• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.164-165
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• 2014

In the case of U.S, various damage prediction models of buildings from natural disasters have been used widely in many organizations such as insurance companies and governments. In South Korea, although studies regarding damage prediction model of hurricane have been conducted, the scope has been only limited to consider the property of hurricane. However, it is necessary to consider various factors such as socio-economic, physical, geographical, and built environmental factors to predict the damages. Therefore, as a basic study on a damage prediction model development of buildings, this study is to analyze the correlation between various factors related to hurricane. The findings of study can be utilized to develop for predicting the damage of hurricane on buildings.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.38-42
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• 2018

In this paper, we consider measurement allocation problem in a spatially correlated sensor field. Our goal is to determine the probability of each sensor's being measured based on its contribution to the estimation reliability; it is desirable that a sensor improving the estimation reliability is measured more frequently. We consider a spatial correlation model of a sensor field reflecting transmission power limit, noise in measurement and transmission channel, and channel attenuation. Then the estimation reliability is defined distortion error between event source and its estimation at sink. Motivated by the correlation nature, we model the measurement allocation problem into a cooperative game, and then quantify each sensor's contribution using Shapley value. Against the intractability in the computation of exact Shapley value, we deploy a randomized method that enables to compute the approximate Shapley value within a reasonable time. Besides, we envisage a measurement scheduling achieving the balance between network lifetime and estimation reliability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.87-107
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• 2015

Considering the localization estimation issue in mixed line-of-sight (LOS)/non-LOS(NLOS) environments based on received signal strength (RSS) measurements in wireless sensor networks, a grid-based correlation method based on the relationship between distance and RSS is proposed in this paper. The Maximum-Likelihood (ML) estimator is appended to further improve the localization accuracy. Furthermore, in order to reduce computation load and enhance performance, an improved recursively version with NLOS mitigation is also proposed. The most advantages of the proposed localization algorithm is that, it does not need any prior knowledge of the propagation model parameters and therefore does not need any offline calibration effort to calibrate the model parameters in harsh environments, which makes it more convenient for rapid implementation in practical applications. The simulation and experimental results evidence that the proposed localization algorithm exhibits good localization performance and flexibilities for different devices.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.345-350
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• 1999

The effectiveness of software error compensation for thermally induced machine tool errors relies on the prediction accuracy of the pre-established thermal error models. The selection of optimal sensor locations is the most important in establishing these empirical models. In this paper, a methodology for the selection of optimal sensor locations is proposed to establish a robust linear model which is not subjected to collinearity. Correlation coefficient and time delay are used as thermal parameters for optimal sensor location. Firstly, thermal deformation and temperatures are measured with machine tools being excited by sinusoidal heat input. And then, after correlation coefficient and time delays are calculated from the measured data, the optimal sensor location is selected through hard c-means clustering and sequential selection method. The validity of the proposed methodology is verified through the estimation of thermal expansion along Z-axis by spindle rotation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1425-1431
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• 2006

In this study, An analysis of correlation between the vibration transmissions and the dynamic characteristics for floor impact sound insulation materials through model test was carried out. As the results, the correlation coefficients between the vibration transmissions and the dynamic characteristics for floor impact sound insulation materials were over 0.8 at the heavy and light floor impact source and less dynamic stiffness was more effective in reducing the vibration transmission.

• Journal of Biosystems Engineering
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• v.29 no.6 s.107
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• pp.539-543
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• 2004

The purpose of this study was to develop a real-time sensor for beef freshness. Contents of biogenic amines (BA), saccharides and proteins were highly related with freshness on the beef meats. Relations of those chemical contents and NIR spectra were studied. Tyramine showed the best correlation coefficient at 1250nm. Correlation between VBN (volatile basic nitrogen) and K value, which were both freshness measurement method, was determined by the PCR (principle component regression). The correlation model had the values of $R^2=0.989$ and SEC=1.78, respectively. The model was validated at $R^2=0.963$ and SEP=2.285, respectively.

• Journal of the Semiconductor & Display Technology
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• v.19 no.3
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• pp.82-87
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• 2020

The comprehensive and physics-based compact noise models for advanced CMOS devices were presented. The models incorporate important physical effects in nanoscale MOSFETs, such as the low frequency correlation effect between the drain and the gate, the trap-related phenomena, and QM (quantum mechanical) effects in the inversion layer. The drain current noise model was improved by including the tunneling assisted-thermally activated process, the realistic trap distribution, the parasitic resistance, and mobility degradation. The expression of correlation coefficient was analytically described, enabling the overall noise performance to be evaluated. With the consideration of QM effects, the comprehensive low frequency noise performance was simulated over the entire bias range.

• Journal of the Optical Society of Korea
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• v.12 no.3
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• pp.170-173
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• 2008

In this study, we simulated a statistical model of FCS(fluorescence correlation spectroscopy) based on a Poisson process to understand and explain observations of the experiment performed on molecules of ultra-low concentration by the home-built laser-scanning confocal microscope. The statistical model confirmed that the relative mean square amplitude of fluctuations is shown to be inversely proportional to the average number of molecules, even in the ultra-low concentration, if some conditions are satisfied. Signal-to-noise ratio and the variability of dwelling time under the confocal volume were found to be effective conditions for the experiment.

• Journal of Korean Society for Quality Management
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• v.21 no.1
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• pp.181-189
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• 1993

Over the past two decades, forecasting has gained widespread acceptance as an integral part of business planning and decision making. Accurate forecasting is a prerequisite to successful planning. Accordingly, recent advances in forecasting techniques are of exceptional value to corporate planners. But most of forecasting mothods are reveal its limit and problem for precision and reliability duing to each relationship for raw data and possibility of explanation for each variable. Therefore, to construct the Integrated Forecasting Model(IFM) for Information Factor Analysis, it shoud be considered that whether law data has time lag and variables are explained. For this. following several method can be used : Least Square Method, Markov Process, Fibonacci series, Auto-Correlation, Cross-Correlation, Serial Correlation and Random Walk Theory. Thus, the unified property of these several functions scales the safety and growth of the system which may be varied time-to-time.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.271-278
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• 2021

In this paper, a tropospheric delay error was calculated by using meteorological data collect from weather station and Saastamoinen model, and an empirical variogram of the tropospheric delay in the Korean peninsula was estimated. In order to estimate the empirical variogram of the tropospheric delay according to weather condition, sunny day, rainy day, and typhoon day were selected as analysis days. Analysis results show that a maximum correlation range of the empirical variogram on sunny day was about 560 km because there is overall trend of the tropospheric delay. On the other hand, the maximum correlation range of the empirical variogram on rainy was about 150 km because the regional variation was large. Although there is regional variation when the typhoon exists, there is a trend of the tropospheric delay due to a movement of the typhoon. Therefore, the maximum correlation range of the empirical variogram on typhoon day was about 280 km which is between sunny and rainy day.