• Magazine of the Korean Society of Agricultural Engineers
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• v.30 no.3
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• pp.114-120
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• 1988

A water surface profile computation model using a standard step procedure was developed for gradually varied flow at an irrigation channel network. Flow characteristics ab Banweol district near Suweon were field monitored during irrigation periol of 1987. The model was applied to the main system at the district and the simulation results were compared to the field data. The results are sumrnarized as follows ; 1. The simulated water surface profiles from the model were in good agreement with the measured water surface profiles at different flow rates. 2. The model applicability for defining a stage-discharge relationship at a channel reach was demonstrated with reasonable accuracy when water stage and friction factor were given. 3. The roughness coefficient was found to be a major factor sigrificantly affecting computed water surface profile among a few physical input parameters for the model.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1669-1683
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• 2021

AI intelligent agriculture and digital agriculture are important for the science of agriculture. Leaf chlorophyll contents(LCC) are one of the most important indicators to determine the growth status of vegetable crops. In this study, a support vector machine (SVM) regression model was produced using an unmanned aerial vehicle-based RGB camera and a multispectral (MSP) sensor for onions and garlic, and the LCC estimation applicability of the RGB camera was reviewed by comparing it with the MSP sensor. As a result of this study, the RGB-based LCC model showed lower results than the MSP-based LCC model with an average R² of 0.09, RMSE 18.66, and nRMSE 3.46%. However, the difference in accuracy between the two sensors was not large, and the accuracy did not drop significantly when compared with previous studies using various sensors and algorithms. In addition, the RGB-based LCC model reflects the field LCC trend well when compared with the actual measured value, but it tends to be underestimated at high chlorophyll concentrations. It was possible to confirm the applicability of the LCC estimation with RGB considering the economic feasibility and versatility of the RGB camera. The results obtained from this study are expected to be usefully utilized in digital agriculture as AI intelligent agriculture technology that applies artificial intelligence and big data convergence technology.

• Journal of Korea Water Resources Association
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• v.50 no.3
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• pp.211-221
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• 2017

In statistical hydrology, various extreme distributions such as the generalized extreme value (GEV), generalized logistic (GLO) and Gumbel (GUM) models have been widely used to analyze the extreme events. In the case of rainfall events in South Korea, the GEV and Gumbel distributions are known to be appropriate among various extreme distribution models. However, the proper probability distribution model may be different depending on the type of extreme events, rainfall duration, region, and statistical characteristics of extreme events. In this regard, it is necessary to apply a wide range of statistical properties that can be represented by the distribution model because it has two shape parameters. In this study, the statistical applicability of rainfall data is analyzed using the Burr XII distribution and the dimensionless L-moment ratio for 620 stations in South Korea. For this purpose, L-skewness and L-kurtosis of the Burr XII distribution are derived and L-moment ratio diagram is drawn and then the applicability of 620 stations was analyzed. As a result, it is found that the Burr XII distribution for the stations of the Han River basin in which L-skewness is relatively larger than L-kurtosis is appropriate, It is possibility of replacing the distribution of commonly used Gumbel or GEV distributions. Therefore, the Burr XII model can be replaced as an appropriate probability model in this basin.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.52 no.4
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• pp.393-402
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• 2007

Remote sensing data can be integrated into crop models, making simulation improved. A crop model that uses remote sensing data was evaluated for its capability, which was performed through comparing three different methods of canopy measurement for cotton(Gossypium hirsutum L.). The measurement methods used were leaf area index(LAI), hand-held remotely sensed perpendicular vegetation index(PVI), and satellite remotely sensed PVI. Simulated values of cotton growth and lint yield showed reasonable agreement with the corresponding measurements when canopy measurements of LAI and hand-held remotely sensed PVI were used for model calibration. Meanwhile, simulated lint yields involving the satellite remotely sensed PVI were in rough agreement with the measured lint yields. We believe this matter could be improved by using remote sensing data obtained from finer resolution sensors. The model not only has simple input requirements but also is easy to use. It promises to expand its applicability to other regions for crop production, and to be applicable to regional crop growth monitoring and yield mapping projects.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1931-1942
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• 2021

