• 한국유기농업학회:학술대회논문집
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• 한국유기농학회 2011년도 상반기 국제 심포지엄
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• pp.128-142
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• 2011

• 한국농림기상학회:학술대회논문집
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• 한국농림기상학회 2016년도 추계 학술발표논문집
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• pp.228-236
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• 2016

• 환경영향평가
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• 제3권2호
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• pp.47-56
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• 1994

AGNPS model is an event-based model to analyze nonpoint-source and to examine potential water quality problems from agricultural watershed. This model uses a square grid-cell system to represent the spatial variability of watershed conditions, and simulates runoff, sediment, and nutrient transport for each cell. AGNPS model was applied on Yeonwha watershed, and the test results were compared with the measured data for runoff volume, peak runoff rate, suspended solids, and phosphorus concentration. The watershed of 278.8 ha was divided into 278 cells, each of which was 1 ha in size. The coefficients of determination for runoff volume and peak flow were (0.893 and 0.801 respectively from regression of the estimated values on the measured values. The concentration of suspendid solid was increased but decreased that of phosphate with runoff volume.

• Asian-Australasian Journal of Animal Sciences
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• 제10권1호
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• pp.70-74
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• 1997

Data on 2,571 lactation records of Nili-Ravi buffaloes from four institutional herds and four field recording centers were analyzed under an animal model to see the effect of season definition on the error variance of the fitted model. Herd-year-season(HYS) was the main fixed effect along with permanent environment, breeding value and residuals as the random effects. All known relationships among the animals were considered. The error variance differed for various HYS combinations. It was minimum when then months were not grouped into seasons. The four or Five season scenarios were better than the two season scenarios. The average number of lactations represented in a HYS combination varied widely from 6 to 28. Very few subclasses for a given HYS combination warrants the use of fewer seasons for animal model evaluation of buffaloes.

• 농촌지도와개발
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• 제24권2호
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• pp.99-115
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• 2017

The purpose of this study is to analyze potential adoption rates and reusing patterns of the new rice direct seeding technology. The model constructed and employed in this study is a system dynamics model of farmer adoption and reusing patterns for this new technology over time. The model incorporates a causal loop diagram that explains interactions among rice cultivation subsystems with feedback loops and further attempts to build a causal loop model with stock-flow diagram for computer simulation. As one example of how the model can be used to provide insight to rice farmers, simulations are run over varying levels on the cultivation process of rice. The major finding is to demonstrate the utility of system dynamics simulation methodology in aiding the rice wet direct seeding farmers' decision making.

• 생물환경조절학회지
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• 제31권3호
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• pp.152-162
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• 2022

본 연구는 데이터를 기반으로 한 인공지능 기계학습 기법을 활용하여 온실 내부온도 예측 시뮬레이션 모델을 개발을 수행하였다. 온실 시스템의 내부온도 예측을 위해서 다양한 방법이 연구됐지만, 가외 변인으로 인하여 기존 시뮬레이션 분석방법은 낮은 정밀도의 문제점을 지니고 있다. 이러한 한계점을 극복하기 위하여 최근 개발되고 있는 데이터 기반의 기계학습을 활용하여 온실 내부온도 예측 모델 개발을 수행하였다. 기계학습모델은 데이터 수집, 특성 분석, 학습을 통하여 개발되며 매개변수와 학습방법에 따라 모델의 정확도가 크게 변화된다. 따라서 데이터 특성에 따른 최적의 모델 도출방법이 필요하다. 모델 개발 결과 숨은층 증가에 따라 모델 정확도가 상승하였으며 최종적으로 GRU 알고리즘과 숨은층6에서 r² 0.9848과 RMSE 0.5857℃로 최적 모델이 도출되었다. 본 연구를 통하여 온실 외부 데이터를 활용하여 온실 내부온도 예측 모델 개발이 가능함을 검증하였으며, 추후 다양한 온실데이터에 적용 및 비교분석이 수행되어야 한다. 이후 한 단계 더 나아가 기계학습모델 예측(predicted) 결과를 예보(forecasting)단계로 개선하기 위해서 데이터 시간 길이(sequence length)에 따른 특성 분석 및 계절별 기후변화와 작물에 따른 사례별로 개발 모델을 관리하는 등의 다양한 추가 연구가 수행되어야 한다.

