• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.5
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• pp.30-35
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• 2008

As the quality of a weld feint is strongly influenced by process parameters during the welding process, an intelligent algorithms that can predict the bead geometry and shape to accomplish the desired mechanical properties of the weldment should be developed. This paper focuses on the development of mathematical models fur the selection of process parameters and the prediction of bead geometry(bead width, bead height and penetration) in robotic GMA(Gas Metal Arc) welding. Factorial design can be employed as a guide for optimization of process parameters. Three factors were incorporated into the factorial model: arc current, welding voltage and welding speed. A sensitivity analysis has been conducted and compared the relative impact of three process parameters on bead geometry in order to verify the measurement errors on the values of the uncertainty in estimated parameters. The results obtained show that developed mathematical models can be applied to estimate the effectiveness of process parameters for a given bead geometry, and a change of process parameters affects the bead width and bead height more strongly than penetration relatively.

• Clinical and Experimental Pediatrics
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• v.62 no.2
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• pp.48-54
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• 2019

Purpose: Liver metabolism plays a pivotal role in the development of metabolic disorders. We aimed to investigate the clinical and laboratory risk factors associated with alanine aminotransferase (ALT) levels in young adolescents from an urban population in Korea. Methods: A population of 120 apparently healthy adolescents aged 12-13 years was included in the cross-sectional design study; 58 were overweight or obese and 62 were of normal weight. We estimated anthropometric and laboratory measurements, including waist-to-height ratio, blood pressure, insulin sensitivity, aspartate aminotransferases (AST), ALT, and lipid profiles. Results: The mean ages of the overweight or obese and normal weight participants were $12.9{\pm}0.3$ and $13.0{\pm}0.3years$, respectively. Height, weight, body mass index, waist circumference, waist-to-height ratio, systolic and diastolic blood pressure, AST, ALT, total cholesterol, low-density lipoprotein-cholesterol, triglyceride, insulin, and the homeostatic model assessment of insulin resistance (HOMA-IR) score were significantly higher and the high-density lipoprotein-cholesterol and quantitative insulin-sensitivity check index were significantly lower in the overweight/obese participants in comparison to the normal-weight participants (all P<0.05). In multivariate linear regression analysis, waist-to-height ratio, systolic blood pressure, and HOMA-IR score were independently and positively associated with serum ALT levels. Conclusion: Screening for ALT levels in adolescents may help to differentiate those at risk of metabolic abnormalities and thus prevent disease progression at an early age.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.274-280
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• 1998

The welding technology and qualities are developed significantly, in recent years, in the use of automated processing technology and welding robot systems. But these automated welding technologies have many difficulties for finding the optimal welding parameter conditions. Because of the lack of mathematical model for determination of optimal welding process parameters. In this study, the sensitivity analysis of the empirical equations for finding weld bead width, height and penetration depth by using the published formulae. The selected major welding process parameters effected to weld bead geometries are the welding speed, current, voltage and weld wire diameter.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.1
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• pp.60-67
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• 2012

This study considers the numerical analysis on parametric roll for container ships. As a method of numerical simulation, an impulse-response-function approach is applied in time domain. A systematic study is carried out for the parametric roll of two container ships, particularly observing the sensitivity of computational results to some parameters which can affect the analysis of parametric roll. The parameters to be considered are metacentric height (GM), simulation time window, and the discretization of wave spectrum. Based on the result of parametric roll simulation, numerical sensitivity and uncertainty in computational analysis are discussed.

• Journal of Sensor Science and Technology
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• v.30 no.3
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• pp.131-138
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• 2021

The optimization of the specifications of vertical silicon on insulator (SOI) slot optical waveguides suitable for integrated-optical biochemical sensors was performed through computational analysis of the confinement factor of the guided mode distributed in the slot in addition to analytical examination of the TE mode. The optimized specifications were confirmed based on sensitivity in terms of the change in the refractive index of the biochemical analyte. When the slot width, rail width, and height were set to 120 nm, 200 nm, and 320 nm, respectively, the confinement factor was evaluated to be about 56% and the sensitivity was at least 0.9 [RIU/nm].

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.266-269
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• 2007

This paper reports the preliminary results on the study of radargrammetry especially for a high-resolution satellite synthetic aperture radar system. Theoretical configurations for radargrammetry in terms of coverage, orbit selection, incidence angles, height sensitivity of parallax and height resolution of DEM were calculated according to the proposed orbit characteristics and the imaging modes of KOMPSAT-5 SAR. Possible imaging strategies and mission scenarios for coverage versus rapidity are suggested for a future mission dedicated to radargrammetry.