As the utility of an optical satellite image with a high spatial resolution (i.e., fine-scale) has been emphasized, recently, various studies of the land surface monitoring using those have been widely carried out. However, the usefulness of fine-scale satellite images is limited because those are acquired at a low temporal resolution. To compensate for this limitation, the spatiotemporal data fusion can be applied to generate a synthetic image with a high spatio-temporal resolution by fusing multiple satellite images with different spatial and temporal resolutions. Since the spatio-temporal data fusion models have been developed for mid or low spatial resolution satellite images in the previous studies, it is necessary to evaluate the applicability of the developed models to the satellite images with a high spatial resolution. For this, this study evaluated the applicability of the developed spatio-temporal fusion models for KOMPSAT-3A and Sentinel-2 images. Here, an Enhanced Spatial and Temporal Adaptive Fusion Model (ESTARFM) and Spatial Time-series Geostatistical Deconvolution/Fusion Model (STGDFM), which use the different information for prediction, were applied. As a result of this study, it was found that the prediction performance of STGDFM, which combines temporally continuous reflectance values, was better than that of ESTARFM. Particularly, the prediction performance of STGDFM was significantly improved when it is difficult to simultaneously acquire KOMPSAT and Sentinel-2 images at a same date due to the low temporal resolution of KOMPSAT images. From the results of this study, it was confirmed that STGDFM, which has relatively better prediction performance by combining continuous temporal information, can compensate for the limitation to the low revisit time of fine-scale satellite images.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.1
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• pp.87-100
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• 1997

The ability of turbulence model to accurately describe the complex characteristics of the flow field and the fuel spray is of great importance in the optimum design of diesel engine. The numerical simulations of the flow field and the spray characteristics within the combustion chamber of direct injection model entgine are performed to examine the applicability of turbulence model. The turbulence models used are the RNG $\varepsilon$ model and the modified $\varepsilon$ model which included the compressibility effect due to the compression/expansion of the charges. In this study, the predicted results in the quiescent condition of direct injection model engine show reasonable trends comparing with the experimental data of spray characteristics, i. e., spray tip penetration, spray tip velocity. The results of eddy viscosity obtained using the $\varepsilon$ model in the spray region is significantly larger than that obtained using the RNG $\varepsilon$ model. The application of the RNG model seems to have some potential for the simulations of the spray characteristics, e. g., spray tip penetration, spray tip velocity, droplets distribution over the $\varepsilon$ model.

• 한국IT서비스학회:학술대회논문집
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• 2007.11a
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• pp.206-209
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• 2007

The work patterns in the organizations performing research and development projects consist of both administrative business with defined processes and knowledge-oriented research and development business with undefined or semidefined processes. This paper describes an enterprise portal model and its services aligned to research and development organization's work patterns. The proposed portal model is focused on constructing personalized workplaces providing knowledge-based services for research and development business, as well as business process management based services for administrative business. The further research will provide more concrete portal model and its applicability to research and development organization's business.

• Korean Journal of Geomatics
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• v.2 no.2
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• pp.139-143
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• 2002

The rational polynomial coefficients (RPC) model is a generalized sensor model that is used as an alternative solution for the physical sensor model for IKONOS of the Space Imaging. As the number of sensors increases along with greater complexity, and the standard sensor model is needed, the applicability of the RPC model is increasing. The RPC model has the advantages in being able to substitute for all sensor models, such as the projective, the linear pushbroom and the SAR. This report aimed to generate a RPC model from the physical sensor model of the KOMPSAT-1(Korean Multi-Purpose Satellite) and aerial photography. The KOMPSAT-1 collects 510~730 nm panchromatic imagery with a ground sample distance (GSD) of 6.6 m and a swath width of 17 km by pushbroom scanning. The least square solution was used to estimate the RPC. In addition, data normalization and regularization were applied to improve the accuracy and minimize noise. This study found that the RPC model is suitable for both KOMPSAT-1 and aerial photography.

• Journal of the Korean Society of Radiology
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• v.9 no.6
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• pp.417-420
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• 2015

We obtained Surviving Fraction (SF) after irradiation carbon beam to compare the applicability of the Linear-Quadratic model, Incomplete Repair model, Marchese model. Mathematica software(ver 9.0) used to calcurate parameters and compared result. LQ model could not explain the entire response of fractionated carbon beam irradiation. It becomes necessary to construct models that extend the LQ model of conventional radiotherapy for the carbon beam therapy. By combining both Potentially Lethal Damage Repair (PLDR) and Sublethal Damage Repair (SLDR) a new LQ model can develop that aptly modeled the cellular response to fractionated irradiation.

• Korean Journal of Computational Design and Engineering
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• v.15 no.4
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• pp.279-288
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• 2010

In this paper, a DEVS(Discrete EVent Systems Specification)-HLA(High Level Architecture) interface was developed in order to perform the simulation using the combined discrete event and discrete time simulation model architecture in a distributed environment. The developed interface connects the combined simulation model with the HLA/RTI(Run-Time Infrastructure) which is an international standard middleware for distributed simulation. The interface consists of an interface model, a model interpreter, and a distributed environment interpreter. The interface model was defined by using the combined simulation architecture in order to easily connect the existing combined simulation model without modification with the HLA/RTI. The model interpreter takes charge of data transmission between the interface model and the combined simulation model. The distributed environment interpreter takes charge of data transmission between the interface model and the HLA/RTI. To evaluate the applicability of the developed interface, it was applied to the diving simulation of a submarine in a distributed environment. The result shows that a simulation result in a distributed environment using the interface is the same to the result in a single computing environment.