• 한국지역사회생활과학회지
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• 제12권2호
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• pp.119-135
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• 2001

This study was conducted to compare the composition table of Korean food with that of foreign food. Analysis was made for Korean food composition table($5^{th}$ revision), Korean food composition table in Appendix of Recommended Dietary Allowances for Korean(6$^{th}$ th/ edition), Standard tables of food composition in Japan($5^{th}$ revised edition) and USDA Composition of Foods - Raw, Processed, Prepared. The method of content analysis was applied for this study and such differences were pointed out as the classification of food items, food items enlisted, the content unit of food and food components presented etc. To improve Korean food composition table, new food items and components should be added and old food items be eliminated based on the change of people's food consumption pattern. Also analysis for the domestic foods consumed by local people should be accomplished rather than borrowing foreign country's data.

• 한국수의병리학회지
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• 제7권1호
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• pp.1-4
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• 2003

Malignant catarrhal fever (MCF) is a systemic disease of ruminants caused by a gamma herpesvirus, ovine herpesvirus 2 (OvHV-2). Dot blot hybridization (DBH) protocols for detecting and differentiating this MCF virus were developed. OvHV-2 specific primer pairs, 556/555, were used for the amplification of target DNA. Then, the amplified DNA was labeled with incorporation of digoxigenin (DIG). The Dig-labeled probe was able to detect and differentiate specifically OvHV-2 DNA. This DBH technique can be applied to confirm the presence of MCF virus on clinical samples and to differentiate specifically between OvHV-2 infection and other viral infections.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2008년도 정기총회 및 학술발표대회
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• pp.161-164
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• 2008

We studied a basic concept and application about FARSITE, which is a forest fire spread simulator for preventing and predicting fire in United States Department of Agriculture(USDA). And, we researched a problem in the transition for introducing, so we serve the basic method for prevention and attacking fire. For this transition, we compared the behavior of the 2005 Yangyang forest fire with the result of a simulation. The spread direction is similar to real data. But, while mean spread of rate was 0.65km/hr on real data, it was 0.3km/hr on simulation. As Damaged area is 1,387ha on real, it was 5,368ha on simulation. Therefore, it is necessary to establish a fuel concept for more accurate simulation.

• 한국환경복원기술학회지
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• 제10권1호
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• pp.23-35
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• 2007

Nowadays, as a result of increasing income and spare time, the social demands for better living environment become more increasing. Above all, landscape improvement, the essential part of physical environment, will be a more important subject in urban planning. In these circumstances, classification of urban scenic quality is required for urban landscape development programs. The major purpose of this study is to suggest a technical method of designing urban scenic quality map for urban district area based on the scenery management system of the USDA forest service and literature studies. As a conclusion of this study, four steps are desirable for the technical method for designing a scenic quality map of urban districts areas : 1) Define a landscape unit on the map, 2) Take a photograph of these landscape unit on site, 3) Evaluate the landscape unit by semantic differential scale with landscape adjectives, and 4) Draw the scenic quality map, investigate the landscape characteristics and suggest the landscape scenic development plans.

• 한국농공학회논문집
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• 제60권6호
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• pp.43-54
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• 2018

The accurate estimation of reference crop evapotranspiration ($ET_o$) is essential in irrigation water management to assess the time-dependent status of crop water use and irrigation scheduling. The importance of $ET_o$ has resulted in many direct and indirect methods to approximate its value and include pan evaporation, meteorological-based estimations, lysimetry, soil moisture depletion, and soil water balance equations. Artificial neural networks (ANNs) have been intensively implemented for process-based hydrologic modeling due to their superior performance using nonlinear modeling, pattern recognition, and classification. This study adapted two well-known ANN algorithms, Backpropagation neural network (BPNN) and Generalized regression neural network (GRNN), to evaluate their capability to accurately predict $ET_o$ using daily meteorological data. All data were obtained from two automated weather stations (Chupungryeong and Jangsu) located in the Yeongdong-gun (2002-2017) and Jangsu-gun (1988-2017), respectively. Daily $ET_o$ was calculated using the Penman-Monteith equation as the benchmark method. These calculated values of $ET_o$ and corresponding meteorological data were separated into training, validation and test datasets. The performance of each ANN algorithm was evaluated against $ET_o$ calculated from the benchmark method and multiple linear regression (MLR) model. The overall results showed that the BPNN algorithm performed best followed by the MLR and GRNN in a statistical sense and this could contribute to provide valuable information to farmers, water managers and policy makers for effective agricultural water governance.