• Agribusiness and Information Management
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• 제4권1호
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• pp.32-40
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• 2012

In recent times, NFC technology adaptations for smartphones have been increasing. This study proposes the adaptation of agri-food business models based on NFC technology and presents the basic technological characteristics of NFC. An NFC tag can store more information than prior tagging technology methods, such as QR codes, and provides a better user experience. Based on the unique features of NFC, this study suggests an NFC business model application for the agri-food business.

• Asian-Australasian Journal of Animal Sciences
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• 제20권10호
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• pp.1517-1524
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• 2007

The [$^2H_5$]phenylalanine model was compared with the [1-$^{13}C$]leucine method to determine whole body protein synthesis (WBPS) and degradation (WBPD) in sheep fed at two levels. The animals were fed either 103 (M-diet) or 151 (H-diet) kcal $ME/kg^{0.75}/day$ once daily in a crossover design for 21 days each. The isotope dilutions were simultaneously conducted as a primed-continuous infusion of [$^2H_5$]phenylalanine, [$^2H_2$]tyrosine and [1-$^{13}C$]leucine on each dietary treatment. The WBPS and WBPD calculated from the [$^2H_5$]phenylalanine model were lower (p = 0.009 and p = 0.003, respectively) than those calculated from the [1-$^{13}C$]leucine method. The WBPS tended to be higher (p = 0.08) and WBPD was numerically higher (p = 0.33) for H-diet than M-diet in the [$^2H_5$]phenylalanine model, whereas the WBPS was numerically higher (p = 0.37) for H-diet and WBPS remained similar (p = 0.79) between diets in the [1-$^{13}C$]leucine method. However, the absolute values and the directions of WBPS as well as WBPD from M-diet to H-diet were comparable between the [$^2H_5$]phenylalanine model and [1-$^{13}C$]leucine method. Moreover, the values vary depending on the use of the respective amino acid contents in the carcass protein when calculating WBPS and WBPD. Therefore, it is concluded that the [$^2H_5$]phenylalanine model could be used as an alternative to the [1-$^{13}C$]leucine method for the determination of WBPS and WBPD in sheep.

• Asian-Australasian Journal of Animal Sciences
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• 제22권1호
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• pp.57-71
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• 2009

Crop-livestock mixed farming systems depend on the efficiency with which nutrients are conserved and recycled. Home-grown forage is used as animal feed and animal excretions are applied to cultivated crop lands as manure. The objective of this study was to develop a mixed farming system model for dairy cattle in Japan. The model consisted of four sub-models: the nutrient requirement model, based on the Japanese Feeding Standards to determine requirements for energy, crude protein, dry matter intake, calcium, phosphorus and vitamin A; the optimum diet formulation model for determining the optimum diets that satisfy nutrient requirements at lowest cost, using linear programming; the herd dynamic model to calculate the numbers of cows in each reproductive cycle; and the whole farm optimization model to evaluate whole farm management from economic and environmental viewpoints and to optimize strategies for the target farm or system. To examine the model' validity, its predictions were compared against best practices for dairy farm management. Sensitivity analyses indicated that higher yielding cows lead to better economic results but higher emvironmental load in dairy cattle systems integrated with forage crop production.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.287-287
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• 2023

Surface water-groundwater interaction (SWGI) is an important hydrological process that influences both the quantity and quality of water resources. However, regional scale SWGI model calibration and uncertainty analysis have been a challenge because integrated models inherently carry a vast number of parameters, modeling assumptions, and inputs, potentially leaving little time and budget to explore questions related to model performance and forecasting. In this study, we have proposed the application of iterative ensemble smoother (IES) for uncertainty analysis and calibration of the widely used integrated surface-subsurface model, SWAT-MODFLOW. SWAT-MODFLOW integrates Soil and Water Assessment Tool (SWAT) and a three-dimensional finite difference model (MODFLOW). The model was calibrated using a parameter estimation tool (PEST). The major advantage of the employed IES is that the number of model runs required for the calibration of an ensemble is independent of the number of adjustable parameters. The pilot point approach was followed to calibrate the aquifer parameters, namely hydraulic conductivity, specific storage, and specific yield. The parameter estimation process for the SWAT model focused primarily on surface-related parameters. The uncertainties both in the streamflow and groundwater level were assessed. The work presented provides valuable insights for future endeavors in coupled surface-subsurface modeling, data collection, model development, and informed decision-making.