric error cost. In the first step of the model, XGB, being recognized as high performance ensemble method in the field of data mining, was applied. And the results of XGB were compared with various prediction models such as LOGIT(logistic regression analysis), DT(decision trees), ANN(artificial neural networks), and SVM(support vector machines). In the next step, the threshold is optimized to minimize the total misclassification cost, which is the weighted average of FNE(False Negative Error) and FPE(False Positive Error). To verify the usefulness of the model, the model was applied to a real recidivism prediction dataset. As a result, it was confirmed that the XGB model not only showed better prediction accuracy than other prediction models but also reduced the cost of misclassification most effectively.

• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.334-346
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• 2022

There is a lack of knowledge and information on the understanding and application of the Process Safety Management (PSM) system, recognized as a major cause of industrial accidents in small-and medium-sized workplaces. Hence, it is necessary to prepare a protocol to secure the practical and continuous levels of implementation for PSM and eliminate human errors through tracking management. However, insufficient research has been conducted on this. Therefore, this study investigated and analyzed the various violations in the administrative measures, based on the regulations announced by the Ministry of Employment and Labor, in approximately 200 small-and medium-sized PSM workplaces with fewer than 300 employees across in korea. This study intended to contribute to the prevention of major industrial accidents by developing a facility maintenance web program that removed human errors in small-and medium-sized workplaces. The major results are summarized as follows. First, It accessed the web via a QR code on a smart device to check the equipment's specification search function, cause of failure, and photos for the convenience of accessing the program, which made it possible to make requests for the it inspection and maintenance in real time. Second, it linked the identification of the targets to be changed, risk assessment, worker training, and pre-operation inspection with the program, which allowed the administrator to track all the procedures from start to finish. Third, it made it possible to predict the life of the equipment and verify its reliability based on the data accumulated through the registration of the pictures for improvements, repairs, time required, cost, etc. after the work was completed. It is suggested that these research results will be helpful in the practical and systematic operation of small-and medium-sized PSM workplaces. In addition, it can be utilized in a useful manner for the development and dissemination of a facility maintenance web program when establishing future smart factories in small-and medium-sized PSM workplaces under the direction of the government.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.623-634
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• 2022

Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.12
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• pp.1895-1904
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• 2015

Foodborne illness associated with food service establishments is an important food safety issue in Korea. In this study, foodborne pathogens (Bacillus cereus, Clostridium perfringens, Escherichia coli, pathogenic Escherichia coli, Listeria monocytogenes, Salmonella spp., Staphylococcus aureus, and Vibrio parahaemolyticus) and hygiene indicator organisms [total viable cell counts (TVC), coliforms] were analyzed for food and environmental samples from foodservice establishments at schools in Gyeonggi province. Virulence factors and antimicrobial resistance of detected foodborne pathogens were also characterized. A total of 179 samples, including food (n=66), utensil (n=68), and environmental samples (n=45), were collected from eight food service establishments at schools in Gyeonggi province. Average contamination levels of TVC for foods (including raw materials) and environmental samples were 4.7 and 4.0 log CFU/g, respectively. Average contamination levels of coliforms were 2.7 and 4.0 log CFU/g for foods and environmental swab samples, respectively. B. cereus contamination was detected in food samples with an average of 2.1 log CFU/g. E. coli was detected only in raw materials, and S. aureus was positive in raw materials as well as environmental swab samples. Other foodborne pathogens were not detected in all samples. The entire B. cereus isolates possessed at least one of the diarrheal toxin genes (hblACD, nheABC, entFM, and cytK enterotoxin gene). However, ces gene encoding emetic toxin was not detected in B. cereus isolates. S. aureus isolates (n=16) contained at least one or more of the tested enterotoxin genes, except for tst gene. For E. coli and S. aureus, 92.7% and 37.5% of the isolates were susceptible against 16 and 19 antimicrobials, respectively. The analyzed microbial hazards could provide useful information for quantitative microbial risk assessment and food safety management system to control foodborne illness outbreaks in food service establishments.