• 유체기계공업학회:학술대회논문집
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• 1998.02a
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• pp.186-189
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• 1998

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2002.10a
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• pp.141-144
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• 2002

• 한국상하수도협회지
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• s.6
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• pp.96-100
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• 2004

• Magazine of the Korean Society of Agricultural Engineers
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• v.56 no.2
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• pp.64-73
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• 2014

• Proceedings of the Korea Water Resources Association Conference
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• 2002.02a
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• pp.59-80
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• 2002

• Proceedings of the Korean Society of Life Science Conference
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• 2003.10a
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• pp.146-146
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• 2003

• Proceedings of the Korean DIstribution Association Conference
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• 2005.11a
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• pp.361-383
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• 2005

• Journal of Korea Water Resources Association
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• v.44 no.7
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• pp.523-536
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• 2011

The objective of this study is to develop the data driven model for the flood forecasting that are improved the problems of the existing hydrological model for flood forecasting in medium and small streams. Neuro-Fuzzy flood forecasting model which linked the Takagi-Sugeno fuzzy inference theory with neural network, that can forecast flood only by using the rainfall and flood level and discharge data without using lots of physical data that are necessary in existing hydrological rainfall-runoff model is established. The accuracy of flood forecasting using this model is determined by temporal distribution and number of used rainfall and water level as input data. So first of all, the various combinations of input data were constructed by using rainfall and water level to select optimal input data combination for applying Neuro-Fuzzy flood forecasting model. The forecasting results of each combination are compared and optimal input data combination for real-time flood forecasting is determined.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.101-108
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• 2003

When drivers encounter multiple available routes, they may evaluate the utility of each route. Two important factors in the evaluation are travel time and travel cost. Without hewing the current travel time of each route, drivers' decisions are not necessarily optimum. It is called 'transparency issue' that drivers are blinded to choose the optimum route among the others because of the limited travel time information. As a result of this, competing route travel times tend to fluctuate. This case study to utilize the data of Namsan traffic information system confirms that this travel time fluctuation can be lessened as real time traffic information is provided.

• Food Science and Preservation
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• v.23 no.6
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• pp.759-764
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• 2016

This purpose of this study was to determine the best enrichment medium for rejuvenating and recovering Salmonella placed in cold temperature prior to the employment of the gold biosensor combined with a light microscopic imaging system. A mixture of nalidixic-resistant Salmonella Typhimurium and Enteritidis were inoculated onto chicken (1,000 CFU/chicken). After cold injury at $4^{\circ}C$ for 24 hr, Salmonella on chicken was enriched for 6 hr with six non-selective media including buffered peptone water broth, lactose broth, brain heart infusion broth (BHI), universal pre-enrichment broth, nutrient broth, and tryptic soy broth, and five selective media including brilliant green broth (BG), rappaport-vassiliadis R10 broth, selenite cystine broth, selenite broth, and tetrathionate brilliant green broth (TBG) for the comparison of Salmonella growth. Various concentrations of Salmonella (10, 50, 100, 500, and 1,000 CFU/chicken) were then enriched for 6 hr in both BHI and BG media to select the best media. BHI was selected as the most effective non-selective enrichment medium, while BG was selected as the most effective selective enrichment medium. Finally, BHI medium was selected as the most efficient enrichment medium for Salmonella growth injured from cold temperature during processing or storage.