• Transactions of Materials Processing
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• v.22 no.8
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• pp.450-455
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• 2013

In the current study, a new dynamic recrystallization model for predicting high temperature flow stress is developed based on a physical model and the mean field theory. In the model, the grain aggregate is assumed as a representative volume element to describe dynamic recrystallization. The flow stress and microstructure during dynamic recrystallization were calculated using three sub-models for work hardening, for nucleation and for growth. In the case of work hardening, a single parameter dislocation density model was used to calculate change of dislocation density and stress in the grains. For modeling nucleation, the nucleation criterion developed was based on the grain boundary bulge mechanism and a constant nucleation rate was assumed. Conventional rate theory was used for describing growth. The flow stress behavior of pure copper was investigated using the model and compared with experimental findings. Simulated results by cellular automata were used for validating the model.

• Journal of the Korean Ceramic Society
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• v.34 no.11
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• pp.1139-1150
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• 1997

A model for predicting the relative density and the compressive strength of open-cell ceramics with three-dimensional network structure was proposed through the interpretation of their macrostructure and fracture mechanics. The equation predicting the relative density was derived under the assumption that the open-cell structure was a periodic array of the tetrakaidecahedron unit cell consisting of cylindrical struts containing the internal hollow with the shape of a triangular prism. The model for compressive strength of open-cell ceramics with the hollow strut was also developed by modifying conventional model which based on fracture behavior of them subjected to the compressive stress. Both the relative density and the compressive strength were expressed in terms of the ratio of the strut diameter to the length together with the ratio of the hollow size to the strut diameter. The proposed model for the relative density and the compressive strength of the alumina-zirconia composite with open-cell structure were accorded well with the experimental values, whereas Gibson-Ashby and Zhang's model did not show such a good agreement.

• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.2
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• pp.73-80
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• 1993

A simplified physiologically-based dynamic model, SIMRIW was selected for predicting the growth and yield of rice. The applicability of the model to the rice cultivars and weather conditions in the Republic of Korea was evaluated. Parameters of the model were calibrated using actual rice yields in Suweon region and an optimization scheme, Constrained Rosenbrock Algorithm. The simulated results from the calibrated model were in good agreement with the field data. The model with parameters calibrated for Suweon was applied to other five regions for the evaluation of transferability, but the simulated results fell short of satisfaction. However, the model is found to be applied to real-time prediction of the growth and yield of rice crop, which is believed to be useful for timely rice crop management, agricultural policy making, and optimal irrigation water management.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.213-221
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• 2021

In this paper, we suggest the Deep Neural Network Model System for predicting results of the match of 'League of Legends (LOL).' The model utilized approximately 26,000 matches of the LOL game and Keras of Tensorflow. It performed an accuracy of 93.75% without overfitting disadvantage in predicting the '2020 League of Legends Worlds Championship' utilizing the real data in the middle of the game. It employed functions of Sigmoid, Relu and Logcosh, for better performance. The experiments found that the four variables largely affected the accuracy of predicting the match --- 'Dragon Gap', 'Level Gap', 'Blue Rift Heralds', and 'Tower Kills Gap,' and ordinary users can also use the model to help develop game strategies by focusing on four elements. Furthermore, the model can be applied to predicting the match of E-sports professional leagues around the world and to the useful training indicators for professional teams, contributing to vitalization of E-sports.

• Honam Mathematical Journal
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• v.40 no.4
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• pp.795-808
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• 2018

Adolescent obesity has a high risk of developing into adult obesity and may cause many psychological problems. This paper aims at giving a mathematical model for the obesity of Korean adolescents and predicting how much the prevalence of obesity among adolescents will increase using real data. We estimate that the obesity rate of boys will increase until about 28 ~ 29% in 2025.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.138-147
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• 2018

Purpose: A narrowband hyperspectral imaging sensor of high-dimensional spectral bands is advantageous for identifying the reflectance by selecting the significant spectral bands for predicting crop yield over the broadband multispectral imaging sensor for each wavelength range of the crop canopy. The images acquired by each imaging sensor were used to develop the models for predicting the Chinese cabbage yield. Methods: The models for predicting the Chinese cabbage (Brassica campestris L.) yield, with multispectral images based on unmanned aerial vehicle (UAV), were developed by simple linear regression (SLR) using vegetation indices, and forward stepwise multiple linear regression (MLR) using four spectral bands. The model with hyperspectral images based on the ground were developed using forward stepwise MLR from the significant spectral bands selected by dimension reduction methods based on a partial least squares regression (PLSR) model of high precision and accuracy. Results: The SLR model by the multispectral image cannot predict the yield well because of its low sensitivity in high fresh weight. Despite improved sensitivity in high fresh weight of the MLR model, its precision and accuracy was unsuitable for predicting the yield as its $R^2$ is 0.697, root-mean-square error (RMSE) is 1170 g/plant, relative error (RE) is 67.1%. When selecting the significant spectral bands for predicting the yield using hyperspectral images, the MLR model using four spectral bands show high precision and accuracy, with 0.891 for $R^2$, 616 g/plant for the RMSE, and 35.3% for the RE. Conclusions: Little difference was observed in the precision and accuracy of the PLSR model of 0.896 for $R^2$, 576.7 g/plant for the RMSE, and 33.1% for the RE, compared with the MLR model. If the multispectral imaging sensor composed of the significant spectral bands is produced, the crop yield of a wide area can be predicted using a UAV.

