• International Journal of Ocean System Engineering
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• v.4 no.1
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• pp.1-18
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• 2014

Heave plates have been widely used to enhance viscous damping and thus reduces the heave response of Spar platforms. Single heave plate attached to the keel of the Spar has been reported in literature (Tao and Cai 2004). The effect of double heave plates on hydrodynamic response in random waves has been investigated in this study. The influence of relative spacing $L_d/D_d$ ($D_d$-the diameter of the heave plate) on the hydrodynamic response in random waves has been simulated in wave basin experiments and numerical model. The experimental investigation has been carried out using 1:100 scale model of Spar with double heave plates in random waves for different relative spacing and varying wave period. The influence of relative spacing between the heave plates on the motion responses of Spar are evaluated and presented. Numerical investigation has been carried out to investigate effect of relative spacing on hydrodynamic characteristics such as heave added mass and hydrodynamic responses. The measured results were compared with those obtained from numerical simulation and found to be in good agreement. Experimental and numerical simulation shows that the damping coefficient and added mass does not increase for relative spacing of 0.4 and the effect greater than relative spacing on significant heave response is insignificant.

• Journal of Korean Association for Spatial Structures
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• v.23 no.3
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• pp.87-94
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• 2023

Chloride is one of the most common threats to reinforced concrete (RC) durability. Alkaline environment of concrete makes a passive layer on the surface of reinforcement bars that prevents the bar from corrosion. However, when the chloride concentration amount at the reinforcement bar reaches a certain level, deterioration of the passive protection layer occurs, causing corrosion and ultimately reducing the structure's safety and durability. Therefore, understanding the chloride diffusion and its prediction are important to evaluate the safety and durability of RC structure. In this study, the chloride diffusion coefficient is predicted by machine learning techniques. Various machine learning techniques such as multiple linear regression, decision tree, random forest, support vector machine, artificial neural networks, extreme gradient boosting annd k-nearest neighbor were used and accuracy of there models were compared. In order to evaluate the accuracy, root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE) and coefficient of determination (R2) were used as prediction performance indices. The k-fold cross-validation procedure was used to estimate the performance of machine learning models when making predictions on data not used during training. Grid search was applied to hyperparameter optimization. It has been shown from numerical simulation that ensemble learning methods such as random forest and extreme gradient boosting successfully predicted the chloride diffusion coefficient and artificial neural networks also provided accurate result.

• Journal of the Korean Society for Heat Treatment
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• v.36 no.6
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• pp.374-381
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• 2023

This study develops and evaluates a deep learning model for predicting oxide and nitride layers based on plasma process data. We introduce a novel deep learning-based Varying Coefficient Regressor (VCR) by adapting the VCR, which previously relied on an existing unique function. This model is employed to forecast the oxide and nitride layers within the plasma. Through comparative experiments, the proposed VCR-based model exhibits superior performance compared to Long Short-Term Memory, Random Forest, and other methods, showcasing its excellence in predicting time series data. This study indicates the potential for advancing prediction models through deep learning in the domain of plasma processing and highlights its application prospects in industrial settings.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.283-286
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• 2000

Comparison for various empirical models of normal incident absorption was made, along with experiments. Comparative result indicates that Voronina model which is function of fiber diameter and porosity is more suitable than the other models. An investigation for correlation between normal and random incident absorption was carried out by experiment and analysis. It appears that at the low frequencies, the random incident absorption is higher than the normal one, whileas at the high frequencies, the random incident absorption is decreased due to the effect of grazing incident components.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.731-739
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• 2000

Conditional least square estimators for the parameters of he NLAR(p) time series models are obtained. it is also shown that these estimators are consistent and asymptotically normal.

• Communications for Statistical Applications and Methods
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• v.11 no.2
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• pp.297-311
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• 2004

In the sample survey for a highly skewed population, stratum jumpers often occur. Stratum jumpers are units having large discrepancies between a stratification variable and a study variable. We propose two models for stratum jumpers: a multiplicative model and a random replacement model. We also consider the modification of the L-H stratification algorithm such that we apply the previous models to L-H algorithm in determination of the sample sizes and the stratum boundaries. We evaluate the performances of the new stratification algorithms using real data. The result shows that L-H algorithm for the random replacement model outperforms other algorithms since the estimator has the least coefficient of variation.

• The Journal of the Acoustical Society of Korea
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• v.22 no.3
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• pp.162-168
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• 2003

The degree of diffusion, characterized by the "scattering coefficient" of surface materials, has been known to be one of the most important factors in determining the acoustical qualities of concert halls. Based on the suggested ISO method, which measures the random-incidence scattering coefficient of surfaces in a diffuse field, the scattering coefficients of different sizes and densities of wooden hemispheres and cubes were measured in model-scale reverberation rooms. As a result, wooden hemispheres with a structural depth of more than 15㎝ have the highest average (500㎐∼4㎑) scattering coefficient. It was also found that the scattering coefficient becomes higher when the diffuser density reaches about 50% for hemispheres and 30% for cubes.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.323-330
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• 2020

This paper proposes the road roughness based Braking Pressure Calculation System(BPCS) for an Autonomous Vehicle Stability. The system consists of an image normalization module that processes the front image of a vehicle to fit the input of the random forest, a Random Forest based Road Roughness Classification Module that distinguish the roughness of the road on which the vehicle is travelling by using the weather information and the front image of a vehicle as an input, and a brake pressure control module that modifies a friction coefficient applied to the vehicle according to the road roughness and determines the braking strength to maintain optimal driving according to a vehicle ahead. To verify the efficiency of the BPCS experiment was conducted with a random forest model. The result of the experiment shows that the accuracy of the random forest model was about 2% higher than that of the SVM, and that 7 features should be bagged to make an accurate random forest model. Therefore, the BPCS satisfies both real-time and accuracy in situations where the vehicle needs to brake.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.662-674
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• 2014

In this study, accident frequency prediction models were constructed by collecting variables such as geometric structures, safety facilities, traffic volume and weather conditions, land use, highway design-satisfaction criteria along 780km (4,372 sections) of 4 lane-highways over 8 areas. As for models, a fixed parameter model and a random parameter model were employed. In the random parameter model, some influences were reversed as the range was expressed based on specific probability in the case of no fixed coefficients. In the fixed parameter model, the influences of independent variables on accident frequency were interpreted by using one coefficient, but in the random parameter model, more various interpretations were took place. In particular, curve radius, securement of shoulder lane, vertical grade design criteria satisfaction showed both positive and negative influence, according to specific probability. This means that there could be a reverse effect depending on the behavioral characteristics of drivers and the characteristics of highway sections. Rather, they influence the increase of accident frequency through the all sections.

• Communications for Statistical Applications and Methods
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• v.13 no.1
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• pp.167-175
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• 2006

It has long been recognized that cancer is a genetic disease. To find this measures of genetic instability, stain cells with chromosome specific probes using chromosome in-situ hybridization technique is adopted. Even though in-situ hybridization technique is powerful, truncation of nuclei often results in under-representation of chromosome copies in slides due to the sectioning of tissue blocks. Because of this problem we suggest three different methods to analyze the cervical cancer data set. We observe that genetic instability is an increasing function of histology and our suggested model is the best in detecting genetic instability of tumorigenesis processes.