• Structural Engineering and Mechanics
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• v.73 no.4
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• pp.455-462
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• 2020

The hybrid method using the extended finite element method (XFEM) and the forward Euler approach is widely employed to predict the fatigue life of plate structures. Due to the accuracy of the forward Euler approach is determined by a small step size, the performance of fatigue life prediction of the hybrid method is not agreeable. Instead the forward Euler approach, a prediction method using midpoint method and support vector regression (SVR) is presented to evaluate the stress intensity factors (SIFs) and the fatigue life. Firstly, the XFEM is employed to calculate the SIFs with given crack sizes. Then use the history of SIFs as a function of either number of fatigue life cycles or crack sizes within the current cycle to build a prediction model. Finally, according to the prediction model predict the SIFs at different crack sizes or different cycles. Three numerical cases composed by a homogeneous plate with edge crack, a composite plate with edge crack and center crack are introduced to verify the performance of the proposed method. The results show that the proposed method enables large step sizes without sacrificing accuracy. The method is expected to predict the fatigue life of complex structures.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.152-159
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• 2023

Due to COVID-19, changes in consumption trends are taking place in the distribution sector, such as an increase in non-face-to-face consumption and a rapid growth in the online shopping market. However, it is difficult for small and medium-sized export sellers to obtain forecast information on the export market by country, compared to large distributors who can easily build a global sales network. This study is about the prediction of export amount and export volume by country and item for market information analysis of small and medium export sellers. A prediction model was developed using Lasso, XGBoost, and MLP models based on supervised learning and deep learning, and export trends for clothing, cosmetics, and household electronic devices were predicted for Korea's major export countries, the United States, China, and Vietnam. As a result of the prediction, the performance of MAE and RMSE for the Lasso model was excellent, and based on the development results, a market analysis system for small and medium sellers was developed.

• The korean journal of orthodontics
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• v.27 no.3 s.62
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• pp.473-479
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• 1997

This author tried to find if the size of the frontal sinus can be used as a diagnostic aid to predict the manldibular growth pattern in growing Patients in lateral cephalogram utilizing the fact the the frontal sinus completes its growth in earlier stage but the mandible continues to grow until later. At this study, the 228 samples were divided into 3 groups as skeletal Class I, II, III malocclusions and three indicies(ANB, APDI, Wits) were measured which indicate the mandibular body length and the antero-posterior relationship of maxilla and mandible to evaluate their relations with frontal sinus. And results were obtained as followings 1. The size of frontal sinus is highly related to ANB, APDI, Wits and mandilar body length.(p<0.001) 2. the size of the frontal sinus of the Cl III malocclusion group was on the lateral cephalogram larger than Cl I and Cl II group.

• Smart Media Journal
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• v.5 no.4
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• pp.75-82
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• 2016

Although Korea's economic and domestic automobile market through the change of road environment are growth, the traffic accident rate has also increased, and the casualties is at a serious level. For this reason, the government is establishing and promoting policies to open traffic accident data and solve problems. In this paper, describe the method of predicting traffic accidents by eliminating the class imbalance using the traffic accident data and constructing the Hybrid Model. Using the original traffic accident data and the sampled data as learning data which use FP-Growth algorithm it learn patterns associated with traffic accident injury severity. Accordingly, In this paper purpose a method for predicting the severity of a victim of a traffic accident by analyzing the association patterns of two learning data, we can extract the same related patterns, when a decision tree and multinomial logistic regression analysis are performed, a hybrid model is constructed by assigning weights to related attributes.

• Journal of the Korean Society of Radiology
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• v.9 no.6
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• pp.349-356
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• 2015

The study is to recognize the interactions with bone ages by measuring the length between the end of the bone and the growth plate on selected highest weight of regions of seven for bone maturity in TW3 method. The experiment is subjected on seventy-two children (36 males, 36 females) who have examined the growth plate test from March, 2014 to March, 2015 and implemented a regression analysis by measuring the length between the end of the bone and the growth plate in Hand AP image of the children. In result, each bone age has produced a mean value and a standard deviation corresponding to the specific range and as bone age increases the length between the end of the bone and the growth plate decreased. In addition, female children showed lower mean value in comparison to male and also the measurement of the length between the end of the bone and the growth plate and its bone age are shown to be statistically valid(p<0.001) according to the results of regression analysis using its result value. Therefore, the probability of prediction on the bone age read off through the applied TW3 method and regression equation in the Hand AP image of the children.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.3
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• pp.267-275
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• 2012

In this study, crack growth in a center-cracked plate is predicted under mode I variable amplitude loading, and the result is validated by experiment. Huang's model is employed to describe crack growth with acceleration and retardation due to the variable loading effect. Experiment is conducted with Al6016-T6 plate, in which the load is applied, and crack length is measured periodically. Particle Filter algorithm, which is based on the Bayesian approach, is used to estimate model parameters from the experimental data, and predict the crack growth of the future in the probabilistic way. The prediction is validated by the run-to-failure results, from which it is observed that the method predicts well the unique behavior of crack retardation and the more data are used, the closer prediction we get to the actual run-to-failure data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.357-359
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• 2022

The market for eco-friendly food materials by online distribution is rapidly growing due to major environmental pollution such as air, soil, and water quality, and radical changes in living patterns caused by COVID-19. In addition, because of the aging population and the decrease in agricultural-related population due to social structural changes, aquaponics is emerging as a system that can solve problems such as independence of old economic activities, environmental protection, and securing healthy and safe food. This paper aims to design an intelligent plant growth measurement system among intelligent aquaponics production management modules for optimal growth environment derivation and quantitative production prediction by converging various ICT technologies into existing aquaponics systems. In particular, the focus is on designing systems suitable for production sites that do not have high-performance processing resources, and we propose a module configuration plan for production environments and training data and prediction systems.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.9
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• pp.1325-1331
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• 2002

This study presents a numerical model to predict the behavior of frost layer growth. The characteristics of the heat and mass transfer inside the frost layer are analyzed by coupling the air flow with the frost layer. The present model is validated by comparing with the several other analytical models. It has been known that most of the previous models cause considerable errors depending on the working conditions or correlations used in predicting the frost thickness growth, whereas the model in this work estimates the thickness of the frost layer more accurately within an error of 10% in comparison with the experimental data. Simulation results are presented for variations of heat and mass transfer during the frost formation and for the behavior of frost layer growth along the direction of air flow.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.168-177
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• 1999

Fatigue damage is the phenomena which is accumulated gradually with loading cycle in material. It is represented by fatigue crack growth rate da/dN and fatigue life ratio $N/N_{f}$. Fracture mechanical parameters estimating large crack growth behavior can calculate quantitative amount of fatigue crack growth resistance in engineering material. But fatigue damage has influence on various load, material and environment. Therefore, In this study, we propose that artificial intelligent fatigue damage model can predicts fatigue crack growth rate da/dN and fatigue life ratio $N/N_{f}$ simultaneously using fracture mechanical and nondestructive parameters.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.182-187
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• 2000

The application of fracture mechanics have traditionally concentrated on cracks leaded by tensile stresses, and growing under an opening or mode I mechanism. However, many cases of failures occur from growth of cracks subjected to mixed mode loading. Several criteria have been proposed regarding the crack growth direction under mixed mode loadings. This paper is aimed at prediction of fatigue crack growth behaviour under mixed mode(I+II) in two dimensional branched type precrack. In this paper, the maximum tangential stress(MTS) criterion was used to predict crack growth direction. Not only experiment but also finite element analysis(FEA) was carried out. The theoretical predictions were compared with experimental results in this paper