• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.588-590
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• 2006

Recently, many on-line approaches to instrument channel surveillance (drift monitoring and fault detection) have been reported worldwide. On-line monitoring (OLM) method evaluates instrument channel performance by assessing its consistency with other plant indications through parametric or non-parametric models. The heart of an OLM system is the model giving an estimate of the true process parameter value against individual measurements. This model gives process parameter estimate calculated as a function of other plant measurements which can be used to identify small sensor drifts that would require the sensor to be manually calibrated or replaced. This paper describes an improvement of auto-associative kernel regression by introducing a correlation coefficient weighting on kernel distances. The prediction performance of the developed method is compared with conventional auto-associative kernel regression.

• Computational Structural Engineering
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• v.8 no.1
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• pp.127-136
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• 1995

In this paper the stochastic FE analysis considering the material and geometrical property of the plate structure is performed by the weighted integral method. To consider the stochasity of the material and geometrical property, the stochastic field is assumed respectively. The mean value of the stochastic field is 0 and the value of variance is assumed as 0.1. The characteristics of the assumed stochastic field is represented by auto-correlation function. This auto-correlation function is used in evaluating the response variability of the plate structure. In this study a new auto-correlation function is derived to concern the uncertainty of the plate thickness. The newly derived auto-correlation function is a function of auto-correlation function and coefficient of variation of the assumed stochastic field. The two results, obtained by proposed Weighted Integral method and Monte Carlo Simulation method, are coincided with each other and these results are almost equal to the theoretical result that is derived in this study. In the case of considering the variability of plate thickness, the obtained result is well coincide with those of Lawrence and Monte Carlo simulation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.654-655
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• 2008

In order to investigate the availability of tire airborne noise for vehicle road noise development, We measured the noise in condition of smooth road and coarse road. The correlation coefficient was analyzed using the articulation index of the tire airborne noise and the vehicle road noise. It has been found that the correlation between the tire airborne noise and the vehicle road noise is positively strong.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1491-1495
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• 2023

This study utilized automated machine learning (AutoML) to calculate Arctic ice surface temperature (IST). AutoML-derived IST exhibited a strong correlation coefficient (R) of 0.97 and a root mean squared error (RMSE) of 2.51K. Comparative analysis with deep neural network (DNN) models revealed that AutoML IST demonstrated good accuracy, particularly when compared to Moderate Resolution Imaging Spectroradiometer (MODIS) IST and ice mass balance (IMB) buoy IST. These findings underscore the effectiveness of AutoML in enhancing IST estimation accuracy under challenging polar conditions.

• Bulletin of the Korean Chemical Society
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• v.35 no.12
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• pp.3527-3531
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• 2014

In this paper, we report thermodynamic and transport properties (diffusion coefficient, viscosity, and thermal conductivity) of diatomic gases ($H_2$, $N_2$, $O_2$, and $Cl_2$) at 273.15 K and 1.00 atm by performing molecular dynamics simulations using Lennard-Jones intermolecular potential and modified Green-Kubo formulas. The results of self-diffusion coefficients of diatomic gases obtained from velocity auto-correlation functions by Green-Kubo relation are in good agreement with those obtained from mean square displacements by Einstein relation. While the results for viscosities of diatomic gases obtained from stress auto-correlation functions underestimate the experimental results, those for thermal conductivities obtained from heat flux auto-correlation functions overestimate the experimental data except $H_2$.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.51-55
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• 2007

In this paper Statistical Energy Analysis has been considered to predict high frequency air borne interior noise. Dash panel Insulation is major part to reduce engine excitation noise. Transmission loss and absorption coefficient are considered to predict dash insulation performance. Transmission lose is derived from coupling loss factor and absorption coefficient is derived from internal damping loss factor. Material Biot properties were used to calculate each loss factors. Insulation geometry thickness distribution was hard to measure, so FeGate software was used to calculate thickness map from CAD drawing. Each predicted transmission losses between conventional insulation and light weight insulation were compared with SEA. Transmission loss measurement was performed to validate each prediction result, and it showed good correlation between prediction and measurement. Finally interior noise prediction was performed and result showed light weight insulation system can reduce 40% weight to keep similar performance with conventional insulation system, even though light weigh insulation system has lower sound transmission loss and higher absorption coefficient than conventional system.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.259-260
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• 2002

In this paper, electrical discharge machined (EDM) surfaces machined with various machining parameters are characterized and simulated. Three-dimensional surface topography of EDM surfaces are measured by a stylus instrument. Surface topography is characterized with auto-correlation coefficient and height probability density functions. Then, EDM surfaces are modeled and computer-simulated by using the non-causal 2-D auto-regressive model. Simulation results show that EDM surfaces are characterized well by a few parameters.

• Journal of Animal Science and Technology
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• v.64 no.1
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• pp.135-142
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• 2022

It is impossible to know the amount of pork primal cut by pig carcass grade which is determined only by carcass weight and backfat thickness in the Korean Pig Carcass System. The aim of this study was to investigate the correlation between the pig carcass grade and the amount of pork primal cut estimated with AutoFom III. A total of 419,321 Landrace, Yorkshire, and Duroc (LYD) pigs were graded with the Korean Pig Carcass Grade System. Amounts of belly, neck, loin, tenderloin, spare ribs, shoulder, and ham were estimated with AutoFom III. Regression equations for seven primal cuts according to each grade were derived. There were significant differences among the three carcass grades due to heteroscedasticity variance (p < 0.0001). Three regression equations were derived from AutoFom III estimation of primal cuts according to carcass grades. The coefficient of determination of the regression equation was 0.941 for grade 1⁺, 0.982 for grade 1, and 0.993 for grade 2. Regression equations obtained from this study are suitable for AutoFom III software, a useful tool for the analysis of each pig carcass grade in the Korean Pig Carcass Grade System. The high reliability of predicting the amount of primal cut with AutoFom III is advantageous for the management of slaughterhouses to optimize their product sorting in Korea.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.560-563
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• 1997

Sound intensity method is well known as a visualization technique of sound field and sound propagation in noise control. Sound intensity is a vector quantity that describes the magnitude and the direction of net flow of acoustic energy at a given position. The current measuring method is expensive and difficult to identify the noise source exactly. In this paper, we have studied the noise source identification and the characteristics of noise source of rotary compressor for air conditioner using complex sound intensity method. The new method for instantaneous sound intensity is also proposed and it is useful for transient state and steady state. The criteria of these states select auto correlation coefficient. The advantage, simplicity and economic attribution of this method are verified by analyzing the characteristics of noise source with instantaneous sound intensity compared to mean sound intensity.

• Bulletin of the Korean Chemical Society
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• v.28 no.8
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• pp.1371-1374
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• 2007

The velocity auto-correlation (VAC) function of liquid argon in the Green-Kubo formula decays quickly within 5 ps to give a well-defined diffusion coefficient because the velocity is the property of each individual particle, whereas the stress (SAC) and heat-flux auto-correlation (HFAC) functions for shear viscosity and thermal conductivity have non-decaying, long-time tails because the stress and heat-flux appear as system properties. This problem can be overcome through N (number of particles)-fold improvement in the statistical accuracy, by considering the stress and the heat-flux of the system as properties of each particle and by deriving new Green-Kubo formulas for shear viscosity and thermal conductivity. The results obtained for the transport coefficients of liquid argon obtained are discussed.