• Journal of the Korean Institute of Navigation
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• v.24 no.3
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• pp.123-132
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• 2000

In order to improve the ship maneuverability, It is important to estimate precisely the hydrodynamic coefficients of added mass forces acting on a ship especially in shallow waters, and simple methods for predicting such hydrodynamic forces Is also very desirable. In the previous paper using 3-Dimension potential flow theory, it has been demonstrated that potential calculation is available to estimate added mass coefficients. The present work is aimed at the suggestion of the simplified formulas for predicting the translation and lateral motion of added mass coefficients in shallow water. So, 3-D potential flow theory is also used to calculate the added mass coefficients in deep and shallow waters for Series 60 model which has 5 different kinds of block coefficients (0.6-0.8), SR196 model and T/S HANNARA. After some series computation, simplified formulas for Predicting the added mass force in shallow waters is suggested based on the computation results of Series 60 model. The formulas consist of the combination of principal dimensions and the water depth; d/B, Cb, d/H. The predicted results are compared with the Computation results for SR196 model and T/S HANNARA. The precision of predicted results by simplified formulas are good enough for the practical use. (d/B : draft-Breadth ratio, d/H draft-Water depth ratio, Cb : Block coefficients).

• Journal of Environmental Science International
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• v.23 no.12
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• pp.2121-2127
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• 2014

Analyzing the observational data of volcanic activities around the northern part of Korean peninsula, the odds of volcano eruption increases continuously. For example, the cumulative seismic moment and frequence observed near Mt. Baekdu show a sudden increased values. In this study, predicting the diffusion of volcanic ash for two cases were carried out by using interactive realtime simulator, which was developed during last 2 years as a research and development project. The first case is Sakurajima volcano (VEI=3) erupted in August 2013. The second case is assumed as the volcanic eruption at Mt. Baekdu (VEI=7) under landing circumstance of typhoon Maemi (August 2003) in Korean peninsula. The synoptic condition and ash diffusion for the two cases were simulated by WRF(Weather Research and Forecast) model and Lagrangian dispersion model, respectively. Comparing the simulated result of the first case (i.e., Sakurajima volcano) with satellite image, the diffusion pattern show acceptable result. The interactive realtime simulator can be available to support decision making under volcanic disaster around East Asia by predicting several days of ash dispersion within several minutes with ordinary desktop personal computer.

• Computers and Concrete
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• v.20 no.1
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• pp.31-38
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• 2017

In the present study an Artificial Neural Network (ANN) was used to predict the compressive strength of self-compacting concrete. The data developed experimentally for self-compacting concrete and the data sets of a total of 99 concrete samples were used in this work. ANN's are considered as nonlinear statistical data modeling tools where complex relationships between inputs and outputs are modeled or patterns are found. In the present ANN model, eight input parameters are used to predict the compressive strength of self-compacting of concrete. These include varying amounts of cement, coarse aggregate, fine aggregate, fly ash, fiber, water, super plasticizer (SP), viscosity modifying admixture (VMA) while the single output parameter is the compressive strength of concrete. The importance of different input parameters for predicting the strengths at various ages using neural network was discussed in the study. There is a perfect correlation between the experimental and prediction of the compressive strength of SCC based on ANN with very low root mean square errors. Also, the efficiency of ANN model is better compared to the multivariable regression analysis (MRA). Hence it can be concluded that the ANN model has more potential compared to MRA model in developing an optimum mix proportion for predicting the compressive strength of concrete without much loss of material and time.

• 유체기계공업학회:학술대회논문집
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• 2004.12a
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• pp.315-320
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• 2004

Swing check valves are the most common type of check valve in nuclear power plant and need to be operated property to perform their functions and to keep the valve internals stable. However, for a swing check valve disc to remain stable, the opening characteristics should be identified and the upstream flow velocity should be enough to hold the disc fully open and without motion. Thus it is necessary to develop a model for predicting the flow velocity for a given disc opening. In the present study, the disc positions with mean flow velocity were measured for 3 inch and 6 inch swing check valves. Comparison of the measurements with the existing models showed that the models underestimate the mean flow velocity for a given disc position. Therefore, the existing model for predicting swing check valve disc position was improved with the realistic disc impingement area perpendicular to the flow stream and the experimental data. The result showed that the improved model with the best estimate of kb = 0.04 predicts well the disc openings of 6 inch swing check valve, especially in the low velocity region. For better prediction of the disc opening at high flow velocity, however, it is recommended to develop a kb correlation with the disc angle.