• The Journal of the Korea Contents Association
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• v.15 no.6
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• pp.276-282
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• 2015

Fetal cerebellum is grow depending on the gestational age, measurement of transverse cerebellar diameter(TCD) is being used import indicator of fetal growth prediction in clinical. In this study, the subjects were normal pregnant women 20~37 week of gestation, and the volume scan was conducted on the 340 subjects. The research reports was indicated by regression curve the growth of fetal TCD in accordance with the gestational age. It got to the value of the results from a linear regression equation. Measurement fetal TCD using 3D US was statistically significant(p<0.001) and useful in the prediction of gestational age. TCD increases with gestational age can also distinguish between the normal fetal and prediction of accurate gestational age of fetal growth retardation. If the basic data of the present study, ongoing research is performed, the TCD using by 3D US are expected to be usefully applied in the correct prediction gestational age.

• Ocean and Polar Research
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• v.43 no.3
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• pp.179-192
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• 2021

In this study, an integrated wave model from global to coastal scales was developed to improve the operational wave prediction performance of the Korean Meteorological Administration (KMA). In this system, the wave model was upgraded to the WaveWatch III version 6.07 with the improved parameterization of the source term. Considering the increased resolution of the wind input field and the introduction of the high-performance KMA 5^th Supercomputer, the spatial resolution of global and regional wave models has been doubled compared to the operational model. The physical processes and coefficients of the wave model were optimized for the current KMA global atmospheric forecasting system, the Korean Integrated Model (KIM), which is being operated since April 2020. Based on the sensitivity experiment results, the wind-wave growth parameter (β_max) for the global wave model was determined to be 1.33 with the lowest root mean square errors (RMSE). The value of β_max showed the lowest error when applied to regional/coastal wave models for the period of the typhoon season when strong winds occur. Applying the new system to the case of August 2020, the RMSE for the 48-hour significant wave height prediction was reduced by 13.4 to 17.7% compared to the existing KMA operating model. The new integrated wave prediction system plans to replace the KMA operating model after long-term verification.

• Spatial Information Research
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• v.18 no.3
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• pp.33-40
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• 2010

Many cities have provided growth management measure for preventing urban sprawl and disordered development by rapid urbanization. Many Korean cities also, have been pressed by development issues as well as the Seoul Metropolitan Area. This study aims to predict urban growth and develop Urban Growth Management Model with Geographic Information System and quantitative method. Especially, this study provides reasonable management method by presenting prediction scenario considered institutional-oriented and demand-oriented. This study also, provides a scientific basis using GIS and quantitative analysis, and present decision making of planning and implementation process through simulation.

• Journal of Welding and Joining
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• v.24 no.4
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• pp.39-49
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• 2006

The austenite grain growth model in low alloyed steel HAZ without precipitates was proposed by analyzing isothermal grain growth behavior. Steels used in this study were designed to investigate the effect of alloying elements. Meanwhile, a systematic procedure was proposed to prevent inappropriate neglect of initial grain size (D0) and misreading both time exponent and activation energy for isothermal grain growth. It was found that the time exponent was almost constant, irrespectively of temperature and alloying elements, and activation energy increased with the addition of alloying elements. From quantification of the effect of alloying elements on the activation energy, an isothermal grain growth model was presented. Finally, combining with the additivity rule, the austenite grain size in the CGHAZ was predicted.

• Journal of Welding and Joining
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• v.20 no.5
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• pp.78-86
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• 2002

A metallurgical model for the prediction of prior austenite grain size considering the dissolution kinetics of M$_3$C precipitates at the heat affected zone of SA508-cl.3 was proposed. The isothermal kinetics of grain growth and dissolution were respectively described by well-known equation, $dD/dT=M({\Delta}F_{eff})^M$ and Whelan's analytical model. The isothermal grain growth experiments were carried out for measure the kinetic parameters of grain growth. The precipitates of the base metal and the specimens exposed to thermal cycle were examined by TEM-carbon extraction replica method. The model was assessed by the comparison of BUE simulation experiments and showed good consistencies. However, there was no difference between the model considering and ignoring $M_3C$ precipitates. It seems considered that pinning force exerted by $M_3C$ Precipitates was lower than driving force for grain growth due to large size and small fraction of precipitates, and mobility of grain boundary was low in the lower temperature range.

• Journal of Preventive Veterinary Medicine
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• v.42 no.4
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• pp.143-147
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• 2018

The present study aimed to develop growth prediction models of Listeria monocytogenes in processed meat products, such as mixed pressed hams, to perform accurate microbial risk assessments. Considering cold storage temperatures and the amount of time in the stages of consumption after opening, the growth of L. monocytogenes was determined as a function of temperature at 0, 5, 10, and $15^{\circ}C$, and time at 0, 1, 3, 6, 8, 10, 15, 20, 25, and 30 days. Based on the results of these measurements, a Baranyi model using the primary model was developed. The input parameters of the Baranyi equation in the variable temperature for polynomial regression as a secondary model were developed: $SGR=0.1715+0.0199T+0.0012T^2$, $LT=5.5730-0.3215T+0.0051T^2$ with $R^2$ values 0.9972 and 0.9772, respectively. The RMSE (Root mean squared error), $B_f$ (bias factor), and $A_f$ (accuracy factor) on the growth prediction model were determined to be 0.30, 0.72, and 1.50 in SGR (specific growth rate), and 0.10, 0.84, and 1.35 in LT (lag time), respectively. Therefore, the model developed in this study can be used to determine microorganism growth in the stages of consumption of mixed pressed hams and has potential in microbial risk assessments (MRAs).

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1012-1020
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• 2006

The crack that occurs on the wheels of railroad cars can be categorized into a surface crack that starts from the surface or a subsurface crack that starts from the inside and can be detrimental to safe railroad operations. Therefore, estimating the growth life span of this type of crack is very important. In this research, the stress distributions, displacements, and the growth-life spans of both surface cracks and subsurface cracks have been studied. By using the finite element analysis, especially in the life span prediction process, the stress conditions and the stress intensity factors of the crack tip have been discovered. The Paris formula has been used to analyze the growth-life span prediction.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.5
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• pp.1097-1103
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• 1988

This paper deals with surface crack behavior and the fatigue life prediction of notched specimens using the relation between surface crack length, a, and the cycle ratio, $N/N_{f}$. From the $a-N\;/\;N_{f}$ curves, UC(the upper limit curve), LC(the lower limit curve) and MC(the middle limit curve) were assumed and utilized to predict the fatigue life and crack growth rate. The data computed from the three assumed curves were compared with the experimental data. It has been found that in the stable crack growth region ($N/N_{f}=0.3-0.8$) fatigue life can be predicted within 20% errors. Using the characteristics of $a-N\;/\;N_{f}$ curve, it is possible to predict the $da/dN-K_{max}$ curve, the $da/dN-{\Delta}K_{{\varepsilon}_t}$ curve, and the $S-N_{f}$ curve.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1997.10a
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• pp.220-223
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• 1997

This paper presents the prediction of microstructure of Inconel 718 disk forgings. The experiments are carried out to examine the recrystallization ratio and grain growth in the forgings. In the experiments, cylindrical billets are forged by two operations with variations of forging temperature and reduction ratio of deformation. Also the finite element program, developed here for the prediction, is used for the analysis, and the results are compared with the experimental ones. It is noted that the comparison appears in sound agreement.