• 한국작물학회지
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• 제41권4호
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• pp.429-433
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• 1996

Giemsa C-banding 방법에 의하여 한국 재래종 옥수수 핵형 및 염색체의 특성을 알아보고자 옥수수의 근단 생장점을 이용하여 조사 분석하였다. 이 방법은 한국 재래종 옥수수의 핵형 분석 및 염색체의 특성 연구에도 효과적으로 활용할 수 있는 방법임이 확인되었다. 조사된 재래종 옥수수에서는 각각 10개의 heterochrornatic knob이 발견되었으며 이것들의 크기와 위치는 계통별로 다른 것으로 나타났고, 모두가 6번 염색체에 부수체를 가지고 있었다. 10번 염색체를 100으로 해서 비교해 본 각 염색체들의 상대적 길이는 조사된 계통별로 큰 차이가 있었다.

• 한국측량학회지
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• 제34권4호
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• pp.383-390
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• 2016

Remote sensing data has been widely used in the estimation of crop yields by employing statistical methods such as regression model. Machine learning, which is an efficient empirical method for classification and prediction, is another approach to crop yield estimation. This paper described the corn yield estimation in Iowa State using four machine learning approaches such as SVM (Support Vector Machine), RF (Random Forest), ERT (Extremely Randomized Trees) and DL (Deep Learning). Also, comparisons of the validation statistics among them were presented. To examine the seasonal sensitivities of the corn yields, three period groups were set up: (1) MJJAS (May to September), (2) JA (July and August) and (3) OC (optimal combination of month). In overall, the DL method showed the highest accuracies in terms of the correlation coefficient for the three period groups. The accuracies were relatively favorable in the OC group, which indicates the optimal combination of month can be significant in statistical modeling of crop yields. The differences between our predictions and USDA (United States Department of Agriculture) statistics were about 6-8 %, which shows the machine learning approaches can be a viable option for crop yield modeling. In particular, the DL showed more stable results by overcoming the overfitting problem of generic machine learning methods.

• Nutrition Research and Practice
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• 제11권2호
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• pp.105-113
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• 2017

BACKGROUND/OBJECTIVES: A high-fat diet (HFD) induces obesity, which is a major risk factor for cardiovascular disease and cancer, while a calorie-restricted diet can extend life span by reducing the risk of these diseases. It is known that health effects of diet are partially conveyed through epigenetic mechanism including DNA methylation. In this study, we investigated the genome-wide hepatic DNA methylation to identify the epigenetic effects of HFD-induced obesity. MATERIALS AND METHODS: Seven-week-old male C57BL/6 mice were fed control diet (CD), calorie-restricted control diet (CRCD), or HFD for 16 weeks (after one week of acclimation to the control diet). Food intake, body weight, and liver weight were measured. Hepatic triacylglycerol and cholesterol levels were determined using enzymatic colorimetric methods. Changes in genome-wide DNA methylation were determined by a DNA methylation microarray method combined with methylated DNA immunoprecipitation. The level of transcription of individual genes was measured by real-time PCR. RESULTS: The DNA methylation statuses of genes in biological networks related to lipid metabolism and hepatic steatosis were influenced by HFD-induced obesity. In HFD group, a proinflammatory Casp1 (Caspase 1) gene had hypomethylated CpG sites at the 1.5-kb upstream region of its transcription start site (TSS), and its mRNA level was higher compared with that in CD group. Additionally, an energy metabolism-associated gene Ndufb9 (NADH dehydrogenase 1 beta subcomplex 9) in HFD group had hypermethylated CpG sites at the 2.6-kb downstream region of its TSS, and its mRNA level was lower compared with that in CRCD group. CONCLUSIONS: HFD alters DNA methylation profiles in genes associated with liver lipid metabolism and hepatic steatosis. The methylation statuses of Casp1 and Ndufb9 were particularly influenced by the HFD. The expression of these genes in HFD differed significantly compared with CD and CRCD, respectively, suggesting that the expressions of Casp1 and Ndufb9 in liver were regulated by their methylation statuses.

