• Journal of Welding and Joining
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• v.22 no.4
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• pp.73-81
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• 2004

Failure mechanisms of welded joints under fatigue loads are interpreted that multiple collinear surface cracks initiating randomly along the weld toes propagate under the mutual interaction and coalescence of adjacent two cracks. To estimate fatigue crack propagation life for three types of the representative welded joints, i.e. non-load carrying cruciform, cover plate and longitudinal stiffener joint, the stress intensity factors at the front of the surface cracks have to be calculated, which are influenced strongly by the geometry of attachments, weld toes and the crack shapes. For the effective calculation of the stress intensity factors the Mk-factor was introduced which can be derived by a parametric study performed by FEM considering influence of the geometrical effects. The fatigue life of the cruciform joint was estimated by using the Mk-factors and the method considering the propagation mechanisms of the multiple surface cracks. Analysis results for the fatigue life had a good agreement with that of experiment.

• ETRI Journal
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• v.38 no.1
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• pp.141-148
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• 2016

This paper proposes a method to estimate directly the incoherent scattered intensity and radar cross section (RCS) from the effective permittivity of a random media. The proposed method is derived from the original concept of incoherent scattering. The incoherent scattered field is expressed as a simple formula. Therefore, to reduce computation time, the proposed method can estimate the incoherent scattered intensity and RCS of a random media. To verify the potential of the proposed method for the desired applications, we conducted a Monte-Carlo analysis using the method of moments; we characterized the accuracy of the proposed method using the normalized mean square error (NMSE). In addition, several medium parameters, such as the density of scatterers and analysis volume, were studied to understand their effect on the scattering characteristics of a random media. The results of the Monte-Carlo analysis show good agreement with those of the proposed method, and the NMSE values of the proposed method and Monte-Carlo analysis are relatively small at less than 0.05.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.312-316
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• 2002

Satellite radar interferometry data shows a strong coherent signal on oyster sea farms where artificial structures installed on the bottom. We obtained 21 highly coherent interferograms from eleven JERS-1 SAR data sets despite of large orbital baseline (~2 km) or large temporal baseline (~l year). The phases observed in sea farms are probably induced by double bouncing on sea surface, and consequently reveal a tide height variation. To restore the absolute sea level changes we counted the number of wrapping by exploiting the intensity of backscattering. Backscattering intensity is closely correlated with the change in water surface height, while interferometry gives the detailed variation within the limit of 2$\pi$ (or 15.3 cm). Comparing the radar measurements with the tide gauge records yielded a correlation coefficient of 0.96 and an ms error of 6.0 cm. The results demostrate that radar interferometry is promising to measure sea level.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1346-1348
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• 2003

In this paper, the interferometric coherence was estimated and the amplitude intensity was extracted using the repeat-pass interferometric data, acquired by European Remote Sensing Satellite 1 and 2. Then discrimination and classification of surface land types in Zhangjiakou test site, Hebei Province were carried out based on the coherence estimation and the intensity extraction. Seven types of land were discriminated and classified, including in two different types of meadows, woodland, dry land, grassland, steppe and water body. The backscatter and coherence characteristics of these land types on the multi-temporal images were analyzed, and the change of surface features with time series was also discussed.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1037-1051
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• 2020

The accurate monitoring and forecasting of the intensity of tropical cyclones (TCs) are able to effectively reduce the overall costs of disaster management. In this study, we proposed a multi-task learning (MTL) based deep learning model for real-time TC intensity estimation and forecasting with the lead time of 6-12 hours following the event, based on the fusion of geostationary satellite images and numerical forecast model output. A total of 142 TCs which developed in the Northwest Pacific from 2011 to 2016 were used in this study. The Communications system, the Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) data were used to extract the images of typhoons, and the Climate Forecast System version 2 (CFSv2) provided by the National Center of Environmental Prediction (NCEP) was employed to extract air and ocean forecasting data. This study suggested two schemes with different input variables to the MTL models. Scheme 1 used only satellite-based input data while scheme 2 used both satellite images and numerical forecast modeling. As a result of real-time TC intensity estimation, Both schemes exhibited similar performance. For TC intensity forecasting with the lead time of 6 and 12 hours, scheme 2 improved the performance by 13% and 16%, respectively, in terms of the root mean squared error (RMSE) when compared to scheme 1. Relative root mean squared errors(rRMSE) for most intensity levels were lessthan 30%. The lower mean absolute error (MAE) and RMSE were found for the lower intensity levels of TCs. In the test results of the typhoon HALONG in 2014, scheme 1 tended to overestimate the intensity by about 20 kts at the early development stage. Scheme 2 slightly reduced the error, resulting in an overestimation by about 5 kts. The MTL models reduced the computational cost about 300% when compared to the single-tasking model, which suggested the feasibility of the rapid production of TC intensity forecasts.