• Journal of the Korean earth science society
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• v.45 no.4
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• pp.349-362
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• 2024

We aimed to evaluate the effectiveness of ensemble optimal interpolation (EnOI) in improving the analysis of significant wave height (SWH) within wave models using satellite-derived SWH data. Satellite observations revealed higher SWH in mid-latitude regions (30° to 60° in both hemispheres) due to stronger winds, whereas equatorial and coastal areas exhibited lower wave heights, attributed to calmer winds and land interactions. Root mean square error (RMSE) analysis of the control experiment without data assimilation revealed significant discrepancies in high-latitude areas, underscoring the need for enhanced analysis techniques. Data assimilation experiments demonstrated substantial RMSE reductions, particularly in high-latitude regions, underscoring the effectiveness of the technique in enhancing the quality of analysis fields. Sensitivity experiments with varying ensemble sizes showed modest global improvements in analysis fields with larger ensembles. Sensitivity experiments based on different decorrelation length scales demonstrated significant RMSE improvements at larger scales, particularly in the Southern Ocean and Northwest Pacific. However, some areas exhibited slight RMSE increases, suggesting the need for region-specific tuning of assimilation parameters. Reducing the observation error covariance improved analysis quality in certain regions, including the equator, but generally degraded it in others. Rescaling background error covariance (BEC) resulted in overall improvements in analysis fields, though sensitivity to regional variability persisted. These findings underscore the importance of data assimilation, parameter tuning, and BEC rescaling in enhancing the quality and reliability of wave analysis fields, emphasizing the necessity of region-specific adjustments to optimize assimilation performance. These insights are valuable for understanding ocean dynamics, improving navigation, and supporting coastal management practices.

• Journal of Ocean Engineering and Technology
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• v.35 no.5
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• pp.336-346
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• 2021

The prediction of wave conditions is crucial in the field of marine and ocean engineering. Hence, this study aims to predict the significant wave height through machine learning (ML), a soft computing method. The adopted metocean data, collected from 2012 to 2020, were obtained from the Korea Institute of Ocean Science and Technology. We adopted the feedforward neural network (FNN) and long-short term memory (LSTM) models to predict significant wave height. Input parameters for the input layer were selected by Pearson correlation coefficients. To obtain the optimized hyperparameter, we conducted a sensitivity study on the window size, node, layer, and activation function. Finally, the significant wave height was predicted using the FNN and LSTM models, by varying the three input parameters and three window sizes. Accordingly, FNN (W48) (i.e., FNN with window size 48) and LSTM (W48) (i.e., LSTM with window size 48) were superior outcomes. The most suitable model for predicting the significant wave height was FNN(W48) owing to its accuracy and calculation time. If the metocean data were further accumulated, the accuracy of the ML model would have improved, and it will be beneficial to predict added resistance by waves when conducting a sea trial test.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.2
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• pp.175-181
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• 2014

A four-link mechanism consisting of torsion bars is used for opening the trunk lid in most midsize sedans. When the weight of the lid is in equilibrium with the spring force exerted by torsion bars, the lid stops opening at a pop-up height. However, the actual pop-up height has large deviations from the specified height even with the same parts in the same car model, which leads to quality issues. Automotive manufacturers have experienced this deviation problem despite much effort to resolve it. In this research, we developed a multi-body dynamics model for the analysis of pop-up deviation of a trunk lid with torsion bars, which can simulate the actual pop-up motion of the trunk lid by considering kinematic constraints of the motion and friction forces in joints. We could also determine the most important factor that governs the pop-up height by sensitivity analysis of all parts. The developed system can be used for the analysis of other trunk lid systems to control the tolerance of parts.

• Atmosphere
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• v.19 no.4
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• pp.331-344
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• 2009

A sensitivity study has been performed using ARPS (Advanced Regional Prediction System) version 5.2.10 in a downslope windstorm case of 12-13 February 2006. The purpose of this study was to find out the role of the inversion layer of temperature mainly in relation to the strength of the downslope winds over the Yeongdong region located downstream of the Taebaek mountains. Under the conditions of N (Brunt-$V{\ddot{a}}is{\ddot{a}}la$ frequency)=0.008 and N=0.016, the effects of the presence of the inversion layer, its variation of height of the layer, and the depth of the layer were identified. The sensitivity experiments suggested that the inversion layer effected the downstream wind speed of the mountains under both conditions of N=0.008 and N=0.016, and notably when the inversion layer was located near the mountain crest the downstream wind speed of the mountains was strong (~ $27ms^{-1}$) only under the condition of N=0.016. In addition, when the atmosphere was rather stable (N=0.016) and the depth of the layer was relatively thin (765 m) the downstream wind speed of the mountains was the strongest (~ $30ms^{-1}$) among the sensitivity experiments.