• International Journal of Advanced Culture Technology
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• 제6권3호
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• pp.178-186
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• 2018

Generally, in terms of the development of irrigation scheme, the efficient water resource management that supplies the irrigation water in consideration of the required time and accurate quantity to grow the crop should be conducted. The water resource assessment should precede to supply the irrigation water efficiently. The water resources assessment is divided into the water requirement analysis and the water availability assessment. In case of Korea, the major crop is paddy rice unlike crops of Africa, such as sugarcane, maize, and cassava, etc. Because it is not familiar with the method for upland irrigation development in tropical area, it needs to know the water resources assessment for irrigation scheme development about these crops. The Natama Scheme in Chiradzulu District of the Southern Malawi was selected as study area, which has tropical climate. From the collected meteorological data, the evapotranspiration was analyzed by Penman-Monteith Method and the effective rainfall was analyzed by USDA Soil Conservation Service Method. This study displays the results that for study area, the evapotranspiration varies from 2.80 mm/day to 5.51 mm/day and the effective rainfall varied from 2.1mm to 149.0mm. According to the selected crop (Green Maize, Dry Maize), the unit water requirement (UWR) and water demand (WD) considering the irrigation efficiency, irrigation time and irrigation area were estimated to be $0.00122m^3/s/ha$ and $0.0122m^3/s$ respectively. For the water availability assessment, the runoff of Natama scheme was calculated by specific yield method. The water availability was evaluated through reviewed differences of discharge between $Q80_{intake}$ and Total WD, and the irrigation water can be supplied sufficiently in the existing 10ha of Natama scheme. As a result of reviewing the extensibility of irrigable area, total WD of scheme is $0.02313m^3/s$, and $Q80_{intake}$ is $0.02387m^3/s$ ($Q80_{intake}$ > Total WD). Therefore, Natama scheme can be extended from 10 ha to 17 ha in the dry season in consideration of the $Q80_{intake}$.

• The Plant Pathology Journal
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• 제21권2호
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• pp.111-118
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• 2005

Weather data for disease forecasts are usually derived from automated weather stations (AWS) that may be dispersed across a region in an irregular pattern. We have developed an alternative method to simulate local scale, high-resolution weather and plant disease in a grid pattern. The system incorporates a simplified mesoscale boundary layer model, LAWSS, for estimating local conditions such as air temperature and relative humidity. It also integrates special models for estimating of surface wetness duration and disease forecasts, such as the grapevine downy mildew forecast model, DMCast. The system can recreate weather forecasts utilizing the NCEP/NCAR reanalysis database, which contains over 57 years of archived and corrected global upper air conditions. The highest horizontal resolution of 0.150 km was achieved by running 5-step nested child grids inside coarse mother grids. Over the Finger Lakes and Chautauqua Lake regions of New York State, the system simulated three growing seasons for estimating the risk of grape downy mildew with 1 km resolution. Outputs were represented as regional maps or as site-specific graphs. The highest resolutions were achieved over North America, but the system is functional for any global location. The system is expected to be a powerful tool for site selection and reanalysis of historical plant disease epidemics.