• Journal of Korea Water Resources Association
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• v.40 no.10
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• pp.811-821
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• 2007

The intensity-duration-frequency (IDF) curves by Talbot, Sherman and Japanese type formulas are widely used in South Korea since the parameters are easily estimated. However, these IDF curves' accuracies are relatively worse than those of the IDF curves developed by Lee et al. (1993) and Heo et al. (1999), and different parameters for the given return periods should be computed. In this study, parameter estimation method for the IDF curve by Heo et al. (1999) is suggested using genetic algorithm (GA). Quantiles computed by at-site frequency analysis using the rainfall data of 22 rainfall gauges operated by Korea Meteorological Administration are employed to estimate the parameters of IDF curves and minimizing root mean squared error (RMSE) and relative RMSE (RRMSE) of observed and computed quantiles are used as objective functions of GA. The comparison of parameter estimation methods between the empirical regression analysis and the suggested method show that the IDF curve in which the parameters are estimated by GA using RRMSE as an objective function is superior to the IDF curves using RMSE.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.2 s.302
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• pp.101-112
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• 2005

As we perceive the world as 3-dimensional through our two eyes, we can extract 3-dimensional information from stereo images obtained from two or more cameras. Since stereo images have a large amount of data, with recent advances in digital video coding technology, efficient compression algorithms have been developed for stereo images. In order to compress stereo images and to obtain 3-D information such as depth, we find disparity vectors by using disparity estimation algorithm generally utilizing pixel differences between stereo pairs. However, it is not unusual to have stereo images having different intensity values for several reasons, such as incorrect control of the iris of each camera, disagreement of the foci of two cameras, orientation, position, and different characteristics of CCD (charge-coupled device) cameras, and so on. The intensity differences of stereo pairs often cause undesirable problems such as incorrect disparity vectors and consequent low coding efficiency. By compensating intensity differences between left and right images, we can obtain higher coding efficiency and hopefully reduce the perceptual burden of brain to combine different information incoming from two eyes. We propose several methods of intensity compensation such as local intensity compensation, global intensity compensation, and hierarchical intensity compensation as very simple and efficient preprocessing tool. Experimental results show that the proposed algerian provides significant improvement in coding efficiency.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.5 s.149
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• pp.597-603
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• 2006

The estimations of distributed and joint-excited input power for Power Flow Analysis are accomplished in this paper. Using Fourier transform, the displacements of infinite structures are derived, and the input power of distributed excitation can be estimated. The obtained results compare the real input power with the estimation of input power. When the exciting force acts on the joint of coupled structures, it is estimating the power that is transferred to each structure. Appling this input power, the results of energy density and intensity of Power Flow Analysis can be compared with the classical solutions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.9
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• pp.729-737
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• 1990

This paper presents a new method of multilevel estimation of dithered images. A dithered picture, a two-tone picture which gives the illusion of picture with many shades of gray, is obtained by comparing the gray-level picture which gives the illusion of picture with a position-dependent threshold. When the intensity of a picture element exeeds the threshold it is classified as white: otherwise it is black. In the new estimation scheme, the simulation results show the SNR of the new method is improved 0.7dB compared with the old method. And we propose a new progressive image transmission by employing thie method.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1822-1829
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• 2015

In this study, artificial neural networks were used to determine the intensity of brightness in interior spaces. The illumination elements to illuminate indoor spaces were considered, not individually, but as a system. So, during the planned maintenance periods of an illumination system, after its design and installation, simple brightness level measurements must be taken. For a three-dimensional evaluation of the brightness level in indoor spaces in a speedy and accurate manner, the obtained brightness level measurement results and artificial neural network model were used. Upon estimation of the most suitable brightness level for indoor spaces by using the artificial neutral network model, the energy demands required by the illumination elements decreased. Consequently, in this study, with estimations of brightness levels, the extent to which the artificial neutral networks become successful was observed and more correct results have been obtained in terms of both economy and usage.